空间目标的联合矩阵束极点估计

极点作为谐振区雷达目标的最主要电磁特性，具有很大的空间目标识别前景。但是在使用频域观测数据提取目标极点时，存在虚假极点和估计精度问题。针对上述问题，首先通过加窗和截断改进了后时响应信号的获取流程，抑制了虚假极点影响；然后采用最小描述长度法（MDL）估计极点个数，避免了定阶错误引起的虚假极点；最后采用联合矩阵束法估计极点，有效减少了单角度数据估计极点时存在的遗漏极点和虚假极点问题。FEKO软件验证表明，所提算法具有更高的精度和抗噪能力。     

The Great Recession,Austerity and Inequality: Lessons from Ireland

The advent of the Great Recession and the widespread adoption of fiscal austerity policies have heightened concern about inequality and its effects. We examine how the distribution of income in Ireland—a country which experienced one of the most severe economic contractions—has evolved over the years 2008 to 2013. Standard cross‐sectional analysis of the income distribution shows broad stability in the Gini coefficient and in decile shares, with one main exception: the share of the bottom decile fell sharply, with the largest fall in average incomes being for that group. Longitudinal analysis shows that the falls in the average income for the bottom decile were not due to decreasing income for those remaining in the bottom decile, but to falls in income from those initially located in higher deciles. The extent of redistribution through taxes and transfers increased strongly, as measured by the Reynolds‐Smolensky index, which rose from 0.20 before the onset of the crisis to 0.27 in 2013. Analysis indicates that about three‐quarters of this increased redistribution is due to automatic stabilisers and one‐quarter to discretionary policy changes.     

Forecast of realized covariance matrix based on asymptotic distribution of the LU decomposition with an application for balancing minimum variance portfolio

We derive the asymptotic distribution for the LU decomposition, that is, the Cholesky decomposition, of realized covariance matrix. Distributional properties are combined with an existing generalized heterogeneous autoregressive (GHAR) method for forecasting realized covariance matrix, which will be referred to as a generalized HARQ (GHARQ) method. An out-of-sample forecast comparison of a real data set shows that the proposed GHARQ method outperforms other existing methods in terms of optimizing the variances of portfolios.     

Structural transformation in emerging economies: leading sectors and the balanced growth hypothesis

The paper uses the World Input-Output Database to address patterns of structural transformation in BRIC countries, Indonesia, South Korea, Mexico and Turkey. Sectoral drivers of aggregate labour productivity growth, and the relative importance of within-sector versus employment reallocation effects on aggregate labour productivity growth, are evaluated using growth accounting decomposition methods. Decomposition results are used to assess how patterns of structural transformation relate to macroeconomic performance in terms of aggregate labour productivity, output and employment growth. Together with the construction of ‘Hirschman compliance indices’, decomposition results are also used to shed light on the balanced versus unbalanced growth debates. The paper goes on to assess the extent of complementarities between manufacturing and information and communications technology-intensive advanced services through intermediate inputs, comparing the eight emerging countries with G7 countries over time.     

一种SAR与可见光图像压缩感知融合增强方法

针对机载多传感器成像战场态势感知的问题，提出了一种合成孔径雷达(Synthetic Aperture Radar，SAR)与可见光图像压缩感知融合增强方法。该方法首先对SAR与可见光图像分别进行压缩感知测量，得到压缩测量值，然后通过基于局部权值的融合方法实现对压缩测量值的融合，再利用有序度最优分割法提取SAR图像的强散射目标，最后对融合测量值重建得到初步融合图像，初步融合图像通过目标对比度增强得到最终融合图像。对多组图像进行了仿真分析，视觉及数值结果表明该方法能显著增强融合图像的目标对比度，提升了图像纹理清晰度，较大程度降低了图像融合过程中的数据计算量。     

决策可靠性分析及在SAR图像目标识别中的应用

决策融合是提高合成孔径雷达（Synthetic Aperture Radar,SAR）目标识别性能的重要手段，然而，可靠性较弱的决策往往会导致最终决策融合的效果变差。将可靠性分析引入基于决策融合的SAR目标识别方法中，分别计算各个决策的可靠性系数并选取可靠性的决策参与最终的决策融合。为了验证方法的有效性，分别将提出的可靠性分析应用于多特征决策融合以及多分类器决策融合并基于MSTAR（Moving and Stationary Target Acquisition and Recognition）数据集进行了目标识别实验。在基于主成分分析、线性鉴别分析和非负矩阵分解三种特征进行多特征决策融合的条件下，所提方法和直接进行决策融合的方法的识别率分别为97.47%和96.50%。在基于K近邻、支持向量机和稀疏表示分类器的多分类器决策融合中，所提方法和直接进行决策融合的方法的识别率分别为97.10%和96.28%。实验结果充分证明了所提方法的有效性。     

Sources of Productivity Growth Dynamics: Is Japan Suffering From Baumol's Growth Disease?

This study examines the sources of labor productivity growth dynamics in Japan (1970–2010) and investigates the extent to which Japanese economic performance has been affected by Baumol's growth disease (BGD). We find that BGD silently undermines Japanese economic growth. However, the magnitude is miniscule, and consequently the aggregate labor productivity growth rate has not been decreasing monotonically. We also explore how BGD is arising and why it is small in the Japanese economy. BGD is weak because (1) the positive Baumol growth effect is also working in certain services sectors and (2) BGD is not a durable phenomenon: even if a sector begins to suffer from BGD, it is likely to recover quickly.     

Gender wage gaps and economic crisis in Greece

ABSTRACT

We examine gender wage gap (GWG) in Greece for 2013, by using a survey data set. Our findings show first, that the unadjusted GWG is 15.3%, while European Commission reports a value of 15%. Secondly, we derive the ‘adjusted’ GWG, using the Oaxaca and Ransom (OR) and the Juhn, Murphy and Pierce (JMP) methods to be ranging from 10% to 13.6%. Thirdly, looking into the behaviour of the full population, we find a decreasing trend for the discrimination effects, an increasing trend for the residuals effects and a ‘random’ endowments effects while moving to higher deciles. These three effects are associated to the economic crisis 2008–2015. Fourthly, our findings do not show evidence of either a ‘glass ceiling’ effect or a ‘sticky floor’ effect. Finally, that there is strong evidence that investing in higher education reduces the wage discrimination between sexes.     

Informal Employment and the Structure of Wages in India: A Review of Trends

The “alternative”, “atypical” or “informal” workforce has grown in developed and developing countries alike. One of the more recent evolutions of informal employment has been of informal employment within formal enterprises. In the interest of flexibility and cost‐reduction, many formal firms increasingly resort to hiring workers on a temporary or informal basis. Alongside, and perhaps, as a result of the persistence and pervasiveness of informal employment, issues relating to inequality have come to the fore. This paper is motivated by these two intertwining aspects of Indian labor market—informality and wage inequality. Using nationally representative sample data, the paper examines trends in wage inequality among various forms of informal workers, overlaying these findings with broader trends in inequality. Using a regression based inequality decomposition, the paper compares the sources of wage inequality across different employment groups and the reasons for differences in wage inequality.     

What do professional forecasters actually predict?

This paper studies what professional forecasters predict. We use spectral analysis and state space modeling to decompose economic time series into trend, business cycle, and irregular components. We examine which components are captured by professional forecasters by regressing their forecasts on the estimated components extracted from both the spectral analysis and the state space model. For both decomposition methods, we find that, in the short run, the Survey of Professional Forecasters can predict almost all of the variation in the time series due to the trend and the business cycle, but that the forecasts contain little or no significant information about the variation in the irregular component.