论文检索

动态面板中的偏误校正共同相关效应合并估计AI 解读

This article extends the common correlated effects pooled (CCEP) estimator to homogenous dynamic panels. In this setting, CCEP suffers from a large bias when the time span (T) of the dataset is fixed. We develop a bias-corrected CCEP estimator that is consistent as the number of cross-sectional units (N) tends to infinity, for T fixed or growing large, provided that the specification is augmented with a sufficient number of cross-sectional averages, and lags thereof. Monte…

动态网络形成与互动的空间建模方法AI 解读

This study primarily seeks to answer the following question: How do social networks evolve over time and affect individual economic activity? To provide an adequate empirical tool to answer this question, we propose a new modeling approach for longitudinal data of networks and activity outcomes. The key features of our model are the inclusion of dynamic effects and the use of time-varying latent variables to determine unobserved individual traits in network formation and…

多因子误差结构下大型面板的聚焦信息准则与模型平均AI 解读

This article considers model selection and model averaging in panel data models with a multifactor error structure. We investigate the limiting distribution of the common correlated effects estimator in a local asymptotic framework and show that the trade-off between bias and variance remains in asymptotic theory. We then propose a focused information criterion and a plug-in averaging estimator for large heterogeneous panels and examine their theoretical properties. The…

国家层面新冠活跃感染人数的面板预测AI 解读

We use a dynamic panel data model to generate density forecasts for daily active Covid-19 infections for a panel of countries/regions. Our specification that assumes the growth rate of active infections can be represented by autoregressive fluctuations around a downward sloping deterministic trend function with a break. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of slopes and then implicitly use this distribution as prior to…

新冠疫情中的消费者恐慌AI 解读

We develop an econometric model of consumer panic (or panic buying) during the COVID-19 pandemic. Using Google search data on relevant keywords, we construct a daily index of consumer panic for 54 countries from January 1st to April 30th 2020. We also assemble data on government policy announcements and daily COVID-19 cases for all countries. Our panic index reveals widespread consumer panic in most countries, primarily during March, but with significant variation in the…

异质系数空间模型的估计与推断：美国房价应用AI 解读

Summary This paper considers the estimation and inference of spatial panel data models with heterogeneous spatial lag coefficients, with and without weakly exogenous regressors, and subject to heteroskedastic errors. A quasi maximum likelihood (QML) estimation procedure is developed and the conditions for identification of the spatial coefficients are derived. The QML estimators of individual spatial coefficients, as well as their mean group estimators, are shown to be…

非线性条件均值面板模型的共同相关效应截面依赖修正AI 解读

Summary This paper provides an approach to estimation and inference for nonlinear conditional mean panel data models, in the presence of cross‐sectional dependence. We modify Pesaran's ( Econometrica , 2006, 74 (4), 967–1012) common correlated effects correction to filter out the interactive unobserved multifactor structure. The estimation can be carried out using nonlinear least squares, by augmenting the set of explanatory variables with cross‐sectional averages of both…

投资需求与产业结构转型AI 解读

We study the joint evolution of the sectoral composition and the investment rate of developing economies. Using panel data for several countries in different stages of development, we document three novel facts: (a) the share of industry and the investment rate are strongly correlated and follow a hump‐shaped profile with development, (b) investment goods contain more domestic value added from industry and less from services than consumption goods do, and (c) the evolution…

作为资产的区位AI 解读

The location of individuals determines their job and schooling opportunities, amenities, and housing costs. We conceptualize the location choice of individuals as a decision to invest in a “location asset.” This asset has a current cost equal to the location's rent, and a future payoff through better job and schooling opportunities. As with any asset, savers in the location asset transfer resources into the future by going to expensive locations with high future returns. In…

伪因子分析AI 解读

This paper draws parallels between the principal components analysis of factorless high‐dimensional nonstationary data and the classical spurious regression. We show that a few of the principal components of such data absorb nearly all the data variation. The corresponding scree plot suggests that the data contain a few factors, which is corroborated by the standard panel information criteria. Furthermore, the Dickey–Fuller tests of the unit root hypothesis applied to the…

分位数因子模型AI 解读

Quantile factor models (QFM) represent a new class of factor models for high‐dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables. We propose a quantile regression approach, labeled Quantile Factor Analysis (QFA), to consistently estimate all the quantile‐dependent factors and loadings. Their asymptotic distributions are established…

具有长期收入与价格效应的经济结构转型AI 解读

We present a new multi‐sector growth model that features nonhomothetic, constant elasticity of substitution preferences, and accommodates long‐run demand and supply drivers of structural change for an arbitrary number of sectors. The model is consistent with the decline in agriculture, the hump‐shaped evolution of manufacturing, and the rise of services over time. We estimate the demand system derived from the model using household‐level data from the United States and…

面板实验与动态因果效应：有限总体视角AI 解读

In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative effectiveness of alternative treatment paths. For a rich class of dynamic causal effects, we provide a nonparametric estimator that is unbiased over the randomization distribution and derive its finite population…

具有随机就业机会的工作阶梯模型AI 解读

We set up a model with on‐the‐job search in which firms infrequently post vacancies for which workers occasionally apply. The model nests the standard job ladder and stock‐flow models as special cases, while remaining analytically tractable and easy to estimate from standard panel data sets. The parameters from a structurally estimated model on US data are significantly different from either the restrictions imposed by a stock‐flow or job ladder model. Imposing these…

处理前拟合不完全的合成控制方法AI 解读

We analyze the properties of the Synthetic Control (SC) and related estimators when the pre‐treatment fit is imperfect. In this framework, we show that these estimators are generally biased if treatment assignment is correlated with unobserved confounders, even when the number of pre‐treatment periods goes to infinity. Still, we show that a demeaned version of the SC method can improve in terms of bias and variance relative to the difference‐in‐difference estimator. We also…

半参数多项响应模型的统计推断AI 解读

We explore inference on regression coefficients in semiparametric multinomial response models. We consider cross‐sectional, and both static and dynamic panel settings where we focus throughout on inference under sufficient conditions for point identification. The approach to identification uses a matching insight throughout all three models coupled with variation in regressors: with cross‐section data, we match across individuals while with panel data, we match within…

青少年欺凌：技能的作用AI 解读

Bullying cannot be tolerated as a normal social behavior portraying a child's life. This paper quantifies its negative consequences allowing for the possibility that victims and nonvictims differ in unobservable characteristics. To this end, we introduce a factor analytic model for identifying treatment effects of bullying in which latent cognitive and noncognitive skills determine victimization and multiple outcomes. We use early test scores to identify the distribution of…

反卷积中的稳健推断AI 解读

Kotlarski's identity has been widely used in applied economic research based on repeated‐measurement or panel models with latent variables. However, how to conduct inference for these models has been an open question for two decades. This paper addresses this open problem by constructing a novel confidence band for the density function of a latent variable in repeated measurement error model. The confidence band builds on our finding that we can rewrite Kotlarski's identity…

空间自回归参数的调整准最大似然估计AI 解读

One simple, and often very effective, way to attenuate the impact of nuisance parameters on maximum likelihood estimation of a parameter of interest is to recenter the profile score for that parameter. We apply this general principle to the quasi-maximum likelihood estimator (QMLE) of the autoregressive parameter λ in a spatial autoregression. The resulting estimator for λ has better finite sample properties compared to the QMLE for λ, especially in the presence of a large…

含主导单元的生产网络计量分析AI 解读

This paper introduces the notions of strongly and weakly dominant units for networks, and shows that pervasiveness of shocks to a network is measured by the degree of dominance of its most pervasive unit; shown to be equivalent to the inverse of the shape parameter of the power law fitted to the network outdegrees. New cross-section and panel extremum estimators of the degree of dominance in networks are proposed, and their asymptotic properties investigated. The small…

具有横截面依赖的异质面板数据模型AI 解读

This paper considers a semiparametric panel data model with heterogeneous coefficients and individual-specific trending functions, where the random errors are assumed to be serially correlated and cross-sectionally dependent. We propose mean group estimators for the coefficients and trending functions involved in the model. It can be shown that the proposed estimators can achieve an asymptotic consistency with rates of root−NT and root−NTh, respectively as (N,T)→(∞,∞), where…

短面板相关性的综合检验AI 解读

Inoue and Solon (2006, Econometric Theory 22, 835–851) presented a test against serial correlation of arbitrary form in fixed-effect models for short panel data. Implementing the test requires choosing a regularization parameter that may severely affect power and for which no optimal selection rule is available. We present a modified version of their test that does not require any regularization parameter. Asymptotic power calculations illustrate the improvement of our…

具有交互固定效应的面板门槛模型AI 解读

This paper studies estimation and inference in a panel threshold model in the presence of interactive fixed effects. We study the asymptotic properties of the least squares estimators of the regression parameters in the shrinking-threshold-effect framework. We find that under some regularity conditions, the threshold parameter estimator possesses super-consistency in the sense that its estimation error has an asymptotically negligible effect on the asymptotic properties of…

双重稳健的双重差分估计量AI 解读

This article proposes doubly robust estimators for the average treatment effect on the treated (ATT) in difference-in-differences (DID) research designs. In contrast to alternative DID estimators, the proposed estimators are consistent if either (but not necessarily both) a propensity score or outcome regression working models are correctly specified. We also derive the semiparametric efficiency bound for the ATT in DID designs when either panel or repeated cross-section…