东部地区十省市规模以上工业企业研发投入绩效评价

选取2021年度数据，采用数据包络分析（DEA）方法对中国东部地区10个省份规模以上工业企业的研发投入绩效进行评价，并采用灰关联分析方法分析确定各项研发投入产出指标相对于DEA效率的灰色关联度。研究结果表明，80%的省份规上工业企业研发投入产出处于非DEA有效状态，存在不同程度的投入冗余或产出不足；规上工业企业发明专利申请数与研发投入产出效率的关联度最高，其次是新产品销售收入和R&D经费内部支出。     

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.     

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.     

How to fight against southern pine beetle epidemics: An insurance approach

The southern pine beetle (SPB) is among the leading biological agents killing southern pine species in the eastern United States. In light of recognized spatiotemporal autocorrelation in SPB outbreaks, we devise a spatiotemporal block bootstrapping method that can be applied to analyze spatiotemporally dependent infestations. We also identify the relevant risk determinants and evaluate their impacts on the frequency of SPB outbreaks. For example, we find forest type, climate, and natural disasters like storm and forest management are all significantly associated with SPB risks. Using the results of a statistical model, we design a county-level group index insurance plan that generates estimates of actuarially fair premium rates for timber stands containing southern pine species. Given that no government-provided compensation scheme for SPB epidemics currently exists, application of this new insurance product could reduce forest owners losses. Our study offers an approach to analyzing and protecting against risks of other destructive pests affecting the timber sector.     

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。     

Capital market integration in ASEAN: A non-stationary panel data analysis

Motivated by the establishment of ASEAN Economic Community (AEC) at the end of 2015, we examine saving-investment relationship in various subgroups of ASEAN to assess their capital market integration. The results from second generation panel unit-root and cointegration tests that account for cross-sectional dependence as well as estimates of long-run saving-retention rate provide some evidence of market integration in ASEAN. The analysis of short-run dynamics suggests that capital mobility in ASEAN during 1980–2014 appears similar to that in OECD countries during 1970–1999. More importantly, across different panel estimators and subgroups of membership, there is considerable heterogeneity among the member countries. The saving-investment association is very weak, thereby implying very high capital mobility, in more developed members such as Singapore, Malaysia, and Brunei; the association is very strong, implying very low capital mobility, for much less developed members such as Laos, Myanmar, and Cambodia. The results call for renewed effort to develop capital markets in less developed nations and integrate them with the rest of the membership in ASEAN. In this paper, we also address several major shortcomings of the original Feldstein-Horioka framework.     

生态旅游视域下的岷江上游贫困山区生态安全评价

[目的]构建科学合理的评价指标体系,准确评价生态旅游影响下的区域生态安全状况,是推动少数民族山区实现旅游资源环境与区域社会、经济协同发展的前提和基础。[方法]以岷江上游贫困山区为例,应用灰色系统理论与熵值赋权法相结合,基于压力—状态—响应模型,构建生态旅游视域下的区域生态安全评估指标体系,并将评估指数与经济收入状况及贫困人口分布进行空间耦合。[结果](1)区域当前处于较安全水平,生态旅游开发适度;(2)综合评估指数与城镇居民可支配收入增长率、旅游收入对国民经济增长的贡献率呈正相关,且城镇居民在旅游开发中受益与机会较农牧民多;(3)综合评估指数与贫困人口比重呈负相关,与农牧民纯收入增长率没有必然联系。[结论]区域脱贫能够改善当地的生态安全状况,适度生态旅游开发是区域脱贫的有效手段,但应注重扶持农牧民在旅游业中的参与度,增加其旅游收益。     

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.     

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.