Econometrics

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Updated Analysis and Scripts

(posted: 18 April 2017)

I have updated my "Analysis of the 'Biagi Law'" so that it includes some of the topics that we have discussed in class and will discuss in class after the break.

The new version adds the minimum wage to my analysis of the OECD data. And to account for serial correlation over space and time, the new version also adds a SARAR model to my analysis of the Italian data.

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Time-Series

(posted: 13 April 2017)

When we return from Spring Break, we will begin discussing time-series. To prepare for those discussions, please read Stock-Watson chaps. 12, 13 and 14 and please read Kennedy chaps. 10 and 19. And for a good set of notes on serial correlation, take a look at Sharyn O’Halloran's notes. I particularly like the way she shows how serial correlation may occur over space as well as time.

To prepare for our discussion, I have updated the R script that I use to analyze the Italian data. To account for serial correlation over time, the new script tests for a unit root in the residuals. And to account for serial correlation over space, the new script also includes a "Spatial Autoregressive Model with Autoregressive Disturbances" (SARAR).

Enjoy the break! See you soon.

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Course Projects

(posted: 13 April 2017)

The purpose of the course project is to help you "learn by doing." In other words, you will learn more about econometrics by conducting an econometric analysis than by reading the textbook.

If you all learned how to conduct an econometric analysis, that would be "good." If you all learned how to assemble a dataset and conduct an econometric analysis, that would be "perfect." But assembling a dataset is consuming too much of time, so let's all focus on doing a "good" job (not a "perfect" job).

So a good place to start is with one of the datasets that I have already given you. For example, you might visit stats.oecd.org, download some additional variables and append them to the OECD dataset.   (Hint:   At my econometrics videos page, I have posted instructions on how to append data in Gretl).

Or if you're interested in finance, you may wish to develop your knowledge of time-series. For example, you might want to know how stock prices respond to interest rate changes. If so, then you might download and analyze a dataset with such variables. Or you might explore the time-series questions in the Italian data. Can you obtain an estimate of the Phillips Curve that does not suffer from serial correlation of the residuals?

Or as an alternative to working with a conventional dataset, you may also conduct a statistical analysis of human language. I started developing some notes on the subject, but I never finished. So another good project would be to help me develop my text mining notes.

Regardless of which dataset you choose, the most important thing to do is think about the null hypotheses that you wish to test. For example, when working with the employment datasets, we want to know what factors affect the employment rate, so one null hypothesis that you might test is the null hypothesis that employment protection does not affect the employment rate. Another that you might test is the null hypothesis that the minimum wage does not affect the employment rate.

Assuming that you have rejected the null hypothesis that the minimum wage does not affect the employment rate, your next step might be to predict the effect that an increase in the minimum wage would have on the employment rate. So, for example, if the minimum wage rose 10 percent, how much would the employment rate rise/fall? What is the standard error of your estimate?

Work through these types of questions, then -- when you begin writing your paper -- imagine that you are an economist working for a government agency and your boss wants to know what actions they could take to increase the employment rate.

Should they increase the minimum wage? Should they protect workers from dismissal? Should they require all employment opportunities to be full-time, permanent jobs (as opposed to temporary and contract work)? Should they encourage workers to join a union?

What actions should they take? How much will those actions increase the employment rate? What is the standard error of your estimate?

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