粤港澳大湾区制造业集聚与区域创新

以2009—2020年粤港澳大湾区11个城市为研究对象，探讨制造业集聚与区域创新的关系。研究发现，制造业集聚显著提高区域创新水平，可通过提高企业竞争这一路径实现。进一步分析发现，金融业集聚对区域创新发展具有显著的正向关系，金融产业和制造业产融协同集聚显著提高区域创新水平。研究结果表明，制造业集聚加剧产业内部企业创新竞争，带动区域创新发展，且金融业在创新中起到积极的推动作用。指出应鼓励区域企业创新竞争，优化营商环境，为产业融合发展提供保障。     

土地市场扭曲如何影响制造业出口产品质量升级*——基于土地市场交易数据和制造业企业数据的实证分析

地方政府“以地谋发展”的策略在促进各地区制造业大规模集聚和出口贸易快速增长的同时，也势必会给企业出口产品质量带来深刻影响。本文综合利用中国土地市场网城市土地交易数据、中国工业企业数据、中国海关进出口产品数据和中国城市面板数据，实证检验了土地市场扭曲对企业出口产品质量升级的影响，并对其内在机制进行了探讨。研究发现：中国城市建设用地配置存在明显的工业偏向性，进而导致工业用地价格被低估，产生工业用地应得收益大于实际价格的反向扭曲问题。这种反向扭曲可通过抑制技术进步、阻碍产业结构高级化、弱化集聚经济效应等机制显著降低制造业企业出口产品质量。土地市场扭曲对企业出口产品质量升级的影响具有明显的异质性特征。具体而言，土地市场扭曲不利于一般贸易企业与混合贸易企业出口产品质量提升，但对加工贸易企业出口产品质量提升具有促进作用。土地市场扭曲对企业出口产品质量升级的抑制作用由东到西依次递增。土地市场扭曲不利于外资企业和国有企业出口产品质量提升，对集体企业及民营企业的影响不显著。     

Effects of broadband availability on total factor productivity in service sector firms: Evidence from Ireland

While broadband is widely believed to augment productivity, there is little firm-level evidence of a generalised causal effect. In this paper we examine whether the introduction of digital subscriber line (DSL) broadband services increased firms' productivity in nine sub-sectors within the services and distribution sector in Ireland from 2006 to 2012. Firm-level panel data on firms' characteristics are linked to spatial information on the rollout of DSL. While we do not find significant productivity effects in the services sectors taken together, we do find positive and significant effects on firm's total factor productivity in Information & Communication and Administrative & Support Services.     

Risk Preferences and Gender Differences in Union Membership in Late Nineteenth-Century Swedish Manufacturing

Women are generally seen as less inclined to join trade unions. This study matches firm–worker data from the Swedish cigar and printing industries around 1900 and examines information on men and women holding the same jobs; such data are rare but important for understanding gender gaps. The results explain the gender gap in union membership among compositors, but not among cigar workers. Differences in union membership varied considerably across firms, with the largest differences found in low-union-density cigar firms where indirect costs (that is, uncertainty and risk) accrued in particular to women workers. The lack of gender differences in mutual aid membership indicates that women were not hard to organize but avoided organizations associated with greater risk for employer retaliation and uncertain returns according to a cost–benefit analysis.     

Public sector innovation in a context of radical populism

This article discusses the effect of radical populism on public sector innovation. It begins by considering the origins and components of radical populism and of public sector innovation. It is shown that the Trump Administration has been undercutting each of the factors research suggests facilitate public sector innovation. While radical populists have gained ground in Europe, they are constrained by being part of governing coalitions, and have a more limited policy agenda, primarily focused on reducing immigration. The paper concludes with suggestions for further research on the effect of populism on public sector innovation, both in the US and Europe.     

Institutions for private sector development and pro‐poor growth: Evidence from Vietnam

Using the Vietnam Household Living Standards Survey 2008, we explore the differences in pro‐poor growth performance in provinces in Vietnam according to the quality of the provinces’ institutions that support private sector activity. We exploit the localized and varying effect of French colonial legacy across Vietnamese provinces to address the endogeneity of institutions. We find strong and robust evidence of a positive effect of good‐quality institutions that support private sector activity on pro‐poor growth and that enhanced working hours and hourly wage and extended income from non‐farm self‐employment play critical roles in this outcome.     

Target‐Setting,Pay for Performance,and Quality Improvement: A Case Study of Ontario Hospitals’ Quality‐Improvement Plans

This study examines whether difficult targets and quality indicators in executives' pay‐for‐performance (P4P) plans affect performance. The impact of target‐setting and P4P plans on quality improvement in the public sector is unclear. The Ontario government initiated the Quality Improvement Plan (QIP), which requires hospitals to set targets for quality indicators annually and link executive pay to target achievement since 2011. Analyzing Health Quality Ontario's database and hospitals' 2012–2013 QIPs, this study shows greater quality improvement in hospitals with difficult targets than hospitals with easy targets or without assigned targets; however, the positive impact disappears for high‐performance hospitals relative to their peers. We find no significant effect of the use of quality indicators in executives' P4P plans on quality improvement. Copyright © 2018 ASAC. Published by John Wiley & Sons, Ltd.     

Determinants of energy use in the informal food sector

Although enterprises in the informal food sector require energy to transform, cook and process food, energy-use patterns in this sector are not well understood by policymakers and the local-level authorities who regulate their trading activities. This paper reviews relevant literature and presents empirical data collected in Rwanda, Senegal and South Africa on the use of traditional and modern energy sources by informal food sector operators. Our sample includes male- and female-operated enterprises in the urban centres of three African countries where the informal food sector is important, not only for providing the convenience of affordable and readily prepared meals, but also as a source of income for women and men in developing countries. Multiple fuel-use and energy-stacking strategies are common among informal food enterprises and policy needs to acknowledge this if it is to intervene in ways that will benefit both enterprises and regulators.     

A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a production possibility frontier with a model of technical inefficiency. The model addresses both spatial dependence and heteroskedastic technical inefficiency. This study applies maximum likelihood methods considering the endogenous spatial lag term. The proposed model nests several existing models. Further, an empirical analysis using data on the Japanese manufacturing industry is conducted and the existing models are tested against the proposed model, which is found to be statistically supported. The findings suggest that estimates in the existing spatial and non-spatial models may exhibit bias because of lack of determinants of technical inefficiency, as well as a spatial lag. This bias also affects the technical efficiency score and its ranking.     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.