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Instrumental Variables (instrumental + variable)
Terms modified by Instrumental Variables Selected AbstractsMental illness, nativity, gender and labor supplyHEALTH ECONOMICS, Issue 4 2010Victoria D. Ojeda Abstract We analyzed the impacts of nativity and mental health (MH) on work by gender for non-elderly adults using the 2002 National Survey on Drug Use and Health. We employed two indicators of MH , the K6 scale of Mental Illness (MI) and an indicator for symptoms of Mania or Delusions (M/D). Instrumental variable (IV) models used measures of social support as instruments for MI. Unadjusted work rates were higher for immigrants (vs US-born adults). Regressions show that MI is associated with lower rates of work among US-born males but not immigrant males and females; M/D is associated lower rates of work among US-born males and females, and among immigrant males. Results did not change using IV models for MI. Most persons with MI work, yet symptom severity reduces labor supply among natives especially. Immigrants' labor supply is less affected by MI. Copyright © 2009 John Wiley & Sons, Ltd. [source] Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patientsHEALTH ECONOMICS, Issue 11 2007Anirban Basu Abstract Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5-year direct costs of breast-conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters. Copyright © 2007 John Wiley & Sons, Ltd. [source] Dragon Children: Identifying the Causal Effect of the First Child on Female Labour Supply with the Chinese Lunar Calendar,OXFORD BULLETIN OF ECONOMICS & STATISTICS, Issue 3 2008James P. Vere Abstract Instrumental variables (IV) estimates of the effect of fertility on female labour supply have only been able to identify the causal effect of second and higher parity children. This study uses exogenous variation in fertility caused by the Chinese lunar calendar to identify the effect of the first child. Additionally, weighting formulas are presented to interpret IV estimates as weighted average treatment effects in the case of multiple endogenous variables, which are useful when children vary in intensity by both number and age. The effect of the first child is found to be much greater than that of other children. [source] Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee EarningsECONOMETRICA, Issue 1 2002Alberto Abadie This paper reports estimates of the effects of JTPA training programs on the distribution of earnings. The estimation uses a new instrumental variable (IV) method that measures program impacts on quantiles. The quantile treatment effects (QTE) estimator reduces to quantile regression when selection for treatment is exogenously determined. QTE can be computed as the solution to a convex linear programming problem, although this requires first-step estimation of a nuisance function. We develop distribution theory for the case where the first step is estimated nonparametrically. For women, the empirical results show that the JTPA program had the largest proportional impact at low quantiles. Perhaps surprisingly, however, JTPA training raised the quantiles of earnings for men only in the upper half of the trainee earnings distribution. [source] Fiscal Policy, Business Cycles and Economic Stabilisation: Evidence from Industrialised and Developing Countries,FISCAL STUDIES, Issue 4 2007Young Lee This paper empirically investigates the responsiveness of fiscal policy to business cycles and the effectiveness of fiscal policy in reducing economic fluctuations. From regressions on the responsiveness of fiscal policy to business cycles, we find that the government's current expenditures and subsidies & transfers move counter-cyclically, whereas taxes and capital expenditures move pro-cyclically. Using economic fluctuations in neighbouring countries as an instrumental variable, we show that ordinary least squares (OLS) estimates understate the responsiveness of fiscal policy to economic fluctuations. We also find that fiscal policy responds asymmetrically over economic fluctuations. In investigating the effectiveness of fiscal policy in reducing economic fluctuations, we mitigate omitted variable bias by adding four important factors - military expenditures, oil production, economic fluctuations in neighbouring countries and fiscal policy responsiveness to business cycles. The results of effectiveness regressions are consistent with the responsiveness regressions, highlighting the importance of current expenditures, especially subsidies and transfers, in responding to business cycles and stabilising the economy. [source] Do competition and managed care improve quality?HEALTH ECONOMICS, Issue 7 2002Nazmi SariArticle first published online: 22 JUL 200 Abstract In recent years, the US health care industry has experienced a rapid growth of managed care, formation of networks, and an integration of hospitals. This paper provides new insights about the quality consequences of this dynamic in US hospital markets. I empirically investigate the impact of managed care and hospital competition on quality using in-hospital complications as quality measures. I use random and fixed effects, and instrumental variable fixed effect models using hospital panel data from up to 16 states in the 1992,1997 period. The paper has two important findings: First, higher managed care penetration increases the quality, when inappropriate utilization, wound infections and adverse/iatrogenic complications are used as quality indicators. For other complication categories, coefficient estimates are statistically insignificant. These findings do not support the straightforward view that increases in managed care penetration are associated with decreases in quality. Second, both higher hospital market share and market concentration are associated with lower quality of care. Hospital mergers have undesirable quality consequences. Appropriate antitrust policies towards mergers should consider not only price and cost but also quality impacts. Copyright © 2002 John Wiley & Sons, Ltd. [source] The Impact of CHIP on Children's Insurance Coverage: An Analysis Using the National Survey of America's FamiliesHEALTH SERVICES RESEARCH, Issue 6 2009Lisa Dubay Objective. To assess the impact of the Children's Health Insurance Program (CHIP) on the distribution of health insurance coverage for low-income children. Data Source. The primary data for the study were from the 1997, 1999, and 2002 National Survey of America's Families (NSAF), which includes a total sample of 62,497 children across all 3 years, supplemented with data from other data sources. Study Design. The study uses quasi-experimental designs and tests the sensitivity of the results to using instrumental variable and difference-in-difference approaches. A detailed Medicaid and CHIP eligibility model was developed for this study. Balanced repeated replicate weights were used to account for the complex sample of the NSAF. Descriptive and multivariate analyses were conducted. Principle Findings. The results varied depending on the approach utilized but indicated that the CHIP program led to significant increases in public coverage (14,20 percentage points); and declines in employer-sponsored coverage (6,7 percentage points) and in uninsurance (7,12 percentage points). The estimated share of CHIP enrollment attributable to crowd-out ranged from 33 to 44 percent. Smaller crowd-out effects were found for Medicaid-eligible children. Conclusions. Implementation of the CHIP program resulted in large increases in public coverage with estimates of crowd-out consistent with initial projections made by the Congressional Budget Office. This paper demonstrates that public health insurance expansions can lead to substantial reductions in uninsurance without causing a large-scale erosion of employer coverage. [source] Effect of Evidence-Based Acute Pain Management Practices on Inpatient CostsHEALTH SERVICES RESEARCH, Issue 1 2009John M. Brooks Objectives. To estimate hospital cost changes associated with a behavioral intervention designed to increase the use of evidence-based acute pain management practices in an inpatient setting and to estimate the direct effect that changes in evidence-based acute pain management practices have on inpatient cost. Data Sources/Study Setting. Data from a randomized "translating research into practice" (TRIP) behavioral intervention designed to increase the use of evidence-based acute pain management practices for patients hospitalized with hip fractures. Study Design. Experimental design and observational "as-treated" and instrumental variable (IV) methods. Data Collection/Extraction Methods. Abstraction from medical records and Uniform Billing 1992 (UB92) discharge abstracts. Principal Findings. The TRIP intervention cost on average $17,714 to implement within a hospital but led to cost savings per inpatient stay of more than $1,500. The intervention increased the cost of nursing services, special operating rooms, and therapy services per inpatient stay, but these costs were more than offset by cost reductions within other cost categories. "As-treated" estimates of the effect of changes in evidence-based acute pain management practices on inpatient cost appear significantly underestimated, whereas IV estimates are statistically significant and are distinct from, but consistent with, estimates associated with the intervention. Conclusions. A hospital treating more that 12 patients with acute hip fractures can expect to lower overall cost by implementing the TRIP intervention. We also demonstrated the advantages of using IV methods over "as-treated" methods to assess the direct effect of practice changes on cost. [source] Prudential Regulation and the "Credit Crunch": Evidence from JapanJOURNAL OF MONEY, CREDIT AND BANKING, Issue 2-3 2007WAKO WATANABE credit crunch; capital crunch; prudential regulation; instrumental variable The underlying causes of sharp declines in bank lending during recessions in large developed economies, as exemplified by the U.S. in the early 1990s and Japan in the late 1990s, are still being debated due to the lack of any convincing identification strategy of the supply side capital,lending relationship from lending demand. Using within bank share of real estate lending in the late 1980s as an instrumental variable for bank capital, we find that Japanese banks cut back on their lending in response to a large loss of bank capital in fiscal year 1997. [source] Measurement error modelling with an approximate instrumental variableJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 5 2007Paul Gustafson Summary., Consider using regression modelling to relate an exposure (predictor) variable to a disease outcome (response) variable. If the exposure variable is measured with error, but this error is ignored in the analysis, then misleading inferences can result. This problem is well known and has spawned a large literature on methods which adjust for measurement error in predictor variables. One theme is that the requisite assumptions about the nature of the measurement error can be stronger than what is actually known in many practical situations. In particular, the assumptions that are required to yield a model which is formally identified from the observable data can be quite strong. The paper deals with one particular strategy for measurement error modelling, namely that of seeking an instrumental variable, i.e. a covariate S which is associated with exposure and conditionally independent of the outcome given exposure. If these two conditions hold exactly, then we call S an exact instrumental variable, and an identified model results. However, the second is not checkable empirically, since the actual exposure is unobserved. In practice then, investigators typically seek a covariate which is plausibly thought to satisfy it. We study inferences which acknowledge the approximate nature of this assumption. In particular, we consider Bayesian inference with a prior distribution that posits that S is probably close to conditionally independent of outcome given exposure. We refer to this as an approximate instrumental variable assumption. Although the approximate instrumental variable assumption is more realistic for most applications, concern arises that a non-identified model may result. Thus the paper contrasts inferences arising from the approximate instrumental variable assumption with their exact instrumental variable counterparts, with particular emphasis on the benefit of basing inferences on a more realistic model versus the cost of basing inferences on a non-identified model. [source] Non-linear finance,growth nexusTHE ECONOMICS OF TRANSITION, Issue 3 2009A threshold with instrumental variable approach Financial development; economic growth; instrumental variable; threshold regression Abstract This paper revisits the question of whether the finance,growth nexus varies with the stages of economic development. Using a novel threshold regression with the instrumental variables approach proposed by Caner and Hansen (2004) to the dataset used in Levine et al. (2000) we detect overwhelming evidence in support of a positive linkage between financial development and economic growth, and this positive effect is larger in the low-income countries than in the high-income ones. The data also reveal that financial development tends to have stronger impacts on capital accumulation and productivity growth in the low-income countries than in the high-income ones. The findings are robust to alternative financial development measures and conditioning information sets. [source] Semiparametric Bayesian Analysis of Nutritional Epidemiology Data in the Presence of Measurement ErrorBIOMETRICS, Issue 2 2010Samiran Sinha Summary:, We propose a semiparametric Bayesian method for handling measurement error in nutritional epidemiological data. Our goal is to estimate nonparametrically the form of association between a disease and exposure variable while the true values of the exposure are never observed. Motivated by nutritional epidemiological data, we consider the setting where a surrogate covariate is recorded in the primary data, and a calibration data set contains information on the surrogate variable and repeated measurements of an unbiased instrumental variable of the true exposure. We develop a flexible Bayesian method where not only is the relationship between the disease and exposure variable treated semiparametrically, but also the relationship between the surrogate and the true exposure is modeled semiparametrically. The two nonparametric functions are modeled simultaneously via B-splines. In addition, we model the distribution of the exposure variable as a Dirichlet process mixture of normal distributions, thus making its modeling essentially nonparametric and placing this work into the context of functional measurement error modeling. We apply our method to the NIH-AARP Diet and Health Study and examine its performance in a simulation study. [source] A Comparison of Methods for Estimating the Causal Effect of a Treatment in Randomized Clinical Trials Subject to NoncomplianceBIOMETRICS, Issue 2 2009Roderick J. Little Summary We consider the analysis of clinical trials that involve randomization to an active treatment (T,=,1) or a control treatment (T,=,0), when the active treatment is subject to all-or-nothing compliance. We compare three approaches to estimating treatment efficacy in this situation: as-treated analysis, per-protocol analysis, and instrumental variable (IV) estimation, where the treatment effect is estimated using the randomization indicator as an IV. Both model- and method-of-moment based IV estimators are considered. The assumptions underlying these estimators are assessed, standard errors and mean squared errors of the estimates are compared, and design implications of the three methods are examined. Extensions of the methods to include observed covariates are then discussed, emphasizing the role of compliance propensity methods and the contrasting role of covariates in these extensions. Methods are illustrated on data from the Women Take Pride study, an assessment of behavioral treatments for women with heart disease. [source] Foreign Direct Investment, Services Trade Negotiations and Development: The Case of Tourism in the CaribbeanDEVELOPMENT POLICY REVIEW, Issue 4 2006Dirk Willem te Velde This article examines whether and how developing countries can use services trade negotiations to increase the amount of inward FDI conducive to development. It reviews how services trade rules can affect inward FDI, and employs panel data analysis with innovative use of instrumental variables in the tourism sectors of 9 Caribbean countries during 1997,2003. It argues that Caribbean countries may want to signal openness to inward FDI in GATS, while maintaining a degree of flexibility in the use of policy measures; in the current negotiations with the EU on Economic Partnership Agreements, the focus could be on emphasising the development dimension. [source] Decision Theory Applied to an Instrumental Variables ModelECONOMETRICA, Issue 3 2007Gary Chamberlain This paper applies some general concepts in decision theory to a simple instrumental variables model. There are two endogenous variables linked by a single structural equation; k of the exogenous variables are excluded from this structural equation and provide the instrumental variables (IV). The reduced-form distribution of the endogenous variables conditional on the exogenous variables corresponds to independent draws from a bivariate normal distribution with linear regression functions and a known covariance matrix. A canonical form of the model has parameter vector (,, ,, ,), where ,is the parameter of interest and is normalized to be a point on the unit circle. The reduced-form coefficients on the instrumental variables are split into a scalar parameter ,and a parameter vector ,, which is normalized to be a point on the (k,1)-dimensional unit sphere; ,measures the strength of the association between the endogenous variables and the instrumental variables, and ,is a measure of direction. A prior distribution is introduced for the IV model. The parameters ,, ,, and ,are treated as independent random variables. The distribution for ,is uniform on the unit circle; the distribution for ,is uniform on the unit sphere with dimension k-1. These choices arise from the solution of a minimax problem. The prior for ,is left general. It turns out that given any positive value for ,, the Bayes estimator of ,does not depend on ,; it equals the maximum-likelihood estimator. This Bayes estimator has constant risk; because it minimizes average risk with respect to a proper prior, it is minimax. The same general concepts are applied to obtain confidence intervals. The prior distribution is used in two ways. The first way is to integrate out the nuisance parameter ,in the IV model. This gives an integrated likelihood function with two scalar parameters, ,and ,. Inverting a likelihood ratio test, based on the integrated likelihood function, provides a confidence interval for ,. This lacks finite sample optimality, but invariance arguments show that the risk function depends only on ,and not on ,or ,. The second approach to confidence sets aims for finite sample optimality by setting up a loss function that trades off coverage against the length of the interval. The automatic uniform priors are used for ,and ,, but a prior is also needed for the scalar ,, and no guidance is offered on this choice. The Bayes rule is a highest posterior density set. Invariance arguments show that the risk function depends only on ,and not on ,or ,. The optimality result combines average risk and maximum risk. The confidence set minimizes the average,with respect to the prior distribution for ,,of the maximum risk, where the maximization is with respect to ,and ,. [source] Structural Equations, Treatment Effects, and Econometric Policy Evaluation1ECONOMETRICA, Issue 3 2005James J. Heckman This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common semiparametric functional form; to organize the literature on alternative estimators; and to explore what policy questions commonly used estimators in the treatment effect literature answer. A fundamental asymmetry intrinsic to the method of instrumental variables (IV) is noted. Recent advances in IV estimation allow for heterogeneity in responses but not in choices, and the method breaks down when both choice and response equations are heterogeneous in a general way. [source] End-of-Sample Instability TestsECONOMETRICA, Issue 6 2003D. W. K. Andrews This paper considers tests for structural instability of short duration, such as at the end of the sample. The key feature of the testing problem is that the number, m, of observations in the period of potential change is relatively small,possibly as small as one. The well-known F test of Chow (1960) for this problem only applies in a linear regression model with normally distributed iid errors and strictly exogenous regressors, even when the total number of observations, n+m, is large. We generalize the F test to cover regression models with much more general error processes, regressors that are not strictly exogenous, and estimation by instrumental variables as well as least squares. In addition, we extend the F test to nonlinear models estimated by generalized method of moments and maximum likelihood. Asymptotic critical values that are valid as n,, with m fixed are provided using a subsampling-like method. The results apply quite generally to processes that are strictly stationary and ergodic under the null hypothesis of no structural instability. [source] From Great Depression to Great Credit Crisis: similarities, differences and lessonsECONOMIC POLICY, Issue 62 2010Miguel Almunia Summary The Great Depression of the 1930s and the Great Credit Crisis of the 2000s had similar causes but elicited strikingly different policy responses. While it remains too early to assess the effectiveness of current policy, it is possible to analyse monetary and fiscal responses in the 1930s as a natural experiment or counterfactual capable of shedding light on the impact of current policies. We employ vector autoregressions, instrumental variables, and qualitative evidence for 27 countries in the period 1925,39. The results suggest that monetary and fiscal stimulus was effective -- that where it did not make a difference it was not tried. They shed light on the debate over fiscal multipliers in episodes of financial crisis. They are consistent with multipliers at the higher end of those estimated in the recent literature, and with the argument that the impact of fiscal stimulus will be greater when banking systems are dysfunctional and monetary policy is constrained by the zero bound. --- Miguel Almunia, Agustín Bénétrix, Barry Eichengreen, Kevin H. O'Rourke and Gisela Rua [source] The governance and performance of universities: evidence from Europe and the USECONOMIC POLICY, Issue 61 2010Philippe Aghion Summary We test the hypothesis that universities are more productive when they are both more autonomous and face more competition. Using survey data, we construct indices of university autonomy and competition for both Europe and the United States. We show that there are strong positive correlations between these indices and multiple measures of university output. To obtain causal evidence, we investigate exogenous shocks to US universities' expenditures over three decades. These shocks arise through the political appointment process, which we use to generate instrumental variables. We find that an exogenous increase in a university's expenditure generates more output, measured by either patents or publications, if the university is more autonomous and faces more competition. Exploiting variation over time in the ,stakes' of competitions for US federal research grants, we also find that universities generate more output for a given expenditure when research competitions are high stakes. We draw lessons, arguing that European universities could benefit from a combination of greater autonomy and greater accountability. Greater accountability might come through increased reliance on competitive grants, enhanced competition for students and faculty (promoted by reforms that increase mobility), and yardstick competitions (which often take the form of assessment exercises). --- Philippe Aghion, Mathias Dewatripont, Caroline Hoxby, Andreu Mas-Colell and André Sapir [source] CAFTA, CAMPAIGN CONTRIBUTIONS, AND THE ROLE OF SPECIAL INTERESTSECONOMICS & POLITICS, Issue 3 2010JAMES M. DEVAULT This paper analyzes the passage of the Central American Free Trade Agreement (CAFTA) in 2005, paying particular attention to the role of campaign contributions. The CAFTA vote is significant in that the context in which it occurred was one in which campaign contributions were more likely to influence votes. By more carefully identifying the special interest groups actively involved in the CAFTA debate, I provide a more accurate assessment of the impact of the contributions made by these groups. I use instrumental variables to control for the potential endogeneity of campaign contributions and find that these contributions played at best a secondary role in determining the outcome of the CAFTA vote in the U.S. House of Representatives. [source] HOW DID THE 2003 PRESCRIPTION DRUG RE-IMPORTATION BILL PASS THE HOUSE?ECONOMICS & POLITICS, Issue 1 2006OMER GOKCEKUS We examine the major interest groups in the debate over allowing the re-importation of prescription drugs by utilizing a logit model and instrumental variables. Consistent with political support approach, the evidence suggests that Representatives are maximizing their electoral prospects: contributions from pharmaceutical manufacturers shrink the probability of voting for the bill; and Representatives are sensitive to their constituencies , employees of pharmaceutical manufacturing and senior citizens. Representatives' gender and ideology regarding free trade and subsidies are also determining factors. However, the decision was, by and large, a partisan one: party affiliation was the most important factor in passing the bill. [source] Cost inefficiency and hospital health outcomesHEALTH ECONOMICS, Issue 7 2008Niccie L. McKay Abstract This study explores the association between cost inefficiency and health outcomes in a national sample of acute-care hospitals in the US over the period 1999,2001, with health outcomes being measured by both mortality and complications rates. The empirical analysis examines health outcomes as a function of cost inefficiency and other determinants of outcomes, using stochastic frontier analysis to obtain hospital cost inefficiency scores. The results showed no systematic pattern of association between cost inefficiency and hospital health outcomes; the basic results were unchanged regardless of whether cost inefficiency was measured with or without using instrumental variables. The analysis also indicated, however, that the association between cost inefficiency and health outcomes may vary substantially across geographical regions. The study highlights the importance of distinguishing between ,good' costs that reflect the efficient use of resources and ,bad' costs that stem from waste and other forms of inefficiency. In particular, the study's results suggest that hospital programs focused on reducing cost inefficiency are unlikely to be associated with worsened hospital-level mortality or complications rates, while, on the other hand, across-the-board reductions in cost could well have adverse consequences on health outcomes by reducing efficient as well as inefficient costs. Copyright © 2007 John Wiley & Sons, Ltd. [source] Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patientsHEALTH ECONOMICS, Issue 11 2007Anirban Basu Abstract Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5-year direct costs of breast-conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters. Copyright © 2007 John Wiley & Sons, Ltd. [source] The impact of diabetes on employment: genetic IVs in a bivariate probitHEALTH ECONOMICS, Issue 5 2005H. Shelton Brown III Abstract Diabetes has been shown to have a detrimental impact on employment and labor market productivity, which results in lost work days and higher mortality/disability. This study utilizes data from the Border Epidemiologic Study on Aging to analyze the endogeneity of diabetes in an employment model. We use family history of diabetes as genetic instrumental variables. We show that assuming that diabetes is an exogenous variable results in an overestimate (underestimate) of the negative impact of diabetes on female (male) employment. Our results are particularly relevant in the case of populations where genetic predisposition has an important role in the etiology of diabetes. Copyright © 2004 John Wiley & Sons, Ltd. [source] The effect of practice budgets on patient waiting times: allowing for selection biasHEALTH ECONOMICS, Issue 10 2004Mark Dusheiko Abstract Under the UK fundholding scheme, general practices could elect to hold a budget to meet the costs of some types of elective surgery (chargeable admissions) for their patients. It was alleged that patients of fundholding practices had shorter waits for elective surgery than the patients of non-fundholders. Comparison of waiting times between fundholding and non-fundholding practices are potentially confounded by selection bias as fundholding was voluntary. We estimate the effect of a practice's fundholding status on the waiting times of its patients using both cross-sectional methods (OLS, propensity score, instrumental variables, Heckman selection correction and Heckman heterogenous effects estimators) and difference in differences methodologies to correct for selection bias. The estimated effect of fundholding status was to significantly reduce the waiting times for chargeable admissions of the patients of fundholders by 4.1,6.6% (or 4,7 days) with the instrumental variables and Heckman selection correction estimators yielding the highest estimates. We also find that patients of fundholding practices had shorter waits (by 3.7% or 2 days) for non-chargeable elective admissions, suggesting that fundholders were able to obtain shorter waits for all types of elective admissions. Copyright © 2004 John Wiley & Sons, Ltd. [source] Medical student indebtedness and the propensity to enter academic medicineHEALTH ECONOMICS, Issue 2 2003Marc FoxArticle first published online: 22 MAY 200 Abstract This paper considers the potential impact of medical school indebtedness and other variables on the propensity of US doctors to enter academic medicine. Probit models provide some evidence that indebtedness reduces the likelihood that physicians will choose academic medicine as their primary activity. Nevertheless, the magnitude of this effect is not large. As indebtedness may be endogenous, the probits are rerun using an instrumental variables approach. These estimates imply that over time indebtedness may have an important impact on the propensity of physicians to enter academic medicine. Copyright © 2002 John Wiley & Sons, Ltd. [source] Iterative correlation-based controller tuningINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2004A. Karimi Abstract This paper gives an overview on the theoretical results of recently developed algorithms for iterative controller tuning based on the correlation approach. The basic idea is to decorrelate the output error between the achieved and designed closed-loop systems by iteratively tuning the controller parameters. Two different approaches are investigated. In the first one, a correlation equation involving a vector of instrumental variables is solved using the stochastic approximation method. It is shown that, with an appropriate choice of instrumental variables and a finite number of data at each iteration, the algorithm converges to the solution of the correlation equation. The convergence conditions are derived and the accuracy of the estimates are studied. The second approach is based on the minimization of a correlation criterion. The frequency analysis of the criterion shows that the two norm of the error between the desired and achieved closed-loop transfer functions is minimized independent of the noise characteristics. This analysis leads to the definition of a generalized correlation criterion which allows the mixed sensitivity problem to be handled in two norm. Copyright © 2004 John Wiley & Sons, Ltd. [source] Economic determinants of biodiversity change over a 400-year period in the Scottish uplandsJOURNAL OF APPLIED ECOLOGY, Issue 6 2008Nick Hanley Summary 1Economic forces are recognized as an important driving factor behind current biodiversity losses. This study investigates whether such factors have been important in determining one measure of biodiversity change over the ,long run', in our case, 400 years , for upland sites in Scotland. 2A combination of palaeoecological, historical and economic methods is used to construct and then analyse a database of factors contributing to changes in plant diversity over time for 11 upland sites. 3Using an instrumental variables panel model, we find livestock prices, our proxy for grazing pressure, to be a statistically significant determinant of diversity change, with higher grazing pressures resulting in lower diversity values on average, although site abandonment is also found to result in a fall in plant diversity. Technological change, such as the introduction of new animal breeds, was not found to be a statistically significant determinant. 4Using later period data (post 1860) on livestock numbers at the parish (local) level, we were able to confirm the main result noted above (3) in terms of the effects of higher grazing pressures on plant diversity. 5Synthesis and applications. This study shows how data from very different disciplines can be combined to address questions relevant to contemporary conservation and understanding. This novel, interdisciplinary approach provides new insights into the role of economic factors as a driver of biodiversity loss in the uplands. Biodiversity levels have varied considerably over 400 years, partly as a function of land management, suggesting that establishing baselines or ,natural' target levels for biodiversity is likely to be problematic. Changes in livestock grazing pressures brought about by changes in prices had statistically significant effects on estimated plant diversity, as did land abandonment. This suggests that long-term management of upland areas for the conservation of diversity should focus on grazing pressures as a key policy attribute. Another policy implication is that drastic cuts in grazing pressures , such as might occur under current reforms of the Common Agricultural Policy , can have adverse biodiversity consequences. [source] Determination of polycyclic aromatic hydrocarbons in olive oil by a completely automated headspace technique coupled to gas chromatography-mass spectrometryJOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 6 2006Francisco J. Arrebola Abstract A new and completely automated method for the determination of ten relevant polycyclic aromatic hydrocarbons (PAHs) in olive oil is proposed using an extraction by the headspace (HS) technique. Quantification and confirmation steps are carried out by gas chromatography-mass spectrometry (GC-MS) combining simultaneously selected-ion monitoring (SIM) and tandem mass spectrometry (MS/MS). This combination offers on one hand an increased sensitivity and on the other hand, selective and reliable qualitative information. Sample pretreatment or clean-up are not necessary because the olive oil sample is put directly into an HS vial, automatically processed by HS and introduced into the GC-MS instrument for analysis. Because of its high selectivity and sensitivity, a triple-quadrupole (QqQ) detector coupled with the gas chromatograph allows us to limit handling. Each sample is completely processed in approximately 63 min (45 min for HS isolation and 18 min for GC-MS determination), a reduced time compared with previously published methods. The chemical and instrumental variables were preliminarily optimized using uncontaminated olive oil samples spiked with 25 µg kg,1 of each target compound. The final method was validated to ensure the quality of the results. The precision was satisfactory, with relative standard deviation (RSD) values in the range 3,9%. Recovery rates ranged from 96 to 99%. Limits of detection (LOD) were calculated as 0.02,0.06 µg kg,1 and the limits of quantification (LOQ) were obtained as 0.07,0.26 µg kg,1. It must be mentioned that the LOD and LOQ are much lower than the maximum levels established by the European Union (EU) in oils and fats intended for direct human consumption or for use as an ingredient in foods, which are set at 2 µg kg,1. All the figures of merit are completely in accordance with the latest EU legislation. This fact makes it possible to consider the proposed method as a useful tool for the control of PAHs in olive oils. Copyright © 2006 John Wiley & Sons, Ltd. [source] Does sex education affect adolescent sexual behaviors and health?JOURNAL OF POLICY ANALYSIS AND MANAGEMENT, Issue 4 2006Joseph J. SabiaArticle first published online: 6 SEP 200 This study examines whether offering sex education to young teenagers affects several measures of adolescent sexual behavior and health: virginity status, contraceptive use, frequency of intercourse, likelihood of pregnancy, and probability of contracting a sexually transmitted disease. Using data from the National Longitudinal Study of Adolescent Health, I find that while sex education is associated with adverse health outcomes, there is little evidence of a causal link after controlling for unobserved heterogeneity via fixed effects and instrumental variables. These findings suggest that those on each side of the ideological debate over sex education are, in a sense, both correct and mistaken. Opponents are correct in observing that sex education is associated with adverse health outcomes, but are generally incorrect in interpreting this relationship causally. Proponents are generally correct in claiming that sex education does not encourage risky sexual activity, but are incorrect in asserting that investments in typical schoolbased sex education programs produce measurable health benefits. © 2006 by the Association for Public Policy Analysis and Management [source] | ||||||||||||||||||||||||||||||||||||||||