Table 4 Error correction representation...

Table 4

Error correction representation for the selected ARDL model, dependent variable is ∆ lnY_t

Independent variables	Coefficients	Standard error	T-ratio	p-values
C	6.7911	1.4781	4.5945	0.0013
∆lnGDP_t-1	0.4355	0.1283	3.3939	0.0079^c
∆lnPOP_t-2	−2.8214	0.7175	−3.9319	0.0034^c
∆lnS_t-3	−0.0123	0.0058	2.1168	0.0634^c
∆lnE_t-2	0.4244	0.1036	4.0941	0.0027^a
ECT_t-1	−0.2982	0.0650	−4.5861	0.0013^a
Diagnostic tests
LM (2)	0.0267 [0.28]^a
ARCH (1)	0.9449 [0.95]^a
J-B normality	1.8765 [0.39]^a
Ramsey's RESET (2)	0.3985 [0.55]^a

Independent variables	Coefficients	Standard error	T-ratio	p-values
C	6.7911	1.4781	4.5945	0.0013
∆lnGDP_t-1	0.4355	0.1283	3.3939	0.0079^c
∆lnPOP_t-2	−2.8214	0.7175	−3.9319	0.0034^c
∆lnS_t-3	−0.0123	0.0058	2.1168	0.0634^c
∆lnE_t-2	0.4244	0.1036	4.0941	0.0027^a
ECT_t-1	−0.2982	0.0650	−4.5861	0.0013^a
Diagnostic tests
LM (2)	0.0267 [0.28]^a
ARCH (1)	0.9449 [0.95]^a
J-B normality	1.8765 [0.39]^a
Ramsey's RESET (2)	0.3985 [0.55]^a

Note(s): ^a, ^b and ^c indicate significance at 1%, 5% and 10%, respectively. Figures in parenthesis are p-values; LM: the Lagrange multiplier test of residual serial correlation. ARCH: autoregressive conditional heteroscedasticity test of residuals. Heteroscedasticity: this is based on the regression of squared residuals on squared fitted values. Normality is based on a test of skewness and kurtosis of residuals. The White test is a test for heteroscedasticity

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