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This chapter uses stated tourist preferences as a proxy of visitor yield measures, in order to analyse and understand the yield potential of different markets’ preferences. A literature review revealed that there is much progress to be made in terms of discussion, consensus and stability of methodology for the measurement of visitor yield. The aim of the visitor yield analysis, in the current chapter, is also to bring another dimension into yield analysis and discussion, contributing with a new form of measuring yield potential. Since the objective is to identify yield patterns based on tourist preferences over a period of time, dynamics may be captured from the fluctuation patterns, or expressed as volatility of visitor yield and length of stay throughout the years. Destination management organisations and tourist companies may potentially adopt this visitor yield matrix in order to support future strategic decisions.

We analyze cumulative abnormal returns (CARs) around key events leading up to the passage of JGTRRA to determine whether a reduction in the individual tax rate on dividend income affects stock prices, and if so, whether that effect differs for different groups of firms. In general, we find that dividend yield is positive and significantly related to CARs around both the December and January announcements that legislation might be enacted to reduce or eliminate the dividend tax. Consistent with this observation, when Congress subsequently passed the final Senate vote to reduce but not eliminate dividend taxes, we observe positive and statistically significant returns for high-yield dividend firms, but not for other firms. Additionally, we analyze the role of institutional ownership in the relation between firm yield and price reaction. The incentive to buy dividend-paying stocks should not be influenced by the degree to which a firm's stock is held by institutional investors but rather by the firm's dividend yield. Our results suggest that this distinction is important – institutional ownership appears to be significant for tax changes that induce seller-initiated market reactions, but not for changes that increase buyer-initiated reactions.

We examine the relationship that exists among bond ratings, bond yields, and various estimates of a firm's contingent environmental remediation liability using a sample of new bond issues. Our results indicate that the largest external EPA-based estimates of the firm's environmental obligations are significantly associated with a firm's bond rating, providing relevant incremental information beyond that supplied by the environmental accruals presented in the financial statements. Furthermore, while the accrued environmental liability is shown to have a direct association with the bond yield, the external EPA-based estimates provide an indirect relationship with the bond yield through their influence on the bond rating. These results contribute to the extant literature by empirically clarifying the role of various environmental liability estimates in establishing a firm's bond rating and further indicating their connection with the pricing of corporate debt.

Recent U.S. Treasury yields have been constrained to some extent by the zero lower bound (ZLB) on nominal interest rates. Therefore, we compare the performance of a standard affine Gaussian dynamic term structure model (DTSM), which ignores the ZLB, to a shadow-rate DTSM, which respects the ZLB. Near the ZLB, we find notable declines in the forecast accuracy of the standard model, while the shadow-rate model forecasts well. However, 10-year yield term premiums are broadly similar across the two models. Finally, in applying the shadow-rate model, we find no gain from estimating a slightly positive lower bound on U.S. yields.

In this chapter the development of new sugarcane varieties in Florida and Louisiana is examined, along with the accompanying advancement in mechanization technology through the widespread adoption of sugarcane harvesters. An econometric analysis is carried out to determine the impact of the price of raw sugar on raw-sugar yields in Louisiana and Florida. This study found that in the case of Louisiana, the 3-year lagged US raw-sugar price had a positive and significant impact on sugar yields. The change in raw-sugar prices did not have a significant impact on sugar yields for the Florida industry. Sugar production has increased over time, in part, due to the development of new sugarcane varieties accompanied by modern sugarcane harvesters. Given the relationship between price and yield, particularly in Louisiana, policy makers and producers must be mindful of the potential impact of policy-induced research and development (R&D) on the competitiveness of their industry.

This chapter reassesses the economics of interest rate risk management in light of the global financial crisis by developing a derivative-based integrated treatment of interest rate and credit risk interrelation. The decade-long historical data on credit default swap spreads and interest rate swap rates are used as proxy measures for credit risk and interest rate risk, respectively. An elasticity of interest rate risk and credit risk, considered a function of the business cycle phases, maturity of instruments, economic sector, creditworthiness, and other macroeconomic parameters, is investigated for optimizing economic capital. This chapter sheds light on how financial institutions may address hedge strategies against downside risks implementing the proposed derivative-based integrated treatment of interest rate and credit risk assessment allowing for optimization of interest rate swap contracts. The developed framework of integrated interest rate and credit risk management is of special importance for emerging markets heavily dependent on foreign capital as it potentially allows emerging market banks to improve risk management practices in terms of capital adequacy and Basel III rules. Analyzing diversification versus compounding effects, it allows enhancing financial stability through jointly optimizing Pillar 1 and Pillar 2 economic capital.

A common feature of certain kinds of data is a high level of statistical dependence across space and time. This spatial and temporal dependence contains useful information that can be exploited to significantly reduce the uncertainty surrounding local distributions. This chapter develops a methodology for inferring local distributions that incorporates these dependencies. The approach accommodates active learning over space and time, and from aggregate data and distributions to disaggregate individual data and distributions. We combine data sets on Kansas winter wheat yields – annual county-level yields over the period from 1947 through 2000 for all 105 counties in the state of Kansas, and 20,720 individual farm-level sample moments, based on ten years of the reported actual production histories for the winter wheat yields of farmers participating in the United States Department of Agriculture Federal Crop Insurance Corporation Multiple Peril Crop Insurance Program in each of the years 1991–2000. We derive a learning rule that combines statewide, county, and local farm-level data using Bayes’ rule to estimate the moments of individual farm-level crop yield distributions. Information theory and the maximum entropy criterion are used to estimate farm-level crop yield densities from these moments. These posterior densities are found to substantially reduce the bias and volatility of crop insurance premium rates.

This chapter presents evidence of persistence in pricing new corporate bond issues. Both transition matrix and regression analyses show that cross-sectional differences in the yields of initial public bond offerings across issuers persist over time, and the persistence effect is stronger for firms with no rating changes, less frequent bond issuance, and higher information asymmetry. Our findings support the hypothesis of the “ride on past” behavior and confirm the value of information production accumulated from the past bond issuances for the pricing of newly issued bonds.

This study investigates the impacts of operational risks and corporate governance on bond yield spreads, examining their impacts on bond yield spreads during the COVID-19 pandemic. The results indicate that operational risks significantly raise yield spreads, especially for high-leverage firms. Moreover, a higher independent director percentage reduces debt costs. Furthermore, the results reveal more pronounced effects of operational risks on yield spreads during the COVID-19 pandemic, with these risks increasing the financing costs for large firms. When the effect of the independent director percentage on the yield spreads increases, this consequently raises the debt costs for large firms.