Institutional Quality and Economic Growth: A Dynamic Panel Data Analysis of MICs and HICs for 2000–2020

ABSTRACTWe investigate the dynamic impact of institutions on economic growth using a panel dataset of 77 countries, divided into MICs and HICs for the period 2000-2020. We critically examine the available institutional indices and construct three weighted indices from 20 indicators closely related to the meaning of the term ‘institutions’ as the ‘rules of the game’ defined by Douglas North. Next, we use the Generalized Method of Moments (GMM) to show that institutions significantly influence economic growth through investment and trade more than the total factor productivity channel. While the quality of the legal system and property rights and regulatory quality all positively and significantly influence output per capita, output gains from each unit of improvement in the quality of legal systems and protection of private property rights are comparatively higher than gains from a unit of improvement in the regulatory environment. An average MIC gains relatively more from improving its quality of legal system and property rights, whereas an average HIC benefits relatively more from each unit of improvement in its regulatory environment. The results from the Granger non-causality test demonstrate and unidirectional causality from institutions to economic growth in MICs but no significant causal relationship between institutions and economic growth in HICsKEYWORDS: Institutionsinstitutional qualityproperty rightsregulationseconomic growthtransmission mechanismGMMJEL CLASSIFICATIONS: O43O47 AcknowledgementThis article is drawn from the first author's Ph.D. thesis, titled ‘Essays in Institutions and Economic Development’, completed at South Asian University, New Delhi, India. The authors gratefully acknowledge the useful comments of the referees on earlier versions of the article. The authors are also grateful to Sunil Kumar and Binoy Goswami for their comments and suggestions. The usual disclaimer applies.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The extent to which regulations and bureaucratic procedures restrain entry and reduce competition.2 We dropped a couple of indicators from Area 4 of EFW database that were relevant to our perception of institutions but had extensive missing values. We excluded Area 1 because it is all about the size of the government. We have included a direct independent variable in the model that captures the size of the government. Adding this area to the index would have led to identification issues. Similarly, we left out some variables from Area Three and Area Four, like ‘control of the movement of capital and people,’ ‘Freedom of foreigners to visit,’ ‘capital controls,’ etc., as we believe these indicators do not relate closely to our perception of institutions.3 The index is based on years of schooling and returns to education.4 One-unit increase in institutional quality in the sample of high-income countries is a difference between the rating of a country like the United States 0.78 and South Korea 0.61, or the United Kingdom 0.82 and Latvia 0.65. In the sample of middle-income countries, a one-unit increase in institutional quality is the difference between countries like Indonesia 0.39 and Zambia 0.25, or countries like Israel 0.6 and India 0.46 (see Table B7, ratings for 2020).5 The marginal impact of domestic investment on output per capita is computed at the average rating of institutional quality for each income group.Additional informationNotes on contributorsMirwais ParsaDr Mirwais Parsa is a Research Scholar at the Center for Governance and Markets, University of Pittsburgh. He holds a Ph.D. in economics from South Asian University. His Ph.D. thesis focuses on institutions and economic development. His research interest lies in the areas of macroeconomic theory, institutions and political economy.Soumya DattaDr Soumya Datta is an Associate Professor of Economics at the Faculty of Economics, South Asian University. His research interest lies broadly in the area of macroeconomic theory, non-linear dynamics and complex systems. His current research work focuses on growth cycles, asset price bubbles, models with heterogeneous agents and macroeconomic epidemiological models.