The following is an excerpt from "The Oregon Experiment- Effects of Medicaid on Clinical Outcomes," by Baicker et al. (2013). Fill in the blank identifying the method used in this paper given the description in the paragraph (I've given you a hint on the key points by italicizing a few phrases): "Adults randomly selected in the lottery were given the option to apply for Medicaid, but not all persons selected by the lottery enrolled in Medicaid (either because they did not apply or because they were deemed ineligible). Lottery selection increased the probability of Medicaid coverage during our study period by 24.1 percentage points (95% confidence interval [CI], 22.3 to 25.9; P<0.001). The subgroup of lottery winners who ultimately enrolled in Medicaid was not comparable to the overall approach... to group of persons who did not win the lottery. We, therefore, used a standard_ estimate the causal effect of enrollment in Medicaid. Intuitively, since the lottery increased the chance of being enrolled in Medicaid by about 25 percentage points, and we assumed that the lottery affected outcomes only by changing Medicaid enrollment, the effect of being enrolled in Medicaid was simply about 4 times (i.e., 1 divided by 0.25) as high as the effect of being able to apply for Medicaid. This yielded a causal estimate of the effect of insurance coverage." Baicker, K., Taubman, S. L., Allen, H. L., Bernstein, M., Gruber, J. H., Newhouse, J. P., ... & Finkelstein, A. N. (2013). The Oregon experiment-effects of Medicaid on clinical outcomes. New England Journal of Medicine, 368(18), 1713-1722. regression discontinuity design (RDD) instrumental variables (IV) difference-in-difference (DID) ООО

The Beveridge model in the United Kingdom uses queues or waiting lists to ration care, rather than prices.

The following is an excerpt describing the Oregon Medicaid lottery: In 2008, Oregon implemented a limited expansion of its Medicaid program for low-income adults through a lottery, selecting names from a waiting list to fill a limited number of available spots. Those selected had the opportunity to apply for Medicaid and to enroll if they met eligibility requirements. Based on the description, you might describe the Oregon Medicaid lottery as a: randomized experiment "As if random" natural experiment a true natural experiment

Indicate whether the statement is true or false, and justify your answer.Results from the Oregon Medicaid Experiment suggest that having health insurance has a positive impact on health status.

Which of the following hypotheses argues that a third variable, "patient", determines both health and wealth: Fuchs hypothesis efficient producer hypothesis thrifty phenotype hypothesis allostatic load hypothesis access to care hypothesis

Suppose that Hubert, an economist from an AM talk radio program, and Kate, an economist from a school of industrial relations, are arguing over health insurance. The following dialogue shows an excerpt from their debate: Kate: A popular topic for debate among politicians as well as economists is the idea of providing government assistance for health benefits. Hubert: I think it is oppressive for the government to tax people who take care of themselves in order to pay for health insurance for those who are obese. Kate: I disagree. I think government funding of health insurance is useful to ensure basic fairness.   The disagreement between these economists is most likely due to (DIFFERENCE IN SCIENTIFIC JUDGEMENT, DIFFERENCE IN VALUES, DIFFERENCE BETWEEN PERCEPTION VERSUS REALITY)   .   Despite their differences, with which proposition are two economists chosen at random most likely to agree? A. Employers should not be restricted from outsourcing work to foreign nations.…

Demand for medical services is price inelastic (Absolute value of price elasticity of demand is less than 1 and greater than zero). Medical services are different from most other goods and services in that the person who determines the demand (the patient) is not the person who makes the payment (payment is made by the insurance company). How does this affect the price elasticity of demand for medical services (increase it or decrease it)? You may assume that this question only refers to people who have health insurance. Ignore co-payments and deductibles and any other out-of-pocket expenses. Please give an explanation.

In the early 2000s, the state of Massachusetts in the U.S. implemented a health reform aimed at enrolling people without health insurance into an insurance plan. The reform required people without health insurance (at least those who could afford it) to buy insurance, and put in place penalties on those who nevertheless chose not to buy insurance. Below is the abstract of a recent National Bureau of Economic Research working paper entitled “Health Reform, Health Insurance, and Selection: Estimating Selection into Health Insurance Using the Massachusetts Health Reform” by Martin Hackmann, Jonathan Kolstad, and Amanda Kowalski. The authors conducted a study of the effects of the Massachusetts reform. They write:   We implement an empirical test for selection into health insurance using changes in coverage induced by the introduction of mandated health insurance in Massachusetts. Our test examines changes in the cost of the newly insured relative to those who were insured prior to the…

Huskamp et. al (2003) showed decreases in copayments are associated with increases in adherence. This is an example of... Increasing adherence with methadone-based reinforcement Increasing adherence with prize-based reinforcement Increasing adherence with traditional economics Increasing adherence with remote voucher-based reinforcement

The following is the abstract from the paper, "The Impact of Health Insurance on Preventive Care and Health Behaviors: Evidence from the First Two Years of the ACA Medicaid Expansions," by Simon, Soni, Cawley (2017). The U.S. population receives suboptimal levels of preventive care and has a high prevalence of risky health behaviors. One goal of the Affordable Care Act (ACA) was to increase preventive care and improve health behaviors by expanding access to health insurance. This paper estimates how the ACA-facilitated state-level expansions of Medicaid in 2014 affected these outcomes. Using data from the Behavioral Risk Factor Surveillance System, and a difference-in-differences model that compares states that did and did not expand Medicaid, we examine the impact of the expansions on preventive care (e.g., dental visits, immunizations, mammograms, cancer screenings), risky health behaviors (e.g., smoking, heavy drinking, lack of exercise, obesity), and self-assessed health. We find…