Does Fiscal Decentralization in Indonesia have Asymmetrical Information?: Principal-Agent Model, Primal-Dual, and a Neural Network Analysis

Kun Haribowo

Abstract


In reality, subnational governments suffer from moral hazard, creating uncertainty which, in turn, causes economic inefficiency. The behavior of subnational governments cannot be observed by the central government. An analysis which takes into account this phenomenon is therefore needed. Decentralization implies delegating authority from central government to subnational governments. In this study, the subnational government is represented by the local government. This study utilizes a model of principal-agent. The central government acts as a principal who delegates fiscal authority to subnational governments who act as agents. By applying principal-agent model, we can use the primal-dual approach to analyze both revenue and expenditure assignment associated with the tax effort of the subnational governments. The result from artificial neural network approach shows that asymmetric information between central and subnational governments exists in Indonesia.

Keywords: Artificial Neural Network, Fiscal Decentralization, Local Tax Effort, Primal-Dual, Principal-Agent.


Full Text:

PDF

References


Bharat, A. et al. (1997). Performance evaluation of neural network decision models. Journal of Management Information Systems, 14(2), 201-216.

Brodjonegoro, B. & Martinez-Marquez, J. (2002). An Analysis of Indonesia’s transfer system: recent performance and future prospect. Working Paper 02-13, International Studies Program, Andrew Young School of Policy Studies, 1-51.

Binner, J. M. et al. (2004). Tools for non-linear time series forecasting in economics an empirical comparison of regime switching vector autoregressive models and recurrent neural networks. Applications of Artificial Intelligence in Finance and Economics, Advances in Econometrics, 19, 71–91.

Chen, J. (2005). Neural network applications in agricultural economics. Dissertation. Kentucky, United States: University of Kentucky.

Eisenhardt, K. M. (1989). Agent theory: an assessment and review. The Academy of Management Review, 14(1).

Fadliya & McLeod, R. H. (2010). Fiscal transfers to regional governments in Indonesia. Working Papers in Trade and Development, Arndt-Corden Department of Economics Crawford School of Economics and Government ANU College of Asia and the Pacific, 1-35.

Ferazi, G. (2000). Using the "F" word: federalism in Indonesia’s decentralization discourse. Publius, 30(2), 63-85.

Furubotn, E. G. & Richter, R. (1998). Institutions and economic theory. Michigan, United States: The University of Michigan Press.

Gramlich, E. M. (1990). The economics of fiscal federalism and its reform: the changing face of fiscal federalism (Swartz & Peck edition). New York, United States: M. E. Sharpe, Inc.

Hill, M. O. & Remus, W. (1996). Neural network models for time series. Management Science, 42(7), 1082-1092.

Lee, D. R., Johnson, W. R., & Philip, J. G. (2008). Public budgeting systems. Massachusetts, United States: Jones and Bartlett Publishers.

Martinez-Vasquez, J. (2002). Asymmetric federalism in the russian federation: cure or poison?. International Study Program Working Paper.

Mirmirani, S. & Li, H. C. (2004). VAR and neural networks with genetic algorithm in forecasting price of oil: applications of artificial intelligence in finance and economics. Advances in Econometrics, 19, 203–223.

Nicholson-Crotty, S. (2009). Fiscal federalism and tax effort in the American states: report 04-2009. Missouri, United States: University of Missouri Columbia, Institute of Public Policy.

Shah, A. (2012). Toward a more transparent, objective, predictable and simpler (TOPS) system of central financing of provincial-local expenditures in Indonesia. Working Paper: The World Bank, East Asia and the Pacific Region Poverty Reduction and Economic Management Unit, 1-31.

Smith, B. (2008). The origins of regional autonomy Indonesia: experts and the marketing of political interests the origins of regional autonomy in Indonesia, experts and the marketing of political interests. Journal of East Asian Studies, 8, 211-234.

Subanar. (2005). Statistical modeling by using neural networks. Mini Symposia, International Conference on Applied Mathematics (ICAM05), Bandung Institute of Technology.

Varian, H. R. (1992). Microeconomic analysis. New York & London: Norton.




DOI: https://doi.org/10.20884/1.erjpe.2019.14.1.1271

Refbacks

  • There are currently no refbacks.


 

Print ISSN : 1907-6827   Online ISSN : 2620-8849

Indexed by :

        

 

Partnership with Professional Association: