Template-Type: ReDIF-Article 1.0 Author-Name: Heejun Lee Author-Email: heejun_lee@brown.edu Author-Workplace-Name: Brown University Author-Name: Arthur Lewbel Author-Email: lewbel@bc.edu Author-Workplace-Name: Boston College Author-Person: ple43 Author-Name: Susanne M. Schennach Author-Email: susanne_schennach@brown.edu Author-Workplace-Name: Brown University Author-Person: psc367 Author-Name: Linqi Zhang Author-Email: linqizhang@cuhk.edu.hk Author-Workplace-Name: Chinese University of Hong Kong Title: Instrument-free estimation of triangular equation systems with the trigmm command Journal: Stata Journal Pages: 68-89 Issue: 1 Volume: 26 Year: 2026 Month: March X-DOI: 10.1177/1536867X261425780 Abstract: In this article, we introduce trigmm, a package designed to estimate the parameters of triangular two-equation systems without the need for instrumental variables. The trigmm command leverages the identification conditions proposed by Lewbel, Schennach, and Zhang (2024, Journal of Business and Economic Statis- tics 42: 14–25), enabling instrument-free identification primarily through the non- Gaussianity assumption of error variables. We also introduce the trigmmset com- mand, which provides bounds on the parameters based on the set identification re- sults from the same article even without the non-Gaussianity assumption, offering complementary analyses alongside the trigmm command. Estimation is performed by integrating these moment conditions with Stata’s built-in generalized method of moments (gmm) framework. The package’s functionality is demonstrated through an empirical application. Keywords: trigmm, trigmmset, instrument-free identification, triangular system File-URL: http://hdl.handle.net/10.1177/1536867X261425780 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj26-1/st0797/ Handle:RePEc:tsj:stataj:v:26:y:2026:i:1:p:68-89 Template-Type: ReDIF-Article 1.0 Author-Name: Paul C. Lambert Author-Email: paul.lambert@fhi.no Author-Workplace-Name: Cancer Registry of Norway Author-Workplace-Name: Karolinska Institutet Author-Name: Mark J. Rutherford Author-Email: mark.rutherford@leicester.ac.uk Author-Workplace-Name: University of Leicester Title: The stpp command for marginal relative survival and related measures Journal: Stata Journal Pages: 7-37 Issue: 1 Volume: 26 Year: 2026 Month: March X-DOI: 10.1177/1536867X261425755 Abstract: For the analysis of survival data obtained from cancer registries, it is common to use the relative survival framework, which incorporates expected mortality rates rather than relying on cause-of-death information. The relative survival framework enables comparisons between population groups where the ef- fect of mortality due to the cancer is isolated to enable fair comparisons when there is differential other-cause mortality between the groups being compared. The stpp command provides nonparametric estimates of marginal relative survival and a range of other nonparametric estimates, including all-cause survival and crude probabilities of death and also recently developed reference-adjusted measures. In addition, it enables (age) standardization to be performed using both traditional standardization and the individual weighting approach. The genindweights com- mand simplifies the process of calculating individual weights. Keywords: stpp, genindweights, strs, stnet, relative survival, survival analysis File-URL: http://hdl.handle.net/10.1177/1536867X261425755 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj26-1/st0795/ Handle:RePEc:tsj:stataj:v:26:y:2026:i:1:p:7-37 Template-Type: ReDIF-Article 1.0 Author-Name: Jerônimo Oliveira Muniz Author-Email: jeronimo@ufmg.br Author-Workplace-Name: Universidade Federal de Minas Gerais Title: The own-children method of fertility estimation using Stata Journal: Stata Journal Pages: 38-67 Issue: 1 Volume: 26 Year: 2026 Month: March X-DOI: 10.1177/1536867X261425769 Abstract: In this article, I present the ownchild command, which calculates age-specific fertility rates using an advanced version of the own-children method, originally proposed by Grabill and Cho (1965, Demography 2: 50–73). ownchild provides a graphical representation of average fertility patterns by age over the last 15 years, generates weighted estimates for population subgroups, enhances accu- racy by restricting calculations to biological connections between children and their mothers, and delivers 15 reproductive measures. These measures include total and net fertility rates, mean age at childbearing, the percentage of teenage pregnan- cies, the proportion of childless women, the percentage of unmatched children, and the replacement level of fertility. I demonstrate the capabilities of ownchild using 2010 Brazilian Census microdata sourced from Integrated Public Use Microdata Series-International to calculate fertility rates by race. Keywords: ownchild, children, age, demography, fertility, reproduction, own-children, Brazil, survival File-URL: http://hdl.handle.net/10.1177/1536867X261425769 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj26-1/st0796/ Handle:RePEc:tsj:stataj:v:26:y:2026:i:1:p:38-67 Template-Type: ReDIF-Article 1.0 Author-Name: Fernando Rios-Avila Author-Email: friosa@upb.edu Author-Workplace-Name: Universidad Privada Boliviana Author-Person: pri214 Author-Name: Andrey Ramos Author-Email: andrey.ramos@bde.es Author-Workplace-Name: Bank of Spain Author-Name: Gustavo Canavire-Bacarreza Author-Email: gcanavire@worldbank.org Author-Workplace-Name: World Bank Author-Person: pca311 Author-Name: Leonardo Siles Author-Email: lsiles@fen.uchile.cl Author-Workplace-Name: Universidad de Chile Title: Estimation of quantile regressions with fixed effects Journal: Stata Journal Pages: 111-131 Issue: 1 Volume: 26 Year: 2026 Month: March X-DOI: 10.1177/1536867X261425793 Abstract: In this article, we introduce two new commands, qregfe and qregplot, that are designed for fitting and visualizing quantile regression models with fixed effects. qregfe provides a unified syntax for implementing three panel-data esti- mators that are commonly used in empirical research: 1) the correlated random- effects specification of Abrevaya and Dahl (2008, Journal of Business and Economic Statistics 26: 379–397); 2) the two-step location-shift estimator of Canay (2011, Econometrics Journal 14: 368–386); and 3) the method of moments quantile re- gression approach of Machado and Santos Silva (2019, Journal of Econometrics 213: 145–173). The companion command qregplot produces coefficient–quantile plots, allowing researchers to visualize how the coefficients of each covariate change across the outcome conditional distribution. Keywords: qregfe, qregplot, quantile regression, fixed effects, panel data File-URL: http://hdl.handle.net/10.1177/1536867X261425793 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj26-1/st0799/ Handle:RePEc:tsj:stataj:v:26:y:2026:i:1:p:111-131 Template-Type: ReDIF-Article 1.0 Author-Name: Lingyun Zhou Author-Email: zhouly.23@pbcsf.tsinghua.edu.cn Author-Workplace-Name: Tsinghua University Title: A robust test for weak instruments with multiple endogenous regressors in Stata Journal: Stata Journal Pages: 90-110 Issue: 1 Volume: 26 Year: 2026 Month: March X-DOI: 10.1177/1536867X261425792 Abstract: In this article, I introduce a novel command, weakivtest2, that imple- ments the robust bias-based test for weak instruments for two-stage least squares with multiple endogenous regressors proposed by Lewis and Mertens (Forthcom- ing, Review of Economic Studies, https: // doi.org / 10.1093 / restud / rdaf103). The weakivtest2 command allows for absolute and relative bias criteria, local- to-zero and local-to-rank-reduction-of-one asymptotics, and testing for either the full vector or the individual elements of the two-stage least-squares estimator. weakivtest2 is a postestimation command for ivreg2, xtivreg2, and ivreghdfe. Keywords: weakivtest2, weak instruments, pretesting, multiple endogenous regressors, heteroskedasticity, serial correlation File-URL: http://hdl.handle.net/10.1177/1536867X261425792 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj26-1/st0798/ Handle:RePEc:tsj:stataj:v:26:y:2026:i:1:p:90-110 Template-Type: ReDIF-Article 1.0 Author-Name: Richard Williams Author-Email: rwilliam@nd.edu Author-Workplace-Name: University of Notre Dame Author-Person: Title: Stata tip 167: Dealing with convergence issues and other seemingly inexplicable problems Journal: Stata Journal Pages: 144-151 Issue: 1 Volume: 26 Year: 2026 Month: March X-DOI: 10.1177/1536867X261425756 File-URL: http://hdl.handle.net/10.1177/1536867X261425756 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj26-1/st0800/ Handle:RePEc:tsj:stataj:v:26:y:2026:i:1:p:144-151 Template-Type: ReDIF-Article 1.0 Author-Name: Nicholas J. Cox Author-Email: n.j.cox@durham.ac.uk Author-Workplace-Name: Durham University Author-Person: pco34 Title: Speaking Stata: How to debug, part I Journal: Stata Journal Pages: 132-143 Issue: 1 Volume: 26 Year: 2026 Month: March X-DOI: 10.1177/1536867X261425801 File-URL: http://hdl.handle.net/10.1177/1536867X261425801 Abstract: Debugging code can be time-consuming, frustrating, and even dismaying, but it is essential for almost any Stata project that is at all original or challenging. In this column, I provide advice on debugging and a variety of exam- ples, structured around a series of simple tips. Read the help. Look at the code. Note or even create error messages. Debug actively. Simplify the problem first, complicate later. Attend to detail. Try to think like Stata. Try to think like the programmer. Find a Stata friend. Ask the Stata community. Keywords: debugging, coding, error messages, programming Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj26-1/pr0084/ Handle:RePEc:tsj:stataj:v:26:y:2026:i:1:p:132-143 Template-Type: ReDIF-Article 1.0 Author-Name: Stephen P. Jenkins Author-Email: S.jenkins@lse.ac.uk Author-Workplace-Name: London School of Economics and Political Science Author-Person: pje7 Author-Name: Nicholas J. Cox Author-Email: n.j.cox@durham.ac.uk Author-Workplace-Name: Durham University Author-Person: pco34 Title: Stata Journal Editors’ Report (articles and tips) Journal: Stata Journal Pages: 1-4 Issue: 1 Volume: 26 Year: 2026 Month: March X-DOI: 10.1177/1536867X261425740 File-URL: http://hdl.handle.net/10.1177/1536867X261425740 Handle:RePEc:tsj:stataj:v:26:y:2026:i:1:p:1-4