股权分置改革受限股份流通次序

本文采用分量回归模型．具体研究国有股权对不同业绩水平上市公司影响程度的差异。结论表明．国有股权对公司业绩具有负面影响,且对不同业绩水平上市公司的影响程度存在明显差异．业绩越好的公司,国有股权带来的负面影响越严重。因此,基于市场承受能力的限制．从提高市场整体效率的角度出发．政府在股权分置改革第二阶段．安排受限股份上市流通时．应该考虑首先安排业绩好的上市公司的受限股份优先进入流通。实证分析结果还验证了现阶段我国市场上规模经济效应的存在。     

RIDGE ESTIMATORS FOR PROBIT REGRESSION: WITH AN APPLICATION TO LABOUR MARKET DATA

In this paper we propose ridge regression estimators for probit models since the commonly applied maximum likelihood (ML) method is sensitive to multicollinearity. An extensive Monte Carlo study is conducted where the performance of the ML method and the probit ridge regression (PRR) is investigated when the data are collinear. In the simulation study we evaluate a number of methods of estimating the ridge parameter k that have recently been developed for use in linear regression analysis. The results from the simulation study show that there is at least one group of the estimators of k that regularly has a lower mean squared error than the ML method for all different situations that have been evaluated. Finally, we show the benefit of the new method using the classical Dehejia and Wahba dataset which is based on a labour market experiment.     

山西省人口城镇化与经济发展水平相关分析

通过对1990-2007年山西省人口与经济发展水平的统计数据的分析,得出山西省人口城镇化与经济发展水平的关系。先采用Pearson相关分析的方法分析了四组变量间相关关系的密切程度和相关方向,得出与人口城镇化相关的线性关系;再对具有高度相关关系的其他三组变量进行回归分析,并建立回归模型;最后,结合区域经济学的相关理论对计算结果作了简要分析。总结提出山西省应把产业结构优化作为今后一段时期的重点,以此来促进人口城镇化水平的提高。     

Amenity values of spatial configurations of forest landscapes over space and time in the Southern Appalachian Highlands

This research analyzes amenity values of spatial configurations of forest landscapes over space and time in the Southern Appalachian Highlands using geographically weighted regression (GWR) in a hedonic housing-price framework with a census-block group (CBG) dataset. Results show that housing-price response to mean forest-patch size and forest-patch density increased substantially between 1990 and 2000 in a few specific areas with economically significant amenity values. The spatial and temporal dynamics of the resulting amenity-value estimates are evaluated for potential use as site-selection indicators for implementation of forest conservation programs.     

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.     

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.     

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.     

An effective going concern prediction model for the sustainability of enterprises and capital market development

The purpose of this study is to construct a two-stage effective and innovative going concern prediction model to predict going concern doubt for the sustainability of enterprises and capital market development. Samples of this study are the companies listed on the Taiwan Stock Exchange or the Taipei Exchange, totalling 196 companies and including 49 companies with going concern doubt and 147 normal companies (with no going concern doubt). The data are taken from the Taiwan Economic Journal (TEJ) and the Market Observation Post System during the period from 2001 to 2016 (totalling 16 years). This study adopts a two-stage way to construct the going concern prediction models. In Stage I, the traditional statistical method of stepwise regression (SR) and the data mining technique artificial neural network (ANN) are applied to select the important variables. In Stage II, two decision tree algorithms (data mining techniques): classification and regression tree (CART) and C5.0 are used to establish the prediction models. The results show that the SR + CART model has the highest going concern prediction accuracy, with an overall accuracy of 87.42%.     

Trade-threshold Effect on Inflation in Tunisia: New Evidence Resulting from a Nonlinear Approach

Trade openness is an important determinant of the inflation process. The effect of trade openness on inflation, however, is still an issue of debate at both theoretical and empirical levels. This study tried to provide a contribution to the literature by examining the relationship between inflation and trade openness in Tunisia over the period 1975Q1-2015Q4 using a nonlinear model. The originality of this study stems from the fact that it is the first investigation considering both the Residual-Based Tests for Cointegration in Models with the Regime Shifts and Threshold Regression model. The linear model confirms the existence of a positive relationship between inflation and trade in Tunisia. Yet, considering the nonlinear model, trade openness growth and Consumer Price Index (CPI) inflation growth show a statistically significant negative link as long as the trade openness evolution does not exceed the threshold. Nevertheless, if the trade openness growth is higher than the threshold, integrating the trade positively affects CPI inflation. Furthermore, a positive influence of Money supply growth on this type of inflation was noticed in Tunisia in all the considered regimes proving the effect of monetary factors on inflation level. Consequently, trade openness could be used to control inflation in Tunisia.