Econ 1150 Applied Econometrics 1

Transcription

Applied Econometrics I -- Economics 1150
Fall 2011
Classes: M and W 4:30 – 5:45 p.m. in 1500 WWPH
Instructor: Irina Murtazashvili
TAs: Jerry Kosoff and Chen Qian
Email: irinam@pitt.edu (the best way to contact me)
TA Email: gak15@pitt.edu / chq2@pitt.edu
Office Hours: M and W 1:45-2:45p.m, and by appointment
TA Office Hours: F 2-3p.m./Tu 2:30-3:30p.m.
Office: 4509 WWPH
TA Office: 4514 WWPH
Website: Blackboard (https://coursweb.pitt.edu)
Please note that I have a 24-hour business days email response policy.
Textbook: Introductory Econometrics: A Modern Approach, Fourth Edition, by Jeffrey M. Wooldridge
Course Description: Economics 1150 is an introductory course in econometrics. The course covers some
statistical tools to understand economic relationships. We will discuss economic applications and we will analyze
real economic data. Students should be comfortable with college-level algebra. Some background in calculus is
useful, and inadequate statistics background may make this course more difficult than necessary. One central goal
of this course is to use and correctly interpret the output of a software package called STATA.
Grading: Problems Sets 20% (I will randomly grade two questions from each Problem Set), Midterm Exams
(Tentatively October 5th and November 16th) 25% each, Term Paper (Due December 7th in class) & Presentation
25%, Attendance (will be taken randomly throughout the semester) 5%.
[98; …) = A+; [93; 98) = A; [90;93) = A-; [88;90) = B+; [83;80) = B, and so on.
University Policies: We will adhere to the University’s Academic Integrity Policy in this class. See the
University of Pittsburgh’s Undergraduate Bulletin or the Guidelines on Academic Integrity; Student and Faculty
Obligations and Hearing Procedures at www.pitt.edu/~provost/ai1.html for full details on this. The Office of
Disability Resources and Services, 216 William Pitt Union (412)-624-7890/(412)-383-7355 (TTY) is available for
students who have or may request an accommodation for a disability. If needed please contact the office as early
as possible in the term.
Lateness and Courtesy: Out of respect for your instructor and your classmates, please arrive to class on time and
turn off all pagers and cell phones during class.
Tentative Course Outline and Reading List:
(1) Introduction (Chapter 1). Approximately 1 class.
(2) Simple Regression (Chapter 2). Approximately 5 classes.
(3) Multiple Regression under “ideal” conditions Approximately 10 classes.
3.1) Estimation (Chapter 3).
3.2) Testing (Chapter 4).
3.3) Functional Form and Dummy Variables (Chapters 6.2, and 7).
3.4) Other Issues (Chapters 6.1, and 6.3).
(4) Violation of the “ideal” conditions. Approximately 6 classes.
4.1) Heteroskedasticity (Chapter 8).
4.2) Endogeneity problems (Chapter 3.3).
4.3) Data problems (Chapter 9).
Note: The primary source of materials for the course is lectures. In general, the textbook presents the materials at
a more difficult level than I will present in the class.
Applied Econometrics I -- Economics 1150 Spring 2012 Classes: M 6:00 – 8:30 p.m. in 4900 WWPH Instructor: Irina Murtazashvili TAs: Akash Goyal and Andrew O’Rourke Email: irinam@pitt.edu TA Email: akg25@pitt.edu/ aco14@pitt.edu Office Hours: M 4:00-‐5:00p.m, and by app. TA Office Hours: TBA Office: 4509 WWPH TA Office: TBA Website: Blackboard (https://coursweb.pitt.edu) Please note that I have a 24-‐hour business days email response policy. Textbook: Introductory Econometrics: A Modern Approach, Fourth Edition, by Jeffrey M. Wooldridge Course Description: Economics 1150 is an introductory course in econometrics. The course covers some statistical tools to understand economic relationships. We will discuss economic applications and we will analyze real economic data. Students should be comfortable with college-‐
level algebra. Some background in calculus is useful, and inadequate statistics background may make this course more difficult than necessary. One central goal of this course is to use and correctly interpret the output of a software package called STATA. Grading: Problems Sets 20% (I will randomly grade two questions from each Problem Set), Midterm Exams (Tentatively February 6th and April 2nd) 25% each, Term Paper (Due April 16th in class) & Presentation 25%, Attendance (will be taken randomly throughout the semester) 5%. [98; …) = A+; [93; 98) = A; [90;93) = A-‐; [88;90) = B+; [83;80) = B, and so on. University Policies: We will adhere to the University’s Academic Integrity Policy in this class. See the University of Pittsburgh’s Undergraduate Bulletin or the Guidelines on Academic Integrity; Student and Faculty Obligations and Hearing Procedures at www.pitt.edu/~provost/ai1.html for full details on this. The Office of Disability Resources and Services, 216 William Pitt Union (412)-‐
624-‐7890/(412)-‐383-‐7355 (TTY) is available for students who have or may request an accommodation for a disability. If needed please contact the office as early as possible in the term. Lateness and Courtesy: Out of respect for your instructor and your classmates, please arrive to class on time and turn off all pagers and cell phones during class. Tentative Course Outline and Reading List (1 class is equivalent to 75 minutes): (1) Introduction (Chapter 1). Approximately 1 class. (2) Simple Linear Regressions (Chapter 2). Approximately 6 classes. 2.1) Definition of the simple linear regression (Ch. 2.1) 2.2) Deriving the ordinary least squares estimates (Ch. 2.2) 2.3) Algebraic properties of the OLS estimators (Ch. 2.3) 2.4) Units of measurement and functional forms (Ch. 2.4) 1
2.5) Statistical properties of the OLS estimators (Ch. 2.5) 2.6) Regression through the origin (Ch. 2.6) (3) Multiple Linear Regressions under “ideal” conditions. Approximately 11 classes. 3.1) Estimation (Chapter 3) 3.1.1) Mechanics and interpretation of the multiple linear regression (Ch. 3.2) 3.1.2) The expected value of the OLS estimator (Ch. 3.3) 3.1.3) The variance of the OLS estimators (Ch. 3.4) 3.1.4) Efficiency of OLS (Ch. 3.5) 3.2) Testing (Chapter 4) 3.2.1) Sampling distribution of the OLS estimators (Ch. 4.1) 3.2.2) Testing hypothesis about a single population parameter (Ch. 4.2) 3.2.3) Testing hypothesis about multiple linear restrictions (Ch. 4.5) 3.3) OLS asymptotics (Ch. 5.1 and 5.2) 3.4) Further Issues with MLRs (Chapter 6) 3.4.1) Models with quadratics (Ch. 6.3) 3.4.2) Models with interaction terms (Ch.3) 3.4.3) Adjusted R-‐squared (Ch. 6.3) 3.5) Dummy variables (Chapter 7) 3.5.1) Explanatory dummy variables (Ch. 7.1-‐7.4) 3.5.2) Dependent dummy variables (Ch. 7.5) (4) Violation of the “ideal” conditions. (If time permits.) 4.1) Heteroskedasticity (Chapter 8) 4.2) Specification Issues (Chapter 9) Note: The primary source of materials for the course is lectures. In general, the textbook presents the materials at a more difficult level than I will present in the class. 2
University of Pittsburgh
Department of Economics
CRN: 19608
ECON 1150: Applied Econometrics
Syllabus
Instructor: Steven Bosworth
Office: 4909 Posvar Hall
Tel: 412-648-1796
E-mail: sjb74@pitt.edu
Website: www.pitt.edu/˜sjb74
Class meets Mondays and Wednesdays 6:00 – 9:15pm in 4716 Posvar Hall.
Office hours
Tuesdays and Thursdays 3:00 – 5:00pm. Additional hours are available by appointment
and can be scheduled by e-mail. Tracking me down in my office is another option but there
are no guarantees I will be there.
Communication
E-mail is my preferred method of out-of-classroom communication. I will make every effort to answer all emails within 24 hours. Likewise it is your responsibility to check your
@pitt.edu address on a regular basis as this is the address I have on file for all of you.
I also have a mailbox in the department, it is located in the 4900 area (across from this
classroom 4716) and is the one labeled ‘Bosworth’.
Course description
This course provides a rigorous introduction to the methodology of econometrics. Upon
completion of this course students will have a deep understanding of:
• What econometrics is
• How economists conduct empirical research
• The linear regression model
• Estimation and inference using Ordinary Least Squares
• Pitfalls of using OLS and how to avoid or work around them
• Pulling causality out of correlation instrumental variables
• Using computer software to programmatically work with data
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Prerequesites
You should be fairly comfortable with concepts from algebra and basic calculus. Furthermore, this course is heavy on probability theory and statistics. Having taken the 1000-level
statistics course is a minimum. If the phrases “cumulative distribution” or “t-statistic”
sound foreign to you; you should seriously reconsider your readiness to take econometrics.
Textbook
The text for this class is Introductory Econometrics: A Modern Approach 4e by Jeffrey M.
Wooldridge. You must purchase this book, but a searchable pdf copy can also be found on
my Dropbox account to which you will receive an invite from me at your Pitt e-mail.
Software
The homework and many in-class exercises will utilize the Mathematica software. You
need not already know how to use this system, as it will be explained in-class. It should be
installed in all campus computing labs. Furthermore, you may obtain a licensed copy for
your personal Windows, Mac or Linux machine for $5 at Software Licensing Services in
204 Bellefield Hall.
Class rules
You are an adult. I do not have an attendance policy because I work off the assumption that
you, as an adult, must have a perfectly valid reason for any absence from my class. My suggestion however, is that you attend every lecture. This semester is extremely compressed
and we will cover a large amount of material in a very short time. Furthermore, while you
are in lecture please refrain from distracting other students by talking, using your phone,
texting, etc.
Students with disabilities
Any student with a need for special accommodation due to disability should inform me of
this. The Disability Resources and Services Office (216 William Pitt Union, 412-624-7890)
will coordinate the needed accommodations.
Exams
Dates of exams are contained in the detailed course schedule below. Exams will contain
mostly problem-solving questions but may also include short writing responses. You may
bring your notes and book to the exams. Exams are not cumulative. I will not offer make-up
exams, with one exception: if you notify me or the department secretary as soon as possible
of a serious reason (such as hospitalization) for missing an exam. This notification should
be given prior to the exam.
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Assignments
There will be periodic homework assignments. Homework will not be accepted after
11:59pm on the due date posted. Homework is worth 13 of your grade, and will be very
helpful in studying for the exams. You are allowed to work in groups, but everyone must
turn in a copy of the assignment individually.
Cheating
I will monitor all tests very aggressively. Any student caught cheating will automatically
fail the course, without exception. The university policies on plagiarism are well defined
and I will follow them.
Help
The material of this course is highly cumulative. If you do not understand something,
please seek help immediately. You are welcome to come to my office with questions about
the general concepts presented in lecture; or to assist you in problem-solving skills required
to complete a homework assignment.
Grading
Although attendance of lectures is not required, missing classes will seriously compromise
your performance in this course.
Your course grade will be computed with the following weights:
Homework assignments
Midterm exam
Final exam
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3
1
3
1
3
The course letter grade will be determined as follows:
• after the final exam I will compute course scores incorporating scores earned on tests
and homework weighted as indicated above
• a student fails the class if the determined course score is below 50
• the rest are graded based on the following scale:
88–100 A range
75–87
B range
60–74
C range
50–59
D range
• there may be curving to the extent that I reserve the right to uniformly add points (or
not) to all exam scores; no points will ever be subtracted
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Course calendar
Week
1
2
3
4
5
6
Dates
Jun 25
Jun 27
Jul 02
Jul 04
Jul 09
Jul 11
Jul 16
Jul 18
Jul 23
Jul 25
Jul 30
Aug 01
Lecture
Review of statistics
The simple regression model
Multiple regression: Estimation
No class – holiday
Multiple regression: Inference & Asmptotics
Midterm exam
Multiple regression: Further issues
Multiple regression: Qualitative information & dummy vars.
Heteroskedasticity
Specification and data issues
Instrumental variables and 2SLS
Final exam
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ECON 1150
S. D. Namoro
Fall Term 2012
ECON 1150: Applied Econometrics 1
Instructor: Soilliou D. Namoro, WWPH 4712, Phone Ext: 8-7141.
Course Description
This course is an introduction to econometric methods from the perspective of users. The
main goal of the course is to guide the student’s incursion into the application of
econometrics to real-world problems. Econometric methods and techniques are always
based on more or less realistic assumptions dictated by the need to reconcile the real-life
constraints imposed by available economic data, with a coherent mathematical
framework. In this course, students will learn to understand and interpret these
assumptions in various empirical settings. The background knowledge needed to succeed
in this course is college algebra and some elements of probability and statistics. But, the
indispensable tools of probability and statistics will be taught as part of the course. Given
the applied nature of the course, basic familiarity with computers is also required. Unless
otherwise stated, the statistical package STATA will be used for most examples.
Time and Classroom
MW 3:00 PM - 4:15 PM, CL00358
Office Hour: Monday 9:50AM-10:50AM
Textbook
Jeffrey M. Woodridge, Introductory Econometrics. A Modern Approach, South-Western
4-Th Edition.
Evaluation
The final grade will be based exclusively on:
1- Two midterm exams and a final exam, all held in the officially assigned class room.
2- Homework assignments. There will be at least one homework assignment per week.
Note that overdue assignments that are not motivated by well documented medical or
other reasons are not accepted. Failure to hand-in on time at least 2/3 of the total number
of homework assignments will result in failing the course.
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ECON 1150
S. D. Namoro
Each midterm exam is assigned the weight 0.20. The average score on homework
assignments will also account for 20 percent of the final grade. The final exam has the
weight 0.40. It is a comprehensive exam.
It is the responsibility of the student to be aware of the University of Pittsburgh's
policy and student obligations regarding academic integrity. This information is
available at the address
http://www.bc.pitt.edu/policies/policy/02/02-03-02.html
Students who have disabilities for which they want to request accommodations are
encouraged to contact me and the Office of Disability Resources and Services, 216
William Pitt Union, 412-648-7890/412-383-7355 (TTY), as early as possible in the
term. Disability Resources and Services will verify each student's disability and
determine reasonable accommodations for this course.
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ECON 1150
S. D. Namoro
Fall Term 2012
Instructor: Soilliou D. Namoro, WWPH 4712, Phone Ext: 8-7141.
Course Description
Time and Classroom
W 6:00 PM - 8:25 PM, WWPH04716
Office Hour: Monday 4:50PM-5:50PM
Textbook
4-Th Edition.
Evaluation
1
ECON 1150
S. D. Namoro
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ECON 1150
S. D. Namoro
Spring Term 2012
Soiliou Daw Namoro
Econ Dept. W.W.Posvar Hall, 4-th floor, office # 4712
Phone: 8-2242
Course Syllabus
Course Description
Time and Classroom
TH 11:00 PM - 12:15 PM, Benedum Hall 227
Office Hour: Thursday 9:30AM-10:30AM
Textbook
5-Th Edition.
Evaluation
1
ECON 1150
S. D. Namoro
2
ECON 1150: Applied Econometrics 1 (Summer 2013)
Instructor: Tate Twinam
Email: tat47@pitt.edu
Office: 4923 Wesley W. Posvar Hall
Course Meetings: MW 6pm–9:15pm
Room: 4716 Wesley W. Posvar Hall
Office Hours: TBA
Textbook:
Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach, 5th Edition
Prerequisites:
A “C” or better in the following courses: ECON (1100 or 1110) and MATH (0120 or 0220 or (0125
and 0126)) and STAT (0200 or 1000 or 1100 or 1152)
Course Outline:
Monday, June 24th
Overview, review of probability theory
Wednesday, June 26th
Review of statistical theory and introduction to linear
regression
Monday, July 1st
Linear regression: Estimation, HW 1 due
Wednesday, July 3rd
Linear regression: Inference
Monday, July 8th
No class
Wednesday, July 10th
Midterm exam
Monday, July 15th
Linear regression: Heteroskedasticity and measurement
error
Linear regression: Model specification
Monday, July 22nd
Linear regression: Model specification cont., HW 2 due
Structural equation models and instrumental variables
Monday, July 29th
Models for limited dependent variables, HW 3 due
Wednesday, July 31st
Final exam
Evaluation Policy:
Evaluations will be based on two exams (a midterm and a final) as well as three homework
assignments. Each exam will be worth 35% of your grade, while each homework will be worth
10%. Homework will be due within the first 10 minutes of class; if you cannot make it to class,
you can turn in your homework early to my departmental mailbox or email it to me. Late
homeworks will not be accepted unless accompanied by a doctor’s/Sheriff’s note indicating
illness/incarceration. Likewise, make–up exams will not be administered unless justified by a
doctor’s/Sheriff’s note. Exceptions are not fair to other students and will not be
granted.
Exam Policy:
Exams will be monitored and any student caught cheating will fail the course; you may not use
any books, notes, or electronic devices during the exams.
Academic Integrity:
This class will adhere to the University of Pittsburgh’s Academic Integrity Policy. See the
guidelines on Academic Integrity, Student and Faculty Obligations, and Hearing Procedures at
http://www.provost.pitt.edu/info/ai1.html.
Students with Disabilities:
If you have a disability for which you are or may be requesting an accommodation, you are
encouraged to contact both me and Disability Resources and Services, 140 William Pitt Union,
412-648-7890, as early as possible in the term.
ECON 1150
S. D. Namoro
Fall Term 2012
ECON 1150-1060 (12411): Applied Econometrics 1
Instructor: Soilliou Namoro, WWPH 4529, Phone Ext: 8-2242
Course Description
Time and Classroom
T/H 2:30:00 PM - 3:45 PM, Posvar Hall 4900
Office Hour: Tue 9:50AM-10:50AM
Textbook
5-Th Edition.
Evaluation
1
ECON 1150
S. D. Namoro
Course outline
Note: All chapters and pages are those of the textbook indicated in the syllabus. Lectures
will unfold according to the following sequence of topics.
1. Introduction and Background Material. Mostly provided in class. Refer to Chapter 1 for
the introduction and to Appendix B for a (rather more demanding) presentation.
2. Chapter 2: The simple Linear Regression
1. Definitions
2. Derivation of OLS estimators
3. Properties of OLS estimators
4. Units of measurement
5. Functional forms
6. Expected values and variances of the OLS estimators.
3. Chapter 3: Multiple Regression Analysis: Estimation
1. Motivations
2. Interpretation of OLS
3. Expected values of OLS estimators
4. Variances of OLS estimators
5. Gauss-Markov theorem
4. Chapter 4: Multiple Regression Analysis: Inference
1. Sampling distribution of the OLS estimators
2. Single-parameter t-tests
3. Confidence intervals
4. Test of about a single linear combination of parameters
5. Testing multiple linear restrictions.
5. Chapter 5: Multiple Regression Analysis: OLS Asymptotics.
1. Consistency
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ECON 1150
S. D. Namoro
2. Asymptotic normality
3. Asymptotic Efficiency
6. Chapter 6: Multiple Regression Analysis: Further Issues
3. More on Goodness-of-fit (page 191)
7. Chapter 7: Multiple Regression Analysis with Qualitative Variables
1. Describing qualitative variables
2. A single dummy independent variable
3. Using dummy variables for multiple categories
4. Interactions involving dummy variables.
8. Chapter 8: Heteroskedasticity
8.3. Testing for heteroskedasticity
STATA ASSIGNMENT ON COMPUTER
3
ECON 1150
S. D. Namoro
Fall Term 2012
ECON 1150-1100 (24158): Applied Econometrics 1
Instructor: Soilliou Namoro, WWPH 4529, Phone Ext: 8-2242
Course Description
Time and Classroom
T/H 400.00 PM – 5:15 PM, Posvar Hall 4900
Office Hour: Th 9:50AM-10:50AM
Textbook
5-Th Edition.
Evaluation
1
ECON 1150
S. D. Namoro
Course outline
Note: All chapters and pages are those of the textbook indicated in the syllabus. Lectures
will unfold according to the following sequence of topics.
1. Introduction and Background Material. Mostly provided in class. Refer to Chapter 1 for
the introduction and to Appendix B for a (rather more demanding) presentation.
2. Chapter 2: The simple Linear Regression
1. Definitions
2. Derivation of OLS estimators
3. Properties of OLS estimators
4. Units of measurement
5. Functional forms
6. Expected values and variances of the OLS estimators.
3. Chapter 3: Multiple Regression Analysis: Estimation
1. Motivations
2. Interpretation of OLS
3. Expected values of OLS estimators
4. Variances of OLS estimators
5. Gauss-Markov theorem
4. Chapter 4: Multiple Regression Analysis: Inference
1. Sampling distribution of the OLS estimators
2. Single-parameter t-tests
3. Confidence intervals
4. Test of about a single linear combination of parameters
5. Testing multiple linear restrictions.
5. Chapter 5: Multiple Regression Analysis: OLS Asymptotics.
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ECON 1150
S. D. Namoro
1. Consistency
2. Asymptotic normality
3. Asymptotic Efficiency
6. Chapter 6: Multiple Regression Analysis: Further Issues
3. More on Goodness-of-fit (page 191)
7. Chapter 7: Multiple Regression Analysis with Qualitative Variables
1. Describing qualitative variables
2. A single dummy independent variable
3. Using dummy variables for multiple categories
4. Interactions involving dummy variables.
8. Chapter 8: Heteroskedasticity
8.3. Testing for heteroskedasticity
STATA ASSIGNMENT ON COMPUTER
3
ECON 1150 - Applied Econometrics I
Department of Economics, University of Pittsburgh
Syllabus - Spring 2014
Instructor: Federico Zincenko, Ph.D.
Lectures: Tuesdays and Thursdays, 2:30pm - 3:45pm,
G36 Benedum Hall
Office Hours: Tuesdays 4:15pm - 5:00pm and Wednesdays 2:00pm - 3:00pm,
4713 Posvar Hall
E-mail: zincenko@pitt.edu
Reader: Yang Song
E-mail: yas27@pitt.edu
Course Description
The goal of this course it to introduce basic tools in applied econometrics that are
commonly employed in government, business, and academic research. These tools are
useful for those intending to become quantitative business and economic analysts, and
also, for those interested in knowing how economics is applied to real-world problems.
The primary topic of the course is the linear regression model, which allows us
to quantify the effect of changing one variable on another one. The course focuses
on interpretation and estimation of parameters, as well as, hypothesis testing. These
issues will be studied following an applied perspective. For this purpose, we can find
many interesting questions such as: does reducing class size improve elementary school
education? Is there racial discrimination in the credit market?
We will employ the statistical package STATA, a computer software widely used in
quantitative economic research. The background knowledge needed for this course is
college algebra, basic probability, and elementary statistics.
Textbooks
Main Reference
J. M. Wooldridge. Introductory Econometrics: A Modern Approach. 5th Edition.
South-Western, 2012.
1
Complementary Textbooks
R. C. Hill, W. E. Griffiths, and G. C. Lim. Principles of Econometrics. 4th
Edition. Wiley, 2011.
J. H. Stock and M. W. Watson. Introduction to Econometrics. 3rd Edition.
Addison-Wesley, 2011.
E. A. Tanis and R. V. Hogg. A Brief Course in Mathematical Statistics. Pearson
Prentice Hall, 2008.
Requirements and Grading Policy
The final grade will be based on six problem sets, two midterms, and a final exam.
The weights are as follows.
Problem Sets (20%): Six problem sets, each weights 3.33%. They involve the
statistical software STATA, which will be taught during lectures. Students are
allowed to submit their answers alone or in pairs. Problem sets will be due in
hardcopy at the beginning of the class on the specified date.
Midterms (40%): Two midterms, each weights 20%. The dates are Tuesday,
February 25th, and Thursday, April 10th. Both are in-class.
Final (40%): It is cumulative.
All exams are closed-book and no calculators or any electronic devices are allowed.
The only valid reason for missing an exam (or a homework) is serious illness to be
verified in writing by a medical doctor. If you cannot make one midterm due to a
serious illness, the final weights 60% instead of 40%. If you know that you cannot
make the final exam on the specified date, you cannot take this course.
Academic dishonesty will be handled according to the university regulations with
no exceptions. Students must be aware of the University of Pittsburgh’s policy on
Academic Integrity.1
1
This information is available at http://www.bc.pitt.edu/policies/policy/02/02-03-02.htm.
2
Disability Resources
If you have a disability for which you are or may be requesting an accommodation, you
are encouraged to contact both your instructor and the Office of Disability Resources
and Services, 216 William Pitt Union, 412-648-7890/412-383-7355 (TTY), as early as
possible in the term. Disability Resources and Services will verify your disability and
Course Outline
1. Introduction and background material. Review of elements of statistics; Chapter
1 and Appendix.
2. The Simple Regression Mode; Ch. 2.
3. Multiple Regression Analysis: Estimation; Ch. 3.
4. Multiple Regression Analysis: Inference; Ch. 4.
5. Multiple Regression Analysis: OLS Asymptotics; Ch. 5.
6. Multiple Regression Analysis: Further Issues; Ch. 6.
7. Multiple Regression Analysis with Qualitative Variables; Ch. 7.
8. Heteroskedasticity; Ch. 8.
9. Specification and Data Issues; Ch. 9.
3
Econ 1150 Applied Econometrics
Spring 2014
Instructor: Dr. Paul J. Noroski
Email: PJN5@pitt.edu
Office Hours: T/Th 12:30-1:30
and by appointment.
Class Times: T/Th 11:00-12:15
Location: CL-0342
Office: WWPH 4918-A
Course Information
Course Description:
Applied Econometrics is meant to familiarize students with the art of application of
econometrics to real world problems. Although theoretical structures will be covered in
some detail, the main emphasis will be on working with datasets and regression analysis
in an effort to find relationships between variables that affect the world.
Course Materials:
Textbook: "Introductory Econometrics: A Modern Approach” 5th ed. J. Wooldridge
CourseWeb: Check here often for assignments, exam dates, etc.
Student Learning Outcomes:
By the end of the course, students should be able to
1. Use statistical software programming (viz. Excel and STATA).
2. Use regression analysis to find the effects of variables on other variables.
3. Have a healthy understanding of the theoretical underpinnings of econometrics.
4. Understand and interpret the assumptions of econometric models in light of actual
empirical applications.
5. Become proficient in the management of datasets.
Course Policies
Attendance:
Although attendance will not figure directly into your grade for the semester, you are highly
encouraged to attend class. You will be responsible for getting any notes or materials for any
lectures that you miss.
Office Hours:
Students are encouraged to attend office hours to discuss any of the course content. If you are
unable to meet during office hours, contact me so that we may coordinate another time to
meet.
Cheating and Academic Integrity:
All students are expected to adhere to the standards of academic honesty. Any student
engaged in cheating, plagiarism, or other acts of academic dishonesty would be subject to
disciplinary action. Any student suspected of violating this obligation for any reason during the
semester will be required to participate in the procedural process, initiated at the instructor
level, as outlined in the University Guidelines on Academic Integrity
http://www.pitt.edu/~provost/ail.html. This may include, but is not limited to the confiscation
of the examination of any individual suspected of violating the University Policy.
If you are caught cheating on an exam or an assignment, you will receive a zero on the exam or
assignment. In addition, the event will be reported to the Office of Judicial Affairs, which may
lead to additional actions from the University.
Use of Electronics:
The use of cell phones during lectures is a disrespectful distraction to your instructor and other
classmates. Use of laptops for activities other than note taking is also distracting. Please turn
your cell phones and electronic devices off while in class. In emergency situations, please
discuss limited use of cell phone with me prior to the class during which you would like to use
your cell phone.
Email:
My Pitt Email is typically the best way to get in touch with me. Try to plan ahead so that you
can ask me questions well before any graded assignments are due. For example, please don't
Email questions about problem sets and exams the night before they're due (or, if you do,
realize that I might not be able to respond in time).
Disability Services:
If you have a disability, please contact me and the Office of Disability Resources and Services
(DRS), 216 William Pitt Union, 412-648-7980/412-383-7355 (TYY) as early as possible in the
term. DRS will verify your disability and determine reasonable accommodations for this course.
Policy Regarding Missed Exams:
Out of fairness to everyone in the class, exams are only given at the assigned time. If you
cannot attend an exam due to a personal emergency outside your control, please let me know
as soon as possible.
Course Grades
Your grade in the course will be a weighted average of problem set scores, papers, and two
exams. The particular weights are given by
Problem Sets and Papers:
Midterm:
Final Exam:
30%
35%
35%
The exams will be based on material from the lectures and from the book. The exams will not
be comprehensive. Note that the exams make up 70% of your grade.
The final exam will be held on the last day of class (Thursday, April 17).
Periodically, I'll assign problem sets relevant to the course material. Each problem set and
written assignment will be equally weighted with respect to your grade. As a whole, problem
sets will make up 30% of your grade.
Your semester average will be converted to a letter grade according to the following table.
Letter
A
AB+
B
BC+
C
CD+
D
DFailure
%
93-100
90-92
87-89
83-86
80-82
77-79
73-76
70-72
67-69
63-66
60-62
<60
ECON 1150: Applied Econometrics 1 (Summer 2014)
Instructor: Tate Twinam
Email: tat47@pitt.edu
Office: 4923 Wesley W. Posvar Hall
Course Meetings: MW 6pm–9:15pm
Room: 4716 Wesley W. Posvar Hall
Office Hours: TBA
Textbooks:
Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach, 5th Edition
Gareth Jones, Daniela Witten, Trevor Hastie, and Robert Tibshirani, Introduction to Statistical Learning
with Applications in R
Both texts are available from the bookstore. The Wooldridge text is on reserve at Hillman library, and
the Jones et al text is available for free online from the author’s website.
Prerequisites:
A “C” or better in the following courses: ECON (1100 or 1110) and MATH (0120 or 0220 or (0125 and
0126)) and STAT (0200 or 1000 or 1100 or 1152)
Course Outline:
Monday, June 23rd
Overview, review of probability theory
Wednesday, June 25th
Review of statistical theory, introduction to R
Monday, June 30th
Linear regression: Introduction, estimation
Wednesday, July 2nd
Linear regression: Inference, HW 1 due
Monday, July 7th
Linear regression: Model specification,
differences–in–differences
Wednesday, July 9th
Midterm exam
Monday, July 14th
Linear regression: Model specification continued, variable
selection, cross–validation, regression discontinuity
Linear regression: Heteroskedasticity, measurement error,
the bootstrap, HW 2 due
Monday, July 21st
Instrumental variables
Wednesday, July 23rd
Models for limited dependent variables, HW 3 due
Monday, July 28th
No class
Final exam
Evaluation Policy:
Evaluations will be based on two exams (a midterm and a final) as well as three homework assignments.
Each exam will be worth 35% of your grade, while each homework will be worth 10%. Homework will
be due within the first 10 minutes of class; if you cannot make it to class, you can turn in your
homework early to my departmental mailbox or email it to me. Late homeworks will not be accepted
unless accompanied by a doctor’s/Sheriff’s note indicating illness/incarceration. Likewise, make–up
exams will not be administered unless justified by a doctor’s/Sheriff’s note. Exceptions are not fair
to other students and will not be granted.
Exam Policy:
Exams will be monitored and any student caught cheating will fail the course; you may not use any
books, notes, or electronic devices during the exams.
Academic Integrity:
This class will adhere to the University of Pittsburgh’s Academic Integrity Policy. See the guidelines on
Academic Integrity, Student and Faculty Obligations, and Hearing Procedures at
http://www.provost.pitt.edu/info/ai1.html.
Students with Disabilities:
If you have a disability for which you are or may be requesting an accommodation, you are encouraged
to contact both me and Disability Resources and Services, 140 William Pitt Union, 412-648-7890, as
early as possible in the term.
Economics 1150: Applied Econometrics
Fall 2014
Prerequisites: [(ECON 1100; MIN GRADE: 'C') or (ECON 1110; MIN GRADE: 'C')]
and (MATH 0120 or 0220) and (STAT 0200 or 1000 or 1100 or 1152).
Lectures:
Instructor:
Tuesday-Thursday, 11:00-12:15 @ 239 Cathedral of Learning
Arie Beresteanu 4929 W.W. Posvar Hall (arie@pitt.edu)
Note: If you need a permission number to add this class, please contact the Economic
advisors at econadv@pitt.edu.
Office Hours:
Wednesday 11:00-12:30AM at my office.
I will occasionally post handouts and solutions on the course web page. Problem sets will
be posted as they are assigned, so check the website frequently.
Required text:
James Stock and Mark Watson (2011), “Introduction to Econometrics,” 3rd Edition,
Addison-Wesley, ISBN 0-13-800900-7.
Supplementary online material: http://wps.aw.com/aw_stock_ie_3/
Software:
We will use the program Stata for homework assignments. Stata is available in Pitt’s
computer labs (for more information see http://technology.pitt.edu/software/computinglabs-software.html). If you wish, you can purchase your own copy of Stata/IC 13 for
$98.00 online at http://www.stata.com/order/new/edu/gradplan.html
Most students do not purchase their own copy of Stata.
University Policies:
 We will adhere to the university’s Academic Integrity Policy in this class. See the
University of Pittsburgh’s Undergraduate Bulletin or the Guidelines on Academic
Integrity: Student and Faculty Obligations and Hearing Procedures at
www.pitt.edu/~provost/ai1.html for full details on this.
 The Office of Disability Resources and Services, 140 William Pitt Union (412)648-7890 is available for students who have or may request an accommodation
for a disability. If needed, please contact the office as early as possible in the
term.
Course Policies:
Grading:
Problem Sets
Midterm 1
Midterm 2
Final
10%
20%
30%
40%
Homework:
 There will be 8 or 9 problem sets which will be posted on the course website.
 Problem sets will not be graded. I will simply record whether you have turned
each one in. I will also drop one, so that if you turn in 7 of 8 (or 8 of 9), you will
receive full credit; if you turn in 4 out of 8 you will receive ½ credit, and so forth.
 I will not return the problem sets to you until the end of the term so that, if you are
on the border between grades, I can refer back to them to break ties. Please take
these assignments seriously.
 While solving the problem sets, you are allowed (in fact encouraged) to work in
groups, as long as each group is comprised of no more than three people and as
long as each member submits their own written answers.
 Problem sets should be turned in at the beginning of class on the day that they are
due. Late homework will not be accepted and there will be no extensions.
Exams:
 There will be no makeup midterms. If you miss a midterm for any reason, you
must fill in the “missed exam form” that can be found on the course webpage and
hand it to me within 7 days of the missed exam. Supporting documentation (if
exists) can be attached to your form. I am not asking you, however, to disclose
any personal information (e.g. medical records) if you wish not to do so. I’m
going to assume that students follow the university’s academic integrity
guidelines.
 The weight of a missed midterm exam will be reallocated to the final exam,
regardless of the respective means of the individual exams.
 The final exam is comprehensive, so you will be responsible for all the material
covered in this course. The time of the final is set and will not be moved under
any circumstances.
 Exams will be closed book, but you will not need to memorize a bunch of
formulas. For each exam, you will be given a set of formulas and notes prepared
by me. I will post a copy of this handout before each exam so you know what to
expect.
Grading:
 This course will be graded on a curve. From my past experience, the median (not
the mean) is a low B, although this could change if this class is particularly weak
or strong. For obvious reasons (i.e. grade lobbying), the exact final cutoff points
will not be disclosed under any circumstances (so don’t ask).

I take objectivity and consistency in grading very seriously. The course policies
outlined here apply to everyone: there will be no extra assignments, no reweighting of existing assignments, and no special consideration given to
individual students who “feel their grade does not reflect their understanding of
the material”.
Re-grading:
 I work very hard to make sure that exams are graded accurately and fairly, but
mistakes sometimes happen. If you think your exam should be re-graded, you
have to submit in writing the detailed reasons why you think this is the case
(unless your points have been added up incorrectly, in which case you can just
bring the exam to me for an immediate correction). Take into account that if you
ask for a re-grade, the entire exam will be checked again, meaning that you may
lose points (since mistakes can happen in both directions). In addition, arguments
for additional partial credit will not be considered: you must believe your answer
is entirely correct as written. You must submit requests for midterm re-grades
within one week of the day the exam was returned.
Course Outline
Note: The due dates for problem sets are tentative and will be subject to change. Refer to
the problem set handouts and the course webpage for the final due dates.
Tuesday August 26
Orientation meeting
Introduction, course description
Part 1: Statistics Review
Thursday August 28
Probability review: random variables; probability functions and distribution functions;
expected value and variance (Chapter 2)
Tuesday September 2
Probability review: relationships between two random variables: marginals, joint,
conditional; law of iterated expectations; Correlation and Independence. (Chapter 2)
Thursday September 4
Statistics review: some important probability distributions; iid; estimators and estimates;
sample mean (Chapter 2, 3)
Tuesday September 9
Statistics review: properties of estimators; bias, variance, Mean Squared Error,
consistency, Asymptotic Normality; the Central Limit Theorem (Chapter 2,3)
PS #1 due
Statistics review: Hypothesis tests and Confidence Intervals, p-values, difference between
means, t-distribution (Chapter 3)
Part 2: Basic Econometrics (Ordinary Least Squares)
Tuesday September 16
Conditional expectations. Ordinary Least Squares (OLS) with only one conditioning
variable. (Chapters 4 & 17)
PS #2 due
The OLS assumptions and properties of the estimators, sampling distribution (Chapters 4
& 17)
Tests and confidence intervals, Goodness of Fit & R-squared. (Chapters 4, 5, & 17)
Homoskedasticity vs Heteroskedasticity, Weighted Least Squares (Chapters 5 & 17)
Omitted variables, introduction to multivariate OLS. (Chapter 6)
PS #3 due
Thursday October 2
Catch up or Review
Tuesday October 7
First Midterm
Thursday October 9
Multivariate OLS, Assumptions and Properties. (Chapter 6)
FALL BREAK (October 14)
Thursday October 16
Imperfect multicollinearity, tests and confidence intervals for single coefficients,
goodness of fit and adjusted R-squared. (Chapters 6 & 7)
Tuesday October 21
Testing joint hypotheses (with and without homoskedasticity) (Chapter 7)
Thursday October 23
Extensions to OLS: nonlinearities, estimation of elasticities, dummy variables and
interactions. (Chapter 8)
PS #4 due
Tuesday October 28
Nonlinearities (continued). (Chapter 8)
Part 3: Advanced Econometrics (beyond OLS)
Thursday October 30
Regression with limited dependent variables; Linear probability model, logit and probit.
(Chapter 11)
PS #5 due
Tuesday November 4
Logit and probit; Maximum Likelihood Estimation (MLE) (Chapter 11)
Thursday November 6
MLE and limited dependent variables (Chapter 11)
PS #6 due
Tuesday November 11
Linear models and panel data. (Chapter 10)
Thursday November 13
Catch up or Review
PS #7 due
Tuesday November 18
Second Midterm
Endogenous regressors, simultaneity, and Instrumental Variables (Chapter 12)
Tuesday November 25
Two Stage Least Squares (2SLS) (Chapter 12)
THANKSGIVING BREAK (November 27)
Tuesday December 2
Strength and Exogeneity (Chapter 12)
Testing for Weak Instruments
The Test of Over-identifying Restrictions
2SLS in Stata
PS #8 due
Thursday December 4
Catch up or Review
Extra material if time permits I
Experiments and Quasi-Experiments (Chapter 13)
The Differences Estimator
Extra material if time permits II
The Differences-in-Differences Estimator (Chapter 13)
Heterogeneous Effects
Review
PS #9 due
The Final Exam will be on Wednesday, December 10th from 10:00 to 11:50 AM.
Fall 2014
and by appointment.
Location: LAWR-0104
Office: WWPH 4918-A
Course Information
Course Description:
Course Materials:
Textbook: "Introduction to Econometrics” 3rd ed. James Stock & Mark Watson
Course Policies
Attendance:
Office Hours:
unable to meet during office hours, contact me so that we may coordinate another time to
meet.
Use of Electronics:
your cell phone.
Email:
Course Grades
Your grade in the course will be a weighted average of problem set scores and two exams. The
particular weights are given by
Problem Set Average
Midterm
Final
40%
30%
30%
October 9
December 4
The exams will be based on material from the lectures and from the book. The exams will not
be comprehensive. Note that the exams make up 60% of your grade.
Notice that the final exam is not during finals week, but rather on the last day of class.
Periodically, I'll assign problem sets relevant to the course material. Each problem set will be
equally weighted with respect to your grade. As a whole, problem sets will make up 40% of
your grade.
Letter
A
AB+
B
BC+
C
CD+
D
DFailure
%
93-100
90-92
87-89
83-86
80-82
77-79
73-76
70-72
67-69
63-66
60-62
<60
Spring 2015
and by appointment.
Location: WWPH-4900
Office: WWPH 4918-A
Course Information
Course Description:
Course Materials:
Recommended Textbook: "Introduction to Econometrics” 3rd ed. Stock & Watson
Course Policies
Attendance:
Office Hours:
unable to meet during office hours, formulate your questions via email. As a last resort, contact
me so that we may coordinate another time to meet.
Use of Electronics:
your cell phone.
Email:
Course Grades
Your grade in the course will be a weighted average of problem set scores and two exams. The
particular weights are given by
Problem Set Average
Midterm
Final
40%
30%
30%
February 26
April 16
The exams will be based on material from the lectures and problem sets. The exams will not be
comprehensive. Note that the exams make up 60% of your grade.
Notice that the final exam is not during finals week, but rather on the last day of class.
equally weighted with respect to your grade. As a whole, problem sets will make up 40% of
your grade.
Letter
A
AB+
B
BC+
C
CD+
D
DFailure
%
93-100
90-92
87-89
83-86
80-82
77-79
73-76
70-72
67-69
63-66
60-62
<60
Economics 1150: Applied Econometrics
Fall 2015
Prerequisites: [(ECON 1100; MIN GRADE: 'C') or (ECON 1110; MIN GRADE: 'C')]
and (MATH 0120 or 0220) and (STAT 0200 or 1000 or 1100 or 1152).
Lectures:
Instructor:
Tuesday-Thursday, 13:00-14:15 @ 216 Cathedral of Learning
Arie Beresteanu 4929 W.W. Posvar Hall (arie@pitt.edu)
Note: If you need a permission number to add this class, please contact the Economic
advisors at econadv@pitt.edu.
Office Hours:
Wednesday 11:00-12:30AM (4929 Posvar Hall).
I will occasionally post handouts and solutions on the course web page. Problem sets will
be posted as they are assigned, so check the website frequently.
Required text:
James Stock and Mark Watson (2011), “Introduction to Econometrics,” 3rd Edition,
Addison-Wesley, ISBN 0-13-800900-7.
Supplementary online material: http://wps.aw.com/aw_stock_ie_3/
Software:
We will use the program Stata for homework assignments. Stata is available in Pitt’s
computer labs (for more information see http://technology.pitt.edu/software/computinglabs-software.html). If you wish, you can purchase your own copy of Stata/IC 13 for
$98.00 online at http://www.stata.com/order/new/edu/gradplan.html
Most students do not purchase their own copy of Stata.
University Policies:
 We will adhere to the university’s Academic Integrity Policy in this class. See the
University of Pittsburgh’s Undergraduate Bulletin or the Guidelines on Academic
Integrity: Student and Faculty Obligations and Hearing Procedures at
www.pitt.edu/~provost/ai1.html for full details on this.
 The Office of Disability Resources and Services, 140 William Pitt Union (412)648-7890 is available for students who have or may request an accommodation
for a disability. If needed, please contact the office as early as possible in the
term.
Course Policies:
Grading:
Problem Sets
Midterm 1
Midterm 2
Final
10%
20% (Oct 13th)
30% (Nov 24th)
40% (Dec 15th)
Homework:
 There will be 8 or 9 problem sets which will be posted on the course website.
 Problem sets will not be graded. I will simply record whether you have turned
each one in. I will also drop one, so that if you turn in 7 of 8 (of 8 of 9), you will
receive full credit; if you turn in 4 out of 8 you will receive ½ credit, and so forth.
 I will not return the problem sets to you until the end of the term so that, if you are
on the border between grades, I can refer back to them to break ties. Please take
these assignments seriously.
 While solving the problem sets, you are allowed (in fact encouraged) to work in
groups, as long as each group is comprised of no more than three people and as
long as each member submits their own written answers.
 Problem sets should be turned in at the beginning of class on the day that they are
due. Late homework will not be accepted and there will be no extensions.
Exams:
 There will be no makeup midterms. If you miss a midterm for any reason, you
must fill in the “missed exam form” that can be found on the course webpage and
hand it to me within 7 days of the missed exam. Supporting documentation (if
exists) can be attached to your form. I am not asking you, however, to disclose
any personal information (e.g. medical records) if you wish not to do so. I’m
going to assume that students follow the university’s academic integrity
guidelines.
 The weight of a missed midterm exam will be reallocated to the final exam,
regardless of the respective means of the individual exams.
 The final exam is comprehensive, so you will be responsible for all the material
covered in this course. The time of the final is set and will not be moved under
any circumstances.
 Exams will be closed book, but you will not need to memorize a bunch of
formulas. For each exam, you will be given a set of formulas and notes prepared
by me. I will post a copy of this handout before each exam so you know what to
expect.
Grading:
 This course will be graded on a curve. From my past experience, the median (not
the mean) is a low B, although this could change if this class is particularly weak
or strong. For obvious reasons (i.e. grade lobbying), the exact final cutoff points
will not be disclosed under any circumstances (so don’t ask).

I take objectivity and consistency in grading very seriously. The course policies
outlined here apply to everyone: there will be no extra assignments, no reweighting of existing assignments, and no special consideration given to
individual students who “feel their grade does not reflect their understanding of
the material”.
Re-grading:
 I work very hard to make sure that exams are graded accurately and fairly, but
mistakes sometimes happen. If you think your exam should be re-graded, you
have to submit in writing the detailed reasons why you think this is the case
(unless your points have been added up incorrectly, in which case you can just
bring the exam to me for an immediate correction). Take into account that if you
ask for a re-grade, the entire exam will be checked again, meaning that you may
lose points (since mistakes can happen in both directions). In addition, arguments
for additional partial credit will not be considered: you must believe your answer
is entirely correct as written. You must submit requests for midterm re-grades
within one week of the day the exam was returned.
Course Outline
Note: The due dates for problem sets are tentative and will be subject to change. Refer to
the problem set handouts and the course webpage for the final due dates.
Tuesday September 1
Orientation meeting
Introduction, course description
Part 1: Statistics Review
Probability review: random variables; probability functions and distribution functions;
expected value and variance (Chapter 2)
Tuesday September 8
Probability review: relationships between two random variables: marginals, joint,
conditional; law of iterated expectations; Correlation and Independence. (Chapter 2)
Statistics review: some important probability distributions; iid; estimators and estimates;
sample mean (Chapter 2, 3)
Statistics review: properties of estimators; bias, variance, Mean Squared Error,
consistency, Asymptotic Normality; the Central Limit Theorem (Chapter 2,3)
PS #1 due
Statistics review: Hypothesis tests and Confidence Intervals, p-values, difference between
means, t-distribution (Chapter 3)
Part 2: Basic Econometrics (Ordinary Least Squares)
Conditional expectations. Ordinary Least Squares (OLS) with only one conditioning
variable. (Chapters 4 & 17)
PS #2 due
The OLS assumptions and properties of the estimators, sampling distribution (Chapters 4
& 17)
Tests and confidence intervals, Goodness of Fit & R-squared. (Chapters 4, 5, & 17)
Thursday October 1
Homoskedasticity vs Heteroskedasticity, Weighted Least Squares (Chapters 5 & 17)
Tuesday October 6
Omitted variables, introduction to multivariate OLS. (Chapter 6)
PS #3 due
Thursday October 8
Catch up or Review
Tuesday October 13
First Midterm
Thursday October 15
Multivariate OLS, Assumptions and Properties. (Chapter 6)
FALL BREAK (October 20)
Thursday October 22
Imperfect multicollinearity, tests and confidence intervals for single coefficients,
goodness of fit and adjusted R-squared. (Chapters 6 & 7)
Tuesday October 27
Testing joint hypotheses (with and without homoskedasticity) (Chapter 7)
Thursday October 29
Extensions to OLS: nonlinearities, estimation of elasticities, dummy variables and
interactions. (Chapter 8)
PS #4 due
Tuesday November 3
Nonlinearities (continued). (Chapter 8)
Part 3: Advanced Econometrics (beyond OLS)
Thursday November 5
Regression with limited dependent variables; Linear probability model, logit and probit.
(Chapter 11)
PS #5 due
Tuesday November 10
Logit and probit; Maximum Likelihood Estimation (MLE) (Chapter 11)
MLE and limited dependent variables (Chapter 11)
PS #6 due
Tuesday November 17
Linear models and panel data. (Chapter 10)
Catch up or Review
PS #7 due
Tuesday November 24
Second Midterm
THANKSGIVING BREAK (November 26)
Thursday December 1
Endogenous regressors, simultaneity, and Instrumental Variables (Chapter 12)
Tuesday December 3
Two Stage Least Squares (2SLS) (Chapter 12)
Tuesday December 8
Strength and Exogeneity (Chapter 12)
Testing for Weak Instruments
The Test of Over-identifying Restrictions
2SLS in Stata
PS #8 due
Thursday December 10
Catch up or Review
Extra material if time permits I
Experiments and Quasi-Experiments (Chapter 13)
The Differences Estimator
Extra material if time permits II
The Differences-in-Differences Estimator (Chapter 13)
Heterogeneous Effects
Review
PS #9 due
The Final Exam will be on Wednesday, December 15th from 16:00 to 17:50.
Fall 2015
Email: pjn5@pitt.edu
Office Hours: T/Th 1:00-2:15, W 2:00-2:50
and by appointment.
Location: WWPH-4900
Office: WWPH 4918-A
Course Information
Course Description:
Course Materials:
Required Textbook: "Introductory Econometrics” 5th ed. Jeffrey M. Wooldridge
Recommended Reading: “Mastering Metrics: The Path from Cause to Effect” Angrist &
Pischke
Course Policies
Attendance:
Office Hours:
http://www.provost.pitt.edu/info/ai1.html. This may include, but is not limited to the
confiscation of the examination of any individual suspected of violating the University Policy.
Use of Electronics:
your cell phone.
Email:
(DRS), 216 William Pitt Union, 412-648-7980 as early as possible in the term. DRS will verify
your disability and determine reasonable accommodations for this course.
Course Grades
Your grade in the course will be a weighted average of problem set scores and three exams.
The particular weights are given by
Problem Set Average
Exam I
Exam II
Exam III
25%
25%
25%
25%
Thursday, Oct. 1
Thursday, Nov. 5
Thursday, Dec. 10
The exams will be based on material from the lectures and problem sets. The exams will NOT
be comprehensive.
equally weighted with respect to your grade.
Letter
A
AB+
B
BC+
C
CD+
D
DFailure
%
93-100
90-92
87-89
83-86
80-82
77-79
73-76
70-72
67-69
63-66
60-62
<60
ECON 1150 - Applied Econometrics I
Department of Economics, University of Pittsburgh
Syllabus - Spring 2016
Instructor: Federico Zincenko, Ph.D.
Lectures: Mondays and Wednesdays, 3:00pm - 4:15pm
358 Cathedral of Learning
Office Hours: Tuesdays 4:00pm - 5:00pm, Wednesdays 11:00am - 12:00pm
4713 Posvar Hall
e-mail: zincenko@pitt.edu
Reader: Marli Wang Dunietz
e-mail: mcw45@pitt.edu
Course Description
The goal of this course it to introduce basic tools in applied econometrics that are
commonly employed in government, business, and academic research. Such tools are
useful for those intending to become quantitative business and economic analysts, and
also, for those interested in knowing how economics is applied to real-world problems.
The primary topic of the course is the linear regression model, which allows us
to quantify the effect of changing one variable on another one. The course focuses
on interpretation and estimation of parameters, as well as, hypothesis testing. These
issues will be studied following an applied perspective. For this purpose, we can find
many interesting questions such as: does reducing class size improve elementary school
education? Is there racial discrimination in the credit market? More generally, we
study how to relate economic theory and real-world data.
We will employ the statistical package Stata, a computer software widely used in
quantitative economic research. The background knowledge needed for this course is
college algebra, basic probability, and elementary statistics.
1
References
Main Reference
The course will be mainly based on my slides, which must be complemented with the
following textbook:
J. M. Wooldridge (2012). Introductory Econometrics: A Modern Approach. 5th
edition. South-Western.
Supplementary Bibliography
R. C. Hill, W. E. Griffiths, and G. C. Lim (2011). Principles of Econometrics.
4th edition. Wiley.
J. H. Stock and M. W. Watson (2011). Introduction to Econometrics. 3rd edition.
Addison-Wesley.
E. A. Tanis and R. V. Hogg (2008). A Brief Course in Mathematical Statistics.
Pearson Prentice Hall.
Requirements and Grading Policy
The final grade will be based on six problem sets, two midterms, and a final exam.
The weights are as follows.
Problem Sets (20%): Six problem sets, each weights 3.33%. They involve using
Stata, which will be taught during lectures. Students are allowed to submit their
answers alone or in pairs. Problem sets will be due in hardcopy at the beginning
of the class on the specified date.
Midterms (40%): Two midterms, both are in-class. Highest grade midterm
weights 25%, the other 15%. The dates are February 2 and April 11 (both
are Mondays).
Final (40%): It is cumulative and will take place on Saturday, April 30, from
4:00pm to 5:50pm. The room will be announced later.
All exams are closed-book and no calculators or any electronic devices are allowed.
The only valid reason for missing an exam (or a homework) is serious illness to be
verified in writing by a medical doctor. If you cannot make one midterm due to a
2
serious illness, the final weights 60% (instead of 40%) and midterm you take 20%. If
you know that you cannot make the final exam on the specified date, you cannot take
this course.
Course materials – such as slides, problem sets, and grades– will uploaded to the
Blackboard: https://courseweb.pitt.edu/webapps/login. In the Syllabus section of this
website, you can find statements regarding academic policies: academic integrity, disability services, accessibility, copyright notice, and statement on classroom recording.
Students must be aware of all these statements. Among others, to ensure the free
and open discussion of ideas, students cannot record classroom lectures. Academic
dishonesty will be handled according to the university regulations with no exceptions.
Disability Resources
If you have a disability for which you are or may be requesting an accommodation,
you are encouraged to contact both your instructor and the Office of Disability Resources and Services, 216 William Pitt Union, (412)648-7890/(412)383-7355, as early
as possible in the term. Disability Resources and Services will verify your disability
and determine reasonable accommodations for this course.
Course Outline
1. Introduction to the course. Definition of Econometrics. Review of probability
and statistics.
References: Wooldridge (2012, ch. 1 & apps. A-C); Stock and Watson (2011, chs. 1-3);
Tanis and Hogg (2008)
2. The simple regression model. The OLS estimator.
Refs: Wooldridge (2012, ch. 2)
3. Multiple regression analysis: estimation.
4. Multiple regression analysis: inference.
5. Multiple regression analysis: OLS asymptotics.
3
6. Multiple regression analysis: further issues and assessment.
Refs: Wooldridge (2012, ch. 6); Stock and Watson (2011, ch. 9)
7. Multiple regression analysis with qualitative variables. Probit and logit.
Refs: Wooldridge (2012, ch. 7 & sec. 1 in ch. 17); Hill, Griffiths, and Lim (2011, secs.
1-2 in ch. 16); Stock and Watson (2011, ch. 11)
8. Heteroskedasticity. generalized least squares.
Refs: Wooldridge (2012, ch. 8); Hill, Griffiths, and Lim (2011, ch. 8)
4
Spring 2016
Email: pjn5@pitt.edu
Office Hours: M/W 12:00-1:50
and by appointment.
Location: WWPH-4900
Office: WWPH 4918-A
Course Information
Course Description:
Course Materials:
Required Textbook: "Introductory Econometrics” 5th ed. Jeffrey M. Wooldridge
Recommended Reading: “Mastering Metrics: The Path from Cause to Effect” Angrist &
Pischke
Course Policies
Attendance:
Office Hours:
http://www.provost.pitt.edu/info/ai1.html. This may include, but is not limited to the
confiscation of the examination of any individual suspected of violating the University Policy.
Use of Electronics:
your cell phone.
Email:
(DRS), 216 William Pitt Union, 412-648-7980 as early as possible in the term. DRS will verify
your disability and determine reasonable accommodations for this course.
Course Grades
Your grade in the course will be a weighted average of problem set scores and three exams.
The particular weights are given by
Problem Set Average
Exam I
Exam II
Exam III
25%
25%
25%
25%
Thursday, Feb. 4
Thursday, Mar. 17
Thursday, Apr. 21
The exams will be based on material from the lectures and problem sets. The exams will NOT
be comprehensive.
equally weighted with respect to your grade.
Letter
A
AB+
B
BC+
C
CD+
D
DFailure
%
93-100
90-92
87-89
83-86
80-82
77-79
73-76
70-72
67-69
63-66
60-62
<60

Econ 1150 Applied Econometrics 1

Transcription

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