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合并还是不合并：面板回归参数估计与预测的策略AI 解读

Summary This paper considers estimating the slope parameters and forecasting in potentially heterogeneous panel data regressions with a long time dimension. We propose a novel optimal pooling averaging estimator that makes an explicit trade‐off between efficiency gains from pooling and bias due to heterogeneity. By theoretically and numerically comparing various estimators, we find that a uniformly best estimator does not exist and that our new estimator is superior in…

考虑排序能力不可观测异质性的排序 Logit 模型AI 解读

Abstract To study preferences, respondents to a survey are usually asked to select their most preferred option from a set. Preferences can be estimated more efficiently if respondents are asked to rank all alternatives. When some respondents are unable to perform the ranking task, using the complete ranking may lead to a substantial bias. We introduce a model which endogenously describes the ranking capabilities of individuals. Estimated preferences based on this model are…

利用品牌层面营销变量建模品类层面的购买时点AI 解读

Abstract Purchase timing of households is usually modeled at the category level. However, many potential explanatory variables are observed at the brand level. To explain interpurchase times one has to either construct category‐level measures of marketing efforts, or integrate the model with a model for brand choice. In this paper we pursue the latter where we use latent brand preferences to capture the relevance of the marketing mix of an individual brand. We compare our…

营销组合变量具有不同长期与短期效应的动态多项 Probit 品牌选择模型AI 解读

Abstract In this paper we propose a dynamic multinomial probit model in order to estimate the long‐run and short‐ run effects of marketing mix variables on brand choice. The latent variables, which contain the unobserved perceived utilities, follow a first‐order vector error correction autoregressive process of order 1 with current and lagged explanatory variables. The unrestricted autoregressive parameter matrix concerns the intertemporal correlation in perceived utilities…