Live webinar
Heterogenous Difference in Differences in Stata 18

About the Webinar

The last years have seen an explosion in the difference-in-differences (DID) literature. We have moved from assuming treatment effects did not change over group or time to assuming treatment effects change over group and time. We have embraced heterogeneity. Stata 18 introduced two commands (each with four estimators) to fit heterogeneous (DID) models: hdidregress for repeated cross-sectional data and xthdidregress for panel/longitudinal data.

This webinar will focus specifically on the new Heterogenous Difference in Differences estimator of Stata 18 but will also offer an overview of Difference in Differences in Stata more generally. Specific attention will be dedicated to interpretation of the results.

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Highlights:

• Examples from Labour Economics, Banking & Corporate Finance

• Learn to undertake Diff - in - Diff analysis in Stata

• Gain the knowledge to interdependently solve Econometrics puzzles in Stata

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Presented by Dr Malvina Marchese of Bayes Business School, London.

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Join us for this one-hour webinar, and learn how you can make your interactions with Stata more efficient and more effective.

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How to Join
The webinar is free, but you must register to attend.
 

Webinar: Heterogenous Difference in Differences

Tomorrow, Thursday, July 18, 2024

5.30pm to 6.30pm IST

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Malvina Marchese is a Senior Lecturer in Finance and Academic Program Director of the Finance degrees at Bayes (formerly Cass) Business School since September 2020. She was previously Head of Risk Management at Shell Oil, in charge of the forecasting outlook and V@R models. She is also invited associate professor at the Norwegian University of Science and Technology ( NTNU), where she lectures on
financial forecasting and empirical finance. Malvina holds the
position of financial forecasting consultant with Maersk Brokers Advisory and CBRE Investment Management. She is an associate editor of Foresight :|The International Journal of Applied Forecasting and of the International Journal of Finance and Economics. She regularly organizes sessions at the CFE-CM Statistics conference and workshops at the International Forecasting Symposium. Malvina holds a PhD in
Econometrics( Statistics) from the London School of Economics and Political Science. Her research focuses on high dimensional models for volatility and correlations forecasting with applications to
commodities, and on fractional integration in volatility modelling.