Mostly Harmless Econometrics: An Empiricist's Companion

By Joshua D. Angrist; Jörn-Steffen Pischke | Go to book overview

Chapter 7
Quantile Regression

Here's a prayer for you. Got a pencil? … [Protect me from
knowing what I don't need to know. Protect me from even
knowing that there are things to know that I don't know.
Protect me from knowing that I decided not to know about
the things I decided not to know about. Amen.] There's
another prayer that goes with it. [Lord, lord, lord. Protect
me from the consequences of the above prayer.]

Douglas Adams, Mostly Harmless

Rightly or wrongly, 95 percent of applied econometrics is concerned with averages. If, for example, a training program raises average earnings enough to offset the costs, we are happy. The focus on averages is partly because it's hard enough to produce good estimates of average causal effects. And if the dependent variable is a dummy for something like employment, the mean describes the entire distribution. But many variables, such as earnings and test scores, have continuous distributions. These distributions can change in ways not revealed by an examination of averages; for example, they can spread out or become more compressed. Applied economists increasingly want to know what is happening to an entire distribution, to the relative winners and losers, as well as to averages.

Policy makers and labor economists have been especially concerned with changes in the wage distribution. We know, for example, that flat average real wages are only a small part of what's been going on in the labor market for the past 25 years. Upper earnings quantiles have been increasing, while lower quantiles have been falling. In other words, the rich are getting richer and the poor are getting poorer. Recently,

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Mostly Harmless Econometrics: An Empiricist's Companion
Table of contents

Table of contents

  • Title Page iii
  • Contents v
  • Figures vii
  • Tables ix
  • Preface xi
  • Acknowledgments xv
  • Organization of This Book xvii
  • Part I - Preliminaries 1
  • Chapter 1 - Questions About Questions 3
  • Chapter 2 - The Experimental Ideal 11
  • Part II - The Core 25
  • Chapter 3 - Making Regression Make Sense 27
  • Chapter 4 - Instrumental Variables in Action: Sometimes You Get What You Need 113
  • Chapter 5 - Parallel Worlds: Fixed Effects, Differences-In-Differences, and Panel Data 221
  • Part III - Extensions 249
  • Chapter 6 - Getting a Little Jumpy: Regression Discontinuity Designs 251
  • Chapter 7 - Quantile Regression 269
  • Chapter 8 - Nonstandard Standard Error Issues 293
  • Last Words 327
  • Acronyms and Abbreviations 329
  • Empirical Studies Index 335
  • References 339
  • Index 361
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