Dividend Imputation and Shareholder Wealth: The Case of New Zealand

On April 1, 1988, New Zealand stopped the double taxation of dividends by implementing a full dividend imputation program. Because many believed that the tax advantage of debt had led to more highly leveraged firms subject to greater financial risk than was socially optimal, it was hoped the removal of incentives to finance with debt would result in a more efficient allocation of capital. The empirical results suggest that the shareholder wealth gain from dividend imputation was more than offset in firms with large debt levels. Moreover, an examination of debt ratios indicates debt levels declined in the post–imputation period.     

Estimating Willingness to Pay for Improved Water Quality in the Presence of Item Nonresponse Bias

This article deals with the problem of item nonresponse in contingent valuation surveys using a payment-card method, by applying a grouped-data sample-selection estimation technique that is capable of imputing the missing values conditional upon a respondent's decision to answer a willingness-to-pay question. The advantage of the technique lies in its ability to utilize all of the information in the sample, permitting a more efficient estimation in the presence of item nonresponse bias. The major determinants of willingness to pay appear to be household income, number of children, education, perception of existing water quality, and identification with environmental issues.     

Wavelet Analysis of the Bombay Stock Exchange Index

The fluctuations in the rate of returns of the Bombay stock exchange are analyzed through wavelet transform. The fluctuations, in various time scales, naturally separated by the wavelets, are subjected to statistical analysis. The localization and multiresolution properties of the wavelets enable one to identify collective behaviour in the stock market and the extent of their influence at various time scales. The Gaussian nature of the rate of returns at certain scales and the periodic nature of the same, at other scales, are clearly brought out by this analysis. The utility of this approach for modeling purpose is also elucidated.

     

THE RELATIONSHIP BETWEEN THE BLACK MARKET AND OFFICIAL EXCHANGE RATES: AN EXAMINATION OF LONG-RUN DYNAMICS IN INDIA

This study is the first to use Johansen's cointegration approach for India in the analysis of the long‐term dynamics between the black and official exchange rates for the period 1953–1993. The study also estimates the long‐run elasticity of the official rate with respect to the black market rate. As monthly data over 40 years are used, and a more robust methodology is employed, the results are likely to be more reliable as compared with the earlier work on India. The results of our study suggest that while there is a long‐term relationship between the two rates, the direction of causality is from the black rate to the official exchange rate. This is plausible in the Indian context where policy has generally lagged behind events in the black market. The hypothesis of a constant black market premium is rejected, implying that there is a mismatch between the percentage change in the official exchange rate and the percentage change in the black market rate.     

An Investigation of the Informational Role of Short Interest in the Nasdaq Market

This paper examines the relationship between the level of short interest and stock returns in the Nasdaq market from June 1988 through December 1994. We find that heavily shorted firms experience significant negative abnormal returns ranging from −0.76 to −1.13 percent per month after controlling for the market, size, book–to–market, and momentum factors. These negative returns increase with the level of short interest, indicating that a higher level of short interest is a stronger bearish signal. We find that heavily shorted firms are more likely to be delisted compared to their size, book–to–market, and momentum matched control firms.     

Short term real earnings management prior to stock repurchases

This study examines whether firms engage in income-decreasing real earnings management before open market stock repurchases to reduce the cost of stock buybacks. In the short run, managers have the ability to underproduce inventory and increase discretionary expenditures, thus decreasing current period earnings. We find that managers engage in both of these activities before repurchasing their firms’ shares, especially the latter. Also, companies increase their discretionary spending before making repurchases to a greater extent following the passage of the Sarbanes–Oxley Act of 2002 as well as when they are financially healthy and have high marginal tax rates. Finally, we document that firms with the most income-decreasing real earnings management experience the largest positive abnormal returns during the subsequent period. Our findings highlight the importance of considering firms’ use of real operating decisions, as opposed to just opportunistic disclosure practices, around significant corporate events, such as the repurchase of their own stock.     

Knowledge Management in Supply Chains: The Role of Explicit and Tacit Knowledge

We theorize, building on the knowledge‐based view and the theoretical distinction between explicit and tacit knowledge, that knowledge management capability across the supply chain manifests itself in explicit and tacit knowledge, which in turn effectuates supply chain performance. The model is tested with survey data from 195 small‐ and medium‐sized enterprises reporting on their primary supply chain. The results indicate that the supply chain's knowledge management capability manifests itself in both explicit and tacit knowledge, with the latter being influenced more strongly. Moreover, it was found that while both explicit and tacit knowledge influence supply chain performance, the latter exerts a significantly greater impact than the former. Exploratory post hoc analyses add robustness to these findings and investigate mechanisms inherent to the transformation of tacit into explicit knowledge. Overall, this research contributes to academic theory development in logistics and supply chain management by the dichotomization of knowledge types and the demonstration of their differential magnitude of effects, and to managerial practice by providing important guidance for logistics managers structuring their knowledge management efforts across supply chains.     

The Effect of Probability Distribution Functions of Economic Life on Retirement Alternatives

Economic analysis, supported by computer hardware and software, can easily overwhelm a decision maker with data. However, this data can be organized in a readily understandable way using well-designed graphs. Some simple guidelines suggest substantial improvements over available examples from papers and textbooks. Although these graphs and sensitivity analyses are useful in many quantitative problems, the long-range focus of engineering economy and its concomitant uncertainty dramatically increase their value.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.