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number of items: 8
total items: 8
item list element: Modern Difference-in-Differences: New Problems, New Solutions - Linear Regression and Panel Data in STATA
item list element: Visualizing Geospatial Data In Stata: Spatial Maps In Stata - Live Online Course
item list element: XIX Italian Stata Conference
item list element: Up and Running in Stata - Live Online Training
item list element: Non-Linear Panel Data Models in Stata - Live Online Training Course
item list element: Linear Panel Data Models in Stata - Live Online Training Course
item list element: Maximising the Potential of Stata’s new Python Capabilities - Live Online Course
item list element: Top Professional Training Courses in Economics
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Modern Difference-in-Differences: New Problems, New Solutions - Linear Regression and Panel Data in STATA
type: Course
title: Modern Difference-in-Differences: New Problems, New Solutions - Linear Regression and Panel Data in STATA
description: PREREQUISITES Working knowledge of linear regression and basic familiarity with panel data concepts (fixed effects, clustering) Prior experience with Stata is expected No prior exposure to the new DiD literature is assumed — the workshop builds from the ground up PROGRAM SESSION I: SIMPLE DID DESIGNS The 2×2 design 2×T event studies Parallel trends Interpreting ATT parameters as estimands Clustering and standard errors SESSION II: VIOLATIONS OF PARALLEL TRENDS Covariates Triple differences Compositional changes over time Addressing weak overlap SESSION III: DIFFERENTIAL TIMING Two-way fixed effects problems Goodman-Bacon decomposition, Callaway and Sant’Anna, Sun and Abraham, Borusyak et al., Wooldridge Imputation vs. weighting estimators SESSION IV: SENSITIVITY ANALYSIS Bounding parallel trends violations Sensitivity of results across packages and languages SESSION V: CONTINUOUS DID AND DOSAGE DESIGNS Extending difference-in-differences to continuous treatments and dosage frameworks SESSION VI: A MODEST SUGGESTION OF CHECKS Walk-throughs using several empirical examples, all in Stata Practical guidance on reporting and diagnostics DATE AND LOCATION This Workshop is being offered on the second day of the Italian Stata Users Conference that will take place in Milan, on the 17th-18th September 2026. COURSE LEADERS Scott Cunningham – Ben H. Williams Professor of Economics, Baylor University REGISTRATION FEE AND REGISTRATION FORM Conference Conference and Workshop Students and PhD Students* full-time € 60.00 € 195.00 Other € 110.00 € 420.00 All participation fees are subject to VAT (applied at the current Italian rate of 22%); *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Individuals interested in participating should return their duly completed registration forms to the conference organizers by the 10.09.2026 at the very latest. To request further information or the registration form…
disambiguating description: This Workshop is being offered on the second day of the Italian Stata Users Conference that will take place in Milan, on the 17th-18th September 2026.
date posted: 2026-08-06T12:18:11Z
date modified: 2026-08-06T12:22:11Z
valid through: 2026-09-10T21:59:59Z
start date: 2026-09-18T08:00:00Z
end date: 2026-09-18T21:59:59Z
hiring organization: TStat Training
job location: Place
  address: PostalAddress
    address locality: Milan
    address region: Lombardy
    address country: IT
employment type: onsite
language: en
keywords: Panel data
keywords: TStat Training
keywords: Linear Regression
keywords: Stata Training
keywords: Stata
keywords: TStat
type: course
disciplines: economics
disciplines: socialscience
disciplines: econometricsstatisticsquantitative
disciplines: statistics
discipline labels: Economics
discipline labels: Economics and Social Sciences
discipline labels: Econometrics, Statistics and Quantitative Methods (JEL C)
discipline labels: Statistics
more info url: https://www.tstat.eu/formazione/modern-difference-in-differences-new-problems-new-solutions/

Visualizing Geospatial Data In Stata: Spatial Maps In Stata - Live Online Course
type: Course
title: Visualizing Geospatial Data In Stata: Spatial Maps In Stata - Live Online Course
description: The creation of spatial maps has become a valuable tool for researchers interested in both the spatial data visualization and the identification of geographical patterns in the data. This interactive course therefore, offers an introduction to the mapping techniques currently available in Stata for visualization of geospatial data. The workshop opens with an overview of the peculiar characteristics of geospatial data, the implications of such for the analysis of such data and an overview of the special terminology used in this field, before moving on to discuss the concept of spatial proximity and its relevance to the visualization of spatial data analysis. The remainder of the workshop is dedicated to the principle mapping techniques, using a combination of both official Stata commands and a series of user written commands, currently adopted to visualize geospatial data in Stata. Participants will learn how to import geospatial data shapefiles in Stata and merge them with their existing Stata databases in order to create, compare and customize different mapping techniques. At the end of the course, participants will be able to autonomously implement (with the help of the Stata routine templates specifically developed for the workshop) the appropriate mapping methods, given both the nature of their spatial data and the analysis in hand, within their own research. TARGET AUDIENCE This online course is of particular interest for criminologists, social psychologists, sociologists, economists, epidemiologists and political scientists seeking to acquire the requisite tools required for the exploration and visualisation of spatial data in Stata. PREREQUISITES A knowledge of basic statistics (distributions of variables, position indices, dispersion indices) and the statistical software Stata is recommended. PROGRAM SESSION I: SPATIAL DATA 1. General characteristics of spatial data 2. Types of spatial objects 3. Spatial coordinate systems 4. Maps and shapefiles 5. The trans…
disambiguating description: This interactive online course offers an introduction to the mapping techniques currently available in Stata for visualization of geospatial data. The next edition of this training course will be offered online on a part-time basis on the 30th of September.
date posted: 2026-01-05T10:20:22Z
date modified: 2026-07-22T07:10:45Z
valid through: 2026-09-20T21:59:59Z
start date: 2026-09-30T08:00:00Z
end date: 2026-09-30T11:30:00Z
hiring organization: TStat Training
job location type: TELECOMMUTE
employment type: online
language: en
keywords: Geospatial Data
keywords: Spatial Maps
keywords: Stata
keywords: Geoeconomics
type: course
disciplines: othereconomics
disciplines: economics
disciplines: socialscience
disciplines: econometricsstatisticsquantitative
disciplines: datascience
disciplines: urbanruraltransportationeconomics
discipline labels: Other Special Economics Topics (JEL Z)
discipline labels: Economics
discipline labels: Economics and Social Sciences
discipline labels: Econometrics, Statistics and Quantitative Methods (JEL C)
discipline labels: Data Science
discipline labels: Urban, Rural and Transportation Economics (JEL R)
more info url: https://www.tstat.eu/formazione/visual-analysis-spatial-data-mapping-stata-ol/

XIX Italian Stata Conference
type: Event
title: XIX Italian Stata Conference
description: XIX Italian Stata Conference Milano, 17-18 September 2026 CALL FOR PAPERS This year the Italian Stata Conference will be held in Milan on the 17th-18th September 2026. The meeting offers participants a unique forum for interdisciplinary exchange through both the presentation of new community user written commands and applied work developed in Stata, giving researchers the opportunity to: EXCHANGE both new community written routines and Tips and Tricks developed for Stata; DISCOVER new applications highlighting Stata 19’s potential capabilities for applied research; MEET Stata users from different disciplinary areas; INTERACT directly with statisticians from StataCorp. We are particularly looking for: New user COMMANDS / ROUTINES focusing on: new estimation methods; user written routines both short and long, developed simply to make life easier in Stata for our “Tips and Tricks” session; Stata’s connectivity to external applications, such as Python, R or Java; and reporting tools for the creation of dynamic dashboards or automatic internet publishing; data visualization. APPLIED STUDIES exploiting the latest methodologies introduced in Stata 19 are also welcome. The second day of the conference will be dedicated to a Stata training course, the subject of which will be announced in due course. SUBMISSION OF ABSTRACTS Stata users interested in participating in the conference are required to submit their proposals via email to the Scientific Committee at conference@tstat.it by the 15.07.2026. The accompanying e-mail should include the following information: the name of the author(s), affiliation, together with a current telephone contact, should we need to contact you. Please note that presentations are “normally” 25 minutes long, followed by 10 minutes of discussion. Longer presentations are also welcome; in such cases, we ask that authors indicate the additional time required. Presentations for the Tips and Tricks session, on the other hand, can range from 5 to 25 min…
disambiguating description: Call for Papers for the upcoming XIX Italian Stata Conference taking place in Milan.
date posted: 2026-06-11T09:56:04Z
date modified: 2026-07-05T09:10:45Z
valid through: 2026-09-10T21:59:59Z
start date: 2026-09-17T08:00:00Z
end date: 2026-09-18T21:59:59Z
hiring organization: TStat Training
job location: Place
  address: PostalAddress
    address locality: Milan
    address region: Lombardy
    address country: IT
employment type: onsite
language: en
keywords: Stata Users Conference
keywords: Stata Italy
keywords: Stata Conference
keywords: TStat
type: conference
disciplines: economics
disciplines: socialscience
disciplines: econometricsstatisticsquantitative
disciplines: statistics
discipline labels: Economics
discipline labels: Economics and Social Sciences
discipline labels: Econometrics, Statistics and Quantitative Methods (JEL C)
discipline labels: Statistics
more info url: https://www.tstat.it/tstat/wp-content/uploads/2026/01/Call_for_Papers_SUG_TStat2026_EN.pdf

Up and Running in Stata - Live Online Training
type: Course
title: Up and Running in Stata - Live Online Training
description: TStat live online training courses are offered interactively via Zoom with a qualified trainer in real-time. All materials (slides, datasets and Stata routines specifically developed for the course) are made available for download before the start of the course. COURSE DESCRIPTION Up and Running in Stata provides participants with the necessary introductory toolset to enable them to carry out efficient data analysis and data management in Stata in a reproducible manner. The interactive course covers everything from the very basics, in order to get one up and running in Stata, to an overview of the available Stata commands for preliminary data analysis, data management, importing and exporting data formats, merging of databases and the creation of graphs in Stata. In common with TStat’s training philosophy, Up and Running in Stata is by its very nature to be considered very much a hands on approach to learning Stata course. Each individual session is composed of both a theoretical component and an applied segment, during which participants have the opportunity to implement the techniques illustrated under the watchful eye of the course tutor. COURSE ID: D-IN10-OL LANGUAGE: English TARGET AUDIENCE This interactive online course is invaluable to both professionals and researchers (working in Epidemiology, Business Studies, Marketing and Management, Biostatistics, Economics, Epidemiology, Medicine, Public Health, Social and Political Sciences and Statistics), wishing to use Stata for applied statistical analysis, data management or data visualization. PREREQUISITES Familiarity with PCs and a working knowledge of English. PROGRAM SESSION I: GETTING STARTED SESSION II: STATA FUNDAMENTALS SESSION III: CREATING SIMPLE STATA ROUTINES: DO FILES SESSION IV: IMPORTING DATA FROM SPREADSHEETS SESSION V: MERGING DATA BASES SESSION VI: GRAPHICS – AN INTRODUCTION SUGGESTED READINGS - Acock, A. (2023). A Gentle Introduction to Stata. Revised Sixth Edition. Stata Press Publication. - …
disambiguating description: Up and Running in Stata provides participants with the necessary introductory toolset to enable them to carry out efficient data analysis and data management in Stata in a reproducible manner. The next 2026 edition of this training course will be offered online on a part-time basis on the 2nd-3rd, 9th-10th of July from 9:30 am to 1:30 pm CEST.
date posted: 2026-01-14T12:14:12Z
date modified: 2026-06-01T06:50:45Z
valid through: 2026-06-22T21:59:59Z
start date: 2026-07-02T08:00:00Z
end date: 2026-07-10T11:30:59Z
hiring organization: TStat Training
job location: Place
  address: PostalAddress
    address locality: Sulmona
    address region: Abruzzo
job location type: TELECOMMUTE
employment type: online
language: en
keywords: data analysis
keywords: Stata
keywords: webinar
keywords: TStat
type: course
disciplines: economics
disciplines: socialscience
disciplines: econometricsstatisticsquantitative
disciplines: datascience
disciplines: statistics
discipline labels: Economics
discipline labels: Economics and Social Sciences
discipline labels: Econometrics, Statistics and Quantitative Methods (JEL C)
discipline labels: Data Science
discipline labels: Statistics
more info url: https://www.tstat.eu/formazione/up-running-stata-2/

Non-Linear Panel Data Models in Stata - Live Online Training Course
type: Course
title: Non-Linear Panel Data Models in Stata - Live Online Training Course
description: COURSE DESCRIPTION Panel data analysis is increasingly used in econometrics, financial analysis, public health, political and social sciences, since it enable researchers to allow for different types of latent heterogeneity between observations. Allowing researchers for example, to control for variables that cannot be directly observed or measured, such as cultural factors or differences in business practices across companies. The use of Panel Data in empirical studies also tends to result in a considerable improvement in the accuracy of the obtained estimates, since panel data sets usually contain more sample variability and higher degrees of freedom. Finally, panel data allows for the estimation of dynamic models, with causal relationships which may not arise instantaneously, but over a period of time. This course follows on from our Linear Panel Data Models in Stata course to offer the necessary theoretical background and the applied skills to enable participants to: i) independently employ non-linear micro panel data techniques to their own research topics, and ii) to understand and evaluate micro panel data analyses published in the academic literature. The focus is therefore on non-linear estimation techniques (more specifically Poisson, Probit, Logit and Tobit panel data models) and issues of sample selection and attrition. In common with TStat’s training philosophy, each individual session is composed of both a theoretical component (in which the techniques and underlying principles behind them are explained), and an applied (hands-on) segment, during which participants have the opportunity to implement the techniques using real data under the watchful eye of the course tutor. Throughout the course, theoretical sessions are reinforced by case study examples, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques. The intuition behind the choice and implementation of a specific technique is of the utm…
disambiguating description: This course follows on from our Linear Panel Data Models in Stata course to offer the necessary theoretical background and the applied skills to enable participants to: i) independently employ non-linear micro panel data techniques to their own research topics, and ii) to understand and evaluate micro panel data analyses published in the academic literature. TStat Training’s live online training courses are offered interactively via Zoom with a qualified trainer in real-time. All materials (slides, datasets and Stata routines specifically developed for the course) are made available for download before the start of the course. The 2026 edition of this training course will be offered online on a part-time basis on the 22nd, 26th-27th of May.
date posted: 2026-04-17T08:54:10Z
date modified: 2026-05-18T08:01:42Z
valid through: 2026-05-12T21:59:59Z
start date: 2026-05-22T08:00:00Z
end date: 2026-05-27T21:59:59Z
hiring organization: TStat Training
job location type: TELECOMMUTE
employment type: online
language: en
keywords: Stata Training
keywords: Stata
keywords: Economics Software
keywords: Modelling Software
keywords: TStat
type: course
disciplines: economics
disciplines: socialscience
disciplines: econometricsstatisticsquantitative
disciplines: datascience
disciplines: statistics
discipline labels: Economics
discipline labels: Economics and Social Sciences
discipline labels: Econometrics, Statistics and Quantitative Methods (JEL C)
discipline labels: Data Science
discipline labels: Statistics
more info url: https://www.tstat.eu/formazione/nonlinear-panel-data-models-stata-ol/

Linear Panel Data Models in Stata - Live Online Training Course
type: Course
title: Linear Panel Data Models in Stata - Live Online Training Course
description: COURSE DESCRIPTION Panel data analysis is increasingly used in econometrics, financial analysis, public health, political and social sciences, since it enable researchers to allow for different types of latent heterogeneity between observations. Allowing researchers for example, to control for variables that cannot be directly observed or measured, such as cultural factors or differences in business practices across companies. The use of Panel Data in empirical studies also tends to result in a considerable improvement in the accuracy of the obtained estimates, since panel data sets usually contain more sample variability and higher degrees of freedom. Finally, panel data allows for the estimation of dynamic models, with causal relationships which may not arise instantaneously, but over a period of time. This introductory course offers participants the opportunity to acquire the necessary theoretical background and the applied skills to enable them to: i) independently employ micro panel data techniques to their own research topics, and ii) to understand and evaluate micro panel data analyses published in the academic literature. This course focuses on the linear model techniques adopted for the analysis of a typical micro panel-data set with a large number of individuals and a small number of time periods. Such techniques include: fixed and random effects models; robust inference and instrumental-variables estimators. In common with TStat’s training philosophy, each individual session is composed of both a theoretical component (in which the techniques and underlying principles behind them are explained), and an applied (hands-on) segment, during which participants have the opportunity to implement the techniques using real data under the watchful eye of the course tutor. Throughout the course, theoretical sessions are reinforced by case study examples, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques…
disambiguating description: This course focuses on the linear model techniques adopted for the analysis of a typical micro panel-data set with a large number of individuals and a small number of time periods. Such techniques include: fixed and random effects models; robust inference and instrumental-variables estimators. TStat Training’s live online training courses are offered interactively via Zoom with a qualified trainer in real-time. All materials (slides, datasets and Stata routines specifically developed for the course) are made available for download before the start of the course. The 2026 edition of this training course will be offered online on a part-time basis on the 23rd-24th, 28th-29th of April.
date posted: 2026-03-10T11:04:55Z
date modified: 2026-05-01T01:15:00Z
valid through: 2026-04-13T21:59:59Z
start date: 2026-04-23T08:00:00Z
end date: 2026-04-29T21:59:59Z
hiring organization: TStat Training
job location type: TELECOMMUTE
employment type: online
language: en
keywords: Online Economics Training
keywords: TStat Training
keywords: Linear Panel Data
keywords: Economics Modelling Course
keywords: TStat
type: course
disciplines: economics
disciplines: socialscience
disciplines: econometricsstatisticsquantitative
disciplines: statistics
discipline labels: Economics
discipline labels: Economics and Social Sciences
discipline labels: Econometrics, Statistics and Quantitative Methods (JEL C)
discipline labels: Statistics
more info url: https://www.tstat.eu/formazione/panel-data-analysis-stata-a-ol/

Maximising the Potential of Stata’s new Python Capabilities - Live Online Course
type: Course
title: Maximising the Potential of Stata’s new Python Capabilities - Live Online Course
description: COURSE DESCRIPTION TStat’s “Maximising the Potential of Stata’s New Python Capabilities” course offers participants an excellent opportunity to acquire the introductory programming skills required to integrate Python’s capability into Stata. The course opens with an introductory session focusing on the Python programming basics required by users wishing to exploit the Stata – Python connectivity, before moving on to illustrate how to use Python in a Stata environment and the vice versa. In the closing session a series of practical applications will be discussed in order to highlight WHEN and HOW one should exploit the connectivity between Python and Stata for one’s research. At the end of the course, participants are expected to be able, with the aid of the Stata routines implemented during the sessions, to independently implement the methodologies and techniques illustrated during the course by adopting the Stata routines to their own particular research needs. In common with TStat’s training philosophy, each session is composed of both a theoretical component (in which the techniques and underlying principles behind them are explained) and an applied (hands-on) segment, during which participants have the opportunity to implement the techniques using real data under the watchful eye of the course tutor. Throughout the course, theoretical sessions are reinforced using applied case studies, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques. TARGET AUDIENCE This course is of particular interest to sociologists, mathematicians, economists, ethnologists, epidemiologists and political scientists wishing to acquire the basic tools necessary to use Python routines within Stata. PREREQUISITES Participants should having a working knowledge of Stata. No prior knowledge of Python is necessary, although it will be an advantage. PROGRAM The potential of Stata/Python connectivity: an overview Python programming basic…
disambiguating description: The course opens with an introductory session focusing on the Python programming basics required by users wishing to exploit the Stata – Python connectivity, before moving on to illustrate how to use Python in a Stata environment and the vice versa. TStat Training’s live online training courses are offered interactively via Zoom with a qualified trainer in real-time. All materials (slides, datasets and Stata routines specifically developed for the course) are made available for download before the start of the course. The 2026 edition of this training course will be offered online on a part-time basis on the 9th-10th of April from 9:30 am to 2:00 pm CEST.
date posted: 2026-02-02T09:52:50Z
date modified: 2026-04-01T01:15:00Z
valid through: 2026-03-31T21:59:59Z
start date: 2026-04-09T08:00:00Z
end date: 2026-04-10T12:59:59Z
hiring organization: TStat Training
job location type: TELECOMMUTE
employment type: online
language: en
keywords: Python in Stata
keywords: Stata Training
keywords: Stata
keywords: learn stata
keywords: TStat
type: course
disciplines: othereconomics
disciplines: economics
disciplines: socialscience
disciplines: econometricsstatisticsquantitative
disciplines: statistics
discipline labels: Other Special Economics Topics (JEL Z)
discipline labels: Economics
discipline labels: Economics and Social Sciences
discipline labels: Econometrics, Statistics and Quantitative Methods (JEL C)
discipline labels: Statistics
more info url: https://www.tstat.eu/formazione/up-running-stata-2/

Top Professional Training Courses in Economics
type: Article
title: Top Professional Training Courses in Economics
description: Professional skills in economics include data analysis skills, developing practical solutions for complex problems, and of course knowledge of subject-specific economics concepts. For professionals working in economics, it's especially important to stay up to date with the latest developments in these rapidly-changing fields. This is especially true in a competitive job markets such as in the United States. Here is our selection of great professional economics training courses. TStatTraining Courses Location: Online, or on-site in various locations in Germany, Italy and more Dates: Courses take place throughout the year Fees: €240 - €2360, depending on topic, format and length of course TStat’s courses are characterized by their theoretical and applied structure. Each course is composed of both a theoretical component and an applied (hands-on) segment, during which participants are given the opportunity to implement these techniques using real data and the latest statistical software under the watchful eye of the course tutor. At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed in the course with the help of the software routines developed specifically for the course. TStat's training portfolio can be classified into three distinct categories: - introductory and advanced courses relating to the use of one of the statistical software which TStat distributes; - introductory/intermediate courses in biostatistics, epidemiology, econometrics, financial analysis, statistics and qualitative and quantitative text analysis; and - advanced “state of the art” courses in each of the aforementioned fields. Deadline: Ongoing Introduction to Python and R Programming for Data Science Provider: Barcelona School of Economics Location: Online Dates: 14 - 17 March 2023 Fee: €300 - €525 This is an 8-hour online course that provides an introduction to programming with Python and R for data analysis and machine …
disambiguating description: Learning shouldn't only be something which you do in school and university – in order to maximize your personal development and career prospects in economics, further education is always valuable online and in-person.
date posted: 2019-02-26T09:00:00Z
date modified: 2026-07-06T09:54:05Z
language: en
keywords: Professional Training
keywords: courses
keywords: economics
keywords: certificate
keywords: professional courses
keywords: course
keywords: training
keywords: professional certificate
keywords: finance
type: advice
disciplines: internationaleconomics
disciplines: economics
disciplines: socialscience
disciplines: financialeconomics
disciplines: econometricsstatisticsquantitative
disciplines: generaleconomics
disciplines: businesseconomics
disciplines: finance
disciplines: urbanruraltransportationeconomics
disciplines: statistics
discipline labels: International Economics (JEL F)
discipline labels: Economics
discipline labels: Economics and Social Sciences
discipline labels: Financial Economics (JEL G)
discipline labels: Econometrics, Statistics and Quantitative Methods (JEL C)
discipline labels: General Economics (JEL A)
discipline labels: Business Economics (JEL M)
discipline labels: Finance
discipline labels: Urban, Rural and Transportation Economics (JEL R)
discipline labels: Statistics