Non-uniform effects of CEO equity-based compensation on firm performance – An application of a panel threshold regression model

We use panel-data threshold models to examine the non-uniform relation between Chief Executive Officer (CEO) equity-based compensation and earnings-based performance. Prior studies examining this very issue have arbitrarily adopted various exogenous criteria to partition the sample, and thus the inferences could be misleading. To address this issue, we employ the threshold regression models that allow the data itself to endogenously generate several regimes identified by the thresholds. Our empirical results show that not only is the positive impact of CEO equity incentives on firm performance more pronounced for companies with lower and moderate levels of CEO stock-based incentive pay, but also for less-profitable firms. The results are consistent with the position that excessive equity-based awards are unable to benefit firm performance, and that share-based compensation is more effective for start-up firms with low profit.     

Post-IPO Operating Performance, Venture Capital and the Bubble Years

Abstract:  We analyse the post-issue operating performance of 316 venture-backed and 274 non-venture UK IPOs 1985–2003. The finding of a statistically significant five-year, operational decline exhibited over the full sample period is not robust. Rather it is driven by the dramatic underperformance during the 1998–2000 bubble years while IPOs perform normally in the remaining years. Cross-section regression results indicate support for venture capital certification in the non-bubble years but a significantly negative relationship between operating performance and venture capitalist board representation during the bubble years. The bubble year underperformance is explained by market timing and by low quality companies taking advantage of investor sentiment.     

Sectoral Patterns of Interactive Learning: An Empirical Exploration of a Case in a Dutch Region

This paper pursues the development of a theoretical framework that explains interactive learning between innovator firms and external actors in both the knowledge infrastructure and the production chain. The research question is: What kinds of factors explain the interactive learning of innovator firms with distinct external actors? Our theoretical framework extends the resource-based perspective, which is predominant in network theory, with both an activity-based and a structural account of interactive learning. We contend basically that higher technological dynamics induce more complex innovative activities. But, more complex innovative activities increase the probability of internal resource deficits/shortages in the innovator firms. The lower the alignment of the innovative activities with the quality of the internal resource base, the higher the resource deficits/shortages and the more likely the search for complementary resources externally, which increases the likeliness of external relationships. In order to test the generality of our theoretical claims we analyse our models in four sectors with distinct technological dynamics as distinguished by Pavitt. For each sector we explore five models of the level of interactive learning of innovator firms with: (1) the public knowledge infrastructure (difficult to access, demands high internal competencies to utilize scientific knowledge), (2) the production chain (easy to access), (3) their users, (4) their suppliers, (5) their competitors. These analyses allow for a comparison between interactive learning with different external actors and give deeper insights into the differentiated interaction patterns involving innovation. Our findings show that patterns of interactive learning between sectors differ. Some are more resource based and others are more affected by the complexity of innovative activities. Particularly the patterns of interactive learning between, on the one hand, firms and the knowledge infrastructure, and on the other hand of firms with the production chain show important differences.     

Random Walks and the Cointegration of the ACLI and NCREIF

Do NCREIF returns influence commercial mortgage underwriters when they adjust capitalization rates? Are the ACLI capitalization series and the NCREIF return series cointegrated at the national and the smaller geographic sub‐division levels? This research uses a two‐step procedure to test for cointegration. First, the Phillips–Perron unit‐root procedure must show that each series is a unit‐root random walk. Previous research usually has assumed that these series are random walks, with the implication that the commercial mortgage market is efficient. Second, the Phillips–Ouliaris test of the residuals of a function of the two series determines the possibility of cointegration. At the national level and for the Northeast and Pacific regions the two series are random walks and cointegrated. In other geographic sub‐divisions, neither or only one series is a random walk and therefore the data does not support a relationship. The lack of functional relationships in four of the six smaller geographic regions suggests that underwriters are not obtaining the NCREIF information or are ignoring it. The lack of random walks with the implication about capital‐market efficiency invites further research.     

Nachhaltigkeit von Biokraftstoffen: Ziele,Probleme und Instrumente

Klimawandel und Versorgungssicherheit bestimmen die Suche nach ?kologisch und ?konomisch nachhaltigen Energietr?gern. Biokraftstoffe scheinen beiden Zielen gleicherma?en gerecht zu werden. Was ist bei der Bewertung der Nachhaltigkeit von Biokraftstoffen zu beachten? Sollte der Staat bei der Bereitstellung eingreifen? Welche wirtschaftspolitischen Instrumente schaffen positive Anreize beim Verbrauch von Biokraftstoffen? Dr. Michael Br?uninger, 43, ist Leiter des Kompetenzbereichs Wirtschaftliche Trends des Hamburgischen WeltWirtschaftsInstituts HWWI; Leon Leschus, 31, Dipl.-Volkswirt, und Dr. Henning V?pel, 35, sind dort wissenschaftliche Mitarbeiter.     

Measuring Business Cycles Intra‐Synchronization in US: A Regime‐switching Interdependence Framework

This paper proposes a Markov‐switching framework to endogenously identify periods where economies are more likely to (i) synchronously enter recessionary and expansionary phases, and (ii) follow independent business cycles. The reliability of the framework is validated with simulated data in Monte Carlo experiments. The framework is applied to assess the time‐varying intra‐country synchronization in the US. The main results report substantial changes over time in the cyclical affiliation patterns of US states, and show that the more similar the economic structures of states, the higher the correlation between their business cycles. A synchronization‐based network analysis discloses a change in the propagation pattern of aggregate contractionary shocks across states, suggesting that the US has become more internally synchronized since the early 1990s.     

Do We Follow the Leader or the Masses? Antecedents of the Willingness to Pay Extra for Eco‐Products

This paper reports on an experiment that tests for the existence of peer effects in consumers' willingness to pay (WTP) for sustainable products. More specifically, we investigate whether the premium for an eco‐labeled laundry detergent is sensitive to receiving information about the premium paid by other members of one's social group. The information manipulations in the experiment test for two distinct types of social influence, i.e., conformist and payoff‐biased transmission. We find strong empirical evidence for a conformist transmission. Participants informed about the positive premium paid by the majority of their peers reported a higher premium than individuals not receiving any information. This result shows that previous studies on the WTP for sustainable products, which explain premiums by attitudinal measures and sociodemographic traits, unwarrantedly provide an under‐socialized account. The inclusion of social influence variables significantly increases the explanatory power of the model.     

Re-examining the risk–return relationship in banks using quantile regression

Financial data for the US banks listed during 2001–2007 are analysed to re-examine the risk–return relationship in the banking industry. A key feature of this study is the analysis of the changing distribution of return on equity across banks and over time by the quantile regression (hereafter QR) model and a meaningful comparative analysis with the results of the ordinary least squares estimates is examined. The following conclusions are drawn from the empirical results. First, while a positive risk–return relationship is presented for the profitable banks, the risk–return relationship is negative for the profitless banks. Second, the ‘V’ shape relationship between bank risk and profitability identified by this study could satisfactorily explain the existing risk–return puzzle among the prior empirical studies.