Econometrics Messages

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Thank You!

(posted: 17 August 2017)

Dear Students,

I just posted your grades. You should also receive an email from me with feedback on your course project.

Thank you once again for a wonderful summer. Thank you for taking an interest in the subject matter. I enjoyed working with you all. And I wish you all the best of luck in your future endeavors.

Sincerely,
- Eryk Wdowiak

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BLS Employment Status by State

(posted: 10 August 2017)

Several of you expressed interest in working with the state-level employment rates that the US Bureau of Labor Statistics publishes. I have reformatted the data into CSV files that you can easily import into Gretl. Most of you will want the annual data. Nonetheless, I have also prepared the monthly data.

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Submission Schedule

(posted: 28 July 2017)

In class, we set the following submission schedule:

  • Thu 27 July -- answers to midterm exam
  • Thu 03 Aug -- project proposal
  • Thu 10 Aug -- answers to final exam
  • Tue 15 Aug -- final project

As discussed in class, I would like you to think of the midterm and final exams as note-taking exercises. And I would like you to think of the course project as your opportunity to learn econometrics by doing it.

For the project proposal, please submit a written description of:

  • the null hypothesis that you wish to test
  • the dataset that you plan to test it with

For the final project, please submit a formal paper, in which you describe:

  • the null hypothesis that you tested
  • the dataset that you tested it with
  • summary statistics
  • how you manipulated the data
  • the regressions that you ran
  • your conclusion:   should we accept or reject the null hypothesis?

Assembling a dataset will be your most difficult task, so I want you to help each other. Please share your data with your classmates and let's discuss it in workshop sessions. I hope this project will help you learn econometrics.

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The Next Two Weeks

(corrected: 30 July 2017)

During the remaining two and a half weeks, I want you to spend most of your time constructing datasets and testing null hypotheses. During that time, we must also discuss two more theoretical components, but you learn econometrics by doing it (not by reading about it).

The two theoretical topics that we must discuss are probability models and time-series. My current plan is to discuss probability models (like the logit and probit models), with you on Tues 01 Aug and to discuss time-series with you on Thurs 03 Aug and Mon 07 Aug. The remaining sessions will be workshop sessions.

To prepare for our discussion of probability models, please read Stock-Watson chap. 9 and Kennedy chap. 16. And to prepare for our discussion of time-series, please read Stock-Watson chaps. 12, 13 and 14 and Kennedy chaps. 10 and 19.

But most importantly, I want you to construct a dataset and test a null hypothesis. That is how you will learn econometrics. So please spend most of your time thinking about what null hypothesis you would like to test. And please look for data to test that null hypothesis.

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Midterm Exam

(posted: 22 July 2017)

As discussed in class, I would like you to submit your answers to the midterm exam questions on   Thurs. 27 July.   When I review your answers, what I will want to see is that you have learned regression analysis. If it helps, you may think of this assignment as an opportunity to develop a set of notes for yourself.

And in developing your own notes on regression analysis, please remember that the problem set will help you understand the topic. And please remember that my notes and my wxMaxima notebooks in lec. 1, lec. 2 and lec. 3 will help you understand the problem set.

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Week of July 24-27

(posted: 22 July 2017)

This week, I would like to continue working with you on datasets. Specifically, I would like to introduce the OECD data. We will test the same null hypothesis, but with a richer dataset. It contains more variables and more detailed variables (than the Italian data).

On the theoretical side, we will also discuss panel data and heteroskedascity. To prepare for our discussion of panel data, please read Stock-Watson chap. 8 and Kennedy chap. 18. To prepare for our discussion of heteroskedascity, please read Kennedy chap 8.

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Week of July 17-20

(posted: 16 July 2017)

This week, we must continue our dicussion of econometric theory, but I must also provide you with practical examples of that theory. The difficult task for me will be to find the right balance.

The theoretical topics that I would like to discuss are:   hypothesis testing, maximum likelihood and the Gauss-Markov assumptions. For background, please read Kennedy chaps. 1-7. You will enjoy the Kennedy's Guide. It will help you develop an intuitive understanding of econometrics.

To provide you with a practical example of how we use this theory, I would like to measure the effect that the "Biagi Law" had on Italian employment rates.

My plan is to start the week by defining the null hypothesis that we will test:   the null hypothesis that the "Biagi Law" did not affect the employment rate. Then I would like to explain hypothesis testing and the role that the normality assumption plays in our hypothesis tests. At the end of the week, I would like to show you how we manipulate the "Biagi Law" data, so that we can perform a proper set of hypothesis tests.

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On Mon. 17 July, I would like to start with a brief discussion of the "Biagi Law" and develop the null hypothesis that we will test. Then I would like to provide some examples of hypothesis testing and discuss the way we use hypothesis testing in econometrics. Specifically, I would like to compare two proportions. Then I would like to use the distribution of beta hat in an explanation of t-tests of regression coefficients. Finally, I would like to discuss the relationship between R^2 and the F-statistic.

On Tues. 18 July, I want to show you that our estimate of the standard error reflects our assumption that the residuals are normally distributed (with mean zero and constant variance). I will show this to you within the context of problems #2 and #3 of the problem set.

On Wed. 19 July, I would like to review the Gauss-Markov assumptions and show you how the "Biagi Law" dataset violates those assumptions. Then I would like to show you how we can manipulate the data, so that it satisfies the Gauss-Markov assumptions.

On Thurs. 20 July, I would like to explore the "Biagi Law" dataset with you in class. The session will be a "lab session," so if possible, please bring a laptop computer to Thursday's session.

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First Assignments

(posted: 07 July 2017)

To prepare for class next week, please read chaps. 1-5 in the Stock-Watson textbook and the minimum wage and monopsonist problem. During the week, I plan to cover problem #4 of the problem set as an in-class exercise. And time-permitting, we may also cover problem #1.

Have a great weekend!

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Welcome to Econometrics

(posted: 06 July 2017)

Welcome to the course website. This site helps me organize the course. I hope you find it helpful.

I have posted a copy of the syllabus. Please review it and please look at the notes and course materials that I have posted below. I have also prepared a problem set for you. We will discuss the solutions to these problems in class.

Please acquire a copy of the Stock and Watson textbook and the Kennedy textbook as soon as possible. To begin the course, I would like to start with a review of statistics and probability, so please read chaps. 1, 2 and 3 in the Stock and Watson textbook before our next class session. To refresh your memory of statistics, you may want to look at my statistics course.

datasets

You must do econometrics to learn econometrics. A textbook is helpful, but not sufficient. To learn econometrics, you must actively explore a dataset.

The best dataset to give you is the dataset that I am most passionate about. I want to know how employment protections affect the employment opportunities available to workers.

This is a personal issue for me, but it's also an issue that affects you, your family and your friends, so together let's explore the data and find out how labor law shapes the career opportunities available to you.

So as a starting point for discussion and as an introduction to econometrics, please read my "Analysis of the 'Biagi Law.'" It tests an important null hypothesis and the dataset that the paper explores is one of the datasets that we will explore together this semester.

Then to place the discussion in an American context, please read John Schmitt's (2013) paper on why the minimum wage has no discernible effect on employment.

Having identified an avenue of inquiry, we must place it in a theoretical context to, so please read the wikipedia article on the minimum wage and please study my "minimum wage and the monopsonist" problem.

With theory and data in hand, we will then test the null hypothesis that the minimum wage does not have a significant effect on employment rates.

software

To conduct a statistical analysis (like the one just described), you will need to install a few (open source) statistical and mathematical software programs on your computer.

Gretl is a great statistical software package for learning econometrics. It has an simple interface and ships with sample datasets. It's a great learning tool and I highly recommend it. As you get better at data analysis, you will want a more flexible tool. I use the R language, which (as the name suggests) is a programming language. For mathematics, I use wxMaxima, which provides a graphical interface to Maxima, a computer algebra system that specializes in symbolic operations (as opposed to numerical computing).

Over the course of the semester, I will provide datasets for you to work with in Gretl. I will avoid asking you to write your own computer code, but to push you in the right direction, I will provide R scripts and wxMaxima notebooks for you to review (and tinker with).

take your time

Finally, please remember that we will cover these topics over the course of the semester. So please begin reading, but please do not rush through the reading. Take the time to understand what you are reading. And enjoy it because econometrics is a lot of fun.

I'm looking forward to working with you this semester.

Sincerely,
- Eryk Wdowiak

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