Perseverance and suspense in tug-of-war

We study a tug-of-war game between two players using the lottery contest success function (CSF) and a quadratic cost (of effort) function. We construct a pure strategy symmetric Markov perfect equilibrium of this game, show that it is unique, and provide closed-form solutions for equilibrium strategies and values. In stark contrast to a model of tug-of-war with an all-pay auction CSF, players exert positive efforts until the very last battle in this equilibrium. We deliver a set of empirically appealing results on effort dynamics.     

跨国并购执行阶段财务风险研究

改革开放以来,中国经济持续高速增长,国内市场逐步开放,国家对“一带一路”的推进也使越来越多的企业试图通过海外并购的方式扩大其国际市场份额,以此提高企业竞争力。但即便有国家政策的支持,想要完成海外并购依旧是困难重重,因此,系统分析所存在的财务风险并加以控制变成重中之重。论文对跨国并购现状进行概述,随后重点分析在执行阶段所存在的几点财务风险,并提出相应的防范建议。     

土壤污染防治法背景下的城乡绿地系统建设：趋势与对策

《中华人民共和国土壤污染防治法》的颁布标志着中国将形成完善的土壤污染防治法律体系，建立从污染土壤调查、修复、风险防控、监测到场地再利用，从环境标准到规划管理的全方位制度。生态文明制度建设的宏观背景，再加上中国土壤污染严重、规模大、修复难、成本高、周期长等特征，将导致大量污染场地转变为绿地或生态用地，最终对绿地系统的数量与规模、布局与功能、规划与管理、环境质量标准等多个维度产生实质性影响。分析这一趋势，对其影响提出预判，最终提出对策建议。     

Debt Overhang and Deleveraging in the US Household Sector: Gauging the Impact on Consumption

Using a novel data set for the U.S. states, this paper examines whether household debt and the protracted debt deleveraging help explain the dismal performance of U.S. consumption since 2007 in the aftermath of the housing bubble. By separating the concepts of deleveraging and debt overhang—a flow and a stock effect—we find that excessive indebtedness exerted a meaningful drag on consumption over and beyond wealth and income effects. The overall effect, however, is modest—‐around one sixth of the slowdown in consumption between 2000–06 and 2007–12—and mostly driven by states with particularly large imbalances in their household sector. This might be indicative of non‐linearities, whereby indebtedness begins to bite only when misalignments from sustainable debt dynamics become excessive.     

Predictive regressions under asymmetric loss: Factor augmentation and model selection

This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly.     

一种级联两箱通用数字预失真器及其辨识算法

提出了一种由单形规范线性分段(SCPWL)函数与记忆多项式级联的数字预失真器，并给出了复数域两步最小二乘参数辨识算法。不同于以往一种预失真器适用一种功放模型的情况，所提的预失真算法利用SCPWL函数的分段特性以及记忆多项式的非线性记忆特性，在完成参数辨识的同时自动地调整结构，可适用于传统以及强非线性新型功放模型的线性化补偿。将所提预失真器分别应用于传统记忆多项式、两箱模型以及新型包络跟踪功放。经过计算机仿真，功放输出的幅频特性和频谱曲线表明所提预失真器能够有效地补偿多种功放的非线性特性。算法仿真比较结果也表明，针对包络跟踪功放，所提复数两步最小二乘算法的邻道泄漏比(ACLR)可改善约35 dB，性能优于最小均方(LMS)类算法约30 dB。     

Re-testing Prebisch–Singer hypothesis: new evidence using Fourier quantile unit root test

The Prebisch–Singer hypothesis in economics asserts that over time the relative price of primary goods relative to manufactured goods should experience a downward trend. To test the hypothesis, we must first establish the unit root properties of the relative price term and then regress the stationary series on a trend term. We use the quantile unit root test which allows for both smooth unknown numbers and the form of breaks in the trend function through a Fourier function to show that the relative price of 23 out of 24 primary goods is stationary. However, the Prebisch–Singer hypothesis is supported only in half of the primary commodities.     

How justified is abandoning money in the conduct of monetary policy in Australia on the grounds of instability in the money‐demand function?

The role of money in the design and conduct of monetary policy has reemerged as an important issue in both advanced and developing economies, especially since the 2007 global financial crisis. A growing body of recent literature suggests that the causal relationship between money supply growth and inflation remains intact across countries and over time and that this relation is not conditional on the stability of the money‐demand function or whether money is endogenous or exogenous. Moreover, critical for a rule‐based monetary policy is the presence of a long‐run stable money‐demand function, rather than a short‐run money‐demand model that may exhibit instability for many reasons, including problems with estimating a money‐demand model with high‐frequency data. Provided that a stable money‐demand function exists, it could be useful to establish long‐run equilibrium relations among money, output, prices, and exchange rates, as the classical monetary theory suggests. Within this analytical framework, this paper addresses the question of whether money has any role in the conduct of monetary policy in Australia. The conventional wisdom is that the money‐demand function in Australia has been unstable since the mid‐1980s due to financial deregulation and reforms; this led to a change in the strategy of monetary policy for price stability in the form of inflation targeting that ignores money insofar as inflation and its control are concerned. This paper reports empirical findings for Australia, obtained from a longer quarterly data series over the period 1960Q1–2015Q1, which suggest that instability in the narrow‐money‐demand function in Australia was primarily due to the exclusion of variables which have become important in the deregulated environment since the 1980s. These findings are confirmed by an expanded form of the narrow‐money‐demand function that was found stable over the past two decades, although it experienced multiple structural breaks over the study period. The paper draws the conclusion that abandoning the monetary aggregate as an instrument of monetary policy in Australia, under a rule‐based monetary policy such as inflation targeting, cannot be justified by instability in the money‐demand function or even by lack of a causal link between money supply growth and inflation.     

中国基本养老保险最优财政支出规模测算——基于柯布-道格拉斯生产函数的一项研究

以内生增长理论为基础，运用巴罗的财政支出自然效率条件和改进的柯布-道格拉斯生产函数分别对中国城镇职工基本养老保险和城乡居民基本养老保险的最优财政支出规模进行测算，发现中国城镇职工基本养老保险和城乡居民基本养老保险的最优财政支出规模分别为2.33%和0.81%，目前两项养老保险的财政支出皆已超过了最优财政支出规模。为缓解养老保险的财政补贴压力，保证养老保险制度的良性运行，建议落实划转国有资本充实全国社会保障基金政策，实施基础养老金全国统筹，激发城镇职工和城乡居民缴费的积极性。     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.