nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2021‒08‒30
fourteen papers chosen by



  1. The Impact of Information and Communication Technology on the Productivity and Efficiency of Smallholder Farms in China By Kang, Shijia; Wimmer, Stefan; Sauer, Johannes
  2. The Productivity Puzzle in Network Industries: Evidence from the Energy Sector By Victor Ajayi; Geoffroy Dolphin; Karim Anaya; Michael Pollitt
  3. U.S. agricultural banks’ efficiency under COVID-19 Pandemic conditions: A two-stage DEA analysis By Gao, Penghui; Secor, William; Escalante, Cesar L.
  4. Density and Allocative Efficiency in Turkish Manufacturing By Orhun Sevinc
  5. How do Technical Education and Vocational Training Affect Labour Productivity in India? By Seema Sangita
  6. Farm Labor Productivity and Mechanization By Hamilton, Stephen F.; Richards, Timothy J.; Shafran, Aric; Vasilaky, Kathryn
  7. Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms By K Hervé Dakpo; Laure Latruffe; Yann Desjeux; Philippe Jeanneaux
  8. Agglomeration Economies and Labour Misallocation in Cote d’Ivoire By BAH, Mamadou Mouminy
  9. Outstanding in the Field: Impacts of Public Small Grains Breeding in Virginia By Garber, Benjamin F.; Alwang, Jeffrey; Norton, George W.
  10. Causal Impact Of European Union Emission Trading Scheme On Firm Behaviour And Economic Performance: A Study Of German Manufacturing Firms By Nitish Gupta; Jay Shah; Satwik Gupta; Ruchir Kaul
  11. The Indian manufacturing sector: finance, investment and performance of firms. By Agarwal, Manmohan; Azim, Rumi
  12. The productivity puzzle in business services By Alexander S. Kritikos; Alexander Schiersch; Caroline Stiel
  13. Evaluating the Profitability of a Small Grain Enterprise and a Novel Pull Behind Combine for Small Scale Farming in Western Wisconsin By Howry, Sierra S.; Jungbluth, Angela; Ratliff, English L.
  14. Why is productivity slowing down? By Lafond, François; Goldin, Ian; Koutroumpis, Pantelis; Winkler, Julian

  1. By: Kang, Shijia; Wimmer, Stefan; Sauer, Johannes
    Keywords: Productivity Analysis, Marketing, Production Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312920&r=
  2. By: Victor Ajayi (EPRG, CJBS, University of Cambridge); Geoffroy Dolphin (EPRG, CJBS, University of Cambridge); Karim Anaya (EPRG, CJBS, University of Cambridge); Michael Pollitt (EPRG, CJBS, University of Cambridge)
    Keywords: Total factor productivity, growth accounting, regulation, energy networks, climate policy
    JEL: D24 O47 H23
    Date: 2020–07
    URL: http://d.repec.org/n?u=RePEc:enp:wpaper:eprg2021&r=
  3. By: Gao, Penghui; Secor, William; Escalante, Cesar L.
    Keywords: Agricultural Finance, Agribusiness, Productivity Analysis
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312923&r=
  4. By: Orhun Sevinc
    Abstract: Using administrative data covering the economic geography of Turkish manufacturing firms I show that density increases a location’s productivity through both typical firm productivity and stronger association of firm size and productivity—a measure of within-sector allocative efficiency. IV estimates suggest a density elasticity of allocative efficiency that accounts for about one third of the overall impact of density on productivity. A model with decreasing returns to scale and convex cost of avoidance from the burden of regulations can explain the estimated density-allocative efficiency relationship on the grounds that denser locations provide lower degree of internal diseconomies.
    Keywords: Density, Allocative efficiency, Cities in developing economies
    JEL: R10
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:tcb:wpaper:2125&r=
  5. By: Seema Sangita (TERI School of Advanced Studies)
    Abstract: Educationists have had long debates on the efficacy of traditional forms of education versus vocational training. Even as India grapples with the challenges of improving the quality of primary and secondary education, there appears to be a policy shift in India, favouring vocational trainings that target the skill development of workers. This paper tries to analyse the impact of two types of technical education—one leading to an engineering degree or diploma and the other, to vocational training in selected fields such as Information and Communications Technology (ICT)— on firms operating in the manufacturing sector in India. A Cobb Douglas production function has been enhanced to incorporate education and training in order to understand the implications of the latter on firm performance. The results show that when a larger number of workers acquire technical education that leads to a degree or diploma in engineering, there is a positive impact on the performance of firms. In contrast, participation in vocational training programmes pertaining to similar disciplines has an insignificant effect on firms.
    Keywords: Technical Education, Vocational Education, Skills, Employability, Productivity, Digital Skills, ICT Skills
    JEL: J4 J24 O1
    Date: 2021–06
    URL: http://d.repec.org/n?u=RePEc:nca:ncaerw:125&r=
  6. By: Hamilton, Stephen F.; Richards, Timothy J.; Shafran, Aric; Vasilaky, Kathryn
    Keywords: Agricultural and Food Policy, Agribusiness, Productivity Analysis
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312678&r=
  7. By: K Hervé Dakpo (ECO-PUB - Economie Publique - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, D-ERDW - Department of Earth Sciences [Swiss Federal Institute of Technology - ETH Zürich] - ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]); Laure Latruffe (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique); Yann Desjeux (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique); Philippe Jeanneaux (VAS - VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement, Territoires - Territoires - AgroParisTech - VAS - VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement - AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UCA - Université Clermont Auvergne)
    Abstract: Our objective is to extend the latent class stochastic frontier (LCSFM) model to compute productivity change, using the robust transitive productivity Fare-Primont index. The application is to three types of grazing livestock farms in France over the period 2002-2016. The LCSFM identified two classes of farms, intensive farms and extensive farms. Results indicate that productivity change and its components show only small differences between the LCSFM and the pooled model that does not account for heterogeneity. Differences across classes exist, but depend on farm type.
    Abstract: Notre objectif est d'étendre le modèle de frontière stochastique à classe de latence (LCSFM) pour calculer le changement de productivité, en utilisant l'indice de productivité transitif robuste de Fare-Primont. L'application porte sur trois types d'exploitations d'élevage herbivore en France sur la période 2002-2016. Le LCSFM a identifié deux classes d'exploitations, les exploitations intensives et les exploitations extensives. Les résultats indiquent que la variation de la productivité et ses composantes ne présentent que de faibles différences entre le LCSFM et le modèle groupé qui ne tient pas compte de l'hétérogénéité. Les différences entre les classes existent, mais dépendent du type d'exploitation.
    Keywords: Efficiency,Färe-Primont,France,Grazing livestock farms,Latent class stochastic frontier,Productivity
    Date: 2021–02–04
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-03280138&r=
  8. By: BAH, Mamadou Mouminy
    Abstract: This paper analyses the effects of agglomeration economies on firm labour misallocation, using the Ivorian firm data from 2013-2016. After measuring the degree of firm labour misallocation in the first step, we assess the level of labour misallocation in denser regions in the second step. The results show on the one hand that the average labour misallocation (labour gap) at the firm level is 2,825,887 FCFA ($5,137.97 ) over the period 2013-2016 and this gap has significantly decreased over years. On the other hand, firms located in denser regions exhibit lower labour misallocation. In terms of the magnitude, both localisation and urbanisation economies are large and statistically significant. A 10% increase in the degree of localisation in a region reduces the labour misallocation by 7.41% on average, while a 10% increase in the degree of urbanisation alters the labour misallocation by 4.26%. These findings confirm that labour misallocation has a geographical dimension, in addition to the firm characteristics. A sound policy needs to accounts for the spatial distribution of firms and the creation of active poles of development in major Ivorian regions.
    Keywords: Localisation, Urbanisation, Misallocation, Total factor productivity, firm-level data
    JEL: D24 L25 O4 R3
    Date: 2021–08–15
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:109314&r=
  9. By: Garber, Benjamin F.; Alwang, Jeffrey; Norton, George W.
    Keywords: Productivity Analysis, Teaching/Communication/Extension/Profession, Production Economics
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312730&r=
  10. By: Nitish Gupta; Jay Shah; Satwik Gupta; Ruchir Kaul
    Abstract: In this paper, we estimate the causal impact (i.e. Average Treatment Effect, ATT) of the EU ETS on GHG emissions and firm competitiveness (primarily measured by employment, turnover, and exports levels) by combining a difference-in-differences approach with semi-parametric matching techniques and estimators an to investigate the effect of the EU ETS on the economic performance of these German manufacturing firms using a Stochastic Production Frontier model.
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2108.07163&r=
  11. By: Agarwal, Manmohan (Centre for International Trade and Development, Jawaharlal Nehru University); Azim, Rumi (Centre for International Trade and Development, Jawaharlal Nehru University)
    Abstract: The paper tests the hypothesis that financial stress caused the stagnation in the manufacturing sector, using firm level data on a sample of 804 large, mid, and small cap manufacturing firms for 15 years from 2005 to 2019. We analyse the trend in the financial indicators and estimate dynamic panel data regression using a two-step GMM method. We do not find substantial for financial stress to be a major determinant of the investment slowdown in these firms. Our results support the Pecking order theory, particularly for larger firms. In addition, we find that the declining growth in sales is a major determinant in explaining the slowdown in fixed investments and profits. For small cap firms, the size of the firms also matters. We therefore suggest that measures to increase demand can help in reviving the sales growth of firms and thereby private investments and profits.
    Keywords: Capital structure ; Investment ; Profitability ; Manufacturing ; India
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:npf:wpaper:21/339&r=
  12. By: Alexander S. Kritikos (DIW Berlin, University of Potsdam, IZA Bonn, IAB Nuremberg); Alexander Schiersch (DIW Berlin); Caroline Stiel (DIW Berlin)
    Abstract: In Germany, the productivity of professional services, a sector dominated by micro and small firms, declined by 40 percent between 1995 and 2014. This productivity decline also holds true for professional services in other European countries. Using a German firm-level dataset of 700,000 observations between 2003 and 2017, we analyze this largely uncovered phenomenon among professional services, the 4th largest sector in the EU15 business economy, which provide important intermediate services for the rest of the economy. We show that changes in the value chain explain about half of the decline and the increase in part-time employment is a further minor part of the decline. In contrast to expectations, the entry of micro and small firms, despite their lower productivity levels, is not responsible for the decline. We also cannot confirm the conjecture that weakening competition allows unproductive firms to remain in the market.
    Keywords: business services, labor productivity, productivity slowdown
    JEL: L84 O47 D24 L11
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:pot:cepadp:37&r=
  13. By: Howry, Sierra S.; Jungbluth, Angela; Ratliff, English L.
    Keywords: Productivity Analysis, Marketing, Agricultural Finance
    Date: 2021–08
    URL: http://d.repec.org/n?u=RePEc:ags:aaea21:312668&r=
  14. By: Lafond, François; Goldin, Ian; Koutroumpis, Pantelis; Winkler, Julian
    Abstract: We review recent research on the slowdown of labor productivity and examine the contribution of different explanations to this decline. Comparing the post-2005 period with the preceding decade for 5 advanced economies, we seek to explain a slowdown of 0.8 to 1.8pp. We trace most of this to lower contributions of TFP and capital deepening, with manufacturing accounting for the biggest sectoral share of the slowdown. No single explanation accounts for the slowdown, but we have identified a combination of factors which taken together account for much of what has been observed. In the countries we have studied, these are mismeasurement, a decline in the contribution of capital per worker, lower spillovers from the growth of intangible capital, the slowdown in trade, and a lower growth of allocative efficiency. Sectoral reallocation and a lower contribution of human capital may also have played a role in some countries. In addition to our quantitative assessment of explanations for the slowdown, we qualitatively assess other explanations, including whether productivity growth may be declining due to innovation slowing down.
    JEL: O40 E66 D24
    Date: 2021–05
    URL: http://d.repec.org/n?u=RePEc:amz:wpaper:2021-12&r=

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