EC995-8-AU-CO:
Topics in Applied Economics
2023/24
Economics
Colchester Campus
Autumn
Postgraduate: Level 8
Current
Thursday 05 October 2023
Friday 15 December 2023
20
04 September 2023
Requisites for this module
(none)
(none)
(none)
(none)
(none)
This module covers the basics for doing sound empirical work at the post-graduate level, including Labour and Public Economics, Development and Experiments, Industrial Organization and Trade.
The identification issue of causal relationship when analyzing experimental and non-experimental data represents the unifying topic of the course. Much in the spirit of "Correlation is not equal to causation!"
This module is particularly aimed at students who plan on doing applied work for their thesis.
By the end of this module, students will be expected to be able to:
- Have a clear understanding of how to do empirical work in applied micro econometrics.
Students will learn how current empirical microeconomic work addresses issues of causality. Emphasis is on the formulation and estimation of a wide range of models and techniques, from randomized control trials to reduced-form techniques, and covering a broad set of design based identification tools, including difference-in-difference models, instrumental variables regressions, regression discontinuity design, synthetic control methods, and panel data econometrics.
Applications of these techniques cover several fields of interest, including labour market effects of education and migration, income inequality, sorting, wage differentials, health, development, and behavioural economics. Throughout the module, attention will be paid to link the analysis to current debates in the public policy context.
This module will be delivered via:
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David A. Freedman (1991a) ‘Statistical Models and Shoe Leather’,
Sociological Methodology, 21 (1991), pp. 291–313. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/270939?sid=primo.
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Angrist, J., Pischke, J.-S. and National Bureau of Economic Research (2010)
The Credibility Revolution in Empirical Economics: How Better Research Design is Taking the Con out of Econometrics. Cambridge, Mass: National Bureau of Economic Research. Available at:
https://essex.alma.exlibrisgroup.com/view/action/uresolver.do?operation=resolveService&package_service_id=4484008750007346&institutionId=7346&customerId=7345.
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Deaton, A. and Cartwright, N. (2016) ‘Understanding and Misunderstanding Randomized Controlled Trials.’ Available at:
http://www.nber.org/papers/w22595.pdf.
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Ioannidis, J.P.A. (2005) ‘Why Most Published Research Findings Are False’,
PLoS Medicine, 2(8). Available at:
https://doi.org/10.1371/journal.pmed.0020124.
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Heckman, James J. (no date) ‘Abducting Economics’,
American Economic Review, 107(5), pp. 298–302. Available at:
https://doi.org/10.1257/aer.p20171118.
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Arthur Lewbel (2019) ‘The Identification Zoo: Meanings of Identification in Econometrics’,
Journal of Economic Literature, 57(4), pp. 835–903. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/26856207?sid=primo.
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Gelman, A., Imbens, G. and National Bureau of Economic Research (2013)
Why ask Why? Forward Causal Inference and Reverse Causal Questions. Cambridge, Mass: National Bureau of Economic Research. Available at:
https://essex.alma.exlibrisgroup.com/view/action/uresolver.do?operation=resolveService&package_service_id=4483821330007346&institutionId=7346&customerId=7345.
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Krueger, A., Ashenfelter, O. and National Bureau of Economic Research (1992)
Estimates of the Economic Return to Schooling from a New Sample of Twins. Cambridge, Mass: National Bureau of Economic Research. Available at:
https://essex.alma.exlibrisgroup.com/view/action/uresolver.do?operation=resolveService&package_service_id=4483846310007346&institutionId=7346&customerId=7345.
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Callaway, B. and Sant’Anna, P.H.C. (2021) ‘Difference-in-Differences with multiple time periods’,
Journal of Econometrics, 225(2), pp. 200–230. Available at:
https://doi.org/10.1016/j.jeconom.2020.12.001.
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Goodman-Bacon, A. (2021) ‘Difference-in-differences with variation in treatment timing’,
Journal of Econometrics, 225(2), pp. 254–277. Available at:
https://doi.org/10.1016/j.jeconom.2021.03.014.
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Bertrand, M., Duflo, E. and Mullainathan, S. (2004) ‘How Much Should We Trust Differences-In-Differences Estimates?’,
The Quarterly Journal of Economics, 119(1), pp. 249–275. Available at:
https://doi.org/10.1162/003355304772839588.
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de Chaisemartin, Clément (no date) ‘Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects’,
American Economic Review, 110(9), pp. 2964–96. Available at:
https://doi.org/DOI: 10.1257/aer.20181169.
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Sun, L. and Abraham, S. (2021) ‘Estimating dynamic treatment effects in event studies with heterogeneous treatment effects’,
Journal of Econometrics, 225(2), pp. 175–199. Available at:
https://doi.org/10.1016/j.jeconom.2020.09.006.
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Imbens, G.W. and Lemieux, T. (2008) ‘Regression discontinuity designs: A guide to practice’,
Journal of Econometrics, 142(2), pp. 615–635. Available at:
https://doi.org/10.1016/j.jeconom.2007.05.001.
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Lee, David S. (no date) ‘Regression Discontinuity Designs in Economics’,
Journal of Economic Literature, 48(2), pp. 281–355. Available at:
https://doi.org/10.1257/jel.48.2.281.
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Thistlewaite, D.L. and Campbell, D.T. (1960) ‘Regression-discontinuity analysis: An alternative to the ex post facto experiment’,
Journal of Educational Psychology [Preprint]. Available at:
https://search-ebscohost-com.uniessexlib.idm.oclc.org/login.aspx?direct=true&db=pdh&AN=1962-00061-001&site=ehost-live&authtype=sso&custid=s9814295.
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Jinyong Hahn, Petra Todd, Wilbert Van der Klaauw (2001) ‘Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design’,
Econometrica, 69(1), pp. 201–209. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2692190?sid=primo.
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McCrary, J. (2008) ‘Manipulation of the running variable in the regression discontinuity design: A density test’,
Journal of Econometrics, 142(2), pp. 698–714. Available at:
https://doi.org/10.1016/j.jeconom.2007.05.005.
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Kolesár, Michal (no date) ‘Inference in Regression Discontinuity Designs with a Discrete Running Variable’,
American Economic Review, 108(8), pp. 2277–2304. Available at:
https://doi.org/10.1257/aer.20160945.
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P. M. Robinson (1988) ‘Root-N-Consistent Semiparametric Regression’,
Econometrica, 56(4), pp. 931–954. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/1912705?sid=primo.
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Hansen, B.E. (1999) ‘Threshold effects in non-dynamic panels: Estimation, testing, and inference’,
Journal of Econometrics, 93(2), pp. 345–368. Available at:
https://doi.org/10.1016/S0304-4076(99)00025-1.
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Bruce E. Hansen (2000) ‘Sample Splitting and Threshold Estimation’,
Econometrica, 68(3), pp. 575–603. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2999601?sid=primo.
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Cattaneo, M.D., Idrobo, N. and Titiunik, R. (2019a)
A practical introduction to regression discontinuity designs: foundations. 1st ed. Cambridge: Cambridge University Press. Available at:
https://essex.alma.exlibrisgroup.com/view/action/uresolver.do?operation=resolveService&package_service_id=4483846300007346&institutionId=7346&customerId=7345.
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Cattaneo, M.D., Idrobo, N. and Titiunik, R. (2019b)
A practical introduction to regression discontinuity designs: foundations. 1st ed. Cambridge: Cambridge University Press. Available at:
https://essex.alma.exlibrisgroup.com/view/action/uresolver.do?operation=resolveService&package_service_id=4483846300007346&institutionId=7346&customerId=7345.
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Joshua D. Angrist (1990) ‘Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records’,
The American Economic Review, 80(3), pp. 313–336. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2006669?sid=primo.
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Card, D. (1999) ‘The Causal Effect of Education on Earnings’, in
Handbook of Labor Economics. Elsevier, pp. 1801–1863. Available at:
https://doi.org/10.1016/S1573-4463(99)03011-4.
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Joshua D. Angrist, Alan B. Krueger (1014) ‘Does Compulsory School Attendance Affect Schooling and Earnings?’,
The Quarterly Journal of Economics, 106(4), pp. 979–1014. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2937954?sid=primo.
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Bound, J., Jaeger, D.A. and Baker, R.M. (1995) ‘Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak’,
Journal of the American Statistical Association, 90(430), pp. 443–450. Available at:
https://doi.org/10.1080/01621459.1995.10476536.
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Mountjoy, Jack (no date) ‘Community Colleges and Upward Mobility’,
American Economic Review, 112(8), pp. 2580–2630. Available at:
https://doi.org/DOI: 10.1257/aer.20181756.
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James J. Heckman (1979) ‘Sample Selection Bias as a Specification Error’,
Econometrica, 47(1), pp. 153–161. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/1912352?sid=primo.
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Joseph G. Altonji, Todd E. Elder, Christopher R. Taber (2005) ‘Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools’,
Journal of Political Economy, 113(1), pp. 151–184. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/10.1086/426036?sid=primo.
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Alan B. Krueger (1993) ‘How Computers Have Changed the Wage Structure: Evidence from Microdata, 1984-1989’,
The Quarterly Journal of Economics, 108(1), pp. 33–60. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2118494?sid=primo.
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John DiNardo, Nicole M. Fortin, Thomas Lemieux (1044) ‘Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach’,
Econometrica, 64(5), pp. 1001–1044. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2171954?sid=primo.
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Rajeev H. Dehejia, Sadek Wahba (1062) ‘Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs’,
Journal of the American Statistical Association, 94(448), pp. 1053–1062. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2669919?sid=primo.
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David Card (1990) ‘The Impact of the Mariel Boatlift on the Miami Labor Market’,
ILR Review, 43(2), pp. 245–257. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2523702?sid=primo&origin=crossref.
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Alberto Abadie, Alexis Diamond, Jens Hainmueller (2010) ‘Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program’,
Journal of the American Statistical Association, 105(490), pp. 493–505. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/29747059?sid=primo.
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Raj Chetty (2008) ‘Moral Hazard versus Liquidity and Optimal Unemployment Insurance’,
Journal of Political Economy, 116(2), pp. 173–234. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/10.1086/588585?sid=primo.
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Steven Berry, James Levinsohn, Ariel Pakes (1995) ‘Automobile Prices in Market Equilibrium’,
Econometrica, 63(4), pp. 841–890. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/2171802?sid=primo.
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James J. Heckman (2005) ‘The Scientific Model of Causality’,
Sociological Methodology, 35 (2005), pp. 1–97. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/4148843?sid=primo.
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David A. Freedman (1991b) ‘Statistical Models and Shoe Leather’,
Sociological Methodology, 21 (1991), pp. 291–313. Available at:
https://www-jstor-org.uniessexlib.idm.oclc.org/stable/270939?sid=primo.
The above list is indicative of the essential reading for the course.
The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students.
Further reading can be obtained from this module's
reading list.
Assessment items, weightings and deadlines
Coursework / exam |
Description |
Deadline |
Coursework weighting |
Coursework |
Presentation slides |
|
50% |
Coursework |
Problem Set |
|
50% |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Yes
No
Yes
Miss Maria Kyriacou
Available via Moodle
Of 38 hours, 34 (89.5%) hours available to students:
4 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.
Economics
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