Does local government competition aggravate haze pollution? A new perspective of factor market distortion

Haze pollution has become a new threat to China's sustainable development, but it may be that local government behaviour can play an important role in the prevention and control of pollutants. A dynamic spatial autoregressive (SAR) model is used to study the relationship between local government competition and haze pollution. To further explore the indirect impact of factor market distortion on haze pollution and control potential endogeneity problems, a newly developed intermediary effect model that incorporates the characteristics of the generalized method of moments (GMM) is utilized to explore how factor market distortion indirectly affects haze pollution. The research results show that regional haze pollution in China is characterized by significant spatial correlation, and local government competition has a positive impact on haze pollution; that is, local government competition exacerbates haze pollution. In general, local government competition not only directly leads to an increase in haze pollution but also further intensifies it by distorting the local factor market, and the intermediary role of factor market distortion is approximately 7.04%. The results of the regional inspection found that competition among local governments in the eastern region did not lead to haze pollution, and distortion of the factor market did not exist as an intermediary effect. However, both direct and intermediary effects are significant in the central and western regions. Therefore, an official performance appraisal system that includes ecological constraints should be established to guide the benign transformation of local government competition, and an environmental management mechanism must be developed for joint prevention and control to reduce haze pollution. In addition, the free flow of factors and marketization are equally important.     

国家高新区设立能够提升城市全要素生产率吗？——基于261个地级市TFP分解数据的路径分析

国家高新区是培育经济增长新动能，实现区域经济高质量发展的重要政策载体，文章利用2001-2014年我国261个城市面板数据，通过渐进双重差分法研究国家高新区设立对城市全要素生产率的影响。研究发现：研究期内国家高新区的设立对城市全要素生产率造成显著的负面影响；从TFP的分解项来看，高新区设立促进了所在城市规模效率提高，却抑制了技术进步和技术效率提高；异质性分析结果表明上述作用具有显著城市等级异质性，在高行政等级城市设立高新区对城市全要素生产率具有促进作用。进一步运用工业企业数据库、微观土地转让数据、城市专利数据等进行机制分析发现，企业间资源错配和土地价格扭曲降低了技术效率，而技术创新下降和产业升级钝化是抑制技术进步的主要机制。     

要素自由流动能实现区域协调发展吗——基于“协调性集聚”的理论假说与实证检验

经济活动的空间集聚是当代经济内涵式增长的源泉,现有文献多从要素流动视角来考察经济集聚过程中的区域差异。然而,若将要素流动引入区域生产函数进行推导,可以发现非区域性要素集中规模的扩大,既能提高要素流入区域的劳动生产率,也能提高要素流出区域的要素收益率,基于此,本文以“协调性集聚”为核心概念,通过拓展现代集聚模型来构建要素在自由流动中走向协调发展的理论假说。实证结果进一步显示,虽然我国发展要素在大规模流向东部发达地区,并呈现进一步向超大城市和城市群集聚的趋势,但要素流动在提高要素流入区域劳动生产率的同时,也显著提高了要素流出区域的要素收益率,并从需求侧激发了要素流出区域的市场潜能,要素流动在要素配置效率不断提高的过程中呈现“协调性集聚”的趋势。因此,发达的要素流入区域通过优化公共服务体系提高劳动生产率,欠发达的要素流出区域通过建立健全要素自由流动机制提高要素回报率和收益率,是新时代我国形成市场主导型区域协调发展机制的有效途径。     

知识型员工冗余对中小上市公司二元创新的影响：环境特征的调节作用

以277家中小板和创业板上市公司2012-2017年平衡面板数据为样本，利用泊松模型，实证分析知识型员工冗余与企业二元创新的关系，并探讨外部环境特征（要素市场发育程度和市场不确定性）的调节机理。研究表明：企业应保持一定的知识型员工冗余，促进企业二元式创新，过多或过少的知识型员工冗余均不利于企业开展创新活动；不同的环境特征对二者间关系的调节作用存在异质性，要素市场发育程度会减弱知识型员工冗余与探索式创新、利用式创新间关系，而市场不确定性会加强知识型员工冗余与探索式创新、利用式创新间关系。     

Understanding machine learning-based forecasting methods: A decomposition framework and research opportunities

Machine learning (ML) methods are gaining popularity in the forecasting field, as they have shown strong empirical performance in the recent M4 and M5 competitions, as well as in several Kaggle competitions. However, understanding why and how these methods work well for forecasting is still at a very early stage, partly due to their complexity. In this paper, I present a framework for regression-based ML that provides researchers with a common language and abstraction to aid in their study. To demonstrate the utility of the framework, I show how it can be used to map and compare ML methods used in the M5 Uncertainty competition. I then describe how the framework can be used together with ablation testing to systematically study their performance. Lastly, I use the framework to provide an overview of the solution space in regression-based ML forecasting, identifying areas for further research.     

Understanding the trend to mobile-only internet connections:A decomposition analysis

A growing portion of internet users rely solely on mobile devices such as smartphones for their online access. The percentage of “mobile-only” households increased from 9% in 2011 to 20% in 2015, more than doubling in only four years. As this shift continues, it leads to the question of what factors are driving the rise in mobile-only adoption. Using nationally representative data, this study uses logistic regressions and a decomposition technique to understand the trend. The decomposition reveals that a significant portion (65%) of the growth was due to an increase in the download speeds of mobile networks. An increased acceptance of mobile-only access by households aged 55 and older was also partly responsible. Understanding (and developing a response to) the trend towards mobile-only adoption will be important as organizations and governments continue to work to close the digital divide.     

A comprehensive evaluation of macroeconomic forecasting methods

We employ datasets for seven developed economies and consider four classes of multivariate forecasting models in order to extend and enhance the empirical evidence in the macroeconomic forecasting literature. The evaluation considers forecasting horizons of between one quarter and two years ahead. We find that the structural model, a medium-sized DSGE model, provides accurate long-horizon US and UK inflation forecasts. We strike a balance between being comprehensive and producing clear messages by applying meta-analysis regressions to 2,976 relative accuracy comparisons that vary with the forecasting horizon, country, model class and specification, number of predictors, and evaluation period. For point and density forecasting of GDP growth and inflation, we find that models with large numbers of predictors do not outperform models with 13–14 hand-picked predictors. Factor-augmented models and equal-weighted combinations of single-predictor mixed-data sampling regressions are a better choice for dealing with large numbers of predictors than Bayesian VARs.     

Are China’s regional agricultural productivities converging: How and why?

This article tests the hypotheses of convergence to a single level of total factor productivity (TFP), and a steady state of TFP growth rate in China’s agricultural sector. Based on multilateral TFP estimates we found that China’s agricultural sector has rebounded in recent years from a slower TFP growth in the 2005–2007 period. While convergence test results confirm a “catch-up” effect that provinces with lower TFP levels tend to grow faster than others, estimated rates of β convergence are conditional on how we capture the heterogeneity effect across regions. The rates of β convergence range from 0.016 to 0.039 under different model specifications. Estimates show that higher growth rates of educational attainment, R&D, and intermediate goods density (per unit of labor) can enhance TFP growth. Unfortunately, there is no evidence of an overall σ convergence, indicating that TFP levels are not converging except in the South region. It implies that to catch up with leading provinces, it would require extra efforts for those lagging behind by increasing their region-specific research investment, promoting rural educational attainment, and enhancing embodied technical change.     

Factor Heterogeneity,Factor Market Imperfection and Trade

This paper develops a tractable model of examining how factor heterogeneity and imperfect factor market interact for determining a pattern of trade. Institution plays a crucial role for the interaction. In my work, firm productivity is defined as a composition of factor productivity and technology. Thus, input selection should affect the pattern of Melitz’s intra-industry allocation due to the incurring transaction cost. For a simple model, I assume two factors (labor and capital) and two sectors, which are relatively less institution-dependent and relatively more institution-dependent. When the economy is open, effect of the transaction cost on income distribution is more drastic for an institutionally underdeveloped country. Depending on institutional quality, the economic openness reallocates resource across countries through job creation or job destruction. The job turnovers redistribute income between heterogeneous labors within countries. The income redistribution is catalyzed by international mobility of capital. As a result, income disparity is widened between the institutionally developed country and the institutionally underdeveloped country. This paper can contribute to the literature of institution and international trade.     

The structure of information release and the factor structure of returns

We model how firms releasing information on different dates causes the CAPM to fail, requiring an additional factor based on the information structure to price assets. We exemplify this mechanism’s empirical relevance using quarterly earnings announcements, which cluster across months along size and book-to-market. Seventy percent of the alpha reduction from including SMB and HML occurs in the four main earnings announcement months. The information structure factor accounts for all of SMB and HML’s seasonal alpha reduction and one third of their overall alpha reduction. Controlling for size and book-to-market, exposures to SMB and HML vary with firms’ earnings announcement month.