Risk Aversion Research Articles

CEO childhood trauma experience and firm internationalization

Purpose The purpose of this study is to examine how the childhood trauma experiences of CEOs influence firms’ internationalization. Design/methodology/approach The research used a difference-in-difference method with constructing a treatment group whose chief executive officer (CEO) experienced the great famine in China between the ages of 7 and 11, and a control group whose CEO was born within three years after 1961. Findings The study reveals a significant inverse correlation between CEOs’ childhood trauma experiences and firm internationalization. However, this correlation is weaker in the case of state-owned enterprises and firms led by CEOs with overseas work experience. Originality/value To the best of the authors’ knowledge, this study is the first to extend the theoretical framework to elucidate firms’ internationalization by introducing childhood trauma theory into the field of international business literature. Second, the authors link the literature on the effect of CEO explicit traits and psychological traits on firm internationalization by exploring how CEOs’ childhood trauma experience shapes their risk aversion, which, in turn, influences firm internationalization. Third, the authors address the call for examining the interplay of CEO life experiences by scrutinizing the moderating effect of CEO overseas work experience on the association between CEOs’ childhood trauma exposure and firm internationalization.

Heterogeneity in crowd‐out by risk aversion: Assessing the effect of the ACA Medicaid expansion

AbstractIn this study, I estimate the heterogeneity in the crowd‐out of private health insurance by risk aversion with the Medicaid expansion under the Affordable Care Act. Using data from the Health and Retirement Study, I find that the Medicaid expansion led to a decrease in private coverage among risk‐loving individuals by 5 percentage points. However, the expansion did not lead to any meaningful change in private coverage for risk‐averse individuals. This finding suggests that risk‐averse individuals are willing to keep their private coverage, even though they become eligible for Medicaid. This potentially signals a sorting effect into private insurance. Under the assumption that highly risk‐averse individuals typically display superior health conditions, this preferential behavior could signify a form of advantageous selection into private insurance. Furthermore, the expansion increased Medicaid coverage by 3.4 percentage points for risk‐loving individuals, while not causing any discernible change in coverage among risk‐averse individuals. Such differential responses could potentially influence the risk composition of Medicaid coverage, and subsequently impact the cumulative expenditure associated with it.

ALM for insurers with multiple underwriting lines and portfolio constraints: a Lagrangian duality approach

We investigate how an insurance firm can optimally allocate its assets to back up liabilities from multiple non-life business lines. The insurance risks are modeled by a multidimensional jump-diffusion process that accounts for simultaneous claims in different insurance lines with policy limits. We use Lagrangian convex duality techniques to derive optimal investment-underwriting strategies that maximize the expected utility from dividends and final wealth over a finite horizon. We examine how risk aversion, prudence, portfolio constraints, and multivariate insurance risk affect the firm’s earnings retention. We obtain explicit solutions for optimal strategies under constant relative risk aversion preferences. Finally, we illustrate our results with numerical examples and show the impact of co-integration for asset-liability management with multiple sources of insurance risk.

The influence and mechanism of female-headed households on household debt risk: empirical evidence from China

With the development of society, the number of female-headed households is on the rise. Based on the data from the China Household Finance Survey (CHFS) in 2019, this paper establishes a Tobit model to study the influence of female-headed households on household debt risk. Results indicate that female-headed households can substantially reduce household debt risk, and this conclusion still holds after overcoming endogeneity issues. Further tests on the mediating effect reveal that risk aversion and housing property holding have partial mediating effects and masking effects, respectively, in the path of female-headed households affecting household debt risk. In addition, the heterogeneity analysis indicates that the influence of female-headed households on household debt risk is more significant in third-tier cities, as well as in families without children, families without elderly members, and families with more than two elderly members. The conclusions of this paper provide a reference for the relevant policy measures to reduce household debt risk and promote gender equality.

Does religious atmosphere affect enterprise digital transformation? Evidence from China

This study examines whether and how religious atmosphere affects enterprise digital transformation. We find religious atmosphere is significantly negatively associated with digital transformation. We also find religion inhibits digital transformation through strengthening risk aversion and weakening innovation consciousness. Additional results show that the effect of religion on enterprise digital transformation is significant primarily in firms with fewer senior executives affiliated with the CPC and managers who possess less conservative personalities. The inhibiting effect is more pronounced for non-state-owned firms and firms with lower institutional ownership. Moreover, the significant effect only exists in areas with lower market competition and weaker government intervention. Moreover, indigenous religious tradition attenuates the positive impact of digital transformation on firm productivity. Overall, our findings provide insights for understanding the role of religion, as an informal institution, in firms’ decision-making in emerging markets.

Mind the Gap: Why Wealthy Voters Support Brexit

Abstract Wealth provides self-insurance against financial risk, reducing risk aversion. We apply this insurance mechanism to electoral behaviour, arguing that a voter who desires a change to the status quo and who is wealthy is more likely to vote for change than a voter who lacks the same self-insurance. We apply this argument to the case of Brexit in the UK, which has been widely characterized as a vote by the ‘economically left-behind’. Our results show that individuals who lacked wealth are less likely to support leaving the EU, explaining why so many Brexit voters were wealthy, in terms of their property wealth. We corroborate our theory using two panel surveys, accounting for unobserved individual-level heterogeneity, and by using a survey experiment. The findings have implications for the potential broader role of wealth-as-insurance in electoral behaviour and for understanding the Brexit case.

Double-edged sword: Does strong creditor protection in the bankruptcy process affect firm productivity

Using data from Chinese A-share listed firms from 2015 to 2022, a difference-in-differences model is employed to empirically examine the impact of bankruptcy regimes, marked by the establishment of the bankruptcy court, on firms' total factor productivity (TFP). The results show a significant decline in TFP among firms in regions following the establishment of the bankruptcy court. This result remains valid after a series of robustness tests. Mechanism tests reveal that bankruptcy court heightens firms' risk aversion by endowing excessive rights to creditors. Consequently, firms tend to downwardly adjust capital structure, curtail innovation investment, and accumulate liquid assets as coping measures, ultimately contributing to a decline in TFP. However, well-developed market mechanisms can alleviate the negative impact of bankruptcy court excessively protecting creditors. Specifically, when firms are located in regions with weak government intervention and strong financial development, as well as in market environments with low uncertainty and strong competition, this negative impact can be mitigated. Moreover, we find that under bankruptcy court operations, while a series of risk reduction measures taken by firms triggers a decline in TFP, it mitigates financial distress. These findings provide fresh insights into the dual nature of creditor protection and offer valuable references for governments to improve the bankruptcy legal system.

Risk-averse behavior and incentive policies: A new perspective on spatial–temporal traceability supervision in construction logistics supply chains

Spatial-temporal decision support systems (STDSS) serve as a crucial strategy for enhancing operational governance and mitigating risk within construction logistics. However, construction supply chains involve many opaque stakeholders, hindering whole industry compliance monitoring. This research formulates a tripartite evolutionary game model that scrutinizes the strategic interactions among government regulators, carriers, and contractors, thereby offering insights into the collaborative supervision outcomes shaped by these stakeholder engagements. Government regulators choose intelligent supervision incentives versus regular oversight. Carriers decide whether to invest in STDSS or not. Contractors cooperate by enrolling or declining STDSS. As key STDSS investors, carriers’ decisions are investigated under varying risk preferences in an extension model. This examines how government incentives influence long-term intelligent supervision and risk aversion behavior emergence to improve safety and quality across construction supply chains. Our findings indicate that increased adverse events motivate government regulators to adopt STDSS incentives for oversight, though carriers and contractors are not necessarily prompted to implement STDSS themselves. Escalating risk aversion reduces carrier STDSS adoption likelihood as they maintain basic services. Carriers perceiving contractor free riding as unfair competition also demotivates STDSS rollout. Although larger subsidies initially raise STDSS implementation probability, carriers become unwilling to adopt STDSS over time even with greater subsidies. In summary, adverse events drive regulator but not necessarily carrier and contractor STDSS adoption, while risk aversion, perceived fairness and changing subsidy effectiveness over time shape carrier decisions.

Risk and time preferences in individuals with lifestyle-related and non-lifestyle-related cardiovascular diseases: a pilot study

ObjectivesTo (1) pilot a study of behavioural characterisation based on risk and time preferences in clinically well-characterised individuals, (2) assess the distribution of preferences in this population and (3) explore...

Interplay between the agriculture firm’s guarantee strategy and the e-commerce platform’s loan strategy with risk averse farmers

Many agricultural firms procure products from smallholders and sell them on platforms by paying a proportional fee. Generally, smallholders lack capital for production, and e-commerce platforms can provide loans to them. However, smallholders are risk averse, leading them to make conservative production decisions. Additionally, smallholders face bankruptcy risk due to output uncertainty and the interest burden of platforms’ loans. These factors further adversely affect smallholders’ conservative decisions. To alleviate this situation, the firm can provide loan guarantees for smallholders. This study considers a supply chain consisting of risk-averse farmers, an agricultural firm, and an e-commerce platform. The firm first decides the number of farmers to provide guarantees, and then the platform sets loan interest rates for guaranteed and non-guaranteed farmers. Thereafter, the firm decides purchase prices, and each farmer decides his production input. Given the number of guaranteed farmers, we find that the platform will charge each farmer a positive loan interest if the proportional fee is small, but it will offer interest-free (non-negative) loans to guaranteed (non-guaranteed) farmers if the proportional fee is large. Additionally, with the increase in guaranteed farmers, the firm’s profit and the farmers’ utilities are not necessarily monotonic. We further show that guaranteeing a portion of farmers is always detrimental to the firm but may be better for all the farmers. Therefore, it is better for the firm to provide a guarantee to all farmers or just offer no guarantee to any farmer, depending on the magnitudes of proportional fees and the production input efficiency.

Confidence and Outcome Expectations in Bilateral Negotiations–A Dynamic Model

AbstractThis work proposes and studies a dynamic model of two bargaining parties exchanging offers over time, considering their confidence about the share of the “pie” they obtain, which translates into expectations regarding the outcome of the bargaining process. The model predicts the sequence of offers as well as the final agreement for given confidence parameters. A mathematical analysis of the model shows the outcome is an Asymmetric Nash Bargaining Solution with exponents determined by the bargainers’ confidence. Moreover, a compensation effect can be found between confidence and risk aversion. This work also considers that confidence levels of bargainers might change during the negotiation, and we conduct a comprehensive simulation study to analyze the effect of such changes. Through Monte-Carlo simulation, we show that a bargainer is better off if its confidence increases, but the advantage is lost if the other party’s confidence increases in a similar way. In that case, concessions are smaller and negotiations last longer. Changing confidence parameters make the outcome harder to predict, as it will depend more on the final confidence than the initial one. The simulations also show that the average size of concessions, and therefore the final agreement, depend not only on whether confidence increases or decreases, but also on the change rate, with stronger effects observed when change accelerates towards the end of the process.

Signature size and individual preferences

In this digital economy, customers' handwriting, such as signatures and related characteristics, can be easily collected and quantitatively analyzed. From the perspective of decision-making, obtaining information from signature characteristics is an important data-driven business leverage. In this regard, can we infer individual preferences from signatures? Thus, through a large-scale laboratory experiment, this study measured the participants’ risk and time preferences and collected their signature information in order to determine the influence of behavioral preferences on their signatures. Based on the empirical results, the higher the risk and ambiguity aversion of the participants, the smaller were their signature sizes. Moreover, the greater their level of patience, the more likely their signatures showed a trend of increasing size. Overall, this study fills a research gap in signature-related behavior by highlighting the application of text mining in digital handwriting, especially in broad business settings such as the insurance industry.

Mortgage choice and inflation experiences in the Eurozone

In the Eurozone, households’ mortgage preferences vary widely, both within and across countries. This persistent heterogeneity in the choice between an adjustable rate mortgage (ARM) and a fixed rate mortgage (FRM) two decades after introducing a common currency is a puzzle. We argue that these patterns relate to the long-lasting effect of personal experiences of high-inflation periods. Analysing rich household data across 9 countries, we show that higher lifetime experienced inflation predicts significantly lower probability of holding an FRM: a 1 log-point increase in experienced inflation predicts a 71% decrease in the odds of holding an FRM. We relate our findings to existing theories on household mortgage risk management and argue that Eurozone prepayment penalties heighten the ‘inflation risk’ associated with FRMs. We also find that past personal inflation experiences are associated to risk aversion: households with histories of high and volatile inflation report lower willingness to take financial risk.

Does time-varying risk aversion sentiment matter in the connectedness among Sub-Saharan African bond markets?

Several bond markets in sub-Saharan Africa (SSA) are defaulting due to hiking spreads amid the stressed states introduced by the COVID-19 pandemic and the geopolitical risk tensions from the Russia-Ukraine conflict. Are there controllable factors that drive these markets? We investigate the dynamic connection shared by SSA bond markets and assess the role of investor sentiment measures, focusing on the risk aversion sentiment of international investors. Our results, across different trading horizons, are expected to aid in the formulation of policies for regulating and developing bond markets of emerging economies, particularly SSA. In terms of both return and volatility of SSA bonds, we find risk aversion sentiment an important transmitter of spillover for all investment horizons.

Distributionally robust disaster relief planning under the Wasserstein set

We study a two-stage natural disaster management problem modeled as a stochastic program, where the first stage consists of a facility location problem, deciding where to open facilities and pre-allocate resources such as medical and food kits, and the second stage is a fixed-charge transportation problem, routing resources to affected areas after observing a disaster. Our model has binary variables present in both stages. Due to the lack of data, classical stochastic programming approaches may be ill-suited, and we propose a two-stage distributionally robust formulation with a Wasserstein ambiguity set, where we consider distributions consistent with historical data and a tunable parameter to control the level of risk aversion. We develop a tailored column-and-constraint generation (CCG) algorithm to solve an extensive reformulation, where scenarios are iteratively generated. We handle the presence of binary variables in the second stage by leveraging the structure of our support set and second-stage problem, and provide conditions under which the optimal value of the latter is concave with respect to the intensity of the disaster, leading to an efficient scenario generation procedure. We also show that our results extend to the case where the second stage is a fixed-charge network flow problem. We perform extensive computational experiments demonstrating the computational advantage of our method over classical CCG implementations on synthetic instances, and illustrate the benefits of our approach on a popular case study from the literature of hurricane threats on the Gulf of Mexico in the United States.

A theory of capital flow retrenchment

During a downturn in the global financial cycle there is a simultaneous retrenchment in gross capital flows and a fall in risky asset prices. The global financial cycle is closely related to fluctuations in risk appetite. We develop a model that can simultaneously produce a fall in gross outflows, inflows, and asset prices following an increase in global risk aversion. There is heterogeneity across investors within a country in the willingness to hold risky assets and to hold foreign assets. The fall in the asset price after a rise in global risk aversion shifts the wealth distribution towards investors that are less willing to hold foreign assets. This leads a drop in gross flows. We calibrate the within country heterogeneity in the model to match heterogeneity observed in micro data of household portfolios. The retrenchment in the calibrated model is quantitatively similar to what we observe in the macro data.

Testing the boundaries of applicability of standard Stochastic Discount Factor models

We provide a joint non-parametric test to gather insights on the boundaries of applicability of Stochastic Discount Factor (SDF) models. We find that a non-trivial class of models cannot price the U.S. stock market equally weighted portfolio, implying non-monotonic SDFs, especially over the last 50/60 years in (recessionary) periods characterized by higher market volatility. Stocks responsible for this rejection mostly belong to the smallest NYSE market cap decile, are characterized by high idiosyncratic risk, and typically cannot be priced via SDF models where the aggregate level of risk aversion is bigger then 9 or 10. Excluding these stocks increases the ability to explain the cross-section of returns without impairing the ability to span the mean–variance frontier.

Does the risk aversion of accountants matter? Female rank-and-file accounting employees and internal control quality

Using novel data on corporate accounting employees, we find that the risk aversion of rank-and-file accounting employees, proxied by the proportion of female accountants, is negatively associated with the likelihood of internal control weaknesses. The results are incremental to controlling for other accounting employee characteristics, such as experience and quality, which are also associated with fewer internal control weaknesses. In contrast, female non-accounting employees explain operating risk and not internal control risk. We mitigate endogeneity concerns by using an entropy balanced sample and an instrumental variable approach that exploits variation in the external supply of female accountants. Our study is among the first to provide large-sample archival evidence that characteristics of accounting employees matter to financial reporting and how these effects differ from non-accounting employees.

Do Climate-Related Risks Perception Drive Corporate Green and Low-Carbon Transformation? Evidence from Listed Companies in China

ABSTRACT The extreme weather and climate occur frequently attracted high attention from society, which brings high uncertainty risks to enterprises. This study uses a fixed effects model to investigate the impact of corporate climate-related risk perceptions on their behavior. We found that increased climate-related risk perception catalyzes corporate green and low-carbon transitions (GLCT). From the perspectives of internal governance and external supervision, it is found that executive risk aversion, government environmental regulation, and investor attention can all contribute to the positive impact of climate-related risk perception on GLCT. Additionally, corporate climate-related risk perceptions can contribute to transition outcomes and lead to favorable capital market responses by improving GLCT actions, and that the contribution of climate-related risk perceptions to GLCT is stronger among non-state-owned enterprises and high-polluting industries. This study provides strategic insights for organizations to effectively manage climate risk.

The volatility of capital flows in emerging markets: Measures and determinants

Capital flow volatility is a concern for macroeconomic and financial stability. Nonetheless, literature is scarce in this topic. Our paper sheds light on this issue along two dimensions. First, using quarterly data for 33 emerging markets and developing economies, we introduce new estimates of volatility for total multilateral gross capital in- and outflows and key categories, based on the residuals of ARIMA models. We find that a combination of our proposed approach and the commonly used standard deviation best identifies sharp rises during episodes of heightened global risk aversion, thus underscoring the need for a multi-faceted approach to gauge capital flow volatility. Second, we perform panel regressions to understand the determinants of volatility using both ARIMA and standard deviation measures of volatility. While there are variations across different categories of capital flows, generally speaking we identify three main drivers: the US interest rates, global risk aversion, and domestic real GDP. Overall, our findings call for a richer set of volatility estimates, beyond standard deviation, and also show that the determinants of capital flow volatility could vary depending on the measurement approach and the category of flow under analysis.