NONLINEAR ESTIMATION OF THE CES PRODUCTION FUNCTION: SAMPLING DISTRIBUTIONS AND TESTS IN SMALL SAMPLES.
In this paper the results of the Monte Carlo experiments presented in [8] are resurrected to estimate the probability density functions of the nonlinear least-squares estimators of the CES parameters. Further, the earlier results are used to estimate the densities of the Student-t and Durbin-Watson...
| Publicado en: | Southern Economic Journal Vol. 41; no. 2; pp. 258 - 267 |
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| Autores principales: | , |
| Formato: | Artículo |
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Wiley-Blackwell
Oct74
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=4632406&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 4632406 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00384038 SEJ jtl: Southern Economic Journal issn: 00384038 maglogo: N pubinfo: dt: Oct74 vid: 41 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 4632406 10.2307/1056737 ppf: 258 ppct: 9 formats: tig: atl: NONLINEAR ESTIMATION OF THE CES PRODUCTION FUNCTION: SAMPLING DISTRIBUTIONS AND TESTS IN SMALL SAMPLES. aug: au: Kumar, T. Krishna Gapinski, James H. su: Density functionals Least squares Monte Carlo method sug: subj: Density functionals Least squares Monte Carlo method ab: In this paper the results of the Monte Carlo experiments presented in [8] are resurrected to estimate the probability density functions of the nonlinear least-squares estimators of the CES parameters. Further, the earlier results are used to estimate the densities of the Student-t and Durbin-Watson statistics, the values of which emerged as by-products of the regression process. The latter densities permit us to shed some light on the appropriateness of the corresponding tests in the nonlinear context. This paper therefore stands as a material extension of [8]. <BR> This study investigated the nature of small sample density functions of nonlinear least-squares regression estimators of the CES production parameters by means of the Monte Carlo technique. The information on such density functions prompted an inquiry into the appropriateness of the Student-t test of significance originally intended for least-squares estimators in linear regression models. An approximation to the sampling distribution of the Durbin-Watson statistic was obtained for the nonlinear regression model. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 1974 holdings: @attributes: islocal: N |
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