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Simultaneous tests and confidence bands for Stata estimation commands Stata估计命令的同步测试和置信带
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175333
D. Drukker
{"title":"Simultaneous tests and confidence bands for Stata estimation commands","authors":"D. Drukker","doi":"10.1177/1536867X231175333","DOIUrl":"https://doi.org/10.1177/1536867X231175333","url":null,"abstract":"Stata estimation commands that implement frequentist methods produce an output table that contains multiple tests and multiple confidence intervals. Presumably, the multiple tests and multiple confidence are designed to help determine which parameters are responsible for a possible rejection of the overall null hypothesis of no effect. When taken by itself, each test and each confidence interval provides valid inference about the null hypothesis of no effect for each parameter at the specified error rate. However, simultaneously using two or more of these tests or confidence intervals provides inference at an error rate that exceeds the one specified. In this article, I discuss the sotable command, which provides p-values that are adjusted for the multiple tests and a confidence band that can be used to simultaneously test multiple parameters for no effect after almost all frequentist estimation commands. I also provide an introduction to the literature on simultaneous inference.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49237775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
posw: A command for the stepwise Neyman-orthogonal estimator posw：阶跃Neyman正交估计器的一个命令
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175272
D. Drukker, Di Liu
{"title":"posw: A command for the stepwise Neyman-orthogonal estimator","authors":"D. Drukker, Di Liu","doi":"10.1177/1536867X231175272","DOIUrl":"https://doi.org/10.1177/1536867X231175272","url":null,"abstract":"Inference for structural and treatment parameters while having high-dimensional covariates in the model is increasingly common. The Neyman-orthogonal (NO) estimators in Belloni, Chernozhukov, and Wei (2016, Journal of Business and Economic Statistics 34: 606–619) produce valid inferences for the parameters of interest while using generalized linear model lasso methods to select the covariates. Drukker and Liu (2022, Econometric Reviews 41: 1047–1076) extended the estimators in Belloni, Chernozhukov, and Wei (2016) by using a Bayesian information criterion stepwise method and a testing-stepwise method as the covariate selector. Drukker and Liu (2022) found a family of data-generating processes for which the NO estimator based on Bayesian information criterion stepwise produces much more reliable inferences than the lasso-based NO estimator. In this article, we describe the implementation of posw, a command for the stepwise-based NO estimator for the high-dimensional linear, logit, and Poisson models.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44242190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Lagrange multiplier test for the mean stationarity assumption in dynamic panel-data models 动态面板数据模型中平均平稳性假设的拉格朗日乘子检验
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175276
Laura Magazzini, G. Calzolari
{"title":"A Lagrange multiplier test for the mean stationarity assumption in dynamic panel-data models","authors":"Laura Magazzini, G. Calzolari","doi":"10.1177/1536867X231175276","DOIUrl":"https://doi.org/10.1177/1536867X231175276","url":null,"abstract":"In this article, we describe the xttestms command, which implements the Lagrange multiplier test proposed by Magazzini and Calzolari (2020, Econometric Reviews 39: 115–134). The test verifies the validity of the initial conditions in dynamic panel-data models, which is required for consistency of the system generalized method of moments estimator.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44575641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Software Updates 软件更新
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175350
G. Longton
{"title":"Software Updates","authors":"G. Longton","doi":"10.1177/1536867X231175350","DOIUrl":"https://doi.org/10.1177/1536867X231175350","url":null,"abstract":"The most important change in this update is the addition of the subcommand breakdown, which issues a report on different missing values; that is, the numbers present as 1) empty strings \"\" if string variables are included and 2) system missing and extended missing values if numeric variables are included. This subcommand is most obviously useful as a check on the presence of extended missing values for numeric variables.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46768549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
lgrgtest: Lagrange multiplier test after constrained maximum-likelihood estimation lgrgtest:约束最大似然估计后的拉格朗日乘数检验
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175265
H. Tauchmann
{"title":"lgrgtest: Lagrange multiplier test after constrained maximum-likelihood estimation","authors":"H. Tauchmann","doi":"10.1177/1536867X231175265","DOIUrl":"https://doi.org/10.1177/1536867X231175265","url":null,"abstract":"Besides the Wald and likelihood-ratio tests, the Lagrange multiplier test (Rao, 1948, Mathematical Proceedings of the Cambridge Philosophical Society 44: 50–57; Aitchison and Silvey, 1958, Annals of Mathematical Statistics 29: 813–828; Silvey, 1959, Annals of Mathematical Statistics 30: 389–407) is the third canonical approach to testing hypotheses after maximum likelihood estimation. While the Stata commands test and lrtest implement the first two, Stata does not have an official command for implementing the third. The community-contributed boottest package (Roodman et al., 2019, Stata Journal 19: 4–60) focuses on methods of bootstrap inference and also implements the Lagrange multiplier test functionality. In this article, I introduce the new community-contributed postestimation command lgrgtest, which allows for straightforwardly using the Lagrange multiplier test after constrained maximum-likelihood estimation. lgrgtest is intended to be compatible with all Stata estimation commands that use maximum likelihood and allow for the options constraints(), iterate(), and from(). lgrgtest can also be used after cnsreg.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47055657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ginteff: A generalized command for computing interaction effects ginteff:计算交互效果的通用命令
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175253
Marius Radean
{"title":"ginteff: A generalized command for computing interaction effects","authors":"Marius Radean","doi":"10.1177/1536867X231175253","DOIUrl":"https://doi.org/10.1177/1536867X231175253","url":null,"abstract":"Interaction analyses are useful tools to examine complex socioeconomic outcomes in which the effect of one variable depends on the presence or values of another variable. Interaction effects capture simultaneous changes in two (or more) covariates, and their computation is especially challenging in nonlinear models. For such models, a statistically significant interaction-term coefficient does not necessarily indicate significant interactive effects. For analyses in which the interaction effect cannot be inferred from the model estimates, I introduce ginteff, a new command that automatically computes two- and three-way interaction effects. The command accommodates a large suite of estimation models and allows researchers to use either the partial derivative or the first difference to model the effect of the interacted variables.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47838342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
xtnumfac: A battery of estimators for the number of common factors in time series and panel-data models xtnumfacc:一组用于时间序列和面板数据模型中公共因子数量的估计器
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175305
J. Ditzen, Simon Reese
{"title":"xtnumfac: A battery of estimators for the number of common factors in time series and panel-data models","authors":"J. Ditzen, Simon Reese","doi":"10.1177/1536867X231175305","DOIUrl":"https://doi.org/10.1177/1536867X231175305","url":null,"abstract":"In this article, we introduce a new community-contributed command, xtnumfac, for estimating the number of common factors in time-series and panel datasets using the methods of Bai and Ng (2002, Econometrica 70: 191–221), Ahn and Horenstein (2013, Econometrica 81: 1203–1227), Onatski (2010, Review of Economics and Statistics 92: 1004–1016), and Gagliardini, Ossola, and Scaillet (2019, Journal of Econometrics 212: 503–521). Common factors are usually unobserved or unobservable. In time series, they influence all predictors, while in paneldata models, they influence all cross-sectional units at different degrees. Examples are shocks from oil prices, inflation, or demand or supply shocks. Knowledge about the number of factors is key for multiple econometric estimation methods, such as Pesaran (2006, Econometrica 74: 967–1012), Bai (2009, Econometrica 77: 1229–1279), Norkute et al. (2021, Journal of Econometrics 220: 416–446), and Kripfganz and Sarafidis (2021, Stata Journal 21: 659–686). This article discusses a total of 10 methods to estimate the number of common factors. Examples based on Kapetanios, Pesaran, and Reese (2021, Journal of Econometrics 221: 510–541) show that U.S. house prices are exposed to up to 10 common factors. Therefore, when one fits models with house prices as a dependent variable, the number of factors must be considered.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48709907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Reporting empirical results to .docx files 将经验结果报告到.docx文件
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175334
Yuan Xue, Chuntao Li, Haitao Si
{"title":"Reporting empirical results to .docx files","authors":"Yuan Xue, Chuntao Li, Haitao Si","doi":"10.1177/1536867X231175334","DOIUrl":"https://doi.org/10.1177/1536867X231175334","url":null,"abstract":"Reporting empirical results to automatically generate structured tables is important but time consuming for empirical researchers. Because of the lack of commands that can effectively create and edit Office Open XML documents (.docx documents), neither official commands nor community-contributed commands could tabulate results to this regularly used document type until putdocx was launched in Stata 15. In this article, we introduce four new commands: sum2docx, corr2docx, t2docx, and reg2docx. These new commands are all based on putdocx. They can be coalesced and can report summary statistics, correlation coefficient matrices, split-sample t tests, and regression results automatically in one .docx file. The commands are user friendly and can provide researchers with new options for reporting empirical results.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47777032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Pseudo-observations in a multistate setting 多态设置中的伪观测
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-06-01 DOI: 10.1177/1536867X231175332
M. Overgaard, Per K. Andersen, E. Parner
{"title":"Pseudo-observations in a multistate setting","authors":"M. Overgaard, Per K. Andersen, E. Parner","doi":"10.1177/1536867X231175332","DOIUrl":"https://doi.org/10.1177/1536867X231175332","url":null,"abstract":"Regression analyses of how state occupation probabilities or expected lengths of stay depend on covariates in multistate settings can be performed using the pseudo-observation method, which involves calculating jackknife pseudo-observations based on some estimator of the expected value of the outcome. In this article, we present a new command, stpmstate, that calculates such pseudo-observations based on the Aalen–Johansen estimator. We give examples of use of the command, and we conduct a small simulation study to offer insights into the pseudo-observation regression approach.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46167390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
robustpf: A command for robust estimation of production functions robustpf：生产函数的鲁棒估计命令
IF 4.8 2区 数学
Stata Journal Pub Date : 2023-03-01 DOI: 10.1177/1536867X231161977
Yingyao Hu, Guofang Huang, Yuya Sasaki
{"title":"robustpf: A command for robust estimation of production functions","authors":"Yingyao Hu, Guofang Huang, Yuya Sasaki","doi":"10.1177/1536867X231161977","DOIUrl":"https://doi.org/10.1177/1536867X231161977","url":null,"abstract":"We introduce a new command, robustpf, to estimate parameters of Cobb–Douglas production functions. The command is robust against two potential problems. First, it is robust against optimization errors in firms’ input choice, unobserved idiosyncratic cost shocks, and measurement errors in proxy variables. In particular, the command relaxes the conventional assumption of scalar unobservables. Second, it is also robust against the functional dependence problem of static input choice, which is known today as a cause of identification failure. The main method is proposed by Hu, Huang, and Sasaki (2020, Journal of Econometrics 215: 375–398).","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41969555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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