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on Efficiency and Productivity |
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Issue of 2018‒07‒23
fourteen papers chosen by |
| By: | Cinzia Daraio; Leopold Simar; Paul W. Wilson |
| Abstract: | Directional distances provide useful, flexible measures of technical efficiency of production units relative to the efficient frontier of the attainable set in input-output space. In addition, the additive nature of directional distances permits negative input or outputs quantities. The choice of the direction allows analysis of different strate- gies for the units attempting to reach the efficient frontier. Simar et al. (2012) and Simar and Vanhems (2012) develop asymptotic properties of full-envelopment, FDH and DEA estimators of directional distances as well as robust order-m and order-± di- rectional distance estimators. Extensions of these estimators to measures conditioned on environmental variables Z are also available (e.g., see Daraio and Simar, 2014). The resulting estimators have been shown to share the properties of their corresponding radial measures. However, to date the algorithms proposed for computing the directional distance estimates suffer from various numerical drawbacks (Daraio and Simar, 2014). In particular, for the order-m versions (conditional and unconditional) only approximations, based on Monte-Carlo methods, have been suggested, involving additional computational burden. In this paper we propose a new fast and efficient method to compute exact values of the directional distance estimates for all the cases (full and partial frontier cases, unconditional or conditional to external factors), that overcome all previous difficulties. This new method is illustrated on simulated and real data sets. Matlab code for computation is provided in an appendix. |
| Keywords: | directional distances, conditional efficiency, robust frontiers, environmental factors, nonparametric methods |
| Date: | 2018–07–13 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2018/21&r=eff |
| By: | Davide Castellani; Mariacristina Piva; Torben Schubert; Marco Vivarelli |
| Abstract: | Using data on the US and EU top R&D spenders from 2004 until 2012, this paper investigates the sources of the US/EU productivity gap. We find robust evidence that US firms have a higher capacity to translate R&D into productivity gains (especially in the high-tech industries), and this contributes to explaining the higher productivity of US firms. Conversely, EU firms are more likely to achieve productivity gains through capital-embodied technological change at least in medium and low-tech sectors. Our results also show that the US/EU productivity gap has worsened during the crisis period, as the EU companies have been more affected by the economic crisis in their capacity to translate R&D investments into productivity. Based on these findings, we make a case for a learning-based and selective R&D funding, which - instead of purely aiming at stimulating higher R&D expenditures - works on improving the firms' capabilities to transform R&D into productivity gains. |
| Keywords: | R&D; productivity; economic crisis; US; EU |
| Date: | 2018–06–17 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2018/16&r=eff |
| By: | Paul, Satya; Shankar, Sriram |
| Abstract: | This paper proposes a stochastic frontier panel data model which includes time-invariant unobserved heterogeneity along with the efficiency effects. Following Paul and Shankar (2018), the efficiency effects are specified by a standard normal cumulative distribution function of exogenous variables which ensures the efficiency scores to lie in a unit interval. This specification eschews one-sided error term present in almost all the existing inefficiency effects models. The model parameters can be estimated by non-linear least squares after removing the individual effects by the usual within transformation or using non-linear least squares dummy variables (NLLSDV) estimator. The efficiency scores are directly calculated once the model is estimated. An empirical illustration based on widely used panel data on Indian farmers is presented. |
| Keywords: | Fixed effects; Stochastic frontier; Technical efficiency; Standard normal cumulative distribution function; Non-linear least squares. |
| JEL: | C51 D24 Q12 |
| Date: | 2018–06–04 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:87437&r=eff |
| By: | Emanuele Ciani (Bank of Italy); Andrea Locatelli (Bank of Italy); Marcello Pagnini (Bank of Italy) |
| Abstract: | In this work we study the geographical differences in total factor productivity (TFP) estimated at firm level for corporations active in the manufacturing sector between 1995 and 2015. In 2015 the average TFP in the South was between 14 and 33 per cent lower than in the North-West: the largest estimate is obtained using the number of employees as a proxy for labor input; the smallest, by using the cost of labor which better captures the skill composition and the actual work intensity. Productivity levels in the North-East were close to those in the other Northern regions; firms in the Centre were in-between. During the two decades the TFP gap between more productive and less productive firms contracted in all areas, but more so in the South; this led to a modest reduction in the North-South TFP divide, which was also driven by a more intense selection process in the Southern regions during the economic recession. |
| Keywords: | total factor productivity, geographical differences |
| JEL: | D14 R12 |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:bdi:opques:qef_438_18&r=eff |
| By: | Yujiao Xian; Ke Wang; Xunpeng Shi; Chi Zhang; Yi-Ming Wei; Zhimin Huang |
| Abstract: | This paper proposes a scenario analysis to address whether the national and provincial CO2 emissions intensity reduction target during 2016-2020 would be achievable for China¡¯s power industry with the identification of change on carbon productivity. This productivity indicator is further decomposed to investigate contributions of different sources to productivity growth when there exists technological heterogeneity. Evaluation results show that even if all electricity-generating units in each region were able to adopt the best practice, the nationwide 18% intensity reduction target is not feasible through improving technical efficiency or upgrading technology on electricity generation and carbon abatement in a short or medium term. The existence of regional technological heterogeneity in power generation and associated CO2 emissions reduction processes implies the necessity of more differentiated regulations and policies for emission reduction across China¡¯s regions and inter-regional technology transfer. The emerging national emission trading scheme could easy some challenges in formulating emission policy for heterogeneous regions. |
| Keywords: | Data Envelopment Analysis (DEA); Endogenous directional distance function (DDF); Meta-technology frontier; Heterogeneity; Technological gap |
| JEL: | Q54 Q40 |
| Date: | 2018–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:biw:wpaper:117&r=eff |
| By: | Bloom, Nick; Lucking, Brian; Van Reenen, John |
| Abstract: | This paper revisits the results of Bloom, Schankerman, and Van Reenen (2013) examining the impact of R&D on the performance of US firms, especially through spillovers. We extend their analysis to include an additional 15 years of data through 2015, and update the measures of firms' interactions in technology space and product market space. We show that the magnitude of R&D spillovers appears to have been broadly similar in the second decade of the 21st Century as it was in the mid-1980s. However, there does seem to have been some increase in the wedge between marginal social returns to R&D and marginal private returns with the ratio of marginal social to private returns increasing to a factor of 4 from 3. There is certainly no evidence that the need to subsidize R&D has diminished. Positive spillovers appeared to increase in the 1995-2004 boom. |
| Keywords: | innovation; RD; patents; productivity and spillovers |
| JEL: | F23 O31 O32 O33 |
| Date: | 2018–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:88699&r=eff |
| By: | A. Arrighetti; F. Landini; E. Bartoloni |
| Abstract: | An extensive literature documents large and persistent within-industry heterogeneity of firm performance. While some authors explain such evidence in terms of factor misallocation, we provide an alternative framework that is based on the interaction among exogenous and endogenous factors. Exogenous factors, both supply and demand-related, define the opportunity set that is available to firms. Endogenous factors reflect instead firm-specific interpretations of such set, which combined with the available resources and capabilities determine firm’s strategic responses that can be markedly heterogeneous. Whenever the diversity of firm conducts is associated with relatively small profit differentials, firm heterogeneity can persist. Evidence based on the evolution of labour productivity and profit dispersion in the Italian manufacturing sector between the 1990s and early 2000s provides support for our interpretative framework. |
| Keywords: | Firm heterogeneity; productivity; profit; misallocation; capabilities; Italy |
| JEL: | D24 L11 L25 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:par:dipeco:2018-ep02&r=eff |
| By: | MORIKAWA Masayuki |
| Abstract: | This study presents evidence on the quantitative relationship between employer-provided training (Off-JT) and productivity among Japanese firms. The important contributions of this study are its construction of a panel of training stock at the firm level, distinction between manufacturing and service firms, and comparison of relative contribution of training on productivity and wages. The results indicate, first, that training significantly contributes to the labor productivity of the firm. Second, the estimated elasticity of productivity with respect to training stock is greater for service firms than manufacturing firms. Third, the elasticities of productivity and wages to training stock are similar in size, meaning that the returns to firms' training investments are shared by their workers proportional to the wage share of the value added. These results suggest that policies to promote firms' training investments have the potential to improve productivity and wages, particularly of firms in the service industries. |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:eti:rdpsjp:18021&r=eff |
| By: | John Forth (National Institute of Social and Economic Research); Alex Bryson (University College London, National Institute of Social and Economic Research and Institute for the Study of Labor) |
| Abstract: | We examine the impact of management practices on firm performance among SMEs in Britain over the period 2011-2014, using a unique dataset which links survey data on management practices with firm performance data from the UK's official business register. We find that SMEs are less likely to use formal management practices than larger firms, but that such practices have demonstrable benefits for those who use them, helping firms to grow and increasing their productivity. The returns are most apparent for those SMEs that invest in human resource management practices, such as training and performance-related pay, and those that set formal performance targets. |
| Keywords: | SMEs; small and medium-sized enterprises; employment growth; high-growth firms; productivity; workplace closure; management practices; HRM; recession |
| JEL: | L25 L26 M12 M52 M53 |
| Date: | 2018–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:qss:dqsswp:1804&r=eff |
| By: | Steven Helfand (Department of Economics, University of California Riverside); Matthew Taylor |
| Abstract: | The relationship between farm size and productivity is a recurrent topic in development economics, almost as old as the discipline itself. This paper emphasizes the importance of choice of productivity measures in the inverse relationship literature. First, we seek to clarify the common measures, their relationships, and their advantages and limitations in empirical work. Second, we argue that much of the existing literature inappropriately uses partial measures such as land productivity. Third, we discuss the dynamic nature of the farm size – productivity relationship and show that the identification of these dynamics will in part depend upon the choice of productivity measure. Lastly, using a pseudo-panel of Brazilian farms that are aggregated at the municipality and farm size levels over the period 1985-2006, we provide new empirical evidence on the inverse relationship between farm size and both land productivity and total factor productivity. The empirical exercise highlights the importance of choice of measure when testing the inverse relationship. The inverse relationship between size and land productivity is alive and well. The relationship between total factor productivity and size, in contrast, has evolved with modernization during this period, becoming increasingly U-shaped or even positive. |
| Keywords: | Inverse relationship, agriculture, farm size, total factor productivity (TFP), Brazil |
| JEL: | O13 Q12 |
| Date: | 2018–07 |
| URL: | http://d.repec.org/n?u=RePEc:ucr:wpaper:201811&r=eff |
| By: | Nilsen, Øivind A. (Dept. of Economics, Norwegian School of Economics and Business Administration); Raknerud, Arvid (Statistics Norway); Iancu, Diana-Cristina (Statistics Norway) |
| Abstract: | We analyse all the major sources of direct and indirect R&D subsidies in Norway in the period 2002-2013 and compare their effects on individual firms’ performance. Firms that received support are matched with a control group of firms that did not receive support using a combination of stratification and propensity score matching. Changes in performance indicators before and after support in the treatment group are compared With contemporaneous changes in the control group. We find that the average effects of R&D support among those who obtained grants and/or subsidies are positive and significant in terms of performance indicators related to economic growth: value added, sales revenue and number of employees. The estimated effects are larger for start-up firms than incumbent firms when the effects are measured as relative effects (in percentage points), but smaller when these effects are translated into level effects. Finally, we do not find positive effects on return to total assets or productivity for firms who received support compared with the control group. |
| Keywords: | Public policy; Firm performance; Treatment effects; Stratification; Propensity score matching; Productivity |
| JEL: | C33 C52 D24 O38 |
| Date: | 2018–06–20 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:nhheco:2018_013&r=eff |
| By: | Stjepan Srhoj (Department for Economics and Business Economics, University of Dubrovnik); Bruno Skrinjaric (The Institute of Economics, Zagreb); Sonja Radas (The Institute of Economics, Zagreb) |
| Abstract: | Impact evaluations of entrepreneurship policies targeting young firms have been somewhat neglected thus far in the literature. This paper seeks to contribute to this topic in the context of a long recession period, such as the one experienced in Croatia from 2009 to 2014. These policies awarded small grant amounts for activities such as business plan development, consultancy, marketing and office renovation. Awarding small grant amounts to many firms might be tempting for politicians, but is this political populism or smart policy? This paper estimates the impact of matching grants for business development on three types of outcomes: bank loans, firm survival and firm performance. The full firm-level census dataset was supplemented with entrepreneur-level court register and firm-level data on grant recipients. Policy evaluation was performed using matching techniques with a combination of nearest neighbor and exact matching, and robustness of results was tested using a placebo test and Rosenbaum bounds. The results show that grants had a positive impact on firm survival after the recession, and on obtaining long-term bank loans during the recession. However, no empirical support was found for the grants’ impact on growth in turnover, employment and labor productivity. |
| Keywords: | grants, recession, young firms, survival, firm performance, bank loans |
| JEL: | H25 |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:iez:wpaper:1802&r=eff |
| By: | Sudeshna Paul; Athula Naranpanawa; Jay Bandaralage; Tapan Sarker |
| Keywords: | Climate change, Crop productivity, Regional disparities, Computable General Equilibrium model, Bangladesh |
| JEL: | Q54 R11 D58 |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:gri:epaper:economics:201803&r=eff |
| By: | WOO JE KIM (Seoul National University of Science and Technology); Jung Kyun Kim (Seoul National University of Science and Technology); Hyo Joo Shin (Seoul National University of Science and Technology); Mi Sun Park (Seoul National University of Science and Technology) |
| Abstract: | IT maintenance services have an important role to operate business processes in a company. There are normally a lot of IT systems in a company and they are maintained with IT maintenance services. So, it is meaningful analysis to compare efficiency of IT maintenance services by IT system in a company. In this paper, a model for efficiency analysis of IT maintenance services using DEA/AHP(data envelop analysis/analytic hierarchy process) is developed in a company. In this paper, the efficiency of IT maintenance services is evaluated with a DEA model which has maintenance cost and complexity of maintenance service as input factors and degree of satisfaction for maintenance service as an output factor. The complexity of maintenance service and the degree of satisfaction for maintenance service are evaluated with AHP models, respectively. We applied this model to evaluate efficiency of IT maintenance services in an insurance company. As a result, we could suggest the best practices among the IT maintenance services and the improving directions for the inefficient IT services in the company. |
| Keywords: | efficiency analysis, IT maintenance service, data envelop analysis, analytic hierarchy process |
| JEL: | C61 |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:5408024&r=eff |