The COVID-19 Shock and Consumer Credit: Evidence from Credit Card Data

Horváth, Ákos; Kay, Benjamin S.; Wix, Carlo

doi:10.17016/feds.2021.008

Cited by 20 publications

(18 citation statements)

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“…This, however, comes at a cost (interest), and can in itself be taken as a measure of financial vulnerability. And even if some families do take out loans to afford housing expenses (Andersen et al 2020), Horvath et al (2020 shows that in the United States, since the onset of COVID-19, new supply of credit to risky borrowers is limited. In the presence of liquidity constrains, another important resource to consider are loans or gifts from family and friends, which can, likewise, ensure minimum levels of consumption.…”

Section: Related Literaturementioning

confidence: 99%

Living with Reduced Income: An Analysis of Household Financial Vulnerability Under COVID-19

Midões

Seré

2021

Soc Indic Res

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The COVID-19 crisis has led to substantial reductions in earnings. We propose a new measure of financial vulnerability, computable through survey data, to determine whether households can withstand a certain income shock for a defined period of time. Using data from the ECB Household Finance and Consumption Survey (HFCS) we analyse financial vulnerability in seven EU countries. We find that, out of the 243 million individuals considered, 47 million are vulnerable to a three month long income shock (the average length of the first wave COVID-19 lockdown), i.e., they cannot afford food and housing expenses for three months without privately earned income. Differences across countries are stark. Individuals born outside the EU are especially likely to be vulnerable. Being younger, a single parent, and a woman are also statistically significant risk factors. Through a tax-benefit microsimulation exercise, we look into the COVID-19 employment protection benefits, the largest income support measure in the countries considered. Considering as our sample individuals in households where someone receives a salary, we derive household net income when employees are laid-off and awarded the COVID-19 employment protection benefits enacted. Our findings suggest that the employment protection schemes are extremely effective in reducing the number of vulnerable individuals. The relative importance of rent and mortgage suspensions, (likewise, widespread COVID-19 policies), in alleviating vulnerability, is highly country dependent.

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Section: Related Literaturementioning

confidence: 99%

Living with Reduced Income: An Analysis of Household Financial Vulnerability Under COVID-19

Midões

Seré

2021

Soc Indic Res

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“…Our paper contributes to the literature on the economic consequences of the COVID-19 pandemic. Previous studies have found that the pandemic strongly affects labor markets ( Coibion et al, 2020b ), stock markets ( Baker et al, 2020a , Fahlenbrach et al, 2020 ), consumer credit ( Horvath et al, 2021 ), household consumption ( Baker et al, 2020b ; Coibion et al, 2020a ), and overall economic activity ( Ludvigson et al, 2020 ). Concerning credit markets, there is evidence that large firms rapidly drew on their existing lines of credit at the beginning of the pandemic because of precautionary motives ( Acharya and Steffen, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

“… Eichenbaum et al (2021) show that the policy interventions in response to the COVID-19 pandemic deepen the economic recession as they reduce consumption and labor supply. Empirical research provides evidence for a significantly negative impact of restrictive interventions on economic activity ( Carletti et al, 2020 ; Coibion et al, 2020a ; Kong and Prinz, 2020 ; Horvath et al, 2021 ). Coibion et al (2020a) show that restrictive policy interventions have a negative effect on real economic activity and household spending.…”

Section: Introductionmentioning

confidence: 99%

“… Coibion et al (2020a) show that restrictive policy interventions have a negative effect on real economic activity and household spending. Horvath et al (2021) document that both the COVID-19 pandemic case severity and policy interventions have negative effects on consumer credit in the early stage of the COVID-19 crisis in the U.S. Spiegel and Tookes (2021) find heterogenous effects of business restriction policies on COVID-19 fatalities. Our study contributes to this literature by analyzing the effects of government policy interventions on local credit empirically and providing novel evidence on the heterogeneous effects of different policy interventions in Brazil during the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

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COVID-19, policy interventions and credit: The Brazilian experience

Nordén

Mesquita

Wang

2021

Journal of Financial Intermediation

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The COVID-19 pandemic caused a global health and economic crisis to which governments responded with massive policy interventions. Using Brazil as a testing ground, we investigate the influence of the pandemic and ensuing policy interventions on local credit markets. First, we find that the pandemic has a significantly negative impact on local credit. Second, using a novel manually collected database on the staggered municipal government policy interventions, we show heterogenous effects of interventions: positive effects of soft interventions (e.g., social distancing and mass gathering restrictions) and late reopening, and negative effects of hard interventions (e.g., closure of non-essential services) and early reopening. Third, we find that state-owned banks grant more local credit than privately owned banks during the COVID-19 crisis but this difference is less pronounced than it was in the 2008 Financial Crisis. We confirm our results using pre-pandemic local political preference as instrument for policy interventions and orthogonalized policy intervention indicators, and in placebo tests.

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“…The credit scoring model is leveraged under credit policies, which is chanced depending on challenge environments. For example, during the COVID-19 pandemic that directly affects the applicants' creditworthiness [2], lenders will maintain the dept to prevent more increasing current NPLs. Besides, many situations affect the applicants' creditworthiness, such as economic conditions, financial crisis, and political situations.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Credit Scoring Based on Cost-Sensitive Neural Network Ensemble

2021

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Most existing studies on credit scoring adapted a concept of classifier ensemble for solving an imbalanced dataset. They apply resampling methods to generate multiple training subsets for constructing multiple base classifiers. However, this approach leads to several problems that degrade the classification performance, such as problems of information loss, model overfitting, and computational cost. Thus, we propose a novel ensemble approach for developing a credit scoring model based on a cost-sensitive neural network, called Cost-sensitive Neural Network Ensemble (CS-NNE). In the proposed approach, multiple class weights are adapted to original training data, enabling the multiple base neural networks to consider imbalanced classes. Following this approach, a high diversity of multiple base classifiers without consequent problems can be achieved. The approach's effectiveness is evaluated on five real-world credit datasets. Among them is a loan-requesting dataset provided by a financial institution in Thailand. The remaining datasets are publicly available and widely used by several existing studies. The experimental results showed that the proposed CS-NNE approach improves the predictive performance over a single neural network based on imbalanced credit datasets, e.g., Thai credit dataset, by achieving 1.36%, 15.67%, and 6.11% Area under the ROC Curve (AUC), Default Detection Rate (DDR), and G-Mean (GM), respectively, and achieving the best Misclassification Cost (MC). The proposed CS-NNE approach can effectively solve a class of imbalance problems and outperform many existing models. The prediction model can well compromise between classes of default (bad credit applicants) and non-default (good credit applicants), whereas existing approaches preferred a class of non-default over default loans (having high specificity and low DDR), resulting in NPL.

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The COVID-19 Shock and Consumer Credit: Evidence from Credit Card Data

Cited by 20 publications

References 0 publications

Living with Reduced Income: An Analysis of Household Financial Vulnerability Under COVID-19

Living with Reduced Income: An Analysis of Household Financial Vulnerability Under COVID-19

COVID-19, policy interventions and credit: The Brazilian experience

A Novel Method for Credit Scoring Based on Cost-Sensitive Neural Network Ensemble

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