The Use of Linear Logit Models for Dynamic Input Demand Systems

Considine, Timothy J.; Mount, Timothy D.

doi:10.2307/1924999

Cited by 81 publications

(58 citation statements)

References 6 publications

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“…For example, Considine and Mount (1984) demonstrated that a multinomial logit specification can represent a "well-behaved" set of demand functions and Dubin (2007) produced a similar proof for the nested logit model.…”

Section: Alternative Specifications For E (Y|x)mentioning

confidence: 94%

Regression Analysis of Multivariate Fractional Data

Murteira

Ramalho

2014

Econometric Reviews

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The present article discusses alternative regression models and estimation methods for dealing with multivariate fractional response variables. Both conditional mean models, estimable by nonlinear least squares and quasi-maximum likelihood, and fully parametric models (Dirichlet and Dirichlet-multinomial), estimable by maximum likelihood, are considered.In contrast to previous papers but similarly to the univariate case, a new parameterization is proposed here for the parametric models, which allows the same specification of the conditional mean of interest to be used in all models, irrespective of the specific functional form adopted for it. The text also discusses at some length the specification analysis of fractional regression models, proposing several tests that can be performed through artificial regressions. Finally, an extensive Monte Carlo study evaluates the finite sample properties of most of the estimators and tests considered.JEL classification code: C35.

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Section: Alternative Specifications For E (Y|x)mentioning

confidence: 94%

Regression Analysis of Multivariate Fractional Data

Murteira

Ramalho

2014

Econometric Reviews

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“…Subsequent studies have approached share equation estimation from theoretically motivated optimization models in which stochastic components are embedded to play particular roles (preference heterogeneity; technical or allocative inefficiency; etc.) in the optimization framework rather than being appended additively to nonstochastic share functions in what might be an ad hoc manner; such examples include Brown and Walker, 1989, Chavas and Segerson, 1987, Kooreman and Kapteyn, 1987, and McElroy, 1987. Considine and Mount, 1984, derive a specification in which the set of share equations has a multinomial logit functional form; this is noteworthy because a multinomial logit form is at the core of the specifications proposed below.…”

Section: Econometric Share Model Estimationmentioning

confidence: 99%

Multivariate Fractional Regression Estimation of Econometric Share Models

Mullahy

2010

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This paper describes and applies econometric strategies for estimating regression models of economic share data outcomes where the shares may take boundary values (zero and one) with nontrivial probability. The main focus of the paper is on the conditional mean structures of such data. The paper proposes an extension of the fractional regression methodology proposed by Wooldridge, 1996, 2008, in univariate cross-sectional and panel contexts. The paper discusses the stochastic aspects of share definition and measurement, and summarizes important features of the existing literature on econometric strategies for share model estimation. The paper then goes on to discuss the univariate fractional regression estimation strategies proposed by Papke and Wooldridge and to extend the fractional regression approach to estimation of and inference about regression models describing the multivariate share data. Some issues involving outcome aggregation/ disaggregation are considered, as is a full likelihood estimation approach based on Dirichlet-multinomial models.

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“…4 This problem could be avoided by using a logistic specification which however so far has not become popular in econometric demand analysis. See Considine and Mount (1984).…”

Section: Econometric Share Equationsmentioning

confidence: 99%

“…Woodland (1979, section 6) demonstrates that this event has very small probability if the economic model is correctly specified. An attractive alternative which does not have this defect is proposed by Considine and Mount (1984) 14 : They start from the stochastic share equations:…”

Section: Competing Approachesmentioning

confidence: 99%