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Our popular course Introduction to QuantLib Development will be taking place June 18-20th, 2018.


Econometrics Beat's Blog

Handbook of Quantile Regression

July 15, 2018 Comments (0)

Quantile regression is a powerful and flexible technique that is widely used by econometricians and other applied statisticians. In modern terms we tend to date it back to the classic paper by Koenker and Bassett (1978). Recently, I reviewed the Handbook of Quantile Regression. This edited volume comprises a number of important, original, contributions to the quantile regression literature. The various chapters cover a wide range of topics that extend the basic quantile regression set-up. You...

What's in a Journal Name?

July 14, 2018 Comments (0)

Back in 2011 I put together a very light-hearted working paper titled, What's in a (Journal) Name? Here's the associated link. That paper addressed the (obviously) important question: "Is there a a correlation between the ranking of an economics journal and the length of the journal's title?" I analyzed a sample of 159 academic economics journals. Although there was no significant association between journal quality and journal title length for the full sample of data, I did find that...

More on Regression Coefficient Interpretation

July 13, 2018 Comments (0)

I get a lot of direct email requests from people wanting help/guidance/advice of various sorts about some aspect of econometrics or other. I like being able to help when I can, but these requests can lead to some pitfalls -  for both of us. More on that in a moment. Meantime, today I got a question from a Ph.D student, "J", which was essentially the following: " Suppose I have the following regression model              log(yi) = α + βXi + εi ...

Interpreting Dummy Variable Coefficients After Non-Linear Transformations

July 6, 2018 Comments (0)

Dummy variables - ones that take only the values zero and one - are commonly used as regressors in regression models. I've devoted several posts to discussing various aspects of such variables, notably here, but also here, here, and here. When the regression model in question is linear, in both the variables and the parameters, the interpretation of coefficient of such a dummy variable is simple. Suppose that the model takes the form:     yi = α + β Di + Σj γj Xji + εi ...

Some Reading Suggestions for July

July 5, 2018 Comments (0)

Some summertime reading:Chen, T., DeJuan, J., & R. Tian, 2018. Distributions of GDP across versions of  the Penn World Tables: A functional data analysis approach. Economics Letters, in press. Clements, K.W., H. Liu, & Y. Tarverdi, 2018. Alcohol consumption, censorship and misjudgment. Applied Economics, onlineJin, H., S. Zhang, J. Zhang,& H. Hao, 2018. Modified tests for change points in variance in the possible presence of mean breaks. Journal of Statistical...

The Series of Unsurprising Results in Economics (SURE)

July 5, 2018 Comments (0)

Andrea Menclover of the University of Canterbury (New Zealand) has recently founded the SURE Journal, whose aims and scope are as follows: 'The Series of Unsurprising Results in Economics (SURE) is an e-journal of high-quality research with “unsurprising” findings. We publish scientifically important and carefully-executed studies with statistically insignificant or otherwise unsurprising results. Studies from all fields of Economics will be considered. SURE is an open-access journal and...

Dummy Variables in a Semilogarithmic Regression: Exact Distributional Results

July 5, 2018 Comments (0)

For better or worse, semilogarithmic regression models are used a lot in empirical economics.  It would be nice to think that this is because the researcher found that a logarithmic transformation of the model's dependent variable led to residuals that were more "normally" distributed than without the transformation. Unfortunately, however, it's often just "for convenience". With this transformation, the estimates of the regression coefficients have a simple interpretation, as explained...

Shout-Out for Marc Bellemare

July 5, 2018 Comments (0)

If you don't follow Marc Bellemare's blog (shame on you - you should!), then you may not have caught up with his recent posts relating to his series of lectures on "Advanced Econometrics - Causal Inference With Observational Data" at the University of Copenhagen in May of this year. Marc is keeping us all on tenterhooks by "releasing" the slides for these lectures progressively - smart move! So far, the first five of the eight lectures in the series are now available for downloading:Lecture...

Suggested Reading for June

June 1, 2018 Comments (0)

Colussi, T., 2018. Social ties in academia: A friend is a treasure. Review of Economics and Statistics, 100, 45-50.Dette, H., K. Möllenhoff, S. Volgushev, & F. Bretz, 2018. Equivalence of regression curves. Journal of the American Statistical Association, online.Kumbhaker, S. C., C. F. Parmeter, & V. Zelenyuk, 2018. Stochastic frontier analysis: Foundations and advances. Working paper No. WP02/2018, Centre for Efficiency and productivity Analysis, School of Economics, University of...

The Uniqueness of the Cointegrating Vector

May 31, 2018 Comments (0)

Suppose that we have (only) two non-stationary time-series, X1t and X2t (t = 1, 2, 3, .....). More specifically suppose that both of these series are integrated of order one (i.e., I(1)). Then there are two possibilities - either X1 and X2 are cointegrated, or they aren't. You'll recall that if they are cointegrated, then there is a linear combination of X1 and X2 that is stationary. Let's write this linear combination as Zt = (X1t + αX2t). (We can normalize the first "weight" to...