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xtusreg: Software for dynamic panel regression under irregular time spacing xtusreg：不规则时间间隔下的动态面板回归软件
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-09-01 DOI: 10.1177/1536867X221124567
Yuya Sasaki, Yi Xin
{"title":"xtusreg: Software for dynamic panel regression under irregular time spacing","authors":"Yuya Sasaki, Yi Xin","doi":"10.1177/1536867X221124567","DOIUrl":"https://doi.org/10.1177/1536867X221124567","url":null,"abstract":"We introduce a new command, xtusreg, that estimates parameters of fixed-effects dynamic panel regression models under unequal time spacing. After reviewing the method, we examine the finite-sample performance of the command using simulated data. We also illustrate the command with the National Longitudinal Survey Original Cohorts: Older Men, whose personal interviews took place in the unequally spaced years of 1966, 1967, 1969, 1971, 1976, 1981, and 1990. The methods underlying xtusreg are those discussed by Sasaki and Xin (2017, Journal of Econometrics 196: 320–330).","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45917182","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 mixture of ordered probit models with endogenous switching between two latent classes 在两个潜在类别之间具有内生转换的有序概率模型的混合
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-09-01 DOI: 10.1177/1536867X221124516
J. Huismans, Jan Willem Nijenhuis, A. Sirchenko
{"title":"A mixture of ordered probit models with endogenous switching between two latent classes","authors":"J. Huismans, Jan Willem Nijenhuis, A. Sirchenko","doi":"10.1177/1536867X221124516","DOIUrl":"https://doi.org/10.1177/1536867X221124516","url":null,"abstract":"Ordinal responses can be generated, in a cross-sectional context, by different unobserved classes of population or, in a time-series context, by different latent regimes. We introduce a new command, swopit, that fits a mixture of ordered probit models with exogenous or endogenous switching between two latent classes (regimes). Switching is endogenous if unobservables in the classassignment model are correlated with unobservables in the outcome models. We provide a battery of postestimation commands; assess via Monte Carlo experiments the finite-sample performance of the maximum likelihood estimator of the parameters, probabilities, and their standard errors (both the asymptotic and bootstrap ones); and apply the new command to model the monetary policy interest rates.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44860851","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
Panel unit-root tests with structural breaks 具有结构断裂的面板单位根检验
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-09-01 DOI: 10.1177/1536867X221124541
Pengyu Chen, Yiannis Karavias, Elias Tzavalis
{"title":"Panel unit-root tests with structural breaks","authors":"Pengyu Chen, Yiannis Karavias, Elias Tzavalis","doi":"10.1177/1536867X221124541","DOIUrl":"https://doi.org/10.1177/1536867X221124541","url":null,"abstract":"In this article, we introduce a new community-contributed command called xtbunitroot, which implements the panel-data unit-root tests developed by Karavias and Tzavalis (2014, Computational Statistics and Data Analysis 76: 391–407). These tests allow for one or two structural breaks in deterministic components of the series and can be seen as panel-data counterparts of the tests by Zivot and Andrews (1992, Journal of Business and Economic Statistics 10: 251–270) and Lumsdaine and Papell (1997, Review of Economics and Statistics 79: 212–218). The dates of the breaks can be known or unknown. The tests allow for intercepts and linear trends, nonnormal errors, and cross-section heteroskedasticity and dependence. They have power against homogeneous and heterogeneous alternatives and can be applied to panels with small or large time-series dimensions.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47534244","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: 11
Computing decomposable multigroup indices of segregation 可分解多群分离指数的计算
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-09-01 DOI: 10.1177/1536867X221124471
Daniel Guinea-Martin, Ricardo Mora
{"title":"Computing decomposable multigroup indices of segregation","authors":"Daniel Guinea-Martin, Ricardo Mora","doi":"10.1177/1536867X221124471","DOIUrl":"https://doi.org/10.1177/1536867X221124471","url":null,"abstract":"Eight multigroup segregation indices are decomposable into a between and a within term. They are two versions of 1) the mutual information index, 2) the symmetric Atkinson index, 3) the relative diversity index, and 4) Theil’s H index. In this article, we present the command dseg, which obtains all of them. It contributes to the stock of segregation commands in Stata by 1) implementing the decomposition in a single call, 2) providing the weights and local indices used in the computation of the within term, 3) facilitating the deployment of the decomposability properties of the eight indices in complex scenarios that demand tailor-made solutions, and 4) leveraging sample data with bootstrapping and approximate randomization tests. We analyze 2017 census data of public schools in the United States to illustrate the use of dseg. The subject topic is school racial segregation.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44518937","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
Panel stochastic frontier models with endogeneity 具有内生性的面板随机前沿模型
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-09-01 DOI: 10.1177/1536867X221124539
M. Karakaplan
{"title":"Panel stochastic frontier models with endogeneity","authors":"M. Karakaplan","doi":"10.1177/1536867X221124539","DOIUrl":"https://doi.org/10.1177/1536867X221124539","url":null,"abstract":"In this article, I introduce xtsfkk as a new command for fitting panel stochastic frontier models with endogeneity. The advantage of xtsfkk is that it can control for the endogenous variables in the frontier and the inefficiency term in a longitudinal setting. Hence, xtsfkk performs better than standard panel frontier estimators such as xtfrontier that overlook endogeneity by design. Moreover, xtsfkk uses Mata’s moptimize() functions for substantially faster execution and completion speeds. I also present a set of Monte Carlo simulations and examples demonstrating the performance and usage of xtsfkk.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48763100","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: 5
graphiclasso: Graphical lasso for learning sparse inverse-covariance matrices graphiclasso：学习稀疏逆协方差矩阵的图形套索
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-09-01 DOI: 10.1177/1536867X221124538
A. Dallakyan
{"title":"graphiclasso: Graphical lasso for learning sparse inverse-covariance matrices","authors":"A. Dallakyan","doi":"10.1177/1536867X221124538","DOIUrl":"https://doi.org/10.1177/1536867X221124538","url":null,"abstract":"In modern multivariate statistics, where high-dimensional datasets are ubiquitous, learning large (inverse-) covariance matrices is imperative for data analysis. A popular approach to estimating a large inverse-covariance matrix is to regularize the Gaussian log-likelihood function by imposing a convex penalty function. In a seminal article, Friedman, Hastie, and Tibshirani (2008, Biostatistics 9: 432–441) proposed a graphical lasso (Glasso) algorithm to efficiently estimate sparse inverse-covariance matrices from the convex regularized log-likelihood function. In this article, I first explore the Glasso algorithm and then introduce a new graphiclasso command for the large inverse-covariance matrix estimation. Moreover, I provide a useful command for tuning parameter selection in the Glasso algorithm using the extended Bayesian information criterion, the Akaike information criterion, and cross-validation. I demonstrate the use of Glasso using simulation results and real-world data analysis.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44870771","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
Flexible parametric survival analysis with multiple timescales: Estimation and implementation using stmt 多时间尺度的灵活参数生存分析:使用stmt的估计和实现
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-09-01 DOI: 10.1177/1536867X221124552
H. Bower, T. Andersson, M. Crowther, P. Lambert
{"title":"Flexible parametric survival analysis with multiple timescales: Estimation and implementation using stmt","authors":"H. Bower, T. Andersson, M. Crowther, P. Lambert","doi":"10.1177/1536867X221124552","DOIUrl":"https://doi.org/10.1177/1536867X221124552","url":null,"abstract":"In this article, we describe methodology that allows for multiple timescales using flexible parametric survival models without the need for time splitting. When one fits flexible parametric survival models on the log-hazard scale, numerical integration is required in the log likelihood to fit the model. The use of numerical integration allows incorporation of arbitrary functions of time into the model and hence lends itself to the inclusion of multiple timescales in an appealing way. We describe and exemplify these methods and show how to use the command stmt , which implements these methods, alongside its postestimation commands.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41889346","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 : 2022-09-01 DOI: 10.1177/1536867x221124568
{"title":"Software Updates","authors":"","doi":"10.1177/1536867x221124568","DOIUrl":"https://doi.org/10.1177/1536867x221124568","url":null,"abstract":"Patching your computer is one of the most important ways to protect yourself online. Windows users should turn on Windows Update [2] and set it to download and install patches automatically Additionally make sure Microsoft Updates [3] has been activated so that Office and other Microsoft updates are being applied. For Mac OS X, patches are installed via the App Store [4], and the settings can be checked under System Preferences>App Store.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47255477","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
kpsstest: A command that implements the Kwiatkowski, Phillips, Schmidt, and Shin test with sample-specific critical values and reports p-values kpsstest:使用特定于样本的临界值实现Kwiatkowski、Phillips、Schmidt和Shin检验并报告p值的命令
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-06-01 DOI: 10.1177/1536867X221106371
Alifyah Y Kagalwala
{"title":"kpsstest: A command that implements the Kwiatkowski, Phillips, Schmidt, and Shin test with sample-specific critical values and reports p-values","authors":"Alifyah Y Kagalwala","doi":"10.1177/1536867X221106371","DOIUrl":"https://doi.org/10.1177/1536867X221106371","url":null,"abstract":"Commonly used unit-root tests in time-series analysis—such as the Dickey–Fuller and Phillips–Perron tests—use a null hypothesis that the series contains a unit root. Such tests have low power against the alternative—when a time series is near integrated or highly autoregressive—implying that they do poorly in distinguishing such a series from having a unit root. Kwiatkowski et al. (1992, Journal of Econometrics 54: 159–178) introduced the Kwiatkowski, Phillips, Schmidt, and Shin test, in which the null hypothesis is that the series is stationary, to deal with this problem. One shortcoming of the presently available Kwiatkowski, Phillips, Schmidt, and Shin test in Stata is that it uses asymptotic critical values regardless of the sample size. This poses a problem in that researchers—especially social scientists—are often presented with short time series. I introduce kpsstest, a command that extends the previous implementation by including an option for a zero-mean-stationary null hypothesis, generating sample and test-specific critical values, and reporting appropriate p-values.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43112305","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: 4
uirt: A command for unidimensional IRT modeling uirt：用于一维IRT建模的命令
IF 4.8 2区 数学
Stata Journal Pub Date : 2022-06-01 DOI: 10.1177/1536867X221106368
Bartosz Kondratek
{"title":"uirt: A command for unidimensional IRT modeling","authors":"Bartosz Kondratek","doi":"10.1177/1536867X221106368","DOIUrl":"https://doi.org/10.1177/1536867X221106368","url":null,"abstract":"In this article, I introduce the uirt command, which allows one to estimate parameters of a variety of unidimensional item response theory models (two-parameter logistic model, three-parameter logistic model, graded response model, partial credit model, and generalized partial credit model). uirt has extended item-fit analysis capabilities, features multigroup modeling, allows testing for differential item functioning, and provides tools for generating plausible values with a latent regression conditioning model. I provide examples to illustrate cases where uirt can be especially useful in conducting analyses within the item response theory approach.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48002765","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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