Empirics of health-aid,education and infant mortality: a semiparametric study

The present article uses semiparametric regression to capture the impact of foreign-aid given for health purposes on the Infant Mortality Rate (IMR) of poor developing countries, after controlling for other covariates. We also investigate whether education (general awareness) helps lower IMR directly or helps improve effectiveness of health-aid in reducing IMR. In addition, the study investigates whether various disaggregated components of health-aid (for example, aid that goes for infectious disease control or nutrition) help lower IMR. We find that although adult education (awareness) always lowers IMR, the overall effect of health-aid remains insignificant. Our conclusion is robust to various disaggregated components of health-aid as well. We also check if health-aid has improved prenatal care for expecting mothers but our conclusion regarding the overall ineffectiveness of aid remains unchanged. Interestingly, we find that total health-aid as well as nutrition aid may lower IMR only after education exceeds a threshold level – a new angle that has not been explicitly explored before. We also find interesting role of education in making the aid more effective for prenatal care. Our semiparametric nonlinear estimation strategy helps us unravel certain interesting thresholds and facts which cannot be captured in a linear parametric estimation framework.     

Feasible Estimation of Nonparametric Generalized Random Effect Model: An Application

This paper considers some feasible estimator for nonparametric random effect panel data model when there are more than one cross section component. A brief discussion about the consistency of the estimator is also included. The paper also discusses an interesting application related to capita-labor ratio and its effect on factor share in a neo-classical set up.

     

Aid,Policies, and Growth in Developing Countries: A New Look at the Empirics

The relationship between foreign aid and economic growth has been the subject of much controversy. A recent theme suggesting that aid promotes growth, but only in a good policy environment has ratcheted up that debate. In this paper, we assess the importance of policy and aid in generating growth when the aid, policy, and growth relationship is nonlinear. This allows us to examine the varying effects of aid and policy in different data segments, which we do without imposing any particular structure on the underlying relationship. We find that policy is an important determinant of growth. We also find partial corroboration of the view that aid is growth enhancing in a good policy environment, and some evidence of diminishing returns to aid. These findings suggest that nonlinearities if not appropriately addressed fail to capture the detailed underlying dynamics and thereby mask some key features of the aid-policy-growth relationship.     

Semiparametric binary regression models under shape constraints with an application to Indian schooling data

We consider estimation of the regression function in a semiparametric binary regression model defined through an appropriate link function (with emphasis on the logistic link) using likelihood-ratio based inversion. The dichotomous response variable Δ$\Delta$ is influenced by a set of covariates that can be partitioned as (X,Z)$(X,Z)$ where Z$Z$ (real valued) is the covariate of primary interest and X$X$ (vector valued) denotes a set of control variables. For any fixed X$X$, the conditional probability of the event of interest (Δ=1$\Delta =1$) is assumed to be a non-decreasing function of Z$Z$. The effect of the control variables is captured by a regression parameter β$\beta$. We show that the baseline conditional probability function (corresponding to X=0$X=0$) can be estimated by isotonic regression procedures and develop a likelihood ratio based method for constructing asymptotic confidence intervals for the conditional probability function (the regression function) that avoids the need to estimate nuisance parameters. Interestingly enough, the calibration of the likelihood ratio based confidence sets for the regression function no longer involves the usual χ²${\chi }^2$ quantiles, but those of the distribution of a new random variable that can be characterized as a functional of convex minorants of Brownian motion with quadratic drift. Confidence sets for the regression parameter β$\beta$ can however be constructed using asymptotically χ²${\chi }^2$ likelihood ratio statistics. The finite sample performance of the methods are assessed via a simulation study. The techniques of the paper are applied to data sets on primary school attendance among children belonging to different socio-economic groups in rural India.     

Do Patent Protection and Technology Transfer Facilitate R&D in Developed and Emerging Countries? A Semiparametric Study

This paper examines if patent protection and technology transfer facilitate R&D in a sample that includes both developed and emerging countries. A semiparametric model is used to estimate the relevant parameters using country level data from 21 countries, of which six are emerging, for the period 1981–1997. The results suggest thresholds in patent protection and technology transfer: patent protection has a positive effect which weakens at high levels of protection, and FDI has a positive effect only if the country depends heavily on FDI.

Nonparametric Sharpe Ratio

Sharpe ratio is a widely accepted tool for comparing the portfolio performance. In this paper we have proposed a nonparametric measure of the Sharpe rule. The statistical properties of this nonparametric measure and the standard Sharpe ratio are then developed under both normality and non-normality of observations. Further thebias corrected measures are given. An empirical application is also provided.