The Cox proportional hazards model is used routinely by researchers from many disciplines to analyze right-censored event-time data, where time to an event of interest is observed exactly. If you recognize the above, you know you want them!Īnd we have made these new features just as easy to use as the rest of the meta suite. Stata 17 adds the following to the excellent (IMHO) meta-analysis suite introduced in Stata 16: If you are studying the effect of a treatment (such as a drug regimen or policy) in observational data and are concerned that the effect may be influenced by time or by some other group effects, DID and DDD models provide intuitive methods to control for such unobserved effects. Read the details, including tables of specific speed gains.ĭID and difference-in-difference-in-differences (DDD) models are appealing to many disciplines, including econometrics, epidemiology, political science, public policy, and many more. We achieved speed gains in part through careful algorithm selection and implementation and in part through integration of the Intel Math Kernel Library (MKL) to underpin many of Mata’s linear algebra functions and operators. With larger datasets and more computationally intensive methods comes the above request, “Give me more speed.” Sometimes, our developers say, “I’m giving her all she’s got, Captain!”, but for Stata 17, they gave us all more. One notable feature is the ability to fit multivariate nonlinear models containing random effects such as multivariate nonlinear growth models.Īs computer capabilities have grown, so have dataset sizes. In addition to the new Bayesian features above that will be of most interest to econometricians, Stata 17 also adds Bayesian multilevel modeling with support for nonlinear, joint, SEM-like, and even more models. With Bayesian DSGE models, prior distributions give you a natural way to incorporate knowledge about model parameters that is motivated by the economic theory.Īs with Stata’s other Bayesian features, our aim is to make specification of these models as intuitive as possible and as similar to the specifications of the frequentist counterparts as possible.Īll the above is in addition to other existing Bayesian features of interest to econometricians such as Bayesian generalized linear models and Bayesian sample-selection models. The Bayesian approach provides a solution by incorporating specialized priors to allow you to obtain more stable parameter estimates.Īs with classical VAR models, you can perform IRF analysis and obtain dynamic forecasts but now within the Bayesian paradigm.īayesian panel-data models are appealing when you have few panels or when you would like to study and compare panel-specific effects. VAR models have many parameters but often not enough data to estimate them reliably. Many of you have been asking us for Bayesian VAR models. In Stata 17, we have added many features for Bayesian econometrics, including I suspect almost all users will be adding this to their Stata repertoire. Excel, HTML, LaTeX, Markdown, PDF, Stata SMCL, Word, and plain text are supported as export formats. Stata’s table command has been completely revamped, and a new collect command allows you to gather and manage results from multiple commands, which can then be shown in tabular form. These are among some of the most-used community-contributed commands! There has been an equally long tradition of the Stata user community asking us to provide more official features to assist with flexible table creation and export. There has been a long tradition in the Stata user community of commands that build various tables. I’ll share my thoughts on some of the new features below. Stronger.” I thought Daft Punk might not like it if we used that, so we aren’t, but really, it is a great overall description of the new version. Looking over this list of features, someone suggested that a potential marketing tagline for Stata 17 could be “Better. Bayesian linear and nonlinear DSGE models.Bayesian longitudinal/panel-data models.Bayesian multilevel models: Nonlinear, joint, SEM-like, and more. Difference-in-differences (DID) and DDD models.Visit /new-in-stata to read all about its 29 major new features.
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