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on Efficiency and Productivity |
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Issue of 2015‒08‒13
nine papers chosen by |
| By: | Eric Nauenberg |
| Keywords: | productivity; potential Pareto improvement |
| Date: | 2015–08 |
| URL: | http://d.repec.org/n?u=RePEc:cch:wpaper:150013&r=eff |
| By: | TOKUI Joji; MAKINO Tatsuji; FUKAO Kyoji |
| Abstract: | Using the Regional-Level Japan Industrial Productivity (R-JIP) Database, we examined prefectural differences in labor productivity from 1970 to 2008 from various angles by looking at prefectural differences in industrial structure and prefectural and industry differences in factor inputs and productivity. First, in section 2, we decomposed prefectural labor productivity differences into the contribution of differences in industrial structure and the contribution of within-industry differences in labor productivity, and further decomposed the latter into the contribution of capital-labor ratio, labor quality, and total factor productivity (TFP). Next, in section 3, we decomposed prefectural differences in productivity and factor inputs into the share effect due to prefectural differences in industrial structure and the within effect due to prefectural differences in productivity or factor intensity within the same industry. Finally, in section 4, we examined which industries make the largest contribution to prefectural differences in productivity and how they do so—namely, through differences in capital-labor ratio, labor quality, or TFP, and through the share effect or the within effect.The results of these analyses show that industrial structures among prefectures became increasingly similar over the roughly four decades, and that this greatly contributed to the decline in labor productivity differences overall. In contrast, within-industry differences in labor productivity among prefectures declined only marginally over the same period and therefore hardly contributed to the reduction in prefectural labor productivity differences. The decomposition of within-industry labor productivity differences shows that although such within-industry differences show relatively little change over time, the factors contributing to them did shift considerably. That is, while regional differences in capital-labor ratios decreased substantially, regional within-industry differences in TFP increased. Therefore, the increase in within-industry differences in TFP is the main cause of the recent slowdown of the convergence of regional labor productivity differences. By decomposing the covariance between within-industry TFP differences and labor productivity differences among prefectures into each industry's contribution, we find vital contribution of service industries, especially wholesale and retail trade, and other non-government services, suggesting the important role of these service industries in recent increase of within-industry differences in TFP, and thereby in the recent slowdown of the convergence of regional labor productivity differences. |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:15089&r=eff |
| By: | Shingo Kimura; Johannes Sauer |
| Abstract: | This report compares the dynamics of productivity growth in the last decade in the dairy farm sector of three EU Member States: Estonia, the Netherlands and the United Kingdom (England and Wales). The evolution of the dairy farm sector in these countries is characterised by a decline in the number of dairy farms and an increase in the average herd size per farm. Policy factors have a strong impact on productivity growth at the farm. In Estonia, the dairy farm sector has expanded significantly in recent years and the productivity growth of the sector is led largely by a resource reallocation in favour of a small number of large and productive farms. In the Netherlands, the dairy farm sector adjusted to the different policy environments over time and the productivity growth of the sector is driven largely by productivity improvement at the farm level through technological adoption and efficient resource use. In the United Kingdom, productivity growth comes from the exit of smaller farms and farm size expansion of the remaining farms. |
| Keywords: | productivity, resource allocation |
| JEL: | D24 O33 Q12 Q18 |
| Date: | 2015–08–06 |
| URL: | http://d.repec.org/n?u=RePEc:oec:agraaa:87-en&r=eff |
| By: | James Alm (Department of Economics, Tulane University); Denvil Duncan (School of Public and Environmental Affairs, Indiana University-Bloomington) |
| Abstract: | Empirical work on a tax agency's production process has been plagued by the absence of comparable tax administrative data across countries and years. Such data are now available from the Organisation of Economic Co-operation and Development. This paper uses these data for the years 2007 to 2011, together with an estimation strategy that utilizes data envelopment analysis and stochastic frontier analysis, to determine the relative efficiency of tax agencies in their use of inputs. Overall, the average efficiency scores indicate that countries should be able to collect their current level of revenues with approximately 10 to 16 percent less inputs. |
| Keywords: | tax administration, tax efficiency, data envelopment analysis, stochastic frontier analysis |
| JEL: | H2 H26 H61 H83 |
| Date: | 2014–03 |
| URL: | http://d.repec.org/n?u=RePEc:tul:wpaper:1404&r=eff |
| By: | Fındık, Derya; Tansel, Aysit |
| Abstract: | This chapter analyzes the effect of intangible investment on firm efficiency with an emphasis on its software component. Stochastic production frontier approach is used to simultaneously estimate the production function and the determinants of technical efficiency in the software intensive manufacturing firms in Turkey for the period 2003-2007. Firms are classified based on the technology group. High technology and low technology firms are estimated separately in order to reveal differentials in their firm efficiency. The results show that the effect of software investment on firm efficiency is larger in high technology firms which operate in areas such as chemicals, electricity, and machinery as compared to that of the low technology firms which operate in areas such as textiles, food, paper, and unclassified manufacturing. Further, among the high technology firms, the effect of the software investment is smaller than the effect of research and development personnel expenditure. This result shows that the presence of R&D personnel is more important than the software investment for software intensive manufacturing firms in Turkey. |
| Keywords: | Intangible assets, Software investment, Efficiency, Software intensive firms, Stochastic frontier analysis, Production Function, Firms, Turkey. |
| JEL: | L21 L22 L23 L25 |
| Date: | 2013–08–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:65955&r=eff |
| By: | Bernard Hoekman; Benjamin Shepherd |
| Abstract: | This paper analyzes the linkage between services and manufacturing productivity performance, using firm-level data for over 100 developing countries. We find strong evidence for such a linkage, although the effect is small: at the average rate of services input intensity, a 10% improvement in services productivity is associated with an increase in manufacturing productivity 0.3%, and a resulting increase in exports of 0.2%. Services trade restrictiveness indices (STRI) are found to be a statistically significant determinant of manufactured exports performance, a finding that is robust to the inclusion of the overall level of trade restrictiveness that is applied against manufactured exports directly. The main channel through which services trade restrictions negatively affect manufactured exports is through FDI, a finding that is consistent with the stylized fact in the literature that FDI is a key channel for trade in services and an important vehicle through which services technology and know-how is transferred across countries. At the sectoral level, restrictions on transport and retail distribution services have the largest negative impact on exports of manufactures. |
| Keywords: | trade, productivity, services, manufacturing, competitiveness |
| JEL: | F14 D24 L80 |
| Date: | 2015–01 |
| URL: | http://d.repec.org/n?u=RePEc:rsc:rsceui:2015/07&r=eff |
| By: | Jorge Galán; Sofía B. Ramos; Helena Veiga |
| Abstract: | This paper studies the efficiency of a sample of mutual funds that invest in the United States. Estimating a production function using Bayesian stochastic frontier analysis, we find evidence that the underlying technology presents economies of scale both at the fund and firm level. We also find evidence that informational asymmetries affect efficiency. Funds that invest domestically are likely to be more efficient than foreign funds investing in the US. Moreover, an inspection at the distribution process shows that funds sold directly to investors rather than by financial intermediaries are more efficient. The level of inefficiency persistence is overall high.Persistency of inefficiency is particularly higher for ethical funds, funds oriented to large firm sand lower in funds oriented to growth firms. The analysis done in two separate periods also shows that the efficiency of the funds changes. In particular, funds oriented to non-ethical, small and growth firms become more efficient over the period. Finally, funds' efficiency decreases during global financial crisis, but at the end of the sample period some funds recover and their efficiency levels are higher than those registered before the financial crisis. Our results have implications for investors' decisions in mutual funds. |
| Keywords: | Economies of Scale , Efficiency , Mutual Funds , Persistence , Stochastic Frontier Analysis |
| JEL: | C11 C23 C51 G11 G14 G15 G24 |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:cte:wsrepe:ws1517&r=eff |
| By: | Daan Steenkamp (Reserve Bank of New Zealand) |
| Abstract: | This note describes the construction of estimates of relative levels of multifactor productivity (MFP) in the `traded' and `non-traded' sectors in New Zealand and 18 other economies. Industry comparisons of MFP levels over time are constructed using relative productivity at a base year adjusted for annual industry MFP growth. Relative industry MFP level estimates are grouped together to estimate relative `traded' and `non-traded' levels. The estimates suggest that there are several small industries where New Zealand has relatively high MFP levels. But estimates of New Zealand's overall traded and non-traded MFP suggest that New Zealand has performed poorly relative to its peers over the last several decades. These estimates are useful not only for assessing New Zealand's relative productivity performance, but also for other empirical analysis. Subsequent research uses these estimates to explore the relationship between the real exchange rate and relative traded and non-traded productivity for New Zealand and the other countries included in this study. |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:nzb:nzbans:2015/04&r=eff |
| By: | Bayo-Moriones, Alberto (University of Navarra); Galdon-Sanchez, Jose Enrique (Universidad Pública de Navarra); Martinez-de-Morentin, Sara (Universidad Pública de Navarra) |
| Abstract: | This study addresses the factors that determine the intensity of pay for performance schemes. The results indicate that the use of individual and group incentives boost intensity, whereas plant or firm pay for performance do not seem to affect the variable of interest. In addition, the adoption of measures of results, such as productivity or quality, has a significant positive effect on intensity. On the contrary, measures of human resource management outcomes, subjective measures and financial measures are not significant or have a negative effect on the intensity of pay for performance. |
| Keywords: | pay for performance |
| JEL: | J30 M52 M12 |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp9243&r=eff |