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Cross-country Growth Regressions (cross-country + growth_regression)
Selected AbstractsModel uncertainty in cross-country growth regressionsJOURNAL OF APPLIED ECONOMETRICS, Issue 5 2001Carmen Fernández We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is spread widely among many models, suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results support this claim. In contrast to Levine and Renelt (1992), our results broadly support the more ,optimistic' conclusion of Sala-i-Martin (1997b), namely that some variables are important regressors for explaining cross-country growth patterns. However, care should be taken in the methodology employed. The approach proposed here is firmly grounded in statistical theory and immediately leads to posterior and predictive inference. Copyright © 2001 John Wiley & Sons, Ltd. [source] Does corporate ownership structure matter for economic growth?MANAGERIAL AND DECISION ECONOMICS, Issue 3 2009A cross-country analysis The role of corporations in allocating resources has been of great importance in the debate about the manner in which enterprises should be governed to enhance economic growth. Corporate governance features seem to be central to the dynamics by which successful firms and economies improve their performance over time as well as relative to each other. In this paper we try to clarify the relationship between corporate ownership structure and output growth by using the data of La Porta et al. (J. Finance 1999; LIV: 471,517) on ownership structure of large- and medium-sized corporations in 27 economies. To search for empirical linkages, we use cross-country growth regressions. The evidence provided in the paper suggests that an environment with a higher percentage of directly and indirectly widely held companies and a lower degree of state than private ownership is associated with a higher growth rate of per capita income. We also conclude that a higher degree of institutional investment does not seem to enhance the growth performance of an economy. Copyright © 2008 John Wiley & Sons, Ltd. [source] Resource abundance vs. resource dependence in cross-country growth regressionsOPEC ENERGY REVIEW, Issue 2 2010Annika Kropf Having analysed the macroeconomic performance of large oil exporters, I found that, in many cases, rents from natural resources have been successfully used to enhance economic growth. Nevertheless, adherents of the ,resource curse' seem to have found ample evidence suggesting that resource-abundant countries grow slower than resource-poor countries. A review of empirical research on the ,resource curse' reveals that the variables used were usually proxies for resource dependence. These variables introduce a bias, making less developed economies per se more resource ,abundant' than developed economies. As a consequence, a new variable, not containing any information on a country's stage of development, was introduced. Comparing the variables on resource dependence and resource abundance in a model by Sachs and Warner, resource abundance was not significant. In a new model, resource abundance was even positively correlated with growth. [source] A non-linear sensitivity analysis of cross-country growth regressionsCANADIAN JOURNAL OF ECONOMICS, Issue 3 2000Pantelis Kalaitzidakis We extend the sensitivity analysis of cross-country growth regressions of Levine and Renelt (1992) by introducing a semi-parametric formulation of their regression function. Our results differ from theirs in how certain policy variables affect growth rates. We find that distortion variables, such as the standard deviation of gross domestic credit and inflation and real exchange rate distortions, have a robust negative effect on growth. JEL Classification: O47, C14 Une analyse de sensibilité non-linéaire des régressions de croissance pour divers pays. Les auteurs utilisent une formulation semi-paramétrique des équations de croissance de Levine et Renelt (1992) pour divers pays afin de rendre leur analyse de sensibilité plus compréhensive. Les résultats different de ceux de Levine et Renelt en ce que certaines variables de politique affectent les taux de croissance. On découvre que certains facteurs comme l'écart type du crédit intérieur brut et de l'inflation, et des distorsions des taux de change réels, ont un effet négatif important sur la croissance. [source] |