Iatrogenic Specification Error: A Cautionary Tale of Cleaning Data

It is common in empirical research to use what appear to be sensible rules of thumb for cleaning data. Measurement error is often the justification for removing (trimming) or recoding (winsorizing) observations whose values lie outside a specified range. This paper considers identification in a linear model when the dependent variable is mismeasured. The results examine the common practice of trimming and winsorizing to address the identification failure. In contrast to the physical and laboratory sciences, measurement error in social science data is likely to be more complex than simply additive white noise. We consider a general measurement error process which nests many processes including the additive white noise process and a contaminated sampling process. Analytic results are only tractable under strong distributional assumptions, but demonstrate that winsorizing and trimming are only solutions for a particular class of measurement error processes. Indeed, trimming and winsorizing may induce or exacerbate bias. We term this source of bias Iatrogenic' (or econometrician induced) error. The identification results for the general error process highlight other approaches which are more robust to distributional assumptions. Monte Carlo simulations demonstrate the fragility of trimming and winsorizing as solutions to measurement error in the dependent variable.

GDP & Beyond – die europäische Perspektive

Earnings nonresponse in the Current Population Survey is roughly 30% in the monthly surveys and 20% in the annual March survey. Even if nonresponse is random, severe bias attaches to wage equation coefficient estimates on attributes not matched in the earnings imputation hot deck. If nonresponse is ignorable, unbiased estimates can be achieved by omitting imputed earners, yet little is known about whether or not CPS nonresponse is ignorable. Using sample frame measures to identify selection, we find clear-cut evidence among men but limited evidence among women for negative selection into response. Wage equation slope coefficients are affected little by selection but because of intercept shifts, wages for men and to a lesser extent women are understated, as are gender wage gaps. Selection is less severe among household heads/co-heads than among other household members.response bias, imputation, earnings nonresponse, gender gap, CPS

Education Pays Everywhere!

Economists and other researchers have long demonstrated the relationship between education and earnings. In this brief, we focus on the relationship between educational attainment and earnings in the state of Kentucky. Our results, in many ways, are unsurprising, as the old ad campaign said, “Education Pays.” What may be surprising is that we demonstrate that education pays not only in the big cities of Lexington and Louisville, but also in the more rural parts of the state, such as eastern Kentucky and western Kentucky

Education for Your Health!

The health of the people of Kentucky is of high concern for policymakers and citizens alike. Individuals want to live healthy, productive lives, while policymakers recognize that chronic illnesses cost the state in myriad ways. In this brief, we examine the link between educational attainment and health outcomes. We focus on two groups of health outcomes. The first are behavioral and include choices: tobacco use, alcohol use, obesity, and exercise. The second group are outcomes highly associated with these behaviors: heart attack, angina, stroke, and diabetes. The Center for Disease Control (CDC) estimates that these four diseases may cost Kentuckians over $5 billion annually in lost days at work and medical bills. Our simulations suggest that if Kentucky were to achieve education levels comparable to the U.S., we could reduce those costs by nearly$200 million per year

Want a Job? Get a College Degree

While it is well known that a positive relationship exists between educational attainment and earnings for those who are in the labor market, an important part of how education impacts the well-being of families in Kentucky is the access to employment that it provides. In this brief, we examine the relationship between education and two measures of employment status: unemployment and labor force participation. What we find is quite striking: not only do those with higher education experience less unemployment, they are far more likely to be participating in the labor market. Education leads to better access to employment

How to Raise State Revenue without Raising Taxes

A positive relationship exists between educational attainment and earnings, which has been well established in the literature through multiple studies. This, in turn, influences the revenues generated for the state of Kentucky through the personal income tax. We predict even the modest change of increasing Associate’s and Bachelor’s degree holders by 1% would increase revenue by $37 million. Kentucky loses between$300 million and $500 million in state tax revenues every year because our educational attainment is lower than the national average

A Measure of the Economic Impact of Keeneland Racing and Sales on Lexington-Fayette County

Keeneland is an important Lexington Institution. This report shows that Keeneland draws individuals into Fayette County who spend money not only at Keeneland but in the city itself. We measure the economic impact of this spending on the local economy. For our initial study, we considered spending by patrons at the 2014 Fall Meet, the September Yearling Sale and the November Breeding Stock Sale. Based upon these findings, we were also able to assess the impact of the Spring Race Meeting, January Horses of All Ages Sale and the April Two-Year-Olds in Training Sale

Impact of Education on Medicaid Eligibility

The individual mandate of the Affordable Care Act (ACA) coupled with the Medicaid expansion in Kentucky makes reducing Medicaid eligibility rates of crucial importance. This brief examines the link between education and eligibility for Medicaid for the citizens of Kentucky. In general, the relationship is nearly mechanical in that higher education leads to higher incomes. Since income is the key determining factor of Medicaid eligibility, and because of the individual mandate eligibility is mostly equivalent to participation, our estimates show that higher education reduces the likelihood that an adult will be on Medicaid or have children and family members on Medicaid. Our results suggest that the state of Kentucky could reduce Medicaid costs by $27 million if we were to increase our education levels modestly and as much as$200 million if we can achieve education levels comparable to the U.S