Abstract: This paper takes a new approach to understanding the sources of regional growth heterogeneity. I integrate model averaging and decomposition methods to understand how cross-country growth differences arise from differences in explanatory variables versus differences in coefficients. My approach allows the growth of different economies to follow distinct processes and accounts for model uncertainty. I study growth rates between 1975-2014 for 135 countries grouped into 6 regions. My results reject the assumption of homogeneous coefficients that is commonly used in the growth literature. Factors that appear important in explaining growth heterogeneity in one region may not necessarily matter in other regions. Moreover, my findings indicate that regional dummies – commonly used in the literature – are insufficient in controlling for regional parameter and growth heterogeneity.
PDF -->Abstract: This paper examines the foreign aid and economic growth relation using cross-country growth regressions and considers the choice of the measure of aid as a source of model uncertainty using model averaging methods. The preliminary results show that the choice of measurement can have a substantial impact on estimates and on the robustness of these estimates. The paper also aims to examine how the identity of donor countries affects the aid-growth relationship. Additionally, this paper uses decomposition methods to address the issue of parameter heterogeneity.
Kindig, David, Nobles, Jenna, Zidan, Moheb. 2018 “Meeting the Institute of Medicine’s 2030 US Life Expectancy Target”, American Journal of Public Health 108, no. 1 (January 1, 2018): pp. 87-92.