一种采用刀切法的单通道信源数估计算法

针对现有信源数估计算法不能直接用于单通道接收模型且抑噪能力较差的问题，提出了一种采用刀切法的单通道信源数估计算法。该算法首先通过间隔抽样实现了单通道接收信号多维数的转换，得到矢量化空间；然后采用刀切法将此组空间重构多个协方差矩阵，经酉变换后结果取平均；最后通过循环迭代得到最优信源数。理论分析和仿真结果表明，该算法在白、色噪声环境下能有效抑制噪声，且在低信噪比及采样点较少时能更准确估计信源数，相较于传统的估计算法，显著提高了检测性能。     

Does the early bird catch the worm? The effect of school starting age on educational attainment and labor market outcomes: Evidence from Chinese urban twins data

This paper estimates the effects of school starting age (SSA) on educational attainment and labor market outcomes by using unique urban adult twins data from China. Ordinary least squares (OLS) estimates indicate that late enrollment in primary school lowers years of education, earnings, wage rate, and probability of employment. However, when we use the within-monozygotic (MZ)-twin fixed effects method to exclude unobservable endowments and family factors, the effects of SSA on years of education become less negative. For earnings, wage rate, and the probability of employment, the within-twin fixed effects estimates become insignificant. The results indicate that a one-year delay in primary school starting age lowers schooling by 0.51 years but does not affect earnings, wage rate, or probability of employment. The difference between OLS and within-MZ-twin fixed effects estimates indicates that the negative return to SSA is due to unobservable family variables and omitted individual-specific endowments. We further find that the earlier primary school starters fail to obtain a level of education with high return. Specifically, early birds do not have a high probability of getting a vocational school degree or above.     

中国农业全要素生产率的动态演进及其影响因素分析

[目的]通过测算中国农业全要素生产率,揭示其动态演进趋势及影响因素,从而为推动我国农业供给侧结构性改革,实现农业现代化提供科学的决策依据。[方法]文章使用SBM-Global Malmqusit生产率指数法测算了中国农业全要素生产率,在此基础上利用Kernel核密度估计方法刻画了中国农业TFP增长的动态演进,并通过建立面板数据模型对影响中国农业TFP增长的诸多因素进行了分析。[结果]中国农业全要素生产率增长的主要源泉是技术进步,而技术效率的下降是阻碍其增长的主要原因;核密度估计表明各省份之间的农业相对全要素生产率水平差距不断扩大,技术效率普遍恶化,而技术进步增长速度显著;农业金融发展水平、工业化水平、农业科技水平对中国农业TFP都产生了显著的促进作用,而农业产业结构调整、对外开放水平对中国农业TFP则产生了阻碍作用,农村人力资本则对农业TFP产生的正效应不显著。[结论]提高农业全要素生产率,实现农业现代化.各省份应加强农业科技创新,深化农业科技体制改革,完善农村金融服务体系,推动工业化和农业现代化深度融合,培育新型职业农民等措施。     

一种新的基于压缩感知的毫米波信道估计算法

针对传统稀疏重构算法需要信道稀疏度先验信息、复杂度高、不利于实际应用的问题，提出了一种新的基于波束空间分解的稀疏度自适应毫米波信道估计算法。该算法利用毫米波信道稀疏性的特点对信道进行波束空间分解，构造基于码本的感知矩阵，获得l1范数约束问题模型；其次结合分段弱匹配追踪算法，采用弱阈值从感知矩阵筛选原子，再通过分组选择机制对选择的原子进行二次优化；最后根据最小二乘法估计出毫米波信道。仿真结果表明，所提算法的估计精度和复杂度在低信噪比和低训练长度情况下明显优于传统匹配追踪算法。     

基于SBE分析法对滨水植物景观的量化 研究——以南京滨水公园为例

滨河植物群落是城市生态景观系统的一个重要组成 部分，提高其绿化效果对城市居民的生活品质与城市的景观 建设都有着积极而广泛的影响。基于SBE景观美景度分析法 (Scenic Beauty Estimation，简称SBE分析法)，对南京 市10个滨水公园内的40个样地的植物景观进行了实地调研。 调研收集的信息被制作成问卷调查表，信息通过计算被转化 为滨河园林植物群落景观的SBE值。计算结果显示，SBE值 最高的20块优秀样地得分由高到低是：B4、J3、B2、I4、 B1、I3、D1、J2、J1、C4、G4、B3、D4、A1、D3、 A2、D2、H1、E1、H4。通过对这20块优秀样地的图片进 行景观要素的分解和量化，又进一步建立了南京滨河植物群落 景观美景度评价模型：SBE=85.658＋35.895×色彩和谐＋ 71.750×尺度适宜－47.432×节奏韵律－32.782×宿根 花卉数量＋35.146×宿根花卉－30.842×乔木背景面积。 成功运用SBE法对滨水植物配置进行了量化分解研究，为城市 滨水植物景观的研究提供新的思路。     

Date-stamping multiple bubble regimes

Identifying the start and end dates of explosive bubble regimes has become a prominent issue in the econometric literature. Recent research has demonstrated the advantage of a model-based minimum sum of squared residuals estimator, combined with Bayesian Information Criterion model selection, over recursive unit root testing methods in providing accurate date estimates for a single explosive regime. However, in the context of multiple bubbles, a large number of models are possible, making such a model-based method unappealing. In this paper, we propose a two-step procedure for dating multiple explosive regimes. First, recursive unit root tests are used to identify a ‘date window’ in which an explosive episode starts and ends. Second, a model-based BIC approach is used to precisely estimate the regime change points within each date window. In addition, our method allows us to distinguish between different types of explosive episode, such as whether or not each explosive regime crashes before reverting back to a unit root process, and date any crash regimes. Monte Carlo simulations highlight the effectiveness of our procedure when compared to existing methods of dating. The value of the new methodology is also demonstrated through an empirical application to housing markets.     

Continuous chain-ladder with paid data

We introduce a continuous-time framework for the prediction of outstanding liabilities, in which chain-ladder development factors arise as a histogram estimator of a cost-weighted hazard function running in reversed development time. We use this formulation to show that under our assumptions on the individual data chain-ladder is consistent. Consistency is understood in the sense that both the number of observed claims grows to infinity and the level of aggregation tends to zero. We propose alternatives to chain-ladder development factors by replacing the histogram estimator with kernel smoothers and by estimating a cost-weighted density instead of a cost-weighted hazard. Finally, we provide a real-data example and a simulation study confirming the strengths of the proposed alternatives.     

Are GDP forecasts optimal? Evidence on European countries

We assess the accuracy of real GDP growth forecasts released by governments and international organizations for European countries in the years 1999–2017. We implement three testing procedures characterized by different assumptions on the forecasters’ loss functions. First, we test forecast rationality within the traditional approach based on a quadratic loss function (Mincer and Zarnowitz, 1969). Second, following Elliott, Timmermann and Komunjer (2005), we test rationality by allowing for a flexible loss function where the shape parameter driving the extent of asymmetry is unknown and estimated from the empirical distribution of forecast errors. Lastly, we implement the tests proposed by Patton and Timmermann (2007a) that hold regardless of the functional form of the loss function. We conclude that governmental forecasts are biased and not rational under a symmetric and quadratic loss function, but they are optimal under more general assumptions on the loss function. We also find that the preferences of forecasters change with the forecasting horizon: when moving from one- to two-year-ahead forecasts, the optimistic bias increases and the parameter of asymmetry in the loss function significantly increases.     

A Race for Long Horizon Bankruptcy Prediction

ABSTRACT

This study compares the accuracy and efficiency of five different estimation methods for predicting financial distress of small and medium-sized enterprises. We apply different methods for a large set of financial and non-financial variables, using filter and wrapper selection, to predict bankruptcy up to 10 years before the event in an open, European economy. Our findings show that logistic regression and neural networks are superior to other approaches. We document how the cost-return ratio considerably affects the location of optimal cut-off points and attainable profit in credit decisions. Once a loan provider selects a particular prediction model, an effort should be made to find the optimal cut-off score to maximize the efficiency of the technique. Indeed, this often involves determining several cut-off levels where the portfolio of products and services exhibits different cost-return characteristics.     

The double trap: Institutions and economic development

The empirical growth literature has established that institutional quality is a deep determinant of economic growth. We examine whether institutional quality in low income countries converges to the level witnessed in high income countries, or whether they are trapped in convergence clubs that stagnate or even deteriorate over time. Using the log-t-test suggested by Phillips and Sul (2007), we find evidence of multiple equilibria in institutional quality, with several countries stuck in poor quality institutions traps. We further find that per capita incomes of some of the developing countries are also stuck in low-level traps. Finally, using bivariate probit estimations, we establish that poor institutional traps are major determinants of low income traps. These results indicate that these countries are caught in a double trap where their incomes are stuck in low-level traps from which it is difficult to escape, because the institutions that enable growth are also stuck in low-quality traps.