Managing the Managed Float in China

Despite the promising reform objectives announced on 21 July 2005, there remain much uncertainty and controversy surrounding China’s managed floating regime and its future. Hence, this research aims to provide a comprehensive analysis of the key issues raised over the course of the post-reform era. We begin by investigating whether the flexibility of RMB has increased following the reform announcement. A daily-based flexibility indicator is developed to more accurately detect the extent to which the Chinese currency is market-driven. This indicator is then utilized in a Markov switching model. The subsequent results suggest that the RMB flexibility has switched between two distinctive regimes, confirming that RMB flexibility did increase after the 2005 reform, while the so-called Fear of Floating was also apparent. Additionally, we discuss possible driving factors underlying the evolution of the RMB flexibility. Next, we consider another crucial aspect of the current managed floating regime, the equilibrium exchange rate level for RMB. The NATREX approach is selected, as we argue that it represents the most suitable solution for the purpose of our research. The empirical findings reveal not only the exogenous fundamental factors that have impacted the real exchange rate of RMB in the manner predicted by the NATREX model, but also evidence that the presumed portfolio channel did not work effectively for China in the sample period, which is contrary to the findings of previous studies. Looking ahead, we argue that the Reference Rate system could be a promising option for China. From the managerial aspect, we propose an optimal exchange rate management for China, which takes the presence of heterogeneous agents into consideration. We demonstrate that this strategy, once adopted, offers the optimal trade-off between the cost of intervention and the cost of no intervention

Drift control with changeover costs

Due to copyright restrictions, the access to the full text of this article is only available via subscription.We model the problem of managing capacity in a build-to-order environment as a Brownian drift control problem and seek a policy that minimizes the long-term average cost. We assume the controller can, at some cost, shift the processing rate among a finite set of alternatives, for example by adding or removing staff, increasing or reducing the number of shifts, or opening or closing production lines. The controller incurs a cost for capacity per unit time and a delay cost that reflects the opportunity cost of revenue waiting to be recognized or the customer service impacts of delaying delivery of orders. Furthermore, he incurs a cost per unit to reject orders or idle resources as necessary to keep the workload of waiting orders within a prescribed range. We introduce a practical restriction on this problem, called the S-restricted Brownian control problem, and show how to model it via a structured linear program. We demonstrate that an optimal solution to the S-restricted problem can be found among a special class of policies called deterministic nonoverlapping control band policies. These results exploit apparently new relationships between complementary dual solutions and relative value functions that allow us to obtain a lower bound on the average cost of any nonanticipating policy for the problem, even without the S restriction. Under mild assumptions on the cost parameters, we show that our linear programming approach is asymptotically optimal for the unrestricted Brownian control problem in the sense that by appropriately selecting the S-restricted problem, we can ensure its solution is within an arbitrary finite tolerance of a lower bound on the average cost of any nonanticipating policy for the unrestricted Brownian control problem