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Carroll School of Management

Faculty Projects

Data Management:

  • Prepared guide to SSH Secure shell for running SAS and other programs on WRDS server.
  • Mapped longitude and latitude coordinates on to the world map using SAS GMAP procedure.
  • Computed quarterly and annual firm-market crash measures from the CRSP/Compustat databases.
  • Parsed and restructured data tables in portable document format (pdf) files and wrote results to comma-separated files (csv).
  • Extracted and restructured unbalanced nested patent data stored in HTML.
  • Compiled links to Securities and Exchange Commission (SEC) filings, downloaded and parsed filings, estimated language complexity and searched for words and phrases.
  • Reshuffled trading data in HDF5 format on Pleiades Linux server.
  • Automated conversion of csv, xlsx, and dta format files into SAS format and vice versa.
  • Reshaped a large wide format marketing dataset into a more usable long format dataset.
  • Acquired and managed data from the WRDS databases including Compustat, CRSP, I/B/E/S, OptionMetrics, RiskMetrics, and Audit Analytics.
  • Efficiently computed leads, lags and moving averages using SAS EXPAND procedure.


Data Analysis:

  • Computed biased-corrected and regular bootstrapped confidence intervals for beta coefficients and R2.
  • Performed Monte Carlo simulations and Bootstrapping to obtain sampling distributions of coefficients and conducted hypothesis tests.
  • Applied Stata gsem procedure to estimate Seemingly Unrelated Regression (SUR) model on unbalanced panel data.
  • Wrote SAS program estimating multivariate Fama-Macbeth regression model that identifies and ranks the best predictors of cross-sectional stock returns.
  • Presented options for addressing common method variance; implemented marker variable technique.
  • Developed intuition for why dummy-variable adjustment procedure leaves regression coefficients unchanged and researched procedure‚Äôs established limitations.
  • Outlined differences among intraclass coefficients (ICC) as measures of reliability in multilevel data and how best to report them in a revise-and-resubmit.
  • Clarified incomplete factorial design, alternative ways to estimate ANOVA, options for multiple comparisons, and how to read SPSS output.
  • Investigated analysis options for cross-classified multi-level data with small sample. Explored generalized mixed-effect models and generalized estimating equations, and found the later performed better, especially with non-normal outcomes.
  • Estimated multi-group Confirmatory Factor Analysis. Identified and addressed item invariance among groups.


Administrative Projects:

  • CSOM Research Reports.
  • CSOM Teaching Reports.
  • Analysis of CSOM Undergraduate Student Survey