Model LF
Hamid et al 2022
11/7/2022
Packages
rm(list = ls())
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## For help type '?bimets'Import data
AAMK <- read_excel("model_data1.xlsx")
globaldemand1 <- read_excel("model_data2.xlsx")
names(AAMK) <- tolower(names(AAMK))
names(globaldemand1) <- tolower(names(globaldemand1))
AAMK=lapply(AAMK, function(t) ts(t, start=c(2005, 2), end=c(2020, 1),frequency=4))
globaldemand1=lapply(globaldemand1, function(t) ts(t, start=c(2005, 2), end=c(2020, 1),frequency=4))
attach(AAMK)## The following object is masked from package:base:
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## piattach(globaldemand1)## The following object is masked from AAMK:
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## xr## Change name in globaldemand1
g_20= globaldemand1$`g-20`eq_nf_l_nf = res_eq_nf_l
eq_f_l_f = res_eq_f_lPARAMETERS
Create dummies
d_2006q1=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2006,1), dummy_end = c(2006,1),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2011q2=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2011,2), dummy_end = c(2011,2),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2013q1=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2013,1), dummy_end = c(2013,1),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2017q3=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2017,3), dummy_end = c(2017,3),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2006q2=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2006,2), dummy_end = c(2006,2),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2006q3=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2006,3), dummy_end = c(2006,3),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2006q4=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2006,4), dummy_end = c(2006,4),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2007q34=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2007,3), dummy_end = c(2007,4),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2007q3=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2007,3), dummy_end = c(2007,3),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2008q2=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2008,2), dummy_end = c(2008,2),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2008q3=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2008,3), dummy_end = c(2008,3),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2008q4=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2008,4), dummy_end = c(2008,4),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2009q4=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2009,4), dummy_end = c(2009,4),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2018q2=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2018,2), dummy_end = c(2018,2),
basic_value = 0, dummy_value = 1, frequency = 4)
##### Er der noget specielt med dem her?????
d_20123 = ts(c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), start = c(2005, 2), end = c(2020,1), frequency = 4)
d_20124 = ts(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1), start = c(2005, 2), end = c(2020,1), frequency = 4)
#### Videre igen
d_2009q1=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2009,1), dummy_end = c(2009,1),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2009q2=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2009,2), dummy_end = c(2009,2),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2011q1=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1), dummy_start=c(2011,1), dummy_end = c(2011,1), basic_value = 0, dummy_value = 1, frequency = 4)
d_2014q3=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2014,3), dummy_end = c(2014,3),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2014q4=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2014,4), dummy_end = c(2014,4),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2013q4=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2013,4), dummy_end = c(2013,4),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2018q1=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2018,1), dummy_end = c(2018,1),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2016q3=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2016,3), dummy_end = c(2016,3),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2017q23=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2017,2), dummy_end = c(2017,3),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2019q3=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2019,3), dummy_end = c(2019,3),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2019q4=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2019,4), dummy_end = c(2019,4),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2020q1=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2020,1), dummy_end = c(2020,1),
basic_value = 0, dummy_value = 1, frequency = 4)
# DUMMY 4
dummy_2018q34 =create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2018,3), dummy_end = c(2018,4),
basic_value = 0, dummy_value = 1, frequency = 4)
dummy_2011q1 =create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2011,1), dummy_end = c(2011,1),
basic_value = 0, dummy_value = 1, frequency = 4)
dummy_2009q2 =create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2009,2), dummy_end = c(2009,2),
basic_value = 0, dummy_value = 1, frequency = 4)
time= ts(1:length(dummy_2009q2), start = c(2005,2), frequency = 4)
DUMMY_4= ts(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0), start = c(2005, 2), end = c(2020,1), frequency = 4)
DUMMY_10= ts(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0), start = c(2005, 2), end = c(2020,1), frequency = 4)
DUMMY_11= ts(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0), start = c(2005, 2), end = c(2020,1), frequency = 4)
#### Variable der kun har en værdi:
wage_2010q3 = ts(c(86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268,86.36268), start = c(2005, 2), end = c(2020,1), frequency = 4)
tax_rate2= ts(c(0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767,0.152767), start = c(2005, 2), end = c(2020,1), frequency = 4)
tax_rate1= ts(c(0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369,0.389369), start = c(2005, 2), end = c(2020,1), frequency = 4)
tax_rate_p <- ts(0.1628809, start=c(2005,2), end=c(2020,1), freq=4)
zz= ts(c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1), start = c(2005, 2), end = c(2020,1), frequency = 4)
urs= ts(c(0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04), start = c(2005, 2), end = c(2020,1), frequency = 4)
shock= ts(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), start = c(2005, 2), end = c(2020,1), frequency = 4)
#### TESTDummies til stød
d_2013q4=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2013,4), dummy_end = c(2013,4),
basic_value = 0, dummy_value = 1, frequency = 4)
d_2017q1=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2017,1), dummy_end = c(2017,1),
basic_value = 0, dummy_value = 1, frequency = 4)Data bank
Setting up the time series variables for the model
pc = cpi1/100 #ændret
px = px/100
pi_1 = pi/100
pg= pg/100
pm = pm/100
py = py/100
pf = pc*xr/rer
rer = pc*xr/pf
pconk = pcon/pc
gk = g/pg
xk = x/px
mk = m/pmi_adj_h = i_h - (i_equip_h + i_bd_h)
i_adj_nfc = i_nf - (i_equip_nfc + i_bd_nfc)
i_adj_fc = i_f - (i_equip_fc + i_bd_fc)
i_adj_g = i_g - (i_equip_g +i_bd_g)i_equip_h_k = i_equip_h/p_equip
i_equip_nfc_k = i_equip_nfc/p_equip
i_equip_g_k = i_equip_g/p_equip
i_equip_fc_k = i_equip_fc/p_equipi_bd_h_k = i_bd_h/p_bd
i_bd_nfc_k = i_bd_nfc/p_bd
i_bd_g_k = i_bd_g/p_bd
i_bd_fc_k = i_bd_fc/p_bdI just deflate the adjustment terms using p_equip as well (assuming most of it is changes in inventories)
i_adj_h_k = i_adj_h /p_equip
i_adj_nfc_k = i_adj_nfc /p_equip
i_adj_fc_k = i_adj_fc /p_equip
i_adj_g_k = i_adj_g /p_equipwe can compare ik with ikk. just to make sure we have all components of investment.
– Ved ik om “ik” og “ikk” skal give det samme men gør de ik –
ik = i_equip_h_k + i_equip_nfc_k + i_equip_g_k + i_equip_fc_k + i_bd_h_k + i_bd_nfc_k + i_bd_g_k + i_bd_fc_k + i_adj_h_k + i_adj_nfc_k + i_adj_fc_k + i_adj_g_k
ikk = i/pi_1yk = ik + pconk + gk + xk - mknpropinc_h = propinc_r_h - propinc_p_h
nsben_h = sben_h_r - scon_h_piba_f = - (iba_h + iba_nf + iba_g + iba_row) # The data from the database is not consistent (the sum of the stocks of IBA does not add up to zero). I fix it by assuming that iba_f is entirely demand-led.
iba_f_tr = - (iba_h_tr + iba_nf_tr + iba_g_tr + iba_row_tr) #The data from the database is not consistent (the sum of IBA transactions does not add up to zero). I fix it by assuming that iba_f_tr is entirely demand-led.### Jeg tager bare og fjerner første observation fra dem der er minuse så den først starer i 2005q3
iba_h_rvx=diff(iba_h)-iba_h_tr[-1]
iba_f_rvx=diff(iba_f)-iba_f_tr[-1]
iba_nf_rvx=diff(iba_nf)-iba_nf_tr[-1]
iba_g_rvx=diff(iba_g)-iba_g_tr[-1]
iba_row_rvx=diff(iba_row)-iba_row_tr[-1]eq_h = - ((eq_f_a - eq_f_l) + (eq_nf_a - eq_nf_l) + eq_g + (eq_row_a - eq_row_l)) #The data from the database is not consistent (the sum of the stocks of equities does not add up to zero). I fix it by assuming that eq_h absorbbs the small discrepancies that come from the database.### Der ages diff så de sarer alle i 2005Q3
eq_h_rvx=diff(eq_h)-eq_h_tr[-1]
eq_f_a_rvx=diff(eq_f_a)-eq_f_a_tr[-1]
eq_f_l_rvx=diff(eq_f_l)-eq_f_l_tr[-1]
eq_nf_a_rvx=diff(eq_nf_a)-eq_nf_a_tr[-1]
eq_nf_l_rvx=diff(eq_nf_l)-eq_nf_l_tr[-1]
eq_g_rvx=diff(eq_g)-eq_g_tr[-1]
eq_row_a_rvx=diff(eq_row_a)-eq_row_a_tr[-1]
eq_row_l_rvx=diff(eq_row_l)-eq_row_l_tr[-1]### Tror også alle disse starer i 2005Q3
Neq_row = eq_row_a - eq_row_l
Neq_nf = eq_nf_a - eq_nf_l
Neq_f = eq_f_a - eq_f_l
Neq_nf_rvx = eq_nf_a_rvx-eq_nf_l_rvx
Neq_f_rvx = eq_f_a_rvx-eq_f_l_rvx
Neq_row_rvx = eq_row_a_rvx-eq_row_l_rvx
Neq_nf_tr = diff(Neq_nf)-(Neq_nf_rvx)
Neq_f_tr = diff(Neq_f)-(Neq_f_rvx)
alpha_neq_nf = -Neq_nf/i_nf
Neq_row_tr = diff(Neq_row) - Neq_row_rvx# Igen starter førsst i 2005Q3
eq_h_tr = - (Neq_nf_tr + Neq_f_tr + eq_g_tr[-1] + Neq_row_tr) # The data from the database is not consistent (the sum of the stocks of equities does not add up to zero). I fix it by assuming that eq_h_tr absorbbs the small discrepancies that come from the database.eq_f_l_rvx = diff(eq_f_l)-eq_f_l_tr[-1]
eq_nf_l_rvx = diff(eq_nf_l)-eq_nf_l_tr[-1]
eq_row_l_rvx = diff(eq_row_l)-eq_row_l_tr[-1]ins_f = - (ins_row + ins_h + ins_nf + ins_g) # The database is almost consistent, but I redifine ins_f to make it fully consistent and avoid carrying discrepancies along when running the simulations.
ins_f_tr = - (ins_row_tr + ins_h_tr + ins_nf_tr + ins_g_tr) # The database is almost consistent, but I redifine ins_f_tr to make it fully consistent and avoid carrying discrepancies along when running the simulations.## Samme som før 2005Q3
ins_h_rvx=diff(ins_h)-ins_h_tr[-1]
ins_f_rvx=diff(ins_f)-ins_f_tr[-1]
ins_nf_rvx=diff(ins_nf)-ins_nf_tr[-1]
ins_g_rvx=diff(ins_g)-ins_g_tr[-1]
ins_row_rvx=diff(ins_row)-ins_row_tr[-1]sec_g = - (sec_row + sec_h + sec_f_a + sec_f_d + sec_nf) # The database is almost consistent, but I redifine sec_g to make it fully consistent and avoid carrying discrepancies along when running the simulations.
sec_g_tr = - (sec_row_tr + sec_h_tr + sec_f_a_tr + sec_f_d_tr + sec_nf_tr) # The database is almost consistent, but I redifine sec_g to make it fully consistent and avoid carrying discrepancies along when running the simulations.sec_h_rvx=diff(sec_h)-sec_h_tr[-1]
sec_f_a_rvx=diff(sec_f_a)-sec_f_a_tr[-1]
sec_f_d_rvx=diff(sec_f_d)-sec_f_d_tr[-1]
sec_nf_rvx=diff(sec_nf)-sec_nf_tr[-1]
sec_g_rvx=diff(sec_g)-sec_g_tr[-1]
sec_row_rvx=diff(sec_row)-sec_row_tr[-1]l_f = - (l_h + l_nf + l_g + l_row) # The database is almost consistent, but I redifine l_f to make it fully consistent and avoid carrying discrepancies along when running the simulations.
l_f_tr = - (l_h_tr + l_nf_tr + l_g_tr + l_row_tr) # The database is almost consistent, but I redifine l_f to make it fully consistent and avoid carrying discrepancies along when running the simulations.l_h_rvx=diff(l_h)-l_h_tr[-1]
l_f_rvx=diff(l_f)-l_f_tr[-1]
l_nf_rvx=diff(l_nf)-l_nf_tr[-1]
l_g_rvx=diff(l_g)-l_g_tr[-1]
l_row_rvx=diff(l_row)-l_row_tr[-1]int_nf_sec = TSLAG(int_nf_sec, 1) + TSDELTA(sec_nf)*ibd
int_nf_adj = (int_r_nf - int_p_nf) - (stats::lag(idep,-1)*stats::lag(iba_nf,-1) + stats::lag(iloan,-1)*stats::lag(l_nf,-1) +
int_nf_sec )
int_h_sec = TSLAG(int_h_sec, 1) + TSDELTA(sec_h)*ibd
int_h_adj = (int_r_h - int_p_h) - (stats::lag(idep,-1)*stats::lag(iba_h,-1) +stats::lag(iloan,-1)*stats::lag(l_h,-1)+ int_h_sec ) # this calculation calculates the discrepancy for interest payments as net flow.#Below I (hamid) compute discrepancy between interest payments and reciepts separately to create a measure of propert income (paid and recieved) instead of just using net property income (npropinc) in the model
int_r_h_adj = int_r_h - (stats::lag(idep,-1)*stats::lag(iba_h,-1) + stats::lag(ibd,-1)*stats::lag(sec_h,-1))
int_p_h_adj = int_p_h + stats::lag(iloan,-1)*stats::lag(l_h,-1)#For the rest of the sectors, we just calculate the discrepancies based on net asset holding
int_g_sec = TSLAG(int_g_sec, 1) + TSDELTA(sec_g)*ibd
int_g_adj = (int_r_g - int_p_g) - (stats::lag(idep,-1)*stats::lag(iba_g,-1) + stats::lag(iloan,-1)*stats::lag(l_g,-1) + int_g_sec)
int_row_sec = TSLAG(int_row_sec, 1) + TSDELTA(sec_row)*iboa
int_row_adj = (int_r_row - int_p_row) - (stats::lag(idep,-1)*stats::lag(iba_row,-1) + stats::lag(iloan,-1)*stats::lag(l_row,-1)) + int_row_sec
int_f_sec = TSLAG(int_f_a_sec, 1) + TSDELTA(sec_f_a)*ibd +
TSLAG(int_f_d_sec, 1) + TSDELTA(sec_f_d)*ibd
int_f_adj = (int_r_f - int_p_f) - (stats::lag(idep,-1)*stats::lag(iba_f,-1) + stats::lag(iloan,-1)*stats::lag(l_f,-1) +
int_f_sec )test = int_nf_adj + int_h_adj + int_g_adj + int_f_adj + int_row_adjBelow we create series for equities viz-a-viz counterparties. The data is only available from 2012 onwards so we use the porportion w.r.t to the aggregate payments to create data back in time (because we have aggregate data)
alpha_nf_rv = eq_h_nf_rv[31:60]/(eq_h_nf_rv[31:60] + eq_h_f_rv[31:60] + eq_h_row_rv[31:60]) ## mean of alpha is 0.57 (excluding the spike in the start of the sample somwhere 2013q3 (not sure about the exact point))
alpha_f_rv = eq_h_f_rv[31:60]/(eq_h_nf_rv[31:60] + eq_h_f_rv[31:60] + eq_h_row_rv[31:60]) # mean of alpha is 0.37 (excluding the spike in the start of the sample somwhere 2013q3 (not sure about the exact point))
alpha_row_rv = eq_h_row_rv[31:60]/(eq_h_nf_rv[31:60] + eq_h_f_rv[31:60] + eq_h_row_rv[31:60]) # mean of alpha is 0.06 (excluding the spike in the start of the sample somwhere 2013q3 (not sure about the exact point))
mean(alpha_nf_rv[c(1:2,4:30)])## [1] 0.5599535mean(alpha_f_rv[c(1:2,4:30)])## [1] 0.3865554mean(alpha_row_rv[c(1:2,4:30)])## [1] 0.05349111dummies for equity revaluation equations
#dummy_1=create_dummy_ts(start_basic = c(2005, 1), end_basic=c(2020,1),
#dummy_start=c(2005,2), dummy_end = c(2012,4),
##basic_value = 0, dummy_value = 1, frequency = 4)
dummy_1=ts(c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), start = c(2005, 2), end = c(2020,1), frequency = 4)
dummy_2=create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2013,1), dummy_end = c(2020,1),
basic_value = 0, dummy_value = 1, frequency = 4)#Tjek om rigtige
eq_h_row_rvx = dummy_1*0.06*eq_h_rvx + dummy_2*eq_h_row_rv
eq_h_nf_rvx = dummy_1*0.57*eq_h_rvx + dummy_2*eq_h_nf_rv
eq_h_f_rvx = dummy_1*0.37*eq_h_rvx + dummy_2*eq_h_f_rv
eq_h_rvx1 = eq_h_nf_rvx + eq_h_f_rvx + eq_h_row_rvxWe now create stock of equities data based on counter parties.
alpha_nf = eq_h_nf[31:60]/eq_h[31:60] #mean of the series 0.275
alpha_f = eq_h_f[31:60]/eq_h[31:60] #mean of the series 0.663
#alpha_row = eq_h_row/eq_h
alpha_row = 1 - alpha_nf - alpha_f
### I create these to keep the same time dimension
alpha_nf= ts(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,alpha_nf),start = c(2005,2), frequency = 4)
alpha_f= ts(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,alpha_f),start = c(2005,2), frequency = 4)
alpha_row= ts(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,alpha_row),start = c(2005,2), frequency = 4)#eq_h_nf = dummy_1*0.275*eq_h + dummy_2*eq_h_nf
#eq_h_f = dummy_1*0.663*eq_h + dummy_2*eq_h_f
#eq_h_row = dummy_1*0.062*eq_h + dummy_2*eq_h_row gamma_1 = eq_h_nf / eq_h
gamma_2 = eq_h_f / eq_h#series iba_h_tr = fnlibrary(stats)
div_nf2_adj = (div_r_nf - div_p_nf) - ((stats::lag(eq_nf_a_nf,-1) + stats::lag(eq_nf_a_f,-1) - stats::lag(eq_nf_l_nf,-1) + stats::lag(eq_h_nf,-1)+ stats::lag(eq_row_a_nf,-1) + stats::lag(eq_f_a_nf,-1) + stats::lag(eq_g_nf,-1)))* stats::lag(divd,-1) + stats::lag(eq_nf_a_row,-1)*stats::lag(diva,-1)div_nf1_adj = (div_r_nf - div_p_nf) - (stats::lag(Neq_nf,-1)*stats::lag(divd,-1))div_nf_adj = d_20124*(div_nf2_adj) + (1-d_20124)*(div_nf1_adj)div_nf =d_20124*(((stats::lag(eq_nf_a_nf,-1) + stats::lag(eq_nf_a_f,-1) - stats::lag(eq_nf_l_nf,-1) + stats::lag(eq_h_nf,-1) + stats::lag(eq_row_a_nf,-1) + stats::lag(eq_f_a_nf,-1) + stats::lag(eq_g_nf,-1)))* stats::lag(divd,-1) + stats::lag(eq_nf_a_row,-1)*stats::lag(diva,-1)) + (1-d_20124)*(stats::lag(Neq_nf,-1)*stats::lag(divd,-1)) + div_nf_adj
div_nf1 = div_r_nf - div_p_nfdiv_f2_adj = (div_r_f - div_p_f) - ((stats::lag(eq_f_a_nf,-1) + stats::lag(eq_f_a_f,-1) - (stats::lag(eq_f_l_f,-1) + stats::lag(eq_h_f,-1)+ stats::lag(eq_row_a_f,-1) + stats::lag(eq_row_a_f,-1) + stats::lag(eq_g_f,-1)))* stats::lag(divd,-1) + stats::lag(eq_f_a_row,-1)*stats::lag(diva,-1))div_f1_adj = (div_r_f - div_p_f) - (stats::lag(Neq_f,-1)*stats::lag(divd,-1))
div_f_adj = d_20124*div_f2_adj + (1-d_20124)*(div_f1_adj)div_f = d_20124 *(((stats::lag(eq_f_a_f,-1) + stats::lag(eq_nf_a_nf,-1)) - (stats::lag(eq_f_l_f,-1) + stats::lag(eq_h_f,-1)+ stats::lag(eq_row_a_f,-1) + stats::lag(eq_nf_a_f,-1) + stats::lag(eq_g_f,-1)))* stats::lag(divd,-1) + stats::lag(eq_f_a_row,-1)*stats::lag(diva,-1)) + (1-d_20124)*((stats::lag(Neq_f,-1)*stats::lag(divd,-1))) + div_f_adj
div_f1 = div_r_f - div_p_fdiv_h2_adj = div_r_h - ((stats::lag(eq_h_nf,-1) + stats::lag(eq_h_f,-1))*stats::lag(divd,-1) + stats::lag(eq_h_row,-1)*stats::lag(diva,-1))
div_h1_adj = div_r_h - (stats::lag(eq_h,-1)*stats::lag(divd,-1))
div_h_adj = d_20124*div_h2_adj + (1-d_20124)*(div_h1_adj)div_h = d_20124*((stats::lag(eq_h_nf,-1) + stats::lag(eq_h_f,-1))*stats::lag(divd,-1) + stats::lag(eq_h_row,-1)*stats::lag(diva,-1)) + (1-d_20124)*(stats::lag(eq_h,-1)*stats::lag(divd,-1)) + div_h_adj
div_h1 = div_r_h - div_p_hdiv_g2_adj = div_r_g - ((stats::lag(eq_g_nf,-1) + stats::lag(eq_g_f,-1))*stats::lag(divd,-1) + stats::lag(eq_g_row,-1)*stats::lag(diva,-1))
div_g1_adj = div_r_g - (stats::lag(eq_g,-1)*stats::lag(divd,-1))
div_g_adj = d_20124*div_g2_adj + (1-d_20124)*(div_g1_adj)
div_g = d_20124 * ( (stats::lag(eq_g_nf,-1) + stats::lag(eq_g_f,-1))*stats::lag(divd,-1) + stats::lag(eq_g_row,-1)*stats::lag(diva,-1) ) + (1-d_20124) * ((stats::lag(eq_g,-1)*stats::lag(divd,-1))) + div_g_adj
div_g1 = div_r_g - div_p_gdiv_row2_adj = (div_r_row - div_p_row) - ((stats::lag(eq_row_a_nf,-1) + stats::lag(eq_row_a_f,-1))*stats::lag(divd,-1) - ((stats::lag(eq_nf_a_row,-1)+stats::lag(eq_f_a_row,-1)+stats::lag(eq_g_row,-1)+stats::lag(eq_h_row,-1))*stats::lag(diva,-1)))
div_row1_adj = (div_r_row - div_p_row) - (stats::lag(Neq_row,-1)*stats::lag(divd,-1))
div_row_adj = d_20124*div_row2_adj + (1-d_20124)*(div_row1_adj)div_row = d_20124 * ( (stats::lag(eq_row_a_nf,-1) + stats::lag(eq_row_a_f,-1))*stats::lag(divd,-1) - ((stats::lag(eq_nf_a_row,-1)+stats::lag(eq_f_a_row,-1)+stats::lag(eq_g_row,-1)+stats::lag(eq_h_row,-1))*stats::lag(diva,-1))) + (1-d_20124) * ((stats::lag(Neq_row,-1)*stats::lag(divd,-1))) + div_row_adjdiv_row1 = div_r_row - div_p_rowcheck_div1 = (div_r_row - div_p_row) + (div_r_g - div_p_g) + (div_r_h - div_p_h) + (div_r_nf - div_p_nf) + (div_r_f - div_p_f)
check_div = div_h + div_f + div_g + div_nf + div_row
check_div_adj1 = div_h1_adj + div_f1_adj +div_nf1_adj +div_g1_adj +div_row1_adj
check_div_adj2 = div_h2_adj + div_f2_adj +div_nf2_adj +div_g2_adj +div_row2_adj ins_nf_adj = (ins_r_nf - ins_p_nf) - (stats::lag(ins_nf,-1)*stats::lag(insu,-1))
ins_f_adj = (ins_r_f - ins_p_f) - (stats::lag(ins_f,-1)*stats::lag(insu,-1))
ins_g_adj = (ins_r_g - ins_p_g) - (stats::lag(ins_g,-1)*stats::lag(insu,-1))
ins_h_adj = (ins_r_h - ins_p_h) - (stats::lag(ins_h,-1)*stats::lag(insu,-1))
ins_row_adj = (ins_r_row - ins_p_row) - (stats::lag(ins_row,-1)*stats::lag(insu,-1))ins_h_tr_excl_d8 = ins_h_tr - d8_hBelow I compute the adjustment variables that correct the discrepancy between net lending and financial net lending
nl_h = s_h - i_h - np_h + ctr_h
fnl_h = iba_h_tr + sec_h_tr + l_h_tr + eq_h_tr + ins_h_tr
nl_h_adj = fnl_h -nl_hnl_nf = s_nf - i_nf - np_nf + ctr_nf
fnl_nf = iba_nf_tr + sec_nf_tr + l_nf_tr + Neq_nf_tr + ins_nf_tr
nl_nf_adj = fnl_nf - nl_nfnl_f = s_f - i_f - np_f + ctr_f
fnl_f = iba_f_tr + sec_f_a_tr + sec_f_d_tr + l_f_tr + eq_f_a_tr - eq_f_l_tr + ins_f_tr
nl_f_adj = fnl_f - nl_fnl_g = s_g - i_g - np_g + ctr_g
fnl_g = iba_g_tr + eq_g_tr + sec_g_tr + l_g_tr + ins_g_tr
nl_g_adj = fnl_g - nl_g int_row = (stats::lag(idep,-1)*stats::lag(iba_row,-1) + stats::lag(iloan,-1)*stats::lag(l_row,-1)) +
TSLAG(int_f_a_sec, 1) + TSDELTA(sec_f_a)*iboa
div_row = d_20124*( (stats::lag(eq_row_a_nf,-1) + stats::lag(eq_row_a_f,-1))*stats::lag(divd,-1) - ((stats::lag(eq_nf_a_row,-1)+stats::lag(eq_f_a_row,-1)+stats::lag(eq_g_row,-1)+stats::lag(eq_h_row,-1))*stats::lag(diva,-1))) + (1-d_20124) * ((stats::lag(Neq_row,-1)*stats::lag(divd,-1))) + div_row_adj
insu_row = stats::lag(ins_row,-1)*stats::lag(insu,-1)
npropinc_row = int_row + int_row_adj + div_row + insu_row + ins_row_adj + (res_r_row) - (res_p_row)
nl_row = m - x + p_tax_row - p_sub_row + (w_row_r - w_row_p) + (npropinc_row) + (tax_row) + scon_row_r - scon_row_p + sben_row_r - sben_row_p + oth_row + ctr_row - np_row
#nl_row1 = s_row + ctr_row - np_row
fnl_row = iba_row_tr + Neq_row_tr + sec_row_tr + l_row_tr + ins_row_tr
nl_row_adj = fnl_row - nl_row sumfnl = fnl_h + fnl_f + fnl_nf + fnl_g + fnl_row
sumnl = nl_h + nl_f + nl_nf + nl_g + nl_row
sumnladj = nl_h_adj + nl_f_adj + nl_nf_adj + nl_g_adj + nl_row_adjtax rates for wages and property income (the two tax rates are determined throgh an exogenous regression without an intercept
tax_h_hat = tax_rate1*(w_h_r +nsben_h + oth_h) + tax_rate2*(propinc_r_h - propinc_p_h + b2_h_r)
tax_h_adj = (-tax_h - tax_h_hat)
tax_h = -(tax_h_hat + tax_h_adj)
yd2a_h =(1 - tax_rate2)*(propinc_r_h + b2_h_r) # property income part of the disposable income (capitalists)
yd2b_h = (1 - tax_rate2)*(-propinc_p_h)
yd1_h =(1 - tax_rate1)*(w_h_r + nsben_h + oth_h) - tax_h_adj # wage and benefits part of the disposable income (workers)
tax_p_hat = y*(tax_rate_p)
tax_p_adj = (p_tax - tax_p_hat)
p_tax = tax_p_hat + tax_p_adj
tax_rate_nf = -tax_nf/yCreating Real variables
yd_hk=yd_h/pc # real disposable income
w_h_rk = w_h_r/pc #real wages recieved by households
nsben_hk = nsben_h /pc #real social benefits recieved by the households
npropinc_hk = npropinc_h/pc # real property income (net)
b2_hk = b2_h_r/pc
yd1_hk = yd1_h/pc
yd2a_hk = yd2a_h/pc
yd2b_hk = yd2b_h/pcfnw_hk = fnw_h/pc #real net wealth of householdsVariables for the estimation of the investment equation
Labour market
#empl = N/1000
#empl_ds = Nadj/1000
wage = w_h_r/emp
# wage = w_h_rk_ds /(empl_ds)
Nu=(w_row_r - w_row_p)/wage
Nf = Nu + emp
prod = y/Nf
LF = unemp + emp
lfadj = unempadj + empadj
ur = unemp/LF
ur_ds = unempadj/lfadj
# yk = y/(py/100)
prodk = yk/Nf
yf = w + b2
ws = w/yf
ps = 1 - ws
# w = w_h_r + (W_row_r - W_row_p)
fdis = yf/y
urterm = ur - urs
wageindex = wage/wage[22] #element from 2010Q3
priv = pconk + ik + xk
part = LF*1000/pop
old_age_ratio = retired_pop/pop
zaland_jesper = pop - LF*1000
nben_h = nsben_h + d8_hnl_check= (nl_h + nl_f + nl_nf + nl_g + nl_row) # needs to be fixed:
fnl_check= (fnl_h + fnl_f + fnl_nf + fnl_g + fnl_row) # this one is fine: because there is almost no connection between the real side and financial side at the moment
check_np = np_row + np_h + np_f + np_nf + np_g # this one is fine:
check_ctr = ctr_row + ctr_h + ctr_f + ctr_nf + ctr_g # this one is fine:
check_invest = i - i_f - i_nf - i_g - i_h # this one is fine:
check_iba = iba_h + iba_f + iba_nf + iba_g + iba_row #needs to be fixed:
check_tax = tax_g + tax_nf + tax_f + tax_h + tax_row # this one is fine:
check_iba_rv = iba_h_rv + iba_f_rv + iba_nf_rv + iba_g_rv + iba_row_rv
check_iba_tr = iba_h_tr + iba_f_tr + iba_nf_tr + iba_g_tr + iba_row_tr
check_eq = eq_h + (eq_f_a - eq_f_l) + (eq_nf_a - eq_nf_l) + eq_g + (eq_row_a - eq_row_l) # This one is now fixed
check_eq_tr = eq_h_tr + Neq_nf_tr + Neq_f_tr + eq_g_tr + Neq_row_tr + eq_g_tr
check_l = l_h + l_f + l_nf + l_g + l_row # problematic after scenario 2
check_l_tr = l_f_tr + l_h_tr + l_nf_tr + l_g_tr + l_row_tr
check_ins = ins_h + ins_f + ins_nf + ins_g + ins_row # problematic after scenario 2
check_ins_tr = ins_f_tr + ins_h_tr + ins_nf_tr + ins_g_tr + ins_row_tr
check_sec = sec_h + sec_f_a + sec_f_d + sec_nf + sec_g + sec_row ## needs to be fixedVed ik helt om nedenstående skal med
#smpl 2005q2 2019q1
#equation eq41.ls emp = P(251) + P(252)*SD1 + P(253)*SD2 + P(254)*SD3
#series emp_ds = emp - (P(251) + P(252)*SD1 + P(253)*SD2 + P(254)*SD3) + @mean(emp)
tobinq = (eq_nf_l) / (equip_nfc + bd_nfc)The model
library(mFilter)
library(bimets)
library(knitr)Deasonalise the variables using the dummy variable technique
## I_BD_H_K
reg_1 = lm(i_bd_h_k~ sd1+ sd2 + sd3)
i_bd_h_k_ds= reg_1$residuals + mean(i_bd_h_k)
i_bd_h_k_ds=ts(i_bd_h_k_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_10 =reg_1$coefficients[1]
alpha_10=ts(alpha_10,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_11=reg_1$coefficients[2]
alpha_11=ts(alpha_11,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_12=reg_1$coefficients[3]
alpha_12=ts(alpha_12,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_13=reg_1$coefficients[4]
alpha_13=ts(alpha_13,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_i_bd_h_k= mean(i_bd_h_k)
mean_i_bd_h_k=ts(mean_i_bd_h_k,start = c(2005,2), end = c(2020,1), frequency = 4 )
## I_EQUIP_H_K
reg_3 = lm(i_equip_h_k~ sd1+ sd2 + sd3)
i_equip_h_k_ds= reg_3$residuals + mean(i_equip_h_k)
i_equip_h_k_ds=ts(i_equip_h_k_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_20 =reg_3$coefficients[1]
alpha_20=ts(alpha_20,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_21=reg_3$coefficients[2]
alpha_21=ts(alpha_21,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_22=reg_3$coefficients[3]
alpha_22=ts(alpha_22,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_23=reg_3$coefficients[4]
alpha_23=ts(alpha_23,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_i_equip_h_k= mean(i_equip_h_k)
mean_i_equip_h_k=ts(mean_i_equip_h_k,start = c(2005,2), end = c(2020,1), frequency = 4 )
# i_bd_nfc_k_ds
reg_4 = lm(i_bd_nfc_k~ sd1+ sd2 + sd3)
i_bd_nfc_k_ds= reg_4$residuals + mean(i_bd_nfc_k)
i_bd_nfc_k_ds=ts(i_bd_nfc_k_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_30 =reg_4$coefficients[1]
alpha_30=ts(alpha_30,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_31=reg_4$coefficients[2]
alpha_31=ts(alpha_31,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_32=reg_4$coefficients[3]
alpha_32=ts(alpha_32,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_33=reg_4$coefficients[4]
alpha_33=ts(alpha_33,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_i_bd_nfc_k= mean(i_bd_nfc_k)
mean_i_bd_nfc_k=ts(mean_i_bd_nfc_k,start = c(2005,2), end = c(2020,1), frequency = 4 )
## ps_ds
reg_6 = lm(ps~ sd1+ sd2 + sd3)
ps_ds= reg_6$residuals + mean(ps)
ps_ds=ts(ps_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## i_equip_nfc_k_ds
reg_7 = lm(i_equip_nfc_k~ sd1+ sd2 + sd3)
i_equip_nfc_k_ds= reg_7$residuals + mean(i_equip_nfc_k)
i_equip_nfc_k_ds=ts(i_equip_nfc_k_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_40 =reg_7$coefficients[1]
alpha_40=ts(alpha_40,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_41=reg_7$coefficients[2]
alpha_41=ts(alpha_41,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_42=reg_7$coefficients[3]
alpha_42=ts(alpha_42,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_43=reg_7$coefficients[4]
alpha_43=ts(alpha_43,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_i_equip_nfc_k= mean(i_equip_nfc_k)
mean_i_equip_nfc_k=ts(mean_i_equip_nfc_k,start = c(2005,2), end = c(2020,1), frequency = 4 )
## pconk_ds
reg_8 = lm(pconk~ sd1+ sd2 + sd3)
pconk_ds= reg_8$residuals + mean(pconk)
pconk_ds=ts(pconk_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_00 =reg_8$coefficients[1]
alpha_00=ts(alpha_00,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_01=reg_8$coefficients[2]
alpha_01=ts(alpha_01,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_02=reg_8$coefficients[3]
alpha_02=ts(alpha_02,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_03=reg_8$coefficients[4]
alpha_03=ts(alpha_03,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_pconk= mean(pconk)
mean_pconk=ts(mean_pconk,start = c(2005,2), end = c(2020,1), frequency = 4 )
## B2_HK_ds
reg_9 = lm(b2_hk~ sd1+ sd2 + sd3)
b2_hk_ds= reg_9$residuals + mean(b2_hk)
b2_hk_ds=ts(b2_hk_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## yd1_hk
reg_10 = lm(yd1_hk~ sd1+ sd2 + sd3)
yd1_hk_ds= reg_10$residuals + mean(yd1_hk)
yd1_hk_ds=ts(yd1_hk_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_100 =reg_10$coefficients[1]
alpha_100=ts(alpha_100,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_101=reg_10$coefficients[2]
alpha_101=ts(alpha_101,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_102=reg_10$coefficients[3]
alpha_102=ts(alpha_102,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_103=reg_10$coefficients[4]
alpha_103=ts(alpha_103,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_yd1_hk= mean(yd1_hk)
mean_yd1_hk=ts(mean_yd1_hk,start = c(2005,2), end = c(2020,1), frequency = 4)
## yd2a_hk
reg_11 = lm(yd2a_hk~ sd1+ sd2 + sd3)
yd2a_hk_ds= reg_11$residuals + mean(yd2a_hk)
yd2a_hk_ds=ts(yd2a_hk_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_110 =reg_11$coefficients[1]
alpha_110=ts(alpha_110,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_111=reg_11$coefficients[2]
alpha_111=ts(alpha_111,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_112=reg_11$coefficients[3]
alpha_112=ts(alpha_112,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_113=reg_11$coefficients[4]
alpha_113=ts(alpha_113,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_yd2a_hk= mean(yd2a_hk)
mean_yd2a_hk=ts(mean_yd2a_hk,start = c(2005,2), end = c(2020,1), frequency = 4)
##w_h_rk
reg_12 = lm(w_h_rk~ sd1+ sd2 + sd3)
w_h_rk_ds= reg_12$residuals + mean(w_h_rk)
w_h_rk_ds=ts(w_h_rk_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## wage
reg_13 = lm(wage~ sd1+ sd2 + sd3)
wage_ds= reg_13$residuals + mean(wage)
wage_ds=ts(wage_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_50 =reg_13$coefficients[1]
alpha_50=ts(alpha_50,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_51=reg_13$coefficients[2]
alpha_51=ts(alpha_51,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_52=reg_13$coefficients[3]
alpha_52=ts(alpha_52,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_53=reg_13$coefficients[4]
alpha_53=ts(alpha_53,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_wage= mean(wage)
mean_wage=ts(mean_wage,start = c(2005,2), end = c(2020,1), frequency = 4)
## pc
reg_14 = lm(pc~ sd1+ sd2 + sd3)
pc_ds= reg_14$residuals + mean(pc)
pc_ds=ts(pc_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_60 =reg_14$coefficients[1]
alpha_60=ts(alpha_60,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_61=reg_14$coefficients[2]
alpha_61=ts(alpha_61,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_62=reg_14$coefficients[3]
alpha_62=ts(alpha_62,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_63=reg_14$coefficients[4]
alpha_63=ts(alpha_63,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_pc= mean(pc)
mean_pc=ts(mean_pc,start = c(2005,2), end = c(2020,1), frequency = 4)
## pm
reg_15 = lm(pm~ sd1+ sd2 + sd3)
pm_ds= reg_15$residuals + mean(pm)
pm_ds=ts(pm_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_200 =reg_15$coefficients[1]
alpha_200=ts(alpha_200,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_201=reg_15$coefficients[2]
alpha_201=ts(alpha_201,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_202=reg_15$coefficients[3]
alpha_202=ts(alpha_202,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_203=reg_15$coefficients[4]
alpha_203=ts(alpha_203,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_pm= mean(pm)
mean_pm=ts(mean_pm,start = c(2005,2), end = c(2020,1), frequency = 4)
### ur
reg_16 = lm(ur~ sd1+ sd2 + sd3)
ur_ds= reg_16$residuals + mean(ur)
ur_ds=ts(ur_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_140 =reg_16$coefficients[1]
alpha_140=ts(alpha_140,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_141=reg_16$coefficients[2]
alpha_141=ts(alpha_141,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_142=reg_16$coefficients[3]
alpha_142=ts(alpha_142,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_143=reg_16$coefficients[4]
alpha_143=ts(alpha_143,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_ur= mean(ur)
mean_ur=ts(mean_ur,start = c(2005,2), end = c(2020,1), frequency = 4)
## yk
reg_17 = lm(yk~ sd1+ sd2 + sd3)
reg_17a = lm(y~ sd1+ sd2 + sd3)
yk_ds= reg_17$residuals + mean(yk)
y_ds= reg_17a$residuals + mean(y)
yk_ds=ts(yk_ds,start = c(2005,2), end = c(2020,1), frequency = 4)
y_ds=ts(y_ds,start = c(2005,2), end = c(2020,1), frequency = 4)
u_ds=yk_ds/(bd_nfc_k+equip_nfc_k) #Rate of capacity utilization
lambda <- 1600
hp = hpfilter(yk_ds, lambda)
yk_ds_potential <- hp$trend
yk_ds_potential=ts(yk_ds_potential, start = c(2005,2), end = c(2020,1), frequency = 4 )
u_ds=ts(u_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
prate=s_nf/(stats::lag(bd_nfc,-1)+stats::lag(equip_nfc,-1)) # Profit rate
alpha_90 =reg_17$coefficients[1]
alpha_90=ts(alpha_90,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_90a =reg_17a$coefficients[1]
alpha_90a=ts(alpha_90a,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_91=reg_17$coefficients[2]
alpha_91=ts(alpha_91,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_91a=reg_17a$coefficients[2]
alpha_91a=ts(alpha_91a,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_92=reg_17$coefficients[3]
alpha_92=ts(alpha_92,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_92a=reg_17a$coefficients[3]
alpha_92a=ts(alpha_92a,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_93=reg_17$coefficients[4]
alpha_93=ts(alpha_93,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_93a=reg_17a$coefficients[4]
alpha_93a=ts(alpha_93a,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_yk= mean(yk)
mean_y = mean(y)
mean_yk=ts(mean_yk,start = c(2005,2), end = c(2020,1), frequency = 4)
mean_y=ts(mean_y,start = c(2005,2), end = c(2020,1), frequency = 4)
## wageindex
reg_18 = lm(wageindex~ sd1+ sd2 + sd3)
wageindex_ds= reg_18$residuals + mean(wageindex)
wageindex_ds=ts(wageindex_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## priv
reg_19 = lm(priv~ sd1+ sd2 + sd3)
priv_ds= reg_19$residuals + mean(priv)
priv_ds=ts(priv_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## mk
reg_20 = lm(mk~ sd1+ sd2 + sd3)
mk_ds= reg_20$residuals + mean(mk)
mk_ds=ts(mk_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_70 =reg_20$coefficients[1]
alpha_70=ts(alpha_70,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_71=reg_20$coefficients[2]
alpha_71=ts(alpha_71,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_72=reg_20$coefficients[3]
alpha_72=ts(alpha_72,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_73=reg_20$coefficients[4]
alpha_73=ts(alpha_73,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_mk= mean(mk)
mean_mk=ts(mean_mk,start = c(2005,2), end = c(2020,1), frequency = 4)
## prodk
reg_21 = lm(prodk~ sd1+ sd2 + sd3)
prodk_ds= reg_21$residuals + mean(prodk)
prodk_ds=ts(prodk_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## prate
##This one is shorter but not sure it also is in the Eviews code
reg_22 = lm(prate~ sd1[-1]+ sd2[-1] + sd3[-1])
prate_ds= reg_22$residuals + mean(prate)
prate_ds=ts(prate_ds,start = c(2005,3), end = c(2020,1), frequency = 4 )
alpha_120 =reg_22$coefficients[1]
alpha_120=ts(alpha_120,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_121=reg_22$coefficients[2]
alpha_121=ts(alpha_121,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_122=reg_22$coefficients[3]
alpha_122=ts(alpha_122,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_123=reg_22$coefficients[4]
alpha_123=ts(alpha_123,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_prate= mean(prate)
mean_prate=ts(mean_prate,start = c(2005,2), end = c(2020,1), frequency = 4)
## bd_nfc_k
reg_23 = lm(bd_nfc_k~ sd1+ sd2 + sd3)
bd_nfc_k_ds= reg_23$residuals + mean(bd_nfc_k)
bd_nfc_k_ds=ts(bd_nfc_k_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## xk
reg_24 = lm(xk~ sd1+ sd2 + sd3)
xk_ds= reg_24$residuals + mean(xk)
xk_ds=ts(xk_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_80 =reg_24$coefficients[1]
alpha_80=ts(alpha_80,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_81=reg_24$coefficients[2]
alpha_81=ts(alpha_81,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_82=reg_24$coefficients[3]
alpha_82=ts(alpha_82,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_83=reg_24$coefficients[4]
alpha_83=ts(alpha_83,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_xk= mean(xk)
mean_xk=ts(mean_xk,start = c(2005,2), end = c(2020,1), frequency = 4)
## rer
reg_25 = lm(rer~ sd1+ sd2 + sd3)
rer_ds= reg_25$residuals + mean(rer)
rer_ds=ts(rer_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## prod
reg_27 = lm(prod~ sd1+ sd2 + sd3)
prod_ds= reg_27$residuals + mean(prod)
prod_ds=ts(prod_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
## ps
reg_28 = lm(ps~ sd1+ sd2 + sd3)
ps_ds= reg_28$residuals + mean(ps)
ps_ds=ts(ps_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_130 =reg_28$coefficients[1]
alpha_130=ts(alpha_130,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_131=reg_28$coefficients[2]
alpha_131=ts(alpha_131,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_132=reg_28$coefficients[3]
alpha_132=ts(alpha_132,start = c(2005,2), end = c(2020,1), frequency = 4 )
alpha_133=reg_28$coefficients[4]
alpha_133=ts(alpha_133,start = c(2005,2), end = c(2020,1), frequency = 4 )
mean_ps= mean(ps)
mean_ps=ts(mean_ps,start = c(2005,2), end = c(2020,1), frequency = 4)
## y
reg_29 = lm(y~ sd1+ sd2 + sd3)
y_ds= reg_29$residuals + mean(y)
y_ds=ts(y_ds,start = c(2005,2), end = c(2020,1), frequency = 4 )## Disse skal komme efter deseason
rw_ds = wage_ds/pc_ds #real wage rate based on deseasonalized variables
reprate_bd_h = (mean(delta_bd_h)*stats::lag(bd_h_k,-1))/i_bd_h_k_ds # replacement rate
#New wage equations
inflation= (pc/TSLAG(pc,4)) - 1
growth = (yk_ds/TSLAG(yk_ds,4)) - 1
inflation_t= (pc/TSLAG(pc,4)) - 1
inflation_t = ts(c(0,0,0, inflation_t), start = c(2005,3), frequency = 4 )
wage_ds_t= sd1* wage_ds*(1+inflation_t) + sd2* TSLAG(wage_ds,1)*(1+TSLAG(inflation_t,1)) + sd3* TSLAG(wage_ds,2)*(1+TSLAG(inflation_t,2)) + sd4* TSLAG(wage_ds,3)*(1+TSLAG(inflation_t,3))
inflation_tt= inflation_t
# New price equations
pg_adj = log(pg) - (0.840852289293*log(pc) - 0.0401650251402)
p_bd_adj = log(p_bd) - (0.988897636487*log(pc) +
0.0286611434831)
p_equip_adj = log(p_equip) -( 0.304376220161*log(pc) +
0.0160136953595 )
px_adj= log(px) - (0.638216896739*log(pc) - 0.012650117362)Extra variables created to run the model:
eq_nf_lx = eq_nf_a_nf + eq_h_nf + eq_row_a_nf + eq_f_a_nf + eq_g_nf
yh2a = propinc_r_h + b2_h_r
yh2b = - propinc_p_h
aa_check = TSLAG(eq_h_f,1)*TSLAG(divd,1)
insu_h = TSLAG(ins_h,1)*TSLAG(insu,1) + ins_h_adj
yd_h1 = yh_h + tax_h + nben_h
sec_h_tr_g=sec_h_tr
eq_h_test = eq_h - (eq_h_nf + eq_h_f + eq_h_row)
lev_h = l_h/yd_h
fa_h = iba_h + sec_h + eq_h + ins_h
sk= pconk + ik + gk + xk
s = pcon + g + i + x
w_nf = w_h_r + (w_row_r - w_row_p)
int_nf = (TSLAG(idep,1)*TSLAG(iba_nf,1) + TSLAG(iloan,1)*TSLAG(l_nf,1) + int_nf_sec )
insu_nf = TSLAG(ins_nf,1)*TSLAG(insu,1)
npropinc_nf = int_nf + int_nf_adj + div_nf + insu_nf + ins_nf_adj + (res_r_nf ) - (res_p_nf)
eq_nf_ax = eq_nf_a_nf + eq_nf_a_f + eq_nf_a_row
eq_nf_a_test = eq_nf_a - eq_nf_ax
eq_f_lx = eq_nf_a_f + eq_h_f + eq_row_a_f + eq_f_a_f + eq_g_f
eq_nf_l_test = eq_nf_l - eq_nf_lx
fnw_nfk = fnw_nf/pc
int_f_sec = TSLAG(int_f_a_sec, 1) + TSDELTA(sec_f_a)*iboa +
TSLAG(int_f_d_sec, 1) + TSDELTA(sec_f_d)*ibd
int_f =(TSLAG(idep,1)*TSLAG(iba_f,1) + TSLAG(iloan,1)*TSLAG(l_f,1) + int_f_sec )
insu_f = TSLAG(ins_f,1)*TSLAG(insu,1)
npropinc_f = int_f + int_f_adj + div_f + insu_f + ins_f_adj + (res_r_f) - (res_p_f)
nben_f = d8_f
eq_f_ax = eq_f_a_nf + eq_f_a_f + eq_f_a_row
eq_f_l_test = eq_f_l - (eq_f_l_f + eq_h_f + eq_row_a_f + eq_nf_a_f + eq_g_f)
sec_f_d_tr_nf=-sec_nf_tr
sec_f_d_tr_g=sec_f_d_tr-sec_f_d_tr_nf
fnw_fk = fnw_f/pc
int_g = (TSLAG(idep,1)*TSLAG(iba_g,1) + TSLAG(iloan,1)*TSLAG(l_g,1) + int_g_sec)
insu_g = TSLAG(ins_g,1)*TSLAG(insu,1)
npropinc_g = int_g + int_g_adj + div_g + insu_g + ins_g_adj + (res_r_g) - ( res_p_g)
nben_row = scon_row_r - scon_row_p + sben_row_r - sben_row_p
nben_g = - (nben_row + nsben_h + nben_f)
eq_g_ax = eq_g_row + eq_g_f + eq_g_nf
eq_g_test = eq_g - (eq_g_nf + eq_g_f + eq_g_row)
fnw_gk = fnw_g/pc
nx = x - m
cab =-nl_row
fab = (fnl_row)
bop = cab + fab
eq_row_ax = eq_row_a_nf + eq_row_a_f
eq_row_a_test = eq_row_a - (eq_row_a_nf + eq_row_a_f)
eq_row_lx = eq_nf_a_row + eq_h_row + eq_f_a_row + eq_g_row
eq_row_l_test = eq_row_l - (eq_nf_a_row + eq_f_a_row + eq_g_row + eq_h_row)
fnw_rowk = fnw_row/pc
mkp = pc_ds / (wage_ds/prodk_ds + pm_ds)
acc_rate = ik / (bd_h_k+equip_h_k+bd_nfc_k+equip_nfc_k+bd_fc_k+equip_fc_k+bd_g_k+equip_g_k)
yh1 = w_h_r + nsben_h + oth_h
yd_hk_ds = yd1_hk_ds +yd2a_hk_ds + yd2b_hk
propinc_p_nf = int_p_nf + div_p_nf + ins_p_nf + res_p_nf
propinc_r_nf = int_r_nf + div_r_nf + ins_r_nf + res_r_nf
## Creating the new shock variables
prodk_ds_shock = prodk_ds
## Shock_1
pf_shock= pf
pf_shock[37:60] = pf_shock[37:60]*(1+c(0.0008974783, 0.0064048133, 0.0125496529, 0.0229082481, 0.0346682007, 0.0453908804, 0.0530307315, 0.0595944607, 0.0650705888, 0.0694345679, 0.0723580212, 0.0746492118, 0.0768781478, 0.0781198283, 0.0785978437, 0.0789294615, 0.0791401958, 0.0789131355,0.0783520463, 0.0775857653, 0.0769318612, 0.0758262745, 0.0746141259, 0.0735664029))
pm_ds_shock= pm_ds_shock
p_expect_shock = p_expect + 30 # it went up during covid-19 from 20 to 60 points so, introduce 30 points increase here
gdp_tp_shock = gdp_tp
#gdp_tp_shock[39:43] = gdp_tp_shock[39:43]*(1-0.02)
#gdp_tp_shock[44:45] = gdp_tp_shock[44:45]*(1-0.015)
#gdp_tp_shock[46:47] = gdp_tp_shock[46:47]*(1-0.01)
#gdp_tp_shock[48:49] = gdp_tp_shock[48:49]*(1-0.005)
yk_ds_potential_shock = yk_ds_potential
#yk_ds_potential_shock[39:43] = yk_ds_potential_shock[39:43]*(1-0.015)
#yk_ds_potential_shock[44:45] =yk_ds_potential_shock[44:45]*(1-0.01)
#yk_ds_potential_shock[46:47] = yk_ds_potential_shock[46:47]*(1-0.005)
#yk_ds_potential_shock[48:49] = yk_ds_potential_shock[48:49]*(1-0.0025)
## Shock 2
iloan_shock= iloan
iloan_shock[39:43] <- iloan_shock[39:43] + 0.030
iloan_shock[44:45] <- iloan_shock[44:45] + 0.025
iloan_shock[46:47] <- iloan_shock[46:47] + 0.020
iloan_shock[48:49] <- iloan_shock[48:49] + 0.015
iloan_shock[50:51] <- iloan_shock[50:51] + 0.01
idep_shock= idep
idep_shock[39:43] <- idep_shock[39:43] + 0.030
idep_shock[44:45] <- idep_shock[44:45] + 0.025
idep_shock[46:47] <- idep_shock[46:47] + 0.020
idep_shock[48:49] <- idep_shock[48:49] + 0.015
idep_shock[50:51] <- idep_shock[50:51] + 0.01
ibd_shock= ibd
ibd_shock[39:43] <- ibd_shock[39:43] + 0.030
ibd_shock[44:45] <- ibd_shock[44:45] + 0.025
ibd_shock[46:47] <- ibd_shock[46:47] + 0.020
ibd_shock[48:49] <- ibd_shock[48:49] + 0.015
ibd_shock[50:51] <- ibd_shock[50:51] + 0.01
iboa_shock= iboa
iboa_shock[39:43] <- iboa_shock[39:43] + 0.030
iboa_shock[44:45] <- iboa_shock[44:45] + 0.025
iboa_shock[46:47] <- iboa_shock[46:47] + 0.020
iboa_shock[48:49] <- iboa_shock[48:49] + 0.015
iboa_shock[50:51] <- iboa_shock[50:51] + 0.01
## Shock 3
tax_rate1_shock = create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2014,4), dummy_end = c(2016,4),
basic_value = 0.389369 , dummy_value = 0.379369, frequency = 4)
## Shock 4
tax_rate_p_shock = create_dummy_ts(start_basic = c(2005, 2), end_basic=c(2020,1),
dummy_start=c(2014,4), dummy_end = c(2016,4),
basic_value = 0.1628809 , dummy_value = 0.1528809, frequency = 4)
#### Shock variables
shock_1_model=ts(0,start = c(2005,2), end = c(2020,1), frequency = 4)
shock_2_model=ts(0,start = c(2005,2), end = c(2020,1), frequency = 4)
shock_3_model=ts(0,start = c(2005,2), end = c(2020,1), frequency = 4)
shock_4_model=ts(0,start = c(2005,2), end = c(2020,1), frequency = 4)Model Behavioural Equations and identities
S_model.txt="MODEL
COMMENT> Pricing Nexus
COMMENT>
IDENTITY> pg
EQ> LOG(pg) = 0.840852289293*LOG(pc) - 0.0401650251402 +
pg_adj
COMMENT>
IDENTITY> p_bd
EQ> LOG(p_bd) = 0.988897636487*LOG(pc) + 0.0286611434831 +
p_bd_adj
COMMENT>
IDENTITY> p_equip
EQ> LOG(p_equip) = 0.304376220161*LOG(pc) + 0.0160136953595
+ p_equip_adj
COMMENT>
IDENTITY> px
EQ> LOG(px) = 0.638216896739*LOG(pc) - 0.012650117362 +
px_adj
COMMENT> Households
COMMENT>
IDENTITY> int_r_h
EQ> int_r_h = TSLAG(idep,1)*TSLAG(iba_h,1) + TSLAG(int_h_sec, 1) + TSDELTA(sec_h)*ibd + int_r_h_adj
COMMENT>
IDENTITY> int_p_h
EQ> int_p_h = - TSLAG(iloan,1)*TSLAG(l_h,1) + int_p_h_adj
COMMENT>
IDENTITY> div_h
EQ> div_h = d_20124*((TSLAG(eq_h_nf,1) + TSLAG(eq_h_f,1))*TSLAG(divd,1) + TSLAG(eq_h_row,1)*TSLAG(diva,1)) + (1-d_20124)*(TSLAG(eq_h,1)*TSLAG(divd,1)) + div_h_adj
COMMENT>
IDENTITY> aa_check
EQ> aa_check = TSLAG(eq_h_f,1)*TSLAG(divd,1)
COMMENT>
IDENTITY> insu_h
EQ> insu_h = TSLAG(ins_h,1)*TSLAG(insu,1) + ins_h_adj
COMMENT> property income H
IDENTITY> propinc_r_h
EQ> propinc_r_h = int_r_h + div_h + insu_h + res_r_h
COMMENT> ' property expenditure H
IDENTITY> propinc_p_h
EQ> propinc_p_h = int_p_h + res_p_h
COMMENT>
IDENTITY> npropinc_h
EQ> npropinc_h = propinc_r_h - propinc_p_h
COMMENT> Gross income H
IDENTITY> yh_h
EQ> yh_h = w_h_r + b2_h_r + (npropinc_h )
COMMENT>
IDENTITY> yh2a
EQ> yh2a = propinc_r_h + b2_h_r
COMMENT>
IDENTITY> yh2b
EQ> yh2b = - propinc_p_h
COMMENT>
IDENTITY> yh1
EQ> yh1 = w_h_r + nsben_h + oth_h
COMMENT>
IDENTITY> w_h_r
EQ> w_h_r = wage * emp
COMMENT> ' property income part of the disposable income (capitalists)
IDENTITY> yd2a_h
EQ> yd2a_h =(1 - tax_rate2)*(yh2a)
COMMENT>
IDENTITY> yd2b_h
EQ> yd2b_h = (1 - tax_rate2)*(yh2b)
COMMENT> age and benefits part of the disposable income (workers) / tax_h_adj is added here because of the relative size versus yh2
IDENTITY> yd1_h
EQ> yd1_h =(1 - tax_rate1)*(yh1) - tax_h_adj
COMMENT>
IDENTITY> tax_h
EQ> tax_h = -(tax_rate2*(yh2a+yh2b) + tax_rate1*yh1 + tax_h_adj)
COMMENT>
IDENTITY> p_tax
EQ> p_tax = tax_rate_p*y + tax_p_adj
COMMENT>
IDENTITY> yd1_hk
EQ> yd1_hk = yd1_h/pc
COMMENT>
IDENTITY> yd2a_hk
EQ> yd2a_hk = yd2a_h/pc
COMMENT>
IDENTITY> yd2b_hk
EQ> yd2b_hk = yd2b_h/pc
COMMENT> Disposable income
IDENTITY> yd_h
EQ> yd_h = yd1_h + yd2a_h + yd2b_h
COMMENT>
IDENTITY> nsben_h
EQ> nsben_h = nben_h - d8_h
COMMENT> Disposable income (redundant for now)
IDENTITY> yd_h1
EQ> yd_h1 = yh_h + tax_h + nben_h
COMMENT>
IDENTITY> yd_hk
EQ> yd_hk = yd1_hk + yd2a_hk + yd2b_hk
COMMENT>
IDENTITY> yd_hk_ds
EQ> yd_hk_ds = yd1_hk_ds + yd2a_hk_ds + yd2b_hk
COMMENT>
IDENTITY> yd1_hk_ds
EQ> yd1_hk_ds = yd1_hk - (alpha_100 + alpha_101*SD1 + alpha_102*SD2 + alpha_103*SD3) + mean_yd1_hk
COMMENT>
IDENTITY> yd2a_hk_ds
EQ> yd2a_hk_ds = yd2a_hk - (alpha_110 + alpha_111*SD1 + alpha_112*SD2 + alpha_113*SD3) + mean_yd2a_hk
COMMENT> Savings H
IDENTITY> s_h
EQ> s_h = yd_h - pcon + d8_h
COMMENT> Sectoral balance
IDENTITY> nl_h
EQ> nl_h = s_h - i_h - np_h + ctr_h
COMMENT>
BEHAVIORAL> pconk_ds
TSRANGE 2006 2 2020 1
EQ> TSDELTALOG(pconk_ds) = C_2*TSLAG(LOG(pconk_ds),1) + C_3*TSLAG(LOG(yd1_hk_ds),1) + C_4*LOG(TSLAG(yd2a_hk_ds,1) + TSLAG(yd2b_hk,1)) + C_5*TSLAG(LOG(fnw_hk),2) + C_6*TSDELTALOG(TSLAG(pconk_ds,2)) + C_7*TSDELTALOG(TSLAG(pconk_ds,3)) + C_8*TSDELTALOG(yd1_hk_ds) + C_9*TSDELTALOG(yd2a_hk_ds + yd2b_hk) + C_10*d_2008q4 + C_11*d_2018q2 + C_12*d_2020q1 + C_13* time
COEFF> C_2 C_3 C_4 C_5 C_6 C_7 C_8 C_9 C_10 C_11 C_12 C_13
STORE> coe(1)
COMMENT>
IDENTITY> pconk
EQ> pconk = pconk_ds + alpha_00 + alpha_01*SD1 + alpha_02*SD2 + alpha_03*SD3 - mean_pconk
COMMENT> nominal private consumption
IDENTITY> pcon
EQ> pcon = pconk*pc
COMMENT> Er ikke helt korrekt
BEHAVIORAL> i_bd_h_k_ds
TSRANGE 2006 3 2020 1
EQ> LOG(i_bd_h_k_ds) = P_620 +
P_621*TSDELTALOG(TSLAG(i_bd_h_k_ds,1)/TSLAG(bd_h_k,2))+
P_622*TSDELTALOG(TSLAG(i_bd_h_k_ds,3)/TSLAG(bd_h_k,4))+
P_623*TSDELTALOG(TSLAG(p_bd,1)/TSLAG(pi_1,1)) +
P_624*TSDELTALOG(TSLAG(p_bd,2)/TSLAG(pi_1,2)) +
P_625*TSDELTALOG(TSLAG(yd_hk_ds,2)/TSLAG(bd_h_k,3))+
P_626*TSDELTALOG(TSLAG(-l_h,1)/TSLAG(bd_h,2)) +
P_627*LOG(TSLAG(i_bd_h_k_ds,1)/TSLAG(bd_h_k,2)) +
P_628*LOG(TSLAG(yd_hk_ds,1)/TSLAG(bd_h_k,2)) +
P_629*LOG(TSLAG(p_bd,1)/TSLAG(pi_1,1)) +
P_630*LOG(TSLAG(-l_h,1)/TSLAG(bd_h,2)) +
P_631*d_2006q4 +
P_632*d_2014q4 +
alpha_1*LOG(TSLAG(bd_h_k,1)) +
alpha_2* TSLAG(LOG(i_bd_h_k_ds),1) +
alpha_3* TSLAG(-LOG(bd_h_k),2)
COEFF> P_620 P_621 P_622 P_623 P_624 P_625 P_626 P_627 P_628 P_629 P_630 P_631 P_632 alpha_1 alpha_2 alpha_3
RESTRICT> alpha_1 = 1
alpha_2 = 1
alpha_3 = 1
STORE> coe(2)
COMMENT>
IDENTITY> i_bd_h_k
EQ> i_bd_h_k = i_bd_h_k_ds + (alpha_10 + alpha_11*SD1 + alpha_12*SD2 + alpha_13*SD3) - mean_i_bd_h_k
COMMENT>
IDENTITY> i_equip_h_k
EQ> i_equip_h_k = i_equip_h_k_ds + alpha_20 + alpha_21*SD1 + alpha_22*SD2 + alpha_23*SD3 - mean_i_equip_h_k
COMMENT> Har ændret fra NBEN_H1 til nben_h
BEHAVIORAL> nben_h
TSRANGE 2005 4 2020 1
EQ> TSDELTALOG(nben_h) = P_671 + P_672*TSDELTALOG(zaland_jesper) + P_673*TSDELTA(unemp) + P_674*TSDELTA(TSLAG(unemp,1)) + P_675*LOG(TSLAG(nben_h,1)) + P_676*TSLAG(unemp,1) + P_677*LOG(TSLAG(zaland_jesper,1))
COEFF> P_671 P_672 P_673 P_674 P_675 P_676 P_677
STORE> coe(4)
COMMENT> Financial side
COMMENT>
IDENTITY> l_h_tr
EQ> l_h_tr= l_h_tr_ratio * (-yd_hk_ds*pc)
COMMENT> Mangler stadig at få tilpasset til ik diff
BEHAVIORAL> l_h_tr_ratio
TSRANGE 2006 2 2020 1
EQ> TSDELTA(l_h_tr_ratio) = p_646
+ p_641*TSDELTA(TSLAG(l_h_tr_ratio,2))
+ p_642*TSDELTA(iloan)
+ p_643*TSDELTALOG(TSLAG(i_bd_h_k_ds,3)/TSLAG(yd_hk_ds,3))
+ p_644* TSLAG(l_h_tr_ratio,1)
+ p_645*LOG(TSLAG(-l_h,2)/(TSLAG(yd_hk_ds,2)*TSLAG(pc,2)))
+ p_647*d_2007q34
+ p_648*time
COEFF> p_646 p_641 p_642 p_643 p_644 p_645 p_647 p_648
STORE> coe(5)
COMMENT>
IDENTITY> iba_h
EQ> iba_h= TSLAG(iba_h,1) + iba_h_tr + iba_h_rvx
COMMENT> For the time being we take sec_h_tr as exogenous. It is assumed that households' holdings of securities are entirely issued by the government.
IDENTITY> sec_h
EQ> sec_h= TSLAG(sec_h,1) + sec_h_tr + sec_h_rvx
COMMENT>
IDENTITY> sec_h_tr_g
EQ> sec_h_tr_g=sec_h_tr
COMMENT>
IDENTITY> l_h
EQ> l_h= TSLAG(l_h,1) + l_h_tr + l_h_rvx
COMMENT>
IDENTITY> eq_h
EQ> eq_h= eq_h_ratio*(TSLAG(eq_h,1) +TSLAG(sec_h,1)+ TSLAG(iba_h,1)) + eq_h_rvx
COMMENT>
BEHAVIORAL> eq_h_ratio
TSRANGE 2006 1 2020 1
EQ> TSDELTA(eq_h_ratio) = p_770
+ p_771* TSDELTA(TSLAG(ibd,1))
+ p_772* TSDELTA(TSLAG(ratio_in_eq_h,1))
+ p_773* TSLAG(eq_h_ratio,1)
+ p_774* TSLAG(ibd,1)
+ p_775* TSLAG(ratio_in_eq_h,2)
COEFF> p_770 p_771 p_772 p_773 p_774 p_775
STORE> coe(6)
COMMENT>
IDENTITY> eq_h_tr
EQ> eq_h_tr = TSDELTA(eq_h) - eq_h_rvx
COMMENT>
IDENTITY> iba_h_tr
EQ> iba_h_tr = nl_h - l_h_tr - eq_h_tr - sec_h_tr - ins_h_tr + nl_h_adj
COMMENT>
IDENTITY> eq_h_nf
EQ> eq_h_nf = d_20124*alpha_nf *eq_h
COMMENT>
IDENTITY> eq_h_f
EQ> eq_h_f = d_20124*alpha_f *eq_h
COMMENT>
IDENTITY> eq_h_row
EQ> eq_h_row = d_20124*alpha_row*eq_h
COMMENT>
IDENTITY> eq_h_nf_tr
EQ> eq_h_nf_tr = TSDELTA(eq_h_nf) - eq_h_nf_rvx
COMMENT>
IDENTITY> eq_h_f_tr
EQ> eq_h_f_tr = TSDELTA(eq_h_f) - eq_h_f_rvx
COMMENT>
IDENTITY> eq_h_row_tr
EQ> eq_h_row_tr = TSDELTA(eq_h_row) - eq_h_row_rvx
COMMENT>
IDENTITY> eq_h_test
EQ> eq_h_test = eq_h - (eq_h_nf + eq_h_f + eq_h_row)
COMMENT>
IDENTITY> ins_h
EQ> ins_h= TSLAG(ins_h,1) + ins_h_tr + ins_h_rvx
COMMENT>
IDENTITY> ins_h_tr
EQ> ins_h_tr = d8_h + ins_h_tr_excl_d8
COMMENT>
BEHAVIORAL> d8_h
TSRANGE 2005 4 2020 1
EQ> TSDELTALOG(d8_h) = p_701*TSDELTALOG(TSLAG(d8_h,1)) + p_702*TSDELTALOG(w_h_r) + p_703*TSDELTALOG(TSLAG(old_age_ratio,1)) + p_704*LOG(TSLAG(d8_h,1)) + p_705*LOG(TSLAG(w_h_r,1)) + p_706*LOG(TSLAG(old_age_ratio,1)) + p_707*d_2014q3
COEFF> p_701 p_702 p_703 p_704 p_705 p_706 p_707
STORE> coe(7)
COMMENT>
IDENTITY> lev_h
EQ> lev_h = l_h/yd_h
COMMENT> NET WEALTH AND FINANCIAL NET WEALTH
COMMENT>
IDENTITY> fa_h
EQ> fa_h = iba_h + sec_h + eq_h + ins_h
COMMENT>
IDENTITY> fnw_h
EQ> fnw_h = fa_h + l_h
COMMENT>
IDENTITY> fnw_hk
EQ> fnw_hk = fnw_h/pc
COMMENT> Capital Account
COMMENT>gross fixed capital formation (buildings and dwellings)
IDENTITY> i_bd_h
EQ> i_bd_h = i_bd_h_k * p_bd
COMMENT> gross fixed capital formation (equipment)
IDENTITY> i_equip_h
EQ> i_equip_h = i_equip_h_k * p_equip
COMMENT> Real net stock of buildings and dwellings
IDENTITY> bd_h_k
EQ> TSDELTA(bd_h_k) = i_bd_h_k - TSLAG(bd_h_k,1) * delta_bd_h
COMMENT> Real net stock of equipment
IDENTITY> equip_h_k
EQ> TSDELTA(equip_h_k) = i_equip_h_k - TSLAG(equip_h_k,1) * delta_equip_h
COMMENT> Nominal net stock of buildings and dwellings
IDENTITY> bd_h
EQ> TSDELTA(bd_h) = i_bd_h + TSLAG(bd_h_k,1) * (1-delta_bd_h)*TSDELTA(p_bd) - TSLAG(bd_h_k,1) * delta_bd_h * p_bd
COMMENT> Nominal net stock of equipment
IDENTITY> equip_h
EQ> TSDELTA(equip_h) = i_equip_h + TSLAG(equip_h_k,1) * (1-delta_equip_h)*TSDELTA(p_equip) - TSLAG(equip_h_k,1) * delta_equip_h * p_equip
COMMENT> NON-FINANCIAL SECTOR
COMMENT> Real side
COMMENT>
IDENTITY> y
EQ> y = pcon + g + i + x - m
COMMENT> real sales
IDENTITY> yk
EQ> yk = pconk + ik + gk + xk - mk
COMMENT> real sales
IDENTITY> yk_ds
EQ> yk_ds = yk - (alpha_90 + alpha_91*SD1 + alpha_92* SD2 + alpha_93*SD3)+ mean_yk
COMMENT> deasonalised nominal gdp
IDENTITY> y_ds
EQ> y_ds = y - (alpha_90a + alpha_91a*SD1 + alpha_92a* SD2 + alpha_93a*SD3)+ mean_y
COMMENT>
IDENTITY> sk
EQ> sk= pconk + ik + gk + xk
COMMENT> real government consumption
IDENTITY> gk
EQ> gk = g/pg
COMMENT> nominal export
IDENTITY> x
EQ> x = xk*px
COMMENT>
IDENTITY> rer
EQ> rer = pc*xr/pf
COMMENT>
BEHAVIORAL> xk_ds
TSRANGE 2006 3 2020 1
EQ> TSDELTALOG(xk_ds) = p_652*TSDELTALOG(TSLAG(gdp_tp,4)) + p_653*TSDELTALOG(rer) + p_654*LOG(TSLAG(xk_ds,1)) + p_655*LOG(TSLAG(gdp_tp,1)) + p_656*LOG(TSLAG(rer,2)) + p_657*d_2008q2 + p_658*d_2018q1 + p_659*d_2019q3 + p_660* time
COEFF> p_652 p_653 p_654 p_655 p_656 p_657 p_658 p_659 p_660
STORE> coe(8)
COMMENT>
IDENTITY> xk
EQ> xk = xk_ds + alpha_80 + alpha_81*SD1 + alpha_82*SD2 + alpha_83*SD3 - mean_xk
COMMENT> nominal import
IDENTITY> m
EQ> m = mk*pm
COMMENT>
IDENTITY> pm
EQ> pm = pm_ds + alpha_200 + alpha_201*SD1 + alpha_202*SD2 + alpha_203*SD3 - mean_pm
COMMENT>
BEHAVIORAL> mk_ds
TSRANGE 2006 2 2020 1
EQ> TSDELTALOG(mk_ds) = p_661 + p_662*TSDELTALOG(TSLAG(mk_ds,2)) + p_663*TSDELTALOG(TSLAG(rer,1)) + p_664*TSDELTALOG(TSLAG(rer,3)) + p_665*TSDELTALOG(yk_ds) + p_666*LOG(TSLAG(mk_ds,1)) + p_667*LOG(TSLAG(yk_ds,1)) + p_668*d_2009q1 + p_669*d_2009q4
COEFF> p_661 p_662 p_663 p_664 p_665 p_666 p_667 p_668 p_669
STORE> coe(9)
COMMENT>
IDENTITY> mk
EQ> mk = mk_ds + alpha_70 + alpha_71*SD1 + alpha_72*SD2 + alpha_73*SD3 - mean_mk
COMMENT> GDP deflator
IDENTITY> py
EQ> py = y/yk
COMMENT> nominal sales
IDENTITY> s
EQ> s = pcon + g + i + x
COMMENT> wage bill paid by NFC
IDENTITY> w_nf
EQ> w_nf = w_h_r + (w_row_r - w_row_p)
COMMENT> Gross operating surplus received by the NFC
IDENTITY> b2_nf_r
EQ> b2_nf_r = b2 - (b2_h_r + b2_f_r + b2_g_r)
COMMENT>
IDENTITY> yf
EQ> yf = y - p_tax - p_tax_row + p_sub + p_sub_row
COMMENT>
IDENTITY> b2
EQ> b2 = yf - w_nf
COMMENT> wage share
IDENTITY> ws
EQ> ws = w_nf/yf * zz
COMMENT> profit share
IDENTITY> ps
EQ> ps = 1 - ws
COMMENT> Rate of capacity utilization
IDENTITY> u_ds
EQ> u_ds=yk_ds/(bd_nfc_k+equip_nfc_k)
COMMENT> Profit rate
IDENTITY> prate
EQ> prate=s_nf/(TSLAG(bd_nfc,1)+TSLAG(equip_nfc,1))
COMMENT> Profit rate
IDENTITY> prate_ds
EQ> prate_ds = prate - (alpha_120 + alpha_121*SD1 + alpha_122*SD2 + alpha_123*SD3) + mean_prate
COMMENT> Profit rate
IDENTITY> ps_ds
EQ> ps_ds = ps - (alpha_130 + alpha_131*SD1 + alpha_132*SD2 + alpha_133*SD3) + mean_ps
COMMENT>
IDENTITY> tobinq
EQ> tobinq = (eq_nf_l) / (equip_nfc + bd_nfc)
COMMENT> Er fixet
BEHAVIORAL> i_bd_nfc_k_ds
TSRANGE 2006 1 2020 1
EQ> LOG(i_bd_nfc_k_ds) = p_800 +
p_801*TSDELTALOG(TSLAG(i_bd_nfc_k_ds,1)/TSLAG(bd_nfc_k,2)) +
p_802*TSDELTALOG(ps_ds) +
p_803*TSDELTALOG(u_ds) +
p_804* LOG(TSLAG(i_bd_nfc_k_ds,1)/TSLAG(bd_nfc_k,2)) +
p_805 * LOG(TSLAG(ps_ds,1)) +
p_806 * LOG(TSLAG(u_ds,1)) +
p_807 * TSDELTALOG(tobinq) +
p_808 * LOG(TSLAG(tobinq,1)) +
alpha_1*TSLAG(LOG(i_bd_nfc_k_ds),1) +
alpha_2*TSLAG(LOG(bd_nfc_k),1) +
alpha_3*TSLAG(-LOG(bd_nfc_k),2)
COEFF> p_800 p_801 p_802 p_803 p_804 p_805 p_806 p_807 p_808 alpha_1 alpha_2 alpha_3
RESTRICT> alpha_1 = 1
alpha_2 = 1
alpha_3 = 1
STORE> coe(10)
COMMENT>
IDENTITY> i_bd_nfc_k
EQ> i_bd_nfc_k = i_bd_nfc_k_ds + (alpha_30 + alpha_31*SD1 + alpha_32*SD2 + alpha_33*SD3) - mean_i_bd_nfc_k
COMMENT>
IDENTITY> i_equip_nfc_k
EQ> i_equip_nfc_k = i_equip_nfc_k_ds + (alpha_40 + alpha_41*SD1 + alpha_42*SD2 + alpha_43*SD3) - mean_i_equip_nfc_k
COMMENT>
IDENTITY> ik
EQ> ik = i_equip_h_k + i_equip_nfc_k + i_equip_g_k + i_equip_fc_k + i_bd_h_k + i_bd_nfc_k + i_bd_g_k + i_bd_fc_k + i_adj_h_k + i_adj_nfc_k + i_adj_fc_k + i_adj_g_k
COMMENT>
IDENTITY> i_h
EQ> i_h = i_equip_h_k*p_equip + i_bd_h_k*p_bd + i_adj_h_k*p_equip
COMMENT>
IDENTITY> i_nf
EQ> i_nf = i_equip_nfc_k*p_equip + i_bd_nfc_k*p_bd + i_adj_nfc_k*p_equip
COMMENT>
IDENTITY> i_f
EQ> i_f = i_equip_fc_k*p_equip + i_bd_fc_k*p_bd + i_adj_fc_k*p_equip
COMMENT>
IDENTITY> i_g
EQ> i_g = i_equip_g_k*p_equip + i_bd_g_k*p_bd + i_adj_g_k*p_equip
COMMENT>
IDENTITY> i
EQ> i = i_nf + i_f + i_g + i_h
COMMENT>
BEHAVIORAL> i_equip_nfc_k_ds
TSRANGE 2006 1 2020 1
EQ> LOG(i_equip_nfc_k_ds) = p_809 + p_810 * TSDELTALOG(TSLAG(i_equip_nfc_k_ds,1)/TSLAG(equip_nfc_k,2)) + p_811 * LOG(TSLAG(i_equip_nfc_k_ds,1)/TSLAG(equip_nfc_k,2)) + p_812 * LOG(TSLAG(ps_ds,1)) + p_813 * LOG(TSLAG(u_ds,1)) + p_814 * dummy_10 + p_815 * dummy_11 + p_816*TSDELTALOG(tobinq) + p_817*LOG(TSLAG(tobinq,1)) + alpha_1*TSLAG(LOG(i_equip_nfc_k_ds),1) + alpha_2*TSLAG(LOG(equip_nfc_k),1) + alpha_3*TSLAG(-LOG(equip_nfc_k),2)
COEFF> p_809 p_810 p_811 p_812 p_813 p_814 p_815 p_816 p_817 alpha_1 alpha_2 alpha_3
RESTRICT> alpha_1 = 1
alpha_2 = 1
alpha_3 = 1
STORE> coe(11)
COMMENT>
IDENTITY> int_nf
EQ> int_nf = (TSLAG(idep,1)*TSLAG(iba_nf,1) + TSLAG(int_nf_sec, 1) + TSDELTA(sec_nf)*ibd)
COMMENT>
IDENTITY> div_nf
EQ> div_nf =d_20124*(((TSLAG(eq_nf_a_nf,1) + TSLAG(eq_nf_a_f,1) - TSLAG(eq_nf_l_nf,1) + TSLAG(eq_h_nf,1)+ TSLAG(eq_row_a_nf,1) + TSLAG(eq_f_a_nf,1) + TSLAG(eq_g_nf,1)))* TSLAG(divd,1) + TSLAG(eq_nf_a_row,1)*TSLAG(diva,1)) + (1-d_20124)*(TSLAG(neq_nf,1)*TSLAG(divd,1)) + div_nf_adj
COMMENT>
IDENTITY> insu_nf
EQ> insu_nf = TSLAG(ins_nf,1)*TSLAG(insu,1)
COMMENT>
IDENTITY> npropinc_nf
EQ> npropinc_nf = int_nf + int_nf_adj + div_nf + insu_nf + ins_nf_adj + (res_r_nf ) - (res_p_nf)
COMMENT> gross income NFC Ændret yil den anden i modellen
IDENTITY> yh_nf
EQ> yh_nf = y + b2_nf_r - b2 - (p_tax + p_tax_row) + (p_sub+p_sub_row) - w_nf + (propinc_r_nf - propinc_p_nf)
COMMENT> savings NFC TAX_NF is negative
IDENTITY> s_nf
EQ> s_nf = yh_nf + tax_nf + oth_nf
COMMENT>
IDENTITY> tax_nf
EQ> tax_nf = -tax_rate_nf*y
COMMENT> Sectoral balance NFC
IDENTITY> nl_nf
EQ> nl_nf = s_nf - i_nf - np_nf + ctr_nf
COMMENT> Financial side
COMMENT> Change in stocks
COMMENT> iba
IDENTITY> iba_nf
EQ> iba_nf = TSLAG(iba_nf,1) + iba_nf_tr + iba_nf_rvx
COMMENT>
IDENTITY> iba_nf_tr
EQ> iba_nf_tr = nl_nf + nl_nf_adj - neq_nf_tr - l_nf_tr - sec_nf_tr - ins_nf_tr
COMMENT> SEC . For the time being, we take sec_nf_tr as exogenous.
IDENTITY> sec_nf
EQ> sec_nf = TSLAG(sec_nf,1) + sec_nf_tr + sec_nf_rvx
COMMENT> Loans
IDENTITY> l_nf
EQ> l_nf = TSLAG(l_nf,1) + l_nf_tr + l_nf_rvx
COMMENT> CHANGE in STOCKS OF EQUITIES:
COMMENT> Equities held as assets by NFC
IDENTITY> eq_nf_a
EQ> eq_nf_a = (1-d_20124)*(TSLAG(eq_nf_a,1) + eq_nf_a_tr + eq_nf_a_rvx) + d_20124*eq_nf_ax
COMMENT>
IDENTITY> eq_nf_a_nf
EQ> eq_nf_a_nf = d_20124 * (TSLAG(eq_nf_a_nf,1) + eq_nf_a_nf_tr + eq_nf_a_nf_rv)
COMMENT> equiteies NFC-NFC asset is obviously equal to equities NFC-NFC liability
IDENTITY> eq_nf_l_nf
EQ> eq_nf_l_nf = eq_nf_a_nf
COMMENT> this is the data for quities as assets for NFC viz-a-viz counter parties, e.g., NFC purchase equities from NFC, FC, and RoW
IDENTITY> eq_nf_ax
EQ> eq_nf_ax = eq_nf_a_nf + eq_nf_a_f + eq_nf_a_row
COMMENT>
IDENTITY> eq_nf_a_f
EQ> eq_nf_a_f = d_20124 * (TSLAG(eq_nf_a_f,1) + eq_nf_a_f_tr + eq_nf_a_f_rv)
COMMENT>
IDENTITY> eq_nf_a_row
EQ> eq_nf_a_row = d_20124 * (TSLAG(eq_nf_a_row,1) + eq_nf_a_row_tr + eq_nf_a_row_rv)
COMMENT> total gross liabilities of equities on firms balance sheet is defined as the sum of NFC-NFC asset + the sum of NFC equities held by other sectors
IDENTITY> eq_nf_l
EQ> eq_nf_l = (1- d_20124)*(TSLAG(eq_nf_l,1) + eq_nf_l_tr + eq_nf_l_rvx) + d_20124*eq_nf_lx
COMMENT> total gross liabilities of equities on firms balance sheet is defined as the sum of NFC-NFC asset + the sum of NFC equities held by other sectors
IDENTITY> eq_nf_lx
EQ> eq_nf_lx = eq_nf_a_nf + eq_h_nf + eq_row_a_nf + eq_f_a_nf + eq_g_nf
COMMENT>
IDENTITY> neq_nf
EQ> neq_nf =d_20123*(-alpha_neq_nf * i_nf) + d_20124*( (eq_nf_a_f+ eq_nf_a_row)-(eq_f_a_nf + eq_g_nf + eq_h_nf + eq_row_a_nf))
COMMENT>
IDENTITY> neq_nf_tr
EQ> neq_nf_tr = TSDELTA(neq_nf)-(neq_nf_rvx)
COMMENT>Some consistency check eqs:
COMMENT> this variable should be zero after 2012 and onwards as it captures the difference between equities as assets for nfc (aggregate) data minus equities as assets for NFC held at difference sectors after 2012. In short, after 2012, we can identify the counter parties where NFC are holding stocks.
IDENTITY> eq_nf_a_test
EQ> eq_nf_a_test = eq_nf_a - eq_nf_ax
COMMENT> this variable should be zero after 2012 and onwards as it captures the difference between equities as liabilities for nfc (aggregate) data minus equities as liabilities for NFC held at difference sectors after 2012.
IDENTITY> eq_nf_l_test
EQ> eq_nf_l_test = eq_nf_l - eq_nf_lx
COMMENT> insurance NFC
IDENTITY> ins_nf
EQ> ins_nf = TSLAG(ins_nf,1) + ins_nf_tr + ins_nf_rvx
COMMENT> FINANCIAL NET WEALTH
COMMENT> net financial wealth
IDENTITY> fnw_nf
EQ> fnw_nf = iba_nf + eq_nf_a - eq_nf_l + sec_nf +l_nf + ins_nf
COMMENT>
IDENTITY> fnw_nfk
EQ> fnw_nfk = fnw_nf/pc
COMMENT> Capital Account
COMMENT> gross fixed capital formation (buildings and dwellings)
IDENTITY> i_bd_nfc
EQ> i_bd_nfc = i_bd_nfc_k * p_bd
COMMENT>
IDENTITY> i_equip_nfc
EQ> i_equip_nfc = i_equip_nfc_k * p_equip
COMMENT> Real net stock of buildings and dwellings
IDENTITY> bd_nfc_k
EQ> TSDELTA(bd_nfc_k) = i_bd_nfc_k - TSLAG(bd_nfc_k,1) * delta_bd_nfc
COMMENT> Real net stock of equipment
IDENTITY> equip_nfc_k
EQ> TSDELTA(equip_nfc_k) = i_equip_nfc_k - TSLAG(equip_nfc_k,1) * delta_equip_nfc
COMMENT> Nominal net stock of buildings and dwellings
IDENTITY> bd_nfc
EQ> TSDELTA(bd_nfc) = i_bd_nfc + TSLAG(bd_nfc_k,1) * (1-delta_bd_nfc)*TSDELTA(p_bd) - TSLAG(bd_nfc_k,1) * delta_bd_nfc * p_bd
COMMENT> Nominal net stock of equipment
IDENTITY> equip_nfc
EQ> TSDELTA(equip_nfc) = i_equip_nfc + TSLAG(equip_nfc_k,1) * (1-delta_equip_nfc)*TSDELTA(p_equip) - TSLAG(equip_nfc_k,1) * delta_equip_nfc * p_equip
COMMENT> FINANCIAL CORP
COMMENT> Real side
COMMENT>
IDENTITY> int_f
EQ> int_f = (TSLAG(idep,1)*TSLAG(iba_f,1) + TSLAG(iloan,1)*TSLAG(l_f,1) +
TSLAG(int_f_a_sec, 1) + TSDELTA(sec_f_a)*iboa +
TSLAG(int_f_d_sec, 1) + TSDELTA(sec_f_d)*ibd)
COMMENT>
IDENTITY> div_f
EQ> div_f = d_20124 *(((TSLAG(eq_f_a_f,1) + TSLAG(eq_nf_a_nf,1)) - (TSLAG(eq_f_l_f,1) + TSLAG(eq_h_f ,1)+ TSLAG(eq_row_a_f,1) + TSLAG(eq_nf_a_f,1) + TSLAG(eq_g_f,1)))* TSLAG(divd,1) + TSLAG(eq_f_a_row,1)*TSLAG(diva,1)) + (1-d_20124)*((TSLAG(neq_f,1)*TSLAG(divd,1))) + div_f_adj
COMMENT>
IDENTITY> insu_f
EQ> insu_f = TSLAG(ins_f,1)*TSLAG(insu,1)
COMMENT>
IDENTITY> propinc_r_f
EQ> propinc_r_f = int_r_f + div_r_f + ins_r_f + res_r_f
COMMENT>
IDENTITY> propinc_p_f
EQ> propinc_p_f = int_p_f + div_p_f + ins_p_f + res_p_f
COMMENT>
IDENTITY> npropinc_f
EQ> npropinc_f = int_f + int_f_adj + div_f + insu_f + ins_f_adj + (res_r_f) - (res_p_f)
COMMENT>
IDENTITY> yh_f
EQ> yh_f = b2_f_r + (npropinc_f)
COMMENT>
IDENTITY> yd_f
EQ> yd_f = yh_f + tax_f + nben_f + oth_f
COMMENT> This is based on the fact that d8_h = d8_f in the data.
IDENTITY> d8_f
EQ> d8_f = d8_h
COMMENT>
IDENTITY> nben_f
EQ> nben_f = d8_f
COMMENT> Savings F
IDENTITY> s_f
EQ> s_f = yd_f - d8_f
COMMENT> Sectoral balance F
IDENTITY> nl_f
EQ> nl_f = s_f - i_f - np_f + ctr_f
COMMENT> FInancial side
COMMENT> Change in stocks of ibas
COMMENT>
IDENTITY> iba_f
EQ> iba_f = TSLAG(iba_f,1) + iba_f_tr + iba_f_rvx
COMMENT>
IDENTITY> iba_f_tr
EQ> iba_f_tr = -(iba_nf_tr + iba_h_tr + iba_g_tr + iba_row_tr)
COMMENT> Change in stocks of equities:
COMMENT>
IDENTITY> eq_f_a
EQ> eq_f_a = (1-d_20124)*(TSLAG(eq_f_a,1) + eq_f_a_tr + eq_f_a_rvx) + d_20124*eq_f_ax
COMMENT>
IDENTITY> eq_f_a_nf
EQ> eq_f_a_nf = d_20124 * (TSLAG(eq_f_a_nf,1) + eq_f_a_nf_tr + eq_f_a_nf_rv)
COMMENT>
IDENTITY> eq_f_a_f
EQ> eq_f_a_f = d_20124 * (TSLAG(eq_f_a_f,1) + eq_f_a_f_tr + eq_f_a_f_rv)
COMMENT>
IDENTITY> eq_f_l_f
EQ> eq_f_l_f = eq_f_a_f
COMMENT>
IDENTITY> eq_f_a_row
EQ> eq_f_a_row = d_20124 * (TSLAG(eq_f_a_row,1) + eq_f_a_row_tr + eq_f_a_row_rv)
COMMENT> this is the data for quities as assets for NFC viz-a-viz counter parties, e.g., NFC purchase equities from NFC, FC, and RoW
IDENTITY> eq_f_ax
EQ> eq_f_ax = eq_f_a_nf + eq_f_a_f + eq_f_a_row
COMMENT>
IDENTITY> eq_f_l
EQ> eq_f_l = (1- d_20124)*(TSLAG(eq_f_l,1) + eq_f_l_tr + eq_f_l_rvx) + d_20124*eq_f_lx
COMMENT>
IDENTITY> eq_f_lx
EQ> eq_f_lx = eq_nf_a_f + eq_h_f + eq_row_a_f + eq_f_a_f + eq_g_f
COMMENT>
IDENTITY> neq_f
EQ> neq_f = eq_f_a - eq_f_l
COMMENT>
IDENTITY> neq_f_tr
EQ> neq_f_tr = TSDELTA(neq_f) - neq_f_rvx
COMMENT>
IDENTITY> eq_f_l_test
EQ> eq_f_l_test = eq_f_l - (eq_f_l_f + eq_h_f + eq_row_a_f + eq_nf_a_f + eq_g_f)
COMMENT> Change in stocks of securities
COMMENT>
IDENTITY> sec_f_d_tr
EQ> sec_f_d_tr = TSDELTA(sec_f_d) - sec_f_d_rvx
COMMENT>
IDENTITY> sec_f_d
EQ> sec_f_d = -sec_g - sec_nf - sec_h
COMMENT>
IDENTITY> sec_f_d_tr_nf
EQ> sec_f_d_tr_nf=-sec_nf_tr
COMMENT>
IDENTITY> sec_row_tr
EQ> sec_row_tr = -sec_f_a_tr
COMMENT>
IDENTITY> sec_f_a
EQ> sec_f_a = TSLAG(sec_f_a,1) + sec_f_a_tr + sec_f_a_rvx
COMMENT>
IDENTITY> sec_f_a_tr
EQ> sec_f_a_tr = nl_f + nl_f_adj - iba_f_tr - ins_f_tr - l_f_tr - neq_f_tr - sec_f_d_tr
COMMENT>
IDENTITY> l_f
EQ> l_f = -(l_h + l_nf + l_g + l_row)
COMMENT>
IDENTITY> l_f_tr
EQ> l_f_tr = TSDELTA(l_f) -l_f_rvx
COMMENT>
IDENTITY> ins_f
EQ> ins_f = -(ins_h + ins_row + ins_nf + ins_g)
COMMENT>
IDENTITY> ins_f_tr
EQ> ins_f_tr = TSDELTA(ins_f) - ins_f_rvx
COMMENT> 'WEALTH
COMMENT>
IDENTITY> fnw_f
EQ> fnw_f = iba_f + sec_f_a + sec_f_d +l_f + eq_f_a - eq_f_l + ins_f
COMMENT>
IDENTITY> fnw_fk
EQ> fnw_fk = fnw_f/pc
COMMENT> Capital Account
COMMENT> gross fixed capital formation (buildings and dwellings)
IDENTITY> i_bd_fc
EQ> i_bd_fc = i_bd_fc_k * p_bd
COMMENT> gross fixed capital formation (equipment)
IDENTITY> i_equip_fc
EQ> i_equip_fc = i_equip_fc_k * p_equip
COMMENT>
IDENTITY> bd_fc_k
EQ> TSDELTA(bd_fc_k) = i_bd_fc_k - TSLAG(bd_fc_k,1) * delta_bd_fc
COMMENT>
IDENTITY> equip_fc_k
EQ> TSDELTA(equip_fc_k) = i_equip_fc_k - TSLAG(equip_fc_k,1) * delta_equip_fc
COMMENT>
IDENTITY> bd_fc
EQ> TSDELTA(bd_fc) = i_bd_fc + TSLAG(bd_fc_k,1) * (1-delta_bd_fc)*TSDELTA(p_bd) - TSLAG(bd_fc_k,1) * delta_bd_fc * p_bd
COMMENT>
IDENTITY> equip_fc
EQ> TSDELTA(equip_fc) = i_equip_fc + TSLAG(equip_fc_k,1) * (1-delta_equip_fc)*TSDELTA(p_equip) - TSLAG(equip_fc_k,1) * delta_equip_fc * p_equip
COMMENT> GOVT
COMMENT> Real side
COMMENT> interest payment on bonds
IDENTITY> int_g_sec
EQ> int_g_sec = TSLAG(int_g_sec, 1) + TSDELTA(sec_g)*ibd
COMMENT>
IDENTITY> int_g
EQ> int_g = (TSLAG(idep,1)*TSLAG(iba_g,1) + TSLAG(iloan,1)*TSLAG(l_g,1) + int_g_sec)
COMMENT>
IDENTITY> div_g
EQ> div_g = d_20124 * ( (TSLAG(eq_g_nf,1) + TSLAG(eq_g_f,1))*TSLAG(divd,1) + TSLAG(eq_g_row,1)*TSLAG(diva,1) ) + (1-d_20124) * ((TSLAG(eq_g,1)*TSLAG(divd,1))) + div_g_adj
COMMENT>
IDENTITY> insu_g
EQ> insu_g = TSLAG(ins_g,1)*TSLAG(insu,1)
COMMENT>
IDENTITY> propinc_r_g
EQ> propinc_r_g = int_r_g + div_r_g + res_r_g
COMMENT>
IDENTITY> propinc_p_g
EQ> propinc_p_g = int_p_g + res_p_g
COMMENT>
IDENTITY> npropinc_g
EQ> npropinc_g = int_g + int_g_adj + div_g + insu_g + ins_g_adj + (res_r_g) - ( res_p_g)
COMMENT>
IDENTITY> yh_g
EQ> yh_g = b2_g_r + p_tax - p_sub + (npropinc_g)
COMMENT>
IDENTITY> yd_g
EQ> yd_g = yh_g + tax_g + nben_g + oth_g
COMMENT>
IDENTITY> nben_g
EQ> nben_g = - (nben_row + nsben_h + nben_f)
COMMENT>
IDENTITY> tax_g
EQ> tax_g = -(tax_h + tax_nf + tax_f + tax_row)
COMMENT>
IDENTITY> s_g
EQ> s_g = yd_g - g
COMMENT>
IDENTITY> nl_g
EQ> nl_g = s_g - i_g - np_g + ctr_g
COMMENT> Financial side
COMMENT> Change in stocks ' we need to have an accomodating asset
COMMENT>
IDENTITY> iba_g
EQ> iba_g= TSLAG(iba_g,1) + iba_g_tr + iba_g_rvx
COMMENT>
IDENTITY> eq_g
EQ> eq_g = (1-d_20124)*(TSLAG(eq_g,1) + eq_g_tr + eq_g_rvx) + d_20124*eq_g_ax
COMMENT>
IDENTITY> eq_g_nf
EQ> eq_g_nf = d_20124 * (TSLAG(eq_g_nf,1) + eq_g_nf_tr + eq_g_nf_rv)
COMMENT>
IDENTITY> eq_g_f
EQ> eq_g_f = d_20124 * (TSLAG(eq_g_f,1) + eq_g_f_tr + eq_g_f_rv)
COMMENT>
IDENTITY> eq_g_row
EQ> eq_g_row = d_20124 * (TSLAG(eq_g_row,1) + eq_g_row_tr + eq_g_row_rv)
COMMENT>
IDENTITY> eq_g_ax
EQ> eq_g_ax = eq_g_row + eq_g_f + eq_g_nf
COMMENT>
IDENTITY> eq_g_test
EQ> eq_g_test = eq_g - (eq_g_nf + eq_g_f + eq_g_row)
COMMENT>
IDENTITY> sec_g
EQ> sec_g = TSLAG(sec_g,1) + sec_g_tr + sec_g_rvx
COMMENT>
IDENTITY> sec_g_tr
EQ> sec_g_tr = nl_g + nl_g_adj - iba_g_tr - l_g_tr - eq_g_tr - ins_g_tr
COMMENT> SKAL REDDUNDANT EQ MED HER???? redundant = (sec_g_tr_0+(sec_h_tr_g_0+sec_f_d_tr_g_0)) 'Redundant equation
COMMENT>
IDENTITY> l_g
EQ> l_g = TSLAG(l_g,1) + l_g_tr + l_g_rvx
COMMENT>
IDENTITY> ins_g
EQ> ins_g = TSLAG(ins_g,1) + ins_g_tr + ins_g_rvx
COMMENT> WEALTH
COMMENT>
IDENTITY> fnw_g
EQ> fnw_g = iba_g + eq_g + sec_g +l_g + ins_g
COMMENT>
IDENTITY> fnw_gk
EQ> fnw_gk = fnw_g/pc
COMMENT> Capital Account
COMMENT> gross fixed capital formation (buildings and dwellings)
IDENTITY> i_bd_g
EQ> i_bd_g = i_bd_g_k * p_bd
COMMENT> gross fixed capital formation (equipment)
IDENTITY> i_equip_g
EQ> i_equip_g = i_equip_g_k * p_equip
COMMENT> Real net stock of buildings and dwellings
IDENTITY> bd_g_k
EQ> TSDELTA(bd_g_k) = i_bd_g_k - TSLAG(bd_g_k,1) * delta_bd_g
COMMENT>
IDENTITY> equip_g_k
EQ> TSDELTA(equip_g_k) = i_equip_g_k - TSLAG(equip_g_k,1) * delta_equip_g
COMMENT>
IDENTITY> bd_g
EQ> TSDELTA(bd_g) = i_bd_g + TSLAG(bd_g_k,1) * (1-delta_bd_g)*TSDELTA(p_bd) - TSLAG(bd_g_k,1) * delta_bd_g * p_bd
COMMENT>
IDENTITY> equip_g
EQ> TSDELTA(equip_g) = i_equip_g + TSLAG(equip_g_k,1) * (1-delta_equip_g)*TSDELTA(p_equip) - TSLAG(equip_g_k,1) * delta_equip_g * p_equip
COMMENT> REST OF THE WORLD
COMMENT> Real side
COMMENT>
IDENTITY> int_row
EQ> int_row = (TSLAG(idep,1)*TSLAG(iba_row,1) + TSLAG(int_row_sec, 1) + TSDELTA(sec_row)*iboa )
COMMENT>
IDENTITY> div_row
EQ> div_row = d_20124*( (TSLAG(eq_row_a_nf,1) + TSLAG(eq_row_a_f,1))*TSLAG(divd,1) - ((TSLAG(eq_nf_a_row,1)+TSLAG(eq_f_a_row,1)+TSLAG(eq_g_row,1)+TSLAG(eq_h_row,1))*TSLAG(diva,1))) + (1-d_20124) * ((TSLAG(neq_row,1)*TSLAG(divd,1))) + div_row_adj
COMMENT>
IDENTITY> insu_row
EQ> insu_row = TSLAG(ins_row,1)*TSLAG(insu,1)
COMMENT>
IDENTITY> propinc_r_row
EQ> propinc_r_row = int_r_row + div_r_row + ins_r_row + res_r_row
COMMENT>
IDENTITY> propinc_p_row
EQ> propinc_p_row = int_p_row + div_p_row + ins_p_row + res_p_row
COMMENT>
IDENTITY> npropinc_row
EQ> npropinc_row = int_row + int_row_adj + div_row + insu_row + ins_row_adj + (res_r_row) - (res_p_row)
COMMENT>
IDENTITY> s_row
EQ> s_row = m - x + p_tax_row - p_sub_row + (w_row_r - w_row_p) + (npropinc_row) + (tax_row) + nben_row + oth_row
COMMENT>
IDENTITY> nl_row
EQ> nl_row = s_row + ctr_row - np_row
COMMENT>
IDENTITY> nben_row
EQ> nben_row = scon_row_r - scon_row_p + sben_row_r - sben_row_p
COMMENT>
IDENTITY> nx
EQ> nx = x - m
COMMENT>
IDENTITY> cab
EQ> cab =-nl_row
COMMENT>
IDENTITY> bop
EQ> bop = cab + fab
COMMENT>
IDENTITY> fab
EQ> fab = (fnl_row)
COMMENT> Financial side
COMMENT>
IDENTITY> iba_row
EQ> iba_row= TSLAG(iba_row,1) + iba_row_tr + iba_row_rvx
COMMENT>
IDENTITY> iba_row_tr
EQ> iba_row_tr = nl_row + nl_row_adj - neq_row_tr - sec_row_tr - l_row_tr - ins_row_tr
COMMENT>
IDENTITY> sec_row
EQ> sec_row = TSLAG(sec_row,1) + sec_row_tr + sec_row_rvx
COMMENT>
IDENTITY> l_row
EQ> l_row = TSLAG(l_row,1) +l_row_tr +l_row_rvx
COMMENT> CHANGE in equities
COMMENT>
IDENTITY> eq_row_a
EQ> eq_row_a = (1-d_20124)*(TSLAG(eq_row_a,1) + eq_row_a_tr + eq_row_a_rvx) + d_20124*eq_row_ax
COMMENT>
IDENTITY> eq_row_a_nf
EQ> eq_row_a_nf = d_20124 * (TSLAG(eq_row_a_nf,1) + eq_row_a_nf_tr + eq_row_a_nf_rv)
COMMENT>
IDENTITY> eq_row_a_f
EQ> eq_row_a_f = d_20124 * (TSLAG(eq_row_a_f,1) + eq_row_a_f_tr + eq_row_a_f_rv)
COMMENT>
IDENTITY> eq_row_ax
EQ> eq_row_ax = eq_row_a_nf + eq_row_a_f
COMMENT>
IDENTITY> eq_row_a_test
EQ> eq_row_a_test = eq_row_a - (eq_row_a_nf + eq_row_a_f)
COMMENT>
IDENTITY> eq_row_l
EQ> eq_row_l = (1-d_20124)*(TSLAG(eq_row_l,1) + eq_row_l_tr + eq_row_l_rvx) + d_20124*(eq_row_lx)
COMMENT>
IDENTITY> eq_row_lx
EQ> eq_row_lx = eq_nf_a_row + eq_h_row + eq_f_a_row + eq_g_row
COMMENT>
IDENTITY> eq_row_l_test
EQ> eq_row_l_test = eq_row_l - (eq_nf_a_row + eq_f_a_row + eq_g_row + eq_h_row)
COMMENT>
IDENTITY> neq_row
EQ> neq_row =-d_20123*(neq_nf + eq_h + neq_f + eq_g) + d_20124*( eq_row_a_nf + eq_row_a_f - (eq_nf_a_row + eq_f_a_row + eq_g_row + eq_h_row))
COMMENT>
IDENTITY> neq_row_tr
EQ> neq_row_tr = TSDELTA(neq_row) - neq_row_rvx
COMMENT>
IDENTITY> ins_row
EQ> ins_row = TSLAG(ins_row,1) + ins_row_tr + ins_row_rvx
COMMENT> WEALTH
COMMENT>
IDENTITY> fnw_row
EQ> fnw_row = iba_row + eq_row_a - eq_row_l + sec_row +l_row + ins_row
COMMENT>
IDENTITY> fnw_rowk
EQ> fnw_rowk = fnw_row/pc
COMMENT> Labour market
COMMENT>
IDENTITY> unadj
EQ> unadj = lf - empadj
COMMENT>
IDENTITY> unemp
EQ> unemp = lf - emp
COMMENT>
IDENTITY> ur
EQ> ur = unemp/lf
COMMENT>
IDENTITY> ur_ds
EQ> ur_ds = ur - (alpha_140 + alpha_141*SD1 + alpha_142*SD2 + alpha_143*SD3) + mean_ur
COMMENT>
IDENTITY> uradj
EQ> uradj = unadj/lf
COMMENT>
IDENTITY> lf
EQ> lf = (part*pop)/1000
COMMENT> The pricing equation implies a mark-up of (1 + 0.38) in the long-run, i.e., the long-run (co-integrating vector) impact of the indepenent variable on pc_ds = 0.029/0.021
COMMENT>
BEHAVIORAL> pc_ds
TSRANGE 2006 3 2020 1
EQ> TSDELTALOG(pc_ds) = C_21*TSDELTALOG(TSLAG(pc_ds,1)) + C_22*TSDELTALOG(TSLAG(pc_ds,2))+ C_23*TSDELTALOG(TSLAG(pc_ds,3)) + C_24*TSDELTALOG(TSLAG(pc_ds,4)) + C_25*TSDELTALOG(wage_ds)+ C_26*TSDELTALOG(pm_ds) + C_27*TSDELTALOG(TSLAG(pm_ds,2)) + C_28*LOG(TSLAG(pc_ds,1)) + C_29*LOG(TSLAG(wage_ds,1)) + C_30*LOG(TSLAG(prod_ds,1)) + C_31*LOG(TSLAG(pm_ds,1)) + C_32* d_2007q3 + C_33*d_2017q23 + C_34*d_2018q1 + C_35*d_2011q2 + C_36*d_2013q1 + C_37*(yk_ds_potential - (pconk_ds + ik + gk))
COEFF> C_21 C_22 C_23 C_24 C_25 C_26 C_27 C_28 C_29 C_30 C_31 C_32 C_33 C_34 C_35 C_36 C_37
STORE> coe(12)
COMMENT>
IDENTITY> pc
EQ> pc = pc_ds + alpha_60 + alpha_61*SD1 + alpha_62*SD2 + alpha_63*SD3 - mean_pc
COMMENT>
IDENTITY> mkp
EQ> mkp = pc_ds / (wage_ds/prodk_ds + pm_ds)
COMMENT>
BEHAVIORAL> emp
EQ> emp = p_250 * (yk/prodk)
COEFF> p_250
STORE> coe(14)
COMMENT>
IDENTITY> urterm
EQ> urterm = ur - urs
COMMENT>
IDENTITY> rw_ds
EQ> rw_ds= wage_ds/pc_ds
COMMENT>
IDENTITY> wage
EQ> wage = wage_ds + (alpha_50 + alpha_51*SD1 + alpha_52*SD2 + alpha_53*SD3) - mean_wage
COMMENT>
IDENTITY> wage_ds_t
EQ> wage_ds_t= SD1* wage_ds*(1+inflation_t) + SD2* TSLAG(wage_ds,1)*(1+TSLAG(inflation_t,1)) + SD3* TSLAG(wage_ds,2)*(1+TSLAG(inflation_t,2)) + SD4* TSLAG(wage_ds,3)*(1+TSLAG(inflation_t,3)) - wage_ds*(0.389369 - tax_rate1)
COMMENT>
IDENTITY> inflation
EQ> inflation = (pc/TSLAG(pc,4)) - 1
COMMENT>
IDENTITY> growth
EQ> growth = (yk_ds/TSLAG(yk_ds,4)) - 1
COMMENT> Capital Stock with switches
IDENTITY> inflation_t
EQ> inflation_t = inflation_tt
IF> inflation_tt <= 0
IDENTITY> inflation_t
EQ> inflation_t = inflation
IF> inflation_tt > 0
COMMENT>
IDENTITY> wageindex
EQ> wageindex = wage/wage_2010q3
COMMENT>
IDENTITY> mkp
EQ> mkp = pc_ds / (wage_ds/prodk_ds + pm_ds)
COMMENT>
BEHAVIORAL> wage_ds
TSRANGE 2006 3 2020 1
EQ> TSDELTALOG(wage_ds) = p_520 + p_522* TSDELTA(TSLAG(ur,4)) + p_523* TSDELTALOG(prod_ds) + p_524* LOG(TSLAG(wage_ds,1)) + p_525* LOG(TSLAG(wage_ds_t,1)) + p_526* LOG(TSLAG(prod_ds,1)) + p_527* (d_2009q1 + d_2009q2)
COEFF> p_520 p_522 p_523 p_524 p_525 p_526 p_527
STORE> coe(20)
COMMENT>
IDENTITY> prod
EQ> prod=prodk * (y/yk)
COMMENT>
IDENTITY> prod_ds
EQ> prod_ds=prodk_ds * (y_ds/yk_ds)
COMMENT>
IDENTITY> acc_rate
EQ> acc_rate = ik / (bd_h_k + equip_h_k + bd_nfc_k + equip_nfc_k + bd_fc_k + equip_fc_k + bd_g_k + equip_g_k)
COMMENT> CONSISTENCY CHEKCS
COMMENT>
IDENTITY> nl_check
EQ> nl_check= (nl_h + nl_f + nl_nf + nl_g + nl_row)
COMMENT>
IDENTITY> fnl_check
EQ> fnl_check= (fnl_h + fnl_f + fnl_nf + fnl_g + fnl_row)
COMMENT>
IDENTITY> check_np
EQ> check_np = np_row + np_h + np_f + np_nf + np_g
COMMENT>
IDENTITY> check_ctr
EQ> check_ctr = ctr_row + ctr_h + ctr_f + ctr_nf + ctr_g
COMMENT>
IDENTITY> check_invest
EQ> check_invest = i - i_f - i_nf - i_g - i_h
COMMENT>
IDENTITY> check_iba
EQ> check_iba = iba_h + iba_f + iba_nf + iba_g + iba_row
COMMENT>
IDENTITY> check_tax
EQ> check_tax = tax_g + tax_nf + tax_f + tax_h + tax_row
COMMENT>
IDENTITY> check_iba_rv
EQ> check_iba_rv = iba_h_rv + iba_f_rv + iba_nf_rv + iba_g_rv + iba_row_rv
COMMENT>
IDENTITY> check_iba_tr
EQ> check_iba_tr = iba_h_tr + iba_f_tr + iba_nf_tr + iba_g_tr + iba_row_tr
COMMENT>
IDENTITY> check_eq
EQ> check_eq = eq_h + (eq_f_a - eq_f_l) + (eq_nf_a - eq_nf_l) + eq_g + (eq_row_a - eq_row_l)
COMMENT>
IDENTITY> check_eq_tr
EQ> check_eq_tr = eq_h_tr + neq_nf_tr + neq_f_tr + eq_g_tr + neq_row_tr + eq_g_tr
COMMENT>
IDENTITY> check_div
EQ> check_div = div_h + div_f + div_g + div_nf + div_row
COMMENT>
IDENTITY> check_l
EQ> check_l = l_h + l_f + l_nf + l_g + l_row
COMMENT>
IDENTITY> check_l_tr
EQ> check_l_tr = l_f_tr + l_h_tr + l_nf_tr + l_g_tr + l_row_tr
COMMENT>
IDENTITY> check_ins
EQ> check_ins = ins_h + ins_f + ins_nf + ins_g + ins_row
COMMENT>
IDENTITY> check_ins_tr
EQ> check_ins_tr = ins_f_tr + ins_h_tr + ins_nf_tr + ins_g_tr + ins_row_tr
COMMENT>
IDENTITY> check_sec
EQ> check_sec = sec_h + sec_f_a + sec_f_d + sec_nf + sec_g + sec_row
COMMENT>
IDENTITY> check_sec
EQ> check_sec = sec_h + sec_f_a + sec_f_d + sec_nf + sec_g + sec_row
COMMENT> Variables for Shock 1 activation
IDENTITY> pf
EQ> pf = pf*1
IF> shock_1_model <= 0
IDENTITY> pf
EQ> pf = pf_shock
IF> shock_1_model > 0
COMMENT> Variables for Shock 1 activation
IDENTITY> pm_ds
EQ> pm_ds = pm_ds*1
IF> shock_1_model <= 0
IDENTITY> pm_ds
EQ> pm_ds = pm_ds_shock
IF> shock_1_model > 0
COMMENT> Variables for Shock 1 activation
IDENTITY> p_expect
EQ> p_expect = p_expect*1
IF> shock_1_model <= 0
IDENTITY> p_expect
EQ> p_expect = p_expect_shock
IF> shock_1_model > 0
COMMENT> Variables for Shock 1 activation
IDENTITY> gdp_tp
EQ> gdp_tp = gdp_tp*1
IF> shock_1_model <= 0
IDENTITY> gdp_tp
EQ> gdp_tp = gdp_tp_shock
IF> shock_1_model > 0
COMMENT> Variables for Shock 1 activation
IDENTITY> yk_ds_potential
EQ> yk_ds_potential = yk_ds_potential*1
IF> shock_1_model <= 0
IDENTITY> yk_ds_potential
EQ> yk_ds_potential = yk_ds_potential_shock
IF> shock_1_model > 0
COMMENT> Variables for Shock 1 activation
IDENTITY> iloan
EQ> iloan = iloan*1
IF> shock_2_model <= 0
IDENTITY> iloan
EQ> iloan = iloan_shock
IF> shock_2_model > 0
COMMENT> Capital Stock with switches
IDENTITY> idep
EQ> idep = idep*1
IF> shock_2_model <= 0
IDENTITY> idep
EQ> idep = idep_shock
IF> shock_2_model > 0
COMMENT> Capital Stock with switches
IDENTITY> ibd
EQ> ibd = ibd*1
IF> shock_2_model <= 0
IDENTITY> ibd
EQ> ibd = ibd_shock
IF> shock_2_model > 0
COMMENT> Capital Stock with switches
IDENTITY> iboa
EQ> iboa = iboa*1
IF> shock_2_model <= 0
IDENTITY> iboa
EQ> iboa = iboa_shock
IF> shock_2_model > 0
COMMENT> Variables for Shock 3 activation
IDENTITY> tax_rate1
EQ> tax_rate1 = tax_rate1*1
IF> shock_3_model <= 0
IDENTITY> tax_rate1
EQ> tax_rate1 = tax_rate1_shock
IF> shock_3_model > 0
COMMENT> Variables for Shock 4 activation
IDENTITY> tax_rate_p
EQ> tax_rate_p = tax_rate_p*1
IF> shock_4_model <= 0
IDENTITY> tax_rate_p
EQ> tax_rate_p = tax_rate_p_shock
IF> shock_4_model > 0
COMMENT> Lavet for at kunne støde til g
IDENTITY> shock_4_model
EQ> shock_4_model = shock_4_model*1
IDENTITY> shock_3_model
EQ> shock_3_model = shock_3_model*1
COMMENT> Lavet for at kunne støde til g
IDENTITY> shock_2_model
EQ> shock_2_model = shock_2_model*1
COMMENT> Lavet for at kunne støde til g
IDENTITY> shock_1_model
EQ> shock_1_model = shock_1_model*1
END"S_model=LOAD_MODEL(modelText = S_model.txt)## Analyzing behaviorals...
## Analyzing identities...
## Optimizing...
## Loaded model "S_model.txt":
## 13 behaviorals
## 287 identities
## 123 coefficients
## ...LOAD MODEL OKDeclaring variables as time series objects for the Bimets package
l_h_tr_ratio= -l_h_tr/(yd_hk_ds*pc)
eq_h_ratio= (eq_h-eq_h_rvx)/(TSLAG(eq_h,1) +TSLAG(sec_h,1)+ TSLAG(iba_h,1))
ratio_in_eq_h= (div_r_h+eq_h_rvx)/TSLAG(eq_h)# I think I should create the timeseries for the coeff.
S_modelData=list(
## Price adjustments
pg_adj = TIMESERIES(c(pg_adj),
START=c(2005,2),FREQ=4),
p_bd_adj = TIMESERIES(c(p_bd_adj),
START=c(2005,2),FREQ=4),
p_equip_adj = TIMESERIES(c(p_equip_adj),
START=c(2005,3),FREQ=4),
px_adj = TIMESERIES(c(px_adj),
START=c(2005,2),FREQ=4),
## Households
int_r_h = TIMESERIES(c(int_r_h),
START=c(2005,2),FREQ=4),
int_p_h = TIMESERIES(c(int_p_h),
START=c(2005,2),FREQ=4),
div_h = TIMESERIES(c(div_h),
START=c(2005,3),FREQ=4),
aa_check = TIMESERIES(c(aa_check),
START=c(2005,2),FREQ=4),
insu_h = TIMESERIES(c(insu_h),
START=c(2005,3),FREQ=4),
propinc_r_h = TIMESERIES(c(propinc_r_h),
START=c(2005,2),FREQ=4),
propinc_r_nf = TIMESERIES(c(propinc_r_nf ),
START=c(2005,2),FREQ=4),
propinc_p_nf= TIMESERIES(c(propinc_p_nf),
START=c(2005,2),FREQ=4),
npropinc_h = TIMESERIES(c(npropinc_h),
START=c(2005,2),FREQ=4),
yh_h = TIMESERIES(c(yh_h),
START=c(2005,2),FREQ=4),
yh2a = TIMESERIES(c(yh2a),
START=c(2005,2),FREQ=4),
yh2b = TIMESERIES(c(yh2b),
START=c(2005,2),FREQ=4),
yh1 = TIMESERIES(c(yh1),
START=c(2005,2),FREQ=4),
w_h_r = TIMESERIES(c(w_h_r),
START=c(2005,2),FREQ=4),
yd2a_h = TIMESERIES(c(yd2a_h),
START=c(2005,2),FREQ=4),
yd2b_h = TIMESERIES(c(yd2b_h),
START=c(2005,2),FREQ=4),
yd1_h = TIMESERIES(c(yd1_h),
START=c(2005,2),FREQ=4),
tax_h = TIMESERIES(c(tax_h),
START=c(2005,2),FREQ=4),
yd1_hk = TIMESERIES(c(yd1_hk),
START=c(2005,2),FREQ=4),
yd2a_hk = TIMESERIES(c(yd2a_hk),
START=c(2005,2),FREQ=4),
yd2b_hk = TIMESERIES(c(yd2b_hk),
START=c(2005,2),FREQ=4),
yd_h = TIMESERIES(c(yd_h),
START=c(2005,2),FREQ=4),
nsben_h = TIMESERIES(c(nsben_h),
START=c(2005,2),FREQ=4),
yd_h1 = TIMESERIES(c(yd_h1),
START=c(2005,2),FREQ=4),
yd_hk = TIMESERIES(c(yd_hk),
START=c(2005,2),FREQ=4),
nsben_h = TIMESERIES(c(nsben_h),
START=c(2005,2),FREQ=4),
s_h = TIMESERIES(c(s_h),
START=c(2005,2),FREQ=4),
nl_h = TIMESERIES(c(nl_h),
START=c(2005,2),FREQ=4),
pconk = TIMESERIES(c(pconk),
START=c(2005,2),FREQ=4),
pcon = TIMESERIES(c(pcon),
START=c(2005,2),FREQ=4),
i_bd_h_k_ds = TIMESERIES(c(i_bd_h_k_ds),
START=c(2005,2),FREQ=4),
i_bd_h_k = TIMESERIES(c(i_bd_h_k),
START=c(2005,2),FREQ=4),
i_equip_h_k_ds = TIMESERIES(c(i_equip_h_k_ds),
START=c(2005,2),FREQ=4),
i_equip_h_k = TIMESERIES(c(i_equip_h_k),
START=c(2005,2),FREQ=4),
propinc_p_h = TIMESERIES(c(propinc_p_h),
START=c(2005,2),FREQ=4),
nben_h = TIMESERIES(c(nben_h),
START=c(2005,2),FREQ=4), ##Skal laves om!!!
## Financial site
sec_h_tr_g = TIMESERIES(c(sec_h_tr_g),
START=c(2005,2),FREQ=4),
l_h = TIMESERIES(c(l_h),
START=c(2005,2),FREQ=4),
iba_h_tr = TIMESERIES(c(iba_h_tr),
START=c(2005,2),FREQ=4),
eq_h_nf = TIMESERIES(c(eq_h_nf),
START=c(2005,2),FREQ=4),
eq_h_f = TIMESERIES(c(eq_h_f),
START=c(2005,2),FREQ=4),
eq_h_row = TIMESERIES(c(eq_h_row),
START=c(2005,2),FREQ=4),
eq_h_nf_tr = TIMESERIES(c(eq_h_nf_tr),
START=c(2005,2),FREQ=4),
eq_h_f_tr = TIMESERIES(c(eq_h_f_tr),
START=c(2005,2),FREQ=4),
eq_h_row_tr = TIMESERIES(c(eq_h_row_tr),
START=c(2005,2),FREQ=4),
eq_h_test = TIMESERIES(c(eq_h_test),
START=c(2005,2),FREQ=4),
ins_h = TIMESERIES(c(ins_h),
START=c(2005,2),FREQ=4),
ins_h_tr = TIMESERIES(c(ins_h_tr),
START=c(2005,2),FREQ=4),
lev_h = TIMESERIES(c(lev_h),
START=c(2005,3),FREQ=4),
## NET WEALTH AND FINANCIAL NET WEALTH
fa_h = TIMESERIES(c(fa_h),
START=c(2005,2),FREQ=4),
fnw_h = TIMESERIES(c(fnw_h),
START=c(2005,2),FREQ=4),
fnw_hk = TIMESERIES(c(fnw_hk),
START=c(2005,2),FREQ=4),
## Capital Account
i_bd_h = TIMESERIES(c(i_bd_h),
START=c(2005,2),FREQ=4),
i_equip_h = TIMESERIES(c(i_equip_h),
START=c(2005,2),FREQ=4),
bd_h_k = TIMESERIES(c(bd_h_k),
START=c(2005,2),FREQ=4),
equip_h_k = TIMESERIES(c(equip_h_k),
START=c(2005,2),FREQ=4),
bd_h = TIMESERIES(c(bd_h),
START=c(2005,2),FREQ=4),
equip_h = TIMESERIES(c(equip_h),
START=c(2005,2),FREQ=4),
## Non-Financial sector
y = TIMESERIES(c(y),
START=c(2005,2),FREQ=4),
yk = TIMESERIES(c(yk),
START=c(2005,2),FREQ=4),
sk = TIMESERIES(c(sk),
START=c(2005,2),FREQ=4),
gk = TIMESERIES(c(gk),
START=c(2005,2),FREQ=4),
x = TIMESERIES(c(x),
START=c(2005,2),FREQ=4),
rer = TIMESERIES(c(rer),
START=c(2005,2),FREQ=4),
xk_ds = TIMESERIES(c(xk_ds),
START=c(2005,2),FREQ=4),
xk = TIMESERIES(c(xk),
START=c(2005,2),FREQ=4),
m = TIMESERIES(c(m),
START=c(2005,2),FREQ=4),
mk_ds = TIMESERIES(c(mk_ds),
START=c(2005,2),FREQ=4),
mk = TIMESERIES(c(mk),
START=c(2005,2),FREQ=4),
py = TIMESERIES(c(py),
START=c(2005,2),FREQ=4),
s = TIMESERIES(c(s),
START=c(2005,2),FREQ=4),
w_nf = TIMESERIES(c(w_nf),
START=c(2005,2),FREQ=4),
b2_nf_r = TIMESERIES(c(b2_nf_r),
START=c(2005,2),FREQ=4),
yf = TIMESERIES(c(yf),
START=c(2005,2),FREQ=4),
b2 = TIMESERIES(c(b2),
START=c(2005,2),FREQ=4),
ws = TIMESERIES(c(ws),
START=c(2005,2),FREQ=4),
ps = TIMESERIES(c(ps),
START=c(2005,2),FREQ=4),
prate = TIMESERIES(c(prate),
START=c(2005,3),FREQ=4),
tobinq = TIMESERIES(c(tobinq),
START=c(2005,2),FREQ=4),
i_bd_nfc_k_ds = TIMESERIES(c(i_bd_nfc_k_ds),
START=c(2005,2),FREQ=4),
i_bd_nfc_k = TIMESERIES(c(i_bd_nfc_k),
START=c(2005,2),FREQ=4),
i_equip_nfc_k = TIMESERIES(c(i_equip_nfc_k),
START=c(2005,2),FREQ=4),
ik = TIMESERIES(c(ik),
START=c(2005,2),FREQ=4),
i_h = TIMESERIES(c(i_h),
START=c(2005,2),FREQ=4),
i_nf = TIMESERIES(c(i_nf),
START=c(2005,2),FREQ=4),
i_f = TIMESERIES(c(i_f),
START=c(2005,2),FREQ=4),
i_g = TIMESERIES(c(i_g),
START=c(2005,2),FREQ=4),
i = TIMESERIES(c(i),
START=c(2005,2),FREQ=4),
i_equip_nfc_k_ds = TIMESERIES(c(i_equip_nfc_k_ds),
START=c(2005,2),FREQ=4),
int_nf = TIMESERIES(c(int_nf),
START=c(2005,3),FREQ=4),
div_nf = TIMESERIES(c(div_nf),
START=c(2005,3),FREQ=4),
insu_nf = TIMESERIES(c(insu_nf),
START=c(2005,2),FREQ=4),
npropinc_nf = TIMESERIES(c(npropinc_nf),
START=c(2005,3),FREQ=4),
yh_nf = TIMESERIES(c(yh_nf),
START=c(2005,2),FREQ=4),
s_nf = TIMESERIES(c(s_nf),
START=c(2005,2),FREQ=4),
tax_nf = TIMESERIES(c(tax_nf),
START=c(2005,2),FREQ=4),
nl_nf = TIMESERIES(c(nl_nf),
START=c(2005,2),FREQ=4),
## Financial site
iba_nf = TIMESERIES(c(iba_nf),
START=c(2005,2),FREQ=4),
iba_nf_tr = TIMESERIES(c(iba_nf_tr),
START=c(2005,2),FREQ=4),
sec_nf = TIMESERIES(c(sec_nf),
START=c(2005,2),FREQ=4),
l_nf = TIMESERIES(c(l_nf),
START=c(2005,2),FREQ=4),
eq_nf_a = TIMESERIES(c(eq_nf_a),
START=c(2005,2),FREQ=4),
eq_nf_a_nf = TIMESERIES(c(eq_nf_a_nf),
START=c(2005,2),FREQ=4),
eq_nf_l_nf = TIMESERIES(c(eq_nf_l_nf),
START=c(2005,2),FREQ=4),
eq_nf_ax = TIMESERIES(c(eq_nf_ax),
START=c(2005,2),FREQ=4),
eq_nf_a_f = TIMESERIES(c(eq_nf_a_f),
START=c(2005,2),FREQ=4),
eq_nf_a_row = TIMESERIES(c(eq_nf_a_row),
START=c(2005,2),FREQ=4),
eq_nf_l = TIMESERIES(c(eq_nf_l),
START=c(2005,2),FREQ=4),
neq_nf = TIMESERIES(c(Neq_nf),
START=c(2005,2),FREQ=4),
neq_nf_tr = TIMESERIES(c(Neq_nf_tr),
START=c(2005,3),FREQ=4),
eq_nf_a_test = TIMESERIES(c(eq_nf_a_test),
START=c(2005,2),FREQ=4),
eq_nf_l_test = TIMESERIES(c(eq_nf_l_test),
START=c(2005,2),FREQ=4),
ins_nf = TIMESERIES(c(ins_nf),
START=c(2005,2),FREQ=4),
fnw_nf = TIMESERIES(c(fnw_nf),
START=c(2005,2),FREQ=4),
fnw_nfk = TIMESERIES(c(fnw_nfk),
START=c(2005,2),FREQ=4),
## Capital account
i_bd_nfc = TIMESERIES(c(i_bd_nfc),
START=c(2005,2),FREQ=4),
i_equip_nfc = TIMESERIES(c(i_equip_nfc),
START=c(2005,2),FREQ=4),
bd_nfc_k = TIMESERIES(c(bd_nfc_k),
START=c(2005,2),FREQ=4),
equip_nfc_k = TIMESERIES(c(equip_nfc_k),
START=c(2005,2),FREQ=4),
bd_nfc = TIMESERIES(c(bd_nfc),
START=c(2005,2),FREQ=4),
equip_nfc = TIMESERIES(c(equip_nfc),
START=c(2005,2),FREQ=4),
## Financial corp
int_f = TIMESERIES(c(int_f),
START=c(2005,3),FREQ=4),
div_f = TIMESERIES(c(div_f),
START=c(2005,3),FREQ=4),
insu_f = TIMESERIES(c(insu_f),
START=c(2005,2),FREQ=4),
propinc_r_f = TIMESERIES(c(propinc_r_f),
START=c(2005,2),FREQ=4),
propinc_p_f = TIMESERIES(c(propinc_p_f),
START=c(2005,2),FREQ=4),
npropinc_f = TIMESERIES(c(npropinc_f),
START=c(2005,3),FREQ=4),
yh_f = TIMESERIES(c(yh_f),
START=c(2005,2),FREQ=4),
yd_f = TIMESERIES(c(yd_f),
START=c(2005,2),FREQ=4),
d8_f = TIMESERIES(c(d8_f),
START=c(2005,2),FREQ=4),
nben_f = TIMESERIES(c(nben_f),
START=c(2005,2),FREQ=4),
s_f = TIMESERIES(c(s_f),
START=c(2005,2),FREQ=4),
nl_f = TIMESERIES(c(nl_f),
START=c(2005,2),FREQ=4),
iba_f = TIMESERIES(c(iba_f),
START=c(2005,2),FREQ=4),
iba_f_tr = TIMESERIES(c(iba_f_tr),
START=c(2005,2),FREQ=4),
eq_f_a = TIMESERIES(c(eq_f_a),
START=c(2005,2),FREQ=4),
eq_f_a_nf = TIMESERIES(c(eq_f_a_nf),
START=c(2005,2),FREQ=4),
eq_f_a_f = TIMESERIES(c(eq_f_a_f),
START=c(2005,2),FREQ=4),
eq_f_l_f = TIMESERIES(c(eq_f_l_f),
START=c(2005,2),FREQ=4),
eq_f_a_row = TIMESERIES(c(eq_f_a_row),
START=c(2005,2),FREQ=4),
eq_f_ax = TIMESERIES(c(eq_f_ax),
START=c(2005,2),FREQ=4),
eq_f_l = TIMESERIES(c(eq_f_l),
START=c(2005,2),FREQ=4),
eq_f_lx = TIMESERIES(c(eq_f_lx),
START=c(2005,2),FREQ=4),
neq_f = TIMESERIES(c(Neq_f),
START=c(2005,2),FREQ=4),
neq_f_tr = TIMESERIES(c(Neq_f_tr),
START=c(2005,3),FREQ=4),
eq_f_l_test = TIMESERIES(c(eq_f_l_test),
START=c(2005,2),FREQ=4),
sec_f_d = TIMESERIES(c(sec_f_d),
START=c(2005,2),FREQ=4),
sec_f_d_tr = TIMESERIES(c(sec_f_d_tr),
START=c(2005,2),FREQ=4),
sec_f_d_tr_nf = TIMESERIES(c(sec_f_d_tr_nf),
START=c(2005,2),FREQ=4),
sec_f_d_tr_g = TIMESERIES(c(sec_f_d_tr_g),
START=c(2005,2),FREQ=4),
sec_f_a = TIMESERIES(c(sec_f_a),
START=c(2005,2),FREQ=4),
sec_f_a_tr = TIMESERIES(c(sec_f_a_tr),
START=c(2005,2),FREQ=4),
l_f = TIMESERIES(c(l_f),
START=c(2005,2),FREQ=4),
l_f_tr = TIMESERIES(c(l_f_tr),
START=c(2005,2),FREQ=4),
ins_f = TIMESERIES(c(ins_f),
START=c(2005,2),FREQ=4),
ins_f_tr = TIMESERIES(c(ins_f_tr),
START=c(2005,2),FREQ=4),
fnw_f = TIMESERIES(c(fnw_f),
START=c(2005,2),FREQ=4),
fnw_fk = TIMESERIES(c(fnw_fk),
START=c(2005,2),FREQ=4),
i_bd_fc = TIMESERIES(c(i_bd_fc),
START=c(2005,2),FREQ=4),
i_equip_fc = TIMESERIES(c(i_equip_fc),
START=c(2005,2),FREQ=4),
bd_fc_k = TIMESERIES(c(bd_fc_k),
START=c(2005,2),FREQ=4),
equip_fc_k = TIMESERIES(c(equip_fc_k),
START=c(2005,2),FREQ=4),
bd_fc = TIMESERIES(c(bd_fc),
START=c(2005,2),FREQ=4),
equip_fc = TIMESERIES(c(equip_fc),
START=c(2005,2),FREQ=4),
## Govt
int_g = TIMESERIES(c(int_g),
START=c(2005,3),FREQ=4),
int_g_sec = TIMESERIES(c(int_g_sec),
START=c(2005,3),FREQ=4),
int_nf_sec = TIMESERIES(c(int_nf_sec),
START=c(2005,3),FREQ=4),
int_f_sec = TIMESERIES(c(int_nf_sec),
START=c(2005,3),FREQ=4),
int_f_a_sec = TIMESERIES(c(int_f_a_sec),
START=c(2005,3),FREQ=4),
int_f_d_sec = TIMESERIES(c(int_f_d_sec),
START=c(2005,3),FREQ=4),
int_h_sec = TIMESERIES(c(int_h_sec),
START=c(2005,3),FREQ=4),
int_row_sec = TIMESERIES(c(int_row_sec),
START=c(2005,3),FREQ=4),
div_g = TIMESERIES(c(div_g),
START=c(2005,3),FREQ=4),
insu_g = TIMESERIES(c(insu_g),
START=c(2005,2),FREQ=4),
propinc_r_g = TIMESERIES(c(propinc_r_g),
START=c(2005,2),FREQ=4),
propinc_p_g = TIMESERIES(c(propinc_p_g),
START=c(2005,2),FREQ=4),
npropinc_g = TIMESERIES(c(npropinc_g),
START=c(2005,3),FREQ=4),
yh_g = TIMESERIES(c(yh_g),
START=c(2005,2),FREQ=4),
yd_g = TIMESERIES(c(yd_g),
START=c(2005,2),FREQ=4),
nben_g = TIMESERIES(c(nben_g),
START=c(2005,2),FREQ=4),
tax_g = TIMESERIES(c(tax_g),
START=c(2005,2),FREQ=4),
s_g = TIMESERIES(c(s_g),
START=c(2005,2),FREQ=4),
nl_g = TIMESERIES(c(nl_g),
START=c(2005,2),FREQ=4),
iba_g = TIMESERIES(c(iba_g),
START=c(2005,2),FREQ=4),
eq_g = TIMESERIES(c(eq_g),
START=c(2005,2),FREQ=4),
eq_g_nf = TIMESERIES(c(eq_g_nf),
START=c(2005,2),FREQ=4),
eq_g_f = TIMESERIES(c(eq_g_f),
START=c(2005,2),FREQ=4),
eq_g_row = TIMESERIES(c(eq_g_row),
START=c(2005,2),FREQ=4),
eq_g_ax = TIMESERIES(c(eq_g_ax),
START=c(2005,2),FREQ=4),
eq_g_test = TIMESERIES(c(eq_g_test),
START=c(2005,2),FREQ=4),
sec_g = TIMESERIES(c(sec_g),
START=c(2005,2),FREQ=4),
sec_g_tr = TIMESERIES(c(sec_g_tr),
START=c(2005,2),FREQ=4),
l_g = TIMESERIES(c(l_g),
START=c(2005,2),FREQ=4),
ins_g = TIMESERIES(c(ins_g),
START=c(2005,2),FREQ=4),
fnw_g = TIMESERIES(c(fnw_g),
START=c(2005,2),FREQ=4),
fnw_gk = TIMESERIES(c(fnw_gk),
START=c(2005,2),FREQ=4),
i_bd_g = TIMESERIES(c(i_bd_g ),
START=c(2005,2),FREQ=4),
i_equip_g = TIMESERIES(c(i_equip_g),
START=c(2005,2),FREQ=4),
bd_g_k = TIMESERIES(c(bd_g_k),
START=c(2005,2),FREQ=4),
equip_g_k = TIMESERIES(c(equip_g_k),
START=c(2005,2),FREQ=4),
bd_g = TIMESERIES(c(bd_g),
START=c(2005,2),FREQ=4),
equip_g = TIMESERIES(c(equip_g),
START=c(2005,2),FREQ=4),
## ROW
int_row = TIMESERIES(c(int_row),
START=c(2005,3),FREQ=4),
div_row = TIMESERIES(c(div_row),
START=c(2005,3),FREQ=4),
insu_row = TIMESERIES(c(insu_row),
START=c(2005,2),FREQ=4),
propinc_r_row = TIMESERIES(c(propinc_r_row),
START=c(2005,2),FREQ=4),
propinc_p_row = TIMESERIES(c(propinc_p_row),
START=c(2005,2),FREQ=4),
npropinc_row = TIMESERIES(c(npropinc_row),
START=c(2005,3),FREQ=4),
s_row = TIMESERIES(c(s_row),
START=c(2005,2),FREQ=4),
nl_row = TIMESERIES(c(nl_row),
START=c(2005,3),FREQ=4),
nben_row = TIMESERIES(c(nben_row),
START=c(2005,2),FREQ=4),
nx = TIMESERIES(c(nx),
START=c(2005,2),FREQ=4),
cab = TIMESERIES(c(cab),
START=c(2005,3),FREQ=4),
bop = TIMESERIES(c(bop),
START=c(2005,3),FREQ=4),
fab = TIMESERIES(c(fab),
START=c(2005,3),FREQ=4),
iba_row = TIMESERIES(c(iba_row),
START=c(2005,2),FREQ=4),
iba_row_tr = TIMESERIES(c(iba_row_tr),
START=c(2005,2),FREQ=4),
sec_row = TIMESERIES(c(sec_row),
START=c(2005,2),FREQ=4),
l_row = TIMESERIES(c(l_row),
START=c(2005,2),FREQ=4),
eq_row_a = TIMESERIES(c(eq_row_a),
START=c(2005,2),FREQ=4),
eq_row_a_nf = TIMESERIES(c(eq_row_a_nf),
START=c(2005,2),FREQ=4),
eq_row_a_f = TIMESERIES(c(eq_row_a_f),
START=c(2005,2),FREQ=4),
eq_row_ax = TIMESERIES(c(eq_row_ax),
START=c(2005,2),FREQ=4),
eq_row_a_test = TIMESERIES(c(eq_row_a_test),
START=c(2005,2),FREQ=4),
eq_row_l = TIMESERIES(c(eq_row_l),
START=c(2005,2),FREQ=4),
eq_row_lx = TIMESERIES(c(eq_row_lx),
START=c(2005,2),FREQ=4),
eq_row_l_test = TIMESERIES(c(eq_row_l_test),
START=c(2005,2),FREQ=4),
neq_row = TIMESERIES(c(Neq_row),
START=c(2005,2),FREQ=4),
neq_row_tr = TIMESERIES(c(Neq_row_tr),
START=c(2005,3),FREQ=4),
ins_row = TIMESERIES(c(ins_row),
START=c(2005,2),FREQ=4),
fnw_row = TIMESERIES(c(fnw_row),
START=c(2005,2),FREQ=4),
fnw_rowk = TIMESERIES(c(fnw_rowk),
START=c(2005,2),FREQ=4),
## Labour market
unadj = TIMESERIES(c(unadj),
START=c(2005,2),FREQ=4),
unemp = TIMESERIES(c(unemp),
START=c(2005,2),FREQ=4),
ur = TIMESERIES(c(ur),
START=c(2005,2),FREQ=4),
uradj = TIMESERIES(c(uradj),
START=c(2005,2),FREQ=4),
lf = TIMESERIES(c(LF),
START=c(2005,2),FREQ=4),
pc_ds = TIMESERIES(c(pc_ds),
START=c(2005,2),FREQ=4),
pc = TIMESERIES(c(pc),
START=c(2005,2),FREQ=4),
mkp = TIMESERIES(c(mkp),
START=c(2005,2),FREQ=4),
wage_ds = TIMESERIES(c(wage_ds),
START=c(2005,2),FREQ=4),
wage_ds_t = TIMESERIES(c(wage_ds_t),
START=c(2006,2),FREQ=4),
inflation = TIMESERIES(c(inflation),
START=c(2006,2),FREQ=4),
growth = TIMESERIES(c(growth),
START=c(2006,2),FREQ=4),
inflation_t = TIMESERIES(c(inflation_t),
START=c(2005,3),FREQ=4),
inflation_tt = TIMESERIES(c(inflation_tt),
START=c(2005,3),FREQ=4),
pm_ds = TIMESERIES(c(pm_ds),
START=c(2005,2),FREQ=4),
mk_ds = TIMESERIES(c(mk_ds),
START=c(2005,2),FREQ=4),
emp = TIMESERIES(c(emp),
START=c(2005,2),FREQ=4),
urterm = TIMESERIES(c(urterm),
START=c(2005,2),FREQ=4),
rw_ds = TIMESERIES(c(rw_ds),
START=c(2005,2),FREQ=4),
wage = TIMESERIES(c(wage),
START=c(2005,2),FREQ=4),
wageindex = TIMESERIES(c(wageindex),
START=c(2005,2),FREQ=4),
mkp = TIMESERIES(c(mkp),
START=c(2005,2),FREQ=4),
prod = TIMESERIES(c(prod),
START=c(2005,2),FREQ=4),
acc_rate = TIMESERIES(c(acc_rate),
START=c(2005,2),FREQ=4),
shock = TIMESERIES(c(shock),
START=c(2005,2),FREQ=4),
pf_shock = TIMESERIES(c(pf_shock),
START=c(2005,2),FREQ=4),
pm_ds_shock = TIMESERIES(c(pm_ds_shock),
START=c(2005,2),FREQ=4),
p_expect_shock = TIMESERIES(c(p_expect_shock),
START=c(2005,2),FREQ=4),
yk_ds_potential_shock = TIMESERIES(c(yk_ds_potential_shock),
START=c(2005,2),FREQ=4),
gdp_tp_shock = TIMESERIES(c(gdp_tp_shock),
START=c(2005,2),FREQ=4),
iloan_shock = TIMESERIES(c(iloan_shock),
START=c(2005,2),FREQ=4),
idep_shock = TIMESERIES(c(idep_shock),
START=c(2005,2),FREQ=4),
ibd_shock = TIMESERIES(c(ibd_shock),
START=c(2005,2),FREQ=4),
iboa_shock = TIMESERIES(c(iboa_shock),
START=c(2005,2),FREQ=4),
tax_rate1_shock = TIMESERIES(c(tax_rate1_shock),
START=c(2005,2),FREQ=4),
tax_rate_p = TIMESERIES(c(tax_rate_p),
START=c(2005,2),FREQ=4),
tax_rate_p_shock = TIMESERIES(c(tax_rate_p_shock),
START=c(2005,2),FREQ=4),
## Dummies
d_2011q2 = TIMESERIES(c(d_2011q2),
START=c(2005,2),FREQ=4),
d_2013q1 = TIMESERIES(c(d_2013q1),
START=c(2005,2),FREQ=4),
d_2017q3 = TIMESERIES(c(d_2017q3),
START=c(2005,2),FREQ=4),
d_2006q1 = TIMESERIES(c(d_2006q1),
START=c(2005,2),FREQ=4),
d_2006q2 = TIMESERIES(c(d_2006q2),
START=c(2005,2),FREQ=4),
d_2006q3 = TIMESERIES(c(d_2006q3),
START=c(2005,2),FREQ=4),
d_2006q4 = TIMESERIES(c(d_2006q4),
START=c(2005,2),FREQ=4),
d_2007q34 = TIMESERIES(c(d_2007q34),
START=c(2005,2),FREQ=4),
d_2008q2 = TIMESERIES(c(d_2008q2),
START=c(2005,2),FREQ=4),
d_2008q3 = TIMESERIES(c(d_2008q3),
START=c(2005,2),FREQ=4),
d_2008q4 = TIMESERIES(c(d_2008q4),
START=c(2005,2),FREQ=4),
d_2009q1 = TIMESERIES(c(d_2009q1),
START=c(2005,2),FREQ=4),
d_2009q2 = TIMESERIES(c(d_2009q2),
START=c(2005,2),FREQ=4),
d_2009q4 = TIMESERIES(c(d_2009q4),
START=c(2005,2),FREQ=4),
d_2018q2 = TIMESERIES(c(d_2018q2),
START=c(2005,2),FREQ=4),
d_20123 = TIMESERIES(c(d_20123),
START=c(2005,2),FREQ=4),
d_20124 = TIMESERIES(c(d_20124),
START=c(2005,2),FREQ=4),
d_2011q1 = TIMESERIES(c(d_2011q1),
START=c(2005,2),FREQ=4),
d_2014q3 = TIMESERIES(c(d_2014q3),
START=c(2005,2),FREQ=4),
d_2014q4 = TIMESERIES(c(d_2014q4),
START=c(2005,2),FREQ=4),
d_2013q4 = TIMESERIES(c(d_2013q4),
START=c(2005,2),FREQ=4),
d_2018q1 = TIMESERIES(c(d_2018q1),
START=c(2005,2),FREQ=4),
d_2016q3 = TIMESERIES(c(d_2016q3),
START=c(2005,2),FREQ=4),
d_2019q3 = TIMESERIES(c(d_2019q3),
START=c(2005,2),FREQ=4),
d_2019q4 = TIMESERIES(c(d_2019q4),
START=c(2005,2),FREQ=4),
d_2020q1 = TIMESERIES(c(d_2020q1),
START=c(2005,2),FREQ=4),
d_2017q1 = TIMESERIES(c(d_2017q1),
START=c(2005,2),FREQ=4),
d_2017q23 = TIMESERIES(c(d_2017q23),
START=c(2005,2),FREQ=4),
d_2007q3 = TIMESERIES(c(d_2007q3),
START=c(2005,2),FREQ=4),
d_2013q4 = TIMESERIES(c(d_2013q4),
START=c(2005,2),FREQ=4),
dummy_2018q34 = TIMESERIES(c(dummy_2018q34),
START=c(2005,2),FREQ=4),
dummy_2011q1 = TIMESERIES(c(dummy_2011q1),
START=c(2005,2),FREQ=4),
dummy_2009q2 = TIMESERIES(c(dummy_2009q2),
START=c(2005,2),FREQ=4),
time = TIMESERIES(c(time),
START=c(2005,2),FREQ=4),
dummy_4 = TIMESERIES(c(DUMMY_4),
START=c(2005,2),FREQ=4),
dummy_10 = TIMESERIES(c(DUMMY_10),
START=c(2005,2),FREQ=4),
dummy_11 = TIMESERIES(c(DUMMY_11),
START=c(2005,2),FREQ=4),
## Deseason variables
alpha_00 = TIMESERIES(c(alpha_00),
START=c(2005,2),FREQ=4),
alpha_01 = TIMESERIES(c(alpha_01),
START=c(2005,2),FREQ=4),
alpha_02 = TIMESERIES(c(alpha_02),
START=c(2005,2),FREQ=4),
alpha_03 = TIMESERIES(c(alpha_03),
START=c(2005,2),FREQ=4),
alpha_10 = TIMESERIES(c(alpha_10),
START=c(2005,2),FREQ=4),
alpha_11 = TIMESERIES(c(alpha_11),
START=c(2005,2),FREQ=4),
alpha_12 = TIMESERIES(c(alpha_12),
START=c(2005,2),FREQ=4),
alpha_13 = TIMESERIES(c(alpha_13),
START=c(2005,2),FREQ=4),
mean_i_bd_h_k = TIMESERIES(c(mean_i_bd_h_k),
START=c(2005,2),FREQ=4),
alpha_20 = TIMESERIES(c(alpha_20 ),
START=c(2005,2),FREQ=4),
alpha_21 = TIMESERIES(c(alpha_21),
START=c(2005,2),FREQ=4),
alpha_22 = TIMESERIES(c(alpha_22),
START=c(2005,2),FREQ=4),
alpha_23 = TIMESERIES(c(alpha_23),
START=c(2005,2),FREQ=4),
mean_i_equip_h_k = TIMESERIES(c(mean_i_equip_h_k),
START=c(2005,2),FREQ=4),
alpha_30 = TIMESERIES(c(alpha_30),
START=c(2005,2),FREQ=4),
alpha_31 = TIMESERIES(c(alpha_31),
START=c(2005,2),FREQ=4),
alpha_32 = TIMESERIES(c(alpha_32),
START=c(2005,2),FREQ=4),
alpha_33 = TIMESERIES(c(alpha_33),
START=c(2005,2),FREQ=4),
mean_i_bd_nfc_k = TIMESERIES(c(mean_i_bd_nfc_k),
START=c(2005,2),FREQ=4),
alpha_40 = TIMESERIES(c(alpha_40),
START=c(2005,2),FREQ=4),
alpha_41 = TIMESERIES(c(alpha_41),
START=c(2005,2),FREQ=4),
alpha_42 = TIMESERIES(c(alpha_42),
START=c(2005,2),FREQ=4),
alpha_43 = TIMESERIES(c(alpha_43),
START=c(2005,2),FREQ=4),
mean_i_equip_nfc_k = TIMESERIES(c(mean_i_equip_nfc_k),
START=c(2005,2),FREQ=4),
alpha_50 = TIMESERIES(c(alpha_50),
START=c(2005,2),FREQ=4),
alpha_51 = TIMESERIES(c(alpha_51),
START=c(2005,2),FREQ=4),
alpha_52 = TIMESERIES(c(alpha_52),
START=c(2005,2),FREQ=4),
alpha_53 = TIMESERIES(c(alpha_53),
START=c(2005,2),FREQ=4),
mean_wage = TIMESERIES(c(mean_wage),
START=c(2005,2),FREQ=4),
alpha_60 = TIMESERIES(c(alpha_60),
START=c(2005,2),FREQ=4),
alpha_61 = TIMESERIES(c(alpha_61),
START=c(2005,2),FREQ=4),
alpha_62 = TIMESERIES(c(alpha_62),
START=c(2005,2),FREQ=4),
alpha_63 = TIMESERIES(c(alpha_63),
START=c(2005,2),FREQ=4),
mean_pc = TIMESERIES(c(mean_pc),
START=c(2005,2),FREQ=4),
alpha_70 = TIMESERIES(c(alpha_70),
START=c(2005,2),FREQ=4),
alpha_71 = TIMESERIES(c(alpha_71),
START=c(2005,2),FREQ=4),
alpha_72 = TIMESERIES(c(alpha_72),
START=c(2005,2),FREQ=4),
alpha_73 = TIMESERIES(c(alpha_73),
START=c(2005,2),FREQ=4),
mean_mk = TIMESERIES(c(mean_mk),
START=c(2005,2),FREQ=4),
alpha_80 = TIMESERIES(c(alpha_80),
START=c(2005,2),FREQ=4),
alpha_81 = TIMESERIES(c(alpha_81),
START=c(2005,2),FREQ=4),
alpha_82 = TIMESERIES(c(alpha_82),
START=c(2005,2),FREQ=4),
alpha_83 = TIMESERIES(c(alpha_83),
START=c(2005,2),FREQ=4),
mean_xk = TIMESERIES(c(mean_xk),
START=c(2005,2),FREQ=4),
alpha_90 = TIMESERIES(c(alpha_90),
START=c(2005,2),FREQ=4),
alpha_90a = TIMESERIES(c(alpha_90a),
START=c(2005,2),FREQ=4),
alpha_91 = TIMESERIES(c(alpha_91),
START=c(2005,2),FREQ=4),
alpha_91a = TIMESERIES(c(alpha_91a),
START=c(2005,2),FREQ=4),
alpha_92 = TIMESERIES(c(alpha_92),
START=c(2005,2),FREQ=4),
alpha_92a = TIMESERIES(c(alpha_92a),
START=c(2005,2),FREQ=4),
alpha_93 = TIMESERIES(c(alpha_93),
START=c(2005,2),FREQ=4),
alpha_93a = TIMESERIES(c(alpha_93a),
START=c(2005,2),FREQ=4),
mean_yd1_hk = TIMESERIES(c(mean_yd1_hk),
START=c(2005,2),FREQ=4),
alpha_100 = TIMESERIES(c(alpha_100),
START=c(2005,2),FREQ=4),
alpha_101 = TIMESERIES(c(alpha_101),
START=c(2005,2),FREQ=4),
alpha_102 = TIMESERIES(c(alpha_102),
START=c(2005,2),FREQ=4),
alpha_103 = TIMESERIES(c(alpha_103),
START=c(2005,2),FREQ=4),
mean_prate = TIMESERIES(c(mean_prate),
START=c(2005,2),FREQ=4),
alpha_120 = TIMESERIES(c(alpha_120),
START=c(2005,2),FREQ=4),
alpha_121 = TIMESERIES(c(alpha_121),
START=c(2005,2),FREQ=4),
alpha_122 = TIMESERIES(c(alpha_122),
START=c(2005,2),FREQ=4),
alpha_123 = TIMESERIES(c(alpha_123),
START=c(2005,2),FREQ=4),
mean_ps = TIMESERIES(c(mean_ps),
START=c(2005,2),FREQ=4),
alpha_130 = TIMESERIES(c(alpha_130),
START=c(2005,2),FREQ=4),
alpha_131 = TIMESERIES(c(alpha_131),
START=c(2005,2),FREQ=4),
alpha_132 = TIMESERIES(c(alpha_132),
START=c(2005,2),FREQ=4),
alpha_133 = TIMESERIES(c(alpha_133),
START=c(2005,2),FREQ=4),
mean_ur = TIMESERIES(c(mean_ur),
START=c(2005,2),FREQ=4),
alpha_140 = TIMESERIES(c(alpha_140),
START=c(2005,2),FREQ=4),
alpha_141 = TIMESERIES(c(alpha_141),
START=c(2005,2),FREQ=4),
alpha_142 = TIMESERIES(c(alpha_142),
START=c(2005,2),FREQ=4),
alpha_143 = TIMESERIES(c(alpha_143),
START=c(2005,2),FREQ=4),
mean_yd2a_hk = TIMESERIES(c(mean_yd2a_hk),
START=c(2005,2),FREQ=4),
alpha_110 = TIMESERIES(c(alpha_110),
START=c(2005,2),FREQ=4),
alpha_111 = TIMESERIES(c(alpha_111),
START=c(2005,2),FREQ=4),
alpha_112 = TIMESERIES(c(alpha_112),
START=c(2005,2),FREQ=4),
alpha_113 = TIMESERIES(c(alpha_113),
START=c(2005,2),FREQ=4),
mean_yk = TIMESERIES(c(mean_yk),
START=c(2005,2),FREQ=4),
mean_y = TIMESERIES(c(mean_y),
START=c(2005,2),FREQ=4),
mean_pconk = TIMESERIES(c(mean_pconk),
START=c(2005,2),FREQ=4),
yd_hk_ds = TIMESERIES(c(yd_hk_ds),
START=c(2005,2),FREQ=4),
i_equip_h_k_ds = TIMESERIES(c(i_equip_h_k_ds),
START=c(2005,2),FREQ=4),
i_bd_nfc_k_ds = TIMESERIES(c(i_bd_nfc_k_ds),
START=c(2005,2),FREQ=4),
u_ds = TIMESERIES(c(u_ds),
START=c(2005,2),FREQ=4),
ps_ds = TIMESERIES(c(ps_ds),
START=c(2005,2),FREQ=4),
i_equip_nfc_k_ds = TIMESERIES(c(i_equip_nfc_k_ds),
START=c(2005,2),FREQ=4),
pconk_ds = TIMESERIES(c(pconk_ds),
START=c(2005,2),FREQ=4),
b2_hk_ds = TIMESERIES(c(b2_hk_ds),
START=c(2005,2),FREQ=4),
yd1_hk_ds = TIMESERIES(c(yd1_hk_ds ),
START=c(2005,2),FREQ=4),
yd2a_hk_ds = TIMESERIES(c(yd2a_hk_ds),
START=c(2005,2),FREQ=4),
w_h_rk_ds = TIMESERIES(c(w_h_rk_ds),
START=c(2005,2),FREQ=4),
pm_ds = TIMESERIES(c(pm_ds),
START=c(2005,2),FREQ=4),
ur_ds = TIMESERIES(c(ur_ds),
START=c(2005,2),FREQ=4),
yk_ds = TIMESERIES(c(yk_ds),
START=c(2005,2),FREQ=4),
y_ds = TIMESERIES(c(y_ds),
START=c(2005,2),FREQ=4),
yk_ds_potential= TIMESERIES(c(yk_ds_potential),
START=c(2005,2),FREQ=4),
wageindex_ds = TIMESERIES(c(wageindex_ds),
START=c(2005,2),FREQ=4),
priv_ds = TIMESERIES(c(priv_ds),
START=c(2005,2),FREQ=4),
mk_ds = TIMESERIES(c(mk_ds),
START=c(2005,2),FREQ=4),
prodk_ds = TIMESERIES(c(prodk_ds),
START=c(2005,2),FREQ=4),
prate_ds = TIMESERIES(c(prate_ds),
START=c(2005,3),FREQ=4),
bd_nfc_k_ds = TIMESERIES(c(bd_nfc_k_ds),
START=c(2005,2),FREQ=4),
xk_ds = TIMESERIES(c(xk_ds),
START=c(2005,2),FREQ=4),
rer_ds = TIMESERIES(c(rer_ds),
START=c(2005,2),FREQ=4),
prod_ds = TIMESERIES(c(prod_ds),
START=c(2005,2),FREQ=4),
ps_ds = TIMESERIES(c(ps_ds),
START=c(2005,2),FREQ=4),
y_ds = TIMESERIES(c(y_ds),
START=c(2005,2),FREQ=4),
SD1 = TIMESERIES(c(sd1),
START=c(2005,2),FREQ=4),
SD2 = TIMESERIES(c(sd2),
START=c(2005,2),FREQ=4),
SD3 = TIMESERIES(c(sd3),
START=c(2005,2),FREQ=4),
SD4 = TIMESERIES(c(sd4),
START=c(2005,2),FREQ=4),
## globaldemand1
oecd = TIMESERIES(c(oecd),
START=c(2005,2),FREQ=4),
oecde = TIMESERIES(c(oecde),
START=c(2005,2),FREQ=4),
g_20 = TIMESERIES(c(g_20),
START=c(2005,2),FREQ=4),
ea19 = TIMESERIES(c(ea19),
START=c(2005,2),FREQ=4),
eu = TIMESERIES(c(eu),
START=c(2005,2),FREQ=4),
gdp_tp = TIMESERIES(c(gdp_tp),
START=c(2005,2),FREQ=4),
rer_old = TIMESERIES(c(rer_old),
START=c(2005,2),FREQ=4),
xr = TIMESERIES(c(xr),
START=c(2005,2),FREQ=4),
p_trade = TIMESERIES(c(p_trade),
START=c(2005,2),FREQ=4),
## Exogene
p_bd = TIMESERIES(c(p_bd),
START=c(2005,2),FREQ=4),
pi_1 = TIMESERIES(c(pi_1),
START=c(2005,2),FREQ=4),
zaland_jesper = TIMESERIES(c(zaland_jesper ),
START=c(2005,2),FREQ=4),
ibd = TIMESERIES(c(ibd),
START=c(2005,2),FREQ=4),
iba_h = TIMESERIES(c(iba_h),
START=c(2005,2),FREQ=4),
sec_h = TIMESERIES(c(sec_h),
START=c(2005,2),FREQ=4),
div_r_h = TIMESERIES(c(div_r_h),
START=c(2005,2),FREQ=4),
eq_h_rvx = TIMESERIES(c(eq_h_rvx),
START=c(2005,3),FREQ=4),
old_age_ratio = TIMESERIES(c(old_age_ratio),
START=c(2005,2),FREQ=4),
iloan = TIMESERIES(c(iloan),
START=c(2005,2),FREQ=4),
l_h_tr = TIMESERIES(c(l_h_tr),
START=c(2005,2),FREQ=4),
l_h_tr_ratio = TIMESERIES(c(l_h_tr_ratio),
START=c(2005,2),FREQ=4),
eq_h = TIMESERIES(c(eq_h),
START=c(2005,2),FREQ=4),
d8_h = TIMESERIES(c(d8_h),
START=c(2005,2),FREQ=4),
eq_h_tr = TIMESERIES(c(eq_h_tr),
START=c(2005,3),FREQ=4),
eq_nf_lx = TIMESERIES(c(eq_nf_lx),
START=c(2005,2),FREQ=4),
idep = TIMESERIES(c(idep),
START=c(2005,2),FREQ=4),
int_r_h_adj = TIMESERIES(c(int_r_h_adj),
START=c(2005,3),FREQ=4),
int_p_h_adj = TIMESERIES(c(int_p_h_adj),
START=c(2005,3),FREQ=4),
div_h_adj = TIMESERIES(c(div_h_adj),
START=c(2005,3),FREQ=4),
diva = TIMESERIES(c(diva),
START=c(2005,2),FREQ=4),
divd = TIMESERIES(c(divd),
START=c(2005,2),FREQ=4),
ins_h_adj = TIMESERIES(c(ins_h_adj),
START=c(2005,3),FREQ=4),
res_r_h = TIMESERIES(c(res_r_h),
START=c(2005,2),FREQ=4),
res_p_h = TIMESERIES(c(res_p_h ),
START=c(2005,2),FREQ=4),
oth_h = TIMESERIES(c(oth_h),
START=c(2005,2),FREQ=4),
tax_rate2 = TIMESERIES(c(tax_rate2),
START=c(2005,2),FREQ=4),
tax_rate1 = TIMESERIES(c(tax_rate1),
START=c(2005,2),FREQ=4),
tax_h_adj = TIMESERIES(c(tax_h_adj),
START=c(2005,2),FREQ=4),
tax_rate_p = TIMESERIES(c(tax_rate_p),
START=c(2005,2),FREQ=4),
tax_p_adj = TIMESERIES(c(tax_p_adj),
START=c(2005,2),FREQ=4),
np_h = TIMESERIES(c(np_h),
START=c(2005,2),FREQ=4),
ctr_h = TIMESERIES(c(ctr_h),
START=c(2005,2),FREQ=4),
iba_h_rvx = TIMESERIES(c(iba_h_rvx),
START=c(2005,3),FREQ=4),
sec_h_tr = TIMESERIES(c(sec_h_tr),
START=c(2005,2),FREQ=4),
sec_h_rvx = TIMESERIES(c(sec_h_rvx),
START=c(2005,3),FREQ=4),
l_h_rvx = TIMESERIES(c(l_h_rvx),
START=c(2005,3),FREQ=4),
sec_h_tr = TIMESERIES(c(sec_h_tr),
START=c(2005,2),FREQ=4),
nl_h_adj = TIMESERIES(c(nl_h_adj),
START=c(2005,3),FREQ=4),
alpha_nf = TIMESERIES(c(alpha_nf),
START=c(2005,2),FREQ=4),
alpha_f = TIMESERIES(c(alpha_f),
START=c(2005,2),FREQ=4),
alpha_row = TIMESERIES(c(alpha_row),
START=c(2005,2),FREQ=4),
eq_h_nf_rvx = TIMESERIES(c(eq_h_nf_rvx),
START=c(2005,3),FREQ=4),
eq_h_row_rvx = TIMESERIES(c(eq_h_row_rvx),
START=c(2005,3),FREQ=4),
ins_h_rvx = TIMESERIES(c(ins_h_rvx),
START=c(2005,3),FREQ=4),
ins_h_tr_excl_d8 = TIMESERIES(c(ins_h_tr_excl_d8),
START=c(2005,2),FREQ=4),
p_equip = TIMESERIES(c(p_equip ),
START=c(2005,2),FREQ=4),
delta_bd_h = TIMESERIES(c(delta_bd_h),
START=c(2005,2),FREQ=4),
delta_equip_h = TIMESERIES(c(delta_equip_h),
START=c(2005,2),FREQ=4),
w_row_r = TIMESERIES(c(w_row_r),
START=c(2005,2),FREQ=4),
w_row_p = TIMESERIES(c(w_row_p),
START=c(2005,2),FREQ=4),
b2_h_r = TIMESERIES(c(b2_h_r),
START=c(2005,2),FREQ=4),
b2_f_r = TIMESERIES(c(b2_f_r),
START=c(2005,2),FREQ=4),
b2_g_r = TIMESERIES(c(b2_g_r),
START=c(2005,2),FREQ=4),
p_tax = TIMESERIES(c(p_tax),
START=c(2005,2),FREQ=4),
p_tax_row = TIMESERIES(c(p_tax_row),
START=c(2005,2),FREQ=4),
p_sub = TIMESERIES(c(p_sub),
START=c(2005,2),FREQ=4),
p_sub_row = TIMESERIES(c(p_sub_row),
START=c(2005,2),FREQ=4),
zz = TIMESERIES(c(zz),
START=c(2005,2),FREQ=4),
i_equip_g_k = TIMESERIES(c(i_equip_g_k),
START=c(2005,2),FREQ=4),
i_equip_fc_k = TIMESERIES(c(i_equip_fc_k),
START=c(2005,2),FREQ=4),
i_bd_g_k = TIMESERIES(c(i_bd_g_k),
START=c(2005,2),FREQ=4),
i_bd_fc_k = TIMESERIES(c(i_bd_fc_k),
START=c(2005,2),FREQ=4),
i_adj_h_k = TIMESERIES(c(i_adj_h_k),
START=c(2005,2),FREQ=4),
i_adj_nfc_k = TIMESERIES(c(i_adj_nfc_k),
START=c(2005,2),FREQ=4),
i_adj_fc_k = TIMESERIES(c(i_adj_fc_k),
START=c(2005,2),FREQ=4),
i_adj_g_k = TIMESERIES(c(i_adj_g_k),
START=c(2005,2),FREQ=4),
insu = TIMESERIES(c(insu),
START=c(2005,2),FREQ=4),
int_nf_adj = TIMESERIES(c(int_nf_adj),
START=c(2005,3),FREQ=4),
ins_f_adj = TIMESERIES(c(ins_f_adj),
START=c(2005,3),FREQ=4),
oth_nf = TIMESERIES(c(oth_nf),
START=c(2005,2),FREQ=4),
tax_rate_nf = TIMESERIES(c(tax_rate_nf),
START=c(2005,2),FREQ=4),
np_nf = TIMESERIES(c(np_nf ),
START=c(2005,2),FREQ=4),
ctr_nf = TIMESERIES(c(ctr_nf),
START=c(2005,2),FREQ=4),
iba_nf_rvx = TIMESERIES(c(iba_nf_rvx),
START=c(2005,3),FREQ=4),
nl_nf_adj = TIMESERIES(c(nl_nf_adj),
START=c(2005,3),FREQ=4),
l_nf_tr = TIMESERIES(c(l_nf_tr),
START=c(2005,2),FREQ=4),
sec_nf_tr = TIMESERIES(c(sec_nf_tr),
START=c(2005,2),FREQ=4),
ins_nf_tr = TIMESERIES(c(ins_nf_tr),
START=c(2005,2),FREQ=4),
sec_nf_tr = TIMESERIES(c(sec_nf_tr),
START=c(2005,2),FREQ=4),
sec_nf_rvx = TIMESERIES(c(sec_nf_rvx),
START=c(2005,3),FREQ=4),
l_nf_rvx = TIMESERIES(c(l_nf_rvx),
START=c(2005,3),FREQ=4),
eq_nf_a_tr = TIMESERIES(c(eq_nf_a_tr),
START=c(2005,2),FREQ=4),
eq_nf_a_rvx = TIMESERIES(c(eq_nf_a_rvx),
START=c(2005,3),FREQ=4),
eq_nf_a_nf_tr = TIMESERIES(c(eq_nf_a_nf_tr),
START=c(2005,2),FREQ=4),
eq_nf_a_nf_rv = TIMESERIES(c(eq_nf_a_nf_rv),
START=c(2005,2),FREQ=4),
eq_nf_a_f_tr = TIMESERIES(c(eq_nf_a_f_tr),
START=c(2005,2),FREQ=4),
eq_nf_a_f_rv = TIMESERIES(c(eq_nf_a_f_rv),
START=c(2005,2),FREQ=4),
eq_nf_a_row_tr = TIMESERIES(c(eq_nf_a_row_tr),
START=c(2005,2),FREQ=4),
eq_nf_a_row_rv = TIMESERIES(c(eq_nf_a_row_rv),
START=c(2005,2),FREQ=4),
eq_nf_l_tr = TIMESERIES(c(eq_nf_l_tr),
START=c(2005,2),FREQ=4),
eq_nf_l_rvx = TIMESERIES(c(eq_nf_l_rvx),
START=c(2005,3),FREQ=4),
alpha_neq_nf = TIMESERIES(c(alpha_neq_nf),
START=c(2005,2),FREQ=4),
ins_nf_rvx = TIMESERIES(c(ins_nf_rvx),
START=c(2005,3),FREQ=4),
delta_bd_nfc = TIMESERIES(c(delta_bd_nfc),
START=c(2005,2),FREQ=4),
delta_equip_nfc = TIMESERIES(c(delta_equip_nfc),
START=c(2005,2),FREQ=4),
iboa = TIMESERIES(c(iboa),
START=c(2005,2),FREQ=4),
div_f_adj = TIMESERIES(c(div_f_adj),
START=c(2005,3),FREQ=4),
div_r_f = TIMESERIES(c(div_r_f),
START=c(2005,2),FREQ=4),
ins_r_f = TIMESERIES(c(ins_r_f),
START=c(2005,2),FREQ=4),
res_r_f = TIMESERIES(c(res_r_f),
START=c(2005,2),FREQ=4),
int_p_f = TIMESERIES(c(int_p_f),
START=c(2005,2),FREQ=4),
div_p_f = TIMESERIES(c(div_p_f),
START=c(2005,2),FREQ=4),
ins_p_f = TIMESERIES(c(ins_p_f ),
START=c(2005,2),FREQ=4),
res_p_f = TIMESERIES(c(res_p_f),
START=c(2005,2),FREQ=4),
int_f_adj = TIMESERIES(c(int_f_adj),
START=c(2005,3),FREQ=4),
tax_f = TIMESERIES(c(tax_f),
START=c(2005,2),FREQ=4),
oth_f = TIMESERIES(c(oth_f),
START=c(2005,2),FREQ=4),
ctr_f = TIMESERIES(c(ctr_f),
START=c(2005,2),FREQ=4),
iba_f_rvx = TIMESERIES(c(iba_f_rvx),
START=c(2005,3),FREQ=4),
iba_g_tr = TIMESERIES(c(iba_g_tr),
START=c(2005,2),FREQ=4),
eq_f_a_rvx = TIMESERIES(c(eq_f_a_rvx),
START=c(2005,3),FREQ=4),
eq_f_a_tr = TIMESERIES(c(eq_f_a_tr),
START=c(2005,2),FREQ=4),
eq_f_a_nf_tr = TIMESERIES(c(eq_f_a_nf_tr),
START=c(2005,2),FREQ=4),
eq_f_a_nf_rv = TIMESERIES(c(eq_f_a_nf_rv),
START=c(2005,2),FREQ=4),
eq_f_a_f_tr = TIMESERIES(c(eq_f_a_f_tr),
START=c(2005,2),FREQ=4),
eq_f_a_f_rv = TIMESERIES(c(eq_f_a_f_rv),
START=c(2005,2),FREQ=4),
eq_f_a_row_tr = TIMESERIES(c(eq_f_a_row_tr),
START=c(2005,2),FREQ=4),
eq_f_a_row_rv = TIMESERIES(c(eq_f_a_row_rv),
START=c(2005,2),FREQ=4),
eq_f_l_tr = TIMESERIES(c(eq_f_l_tr),
START=c(2005,2),FREQ=4),
eq_f_l_rvx = TIMESERIES(c(eq_f_l_rvx),
START=c(2005,3),FREQ=4),
neq_f_rvx = TIMESERIES(c(Neq_f_rvx),
START=c(2005,3),FREQ=4),
sec_f_d_rvx = TIMESERIES(c(sec_f_d_rvx),
START=c(2005,3),FREQ=4),
nl_f_adj = TIMESERIES(c(nl_f_adj),
START=c(2005,2),FREQ=4),
sec_f_a_rvx = TIMESERIES(c(sec_f_a_rvx),
START=c(2005,3),FREQ=4),
sec_row_tr = TIMESERIES(c(sec_row_tr),
START=c(2005,2),FREQ=4),
l_f_rvx = TIMESERIES(c(l_f_rvx),
START=c(2005,3),FREQ=4),
ins_f_rvx = TIMESERIES(c(ins_f_rvx),
START=c(2005,3),FREQ=4),
delta_bd_fc = TIMESERIES(c(delta_bd_fc),
START=c(2005,2),FREQ=4),
delta_equip_fc = TIMESERIES(c(delta_equip_fc),
START=c(2005,2),FREQ=4),
div_g_adj = TIMESERIES(c(div_g_adj),
START=c(2005,3),FREQ=4),
int_r_g = TIMESERIES(c(int_r_g),
START=c(2005,2),FREQ=4),
div_r_g = TIMESERIES(c(div_r_g),
START=c(2005,2),FREQ=4),
res_r_g = TIMESERIES(c(res_r_g),
START=c(2005,2),FREQ=4),
int_p_g = TIMESERIES(c(int_p_g),
START=c(2005,2),FREQ=4),
res_p_g = TIMESERIES(c(res_p_g),
START=c(2005,2),FREQ=4),
int_g_adj = TIMESERIES(c(int_g_adj),
START=c(2005,3),FREQ=4),
ins_g_adj = TIMESERIES(c(ins_g_adj),
START=c(2005,3),FREQ=4),
oth_g = TIMESERIES(c(oth_g),
START=c(2005,2),FREQ=4),
tax_row = TIMESERIES(c(tax_row),
START=c(2005,2),FREQ=4),
ctr_g = TIMESERIES(c(ctr_g),
START=c(2005,2),FREQ=4),
iba_g_rvx = TIMESERIES(c(iba_g_rvx),
START=c(2005,3),FREQ=4),
eq_g_tr = TIMESERIES(c(eq_g_tr),
START=c(2005,2),FREQ=4),
eq_g_rvx = TIMESERIES(c(eq_g_rvx),
START=c(2005,3),FREQ=4),
eq_g_nf_tr = TIMESERIES(c(eq_g_nf_tr),
START=c(2005,2),FREQ=4),
eq_g_f_tr = TIMESERIES(c(eq_g_f_tr),
START=c(2005,2),FREQ=4),
eq_g_f_rv = TIMESERIES(c(eq_g_f_rv),
START=c(2005,2),FREQ=4),
eq_g_row_tr = TIMESERIES(c(eq_g_row_tr),
START=c(2005,2),FREQ=4),
eq_g_row_rv = TIMESERIES(c(eq_g_row_rv),
START=c(2005,2),FREQ=4),
sec_g_rvx = TIMESERIES(c(sec_g_rvx),
START=c(2005,3),FREQ=4),
nl_g_adj = TIMESERIES(c(nl_g_adj),
START=c(2005,2),FREQ=4),
l_g_tr = TIMESERIES(c(l_g_tr),
START=c(2005,2),FREQ=4),
eq_g_tr = TIMESERIES(c(eq_g_tr),
START=c(2005,2),FREQ=4),
ins_g_tr = TIMESERIES(c(ins_g_tr),
START=c(2005,2),FREQ=4),
l_g_rvx = TIMESERIES(c(l_g_rvx),
START=c(2005,3),FREQ=4),
ins_g_rvx = TIMESERIES(c(ins_g_rvx),
START=c(2005,3),FREQ=4),
delta_bd_g = TIMESERIES(c(delta_bd_g),
START=c(2005,2),FREQ=4),
i_equip_g_k = TIMESERIES(c(i_equip_g_k),
START=c(2005,2),FREQ=4),
delta_equip_g = TIMESERIES(c(delta_equip_g),
START=c(2005,2),FREQ=4),
delta_bd_g = TIMESERIES(c(delta_bd_g),
START=c(2005,2),FREQ=4),
div_row_adj = TIMESERIES(c(div_row_adj),
START=c(2005,3),FREQ=4),
int_r_row = TIMESERIES(c(int_r_row),
START=c(2005,2),FREQ=4),
div_r_row = TIMESERIES(c(div_r_row),
START=c(2005,2),FREQ=4),
ins_r_row = TIMESERIES(c(ins_r_row),
START=c(2005,2),FREQ=4),
res_r_row = TIMESERIES(c(res_r_row),
START=c(2005,2),FREQ=4),
int_p_row = TIMESERIES(c(int_p_row),
START=c(2005,2),FREQ=4),
div_p_row = TIMESERIES(c(div_p_row),
START=c(2005,2),FREQ=4),
ins_p_row = TIMESERIES(c(ins_p_row),
START=c(2005,2),FREQ=4),
res_p_row = TIMESERIES(c(res_p_row),
START=c(2005,2),FREQ=4),
int_row_adj = TIMESERIES(c(int_row_adj),
START=c(2005,3),FREQ=4),
ins_row_adj = TIMESERIES(c(ins_row_adj),
START=c(2005,3),FREQ=4),
oth_row = TIMESERIES(c(oth_row),
START=c(2005,2),FREQ=4),
ctr_row = TIMESERIES(c(ctr_row),
START=c(2005,2),FREQ=4),
np_row = TIMESERIES(c(np_row),
START=c(2005,2),FREQ=4),
scon_row_r = TIMESERIES(c(scon_row_r),
START=c(2005,2),FREQ=4),
scon_row_p = TIMESERIES(c(scon_row_p),
START=c(2005,2),FREQ=4),
sben_row_r = TIMESERIES(c(sben_row_r),
START=c(2005,2),FREQ=4),
sben_row_p = TIMESERIES(c(sben_row_p),
START=c(2005,2),FREQ=4),
iba_row_rvx = TIMESERIES(c(iba_row_rvx),
START=c(2005,3),FREQ=4),
nl_row_adj = TIMESERIES(c(nl_row_adj),
START=c(2005,3),FREQ=4),
l_row_tr = TIMESERIES(c(l_row_tr),
START=c(2005,2),FREQ=4),
ins_row_tr = TIMESERIES(c(ins_row_tr),
START=c(2005,2),FREQ=4),
sec_row_rvx = TIMESERIES(c(sec_row_rvx),
START=c(2005,3),FREQ=4),
l_row_tr = TIMESERIES(c(l_row_tr),
START=c(2005,2),FREQ=4),
l_row_rvx = TIMESERIES(c(l_row_rvx),
START=c(2005,3),FREQ=4),
eq_row_a_tr = TIMESERIES(c(eq_row_a_tr),
START=c(2005,2),FREQ=4),
eq_row_a_rvx = TIMESERIES(c(eq_row_a_rvx),
START=c(2005,3),FREQ=4),
eq_row_a_nf_rv = TIMESERIES(c(eq_row_a_nf_rv),
START=c(2005,2),FREQ=4),
eq_row_a_nf_tr = TIMESERIES(c(eq_row_a_nf_tr),
START=c(2005,2),FREQ=4),
eq_row_a_f_tr = TIMESERIES(c(eq_row_a_f_tr),
START=c(2005,2),FREQ=4),
eq_row_a_f_rv = TIMESERIES(c(eq_row_a_f_rv),
START=c(2005,2),FREQ=4),
eq_row_l_tr = TIMESERIES(c(eq_row_l_tr),
START=c(2005,2),FREQ=4),
eq_row_l_rvx = TIMESERIES(c(eq_row_l_rvx),
START=c(2005,3),FREQ=4),
neq_row_rvx = TIMESERIES(c(Neq_row_rvx),
START=c(2005,3),FREQ=4),
ins_row_tr = TIMESERIES(c(ins_row_tr),
START=c(2005,2),FREQ=4),
ins_row_rvx = TIMESERIES(c(ins_row_rvx),
START=c(2005,3),FREQ=4),
empadj = TIMESERIES(c(empadj),
START=c(2005,2),FREQ=4),
part = TIMESERIES(c(part),
START=c(2005,2),FREQ=4),
pop = TIMESERIES(c(pop),
START=c(2005,2),FREQ=4),
urs = TIMESERIES(c(urs),
START=c(2005,2),FREQ=4),
wage_2010q3 = TIMESERIES(c(wage_2010q3),
START=c(2005,2),FREQ=4),
neq_nf_rvx = TIMESERIES(c(Neq_nf_rvx),
START=c(2005,3),FREQ=4),
eq_h_f_rvx = TIMESERIES(c(eq_h_f_rvx),
START=c(2005,3),FREQ=4),
g = TIMESERIES(c(g),
START=c(2005,2),FREQ=4),
pg = TIMESERIES(c(pg),
START=c(2005,2),FREQ=4),
px = TIMESERIES(c(px),
START=c(2005,2),FREQ=4),
pf = TIMESERIES(c(pf),
START=c(2005,2),FREQ=4),
p_expect = TIMESERIES(c(p_expect),
START=c(2005,2),FREQ=4),
pm = TIMESERIES(c(pm),
START=c(2005,2),FREQ=4),
div_nf_adj = TIMESERIES(c(div_nf_adj),
START=c(2005,3),FREQ=4),
ins_nf_adj = TIMESERIES(c(ins_nf_adj),
START=c(2005,3),FREQ=4),
res_p_nf = TIMESERIES(c(res_p_nf),
START=c(2005,2),FREQ=4),
res_r_nf = TIMESERIES(c(res_r_nf),
START=c(2005,2),FREQ=4),
int_r_f = TIMESERIES(c(int_r_f),
START=c(2005,2),FREQ=4),
np_f = TIMESERIES(c(np_f),
START=c(2005,2),FREQ=4),
np_g = TIMESERIES(c(np_g),
START=c(2005,2),FREQ=4),
eq_g_nf_rv = TIMESERIES(c(eq_g_nf_rv),
START=c(2005,2),FREQ=4),
prodk = TIMESERIES(c(prodk),
START=c(2005,2),FREQ=4),
### Checks
nl_check = TIMESERIES(c(nl_check),
START=c(2005,3),FREQ=4),
fnl_check = TIMESERIES(c(fnl_check),
START=c(2005,3),FREQ=4),
check_np = TIMESERIES(c(check_np),
START=c(2005,2),FREQ=4),
check_ctr = TIMESERIES(c(check_ctr),
START=c(2005,2),FREQ=4),
check_invest = TIMESERIES(c(check_invest ),
START=c(2005,2),FREQ=4),
check_iba = TIMESERIES(c(check_iba ),
START=c(2005,2),FREQ=4),
check_tax = TIMESERIES(c(check_tax ),
START=c(2005,2),FREQ=4),
check_iba_rv = TIMESERIES(c(check_iba_rv ),
START=c(2005,2),FREQ=4),
check_iba_tr = TIMESERIES(c(check_iba_tr ),
START=c(2005,2),FREQ=4),
check_eq = TIMESERIES(c(check_eq ),
START=c(2005,2),FREQ=4),
check_eq_tr = TIMESERIES(c(check_eq_tr ),
START=c(2005,3),FREQ=4),
check_div = TIMESERIES(c(check_div ),
START=c(2005,3),FREQ=4),
check_l = TIMESERIES(c(check_l ),
START=c(2005,2),FREQ=4),
check_l_tr = TIMESERIES(c(check_l_tr ),
START=c(2005,2),FREQ=4),
check_ins = TIMESERIES(c(check_ins ),
START=c(2005,2),FREQ=4),
check_ins_tr = TIMESERIES(c(check_ins_tr ),
START=c(2005,2),FREQ=4),
check_sec = TIMESERIES(c(check_sec ),
START=c(2005,2),FREQ=4),
fnl_f = TIMESERIES(c(fnl_f ),
START=c(2005,2),FREQ=4),
fnl_nf = TIMESERIES(c(fnl_nf ),
START=c(2005,3),FREQ=4),
fnl_g = TIMESERIES(c(fnl_g ),
START=c(2005,2),FREQ=4),
fnl_row = TIMESERIES(c(fnl_row),
START=c(2005,3),FREQ=4),
iba_h_rv = TIMESERIES(c(iba_h_rv),
START=c(2005,2),FREQ=4),
iba_f_rv = TIMESERIES(c(iba_f_rv ),
START=c(2005,2),FREQ=4),
iba_nf_rv = TIMESERIES(c(iba_nf_rv ),
START=c(2005,2),FREQ=4),
iba_g_rv = TIMESERIES(c(iba_g_rv ),
START=c(2005,2),FREQ=4),
iba_row_rv = TIMESERIES(c(iba_row_rv ),
START=c(2005,2),FREQ=4),
fnl_h = TIMESERIES(c(fnl_h ),
START=c(2005,3),FREQ=4),
eq_h_ratio = TIMESERIES(c(eq_h_ratio ),
START=c(2005,3),FREQ=4),
ratio_in_eq_h = TIMESERIES(c(ratio_in_eq_h ),
START=c(2005,3),FREQ=4),
## Test
tax_rate1_shock = TIMESERIES(c(tax_rate1_shock ),
START=c(2005,2),FREQ=4),
shock_1_model = TIMESERIES(c(shock_1_model ),
START=c(2005,2),FREQ=4),
shock_2_model = TIMESERIES(c(shock_2_model ),
START=c(2005,2),FREQ=4),
shock_3_model = TIMESERIES(c(shock_3_model ),
START=c(2005,2),FREQ=4),
shock_4_model = TIMESERIES(c(shock_4_model ),
START=c(2005,2),FREQ=4),
alpha_200 = TIMESERIES(c(alpha_200),
START=c(2005,2),FREQ=4),
alpha_201 = TIMESERIES(c(alpha_201),
START=c(2005,2),FREQ=4),
alpha_202 = TIMESERIES(c(alpha_202),
START=c(2005,2),FREQ=4),
alpha_203 = TIMESERIES(c(alpha_203),
START=c(2005,2),FREQ=4),
mean_pm = TIMESERIES(c(mean_pm),
START=c(2005,2),FREQ=4)
)S_model=LOAD_MODEL_DATA(S_model,S_modelData)## Load model data "S_modelData" into model "S_model.txt"...
## ...LOAD MODEL DATA OKEstimations
#Estimate model coefficients
S_model=ESTIMATE(S_model
,TSRANGE=c(2006,3,2020,1)
)##
## Estimate the Model S_model.txt:
## the number of behavioral equations to be estimated is 13.
## The total number of coefficients is 123.
##
## _________________________________________
##
## BEHAVIORAL EQUATION: pconk_ds
## Estimation Technique: OLS
##
## TSDELTALOG(pconk_ds)= - 0.2199022 TSLAG(LOG(pconk_ds),1)
## T-stat. -3.270457 **
##
## + 0.1622918 TSLAG(LOG(yd1_hk_ds),1)
## T-stat. 2.778486 **
##
## + 0.008527938 LOG(TSLAG(yd2a_hk_ds,1)+TSLAG(yd2b_hk,1))
## T-stat. 0.529185
##
## + 0.04593879 TSLAG(LOG(fnw_hk),2)
## T-stat. 3.212245 **
##
## - 0.3998632 TSDELTALOG(TSLAG(pconk_ds,2))
## T-stat. -3.658359 ***
##
## - 0.1930734 TSDELTALOG(TSLAG(pconk_ds,3))
## T-stat. -1.676231
##
## + 0.1326 TSDELTALOG(yd1_hk_ds)
## T-stat. 3.073788 **
##
## + 0.03893974 TSDELTALOG(yd2a_hk_ds+yd2b_hk)
## T-stat. 3.268536 **
##
## - 0.02171506 d_2008q4
## T-stat. -2.165614 *
##
## + 0.01765262 d_2018q2
## T-stat. 1.930952
##
## - 0.03933712 d_2020q1
## T-stat. -4.365152 ***
##
## - 0.0006488169time
## T-stat. -3.323956 **
##
##
## STATs:
## R-Squared : 0.6860189
## Adjusted R-Squared : 0.6003877
## Durbin-Watson Statistic : 2.600495
## Sum of squares of residuals : 0.003076613
## Standard Error of Regression : 0.008361998
## Log of the Likelihood Function : 195.1992
## F-statistic : 8.011318
## F-probability : 1.161298e-07
## Akaike's IC : -364.3984
## Schwarz's IC : -338.0689
## Mean of Dependent Variable : 0.001911903
## Number of Observations : 56
## Number of Degrees of Freedom : 44
## Current Sample (year-period) : 2006-2 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: i_bd_h_k_ds
## Estimation Technique: OLS
##
## LOG(i_bd_h_k_ds) = 0.383683
## T-stat. 1.081724
##
## - 0.3930929 TSDELTALOG(TSLAG(i_bd_h_k_ds,1)/TSLAG(bd_h_k,2))
## T-stat. -3.822694 ***
##
## - 0.414934 TSDELTALOG(TSLAG(i_bd_h_k_ds,3)/TSLAG(bd_h_k,4))
## T-stat. -4.136796 ***
##
## + 0.6021287 TSDELTALOG(TSLAG(p_bd,1)/TSLAG(pi_1,1))
## T-stat. 1.372137
##
## + 0.6690714 TSDELTALOG(TSLAG(p_bd,2)/TSLAG(pi_1,2))
## T-stat. 1.760343
##
## + 0.2135258 TSDELTALOG(TSLAG(yd_hk_ds,2)/TSLAG(bd_h_k,3))
## T-stat. 1.668792
##
## - 0.6750708 TSDELTALOG(TSLAG(-l_h,1)/TSLAG(bd_h,2))
## T-stat. -2.460299 *
##
## - 0.1608636 LOG(TSLAG(i_bd_h_k_ds,1)/TSLAG(bd_h_k,2))
## T-stat. -2.741878 **
##
## + 0.5081996 LOG(TSLAG(yd_hk_ds,1)/TSLAG(bd_h_k,2))
## T-stat. 3.954954 ***
##
## - 0.5774002 LOG(TSLAG(p_bd,1)/TSLAG(pi_1,1))
## T-stat. -1.292538
##
## - 0.313307 LOG(TSLAG(-l_h,1)/TSLAG(bd_h,2))
## T-stat. -2.2524 *
##
## - 0.05921963 d_2006q4
## T-stat. -1.59554
##
## + 0.09830508 d_2014q4
## T-stat. 3.017889 **
##
## + 1 LOG(TSLAG(bd_h_k,1))
## RESTRICT
##
## + 1 TSLAG(LOG(i_bd_h_k_ds),1)
## RESTRICT
##
## + 1 TSLAG(-LOG(bd_h_k),2)
## RESTRICT
##
## RESTRICTIONS:
## alpha_1=1
## alpha_2=1
## alpha_3=1
##
## RESTRICTIONS F-TEST:
## F-value :-12.99997
## F-prob(3,39) : 1
##
##
## STATs:
## R-Squared : 0.9685063
## Adjusted R-Squared : 0.9595081
## Durbin-Watson Statistic : 2.233769
## Sum of squares of residuals : 0.03757224
## Standard Error of Regression : 0.02990948
## Log of the Likelihood Function : 122.401
## F-statistic : 107.6334
## F-probability : 0
## Akaike's IC : -216.802
## Schwarz's IC : -188.6994
## Mean of Dependent Variable : 9.822329
## Number of Observations : 55
## Number of Degrees of Freedom : 42
## Current Sample (year-period) : 2006-3 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: nben_h
## Estimation Technique: OLS
##
## TSDELTALOG(nben_h)= - 28.18008
## T-stat. -6.541415 ***
##
## + 1.652034 TSDELTALOG(zaland_jesper)
## T-stat. 4.09111 ***
##
## + 0.001781876 TSDELTA(unemp)
## T-stat. 8.204793 ***
##
## + 0.0005047051TSDELTA(TSLAG(unemp,1))
## T-stat. 2.097979 *
##
## - 0.7715639 LOG(TSLAG(nben_h,1))
## T-stat. -6.466408 ***
##
## + 0.0004266324TSLAG(unemp,1)
## T-stat. 3.499584 ***
##
## + 2.479639 LOG(TSLAG(zaland_jesper,1))
## T-stat. 6.583079 ***
##
##
## STATs:
## R-Squared : 0.7507552
## Adjusted R-Squared : 0.7214323
## Durbin-Watson Statistic : 1.775083
## Sum of squares of residuals : 0.03128254
## Standard Error of Regression : 0.02476657
## Log of the Likelihood Function : 135.9306
## F-statistic : 25.60302
## F-probability : 8.65974e-14
## Akaike's IC : -255.8611
## Schwarz's IC : -239.3776
## Mean of Dependent Variable : 0.008585268
## Number of Observations : 58
## Number of Degrees of Freedom : 51
## Current Sample (year-period) : 2005-4 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: l_h_tr_ratio
## Estimation Technique: OLS
##
## TSDELTA(l_h_tr_ratio)= 1.269338
## T-stat. 2.907892 **
##
## + 0.1309973 TSDELTA(TSLAG(l_h_tr_ratio,2))
## T-stat. 1.458615
##
## - 26.23222 TSDELTA(iloan)
## T-stat. -1.906892
##
## + 0.2642999 TSDELTALOG(TSLAG(i_bd_h_k_ds,3)/TSLAG(yd_hk_ds,3))
## T-stat. 2.084077 *
##
## - 0.7210749 TSLAG(l_h_tr_ratio,1)
## T-stat. -6.170257 ***
##
## - 0.4870384 LOG(TSLAG(-l_h,2)/(TSLAG(yd_hk_ds,2)*TSLAG(pc,2)))
## T-stat. -2.783487 **
##
## + 0.1758334 d_2007q34
## T-stat. 4.384873 ***
##
## - 0.003050333 time
## T-stat. -3.293581 **
##
##
## STATs:
## R-Squared : 0.6230497
## Adjusted R-Squared : 0.5680778
## Durbin-Watson Statistic : 2.211288
## Sum of squares of residuals : 0.1350194
## Standard Error of Regression : 0.05303681
## Log of the Likelihood Function : 89.31472
## F-statistic : 11.33396
## F-probability : 2.231096e-08
## Akaike's IC : -160.6294
## Schwarz's IC : -142.4013
## Mean of Dependent Variable : -0.006328667
## Number of Observations : 56
## Number of Degrees of Freedom : 48
## Current Sample (year-period) : 2006-2 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: eq_h_ratio
## Estimation Technique: OLS
##
## TSDELTA(eq_h_ratio) = 0.07073023
## T-stat. 3.835776 ***
##
## + 6.847554 TSDELTA(TSLAG(ibd,1))
## T-stat. 3.188338 **
##
## + 0.1632282 TSDELTA(TSLAG(ratio_in_eq_h,1))
## T-stat. 8.194419 ***
##
## - 0.09771638 TSLAG(eq_h_ratio,1)
## T-stat. -3.747154 ***
##
## - 2.143093 TSLAG(ibd,1)
## T-stat. -3.90913 ***
##
## + 0.1593011 TSLAG(ratio_in_eq_h,2)
## T-stat. 6.106703 ***
##
##
## STATs:
## R-Squared : 0.7425515
## Adjusted R-Squared : 0.7173115
## Durbin-Watson Statistic : 2.195081
## Sum of squares of residuals : 0.003676245
## Standard Error of Regression : 0.008490185
## Log of the Likelihood Function : 194.1146
## F-statistic : 29.41958
## F-probability : 6.37268e-14
## Akaike's IC : -374.2291
## Schwarz's IC : -359.9278
## Mean of Dependent Variable : 0.003354189
## Number of Observations : 57
## Number of Degrees of Freedom : 51
## Current Sample (year-period) : 2006-1 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: d8_h
## Estimation Technique: OLS
##
## TSDELTALOG(d8_h) = 0.09283815 TSDELTALOG(TSLAG(d8_h,1))
## T-stat. 0.7795912
##
## + 0.2691943 TSDELTALOG(w_h_r)
## T-stat. 0.2989312
##
## - 46.16681 TSDELTALOG(TSLAG(old_age_ratio,1))
## T-stat. -2.090658 *
##
## - 0.6093494 LOG(TSLAG(d8_h,1))
## T-stat. -5.252142 ***
##
## + 0.3638694 LOG(TSLAG(w_h_r,1))
## T-stat. 4.036461 ***
##
## - 0.9542551 LOG(TSLAG(old_age_ratio,1))
## T-stat. -2.463546 *
##
## - 0.9574316 d_2014q3
## T-stat. -3.427795 **
##
##
## STATs:
## R-Squared : 0.4313099
## Adjusted R-Squared : 0.3532544
## Durbin-Watson Statistic : 2.398285
## Sum of squares of residuals : 3.380858
## Standard Error of Regression : 0.257471
## Log of the Likelihood Function : 0.1286532
## F-statistic : 5.525682
## F-probability : 9.062724e-05
## Akaike's IC : 15.74269
## Schwarz's IC : 32.22624
## Mean of Dependent Variable : 0.009375461
## Number of Observations : 58
## Number of Degrees of Freedom : 51
## Current Sample (year-period) : 2005-4 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: xk_ds
## Estimation Technique: OLS
##
## TSDELTALOG(xk_ds) = 1.30476 TSDELTALOG(TSLAG(gdp_tp,4))
## T-stat. 2.608957 *
##
## - 0.6306058 TSDELTALOG(rer)
## T-stat. -2.352001 *
##
## - 0.6194444 LOG(TSLAG(xk_ds,1))
## T-stat. -5.527303 ***
##
## + 0.6152416 LOG(TSLAG(gdp_tp,1))
## T-stat. 5.307337 ***
##
## - 0.2496434 LOG(TSLAG(rer,2))
## T-stat. -1.580101
##
## + 0.0564434 d_2008q2
## T-stat. 2.872868 **
##
## - 0.01825776 d_2018q1
## T-stat. -0.9323064
##
## + 0.03442057 d_2019q3
## T-stat. 1.633706
##
## - 0.001642554 time
## T-stat. -2.314362 *
##
##
## STATs:
## R-Squared : 0.5167788
## Adjusted R-Squared : 0.4222355
## Durbin-Watson Statistic : 1.902675
## Sum of squares of residuals : 0.01643957
## Standard Error of Regression : 0.01890455
## Log of the Likelihood Function : 145.1318
## F-statistic : 5.466055
## F-probability : 4.302328e-05
## Akaike's IC : -270.2636
## Schwarz's IC : -250.1903
## Mean of Dependent Variable : 0.005666025
## Number of Observations : 55
## Number of Degrees of Freedom : 46
## Current Sample (year-period) : 2006-3 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: mk_ds
## Estimation Technique: OLS
##
## TSDELTALOG(mk_ds) = - 3.755903
## T-stat. -2.819303 **
##
## - 0.1269196 TSDELTALOG(TSLAG(mk_ds,2))
## T-stat. -1.445772
##
## + 0.2812692 TSDELTALOG(TSLAG(rer,1))
## T-stat. 1.149754
##
## + 0.3837578 TSDELTALOG(TSLAG(rer,3))
## T-stat. 1.44147
##
## + 1.222592 TSDELTALOG(yk_ds)
## T-stat. 5.407395 ***
##
## - 0.3016465 LOG(TSLAG(mk_ds,1))
## T-stat. -3.803362 ***
##
## + 0.5724419 LOG(TSLAG(yk_ds,1))
## T-stat. 3.345498 **
##
## - 0.07882542 d_2009q1
## T-stat. -3.789917 ***
##
## - 0.0697917 d_2009q4
## T-stat. -3.236259 **
##
##
## STATs:
## R-Squared : 0.6625684
## Adjusted R-Squared : 0.6051332
## Durbin-Watson Statistic : 2.53092
## Sum of squares of residuals : 0.01725372
## Standard Error of Regression : 0.01915987
## Log of the Likelihood Function : 146.9217
## F-statistic : 11.53594
## F-probability : 6.985006e-09
## Akaike's IC : -273.8433
## Schwarz's IC : -253.5898
## Mean of Dependent Variable : 0.006829911
## Number of Observations : 56
## Number of Degrees of Freedom : 47
## Current Sample (year-period) : 2006-2 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: i_bd_nfc_k_ds
## Estimation Technique: OLS
##
## LOG(i_bd_nfc_k_ds) = 0.4243644
## T-stat. 1.832432
##
## - 0.4454137 TSDELTALOG(TSLAG(i_bd_nfc_k_ds,1)/TSLAG(bd_nfc_k,2))
## T-stat. -4.412219 ***
##
## - 0.1430804 TSDELTALOG(ps_ds)
## T-stat. -0.6151961
##
## + 1.279077 TSDELTALOG(u_ds)
## T-stat. 2.907603 **
##
## - 0.3345672 LOG(TSLAG(i_bd_nfc_k_ds,1)/TSLAG(bd_nfc_k,2))
## T-stat. -3.565137 ***
##
## + 0.4505228 LOG(TSLAG(ps_ds,1))
## T-stat. 2.345067 *
##
## + 0.8712331 LOG(TSLAG(u_ds,1))
## T-stat. 3.359947 **
##
## - 0.01286328 TSDELTALOG(tobinq)
## T-stat. -0.1833376
##
## + 0.07161845 LOG(TSLAG(tobinq,1))
## T-stat. 2.108168 *
##
## + 1 TSLAG(LOG(i_bd_nfc_k_ds),1)
## RESTRICT
##
## + 1 TSLAG(LOG(bd_nfc_k),1)
## RESTRICT
##
## + 1 TSLAG(-LOG(bd_nfc_k),2)
## RESTRICT
##
## RESTRICTIONS:
## alpha_1=1
## alpha_2=1
## alpha_3=1
##
## RESTRICTIONS F-TEST:
## F-value :-14.99679
## F-prob(3,45) : 1
##
##
## STATs:
## R-Squared : 0.947658
## Adjusted R-Squared : 0.9389344
## Durbin-Watson Statistic : 2.041605
## Sum of squares of residuals : 0.04445203
## Standard Error of Regression : 0.03043163
## Log of the Likelihood Function : 123.0778
## F-statistic : 108.6308
## F-probability : 0
## Akaike's IC : -226.1556
## Schwarz's IC : -205.7251
## Mean of Dependent Variable : 9.809868
## Number of Observations : 57
## Number of Degrees of Freedom : 48
## Current Sample (year-period) : 2006-1 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: i_equip_nfc_k_ds
## Estimation Technique: OLS
##
## LOG(i_equip_nfc_k_ds)= - 0.07591725
## T-stat. -0.2741074
##
## - 0.185652 TSDELTALOG(TSLAG(i_equip_nfc_k_ds,1)/TSLAG(equip_nfc_k,2))
## T-stat. -2.126976 *
##
## - 0.4121769 LOG(TSLAG(i_equip_nfc_k_ds,1)/TSLAG(equip_nfc_k,2))
## T-stat. -4.593342 ***
##
## + 0.4470917 LOG(TSLAG(ps_ds,1))
## T-stat. 2.405399 *
##
## + 0.4533458 LOG(TSLAG(u_ds,1))
## T-stat. 3.21101 **
##
## + 0.1826936 dummy_10
## T-stat. 6.365303 ***
##
## - 0.1328606 dummy_11
## T-stat. -5.96053 ***
##
## - 0.2269816 TSDELTALOG(tobinq)
## T-stat. -2.811841 **
##
## + 0.06576628 LOG(TSLAG(tobinq,1))
## T-stat. 2.12006 *
##
## + 1 TSLAG(LOG(i_equip_nfc_k_ds),1)
## RESTRICT
##
## + 1 TSLAG(LOG(equip_nfc_k),1)
## RESTRICT
##
## + 1 TSLAG(-LOG(equip_nfc_k),2)
## RESTRICT
##
## RESTRICTIONS:
## alpha_1=1
## alpha_2=1
## alpha_3=1
##
## RESTRICTIONS F-TEST:
## F-value :-14.96284
## F-prob(3,45) : 1
##
##
## STATs:
## R-Squared : 0.9351597
## Adjusted R-Squared : 0.924353
## Durbin-Watson Statistic : 2.144885
## Sum of squares of residuals : 0.05944281
## Standard Error of Regression : 0.03519079
## Log of the Likelihood Function : 114.7956
## F-statistic : 86.53511
## F-probability : 0
## Akaike's IC : -209.5911
## Schwarz's IC : -189.1606
## Mean of Dependent Variable : 10.45856
## Number of Observations : 57
## Number of Degrees of Freedom : 48
## Current Sample (year-period) : 2006-1 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: pc_ds
## Estimation Technique: OLS
##
## TSDELTALOG(pc_ds) = - 0.1872875 TSDELTALOG(TSLAG(pc_ds,1))
## T-stat. -2.789388 **
##
## - 0.2897875 TSDELTALOG(TSLAG(pc_ds,2))
## T-stat. -4.030243 ***
##
## - 0.08280849 TSDELTALOG(TSLAG(pc_ds,3))
## T-stat. -1.151158
##
## + 0.4111479 TSDELTALOG(TSLAG(pc_ds,4))
## T-stat. 5.019137 ***
##
## + 0.03813072 TSDELTALOG(wage_ds)
## T-stat. 1.072996
##
## + 0.1343751 TSDELTALOG(pm_ds)
## T-stat. 6.565967 ***
##
## + 0.0565461 TSDELTALOG(TSLAG(pm_ds,2))
## T-stat. 2.408652 *
##
## - 0.04302053 LOG(TSLAG(pc_ds,1))
## T-stat. -2.829793 **
##
## + 0.09249241 LOG(TSLAG(wage_ds,1))
## T-stat. 3.395095 **
##
## - 0.07906866 LOG(TSLAG(prod_ds,1))
## T-stat. -3.347823 **
##
## + 0.03653276 LOG(TSLAG(pm_ds,1))
## T-stat. 1.910868
##
## - 0.01005443 d_2007q3
## T-stat. -3.639143 ***
##
## + 0.005365535 d_2017q23
## T-stat. 2.789396 **
##
## - 0.006740126 d_2018q1
## T-stat. -2.498762 *
##
## + 0.009059267 d_2011q2
## T-stat. 3.432093 **
##
## - 0.006780253 d_2013q1
## T-stat. -2.532523 *
##
## - 1.646395e-07(yk_ds_potential-(pconk_ds+ik+gk))
## T-stat. -2.982922 **
##
##
## STATs:
## R-Squared : 0.9292055
## Adjusted R-Squared : 0.8975343
## Durbin-Watson Statistic : 2.032551
## Sum of squares of residuals : 0.0002210589
## Standard Error of Regression : 0.002411916
## Log of the Likelihood Function : 263.6298
## F-statistic : 29.3391
## F-probability : 1.110223e-16
## Akaike's IC : -491.2596
## Schwarz's IC : -455.1276
## Mean of Dependent Variable : 0.003255037
## Number of Observations : 55
## Number of Degrees of Freedom : 38
## Current Sample (year-period) : 2006-3 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: emp
## Estimation Technique: OLS
##
## emp = 0.9887852 (yk/prodk)
## T-stat. 3584.811 ***
##
##
## STATs:
## R-Squared : 0.9999958
## Adjusted R-Squared : 0.9999957
## Durbin-Watson Statistic : 0.3914249
## Sum of squares of residuals : 1702.921
## Standard Error of Regression : 5.615189
## Log of the Likelihood Function : -172.4427
## F-statistic : 1.284874e+07
## F-probability : 0
## Akaike's IC : 348.8854
## Schwarz's IC : 352.9001
## Mean of Dependent Variable : 2713.4
## Number of Observations : 55
## Number of Degrees of Freedom : 54
## Current Sample (year-period) : 2006-3 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
##
## _________________________________________
##
## BEHAVIORAL EQUATION: wage_ds
## Estimation Technique: OLS
##
## TSDELTALOG(wage_ds) = 0.01046746
## T-stat. 0.18909
##
## - 0.3317065 TSDELTA(TSLAG(ur,4))
## T-stat. -1.884692
##
## + 0.625003 TSDELTALOG(prod_ds)
## T-stat. 8.464003 ***
##
## - 0.4735599 LOG(TSLAG(wage_ds,1))
## T-stat. -5.028026 ***
##
## + 0.1801716 LOG(TSLAG(wage_ds_t,1))
## T-stat. 3.021517 **
##
## + 0.2547773 LOG(TSLAG(prod_ds,1))
## T-stat. 4.253603 ***
##
## + 0.01926087 (d_2009q1+d_2009q2)
## T-stat. 3.105556 **
##
##
## STATs:
## R-Squared : 0.7712423
## Adjusted R-Squared : 0.7426476
## Durbin-Watson Statistic : 2.107484
## Sum of squares of residuals : 0.002371733
## Standard Error of Regression : 0.007029304
## Log of the Likelihood Function : 198.3737
## F-statistic : 26.97151
## F-probability : 8.348877e-14
## Akaike's IC : -380.7475
## Schwarz's IC : -364.6888
## Mean of Dependent Variable : 0.005914766
## Number of Observations : 55
## Number of Degrees of Freedom : 48
## Current Sample (year-period) : 2006-3 / 2020-1
##
##
## Signif. codes: *** 0.001 ** 0.01 * 0.05
##
##
## ...ESTIMATE OKBaseline Simulations
# In-sample prediction (no add factors)
S_model <- SIMULATE(S_model
,simType='DYNAMIC'
,TSRANGE=c(2006,3,2020,1)
,simConvergence=0.00001
,simIterLimit=100
)Shocks
Scenario 1 (without MP)
shock_1_model_shock = shock_1_model %>% window(start= c(2014,2))constantAdjList <- list(
shock_1_model = TIMESERIES(shock_1_model_shock+1 ,START=c(2014,2), FREQ='Q')
)# Simulate the model (following shock)
Shock_1 <- SIMULATE(S_model
,simType='DYNAMIC'
,TSRANGE=c(2006,3,2020,1)
,simConvergence=0.00001
,simIterLimit=100
,ConstantAdjustment=constantAdjList
)Scenario 1 (with MP)
shock_2_model_shock=shock_2_model %>% window(start= c(2014,4))# Define add-factor list (defining shock)
constantAdjList <- list(
shock_1_model = TIMESERIES(shock_1_model_shock+1 ,START=c(2014,2), FREQ='Q'),
shock_2_model = TIMESERIES(shock_2_model_shock+1 ,START=c(2014,4), FREQ='Q')
)# Simulate the model (following shock)
Shock_2 <- SIMULATE(S_model
,simType='DYNAMIC'
,TSRANGE=c(2006,3,2020,1)
,simConvergence=0.00001
,simIterLimit=100
,ConstantAdjustment=constantAdjList
)Secnario 2a (Discretionary fiscal policy - only lower labour income tax)
shock_3_model_shock = shock_3_model %>% window(start= c(2014,4))# Define add-factor list (defining shock)
constantAdjList <- list(
shock_1_model = TIMESERIES(shock_1_model_shock+1 ,START=c(2014,2), FREQ='Q'),
shock_2_model = TIMESERIES(shock_2_model_shock+1 ,START=c(2014,4), FREQ='Q'),
shock_3_model = TIMESERIES(shock_3_model_shock+1 ,START=c(2014,4), FREQ='Q')
)# Simulate the model (following shock)
Shock_3 <- SIMULATE(S_model
,simType='DYNAMIC'
,TSRANGE=c(2006,3,2020,1)
,simConvergence=0.00001
,simIterLimit=100
,ConstantAdjustment=constantAdjList
)Scenario 2b (Discretionary fiscal policy - lower labour income tax + lower production taxes)
shock_4_model_shock = shock_4_model %>% window(start= c(2014,4))# Define add-factor list (defining shock)
constantAdjList <- list(
shock_1_model = TIMESERIES(shock_1_model_shock+1 ,START=c(2014,2), FREQ='Q'),
shock_2_model = TIMESERIES(shock_2_model_shock+1 ,START=c(2014,4), FREQ='Q'),
shock_3_model = TIMESERIES(shock_3_model_shock+1 ,START=c(2014,4), FREQ='Q'),
shock_4_model = TIMESERIES(shock_4_model_shock+1 ,START=c(2014,4), FREQ='Q')
)# Simulate the model (following shock)
Shock_4 <- SIMULATE(S_model
,simType='DYNAMIC'
,TSRANGE=c(2006,3,2020,1)
,simConvergence=0.00001
,simIterLimit=100
,ConstantAdjustment=constantAdjList
)Extract the key variable from the baseline and shocks
# Baseline
yk_ds_00 = S_model$simulation$yk_ds; yk_ds_0 <- window(yk_ds_00, start=c(2012,1), freq=4)
wage_ds_t_00 = S_model$simulation$wage_ds_t;
check_sec_00 = S_model$simulation$check_sec
check_eq_00 = S_model$simulation$check_eq
cab_00 = S_model$simulation$cab
fab_00 = S_model$simulation$fab
growth_00 = S_model$simulation$growth; growth_0 <- window(growth_00, start=c(2012,1), freq=4)
emp_00 = S_model$simulation$emp
wage_ds_00 = S_model$simulation$wage_ds
rw_ds_00=S_model$simulation$rw_ds; rw_ds_0 <- window(rw_ds_00, start=c(2012,1), freq=4)
ik_00 = S_model$simulation$ik; ik_0 <- window(ik_00, start=c(2012,1), freq=4)
i_bd_nfc_k_ds_00 = S_model$simulation$i_bd_nfc_k_ds
i_bd_h_k_ds_00 = S_model$simulation$i_bd_h_k_ds
i_equip_nfc_k_ds_00 = S_model$simulation$i_equip_nfc_k_ds
i_equip_h_k_ds_00 = S_model$simulation$i_equip_h_k_ds
pc_ds_00 = S_model$simulation$pc_ds; pc_ds_0 <- window(pc_ds_00, start=c(2012,1), freq=4)
yd_hk_ds_00 = S_model$simulation$yd_hk_ds
pconk_ds_00 = S_model$simulation$pconk_ds; pconk_ds_0 <- window(pconk_ds_00, start=c(2012,1), freq=4)
ur_ds_00 = S_model$simulation$ur_ds ; ur_ds_0 <- window(ur_ds_00, start=c(2012,1), freq=4)
tax_rate1_00 = S_model$simulation$tax_rate1
iloan_00 = S_model$simulation$iloan
iboa_00 = S_model$simulation$iboa
pm_ds_00 = S_model$simulation$pm_ds
yk_ds_potential_00 = S_model$simulation$yk_ds_potential
gdp_tp_00= S_model$simulation$gdp_tp
pf_00 = S_model$simulation$pf
p_expect_00 = S_model$simulation$p_expect
inflation_t_00= S_model$simulation$inflation_t
inflation_00= S_model$simulation$inflation; inflation_0 <- window(inflation_00, start=c(2012,1), freq=4)
rer_00= S_model$simulation$rer; rer_0 <- window(rer_00, start=c(2012,1), freq=4)
eq_h_00 = S_model$simulation$eq_h
l_h_00 = S_model$simulation$l_h
l_h_tr_00 = S_model$simulation$l_h_tr
xk_ds_00= S_model$simulation$xk_ds; xk_ds_0 <- window(xk_ds_00, start=c(2012,1), freq=4)
mk_ds_00= S_model$simulation$mk_ds; mk_ds_0 <- window(mk_ds_00, start=c(2012,1), freq=4)
yd1_h_00 = S_model$simulation$yd1_h
nl_g_00 <- S_model$simulation$nl_g; nl_g_0 <- window(nl_g_00, start=c(2012,1), freq=4)
fnw_g_00 <- S_model$simulation$fnw_g; fnw_g_0 <- window(fnw_g_00, start=c(2012,1), freq=4)
fnw_h_00 <- S_model$simulation$fnw_h; fnw_h_0 <- window(fnw_h_00, start=c(2012,1), freq=4)
fnw_nf_00 <- S_model$simulation$fnw_nf; fnw_nf_0 <- window(fnw_nf_00, start=c(2012,1), freq=4)
fnw_f_00 <- S_model$simulation$fnw_f; fnw_f_0 <- window(fnw_f_00, start=c(2012,1), freq=4)
fnw_row_00 <- S_model$simulation$fnw_row; fnw_row_0 <- window(fnw_row_00, start=c(2012,1), freq=4)
y_00 <- S_model$simulation$y; y_0 <- window(y_00, start=c(2012,1), freq=4)
# Scenario 1 variables
yk_ds_01 = Shock_1$simulation$yk_ds; yk_ds_1 <- window(yk_ds_01, start=c(2012,1), freq=4)
wage_ds_t_01 = Shock_1$simulation$wage_ds_t;
growth_01 = Shock_1$simulation$growth; growth_1 <- window(growth_01, start=c(2012,1), freq=4)
y_01 = Shock_1$simulation$y; y_1 <- window(y_01, start=c(2012,1), freq=4)
emp_01 = Shock_1$simulation$emp
wage_ds_01 = Shock_1$simulation$wage_ds
rw_ds_01=Shock_1$simulation$rw_ds; rw_ds_1 <- window(rw_ds_01, start=c(2012,1), freq=4)
ur_ds_01 = Shock_1$simulation$ur_ds; ur_ds_1 <- window(ur_ds_01, start=c(2012,1), freq=4)
pc_ds_01 = Shock_1$simulation$pc_ds; pc_ds_1 <- window(pc_ds_01, start=c(2012,1), freq=4)
yd_hk_ds_01 = Shock_1$simulation$yd_hk_ds
pconk_ds_01 = Shock_1$simulation$pconk_ds; pconk_ds_1 <- window(pconk_ds_01, start=c(2012,1), freq=4)
ik_01 = Shock_1$simulation$ik ; ik_1 <- window(ik_01, start=c(2012,1), freq=4)
inflation_01 = Shock_1$simulation$inflation; inflation_1 <- window(inflation_01, start=c(2012,1), freq=4)
inflation_t_01= Shock_1$simulation$inflation_t
eq_h_01 = Shock_1$simulation$eq_h
l_h_01 = Shock_1$simulation$l_h
l_h_tr_01 = Shock_1$simulation$l_h_tr
rer_01= Shock_1$simulation$rer; rer_1 <- window(rer_01, start=c(2012,1), freq=4)
xk_ds_01= Shock_1$simulation$xk_ds ; xk_ds_1 <- window(xk_ds_01, start=c(2012,1), freq=4)
mk_ds_01= Shock_1$simulation$mk_ds; mk_ds_1 <- window(mk_ds_01, start=c(2012,1), freq=4)
i_bd_nfc_k_ds_01 = Shock_1$simulation$i_bd_nfc_k_ds
i_bd_h_k_ds_01 = Shock_1$simulation$i_bd_h_k_ds
i_equip_nfc_k_ds_01 = Shock_1$simulation$i_equip_nfc_k_ds
i_equip_h_k_ds_01 = Shock_1$simulation$i_equip_h_k_ds
nl_g_01 <- Shock_1$simulation$nl_g; nl_g_1 <- window(nl_g_01, start=c(2012,1), freq=4)
fnw_g_01 <- Shock_1$simulation$fnw_g; fnw_g_1 <- window(fnw_g_01, start=c(2012,1), freq=4)
# Scenario 1 + 2 variables
yk_ds_02 = Shock_2$simulation$yk_ds; yk_ds_2 <- window(yk_ds_02, start=c(2012,1), freq=4)
wage_ds_t_02 = Shock_2$simulation$wage_ds_t;
y_02 = Shock_2$simulation$y; y_2 <- window(y_02, start=c(2012,1), freq=4)
growth_02 = Shock_2$simulation$growth; growth_2 <- window(growth_02, start=c(2012,1), freq=4)
emp_02 = Shock_2$simulation$emp
rw_ds_02=Shock_2$simulation$rw_ds; rw_ds_2 <- window(rw_ds_02, start=c(2012,1), freq=4)
ik_02 = Shock_2$simulation$ik; ik_2 <- window(ik_02, start=c(2012,1), freq=4)
ur_ds_02 = Shock_2$simulation$ur_ds; ur_ds_2 <- window(ur_ds_02, start=c(2012,1), freq=4)
pc_ds_02 = Shock_2$simulation$pc_ds; pc_ds_2 <- window(pc_ds_02, start=c(2012,1), freq=4)
yd_hk_ds_02 = Shock_2$simulation$yd_hk_ds
pconk_ds_02 = Shock_2$simulation$pconk_ds; pconk_ds_2 <- window(pconk_ds_02, start=c(2012,1), freq=4)
inflation_02 = Shock_2$simulation$inflation; inflation_2 <- window(inflation_02, start=c(2012,1), freq=4)
inflation_t_02 = Shock_2$simulation$inflation_t
rer_02= Shock_2$simulation$rer
eq_h_02 = Shock_2$simulation$eq_h
l_h_02 = Shock_2$simulation$l_h
l_h_tr_02 = Shock_2$simulation$l_h_tr
xk_ds_02= Shock_2$simulation$xk_ds; xk_ds_2 <- window(xk_ds_02, start=c(2012,1), freq=4)
mk_ds_02= Shock_2$simulation$mk_ds; mk_ds_2 <- window(mk_ds_02, start=c(2012,1), freq=4)
i_bd_nfc_k_ds_02 = Shock_2$simulation$i_bd_nfc_k_ds
i_bd_h_k_ds_02 = Shock_2$simulation$i_bd_h_k_ds
i_equip_nfc_k_ds_02 = Shock_2$simulation$i_equip_nfc_k_ds
i_equip_h_k_ds_02 = Shock_2$simulation$i_equip_h_k_ds
nl_g_02 <- Shock_2$simulation$nl_g; nl_g_2 <- window(nl_g_02, start=c(2012,1), freq=4)
fnw_g_02 <- Shock_2$simulation$fnw_g; fnw_g_2 <- window(fnw_g_02, start=c(2012,1), freq=4)
# Scenraio 1 + 2 +3 variables
yk_ds_03 = Shock_3$simulation$yk_ds; yk_ds_3 <- window(yk_ds_03, start=c(2012,1), freq=4)
yk_ds_04 = Shock_4$simulation$yk_ds; yk_ds_4 <- window(yk_ds_04, start=c(2012,1), freq=4)
wage_ds_t_03 = Shock_3$simulation$wage_ds_t;
y_03 = Shock_3$simulation$y; y_3 <- window(y_03, start=c(2012,1), freq=4)
y_04 = Shock_4$simulation$y; y_4 <- window(y_04, start=c(2012,1), freq=4)
growth_03 = Shock_3$simulation$growth; growth_3 <- window(growth_03, start=c(2012,1), freq=4)
growth_04 = Shock_4$simulation$growth; growth_4 <- window(growth_04, start=c(2012,1), freq=4)
emp_03 = Shock_3$simulation$emp
rw_ds_03=Shock_3$simulation$rw_ds; rw_ds_3 <- window(rw_ds_03, start=c(2012,1), freq=4)
rw_ds_04=Shock_4$simulation$rw_ds; rw_ds_4 <- window(rw_ds_04, start=c(2012,1), freq=4)
ur_ds_03 = Shock_3$simulation$ur_ds; ur_ds_3 <- window(ur_ds_03, start=c(2012,1), freq=4)
ur_ds_04 = Shock_4$simulation$ur_ds; ur_ds_4 <- window(ur_ds_04, start=c(2012,1), freq=4)
pc_ds_03 = Shock_3$simulation$pc_ds; pc_ds_3 <- window(pc_ds_03, start=c(2012,1), freq=4)
pc_ds_04 = Shock_4$simulation$pc_ds; pc_ds_4 <- window(pc_ds_04, start=c(2012,1), freq=4)
yd_hk_ds_03 = Shock_3$simulation$yd_hk_ds
pconk_ds_03 = Shock_3$simulation$pconk_ds; pconk_ds_3 <- window(pconk_ds_03, start=c(2012,1), freq=4)
pconk_ds_04 = Shock_4$simulation$pconk_ds; pconk_ds_4 <- window(pconk_ds_04, start=c(2012,1), freq=4)
ik_03 = Shock_3$simulation$ik; ik_3 <- window(ik_03, start=c(2012,1), freq=4)
ik_04 = Shock_4$simulation$ik; ik_4 <- window(ik_04, start=c(2012,1), freq=4)
yd1_h_03 = Shock_3$simulation$yd1_h
yh1_03 = Shock_3$simulation$yh1
inflation_03 = Shock_3$simulation$inflation; inflation_3 <- window(inflation_03, start=c(2012,1), freq=4)
inflation_04 = Shock_4$simulation$inflation; inflation_4 <- window(inflation_04, start=c(2012,1), freq=4)
rer_03= Shock_3$simulation$rer
rer_04= Shock_4$simulation$rer
xk_ds_03= Shock_3$simulation$xk_ds; xk_ds_3 <- window(xk_ds_03, start=c(2012,1), freq=4)
xk_ds_04= Shock_4$simulation$xk_ds; xk_ds_4 <- window(xk_ds_04, start=c(2012,1), freq=4)
mk_ds_03 = Shock_3$simulation$mk_ds; mk_ds_3 <- window(mk_ds_03, start=c(2012,1), freq=4)
mk_ds_04 = Shock_4$simulation$mk_ds; mk_ds_4 <- window(mk_ds_04, start=c(2012,1), freq=4)
nl_g_03 <- Shock_3$simulation$nl_g; nl_g_3 <- window(nl_g_03, start=c(2012,1), freq=4)
nl_g_04 <- Shock_4$simulation$nl_g; nl_g_4 <- window(nl_g_04, start=c(2012,1), freq=4)
fnw_g_03 <- Shock_3$simulation$fnw_g; fnw_g_3 <- window(fnw_g_03, start=c(2012,1), freq=4)
fnw_g_04 <- Shock_4$simulation$fnw_g; fnw_g_4 <- window(fnw_g_04, start=c(2012,1), freq=4)
#Shocks
p_expect_01 = Shock_1$simulation$p_expect
yk_ds_potential_01 = Shock_1$simulation$yk_ds_potential
gdp_tp_01= Shock_1$simulation$gdp_tp
pf_01 = Shock_1$simulation$pf
pm_ds_01 = Shock_1$simulation$pm_ds
idep_02 = Shock_2$simulation$idep
ibd_02 = Shock_2$simulation$ibd
iboa_02 = Shock_2$simulation$iboa
iloan_02 = Shock_2$simulation$iloan
tax_rate1_03 = Shock_3$simulation$tax_rate1
p_tax_04 = Shock_4$simulation$p_taxPlots
Plot the shocks
options(scipen = 999)
plot(pm_ds_01 - pm_ds_00)
plot(idep_02 - idep, main="interest rate on deposits")
plot(iboa_02 - iboa, main="interest rate on foreign bonds")
plot(iloan_02- iloan, main="interest rate on loans")
Data vs Estimation
plot(yk_ds_00, col= "red", lwd=2, ylim=c(435000, 550000),ylab="Mil. of Kronas", xlab="", frame.plot = FALSE)
lines(yk_ds, col = "black", lwd=2, ylab="");
legend("topleft",legend=c("Baseline (Real GDP)", "Real data (Real GDP)"),lty=c(1,1),lwd=c(2,2),bty="n", col = c("red", "black"));
grid()
box(bty="l"); grid()
plot(pconk_ds_00, col= "cyan"); lines(pconk_ds, col = "black");
legend("top",legend=c("Baseline", "Real data"),lty=c(1,1),lwd=c(2),bty="n", col = c("cyan", "black"));
grid()
plot(ik_00, col= "cyan"); lines(ik, col = "black");
legend("top",legend=c("Baseline", "Real data"),lty=c(1,1),lwd=c(2),bty="n", col = c("cyan", "black"));
grid()
plot(xk_ds_00, col= "cyan"); lines(xk_ds, col = "black");
legend("top",legend=c("Baseline", "Real data"),lty=c(1,1),lwd=c(2),bty="n", col = c("cyan", "black"));
grid()
plot(mk_ds_00, col= "cyan"); lines(mk_ds, col = "black");
legend("top",legend=c("Baseline", "Real data"),lty=c(1,1),lwd=c(2),bty="n", col = c("cyan", "black"));
grid()
plot(emp_00, col= "red", lwd=2, ylim=c(2400, 3000), ylab="1000 of individuals", xlab="", frame.plot = FALSE);
lines(emp, col = "black", lwd=2);
legend("topleft",legend=c("Baseline (Employment)", "Real data (Employment)"),lty=c(1,1),lwd=c(2,2),bty="n", col = c("red", "black"));
box(bty="l"); grid()
plot(inflation_00*100, col= "red", lwd=2, ylim=c(-0.7, 6), ylab="Inflation rate", xlab="", frame.plot = FALSE);
lines(inflation*100, col = "black", lwd=2);
legend("topleft",legend=c("Baseline (Inflation)", "Real data (Inflation)"),lty=c(1,1),lwd=c(2,2),bty="n", col = c("red", "black"));
box(bty="l"); grid()
plot(pc_ds_00, col= "red", lwd=2, xlab="", ylab="CPI index", ylim=c(0.9, 1.15), frame.plot = FALSE)
lines(pc_ds, col = "black", lwd=2);
legend("topleft",legend=c("Baseline (CPI)", "Real data (CPI)"),lty=c(1,1),lwd=c(2,2),bty="n", col = c("red", "black"));
box(bty="l"); grid()
plot(wage_ds_00, col= "red", lwd=2, ylab="Wages per 1000 employees (Mil. of kronas)", xlab="", ylim=c(70,120), frame.plot = FALSE)
lines(wage_ds, col = "black", lwd=2);
legend("topleft",legend=c("Baseline (Nominal wage rate)", "Real data (Nominal wage rate)"),lty=c(1,1),lwd=c(2),bty="n", col = c("red", "black"));
box(bty="l"); grid()
plot(nl_g_00/y_00, col= "red", lwd=2); lines(nl_g/y, col = "black", lwd=2);
legend("top",legend=c("Baseline (Govt. net lending)", "Real data (Govt. net lending)"),lty=c(1,1),lwd=c(2),bty="n", col = c("red", "black"));
grid()
plot(fnw_g_00/y_00, col= "cyan"); lines(fnw_g/y, col = "black");
legend("top",legend=c("Baseline", "Real data"),lty=c(1,1),lwd=c(2),bty="n", col = c("cyan", "black"));
grid()
Plot scenario 1
plot( (yk_ds_1 - yk_ds_0)/yk_ds_0, col= "cyan", ylim=c(-0.17, 0.10), ylab="", xlab="", lwd=2, xaxt = "n", frame.plot = FALSE)
lines( (pconk_ds_1-pconk_ds_0)/pconk_ds_0, col="blue", lwd=2);
lines( (ik_1-ik_0)/ik_0, col="red", lwd=2);
lines( (xk_ds_1-xk_ds_0)/xk_ds_0, col="orange", lwd=2);
lines( (mk_ds_1-mk_ds_0)/mk_ds_0, col="black", lwd=2);
box(bty="l"); grid()
legend("bottomleft",
legend=c("GDP", "Consumption", "Investment", "Exports", "Imports"),
lty=c(1,1,1,1,1), lwd=c(2,2,2,2,2), bty="n",
col = c("cyan", "blue", "red", "orange", "black")
);
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.02, labels = lablist, pos = 1, xpd = TRUE)
plot( (ur_ds_1-ur_ds_0), xaxt = "n", col= "red", ylim=c(-0.03, 0.07), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(inflation_1 - inflation_0, col = "blue", lwd=2);
box(bty="l"); grid()
legend("topleft",legend=c("Unemployment rate", "Inflation"),lty=c(1,1),lwd=c(2),bty="n", col = c("red", "blue"));
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot( ur_ds_0, col= "red", xaxt = "n", ylim=c(0.025, 0.15), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(ur_ds_1, col = "blue", lwd=2);
box(bty="l"); grid()
legend("topleft",legend=c("Unemployment rate (baseline)", "Unemployment rate (Shock 1)"),lty=c(1,1),lwd=c(2),bty="n", col = c("red", "blue"));
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, srt = 45, pos = 1, xpd = TRUE)
plot( inflation_0, col= "red", xaxt = "n", ylim=c(-0.02, 0.06), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(inflation_1, col = "blue", lwd=2);
box(bty="l"); grid()
legend("topleft",legend=c("Inflation (baseline)", "Inflation (Shock 1)"),lty=c(1,1),lwd=c(2),bty="n", col = c("red", "blue"));
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot( (pc_ds_1 - pc_ds_0)/pc_ds_0, xaxt = "n", col= "red", ylim=c(-0.12, 0.1), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines((rer_1 - rer_0)/rer_0, col = "blue", lwd=2);
lines((rw_ds_1 - rw_ds_0)/rw_ds_0, col = "black", lwd=2);
box(bty="l"); grid()
legend("topleft",
legend=c("CPI", "Real ex. rate", "Real wages"),
lty=c(1,1,1,1,1), lwd=c(2,2,2), bty="n",
col = c("red", "blue", "black")
);
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
Plot scenario 1 + 2
plot( (yk_ds_1 - yk_ds_0)*100/yk_ds_0, xaxt = "n", col= "red", ylim=c(-5, 3), ylab="% deviation from baseline", xlab="", lwd=2, frame.plot = FALSE);
lines( (yk_ds_2 - yk_ds_0)*100/yk_ds_0, col="blue", lwd=2);
box(bty="l"); grid()
legend("topleft", ncol=1,
legend=c("GDP (scenario 1 without MP intervention)", "GDP (scenario with MP intervention)"),
lty=c(1,1), lwd=c(2,2), bty="n",
col = c("red", "blue")
);
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.004, labels = lablist, pos = 1, xpd = TRUE)
plot( (pconk_ds_1 - pconk_ds_0)*100/pconk_ds_0, xaxt = "n", col= "black", ylim=c(-12.5, 8), ylab="% deviations from baseline", xlab="", lwd=2, frame.plot = FALSE);
lines( (pconk_ds_2 - pconk_ds_0)*100/pconk_ds_0, col="blue", lwd=2);
lines((ik_1 - ik_0)*100/ik_0, col= "red",lwd=2);
lines( (ik_2 - ik_0)*100/ik_0, col="orange", lwd=2);
box(bty="l"); grid()
legend("topleft",ncol=1,
legend=c("Consumption (scenario 1 without MP intervention)", "Consumption (scenario 1 with MP intervention)", "Investment (scenario 1 without MP intervention)", "Investment (scenario 1 with MP intervention)"),
lty=c(1,1,1,1,1), lwd=c(2,2,2,2,2), bty="n",
col = c("black", "blue", "red", "orange")
);
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
plot( (xk_ds_1 - xk_ds_0)*100/xk_ds_0, xaxt = "n", col= "black", ylim=c(-10, 8), ylab="% deviations from baseline", xlab="", lwd=2, frame.plot = FALSE);
lines( (xk_ds_2 - xk_ds_0)*100/xk_ds_0, col="blue", lwd=2);
lines((mk_ds_1 - mk_ds_0)*100/mk_ds_0, col= "red",lwd=2);
lines( (mk_ds_2 - mk_ds_0)*100/mk_ds_0, col="orange", lwd=2);
box(bty="l"); grid()
legend("topleft",ncol=1,
legend=c("Exports (scenario 1 without MP intervention)", "Exports (scenario 1 with MP intervention)", "Imports (scenario 1 without MP intervention)", "Imports (scenario 1 with MP intervention)"),
lty=c(1,1,1,1,1), lwd=c(2,2,2,2,2), bty="n",
col = c("black", "blue", "red", "orange")
);
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot( (ur_ds_1*100-ur_ds_0*100), col= "black", xaxt = "n", xlab="", ylim=c(-3, 5), ylab="Difference from baseline", lwd=2, frame.plot = FALSE);
lines(ur_ds_2*100 - ur_ds_0*100, col = "blue", lwd=2);
lines(inflation_1*100 - inflation_0*100, col = "red", lwd=2);
lines(inflation_2*100 - inflation_0*100, col = "orange", lwd=2);
box(bty="l"); grid()
legend("bottomleft",ncol=1,
legend=c("Unemployment rate (scenario 1 without MP intervention)", "Unemployment rate (scenario with MP intervention)", "Annual inflation (scenario 1 without MP intervention)", "Annual inflation (scenario with MP intervention)"),lty=c(1,1,1,1),lwd=c(2,2,2,2),bty="n", col = c("black", "blue", "red", "orange"));
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.3, labels = lablist, pos = 1, xpd = TRUE)
plot(ur_ds_0, col= "black", xaxt = "n", xlab="", ylim=c(0.025, 0.15), ylab="", lwd=2, frame.plot = FALSE);
lines(ur_ds_1, col = "red", lwd=2);
lines(ur_ds_2, col = "blue", lwd=2);
box(bty="l"); grid()
legend("topleft",ncol=2,
legend=c("Unemployment rate (baseline)", "Unemployment rate (shock 1)", "Unemployment rate (shock 1+2)"),lty=c(1,1,1),lwd=c(2,2,2),bty="n", col = c("black", "red", "blue"));
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot(inflation_0, col= "black", xaxt = "n", ylim=c(-0.01, 0.06), ylab="", lwd=2, xlab="", frame.plot = FALSE);
lines(inflation_1, col = "red", lwd=2);
lines(inflation_2, col = "blue", lwd=2);
box(bty="l"); grid()
legend("topleft",ncol=2,
legend=c("Inflation (baseline)", "Inflation (shock 1)", "Inflation (shock 1+2)"),lty=c(1,1,1),lwd=c(2,2,2),bty="n", col = c("black", "red", "blue"));
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot( (pc_ds_1 - pc_ds_0)/pc_ds_0, xaxt = "n", col= "black", ylim=c(-0.15, 0.15), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines( (pc_ds_2 - pc_ds_0)/pc_ds_0, col="red", lwd=2);
lines( (rw_ds_1 - rw_ds_0)/rw_ds_0, col= "orange",lwd=2);
lines( (rw_ds_2 - rw_ds_0)/rw_ds_0, col="blue", lwd=2);
box(bty="l"); grid()
legend("topleft", ncol=2,
legend=c("CPI (shock 1)", "CPI (shock 1 +2)", "Real wages (shock 1)", "Real wages (shock 1+2)"),
lty=c(1,1,1,1,1), lwd=c(2,2,2,2,2), bty="n",
col = c("black", "red", "orange", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.02, labels = lablist, pos = 1, xpd = TRUE)
PLot scenario 1+2+3
plot( (yk_ds_1 - yk_ds_0)/yk_ds_0, xaxt = "n", col= "black", ylim=c(-0.06, 0.035), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines( (yk_ds_2 - yk_ds_0)/yk_ds_0, col="orange", lwd=2);
lines( (yk_ds_3 - yk_ds_0)/yk_ds_0, col="blue", lwd=2);
box(bty="l"); grid()
legend("topright",
legend = c("GDP (shock 1)", "GDP (shock 1 +2)", "GDP (shock 1 +2 + 3)"),
lty=c(1,1,1), lwd=c(2,2,2), bty="n",
col = c("black", "orange", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot((yk_ds_4 - yk_ds_0)/yk_ds_0 , xaxt = "n", col= "orange", ylim=c(-0.05, 0.03), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines((yk_ds_2 - yk_ds_0)/yk_ds_0, col="blue", lwd=2);
box(bty="l"); grid()
legend("topleft",
legend = c("GDP (scenario 1 with MP intervention)", "GDP (scenario 2)"),
lty=c(1,1,1), lwd=c(2,2,2), bty="n",
col = c("blue", "orange")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot(ur_ds_4*100 - ur_ds_0*100, col= "orange", xaxt = "n", ylim=c(-3, 5), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(ur_ds_2*100 - ur_ds_0*100, col = "blue", lwd=2);
lines(inflation_4*100 - inflation_0*100, col = "black", lwd=2);
lines(inflation_2*100 - inflation_0*100, col = "red", lwd=2);
box(bty="l"); grid()
legend("bottomleft", ncol=1, legend=c("Unemployment rate (scenario 1 with MP intervention)", "Unemployment rate (scenario 2)", "Inflation (scenario 1 with MP intervention)","Inflation (scenario 2)")
,lty=c(1,1,1,1,1,1),lwd=c(2,2,2,2,2,2),bty="n", col = c("blue", "orange", "red", "black"))
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.3, labels = lablist, pos = 1, xpd = TRUE)
plot( (pconk_ds_1 - pconk_ds_0)/pconk_ds_0, xaxt = "n", col= "orange", ylim=c(-0.17, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines( (pconk_ds_2 - pconk_ds_0)/pconk_ds_0, col="blue", lwd=2);
lines( (pconk_ds_3 - pconk_ds_0)/pconk_ds_0, col="black", lwd=2);
lines((ik_1 - ik_0)/ik_0, col= "red",lwd=2);
lines( (ik_2 - ik_0)/ik_0, col="green", lwd=2);
lines( (ik_3 - ik_0)/ik_0, col="cyan", lwd=2);
box(bty="l"); grid()
legend("topright", ncol=2,
legend=c("Consumption (shock 1)", "Consumption (shock 1 +2)", "Consumption (shock 1 +2+3)", "Investment (shock 1)", "Investment (shock 1+2)", "Investment (shock 1+2+3)"),
lty=c(1,1,1,1,1,1,1), lwd=c(2,2,2,2,2,2,2), bty="n",
col = c("orange", "blue", "black", "red", "green", "cyan")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
plot( (ur_ds_1-ur_ds_0), col= "orange", xaxt = "n", ylim=c(-0.025, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(ur_ds_2 - ur_ds_0, col = "blue", lwd=2);
lines(ur_ds_3 - ur_ds_0, col = "black", lwd=2);
lines(inflation_1 - inflation_0, col = "red", lwd=2);
lines(inflation_2 - inflation_0, col = "green", lwd=2);
lines(inflation_3 - inflation_0, col = "cyan", lwd=2);
box(bty="l"); grid()
legend("topleft", ncol=2, legend=c("Unemployment rate (shock 1)", "Unemployment rate (shock 1+2)", "Unemployment rate (shock 1+2+3)","Inflation (shock 1)", "Inflation (shock 1+2)", "Inflation (shock 1+2+3)"),lty=c(1,1,1,1,1,1),lwd=c(2,2,2,2,2,2),bty="n", col = c("orange", "blue", "black", "red", "green", "cyan"))
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot(ur_ds_0, col= "black", xaxt = "n", ylim=c(0.025, 0.15), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(ur_ds_1, col = "red", lwd=2);
lines(ur_ds_2, col = "blue", lwd=2);
lines(ur_ds_3, col = "orange", lwd=2);
box(bty="l"); grid()
legend("topleft",ncol=2,
legend=c("Unemployment rate (baseline)", "Unemployment rate (shock 1)", "Unemployment rate (shock 1+2)", "Unemployment rate (shock 1+2+3)" ),lty=c(1,1,1,1),lwd=c(2,2,2,2),bty="n", col = c("black", "red", "blue", "orange"));
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot(inflation_0, col= "black", xaxt = "n", ylim=c(-0.02, 0.06), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(inflation_1, col = "red", lwd=2);
lines(inflation_2, col = "blue", lwd=2);
lines(inflation_3, col = "orange", lwd=2);
box(bty="l"); grid()
legend("topleft",ncol=2,
legend=c("Inflation (baseline)", "Inflation (shock 1)", "Inflation (shock 1+2)", "Inflation (shock 1+2+3)"),lty=c(1,1,1,1),lwd=c(2,2,2,2),bty="n", col = c("black", "red", "blue", "orange"));
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot( (pc_ds_1 - pc_ds_0)/pc_ds_0, xaxt = "n", col= "orange", ylim=c(-0.15, 0.1), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines( (pc_ds_2 - pc_ds_0)/pc_ds_0, col="blue", lwd=2);
lines( (pc_ds_3 - pc_ds_0)/pc_ds_0, col="black", lwd=2);
lines((rw_ds_1 - rw_ds_0)/rw_ds_0, col= "red",lwd=2);
lines( (rw_ds_2 - rw_ds_0)/rw_ds_0, col="green", lwd=2);
lines( (rw_ds_3 - rw_ds_0)/rw_ds_0, col="cyan", lwd=2);
box(bty="l"); grid()
legend("bottomleft", ncol=2,
legend=c("CPI (shock 1)", "CPI (shock 1 +2)", "CPI (shock 1 +2+3)", "Real wages (shock 1)", "Real wages (shock 1+2)", "Real wages (shock 1+2+3)"),
lty=c(1,1,1,1,1,1,1), lwd=c(2,2,2,2,2,2,2), bty="n",
col = c("orange", "blue", "black", "red", "green", "cyan")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.02, labels = lablist, pos = 1, xpd = TRUE)
plot( (fnw_g_0/y_0), col= "orange", xaxt = "n", xlab="", ylab="", ylim=c(-0.8, 0.2), lwd=2, frame.plot = FALSE);
lines( (fnw_g_1/y_1), col="blue", lwd=2);
lines( (fnw_g_2/y_2), col="red", lwd=2);
lines( (fnw_g_3/y_3), col="black", lwd=2);
box(bty="l"); grid()
legend("topleft", ncol=2,
legend=c("FNW.gov (baseline)", "FNW.gov (shock 1)", "FNW.gov (shock 1 +2)", "FNW.gov (shock 1 +2+3)"),
lty=c(1,1,1,1), lwd=c(2,2,2,2), bty="n",
col = c("orange", "blue", "red", "black")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.04, labels = lablist, pos = 1, xpd = TRUE)
plot( (fnw_g_0), col= "orange", xaxt = "n", ylab="", xlab="", ylim=c( -500000, 20000), lwd=2, frame.plot = FALSE);
lines( (fnw_g_1), col="blue", lwd=2);
lines( (fnw_g_2), col="red", lwd=2);
lines( (fnw_g_3), col="black", lwd=2);
lines( (fnw_g_4), col="cyan", lwd=2);
box(bty="l"); grid()
legend("bottomleft", ncol=2,
legend=c("FNW.gov (baseline)", "FNW.gov (shock 1)", "FNW.gov (shock 1 +2)", "FNW.gov (shock 1 +2+3)"),
lty=c(1,1,1,1), lwd=c(2,2,2,2), bty="n",
col = c("orange", "blue", "red", "black")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 35000, labels = lablist, pos = 1, xpd = TRUE)
plot( (nl_g_1/y_1 - nl_g_0/y_0), xaxt = "n", col= "orange", ylab="", xlab="", ylim=c(-0.08, 0.06), lwd=2, frame.plot = FALSE);
lines( (nl_g_2/y_1 - nl_g_0/y_0), col="blue", lwd=2);
lines( (nl_g_3/y_1 - nl_g_0/y_0), col="black", lwd=2);
box(bty="l"); grid()
legend("topleft", ncol=2,
legend=c("Net lending.gov (shock 1)", "Net lending.gov (shock 1 +2)", "Net lending.gov (shock 1 +2+3)"),
lty=c(1,1,1), lwd=c(2,2,2), bty="n",
col = c("orange", "blue", "black"))
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot( (nl_g_0/y_0), col= "orange", xaxt = "n", ylab="", xlab="", ylim=c(-0.08, 0.06), lwd=2, frame.plot = FALSE);
lines( (nl_g_1/y_1), col="blue", lwd=2);
lines( (nl_g_2/y_2), col="black", lwd=2);
lines( (nl_g_3/y_3), col="red", lwd=2);
lines( (nl_g_4/y_4), col="cyan", lwd=2);
box(bty="l"); grid()
legend("topleft", ncol=2,
legend=c("NL.gov (baseline)", "NL.gov (shock 1)", "NL.gov (shock 1 +2)", "NL.gov (shock 1 +2+3)"),
lty=c(1,1,1,1), lwd=c(2,2,2,2), bty="n",
col = c("orange", "blue", "black", "red"))
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.005, labels = lablist, pos = 1, xpd = TRUE)
plot( (nl_g_0), col= "orange", xaxt = "n", ylab="", xlab="", ylim=c( -60000, 25000), lwd=2, frame.plot = FALSE);
lines( (nl_g_1), col="blue", lwd=2);
lines( (nl_g_2), col="black", lwd=2);
lines( (nl_g_3), col="red", lwd=2);
lines( (nl_g_4), col="cyan", lwd=2);
box(bty="l"); grid()
legend("bottomleft", ncol=2,
legend=c("NL.gov (baseline)", "NL.gov (shock 1)", "NL.gov (shock 1 +2)", "NL.gov (shock 1 +2+3)"),
lty=c(1,1,1,1), lwd=c(2,2,2,2), bty="n",
col = c("orange", "blue", "black", "red"))
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 4000, labels = lablist, pos = 1, xpd = TRUE)
plot( ((yk_ds_2 - yk_ds_1)/yk_ds_1)*100, xaxt = "n", col= "black", ylim=c(-4, 3), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines( (inflation_2*100 - inflation_1*100), col="orange", lwd=2);
lines( (ur_ds_2*100 - ur_ds_1*100), col="blue", lwd=2);
box(bty="l"); grid()
legend("bottomleft",
legend = c("Real GDP (% deviation from scenario 1 without MP)", "Annual inflation (diference from scenario 1 without MP)", "Unemployment rate (difference from scenario 1 without MP)"),
lty=c(1,1,1), lwd=c(2,2,2), bty="n",
col = c("black", "orange", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.25, labels = lablist, pos = 1, xpd = TRUE)
plot( ((yk_ds_3 - yk_ds_2)/yk_ds_2)*100, xaxt = "n", col= "black", ylim=c(-0.5, 0.5), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines( (inflation_3*100 - inflation_2*100), col="orange", lwd=2);
lines( (ur_ds_3*100 - ur_ds_2*100), col="blue", lwd=2);
box(bty="l"); grid()
legend("bottomleft",
legend = c("Real GDP (% deviation from scenario 1 with MP)", "Annual inflation (difference from scenario 1 with MP)", "Unemployment rate (difference from scenario 1 with MP)"),
lty=c(1,1,1), lwd=c(2,2,2), bty="n",
col = c("black", "orange", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.02, labels = lablist, pos = 1, xpd = TRUE)
plot( ((yk_ds_4 - yk_ds_3)/yk_ds_3)*100, xaxt = "n", col= "black", ylim=c(-0.5, 0.5), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines( (inflation_4*100 - inflation_3*100), col="orange", lwd=2);
lines( (ur_ds_4*100 - ur_ds_3*100), col="blue", lwd=2);
box(bty="l"); grid()
legend("bottomleft",
legend = c("Real GDP", "Annual inflation", "Unemployment rate"),
lty=c(1,1,1), lwd=c(2,2,2), bty="n",
col = c("black", "orange", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.02, labels = lablist, pos = 1, xpd = TRUE)
plot( ((yk_ds_4 - yk_ds_2)/yk_ds_2)*100, xaxt = "n", col= "black", ylim=c(-0.7, 0.7), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(inflation_4*100 - inflation_2*100, col="orange", lwd=2);
lines( (ur_ds_4*100 - ur_ds_2*100), col="blue", lwd=2);
box(bty="l"); grid()
legend("bottomleft",
legend = c("Real GDP (% deviation from scenario 1 with MP)", "Annual inflation (difference from scenario 1 with MP)", "Unemployment rate (difference from scenario 1 with MP)"),
lty=c(1,1,1), lwd=c(2,2,2), bty="n",
col = c("black", "orange", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.02, labels = lablist, pos = 1, xpd = TRUE)
Debt sustainability condition
yd_g_00 <- S_model$simulation$yd_g
yd_g_01 <- Shock_1$simulation$yd_g
yd_g_02 <- Shock_2$simulation$yd_g
yd_g_03 <- Shock_3$simulation$yd_g
yd_g_04 <- Shock_4$simulation$yd_g
y_ds_00 <- S_model$simulation$y_ds
y_ds_01 <- Shock_1$simulation$y_ds
y_ds_02 <- Shock_2$simulation$y_ds
y_ds_03 <- Shock_3$simulation$y_ds
y_ds_04 <- Shock_4$simulation$y_ds
npropinc_g_00 <- S_model$simulation$npropinc_g
npropinc_g_01 <- Shock_1$simulation$npropinc_g
npropinc_g_02 <- Shock_2$simulation$npropinc_g
npropinc_g_03 <- Shock_3$simulation$npropinc_g
npropinc_g_04 <- Shock_4$simulation$npropinc_g
ibd_00 <- S_model$simulation$ibd
ibd_01 <- Shock_1$simulation$ibd
ibd_02 <- Shock_2$simulation$ibd
ibd_03 <- Shock_3$simulation$ibd
ibd_04 <- Shock_4$simulation$ibd
primary_g_bal_00 <- yd_g_00 - npropinc_g_00 - g;
primary_g_bal_01 <- yd_g_01 - npropinc_g_01 - g
primary_g_bal_02 <- yd_g_02 - npropinc_g_02 - g
primary_g_bal_03 <- yd_g_03 - npropinc_g_03 - g
primary_g_bal_04 <- yd_g_04 - npropinc_g_04 - g
gy_00 <- (y_ds_00/TSLAG(y_ds_00,1) - 1)
gy_01 <- (y_ds_01/TSLAG(y_ds_01,1) - 1)
gy_02 <- (y_ds_02/TSLAG(y_ds_02,1) - 1)
gy_03 <- (y_ds_03/TSLAG(y_ds_03,1) - 1)
gy_04 <- (y_ds_04/TSLAG(y_ds_04,1) - 1)primary_bal_00 <- primary_g_bal_00/y_ds_00
primary_bal_01 <- primary_g_bal_01/y_ds_01
primary_bal_02 <- primary_g_bal_02/y_ds_02
primary_bal_03 <- primary_g_bal_03/y_ds_03
primary_bal_04 <- primary_g_bal_04/y_ds_04
# - we use minus fnw_g because we need net debt
debt_burden_00 <- (ibd_00 - gy_00)*-fnw_g_00/y_00
debt_burden_01 <- (ibd_01 - gy_01)*-fnw_g_01/y_01
debt_burden_02 <- (ibd_02 - gy_02)*-fnw_g_02/y_02
debt_burden_03 <- (ibd_03 - gy_03)*-fnw_g_03/y_03
debt_burden_04 <- (ibd_04 - gy_04)*-fnw_g_04/y_04
plot(primary_bal_03)
lines(primary_bal_01, col="blue")
lines(primary_bal_02, col="orange")
lines(primary_bal_00, col="cyan")
lines(primary_bal_04, col="red")
plot(debt_burden_03)
lines(debt_burden_01, col="blue")
lines(debt_burden_02, col="orange")
lines(debt_burden_00, col="cyan")
lines(debt_burden_04, col="red")
library(dplyr)
library(zoo)
#calculate 4-period rolling average of debt sustainability
df2 <- data.frame(debt_burden_00, debt_burden_01, debt_burden_02, debt_burden_03, debt_burden_04)
debt <- df2 %>%
mutate(
debt_burden_00_ma = rollmean(debt_burden_00, k=4, fill=NA, align="right"),
debt_burden_01_ma = rollmean(debt_burden_01, k=4, fill=NA, align="right"),
debt_burden_02_ma = rollmean(debt_burden_02, k=4, fill=NA, align="right"),
debt_burden_03_ma = rollmean(debt_burden_03, k=4, fill=NA, align="right"),
debt_burden_04_ma = rollmean(debt_burden_04, k=4, fill=NA, align="right"),
)
#calculate 4-period rolling average of public balance
df1 <- data.frame(primary_bal_00, primary_bal_01, primary_bal_02, primary_bal_03, primary_bal_04)
balance <- df1 %>%
mutate(
primary_bal_00_ma = rollmean(primary_bal_00, k=4, fill=NA, align = "right"),
primary_bal_01_ma = rollmean(primary_bal_01, k=4, fill=NA, align="right"),
primary_bal_02_ma = rollmean(primary_bal_02, k=4, fill=NA, align="right"),
primary_bal_03_ma = rollmean(primary_bal_03, k=4, fill=NA, align="right"),
primary_bal_04_ma = rollmean(primary_bal_04, k=4, fill=NA, align="right"),
)#reduce sample
p_bal_ma_00 <- window(balance$primary_bal_00_ma, start=c(2012,1), freq=4)
p_bal_ma_01 <- window(balance$primary_bal_01_ma, start=c(2012,1), freq=4)
p_bal_ma_02 <- window(balance$primary_bal_02_ma, start=c(2012,1), freq=4)
p_bal_ma_03 <- window(balance$primary_bal_03_ma, start=c(2012,1), freq=4)
p_bal_ma_04 <- window(balance$primary_bal_04_ma, start=c(2012,1), freq=4)
debt_ma_00 <- window(debt$debt_burden_00_ma, start=c(2012,1), freq=4)
debt_ma_01 <- window(debt$debt_burden_01_ma, start=c(2012,1), freq=4)
debt_ma_02 <- window(debt$debt_burden_02_ma, start=c(2012,1), freq=4)
debt_ma_03 <- window(debt$debt_burden_03_ma, start=c(2012,1), freq=4)
debt_ma_04 <- window(debt$debt_burden_04_ma, start=c(2012,1), freq=4)#Debt sustainability after shock 1
plot(p_bal_ma_00, xaxt = "n", col= "red", lty=2, ylim=c(-0.08, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(p_bal_ma_01, col="red", lwd=2)
lines(debt_ma_00, col="blue", lwd=2, lty=2)
lines(debt_ma_01, col="blue", lwd=2)
box(bty="l"); grid()
legend("bottomleft",
legend = c("Primary balance (baseline)", "Primary balance (shock 1)", "Net change in int. burden (baseline)", "Net change in int. burden (shock 1 )"),
lty=c(2,1,2,1), lwd=c(2,2,2,2), bty="n",
col = c("red", "red", "blue", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
#Debt sustainability after shock 1 +2
plot(p_bal_ma_00, xaxt = "n", col= "red", lty=2, ylim=c(-0.08, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(p_bal_ma_02, col="red", lwd=2)
lines(debt_ma_00, col="blue", lwd=2, lty=2)
lines(debt_ma_02, col="blue", lwd=2)
box(bty="l"); grid()
legend("bottomleft",
legend = c("Primary balance (baseline)", "Primary balance (shock 1 +2)", "Net change in int. burden (baseline)", "Net change in int. burden (shock 1 + 2)"),
lty=c(2,1,2,1), lwd=c(2,2,2,2), bty="n",
col = c("red", "red", "blue", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
#Debt sustainability after shock 1 +2 +3
plot(p_bal_ma_00, xaxt = "n", col= "red", lty=2, ylim=c(-0.08, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(p_bal_ma_03, col="red", lwd=2)
lines(debt_ma_00, col="blue", lwd=2, lty=2)
lines(debt_ma_03, col="blue", lwd=2)
box(bty="l"); grid()
legend("bottomleft",
legend = c("Primary balance (baseline)", "Primary balance (shock 1 + 2 + 3)", "Net change in int. burden (baseline)", "Net change in int. burden (shock 1 + 2 + 3)"),
lty=c(2,1,2,1), lwd=c(2,2,2,2), bty="n",
col = c("red", "red", "blue", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
plot((p_bal_ma_00-debt_ma_00), xaxt = "n", col="orange", ylim=c(-0.06, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
abline(h=0, lwd=2, lty=2, col="green")
lines((p_bal_ma_01-debt_ma_01), lwd=2, col="black")
lines((p_bal_ma_02-debt_ma_02), lwd=2, col="red")
lines((p_bal_ma_03-debt_ma_03), lwd=2, col="blue")
lines((p_bal_ma_04-debt_ma_04), lwd=2, col="cyan")
box(bty="l"); grid()
legend("bottomleft", ncol=1,
legend = c("Debt sustainability (baseline)", "Debt sustainability (shock 1)", "Debt sustainability (shock 1 + 2)", "Debt sustainability (shock 1 + 2 + 3)"),
lty=c(1,1,1,1), lwd=c(2,2,2,2), bty="n",
col = c("orange", "black", "red", "blue")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
Annual debt sustainability
ya_00 <- window(y_00, start=c(2007,1), freq=4)
ya_00 <- aggregate(ya_00, nfrequency=1)
ya_01 <- window(y_01, start=c(2007,1), freq=4)
ya_01 <- aggregate(ya_01, nfrequency=1)
ya_02 <- window(y_02, start=c(2007,1), freq=4)
ya_02 <- aggregate(ya_02, nfrequency=1)
ya_03 <- window(y_03, start=c(2007,1), freq=4)
ya_03 <- aggregate(ya_03, nfrequency=1)
ya_04 <- window(y_04, start=c(2007,1), freq=4)
ya_04 <- aggregate(ya_04, nfrequency=1)
y_ds_a_00 <- window(y_ds_00, start=c(2007,1), freq=4)
y_ds_a_00 <- aggregate(y_ds_a_00, nfrequency=1)
y_ds_a_01 <- window(y_ds_01, start=c(2007,1), freq=4)
y_ds_a_01 <- aggregate(y_ds_a_01, nfrequency=1)
y_ds_a_02 <- window(y_ds_02, start=c(2007,1), freq=4)
y_ds_a_02 <- aggregate(y_ds_a_02, nfrequency=1)
y_ds_a_03 <- window(y_ds_03, start=c(2007,1), freq=4)
y_ds_a_03 <- aggregate(y_ds_a_03, nfrequency=1)
y_ds_a_04 <- window(y_ds_04, start=c(2007,1), freq=4)
y_ds_a_04 <- aggregate(y_ds_a_04, nfrequency=1)
gya_00 <- (y_ds_a_00/TSLAG(y_ds_a_00,1) - 1)
gya_01 <- (y_ds_a_01/TSLAG(y_ds_a_01,1) - 1)
gya_02 <- (y_ds_a_02/TSLAG(y_ds_a_02,1) - 1)
gya_03 <- (y_ds_a_03/TSLAG(y_ds_a_03,1) - 1)
gya_04 <- (y_ds_a_04/TSLAG(y_ds_a_04,1) - 1)
fnw_ga_00 <- window(fnw_g_00, start=c(2007,1), freq=4)
fnw_ga_00 <- aggregate(fnw_ga_00, nfrequency=1)
fnw_ga_01 <- window(fnw_g_01, start=c(2007,1), freq=4)
fnw_ga_01 <- aggregate(fnw_ga_01, nfrequency=1)
fnw_ga_02 <- window(fnw_g_02, start=c(2007,1), freq=4)
fnw_ga_02 <- aggregate(fnw_ga_02, nfrequency=1)
fnw_ga_03 <- window(fnw_g_03, start=c(2007,1), freq=4)
fnw_ga_03 <- aggregate(fnw_ga_03, nfrequency=1)
fnw_ga_04 <- window(fnw_g_04, start=c(2007,1), freq=4)
fnw_ga_04 <- aggregate(fnw_ga_04, nfrequency=1)
primary_g_bala_00 <- window(primary_g_bal_00, start=c(2007,1), freq=4)
primary_g_bala_00 <- aggregate(primary_g_bala_00, nfrequency=1)
primary_g_bala_01 <- window(primary_g_bal_01, start=c(2007,1), freq=4)
primary_g_bala_01 <- aggregate(primary_g_bala_01, nfrequency=1)
primary_g_bala_02 <- window(primary_g_bal_02, start=c(2007,1), freq=4)
primary_g_bala_02 <- aggregate(primary_g_bala_02, nfrequency=1)
primary_g_bala_03 <- window(primary_g_bal_03, start=c(2007,1), freq=4)
primary_g_bala_03 <- aggregate(primary_g_bala_03, nfrequency=1)
primary_g_bala_04 <- window(primary_g_bal_04, start=c(2007,1), freq=4)
primary_g_bala_04 <- aggregate(primary_g_bala_04, nfrequency=1)
ibd_a_00 <- window(ibd_00, start=c(2007,1), frequency=4)
ibd_a_00 <- aggregate(ibd_a_00, nfrequency=1, FUN=mean)
ibd_a_01 <- window(ibd_01, start=c(2007,1), frequency=4)
ibd_a_01 <- aggregate(ibd_a_01, nfrequency=1, FUN=mean)
ibd_a_02 <- window(ibd_02, start=c(2007,1), frequency=4)
ibd_a_02 <- aggregate(ibd_a_02, nfrequency=1, FUN=mean)
ibd_a_03 <- window(ibd_03, start=c(2007,1), frequency=4)
ibd_a_03 <- aggregate(ibd_a_03, nfrequency=1, FUN=mean)
ibd_a_04 <- window(ibd_04, start=c(2007,1), frequency=4)
ibd_a_04 <- aggregate(ibd_a_04, nfrequency=1, FUN=mean)
debt_burden_a_00 <- (ibd_a_00 - gya_00)*-fnw_ga_00/ya_00
debt_burden_a_01 <- (ibd_a_01 - gya_01)*-fnw_ga_01/ya_01
debt_burden_a_02 <- (ibd_a_02 - gya_02)*-fnw_ga_02/ya_02
debt_burden_a_03 <- (ibd_a_03 - gya_03)*-fnw_ga_03/ya_03
debt_burden_a_04 <- (ibd_a_04 - gya_04)*-fnw_ga_04/ya_04
primary_bala_00 <- primary_g_bala_00/y_ds_a_00
primary_bala_01 <- primary_g_bala_01/y_ds_a_01
primary_bala_02 <- primary_g_bala_02/y_ds_a_02
primary_bala_03 <- primary_g_bala_03/y_ds_a_03
primary_bala_04 <- primary_g_bala_04/y_ds_a_04Create windows of annual data for plotting:
# For GDP growth rates
gya_00 <- window(gya_00, start=2012)
gya_01 <- window(gya_01, start=2012)
gya_02 <- window(gya_02, start=2012)
gya_03 <- window(gya_03, start=2012)
gya_04 <- window(gya_04, start=2012)
# For GDP
ya_00 <- window(ya_00, start=2012)
ya_01 <- window(ya_01, start=2012)
ya_02 <- window(ya_02, start=2012)
ya_03 <- window(ya_03, start=2012)
ya_04 <- window(ya_04, start=2012)
y_ds_a_00 <- window(y_ds_a_00, start=2012)
y_ds_a_01 <- window(y_ds_a_01, start=2012)
y_ds_a_02 <- window(y_ds_a_02, start=2012)
y_ds_a_03 <- window(y_ds_a_03, start=2012)
y_ds_a_04 <- window(y_ds_a_04, start=2012)
# Net debt
fnw_ga_00 <- window(fnw_ga_00, start=2012)
fnw_ga_01 <- window(fnw_ga_01, start=2012)
fnw_ga_02 <- window(fnw_ga_02, start=2012)
fnw_ga_03 <- window(fnw_ga_03, start=2012)
fnw_ga_04 <- window(fnw_ga_04, start=2012)
primary_g_bala_00 <- window(primary_g_bala_00, start=2012)
primary_g_bala_01 <- window(primary_g_bala_01, start=2012)
primary_g_bala_02 <- window(primary_g_bala_02, start=2012)
primary_g_bala_03 <- window(primary_g_bala_03, start=2012)
primary_g_bala_04 <- window(primary_g_bala_04, start=2012)
# Interest rates
ibd_a_00 <- window(ibd_a_00, start=2012)
ibd_a_01 <- window(ibd_a_01, start=2012)
ibd_a_02 <- window(ibd_a_02, start=2012)
ibd_a_03 <- window(ibd_a_03, start=2012)
ibd_a_04 <- window(ibd_a_04, start=2012)
# The following debt burden to GDP and primary balance to GDP are based on short samples:
debt_burden_a_00 <- (ibd_a_00 - gya_00)*-fnw_ga_00/ya_00
debt_burden_a_01 <- (ibd_a_01 - gya_01)*-fnw_ga_01/ya_01
debt_burden_a_02 <- (ibd_a_02 - gya_02)*-fnw_ga_02/ya_02
debt_burden_a_03 <- (ibd_a_03 - gya_03)*-fnw_ga_03/ya_03
debt_burden_a_04 <- (ibd_a_04 - gya_04)*-fnw_ga_04/ya_04
primary_bala_00 <- primary_g_bala_00/y_ds_a_00
primary_bala_01 <- primary_g_bala_01/y_ds_a_01
primary_bala_02 <- primary_g_bala_02/y_ds_a_02
primary_bala_03 <- primary_g_bala_03/y_ds_a_03
primary_bala_04 <- primary_g_bala_04/y_ds_a_04#Debt sustainability after shock 1
plot(primary_bala_00, xaxt = "n", col= "red", lty=2, ylim=c(-0.08, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(primary_bala_01, col="red", lwd=2)
lines(debt_burden_a_00, col="blue", lwd=2, lty=2)
lines(debt_burden_a_01, col="blue", lwd=2)
box(bty="l"); grid()
legend("bottomleft",
legend = c("Primary balance (baseline)", "Primary balance (shock 1)", "Net change in int. burden (baseline)", "Net change in int. burden (shock 1 )"),
lty=c(2,1,2,1), lwd=c(2,2,2,2), bty="n",
col = c("red", "red", "blue", "blue")
)
lablist<- c('t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
#Debt sustainability after shock 1 +2
plot(primary_bala_00, xaxt = "n", col= "red", lty=2, ylim=c(-0.08, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(primary_bala_02, col="red", lwd=2)
lines(debt_burden_a_00, col="blue", lwd=2, lty=2)
lines(debt_burden_a_02, col="blue", lwd=2)
box(bty="l"); grid()
legend("bottomleft",
legend = c("Primary balance (baseline)", "Primary balance (shock 1 + 2)", "Net change in int. burden (baseline)", "Net change in int. burden (shock 1 + 2 )"),
lty=c(2,1,2,1), lwd=c(2,2,2,2), bty="n",
col = c("red", "red", "blue", "blue")
)
lablist<- c('t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
# Debt sustainability after shock 1 +2 +3
plot(primary_bala_00, xaxt = "n", col= "red", lty=2, ylim=c(-0.08, 0.08), ylab="", xlab="", lwd=2, frame.plot = FALSE);
lines(primary_bala_03, col="red", lwd=2)
lines(debt_burden_a_00, col="blue", lwd=2, lty=2)
lines(debt_burden_a_03, col="blue", lwd=2)
box(bty="l"); grid()
legend("bottomleft",
legend = c("Primary balance (baseline)", "Primary balance (shock 1 + 2 + 3)", "Net change in int. burden (baseline)", "Net change in int. burden (shock 1 + 2 + 3)"),
lty=c(2,1,2,1), lwd=c(2,2,2,2), bty="n",
col = c("red", "red", "blue", "blue")
)
lablist<- c('t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
Debt sustainability all shocks in one plot
plot((primary_bala_04-debt_burden_a_04), xaxt = "n", col="orange", ylim=c(-0.12, 0.08), ylab="ratio of GDP", xlab="", lwd=2, frame.plot = FALSE);
abline(h=0, lwd=2, lty=2, col="green")
lines((primary_bala_01-debt_burden_a_01), lwd=2, col="red")
lines((primary_bala_02-debt_burden_a_02), lwd=2, col="blue")
lines((primary_bala_00-debt_burden_a_00), lwd=2, col="black")
box(bty="l"); grid()
legend("bottomleft", ncol=1,
legend = c("Debt sustainability (baseline)", "Debt sustainability (scenario 1 without MP intervention)", "Debt sustainability (scenario 1 with MP intervention)", "Debt sustainability (scenario 2)"),
lty=c(1,1,1,1), lwd=c(2,2,2,2,2), bty="n",
col = c("black","red", "blue", "orange")
)
lablist<- c('t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.01, labels = lablist, pos = 1, xpd = TRUE)
plot( (fnw_ga_04/ya_04), col= "orange", xaxt = "n", xlab="", ylab="", ylim=c(-1.1, 0.2), lwd=2, frame.plot = FALSE);
lines( (fnw_ga_01/ya_01), col="red", lwd=2);
lines( (fnw_ga_02/ya_02), col="blue", lwd=2);
lines( (fnw_ga_03/ya_03), col="black", lwd=2);
box(bty="l"); grid()
legend("bottomleft", ncol=1,
legend=c("Net public debt to GDP (baseline)", "Net public debt to GDP (scenario 1 without MP intervention)", "Net public debt to GDP (scenario 1 with MP interention)", "Net public debt to GDP (scenario 2)"),
lty=c(1,1,1,1), lwd=c(2,2,2,2), bty="n",
col = c("black", "red", "blue", "orange")
)
lablist<- c('t-2','t-1','t','t+1','t+2','t+3','t+4','t+5','t+6')
axis(1, at=seq(2012, 2020, by=1), labels = FALSE)
text(seq(2012, 2020, by=1), par("usr")[3] - 0.04, labels = lablist, pos = 1, xpd = TRUE)