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基于时序与信息集假设的结构模型识别不足AI 解读

We revisit identification based on timing and information set assumptions in structural models, which have been used in the context of production functions, demand equations, and hedonic pricing models (e.g. Olley and Pakes, 1996, Blundell and Bond, 2000). First, we demonstrate a general under-identification problem using these assumptions in a simple version of the Blundell–Bond dynamic panel model. In particular, the basic moment conditions can yield multiple discrete…

结构模型中随机系数分布估计的简便非参数方法AI 解读

We explore least squares and likelihood nonparametric mixtures estimators of the joint distribution of random coefficients in structural models. The estimators fix a grid of heterogeneous parameters and estimate only the weights on the grid points, an approach that is computationally attractive compared to alternative nonparametric estimators. We provide conditions under which the estimated distribution function converges to the true distribution in the weak topology on the…

资本存在测量误差时的控制函数生产函数估计AI 解读

We revisit the production function estimators of Olley and Pakes (1996) and Levinsohn and Petrin (2003). They use control functions to address the simultaneous determination of inputs and productivity. Both assume that input demand is a monotonic function of productivity holding capital constant and then invert this function to condition on productivity during estimation. If the observed capital variable is measured with error, input demand will not generally be monotonic in…

随机系数 Logit 模型的识别AI 解读

The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the distribution of random coefficients in the multinomial logit model is nonparametrically identified. Our approach requires variation in product characteristics only locally and does not rely on the special regressors with large supports used in related papers. One of our two identification…

随机系数分布的简便估计方法AI 解读

We propose a simple mixtures estimator for recovering the joint distribution of parameter heterogeneity in economic models, such as the random coefficients logit. The estimator is based on linear regression subject to linear inequality constraints, and is robust, easy to program, and computationally attractive compared to alternative estimators for random coefficient models. For complex structural models, one does not need to nest a solution to the economic model during…

半非参数密度估计的一致收敛速度与两未知密度的相似性检验AI 解读

This paper studies the uniform convergence rate of the truncated seminonparametric (SNP) density estimator. Using the uniform convergence rate result we obtain, we propose a test statistic testing the equivalence of two unknown densities where two densities are estimated using the SNP estimator and supports of densities are possibly unbounded. Copyright Royal Economic Society 2007