Under the assumption of no unmeasured confounders, a large literature exists on methods that can be used to estimating average treatment effects (ATE) from observational data and that spans regression models, propensity score adjustments using stratification, weighting or regression and even the...

This paper examines the relationship between health aid and infant mortality, using data from in total 135 countries (for the purposes of this study, developing countries), between 1975 and 2010. Utilizing both conventional Instrumental Variable and System GMM approaches, a tentative conclusion...

Instrumental variables methods (IV) are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of instrumental variables if treatment...

Los modelos de diferencias en diferencias (DD) son posiblemente la especificación econométrica más utilizada para analizar el efecto o impacto de un cambio sobre un sistema. La mayoría de sus aplicaciones se basan en datos de unidades o sujetos, por lo que puede considerarse a la...

Rural development is a veritable tool for fighting poverty and achieving economic prosperity at the grassroots level. The concept of rural development embraced by most countries connotes a process through which rural poverty is alleviated by sustained increases in the productivity and incomes of...

This paper derives some exact power properties of tests for spatial autocorrelation in the context of a linear regression model. In particular, we characterize the circumstances in which the power vanishes as the autocorrelation increases, thus extending the work of Krämer (2005, Journal of...

Propensity Score Matching (PSM) has become a popular approach to estimation of causal effects. It relies on the assumption that selection into a treatment can be explained purely in terms of observable characteristics (the “unconfoundedness assumption”) and on the property that balancing on...

The purpose of this paper is to show the capacity of a new non-parametric test based on symbolic entropy and symbolic dynamics to deal with the detection of linear and non-linear spatial causality. The good performance of the new test in detecting spatial causality and causal weighting matrix is...

This study is conducted to determine the factors affecting magnitude of poor families in the Philippines and measure the effect of the variables presented. The model was estimated using the Ordinary Least Square (OLS) procedure and cross sectional data set consisting of the 16 regions in the...

The paper introduces for the most frequently used three-dimensional panel data sets several random effects model specifications. It derives appropriate estimation methods for the balanced and unbalanced cases. An application is also presented where the bilateral trade of 20 EU countries is...