How to Measure Spillover Effects of Public Capital Stock: A Spatial Autoregressive Stochastic Frontier Model

Abstract

This paper aims to investigate spillover effects of public capital stock in a production function model that accounts for spatial dependencies. In many settings, ignoring spatial dependency yields inefficient, biased and inconsistent estimates in cross country panels. Although there are a number of studies that estimate the output elasticity of public capital stock, they suffer from a failure to refine the output elasticity of public capital stock as well as to account for spillover effects of the public capital stock on the production efficiency when such spatial dependencies exist. For this purpose we employ a spatial autoregressive stochastic frontier model and analyze estimates based on a number of specifications of the spatial dependency structure. We use geographic and economic relations to derive our spatial weights matrices. Using data for 21 OECD countries from 1960 to 2001, we estimate a spatial autoregressive stochastic frontier model and derive the mean indirect marginal effects of public capital stock, which are interpreted as spillover effects. We found that spillover effects can be an important factor explaining variations in technical inefficiency across countries as well as in explaining the discrepancies among various levels of output elasticity of public capital stock in traditional production function approaches.