Halkos, George and Tzeremes, Nickolaos (2011): A conditional full frontier approach for investigating the Averch-Johnson effect.
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This paper applies a probabilistic approach in order to develop conditional and unconditional Data Envelopment Analysis (DEA) models for the measurement of sectors’ input oriented technical and scale efficiency levels for a sample of 23 Greek manufacturing sectors. In order to capture the Averch and Johnson effect (A-J effect), we measure sectors’ efficiency levels conditioned on the number of companies competing within the sectors. Particularly, various DEA models have been applied alongside with bootstrap techniques in order to determine the effect of competition conditions on sectors’ inefficiency levels. Additionally, this study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating the effect of regulations in an industry. The results reveal that sectors with fewer numbers of companies appear to have greater scale and technical inefficiencies due to the existence of the A-J effect.
|Item Type:||MPRA Paper|
|Original Title:||A conditional full frontier approach for investigating the Averch-Johnson effect|
|Keywords:||Averch-Johnson effect; Industry regulations; Manufacturing sectors; Nonparametric analysis|
|Subjects:||L - Industrial Organization > L2 - Firm Objectives, Organization, and Behavior > L25 - Firm Performance: Size, Diversification, and Scope
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General
L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L10 - General
L - Industrial Organization > L5 - Regulation and Industrial Policy > L59 - Other
|Depositing User:||G.E. Halkos|
|Date Deposited:||20. Dec 2011 07:26|
|Last Modified:||19. Feb 2013 10:35|
Averch, H. & Johnson, L.L. (1962). Behavior of the firm under regulatory constraint. American Economic Review, 52(5), 1052-1069.
Bădin, L., Daraio, C. & Simar, L. (2010). Optimal bandwidth selection for conditional efficiency measures: A Data-driven approach. European Journal of Operational Research, 201, 633-640.
Balk, B.M. (2001). Scale efficiency and productivity change. Journal of Productivity Analysis, 15, 159-183.
Banker, R.D., Charnes, A. & Cooper, W.W. (1984). Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30, 1078 – 1092.
Baumol, W.J. & Klevorick, A.K. (1970). Input choices and rate-of-return regulation: An overview of the discussion. Bell Journal of Economics, 1(2), 162-190.
Blank, L. & Mayo, J.W. (2009). Endogenous regulatory constraints and the emergence of hybrid regulation. Review of Industrial Organization, 35, 233-255.
Boles, J.N. (1967). Efficiency squared—efficient computation of efficiency indexes. In: Proceedings of the thirty ninth annual meeting of the western farm economics association, pp 137–142.
Caputo, M.R. & Partovi, M.H. (2002). Reexamination of the A-J effect. Economics Bulletin, 12(10), 1-9.
Cazals, C., Florens, J.P. & Simar, L. (2002). Nonparametric frontier estimation: a robust approach. Journal of Econometrics, 106, 1-25.
Charnes, A., Cooper, W.W. & Rhodes, L.E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429-444.
Christopoulos, D.K. & Tsionas, E.G. (2001). Banking economic efficiency in the deregulation period: results from heteroscedastic stochastic frontier models. Manchester School, 69(6), 656-676.
Coelli, T. J., Rao, D. S. P., O'Donnell, C. J. & Battese, G.E. (2005). An Introduction to Efficiency and Productivity Analysis. Second ed. New York: Springer.
Cooper, W.W. & Lovell, C.A.K. (2011). History lessons. Journal of Productivity Analysis, 36(2), 193-200.
Daraio, C. & Simar, L. (2005). Introducing environmental variables in nonparametric frontier models: A probabilistic approach. Journal of Productivity Analysis, 24(1), 93–121.
Daraio, C. & Simar, L. (2007a). Advanced robust and nonparametric methods in efficiency analysis. Springer Science: New York.
Daraio, C. & Simar, L. (2007b). Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach. Journal of Productivity Analysis, 28, 13-32.
De White, K. & Marques, R.C. (2007). Designing incentives in local public utilities, an international comparison of the drinking water sector. Center for Economic Studies, Discussions Paper Series (DPS) 07.32, Department of Economics, UniversitéCatholique de Louvain.
De White, K. & Verschelde, M. (2010). Estimating and explaining efficiency in a multilevel setting: A robust two-stage approach. TIER working paper series, TIER WP 10/04, Top Institute for Evidence Based Education Research, University of Amsterdam, Maastricht University, University of Groningen.
Debreu, G. (1951). The coefficient of resource utilization. Econometrics, 19(3), 273–292.
Derpins, D., Simar, L. & Tulkensmm H. (1984). Measuring labor efficiency in post offices. In M. Marchand, P. Pestieau & H. Tulkens (Eds.), The performance of public enterprises: Concepts and measurement. Amstredam: North-Holland, pp. 243-267.
Dixon, H. & Easaw, J. (2001). Strategic responses to regulatory policies: What lessons can be learned from the U.K. contract gas market. Review of Industrial Organization, 18, 379-396.
Farrell, M. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society Series A, 120, 253–281.
Førsund, F.R. & Sarafoglou, N. (2002). On the origins of data envelopment analysis. Journal of Productivity Analysis, 17(1/2), 23–40.
Førsund, F.R. & Sarafoglou, N. (2005) The tale of two research communities: the diffusion of research on productive efficiency. International Journal of Production Economics, 98(1), 17–40.
Førsund, F.R. & Sarafoglou, N. (2009). Farrell revisited–Visualizing properties of DEA production frontiers. Journal of the Operational Research Society, 60, 1535-1545.
Frank, M.W. (2003a). The impact of rate-of-return regulation on technological innovation. The Burtun Center for Development Studies, VT: Ashgate Publishing Company.
Frank, M.W. (2003b). An empirical analysis of electricity regulation on technical change in Texas. Review of Industrial Organization, 22, 313-331.
Halkos, G.E. & Tzeremes, N.G. (2010). The effect of foreign ownership on SMEs performance: An efficiency analysis perspective. Journal of Productivity Analysis, 34, 167-180.
Halkos, G.E. & Tzeremes, N.G. (2011). Industry performance evaluation with the use of financial ratios: An application of bootstrapped DEA. Expert Systems with Applications, doi:10.1016/j.eswa.2011.11.080.
Hall, P., Racine, J.S. & Li, Q. (2004). Cross-validation and the estimation of conditional probability densities. Journal of the American Statistical Association, 99, 1015–1026.
Hayfield, T. & Racine, J.S. (2008). Nonparametric Econometrics: The np Package. Journal of Statistical Software, 27(5), 1-32.
Hoffman, A.J. (1957). Discussion on Mr. Farrell’s Paper. Journal of the Royal Statistical Society Series A, 120(III), 284.
Irwin, M.R. (1997). Confessions of a telephone regulator: The FCC’s AT&T investigation of 1972-1977. Review of Industrial Organization, 12, 303-315.
Jeong, S.O., Park, B.U. & Simar, L. (2010). Nonparametric conditional efficiency measures: asymptotic properties. Annals of Operations Research, 173, 105-122.
Johnson, L.L. (1973). Behavior of the firm under regulatory constraint: A reassessment. American Economic Review, 63(2), 90-97.
Joskow, P.L. (2005). Regulation and deregulation after 25 years: Lessons learned for research in industrial organization. Review of Industrial Organization, 26, 169-193.
ICAP. (2007). Greece in Figures of ICAP 2007 Financial Directory. Greece: ICAP.
Kim, H.Y. (1999). Economic capacity utilization and its determinants: Theory and evidence. Review of Industrial Organization, 15, 321-339.
Klevorick, A.K. (1966). The graduated fair return: A regulatory proposal. American Economic Review, 56(3), 477-484.
Kolpin, V. (2001). Regulation and cost inefficiency. Review of Industrial Organization, 18, 175-182.
Koopmans, T.C. (1951). An analysis of production as an efficient combination of activities. In T.C. Koopmans (Ed) Activity analysis of production and allocation. New York : Wiley, pp 33–97.
Li, Q. & Racine, J.S. (2004). Cross-validated local linear nonparametric regression. Statistica Sinica, 14, 485-512.
Li, Q. & Racine, J.S. (2007). Nonparametric Econometrics: Theory and Practice. Princeton, NJ: Princeton University Press.
Maloney, M.T. (2001). Economies and diseconomies: Estimating electricity cost functions. Review of Industrial Organization, 19, 165-180.
Nadaraya, E.A. (1965). On nonparametric estimates of density functions and regression curves. Theory of Applied Probability, 10, 186–190.
Oum, T.H. & Zhang, Y. (1995). Competition and allocative efficiency: The case of the U.S. telephone industry. Review of Economics and Statistics, 77(1), 82-96.
Petersen, H.C. (1975). An empirical test of regulatory effects. Bell Journal of Economics, 6(1), 111-126.
Racine, J.S. (1997). Consistent significance testing for nonparametric regression. Journal of Business and Economic Statistics, 15, 369-379.
Racine, J.S., Hart, J, & Li, Q. (2006). Testing the significance of categorical predictor variables in nonparametric regression models. Econometric Reviews, 25, 523-544.
Rumbos, B. (1999). Endogenous capital utilization and the Averch-Johnson effect. Pennsylvania Economic Review, 8(1), 52-61.
Shephard, RW. (1970). Theory of Cost and Production Function. Princeton, NJ: Princeton University Press.
Sherman, R. (1972). The rate-of-return regulated public utility firm is schizophrenic. Applied Economics, 4(1), 23-31.
Sherman, R. (1985). The Averch and Johnson analysis of public utility regulation twenty years later. Review of Industrial Organization, 2(2), 178-193.
Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. London, Chapman and Hall.
Simar, L. & Wilson, P.W. (2011). Two-stage DEA: caveat emptor. Journal of Productivity Analysis, 36(2), 205-218.
Simar, L. & Wilson, P.W. (1999). Estimating and Bootstrapping Malmquist Indices. European Journal of Operational Research, 115, 459– 471.
Simar, L. & Wilson, P.W. (2002). Nonparametric tests of returns to scale. European Journal of Operational Research, 139, 115– 132.
Simar, L. & Wilson, P.W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136(1), 31-64.
Simar, L. & Zelenyuk, V. (2006). On testing equality of distributions of technical efficiency scores. Econometric Reviews, 25(4), 1-26.
Simar, L. & Zelenyuk, V. (2007). Statistical inference for aggregates of Farrell-type efficiencies. Journal of Applied Econometrics, 22: 1367-1394.
Simar, L. & Wilson, P.W. (2008). Statistical inference in non-parametric frontier models: Recent development and Perspectives. In H.O. Fried, C.A.K. Lovell & S.S. Schmidt (Eds.) The measurement of productive efficiency and productivity growth. New York: Oxford University Press, pp. 421-522.
Simar, L. & Wilson, P.W. (2000a). A general methodology for bootstrapping in nonparametric frontier models. Journal of Applied Statistics, 27, 779–802.
Simar, L. & Wilson, P.W. (2000b). Statistical inference in nonparametric frontier models: the state of the art. Journal of Productivity Analysis, 13, 49–78.
Spann, R.M. (1974). Rate of return regulation and efficiency in production: An empirical test of the Averch-Johnson thesis. Bell Journal of Economics and Management Science, 5(1), 38-52.
Stigler, G.J. & Friedland, C. (1962). What can regulators regulate? The case of electricity. Journal of Law and Economics, 5, 1-16.
Takayama, A. (1969). Behavior of the firm under regulatory constraint. American Economic Review, 59(3), 255-260.
Watson, G.S. (1964). Smooth regression analysis. Sankhya Series A, 26, 359–372.
Westfield, F.M. (1965). Regulation and Conspiracy. American Economic Review, 55(3), 424-443.
Ying, J.S. & Shin, R.T. (1993). Costly gains to breaking up: Lecs and baby bells. Review of Economics and Statistics, 75(2), 357-361.
Zajac, E.E. (1970). A geometric treatment of Averch-Johnson’s behavior of the firm model. American Economic Review, 60(1), 117-125.