Default Costs Research Articles

The bright side of the doom loop: Banks’ sovereign exposure and default incentives

The feedback loop between sovereign and financial sector insolvency, termed the “doom loop”, was a key driver of the European debt crisis and motivated an array of policy proposals. This paper revisits the “doom loop” focusing on governments’ incentives to default. We introduce a 3-period model with strategic sovereign default, where debt is held by both domestic banks and foreign investors. The government maximizes domestic welfare; thus, the temptation to default increases with externally-held debt. Importantly, the cost of default arises endogenously from the damage that default causes to domestic banks’ balance sheets. Domestically-held debt thus serves as a commitment device for the government. We show that two prominent policy prescriptions – lower exposure of domestic banks to domestic sovereign debt or a commitment not to bailout banks – can backfire, since default incentives depend not only on the quantity of debt, but also on who holds it. Conversely, allowing domestic banks to buy additional domestic sovereign debt during times of sovereign distress can avert the doom loop. In the context of a monetary union similar unintended negative consequences may arise from a backstop by the central bank (e.g., the ECB’s Transmission Protection Instrument) if imprecisely calibrated or the pooling of debt (e.g., European safe bond, also known as ESBies).

Sovereign default and FDI transactions: Evidence from Argentina

This paper investigates the effect of sovereign debt default on foreign direct investment (FDI) transactions by US firms into Argentina following the Argentine sovereign default in 2019–20. Using the synthetic control approach, we find that the number of FDI transactions decreased by approximately 60% after the Argentine default with a particularly pronounced decline in the non-manufacturing sector. By examining the changes in the number of transactions, we provide a more precise picture of the cost of sovereign default, capturing the FDI activity of small firms better.

Sovereign Debt Tolerance with Potentially Permanent Costs of Default

Sovereign Debt Tolerance with Potentially Permanent Costs of Default

The real effect of CDS trading: Evidence from corporate employment

AbstractThis paper examines whether the inception of credit default swaps (CDS) trading curbs corporate employment. We show that firms with CDS trading have significantly lower employment growth. Our baseline results are robust to alternative measures of corporate employment growth, various approaches that mitigate endogeneity concerns due to omitted variables and reverse causality, and additional control variables. The decrease in firms' employment growth after CDS trading is more pronounced in firms with larger financial constraints and lower CEO risk‐taking. In addition, we find that the inception of CDS trading affects employment growth through the financial distress channel. Further analysis finds that the inception of CDS trading could mitigate the labor over‐investment problem, stimulating employment efficiency. Our evidence suggests that corporate employment growth is reduced after the initiation of CDS trading due to the heightened cost of defaults.

Green innovation ecosystem evolution: Diffusion of positive green innovation game strategies on complex networks

The essence of the evolution of the green innovation ecosystem is the process by which the positive strategy of green innovation spreads in a complex network. In this study, the "Object-Technology-Environment-Management-Culture (OETMC)" structure paradigm of innovation ecosystems is presented, and a causal analysis framework of green innovation ecosystem evolution based on green innovation behavior strategy, supported by green innovation efficiency and focused on green innovation ecosystems is developed. Based on this framework, the structure of the green innovation ecosystem and the diffusion process of positive green innovation in the network are discussed. The results reveal the following. (1) The complexity of the green innovation ecological network has visibly improved, but numerous blank connections remain. These are the key constraints that hinder structural evolution. (2) The appearance of a large number of long-range connections weakens the constraint of geographical distance but also hinders edge nodes from joining the network. (3) The existence of preference attachment and power law distribution of the green innovation ecological network leads to the incomplete convergence of positive green innovation strategy at any initial strategy ratio. (4) Default cost and pollution tax rate ensure the enthusiasm of green innovation actors to seek innovation cooperation by increasing opportunity costs, thus accelerating the formation and reconstruction of the green innovation ecological network. These conclusions provide a decision-making reference for governments to encourage green innovation subjects to formulate targeted policies.

Reprint of “Sovereign debt and economic growth when government is myopic and self-interested”

We examine how a sovereign’s ability to borrow abroad affects the country’s growth and steady-state consumption when the government is both myopic and self-interested. Surprisingly, government myopia can increase a country’s access to external borrowing and extend the government’s effective horizon, giving it a stake in incentivizing private production and savings despite its self-interest. In a high-saving country, the lengthening of the government’s effective horizon can incentivize it to tax less, resulting in a “growth boost”, with higher steady-state household consumption than if it could not borrow abroad. However, in a country that saves little, the government may engage in repressive tax policies to channel domestic savings into government bonds. This increases future governments’ costs of default, and in turn enhances current debt capacity and spending, but can lead to a “growth trap” where steady-state household consumption is lower than without government’s access to external borrowing.

Optimizing Ensemble Learning to Reduce Misclassification Costs in Credit Risk Scorecards

Credit risk scorecard models are utilized by lending institutions to optimize decisions on credit approvals. In recent years, ensemble learning has often been deployed to reduce misclassification costs in credit risk scorecards. In this paper, we compared the risk estimation of 26 widely used machine learning algorithms based on commonly used statistical metrics. The best-performing algorithms were then used for model selection in ensemble learning. For the first time, we proposed financial criteria that assess the impact of losses associated with both false positive and false negative predictions to identify optimal ensemble learning. The German Credit Dataset (GCD) is augmented with simulated financial information according to a hypothetical mortgage portfolio observed in UK, European and Australian banks to enable the assessment of losses arising from misclassification costs. The experimental results using the simulated GCD show that the best predictive individual algorithm with the accuracy of 0.87, Gini of 0.88 and Area Under the Receiver Operating Curve of 0.94 was the Generalized Additive Model (GAM). The ensemble learning method with the lowest misclassification cost was the combination of Random Forest (RF) and K-Nearest Neighbors (KNN), totaling USD 417 million in costs (USD 230 for default costs and USD 187 for opportunity costs) compared to the costs of the GAM (USD 487, USD 287 and USD 200). Implementing the proposed financial criteria has led to a significant USD 70 million reduction in misclassification costs derived from a small sample. Thus, the lending institutions’ profit would considerably rise as the number of submitted credit applications for approval increases.

The effect of minimum wages on consumer bankruptcy

We use cross-state differences in minimum wage (MW) levels and county-level consumer bankruptcy rates from 1991–2017 to estimate the effect of changes in minimum wages on consumer bankruptcy. We find that Chapter 7 bankruptcy rates are significantly lower in counties belonging to states with higher MW compared to neighboring counties in the lower MW state: a 10% increase in MW decreases the bankruptcy rate by around 4%. Before the 2005 bankruptcy reform, this effect was almost twice as large as for the entire sample. Theoretically, we cannot sign the effect of MW on bankruptcy and credit utilization; we use a stylized consumption/saving model with default to illustrate the dependence on critical aspects of the model (costs of default, minimum wage levels, and disemployment effects) and to provide intuition on how to interpret our results.

Risk Hedging and Loan Covenants

We study lending agreements and derivative positions of U.S. oil and gas producers, showing that loan covenants are important determinants of hedging policies. Hedging covenants appear in more than 85% of sample loan agreements, with explicit minimum hedging requirements in more than half. Covenants are more common when expected default costs are larger. The well-documented positive relation between borrowing and hedging is largely attributable in our sample to binding covenants, as the relation is much weaker in their absence. These results suggest that understanding firms’ hedging choices requires the consideration of lender interests along with those of owners and managers. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01616 .

Taking P2P Online Lending as An Example

This paper is based on the critical reflection of P2P online lending, with the supervision mechanism as the main analysis Angle, credit assessment and risk prevention and control as the auxiliary to carry out the discussion of P2P online lending, hoping to provide more thinking for the future development of China's Internet + finance. The main research method adopted in this paper is case study, mainly based on typical cases at home and abroad to carry out analysis. After case analysis, the conclusions are as follows: 1. In terms of supervision mechanism: (1) Let the platform and the bank reach a commercial cooperation relationship. (2) When the debt relationship is formed, it is suggested to sign smart contracts. (3) When the debtor registers as a user on the platform, it can use the bank to evaluate the assets and liabilities. (4) The platform can also learn from the Dutch supervision mechanism for creditors on the Internet platform. 2. In terms of credit evaluation, China can build a credit evaluation system belonging to Internet finance in the credit investigation system of the People's Bank of China. 3. In terms of risk prevention and control, default records should be synchronized with banks and default costs should be raised.

Application of project management tools in construction phases to optimize the impact on quality, cost, and time: A case study

This work deals with the disturbed construction process, evaluated using the parameters cost, time, and quality. The aim is to transfer the actual situation of the disturbed construction process into a structured construction process. In this context, the possibility of data analysis and the associated creation of a resilient initial situation is demonstrated. One factor, time, is classified into a measurability with the possibilities of Gantt and Lean Construction Management. A representation of the monetary situation is the determination of additional costs. Here, the best case and worst case are presented and evaluated. The execution of the quality requires the comparison with the fictitious, planning quality defaults at project initiation and the now under consideration of the default costs and dates possible degree of fulfilment. The realization at the considered object has the following initial situation. Construction delay approx. 1 year, delta costs approx. 250 million euros, quality approaches were revised and partly reduced. This was the base for the creation of a schedule. The milestones from the Gantt schedule were incorporated into the system for the Lean Construction system. The monitoring between the milestones or intermediate goals was measured in the target-actual comparison.

Blockchain-driven incentive mechanism for agricultural water-saving: A tripartite game model

Implementing water-saving agriculture is an important measure to alleviate water resource shortage, improve agricultural ecological environment, and achieve sustainable agricultural development. However, both water-saving service companies (WSSCs) and farmers often lack the motivation to adopt water-saving practices due to the high implementation costs involved. To overcome this shortcoming, this study aims to design a blockchain-driven incentive mechanism based on the evolutionary game theory, in which the government, WSSCs and farmers are game subjects and the idea of cooperative incentive for the government is introduced. Through analyzing the complex interactions among various stakeholders and agricultural water-saving incentives, some findings of this study are obtained. Firstly, the usage of blockchain technology (BT) in the incentive mechanism for agricultural water-saving is reflected in supervision and additional default costs, which promote the sustainable cooperation among government, WSSCs and farmers in varying degrees. Secondly, the additional default costs brought by the usage of BT have a deterrent effect on WSSCs and farmers, which makes them to actively implement water-saving practices. Thirdly, the additional default cost brought by BT has become the main basis for the government to choose BT supervision. As the additional default cost increases, the government are not more inclined to use BT. It provides valuable insights into motivating diverse stakeholders to actively participate in water-saving practices, promoting sustainable water resources management in agriculture.

Mitigating information frictions in trade: Evidence from export credit guarantees

Information frictions make foreign trade risky. In particular, the risk of buyer default deters firms from selling abroad. To address this issue, many countries offer export credit guarantees to provide insurance to exporters. In this paper, we investigate the causal effects of guarantees by exploiting a quasi-natural experiment in Sweden and rich register data on guarantees, firms and trade. Estimates from a fuzzy regression discontinuity design show large positive effects on the probability of exporting and the value of exports to the destination for which the guarantees are issued. These results are robust to an alternative approach using a difference-in-differences matching estimator. Further findings suggest that guarantees impact firms heterogeneously and play an important role in resolving buyer default risk and easing liquidity constraints. Larger impacts are observed in non-OECD countries, on smaller, liquidity constrained exporters and for firms selling products that face a relatively high cost of buyer default.

On the Interplay of Production Flexibility, Capital Structure, and Investment Timing

Problem definition: Modern technologies have made it viable for firms to lower the costs of switching on and off production in response to market changes. In this paper, we explore how production start–stop flexibility impacts joint operating policies, financing, and investment timing decisions. Methodology/results: We develop a continuous-time, optimal stopping model in which equity holders of the firm make operational decisions regarding pausing and restarting production as well as when to default. The degree of production flexibility is measured by switching costs. On the one hand, production flexibility influences the trade-off between tax shields and default costs for the capital structure decision; on the other hand, debt levels impact the equity holders’ incentive to use flexibility by pausing and restarting operations. We find that optimal debt usage is not monotone in production flexibility. Specifically, when switching costs are in a low region, the optimal debt level decreases slowly as switching costs increase. As switching costs increase into an intermediate region, the optimal debt level decreases sharply because the firm needs to reduce its debt to ensure the equity holders maintain flexible operating policies. However, when switching costs exceed a threshold, the cost of compromising the use of debt becomes excessive, and the firm substantially increases its debt to gain the full benefit of the tax shield; in so doing, the equity holders forgo flexibility and maintain production continuously until default. This financing strategy affects the firm’s investment timing decision, which also exhibits a nonmonotone pattern. Managerial implications: When a firm optimizes the debt usage and investment timing, the incentive of utilizing flexibility embedded in the production technology by the equity holders needs to be taken into account. Our findings also reveal new benefits and guidance for the potential design of incentive contracts to mitigate agency costs. Funding: Q. Wu was supported by Weatherhead School of Management Intramural Grant [Grant IG121420-05-QXW132] for this research. Supplemental Material: The online supplement is available at https://doi.org/10.1287/msom.2022.0213 .

Computation of Systemic Risk Measures: A Mixed-Integer Programming Approach

Mixed-Integer Programming Formulations for Systemic Risk Measures Measurement and allocation of systemic risk have become important tasks in interconnected financial networks. In “Computation of Systemic Risk Measures: A Mixed-Integer Programming Approach,” Ararat and Meimanjan consider a clearing model that considers external assets and business costs of a bank simultaneously by extending the Rogers–Veraart network model with default costs. They prove that clearing payment vectors can be calculated by solving mixed-integer programming problems in which the existence of business costs and default costs are represented by binary variables. The systemic risk measure corresponding to this model yields nonconvex sets of capital allocation vectors. The authors compute these nonconvex sets by solving a multiobjective optimization problem whose scalarizations are two-stage mixed-integer programming problems with an expectation constraint. The computational procedure is versatile enough to accommodate other applications of systemic risk where the risk factors are aggregated by solving a general mixed-integer programming problem.

Compensation and profit allocation for collaborative multicenter vehicle routing problems with time windows

With the growing interest in win–win cooperation within the logistics industry recently, collaborative multicenter logistics networks have witnessed the establishment of numerous alliances aimed at achieving cost savings. However, alliance members may choose to withdraw from an alliance due to changes in market positioning strategies and short-term profit considerations. Such withdraws often lead to the disintegration of the alliance and result in financial losses for the remaining non-defaulting members. This study focuses on addressing the issues of compensation and profit allocation in a specific scenario known as the collaborative multicenter vehicle routing problem with time windows and defaulting members withdrawal (CMVRPTWDMW). The objective is to ensure alliance stability and fair profit distribution among its members. To achieve this, a tri-objective mathematical model is proposed to optimize the re-formed alliances by considering the total operating cost, number of vehicles, and service waiting time. Additionally, an improved minimum cost remaining saving method is introduced to accurately quantify the deserved profits of non-defaulting members. Compensation quantification and default cost allocation models are then developed based on this analysis. To solve the CMVRPTWDMW and obtain Pareto optimal solutions, a hybrid heuristic algorithm is designed. This algorithm combines a 3D k-means clustering algorithm for customer reassignment after the withdrawal of defaulting members, effectively reducing the complexity of the problem. Furthermore, the algorithm employs a Clarke-Wright saving method-based non-dominated sorting genetic algorithm-III (CW-NSGA-III) to search for optimal solutions. To enhance the algorithm’s search ability, an elite alteration strategy and a penalty-based boundary intersection approach are incorporated into CW-NSGA-III. Finally, a real-world case study conducted in Chongqing City, China, is presented to demonstrate the feasibility of the proposed models and solution algorithms. The study contributes valuable insights into the sustainable operation of urban logistics networks that may experience unpredictable defaults, providing guidance for the stability of logistics alliances in the transportation sector.

The Conditionality of Wetland Ecological Compensation: Supervision Analysis Based on Game Theory

Wetland ecological compensation (WEC) is the key to the conflict between wetland conservation and economic development. While “conditionality” is critical to the efficiency and equity of WEC projects, supervision guarantees the conditionality and effects of WEC policies. Based on field research around the Poyang Lake, this paper applies game theory to systematically analyze WEC supervision and leverages the model of dynamic game with incomplete information to discuss the effects of weak supervision on rural households’ future behaviors. The results show that (1) weak supervision greatly dampens the effects of WEC projects; (2) the key underlying causes of weak supervision include low compensation rates, low default costs, and low probability of actual supervision, and the respective relevance of the three causes is not parallel but decreasing; (3) further analysis based on the model of dynamic game with incomplete information demonstrated that weak supervision affects rural households’ current and future behaviors. The paper concludes that, in order to address the roots of weak WEC supervision, appropriate compensation rates should be developed; default costs should be increased; and the actual supervision probability of authorities should be raised. The paper provides detailed explanations of real-life problems and fills the gap in the existing research by defining “weak regulation”, exploring its root causes, and comprehensively analyzing and forecasting its impacts.

Impact of Credit Risk Management on Profitability of Nepalese Commercial Banks

This study examines the impact of credit risk management on profitability of Nepalese commercial banks. Default rate, cost per loan assets and capital adequacy ratio are the independent variables used in this study. The dependent variables are return on assets (ROA) and return on equity (ROE). The secondary sources of data have been used from annual reports of selected commercial banks and supervision report of Nepal Rastra Bank. The regression models are estimated to test the significance and effect of credit risk management on profitability of Nepalese commercial banks. The beta coefficient of default rate and cost per assets with profitability (ROA, ROE) has been found negative and statistically significant. The negative sign indicates that there is statistically negative relationship between default rate and cost per loan assets with profitability. Likewise, the beta coefficient of capital adequacy ratio with ROA and ROE is found to be positive and statistically significant. The positive sign of beta coefficient indicates that there is statistically positive relationship between capital adequacy ratio and profitability. The study thus recommends an effective credit risk management for commercial banks of Nepal that maintains an optimum level of capital adequacy ratio, controls and monitors cost per loan assets and balances default rate to enhance financial performance.

Debt enforcement, financial leverage, and product failures: Evidence from China and the United States

AbstractBuilding on capital structure and product market interactions, and the role of debt enforcement in leveraged firms' investments, we examine whether cross‐country debt enforcement can produce different associations between financial leverage and product failures. Results show that different debt enforcement systems can generate opposite leverage effects. In countries with weak/nearly ineffective debt enforcement, financial leverage shows an incentive investment effect due to low default costs, and thus highly leveraged firms tend to invest more and are less likely to have product failures. Conversely, in countries with strict/effective debt enforcement, distressed companies tend to have an underinvestment effect and more product failures.

The digital economy and corporate credit risk: An empirical study based on Chinese new energy enterprises

The integration of digital technologies is exhibiting an upward trend in Chinese enterprises, and the degree of corporate credit risk is directly proportional to their financial sustainability. Based on panel data of new energy enterprises from 2012 to 2020, this article makes an empirical study on the direct effect, mediating effect, and moderating effect of the digital economy (DE) on the new energy enterprises’ credit risk. It is found that the digital economy could significantly mitigate the credit risk of new energy enterprises by improving total factor productivity and amplifying the potential default cost. When the digital economy affects corporate credit risk, the development of the new energy industry acts as an intermediary, and knowledge spillover acts as a moderator. Furthermore, considering knowledge spillover as the threshold variable, the digital economy has a double-threshold effect. The marginal impact fluctuates from dropping to increasing as the knowledge spillover level increases. As for the region’s heterogeneity, the digital economy has benefited eastern China more than central and western China, possibly due to the differences in economic structure, capital intensity, and policy institutions. In view of these findings, this study provides a reference for China to mitigate corporate credit risk in the digital economy era.