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从二元响应数据估计潜在分布特征AI 解读

We propose estimators of features of the distribution of an unobserved random variable W. What is observed is a sample of Y,V,X where a binary Y equals one when W exceeds a threshold V determined by experimental design, and X are covariates. Potential applications include bioassay and destructive duration analysis. Our empirical application is referendum contingent valuation in resource economics, where one is interested in features of the distribution of values W…

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离散响应的混合多项 Logit 模型AI 解读

This paper considers mixed, or random coefficients, multinomial logit (MMNL) models for discrete response, and establishes the following results. Under mild regularity conditions, any discrete choice model derived from random utility maximization has choice probabilities that can be approximated as closely as one pleases by a MMNL model. Practical estimation of a parametric mixing family can be carried out by Maximum Simulated Likelihood Estimation or Method of Simulated…

多元正态矩形概率及其导数的模拟：理论与计算结果AI 解读

An extensive literature in econometrics and in numerical analysis has considered the problem of evaluating the multiple integral P(B; μ, Ω) = ∝ab n(v − μ, Ω)dv ≡ Ev1(V ϵ B), where V is a m-dimensional normal vector with mean μ, covariance matrix Ω, and density n(v − μ, Ω), and 1(V ϵ B) is an indicator for the event B = (V¦a < V < b). A leading case of such an integral is the negative orthant probability, where B = (V ¦V < 0). The problem is computationally difficult except…

无需数值积分的离散响应模型模拟矩估计方法AI 解读

This paper proposes a simple modification of a conventional generalized method of moments estimator for a discrete response model, replacing response probabilities that require numerical integration with estimators obtained by Monte Carlo simulation. This method of simulated moments does not require precise estimates of these probabilities, as the law of large numbers operating across observations controls simulation error, and, hence, can use simulations of practical size.…

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多项 Logit 模型的设定检验AI 解读

Discrete choice models are now used in a variety of situations in applied econometrics. By far the model specification which is used most often is the multinomial logit model. Yet it is widely known that a potentially important drawback of the multinomial logit model is the independence from irrelevant alternatives property. While most analysts recognize the implications of the independence of irrelevant alternatives property, it has remained basically a maintained…