How do we count the number of poor people in America? How do we operationalize "poor"? That is the psychometric topic of this opinion piece from the New York Times (.pdf of same here).
This article outlines several ways of defining poor in America, including:
In addition to providing a real life example of how one goes about operationalizing a variable, I think this article demonstrates how we can fib with statistics in a manner that doesn't require dirty data collection or outright lying: We make a logical argument to use a certain dependent variable (typically, one that supports our cause) and we roll with it. For example, an up and coming presidential candidate may be inclined to use a poverty rate that inflates the number while an incumbent president is aided by a more conservative estimate.
This article outlines several ways of defining poor in America, including:
1)"Jencks’s methodology is simple. He starts with the official 2013 United States poverty rate of 14.5 percent. In 2013, the government determined that 45.3 million people in the United States were living in poverty, or 14.5 percent of the population.Jencks makes three subtractions from the official level to account forexpanded food and housing benefits (3 percentage points); the refundable earned-income tax credit and child tax credit (3 points); and the use of the Personal Consumption Expenditures index instead of the Consumer Price Index to measure inflation (3.7 percentage points)."
2) "Other credible ways to define poverty paint a different picture. One is to count all those living with less than half the median income as poor. "
3)"Timothy Smeeding, a professor of public affairs and economics at the University of Wisconsin-Madison, notes in an email that that “the official poverty line was about half of median income in 1963, but is less than 30 percent of median now because of general economic growth.”
4) Other debates included in the article is how to measure and apply inflation in order to understand how far you can stretch a dollar at different points in time.This article also discusses the relative success of different governmental programs in combating poverty, and how these must be taken into account when selecting the best way to measure poverty.
In addition to providing a real life example of how one goes about operationalizing a variable, I think this article demonstrates how we can fib with statistics in a manner that doesn't require dirty data collection or outright lying: We make a logical argument to use a certain dependent variable (typically, one that supports our cause) and we roll with it. For example, an up and coming presidential candidate may be inclined to use a poverty rate that inflates the number while an incumbent president is aided by a more conservative estimate.