Barnett, William A. and Seck, Ousmane (2008): Estimation with Inequality Constraints on Parameters and Truncation of the Sampling Distribution.
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Abstract
Theoretical constraints on economic model parameters often are in the form of inequality restrictions. For example, many theoretical results are in the form of monotonicity or nonnegativity restrictions. Inequality constraints can truncate sampling distributions of parameter estimators, so that asymptotic normality no longer is possible. Sampling theoretic asymptotic inference is thereby greatly complicated or compromised. We use numerical methods to investigate the resulting sampling properties of inequality-constrained estimators produced by popular methods of imposing inequality constraints, with particular emphasis on the method of squaring, which is the most widely used method in the applied literature on estimating integrable neoclassical systems of demand equations. See Barnett and Binner (2004).
Item Type: | MPRA Paper |
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Original Title: | Estimation with Inequality Constraints on Parameters and Truncation of the Sampling Distribution |
Language: | English |
Keywords: | inequality constraints; truncation of sampling distribution; asymptotics; constrained estimation |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General |
Item ID: | 14987 |
Depositing User: | William A. Barnett |
Date Deposited: | 04 May 2009 00:47 |
Last Modified: | 27 Sep 2019 16:31 |
References: | Barnett, WA. 1977. Recursive subaggregation and a generalized hypocycloidal demand model, Econometrica vol. 45, issue 5, pages 1117-36. Barnett, WA. 1978. The User Cost of Money. Economics Letters, Vol. 1, No. 2. Barnett, WA. 1980. Economic Monetary Aggregates: An Application of Index Number and Aggregation Theory. Journal of Econometrics, September. Efron, B. 1979. Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7, 1-26. Efron, B. 1981. Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods. Biometrika, 68, 589-599. Efron, B. 1982. The jackknife, the bootstrap, and other resampling plans. Society of Industrial and Applied Mathematics CBMS-NSF Monographs, 38. Efron, B. 1985. Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods. Biometrika, 68, 589-599. Efron, B., Tibshirani, R J. (1993). An introduction to the bootstrap. New York: Chapman and Hall. Miller, R. G. 1974. The jackknife–A review. Biometrika 61:115. Theil, H. 1971. Principles of Econometrics. North Holland, Amsterdam. Wu, CFJ. 1985. ”Statistical methods based on data resampling”. Special invited paper presented at IMS meeting in Stony Brook. Wu, CFJ. 1986. ”Jackknife, bootstrap and other resampling plans in regression analysis”, Ann.Statist. 14, pp.1261-1350. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/14987 |
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Estimation with inequality constraints on the parameters: dealing with truncation of the sampling distribution. (deposited 05 Jan 2009 06:41)
- Estimation with Inequality Constraints on Parameters and Truncation of the Sampling Distribution. (deposited 04 May 2009 00:47) [Currently Displayed]