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Course: Applied Econometrics for Practitioners

December 10, 2018-January 20, 2019

Kathmandu (Two to three classes per week)

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  • The course aims to teach the tools and techniques of applied statistics while working with complex household survey data. The focus of the course will be on cross-sectional econometric analysis, with some discussion of panel data analysis. The course examples and exercises will focus on issues related to economic development and domestic social issues (e.g. poverty, education, health, labor issues). The course will cover some advanced, but commonly needed, methods of statistical analysis. The emphasis is on applications, not derivations, of methodology. The course will entail a significant amount of data analysis using Stata software. For assessing syllabus of the course, please click here.

    After successful completion of the course, the participants will have learned several econometric techniques and will be able to carry out on their own empirical analysis. For example, the participants can answer research question such as: What factors are associated with the poverty outcomes in Nepal? Participants will be able to critically review and correctly interpret regression results. Moreover participants will develop a habit of working on Stata dofile and be comfortable implementing the econometric software: Stata-12.

    Course Schedule and Calendar

    The lectures will be delivered in two phases. The first phase consists of five lectures and starts from December 10th, to December 20th, 2018. The second phase consists of seven lectures and resumes on January 7th and concludes on January 20th, 2019.  

    Please click here for the detailed course schedule and course calendar.

    The venue will be in Durbar Marg/Thamel area in Kathmandu and to be announced upon final confirmation. Lectures will be from 8 AM to 10 AM and breakfast will be served from 7:30 am.

    Resources

    The World Bank will provide the soft copies of lecture slides, problem sets, reading materials, and a book. The World Bank will not provide transportation and lodging costs.

    Instructors:
    1. Dr. Dean Jolliffe
    2. Dr. Hiroki Uematsu
    3. Dr. Ganesh Thapa

    How to Apply:

    Please send your updated CV, a scanned copy of your academic transcript of the highest degree completed, and a brief statement describing your previous use of Stata and motivation for taking this course to nepaldata@worldbank.org.

    Please apply by 30th November 2018. Seats are limited; accepted candidates will be notified via email by 3rd December. The course attendance is free for selected candidates.

    Requirements:
    1. Ability to regularly attend the course and complete out-of-classroom
        assignments
    2. Personal laptop with the installation of Stata-12
    3. Basic knowledge of statistics or econometrics
    4. Basic skills in using Stata or an aptitude for learning software from
        manuals or online help
    5. Any course on micro-economics on your transcripts will be a plus
     

     

     

  • Applied Econometrics for Practitioners
    World Bank, Kathmandu, Nepal
    2018-19

    Lectures: Monday, Wednesday and Fridays: 8-10AM  
    Venue: TBD
     
    Instructor: Dean Jolliffe 
    Teaching Assistant: Ganesh Thapa

    Course Description

    This course is designed to teach the tools and techniques of applied statistics and empirical microeconomics. The class focus is on cross-sectional econometric analysis, with some discussion of panel data analysis (there is essentially no coverage of time-series econometrics). The class will focus on the issues related to international development and domestic social issues (e.g. poverty, education, health, agriculture, labor issues) of Nepal, and will rely on exercises and examples from the Nepal Living Standard Survey (NLSS 2011) data. This course covers some advanced, but commonly needed, methods of statistical analysis. The emphasis is on applications, not derivations, of methodology. The course will entail a significant amount of data analysis with the Stata software (version 12). Topics covered include: Review of multivariate regression and violations of model assumptions, complex sample design – stratification and multi-stage selection, proper use of sample weights and population inference from sample statistics, instrumental variables estimation, limited dependent variables (Linear Probability, Logit & Probit models), censored dependent variables (Poisson & Tobit models), quantile regression and robust estimation, introduction to the bootstrap, introduction to fixed effects modeling with cross-sectional and panel data.

    Prerequisites: Basic Stata skills, or an aptitude for learning software from manuals or online help and exposure to the statistics/microeconomics.

    Texts and Materials: Wooldridge, Jeffrey M.  Introductory Econometrics: A Modern Approach, Fifth Edition.

    Optional/Supplemental:  Deaton, Angus. The Analysis of Household Surveys: A Microeconometric Approach to Development Policy. Baltimore, MD: Johns Hopkins University.

    Course Requirements and Rules

    Upon successful completion of 4 problem sets and active class participation, we will provide you with a certificate of course completion. The write-up for the problem set should include the essential program code and output when appropriate. Do not hand in entire log files, but do include enough of the Stata code to show the core commands used along with other relevant information (e.g. whether the results are weighted, clustered, stratified). Problem sets are due at the beginning of class on the due date, to be announced at the beginning of the course. Late problem sets are not accepted because we may discuss them in class on the due date.

     

    Course Schedules

    The First Phase

    1. December 10:  Course Overview, Introduction and Review of OLS

                                Review OLS assumptions with a focus on how they affect our
                                ability to answer policy questions. Discuss bivariate OLS
                                estimator, the variance of this estimator, and the implications
                                for assessing data quality.

                                Wooldridge chapters 2, 3, 4 & 7;

                                NPR story on anti-smoking campaign. Reply by Steven Landsburg,
                                Slate (2003). Kristof editorial on infant mortality rates ("Health
                                Care: Ask Cuba").

     

    2. December 12:  A. Brief discussion of NPR story on smoking, Kristof editorial, NYT story on HIV estimate.

                                   B. Begin discussion of Sample Design and Weights

                                 NYT story on HIV overestimate.

                                 Deaton chapters 1 & 2

                                                                                

    3. December 14:   Sample Design and Weights (cont.)

                            Discuss sampling, sample frame & inference, sample design &

                            precision.

                            Mortality before and after the 2003 invasion of Iraq: cluster sample 
                           survey,” Lancet, 2004. Responses from Slate and the Economist. “
                           Mortality after the 2003 invasion of Iraq: a cross-sectional cluster 
                           sample survey,”  Lancet, 2006.

     

    4. December 17:  A. Discuss Lancet article and responses.

                                B. Data Problems: Measurement Error

                                Iron Law of Econometrics

                                ME: Wooldridge 9.3 & 9.4,

     

    5. December 19:   A. Data Problems: Non-response bias, Missing Observations, Heteroscedasticity

                                   B. Binary Dependent Variable (Linear Probability, Logit, 
                                   Probit Models)

                                   Wooldridge 8.1, 8.2, 8.3; 7.5 & 17.1

     

    The Second Phase

    6. January 7:       Binary Dependent Variable (cont.)

     

    7. January 9:       Instrumental Variable (IV) estimation & Simultaneous Equations Model (SEM)

                                Simultaneity bias. Identification and simultaneous equations.

                                IV: Wooldridge 15.1 – 15.3, 15.5—15.6; SEM: Wooldridge 16.1 – 
                               16.3.

                                “The Effect of Cocaine Prices on Crime” (Desimone, 2001).

                                “Landing on all fours: Communist elites in post-Soviet
                                Russia” (Geishecker & DeNew, Journal of Comparative Economics,
                                2004.)

                                “Health Economics and Applications in Developing Countries” 
                                (T. Paul Schultz, Journal of Health Economics, 2004, 
                                23(4)636-641.)

                               

    8. January 11:     A. Discuss Desimone & Geishecker papers, comment on Manski & Schultz

                                B. Sample-selection Bias         

                               Heckman correction: benefits, problems and alternatives.

                               Wooldridge section 17.5,

                               Identification Problems in the Social Sciences and Everyday 
                               Life” (Manski, 2003).

                               “The Ambulance-Homicide Theory” (NYTimes Magazine, 2002).

                               "Sample Selection in the Estimation of Air Bag and Seat
                                Belt Effectiveness” (Levitt & Porter, 2001).

     

    9. January 13:     A. Discuss Levitt & Porter

                                B. Poisson & Tobit Estimators

                               Estimation when the dependent variable is censored at zero.

                                Wooldridge 17.2 & 17.3

                 

    10. January 15:    Robust Estimation, Least Absolute Deviations, Bootstrap Estimation

                               Outliers, Violations of normality

                                Wooldridge 9.4, Efron and Tibshirani, An Introduction to the 
                               Bootstrap, 1993: Chapters 1, 2, 4 & 6.

     

    11. January 18:    Robust Estimation, Least Absolute Deviations, 
                                   Bootstrap Estimation (cont.)

                                                                  

    12. January 20:   Fixed Effects Estimation

                                Fixed-effects estimation using cross-sectional data. Fixed
                                effects estimation using panel data. Benefits of panel data. 
                               Compare with independently sampled data from two time 
                               periods.

                                Wooldridge chapter 13

    In addition to the lectures, there will be 4 to 5 TA sessions to assist the participants on the problem sets (dates are to be determined in consultation with the participants). Below are tentative topics for the TA sessions:

    1. Introduction to Stata – basic tips on using Stata, loading the NLSS data

    2. More Stata tips, guidance for problem set 1

    3. Review problem set 1, guidance for problem set 2

    4. Review problem set 2, guidance for problem set 3

    5. Review problem set 3, guidance for problem set 4

     

     

     

    Last Updated: Nov 23, 2018

  • Dean Jolliffe

    Dean Jolliffe is a lead economist in the Living Standards Measurement Study (LSMS) team in the Survey Unit of the Data Group at the World Bank. He has experience in the design and implementation of household surveys in several countries and is currently co-managing ongoing LSMS work in Ethiopia. He previously worked in the Research Group of the World Bank on issues related to the global poverty counts and more generally on measuring poverty with household survey data. Prior to the Bank, he was a research economist at the Economic Research Service of US Department of Agriculture, an adjunct professor at the Johns Hopkins University School of Advanced International Studies, an assistant professor at the Center for Economic Research and Graduate Education in Prague, and a post-doctoral fellow at the International Food Policy Research Institute. Dean holds appointments as a Research Fellow with the Institute for the Study of Labor in Bonn, and as a Research Affiliate with the National Poverty Center at the University of Michigan. He received his Ph.D. in economics from Princeton University.

    Hiroki Uematsu

    Hiroki Uematsu is a senior economist in the Poverty and Equity Global Practice of the World Bank, based in Kathmandu, Nepal. He currently leads the country work program on Partnership for Knowledge-based Poverty Reduction and Shared Prosperity in Nepal. Prior to moving to Kathmandu, his earlier work focused on global poverty and county engagement in South Asia and Middle East. He received his Ph.D in Agricultural Economics from Louisiana State University.

    Ganesh Thapa

    Ganesh Thapa is an economist at the Poverty and Equity Global Practice of the World Bank and is based in Kathmandu, Nepal. He previously worked with the World Food Program (WFP), International Food Policy Research Institute (IFPRI) and Feed the Future Nutrition Innovation Lab (FtF-NIL). He also worked as Fisheries Development Officer with the Ministry of Agriculture, Nepal. He received his Ph.D. in Agricultural Economics from Purdue University.