DMA 812S: Cross Section Analysis 3 CREDITS
Cross sectional data provides ‘spot-check’ perspective of a phenomenon and thereby offers an opportunity to generate an understanding of the context and to determine possible solutions. The course in cross sectional analysis will target analyses mainly at the micro level.
Students should be able to:
- Estimate and test hypothesis using cross sectional data
- Address issues related to sample selection bias and endogeneity.
- Demonstrate practical knowledge in the handling of cross sectional data.
The course will cover topics including; data structure of cross sectional data and estimation concerns, directional and causal estimations, tobit and related censored regression models, models dealing with sample selectivity, treatment effects, propensity score matching and post estimation analyses.
- Anwar, N. & Najam, F. A. (2016). Structural Cross Sections: Analysis and Design. Butterworth-Heinemann.
Suggested Reading List
- Asteriou, D. & Hall, S. G. (2011). Applied econometrics. New York: Palgrave Macmillan.
- Cameron, A. C. & Trivedi, P. K. (2009). Microeconometrics using stata (Vol. 5). College Station, TX: Stata Press.
- Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT press