中国城镇正规就业与非正规就业的工资差异演变研究——基于非条件分位数回归的分解方法

基于CHNS历次调查的数据资料,利用非条件分位数回归与分解方法,实证研究1989-2011年三个时期中国城镇正规就业与非正规就业的工资差异问题.研究表明:(1)两个就业群体间的工资差距在不断扩大,正规就业的个体禀赋优势在工资决定中发挥了关键作用;(2)正规就业与非正规就业的工资差距存在不对称性现象,且在工资分布的末端表现明显,符合"黏地板效应",而造成这一现象的主要原因在于低收入群体存在较为严重的市场分割和就业歧视;(3)由个体禀赋所解释的特征差异呈现上升趋势,而由非市场因素解释的参数差异则在不断下降,反映出我国劳动力市场在整体上趋于公平和完善,工资的决定机制更加以市场为导向.     

Which Part of the Chinese Art Market Is More Worth Investing In? Applying the Quantile Regression to Analyze Chinese Oil Paintings 2000–2014

This article uses a quantile regression approach to analyze the structure of the hedonic characteristics of 12,701 Chinese oil paintings sold at auctions in China and Hong Kong during the period 2000–2014. A hedonic model for both the full sample and the 0.20, 0.40, 0.60, 0.80, and 0.95 quantiles of the price distribution is estimated. The result indicates that noticeable differences exist in painting characteristics across different price ranges. The empirical evidence also suggests that highly priced Chinese oil paintings have both higher expected returns and less risk than those that are priced lower, which appear to be favorable assets to invest in.     

Predictive spatial network analysis for high-resolution transport modeling,applied to cyclist flows,mode choice,and targeting investment

Betweenness is a measure long used in spatial network analysis (SpNA) to predict flows of pedestrians and vehicles, and more recently in public health research. We improve on this approach with a methodology for combining multiple betweenness computations using cross-validated ridge regression to create wide-scale, high-resolution transport models. This enables computationally efficient calibration of distance decay, agglomeration effects, and multiple trip purposes. Together with minimization of the Geoffrey E. Havers (GEH) statistic commonly used to evaluate transport models, this bridges a gap between SpNA and mainstream transport modeling practice. The methodology is demonstrated using models of bicycle transport, where the higher resolution of the SpNA models compared to mainstream (four-step) models is of particular use. Additional models are developed incorporating heterogeneous user preferences (cyclist aversion to motor traffic). Based on network shape and flow data alone the best model gives reasonable correlation against cyclist flows on individual links, weighted to optimize GEH (r² = 0.78, GEH = 1.9). As SpNA models use a single step rather than four, and can be based on flow data alone rather than demographics and surveys, the cost of calibration is lower, ensuring suitability for small-scale infrastructure projects as well as large-scale studies.     

投资者关注对金银期货市场收益影响的时频分位研究

根据Google投资者关注度指数和金银期货市场交易数据,构建基于小波分解序列的时频门限自回归分布滞后模型,通过分位数模型参数估计,基于时域与频域联合分析视角,考量投资者关注度对金银期货市场收益的影响。结果表明：投资者关注度对金银期货市场的影响具有异质性;在低频域内,投资者关注度对金银期货市场影响相对较小;极端分位数水平下,投资者关注度对金银期货市场收益影响的时效性较短,投资者关注度对白银期货市场收益的影响较弱。     

Examining the influencing factors of CO2 emissions at city level via panel quantile regression: evidence from 102 Chinese cities

Ascertaining the influencing factors of carbon dioxide emissions in Chinese cities is an important issue for policy-makers. This paper investigates the effect of several determinants on carbon emissions per capita in Chinese cities. Non-normally distributed and heterogeneous features of carbon emissions per capita in Chinese cities are considerably important. The empirical results demonstrate that GDP per capita has an increasingly positive impact on carbon emissions per capita due to the growth in household consumption. Urbanization has a slightly decreasing positive effect on carbon emissions per capita with a quantile increase resulting from continuous highway construction. Industrialization has a decreasing positive effect with carbon emission per capita quantile increases because of increasing energy efficiency and lower costs related to carbon reductions. The population has a decreasing negative effect on carbon emissions because of people’s increasing demand for environmental safety. The distributions of emissions per capita conditional on the 10th and 90th quantiles of independent variables also vary considerably. Specific policy implications are provided based on these results.     

Predicting bid prices by using machine learning methods

It is well-known that empirical analysis suffers from multicollinearity and high dimensionality. In particular, this is much more severe in an empirical study of itemized bids in highway procurement auctions. To overcome this obstacle, this article employs the regularized linear regression for the estimation of a more precise interval for project winning bids. The approach is put to the test using empirical data of highway procurement auctions in Vermont. In our empirical analysis, we first choose a set of crucial tasks that determine a bidder’s bid amounts by using the random forest variable selection method. Given the selected tasks, project bid forecasting is conducted. We compare our proposed methodology with the least square linear model based on the bias and the standard root mean square error of the bid estimates. There is evidence supporting that the suggested approach provides superior forecasts for an interval of winning bids over the competing model. As far as we know, this article is the first attempt to provide reference bids of highway construction contracts.     

How Do Household Tasks Shape Employment Contracts? The Provision of Care in Portugal

This study illustrates the complexities involved in outsourcing domestic work to the market. It draws on an original dataset of paid domestic workers in Portugal to examine how specific tasks interact with and explain contractual arrangements. A fuzzy cluster analysis categorizes paid domestic workers into caregivers and cleaners; however, a great degree of overlap implies that caring also entails cleaning tasks necessary for the care receiver’s well-being. A subsequent Tobit regression analysis shows that caregivers have more formal and stable contracts but earn lower wages and have longer working hours relative to cleaners. The study finds a segmentation of national origin and that some migrants are at a disadvantage in care work. The study also examines how employers deal with the idiosyncrasies of domestic work such as navigating trust-related issues.     

Continuity Under a Different Name: The Outcome of Privatisation in Serbia

Normally, privatisation is seen as beneficial. This paper considers the case of Serbia – a latecomer in the matter – where privatisation was partly a result of exogenous pressures and where the process has been deemed a failure. In Serbia, a sizeable number of privatised firms were bought by bureaucrats and politicians and all firms were subjected to a period of supervision. We argue that the design of this process allowed rent-seekers to conserve their privileges through asset-stripping, which explains the failure. In order to do so, we perform an empirical analysis of the determinants of liquidation, merger and bankruptcy of privatised firms from 2002 to 2015. We construct a novel data set from primary sources, free of the ‘survivorship bias’ and containing proxies for various types of owners, indirect signs of asset-stripping strategy and a broad range of controls. Our results indicate that firms owned by politicians faced significantly higher risks of bankruptcy, especially after the end of supervision.     

上市公司成长性的实证研究

上市公司的成长性与广大投资者、公司债权人、证券监管机构等都有着十分密切的关系。从某种意义上来说,公司的利润增长率比其利润本身更为重要。投资于某公司的股票,实际上是投资于公司的未来。因而,上市公司的成长性问题成为证券投资分析理论与实践中的一项十分重要的内容。运用相关分析、回归分析和方差分析等方法对上市公司的成长性与上期多项财务指标的关联性进行了探讨。     

行业进入壁垒与中国文化产业高质量发展:保护还是抑制?

基于2000—2012年中国文化产业相关上市公司的微观数据,利用分位数回归模型研究了行业进入壁垒对文化产业全要素生产率的影响。结果表明:行业进入壁垒对文化产业全要素生产率具有较强的抑制效应,并对生产率分布两端行业的负面影响较大,呈"U"型结构;行业进入壁垒存在国有文化企业保护倾向,其对国有文化企业生产率具有不显著的负面影响,而对非国有文化企业具有显著的负面效应;以文化企业补贴渠道存在的行业进入壁垒,不利于文化产业全要素生产率的提升,而由市场自发形成的市场壁垒能够提升文化产业的全要素生产率。这些研究成果为文化体制改革在全国范围内的进一步实施推广提供了依据,同时也为地区文化产业的转型升级和区域经济平衡提供了政策启示。