CEO career horizon,corporate governance,and real options: The role of economic short‐termism

Research Summary: Combining studies on real options theory and economic short‐termism, we propose that, depending on CEOs’ career horizons, CEOs have heterogeneous interests in strategic flexibility, and thus, have different incentives to make real options investments. We argue that compared to CEOs with longer career horizons, CEOs with shorter career horizons will be less inclined to make real options investments because they may not fully reap the rewards during their tenure. In addition, we argue that long‐term incentives and institutional ownership will mitigate the relationship between CEOs’ career horizons and real options investments. U.S. public firms as an empirical setting produced consistent evidence for our predictions. Our study is the first to theoretically explain and empirically show that a CEO's self‐seeking behavior will impact real options investments. Managerial Summary: This article helps to explain how a CEO's self seeking‐behavior may shape a firm's real option investment, which could result in different level of strategic flexibility. We argue that CEOs with short career horizons have less time to exercise their firms’ real options, which should lower the investments in the firms’ real options portfolios relative to CEOs with long career horizons. We study a sample of U.S. public firms and find strong evidence that a CEO's expected tenure in the firm is positively related to the real options investments at the firm level. We find that this agency issue can be mitigated by adopting appropriate corporate governance mechanisms such as long‐term incentives and institutional investors.     

A Study on Flow Experience Structures: Enhancement or Death,Prospects for the Korean Wave

In proposing the concept of flow which focuses on experiencing the sites visited by Korean Wave tourists as induced by drama or movies, the role of involvement level (variables) of Korean Wave tourists in influencing flow construct as they experience the sites of FIT (Film Induced Tourism) was investigated. The involvement level of Korean Wave visitors was found to operate as a mechanism by which challenge, skills, and focused attention on site might be more organized or more actively experienced. This recognizes that there is clearly a need for making the FIT sites exposed much by any mix of various media. The findings of this study showed that challenges and skills influence enjoyment as an output factor of flow. Film site visitors are assumed to participate in the roles of film characters, experiencing the places and the atmosphere. The degree of visitors' reflections of the film optimizes awareness of flow experiences on the site. Therefore it is necessary to provide more detailed experiential programs on the film sites with a wide variety of flow-related contents in the film.     

Introduction to APPC-2018, a Special Issue of the Journal of Productivity Analysis, “Novel Applications of Efficiency and Productivity Analyses in the Asia-Pacific Region”

In this study, an appropriate nonparametric two-step approach to conditional efficiencies is used to investigate how size and time affect the performance of companies. Using a dataset of Italian manufacturing firms over the period 2006–2015, we explore the effect of size on the attainable production set (input-output space) and on the efficiency distribution, without making any a priori assumptions on the role of size on efficiency. Main findings suggest that size positively affects the efficiency of companies. By exploring the idiosyncratic efficiency, an additional empirical result from the conditional efficiency approach shows that the economic disparities between North, Centre and South of Italy not only limit the foreign investment but also seem to penalize the productivity of Italian-owned companies.

     

GMM and 2SLS estimation of mixed regressive,spatial autoregressive models

The GMM method and the classical 2SLS method are considered for the estimation of mixed regressive, spatial autoregressive models. These methods have computational advantage over the conventional maximum likelihood method. The proposed GMM estimators are shown to be consistent and asymptotically normal. Within certain classes of GMM estimators, best ones are derived. The proposed GMM estimators improve upon the 2SLS estimators and are applicable even if all regressors are irrelevant. A best GMM estimator may have the same limiting distribution as the ML estimator (with normal disturbances).     

Identification and estimation of econometric models with group interactions,contextual factors and fixed effects

This paper considers identification and estimation of structural interaction effects in a social interaction model. The model allows unobservables in the group structure, which may be correlated with included regressors. We show that both the endogenous and exogenous interaction effects can be identified if there are sufficient variations in group sizes. We consider the estimation of the model by the conditional maximum likelihood and instrumental variables methods. For the case with large group sizes, the possible identification can be weak in the sense that the estimates converge in distribution at low rates.     

On a family of data-based transformed models useful in forecasting technological substitutions

This paper examines, via real data, some well known models for technology substitution analysis. We propose a family of data-based transformed models that will include the models under examination as special cases. The basic thrust of the paper is the recognition that for technology substitution analysis, the observations are time series data and hence are not independent. Also, the functional form of the model should be determined by both theoretical considerations as well as the data on hand. This suggests that the traditional ordinary least squares procedure used in estimating the parameters and the resulting forecasting procedures are not adequate. The existing models examined here are Fisher–Pry, Gompertz, Weibull, and Normal. We stress the statistical aspects of the models and their relative merits in terms of predictive power. The criteria used for the purpose of comparison are the mean squared deviation and the mean absolute deviation of the predicted values compared with the actual observations.     

The asymmetric relationship between executive earnings management and compensation: a panel threshold regression approach

Prior research shows that chief executive officers (CEOs) are rewarded for their earnings management. We re-examine this issue using a panel threshold regression approach, which allows the effect of earnings management on the CEO compensation to change across the level of earnings management and CEO compensation. Our results show that the effect of CEOs’ discretionary accounting choices on their compensation is not homogeneous across various degrees of earnings management and compensation. In particular, for firms with moderate (inordinate) levels of earnings management and CEO compensation, earnings management is rewarded (penalized).