Not Featherbedding,but Feathering the Nest: Human Resource Management and Investments in Information Technology

This study draws on employment relations and management theory, claiming that certain innovative employment practices and work structures pave the way for organizational innovation, namely investments in information technology (IT). It then finds support for the theory in a cross‐section of UK workplaces. The findings suggest that firms slow to adopt IT realize that their conventional employment model hinders their ability to make optimal use of new technologies. Therefore, the paper advances the literature beyond studies of unionization's impact on business investment to a broader set of issues on the employment relations features that make organizations ripe for innovation.     

Estimating Olympic‐related investment and expenditure

The analysis of the impact of mega events has included frameworks that evaluate different impacts under different criteria, for example, separating impacts according to whether they occur before, during or after the event itself. Analysis of the economic impacts of such events has shown that the distributional effects between the host city and the rest of an economy can be important, and can have opposite signs. This paper introduces frameworks to show the origin of the economic scale, that is, Olympic‐related investment and expenditure, and shows how the frameworks can be used with reference to the Beijing 2008 Olympics. Copyright © 2008 John Wiley & Sons, Ltd.     

REAL OPTIONS: STATE OF THE PRACTICE

In the mid‐1980s, financial economists began building option‐based models to value corporate investments in real assets, laying the foundation for an extensive academic literature in this area. The 1990s saw several books, numerous conferences, and many articles aimed at corporate practitioners, who began to experiment with these techniques. Now, as we approach the end of 2001, the real options approach to valuing real investments has established a solid, albeit limited, foothold in the corporate world. Based on their recent interviews with 39 individuals from 34 companies in seven different industries, the authors of this article attempt to answer the question, “How is real options being practiced, and what impact is it having in the corporate setting?” The article identifies three main corporate uses of real options—as a strategic way of thinking, an analytical valuation tool, and an organization‐wide process for evaluating, monitoring, and managing capital investments. For example, in some companies, real options is used as an input into an M&A process in which rigorous numerical analysis plays only a small role. In such cases, real options contributes as a qualitative way of thinking, with little formality either in terms of analytical rigor or organizational procedure. In other firms, real options is used in a commodity trading environment where options are clearly specified in contracts and simply need to be valued. In this case, real options functions as an analytical tool, though generally only in specialized areas of the firm and not on an organization‐wide basis. In still other companies, real options is used in a technology or R&D context where the firm's success is driven by identifying and managing potential sources of flexibility. In such cases, real options functions as an organization‐wide process with both a broad conceptual and analytical core. The companies that have shown the greatest interest in real options generally operate in industries where large investments with uncertain returns are commonplace, such as oil and gas, and life sciences. Major applications include the evaluation of exploration and production investments in oil and gas firms, generation plant investments in power firms, R&D portfolios in pharmaceutical and biotech firms, and technology investment portfolios in high‐tech firms. While the approaches to implementation are quite varied, there appears to be a common path to the successful adoption of real options. The key steps of the adoption process are: (1) conducting pilot projects; (2) getting buy‐in from senior‐level and rank‐and‐file managers; (3) codifying real options through expert working groups, specialist training, and customization; and (4) institutionalizing and integrating real options firm‐wide. After citing best practices for each of these four steps, the authors close by predicting that a “network” effect and acceptance by Wall Street will serve as catalysts for more widespread corporate use of real options.     

Do alliances promote knowledge flows?

We explore the role of interfirm alliances as a mechanism for sharing technological knowledge. We argue that knowledge flows between alliance partners will be greater than flows between pairs of nonallied firms, and less than flows between units within single firms. Using patent citations as a proxy for knowledge flows, we find results that are consistent with these expectations. We then explore how firm characteristics affect knowledge flows within alliances and find positive effects due to technological, geographic, and business similarities between partners. We use alliance data from MERIT, patent data from the USPTO, and firm data from Compustat.     

Discretionary monetary policy and the zero lower bound on nominal interest rates

Ignoring the existence of the zero lower bound on nominal interest rates one considerably understates the value of monetary commitment in New Keynesian models. A stochastic forward-looking model with an occasionally binding lower bound, calibrated to the U.S. economy, suggests that low values for the natural rate of interest lead to sizeable output losses and deflation under discretionary monetary policy. The fall in output and deflation are much larger than in the case with policy commitment and do not show up at all if the model abstracts from the existence of the lower bound. The welfare losses of discretionary policy increase even further when inflation is partly determined by lagged inflation in the Phillips curve. These results emerge because private sector expectations and the discretionary policy response to these expectations reinforce each other and cause the lower bound to be reached much earlier than under commitment.     

Practitioners' Corner

The first 150 words of the full text of this article appear below. In our discussion in the last issue of Journal of FinancialEconometrics (JFEC) of the nonparametric methods developed byBarndorff-Nielsen and Shephard (2006) to detect jumps in thelocal behavior of the continuous time path of a price process,we observed these tests were not designed to detect major pricediscontinuity events such as the 1987 crash, since the testingmethodology precludes jumps in adjacent time intervals. Indeed,a major event such as Black Monday is characterized by a sequenceof jumps in consecutive time intervals throughout the day. Inthe interest of thematic continuity, let’s pursue thematter of jumps further. The first article in the current issue by Hossein Asgharianand Chistoffer Bengtsson addresses directly the detection ofbig events in stock prices. More particularly, the authors analyzethe spillover of jumps across international stock markets. Tomeasure jumps, the authors formulate a parametric model in . . . [Full Text of this Article]     

Practitioners' Corner

The first 150 words of the full text of this article appear below. Spring at last. Here in Montreal, the transition from winteris particularly delicious. There is more light, the world looksless grey, and the trepidation that another storm may be aroundthe corner is put away with the winter tires. In this issueof JFEC, the editors appear to be underscoring seasonal changein an issue whose unifying theme involves parameter and modelstability. Parameter stability is an important issue in econometrics. Achanging economic environment may be captured by allowing theparameters of a reduced form model to vary to reflect changingconditions. The challenge for the econometrician is to constructmodels that do more than reflect changes in an ad hoc manner.For want of more insightful approaches, the challenge is oftensidestepped in practice by focusing on shorter samples whereno structural change can be assumed to have occurred. However,in so constricting the sample size, . . . [Full Text of this Article]     

Practitioners' Corner: Introduction to the Special Issue

The first 150 words of the full text of this article appear below. The material in this volume is the result of a call for papersto the participants of the "Conference on Analysis of High-FrequencyFinancial Data and Market Microstructure" held in December 2003in Taipei, Taiwan. Jeffrey Russell and Ruey Tsay have actedas guest editors for this special issue, together with the editorsRené Garcia and Eric Renault. The availability of high-frequency data has spawned considerableliterature on volatility measurement and forecasting. The materialis mathematically delicate and perhaps "Practitioners’Corner" would be well advised to let the dust settle a bit tosee what emerges at the end of the day. On the other hand, thepractically minded may well be served by a good road map ofthe issues. So with only mild apology do we take up the cartographyof some difficult terrain. To fix ideas, let S(t) denote the price process of a . . . [Full Text of this Article]