Opt Out or Top Up? Voluntary Healthcare Insurance and the Public vs. Private Substitution

We investigate whether people enrolled into voluntary health insurance (VHI) substitute public consumption with private (opt out) or just enlarge their private consumption, without reducing reliance upon public provisions (top up). We study the case of Italy, where a mixed insurance system is in place. To this purpose, we specify a joint model for public and private specialist visits counts, and allow for different degrees of endogenous supplementary insurance coverage, looking at the insurance coverage as driven by a trinomial choice process. We disentangle the effect of income and wealth by going through two channels: the direct impact on the demand for healthcare and that due to selection into VHI. We find evidence of opting out: richer and wealthier individuals consume more private services and concomitantly reduce those services publicly provided through selection into for-profit VHI. These results imply that the market for VHI eases the redistribution from high income (doubly insured) individuals to low income (not doubly insured) ones operated by the Italian National Health Service (NHS). Accounting for VHI endogeneity in the joint model of the two counts is crucial to this conclusion.public provision of private goods, health insurance, bivariate count data model, endogenous multinomial treatment, simultaneous equation modeling

Genetics in psychiatry: Methods, clinical applications and future perspectives

Psychiatric disorders and related traits have a demonstrated genetic component, with heritability estimated by twin studies generally between 80% and 40%. Their pathogenesis is complex and multi‐determined: environmental factors interact with a polygenic architecture, making difficult the development of models able to stratify patients or predict mental health outcomes. Despite this difficult challenge, relevant progress has been made in the field of psychiatric genetics in recent years. This review aims to present the main current methods in psychiatric genetics, their output, limitations, clinical applications, and possible future developments. Genome‐wide association studies (GWASs) performed in increasingly large samples have led to the identification of replicated genetic loci associated with the risk of major psychiatric disorders, including schizophrenia and mood disorders. Statistical and biological approaches have been developed to improve our understanding of the etiopathogenetic mechanisms behind genome‐wide significant associations, as well as for estimating the cumulative effect of risk variants at the individual level and the genetic overlap between different disorders, as pleiotropy is the rule rather than the exception. Clinical applications are available in the pharmacogenetics field. The main issues that remain to be addressed include improving ethnic diversity in genetic studies and the optimization of statistical power through methodological improvements, such as the definition of dimensional phenotypes with specific biological correlates and the integration of different types of omics data

Style of practice and assortative mating: a recursive probit analysis of cesarean section scheduling in Italy

We study practice variation in scheduling of cesarean section delivery across public and private hospitals in Italy. Adopting a novel perspective, we look at the role played by patients’ preferences for the treatment. The recursive probit model is revisited as a useful tool to assess the presence of assortative mating of patients and provider driven by style of practice. According to our evidence the propensity to scheduling a cesarean section is codetermined with patient self-sorting into hospital types. We measure a significantly higher inclination to practice cesarean section scheduling in private hospitals and conclude that assortative mating is of minor relevance in our case, even if we cannot exclude it to be presen

Public vs. private health care services demand in Italy

In this paper we use data coming from the new Italian Survey on Health Ageing and Wealth (SHAW) to analyse physician services utilization in Italy explicitly acknowledging the existence of two different classes of providers: public and private. We consider visits by a specialist physician as the measure of individual services utilization. In particular we assess the relative importance of variables like income, education, private insurance and supply characteristics as determinants of the utilization of such services, while controlling for individual health and need. We do that by estimating some alternative count data regression models of which we discuss the relative advantages and disadvantages and the entailed different interpretation of the results

Opt out or Top up? Voluntary Healthcare Insurance and the Public vs. Private Substitution

We investigate whether people enrolled into voluntary health insurance (VHI) substitute public consumption with private (opt out) or just enlarge their private consumption, without reducing reliance upon public provisions (top up). We study the case of Italy, where a mixed insurance system is in place. To this purpose, we specify a joint model for public and private specialist visits counts, and allow for different degrees of endogenous supplementary insurance coverage, looking at the insurance coverage as driven by a trinomial choice process. We disentangle the effect of income and wealth by going through two channels: the direct impact on the demand for healthcare and that due to selection into VHI. We find evidence of opting out: richer and wealthier individuals consume more private services and concomitantly reduce those services publicly provided through selection into for-profit VHI. These results imply that the market for VHI eases the redistribution from high income (doubly insured) individuals to low income (not doubly insured) ones operated by the Italian National Health Service (NHS). Accounting for VHI endogeneity in the joint model of the two counts is crucial to this conclusion

Throughput Analysis of Wireless Sensor Networks via Evaluation of Connectivity and MAC Performance

Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide

New insights on the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at SNP, gene and pathway level. Coverage of genetic variants was increased compared to previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. 7,062,950 SNPs were analysed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (p=1.80e-08, ITGA9 (integrin alpha 9)) and rs76191705 (p=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At gene level, no consistent effect was found. At pathway level, the Gene Ontology terms GO:0005694 (chromosome) and GO:0044427 (chromosomal part) were associated with improvement (corrected p=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (p=0.047), while rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role

Testing exogeneity in the bivariate probit model: Monte Carlo evidence and an application to health economics

Many economic applications involve the modeling of a binary variable as simultaneously determined with one of its dycotomous regressors. In this paper we deal with a prominent health economics case study, that of cesarean section delivery utilization across public and private hospitals. Estimating the probability of cesarean section in a univariate framework neglecting the potential endogeneity of the hospital type dummy might lead to invalid inference. Since little is known about the exact sampling properties of alternative statistics for testing exogeneity of a dycotomous regressor in probit models, we conduct an extensive Monte Carlo experiment. Equipped with the simulation results we apply a comprehensive battery of tests to an Italian sample of women and find clear evidence against exogeneity of the hospital type dummy. We speculate on the economic implications of these results and discuss the misleading interpretation arising from the adoption of either univariate probit model or seemingly unrelated bivariate probit model

Testing exogeneity of multinomial regressors in count data models: does two stage residual inclusion work?

We study a simple exogeneity test in count data models with possibly endogenous multinomial treatment. The test is based on Two Stage Residual Inclusion (2SRI). Results from a broad Monte Carlo study provide novel evidence on important features of this approach in nonlinear settings. We find differences in the finite sample performance of various likelihood-based tests under correct specification and when the outcome equation is misspecified due to neglected over-dispersion or non-linearity. We compare alternative 2SRI procedures and uncover that standardizing the variance of the first stage residuals leads to higher power of the test and reduces the bias of the treatment coefficients. An original application in health economics corroborates our findings

The Possibilities of Graphic Ethnography: An Interview with Claudio Sopranzetti, Sara Fabbri and Chiara Natalucci

Claudio Sopranzetti, Sara Fabbri, and Chiara Natalucci are the team behind the new graphic ethnography The King of Bangkok (University of Toronto Press 2021). The King of Bangkok tells the story of Nok, an urban migrant from Thailand’s northeastern region as he moves back and forth from his home village and attempts to build a life in the country’s capital across periods of massive economic growth and collapse and periods of democratic expansion, state violence, and political closure. Structured around a series of flashbacks, The King of Bangkok shows how these historical events shaped Nok’s life and how Nok’s life came to shape those events. The book was originally published in Italian (Add Editore, 2019) and was subsequently translated into Thai as Taa Sawaang (Awakening, อ่านอิตาลี 2020). In this interview we ask Claudio, Sara, and Chiara about their experience creating this text, its relationship with more traditional ethnographic genres of writing, and the effects their project has had in Thailand. We are delighted to feature a small section of the book following the interview