摘要翻译：
因素结构或交互效应是在面板数据模型中引入潜在变量的方便工具。考虑了在不可观测条件下具有因子结构的非线性面板单指标模型的固定效应估计，这些模型包括logit、probit、有序probit和Poisson规范。当面板的两个维度变大时，模型参数的固定效应估计量和平均部分效应估计量均服从正态分布，但可能会出现附带的参数偏差。我们展示了具有因子结构的模型也可以应用于捕捉网络数据的重要特征，如互易性、程度异质性、潜在变量的同源性和聚类。我们用一个多因素泊松模型估计国家间国际贸易重力方程的实证例子说明了这种适用性。
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英文标题：
《Nonlinear Factor Models for Network and Panel Data》
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作者：
Mingli Chen, Iv\'an Fern\'andez-Val, and Martin Weidner
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最新提交年份：
2019
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  Factor structures or interactive effects are convenient devices to incorporate latent variables in panel data models. We consider fixed effect estimation of nonlinear panel single-index models with factor structures in the unobservables, which include logit, probit, ordered probit and Poisson specifications. We establish that fixed effect estimators of model parameters and average partial effects have normal distributions when the two dimensions of the panel grow large, but might suffer of incidental parameter bias. We show how models with factor structures can also be applied to capture important features of network data such as reciprocity, degree heterogeneity, homophily in latent variables and clustering. We illustrate this applicability with an empirical example to the estimation of a gravity equation of international trade between countries using a Poisson model with multiple factors.
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PDF链接：
https://arxiv.org/pdf/1412.5647