Abstract
Despite its paramount importance in the empirical growth literature, productivity convergence analysis has three problems that have yet to be resolved: (1) little attempt has been made to explore the hierarchical structure of industry-level datasets; (2) industry-level technology heterogeneity has largely been ignored; and (3) cross-sectional dependence has rarely been allowed for. This paper aims to address these three problems within a hierarchical panel data framework. We propose an estimation procedure and then derive the corresponding asymptotic theory. Finally, we apply the framework to a dataset of 23 manufacturing industries from a wide range of countries over the period 1963-2018. Our results show that both the manufacturing industry as a whole and individual manufacturing industries at the ISIC two-digit level exhibit strong conditional convergence in labour productivity, but not unconditional convergence. In addition, our results show that both global and industry-specific shocks are important in explaining the convergence behaviours of the manufacturing industries.
Highlights
Starting with the seminal studies by Baumol (1986), Barro (1991), and Barro and Sala-i Martin (1992), numerous studies have been devoted to testing whether income or productivity of poorer economies are converging to those of richer economies
We have identified one global factor that affects the growth in labour productivity of every individual manufacturing industry
Income and productivity convergence has long been a question of great interest in the economic growth literature
Summary
Starting with the seminal studies by Baumol (1986), Barro (1991), and Barro and Sala-i Martin (1992), numerous studies have been devoted to testing whether income or productivity of poorer economies are converging to those of richer economies. A substantial body of the literature (e.g., Mankiw et al, 1992; de la Fuente, 1999) uses aggregate-level data and focus exclusively on aggregate-level cross-country variations and attributes As a result, they ignore industry-level attributes in influencing the convergence of aggregatelevel income or productivity. They ignore industry-level attributes in influencing the convergence of aggregatelevel income or productivity Another strand of the literature (e.g., Bernard and Jones, 1996) uses industry-level data and focus exclusively on industry-level crosscountry variations and attributes by running a separate regression for each industry. These latter studies ignore aggregate-level attributes in influencing the convergence of industry-level income or productivity
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