城镇就业市场上劳动力工资扭曲程度测度

本文利用CHIPS2007数据库，基于随机前沿模型对我国城镇就业市场上劳动力的工资扭曲程度进行测度。研究结果表明：（1）在城镇就业市场上，由于工资扭曲现象的存在，劳动力实际获得的工资要比他们的边际生产率低45％～60％；（2）已婚、子女个数较少、本地、拥有失业保险、男性、大中型企业的劳动力工资扭曲程度要低于未婚、子女个数较多、外来、没有失业保险、女性、小型企业的劳动力；（3）中低工资水平的劳动力工资扭曲程度要比高工资水平的劳动力严重，且中低工资水平劳动力工资扭曲程度的方差更大。由此，本文提出推进就业市场的市场化改革，完善就业市场信息网络，从而减轻劳动力工资扭曲程度。     

The nexus between competition and efficiency: The European banking industries experience

In this paper, we investigate competition in banking systems in the EU27 as a whole for the period 2004–2010, but also for old members’ banking systems compared with new members’ banking systems and for banking systems from countries member of euro zone compares with banking systems from countries non-member of euro zone. In order to investigate this issue, we estimate a non-structural indicator of banking competition, using the H-statistic indicator that is estimated using bank-level data. Also, we apply two tests of convergence, β- and σ-convergence, for assessing competition evolution during the specified period. We want to fill the gap in the banking literature testing the validity of the Competition–Efficiency Hypothesis, analysing the impact of the banking competition measures on two alternative measures of efficiency, cost and profit efficiency, in the European banking systems in a Granger-causality manner. The results confirm us that in the EU the convergence process occur from the banking systems with higher competition level than the mean score of all countries. The evidence for all groups of countries, except non-euro zone group, where results are not statistically significant, confirm the Competition–Efficiency Hypothesis in terms of cost and profit efficiency.     

Structured deplaning via simulation and optimization

Deplaning naturally occurs row by row down the length of an aircraft. Using simulation and optimization, we design deplaning strategies (e.g., deplane by group and/or column) that significantly reduce the overall unstructured deplaning time. The evaluations derived from a combination of optimization and simulation were tested across several equipment types using data gathered through field observations for calibration.     

An options pricing approach to ramping rate restrictions at hydro power plants

This paper investigates the impact of ramping rate restrictions imposed on hydro operations to protect aquatic ecosystems. The optimal ramping decision is specified as an optimal control problem which results in a Hamilton Jacobi Bellman (HJB) equation. Electricity prices are modelled as a regime switching stochastic process. The optimal control is determined by solving the HJB equation numerically using a fully implicit finite difference approach with semi-Lagrangian time stepping. The paper focuses on the effect of ramping restrictions on a hydro plant׳s value and optimal operations, and provides an analysis of which factors cause ramping restrictions to have a greater or lesser impact on profitability. It is shown that hydro plant value is negatively affected by ramping restrictions, but the extent of the impact depends on key parameters which determine the desirability of frequent changes in water release rates. Interestingly for the case considered, value is not sensitive to ramping restrictions over a large range of restrictions. The results point to the importance of accurately modelling electricity prices in gauging the trade offs involved in imposing restrictions on hydro operators which may hinder their ability to respond to volatile electricity prices and meet peak demands.     

Stochastic costly state verification and dynamic contracts

I consider a dynamic costly state verification environment in which a risk-averse agent enters into a contract with a risk-neutral principal. The agent has random income which is unknown to the principal but can be verified at a cost. The principal can commit to executing random verifications.I extend the standard recursive methods to study the problem and show that it is optimal to set verification probabilities strictly less than 1. If the agent׳s absolute risk aversion declines sufficiently slowly, the principal will use verification regardless of its cost. If the agent's income is verified then he would get consumption and continuation utility strictly higher than if his income were not verified.     

Valuation of forward start options under affine jump-diffusion models

Under the general affine jump-diffusion framework of Duffie et al. [Econometrica, 2000, 68, 1343–1376], this paper proposes an alternative pricing methodology for European-style forward start options that does not require any parallel optimization routine to ensure square integrability. Therefore, the proposed methodology is shown to possess a better accuracy–efficiency trade-off than the usual and more general approach initiated by Hong [Forward Smile and Derivative Pricing. Working paper, UBS, 2004] that is based on the knowledge of the forward characteristic function. Explicit pricing solutions are also offered under the nested jump-diffusion setting proposed by Bakshi et al. [J. Finance, 1997, 52, 2003–2049], which accommodates stochastic volatility and stochastic interest rates, and different integration schemes are numerically tested.     

Effects of carbon emission reduction policies on transportation mode selections with stochastic demand

We are witnessing more frequent extreme weather events due to the global warming. There is an urgent need for governments, industries, general public, and academics to take coordinated actions in order to tackle the challenges imposed by the climate change. It is essential to incorporate the environmental objective in the transportation mode selection problem as transportation is a main contributor to carbon emissions. With this in mind, our paper studies the retailer’s ordering and transportation mode selection problem using stochastic customer demand and investigates the optimal ordering and transportation mode selection decisions under different carbon emission reduction policies. Our analytical results reveal that there are some important transportation mode shifting thresholds under different carbon emissions reduction policies. These findings do not only help firms to make optimal decisions under different carbon emission reduction policies but also support policy makers to develop effective policies on carbon emissions reduction.     

Stochastic optimization for investment in facilities in emergency prevention

A coordinated approach is developed to integrate three preventive measures (i.e. building reinforcement, reinforcement of road networks, and facility location of relief supplies), with the objectives of minimizing budgets and risk-induced penalties. The Conditional Value-at-Risk is employed as a decision-making tool to evaluate diverse decisions of prevention based on the degree of risk aversion. Based on a real-world case of an earthquake, a series of scenarios were designed, and the applicability of the proposed model was studied. The coordinated approach for investing preventive measures is cost-efficient in helping reduce the impact of disaster on society.     

Stochastic seat allocation models for passenger rail transportation under customer choice

We study the seat allocation problem for passenger rail revenue management, in which a rail operator attempts to determine the optimal quantity of seats to be allocated to each cabin class for each train service. We formulate the problem with single-stage and multi-stage decisions as two stochastic programming models that incorporate passengers’ choice behavior. We transform the stochastic models into equivalent deterministic mathematical programs that are easy to solve. Then, we form a variety of seat allocation polices from the optimal solutions to the seat allocation models. A number of simulation tests are offered to test the policies.     

Asset prices in affine real business cycle models

I describe a tractable way to study macroeconomic quantities and asset prices in a large class of dynamic stochastic general equilibrium models. The proposed approximate solution is analytical, log-linear, and adjusted for risk. Therefore, it is well suited to investigate economic mechanisms, describe the time series properties or estimate the model, and deal with stochastic volatility. I explain the pitfalls encountered by previous attempts to use simple approximation techniques, in particular with models featuring recursive preferences. Finally, I show the theoretical relationship between my solution and higher-order perturbation methods.