Examining the Relationship between Total Factor Productivity and Crime Rate: Evidence from US Courts, 1960-2011

  • Hande Emin BENLİ Faculty of Management, Golbası, Ankara, Turkey
  • Erman BENLİ Faculty of Law, Social Sciences University of Ankara, Turkey

Abstract

Following the literature, undesirable attitudes affect productivity and growth negatively. Societal attitudes such as criminal and violent behavior are the important and ignored long-run determinants of total factor productivity. This paper aims to examine the relationship between total factor productivity and crime rate in U.S. for the period 1960-2011 by using production function approach. FM-OLS method is employed to analyze this long-run relationship. Productivity equation also analyzes the effect of unemployment rate and inflation rate to total factor productivity. The empirical results indicate that unemployment rate has no meaningful relationship with total factor productivity while inflation rate has a negative impact on this long-run growth indicator. Suitable with the aim and expectations of this study, the main empirical finding is the negative impact of crime rate on total factor productivity.

References

[1] Anderson, D.A. 1999. The Aggregate Burden of Crime. Journal of Law and Economics, 42(2): 611-642.
[2] Asteriou, D., and Hall, S.G. 2007. Applied Econometrics. New York: Palgrave Macmillan.
[3] Becker, G.S. 1968. Crime and Punishment: An Economic Approach. The journal of Political Economy, 76(2): 169-217.
[4] Benhabib, J., and Spiegel, M. 1994. The Role Of Human Capital İn Economic Development Evidence From Aggregate Cross-Country Data. Journal of Monetary Economics 34 (2): 143-173.
[5] Bräuninger, M., and Pannenberg, M. 2002. Unemployment and productivity growth: an empirical analysis within an augmented Solow model. Economic Modelling, 19(1): 105-120.
[6] Cardenas, M. 2007. Economic Growth in Colombia: A reversal of ‘fortune’?. Working Papers Series Documentos de Trabajo: 1-36.
[7] Feldstein, M. 1982. Inflation, Tax Rules and Investment: Some Econometric Evidence. Econometrica, 50: 825-862.
[8] Fischer, S. 1993. The Role of Macroeconomic Factors in Growth. Journal of Monetary Economics, 32(3): 485-512.
[9] Gordon, R.J., and Baily, M. 1993. The Jobless Recovery: Does it signal a new era of productivity-led growth? Brookings Papers on Economic Activity, 1: 271-316.
[10] Granger, C.W. 1986. Developments in The Study of Cointegrated Economic Variables. Oxford Bulletin of Economics and Statistics 48.(3): 213-228.
[11] Gujarati, D.N. 2009. Temel Ekonometri (Ü, Şenesen, ve G. G. Şenesen, Çeviri). İstanbul: Literatür Yayıcılık Dağıtım Pazarlama (İlk Baskı 1978).
[12] Ismihan, M. 2012. The Political Economy of Productivity Collapses and Accelerations: The Turkish Experience, 1950-2010.
[13] İsmihan, M. 2003. The Role of Politics and İnstability on Public Spending Dynamics and Macroeconomic Performance: Theoryand Evidence from Turkey, PhD thesis. Middle East Technical University, Ankara.
[14] İsmihan, M. 2009. Chroni Instability and Potential Growth Rate: The Turkish Experience, 1960-2006. Dokuz Eylül University. Journal of Faculty of Economics and Administrative Sciences, Vol. 24 (1): 73 -91.
[15] İsmihan, M., and Özcan, K. 2006. The Reasons of Growth in Turkish Economy: 1960-2004. İktisat İşletme ve Finans, 241: 74-86.
[16] Johansen, S. 1988. Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12: 231-254.
[17] Jorgenson, D.W, et al. 2011. Information Technology and US Productivity Growth: Evidence from a Prototype Industry Production Account. Journal of Productivity Analysis 36(2): 159-175.
[18] Krugman, P. 1994. Past and Prospective Causes of High Unemployment. Economic Review of the Federal Reserve Bank of Ranses City, Fourth Quarter: 23-44.
[19] Mankiw, G., et. al. 1992. A Contribution to the Empirics of Economic Growth. The Quarterly Journal of Economics: 407-437.
[20] Mayer, J. 2001. Technology Diffusion, Human Capital and Economic Growth in Developing Countries. United Nations Conference on Trade and Development.
[21] McCollister, K.E., et. al. 2010. The Cost of Crime to Society. New Crime-Specific Estimates for policy and program evaluation. Drug and alcohol dependence 108 (1): 98-109.
[22] Obadan, M.I., and Odusola, A.F. 2000. Productivity and unemployment in Nigeria. National Centre for Economics Management and Administration. Ibadan: 1-36.
[23] Peri, G. 2004. Socio-cultural variables and economic success: evidence from Italian provinces 1951–1991. Topics in Macroeconomics, 4: 1–34.
[24] Pinotti, P. 2011. The Economic Consequences of Organized Crimes: Evidence From Southern Italy. Bank of Italy.
[25] Ray, et al. 2009. Crime, Corruption and Institutions. Monash University Discussion Paper, No: 20: 1-52.
[26] Rondán, N., and Chávez, J. 2004. Hıgh Inflatıon, Volatility and Total Factor Productivity. Banco Central De Reserva Del Peru 5: 1-18.
[27] Rudebusch, G., and Wicox, D.W. 1994. Productivity and Inflation: Evidence and Interpretations. Board of Governors of the Federal Reserve System.
[28] World Bank. 2006. Crime, violence and economic development in Brazil: elements for effective public policy, Report No. 36525.
Published
2018-03-31
How to Cite
BENLİ, Hande Emin; BENLİ, Erman. Examining the Relationship between Total Factor Productivity and Crime Rate: Evidence from US Courts, 1960-2011. Journal of Advanced Research in Law and Economics, [S.l.], v. 9, n. 2, p. 409-415, mar. 2018. ISSN 2068-696X. Available at: <https://journals.aserspublishing.eu/jarle/article/view/2460>. Date accessed: 22 dec. 2024. doi: https://doi.org/10.14505//jarle.v9 2(32).05.