Licensing and technology dependence in the Andean group

This paper explores the extent to which licensing promotes technology transfer and future technological self-reliance in 47 metalworking and 43 chemical firms located in Peru, Ecuador and Colombia. The analysis proceeds in three steps. First, a set of factors which, it has been suggested, influence the choice of licensing as opposed to other means of acquiring technology were examined. Second, the relationship between licensing and future ‘technology dependency’ was explored statistically. Finally, an effort was made to explain these findings in terms of a ‘technological dependence syndrome’ in which opportunities for ‘learning by doing’ are consistently missed.     

Abnormal Returns from Predicting Earnings Thresholds

This study examines the performance of a trading strategy based on the prediction of firms concurrently reporting a positive earnings change and meeting analysts’ earnings forecasts. The evidence indicates that a model predicting both earnings thresholds concurrently can yield excess returns that are incremental to predicting only one earnings threshold. Further, I find that the prediction of forecast errors is relatively more important than predicting earnings changes as the incremental benefit from predicting earnings changes concurrently with forecast errors is small relative to a model that predicts only forecast errors. The results hold while controlling for various risk factors and known anomalies.     

Are Investors the Bad Guys? Tenure and Neighborhood Stability in Chelsea,Massachusetts

In this article, we examine the role of investors and occupant‐owners in an urban context during the recent housing crisis. We focus on Chelsea, Massachusetts, because it is a dense city, dominated by multifamily housing structures with high rates of foreclosure for which we have particularly good data. We distinguish between occupant‐owners and investors using local data, and we find that many investors are misclassified as occupant‐owners in the Home Mortgage Disclosure Act data. Then, employing a competing risks framework to study ownerships during the period 1998 through mid‐2010, we find that local investors, who tend to invest more in relation to purchase prices and sell more quickly, experienced approximately 1.8 times the mortgage foreclosure risk of occupant‐owners, conditional on financing. Nonlocal investors have no statistically significant difference in foreclosure risk from occupant‐owners. Nonetheless, those owners with subprime purchase mortgages (most of whom are occupant‐owners) faced the highest foreclosure risk when house prices fell.     

Minimum nurse staffing ratios for nursing homes

The authors explored minimum nurse staffing ratios for nursing homes using production function simulations. Minimum levels of registered nurse hours per resident day were 0.31, 1.83, and 3.3 at 50%, 75%, and 90% levels of quality respectively. These results suggest that efficiency-oriented minimum nurse staffing points exist, and could be used to inform policymakers and nursing home administrators on better resource allocation and health care delivery.     

Incorporating price elasticity in financial forecasting models: From theory to practice and implementation

The authors use a capital budgeting example to show students how to incorporate price elasticity into financial analysis as an application of what students learn in their microeconomics course. They present simple as well as more advanced price-quantity relationships, and using various “what-if” scenarios; the authors show how risk analysis can be used to improve revenue projections and valuation models. A project analysis example is employed to illustrate results for negative predictive value and IRR based on three models of price elasticities across a range of potential product pricing. Students are then encouraged to replicate and create similar models, helping them improve their vital Excel and financial modeling skills.     

2015 will See Great Opportunities in Segment Market of Tablet PCs

【正】According to the latest Quarterly Report on the Chinese Tablet PC Market(Nov,2014)released by IDC,the Chinese tablet PC market will have a product delivery o...     

Building multivariate Sato models with linear dependence

The increased trading in multi-name financial products has required the development of state-of-the-art multivariate models. These models should be computationally tractable and, at the same time, flexible enough to explain the stylized facts of asset log-returns and of their dependence structure. The popular class of multivariate Lévy models provides a variety of tractable models, but suffers from one major shortcoming: Lévy models can replicate single-name derivative prices for a given time-to-maturity, but not for the whole range of quoted strikes and maturities, especially during periods of market turmoil. Moreover, there is a significant discrepancy between the moment term structure of Lévy models and the one observed in the market. Sato processes on the other hand exhibit a moment term structure that is more in line with empirical evidence and allow for a better replication of single-name option price surfaces. In this paper, we propose a general framework for multivariate models characterized by independent and time-inhomogeneous increments, where the asset log-return processes at unit time are modeled as linear combinations of independent self-decomposable random variables, where at least one self-decomposable random variable is shared by all the assets. As examples, we consider two general subclasses within this new framework, where we assume a normal variance-mean mixture with a one-sided tempered stable mixing density or a difference of one-sided tempered stable laws for the distribution of the risk factors. Particular attention is given to the models' ability to explain the asset dependence structure. A numerical study reveals the advantages of these new types of models.     

Determinants of Ethical Decision Making: The Relationship of the Perceived Organizational Environment

This study attempts to help explain the ethical decision making of individual employees by determining how the perceived organizational environment is related to that decision. A self- administered questionnaire design was used for gathering data in this study with a sample size of 245 full-time employees. Perceived supervisor expectation, formal policies, and informal policies were used to assess the expressed ethical decision of the respondents. The findings indicate that the perceived organizational environment is significantly related to the ethical decision of the respondent.