A review of: “CAPACITY UTILIZATION AND BUSINESS INVESTMENT” By Donald C. Streever University of Illinois,Urbana, Ill., 1960 Bureau of Economic and Business Research Bulletin No. 86 76 pp. $1.50

This book is a collection of papers originally written, for the most part, during the period from 1954 through June 1957, and gathered from a variety of sources. One-third of the contributed material comes from sections of other books, and another third from Harvard publications, primarily the Harvard Business Review. The remaining third is about equally divided among other professional societies and corporate manuals.     

Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration

Several studies that have investigated a few stocks have found that the spacing between consecutive financial transactions (referred to as trade duration) tend to exhibit long-range dependence, heavy tailedness, and clustering. In this study, we empirically investigate whether a larger sample of stocks exhibit those characteristics. We do so by comparing goodness of fit in modeling trade duration data for stable distribution and fractional stable noise based on a procedure applying bootstrap methods developed by the authors with several alternative distributional assumptions in modeling trade duration data. The empirical results suggest that the autoregressive conditional duration model with stable distribution fits better than other combinations, while fractional stable noise itself fits better for the time series of trade duration. Our result is consistent with the general findings in the literature that trade duration is informative and that short trade durations move prices more than long trade duration. In addition, our result confirms the advantage of fractal models in the study of roughness in trade duration and provides some evidence for duration dependence. S. Rachev’s research was supported by grants from the Division of Mathematical, Life and Physical Science, College of Letters and Science, University of California, Santa Barbara, and the Deutschen Forschungsgemeinschaft. W. Sun’s research was supported by grants from the Deutschen Forschungsgemeinschaft. P.S. Kalev’s research was supported with a NCG grant from the Faculty of Business and Economics, Monash University. Data are supplied by Securities Industry Research Center of Asia-Pacific (SIRCA) on behalf of Reuters. The first draft of this paper was presented at the International Conference on High Frequency Finance 2006; the authors would like to thank the conference participants for their valuable comments.     

Liquidity,default, taxes,and yields on municipal bonds

We examine the effects of liquidity, default and personal taxes on the relative yields of Treasuries and municipals using a generalized model with liquidity risk. The municipal yield model includes liquidity as a state factor. Using a unique transaction dataset, we estimate the liquidity risk of municipals and its effect on bond yields. Empirical evidence shows that municipal bond yields are strongly affected by all three factors. The effects of default and liquidity risk on municipal yields increase with maturity and credit risk. Liquidity premium accounts for about 9–13% of municipal yields for AAA bonds, 9–15% for AA/A bonds and 8–19% for BBB bonds. A substantial portion of the maturity spread between long- and short-maturity municipal bonds is attributed to the liquidity premium. Ignoring the liquidity risk effect thus results in a severe underestimation of municipal bond yields. Conditional on the effects of default and liquidity risk, we obtain implicit tax rates very close to the statutory tax rates of high-income individuals and institutional investors. Furthermore, these implicit income tax rates are quite stable across bonds of different maturities. Results show that including liquidity risk in the municipal bond pricing model helps explain the muni puzzle.     

Common information asymmetry factors in syndicated loan structures

This paper provides a comprehensive study of the syndicate structure and its relationship to information asymmetry and loan spread by using principal component analysis on a large set of 40 structure-related variables. A total of six structure components are identified and related to syndicate quality, syndicate members’ heterogeneity or share concentration, lead arranger’s characteristics, lead lender’s or syndicate’s location, lender–borrower relationships, and lead institution type. In multivariate settings, all six components are significant determinants of loan spread, either directly or indirectly through their impact on other components. Lead share retention, previous lender–borrower relationships and syndicate quality are shown to be bilaterally related to loan spread. Structure components differ regionally, which can provide an explanation for the European pricing discount observed in the literature. An Asian discount is observed and cannot be explained by structure differences.     

Does uncertainty matter for loan charge-offs?

Using a stylized real options model, we show that discretion over the timing of charging off a non-performing loan could be economically justified when collateral values are uncertain and there is a chance of loan recovery. The implied hypothesis of an “uncertainty dependence” aspect in loan charge-offs is empirically tested and validated using a panel of European banks. A welfare-maximizing regulator might want to let banks pursue such discretionary loan charge-off behavior, with the problem of distinguishing it from alternative capital management and income smoothing objectives, while transparency-seeking accounting standards setters would presumably not.     

Groups of Companies in Insolvency: A German Perspective

Based on an analysis concerning the disadvantages of the previous understanding of handling groups of companies by means of consolidation of jurisdiction, the following article illustrates the basic idea of group‐specialized proceedings (konzernspezifisches Sachwalterverfahren), avoiding ‘domino effects’ and thereby unnecessary insolvencies of profitable subsidiaries and preserving the assets of these parts of the group to a greater extent than an insolvency situation can. Copyright © 2013 INSOL International and John Wiley & Sons, Ltd     

Citizen participation in public administration: investigating open government for social innovation

In recent years, public sector organizations have increasingly focused on citizen contribution by adopting instruments known from open innovation. By collaborating with the periphery and leveraging external knowledge, government institutions initiate social innovation and stimulate a positive change for society. This article examines the involvement of citizens in an ideation platform initiated by a local government and investigates the motivations affecting participation intensity. Drawing on self‐determination theory, we analyze what motivates citizens to participate in an open government platform and how these motivations influence participation quantity. Based on a survey among platform users and the analysis of usage data from the platform operator, we find that motivations of citizen participation in public administration greatly vary across forms of participation. Whereas, intrinsic motivation is positively associated with producing and consuming platform content, external and introjected regulation negatively relate to individuals’ active contribution. At the same time, external regulation is positively associated with evaluation behavior.     

Old technology meets new technology: complementarities,similarities, and alliance formation

Alliance formation is commonplace in many high‐technology industries experiencing radical technological change, where established firms use alliances with new entrants to adapt to technological change, while new entrants benefit from the ability of established players to commercialize the new technology. Despite the prevalence of these alliances, we know little about how these firms choose to ally with specific firms given the range of possible partners they may choose from. This study explores factors that lead to alliance formation between pharmaceutical and biotechnology companies. We focus on the alliance tie as the unit of analysis and argue that dyadic complementarities and similarities directly influence alliance formation. We then introduce a contingency model in which the positive effect of complementarities and similarities on alliance formation is moderated by the age of the new technology firm. We draw theoretical attention to the intersection between levels of analysis, in particular, the intersection between dyadic and firm‐level constructs. We find that a pharmaceutical and a biotechnology firm are more likely to enter an alliance based on complementarities when the biotechnology firm is younger. Another noteworthy finding is that proxies for broad capabilities appear to be at least as effective, if not more so, in predicting alliance formation compared to fine‐grained science and technology‐related indicators, like patent cross‐citations or patent common citations. We conclude by suggesting that future studies on alliance formation need to take into account interactions across levels; for example, how dyadic capabilities interact with firm‐level factors, and the advantages and disadvantages of more or less fine‐grained measures of organizational capabilities. Copyright © 2007 John Wiley & Sons, Ltd.