EC303: Empirical Economic Analysis Spring 2023
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EC303: Empirical Economic Analysis
Spring 2023
Instructor
Hiroaki Kaido
Email: [email protected]
Office hours: Tue 3:30-5:00pm (in person, Rm. 415C), Fri 9:00-10:30am (via Zoom). Lectures: Tue, Thu, 2-3:30pm
Teaching Assistant
Yunus Kurt
Email: [email protected]
Office hours: Mon 9:00-10:30am in Rm. B10
Objectives
The aim of this course is to familiarize the students with fundamental concepts in modern statistics and to build their skills to analyze data. After introducing tools to summarize data, the course covers basic probability theory, which provides theoretical foundations for statistical inference. This course covers point and interval estimation of parameters and hypothesis testing. If time allows, we will have a quick overview of regression analysis. The emphasis of this course will be on having a solid understanding of statistical theory and knowing how to apply them to economic data. The students will use Stata to analyze empirical examples. This course belongs to the theoretically advanced track (EC303-304) of the statistics/econometrics sequence. After completing this course, the students are expected to be ready for taking EC304.
Course website:
The course website is on Blackboard Learn. Announcements will be made through the course website. Please check it periodically.
Textbook
Jay L. Devore, Kenneth N. Berk, and Matthew A. Carlton Modern Mathematical Statistics with Applications, 3rd edition, 2021, Springer.
This book’s E-book version can be downloaded from Springer Link using BU’s ez-proxy.
References:
• Advanced textbook: Casella, G., and R. Berger Statistical Inference, 2nd Edition, 2002, Duxbury Press,
• Online resources on Stata: https://www.stata.com/features/documentation/. See in particular “Getting Started with Stata” (for your operating system).
Prerequisites
EC101 or EC111
EC102 or EC112
No prior preparation in statistics is required, but familiarity with calculus is assumed. If you think you need to review calculus, a good undergraduate level textbook is
Kenneth A. Ross Elementary Analysis, 2013 Springer
(This book’s E-book version is available from Springer Link.)
Software: Students who are taking EC203/204 or EC303/304 are required to purchase the econometric software package Stata. It can be ordered online at: http://www.stata. com/order/new/edu/gradplans/student-pricing/. For the class you should purchase Stata/BE 17 ($225 for a perpetual license, $94 for a one-year license, $48 for a six-month license) which has no limitations on the size of the data set used, and which would be very useful for any type of analysis you might want to do in the future, either for an internship or a senior honors thesis. You will also be using Stata in EC304 (in both classes the use of Stata is an integral part of the course). We will start using Stata right away, so students should be sure to buy their copy of Stata within the first week of class.
Grading and Exam policies
The final grade will be determined based on problem sets (25% of final grade), a midterm exam (30% of final grade), and a final exam (45% of final grade).
• Problem sets:
Problem-set due dates will be announced in class and on Blackboard. There will be 5-6 problem sets. You are allowed to work in groups on problem sets, but you must turn in your own copy through Blackboard. Late problem sets will not be accepted because the answer key will be posted on the course website immediately. Upon computing the total score for the problem sets, we will drop the problem set with the lowest score and take the sum of the rest. There will be some questions that require the use of
Stata. When you report graphs or tables created by Stata, you must ensure they have meaningful titles and labels.
• Exams:
The midterm will be held on March 14 (in class). The date of the final exam will be announced.
If you have questions on grading (both problem sets and exams), you must contact the TA within a week after you receive your homework or exams.
Academic conduct
Students should know and understand the CAS Academic Conduct Code. Copies of the are available in room CAS 105. Any suspected academic misconduct will be reported to Dean’s Office.
Office hours
You are encouraged to come to our online office hours if you have any questions about the course material. If you are unable to come to our regular office hours, please make an appointment by sending us an email. If you have questions that need brief answers, you can also ask me or TA by email, but please be aware that we may not be able to answer questions that need lengthy explanations. If you have such questions, please come to our online office hours.
Course outline
The following is a tentative outline of the course.
Class
Topics
Textbook Chapters
Class |
1 |
Introduction |
|
Class |
2 |
Descriptive Statistics I |
Ch. 1.1-1.2 |
Class |
3 |
Descriptive Statistics II |
Ch. 1.3-1.4 |
Class |
4 |
Introduction to Probability Theory |
Ch 2 1-2 2 |
Class |
5 |
Joint and Conditional Probabilities |
Ch. 2.4 |
Class |
6 |
Bayes’Theorem & Independence |
Ch 2 5 |
Class |
7 |
Random Variables & Moments |
Ch. 3.1-3.4 |
Class |
8 |
Discrete RVs |
Ch. 3.5, 3.7 |
Class |
9 |
Continuous RVs |
Ch. 4.1-4.3 |
Class |
10 |
Continuous RVs |
Ch. 4.4, 4.6-4.7 |
Class |
11 |
Joint Distributions I |
Ch. 5.1-5.3 |
Class |
12 |
Joint Distributions II |
Ch. 5.4-5.5 |
Class |
13 |
Sampling & χ2 ,t,F distributions |
Ch. 6.1, 6.2, 6.4 |
Class |
14 |
Large Sample Theory |
Ch. 6.2 & Appendix |
Class |
15 |
Point Estimation I |
Ch. 7.1-7.2 |
Class |
16 |
Point Estimation II |
Ch. 7.3-7.4 |
Class |
17 |
Confidence Intervals |
Ch. 8.1-8.4 |
Class |
18 |
Hypothesis Testing I |
Ch. 9.1-9.3 |
Class |
19 |
Hypothesis Testing II |
Ch. 9.4-9.5 |
Class |
20 |
Bayesian Inference I |
Lecture Notes |
Class |
21 |
Bayesian Inference II |
Lecture Notes |
Class |
22 |
Linear Regression I |
Ch. 12.1-12.3 |
Class |
23 |
Linear Regression II |
Ch. 12.4-12.5 |
Class |
24 |
Summary of the 2nd half |
|
Class |
25 |
Additional Topics |
|
2023-01-31