Modern Difference-in-Differences: New Problems, New Solutions - Linear Regression and Panel Data in STATA
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, please fill in the following form or send an email to training@tstat.eu
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.
Econometrics, Statistics and Quantitative Methods (JEL C)
Visualizing Geospatial Data In Stata: Spatial Maps In Stata - Live Online Course
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 transformation of spatial databases SESSION II: SPATIAL PROXIMITY 1. Spatial distance 2. Spatial proximity matrices 3. Spatial lags 4. Spatial autocorrelation SESSION III: VISUAL ANALYSIS OF SPATIAL DATA 1. Visual analytics and data science 2. Thematic maps 3. Dot maps 4. Graduated symbol maps 5. Diagram maps 6. Choropleth Maps 7. Isarithmic Maps 8. Multivariate Maps SUGGESTED READING Anthamatten, P. (2021). How to Make Maps: An Introduction to Theory and Practice of Cartography. Abingdon: Routledge. Lambert, N. & Zanin, C. (2020). Practical Handbook of Thematic Cartography: Principles, Methods, and Applications. Boca Raton, FL: CRC Press. DATE AND LOCATION The next edition of this training course will be offered online on a part-time basis on the 30th of September from 9:00 am to 1:30 pm CET. COURSE LEADERS Professor Maurizio Pisati, University of Milano-Bicocca, Department of Sociology and Social Research, Milan (IT). REGISTRATION FEE AND REGISTRATION FORM Full-time Students*: € 155 Ph.D. Students: € 205 Academic: € 370 Commercial: € 495 *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. Register Here The number of participants is limited to 8. Places will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled. Course fees cover: I) teaching materials – copies of lecture slides, databases and Stata programs specifically developed for the course; ii) a temporary licence of StataNow™ valid for 30 days from the day before the course commences. Individuals interested in attending this course must return their completed registration forms by e-mail to TStat by the 20th of September 2026.
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.
Urban, Rural and Transportation Economics (JEL R)
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 minutes. Authors selected for presentation by the Scientific Committee will be contacted directly by the 05.08.2026. The final version of the presentation should be submitted by the 05.09.2026. REGISTRATION FEES Meeting Only Students*: € 60.00 Others: € 110.00 Meeting / Training Course Students*: € 250.00 Others: € 420.00 *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. All participation fees are subject to VAT (applied at the current Italian rate of 22%). Individuals interested in participating should return their duly completed registration forms to the conference organizers by the 10.09.2026 at the very latest. FUNDING FOR DOCTORAL STUDENTS TStat is delighted to sponsor, via our project “Investing in Young Researchers”, TWO full-time Ph.D. students from any of the countries for which TStat is the official Stata Distributor. Sponsorship covers both the first day of the conference and the training course. Travel expenses are however to be paid by the participant. TStat S.r.l. | StataCorp’s Exclusive Distributor serving Albania, Bosnia and Herzegovina, Croatia, Greece, Italy, Kosovo, North Macedonia, Malta, Montenegro, Serbia, Slovenia, Slovakia Stata Official Trainer for Europe Stata is a registered trademark of StataCorp LP, College Station, TX, USA, and the Stata logo is used with the permission of StataCorp. More Information (in Italian) here. Call for Papers (in English) here. SCIENTIFIC COMMITTEE Una-Louise Bell, TStat - TStat Training | Rino Bellocco, Università degli Studi di Milano-Bicocca | Giovanni Capelli, Istituto Superiore di Sanità | Giovanni Cerulli, IRCRES-CNR | Jan Ditzen Libera Università di Bolzano | Maurizio Pisati, Università degli Studi di Milano-Bicocca
Call for Papers for the upcoming XIX Italian Stata Conference taking place in Milan.
Up and Running in Stata - Live Online Training
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. - Kohler, U. & Kreuter, F. (2012). Data Analysis Using Stata. Third Edition. Stata Press Publication. - Mitchell, M. N. (2020). Data Management Using Stata: A Practical Handbook. Second Edition. Stata Press Publication. DATE AND LOCATION 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. REGISTRATION FEE AND REGISTRATION FORM Full-Time Students*: € 545.00 Ph.D. Students: € 710.00 Academic: € 1295.00 Commercial: € 1505.00 *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. The number of participants is limited to 8. Places will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled. Course fees cover: I) teaching materials – copies of lecture slides, databases and Stata programs specifically developed for the course; ii) a temporary licence of StataNow™ valid for 30 days from the day before the course commences. Individuals interested in attending this course must return their completed registration forms by e-mail to TStat by the 22nd of June 2026. To request further information or the registration form, please fill in the form on our website or send an email to training@tstat.eu
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.
Non-Linear Panel Data Models in Stata - Live Online Training Course
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 utmost importance. In this manner, the course leader is able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data. At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed during the course. TARGET AUDIENCE TStat Training’s Non-Linear Panel Data training course is of particular interest to Master and Ph.D. Students, researchers in public and private research centres and professionals working in the following fields: Agricultural Economics, Economics, Finance, Management, Public Health, and the Political and Social Sciences seeking to acquire the “introductory” applied and theoretical toolset to enable them to undertake independent empirical research using panel data. PREREQUISITES Participants are required to have a working knowledge of: the classical OLS regression model: Model Assumptions, Estimation and Inference; the arguments covered in TStat’s Linear Panel Data in Stata; the arguments illustrated in TStat’s course Analysis Micro Data in Stata; the statistical software Stata: including familiarity with Stata variable creation commands and Stata do files. Those needing to refresh these concepts are referred to the reading lists on the respective course pages and to: Cameron, A. C. & Trivedi, P. K. (2022). Microeconometrics Using Stata, Volume I: Cross-Sectional and Panel Regression Methods. Second Edition. Stata Press. Chapters: 1-9 PROGRAM The incidental parameter problem in non-linear models Poisson panel data models: poisson, xtpoisson - Random effects - Correlated effects (conditional poisson) Probit panel data models: probit, xtprobit, oprobit, xtoprobit - Random-effect models - Correlated effects modelled as group means (a la Mundlak) Logit panel data models: logit, xtlogit, ologit, xtologit - Random effects - Correlated effects (conditional logit) Tobit and interval regression models: tobit, xttobit, intreg, xintreg - Random effects - Correlated effects (modelled as group means (a la Mundlak) Postestimation analysis: - Average marginal effects: margins - Goodness-of-fit measures: predict SUGGESTED READINGS Cameron, A. C., & Trivedi, P. K. (2022). Microeconometrics Using Stata, Second Edition Volume I: Cross-Sectional and Panel Regression Methods, Stata Press Cameron, A. C., & Trivedi, P. K. (2022). Microeconometrics Using Stata, Second Edition Volume II: Nonlinear Models and Casual Inference Methods, Stata Press Woodridge, J. (2010). Econometric Analysis of Cross Section and Panel Data, MIT Press DATE AND LOCATION The 2026 edition of this training course will be offered online on a part-time basis on the 22nd, 26th-27th of May from 9:30 am to 1:00 pm CEST. REGISTRATION FEE AND REGISTRATION FORM Full-Time Students*: € 585.00 Ph.D. Students: € 750.00 Academic: € 830.00 Commercial: € 1100.00 *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. The number of participants is limited to 8. Places will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled. Course fees cover: I) teaching materials – copies of lecture slides, databases and Stata programs specifically developed for the course; ii) a temporary licence of StataNow™ valid for 30 days from the day before the course commences. Individuals interested in attending this course must return their completed registration forms by e-mail to TStat by the 12th of May 2026. To request further information or the registration form, please fill in the form on the TStat website, or send an email to training@tstat.eu
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.
Linear Panel Data Models in Stata - Live Online Training Course
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. The intuition behind the choice and implementation of a specific technique is of the utmost importance. In this manner, the course leader is able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data. At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed during the course. TARGET AUDIENCE The panel data training course is of particular interest to Master and Ph.D. Students, researchers in public and private research centres and professionals working in the following fields: Agricultural Economics, Economics, Finance, Management, Public Health, and the Political and Social Sciences seeking to acquire the “introductory” applied and theoretical toolset to enable them to undertake independent empirical research using panel data. PREREQUISITES Participants are required to have a good working knowledge of: the classical linear regression model: Model Assumptions, Estimation and Inference; and the statistical software Stata: including familiarity with Stata variable creation commands and Stata do files. Those needing to refresh these concepts are referred to: Cameron, A. C., & Trivedi, P. K. (2022). Microeconometrics Using Stata, Second Edition Volume I: Cross-Sectional and Panel Regression Methods, Stata Press. Chapters 1-9 PROGRAM SESSION I: INTRODUCTION Panel data: benefits for estimation and inference Preliminary commands: xtset, xtdescribe SESSION II: LINEAR PANEL DATA MODELS WITH EXOGENOUS VARIABLES One-way and two-way fixed effect estimators: xtreg, fe Random Effects Estimators: xtreg, re, xtmixed SESSION III: LINEAR PANEL DATA MODELS WITH EXOGENOUS VARIABLES: ROBUST INFERENCE Robust covariance estimators The first-difference estimator Testing for non i.i.d. errors Testing Random Effects against Fixed Effects: non-robust approach using Hausman robust approach using Mundlak auxiliary regression (Wooldridge, 2010) SESSION IV: LINEAR PANEL DATA MODELS WITH ENDOGENOUS VARIABLES Fixed and Random Effect IV Estimators: xtivreg Hausman and Taylor’s estimator: xthtaylor USEFUL REFERENCES Cameron, A. C., & Trivedi, P. K. (2022). Microeconometrics Using Stata, Second Edition Volume I: Cross-Sectional and Panel Regression Methods, Stata Press Cameron, A. C., & Trivedi, P. K. (2022). Microeconometrics Using Stata, Second Edition Volume II: Nonlinear Models and Casual Inference Methods, Stata Press Woodridge, J. (2010). Econometric Analysis of Cross Section and Panel Data, MIT Press DATE AND LOCATION The 2026 edition of this training course will be offered online on a part-time basis on the 23rd-24th, 28th-29th of April from 9:30 am to 1:00 pm CEST. REGISTRATION FEE AND REGISTRATION FORM Full-time Students*: € 780.00 Ph.D. Students: € 1000.00 Academic: € 1160.00 Commercial: € 1555.00 *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. The number of participants is limited to 8. Places will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled. Course fees cover: I) teaching materials – copies of lecture slides, databases and Stata programs specifically developed for the course; ii) a temporary licence of StataNow™ valid for 30 days from the day before the course commences. Individuals interested in attending this course must return their completed registration forms by e-mail to TStat by the 13th of April 2026. To request further information or the registration form, please fill in the following form or send an email to training@tstat.eu
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.
Maximising the Potential of Stata’s new Python Capabilities - Live Online Course
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 basics Alternative ways to implement Python in Stata: the PyStata Module Calling Python from within Stata Calling Stata from within Python Mata/Python integration Practical examples Stata integration of Python Scikit-learn for Machine Learning Least squares regression in Mata/Python Stata/Python data visualization DATE AND LOCATION 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. COURSE LEADERS Dr. Giovanni Cerulli IRCrES-CNR Research Institute on Sustainable Economic Growth National Research Council of Italy – Rome REGISTRATION FEE AND REGISTRATION FORM Full-Time Students*: € 325.00 Ph.D. Students: € 425.00 Academic: € 770.00 Commercial: € 900.00 *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. The number of participants is limited to 8. Places will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled. Course fees cover: I) teaching materials – copies of lecture slides, databases and Stata programs specifically developed for the course; ii) a temporary licence of StataNow™ valid for 30 days from the day before the course commences. Individuals interested in attending this course must return their completed registration forms by e-mail to TStat by the 31st of March 2026. To request further information or the registration form, please fill in the following form or send an email to training@tstat.eu
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.
Top Professional Training Courses in Economics
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 learning. The course is taught with a hands-on approach via Jupyter notebooks. This course has been specifically designed to provide you with the coding skills that are essential for training in data science. If you are interested in mastering this area and learning the tools to apply modern machine learning techniques – from data exploration to building predictive models and extracting insights – this course is the ideal preparation to get started. Application Deadline: 9 March 2023 Foundations of Data Science Provider: Barcelona School of Economics Location: Online Dates: 20 - 31 March 2023 Fee: €1,100 - €1,950 Get up to speed on the latest developments in data science in a short time. This is a 20-hour online course that exposes you to state-of-the-art tools employed in data science. The course is taught with a hands-on approach via Jupyter notebooks. This course is specifically aimed at professionals, researchers, and Master's/PhD students who want to learn machine learning tools to get insights from large collections of data for their business or research projects. Application Deadline: 15 March 2023 2023 Short Course in Dynamic Global Trade Analysis Provider: Purdue University Location: West Lafayette, Indiana - On-site/online Dates: 14 August - 13 October 2023 Fee: $2,000 (Student), $4,500 (Regular) "Applied General Equilibrium Analysis using a Dynamic Multi-Region Model" Phase 1 (Asynchronous Online Learning) August 14 – September 24, 2023 Phase 2 (Onsite Residency) October 9-13, 2023 The objective of this course is to introduce participants to dynamic economic analysis in an applied general equilibrium setting. This course is designed to provide participants with ample hands-on training with software that has been tailored for undertaking analysis using a dynamic recursive model. Participants will interact with economists working on global trade and environmental issues using a dynamic model. The end goal of the course is for participants to leave with the capability of conducting and analyzing their own dynamic simulations. Application Deadline: 14 May 2023 2023-2 GTAP 101 Course Location: Online Start Date: 4 September - 22 October, 2023 Fee: $1,500 (Student), $4,000 (Regular) The objective of the GTAP 101 course is to engage participants in an active, team-based process of learning about the GTAP computable general equilibrium (CGE) model and its use in applied economic policy analysis. The curriculum emphasizes an intuitive and graphical treatment of economic theory in the CGE model and provides structured experiences in manipulating and running the standard GTAP Model, v7 within the RunGTAP software environment. RunGTAP is an intuitive, menu-driven CGE model interface that minimizes technological hurdles and allows students to quickly begin to focus on their economic thinking and experimentation. The curriculum is geared to advanced undergraduates, graduates, and professionals. At the end of the course, participants will be entry-level modelers and more informed consumers of CGE-based analyses. The course also serves as an entry point for developing the technical skills required for the GTAP Short Course and other courses offered through GTAP-U. Application Deadline: 18 June 2023 Financial Management and Decision-Making for the 21st Century Course Provider: University of Chicago Location: Online Start Date: Ongoing Fee: $9,500 Volatility, uncertainty, complexity, and ambiguity (commonly known as VUCA) are some of the main factors impacting the business world today. That is why professionals should equip themselves with the tools they need to make impactful financial decisions in the 21st century VUCA context. leveraging the University of Chicago’s leadership in the financial sector and the fields of behavioral economics and analytics, our ten-month Financial Management and Decision-Making for the 21st Century certificate program is designed to provide solid theoretical knowledge of cutting-edge financial topics, as well as to offer a practical application for you to implement at work. Application Deadline: Ongoing Energy Innovation and Emerging Technologies Program Course Provider: Stanford University Location: Online Start Date: Ongoing Fee: $1,975 (all access plan) The Energy Innovation and Emerging Technologies Program (EIET) examines emerging technologies, policies, economics, finance, and management that will transform how we obtain, distribute, store, and use energy. Through a variety of online energy courses, you may focus your studies based on your interests. This online energy education program brings together some of the world's most preeminent researchers in the energy and sustainability field to share their knowledge and expertise. Some parts of the modules are technical in nature, so a scientific or engineering background is helpful but not required. Application Deadline: Ongoing Graduate Certificate in Accounting Analytics Course Provider: Michigan State University Location: Online Dates: Ongoing Fees: $817.25 per credit hour The nine-credit, online Graduate Certificate in Accounting Analytics program is designed to meet the professional development needs of accounting professionals, and it also provides an alternative pathway for students seeking to meet the 150 Hour Rule for CPA certification. Information processing technologies and the availability of data are changing how accountants work and what they do. The program not only focuses on understanding accounting implications of emerging data analytical technologies and technical skill development, but also managing projects. The certificate provides a foundation for understanding and adapting in this quickly changing arena. Application Deadline: Ongoing Foundations for Data Science Course Provider: Stanford University Location: Online Dates: Ongoing Fees: $129 Break into the rapidly growing field of data science with Stanford University's Foundations for Data Science professional program. Comprised of three comprehensive and introductory online courses, this program will teach you the foundational programming and statistics skills you need to kick-start a career in data science—no prior experience necessary. Learn from Stanford faculty with step-by-step instructions, listen to insights from industry experts, and develop your understanding through case studies and real-world examples. The program includes ungraded programming exercises to help build and practice your skills. No final exam or capstone project is required. Application Deadline: Ongoing See all Professional Training Opportunities <use xlink:href="/themes/custom/venice/images/icons.svg#launch-18px"></use>
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.