Zhangliang Chen, Sandy Dall'Erba and Bruce J. Sherrick
Federal crop insurance programs are the primary risk management programs of the US farm programs. Currently, these programs have been criticized for being disproportionally in…
Abstract
Purpose
Federal crop insurance programs are the primary risk management programs of the US farm programs. Currently, these programs have been criticized for being disproportionally in favor of the riskier areas. Despite previous researchers having widely speculated its existence, a formal study of the scale, spatial pattern and fiscal impacts of such misrating phenomenon is still missing in the literature.
Design/methodology/approach
This paper first purposes an empirically testable definition of misrating, and then detects the scale of the misrating phenomenon by using over two million actuarial records collected by United States Department of Agriculture (USDA's) risk management agency since 1989. Furthermore, multiple spatial statistics methods have been adopted to study the spatial patterns of the misrating statuses. Finally, the paper builds a simple theoretical model to study the potential fiscal impacts of any policy attempts to mitigate the misrating issue.
Findings
The result reveals that roughly 40% of the counties display some degree of misrating. Furthermore, the distribution of misrating displays a significant pattern of positive global spatial autocorrelation, which reflects the existence of regional clusters of premium rate mispricing. Last but not least, the paper concludes that whether an attempt toward fair rating decreases the total program outlay or not relies on the demand elasticity of crop insurance in both overrated and underrated regions.
Originality/value
This paper offers the first attempt to quantify the scale, identify the spatial pattern and evaluate the fiscal impact of the premium misrating in federal crop insurance programs.
Details
Keywords
Matteo Foglia, Alessandra Ortolano, Elisa Di Febo and Eliana Angelini
The purpose of this paper is to study the evolution of financial contagion between Eurozone banks, observing the credit default swaps (CDSs) market during the period 2009–2017.
Abstract
Purpose
The purpose of this paper is to study the evolution of financial contagion between Eurozone banks, observing the credit default swaps (CDSs) market during the period 2009–2017.
Design/methodology/approach
The authors use a dynamic spatial Durbin model that enables to explore the direct and indirect effects over the short and long run and the transmission channels of the contagion.
Findings
The results show how contagion emerges through physical and financial market links between banks. This finding implies that a bank can fail because people expect other related financial institutions to fail as well (self-fulfilling crisis). The study provides statistically significant evidence of the presence of credit risk spillovers in CDS markets. The findings show that equity market dynamics of “neighbouring” banks are important factors in risk transmission.
Originality/value
The research provides a new contribution to the analysis of EZ banking risk contagion, studying CDS spread determinants both under a temporal and spatial dimension. Considering the cross-dependence of credit spreads, the study allowed to verify the non-linearity between the probability of default of a debtor and the observed credit spreads (credit spread puzzle). The authors provide information on the transmission mechanism of contagion and, on the effects among the largest banks. In fact, through the study of short- and long-term impacts, direct and indirect, the paper classify banks of systemic importance according to their effect on the financial system.