Suchergebnisse

The effects of heavy episodic drinking on studying and grades are modeled separately for college men and women using instrumental variable, simultaneous equation techniques with the 1993 & 1997 College Alcohol Studies data. Binge drinking lowers predicted grades by three tenths of a point for both genders. Current drinking is predicted to increase study hours for women; the effects for men are ambiguous. High school binging decreases study hours for women. The direct effect of drinking on grades remains negative under all robustness checks; the effect on study hours for women is robust to most specifications changes.

This article measures the effects of college drinking on study hours, grade point average (GPA), and major choice using simultaneous equation models and data from the 1993 College Alcohol Study. Binging and intoxication decrease GPA directly and indirectly by reducing study hours. Greater frequency of drinking increases the effect on study hours but not the total effect on GPA. College drinking increases the probability of choosing a business major but decreases the probability of choosing engineering. Simulations show that the effects of heavy drinking on GPA and major choice reduce future weekly earnings by between 0.3 and 9.8%.

AbstractBackgroundBehavioral responses to the COVID‐19 pandemic have become highly polarized, and public health initiatives often try to use different frames to influence behavior. If the polarization of behaviors is related to differences in responses to frames, then different health messages could be targeted to different groups to influence behavior.ObjectiveTo determine whether risk preferences and susceptibility to gain/loss frames have been affected by COVID‐19 and whether they differ along partisan lines.MethodsUsing repeated cross‐sectional data from a nationally representative dataset in the United States replicating the disease outbreak scenario collected before and after the onset of COVID‐19, we test whether responsiveness to the gain/loss frames has changed over time and whether the responsiveness varies by political affiliation.ResultsThe experimental results show that the risk preferences of the U.S. population is very susceptible to the framing of
choices, consistent with the literature finding risk loving preferences under the loss frame and risk aversion under the gain frame. However, the experience of COVID‐19 does not appear to have changed the responsiveness, nor are there
significant differences between conservatives/Republicans and liberals/Democrats.ConclusionTargeting different partisan groups with different risk‐related message frames is unlikely to be effective at altering behaviors.

Abstract
This paper examines representatives' voting on the HEALTH Act of 2003, which proposed a limit on noneconomic damages in medical malpractice lawsuits. The estimates show that the more campaign contributions a representative received from law firm PACs, the less likely he or she was to vote for the bill, while money from insurance and health care industry PACs increased the likelihood of an aye vote. These effects remain after controlling for the endogeneity of campaign contributions. Other factors affecting voting decisions include party affiliation, representative ideology, whether or not the representative was an attorney, the change in state malpractice premiums and payouts, and the change in the number of doctors in the state. There is no strong evidence that the AMA's strategy of naming certain states as being in "crisis" increased the probability that representatives from those states supported the bill.

Objective. This article investigates the extent to which opposing candidates for the U.S. House of Representatives adopt differing policy stances and examines explanations for policy divergence.Methods. We use a Congressional Quarterly survey of 1996 House candidates to measure policy divergence on eight issues. We then test explanations for this divergence: party pressures, primaries, third‐party candidates, campaign contributions, candidate preferences, and uncertainty.Results. Primaries, third‐party challenges, and contributions play little role in explaining policy divergence. We find that party and candidate preferences contribute to differences in the policy platforms of opposing candidates while uncertainty weakens the pressure for policy convergence.Conclusion. Imperfect information weakens pressure on candidates to adopt positions favored by the majority of voters in a district. This lack of pressure allows candidates to indulge their personal and party preferences in taking policy stances.

Objective. This article investigates the extent to which opposing candidates for the U.S. House of Representatives adopt differing policy stances & examines explanations for policy divergence. Methods. We use a Congressional Quarterly survey of 1996 House candidates to measure policy divergence on eight issues. We then test explanations for this divergence: party pressures, primaries, third-party candidates, campaign contributions, candidate preferences, & uncertainty. Results. Primaries, third-party challenges, & contributions play little role in explaining policy divergence. We find that party & candidate preferences contribute to differences in the policy platforms of opposing candidates while uncertainty weakens the pressure for policy convergence. Conclusion. Imperfect information weakens pressure on candidates to adopt positions favored by the majority of voters in a district. This lack of pressure allows candidates to indulge their personal & party preferences in taking policy stances. 4 Tables, 31 References. Adapted from the source document.

AbstractWe show the impact of migration type on real wages over time. We create a migration and earnings history from the National Longitudinal Survey of Youth over the period 1979–2002. We estimate the effects of primary, onward, and two types of return migration on real wages using a panel data model with individual, location, and time fixed effects. Panel data are well suited for the study of the returns to U.S. internal migration because the influence of migration on wages has been found to occur years after the event. We differentiate return migration into two types: return to a location with ties that form a geographical anchor ("home") and return to a prior place of work. We find that real wage growth varies by migration type. Education attainment is a significant factor in real wage growth. Our results show that onward migration is an important channel by which the monetary rewards to a college education are manifested.