Revisiting the matching function

There is strong empirical evidence for Cobb–Douglas matching functions. We show in this paper that this widely found relation between matches on the one hand and unemployment and vacancies on the other hand can be the result of different underlying mechanisms. Obviously, it can be generated by assuming a Cobb–Douglas matching function. Less obvious, the same relationship results from a vacancy free-entry condition and idiosyncratic productivity shocks. A positive aggregate productivity shock leads to more vacancy posting, a shift of the idiosyncratic selection cutoff and thereby more hiring. We calibrate a model with both mechanisms to administrative German labor market data and show that idiosyncratic productivity for new contacts is an important driver of the elasticity of the job-finding rate with respect to the market tightness. Accounting for idiosyncratic productivity can explain the observed negative time trend in estimated matching efficiency and asymmetric business cycle responses to large aggregate shocks.     

Productivity changes in pre-crisis Western European banks: Does scale effect really matter?

Insofar as the completion of the Single Market for Financial Services, it has presented new challenges for European Banking industries. In this study, we use a recently developed generalized metafrontier Malmquist productivity index (gMMPI) to provide insights on productivity growth. We extend the gMMPI to broaden the index's capacity by decomposing various sources of productivity change in the metafrontier context. The sample contains commercial banks from 12 Western European countries prior to the recent financial crisis. A key advantage of our extension is that it introduces the role of scale effects. The empirical results show that an average bank's productivity growth arises mainly from technical changes and scale effects. Moreover, smaller and larger banks grow faster than medium ones. In addition, conservative banks tend to grow faster. These findings suggest that a more competitive and integrated financial market induced by financial deregulation is indeed able to improve banks’ productivity.     

Productivity change in a multisectoral economic system

We estimate productivity growth without recourse to data on factor input shares or prices. In the proposed model, the economy is represented by the Leontief input–output model, which is extended by the constraints of primary inputs. A Luenberger productivity indicator is proposed to estimate productivity change; this is then decomposed in a way that enables us to examine the contributions of individual production factors and individual commodities to productivity change. The results allow for the identification of inputs or outputs that are the drivers of the overall productivity change. Their contributions are then decomposed into efficiency change and technical change components. Using input–output tables of the US economy for the period 1977–2006, we show that technical progress has been the main source of productivity change. Technical progress was mostly driven by capital, whereas low-skilled labour contributed negatively.     

Innovation and productivity: insights from Malaysia's logistics industry

Efficient logistics is critical to a country's trade competitiveness. This paper uses the Data Envelopment Analysis Malmquist Index that includes an innovation component comprising three dimensions (input, process, and output), to assess the impact of innovation by third-party logistics (3PL). We treat the panel data of asset-based 3PL in Malaysia from 2007 to 2012. Three findings hold. First, innovation is not always accompanied by productivity gains. Second, innovation is still lacking in the logistics industry in Malaysia. Third, 3PL need to invest more in technology and stay financially healthy to accelerate the diffusion of innovation under a more competitive cost structure. This paper has two contributions. First, we offer an enhanced methodology for total factor productivity by including an innovation component and apply it for the first time to the logistics industry. Second, we augment the performance measurement literature specific to the logistics industry and our research suggests that the antecedents of productivity in logistics companies are investment and financial strength. These productivity–innovation findings provide insights into Malaysia's logistics industry and may be helpful for economies similar to Malaysia.     

The Business Case for Gender Diversity: Examining the Role of Human Resource Management Investments

Integrating opposing theoretical perspectives from the past literature, the authors hypothesize and test a U‐shaped curvilinear relationship between gender diversity and workforce productivity. They further propose that the curvilinear effects vary depending on the levels of an organization's human resource management (HRM) investments in pay, benefit, training, and communication; that is, the patterns are more salient when HRM investments are high rather than low. To enhance understanding of how HRM investments have impact on diverse employees, the authors also examine the moderating influence of organizational identification of diverse members that can exert proximal influence on the diversity‐productivity relationship. As predicted, results reveal that high levels of HRM investments influence the gender diversity–workforce productivity association to form a U‐shaped curvilinear relationship. Organizational identification also yields the same moderating patterns. Research and practical implications are discussed. © 2015 Wiley Periodicals, Inc.     

企业金融资产配置与全要素生产率之谜——基于中国A股制造业上市公司财务数据的GMM分析

全要素生产率增长放缓的"生产率之谜"根源之一在于企业金融化行为,表现为企业越来越偏好配置金融资产。理论上,企业金融资产配置对全要素生产率存在"储蓄"和"挤出"的双重作用机制。进一步地,基于2008-2016年A股制造业上市公司的财务数据,采用GMM方法,实证了"生产率之谜"来自金融化假说的一个解释。实证结果显示：（1）金融资产配置与TFP二者之间呈现倒U型关系,说明金融资产配置在"TFP增速下降"之谜中扮演了促进因子的角色;（2）金融资产配置的挤出效应大于储蓄效应,表明企业套利动机强于储蓄动机,意味着长期来看TFP增长动力趋于弱化;（3）对TFP作用大小随企业所有权性质呈现出较大差异,非国有制造业企业的"储蓄"效应更加显著,而国有制造业企业则更多的是挤出效应;（4）融资约束越小、杠杆率越高、机构投资者越集中、企业规模越大和托宾Q值越低的企业更加偏好金融资产配置,其通过"挤出"效应而对TFP的负向作用也越大。因此,警惕企业金融活动的过度化,并采用差别化的"疏""堵"结合的金融供给侧结构性改革让制造业企业能"安心做好主业"。     

中国乡镇企业产出增长来源实证分析

本文简要介绍了中国乡镇企业的发展概况和影响其发展的主要因素 ,以实际总产值作为产出指标 ,对乡镇企业产出增长与全要素生产率增长率、资本投入、劳动投入和规模损益之间的联系进行了详细的实证分析 ,分别考察了技术进步 (全要素生产率增长率 )、资本投入、劳动投入和规模损益对乡镇企业产出增长的绝对拉动作用和相对贡献份额 ,并分别考察了乡镇企业产出增长的波动程度、乡镇企业的资本生产率、劳动生产率及有机资本构成情况。在此基础上 ,提出了保证乡镇企业健康、稳定、持续增长的若干政策建议     

Measurement of Productivity Changes: Two Malmquist Index Approaches

The adjacent Malmquist productivity index is compared to the more recently suggested base period Malmquist productivity index. The two index approaches are evaluated with respect to base period dependency, the circular test, and with respect to a set of additional classical index tests. In addition it is shown that the base period index is independent of base period if and only if the marginal rate of substitution of inputs is independent of time. Finally, the adjacent and the base period indexes are put through a Monte Carlo (bootstrap) test to see if they yield similar results when applied to a panel of Swedish pharmacy data.     

Applying efficiency measurement techniques to the measurement of productivity change

Deterministic frontier analysis (DFA), stochastic frontier analysis (SFA), and data envelopment analysis (DEA) are alternative analytical techniques designed to measure the efficiency of producers. All three techniques were originally developed within a cross-sectional context, in which the objective is to compare the efficiencies of producers. More recently all three techniques have been extended for use in a panel data context. In the latter context it is possible to measure productivity change, and to decompose measured productivity change into its sources, one of which is efficiency change. However when efficiency measurement techniques, particularly SFA, have been applied to panel data, it has infrequently been made clear what the objective of the analysis is: the measurement of efficiency, which may vary through time as well as across producers, or the measurement and decomposition of productivity change. In this paper I explore the use of each technique in a panel data context. I find DFA and DEA to have achieved a more satisfactory reorientation toward productivity measurement than SFA has.     

A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies

This paper uses Bayesian stochastic frontier methods to measure the productivity gap between Poland and Western countries that existed before the beginning of the main Polish economic reform. Using data for 20 Western economies, Poland and Yugoslavia (1980–1990) we estimate a translog stochastic frontier and make inference about individual efficiencies. Following the methodology proposed in our earlier work, we also decompose output growth into technical, efficiency and input changes and examine patterns of growth in the period under consideration. This revised version was published online in July 2006 with corrections to the Cover Date.