TESTING FOR PARAMETER STABILITY IN EXECUTIVE REMUNERATION FUNCTIONS

1993 ◽  
Vol 14 (2) ◽  
pp. 54-73
Author(s):  
Andrew W. Braunstein
Author(s):  
Stefan Schmid ◽  
Sebastian Baldermann

AbstractIn this paper, we study the effect a CEO’s international work experience has on his or her compensation. By combining human capital theory with a resource dependence and a resource-based perspective, we argue that international work experience translates into higher pay. We also suggest that international work experience comprises several dimensions that affect CEO compensation: duration, timing and breadth of stays abroad. With data from Europe’s largest stock market firms, we provide evidence that the longer the international work experiences and the more numerous they are, the higher a CEO’s compensation. While, based on our theoretical arguments, we expect to find that later international work experiences pay off for CEOs, our empirical analysis shows that earlier international work experiences are particularly valuable in terms of compensation. In addition, our data support the argument that maturity allows a CEO to take advantage of the skills, knowledge and competencies obtained via international experience—and to receive a higher payoff. With our study, we improve the understanding of how different facets of a CEO’s background shape executive remuneration.


2013 ◽  
Vol 45 (1) ◽  
pp. 26-33 ◽  
Author(s):  
Mark Farmer ◽  
Duncan Brown ◽  
Peter Reilly ◽  
Stephen Bevan

2008 ◽  
Vol 10 (2) ◽  
pp. 153-162 ◽  
Author(s):  
B. G. Ruessink

When a numerical model is to be used as a practical tool, its parameters should preferably be stable and consistent, that is, possess a small uncertainty and be time-invariant. Using data and predictions of alongshore mean currents flowing on a beach as a case study, this paper illustrates how parameter stability and consistency can be assessed using Markov chain Monte Carlo. Within a single calibration run, Markov chain Monte Carlo estimates the parameter posterior probability density function, its mode being the best-fit parameter set. Parameter stability is investigated by stepwise adding new data to a calibration run, while consistency is examined by calibrating the model on different datasets of equal length. The results for the present case study indicate that various tidal cycles with strong (say, >0.5 m/s) currents are required to obtain stable parameter estimates, and that the best-fit model parameters and the underlying posterior distribution are strongly time-varying. This inconsistent parameter behavior may reflect unresolved variability of the processes represented by the parameters, or may represent compensational behavior for temporal violations in specific model assumptions.


2021 ◽  
Vol 14 (3) ◽  
pp. 136
Author(s):  
Holger Fink ◽  
Stefan Mittnik

Since their introduction, quanto options have steadily gained popularity. Matching Black–Scholes-type pricing models and, more recently, a fat-tailed, normal tempered stable variant have been established. The objective here is to empirically assess the adequacy of quanto-option pricing models. The validation of quanto-pricing models has been a challenge so far, due to the lack of comprehensive data records of exchange-traded quanto transactions. To overcome this, we make use of exchange-traded structured products. After deriving prices for composite options in the existing modeling framework, we propose a new calibration procedure, carry out extensive analyses of parameter stability and assess the goodness of fit for plain vanilla and exotic double-barrier options.


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