Sparse Functional Concurrent Regression with Instrumental Variables


In economic theory, labor supply elasticities measure a person’s response, in terms of hours worked, to a change in that person’s hourly wage. Labor supply elasticities signal attitudes about working which can contribute to policy decisions. In this project, we show how to estimate labor supply elasticities using an instrumental variables estimator in functional concurrent regression models. Though some recent works have adapted instrumental variables estimation to functional regression models, they have focused on scalar-on-function and function-on-function regression models. Our estimation method is novel in that it applies to functional concurrent regression with longitudinal, or sparsely observed functional data. We illustrate the accuracy of our estimation strategy through a detailed simulation study and apply it to data from the Current Population Survey to estimate labor supply elasticities for different demographic groups of the U.S. population.

Aug 11, 2022 8:00 AM — 10:20 AM
Walter E. Washington Convention Center
801 Mount Vernon Place NW, Washington, D.C., 20001
Click on the Slides button above to view the built-in slides feature.

Slides can be added in a few ways:

  • Create slides using Wowchemy’s Slides feature and link using slides parameter in the front matter of the talk file
  • Upload an existing slide deck to static/ and link using url_slides parameter in the front matter of the talk file
  • Embed your slides (e.g. Google Slides) or presentation video on this page using shortcodes.

Further event details, including page elements such as image galleries, can be added to the body of this page.

Justin Petrovich
Justin Petrovich
Assistant Professor of Statistics and Business Data Analytics

My research interests include functional and longitudinal data analysis, applied statistics, and statistics education.