On the estimation of simultaneous‐equations error‐components models with an application to a model of developing country foreign trade
联立方程误差成分模型估计及其在发展中国家对外贸易中的应用AI 解读 ↓
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AI 根据所提供的论文材料归类:摘要明确使用多个发展中国家的多年面板数据估计国际收支与贸易模型,直接对应宏观面板方向。
联立方程误差成分模型估计及其在发展中国家对外贸易中的应用AI 解读 ↓
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Abstract An empirical balance of payments model involving the demand and supply of imports and exports for 31 developing countries is estimated utilizing panel data over 1964‐1987. In order to compute error‐components 3SLS estimates of this model, which requires different instruments for different equations, we propose a generalization of the Fuller‐Battese transformation to obtain GMM estimates. Our empirical results suggest that very little of the short‐run adjustment in external imbalances is likely to be achieved by exchange rate policies, and most of the burden must fall on aggregate demand management.
面板数据分位数回归的GMM方法
This paper develops a smoothed generalized method of moments (GMM) framework for panel quantile models with individual-specific fixed-effects and endogenous regressors. By smoothing the indicator in the quantile moment conditions and profiling out the individual effects through smoothed individual quantile restrictions, the proposed estimator can be implemented using standard GMM algorithms. We establish consistency, asymptotic normality, and feasible inference under weak…
面板数据中所选群组的条件选择后推断
We consider the problem of testing for differences in group-specific slopes between the selected groups in panel data identified via k-means clustering. In this setting, the classical Wald-type test statistic is problematic because it produces an extremely inflated type I error probability. The underlying reason is that the same dataset is used to identify the group structure and construct the test statistic, simultaneously. This creates dependence between the selection and…
收入不平等与经济增长:元分析方法
The empirical literature on the relationship between income inequality and economic growth has produced highly heterogeneous and often conflicting results. This paper investigates the sources of this heterogeneity using a meta-analytic approach that systematically combines and analyzes evidence from relevant studies published between 1994 and 2025. We find an economically small but statistically significant negative average effect of income inequality on subsequent economic…
多重结构突变与多因子误差下空间面板模型的收缩估计
This study investigates spatial panel data models with a multifactor error structure and multiple structural breaks occurring in the coefficients of both spatial lagged and explanatory variables. While extensive research has addressed cross-sectional dependence in panel data, including approaches that integrate spatial and factor structures within a single framework, few studies account for time-varying model parameters and achieving consistent estimation remains a…
P-CRE-DML:非线性面板数据因果推断的新方法
This paper introduces a novel Proxy-Enhanced Correlated Random Effects Double Machine Learning (P-CRE-DML) framework to estimate causal effects in panel data with non-linearities and unobserved heterogeneity. Combining Double Machine Learning (DML, Chernozhukov et al., 2018), Correlated Random Effects (CRE, Mundlak, 1978), and lagged variables (Arellano & Bond, 1991) and innovating within the CRE-DML framework (Chernozhukov et al., 2022; Clarke & Polselli, 2025; Fuhr &…
Summary This paper investigates the relationship between democracy and economic growth in the context of a linear index threshold regression model. We first introduce the baseline model with endogeneity and propose a two-step smoothed generalised method of moments estimation method. We establish the consistency and derive the asymptotic distributions of the proposed estimators. We then extend the approach to a dynamic panel context and employ the model to explore the impact…