This paper develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA). The proposed approach accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest, and it simultaneously addresses the biases associated with endogenous and omitted variables by incorporating a panel data systems Generalized Method of Moments estimator. Practical applications of the developed methodology are discussed, including testing for the robustness of explanatory variables in the analyses of the determinants of economic growth and poverty.
Despite the liberalization of foreign portfolio investment around the globe since the early 1980s, the home-bias phenomenon is still found to exist. Using a relatively new IMF survey dataset of cross-border equity holdings, this paper tests new structural equations from a consumption-based asset-pricing model on international portfolio holdings. Using of stock data allows us to provide new and clear-cut evidence on the determinants of international portfolio holdings.
This paper examines the dynamic relationship between trade and income. While most economists agree that increased trade leads to an increase in average income, economic theory is ambiguous about the possible effects on the long-run growth rate of the economy. Using a dynamic panel data model, the hypotheses of no long-run effects of trade on income and on income growth are tested explicitly. The possibility of endogeneity is addressed by constructing an instrument for trade by extending Frankel and Romer's (1999) cross-sectional approach to the case of a panel data model. The empirical results indicate that trade has a large and significant effect on the level of income, but the effect on income growth is small and non-robust to model specification.
This paper examines dynamic patterns of investment in Cameroon, Ghana, Kenya, Zambia and Zimbabwe, assessing the consistency of those patterns with different adjustment cost structures. Using survey data on manufactured firms, we document the importance of zero investment episodes and lumpy investment. The proportion of firms experiencing large investment spikes is significant in explaining aggregate manufacturing investment. Taken together, evidence from descriptive statistics, average investment regressions modeling the response to capital imbalance, and transition data analysis indicate that irreversibility is an important factor considered by firms when making investment plans. The picture is not unanimous however, and some explanations for the mixed results are proposed.