ECONOMICS 122A --- Applied Econometrics I (ONLINE)

Description: Econometrics provides powerful statistical tools to analyze economic data. Applied econometrician skills are widely appreciated in the private and public sector. This is the first course in the 122 sequence of applied econometrics. Students will learn different econometric techniques and their underlying assumptions and limitations. Moreover, students will have the opportunity to apply these techniques to real economic data.

Textbook: J.H. Stock and M.W. Watson, Introduction to Econometrics, Fourth Edition (Pearson, 2019). Pearson provides a bundle that includes etext and MyLab ($55 for one quarter, $75 for two quarters). To get access, register via the course Canvas website by following the link in “MyLab and Mastering”. If you face registration issues, please register using the free-trial and send me an email.

Contact info: My office hours are on Thursdays from 9 to 10:30am via Zoom (https://uci.zoom.us/my/jantonio). Please visit the course Canvas website for course information, announcements and homework assignments. My e-mail is [email protected].

Grading: Homework (20%), lecture quizzes (10%), midterm (30%) and final (40%). The midterm will be held on August 17 from 7 to 8:30pm. The final is scheduled for September 7 from 7 to 9pm. I will use Respondus Lockdown Browser and Monitor (from within the course Canvas website) for the examinations. There won’t be make-up exams.

Homework: Homework assignments are done in MyLab. You can complete your assignments immediately after they are available. The submission deadline has been set on Sundays at 11:59pm. See table with deadlines in page 3. There is a total of 64 homework points. When calculating your final homework grade (20%), you will be allowed to miss 10 percent of the points (if you get at least 57 points, you will get the full 20% that homework is worth).

Lecture quizzes: There will be 19 lectures. Each lecture has several questions and your “lecture quizzes” grade will depend on the number of questions you get right in the entire quarter. There is a total of 149 questions. When calculating your final “lecture quizzes” grade (10%), you will be allowed to miss or get wrong 10 percent of the questions (if you answer and get right at least 134, you will get the full 10% that quizzes are worth). This is the process we will follow:

1. At the beginning of every week, the lectures of that week will be posted on the “Assignments” tab in Canvas under the name “Lecture X with quiz”.

2. You will have up to Friday at 11:59pm to watch the lectures of that week. While you watch each lecture, the video will stop from time to time to ask you questions about the material (you will not be able to fast forward). The questions are typically easy, and their objective is to make sure you are following the lecture as if you were in the lecture hall.

3. After Friday at 11:59pm, you will no longer have access to the quizzes of that week. You would lose those points, so please organize yourself to make sure you watch the lecture videos with enough time. To absorb better the material, I suggest you split the videos during the week as if you are taking the class on campus.

4. After Friday at 11:59pm, the lecture videos of the week will be posted under the “Lecture videos” module, but it will no longer allow you to answer the quiz questions. At that time, I will also post an incomplete set of lecture slides under the module “Lecture slides”. They are incomplete so that you have the incentive to watch the lecture videos.

Course Outline: We will cover 36 bullets organized around 5 topics.

I. Introduction (Chapter 1)

1. Introduction to Econometrics

2. The use of summation operators

II. Review of Probability (Chapter 2)

3. The properties of the expectations operator

4. Covariance and correlation

5. The distribution of a continuous random variable

6. The Normal distribution

7. The Central Limit Theorem

8. Other distributions

III. Review of Statistics (Chapter 3)

9. Introduction to Statistics

10. Statistical inference about a population mean

11. Properties of the average

12. Hypothesis testing for the population mean

13. Confidence intervals

14. p-values

15. Comparing means from two populations

16. Exercise for comparing means

17. t-statistic and testing when sample size is small

IV. Linear Regression with One Regressor (Chapters 4 and 5)

18. Introduction to Ordinary Least Squares (OLS)

19. Goodness of fit

20. OLS assumptions

21. Distribution of OLS estimators

22. Hypothesis testing

23. Confidence intervals and p-values

24. Heteroskedasticity and homoskedasticity

25. Exercise: Wages and education

V. Linear Regression with Multiple Regressors (Chapters 6 and 7)

26. Omitted variable bias

27. Multiple linear regression model

28. OLS in the multiple linear regression model

29. Single hypothesis testing

30. Single hypothesis testing involving more than one parameter

31. Joint hypothesis testing

32. Goodness of fit

33. OLS assumptions

34. Multicollinearity and the dummy variable trap

35. Exercise: Wages and education reloaded (Part 1)

36. Exercise: Wages and education reloaded (Part 2)

Course pace:

Lecture	Bullets covered	Quiz points	Week	Deadline (FRIDAY, 11:59PM)
1	1, 2	4	1	August 6
2	3	7	1	August 6
3	4,5,6	9	1	August 6
4	7,8	1	1	August 6
5	9, 10, 11	5	2	August 13
6	12	12	2	August 13
7	13, 14, 15	10	2	August 13
8	16, 17	7	2	August 13
9	18, 19	5	3	August 20
10	20, 21, 22	11	3	August 20
11	23, 24	14	3	August 20
12	25	12	4	August 27
13	26	8	4	August 27
14	27, 28, 29	7	4	August 27
15	30	3	4	August 27
16	31,32	7	5	September 3
17	33, 34	8	5	September 3
18	35	12	5	September 3
19	36	7	5	September 3

MyLab homework deadlines: There are seven MyLab homeworks (one for each textbook chapter). There are 64 points across the seven homeworks.

Chapter	Points	Deadline (SUNDAY, 11:59PM)
1	7	August 8
2	10	August 8
3	10	August 15
4	10	August 22
5	9	August 29
6	10	September 5
7	8	September 5

Examinations:

Examinations	Bullets covered	Dates
Midterm (30%)	1 to 17	August 17, 7-8:30pm
Final (40%)	18 to 36	September 7, 7-9pm

Remote discussion sections: In section you will review important concepts, get help for problem sets and practice with real world data using EViews. Your TAs will help you succeed in this class, so please make sure you are closely following their communications and attending scheduled meetings.

Letter grade scale: This is the scale that will be used to compute your final letter grade

A+	A	A-	B+	B	B-	C+	C	C-	F
(99,100)	(93,98.99)	(88,92.99)	(83,87.99)	(78,82.99)	(73,77.99)	(68,72.99)	(63,67.99)	(58,62.99)	<58

Remember that in the calculation of your final grade, you are allowed to miss (or get wrong) 10% of the lecture quizzes questions---as long as you get 134 or more questions right (out of 149) you will get the full 10% that quizzes are worth. As well, in the calculation of your homework grade, you will be allowed to miss 10 percent of MyLab points---as long as you get 57 points (out of 64) across the 7 assignments, you will get the full 20% that homework is worth.

Example 1: John got 65 in his midterm, 75 in the final, 45 points in MyLab, and answered correctly 107 of the quizzes questions. His grade will be:

65*.3+75*.4+(45/57*100)*.2+(107/134*100)*.1=73.27 (B-)

Example 2: Maria got 85 in her midterm, 95 in the final, 61 points in MyLab, and answered correctly 147 questions. Her grade will be:

85*.3+95*.4+20+10=93.5 (A)

Academic Integrity Statement

Learning, research, and scholarship depend upon an environment of academic integrity and honesty. This environment can be maintained only when all participants recognize the importance of upholding the highest ethical standards. All student work, including quizzes, exams, reports, and papers must be the work of the individual receiving credit. Academic dishonesty includes, for example, cheating on examinations or any assignment, plagiarism of any kind (including improper citation of sources), having someone else take an examination or complete an assignment for you (or doing this for someone else), or any activity in which you represent someone else’s work as your own. Violations of academic integrity will be referred to the Office of Academic Integrity and Student Conduct. The impact on your grade will be determined by the individual instructor’s policies. Please familiarize yourself with UCI’s Academic Integrity Policy (https://aisc.uci.edu/policies/academic-integrity/index.php) and speak to your instructor if you have any questions about what is and is not allowed in this course.