This article examines the interrelationships between public spending composition and Uganda’s development goals including economic growth and poverty reduction. The authors utilize a dynamic computable general equilibrium model to study these interrelationships. These results demonstrate that public spending composition does indeed influence economic growth and poverty reduction. In particular, the authors show that improved public sector efficiency coupled with reallocation of public expenditure away from the unproductive sectors such as public administration and security to the productive sectors including agriculture, energy, water, and health leads to higher gross domestic product growth rates and accelerates poverty reduction. Moreover, the rate of poverty reduction is faster in rural households relative to the urban households. A major contribution of this article is that investments in agriculture, particularly with a view to promoting value addition and investing in complementary infrastructure (e.g., roads and affordable energy), contribute to higher economic growth rates and also accelerate the rate of poverty reduction.
This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate.There is strong evidence that interest rates and bond yield movements exhibit both stochastic volatility and unanticipated jumps. The presence of frequent jumps makes it natural to ask whether there is a premium for jump risk embedded in observed bond yields. This paper identifies a class of jump-diffusion models that are successful in approximating the term structure of interest rates of emerging markets. The parameters of the term structure of interest rates are reconciled with the associated bond yields by estimating the volatility and jump risk premia in highly volatile markets. Using the simulated method of moments (SMM), results suggest that all variants of models which do not take into account stochastic volatility and unanticipated jumps cannot generate the non-normalities consistent with the observed interest rates. Jumps occur (8,10) times a year in Argentina and Brazil, respectively. The size and variance of these jumps is also of statistical significance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.