Quantitative Economics and Econometrics ECON 0019 Term 2, 2020-2021 Instructors: Kirill Borusyak (k

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Quantitative Economics and Econometrics ECON 0019 Term 2, 2020-2021 Instructors: Kirill Borusyak (k.borusyak@ucl.ac.uk, Drayton House office 307) — weeks 20–24 A?ureo de Paula (a.paula@ucl.ac.uk, Drayton House office 228) — weeks 26–30 Feedback and consultation with instructors: Friday, 12-1:30pm (tentatively). Please do not email the instructors, except on personal matters; please come to the feedback and consultation sessions or use the Moodle forum instead. The emails about the module material and logistics will not be answered. Aims: To provide students with a thorough understanding of core techniques of quantitative economics and econometrics and their application to test economic theories and measure magnitudes relevant for economic policy. The course serves as a foundation for subsequent study of quantitative topics. Term 2 expands on the topics learned on Term 1 for cross-sectional data and introduces basic concepts in time series models. Objectives: At the end of the module, students should: • Understand the main techniques of quantitative economics and econometrics, including their strengths and limitations. • Understand how these techniques can be applied to test economic theories and measure economic magnitudes. • Have some practical experience of the application of econometric methods using Stata. Assessment: There will be one final mark for the entire year. It consists of the Term 1 exam (40%), Empirical Project (20%), and a two-hour Term 3 exam (40%). Problem Sets and Tutorials: There will be three problem sets that do not carry weight for the final mark. Students must hand in all problem sets and there is no tolerance for late assignments. Additional problems will also be covered in tutorials (in the weeks with no problem set due), and the problems will be made available in advance on Moodle. Empirical Project: There will be an empirical project covering material from Terms 1 1 and 2 and it will correspond to 20% of the final marks in the module. The project will be a group assignment with 3 or 4 students per group. Details about the project requirements will be provided on Week 25 (during the reading week), discussed in tutorials on Week 26, and due on Week 30. Practical sessions: will take place on Mondays, 13:00-14:00 and are currently scheduled for Feb 1, 8, 22, and Mar 8 (there may be one more at the end of the term). The practical sessions will be led by Lorenzo Incoronato. Lectures: There will be a combination of pre-recorded lectures posted on Moodle (via LectureCast) and live sessions taking place on Fridays at 11-12pm (online or in Logan Hall IOE, depending on the week and university policy allowing; they will be recorded and available on Moodle. Textbooks: The main textbook is Wooldridge “Introductory Econometrics” (labeled W below), like in Term 1. We will additionally use Stock and Watson “Introduction to Econometrics” (labeled SW). SW is optional for the topics covered by W, but required for the topics that are only in SW. Course Plan (check for updates): Week 20 (15/01): Potential Outcomes and Experiments (SW Ch.13.1-13.3 and Appendix 13.3) Week 21 (22/01): IV (W Ch.15.1-15.6 or SW Ch.12) Week 22 (29/01): IV and LATE (Same plus SW Ch13.6 and Appendix 13.2) Week 23 (05/02): Simultaneous Equations Models (W Ch.16.1-16.3) (PS1 Due) Week 24 (12/02): Limited Dependent Variables (W Ch.17 or SW Ch.11) (Empirical Project Assigned) Week 26 (26/02): Limited Dependent Variables (W Ch.17 or SW Ch.11) Week 27 (05/03): Limited Dependent Variables (W Ch.17 or SW Ch.11) (PS2 Due) Week 28 (12/03): Regression with Time Series (W Ch.10, 11.1-3 or SW Ch.14, 15) Week 29 (19/03): Regression with Time Series (W Ch.10, 11.1-3 or SW Ch.14, 15) Week 30 (26/03): Serial Corr. and Heteroskedasticity (W Ch.12 or SW Ch.15) (PS3 Due) (Empirical Project Due) 2 You will be awarded a mark of 0% or Grade F in any examination, or other summative assessment component (essay, multiple choice questions, projects, etc.) where you: (1) are absent from the summative assessment component or, (2) do not attempt the summative assessment component or, (3) attempt so little of the summative assessment component that it cannot be assessed. Please check the UCL Academic Manual (Section 3.11) for information on the consequences of not submitting or engaging with any of your assessment components. If you are a re-sitting student or taking deferred assessment the academic regulations for 2017/18 apply to you. In this case if you do not complete or take an assessment component that is worth more than 20% of the total assessment you will be considered incomplete. This means that you can not pass the module. If this is your first attempt you may be entitled to LSA in the component. Please discuss with the Departmental Tutor (f.witte@ucl.ac.uk) if you are unsure of the consequences for you. If you have extenuating circumstances that affect your ability to engage with any of the module assessment components please apply for alternative arrangements to the Economics Department as soon as possible. See details in Section 6 of the Academic Manual and send your request to economics.ug@ucl.ac.uk. If you have a disability or long-term medical condition, you may be entitled to adjustments for assessments. Please see Section 5 of the Academic Manual for information on how to apply for adjustments. If part of your assessment includes an in-class quiz and you feel that you are unable to complete it in the time allocated please contact the Departmental Tutor, Dr Frank Witte (f.witte@ucl.ac.uk) and the UG Admin team (economics.ug@ucl.ac.uk). Do not contact the course lecturer about this. 3 1. In “Does Trade Cause Growth?” (American Economic Review, 1999), Jeffrey Frankel and David Romer study the effect of trade on income. Their simple specification is log Yi = a + BT; + yWit Ei, where Y? is per capita income of country i, Ti is international trade, W? is within-country trade, and Ei reflects other determinants of income. Since εi is likely to be correlated with the trade variables, Frankel and Romer decide to use instrumental variables to estimate the coefficients ß and y. As instruments, they use a measure of country's geographic position (its proximity to other countries) Pi and the country size Si. (a) Explain in detail (step by step) how one can construct the instrumental variable estimates B and û when one has data on Yi, Ti, Wi, Pi, and S; for a random sample of countries. (b) Provide formal conditions for these estimates to be consistent. Which of them can be tested? (c) Explain the economic intuition why the conditions from Question 1(b) may be satisfied in this context. Also give at least one economic justification why at least one of them may be violated. (d) Suppose that, unfortunately, data on within-country trade Wi are not available. In order to be able to estimate B, the researchers add another assumption (on top of those you proposed in item (b)): that W; follows the model Wi= n + 1S; + Vig and Pi is uncorrelated with vi. Explain in detail (step by step) how one can estimate B from the data on Yi, Ti, Pi, and Si only and why that estimator will be consistent.