This paper considers the problem of estimating a local interaction model defined at the level of individual agents, in the absence of perfect information about agent locations in the relevant socio-economic space. We consider two types of data limitations: one in which individual locations are...

This paper presents results from a Monte Carlo study concerning inference with spatially dependent data. It investigates the impact of location/distance measurement errors upon the accuracy of parametric and nonparametric estimators of asymptotic variances.

This paper examines whether spillovers from local market human capital are important in explaining the distribution of productivity across Malaysia. We develop an empirical method for describing local human capital distributions based on the idea that spillovers are limited in scope by costs of...

In this paper we develop new estimation methods for identifying causal effects based on the idea that the amount of selection on the observed explanatory variables in a model provides a guide to the amount of selection on the unobservables. Our approach involves the use of factor model as a way...

Difference in differences methods have become very popular in applied work. These models are typically quite easy to implement and to interpret. However, performing inference with these models is not. This paper addresses one particular aspect that is likely to be very important in most...