econometrics econ/decs b360-001 fall 20191 econometrics econ/decs b360-001 fall 2019 course...

1

ECONOMETRICS

ECON/DECS B360-001 Fall 2019

Course Location: 1st floor computer lab, Miller Hall

Class hours: 2:00 – 3:15 Tuesdays and Thursdays

Instructor: John Levendis

Office: Miller 315

Office phone: 864-7941

Email: [email protected]

Office Hours: 3:30-4:30 am Tuesdays and Thursdays and by appointment.

Course Prerequisites: Principles of Microeconomics (ECON B100), Principles of

Macroeconomics (ECON B101), Business Statistics (DECS 205), and Junior standing.

Terms of Use: A student's continued enrollment in this course signifies acknowledgment of, and

agreement with, the statements, disclaimers, policies, and procedures outlined within this

syllabus and elsewhere in the Blackboard environment. This Syllabus is a dynamic document.

Elements of the course structure (e.g., dates and topics covered, but not policies) may be

changed at the discretion of the professor.

College of Business Mission Statement: In the Ignatian tradition, the mission of the College of

Business is to provide a superior value-laden education that motivates and enables students to

become effective and socially responsible business leaders. We strive to contribute quality

research, serve local and intellectual communities, and graduate students who possess critical

thinking skills and courage to act justly in a global business environment.

Course Description: Econometrics is an intermediate level statistics course. After a brief

overview of statistics, the course covers least squares estimation, statistical inference, diagnostic

methods, selection and evaluation of functional form, and simultaneous equations estimation.

The course focuses more on applied work than on its theoretical underpinnings. Students are

actively involved with computer exercises in this course, using the STATA software program.

Students will complete a comprehensive statistical research project.

By the time you are finished, you will have learned a skill that most employers value, are willing

to pay for, and are utterly mystified by!

Expected outcomes: Students completing this course should be able to:

Articulate a statistically testable claim

Choose the right statistical method to test this claim

Use tools of statistical inference in order to evaluate claims based on sample data

mailto:[email protected]

2

Correct your method for violations of the standard assumptions

Use modern software packages to estimate your model

Produce a cogent report explaining the results of quantitative analysis in terms that are

both precise, and yet comprehensible to those who are unfamiliar with quantitative

research.

What you might do with these skills:

Economists – might use regression analysis to investigate how quickly increases in the rate of

money growth are reflected in price indices.

Social Scientists – might investigate how much a murder in a neighborhood decreases the value

of nearby homes.

Accountants – separate bundled prices into its constituent parts, or to estimate costs.

Managers – forecast sales, and increase efficiency by identifying processes that are the biggest

contributors to waste and lost time.

Marketers – investigate how various product characteristics influence the decision to buy

Financiers – test for empirical regularities between different financial assets.

Required Texts:

McCloskey, D. (1999). Economical Writing, 2nd

ed. Waveland Press, Inc.

Pedace, Roberto (2013). Econometrics for Dummies. Wiley Press. Hoboken, NJ.

Some other useful textbooks:

Achen, Christopher H. H. Interpreting and Using Regression. Quantitative Applications in the

Social Sciences, Vol. 29. Sage Publications: London.

Berry, William Dale and Stanley A. Feldman. Multiple Regression in Practice. Quantitative

Applications in the Social Sciences, v. 50. Sage Publications: London.

Lewis-Beck, Michael S. (1980). Applied Regression: An Introduction. Quantitative Applications

in the Social Sciences. Sage Publications: London.

Schmidt, Stephen J. (2005). Econometrics. McGraw-Hill: NY, NY.

Software:

We will be using a program called Stata. The College of Business has installed Stata in the

computers in the 1st floor lab. I really recommend getting your own copy of Stata. (It’ll save you

trips to the computer lab, and you can do your work when you feel it’s most productive.) “Small

Stata” only allows for datasets with fewer than 1000 observations, so if you’re planning on

working with microeconomic datasets (like labor market or census data) then you’ll need a more

hefty version of Stata like Stata/IC.

3

You can get your own copies of the student version for cheap(er). During the semester in which

you are enrolled, you may order Stata at

http://www.Stata.com/coursegp.html

Specify JL360 for the GRADPLAN ID, and choose which version of Stata you would like to

order. I recommend a six-month or one-year license for Stata/IC.

Alternatively, Stata 14.2 is on our Virtual Lab, which can be accessed from any computer on

campus outside of the Miller Trader Lab and off campus, at: www.loyno.edu/vlab

Digital storage:

While not required, you might find it useful to keep your work (datasets, articles, etc.) on a

thumb (flash) drive, or on “the cloud” via DropBox or Google Drive.

Homework:

Learning by doing is extremely important in this class. There will be hw assignments from

almost every chapter that we cover. These will consist of a series of problems to be solved using

Stata. Each homework assignment will be worth 10 points. You can drop one of the hws.

Homework will be collected at the beginning of class. For every day that your assignment is late,

10% will be deducted from your grade. Solutions will be posted on the morning of the next class

day. After this point, late assignments will not be accepted.

While student cooperation and discussion is encouraged, homework assignments must be the

work of the individual student. If your hw is a copy, or near copy, of a classmate’s hw, both

students will receive zeros for the assignment.

Project:

You will be responsible for completing a 15-20 page research project from start to finish. To

make sure you stay on track, you will have to turn in portions of the project periodically. These

smaller portions will eventually add up to the four major sections of your research paper:

introduction and literature review, description of the data, analysis, and conclusion.

Grading:

Homeworks 60 pts

Prelim report 1 (topic) 10

Prelim report 2 (lit review) 30

Prelim report 3 (data) 30

Prelim report 4 (draft) 50

Referee report 20

Final paper 100

---------------------------------- ----------

Total 300 pts

http://www.stata.com/coursegp.html

http://www.loyno.edu/vlab

4

Grade Percent

A 93-100

A- 90-92

B+ 88-89

B 83-87

B- 80-82

C+ 78-79

C 73-77

C- 70-72

D+ 68-69

D 60-67

F 59 and below

I reserve the right to raise or lower your final grade by an increment of a letter grade (from a C to

a C+, or a B to a B-, etc…)

Tentative calendar:

Topics will be covered in the following order. The pace of the class varies each year, depending

upon the idiosyncrasies of the students and of the academic calendar; therefore, the due dates

cannot be given with precision. Additional materials may be added as appropriate. This schedule

is subject to change.

8/20 Introduction, syllabus

Basic concepts

Conducting a research project

Sample paper handout

Textbook (Schmidt) chapters 1 and 2

8/22 Stata example from Kohler and Kreuter

Anscombe’s Quartet

Distribute HW-1

8/27 Do-files and log-files

The grammar of Stata commands

Paper discussion

Class time for HW-1

8/29 HW-1 due

OLS lecture (Ch6 in Schmidt)

9/3 Return graded HW-1

Discuss HW-1

Distribute HW-2

5

In class Stata exercise on OLS

9/5 Discuss various student projects

9/10 Preliminary report #1 (topic) is due

Ch4: Estimation

Lecture on scaling

Lecture on converting between nominal and real values

Ch5: Hypothesis testing

Central Limit Theorem

9/12 HW-2 due

Ch5 continued

Distribute HW-3

Do the in-class portion of HW-3

9/17 Return graded HW-2, discuss

Discuss sample paper

9/19 Ch7: Properties of OLS

9/24 HW-3 due

Ch7, continued


10/1 Ch8: Multivariate regression

The Frisch-Waugh Theorem

Multicolinearity

R2

10/3 Ch9: Functional form

Assign HW-4

10/8 Preliminary report 2 (lit review) due

Ch9 continued

10/10 Students work on HW-4 in class

10/15 Fall break. No class.

10/17 HW-4 (ch.9) due

Lecture on data management, appending, and merging.


6

10/24 Assign HW-5 (data management)

Chapter 10: Determining the specification of the model

Which variables to include?

10/29 Chapter 10 continued

In-class HW time

10/31 HW-5 (data management) due

11/5 Return graded HW-5, discuss.

Using logarithms

11/7 Chapter 11: Dummy variables

Distribute HW-6 (chapter 11)

11/12 Preliminary report 3 (data section) due

Ch 11: Dummy variables continued

In-class portion of HW-6

11/14 HW-6 (ch.11) due


11/21 Ch14, 2sls and endogenous variables

Distribute HW-6 (on ch14, 2sls)

In-class time for HW-7

11/26 HW-7 due

11/28 Thanksgiving holidays. No class.

12/03 Rough draft due, bring three hard copies.

Swap drafts with other students

12/5 Referee report due

Return my referee reports

Workshop student papers

12/12 Your final paper is due on Thursday, December 12th

at 11:30am.

7

Academic Integrity Statement:

It is very important that you do your work yourself. It is OK to work with others, but the written

product that you turn in must be your own work. Violations will result in academic penalties,

including receiving an “F” for the assignment, and possibly for the course. More serious

violations will be taken through the appropriate administrative channels.

According to the Loyola University Student Handbook

(http://www.loyno.edu/studentaffairs/conduct/handbook/academic_policies.html):

“All academic work will be done by the student to whom it is assigned without

unauthorized data or help of any kind. A student who supplies another with such data or

help is considered deserving of the same sanctions as the recipient. Specifically, cheating,

plagiarism, and misrepresentation are prohibited. Plagiarism is defined by Alexander

Lindley as “the false assumption of authorship: the wrongful act of taking the product of

another person’s mind, and presenting it as one’s own” (Plagiarism and Originality).

“Plagiarism may take the form of repeating another’s sentences as your own, adopting a

particularly apt phrase as your own, paraphrasing someone else’s argument as your own,

or even presenting someone else’s line of thinking in the development of a thesis as

though it were your own” (MLA Handbook, 1985). A student who is found to have

cheated on any examination may be given a failing grade in the course. In case of a

second violation, the student may be excluded for one or two terms or dismissed from the

University.

“A student who engages in cheating, plagiarism, or misrepresentation on term papers,

seminar papers, quizzes, laboratory reports, and such may receive a sanction of a failing

grade in the course. A second offense may be cause for exclusion or dismissal from the

University. Faculty members are required to report immediately to the dean of the

student’s college any case of cheating, plagiarism, or misrepresentation which they have

encountered and, later, the manner in which it was resolved.”

Attendance Policy:

None. You are adults. But there is a high correlation between attendance and performance. This

correlation is statistically and economically significant.

Cell Phones and Computers:

Please keep cell phones turned off during class. Do not check messages or send messages during

the lecture.

You will be tempted to browse on the internet during class. Do not do this. It is rude, I take

offense to it, and it’ll cost you. All applications that are not related to classwork should be

closed, not just minimized.

http://www.loyno.edu/studentaffairs/conduct/handbook/academic_policies.html

8

Additional Expectations:

Free discussion, inquiry, and expression are encouraged in this class. Classroom behavior that

interferes with either (a) the instructor’s ability to conduct the class or (b) the ability of students

to benefit from the instruction is not acceptable. Examples may include routinely entering class

late or departing early; use of beepers, cellular telephones, or other electronic devices; talking

while others are speaking; or arguing in a way that is perceived as “crossing the line of civility.”

The Term Paper

Your assignment is to construct an econometric model of a functional relation that is

interesting to you, collect the relevant data, and estimate the model dealing with possible

statistical problems that might arise.

You must clear your idea with your professor before getting started on your project. You can

find ideas for possible projects from examples in our text, from questions that are raised in your

other classes, or from journals that publish applied statistical research, such as The Review of

Economics and Statistics, Applied Economics, The Journal of Applied Econometrics, and various

other journals from almost any business field.

I will impose very few restrictions on the nature of this project; the application does not

have to be an economic relation. However, there are some projects that are likely to be less

suitable than others, because of unavailable data or lack of interesting testable hypotheses.

Therefore, to guarantee that your project remains on the right track, you are required to regularly

submit portions of your paper.

Once we have agreed on a project, you should collect the data. If you were to propose a model of

wage determination, would you observe wages of individuals at a point in time, or would you

model average wages in the US over time, or possibly average wages of states observed across

states? Clear thinking about this issue is vital to developing a reasonable econometric model.

The next step is to begin estimation. You will probably want to try several alternative

specifications of your model, and you will undoubtedly encounter various statistical problems.

An important part of the project is the testing and treatment of these various econometric

problems, using procedures presented in the course. You should document your use of these

procedures.

Grading is neither by pound of output or written material, nor by complexity of project, but

rather by:

1. Economic theory behind the design of your econometric model;

2. Appropriateness of the procedures selected; and

3. Completeness and clarity in communicating the results and the policy implications.

9

The Progression of the Paper Preliminary Report 1: The Problem Statement, its significance.

1. Select your topic in consultation with your instructor. 2. Justify the selection of your topic: Why should we care? 3. Make sure that the necessary data are, at least in principle, available. 4. Fill out and turn in the “Preliminary Report 1: Paper Topic” sheet. You will find it a couple of pages

after this one. Preliminary Report 2: Literature Review:

1. Type up a proper introduction to your paper. You should establish what your research question is, and why it is important. (See your Preliminary Report 1 if you’ve forgotten.)

2. Survey the literature a. What type of analysis did previous researchers do? b. What data did they use? Where did they get it? c. What were their results?

3. Include a proper bibliography. 4. Very briefly, what type of economic model and data do you intend to use?

Preliminary Report 3: A fixed-up version of Report 2, plus a description of your data:

1. Define your variables. 2. Describe the data. Are they categorical, ordinal, continuous… 3. Describe your data sources. 4. Summarize the data using simple summary-stats and graphs. 5. Write your hypotheses and speculate on what you expect to find and why

(i.e. what are the expected effects of each variable?)

Rough Draft: A fully written paper, submitted for peer review

1. Treat this as though it were your final submission. 2. Perform the data analysis. 3. Explain to the reader why you did what you did. 4. What are your estimation results? Conclusions? 5. Your paper will be reviewed, anonymously, by your peers for constructive feedback,

so only put your name on a cover sheet. Referee’s Report

1. Summarize in your own words a classmate’s paper 2. Offer criticisms and suggestions for improvement 3. Grade the paper

Final Report: Final Submission This final submission will be a finished, polished research paper.

1. You should stress your conclusions, 2. Explain how they compare with previous studies’ results, and 3. Discuss how your results have any implications for theory or policy.

10

Preliminary Report 1: Paper Topics

You can research whatever topic you want, as long as you research it statistically, using the tools

presented in this class. Coming up with a paper topic that is doable is harder than it seems. It is

easy to come up with interesting research questions; it is much more difficult to find the data you

would need to answer those questions.

Here are some preapproved topics:

Micro

1. The correlation between sexual orientation and wages (Are LGBT discriminated

against?)

2. What is the relationship between alcohol consumption and personal income?

Macro

3. The correlation between economic freedom and economic growth/income? (Are freer

countries richer? Do they grow quicker?)

4. What is the correlation between corruption and economic growth/income?

5. What is the relationship between gender equality and economic growth/incomes? (Is it

bad for the economy to discriminate against women?)

6. What is the relationship between income inequality and economic growth/income?

7. What is the relationship between pollution and economic growth/income?

Finance

8. What is the relationship between economic freedom and stock market returns/volatility?

9. What is the relationship between corruption and stock market returns/volatility?

Some suggestions:

Stay away from sports topics. Baseball has tons of data, but it is not provided in a format

that is amenable to regression analysis.

Don’t do country-specific macroeconomic studies. If you’re going to do macro, stick with

cross-country research questions. Ex: do countries with high inflation rates have lower

rates of long-term growth? Rather than, did the US experience higher growth when it had

higher inflation rates?

Don’t do a study on drugs. It’s a fun topic to think about, but the data are much too hard

to find.

Flip through your old textbooks, and remind yourself what questions you had. For

example, when in an environmental econ class, did you ever wonder how GDP varies

with gasoline prices? Or what the correlation is between unleaded and diesel prices?

Keep it simple: what is the relationship between X and Y. (We’ll have ample opportunity

to complicate things later.)

Meet with me to discuss your ideas. You should come prepared to our meeting with ten

research questions.

After we have discussed your paper ideas, you should pick one. Think about what your X

and Y variables will be, as well as what these factors (in “holding other factors constant”)

might be. Fill out and turn in the sheet on the next page.

11

Preliminary Report 1: Paper Topic

Name:______________________________ Date: ______________________________

My paper will investigate the following hypothesis: ____________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

It is an interesting and relevant question because: ____________________________________

______________________________________________________________________________

______________________________________________________________________________

______________________________________________________________________________

My paper will investigate the effect of X on Y, holding other things constant.

Here is what my variables will likely consist of:

Y (my one dependent variable) = _____________________________________

X1 (my main independent variable) = ___________________________________

X2 (other variables that might affect Y) = ___________________________________









You don’t need to have all X2-X10 filled out, but you should have some idea of what these

“other factors” might be that affect Y.

12

Preliminary Report 2: The Literature Review

Not to be confused with a book review, a literature review surveys scholarly articles (and

sometimes books) relevant to a particular area of research and provides a description, summary,

and thematic grouping of each work. The purpose is to offer an overview of significant literature

published on a topic.

You can find relevant articles using:

1. EconLit – a database of all economics articles, which you can access through the Monroe

Library website.

2. Google Scholar – provides a broader search, beyond strictly economics articles.

3. The bibliographies from papers that are already in your lit review

4. Web of Science’s “cited reference search”. This allows you to do a bibliography going

forward in time; that is, it gives you a list of all the papers that have cited a particular

paper. Think of it as a reverse bibliography.

You will notice that each academic article follows a specified format. Usually, they motivate the

research in the first couple of paragraphs. That is, they explain why the topic is of interest. Then

they dive right into a literature review. This is their attempt to bring the reader up to speed on the

literature. (It also points out areas where the current research is lacking, and where their research

will fill those gaps.)

These papers’ literature reviews will be a second source of relevant articles. If they mention an

article, you should probably read that article, too. So the bibliography provides a third place to

find articles to cite.

How many articles should you cite? It’s hard to say. You just have to be thorough. Some topics

have been studied at length, so a proper literature review will have survey 15-30 articles. Other

topics have received little attention, so you can only cite 10 or so articles.

Components

Literature reviews should comprise the following elements:

An overview of the subject, issue or theory under consideration, along with the objectives

of the literature review

Division of works under review into categories (e.g. those in support of a particular

position, those against, and those offering alternative theses entirely)

Explanation of how each work is similar to and how it varies from the others

Conclusions as to which pieces are best considered in their argument, are most

convincing of their opinions, and make the greatest contribution to the understanding and

development of their area of research

The purpose of a literature review is to:

Place each work in the context of its contribution to the understanding of the subject

under review

13

Describe the relationship of each work to the others under consideration

Identify areas of prior scholarship to prevent duplication of effort

Point the way forward for further research

Again, please use the articles’ own literature reviews as templates for your own reviews. Don’t

copy, but just follow their style of writing.

Speaking of style of writing: you must write in a professional, academic tone. There is no room

for slang, or even “I will” or “I think”, etc… Follow the writing style of the articles you’ve read.

You’ll find it useful to outline your lit review before you begin writing. This way, you’ll have a

well-defined structure that organizes the papers thematically.

Your first paragraph should briefly introduce the research question, and motivate the reader that

the question is important and worth answering. Make sure you have a thesis statement that

indicates what your research will investigate.

Do not just have one paragraph-per-paper: A said X, B said Y, C agreed with X, and D agreed

with X. I could just read each paper’s abstract for that. Rather, what I need from you, is to help

me relate the papers to each other. Group the papers together in terms of their results, or

approaches, or statistical techniques, or some other such theme that helps your reader understand

the overall outlines of the debate.

If you quote, you must cite the page number. If you have a quote that runs more

than four lines, you must use a “block” quote format. This is where you indent a

half-inch from both the left and the right margins.

Try to conform to the citation style described in the course BlackBoard site, under Course

Materials Literature Review folder.

Google Scholar now has a feature which actually generates properly formatted references in all

the major styles: MLA, APA, and Chicago. Use it!

In your References section, each entry should use a “hanging indent” such as:

Lee, S. H., Levendis, J., & Gutierrez, L. (2012). Telecommunications and economic growth: An

empirical analysis of sub-Saharan Africa. Applied Economics, 44(4), 461-469.

Google how to do this in your specific word processor. The lit review in that paper is pretty

good, btw.

You may also want to read the following:

Denney, Andrew S. and Tewskbury, Richard (2013). How to write a literature review. Journal of

Criminal Justice Education, 24(2): 218-234.

14

You should consult the sample paper for formatting, and general writing style. D.

McCloskey’s Economical Writing is a great guide on how to write for an audience of

academic economists. And don’t be afraid to go to the WAC lab for an extra pair of

proofreading eyes.

15

GRADING RUBRIC FOR LITERATURE REVIEW

Paper authors:

Criteria and qualities Poor (1)

Good (2)

Excellent (3)

Point Value

Scaling factor

Introduction: the Problem statement

Vague reference is made to the topic to be examined.

Readers are aware of the overall problem or topic to be examined.

The topic is introduced, and its relevance is explained.

5%

Articles: appropriateness of

sources

Information is gathered from limited, dubious, sources.

Information is gathered from a few sources, some of dubious quality.

Information is gathered from multiple, research-based sources.

20%

Articles: appropriateness of

content

Major sections of pertinent content have been neglected or greatly run-on. The topic is of little significance to the field.

Some discussion of broader scholarly literature.

The appropriate content is covered in depth without being redundant. Sources are cited when specific statements are made. Relevance and significance are unquestionable.

10%

Articles: Balanced viewpoint

Presents only one answer to the research question.

Some discussion of alternative viewpoints, but heavily favors one side.

Objective, balanced viewpoint from various perspectives.

10%

Conclusion: Synthesis of

literature's findings and research

question.

There is no indication the author tried to synthesize the information or make a conclusion based on the literature under review. No hypothesis or research question is provided.

The author provides concluding remarks that show an analysis and synthesis of ideas occurred. Some of the conclusions, however, were not supported in the body of the report. The hypothesis or research question is stated.

The author was able to make succinct and precise conclusions based on the review. Insights into the problem are appropriate. Conclusions and the hypothesis or research question are strongly supported in the report.

10%

16

Presentation

Grammar Four or more spelling and/or grammatical mistakes per page.

Two or three spelling +/- grammatical mistakes per page.

One or fewer spelling and/or grammatical mistakes per page.

20%

Clarity of writing and writing technique

It is hard to know what the writer is trying to express. Writing is convoluted.

Writing is generally clear, but unnecessary words are occasionally used. Meaning is sometimes hidden. Paragraph or sentence structure is too repetitive.

Writing is crisp, clear, and succinct. The use of pronouns, modifiers, and parallel construction is appropriate.

10%

Coherence and structure

Poorly conceptualized, haphazard. Some coherent structure. Well developed, coherent. 10%

Citation format

Citations for statements included in the report were not present, or references which were included were not found in the text.

Citations within the body of the report and a corresponding reference list were presented. Some formatting problems exist, or components were missing.

All needed citations were included in the report. References matched the citations, and all were encoded in the appropriate format.

5%

Lagniappe

Timeliness Material was submitted more than one class late.

Material was submitted up to one class late.

Material is submitted on time. 10% reduction

per day late

Additional Comments Final Score:

As a percent:

17

The Data Section

Please do not put off working on the data too late. You should consider availability of data

from the beginning of the project.

If your paper is microeconomic in nature, some useful sources of data are:

National Longitudinal Study of Youth

Panel Study of Income Dynamics

Current Population Survey

General Social Survey

Macro data are easier to find. Check out:

World Bank. The Stata command, wbopendata, download this data directly into Stata.

International Monetary Fund

FRED (The Federal Reserve’s database) The Stata command, freduse, downloads this

data directly into Stata.

Penn World Tables. This dataset is very good for cross-country comparisons. You can

also access these data from freduse.

Several macro databases, in Stata format no less, can be accessed through

http://graduateinstitute.ch/md4Stata/datasets.html. This includes the Penn World Tables.

If you download from here, or from wbopendata or freduse, you will not have to

convert your data to Stata format; your life will be easier.

A useful portal to find data is: http://www.oswego.edu/~economic/data.htm. It includes dozens

of links to data sources.

In getting your dataset in order, try to do all your work in one do-file. This do-file should include

everything from loading your original datasets, and the commands for making any alterations to

them.

Some useful commands are:

destring (this command converts a text variable to numeric. This is especially useful

if your data originally came in Excel format, and you copy-and-pasted into Stata.)

xpose (transpose. It rotates your dataset so that columns become rows and rows become

columns)

merge (to splice together two different datasets.)

collapse (helps you calculate averages and sums. For example, you might have data

for 100 countries, each with 10 years. This lets you calculate the 10-year average for each

country.)

reshape (useful if you have panel data and you want to switch between long and wide

format)

Also, Dr. Mehmet Dicle and I wrote a Stata command to simplify some of the tedium of

renaming countries so that they share the same standard names across datasets. You can install

this command by typing into the command line: .net from http://dlacademics.com/Stata

or

http://graduateinstitute.ch/md4stata/datasets.html

http://www.oswego.edu/~economic/data.htm

18

.net from http://www.loyno.edu/~mfdicle/Stata

then clicking on click on “countrynames,” and then clicking on “(click here to install).”

The data section of the paper describes the sources of the data that you will be using. Your

readers should be able to find the same data you used pretty easily after reading this section.

It is common to provide a table of summary statistics, too. (Remember the summarize

command in Stata.) If you do this, remember that readability is important for your reader: keep

the number of decimal places to the necessary minimum.

Variable Obs Mean Std. Dev. Min Max

lnPRICE 33808 11.97 0.65 4.25 15.15

PRICE 33808 194134.40 152564.30 70.00 3800000.00

elevation (ft) 25786 9.08 26.60 -13.80 354.70

dist_mi 25786 17.17 14.40 0.18 78.83

bdrms 33808 3.28 0.77 0.00 10.00

hbaths 33808 0.28 0.48 0.00 5.00

fbaths 33804 2.01 0.66 0.00 9.00

age 33158 2.72 2.56 0.00 20.00

condition 33807 3.32 1.23 0.00 5.00

LotArea 28909 186.72 1000.76 3.39 75020.46

LivingArea 33739 19.16 8.18 0.01 131.76

FoundRaised 33808 0.21 0.41 0.00 1.00

percent white 25786 0.71 0.28 0.00 0.99

PostK 33808 0.33 0.47 0.00 1.00

lnMHI 25775 3.74 0.37 1.76 4.98

MHI 25775 45.08 16.61 5.82 146.16

Table 2: Summary Statistics

If data are categorical, or ordinal, explain this. For example, property rights are often reported

on a 1-5 scale. Be sure to mention this, and also explain whether a score of 5 means that there are

good property rights or poor ones. Age is probably a continuous variable. But sometimes it is

lumpy, so that age is reported in decades. If so, let your reader know.

Keep the decimal points to a minimum. Three decimal places are usually more than enough.

It is often useful to provide a scatterplot of the main variables that you will be focusing on. For

example, your paper might focus on the effects of property rights on per capita GDP. You will,

of course, have to control for other variables, such as education, political rights, or whatever. But

presuming the main variables you are interested in are property rights and pcGDP, it is not a bad

idea to provide a scatterplot, and even maybe a simple regression line overlaid on the scatterplot.

A similar and powerful way of making the case that X affects Y is to provide two summary

tables that compare two groups. For example, suppose that X is TaxRates and Y is GDP. Then it

might be presumed that higher tax rates correlate to lower GDP. So, split your dataset into two

groups, one with low tax rates and another with higher ones, and report summary statistics for

19

each. You should be able to tell at a glance whether GDP is higher in the low tax country. You

will also be able to tell how high- and low-tax countries differ regarding all the other X variables,

too.

As always, use as templates the articles you’ve read in your literature review.

And remember, this is an important part of your paper. Your tables should be formatted to

look like ones in the academic journals you are reading. You’ll have to cut and paste from

Stata into Excel, and then format the tables before they are presentable. Tables should

have titles and be numbered (Table 1: Description of the Data; Table 2: Data Sources,

etc…).

You don’t have to report regression results at this stage. That comes later.

This new portion of your paper should be approximately 2-4 pages long. Not much writing

is involved, but be sure to include a revised intro and literature review. And don’t be afraid

to go to the WAC lab for an extra pair of proofreading eyes.

20

GRADING RUBRIC FOR DATA SECTION

Paper author:


Good (2)

Excellent (3)

Point Value

Scaling factor

Introduction & Literature Review

The introduction and literature review were barely revised.

Some revisions were made. Revisions were thorough and appropriate.

10%

Appropriateness of data sources

Most data are gathered from dubious sources.

Some data are gathered from dubious sources.

All data are gathered from reputable sources.

20%

Appropriateness of dataset

No explanation of the strengths and limitations of your dataset.

Some discussion of the strengths and limitations of your dataset.

You explained the strengths and limitations of your dataset.

5%

Appropriateness of dataset: number of obs.

You had too few observations (less than 20 per variable).

You had between 20 and 30 observations per variable.

You had more than 30 observations per variable.

10%

Appropriateness of dataset: variable relevance

Your dataset contains many variables with limited relevance to the research question.

Your dataset contains some variables of limited relevance.

Your variables are appropriate to the research question.

20%

21

Explanation of the variables (definition of terms, nominal vs real, units used, categorical vs ordinal, etc…)

It is not clear you understand what your data are about.

You have some understanding of your data, and are able to impart some of that to your reader.

You have a clear understanding of your data. Your explanation of the variables is also clear.

10%

Graphics and Scatterplots No extra graphs were provided.

Scatterplots of the main variables of interest were provided, but many were extraneous.

Scatterplots were provided, and were appropriate to the question at hand.

. . .

10%

Table of Summary Statistics: Thoroughness

Your table includes few summary statistics.

Your table includes summary statistics.

Table includes the appropriate summary statistics, and comparisons across groups.

10%

Table of Summary Statistics: Presentation

Your table was more like a cut-and-paste from Stata.

Your table was formatted, somewhat, but could stand improvement.

Your table was appropriately titled; you use descriptive variable names; your table was readable (without too much meaningless detail).

5%

Lagniappe

Lateness. Material was submitted more than one class late.

Material was submitted up to one class late.

Material is submitted on time. 10% reduction per day late

Additional Comments Final Score:

As a percent:

22

Drafts

Please treat your draft as though it were your final submission. That’ll allow me to make

more substantive comments to your paper. It would be a waste to have me tell you to check for

punctuation and grammar; to tell you to format, number and title your tables; etc…

Be kind to your readers and use descriptive variable names. It is ok to have ED2LJJK as a

variable name in your do-file, but it’s not very informative for your readers. Rename your

variables so that your readers can easily tell what the variables mean.

Be kind to your readers and summarize regression results in tables. Don’t provide scores and

scores of regression results. Rather, you should focus on your main findings and can summarize

your results in one large table. If you used a testing-down procedure, for example, you could

show the sequence of regressions in a table as follows:

Table 3: Regressions on ln(wages): Testing Down

(1) (2) (3)

Age 32*** 23*** 30**

(0.003) (0.005) (0.04)

Education 456 555 644*

(0.30) (0.20) (0.03)

Female 100

(0.35)

Hair color 42* 50

(0.08) (0.25)

Constant 100 120 90

(0.20) (0.25) (0.15)

N 100 100 100

Adj-R2 0.65 0.70 0.80

Note: *** indicate the coefficient is significant at the 0.01 level; ** are significant at

the 0.05 level; * at the 0.10 level. P-values are in parenthesis.

If you did a testing up procedure, then you would have tons and tons of regressions. Don’t show

these. Rather, put your “final” regression as column (1). Then, in columns (2) and (3), show what

happens when you throw in an additional variable. In the body of the paper, discuss the results

from (1). Columns (2) and (3) will show the reader how robust your results are to including some

other variables. One or two sentences to this regard should suffice.

Format your tables so that they can be understood without referring to the body of the paper.

Don’t report too many decimal places. If you require many decimal places, perhaps you can

redefine your variable (income in thousands rather than in dollars).

Some students find Stata’s outreg command simplifies the construction of tables like the one

above.

The conclusion is usually brief. One or two paragraphs. Restate your research question, give the

high points of the literature review, and restate your conclusion and why it is important.

23

Consider going to the WAC-lab or have a friend proofread your paper.

You should consult the sample paper for formatting, and general writing style. As always,

consult D. McCloskey’s Economical Writing! And don’t be afraid to go to the WAC lab for an

extra pair of proofreading eyes. Did I mention that you should proofread your work?!

Please turn in three copies. Your name should appear only on a detachable cover page; this

page should only include your name and the paper’s title. Please include the paper’s title on the

first page of the body of the paper as well.

24

GRADING RUBRIC FOR DRAFT/FINAL PAPER

Paper title: Paper author:

Referee:

Criteria and qualities

Poor (1)

Good (2)

Excellent (3)

Point Value

Scaling factor

Introduction Does not convince the reader that the issue is important. The intro either wanders or is too short.

Decent introduction. Could use some improvements.

Convinces the reader that the issue is worth investigating.

5%

Literature review

Scattered treatment of disconnected sources. Little connection to your data analysis.

Sources/papers are listed one after the other. The papers raise issues that are not addressed by you in the analysis section.

The sources are integrated. They relate to the question at hand, and with your statistical treatment of the research question.

10%

Data section: variables

Your dataset contains many variables with limited relevance to the research question. Most data are gathered from dubious sources.

Some variables are included which are unjustified; other relevant ones are excluded. Some data are gathered from dubious sources.

All, and only, relevant variables are included. All data are gathered from reputable sources.

10%

Data Section: text

Variables are unexplained. Strengths and limitations of your dataset are not discussed.

Variable definitions, sources, strengths and weaknesses are somewhat explained.

You explain clearly what each variable (and its abbreviation) mean. You explained the strengths and limitations of your dataset.

5%

Data section: graphs and tables

No extra graphs or summary tables were provided. Or, there were way too many or way too few of them. Tables and graphs not formatted.

Scatterplots of the main variables of interest were provided, but many were extraneous. Tables and graphs could benefit from formatting.

Targeted use of graphs and tables. They are appropriate to the question at hand. They are properly formatted.

10%

25


Good (2)

Excellent (3)

Point Value

Scaling factor

Model specification: non-linear effects (squared variables, polynomials, etc.)

What’re polynomials?

Used a polynomial, but without justification, or without seeming to know why.

You don’t need to use polynomials, but you should at least consider their use. Explain why you did or did not use them.

5%

Consideration given to model specification: interaction effects.

What’re interaction effects?

You interacted some stuff, but without much justification.

You used interactions appropriately and interpreted the coefficients properly.

10%

Heteroskedasticity/autocorrelation tested and accounted for.

What are Hetero-skedasticity or autocorrelation?

You have an incomplete grasp of the problem of heteroskedasticity and/or autocorrelation.

You tested for both and, where appropriate, used

robust standard errors. 5%

Model specification: log or un-logged variables, as appropriate.

Linear model with no justification for the choice

Discussion on apriori grounds for log v no-log.

Full explanation and statistical justification for log v no-log.

10%

Appropriate use of Dummy Variables. What are dummy variables?

Dummies used when continuous variables would have been better.

Dummies are used where appropriate.

10%

26


Good (2)

Excellent (3)

Point Value

Scaling factor

Table of regression output

Cut and paste from Stata.

Could use some more formatting.

Are properly titled, formatted, and professional looking. No extraneous decimals. Units are appropriate.

5%

Interpretation of coefficients

Very little comment on the coefficients.

Focus only on the signs of the coefficients.

Coefficients are properly interpreted. Explain not only the signs of the coefficients, but the numbers as well.

10%

Conclusions: Poorly written. Could use improvements.

Restate the problem, why it is interesting, and how your paper addressed the outstanding questions of the literature.

5%

Bonus:

Model specification:

RESET test. Ramesy’ RESET test was used appropriately. The procedure was explained. The final model passes the test.

10% bonus

Instrumental Variables Instrumental variables were used when appropriate. The procedure was explained. 10% bonus

Deductions

Grammar By this stage in the game, your paper should have been read and reread, so that there are no grammatical mistakes whatsoever.

2% reduction per grammatical error

Lateness. Grades are due to the registrar’s office two days after the end of exams. 10% reduction per day late

Additional comments Final score:

_____________________________

27

Referee Reports

Write a 2-3 page referee report summarizing the contribution of the paper, its key weaknesses

and how these problems might be addressed, portions of the paper that might be strengthened,

expanded, shortened, etc. Be clear about the exact revisions required.

It is important that the referee provide the author with useful feedback on his manuscript.

The most important part of the referee report is your critical analysis of the paper. Exactly what

you do will depend on the paper and its content. There is no single checklist, but below are some

questions that you might ask of the paper. The list is not exhaustive. In addition, the paper you

are refereeing might not require answers to all of the questions.

Most important is the answer to the question: Does the paper accomplish what it set out to do?

Other possible questions to ask are the following:

If the paper contains theory (explicit or implicit), does it hold up upon closer scrutiny? Is

there an alternative theory that is better suited that the author has ignored?

Is the paper convincing? If not, why not?

Are the appropriate econometric tools being used? Is an inappropriate model being used?

(For example, if you think endogeneity is a problem and someone estimated a 1-equation

model. Or, if you think that a logit model would have been more appropriate.)

Are the coefficients of interest properly identified?

Should the author subject the empirical work to robustness tests?

Would the reader be better served by some simple tabulations or simple means and

standard deviations or by some graphical presentation?

Are the tables and figures self-contained and easy to comprehend, and could you, if

needed, replicate them?

Is there a relevant and important literature that the author does not cite and/or use when it

should be cited and/or used?

What do you as the referee suggest that the author do to correct the errors of commission

or omission that you have found?

In writing your report you can consult additional literature. A quick lit review using JSTOR or

EconLit is a good idea. This way you can verify whether the author has undertaken a thorough

literature review and has understood the topic before trying to make the new contribution.

Also, include your assessment of the paper, using the draft/final-paper rubric, which you

can find above. For each item, multiply the given points by their weight (say 2pts * 0.10 = 0.2

pts) and then add up all these weighted points. This is the score of the paper, on a scale of 0-3. If

you want, divide by 3 to get the percentage score. Turn in two of these (one for me, and one for

the paper’s author.)

The first page of your referee’s report should be a detachable cover sheet which includes

your name and the title of the paper you refereed. Please turn in two copies for each paper

you have refereed. Use a stapler.

28

Structure of a Referee Report

A referee report is usually organized as:

Referee Report

Title of the Paper You are Reviewing

A. Summary:

When you summarize the paper, without evaluation, write neutrally as you might

if you were recording information for yourself or for a member of a research team

that you were working in. The key is that this part of your report is like notes that

you would put in your files to answer the question: "what did the author of this

paper view himself as doing?"

This should be about ½ to 1 page.

B. Evaluation

1. Larger issues:

Did the author accomplish what he set out to? Is the survey of the

literature complete? Does it help conceptualize the literature, or is it

simply bullet points. Are there weaknesses with the data? With the

argument? With the statistics? Are the tables properly formatted, and even

more importantly, are they readable? Are the results (the coefficients)

properly interpreted? Are the results explained in an accessible way?

Etc…

2. Smaller Issues (by page):

Point out areas with spelling and grammatical problems. Areas where the

writing was unclear.

econometrics econ/decs b360-001 fall 20191 econometrics econ/decs b360-001 fall 2019 course...

Documents