How Do Institutions Determine Economic Growth? Evidеnce from Central and Eastern Europe before and during Global Economic Crisis

Abstract

We investigate the influence of institutions on economic growth and the level of income per capita in CEE region, before and during the global economic crisis. We use principal factor component analysis in order to create a more reliable and representative variable that will measure the institutional quality in our regression models, and avoid the multi colinearity, a common statistical weakness for this type of regression models. The results from panel (random and fixed effects) regressions and GMM dynamic panel regression lead to two contrasting insights. The first regression model shows positive and statistically significant correlation between institutions and economic growth, which would imply that the CEE countries that have created a strong institutional capacity during transition and post-transition period have experienced higher economic growth. The second regression model, which refers to the global economic crisis period, shows a negative influence of institutions on economic growth for the same sample of countries. One explanation for this result might be the fact that countries with a higher degree of integration into the EU were also more vulnerable to the global economic crisis.

Globalization and politico‐administrative factor‐driven energy‐growth nexus: A case of South Asian economies

“…Thus, country risk issues of these countries adversely affect economic development. The study's finding of the negative role of CRI on economic development in South Asia is in line with Slaveski and Lazarov (2014); Nguyen et al (2018) and Sekrafi and Sghaier (2018), and contradicted with Mehlum et al (2006), and Sala‐i‐Martin and Subramanian (2013). These studies concluded that CRI's positive and negative magnitudes contribute to fortifying and weakening the state‐owned institutions and their qualities, respectively in the context of developing economies.…”

Essays on international trade, foreign direct investment, and economic growth

“…More importantly, it is argued from the same authors that the smoothing of times series data, results to loss of valuable variation from the dataset, which could assist to ascertain the variables of interest more accurately. It is indicative, that in the case of transition economies, most of the recent empirical studies in the same field, that apply growth dynamic model specifications with GMM estimators, use solely annual data (see, for example, Zeneli, 2015;Fetahi-Vehapi, et al 2015;Slaveski, et al 2014;Raimbaev 2011;Campos and Kinoshita, 2008;Kottaridi and Filippaios, 2015).…”

“…Thus, in a later period of time, other scholars started to apply different institutional proxies. For instance: Beck, and Laeven, (2006);Raimbaev, (2011);Slaveski, et al (2014) applied the World Bank Governance Indicators; while the studies ofEicher and Schreiber (2010);Kottaridi, and Filippaios, (2015); andTrojette (2016) use the International Country Risk Guide (ICRG).Finally, more lately, the studies ofAdigozalov, and Rahimov (2015);Tamilina, and Tamilina, (2014) utilise the Economic Freedom indexes from Heritage Foundation; whileZeneli, (2015);and Tsanana, et al (2016) employ the Transparency International Index.…”