Journal of Econometric Methods最新文献_第10页

What Do Kernel Density Estimators Optimize? 核密度估计器优化了什么?

Journal of Econometric Methods Pub Date : 2012-01-01 DOI: 10.1515/2156-6674.1011

R. Koenker, I. Mizera, Jungmo Yoon

引用次数: 0

A Comparison of the Robustness of Several Tests of Short Memory to Autocorrelated Errors 几种短时记忆测试对自相关错误的鲁棒性比较

Journal of Econometric Methods Pub Date : 2012-01-01 DOI: 10.1515/2156-6674.1002

Christine E. Amsler, P. Schmidt

引用次数: 0

Estimation of Panel Data Regression Models with Two-Sided Censoring or Truncation 双侧删减或截断面板数据回归模型的估计

Journal of Econometric Methods Pub Date : 2011-11-14 DOI: 10.2139/ssrn.1961703

Sule Alan, Bo E. Honoré, Luojia Hu, Søren Leth-Petersen

引用次数: 40

On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments 用社会实验估计因果影响的本质异质性的含义

Journal of Econometric Methods Pub Date : 2011-09-01 DOI: 10.1515/jem-2013-0009

M. Ravallion

引用次数: 11

Quantile Uncorrelation and Instrumental Regressions 分位数不相关和工具回归

Journal of Econometric Methods Pub Date : 2010-09-01 DOI: 10.1515/2156-6674.1001

T. Komarova, T. Severini, E. Tamer

{"title":"Quantile Uncorrelation and Instrumental Regressions","authors":"T. Komarova, T. Severini, E. Tamer","doi":"10.1515/2156-6674.1001","DOIUrl":"https://doi.org/10.1515/2156-6674.1001","url":null,"abstract":"Abstract We introduce a notion of median uncorrelation that is a natural extension of mean (linear) uncorrelation. A scalar random variable Y is median uncorrelated with a k-dimensional random vector X if and only if the slope from an LAD regression of Y on X is zero. Using this simple definition, we characterize properties of median uncorrelated random variables, and introduce a notion of multivariate median uncorrelation. We provide measures of median uncorrelation that are similar to the linear correlation coefficient and the coefficient of determination. We also extend this median uncorrelation to other loss functions. As two stage least squares exploits mean uncorrelation between an instrument vector and the error to derive consistent estimators for parameters in linear regressions with endogenous regressors, the main result of this paper shows how a median uncorrelation assumption between an instrument vector and the error can similarly be used to derive consistent estimators in these linear models with endogenous regressors. We also show how median uncorrelation can be used in linear panel models with quantile restrictions and in linear models with measurement errors.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"1 1","pages":"14 - 2"},"PeriodicalIF":0.0,"publicationDate":"2010-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/2156-6674.1001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66807697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

A Score Based Approach to Wild Bootstrap Inference 基于分数的野生引导推理方法

Journal of Econometric Methods Pub Date : 2010-06-01 DOI: 10.1515/2156-6674.1006

Patrick M. Kline, Andrés Santos

引用次数: 154

Nonparametric Instrumental Variable Estimation in Practice 实践中的非参数工具变量估计

Journal of Econometric Methods Pub Date : 2008-01-01 DOI: 10.1515/jem-2013-0002

P. Shaw, Michael Andrew Cohen, Tao Chen

{"title":"Nonparametric Instrumental Variable Estimation in Practice","authors":"P. Shaw, Michael Andrew Cohen, Tao Chen","doi":"10.1515/jem-2013-0002","DOIUrl":"https://doi.org/10.1515/jem-2013-0002","url":null,"abstract":"Abstract This paper investigates recent developments in the literature on nonparametric instrumental variables estimation and considers the practical importance of the features of these estimators in the context of typically applied econometric models. Our primary focus is on the estimation of econometric models with endogenous regressors, and their marginal effects, without a known functional form. We develop an estimator for the marginal effects and investigate its finite sample performance. We show that when instruments are weak, in the classic sense, the nonparametric estimates of the marginal effect outperforms the classic two-stage least squares estimator, even when the model is correctly specified. When the instruments are strong, we show that the nonparametric estimator for the partial effects is still effective compared to the two-stage least squares estimator even as the number of IVs increases. We also investigate bandwidth choice and find that a rule-of-thumb bandwidth performs relatively well. Whereas cross-validation leads to a better fit when the number of instruments is small, as the number of instruments increases the rule-of-thumb standard actually results in better model fit. In an empirical application we estimate the work-horse aggregate logit demand model, discuss the required nonparametric identification properties, and document the differences between nonparametric and parametric specifications on the estimation of demand elasticities.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"7 1","pages":"153 - 177"},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2013-0002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66939556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Estimation of Panel Data Models with Parameter Heterogeneity when Group Membership is Unknown 群体隶属未知时参数异质性面板数据模型的估计

Journal of Econometric Methods Pub Date : 2007-11-01 DOI: 10.1515/2156-6674.1000

Chang‐Ching Lin, Serena Ng

引用次数: 120