Demand & Supply in Health Economics eJournal最新文献

{"title":"Procurement Institutions and Essential Drug Supply in Low and Middle-Income Countries","authors":"Lucy Xiaolu Wang, N. Zahur","doi":"10.2139/ssrn.3926761","DOIUrl":"https://doi.org/10.2139/ssrn.3926761","url":null,"abstract":"International procurement institutions have played an important role in drug supply. This paper studies price, delivery, and shipment time of essential drugs supplied in 106 developing countries from 2007-2017 across four procurement institution types. We find that pooled procurement institutions lower prices: pooling internationally is most effective for small buyers and more concentrated markets, and pooling within-country is most effective for large buyers and less concentrated markets. Pooling can reduce delays, but at the cost of longer anticipated shipment times. Finally, pooled procurement is more effective for older generation drugs, complementing IP licensing institutions that focus on newer, patented drugs. We corroborate the findings using multiple identification strategies, including an instrumental variable strategy as well as the Altonji-Elder-Taber-Oster method for selection on unobservables. Our results suggest that the optimal mixture of procurement institutions depends on the trade-off between costs and urgency of need, with pooled international procurement institutions particularly valuable when countries can plan well ahead of time.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90200756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Watching the Grass Grow: Does Recreational Cannabis Legalization Affect Labor Outcomes?","authors":"Sichao Jiang, Keaton S. Miller","doi":"10.2139/ssrn.3907412","DOIUrl":"https://doi.org/10.2139/ssrn.3907412","url":null,"abstract":"Over the past several years, cannabis has become legal for recreational use in several U.S. states and jurisdictions around the world. The opening of these markets has led to the establishment of hundreds of cannabis production and retail firms with accompanying demand for labor, leading to concerns about spillover effects on wages from incumbents. We study the markets for agricultural and retail labor in Washington and Colorado, early legalizers with now-established cannabis markets. Using a synthetic control technique to account for the possibility of border-state spillover effects and machine learning techniques for data imputation and variable selection, we find no evidence that cannabis legalization is associated with increases in per-employee wages, neither within industries most similar to cannabis production or retail, nor in more broad industry categories. We conclude that cannabis legalization is unlikely to negatively impact incumbent firms through the labor market channel.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78627438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decomposition of Clinical Disparities with Machine Learning","authors":"N. Hammarlund","doi":"10.2139/ssrn.3895952","DOIUrl":"https://doi.org/10.2139/ssrn.3895952","url":null,"abstract":"Differences in average rates of access to quality care, mortality from specific diseases, and surgery for conditions such as emergency cardiac care point to racial disparities in healthcare. The optimal approach to alleviate a given disparity depends on whether the main driver is differential health risk or differential treatment within the healthcare system. In this paper, I propose an extension of the Oaxaca-Blinder decomposition framework that capitalizes on advances in clinical data and machine learning prediction to quantify the portions of a given disparity due to differential clinical health and differential healthcare treatment. The proposed method applied to the surgery decision for heart attacks using electronic medical records data from a major academic hospital system in Indiana suggests a smaller potential healthcare treatment disparity compared to the conclusion from the standard approach. The method reveals that 1/3 of the cardiac surgery rate difference can be explained by differences in clinical health variables between Black and non-Black patients pointing towards the existence of worse relative social health risks for patients clinically recorded as Black. Differential health risks for the socially constructed concept of race indicates the need for society-wide solutions to address differences in risk factors such as healthcare access and socioeconomic status. However, a substantial cardiac surgery disparity, constituting 2/3 of the rate difference, remains even after machine learning-based clinical health adjustment pointing towards the need for solutions that target differential clinical treatment.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83264155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Consequences of Hospital Closures","authors":"D. Alexander, Michael R Richards","doi":"10.2139/ssrn.3848927","DOIUrl":"https://doi.org/10.2139/ssrn.3848927","url":null,"abstract":"Hospitals anchor much of US health care and receive a third of all medical spending, including various subsidies. Nevertheless, some become insolvent and exit the market. Research has documented subsequent access problems; however, less is understood about broader implications. We examine over 100 rural hospital closures spanning 2005-2017 to quantify the effects on the local economy. We find sharp and persistent reductions in employment, but these localize to health care occupations and are largely driven by areas experiencing complete closures. Aggregate consumer financial health is only modestly affected, and housing markets were already depressed prior to hospital closures.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75004168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Price-Leverage Covariation as a Measure of the Response of the Leverage Effect To Price and Volatility Changes","authors":"Giacomo Toscano","doi":"10.2139/ssrn.3776771","DOIUrl":"https://doi.org/10.2139/ssrn.3776771","url":null,"abstract":"We study the sensitivity of the leverage effect to changes in the volatility and the price, showing the existence of an analytical link between the latter and the price-leverage covariation in settings with, respectively, stochastic and level-dependent volatility. From the financial standpoint, the results we obtain allow for the interpretation of the price-leverage covariation as a gauge of the responsiveness of the leverage effect to price and volatility changes. The empirical study of S&P500 high-frequency prices over the period March, 2018-April, 2018, carried out by means of non-parametric Fourier estimators, supports this interpretation of the role of the price-leverage covariation.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82584856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the Impact of Social Security Insurance on the Wellbeing of Pensioners in Ghana Using the Regression Discontinuity Framework","authors":"Kofi Amanor, E. F. Oteng-Abayie, P. B. Frimpong","doi":"10.2139/ssrn.3901706","DOIUrl":"https://doi.org/10.2139/ssrn.3901706","url":null,"abstract":"This paper assesses the effect of pension receipt on household and individual wellbeing in Ghana using a fuzzy regression discontinuity design. We used data obtained from 3,086 individuals of which retired workers constituted 33% of the final sample. Data was extracted from the current wave of the Ghana Living Standards Survey (GLSS 7). We find pension receipts is significantly and positively associated with expenditure for outpatient services and energy use but significantly reduces expenditure on alcohol and smoking and food consumption at the household level. However, at the individual level, we detected an increase in body mass index and acquisition of home appliances; along with a reduction in hospitalisation and consultation.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"202 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80196214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Cost of Task Switching: Evidence from Emergency Departments","authors":"Yige Duan, Yiwen Jin, Yichuan Ding, M. Nagarajan, G. Hunte","doi":"10.2139/ssrn.3756677","DOIUrl":"https://doi.org/10.2139/ssrn.3756677","url":null,"abstract":"Emergency department (ED) physicians treat patients with different symptoms and constantly switch between tasks. Using a comprehensive data set with over 650,000 patient visits to four EDs, we investigate the impact of task switching on physician productivity, quality of care, patient routing, and patient waiting time. To address estimation bias due to measurement errors and endogenous patient routing, we construct an instrumental variable that exploits the exogenous composition of waiting patients. Our estimates indicate that, at different EDs, switching between different types of patients increases the average pick-to-pick time by 3.4 to 16 percent or 0.8 to 3.1 minutes per patient, and reduces patient throughput rates accordingly. Task switching also affects how physicians route patients, although we find little impact on healthcare quality. Our counterfactual analysis further shows that eliminating the switch cost can reduce the average waiting time per patient by 25.3 to 48.3 percent and the average waiting census by 21.6 to 43.1 percent. To mitigate the switch cost, we suggest ED layout designs to facilitate patient sorting and communication between healthcare workers. Accounting for the switch cost in patient routing will also help.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87507530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Analysis of the Dynamics of Healthcare Expenditures From Country GDP and Cash Payments of Families to Medical and Pharmaceutical Support in Ukraine, CIS Countries and ЕU","authors":"O. Samborskyi, M. Slobodyanyuk, Нanna Panfilova","doi":"10.15587/2519-4852.2020.206569","DOIUrl":"https://doi.org/10.15587/2519-4852.2020.206569","url":null,"abstract":"The aim: conducting a comparative analysis of the dynamics of changes in health expenditures (%) from GDP and cash payments of families for medical and pharmaceutical support from total health expenditures in Ukraine, CIS countries and the EU (members since 2004).<br><br>Materials and methods. The data of the WHO Regional Office for Europe and such analysis methods as historical, analytical, comparative, systemic, logical, graphic, mathematical and statistical, etc. were used.<br><br>Results. According to the results of the analysis, it was found that the ex­penditures (%) on health care from the GDP of countries and the cash payments (%) made by families on medical and pharmaceutical support from the total ex­penditures on health care in 1990-2014 steadily increasing. At the same time, it was proved that the growth rate (%) of these indicators in Ukraine, the CIS coun­tries and the EU differed both in numerical values and in years of research. The largest and smallest growth values of these indicators were characteristic of Ukraine. In addition, it was internal indicators that were zigzag in their changes, for example, expenditures (%) on health care of the country's GDP in 1995 in­creased to 7.0 % from 3.3 % (1994). It is proved that in Ukraine during 1990-2014 against the background of an increase in expenditures (%) on healthcare from the country's GDP by 2.14 times. Cash (%) payments to the population of total health spending increased 1.9 times. In the CIS countries, over the same period, the above expenses increased 1.7 times, and family cash payments 1.8 times, and in the EU 1.4 times and 1.04 times respectively. Thus, it can be argued that the population of European countries against the background of a systematic increase in health care costs (%) of the country's GDP invariably spends in the form of cash payments for medical and pharmaceutical support no more than 25.0 % of the total health care costs in national health systems.<br><br>Conclusions. The presence of unstable dynamics of changes in these macro­economic indicators in Ukraine and the CIS countries compared with similar data that are presented for the EU countries is the result of a lack of a systematic vision of the reform processes of national health systems, as well as a lack of a consistent state policy to provide effective financial support to the population in the process of providing medical and pharmaceutical care<br>","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79265575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SARS-CoV-2, COVID-19, Infection Fatality Rate (IFR) Implied by the Serology, Antibody, Testing in New York City","authors":"Linus Wilson","doi":"10.2139/ssrn.3590771","DOIUrl":"https://doi.org/10.2139/ssrn.3590771","url":null,"abstract":"The SARS-CoV-2, COVID-19, infection fatality rate (IFR) has been hard to accurately estimate. It is a key parameter for disease modeling and policy decisions. Asymptomatic spread and limited testing have understated infections in hard to predict ways across jurisdictions. We survey serology, antibody, studies of the COVID-19 infection to find official cases are understated by an average of 25-to-1. Further, we analyze the deaths and infections in New York City to estimate an overall IFR for the United States of 0.863 percent.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"133 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78188945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of RCTs on Demand for Off-Label Cancer Drugs","authors":"Rebecca Mckibbin","doi":"10.2139/ssrn.3574623","DOIUrl":"https://doi.org/10.2139/ssrn.3574623","url":null,"abstract":"This paper investigates the role of randomized controlled clinical trials in the demand for cancer drugs. The unique setting of off-label prescribing, where it is possible to observe demand for a drug for a particular cancer both before and after a trial result is released, is used. A new data set combining information from scientific articles, FDA data, and Medicare claims data is constructed to estimate the effect of the release of a randomized controlled trial (RCT) on demand for off-label uses of a drug. Using variation in the timing of RCTs across off-label uses of drugs, the results show that demand for an off-label use of a drug increases on average by 85% if the RCT for that use of the drug shows a statistically significant increase in overall survival. In contrast, there is no statistically significant change in the absolute level of demand if the trial result is inconclusive. Evidence from RCTs has an important role in the extent to which new uses of drugs are adopted.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"940 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77570793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}