Executive Compensation and CEO Equity Incentives in China’s Listed Firms (CRI 2009-006)

This study investigates the economic, ownership and governance determinants of executive compensation and CEO equity incentives in China’s listed firms. Consistent with the agency theory, we find that executive compensation is positively correlated with firm size, performance, and growth opportunities. CEO incentives are negatively associated with firm size, positively linked with firm performance and growth opportunity. Firm risk has a negative effect on pay and incentives. Compensation and CEO incentives are significantly greater in privately-controlled firms compared to state-run firms and are lower in firms with concentrated ownership structures. Boardroom governance is important: firms with compensation committees or a greater fraction of independent directors on the board have higher executive pay and greater CEO equity incentives

Succinct Representations of Dynamic Strings

The rank and select operations over a string of length n from an alphabet of size $\sigma$ have been used widely in the design of succinct data structures. In many applications, the string itself need be maintained dynamically, allowing characters of the string to be inserted and deleted. Under the word RAM model with word size $w=\Omega(\lg n)$, we design a succinct representation of dynamic strings using $nH_0 + o(n)\lg\sigma + O(w)$ bits to support rank, select, insert and delete in $O(\frac{\lg n}{\lg\lg n}(\frac{\lg \sigma}{\lg\lg n}+1))$ time. When the alphabet size is small, i.e. when \sigma = O(\polylog (n)), including the case in which the string is a bit vector, these operations are supported in $O(\frac{\lg n}{\lg\lg n})$ time. Our data structures are more efficient than previous results on the same problem, and we have applied them to improve results on the design and construction of space-efficient text indexes

Many-server queues with customer abandonment: numerical analysis of their diffusion models

We use multidimensional diffusion processes to approximate the dynamics of a queue served by many parallel servers. The queue is served in the first-in-first-out (FIFO) order and the customers waiting in queue may abandon the system without service. Two diffusion models are proposed in this paper. They differ in how the patience time distribution is built into them. The first diffusion model uses the patience time density at zero and the second one uses the entire patience time distribution. To analyze these diffusion models, we develop a numerical algorithm for computing the stationary distribution of such a diffusion process. A crucial part of the algorithm is to choose an appropriate reference density. Using a conjecture on the tail behavior of a limit queue length process, we propose a systematic approach to constructing a reference density. With the proposed reference density, the algorithm is shown to converge quickly in numerical experiments. These experiments also show that the diffusion models are good approximations for many-server queues, sometimes for queues with as few as twenty servers

Switching speed distribution of spin-torque-induced magnetic reversal

The switching probability of a single-domain ferromagnet under spin-current excitation is evaluated using the Fokker-Planck equation(FPE). In the case of uniaxial anisotropy, the FPE reduces to an ordinary differential equation in which the lowest eigenvalue $\lambda_1$ determines the slowest switching events. We have calculated $\lambda_1$ by using both analytical and numerical methods. It is found that the previous model based on thermally distributed initial magnetization states \cite{Sun1} can be accurately justified in some useful limiting conditions.Comment: The 10th Joint MMM/Intermag, HA-0