Article thumbnail
Location of Repository

Political competition and debt : Evidence from New Zealand local governments

By Bikram Chatterjee, Sukanto Bhattacharya, Grantley Taylor and Brian West

Abstract

Purpose This paper aims to investigate whether the amount of local governments' debt can be predicted by the level of political competition. Design/methodology/approach The study uses the artificial neural network (ANN) to test whether ANN can "learn" from the observed data and make reliable out-of-sample predictions of the target variable value (i.e. a local government's debt level) for given values of the predictor variables. An ANN is a non-parametric prediction tool, that is, not susceptible to the common limitations of regression-based parametric forecasting models, e.g. multi-collinearity and latent non-linear relations. Findings The study finds that "political competition" is a useful predictor of a local government's debt level. Moreover, a positive relationship between political competition and debt level is indicated, i.e. increases in political competition typically leads to increases in a local government's level of debt. Originality/value The study contributes to public sector reporting literature by investigating whether public debt levels can be predicted on the basis of political competition while discounting factors such as "political ideology" and "fragmentation". The findings of the study are consistent with the expectations posited by public choice theory and have implications for public sector auditing, policy and reporting standards, particularly in terms of minimising potential political opportunism

Topics: 1501 Accounting, Auditing and Accountability, 1502 Banking, Finance and Investment, New Zealand, Debt
Publisher: Emerald
Year: 2019
DOI identifier: 10.1108/ARJ-11-2016-0146
OAI identifier:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://doi.org/10.1108/ARJ-11... (external link)
  • http://researchonline.federati... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.