The International Food Policy Research Institute (IFPRI) in collaboration with its partner institution based in Central Asia - Westminster International University in Tashkent (WIUT) - held a Regional Training Course (Summer School) on Applied Econometric Analysis from June 10 – 21, 2019, for the fifth consecutive year. This two-week training course for young researchers from the region took place at WIUT in Tashkent, Uzbekistan. More than 20 participants from Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan participated in the training. Participants were selected on a competitive basis based on their interest and background in applied research, as well as their knowledge and skill level in quantitative methods.

Day 1 - June 10

• Introduction to applied research in economics and overview of the training program, Kamiljon Akramov (IFPRI)
• Introduction to Stata (do files, global and local macros, types of variables, descriptive statistics, exporting results of regression to word processor and spreadsheet), Ziyodullo Parpiev (WIUT)
• Introduction to Stata (data management: importing, reshaping, merging, appending, and cleaning data), Ziyodullo Parpiev (WIUT)
  • Related Materials: https://www.stata.com/manuals14/u.pdf 
  • Related Materials (do files)

Day 2 - June 11 

• Looping and useful shortcuts in Stata, Kakhramon Yusupov (WIUT)
• Drawing graphs and maps in Stata, Kakhramon Yusupov (WIUT)
  • Related Materials
• Review of probability (Random variables and probability distributions; Expected values, mean, and variance; Joint and marginal distributions; Conditional distributions; Covariance and correlation), Farrukh Ataev (WIUT)
• Review of probability (cont.), Farrukh Ataev (WIUT)
  • Related Materials

Day 3 - June 12 

• Distributions in statistics (Normal, Chi-squared, Student t, and F distributions; Random sampling and sample distributions), Farrukh Ataev (WIUT)
• Distributions in statistics (cont.), Farrukh Ataev (WIUT)
• Introduction to statistical inference (Estimation of the population mean; Hypothesis testing: p-value, t-test, F-test, confidence intervals), Farrukh Ataev (WIUT)
• Introduction to statistical inference (cont.), Farrukh Ataev (WIUT)
  • Related Materials

Day 4 - June 13 

• Linear regression model, Kakhramon Yusupov (WIUT)
• Hypothesis tests, model specification and diagnostics in linear regression, Obid Khakimov (WIUT)

Day 5 - June 14 

• Regression with binary dependent variable (Linear probability, probit, and logit models), Obid Khakimov (WIUT)
• Assessing studies based on standard regression analysis with examples, Kamiljon Akramov (IFPRI)
• Regression and causal inference (Counterfactual model of causality, Potential outcomes, Assignment mechanisms, Estimands, and estimator), Kamiljon Akramov (IFPRI)

Additional Reading and Related Materials:

Cassidy, J. (2013). The Reinhart and Rogoff Controversy: A Summing Up. The New Yorker. Available from https://www.newyorker.com/news/john-cassidy/the-reinhart-and-rogoff-controversy-a-summing-up.

Imbens, G. and Rubin, D., ed. Causal Inference for Statistics, Social, and Biomedical Sciences An Introduction. New York: Cambridge University Press, 31-42. Available from https://books.google.co.uz/books?hl=en&lr=&id=Bf1tBwAAQBAJ&oi=fnd&pg=PR17&dq=Imbens+%26+Rubin,+Causal+Inference,+Part+I,+Chapter+3,+November+25,+2009&ots=jd-Ecc-NzB&sig=_5Wj7ce83aov0VCMnO7DKCGZy-k&redir_esc=y#v=onepage&q&f=false 

Day 6 - June 17 

• Identification: Regression analysis of RCTs, Bakhrom Mirkasimov (WIUT)

• Panel data econometrics (fixed effects, random effects, incidental parameter problem), Obid Khakimov (WIUT)