Preliminary testing of the Cobb–Douglas production function and related inferential issues

References

• Akdeniz, D. E., Akdeniz, F. (2012). Efficiency of the modified jackknifed Liu-type estimator. Statistical Papers 53:265–280.
   Google Scholar
• Akdeniz, F., Erol, H. (2003). Mean squared error matrix comparisons of some biased estimators in linear regression. Communications in Statistics - Theory and Methods 32:2389–2413.
   Google Scholar
• Akdeniz, F., Kaciranlar, S. (1995). On the almost unbiased generalized Liu estimator and unbiased estimation of the bias and MSE. Communications in Statistics -Theory and Methods 24:1789–1797.
   Google Scholar
• Akdeniz, F., Tabakan, G. (2009). Restricted ridge estimators of the parameters in semiparametric regression model. Communications is Statistics -Theory and Methods 38:1852–1869.
   Google Scholar
• Arashi, M., Valizadeh, T. (2015). Performance of Kibria’s methods in partial linear ridge regression model. Statistical Papers 56(1):231–246. DOI: 10.1007/s00363-014-0578-6.
   Google Scholar
• Barro, R., Gordon, D. (1983). A positive theory of monetary policy in a natural rate model. Journal of Political Economy 91(3):589–610.
   Google Scholar
• Christofferson, P. F., Diebold, F. X. (1996). Further results on forecasting and model selection under asymmetric loss. Journal of Applied Econometrics 11:561–571.
   Google Scholar
• Christofferson, P. F., Diebold, F. X. (1997). Optimal prediction under asymmetric loss. Econometric Theory 13:808–817.
   Google Scholar
• Cobb, C. W., Douglas, P. H. (1928). A theory of production. American Economic Review 18(1):139–165.
   Google Scholar
• Coetsee, J., Bekker, A., Millard, S. (2014). Preliminary-test and Bayes estimation of a location parameter under BLINEX loss. Communications in Statistics - Theory and methods 43(17):3641–3660.
   Google Scholar
• Gibbons, D. G. (1981). A simulation study of some ridge estimators. Journal of American Statistical Association 76:131–139.
   Google Scholar
• Gisela, M., Kibria, B. M. G. (2009). On some ridge regression estimator: An empirical comparison. Communications in Statistics - Simulation and Computation 38(3):621–630.
   Google Scholar
• Granger, C. W. J. (1999). Outline of forecast theory using generalized cost functions. Spanish Economic Review 1:161–173.
   Google Scholar
• Groβ, J. (2003). Restricted ridge regression. Statistics and Probability letters 65:57–64.
   Google Scholar
• Gujarati, D. N. (2003). Basic Econometrics. New York: McGraw-Hill.
   Google Scholar
• Hocking, R. R., Speed, F. M., Lynn, M. J. (1976). A class of biased estimators in linear regression models. Technometrics 18:425–438.
   Google Scholar
• Hoerl, A. E., Kennard, R. W. (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics 12(1):55–67.
   Google Scholar
• Hoerl, A. E., Kennard, R. W., Baldwin, K. F. (1975). Ridge regression: Some simulations. Communications in Statistics 4(2):105–123.
   Google Scholar
• Horowitz, A. (1987). Loss functions and public policy. Journal of Macroeconomics 9:489–504.
   Google Scholar
• Judge, G. G., Bock, M. E. (1978). The Statistical Implications of Pre-test and Stein-rule Estimation in Econometrics. Amsterdam: North-Holland Publishing Company.
   Google Scholar
• Kibria, B. M. G. (1996). On preliminary test ridge regression estimators for linear restriction in a regression model with non-normal disturbances. Communications in Statistics - Theory and Methods 25:2349–2369.
   Google Scholar
• Kibria, B. M. G. (2003). Performance of some new ridge estimation. Communications in Statistics Simulation and Computations 32(2):419–435.
   Google Scholar
• Kibria, B. M. G. (2012). Some liu and ridge type estimators and their properties under the ill-conditioned Gaussian linear regression model. Journal of Statistical Computations and Simulation 82:1–17.
   Google Scholar
• Kibria, B. M. G., Banik, S. (2016). Some Ridge Regression Estimators and Their Performances. Journal of Modern Applied Statistical Method, 15(1):206–238.
   Google Scholar
• Kibria, B. M. G., Saleh, A. K. Md. E. (2012). Improving the estimators of the parameters of a probit regression model: A ridge regression approach. Journal of Statistical Planning and Inference 142:1421–1435.
   Google Scholar
• Kleyn, J. (2014). The Performance of the Preliminary Test Estimator Under Different Loss Functions. Ph.D. dissertation, South Africa: University of Pretoria.
   Google Scholar
• Kristofer, M., Kibria, B. M. G., and Shukur, G. (2012). On Liu estimators for the logit regression model. Economic Modeling 29:1483–1488.
   Google Scholar
• Kunstman, A. (1984). Controlling a linear dynamic system according to asymmetric preferences. Journal of Economic Dynamics and Control 7:261–281.
   Google Scholar
• Lahiri, S. N. (2003). Resampling Methods for Dependent Data (Springer Series in Statistics), Springer, New York.
   Google Scholar
• Lawless, J. F., Wang, P. (1976). A simulation study of ridge and other regression estimators. Communications in Statistics - Theory and Methods 5:307–323.
   Google Scholar
• McDonald, G. C., Galarneau, D. I. (1975). A Monte Carlo evaluation of some Ridge type estimators. Journal of American Statistical Association 70:407–416.
   Google Scholar
• Najarian, S., Arashi, M., Kibria, B. M. G. (2013). A simulation study on some restricted ridge regression estimators. Communications in Statistics - Simulations and computations 42(4):871–889.
   Google Scholar
• Newhouse, J. P., Oman, S. D. (1971). An Evaluation of Ridge Estimators. Report no. R-716-PR. Santa Monica, CA: Rand Corporation.
   Google Scholar
• Ruge-Murcia, F. J. (2002). The inflation bias when the central bank targets the natural rate of unemployment. European Economic Review 48(1):91–107.
   Google Scholar
• Saleh, A. K. Md. E. (2006). Theory of Preliminary Test and Stein-Type Estimation with Applications. New Jersey: John Wiley.
   Google Scholar
• Saleh, A. K. Md. E., Kibria, B. M. G. (2011). On some ridge regression estimators: A nonparametric approach. Journal of Nonparametric Statistics 23:819–851.
   Google Scholar
• Santana, L., Allison, J. S. (2013). The Bootstrap: An Introductory Course. STTN613. University of North West, South Africa.
   Google Scholar
• Sarkar, N. (1992). A new estimator combining the ridge regression and the restricted least squares method of estimation. Communication in Statistics - Theory and Methods 21:1987–2000.
   Google Scholar
• Waud, R. (1976). Asymmetric policymaker utility functions and optimal policy under uncertainty. Econometrics 44:53–66.
   Google Scholar
• Wen, D., Levy, S. (2001). BLINEX: A bounded asymmetric loss function with application to Bayesian Estimation. Communications in Statistics -Theory and Methods 30(1):147–153.
   Google Scholar
• Zellner, A. (1986). Bayesian estimation and prediction under asymmetric loss functions. Journal of American Statistical Association 81:446–451.
   Google Scholar