Tag: Senay Agca

June 2021

Senay Agca (George Washington University)
Pablo Slutzky (University of Maryland)
Stefan Zeume (UIUC)

IIEP working paper 2021-20

Abstract: We exploit a tightening of anti-money laundering (AML) enforcement that imposed disproportionate costs on small banks to examine the effects of a change in bank composition on real economic outcomes. In response to intensified enforcement, counties prone to high levels of money laundering experience a departure of small banks and increased activity by large banks. This results in an increase in the number of small establishments and real estate prices. Consistent with a household demand channel, wages and employment increase in the non-tradable sector. Last, we document secured lending as a potential driver of this outcome.

JEL Codes: G21, G28

Key Words: Money laundering, Financial Institutions, Real economy, Deposits and lending, Financial crime

June 2021

Senay Agca (George Washington University)
John R. Birge (University of Chicago)
Zi’ang Wang (Chinese University of Hong Kong)
Jing Wu (Chinese University of Hong Kong)

IIEP working paper 2021-19

Abstract: Global supply chains expose firms to multi-regional risks, but also provide benefits by creating a buffer against local shocks. The COVID-19 pandemic and its differential impact on different parts of the world provide an opportunity for insight into supply chain credit risk, and how operational and structural characteristics of global supply chains affect this risk. In this paper, we examine supply chain credit risk during different phases of the COVID-19 pandemic by focusing on Credit Default Swap (CDS) spreads and US-China supply chain links. CDS spreads reflect both the probability of default and expected loss given default, and are available with daily frequency, which allows the assessment of supply chain partners’ credit risk in a timely manner. We find that CDS spreads for firms with China supply chain partners increase with the economic shutdown in China during the pandemic, and the spreads go down when the economic activity resumed with the re-opening in China. We consider Swift, Even Flow (SEF) and Social Network Theories (SNT) within our context. Supporting SEF theory, we find that the impact of pandemic-related disruptions to even flow of goods and materials reflected in supply chain credit risk is mitigated for firms with lower inventory turnover and those with better ability to work with longer lead times and operating cycles. Examining supply chain structural characteristics through SNT reveals that spatial and horizontal complexity, as well as network centrality (degree, closeness, betweenness, information) mitigate the impact of supply chain vulnerabilities on supply chain credit risk.

JEL Codes: E21, E51, F23, G12, G14, G23, G32, L11

Key Words: Supply Chains, Credit Risk, CDS, COVID-19, Pandemic

June 2021

Senay Agca (George Washington University)
Volodymyr Babich (GeorgetownUniversity)
John R. Birge (University of Chicago)
Jing Wu (Chinese University of Hong Kong)

IIEP working paper 2021-18

Abstract: Using a panel of Credit Default Swap (CDS) spreads and supply chain links, we observe that both favorable and unfavorable credit shocks propagate through supply chains in the CDS market. Particularly, the three-day cumulative abnormal CDS spread change (CASC) is 63 basis points for firms whose customers experienced a CDS up-jump event (an adverse credit shock). The value is 74 basis points if their suppliers experienced a CDS up-jump event. The corresponding three-day CASC values are −36 and −38 basis points, respectively, for firms whose customers and suppliers, respectively, experienced an extreme CDS down-jump event (a favorable credit shock). These effects are approximately twice as large for adverse credit shocks originating from natural disasters. Credit shock propagation is absent in inactive supply chains, and is amplified if supply-chain partners are followed by the same analysts. Industry competition and financial linkages between supply chain partners, such as trade credit and large sales exposure, amplify the shock propagation along supply chains. Strong shock propagation persists through second and third supply-chain tiers for adverse shocks but attenuates for favorable shocks.

JEL Codes: E43, E51, G12, G14, G23, G24, G32, L11, L22

Key Words: supply chains, credit risk, CDS, propagation, supply networks