What Exogenous Factors Generate Municipal Inefficiency? An Empirical Investigation of the Determinants of Input Excess in Local Government

Abstract

A substantial empirical literature has investigated the performance of local authorities in a host of countries across the world. While this body of knowledge has made a significant contribution to our understanding of local government performance, including the role played by ‘non-discretionary’ environmental factors, much remains to be done. In an attempt to address some of the shortcomings of extant studies on the determinants of municipal performance, especially in terms of their treatment of environmental factors, in this paper we investigate the technical efficiency of local government in South Australia (SA) by examining input slacks (input excess) in the different municipal services However, in contrast to existing empirical work in the area, which is focused almost exclusively on the direct impact of determinants on efficiency scores, we examine the effects of determinants on input excess, in order to determine which factors stimulate local councils to perform inefficiently, then internalize their influence and filter out unobserved biases via a bootstrapping methodology to evaluate the managerial inefficiency of SA local government. We find that the efficiency of SA local councils is on average 0.734, implying that local councils could potentially improve their performance by 0.267 to reach the full efficiency. After filtering out the influence of environmental factors on inputs slacks and unobserved disturbances with the bootstrapping method, the residual inefficiency can be attributed to managerial inefficiency. Various policy implications are then considered.

Keywords:

• Exogenous factors
• efficiency
• input excess
• local government
• South Australia

Notes

1 As defined by Simar and Wilson (1998, p. 49), ‘bootstrapping is based on the idea of repeatedly simulating the data generating, usually through resampling and applying the original estimator to each simulated sample so that resulting estimates mimic the sampling distribution of the original estimator’.

Additional information

Notes on contributors

Carolyn-Thi Thanh Dung Tran

Carolyn-Thi Thanh Dung Tran is Senior Research Officer at NSW Public Policy Institute, the University of Sydney, Australia. She has written extensively on higher education and local government Local Government Studies, Australian Journal of Public Administration, Public Management Quarterly, Applied Economics, and Asian Economic Journal.

Brian Dollery

Brian Dollery is Professor of Economics at the University of New England in Australia. He has written extensively on local government and recent books include Perspectives on Australian Local Government Reform (2015) and Local Public, Fiscal and Financial Governance: An International Perspective (2020).