Estimation of the mean in ranked set sampling with non responses

The estimation of the population mean when ranked set sampling [rss] is used for selecting the sample and non responses [nr] are present, is studied. The nr stratum is sub sampled using simple random sampling with replacement. Two strategies are analyzed. One of them is based on the selection of a sub sample from the nr in each cycle. The other uses sub samples selected among the nr in each rank.  The accuracy of the proposed estimators is characterized by the corresponding expected variances. Simulations and real life data are used for analyzing the behavior of them. Acknowledgements: This paper was developed partially during the visit of the author to Université des Antilles et Gouyane. The author gratefully acknowledges the helpful suggestions of the referees and thanks the support of DAAD for visiting Humboldt University where a version of the paper version was made.     

Open economy and financial burden of corruption: theory and application to Asia

We discuss why corruption remains high and show that corruption contributes to the Banking distress and to the rapid transmission across international stock and currency markets. Undeveloped ‘derivative securities’ markets make the risk from stress-induced volatility difficult to manage. Vinod’s (1999) closed economy model is extended to indicate the asymmetry of ‘home bias’ and the effect of corruption on the value at risk (VaR). Our theory predicts that capital flight controls will be many, foreign direct investment (FDI) will be low and cost of capital will be high in corrupt developing countries, which is supported by Asian data. We include some policy recommendations regarding financial institutions and markets.     

Finding Pareto Optimal Insurance Contracts

This paper deals with on-line computation—or step-wise learning—of Pareto optimal insurance contracts. Our approach tolerates that the loss distribution might be unknown, intractable, or not well specified. Thus we accommodate fairly inexperienced parties. Losses are here simulated or observed, one at a time, and they cause iterated revisions of the premium. The mechanical and global nature of probability calculus thereby yields to more tentative, myopic procedures, possibly closer to how humans operate or reason in face of risk. Sequential revisions may also reduce the expense of insurers' time and money in seeking sufficient statistics. Emphasized below is the remarkable simplicity and stability of the resulting adaptive procedures. Special attention goes to catastrophic risks, and to subsidized or competitive insurance.     

Stop and Go Agricultural Policies with a Land Market

This article studies the design of farm policy in the presence of asymmetric information about farmers' productivity, a government objective to insure farmers a minimum "parity" income, an endogenous land rent, and diminishing returns on alternative (nonprogram crop) land uses. In this setting, acreage set asides are never part of an optimal farm policy, although compensated acreage limits are. When there are new farmer entrants who cannot be excluded from farm programs, optimal policy takes the form of a pure voluntary acreage limitation—or "buyout"—program in which high-cost producers participate and low-cost producers do not.     

基于集对分析法的地区大中型工业企业自主创新能力评价

为了对地区大中型工业企业自主创新能力进行全面、科学的评价,基于集对分析法,提出了地区大中型工业企业自主创新能力评价指标体系及综合评价模型。通过对我国30个省市区大中型工业企业的实证分析,表明该方法科学简便,具有很好的实用价值。     

我国城市规模分布Pareto指数测算及影响因素分析

本文用OLS方法测算我国各省、三大区域以及全国的城市人口规模分布和经济规模分布Pareto指数(1997年、2000年和2003年),对Pareto指数进行跨区域和跨时间的对比分析,并实证分析我国城市规模分布的影响因素。分析表明,我国的城市规模分布显著地服从Pareto分布,并具有明显的结构性特征。工业化、产业结构以及运输能力对城市人口规模分布具有显著影响,而工业化和运输能力则是影响城市经济规模分布的重要因素。     

从公共产品的私人供给看税收的自愿缴纳

据公共产品的私人供给与税收的自愿缴纳问题 ,提出完全信息下的税收方案 ,具有税收管理成本最低 ,逃税的超额负担得以消除的特点。如采用该税收方案作为常规税收制度的补充 ,可以达到帕累托改进的效果。     

区域旅游协作的帕累托分析

加强区域旅游协作，实现优势互补，谋求共同发展，已经成为了我国旅游界的共识。本文借鉴西方福利经济学的理论，探讨了区域旅游协作过程中实现旅游产业效益帕累托最优、旅游者效用帕累托最优以及两者联合最优的条件。     

休闲位置消费的经济分析及对策研究

争名与逐利一样都是人的经济本性,因而位置消费现象在休闲消费领域也同样存在。运用经济学的相关理论对休闲消费中的位置消费行为进行分析发现:该行为既无法使休闲消费资源达到帕累托最优状态,也不能使人们从休闲消费中获得最大效用,且个人休闲位置消费的理性选择还会导致集体消费的非理性结果。因此,政府应加强引导,采取有效措施降低位置消费的负面影响,促进休闲经济健康发展。     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.