This paper tests a series of prominent hypotheses regarding how institutions, geography, and trade interact to influence income per capita using a novel spatial econometric approach to control for both spillovers among neighboring countries and spatially correlated omitted variables. Simultaneous equations are used to identify alternative channels through which country characteristics might affect income through trade and institutions, and then to test the robustness of those effects. Evidence indicated that both institutions and trade influence growth. Geographical factors such as whether a country is landlocked and its distance to the equator influence income, but only through trade. Data covering 95 countries across the world from 1960 through 2002 was used to construct a pooled dataset of 5-year averages (9 in all) centered on 1960, 1965, and so on through 2000. Both limited and full information estimators, partly based on a generalized moments (GM) estimator for spatial autoregressive coefficients, were used. These allow for spatial error correlation, correlation across equations, and the presence of spatially lagged dependent variables.
A spatial-simultaneous equation approach
International Food Policy Research Institute (IFPRI)