Category THE PATH FROM CAUSE TO EFFECT

Instrumental Variables

kwai chang caine: From a single action, you draw an entire universe.

Kung Fu, Season 1, Episode 1

Our Path

Statistical control through regression may fail to produce convincing estimates of causal

effects. Luckily, other paths lead to other things equal. Just as in randomized trials, the forces of nature, including human nature, sometimes manipulate treatment in a manner that obviates the need for controls. Such forces are rarely the only source of variation in treatment, but this is an obstacle easily surmounted. The instrumental variables (IV) method harnesses partial or incomplete random assignment, whether naturally occuring or generated by researchers. We illustrate this important idea three ways...

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EMPIRICAL NOTES

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Tables

Table 1.1 Health and demographic characteristics of insured and uninsured couples in the

NHIS

Data source. The 2009 NHIS data are from the Integrated Health Interview Series (IHIS) and are available at www. ihis. us/ihis/.

Sample. The sample used to construct this table consists of husbands and wives aged 26- 59, with at least one spouse working.

Variable definitions. Insurance status is determined by the IHIS variable UNINSURED. The health index is on a five-point scale, where 1 = poor, 2 = fair, 3 = good, 4 = very good, 5 = excellent; this comes from the variable HEALTH. Education is constructed from the variable EDUC and measures completed years of schooling. High school graduates and GED holders are assigned 12 years of schooling...

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Randomized Trials

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kwai chang caine: What happens in a man’s life is already written. A man must move through life as his destiny wills.

old man: Yet each is free to live as he chooses. Though they seem opposite, both are true.

Kung Fu, Pilot

Our Path

Our path begins with experimental random assignment, both as a framework for causal

questions and a benchmark by which the results from other methods are judged. We illustrate the awesome power of random assignment through two randomized evaluations of the effects of health insurance. The appendix to this chapter also uses the experimental framework to review the concepts and methods of statistical inference.

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The Elite Illusion

kwai chang caine: I seek not to know the answers, but to understand the questions.

Kung Fu, Season 1, Episode 14

The Boston and New York City public school systems include a handful of selective exam schools. Unlike most other American public schools, exam schools screen applicants on the basis of a competitive admissions test. Just as many American high school seniors compete to enroll in the country’s most selective colleges and universities, younger students and their parents in a few cities aspire to coveted seats at top exam schools. Fewer than half of Boston’s exam school applicants win a seat at the John D...

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Public-Private Face-Off

The C&B data set includes more than 14,000 former students. These students were admitted and rejected at many different combinations of schools (C&B asked for the names of at least three schools students considered seriously, besides the one attended). Many of the possible application/acceptance sets in this data set are represented by only a single student. Moreover, in some sets with more than one student, all schools are either public or private. Just as with groups C and D in Table 2.1. these perfectly homogeneous groups provide no guidance as to the value of a private education.

We can increase the number of useful comparisons by deeming schools to be matched if they are equally selective instead of insisting on identical matches...

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The Wages of Schooling

Legend tells of a legendary econometrician whose econometric skills were the stuff of legend.

Masters at Work

This chapter completes our exploration of paths from cause to effect with a multifaceted

investigation of the causal effect of schooling on wages. Good questions are the foundation of our work, and the question of whether increased education really increases earnings is a classic. Masters have tackled the schooling question with all tools in hand, except, ironically, random assignment. The answers they’ve fashioned are no less interesting for being incomplete.

6.1 Schooling, Experience, and Earnings

British World War II veteran Bertie Gladwin dropped out of secondary school at age 14, though he still found work as a radio communication engineer in the British intelligence service...

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