Substance abuse treatment: what do we know? an economist's perspective

The substance abuse treatment literature has basically dealt with four important questions: 1) Is treatment effective? 2) Are all programs equally effective? 3) why do programs differ in their effectiveness? and 4) which treatments are most cost-effective?. This paper reviews the substance abuse literature around these four questions

A consistent estimator for the binomial distribution in the presence of "incidental parameters": an application to patent data

In this paper a consistent estimator for the Binomial distribution in the presence of incidental parameters, or fixed effects, when the underlying probability is a logistic function is derived. The consistent estimator is obtained from the maximization of a conditional likelihood function in light of Andersen's work. Monte Carlo simulations show its superiority relative to the traditional maximum likelihood estimator with fixed effects also in small samples, particularly when the number of observations in each cross-section, T, is small. Finally, this new estimator is applied to an original dataset that allows the estimation of the probability of obtaining a patent

Dollars and Performance: Treating Alcohol Misuse in Maine

If public funds are allocated efficiently, then an increase in funding should improve the performance of substance abuse treatment programs. In the data used in this paper, performance (measured as abstinence rates) and expenditures per patient are not positively correlated. One explanation is that funding is endogeneous, i.e. programs treating more difficult patients receive more funding. The data comes from all Maine´s outp/atient drug-free programs that received public funding between 1991 and 1994. After controlling for endogeneity, this paper concludes that the marginal impact of expenditures per patient on abstinence rates is small and statistically insignificantly different from zero.Publicad

SUBSTANCE ABUSE TREATMENT: WHAT DO WE KNOW? AN ECONOMIST’S PERSPECTIVE

The substance abuse treatment literature has basically dealt with four important questions: 1) Is treatment effective? 2) Are all programs equally effective? 3) why do programs differ in their effectiveness? and 4) which treatments are most cost-effective?. This paper reviews the substance abuse literature around these four questions.

Can we measure hospital quality from physicians' choices?

In this paper, we propose an alternative methodology for ranking hospitals based on the choices of Medical School graduates over hospital training vacancies. Our methodology is therefore a revealed preference approach. Our methodology for measuring relative hospital quality has the following desirable properties: a) robust to manipulation from hospital administrators; b) conditional on having enough observations, it allows for differences in quality across specialties within a hospital; c) inexpensive in terms of data requirements, d) not subject to selection bias from patients nor hospital screening of patients; and e) unlike other rankings based on experts' evaluations, it does not require physicians to provide a complete ranking of all hospitals. We apply our methodology to the Spanish case and find, among other results, the following: First, the probability of choosing the best hospital relative to the worst hospital is statistically significantly different from zero. Second, physicians value proximity and nearby hospitals are seen as more substitutable. Third, observable time-invariant city characteristics are unrelated to results. Finally, our estimates for physicians' hospital valuations are significantly correlated to more traditional hospital quality measures

A methodology to measure hospital quality using physicians' choices over training vacancies

In this paper, we propose an alternative methodology to rank hospitals based on the choices of Medical Schools graduates over training vacancies. We argue that our measure of relative hospital quality has the following desirable properties: a) robustness to manipulation from the hospital's administrators; b) comprehensiveness in the scope of the services analyzed; c) inexpensive in terms of data requirements, and d) not subject to selection biases. Accurate measures of health provider quality are needed in order to establish incentive mechanisms, to assess the need for quality improvement, or simply to increase market transparency and competition. Public report cards in certain US states and the NHS ranking system in the UK are two attempts at constructing quality rankings of health care providers. Although the need for such rankings is widely recognized, the criticisms at these attempts reveal the difficulties involved in this task. Most criticisms alert to the inadequate risk-adjustment and the potential for perverse consequences such as patient selection. The recent literature, using sophisticated econometric models is capable of controlling for case-mix, hospital and patient selection, and measurement error. The detailed data needed for these evaluations is, however, often unavailable to researchers. In those countries, such as Spain, where there is neither public hospital rankings nor public data on hospital output measures such as mortality rates our methodology is a valid alternative. We develop this methodology for the Spanish case. In a follow-up paper we will present results using Spanish data. In Spain graduates choose hospital training vacancies in a sequential manner that depends on their average grade. Our framework relies on three assumptions. First, high quality hospitals provide high quality training. Second, graduates are well informed decision makers who are well qualified to assess hospital quality. Third, they prefer to choose a high quality vacancy rather than a low quality one ceteris paribus. If these assumptions hold, then the first physicians to choose are likely to grab the best vacancies while the ones who choose last are stuck with the worst available. Thus, it is possible to infer from physicans' choices quality differentials amongst hospitals. We model the physician's decision as a nested-logit a la McFadden. Unlike in standard applications of McFadden's model, in our application the choice set is not constant across physicians but it shrinks along the sequential hospital choice proces

Coverage of Infertility Treatment and Fertility Outcomes: Do Women Catch Up?

The ageing of first-time mothers and the changes in women's labor market conditions have been accompanied by the introduction and subsequent increase in the use of assisted reproductive therapies (ART) that help extend women's reproductive lives. Considering the financial cost of infertility treatments, policy interventions that increase insurance coverage may significantly affect fertility trends, and ultimately, population age structures. However, policies have ignored the overall impact of ART coverage on fertility. In this paper, long-term effects of insurance coverage for infertility on the timing of first births and on total fertility rates are examined. Variation in the enactment of infertility insurance mandates over time and across U.S. states allows the estimation of both the short-term and long-term effects. We concentrate on the effects of the more demanding mandates enacted in six states in the later 80s and 90s. Our results show that the effect of these mandates to cover infertility treatment is positive on the average age at first birth and increases over time. The long-term estimates of the increase in age of first-time mothers range from 3 to 5 months. Importantly, we also show that these mandates do not increase the total fertility rates of women by the end of their reproductive lives.assisted reproductive technologies, infertility insurance mandates, total fertility, synthetic control methods

A METHODOLOGY TO MEASURE HOSPITAL QUALITY USING PHYSICIANS' CHOICES OVER TRAINING VACANCIES

In this paper, we propose an alternative methodology to rank hospitals based on the choices of Medical Schools graduates over training vacancies. We argue that our measure of relative hospital quality has the following desirable properties: a) robustness to manipulation from the hospital’s administrators; b) comprehensiveness in the scope of the services analyzed; c) inexpensive in terms of data requirements, and d) not subject to selection biases. Accurate measures of health provider quality are needed in order to establish incentive mechanisms, to assess the need for quality improvement, or simply to increase market transparency and competition. Public report cards in certain US states and the NHS ranking system in the UK are two attempts at constructing quality rankings of health care providers. Although the need for such rankings is widely recognized, the criticisms at these attempts reveal the difficulties involved in this task. Most criticisms alert to the inadequate risk-adjustment and the potential for perverse consequences such as patient selection. The recent literature, using sophisticated econometric models is capable of controlling for case-mix, hospital and patient selection, and measurement error. The detailed data needed for these evaluations is, however, often unavailable to researchers. In those countries, such as Spain, where there is neither public hospital rankings nor public data on hospital output measures such as mortality rates our methodology is a valid alternative. We develop this methodology for the Spanish case. In a follow-up paper we will present results using Spanish data. In Spain graduates choose hospital training vacancies in a sequential manner that depends on their average grade. Our framework relies on three assumptions. First, high quality hospitals provide high quality training. Second, graduates are well informed decision makers who are well qualified to assess hospital quality. Third, they prefer to choose a high quality vacancy rather than a low quality one ceteris paribus. If these assumptions hold, then the first physicians to choose are likely to grab the best vacancies while the ones who choose last are stuck with the worst available. Thus, it is possible to infer from physicans’ choices quality differentials amongst hospitals. We model the physician’s decision as a nested-logit a la McFadden. Unlike in standard applications of McFadden’s model, in our application the choice set is not constant across physicians but it shrinks along the sequential hospital choice process

Moral hazard and the demand for health services: a matching estimator approach

We estimate the impact of health insurance coverage beyond National Health Insurance on the demand for several health services. Traditionally, the literature has tried to deal with the endogeneity of the private (extra) insurance decision by finding instrumental variables. Since a priori instrumental variables are hard to find we take a different approach. We focus on the most common health insurance plan in Portugal, ADSE, which is given to all civil servants and their dependants. We argue this insurance is exogenous i.e. not correlated with beneficiaries’ health status. This identifying assumption allows us to estimate the impact of having ADSE coverage on three different health services using a matching estimator technique. The health services used are: number of visits, number of blood and urine tests, and the probability of visiting a dentist. Results show large positive effects of ADSE for number of visits and tests among the young (18 to 30 years old) but only the latter is statistically significantly different from zero. The effects represent 21.8 and 30% of the average number of visits and tests for the young. On the contrary, we find no evidence of moral hazard on the probability of visiting a dentist

Moral hazard and the demand for health services: A matching estimator approach

We estimate the impact of extra health insurance coverage beyond a National Health System on the demand for several health services. Traditionally, the literature has tried to deal with the endogeneity of the private (extra) insurance decision by finding instrumental variables. Since a priori instrumental variables are hard to find we take a different approach. We focus on the most common health insurance plan in Portugal, ADSE, which is given to all civil servants and their dependents. We argue that this insurance is exogenous, i.e., not correlated with the beneficiaries’ health status. This identifying assumption allows us to estimate the impact of having ADSE coverage on the demand for three different health services using a matching estimator technique. The health services used are number of visits, number of blood and urine tests, and the probability of visiting a dentist. Results show large positive effects of ADSE coverage for number of visits and tests among the young (18–30 years old) but only the latter is statistically significantly different from zero. The effects represent 21.8% and 30% of the average number of visits and tests for the young. On the contrary, we find no evidence of moral hazard on the probability of visiting a dentist.Publicad