Breast Cancer-Related Employment Disruption and Financial Hardship in the Sister Study.

Background: More than one-half of breast cancer cases are diagnosed among women aged younger than 62 years, which may result in employment challenges. This study examined whether cancer-related employment disruption was associated with increased financial hardship in a national US study of women with breast cancer. Methods: Women with breast cancer who were enrolled in the Sister or Two Sister Studies completed a survivorship survey in 2012. Employment disruption was defined as stopping work completely or working fewer hours after diagnosis. Financial hardship was defined as: 1) experiencing financial problems paying for cancer care, 2) borrowing money or incurring debt, or 3) filing for bankruptcy because of cancer. Prevalence ratios and 95% confidence intervals for the association between employment disruption and financial hardship were estimated using multivariable Poisson regression with robust variance. Results: We analyzed data from women employed at diagnosis (n = 1628). Women were a median age of 48 years at diagnosis and 5.6 years from diagnosis at survey completion. Overall, 27.3% of women reported employment disruption (15.4% stopped working; 11.9% reduced hours), and 21.0% experienced financial hardship (16.0% had difficulty paying for care; 12.6% borrowed money or incurred debt; 1.8% filed for bankruptcy). In adjusted analysis, employment disruption was associated with nearly twice the prevalence of financial hardship (prevalence ratio = 1.93, 95% confidence interval = 1.58 to 2.35). Conclusions: Women experiencing employment disruptions after breast cancer may be more vulnerable to financial hardship. Findings highlight the need to target risk factors for employment disruption, facilitate return to work or ongoing employment, and mitigate financial consequences after cancer.

Predicting corporate credit risk: Network contagion via trade credit.

Trade credit is a payment extension granted by a selling firm to its customer. Companies typically respond to late payments from their customers by delaying payments to suppliers, thus generating a ripple through the transaction network. Therefore, trade credit is as a potential vehicle of propagation of losses in case of default events. The goal of this work is to leverage information on the trade credit among connected firms to predict imminent defaults of firms. We use a unique dataset of client firms of a major Italian bank to investigate firm bankruptcy between October 2016 to March 2018. We develop a model to capture network spillover effects originating from the supply chain on the probability of default of each firm via a sequential approach: the output of a first model component on single firm features is used in a subsequent model which captures network spillovers. While the first component is the standard econometrics way to predict such dynamics, the network module represents an innovative way to look into the effect of trade credit on default probability. This module looks at the transaction network of the firm, as inferred from the payments transiting via the bank, in order to identify the trade partners of the firm. By using several features extracted from the network of transactions, this model is able to predict a large fraction of the defaults, thus showing the value hidden in the network information. Finally, we merge firm and network features with a machine learning model to create a 'hybrid' model, which improves the recall for the task by almost 20 percentage points over the baseline.

Graduate Medical Education Should Not Be A Commodity.

The demise of Hahnemann University Hospital demonstrates the need for health care and graduate medical education policy reform.

A model of the indirect losses from negative shocks in production and finance.

Economies are frequently affected by natural disasters and both domestic and overseas financial crises. These events disrupt production and cause multiple other types of economic losses, including negative impacts on the banking system. Understanding the transmission mechanism that causes various negative second-order post-catastrophe effects is crucial if policymakers are to develop more efficient recovery strategies. In this work, we introduce a credit-based adaptive regional input-output (ARIO) model to analyse the effects of disasters and crises on the supply chain and bank-firm credit networks. Using real Japanese networks and the exogenous shocks of the 2008 Lehman Brothers bankruptcy and the Great East Japan Earthquake (March 11, 2011), this paper aims to depict how these negative shocks propagate through the supply chain and affect the banking system. The credit-based ARIO model is calibrated using Latin hypercube sampling and the design of experiments procedure to reproduce the short-term (one-year) dynamics of the Japanese industrial production index after the 2008 Lehman Brothers bankruptcy and the 2011 Great East Japan earthquake. Then, through simulation experiments, we identify the chemical and petroleum manufacturing and transport sectors as the most vulnerable Japanese industrial sectors. Finally, the case of the 2011 Great East Japan Earthquake is simulated for Japanese prefectures to understand differences among regions in terms of globally engendered indirect economic losses. Tokyo and Osaka prefectures are the most vulnerable locations because they hold greater concentrations of the above-mentioned vulnerable industrial sectors.

Presence of Any Medical Debt Associated With Two Additional Years of Homelessness in a Seattle Sample.

Although medical debt has been associated with housing instability, almost no research has connected homelessness to medical debt. We interviewed 60 individuals experiencing homelessness in Seattle, selected from those participating in self-governed encampments organized by a homeless advocacy organization. Most respondents reported having at least one kind of debt, with two-thirds reporting current medical debt. Almost half reported trouble paying medical bills for themselves or family members. Almost one-third believed medical debt was in part responsible for their current housing situation. More than half with medical debt incurred this debt while they were covered under insurance. People who had trouble paying medical bills experienced a more recent episode of homelessness 2 years longer than those who did not have such trouble, even after controlling for race, education, age, gender, and health status. People of color who had trouble paying medical bills reported almost 1 year more homelessness than whites.

The dynamics of the aggressive order during a crisis.

We investigate the dynamics of aggressive order in the financial market to further understand volatility. To analyze aggressive order, market orders in the order book are scrutinized. The market orders have different degrees of aggressiveness; therefore, we categorize market orders into four types: types Zero, One, A, and B, of which type B is the most aggressive. To examine the dynamics and impacts of each type of order, we use both macro- and micro-level approaches. From the macroscopic perspective, the burstiness and memory of type B is highly correlated with volatility. When traders face a financial crisis, they place bursty aggressive orders, and the orders are more predictable than usual. From the microscopic perspective, we additionally focus on the influence of the orders, particularly the price impact and resilience. The aggressive order has a greater impact than others, even when the price change of the aggressive order is smaller. Moreover, the aggressive order delivers more information on price because the aggressive order has a higher price impact than the execution cost.

[Financial fraud and health: a qualitative approach]. / Fraudes financieros, salud y calidad de vida: un estudio cualitativo.

During the economic crisis, developed countries have experienced financial fraud, with effects on the physical and mental health of the people affected, and on social domains. Based on the theoretical framework in literature reviews and in quantitative studies, this paper aims to obtain evidence on the effects of financial fraud on health and on the family and social environments of those affected. An intentional sample of 32 people affected by abusive and multi-currency mortgages, preferred and swap stock in Madrid was approached. In-depth interviews were conducted, and the resulting data was analysed using content analysis. Fraud-affected individuals had conditions of age, sex, educational level and occupations that possibly allowed them to accumulate economic resources throughout the course of their lives and, predictably in many cases, to take out fraudulent financial products, based on trust in the financial institutions. Financial fraud has led to the emergence of various processes of anomia and adverse health effects. The consequences on health were physical ailments (symptoms and diseases in various systems and parts of the body) and mental disorders (anxiety, depression, suicidal ideation), all affecting lifestyles, behaviour and personal and social relationships, both in affected individuals and their families. The increase in the use of medical drugs and health services serves as a final corollary to the imbalances on the affected people's health. Individuals and the Spanish society demand public health policy measures to mitigate the effects on health and the recovery of their confidence in the banking and political system.

Against the proportionality principle: Experimental findings on bargaining over losses.

The outcomes of bargaining over losses, the subject of this paper, have rarely been studied. But experimental studies of related situations, such as those involving bankruptcies or bequests in which the sum of the legal claims that can be made against a bank or firm or estate are greater than their values, have produced strong support for the proportionality principle. To test whether this principle would find support in other situations involving losses we designed an experimental game in which four players start out with differing initial endowments of real money. They are then informed that a certain amount of this resource has to be given back to the experimenter. How should the loss be shared among the agents? This game was run at different locations and under different treatments over a period of almost three years. We found that the proportionality principle was rarely proposed and even less frequently accepted as a solution to this problem. One of the main reasons for this result was that the two players with the smallest endowments opposed most of the proposals which asked them to contribute at least some positive amount of their own initial resource.

The Economic Consequences of Hospital Admissions.

We use an event study approach to examine the economic consequences of hospital admissions for adults in two datasets: survey data from the Health and Retirement Study, and hospitalization data linked to credit reports. For non-elderly adults with health insurance, hospital admissions increase out-of-pocket medical spending, unpaid medical bills, and bankruptcy, and reduce earnings, income, access to credit, and consumer borrowing. The earnings decline is substantial compared to the out-of-pocket spending increase, and is minimally insured prior to age-eligibility for Social Security Retirement Income. Relative to the insured non-elderly, the uninsured non-elderly experience much larger increases in unpaid medical bills and bankruptcy rates following a hospital admission. Hospital admissions trigger fewer than 5 percent of all bankruptcies in our sample.

Taxes, bankruptcy costs, and capital structure in for-profit and not-for-profit hospitals.

About 60% of the US hospitals are not-for-profit and it is not clear how traditional theories of capital structure should be adapted to understand the borrowing behavior of not-for-profit hospitals. This paper identifies important determinants of capital structure taken from theories describing for-profit firms as well as prior literature on not-for-profit hospitals. We examine the differential effects these factors have on the capital structure of for-profit and not-for-profit hospitals. Specifically, we use a difference-in-differences regression framework to study how differences in leverage between for-profit and not-for-profit hospitals change in response to key explanatory variables (i.e. tax rates and bankruptcy costs). The sample in this study includes most US short-term general acute hospitals from 2000 to 2012. We find that personal and corporate income taxes and bankruptcy costs have significant and distinct effects on the capital structure of for-profit and not-for-profit hospitals. Specifically, relative to not-for-profit hospitals: (1) higher corporate income tax encourages for-profit hospitals to increase their debt usage; (2) higher personal income tax discourages for-profit hospitals to use debt; and (3) higher expected bankruptcy costs lead for-profit hospitals to use less debt. Over the past decade, the capital structure of for-profit hospitals has been more flexible as compared to that of not-for-profit hospitals. This may suggest that not-for-profit hospitals are more constrained by external financing resources. Particularly, our analysis suggests that not-for-profit hospitals operating in states with high corporate taxes but low personal income taxes may face particular challenges of borrowing funds relative to their for-profit competitors.

How financial strain affects health: Evidence from the Dutch National Bank Household Survey.

The mechanisms by which financial strain affects health are not well understood. In this paper, we conduct a longitudinal mediation analysis of the Dutch National Bank Household Survey. To quantify the relative importance of biological and nonbiological pathways from financial strain to health, we consider smoking, heavy drinking and being overweight as plausible behavioural responses to financial strain but find that only 4.9% of the response of self-reported health to financial strain is mediated by these behaviours. Further analysis indicates that although financial strain increases impulsivity this has little effect on unhealthy behaviours. Economic stresses therefore appear to be distinct from other forms of stress in the relatively minor influence of nonbiological pathways to ill-health.

A Global Model for Bankruptcy Prediction.

The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world. The objective is to construct a global model with a high capacity for predicting bankruptcy in any region of the world. The results obtained have allowed us to confirm the superiority of the global model in comparison to regional models over periods of up to three years prior to bankruptcy.

Bankruptcy as Implicit Health Insurance.

This paper examines the implicit health insurance that households receive from the ability to declare bankruptcy. Exploiting multiple sources of variation in asset exemption law, I show that uninsured households with a greater financial cost of bankruptcy make higher out-of-pocket medical payments, conditional on the amount of care received. In turn, I find that households with greater wealth at risk are more likely to hold health insurance. The implicit insurance from bankruptcy distorts the insurance coverage decision. Using a microsimulation model, I calculate that the optimal Pigovian penalties are three-quarters as large as the average penalties under the Affordable Care Act.