Taxes, Default Risk, and Yield Spreads

This paper represents an extension and integration of recent empirical and theoretical research on default risk and taxability. The purpose of the paper is to develop and test a model of interest rate spreads which incorporates both the effect of taxes and differences in default probabilities in a theoretically correct manner. There is an important fundamental difference between our approach to explaining yield spreads and the approach most commonly taken in literature. Unlike nearly all of the previous work, we do not begin with a yield spread model, i.e.,one which begins by examining differences in yields, but rather begin with an expected return or pricing model, which can then be expressed in the yield spread format. This is a fundamental difference in approaches which we feel leads to a superior theoretical formulation which can then be tested empirically without many of the problems inherent in the alter-native approach. The theoretical model is a simple extension of earlierwork on default by Bierman and Hass (1975) and Yawitz (1977), altered appropriately to take explicit account of tax effects. While there is a considerable literature that analyzes the effect of taxability on rate spreads, we are unaware of any previous study that considers tax consequences in the event of default, a rather surprising omission.

The impact of attention to news about tax changes on the stock market

We approach to point out new direction of measurement the attention of the news related to changes in taxes by using the application Google Trends. The objective of the study is to extend literature that investigates the impact of the information's search intensity provided by Google Trends on capital market. We show that increasing attention on tax changes measured by Google search decrease stock prices of the US companies listed on NASDAQ. Moreover, we focus on abnormal Google searches related to particular shocks. The study investigates the positive relationship between attention to news about tax changes and stock prices in a specific year. The cross-sectional analysis employs data from 2004 and 2005. At that time, President George Bush enacted tax breaks for overseas corporate profits, which had a great impact on search intensity within the period. Additionally, we differentiate between market capitalisation by using the dummy variables to put on the role changes of probability on selected datasets. The results confirmed higher impact of attention on large cap companies and point out the importance of sentiment analysis at liquid markets.O

Do audit fees and audit hours influence credit ratings?: A comparative analysis of Big4 vs Non-Big4

We examine the relationship between credit ratings / changes and audit fees (hours) for Big4 and Non-Big4 firms. Audit fee (hours) may be considered as a default risk metric for credit ratings agencies. However, firms audited by Big4 are larger, better performing and operate with lower leverage compared to firms followed by Non-Big4. Therefore, the association between audit fee (hours) may be different for firms followed by Big4 and Non-Big4 audit firms. We find that there is a negative association between audit fees and credit ratings for firms followed by Big4 audit firms. However, we find an insignificant relation for firms followed by Non-Big4. We conjecture the different association due to the Big4 firms having more robust accounting procedures; Big4 firms must offer competitive audit fees because they are engaged in fierce competition with other Big4 firms. Moreover, Big4 and Non-Big4 firms have different relationships with their clients because Non-Big4 firms are more income dependent on their clients. Using a sample of 1,717 firm–year observations between 2002 and 2013, we establish a relation between audit fees in period t and credit ratings in period t+1, for firms followed by Big4 auditors. We do not find a significant relation for firms followed by Non-Nig4 firms, suggesting that credit ratings agencies perceive audit fee differently for Big4 and Non-Big4 firms. Client firms followed by Big4 auditors that experience a credit rating change in period t+1 pay lower audit fees in period t compared to firms that do not experience a credit rating change. Our additional analysis suggests a different association between firms audit fees and firm performance for firms that experience a credit rating increase and decrease. Firms that experience a credit ratings increase in period t+1 have strong performance and lower audit fees in period t. On the other hand, firms that experience a credit rating decrease have weak financial performance and negative audit fees compared to firms that do not experience a credit ratings change. Our results suggest that audit fees combined with financial performance influence a credit ratings agency' perception of default risk

Economic Growth and the Diffusion of Clean Technologies: Explaining Environmental Kuznets Curves

Production often causes pollution as a by-product. Once environmental degradation becomes too severe, regulation is introduced by which society forces the economy to make a transition to cleaner production processes. We model this transition as a change in general purpose technology" and investigate how it interferes with economic growth driven by quality-improvements. The model gives an explanation for the inverted U-shaped pollution-income relation found in empirical research for many pollutants (Environmental Kuznets Curve). We provide an analytical foundation for the claim that the rise and decline of pollution can be explained by policy-induced technology shifts and intrasectoral changes

Heterogeneity and Strategic Choices: The Case of Stock Repurchases

Strategic decisions are fundamentally tough choices. Theory suggests that managers are likely to display bounded rationality. Empirics on the other hand assume rationality in choice behavior. Recognizing this inherent disconnect between theory and empirics, we try to account for behavioral biases using a theoretically consistent choice model. The traditional approach to modeling strategic choice has been to use discrete choice models and make inference on the conditional mean effects. We argue that the conditional mean effect does not capture behavioral biases. The focus should be on the conditional variance. Explicitly modeling the conditional variance (in the discrete choice framework) provides us with valuable information on individual level variation in decision-making. We demonstrate the effect of ignoring the role of variance in choice modeling in the context of firm’s decisions to conduct open market repurchases. We show that when taking into account the heterogeneity in choices, manager’s choices of conducting open market repurchases displays considerable heterogeneity and that not accounting for such heterogeneity might lead to wrong conclusions on the mean effects