Summary of Joshua Angrist & Jörn-Steffen Pischke's Mastering 'Metrics

By IRB Media

Please note: This is a companion version & not the original book. Book Preview:

#1 Without universal health insurance, Americans are less healthy than Canadians, who spend just two-thirds as much on care.

#2 Americans with health insurance are healthier than those without. Table 1. 1 Health of Uninsured and Insured Americans Note: NHIS 2009 data. Health index is based on the 5-to-1 scale: excellent health is given a score of 5, while poor health is given a score of 1. But the story isn’t so simple. First, a word about the statistical technique that produced this table: logistic regression. logistic regression is one method of statistical analysis that attempts to explain differences in an outcome variable between two groups by considering the variables in an inclusion/exclusion list: variables that predict whether a person has health insurance, or whether they are in the treatment group, and variables that predict the health index itself. The logistic regression model includes variables from the list in addition to other independent variables, and it models the dependent variable as a linear function of all these independent variables and their interactions. 4 The model is based on statistical theory and can be estimated using software like Stata, SPSS, or R. -> The National Health Interview Survey asks Americans if their health is excellent, very good, good, fair, or poor. Those with health insurance are healthier than those without, a difference of about.

#3 If you want to understand the link between health insurance and health, you must compare people with and without insurance in a way that takes other factors into account.

#4 To understand the link between health insurance and health, you must compare people with and without insurance in a way that takes other factors into account.

• Language: English
• Publisher: IRB Media
• Release date: Sep 15, 2022
• ISBN: 9798350029291

IRB Media

With IRB books, you can get the key takeaways and analysis of a book in 15 minutes. We read every chapter, identify the key takeaways and analyze them for your convenience.

Book preview

Insights on Joshua Angrist & Jörn-Steffen Pischke's Mastering Metrics

Contents

Insights from Chapter 1

Insights from Chapter 2

Insights from Chapter 3

Insights from Chapter 4

Insights from Chapter 5

Insights from Chapter 6

Insights from Chapter 1

#1

The ACA requires Americans to buy health insurance, with a tax penalty for those who don’t voluntarily buy in. The question of the proper role of government in the market for health care has many angles. One is the causal effect of health insurance on health.

#2

The National Health Interview Survey, an annual survey of the U. S. population with detailed information on health and health insurance, asked respondents if their health was excellent, very good, good, fair, or poor. Those with health insurance were healthier than those without, a difference of about. 3 in the index for men and. 4 in the index for women.

#3

The problem with comparing people with and without health insurance is that they are not apples to apples. People with health insurance are better educated, have higher income, and are more likely to be working than the uninsured.

#4

The Frostian two-roads metaphor is used to explain the connection between insurance and health. The outcome variable, Y, is recorded in our data. But, facing the choice of whether to pay for health insurance, person i has two potential outcomes, only one of which is observed.

#5

The comparison between Khuzdar and Maria tells us little about the causal effects of their choices. This can be seen by linking observed and potential outcomes.

#6

The difference in average health by insurance status is the difference between the average health of those with insurance and those without insurance, plus the average causal effect of insurance, which is κ.

#7

The subtle role played by information like that shown in panel B of Table 1. 1 is that it suggests that the groups being compared might differ in ways that we can’t see. Even in a sample of insured and uninsured people with the same education, income, and employment status, the uninsured might have higher values of Y0i.

#8

The Law of Large Numbers states that the sample average can be brought as close as we like to the average in the population from which it is drawn simply by enlarging the sample.

#9

When Di