Spatial correlation robust inference with Errors in Location or Distance

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.

Spatial Correlation Robust Inference with Errors in Location or Distance

This paper presents results from a Monte Carlo study concerning inference with spatially dependent data. We investigate the impact of location/distance measurement errors upon the accuracy of parametric and nonparametric estimators of asymptotic variances. Nonparametric estimators are quite robust to such errors, method of moments estimators perform surprisingly well, and MLE estimators are very poor. We also present and evaluate a specification test based on a parametric bootstrap that has good power properties for the types of measurement error we consider.

Social Networks in Ghana

In this chapter we examine social networks among farmers in a developing country. We use detailed data on economic activities and social interactions between people living in four study villages in Ghana. It is clear that economic development in this region is being shaped by the networks of information, capital and influence that permeate these communities. This chapter explores the determinants of these important economic networks. We first describe the patterns of information, capital, labor and land transaction connections that are apparent in these villages. We then discuss the interconnections between the various economic networks. We relate the functional economic networks to more fundamental social relationships between people in a reduced form analysis. Finally, we propose an equilibrium model of multi-dimensional network formation that can provide a foundation for further data collection and empirical research.Endogenous Networks, Informal Credit, Social Learning

Learning About a New Technology: Pineapple in Ghana

The University Archives has determined that this item is of continuing value to OSU's history.Timothy G. Conley is an Economist who researches Applied and Theoretical Econometrics, Development, and Empirical Industrial Organization. Conley received his Ph.D. in Economics from the University of Chicago, where he is currently Assistant Professor of Econometrics and Statistics at the University of Chicago Graduate School of Business. He was formerly Assistant Professor of Economics at Northwestern University.Ohio State University. Mershon Center for International Security Studiesweb page announcemen

Learning about a new technology: pineapple in Ghana

This paper investigates the role of social learning in the diffusion of a new agricultural technology in Ghana. We use unique data on farmers' communication patterns to define each individual's information neighborhood, the set of others from whom he might learn. Our empirical strategy is to test whether farmers adjust their inputs to align with those of their information neighbors who were surprisingly successful in previous periods. We present evidence that farmers adopt surprisingly successful neighbors' practices, conditional on many potentially confounding factors including common growing conditions, credit arrangements, clan membership, and religion. The relationship of these input adjustments to experience further supports their interpretation as resulting from social learning. In addition, we apply our methods to input choices for another crop with known technology and they correctly indicate an absence of social learning effects.

Learning About a New Technology: Pineapple in Ghana

This paper investigates the role of social learning in the diffusion of a new agricultural technology in Ghana. We use unique data on farmers’ communication patterns to define each individual’s information neighborhood, the set of others from whom he might learn. Our empirical strategy is to test whether farmers adjust their inputs to align with those of their information neighbors who were surprisingly successful in previous periods. We present evidence that farmers adopt surprisingly successful neighbors’ practices, conditional on many potentially confounding factors including common growing conditions, credit arrangements, clan membership, and religion. The relationship of these input adjustments to experience further supports their interpretation as resulting from social learning. In addition, we apply our methods to input choices for another crop with known technology and they correctly indicate an absence of social learning effects.Social Learning, Technology, Innovation