Econometric Reviews最新文献_第8页

Testing for time-varying factor loadings in high-dimensional factor models 高维因子模型中时变因子负荷的测试

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-05-30 DOI: 10.1080/07474938.2022.2074188

Wen Xu

引用次数: 2

A state-space approach to time-varying reduced-rank regression 时变降秩回归的状态空间方法

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-05-28 DOI: 10.1080/07474938.2022.2073743

B. Brune, W. Scherrer, E. Bura

引用次数: 1

Unified M-estimation of matrix exponential spatial dynamic panel specification 矩阵指数空间动态面板规格的统一m估计

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-05-14 DOI: 10.1080/07474938.2022.2039494

Ye Yang

引用次数: 0

Binary outcomes, OLS, 2SLS and IV probit 二元结果，OLS、2SLS和IV probit

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-05-13 DOI: 10.1080/07474938.2022.2072321

Chuhui Li, D. Poskitt, F. Windmeijer, Xueyan Zhao

{"title":"Binary outcomes, OLS, 2SLS and IV probit","authors":"Chuhui Li, D. Poskitt, F. Windmeijer, Xueyan Zhao","doi":"10.1080/07474938.2022.2072321","DOIUrl":"https://doi.org/10.1080/07474938.2022.2072321","url":null,"abstract":"Abstract For a binary outcome Y, generated by a simple threshold crossing model with a single exogenous normally distributed explanatory variable X, the OLS estimator of the coefficient on X in a linear probability model is a consistent estimator of the average partial effect of X. Even in this very simple setting, we show that when allowing for X to be endogenously determined, the 2SLS estimator, using a normally distributed instrumental variable Z, does not identify the same causal parameter. It instead estimates the average partial effect of Z, scaled by the coefficient on Z in the linear first-stage model for X, denoted γ 1, or equivalently, it estimates the average partial effect of the population predicted value of X, These causal parameters can differ substantially as we show for the normal Probit model, which implies that care has to be taken when interpreting 2SLS estimation results in a linear probability model. Under joint normality of the error terms, IV Probit maximum likelihood estimation does identify the average partial effect of X. The two-step control function procedure of Rivers and Vuong can also estimate this causal parameter consistently, but a double averaging is needed, one over the distribution of the first-stage error V and one over the distribution of X. If instead a single averaging is performed over the joint distribution of X and V, then the same causal parameter is estimated as the one estimated by the 2SLS estimator in the linear probability model. The 2SLS estimator is a consistent estimator when the average partial effect is equal to 0, and the standard Wald test for this hypothesis has correct size under strong instrument asymptotics. We show that, in general, the standard weak instrument first-stage F-test interpretations do not apply in this setting.","PeriodicalId":11438,"journal":{"name":"Econometric Reviews","volume":"41 1","pages":"859 - 876"},"PeriodicalIF":1.2,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49510563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

A new Bayesian model for contagion and interdependence 传染和相互依赖的新贝叶斯模型

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-05-13 DOI: 10.1080/07474938.2022.2072319

Aubrey Poon, Dan Zhu

引用次数: 0

Testing independence between exogenous variables and unobserved errors 检验外生变量和未观察到的误差之间的独立性

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-04-18 DOI: 10.1080/07474938.2022.2039493

Shuo Li, Liuhua Peng, Y. Tu

{"title":"Testing independence between exogenous variables and unobserved errors","authors":"Shuo Li, Liuhua Peng, Y. Tu","doi":"10.1080/07474938.2022.2039493","DOIUrl":"https://doi.org/10.1080/07474938.2022.2039493","url":null,"abstract":"Abstract Although the exogeneity condition is usually used in many econometric models to identify parameters, the stronger restriction that the error term is independent of a vector of exogenous variables might lead to theoretical benefits. In this paper, we develop a unified methodology for testing the independence assumption. Our methodology can deal with a wide class of parametric models and allows for endogeneity and instrumental variables. In the first-step development, we construct tests that are continuous functionals of the estimated difference of the joint distribution and the product marginal distributions. Next, to remedy the dimensionality issue that arises when the dimension of the exogenous random vector is large, we propose a multiple testing approach which combines marginal p-values obtained by employing the original tests to test independence between the error term and each exogenous variable, while taking full account of the multiplicity nature of the testing problem. We obtain null limiting distributions of our tests, establish the testing consistency, and justify the sensitivity to -local alternatives, with n the sample size. The multiplier bootstrap is employed to estimate the critical values. Our methodology is illustrated in the linear regression, the instrumental variables regression, and the nonlinear quantile regression. Our tests are found to perform well in simulations and are demonstrated via an empirical example.","PeriodicalId":11438,"journal":{"name":"Econometric Reviews","volume":"41 1","pages":"697 - 728"},"PeriodicalIF":1.2,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45017714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Model selection and model averaging for matrix exponential spatial models 矩阵指数空间模型的模型选择和模型平均

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-03-21 DOI: 10.1080/07474938.2022.2047507

Ye Yang, Osman Doğan, Suleyman Taspinar

{"title":"Model selection and model averaging for matrix exponential spatial models","authors":"Ye Yang, Osman Doğan, Suleyman Taspinar","doi":"10.1080/07474938.2022.2047507","DOIUrl":"https://doi.org/10.1080/07474938.2022.2047507","url":null,"abstract":"Abstract In this paper, we focus on a model specification problem in spatial econometric models when an empiricist needs to choose from a pool of candidates for the spatial weights matrix. We propose a model selection (MS) procedure for the matrix exponential spatial specification (MESS), when the true spatial weights matrix may not be in the set of candidate spatial weights matrices. We show that the selection estimator is asymptotically optimal in the sense that asymptotically it is as efficient as the infeasible estimator that uses the best candidate spatial weights matrix. The proposed selection procedure is also consistent in the sense that when the data generating process involves spatial effects, it chooses the true spatial weights matrix with probability approaching one in large samples. We also propose a model averaging (MA) estimator that compromises across a set of candidate models. We show that it is asymptotically optimal. We further flesh out how to extend the proposed selection and averaging schemes to higher order specifications and to the MESS with heteroscedasticity. Our Monte Carlo simulation results indicate that the MS and MA estimators perform well in finite samples. We also illustrate the usefulness of the proposed MS and MA schemes in a spatially augmented economic growth model.","PeriodicalId":11438,"journal":{"name":"Econometric Reviews","volume":"41 1","pages":"827 - 858"},"PeriodicalIF":1.2,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45976576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Optimal model averaging for divergent-dimensional Poisson regressions 发散维泊松回归的最优模型平均

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-03-15 DOI: 10.1080/07474938.2022.2047508

Jiahui Zou, Wendung Wang, Xinyu Zhang, Guohua Zou

引用次数: 10

Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models 异方差VAR模型中确定协整秩的自适应信息方法

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-02-05 DOI: 10.1080/07474938.2023.2222633

H. Boswijk, Giuseppe Cavaliere, L. Angelis, A. Taylor

{"title":"Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models","authors":"H. Boswijk, Giuseppe Cavaliere, L. Angelis, A. Taylor","doi":"10.1080/07474938.2023.2222633","DOIUrl":"https://doi.org/10.1080/07474938.2023.2222633","url":null,"abstract":"Abstract Standard methods, such as sequential procedures based on Johansen’s (pseudo-)likelihood ratio (PLR) test, for determining the co-integration rank of a vector autoregressive (VAR) system of variables integrated of order one can be significantly affected, even asymptotically, by unconditional heteroskedasticity (non-stationary volatility) in the data. Known solutions to this problem include wild bootstrap implementations of the PLR test or the use of an information criterion, such as the BIC, to select the co-integration rank. Although asymptotically valid in the presence of heteroskedasticity, these methods can display very low finite sample power under some patterns of non-stationary volatility. In particular, they do not exploit potential efficiency gains that could be realized in the presence of non-stationary volatility by using adaptive inference methods. Under the assumption of a known autoregressive lag length, Boswijk and Zu develop adaptive PLR test based methods using a non-parametric estimate of the covariance matrix process. It is well-known, however, that selecting an incorrect lag length can significantly impact on the efficacy of both information criteria and bootstrap PLR tests to determine co-integration rank in finite samples. We show that adaptive information criteria-based approaches can be used to estimate the autoregressive lag order to use in connection with bootstrap adaptive PLR tests, or to jointly determine the co-integration rank and the VAR lag length and that in both cases they are weakly consistent for these parameters in the presence of non-stationary volatility provided standard conditions hold on the penalty term. Monte Carlo simulations are used to demonstrate the potential gains from using adaptive methods and an empirical application to the U.S. term structure is provided.","PeriodicalId":11438,"journal":{"name":"Econometric Reviews","volume":"42 1","pages":"725 - 757"},"PeriodicalIF":1.2,"publicationDate":"2022-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44999231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Large dimensional portfolio allocation based on a mixed frequency dynamic factor model 基于混合频率动态因子模型的大维投资组合配置

IF 1.2 4区经济学

Econometric Reviews Pub Date : 2022-02-02 DOI: 10.1080/07474938.2021.1983327

Siyang Peng, Shaojun Guo, Yonghong Long

引用次数: 0