Peabody Quantiative Workshop

Schedule for Meetings, Readings, Associated Notes and Code

Spring 2010

January 13, 2010

    Park, D. K., Gelman, A., & Bafumi, J. (2004). Bayesian Multilevel Estimation with Poststratification: State-Level Estimates from National Polls. Political Analysis, 12(4),  375-385. doi:10.1093/pan/mph024  [Link]

Notes on Gelman: [100112gelman_notes.pdf]

Datasets used by Park, Gelman et al:
                Poll Data: [election88.dta]
                Census Data: [census88.dta]

Code to replicate Gelman Analysis:
            R Code:[gelman_analysis.r] (Uses Jags, see: http://www-fis.iarc.fr/~martyn/software/jags/)
            Bugs Code: [election88.M2.bug]

Stata code to implement a single-level fixed effects model:
                        Do File: [100127gelman.do]

January 27, 2010

Moffitt, R. A. (2004). Introduction to the Symposium on the Econometrics of Matching. Review of Economics and Statistics, 86(1), 1-3. doi:10.1162/003465304323023642   [Link]

Imbens, G. W. (2004). Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review. Review of Economics and Statistics, 86(1), 4-29. doi:10.1162/003465304323023651  [Link]

February 3 2010
Zhao, Z. (2004). Using Matching to Estimate Treatment Effects: Data Requirements, Matching Metrics, and Monte Carlo Evidence. Review of Economics and Statistics, 86(1), 91-107. doi:10.1162/003465304323023705  [Link]

Examples of various matching programs implemented in Stata:
Lalonde Data: [lalonde.dta]
Stata Code: [matching.do]

 February 10, 2010

            Coding Session: Attempting to replicate Zhao MC approach
Code: [monte_carlo_zhao.do]

February 17, 2010

Heckman, J., & Navarro-Lozano, S. (2004). Using Matching, Instrumental Variables, and Control Functions to Estimate Economic Choice Models. Review of Economics and Statistics, 86(1), 30-57. doi:10.1162/003465304323023660  [Link]

March 3, 2010

Angrist, J., & Hahn, J. (2004). When to Control for Covariates? Panel Asymptotics for Estimates of Treatment Effects. Review of Economics and Statistics, 86(1), 58-72. doi:10.1162/003465304323023679  [Link]

March 24, 2010

Agodini, R., & Dynarski, M. (2004). Are Experiments the Only Option? A Look at Dropout Prevention Programs. Review of Economics and Statistics, 86(1), 180-194. doi:10.1162/003465304323023741 


Pohl, S., Steiner, P. M., Eisermann, J., Soellner, R., & Cook, T. D. (2009). Unbiased Causal Inference From an Observational Study: Results of a Within-Study Comparison. Educational Evaluation and Policy Analysis, 31(4), 463-479. doi:10.3102/0162373709343964 

March 31, 2010

Rubin, D. B. (2001). Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation. Health Services and Outcomes Research Methodology, 2(3), 169-188. doi:10.1023/A:1020363010465 

April 14,  2010


April 21,  2010