gets_ardl_uecm {ardl.nardl} R Documentation

## General-to-specific approach for the autoregressive distributed lag model

### Description

Adopt the general-to-specific approach to estimate the autoregressive distributed lag model

### Usage

gets_ardl_uecm(x, dep_var, expl_var, p_order = c(2), q_order = c(3),
gets_pval = 0.1, case = 3, F_HC = FALSE, order_l = 5,
graph_save = FALSE)

### Arguments

 x data frame dep_var A character vector. The dependent variable. expl_var Character vector. List of explanatory variable(s) p_order Integer. Maximum number of lags for 'dep_var' q_order Integer. Maximum number of lags for 'expl_var' gets_pval Integer value between 0 and 1 needed for the general-to-specific approach. The default is 0.1 (10 percent significance level). The chosen p-value is the criteria for determining non-significant repressors to be eliminated in a backward elimination path. The final parsimonious model is the best fit model based on the Schwarz information criteria case Positive integer 1 to 5. Default is 3 F_HC Logical (default is FALSE). If TRUE, Heteroscedasticity-Consistent Covariance Matrix Estimation is applied to the model before when estimating F statistic graph_save Logical. If TRUE, display stability plot. Default is FALSE order_l Integer. order for the serial correlation, and heteroscedasticity test

### Value

 Parsimonious_ARDL_fit  Return an estimated general-to-specific ARDL model Parsimonious_ECM_fit  Return an estimated general-to-specific error correction model Summary_ecm_fit  Return the summary of 'Parsimonious_ECM_fit' Parsimonious_ECM_diagnostics_test  Return the diagnostic test for 'Parsimonious_ECM_fit'.The diagnostic tests items are the Breusch-Godfrey test for higher-order serial correlation (BG_SC_lm_test). The Engle (1982) test for conditional heteroscedasticity (LM_ARCH_test). The test for non-normality is that of Jarque and Bera (1980). The RESET null hypothesis adopted implies - including the 2nd - degree terms improve the fit (over the model specified). Ljung and Box (1978) tests for autocorrelation in the residuals cointegration  Return the F statistic, the upper and lower critical values for PSS (2001) bounds test Longrun_relation  The estimated longrun relation from the error correction model

### References

Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflations. Econometrica (50) 987 - 1007

Ljung GM, Box GEP (1978). On a Measure of Lack of Fit in Time Series Models. Biometrika, 65(2), 297 - 303. https://doi.org/10.2307/2335207

Jarque C, Bera A (1980). Efficient Tests for Normality, Homoskedasticity, and Serial Independence. Economics Letters, 6(3), 255 - 259. https://doi.org/10.1016/0165-1765 (80) 90024-5

Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships Journal of applied econometrics, 16(3), 289-326

gets_nardl_uecm ardl_uecm

### Examples

  data(expectation)
out <- gets_ardl_uecm(x = expectation,
dep_var = c('nq_inf_exp'),
expl_var = c('food_inf','nethawkish'),
p_order = c(4),
q_order = c(5,7),
gets_pval = 0.1,
case = 4,
graph_save = FALSE,
F_HC = FALSE,
order_l = 7)
out


[Package ardl.nardl version 1.2.3 Index]