The effect of management changes on winning in professional sports: Analysis using a dynamic lag adjustment model

This paper examines whether coaching and general manager (GM) changes among three professional sports leagues—the National Football League (NFL), the Major League Baseball (MLB), and the National Basketball Association (NBA)—effect on‐field performance. Our empirical methodology uses team‐level data by season and adapts a lag adjustment econometric approach designed to resolve several statistical challenges that arise both in general managerial settings and in sports settings. Our main finding is that coaching changes in the NFL boost the number of wins per season by between 0.5 and 1.2 in each of the first five seasons. Coaching changes have smaller, but still positive, impacts in the MLB and NBA. For all the three leagues, we find that GM changes have no discernable impact on performance. A separate cross‐sectional analysis suggests that those small impacts stem from coaches and GMs having extremely compressed talent distributions. The data indicate that coaches and GMs, en masse, are important, but changing the people who occupy those positions rarely seems to move teams to different locations on the performance distribution.     

Bettor preferences and market efficiency in football totals markets

The betting markets for totals in college football and arena football provide additional evidence of bettor preference for scoring. The results for college football and arena football markets are similar to those found in the professional football and professional basketball totals market. In all of these leagues, the overs are overbet. We suggest that there is a clear preference for bettors to bet the over and the extent of the bias depends upon the volume of uninformed bettors to informed bettors and limits placed on bets in these markets.     

Revisiting the issue of survivability and market efficiency with the Santa Fe Artificial Stock Market

The relevance of risk preference and forecasting accuracy for investor survival has recently been the focus of a series of theoretical and simulation studies. At one extreme, it has been proven that risk preference can be entirely irrelevant (Sandroni in Econometrica 68:1303–1341, 2000; Blume and Easley in Econometrica 74(4):929–966, 2006). However, the agent-based computational approach indicates that risk preference matters and can be more relevant for survivability than forecasting accuracy (Chen and Huang in Advances in natural computation, Springer, Berlin, 2005; J Econ Behav Organ 67(3):702–717, 2008; Huang in J Econ Interact Coord, 2015). Chen and Huang (Inf Sci 177(5):1222–1229, 2007, 2008) further explained that it is the saving behavior of traders that determines their survivability. However, institutional investors do not have to consider saving decisions that are the most influential investors in modern financial markets. Additionally, traders in the above series of theoretical and simulation studies have learned to forecast the stochastic process that determines which asset will pay dividends, not the market prices and dividends. To relate the research on survivability to issues with respect to the efficient markets hypothesis, it is better to endow agents with the ability to forecast market prices and dividends. With the Santa Fe Artificial Stock Market, where traders do not have to consider saving decisions and can learn to forecast both asset prices and dividends, we revisit the issue of survivability and market efficiency. We find that the main finding of Chen and Huang (2008) that risk preference is much more relevant for survivability than forecasting accuracy still holds for a wide range of market conditions but can fail when the baseline dividend becomes very small. Moreover, the advantage of traders who are less averse to risk is revealed in the market where saving decisions are not taken into account. Finally, Huang’s (2015) argument regarding the degree of market inefficiency is confirmed.     

Sportsbook pricing and the behavioral biases of bettors in the NHL

The betting market for the NHL is investigated using actual betting percentages on favorites and underdogs from real sportsbooks. Sportsbooks do not appear to attempt to price to balance the book as betting percentages are not proportional to set odds. As in the NFL and NBA, bettors are shown to have a strong preference for favorites and road favorites in particular. Simple strategies of betting against significant imbalances toward the favorite are shown to generate positive returns. Although not pricing to balance the book, sportsbooks do not appear to price to exploit known bettor biases in all cases. Clear bettor behavioral biases for road favorites are not priced into the odds as the prices set in these cases appear to be a forecast of game outcomes. Pricing as a forecast may ensure long-run viability for the sportsbook as it discourages entry into this market by informed traders and still allows the sportsbook to capture its commission on losing bets over time.     

Estimating heterogeneous agents behavior in a two-market financial system

In this paper, we propose a two-market empirical model with heterogeneous agents based on Chiarella et al. (J Econ Behav Organ 83(3):446–460, 2012). Using monthly data of French and US stock markets, the regression shows that individual markets have features of a two-regime switching process. By including inter-market traders whose trading decision is based on fundamental value of foreign market, the two-market model has a better capability in explaining both markets with domestic fundamental traders turning to be significant. The existence of inter-market traders implies that the two markets impact each other through their fundamentals and hence share some common set of factors, which provides foundation of market interactions, such as market co-movement.     

Interest rate dynamics and volatility transmission in the European short term interest rate market

This paper investigates the price and volatility relationship in European short-term interest rate markets. Cointegration analysis is used to analyse the long and short run relationship and a GARCH BEKK model is estimated to analyse the volatility transmission between the markets. The stability of the long run relationship is also examined using Bai and Perron (Econometrica 66(1),47–78, 1998, J Appl Econ 18(1):1–22, 2003) structural break methodology. The results show that the relationship between the EURIBOR spot deposit rate and the EURIBOR future contract has changed significantly since 2001 and several structural breaks are present in the 13 year sample period. During periods where there is a long run relationship present the spot deposit rate generally leads the future rate in price discovery. In the short run there is bi-directional causality present between the markets. There is also significant evidence of volatility transmission from the spot market to the futures market throughout the sample period.     

An evaluation of the performance and suitability of R × C methods for ecological inference with known true values

Ecological inference refers to the study of individuals using aggregate data and it is used in an impressive number of studies; it is well known, however, that the study of individuals using group data suffers from an ecological fallacy problem (Robinson in Am Sociol Rev 15:351–357, 1950). This paper evaluates the accuracy of two recent methods, the Rosen et al. (Stat Neerl 55:134–156, 2001) and the Greiner and Quinn (J R Stat Soc Ser A (Statistics in Society) 172:67–81, 2009) and the long-standing Goodman’s (Am Sociol Rev 18:663–664, 1953; Am J Sociol 64:610–625, 1959) method designed to estimate all cells of R × C tables simultaneously by employing exclusively aggregate data. To conduct these tests we leverage on extensive electoral data for which the true quantities of interest are known. In particular, we focus on examining the extent to which the confidence intervals provided by the three methods contain the true values. The paper also provides important guidelines regarding the appropriate contexts for employing these models.     

Market efficiency in Scandinavian racetrack betting

This study analyzes Scandinavian racetrack betting markets. We discuss market efficiency and investor behavior in light of the fact that investors earn negative returns on average. Show bets on favorites in Norway yield a small positive return, while all the other betting markets are weak form efficient. We establish the favorite-longshot bias for quinella and exactor bettors, but not for win bettors. Our results can be explained by small pools and high track takes. Investors wagering at the racetrack have a different risk attitude than investors wagering off the track. We explain how our results should influence the design of betting products, especially with respect to the fraction of the pool returned to winners.     

One-sided hyperbolic simultaneous confidence bands for multiple and polynomial regression models

A simultaneous confidence band is a useful statistical tool in a simultaneous inference procedure. In recent years several papers were published that consider various applications of simultaneous confidence bands, see for example Al-Saidy et al. (Biometrika 59:1056–1062, 2003), Liu et al. (J Am Stat Assoc 99:395–403, 2004), Piegorsch et al. (J R Stat Soc 54:245–258, 2005) and Liu et al. (Aust N Z J Stat 55(4):421–434, 2014). In this article, we provide methods for constructing one-sided hyperbolic imultaneous confidence bands for both the multiple regression model over a rectangular region and the polynomial regression model over an interval. These methods use numerical quadrature. Examples are included to illustrate the methods. These approaches can be applied to more general regression models such as fixed-effect or random-effect generalized linear regression models to construct large sample approximate one-sided hyperbolic simultaneous confidence bands.     

Persistent and transient productive inefficiency: a maximum simulated likelihood approach

The productive efficiency of a firm can be seen as composed of two parts, one persistent and one transient. The received empirical literature on the measurement of productive efficiency has paid relatively little attention to the difference between these two components. Ahn and Sickles (Econ Rev 19(4):461–492, 2000) suggested some approaches that pointed in this direction. The possibility was also raised in Greene (Health Econ 13(10):959–980, 2004. doi:10.1002/hec.938), who expressed some pessimism over the possibility of distinguishing the two empirically. Recently, Colombi (A skew normal stochastic frontier model for panel data, 2010) and Kumbhakar and Tsionas (J Appl Econ 29(1):110–132, 2012), in a milestone extension of the stochastic frontier methodology have proposed a tractable model based on panel data that promises to provide separate estimates of the two components of efficiency. The approach developed in the original presentation proved very cumbersome actually to implement in practice. Colombi (2010) notes that FIML estimation of the model is ‘complex and time consuming.’ In the sequence of papers, Colombi (2010), Colombi et al. (A stochastic frontier model with short-run and long-run inefficiency random effects, 2011, J Prod Anal, 2014), Kumbhakar et al. (J Prod Anal 41(2):321–337, 2012) and Kumbhakar and Tsionas (2012) have suggested other strategies, including a four step least squares method. The main point of this paper is that full maximum likelihood estimation of the model is neither complex nor time consuming. The extreme complexity of the log likelihood noted in Colombi (2010), Colombi et al. (2011, 2014) is reduced by using simulation and exploiting the Butler and Moffitt (Econometrica 50:761–764, 1982) formulation. In this paper, we develop a practical full information maximum simulated likelihood estimator for the model. The approach is very effective and strikingly simple to apply, and uses all of the sample distributional information to obtain the estimates. We also implement the panel data counterpart of the Jondrow et al. (J Econ 19(2–3):233–238, 1982) estimator for technical or cost inefficiency. The technique is applied in a study of the cost efficiency of Swiss railways.     

Organizational Socialization and Psychological Contract: the Vulnerability of Temporary Newcomers. A Case Study from an Italian <Emphasis Type="Italic">Call Center</Emphasis>

This study aims to analyze the link between the construction of an effective psychological contract with the organization and the success of the socialization process. To this purpose 241 employees of a Call Center organization have been contacted. A questionnaire composed by measures of Organizational Socialization (Haueter et al. Journal of Vocational Behavior, 63, 20–39, 2003), Psychological Contract (Rousseau 1995), Job Satisfaction (Wanous et al. Journal of Applied Psychology, 82, 247–252, 1997) and Organizational Committment (Allen and Meyer 1990) was administered. Results have underlined that organizational socialization may influence the development of the psychological contract thus determining job satisfaction and organizational commitment. This research has been developed in an interdisciplinary perspective, taking into account the peculiarity of the Italian legal framework. In this regard, the analysis has been focused on how the E.U. flexicurity strategy has been implemented in Italy, according to the recent reform of labour market regulation (2012–13) and on the specific regulations introduced for call centres.     

Convex incentives in financial markets: an agent-based analysis

We investigate whether convex incentive contracts are a source of instability of financial markets as indicated by the results of a continuous double-auction asset market experiment performed by Holmen et al. (J Econ Dyn Control 40:179–194, 2014). We develop a model to replicate the setting of the experiment and perform an agent-based simulation where agents have linear or convex incentives. Extending the simulation by varying features of actual asset markets that were not studied in the experiment, our main results show that increasing the number of convex incentive contracts increases prices and volatility and decreases market liquidity, measured both as bid–ask spreads and volumes. We also observe that the influence of risk aversion on traders’ decisions decreases when there are convex contracts and that increasing the differences in initial wealth among the traders has similar effects as increasing number of convex incentive contracts.     

Multidimensional strong large deviation results

We establish strong large deviation results for an arbitrary sequence of random vectors under some assumptions on the normalized cumulant generating function. In other words, we give asymptotic approximations for a multivariate tail probability of the same kind as the one obtained by Bahadur and Rao (Ann Math Stat 31:1015–1027, 1960) for the sample mean (in the one-dimensional case). The proof of our results follows the same lines as in Chaganty and Sethuraman (J Stat Plan Inference, 55:265–280, 1996). We also present three statistical applications to illustrate our results, the first one dealing with a vector of independent sample variances, the second one with a Gaussian multiple linear regression model and the third one with the multivariate Nadaraya–Watson estimator. Some numerical results are also presented for the first two applications.     

Individual entrepreneurship,collective entrepreneurship and innovation in small business: an empirical study

The study reported in this article examines simultaneously the impact of individual entrepreneurship and collective entrepreneurship on innovation in small business. It intends to address the weakness in previous entrepreneurship research that either only focuses on the individual entrepreneur's role in innovation (Miller 1983 Management Science, 29:770-791), or only stresses the importance of collective entrepreneurship (Reich 1987 Harvard Business Review, 65 (3), 22-83; Stewart 1989). The results of structural equation modeling analysis of data from more than 200 small businesses show that both individual entrepreneur(s) and the collective contribute to innovation in small business. Analysis results also reveal the complex relationships between the two types of entrepreneurship in terms of their impact on innovation in small business. Factors that contribute to collective entrepreneurship were found to contribute to individual entrepreneurship, while factors that are often associated with individual entrepreneurship were found to have negative impact on collective entrepreneurship. Communication among members of the small business, which was found to directly contribute to collective entrepreneurship, was found to contribute to individual entrepreneur's knowledge of emerging markets, products, and technologies. In contrast, centralized decision making, which was found to have direct negative impact on innovation, was found to have negative impact on collaboration and communication. Implications of the study are discussed.     

What does the financial market pricing do? A simulation analysis with a view to systemic volatility,exuberance and vagary

Biondi et al. (Phys A 391(22):5532–5545, 2012) develop an analytical model to examine the emergent dynamic properties of share market price formation over time, capable to capture important stylized facts. These latter properties prove to be sensitive to regulatory regimes for fundamental information provision, as well as to market confidence conditions among actual and potential investors. We comparatively assess accounting models belonging to two main families: historical cost accounting and mark-to-market (fair value) accounting regimes. Regimes based upon mark-to-market measurement of traded security, while generating higher linear correlation between market prices and fundamental signals, also involve higher market instability and volatility. These regimes also incur more relevant episodes of market exuberance and vagary in some regions of the market confidence space, where lower market liquidity further occurs.     

A note on fourth-order risk aversion

Keenan et al. (J Risk Uncertain 24:264–277, 2002) introduced a measure of downside risk aversion (third-order risk aversion), and in Theorem 1, they showed four equivalent definitions of increased downside risk aversion. This result is thought as a higher-order extension of Theorem 3 in Diamond et al. (J Econ Theory 8:337–360, 1974). We consider fourth-order risk aversion and show four equivalent definitions of increased fourth-order risk aversion. Our result is thought as a higher-order extension of Theorem 1 in Keenan et al. (2002).     

Kalai and Muller’s possibility theorem: a simplified integer programming version

We provide a respecification of an integer programming characterization of Arrovian social welfare functions introduced by Sethuraman et al. (Math Oper Res 28:309–326, 2003). By exploiting this respecification, we give a new and simpler proof of Theorem 2 in Kalai and Muller (J Econ Theory 16:457–469, 1977).     

Universally optimal designs under mixed interference models with and without block effects

The literature on neighbor designs as introduced by Rees (Biometrics 23:779–791, 1967) is mainly devoted to construction methods, providing few results on their statistical properties, such as efficiency and optimality. A review of the available literature, with special emphasis on the optimality of neighbor designs under various fixed effects interference models, is given in Filipiak and Markiewicz (Commun Stat Theory Methods 46:1127–1143, 2017). The aim of this paper is to verify whether the designs presented by Filipiak and Markiewicz (2017) as universally optimal under fixed interference models are still universally optimal under models with random interference effects. Moreover, it is shown that for a specified covariance matrix of random interference effects, a universally optimal design under mixed interference models with block effects is universally optimal over a wider class of designs. In this paper the method presented by Filipiak and Markiewicz (Metrika 65:369–386, 2007) is extended and then applied to mixed interference models without or with block effects.     

Can structural change explain the Meese-Rogoff puzzle?

This paper provides empirical evidence suggesting that fundamentals matter for stock price fluctuations once temporal instability underpinning stock price-relations is accounted for. Specifically, this study extends the out-of sample forecasting methodology of Meese and Rogoff (J Int Econ 14:3–24 (1983)) to the stock market after explicitly testing for parameter nonconstancy using recursive techniques. The predictive ability of a present value model based on Imperfect Knowledge Economics (IKE) is found to match that of the pure random walk benchmark at short forecasting horizons and to perform significantly better at medium to longer-run horizons based on conventional measures of predictability and direction of change statistics. In addition, the presence of a cointegrating relation is found only within regimes of statistical parameter constancy. Augmenting the MR methodology in a piecewise linear fashion yields empirical results in favor of a fundamentals-based account of stock price behavior overturning the recent results of Flood and Rose (2010).     

Technological change and timing reductions in greenhouse gas emissions

In 2007 Nicholas Stern’s Review (in Science 317:201–202, 2007) estimated that global GDP would shrink by 5–20% due to climate change which brought forth calls to reduce emissions by 30–70% in the next 20 years. Stern’s results were contested by Weitzman (in J Econ Lit XLV(3):703–724, 2007) who argued for more modest reductions in the near term, and Nordhaus (in Science 317:201–202, 2007) who questioned the low discount rate and coefficient of relative risk aversion employed in the Stern Review, which caused him to argue that ‘the central question about global-warming policy—how much how, how fast, and how costly—remain open.’ We present a simulation model developed by Färe et al. (in Time substitution with application to data envelopment analysis, 2009) on intertemporal resource allocation that allows us to shine some light on these questions. The empirical specification here constrains the amount of undesirable output a country can produce over a given period by choosing the magnitude and timing of those reductions. We examine the production technology of 28 OECD countries over 1992–2006, in which countries produce real GDP and CO₂ using capital and labor and simulate the magnitude and timing necessary to be in compliance with the Kyoto Protocol. This tells us ‘how fast’ and ‘how much’. Comparison of observed GDP and simulated GDP with the emissions constraints tells us ‘how costly’. We find these costs to be relatively low if countries are allowed reallocate production decision across time, and that emissions should be cut gradually at the beginning of the period, with larger cuts starting in 2000.