Adverse Selection Research Articles

More Quality, Less Trust?

This study investigates how an increase in the quality of business ventures, measured as their success probability, affects trust and return on investment (ROI) in situations where the investor–entrepreneur interaction is affected by moral hazard and asymmetric information. We model a repeated trust problem between investors and entrepreneurs, featuring moral hazard and adverse selection. Hidden Markov techniques and computer simulations are used to derive the main results. We find that trust and ROI may decline as quality improves. Although lenders tend to reduce the requirements for granting initial credit, they nevertheless become less tolerant of current borrowers who fail to pay back. Additionally, we demonstrate a novel substitution effect, where lenders prefer new borrowers over existing borrowers that experienced early failures. The main conclusions of our study are that while impressing early on is effective in gaining first access to credit, it may nevertheless hurt the cause of getting credit in subsequent periods, following an early failure. In business environments plagued with ex post moral hazard, entrepreneurs might do better by gaining trust first and impressing later. Furthermore, our results imply that in a thriving economy, not only are bad loans made, but good loans are lost as well.

Exploring the Effect of the Government Interventions on the Information Asymmetry in the Post-Pandemic

The article aimed to explore the effect of the government intervention on the information asymmetry in Taiwan’s credit card market during the post-pandemic. To achieve the goal, the article constructed the information asymmetry model which was combined with the government interventions, adverse selections and moral hazards and designed the hypotheses. It was concluded that the government interventions involved with the fiscal and monetary policies failed to improve the market failure and even caused the government failure. The conclusions revealed a significant implication for the policymakers to make the proper policies when facing the challenges in the future.

A Literature Review on the Theory of Asymmetric Information

Asymmetric information refers to a situation in which one of the parties involved in a market transaction has more information than the other, which reduces efficiency in resource allocation. The basic reasons are the high cost of information acquisition, blocked information transmission channels, and lack of enough information disclosure. Problems such as adverse selection and moral hazard created by asymmetric information damage the efficiency of the market. Asymmetric information has played a very important role in lending, hotel, and catering. As for the industry of lending, the existence of asymmetric information between borrowers and lenders would make it easy for high-risk borrowers to obtain loans and, further, increase the risk of default. Asymmetric information within the hotel industry makes it hard for consumers to judge the hotels service quality and price rationality. Asymmetric information affects investment decisions and enterprise efficiency in the catering industry, distorting valuation and causing investment loss. Addressing asymmetric information in various industries is crucial for fostering market transparency and efficiency. To achieve this, researchers must employ both signaling and screening models to mitigate the adverse effects of information asymmetry. This paper examines historical literature on asymmetric information across diverse industries and delineates strategies to enhance information transparency and promote more informed decision-making.

Antimicrobial prescribing in French nursing homes and interventions for antimicrobial stewardship: a qualitative study

BackgroundOveruse of antibiotics is frequent in nursing homes (NHs) leading to adverse events and selection of resistant bacteria. Antimicrobial stewardship interventions showed heterogeneous effects on reducing inappropriate use of antimicrobials in NHs.ObjectivesThis study aimed (1) to analyze antimicrobial prescribing determinants in NHs; (2) to identify which resources for antimicrobial prescribing are used by NHs’ physicians (3) understand which antimicrobial stewardship interventions are required and how they should be implemented in NHs.MethodsWe conducted individual semi-directed interviews with NHs’ prescribing physicians in Ile-de-France, France. A thematic content analysis was conducted iteratively.ResultsThirteen interviews were conducted. Participants were mostly women, with a median age of 48 years and a median professional experience in NHs of three years. Participants included medical coordinators, general practitioners and salaried physicians. Main determinants of antimicrobial prescribing in NHs were the perceived risk of infectious complications and discomfort in residents, the difficulty in obtaining microbiological samples and the lack of healthcare professionals to monitor patients. Most participants reported using national guidelines and electronic decision support systems to guide their antimicrobial prescribing. Institutional constraints accentuate situations of doubt and prompt physicians to prescribe antimicrobials “just in case” despite the will to follow guidelines and the known risks of antimicrobial misuse. Physicians stated that proper antimicrobial use in NHs would require a major effort but was not judged a priority as compared to other medical issues. Producing guidelines tailored to the NH’s context, performing good practice audits with feedback on antimicrobial prescribing, and reinforcing multidisciplinary relationships and discussions between city and hospital professionals were cited as potential interventions. The role of the medical coordinator was described as central. According to physicians, collaboration among stakeholders, providing support and training during the process might prove effective strategies to ensure successful implementation.ConclusionAntimicrobial prescribing is a complex decision-making process involving different factors and actors in NHs. Tailored guidelines, good practice audits, strengthened multidisciplinary collaboration were proposed as key AMS interventions. Physicians emphasized the central role of the medical coordinator supported by stakeholder engagement, collaboration, training and ongoing support for successful implementation.

Effect of households’ members disability and serious illness on public health insurance subscription among urban refugees during the COVID-19 pandemic in Kenya

BackgroundThe adverse selection theory speculates a high level of demand for health insurance by people with vulnerable health conditions. However, the COVID-19 pandemic changed the prevailing narratives and pattern of healthcare utilization in many African countries. This study estimated the effects of household member’s disability and presence of serious illness on the probability of National Hospital Insurance Fund (NHIF) subscription with the average treatment effect (ATE) and average treatment effect on the treated (ATET).MethodsThe data were collected telephonically in 2020 using the sampling frame of the United Nations High Commission on Refugees (UNHCR). The respondents were refugees with active phone numbers who were registered by the UNHCR in Nairobi, Mombasa and Nakuru cities. A total of 2,438 completed the surveys. The data were analysed with Treatment Effects Probit regression model using the regression adjustment estimator.ResultsThe results showed that 24.89% of the respondents had health insurance. Also, 3.28%, 1.39% and 2.46%, respectively suffered from physical, cognitive and sensory disability, while 8.28% had some form of serious illness. The Probit regression results showed that probability of being health insured significantly increased (p < 0.05) with membership of community-based organizations (CBO), asset index, possession of bank savings account, residence in Nairobi and household size, while residence in Nakuru reduced it. The ATE for physical and cognitive disabilities were significant (p < 0.05) with 0.1100 and 0.1816, respectively, while that for serious illness was 0.1046 (p < 0.01). The ATET for physical disability and serious illness were also significant (p < 0.05) with 0.1251 and 0.0996, respectively.ConclusionIt was concluded that efforts to facilitate NHIF subscriptions among the refugees should be channelled among people with disability and serious illness. In addition, there is the need to promote refugees’ welfare through employment that can induce formal savings and promote less reliance on informal borrowing. The operational mechanisms and differences in healthcare service distribution between the three cities should be considered along some salient interventions for health insurance subscription that are channelled through some CBOs.

Multi-Borrowing Practices and Loan Repayment of Micro and Small Enterprises in Trade Sector in Meru County, Kenya

In Kenya, the increase in multi-borrowing and its effects on loan repayment is a growing concern for microfinance institutions. The general purpose of this research was to establish the effect of multi-borrowing on loan repayment among MSEs in Meru County. Specifically, the study aimed to determine how the number of loans borrowed, interest payable, and the financial literacy of borrowers influenced loan repayment within Meru County Microfinance. The research was anchored on information asymmetry, prospect theory, moral hazard, and adverse selection theories. The study targeted 6,000 MSE owners who were members of Meru County Microfinance, from which a sample of 200 borrowers was selected. A descriptive research design was employed to assess how multiple borrowings affected loan repayment. Cluster and random sampling methods were used to identify respondents across the seven branches of Meru County Microfinance. Primary data was collected using questionnaires, and analyzed by use of descriptive, correlational, and regression analysis techniques. Inferential analysis was conducted at a 0.05 significance threshold, utilizing the Statistical Package for Social Sciences (SPSS) version 28 for data analysis. Ethical standards were strictly observed throughout the study. The study revealed that the number of loans borrowed had a significant impact on loan repayment among MSEs in Meru County. Effective management of borrowing was crucial for better repayment outcomes. Interest payable was identified as a critical factor affecting loan repayment; enterprises with well-managed credit risk practices, including the adjustment of interest rates and repayment schedules, exhibited better repayment performance. Furthermore, the level of financial literacy positively influenced loan repayment, with higher financial literacy levels leading to improved loan management and repayment behaviors. The study concluded that the number of loans borrowed significantly affected loan repayment, although its impact was less direct compared to other factors. Interest payable had the most substantial effect on loan repayment, with effective credit risk management correlating strongly with better repayment outcomes. Additionally, a higher level of financial literacy was found to significantly enhance loan repayment. Based on the findings, it is recommended that micro and small enterprises regularly review and manage their borrowing policies to improve loan repayment. Financial institutions should implement clear policies on irrecoverable loan provisions and adopt robust credit management practices to ensure better loan repayment. Moreover, enhancing financial literacy among borrowers is crucial for improving loan repayment, and thus, targeted financial education programs should be developed. Policymakers should also evaluate and update regulatory frameworks to support effective loan management and repayment practices within microfinance institutions.

Exploring the Impact of the Cash Cards on Taiwan’s Dual-Card Crisis under the Information Asymmetry

Abstract The purpose of the article was to explore the impact of the cash cards on Taiwan’s dual-card crisis under the information asymmetry. Accordingly, the article was based on the quality analysis primarily combined with the method of the document analysis and constructed the information asymmetry model ,including the two criteria of the adverse selections and the moral hazards. The results of the article showed that the impact of the cash cards on Taiwan’s dual-card crisis was no less than that of the credit cards even if the issuing scale of the cash cards was much smaller . The findings revealed the significant management implication for the financial authorities that the cash cards shouldn’t be ignored if the dual-card crisis needed to be solved. JEL classification: G01, G21, G28. Keywords: Cash card, Information asymmetry, Adverse selections, Moral hazards, Dual-card crisis.

Cream Skimming and Technological Innovations in Automobile Insurance Market

Abstract This study examines the effect of telematics devices on the automobile insurance market. Automobile insurance using these devices is marketed as pay-how-you-drive (PHYD) automobile insurance. Insurers can directly monitor the insured’s vehicle for risky driving behaviors such as speeding. Some of insureds receive discounts on their premiums for driving more cautiously. On the other hand, accumulating the insured’s driving skills, insurers may be able to only sign up insureds with low accident rates, widely known as cream skimming. By applying Hodgson (2014. “Adverse Selection in Health Insurance Markets: A Classroom Experiment.” The Journal of Economic Education 45 (2): 90–100), we tested whether PHYD programs makes it easier for insurers to contract with low-risk drivers. Repeated cream skimming suggests that only high-risk drivers remain in the market and a residual market cannot be established, which could lead to adverse selection and market failure in the absence of any regulations. However, the experiment revealed that low-risk but highly risk-averse subjects tend to dislike the fluctuation in premiums by enrolling in PHYD programs. The results could be effective in future regulatory construction.

Promotions, Adverse Selection, and Efficiency

Promotions, Adverse Selection, and Efficiency

Higher Education, Higher Salaries? A Case Applied to Graduates in Economics

This document aims to contribute to the understanding of the determinants for choosing the Economics career in Bolivia, as well as the impact that postgraduate education has on the salary levels of graduates in this field. Regarding the latter aspect, it seeks to test whether the number of years of study following the undergraduate degree of an economist determines a higher salary level and whether postgraduate studies serve as a signal of differentiation in the labour market. To achieve the objectives outlined in this document, various linear probability econometric models are employed, constructed from the results of a survey conducted in 2024 with 79 graduates and 45 students from the Economics program at the Universidad Católica Boliviana “San Pablo.” The results suggest that the choice of the Economics career is more likely influenced by close individuals rather than by the information provided by the University about the content of the program. Furthermore, a greater number of years of study after obtaining an undergraduate degree decreases the likelihood of achieving higher salary returns, indicating signs of adverse selection within the labour market for economists in Bolivia.

Equity offering following cyberattacks

We investigate the impact of cyberattacks on a firm's equity issuance decisions. Our findings indicate that firms targeted by cyberattacks are less likely to pursue seasoned equity offerings (SEOs) afterward. This effect is more pronounced when the target firm has lower external financing needs and operates in a poor information environment. This result remains robust after addressing sample selection bias through propensity score matching and entropy balancing approaches. We attribute this reduction in SEO activities to reputation loss, investors' adverse selection, and the resulting higher equity financing costs. Furthermore, we demonstrate that the negative impact of cyberattacks on SEOs extends to industry peers. This spillover effect is stronger when the target firm suffers significant reputation loss, when the stock prices of peers closely correlate with those of the target firm, when peer firms possess a higher ex-ante cyber risk, and when they are more vulnerable to future cyberattacks.

Employer Credit Checks: Poverty Traps Versus Matching Efficiency

Abstract We develop a framework to understand pre-employment credit screening as a signal from credit markets that alleviates adverse selection in labour markets. In our theory, people differ in both their propensity to default on debt and the profits they create for firms that employ them; in our calibrated economy, highly productive workers have a low default probability. This leads firms to create more jobs for those with good credit, which creates a poverty trap: an unemployed worker with poor credit has a low job finding rate, but cannot improve her credit without a job. This manifests as an endogenous loss in present-discounted wages that is typically taken as exogenous in quantitative models of consumer default. Banning employer credit checks eliminates the poverty trap, but pools job seekers and reduces matching efficiency: average unemployment duration rises by 2 days for high productivity workers and falls by 13 days for low-productivity workers.

The Economics of Education: A Panel Data Analysis of the Impact of Gendered Human Capital on Output Growth in India

Using panel regressions, this article investigates to what extent a reduction in gender inequality in education may increase growth of output at sub-national level in India. The article finds a considerable impact of gender inequality on economic growth which is robust. Point estimates suggest that 0.58% of the growth rate is accounted for by a better gender ratio in education attainment. Given the assumption that the distribution of innate abilities among males and females is equal, it is observed that under-addressed issue of gender equity has resulted in educational inequality and further to the adverse selection of a less efficient pool of labour having a negative impact on economic growth through lowering the average quality of human capital. Gender equality is an outcome-based achievement depending upon the successful accessibility of opportunities by females thereby the issue of gender equity becomes the precondition for gender equality.

Dilemmas and Governance Strategies in the Implementation of the Modern Apprenticeship System in Chinese Vocational Colleges: A Perspective from Principal-Agent Theory

As China's industrial economy transitions towards high-quality development, the demand for highly skilled technical personnel has surged. The modern apprenticeship system, an important mechanism for deepening collaboration between educational institutions and enterprises, has been widely promoted within vocational colleges. However, nearly a decade into its implementation, this system faces challenges such as insufficient engagement from enterprises, loose relationships between schools and businesses, and a lack of assessment and feedback mechanisms. These issues have led to suboptimal outcomes in talent development. This paper innovatively applies principal-agent theory to expose conflicts in value demands, adverse selection, and moral hazards within the multifaceted principal-agent relationships among vocational colleges, enterprises, and the government. It proposes governance strategies that involve multi-stakeholder participation in policy-making, the establishment of qualification entry systems for cooperative enterprises, and the improvement of supervision and incentive mechanisms. These strategies aim to resolve conflicts and enhance cooperation efficiency, thereby providing robust support for the effective implementation of the modern apprenticeship system in vocational colleges.

Big data and machine learning-based decision support system to reshape the vaticination of insurance claims

Based on actuarial science theory, decision-making theory, and anonymous big data, this study employs machine learning to advance insurance claim forecasting, aiming to enhance pricing accuracy, mitigate adverse selection risks, and optimize operational efficiency for improved customer satisfaction and global competitiveness. The study utilized the Boruta algorithm with LightGBM for feature selection, analyzing a 57-dimensional dataset and identifying an optimal subset of 24 features. The improved LightGBM model achieved superior results (AUC ∼ 0.9272 and accuracy ∼ 92.94 %), surpassing other models evaluated. Beyond operational improvements, the proposed model holds the potential to contribute to various United Nations SDGs, such as promoting financial inclusion (SDG 1; SDG 10), reducing fraud, improving public safety (SDG 3; SDG 11; SDG 13), and encouraging sustainable practices (SDG 9; SDG 11). By utilizing data-driven insights to make more informed and accurate decisions, insurance companies can provide better services to their policyholders and contribute to a more equitable and sustainable society.

A duality and free boundary approach to adverse selection

Adverse selection is a version of the principal-agent problem that includes monopolist nonlinear pricing, where a monopolist with known costs seeks a profit-maximizing price menu facing a population of potential consumers whose preferences are known only in the aggregate. For multidimensional spaces of agents and products, Rochet and Choné (Econometrica, 1998) reformulated this problem as a concave maximization over the set of convex functions, by assuming agent preferences combine bilinearity in the product and agent parameters with a quasilinear sensitivity to prices. We characterize solutions to this problem by identifying a dual minimization problem. This duality allows us to reduce the solution of the square example of Rochet–Choné to a novel free boundary problem, giving the first analytical description of an overlooked market segment.

Insurance Coverage and Flood Exposure in the Gulf of Mexico: Scale, Social Vulnerability, Urban Form, and Risk Measures

Increasing flood losses in the Gulf of Mexico related to development patterns and climate hazards pose serious threats to resilience and insurability. The purpose of this study is to understand how scale, social vulnerability, risk, and urban form relate to National Flood Insurance Program (NFIP) policy coverage and flood exposure. Our multilevel models identify that flooding is significantly clustered by region and counties, especially shoreline counties. Our measures of risk suggest that the Federal Emergency Management Agency (FEMA) special flood hazard area (SFHA) underestimates risk and exposure when compared with the Flood Factor and that there is some compensation in terms of insurance coverage, suggesting a pattern of adverse selection. Older housing stock appears both less insured and less exposed, raising questions of whether current growth patterns are increasing risk independent of environmental change. Our models suggest that census tracts with higher percentages of black residents are less insured and more exposed, and a similar pattern exists for rural areas. Our results highlight the need to seek common solutions across the Gulf of Mexico, concentrating on the most flood-exposed counties, and that specific resilience strategies may be necessary to protect areas with socially vulnerable populations, especially in rural areas. Underlying challenges exist due to the spatial relationship between exposure and social vulnerability and the potential for adverse selection in insurance markets due to different measures of risk.

Exploring the Effects of the Information Asymmetry on the Card-Debt Crisis

The article aimed to explore the effects of the information asymmetry on the card-debt crisis in Taiwan’s credit card market. The card-debt crisis of the credit cards broke out in Taiwan in 2005. To improve this situation, the financial authorities were forced to intervene in the market. The article employed the documents analysis and collected the related literature and statistical data to construct the information asymmetry model and the proposed hypotheses of the adverse selections and the moral hazards. The results concluded that the card-debt crisis did stem from the information asymmetry, and was alleviated by the intervention of the financial authorities.

Small and medium-sized enterprises and sustainable transition: Role of FinTech in a country's banking ecosystem

During the sustainable transition, small and medium-sized enterprises (SMEs) request funding to support environmental, social, and governance (ESG) investments. In particular, these requests clash with information asymmetries typical of the bank–firm relationship, causing SMEs to experience credit crunch phenomena or increased loan costs. This aforementioned phenomenon prompted this study to examine whether FinTech increases banks’ ability to support the development of SMEs aimed at achieving ESG or, better yet, sustainable transition goals. The results suggest that FinTech in a country’s banking ecosystem improves the ESG performance of Italian and British SMEs by addressing adverse selection and moral hazard issues. This study also shows a more pronounced effect in the UK banking ecosystem, which has a higher level of FinTech development and diffusion.

Adverse selection in tontines

Adverse selection in tontines