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    • The econometric analysis of this kind should account

    2018-10-22

    The econometric analysis of this kind should account for a number of specific steps. First, a non-stationarity of the time series variables must exist and appropriate panel unit root tests must be performed. Secondly, if the time series are non-stationary, a panel cointegration approach is needed to test if a long-run equilibrium relationship exists between non-stationary variables. Then there is a high probability that the included variables are endogenous so that the models should consider the existence of Granger causality. The following are the steps followed in this paper:
    Data set analysis Unit root tests have been computed under two different specifications, represented by the inclusion of individual effects or individual effects and trends as reported in Table 3. The unit root this explanation cannot be rejected when the variables are taken in levels and any causal inference from the series in levels would therefore be invalid. However, when using the first differences, the null of unit roots is strongly rejected at the 1% significance level for all series. Therefore, it is concluded that all the series are non-stationary and integrated of order one. This finding is confirmed by all the tests employed in all the three alternative country samples that are under examination. The variables properties need to avoid the possibility of spurious regressions. In order to assess the stationary of the variables employed, this paper employs five different unit root tests including LLC׳s test, IPS-W-statistic, ADF-Fisher Chi-square, and PP-Fisher Chi-square tests. The results of these tests are reported in Table 3 indicating the statistics significantly of the variables, as they are stationary at the level values especially for the LLC׳s test at the 10%. An analysis of cointegration on multivariate models including economic growth for the three group of countries, which strongly supports the existence of a long-run relationship demonstrating that the inclusion of the relation between economic growth and entrepreneurial activities represented in the firm density and to reinforce the statistical robustness of the linkages between the variables are examined here. Tests conducted on the period 2004–2008 for multivariate models were with full heterogeneity results are presented in Table 4. The panel cointegration tests revealed the existence of a long-run co integrating relationship between the economic and the energy dimensions in all the enrolment to secondary schools, research and development, ICT goods exports, trade and pricing policy in the innovative countries.
    Empirical results Empirical results provide the answer for the first question showing the direct and significant relation of entrepreneurs on economic growth and trade. Using panel fixed effects to test for main variables affecting the firm density, results for the countries under study presented in Table 5 shows the positive significant relationships between ED and economic growth with the level of significance at 1%. The sign of the coefficients estimated support previous literature and previous empirical studies. In this study economic growth effect is more in the innovative stage than efficiency stage countries, as estimates of the coefficient of economic growth is (0.1) while efficiency stage countries estimates is (0.02) reflecting the relative contribution of ED on economic growth. In addition, the trade and entry density shows a positive and significant relationship, as estimates of the coefficient of trade is (0.13) in innovative stage countries while it is (0.05) in efficiency stage explaining the effect of ED on trade. Future more, taxes have a negative impact on entry density in innovate drive countries but it is insignificant, while efficiency driven countries it provide negative and significant relation at 1%. This reflects the sensitivity of each group to the tax policy as in efficiency driven countries tries to increase investment and provide more incentives.