Modelling Exogenous Variables in Human Capital Formation through a Heteroscedastic Stochastic Frontier

Ahn, T., Charnes, A., & Cooper, W. W. (1988). Some statistical and DEA evaluations of relative efficiencies of public and private institutions of higher learning. Socio-economic Planning Sciences, 22(6), 259–269.

Aigner, D. J., Lovell, C. A. K., & e Schimdt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21–37.

Alvarez, A., Amsler, C., Orea, L., & Schmidt, P. (2006). Interpreting and testing the scaling property in models where inefficiency depends on firm characteristics. Journal of Productivity Analysis, 25, 201–212.

Athanassopoulos, A. D., & Shale, E. (1997). Assessing the comparative efficiency of higher education institutions in the UK by means of data envelopment analysis. Education Economics, 5(2), 117–134.

Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20, 325–332.

Beasley, J. E. (1995). Determining teaching and research efficiencies. Journal of the Operational Research Society, 46, 441–452.

Boero, G., Laureti, T., & Naylor, R. (2005) University reform in Italy: An analysis of student progression, Working paper CRENOS, N. 4, 2005.

Bojanic, A. N., Caudill, S. B., & Ford, J. M. (1998). Small-sample properties of ML, COLS, and DEA estimators of frontier models in the presence of heteroscedasticity. European Journal of Operational Research, 108(2), 468–469.

Caudill, S. B., & Ford, J. M. (1993). Biases in frontier estimation due to heteroscedasticity. Economics Letters, 41, 17–20.

Caudill, S., Ford, J. M., & Gropper, (1995). Frontier estimation and firm-specific inefficiency measures in the presence of heteroscedasticity. Journal of Business & Economic Statistics, 13(1), 105–111 January.

Domınguez-Molina, J. A., Gonzalez-Farias, G., & Ramos-Quiroga, R. (2004). Skew-normality in stochastic frontier analysis. In M. G. Genton (Ed.) Skew-elliptical distributions and their applications, chapter 13 (pp. 223–242). London: Chapman & Hall/CRC.

Ferrari, G., & Laureti T. (2004). Multi-factor efficiency analysis of the Florence University graduates, Proceedings of XLII Italian Statistical Society Conference, 503–506.

Ferrari, G., & Laureti, T. (2005). Evaluating the technical efficiency of human capital formation in the Italian University: Evidence from Florence. Statistical Methods and Applications, 14(2), 243–270.

Fuss, M., McFadden, D., & Mundlak, Y. (1978). A survey of functional forms in the economic analysis of production. In Fuss and McFadden D. (1978) Production Economics: A dual approach to the theory and applications, Volume I: The theory of production. Amsterdam: North-Holland.

Greene, W. H. (1990). A gamma-distributed stochastic frontier model. Journal of Econometrics, 43, 141–163.

Guermat, C., & Hadri, K. (1999). Heteroscedasticity in stochastic frontier models: A Monte Carlo analysis, Discussion Papers in Economics, 99/14, University of Exeter.

Hadri, K. (1999). Estimation of a doubly heteroscedastic frontier cost function. Journal of Business & Economic Statistics, 17(3), 359–363.

Hadri, K., Guermat, C., & Whittaker, J. (2003). Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers. Empirical Economics, 28, 203–222.

Harvey, A. C. (1976). Estimating regression models with multiplicative heteroscedasticity. Econometrica, 44(3), 461–465.

Johnes, J., & Johnes, G. (1995). Research funding and performance in U.K. university departments of economics: A frontier analysis. Economics of Education Review, 14(3), 301–314.

Jondrow, J., Lovell, C. A. K., Materov, I. S., & Schimdt, P. (1982). On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics, 19, 233–238.

Jorgenson, D. (1986). Econometric methods for modeling producer behavior. In Z. Griliches, & M. D. Intriligator (Eds.), Handbook of econometrics, Vol. 3, Amsterdam, North-Holland, (1841–1915). Econometrics 2, ch. 1, 1–72.

Kumbhakar, S. C., & Lovell, C. A. K. (2000). Stochastic frontier analysis. Cambridge University Press.

Liu, Y. (2006). Model selection and implications in stochastic frontier analysis: Maize production in Kenya, Mimeo, Department of Agricultural Economics and Department of Economics, Michigan State University.

Prais, S. J., & Houthakker, H. S. (1955). The analysis of family budgets. Cambridge: Cambridge University Press.

Rutemiller, H. C., & Bowers, D. A. (1968). Estimation in a heteroscedastic regression model. Journal of the American Statistical Association, 63, 552–557.

Stevenson, R. E. (1980). Likelihood functions for generalized stochastic frontier estimation. Journal of Econometrics, 13, 57–66.

Valavanis, S. (1959). Econometrics. New York: McGraw-Hill.

Wang, H. J. (2002). Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model. Journal of Productivity Analysis, 18, 241–253.

Wang, H. J. (2003). A stochastic frontier analysis of financing constraints on investment: The case of financial liberalization in Taiwan. Journal of Business and Economic Statistics, 1, 406–419.

Wang, H. J., & Schmidt, P. (2002). One-step and two-step estimation of the exogenous variables on technical efficiency. Journal of Productivity Analysis, 18, 129–144.

Weinstein, M. A. (1964). The sum of values from a normal and a truncated normal distribution. Technometrics, 6, 104–105.

Wilson, P., Hadley, D., & Asby, C. (2001). The influence of management characteristics on the technical efficiency of wheat farmers in Eastern England. Agricultural Economics, 24, 329–338.