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基于潜在结果与贝叶斯推断的品类及品牌购买动态两阶段模型AI 解读

We propose an econometric two-stage model for category-level purchase and brand-level purchase that allows for simultaneous brand purchases in the analysis of scanner panel data. The proposed model formulation is consistent with the traditional theory of consumer behavior. We conduct Bayesian estimation with the Markov chain Monte Carlo algorithm for our proposed model. The simulation studies show that previously proposed related models can cause severe bias in predicting…

识别内生解释变量参数的简约工具变量替代方法AI 解读

Abstract A review of the econometric literature on instrumental variables (IV) estimation shows that the performance of traditional IV estimation relies critically on the quality of the instruments. We discuss three different approaches that do not require the availability of observed instrumental variables: the ‘Higher Moments’ (HM) estimator, the ‘Identification trough Heteroscedasticity’ (IH) estimator, and the ‘Latent Instrumental Variable’ (LIV) approach. These methods…

用自回归负多项回归模型分析多种情绪的时间变化AI 解读

This article presents an autoregressive random coefficient model with overdispersed negative multinomial marginal distributions for the analysis of heterogeneity and serial dependencies in multivariate longitudinal count data. The model structure consists of four components that take into account (a) individual difference effects, (b) random time effects, (c) multiple event categories, and (d) autodependencies. The last component is based on a stochastic integer-valued…

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