Dividend Pricing Models and REITs

Dividend pricing/present value models relate current stock prices to expectations of future dividends. In this study we apply the West and Campbell–Shiller tests of the dividend pricing relation to an index of real estate investment trusts (REITs). REITs provide a unique test of these models since, during our study period, REITs were mandated to pay out at least 95% of taxable income as dividends. While our results complement previous research which finds that the dividend pricing model cannot be rejected if share repurchase is included as part of dividends, our data contain a much less significant amount of share repurchase, so that our approach to the issue of the viability of dividend pricing models offers an alternative insight. Our research suggests that, for our REIT population, dividend pricing models cannot be rejected.     

Capability hierarchy in electronic procurement and procurement process performance: An empirical analysis

This paper examines the interrelationship between two hierarchically structured functional capabilities pertinent in the organizational procurement process, and the impact of these capabilities on procurement process performance. These functional capabilities operate at different levels in an organization's procurement process. We draw upon resource- and knowledge-based views of the firm to theorize that in this hierarchy of information technology-enabled procurement capabilities, the higher-level capability – procurement integration competence – enables firms to develop and deploy a lower-level capability – digital procurement competence. Further, we theorize that the lower-level capability impacts procurement process performance directly and completely mediates the relationship between higher-level capability and performance. Thus, although performance is impacted directly only by the lower-level capability, the higher-level capability facilitates the development and use of the lower-level capability. Our research model is tested using survey data from a large sample of 412 manufacturing firms. The results provide strong support for the proposed research model. In particular, we find that as hypothesized, the impact of procurement integration competence on performance is completely mediated by digital procurement competence. Our results suggest that when examined at the procurement process level, the impact of higher-level capabilities may be manifested completely through the lower-level capabilities. Theoretical and practical implications of the research are discussed.     

An Investigation of Justice in supply chain relationships and their performance impact

Justice is important in improving performance of supply chain relationships. However, the role of justice in improving performance in supply chain relationships is an under-investigated subject in the literature. In studying the joint impact of justice dimensions, the traditional assumption is that the three forms of justice interact with each other in a multiplicative manner. However, this assumption creates a managerial problem as discussed in this paper. We outline a different view of how the justice dimensions interact with one another utilizing the constraining factor model (CFM). We show that the CFM resolves some of the problems arising from the choice of multiplicative interaction of justice measures on performance. Specifically, we demonstrate that an increase in procedural, distributive or interactional justice results in a significant and positive improvement in performance only if the specific justice dimension is the constraining factor in the relationship. Overall, our analysis suggests that all three dimensions are important and a high level of one of the justice elements will not compensate for a low level of another, a view that is put forward by a number of past research studies in justice. We discuss the theoretical and managerial implications of our findings.     

THE IMPACT OF LABOR MARKET REGULATION ON EMPLOYMENT IN LOW‐INCOME COUNTRIES: A META‐ANALYSIS

Controversy over labor market policy often centers on achieving a balance between preventing worker exploitation, and avoiding loss of productivity or employment through excessive regulation. Although the literature documenting the impact of labor market regulation on employment is extensive, there is a dearth of evidence on the impact of such policies in low‐income countries (LICs). Since it is easier for workers, especially women, to slip into the informal sector in LICs, regulations are likely to have stronger impacts on formal employment in these countries (but lower impacts on unemployment). We systematically reviewed available research from countries that are, or were until recently, LICs. Most studies document that more stringent labor regulations are associated with lower formal sector employment and higher informal sector employment. We also conducted a metaregression analysis of the impact of minimum wages on formal and informal employment. After controlling for publication bias, higher minimum wages are associated with lower formal employment and a higher share of informal workers.     

ExpertLens: A system for eliciting opinions from a large pool of non-collocated experts with diverse knowledge

The complexity of policy decision-making raises the need to elicit opinions from large and heterogeneous groups of stakeholders with broad and diverse sets of expertise. Existing options for elicitation include small face-to-face panels of experts by using the Nominal Group Technique (NGT), large Delphi panels whose members do not interact with each other face-to-face, and crowdsourcing, which involves an open call for input issued to a large community of people. In an attempt to close the gap between the practical needs of policy makers and the methodological challenges associated with eliciting opinions of large, diverse, and distributed groups, we have developed a new online elicitation system and methodology called ExpertLens. By optimizing the direct interactions of NGT with the larger number of Delphi participants and the wisdom of “selected crowds,” our approach is designed to save on the costs associated with traditional expert panels, while increasing accuracy in elicitation by reducing the potential for group process losses that can occur in large, diverse, and non-collocated panels whose members interact via asynchronous online discussion boards. The ExpertLens approach is iterative, does not require participants to develop consensus, and determines what the group “thinks” by statistically analyzing data collected in all rounds of the elicitation. This paper describes the ExpertLens system and methodology, briefly discusses recent ExpertLens trials, provides conceptual arguments for why it is an appropriate model for eliciting expert opinions, illustrates its main components and analytics by using an infrastructure investment example, and discusses a research agenda for testing the underlying tenets of the ExpertLens approach.     

The Impact of Fundamentals on IPO Valuation

We examine how initial public offering (IPO) valuation has changed over time by focusing on three time periods: 1986-1990, January 1997 to March 2000 (designated as the boom period), and April 2000 to December 2001 (designated as the crash period). Using a sample of 1,655 IPOs, we find that firms with more negative earnings have higher valuations than do firms with less negative earnings and firms with more positive earnings have higher valuations than firms with less positive earnings. Our results suggest that negative earnings are a proxy for growth opportunities for Internet firms and that such growth options are a significant component of IPO firm value.     

The value of combining the information content of analyst recommendations and target prices

In assessing the usefulness of the analysts’ stock picking advice, the extant literature has largely focused on the profitability of either their stock recommendations or target prices in isolation. In this paper, we examine the profitability of investment strategies that exploit the information analysts convey through revisions in both their stock recommendations and target prices. We find that these strategies significantly outperform the comparable strategies that make use of only one analyst output.