tests/testthat/test-lp_nl_iv.R
In AdaemmerP/lpirfs: Local Projections Impulse Response Functions
# Load package data
ag_data <- ag_data
sample_start <- 7
sample_end <- dim(ag_data)[1]
# Endogenous data
endog_data <- ag_data[sample_start:sample_end,3:5]
# 'Instrument' variable
instrument <- as.data.frame(ag_data$Gov[sample_start:sample_end])
# Choose the 7-quarter moving average growth rate as switching variable.
# and adjust it to have suffiently long recession periods.
switching_variable <- ag_data$GDP_MA[sample_start:sample_end] - 0.8
test_that("Test whether endogenous data is a data.frame", {
endog_data <- as.matrix(endog_data)
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = 0,
lambda = NaN,
gamma = 3,
num_cores = 1),
'The endogenous data has to be a data.frame.', fixed = TRUE)
})
test_that("Test whether trend is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = NULL,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = 0,
lambda = NaN,
gamma = 3,
num_cores = 1),
'Please specify whether and which type of trend to include.', fixed = TRUE)
})
test_that("Test whether switching variable is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = NULL,
use_hp = 0,
lambda = NaN,
gamma = 3,
num_cores = 1),
'Please provide a switching variable.', fixed = TRUE)
})
test_that("Test whether use_hp is set", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = NULL,
lambda = NaN,
gamma = 3,
num_cores = 1),
'Please specify whether to use the HP-filter for the switching variable.', fixed = TRUE)
})
test_that("Test whetherlambda is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = NULL,
gamma = 3,
num_cores = 1),
'Please specify lambda for the HP-filter.', fixed = TRUE)
})
test_that("Test whether gamma is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = NULL,
num_cores = 1),
'Please specify gamma for the transition function.', fixed = TRUE)
})
test_that("Test whether width for confidence bands is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = NULL,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'Please specify a value for the width of the confidence bands.', fixed = TRUE)
})
test_that("Test whether number of horizons is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 2,
hor = NULL,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'Please specify the number of horizons.', fixed = TRUE)
})
test_that("Test whether lag length criterion is correctly spelled", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIP',
max_lags = 4,
trend = 0,
confint = 2,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'Possible lag length criteria are AICc, AIC or BIC or NaN if lag length is specified.', fixed = TRUE)
})
test_that("Test whether lags criterion and fixed number of lags for nonlinear model is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = NULL,
trend = 0,
confint = 2,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'You can not provide a lag criterion (AICc, AIC or BIC) and a fixed number of lags.', fixed = TRUE)
})
test_that("Test whether maximum number of lags is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = NaN,
trend = 0,
confint = 2,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'Please provide a maximum number of lags for the lag length criterion.', fixed = TRUE)
})
test_that("Test whether number of horizons is positive", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = 0,
confint = 2,
hor = -1,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'The number of horizons has to be an integer and > 0.', fixed = TRUE)
})
test_that("Test whether trend is correctly specified", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = -1,
confint = 2,
hor = 12,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'For trend please set 0 = no trend, 1 = trend, 2 = trend and quadratic trend.', fixed = TRUE)
})
test_that("Test whether width of confidence bands is correctly specified", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = 1,
confint = -2,
hor = 12,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'The width of the confidence bands has to be >=0.', fixed = TRUE)
})
test_that("Test whether gamma is negative number", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = 1,
confint = 2,
hor = 12,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = -3,
num_cores = 1),
'Gamma has to be a positive number.', fixed = TRUE)
})
test_that("Test that data is correctly specified when lag length criterion is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = 2,
confint = 2,
hor = 12,
switching = switching_variable,
use_logistic = FALSE,
lag_switching = TRUE,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
NA)
})
# This example replicates results from the Supplementary Appendix
# by Ramey and Zubairy (2018), based on results from their provided
# Matlab code. The results evaluate findings from Auerbach and
# Gorodnichenko (2012) with local projections by Jordá (2005).
# The data and Matlab code is available on \url{https://www.journals.uchicago.edu/doi/10.1086/696277}{JoPE}
# Load and prepare data
# The sample length of RZ-2018 is 1948:III-2008:III
ag_data <- ag_data
sample_start <- 7
sample_end <- dim(ag_data)[1]
endog_data <- ag_data[sample_start:sample_end, 3:5]
# Choose instrument
instrument <- as.data.frame(ag_data$Gov_shock_mean[sample_start:sample_end])
# Choose exogenous data
exog_data <- as.data.frame(ag_data$GDP_MA[sample_start:sample_end])
# Choose exogenous data
switching_variable <- as.data.frame(ag_data$GDP_MA[sample_start:sample_end]) - 0.8
# These results are taken from the available Matlab code by Ramey and Zubairy (2018)
# They coresspond to row 2 and 3 in table 'regg' from the Matlab output
rz_s1_results <- c(1.00, 1.02, 0.78, 0.60, 0.37, 0.12, 0.04, -0.09, 0.04, -0.07, -0.21,
-0.30, -0.28, -0.42, -0.29, -0.23, 0.02, 0.11, 0.13, -0.01)
rz_s2_results <- c(1.00, 1.24, 1.65, 2.01, 2.24, 2.12, 1.97, 1.73, 1.44, 1.48, 1.45,
1.27, 1.26, 1.19, 1.04, 1.10, 0.87, 0.86, 0.89, 0.97)
test_that("Compare results with RZ-2018", {
# Estimate local projections
results_nl_iv <- lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = exog_data,
lags_exog = 4,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_logistic = TRUE,
lag_switching = TRUE,
use_hp = 0,
lambda = NaN,
gamma = 3,
num_cores = 1)
s1_results <- round(results_nl_iv$irf_s1_mean[1, ], 2)
s2_results <- round(results_nl_iv$irf_s2_mean[1, ], 2)
testthat::expect_equal(rz_s1_results, s1_results)
testthat::expect_equal(rz_s2_results, s2_results)
})
test_that("Test that cumul_multiplier works", {
# Load package data
ag_data <- ag_data
sample_start <- 7
sample_end <- dim(ag_data)[1]
# Endogenous data
endog_data <- ag_data[sample_start:sample_end,3:5]
# 'Instrument' variable
instrument <- as.data.frame(ag_data$Gov[sample_start:sample_end])
testthat::expect_error(lp_lin_iv(endog_data,
shock = instrument,
cumul_mult = TRUE,
lags_endog_lin = 4,
exog_data = as.data.frame(rnorm(length(instrument[, 1]))),
lags_exog = 2,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = 4,
trend = 2,
confint = 1,
hor = 12,
num_cores = 1),
NA)
})
test_that("Test whether cumul_mult is only used for fixed lag lengths", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
cumul_mult = TRUE,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 3,
trend = 0,
confint = 2,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'The option cumul_mult = TRUE only works for a fixed number of lags.', fixed = TRUE)
})
AdaemmerP/lpirfs documentation built on July 27, 2023, 6:15 p.m.
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# Load package data
ag_data <- ag_data
sample_start <- 7
sample_end <- dim(ag_data)[1]
# Endogenous data
endog_data <- ag_data[sample_start:sample_end,3:5]
# 'Instrument' variable
instrument <- as.data.frame(ag_data$Gov[sample_start:sample_end])
# Choose the 7-quarter moving average growth rate as switching variable.
# and adjust it to have suffiently long recession periods.
switching_variable <- ag_data$GDP_MA[sample_start:sample_end] - 0.8
test_that("Test whether endogenous data is a data.frame", {
endog_data <- as.matrix(endog_data)
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = 0,
lambda = NaN,
gamma = 3,
num_cores = 1),
'The endogenous data has to be a data.frame.', fixed = TRUE)
})
test_that("Test whether trend is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = NULL,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = 0,
lambda = NaN,
gamma = 3,
num_cores = 1),
'Please specify whether and which type of trend to include.', fixed = TRUE)
})
test_that("Test whether switching variable is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = NULL,
use_hp = 0,
lambda = NaN,
gamma = 3,
num_cores = 1),
'Please provide a switching variable.', fixed = TRUE)
})
test_that("Test whether use_hp is set", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = NULL,
lambda = NaN,
gamma = 3,
num_cores = 1),
'Please specify whether to use the HP-filter for the switching variable.', fixed = TRUE)
})
test_that("Test whetherlambda is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = NULL,
gamma = 3,
num_cores = 1),
'Please specify lambda for the HP-filter.', fixed = TRUE)
})
test_that("Test whether gamma is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = NULL,
num_cores = 1),
'Please specify gamma for the transition function.', fixed = TRUE)
})
test_that("Test whether width for confidence bands is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = NULL,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'Please specify a value for the width of the confidence bands.', fixed = TRUE)
})
test_that("Test whether number of horizons is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 2,
hor = NULL,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'Please specify the number of horizons.', fixed = TRUE)
})
test_that("Test whether lag length criterion is correctly spelled", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIP',
max_lags = 4,
trend = 0,
confint = 2,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'Possible lag length criteria are AICc, AIC or BIC or NaN if lag length is specified.', fixed = TRUE)
})
test_that("Test whether lags criterion and fixed number of lags for nonlinear model is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = NULL,
trend = 0,
confint = 2,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'You can not provide a lag criterion (AICc, AIC or BIC) and a fixed number of lags.', fixed = TRUE)
})
test_that("Test whether maximum number of lags is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = NaN,
trend = 0,
confint = 2,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'Please provide a maximum number of lags for the lag length criterion.', fixed = TRUE)
})
test_that("Test whether number of horizons is positive", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = 0,
confint = 2,
hor = -1,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'The number of horizons has to be an integer and > 0.', fixed = TRUE)
})
test_that("Test whether trend is correctly specified", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = -1,
confint = 2,
hor = 12,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'For trend please set 0 = no trend, 1 = trend, 2 = trend and quadratic trend.', fixed = TRUE)
})
test_that("Test whether width of confidence bands is correctly specified", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = 1,
confint = -2,
hor = 12,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'The width of the confidence bands has to be >=0.', fixed = TRUE)
})
test_that("Test whether gamma is negative number", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = 1,
confint = 2,
hor = 12,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = -3,
num_cores = 1),
'Gamma has to be a positive number.', fixed = TRUE)
})
test_that("Test that data is correctly specified when lag length criterion is given", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = NaN,
shock = instrument,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 4,
trend = 2,
confint = 2,
hor = 12,
switching = switching_variable,
use_logistic = FALSE,
lag_switching = TRUE,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
NA)
})
# This example replicates results from the Supplementary Appendix
# by Ramey and Zubairy (2018), based on results from their provided
# Matlab code. The results evaluate findings from Auerbach and
# Gorodnichenko (2012) with local projections by Jordá (2005).
# The data and Matlab code is available on \url{https://www.journals.uchicago.edu/doi/10.1086/696277}{JoPE}
# Load and prepare data
# The sample length of RZ-2018 is 1948:III-2008:III
ag_data <- ag_data
sample_start <- 7
sample_end <- dim(ag_data)[1]
endog_data <- ag_data[sample_start:sample_end, 3:5]
# Choose instrument
instrument <- as.data.frame(ag_data$Gov_shock_mean[sample_start:sample_end])
# Choose exogenous data
exog_data <- as.data.frame(ag_data$GDP_MA[sample_start:sample_end])
# Choose exogenous data
switching_variable <- as.data.frame(ag_data$GDP_MA[sample_start:sample_end]) - 0.8
# These results are taken from the available Matlab code by Ramey and Zubairy (2018)
# They coresspond to row 2 and 3 in table 'regg' from the Matlab output
rz_s1_results <- c(1.00, 1.02, 0.78, 0.60, 0.37, 0.12, 0.04, -0.09, 0.04, -0.07, -0.21,
-0.30, -0.28, -0.42, -0.29, -0.23, 0.02, 0.11, 0.13, -0.01)
rz_s2_results <- c(1.00, 1.24, 1.65, 2.01, 2.24, 2.12, 1.97, 1.73, 1.44, 1.48, 1.45,
1.27, 1.26, 1.19, 1.04, 1.10, 0.87, 0.86, 0.89, 0.97)
test_that("Compare results with RZ-2018", {
# Estimate local projections
results_nl_iv <- lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
exog_data = exog_data,
lags_exog = 4,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = NaN,
trend = 0,
confint = 1.96,
hor = 20,
switching = switching_variable,
use_logistic = TRUE,
lag_switching = TRUE,
use_hp = 0,
lambda = NaN,
gamma = 3,
num_cores = 1)
s1_results <- round(results_nl_iv$irf_s1_mean[1, ], 2)
s2_results <- round(results_nl_iv$irf_s2_mean[1, ], 2)
testthat::expect_equal(rz_s1_results, s1_results)
testthat::expect_equal(rz_s2_results, s2_results)
})
test_that("Test that cumul_multiplier works", {
# Load package data
ag_data <- ag_data
sample_start <- 7
sample_end <- dim(ag_data)[1]
# Endogenous data
endog_data <- ag_data[sample_start:sample_end,3:5]
# 'Instrument' variable
instrument <- as.data.frame(ag_data$Gov[sample_start:sample_end])
testthat::expect_error(lp_lin_iv(endog_data,
shock = instrument,
cumul_mult = TRUE,
lags_endog_lin = 4,
exog_data = as.data.frame(rnorm(length(instrument[, 1]))),
lags_exog = 2,
contemp_data = NULL,
lags_criterion = NaN,
max_lags = 4,
trend = 2,
confint = 1,
hor = 12,
num_cores = 1),
NA)
})
test_that("Test whether cumul_mult is only used for fixed lag lengths", {
testthat::expect_error(lp_nl_iv(endog_data,
lags_endog_nl = 3,
shock = instrument,
cumul_mult = TRUE,
exog_data = NULL,
lags_exog = NULL,
contemp_data = NULL,
lags_criterion = 'AIC',
max_lags = 3,
trend = 0,
confint = 2,
hor = 20,
switching = switching_variable,
use_hp = TRUE,
lambda = 1600,
gamma = 3,
num_cores = 1),
'The option cumul_mult = TRUE only works for a fixed number of lags.', fixed = TRUE)
})
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