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120C-econ120c代写
时间：2023-08-14
Econ 120C: Econometrics
Professor Yixiao Sun
Department of Economics,
University of California, San Diego
Summer 2023
1. Teaching Team
Instructor: Professor Yixiao Sun, yisun@ucsd.edu, Ph.D., Yale, 2002.
Teaching Assistants:
Chen (James) Lin, chl029@ucsd.edu
Jin Xi, x5jin@ucsd.edu
2. Organization
Delivery and class time
Lectures and discussion sessions will be delivered remotely via Zoom.
Please log onto canvas.ucsd.edu to get Zoom links (under Zoom) for all teach-
ing activities.
Videos for lectures and discussion sessions will be posted as soon as they become
available. They can be found on Canvas under Media Gallery.
Lecture time: TTH 2:00p-4:50p or MW 2:00p-4:50p
Discussion session time: W 11:00a-12:50p or TH 2:00p-3:50p
O¢ ce hours
We will hold our o¢ ce hours via Zoom. Zoom links will be posted on Canvas (under
Zoom)
Professor Yixiao Suns o¢ ce hours: 5:30 pm 6:30 pm on Wednesday and Thurs-
day.
TAso¢ ce hours will be posted on Canvas.
Communications
1. You are encouraged to post your questions to Piazza, which is linked to Can-
vas. We will check Piazza regularly and answer your questions there. Please
use Piazza rather than emailing us as much as possible. You can post
1
a private message that only you and the teaching team can view and
reply. Most of the questions should not be set private, but you can
post a question anonymously.
2. We are also available for questions during our o¢ ce hours.
3. As your instructor and teaching assistant, we do not have any control over
enrollment, waiting list, and any other administrative issues. These matters
are handled by the departments undergraduate advising o¢ ce or O¢ ce of the
Registar.
3. Course Description
This course covers contemporary causal inference methods in observational studies.
In a complex system, economic and beyond, causal inference aims at determining
the causes and e¤ects of the actions being studied for example, the e¤ect of in-
creasing the minimum wage on employment, the impact of increasing the education
level on earnings, the e¤ect of more (or less) aggressive police responses on reducing
domestic violence, and the inuence of introducing higher property-right protection
on economic growth. The course introduces students to the concepts and methods
that are commonly used by economists and other practitioners to identify and es-
timate the causal e¤ects of an action or policy. The main topics are correlation
vs causality, panel data methods, instrumental variable regression, experiments and
quasi-experiment, di¤erence-in-di¤erences, and regression discontinuity. The course
will enable students to provide insightful and enlightening answers to many interest-
ing questions of causation. It will also equip students with the knowledge to estimate
the fundamental relationships in economics such as the demand and supply. The
course is particularly recommended for students who plan to pursue a quantitative
career in business analytics, policy evaluation, etc.
Throughout, we will focus on both understanding and doing. The understanding
part will come from lectures and discussion sessions. The doing part will come from
problem-solving and extensive statistical software use. This course requires serious
commitment. Econometrics is best learned by doing, and you will be asked to do a
fair amount of hands-on work.
Prerequisites
ECON120C is the continuation of ECON120B, building upon the foundational con-
cepts of the linear regression model. To ensure a successful understanding of the
course material, it is essential that you possess a comprehensive grasp of the topics
covered in ECON120B. While MATH 181B can serve as a substitute for Econ 120B to
meet the prerequisite requirement, it is recommended that you have taken Econ120B
recently. In addition to the prerequisite knowledge, a solid background in basic sta-
tistics and probability is expected. Working knowledge of calculus will also prove
bene cial. As ECON120C involves practical applications of statistical analysis, it is
2
essential that you have some experience with Stata, as this software will be utilized
throughout the course.
Textbook
The required textbook for this class is Introduction to Econometrics, by James
Stock and Mark Watson. The book will be available as an eBook through Canvas.
The eBook is provided by the UC San Diego Bookstore through Canvas and is
free for the rst two weeks of classes. After two weeks, your student account will
be charged a special reduced price unless you opt out. If you decide to opt out, you
must complete the process before a deadline and you will be responsible for sourcing
the materials elsewhere.
Note that the lectures will cover many additional materials not found in the
textbook. Reading the book only will not be enough for this course.
Econometrics Video Handbook
The course will follow the Econometrics Video Handbook (EVH) fairly closely. The
EVH is available through Canvas. For some topics, you may be asked to watch videos
in the EVH. I will post on Canvas which video(s) to watch. The EVH is the product
of the departments most recent e¤ort in modernizing econometric training at UCSD.
Main Topics (subject to change)
Part I. Review of Econ120A/120B.
Part II. Causality and Causal Models; Threat to the validity of OLS for causal
inference
Part III. Panel Data Models
Part IV. IV and 2SLS
Part V. Experiments and Quasi-experiments: DID
4. Software
In this course, you will be required to utilize the statistical software package Stata for
solving certain assignment problems. Access to download and license information for
Stata is available on Canvas. However, please remember that the license information
should not be shared or distributed outside of UCSD.
Strict adherence to this policy is of the utmost importance since sharing the
Stata license information could have severe legal consequences and potentially put
our privilege to use the software at risk. The acquisition of a site license for Stata
required substantial e¤ort and communication among the economics department, the
university administration, and the Stata company.
3
5. Assessment
Assignments (10%)
There will be four assignments, each of which will carry a weight of 2.5% toward
the nal class grade. For each assignment, (a random) half of the questions will be
graded based on completeness, and the other half will be graded based on correctness.
Completeness grading will use three scales. A score of 50% will be given to a question
that is clearly incomplete, but has made a start towards answering some part of the
question. A score of 75% will be given to a question that is largely complete, but
does not answer every part in full. A score of 100% will be given to a question that
is clearly well-done, and answers all parts of the question.
If you have any question on the problem sets, please ask us during our o¢ ce
hours. Our o¢ ce hours are for you. You are also encouraged to post your questions
on Piazza.
Answers to assignments are to be submitted via Canvas. You can scan your answer
into a pdf using a free app on your smartphone. DO NOT email any assignment
(we will ignore the assignment sent to our email accounts).
Assignments are due at 11:59 pm on the rst four Sundays of SSII. The lowest
assignment score will be dropped. If you are happy with the rst three scores, you do
not need to submit the last assignment. The average of the highest three scores will be
counted toward your nal grade. The tradeo¤ for this bene t is that we will be strict
about not accepting late assignments. Please DO not request an extension for
ANY reason. Such a request will be ignored automatically. Requesting
for an exception is not fair to other students and imposes extra burdens
on the teaching team.
For each assignment, a solution will be posted on Canvas after its due date. The
solution will be posted together with the assignment. Some assignment problems
will appear in the exams.
Midterm Exam (35%) and Final Exam (55%)
There will be one midterm exam and one nal exam. The nal exam will be cumu-
lative.
Midterm Exam Time: August 25, 2023; 6:00-8:00pm
Final Exam Time: September 8, 2023; 3:00pm-5:59pm
Both exams will be delivered via Canvas. Please make sure you have a good
and stable internet connection.
Both exams will be closed-book. No calculator is needed or allowed. You
are not supposed to get assistance from others or post your question on the
Internet during an exam. You are not allowed to use any search engine or
online translator. You can have ONE page (double-sided, no larger than 8.5in
by 11in) of note. It must be hand-written (on paper or using a digital device);
photo reducing and pasting are not permitted. The one-page policy applies to
both the midterm exam and the nal exam.
4
There will be no make-up exam. If you miss the midterm for a veri able medical
reason, I will use your nal exam score for the missing midterm. Failure to notify
me promptly that you must miss the midterm will result in a zero grade. I will
not excuse any other absences, as the exam time is given well in advance. Please
do not request an exception. Such a request will be ignored automatically.
Unexcused absences will result in a zero.
There will be no alternative exam time for either the midterm exam or
the nal exam. Please do not request a di¤erent exam time for any personal
reason (e.g., a ceremony of any type, organization activity of any type, family
reunion, ...) unless it is related to an unexpected health issue. In such a case, a
doctors certi cate is required. Please make sure that the doctors name, phone
number, and email address are legible. We may contact the doctor to con rm
the health issue.
We will use Zoom to proctor the exams live. You are required to show your
student ID to your camera at the beginning of the exam.
Attendance
Class attendance will be recorded automatically by Zoom. Each attendance will add
1/3 points to your weighted score.
Your letter grade will not be a¤ected in any way by the attendance credits that
your classmates will get. There is no penalty for not attending classes, but there is a
reward for doing so!
Please do not request an attendance credit for any reason you miss a leture. It
takes too much of my time to handle these requests. Attendance check is supposed
to be automated without my further intervention. Here are some of the reasons that
I will not consider:
I was late for the class (you will still get the partial credit)
I left the class earlier (you will still get the partial credit)
I was sick on that day
I had a schedule conict
Grading
All three parts (the assignments, the midterm exam, and the nal exam) are needed
to pass the class. If there is a zero in any of the three parts, you will get an F.For
example, if you turn in none of the assignments, you will receive an Fregardless
of your exam scores.
Conditional on a non-zero score on each of the three parts, the course grade will
be assigned as follows.
5
First, the weighted average of numerical scores will be obtained. Suppose your
scores on the assignment are 100, 100, 100, and 75. Your midterm and nal exam
scores are 80 and 85, respectively. Then the weighted average is
100 2:5% + 100 2:5% + 100 2:5% + 100 2:5%
+80 35% + 85 55%
= 84:75
The weights on the assignments, the midterm, and the nal exam cannot be changed.
Second, if the class median of the weighted average is below 70 points, points
will be added to all scores to bring the median score up to 70 points. Third, if the
class median of the weighted average is above 75 points, points will be subtracted
from all scores to bring the median score down to 75 points. The possible adjustment
is based on the weighted score only. No adjustment will be made for either
the midterm or the nal exam, that is, there is no curve for either exam.
Depending on the class performance, there may be an adjustment.
Finally, letter grades will be assigned using the following scale:
95 A+ [80,85) B+ [65, 70) C+ [45, 50) D
[90,95) A [75,80) B [60, 65) C < 45 F
[85,90) A- [70,75) B- [50,60) C-
Note that the scale is exact. For example, if your score is 89:4; which will be
rounded up to 90, you will get an A; If your score is 88:90, which will be rounded up
to 89, you will get an A-. Please do not email me for a grade change because you are
only 0.1 away from the next grade.
Note: We will follow the above grading criteria as much as possible
but the instructor may have to make a change upon a request from the
department, the university, or for other unforeseeable reasons.
When considering a re-grading request for either the midterm or nal exam, please
note that only obvious grading errors will be eligible for review. No adjustments will
be made for partial credits. If you decide to request a re-grading, please be aware
that the entire exam may be subject to reassessment. This means that the regrading
process will involve a comprehensive review of the entire exam, not just speci c
portions. We take the process of regrading seriously and strive to ensure fairness and
accuracy in evaluating studentsperformance. Therefore, it is crucial to submit a
regrading request only when there is a clear and evident grading error to maintain
the integrity of the evaluation process.
During the entire summer session, we are available to assist with any questions.
However, there will be no opportunities for extra credits once the nal exam has con-
cluded. Instead, we encourage you to proactively address any concerns or questions
you may have before the nal exam. Our goal is to support your academic success,
and early communication and proactive e¤orts can greatly contribute to achieving
that success.
6
5. Discussion Sessions
A common complaint is that the class lacks problem-solving sessions. Please note
that each discussion session serves as a valuable problem-solving opportunity. During
these sessions, the Teaching Assistant (TA) will engage you in various problem-solving
exercises, including tackling variations of upcoming assignments before their due
dates. Additionally, the TA may work through problems from past exams and other
practice materials they have prepared.
Although the discussion sessions wont introduce new course material, they play
a crucial role in teaching you how to apply and utilize what you learned from lectures
to solve problems. It is essential to attend discussion sessions for this class.
6. Other Policies
If you have a documented disability, please email me your documentation as soon
as possible so that I can make suitable accommodations for you. If you believe that
you have a disability and need some special accommodations, please register with the
O¢ ce for Students with Disabilities.
Students who violate UCSDs academic integrity policy will earn a failing grade
for the course. In addition, the Council of Deans of Student A¤airs will impose a
disciplinary penalty.
I am a rst-generation faculty. I will be more than happy to share my rst-gen
experiences and journey during o¢ ce hours. I want to foster an inclusive classroom
environment. I encourage you to interrupt me with questions during each lecture.
Professor Yixiao Sun
Department of Economics,
University of California, San Diego
Summer 2023
1. Teaching Team
Instructor: Professor Yixiao Sun, yisun@ucsd.edu, Ph.D., Yale, 2002.
Teaching Assistants:
Chen (James) Lin, chl029@ucsd.edu
Jin Xi, x5jin@ucsd.edu
2. Organization
Delivery and class time
Lectures and discussion sessions will be delivered remotely via Zoom.
Please log onto canvas.ucsd.edu to get Zoom links (under Zoom) for all teach-
ing activities.
Videos for lectures and discussion sessions will be posted as soon as they become
available. They can be found on Canvas under Media Gallery.
Lecture time: TTH 2:00p-4:50p or MW 2:00p-4:50p
Discussion session time: W 11:00a-12:50p or TH 2:00p-3:50p
O¢ ce hours
We will hold our o¢ ce hours via Zoom. Zoom links will be posted on Canvas (under
Zoom)
Professor Yixiao Suns o¢ ce hours: 5:30 pm 6:30 pm on Wednesday and Thurs-
day.
TAso¢ ce hours will be posted on Canvas.
Communications
1. You are encouraged to post your questions to Piazza, which is linked to Can-
vas. We will check Piazza regularly and answer your questions there. Please
use Piazza rather than emailing us as much as possible. You can post
1
a private message that only you and the teaching team can view and
reply. Most of the questions should not be set private, but you can
post a question anonymously.
2. We are also available for questions during our o¢ ce hours.
3. As your instructor and teaching assistant, we do not have any control over
enrollment, waiting list, and any other administrative issues. These matters
are handled by the departments undergraduate advising o¢ ce or O¢ ce of the
Registar.
3. Course Description
This course covers contemporary causal inference methods in observational studies.
In a complex system, economic and beyond, causal inference aims at determining
the causes and e¤ects of the actions being studied for example, the e¤ect of in-
creasing the minimum wage on employment, the impact of increasing the education
level on earnings, the e¤ect of more (or less) aggressive police responses on reducing
domestic violence, and the inuence of introducing higher property-right protection
on economic growth. The course introduces students to the concepts and methods
that are commonly used by economists and other practitioners to identify and es-
timate the causal e¤ects of an action or policy. The main topics are correlation
vs causality, panel data methods, instrumental variable regression, experiments and
quasi-experiment, di¤erence-in-di¤erences, and regression discontinuity. The course
will enable students to provide insightful and enlightening answers to many interest-
ing questions of causation. It will also equip students with the knowledge to estimate
the fundamental relationships in economics such as the demand and supply. The
course is particularly recommended for students who plan to pursue a quantitative
career in business analytics, policy evaluation, etc.
Throughout, we will focus on both understanding and doing. The understanding
part will come from lectures and discussion sessions. The doing part will come from
problem-solving and extensive statistical software use. This course requires serious
commitment. Econometrics is best learned by doing, and you will be asked to do a
fair amount of hands-on work.
Prerequisites
ECON120C is the continuation of ECON120B, building upon the foundational con-
cepts of the linear regression model. To ensure a successful understanding of the
course material, it is essential that you possess a comprehensive grasp of the topics
covered in ECON120B. While MATH 181B can serve as a substitute for Econ 120B to
meet the prerequisite requirement, it is recommended that you have taken Econ120B
recently. In addition to the prerequisite knowledge, a solid background in basic sta-
tistics and probability is expected. Working knowledge of calculus will also prove
bene cial. As ECON120C involves practical applications of statistical analysis, it is
2
essential that you have some experience with Stata, as this software will be utilized
throughout the course.
Textbook
The required textbook for this class is Introduction to Econometrics, by James
Stock and Mark Watson. The book will be available as an eBook through Canvas.
The eBook is provided by the UC San Diego Bookstore through Canvas and is
free for the rst two weeks of classes. After two weeks, your student account will
be charged a special reduced price unless you opt out. If you decide to opt out, you
must complete the process before a deadline and you will be responsible for sourcing
the materials elsewhere.
Note that the lectures will cover many additional materials not found in the
textbook. Reading the book only will not be enough for this course.
Econometrics Video Handbook
The course will follow the Econometrics Video Handbook (EVH) fairly closely. The
EVH is available through Canvas. For some topics, you may be asked to watch videos
in the EVH. I will post on Canvas which video(s) to watch. The EVH is the product
of the departments most recent e¤ort in modernizing econometric training at UCSD.
Main Topics (subject to change)
Part I. Review of Econ120A/120B.
Part II. Causality and Causal Models; Threat to the validity of OLS for causal
inference
Part III. Panel Data Models
Part IV. IV and 2SLS
Part V. Experiments and Quasi-experiments: DID
4. Software
In this course, you will be required to utilize the statistical software package Stata for
solving certain assignment problems. Access to download and license information for
Stata is available on Canvas. However, please remember that the license information
should not be shared or distributed outside of UCSD.
Strict adherence to this policy is of the utmost importance since sharing the
Stata license information could have severe legal consequences and potentially put
our privilege to use the software at risk. The acquisition of a site license for Stata
required substantial e¤ort and communication among the economics department, the
university administration, and the Stata company.
3
5. Assessment
Assignments (10%)
There will be four assignments, each of which will carry a weight of 2.5% toward
the nal class grade. For each assignment, (a random) half of the questions will be
graded based on completeness, and the other half will be graded based on correctness.
Completeness grading will use three scales. A score of 50% will be given to a question
that is clearly incomplete, but has made a start towards answering some part of the
question. A score of 75% will be given to a question that is largely complete, but
does not answer every part in full. A score of 100% will be given to a question that
is clearly well-done, and answers all parts of the question.
If you have any question on the problem sets, please ask us during our o¢ ce
hours. Our o¢ ce hours are for you. You are also encouraged to post your questions
on Piazza.
Answers to assignments are to be submitted via Canvas. You can scan your answer
into a pdf using a free app on your smartphone. DO NOT email any assignment
(we will ignore the assignment sent to our email accounts).
Assignments are due at 11:59 pm on the rst four Sundays of SSII. The lowest
assignment score will be dropped. If you are happy with the rst three scores, you do
not need to submit the last assignment. The average of the highest three scores will be
counted toward your nal grade. The tradeo¤ for this bene t is that we will be strict
about not accepting late assignments. Please DO not request an extension for
ANY reason. Such a request will be ignored automatically. Requesting
for an exception is not fair to other students and imposes extra burdens
on the teaching team.
For each assignment, a solution will be posted on Canvas after its due date. The
solution will be posted together with the assignment. Some assignment problems
will appear in the exams.
Midterm Exam (35%) and Final Exam (55%)
There will be one midterm exam and one nal exam. The nal exam will be cumu-
lative.
Midterm Exam Time: August 25, 2023; 6:00-8:00pm
Final Exam Time: September 8, 2023; 3:00pm-5:59pm
Both exams will be delivered via Canvas. Please make sure you have a good
and stable internet connection.
Both exams will be closed-book. No calculator is needed or allowed. You
are not supposed to get assistance from others or post your question on the
Internet during an exam. You are not allowed to use any search engine or
online translator. You can have ONE page (double-sided, no larger than 8.5in
by 11in) of note. It must be hand-written (on paper or using a digital device);
photo reducing and pasting are not permitted. The one-page policy applies to
both the midterm exam and the nal exam.
4
There will be no make-up exam. If you miss the midterm for a veri able medical
reason, I will use your nal exam score for the missing midterm. Failure to notify
me promptly that you must miss the midterm will result in a zero grade. I will
not excuse any other absences, as the exam time is given well in advance. Please
do not request an exception. Such a request will be ignored automatically.
Unexcused absences will result in a zero.
There will be no alternative exam time for either the midterm exam or
the nal exam. Please do not request a di¤erent exam time for any personal
reason (e.g., a ceremony of any type, organization activity of any type, family
reunion, ...) unless it is related to an unexpected health issue. In such a case, a
doctors certi cate is required. Please make sure that the doctors name, phone
number, and email address are legible. We may contact the doctor to con rm
the health issue.
We will use Zoom to proctor the exams live. You are required to show your
student ID to your camera at the beginning of the exam.
Attendance
Class attendance will be recorded automatically by Zoom. Each attendance will add
1/3 points to your weighted score.
Your letter grade will not be a¤ected in any way by the attendance credits that
your classmates will get. There is no penalty for not attending classes, but there is a
reward for doing so!
Please do not request an attendance credit for any reason you miss a leture. It
takes too much of my time to handle these requests. Attendance check is supposed
to be automated without my further intervention. Here are some of the reasons that
I will not consider:
I was late for the class (you will still get the partial credit)
I left the class earlier (you will still get the partial credit)
I was sick on that day
I had a schedule conict
Grading
All three parts (the assignments, the midterm exam, and the nal exam) are needed
to pass the class. If there is a zero in any of the three parts, you will get an F.For
example, if you turn in none of the assignments, you will receive an Fregardless
of your exam scores.
Conditional on a non-zero score on each of the three parts, the course grade will
be assigned as follows.
5
First, the weighted average of numerical scores will be obtained. Suppose your
scores on the assignment are 100, 100, 100, and 75. Your midterm and nal exam
scores are 80 and 85, respectively. Then the weighted average is
100 2:5% + 100 2:5% + 100 2:5% + 100 2:5%
+80 35% + 85 55%
= 84:75
The weights on the assignments, the midterm, and the nal exam cannot be changed.
Second, if the class median of the weighted average is below 70 points, points
will be added to all scores to bring the median score up to 70 points. Third, if the
class median of the weighted average is above 75 points, points will be subtracted
from all scores to bring the median score down to 75 points. The possible adjustment
is based on the weighted score only. No adjustment will be made for either
the midterm or the nal exam, that is, there is no curve for either exam.
Depending on the class performance, there may be an adjustment.
Finally, letter grades will be assigned using the following scale:
95 A+ [80,85) B+ [65, 70) C+ [45, 50) D
[90,95) A [75,80) B [60, 65) C < 45 F
[85,90) A- [70,75) B- [50,60) C-
Note that the scale is exact. For example, if your score is 89:4; which will be
rounded up to 90, you will get an A; If your score is 88:90, which will be rounded up
to 89, you will get an A-. Please do not email me for a grade change because you are
only 0.1 away from the next grade.
Note: We will follow the above grading criteria as much as possible
but the instructor may have to make a change upon a request from the
department, the university, or for other unforeseeable reasons.
When considering a re-grading request for either the midterm or nal exam, please
note that only obvious grading errors will be eligible for review. No adjustments will
be made for partial credits. If you decide to request a re-grading, please be aware
that the entire exam may be subject to reassessment. This means that the regrading
process will involve a comprehensive review of the entire exam, not just speci c
portions. We take the process of regrading seriously and strive to ensure fairness and
accuracy in evaluating studentsperformance. Therefore, it is crucial to submit a
regrading request only when there is a clear and evident grading error to maintain
the integrity of the evaluation process.
During the entire summer session, we are available to assist with any questions.
However, there will be no opportunities for extra credits once the nal exam has con-
cluded. Instead, we encourage you to proactively address any concerns or questions
you may have before the nal exam. Our goal is to support your academic success,
and early communication and proactive e¤orts can greatly contribute to achieving
that success.
6
5. Discussion Sessions
A common complaint is that the class lacks problem-solving sessions. Please note
that each discussion session serves as a valuable problem-solving opportunity. During
these sessions, the Teaching Assistant (TA) will engage you in various problem-solving
exercises, including tackling variations of upcoming assignments before their due
dates. Additionally, the TA may work through problems from past exams and other
practice materials they have prepared.
Although the discussion sessions wont introduce new course material, they play
a crucial role in teaching you how to apply and utilize what you learned from lectures
to solve problems. It is essential to attend discussion sessions for this class.
6. Other Policies
If you have a documented disability, please email me your documentation as soon
as possible so that I can make suitable accommodations for you. If you believe that
you have a disability and need some special accommodations, please register with the
O¢ ce for Students with Disabilities.
Students who violate UCSDs academic integrity policy will earn a failing grade
for the course. In addition, the Council of Deans of Student A¤airs will impose a
disciplinary penalty.
I am a rst-generation faculty. I will be more than happy to share my rst-gen
experiences and journey during o¢ ce hours. I want to foster an inclusive classroom
environment. I encourage you to interrupt me with questions during each lecture.
