The Impact of Globalization, Demographic, and Economic Development Variables on Entrepreneurship Using the Pooled Mean Group (PMG) Approach (Case Study: Selected Developing Asian Countries)

Abstract

Abstract: Entrepreneurship is regarded as a symbol of effort and success in business affairs, and entrepreneurs are the pioneers of commercial achievement in society. Today, entrepreneurship has emerged as a profession and, like other professions, must be developed and nurtured through specific educational and academic programs based on behavioral and empirical studies. Given the importance of entrepreneurship in the development process of today's world—an era marked by the expansion of international trade and economic globalization—the necessity of addressing entrepreneurship-related issues, especially from an economic perspective, is increasingly recognized. Therefore, the objective of this study is to examine the impact of globalization variables—including export diversification and foreign direct investment (FDI); demographic variables—including labor force and urbanization; and economic development variables—including industrialization and human development—on entrepreneurship in selected developing Asian countries (i.e., those with relatively high Human Development Index) over the period 2006–2023, using the Pooled Mean Group (PMG) approach. The estimation results revealed that the effects of export diversification, foreign direct investment, active population, urbanization, industrialization, and human capital on entrepreneurship in the selected developing Asian countries are positive and statistically significant in both the short and long term. Moreover, the error correction term coefficient in this model was estimated at –0.62 and is statistically significant, indicating the speed of adjustment toward long-run equilibrium. This coefficient suggests that export diversification, foreign direct investment, the active population, urbanization, industrialization, and human capital eliminate 62% of the disequilibria in the model in each period to restore long-run equilibrium. Given that the error correction term is negative and significant, it can be concluded that there exists at least one long-run causal relationship among the variables in the model.