Department of Economics, University of California - Davis
Spring 2016

Professor Colin Cameron
1124 Social Sciences and Humanities

Tues Thurs 1.40 - 3.00 p.m. Hunt 100

Office Hours:
Wednesday afternoon    2.00 p.m. - 4.00 pm.
Thursday morning         10.00 a.m. - 11.00 a.m..

Teaching Assistants: 
   Ilhyun Cho   Sections A01, A02 and A03 
    Office hours: Wednesday 11.00-2.00 pm   SSH 0115
   Brendan Callahan   Sections A04 and A05 
    Office hours: Wednesday 10.00-11.00, Thursday 12.15-1.15pm   SSH 0120
   Bingwei Yu   Section A06
    Office hours: Thursday 10-11am  SSH0121

Section A01  Wednesday   8.00-8.50 am  in Hutchison 93
    Section A02  Wednesday   9.00-9.50 am  in Hutchison 93
    Section A03  Wednesday 10.00-10.50 am  in Hutchison 93
    Section A04  Wednesday 11.00-11.50 am  in Hutchison 93
    Section A05  Wednesday 12.10-1.00 pm  in Scilab 2020
    Section A06  Wednesday   1.10-2.00 pm  in Scilab 2020

Course Goals:
(1) Locate economics data and provide meaningful economic analysis of these data.
(2) Use a standard econometrics package (Stata) to produce charts, scatter plots, descriptive statistics and simple linear regression.
(3)  Provide a bridge between introductory statistics and more advanced data analysis courses (e.g. between Statistics 13 and Economics 140).

Economics 1A-B, Statistics 13 or 32 and Math 16A-B or consent of instructor.
The essential prerequisites are exposure to introductory lower-division courses in economics and statistics.

Relationship to Economics 140
Economics 140 (Econometrics) is a more advanced course that also covers the methods of Economics 102.
Economics 140 has Economics 102 or any upper division statistics class as a prerequisite. i.e. Those wanting to take Economics 140 do not have to take 102, but can instead take an upper division statistics class.

Topical Outline by Lecture Number:

For all topics an essential ingredient is that economics data be analyzed throughout. This includes case studies that include key introductory economics relationships, such as the Phillips curve.

A. Introduction:
  1.- Introduction and getting going on Stata  (chapter 1 + Stata).

B. Univariate: Analysis of a single economics variable
  2. - Summarizing data using descriptive statistics and visualizing data using charts (chapter 2).
  3. - Economics Data (chapter 3)
  4. - Univariate data transformation (chapter 4)
  5. - The sample mean (chapter 5) 
  6. - Statistical inference based on the sample mean using confidence intervals and t tests (chapter 6)
  7. - Statistical inference generalizations (ch.7.1-7.2)
  8. - ***** First midterm exam  *****

C. Bivariate: The relationship between two economic variables
 9. - Bivariate data summary: scatter plots, correlation and regression (chapter 8)
10. - The least squares estimates (chapter 9)
11. - Statistical inference on regression coefficients (chapter 10)
12. - Bivariate case studies (chapter 11)
13. - Data Transformations for bivariate regression (chapter 12)
14. - ***** Second midtem exam *****

4. Multivariate: The relationship between more than two economic variables
15. - Multiple regression (chapter 13)
16. - Inference for multiple regression (chapter 14)
17. - Case study (chapter 15)
18. - Data Transformations for multivariate regression (chapter 16)
19. - Model Checking (chapter 17)
20. - Review

Required Materials:
Available March 30 (hopefully) at Davis Copy Maxx (Phone: (530)758-2311 at 232 Third Street - corner of 3rd and University Avenue). This material will not be posted on the web.
Lecture Notes for Analysis of Economics Data 102.
These lecture notes cover the entire course.
Earlier versions of the notes may also be adequate if Fall 2012 or later, though there have been substantial recent changes.

Additional Materials:
Stata handouts are also at
Data sets and Stata programs will be made available.

Reading List:  
Topic Lecture Notes
1. Univariate Chapters 1-7, Appendix A-B

2. Bivariate Chapters 8-12
3. Multivariate Chapters 13-16

4. Additional topics Chapter 17

Discussion Sections:
These are held in a university computer lab in Hutchison 93 or 2020 SciLab.
For university computer lab availability go to

Computer Materials: Assignments use Stata.
There are two options ...

1. Use Stata on university lab computers (free).
a. Stata can be accessed in Hutchison 93 lab in our discussion section and when it is open and no other class is using it.
b. Stata can also be accessed in 2020 SciLab when it is open and no other class is using it.
c. For computer room availability see
d. You can access Stata remotely, but only when 2020 SciLab or 93 Hutchison is closed (for SciLab after 6 pm (?) and for Huthison after 10 pm  (?) plus late nights, early morning and weekends).
See  This requires a Remote Desktop Connection Client.
In Spring 2015 (this may have changed) only 30 remote connections per lab are possible - you remotely connect to 2020 SciLab or 92 Hutchison lab computer and there are only 30 computers in each. So try to be quick so other students can get access.

2. P
urchase Stata for PC or Mac. This is NOT a requirement.
Go to to order Stata
a. Cheapest is Small Stata for six months at $38. This is adequate for this class.
b. If you plan to go on and do Economics 140 (Econometrics) this uses Stata/IC (for moderate-sized data sets) which costs $75 for six months or $125 for a year.
c. If really serious about data analysis best is a perpetual (i.e. forever) license for Stata/IC costing $198.

Course Grading:
Midterm Exam1:   22.5%    Thursday April 21    
Midterm Exam2:   22.5%    Thursday May 12  
Assignments:         10%       Due 1.40 p.m. Thursdays 
April 7, 14, 28; May 5, 26; June 2.
Final Exam:           45%       Tuesday June 7  10.30 a.m.-12.30 p.m.   

Assignments will be graded satisfactory (2%) or unsatisfactory (0%). Full solutions will be distributed. Satisfactory means a serious attempt to answer at least 80% of the questions. The lowest of the scores on the six assignments is dropped, i.e. no penalty for not handing in one assignment if the other five are graded satisfactory. No credit for late assignments. Academic honesty is required - see below.

Exams will be closed book. Exams will include questions on use of Stata.
A formula sheet will be provided. Note that the final exam is comprehensive.

Scores are posted at Smartsite.
Regrading: Assignment scores and exam scores will be posted on myucdavis. Any concerns about scores must be raised within one week of when graded work is first returned in class.

Given the course total score I form a curve and allocate grades using this course score curve and to fit in with the department policy: "To ensure fairness and consistency in grading, the Department expects that the GPA in Economics undergraduate class will average 2.7." (For example, a distribution with 25% A's, 35% B's, 30% C's, 5% D's, and 5% F's could be consistent with an overall GPA of 2.7.)

Note that there is no automatic conversion formula such as an 85 is a B. Instead if 85 was the median (middle) score among all students who took the class then you would get the median grade which is most often C+/B-. To let you know how you are going on each exam I give the distribution of the scores for the exam along with a "suggestive" grading curve. But the course grade is based on a course curve.

Academic integrity is required. What is academic integrity? From the UCD Student Judicial Affairs website, examples of Academic Misconduct include:

- includes receiving or providing unpermitted assistance on exams; using unauthorized materials during an exam; altering an exam and submitting it for regrading; taking an exam for another; failing to stop working on an exam when time is called; providing false excuses to postpone tests or due dates; fabricating data or references.

Unauthorized Collaboration - working with others on graded coursework without specific permission of faculty (on in-class or take-home tests, papers, labs, or homework assignments).
Plagiarism - using another's work without giving credit. You must put others' words in quotation marks and cite your source, and must give citations when using others' ideas, even if paraphrased in your own words.
Repeated Work: Submitting the same work in more than one course, unless authorized by the instructor.
Exams: "Wandering eyes," talking during exams, having notes visible, or leaving the exam room without permission.

IMPORTANT: For my class the assignment work handed in must be your own. Each person must create their own Stata output and write up their own answers.