Impact of copula choice on the modeling of crop yield basis risk

A number of problems in agricultural economics involve modeling joint distributions for which the assumption of multivariate normality may not be warranted. Yet, very little work has been conducted evaluating competing methods for modeling joint dependence. We develop a simulation framework to evaluate the bias and efficiency impacts of copula choice in the context of evaluating county‐to‐farm basis risk. The results suggest significant differences in performance across various copulas and approaches. The findings have important implications for risk analysis, insurance, and policy modeling problems in agriculture regarding the selection of method to model dependence among random variables.     

Toward a more complete understanding of offshoring: bringing employees into the conversation

The rapid increase in the practice of offshoring over the past decade has generated considerable debate about the consequences of this trend for the economy and for labor. A burgeoning literature examines a variety of issues related to offshoring; however, the majority have focused primarily on macro-level issues such as why organizations decide to offshore or why some ventures succeed and some fail. Very little research has examined the impact of exporting work on the attitudes and behaviors of employees in the destination country who are performing the work. We seek to address this gap in the literature by identifying the distinguishing characteristics of the offshore work environment and developing a theoretical framework for understanding destination workers' experiences and responses in this environment. Drawing on social identity theory and related research, we develop a multilevel model for explaining the antecedents and consequences of the identity conflicts that often arise among destination workers employed in voice-based service work.     

U.S. Monetary Policy and International Bond Markets

This paper analyzes how U.S. monetary policy affects the pricing of dollar‐denominated sovereign debt. We document that yields on dollar‐denominated sovereign bonds are highly responsive to U.S. monetary policy surprises—during both the conventional and unconventional policy regimes—and that the passthrough of unconventional policy to foreign bond yields is, on balance, comparable to that of conventional policy. In addition, a conventional U.S. monetary easing (tightening) leads to a significant narrowing (widening) of credit spreads on sovereign bonds issued by countries with a speculative‐grade credit rating but has no effect on the corresponding weighted average of bilateral exchange rates for a basket of currencies from the same set of risky countries; this indicates that an unanticipated tightening of U.S. monetary policy widens credit spreads on risky sovereign debt directly through the financial channel, as opposed to indirectly through the exchange rate channel. During the unconventional policy regime, yields on both investment‐ and speculative‐grade sovereign bonds move one‐to‐one with policy‐induced fluctuations in yields on comparable U.S. Treasuries. We also examine whether the response of sovereign credit spreads to US monetary policy differs between policy easings and tightenings and find no evidence of such asymmetry.     

Inferring fundamental value and crash nonlinearity from bubble calibration

Identifying unambiguously the presence of a bubble in an asset price remains an unsolved problem in standard econometric and financial economic approaches. A large part of the problem is that the fundamental value of an asset is, in general, not directly observable and it is poorly constrained to calculate. Further, it is not possible to distinguish between an exponentially growing fundamental price and an exponentially growing bubble price. In this paper, we present a series of new models based on the Johansen–Ledoit–Sornette (JLS) model, which is a flexible tool to detect bubbles and predict changes of regime in financial markets. Our new models identify the fundamental value of an asset price and a crash nonlinearity from a bubble calibration. In addition to forecasting the time of the end of a bubble, the new models can also estimate the fundamental value and the crash nonlinearity, meaning that identifying the presence of a bubble is enabled by these models. In addition, the crash nonlinearity obtained in the new models presents a new approach to possibly identify the dynamics of a crash after a bubble. We test the models using data from three historical bubbles ending in crashes from different markets. They are the Hong Kong Hang Seng index 1997 crash, the S&P 500 index 1987 crash (Black Monday) and the Shanghai Composite index 2009 crash. All results suggest that the new models perform very well in describing bubbles, forecasting their ending times and estimating fundamental value and the crash nonlinearity. The performance of the new models is tested under both the Gaussian residual assumption and non-Gaussian residual assumption. Under the Gaussian residual assumption, nested hypotheses with the Wilks' statistics are used and the p-values suggest that models with more parameters are necessary. Under the non-Gaussian residual assumption, we use a bootstrap method to obtain type I and II errors of the hypotheses. All tests confirm that the generalized JLS models provide useful improvements over the standard JLS model.     

Women in top management and agency costs

This study investigates gender diversity among the top managers of Fortune 500 firms and its effect on agency costs. The study finds that firms with a greater percentage of female officers present lower agency costs but that the negative relation is not robust when considering the endogeneity of diversity. The study also finds that external governance influences the relationship. Although increasing diversity does not reduce agency costs for all firms, the evidence shows that diversity is significantly negatively related to agency costs in firms in less competitive markets. The results suggest that increasing diversity in management can have beneficial effects for firms where strong external governance is absent.     

Using a highly portable computer to gather qualitative social network data

We report on the use of a highly portable computer for collecting precise and accurate data concerning specific social network ties. Our experience confirmed that a highly portable computer, when loaded with a flexible database management program, is a useful tool for such a task. Data entry can be done during the interview and information retrieval can provide immediate and useful information for the respondents. The use of the computer with semistructured interviews changes the dynamics of the interview situation. A three-way interaction is created between the interviewers, the respondents and the information in the database. We found that there were great benefits from having two or three respondents in the session, and that it was desirable to have two interviewers.     

Impacts of Weather and Time Horizon Selection on Crop Insurance Ratemaking: A Conditional Distribution Approach

An important issue in the agricultural risk and actuarial literatures is the extent to which sample period selection affects the accuracy of insurance rating. This is typically more problematic in agriculture than in other types of insurance because of the variation in weather through time. A conditional Weibull distribution approach is developed that explicitly models the interaction of weather, technology, and other variables on probabilistic yield outcomes to address this issue. Results from an application with an extensive producer-level yield dataset representing commercial-scale Illinois firms suggest that the impact of weather heterogeneity on risk estimation across reasonable samples is likely not as great as is often claimed. The results also suggest that yield risk is decreasing significantly through time and indicate the presence of trend acceleration. A rating analysis indicates that violations in the risk evolution assumptions of the rating approaches used in the Federal Crop Insurance Program—which implicitly assume increasing yield risk through time when yields trend—result in severely biased rates, with typical overstatements of 200% to 400% for Midwest corn.     

The Impact of the Federal Reserve's Large‐Scale Asset Purchase Programs on Corporate Credit Risk

Estimating the effect of Federal Reserve's announcements of Large‐Scale Asset Purchase (LSAP) programs on corporate credit risk is complicated by the simultaneity of policy decisions and movements in prices of risky financial assets, as well as by the fact that both interest rates of assets targeted by the programs and indicators of credit risk reacted to other common shocks during the recent financial crisis. This paper employs a heteroskedasticity‐based approach to estimate the structural coefficient measuring the sensitivity of market‐based indicators of corporate credit risk to declines in the benchmark market interest rates prompted by the LSAP announcements. The results indicate that the LSAP announcements led to a significant reduction in the cost of insuring against default risk—as measured by the CDX indexes—for both investment‐ and speculative‐grade corporate credits. While the unconventional policy measures employed by the Federal Reserve to stimulate the economy have substantially lowered the overall level of credit risk in the economy, the LSAP announcements appear to have had no measurable effect on credit risk in the financial intermediary sector.