Panel Data for Banking Sector Analysts 2020

The course will cover the basics of panel data analysis and some more advanced extensions, focusing mainly on microeconometric settings with a large number of cross-sectional observations. The statistical package Stata will be used to illustrate all of the methods, including applications to the banking sector.

The common estimators – random effects, fixed effects, and first differencing will be discussed, with emphasis on robust inference and specification tests. During the course modules, the instructor will present in details:

• The extensions that allow heterogeneous slopes and trends
• Instrumental variables methods
• Estimation of dynamic models also will be covered.
• Fixed effects estimation and inference with a large number of time periods, applicable to more aggregated data.
• The problem of unbalanced panels and how to test for nonrandom sample selection
• The panel data methods will be applied to estimate bank cost functions as well as estimating the effect of foreign ownership on market power, as in Delis, Kokas, and Ongena (2016, JMCB). Also, difference-in-differences methods will be illustrated by studying the effects of changes in banking regulations, such as the European Bank and Recovery
• Resolution Directive, on credit default swaps.

The panel data methods will be applied to estimate bank cost functions as well as estimating the effect of foreign ownership on market power, as in Delis, Kokas, and Ongena (2016, JMCB). Also, difference-in-differences methods will be illustrated by studying the effects of changes in banking regulations, such as the European Bank and Recovery Resolution Directive, on credit default swaps.