Posts tagged ‘econometrics’

October 8, 2013

Remarks on Chen and Pearl on causality in econometrics textbooks

Bryant Chen and Judea Pearl have published a interesting piece in which they critically examine the discussions (or lack thereof) of causal interpretations of regression models in six econometrics textbooks. In this post, I provide brief assessments of the discussion of causality in nine additional econometrics texts of various levels and vintages, and close with a few remarks about causality in textbooks from the perspective of someone who does, and teaches, applied econometrics. Like Chen and Pearl, I find some of these textbooks provide weak or misleading discussion of causality, but I also find one very good and one excellent discussion in relatively recent texts. I argue that the discussion of causality in econometrics textbooks appears to be improving over time, and that the oral tradition in economics is not well-reflected in econometrics textbooks.

The Chen and Pearl paper has been around for a while in working paper form and recently came out in the Real World Economics Review, also available here from the authors with much clearer typesetting.

The additional textbooks I discuss below are: Amemiya (1985), Kmenta (1986), Davidson and MacKinnon (1993), Gujarati (1999), Hayashi (2000), Wooldridge (2002), Davidson and MacKinnon (2004), Deilman (2005), and Cameron and Trivedi (2005).

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October 31, 2012

The intuition of robust standard errors

Commonly econometricians conduct inference based on covariance matrix estimates which are consistent in the presence of arbitrary forms of heteroskedasticity; the associated standard errors are referred to as “robust” (also, confusingly, White, or Huber-White, or Eicker-Huber-White) standard errors. These are easily requested in Stata with the “robust” option, as in the ubiquitous

reg y x, robust.

Everyone knows that the usual OLS standard errors are generally “wrong,” that robust standard errors are “usually” bigger than OLS standard errors, and it often “doesn’t matter much” whether one uses robust standard errors.  It is whispered that there may be mysterious circumstances in which robust standard errors are smaller than OLS standard errors. Textbook discussions typically present the nasty matrix expressions for the robust covariance matrix estimate, but do not discuss in detail when robust standard errors matter or in what circumstances robust standard errors will be smaller than OLS standard errors. This post attempts a simple explanation of robust standard errors and circumstances in which they will tend to be much bigger or smaller than OLS standard errors.

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October 7, 2012

What do we know about the effect of income inequality on health?

This post briefly surveys some of the methods and results in the literature on health and income inequality, closing with some remarks on problems with the existing literature and where future research may take us. It is not intended as anything resembling a comprehensive survey; Lynch et al (2004) provides a useful review of the empirical literature up to that time.

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October 24, 2011

Patient knowledge, antibiotic abuse, and impolite physicians

Antibiotic overuse causes great social harm yet is largely absent from public discussion of drug policy. There is a textbook external effect of an antibiotic prescription: the more antibiotics are used, the higher the risk we all face of resistant infections. As a result, there tends to be too much use of antibiotics. There have been ongoing efforts to reduce use of antibiotics, particularly in the context of treating respiratory infections, in part by educating GPs, the supply side of the relationship, on appropriate use.

In “Patient knowledge and antibiotic abuse: Evidence from an audit study in China” Janet Currie, Wanchuan Lin, and Wei Zhang consider the demand side of the relationship: what is the effect of patient knowledge on antibiotic use?

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October 3, 2011

Will Yelp kill Applebee’s?

A new working paper by Michael Luca estimates the effect of Yelp reviews on Seattle restaurant revenues. Disentangling causality here is difficult, as even if reviews have no effect on revenues we would expect to observe reviews and revenues both moving with changes in underlying relative quality. Luca exploits a quirk in the way Yelp presents information: average scores are reported rounded in 0.5 star bins on a 5 star scale. For example, underlying average scores of 2.76 and 3.24 are both reported as “3 stars,” but a good review which bumps the average up to 3.25 bumps the reported score up to 3.5 stars. The estimates show that Yelp reviews do have a substantial effect on revenues.

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October 1, 2011

Chetty, Friedman, and Saez on detecting knowledge differences with observational data

Models usually implicitly assume that people are aware of the incentives they face. People in a labor supply model, for example, usually make their decisions based on the actual schedule, not their subjective impression of the schedule. But many people may not even be aware of changes in income taxes schedules: how can they then respond to changes in the schedule? In current research, Raj Chetty, John Friedman, and Emmanuel Saez turn this apparent difficulty into an advantage. They estimate the causal effect of changes in an aspect of the income tax schedule on labor supply. Since the policy they study is Federal, there is not much variation to identify the effects of interest using traditional methods, but the authors show how to recover regional variation in knowledge of the schedule. The interaction of knowledge and the schedule then varies across regions and time even though the schedule only varies over time, so there’s lots more variation to identify the effect of the schedule on labor supply.

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September 27, 2011

Manski and Pepper on the deterrent effect of the death penalty

Chuck Manski and John Pepper have issued a new working paper on the effect of the death penalty on homicide rates. If you’re interested in the issue the paper is of course something you should read, but it’s also a great, readable, and not overly technical exposition by way of example of some of Manski’s work over the last couple of decades on partial identification.

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September 5, 2011

Trucks and SUVs should be heavily taxed.

Large, heavy vehicles are safe, as everyone knows. If you’re going to be in an accident, would you rather be in a Miata or an Escalade? More large vehicles on the road make us safer, and we should worry about anything which reduces vehicle sizes. Notably, fuel economy standards decrease vehicle size, so we will become less safe as fuel economy standards become more strict. See for example Crandall and Graham (1989).

Or so conventional wisdom goes, but it turns out the truth is more subtle, according to recent research.

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August 30, 2011

Did a Liberal MLA cause a change in district HST support?

Local linear sharp RD estimate: -0.12%, z=-0.05.

Filed under: Exercises in rigorous, pointless causal analyis.

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August 29, 2011

Which districts voted against the HST?

Stephen Gordon laments British Columbians’ failure to ratify the HST, which will reduce our standard of living in B.C. for many years.The case in favour of the HST was overwhelming and no expert opposed the HST in public. Which people voted against their own best interests?

The Globe and Mail’s Chris Hannay presents some graphs showing proportion voting for the HST against certain demographic characteristics at the electoral district level. Districts with higher incomes tended to vote to keep the HST:


and a similar pattern holds for education: unconditionally, districts with more educated people were more likely to vote to keep the HST. Hannay implies that these effects are really the same effect: more educated people also tend to earn more, so the education—vote correlation is just another way of seeing that higher income people voted in their class interest.

An alternate explanation draws on my post from a couple of days ago on education and beliefs that economists understand the effects of taxation on the economy: uneducated people tend to place low weight on expert analysis, certainly including economic analysis. The direct impact of the HST on prices was easy for everyone to observe—they’re printed on cash register receipts. But the indirect effects, the effects on changes in embedded prices, were hard to observe. The HST was not in place long enough to observe effects on investment and growth. One had to yield to expert opinion to draw the correct conclusion that the HST is good policy.

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