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858 Arshad Hasan and Safdar Butt Table 2a: Autoregressive Distributed Lag Estimates ARDL(1,1,0,0,0) selected based on Schwarz Bayesian Criterion Independent variables Coefficient S. E t Statistics P value Ln GDPt-I 0.5487 0.2005 2.7363 0.01 lnTTt 0.2830 0.1500 1.8862 0.07 lnTTt-1 - 0.2688 0.1190 -2.2584 0.03 lnTDt -0.0810 0.1931 -0.4643 0.65 Edut 0.0032 0.0405 0.0785 0.94 lnLFt 1.2120 0.4637 2.6141 0.01 C 1.2949 0.8583 Table 2b: R-Squared 0.99 R-Bar-Squared 0.98 S.E. of Regression 0.06 S.D. of Dependent Variable 0.51 DW-statistic 2.37 F-stat. F(6, 22) 306.95 significance [.000] Table 2 (a & b) indicates that total trade and labor force has significant relationship with economic growth whereas total debt and education have insignificant relationship. The value of R-Bar- Squared is 0.98 which indicates a high degree of correlation among variables. F statistics is also significant at 1% which indicates overall goodness of fit. The test for the presence of long-run relationship amongst the variables of equation (1) highlights the following results. Bahmani-Oskooee and Bohal (2000) have shown that the results of this first step are sensitive to lag length selected in equation (2). As we are using annual data so a shorter lag length is considered. Table 3: ARDL (1,1,0,0,0) Model Long Run Results Dependent variable log (GDP) Independent variables Coefficient Standard Error t value P value LTT 0.0313 0.2344 0.1333 0.89 LLF 2.6859 0.8924 3.0098 0.00 LED -0.1987 0.4316 -0.4603 0.65 Edu 0.0070 0.0894 0.0786 0.93 C 2.8694 1.6401 1.7495 0.09 A careful examination of results in Table 3 reveals that Labor Force has significant long term relationship with economic growth. External debt has insignificant negative association with economic growth. Similarly total trade and education have no significant impact in economic growth. Short-run dynamics of the relationship has also been examined by employing ARDL error correction representation. Estimates of error correction representation of ARDL model are given table below
Role of Trade, External Debt, Labor Force and Education in Economic Growth Empirical Evidence from Pakistan by using ARDL Approach 859 Table 4: Error Correction Representation for the ARDL Model ARDL (1,1,0,0,0) Independent variables Coefficient S .E t Statistics P value Δ lnTT 0.2829 0.1500 1.8862 0.07 Δ lnLF 1.2120 0.4636 2.6141 0.02 Δ lnTD -0.8966 0.1931 0.4643 0.64 Δ Edu 0.0031 0.0405 0.0784 0.93 ECM(-1) -0.4512 0.2005 2.2502 0.03 R-Squared .39 S.E. of Regression .06 S.D. of Dependent Variable .07 DW-statistic 2.37 F-stat. F(5, 23) 2.87 significance [.037] The ECM equation is given as ECM = Ln GDPt -.031266* lnTT t +0.19869* lnTD t + 0.0070366* Edu t -2.6859* lnLF t - 2.8694*C Examination of error correction model in Table 4 shows that labor force has the strongest effect on economic growth in the short run which is followed by total trade. The short-run effect of total external debt on economic growth in Pakistan is weak and statistically insignificant at even 10% level of significance. The coefficient of ECM term has correct sign and significant at 10 %. It confirms the presence of relationship between the variables. The Coefficient of the ECM term suggests that adjustment process is quite fast and 45% of the previous year’s disequilibrium in economic growth from its equilibrium path will be corrected in the current year. Thus, the evidence presented in this section suggests that economic growth in Pakistan is mainly determined by fluctuations in labor force , and trade both in the short run and the long run. Total debt is not an important determinant of economic growth either in the short-run or the long-run. The CUSUM and CUSUMSQ plots to check the stability of short run and long run coefficients in the ARDL error correction model are given below in figure 1: 1.5 1.0 0.5 0.0 Figure 1: Plot of Cumulative Sum of Squares of Recursive Residuals -0.5 1977 1982 1987 1992 1997 2002 2005 The straight lines represent critical bounds at 5% significance level
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