nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2021‒10‒11
thirteen papers chosen by

  1. Productivity and Efficiency in Uruguay: A Stochastic Approach By García-Suarez, Federico
  2. Analysis of Agricultural Productivity in Paraguay: A MICRO Econometric Approach By Gatti, Nicolás
  3. Data Sharpening for improving CLT approximations for DEA-type efficiency estimators By Bao Hoang Nguyen; Léopold Simar; Valentin Zelenyuk
  4. Bridging the Divide? Bayesian Artificial Neural Networks for Frontier Efficiency Analysis By Mike Tsionas; Christopher F. Parmeter; Valentin Zelenyuk
  5. Misallocation in Indian Agriculture By Marijn Bolhuis; Swapnika Rachapalli; Diego Restuccia
  6. Inference in the Nonparametric Stochastic Frontier Model By Christopher F. Parameter; Léopold Simar; Ingrid Van Keilegom; Valentin Zelenyuk
  7. Are small farms really more productive than large farms? By Fernando Aragon; Diego Restuccia; Juan Pablo Rud
  8. Structural Change and Productivity Growth in Europe - Past, Present and Future By Georg Duernecker; Miguel Sanchez-Martinez
  9. Efficiency of judicial conciliation activities in French courts: Evidence from a bad-output Data Envelopment Analysis (DEA) framework By Matthieu Belarouci
  10. Why do firms compete on price comparison websites? The impact on productivity, profits, and wages By Lindgren, Charlie; Li, Yujiao; Rudholm, Niklas
  11. Environmental Drivers of Agricultural Productivity Growth: CO2 Fertilization of US Field Crops By Charles A. Taylor; Wolfram Schlenker
  12. Application of DEA in International Market Selection for the export of products from Spain By Safa El Kefi
  13. Information Technology and Returns to Scale By D. LASHKARI; A. BAUER; J. BOUSSARD

  1. By: García-Suarez, Federico
    Keywords: Productivity Analysis
    Date: 2021–08
  2. By: Gatti, Nicolás
    Keywords: Productivity Analysis
    Date: 2021–08
  3. By: Bao Hoang Nguyen (School of Economics, University of Queensland, Brisbane, Qld 4072, Australia); Léopold Simar (Institut de Statistique, Biostatistique et Sciences Actuarielles, Université Catholique de Louvain.); Valentin Zelenyuk (School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia)
    Abstract: Asymptotic statistical inference on productivity and production efficiency, using nonparametric envelopment estimators, is now available thanks to the basic central limit theorems (CLTs) developed in Kneip et al. (2015). They provide asymptotic distributions of averages of Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH) estimators of production efficiency. As shown in their Monte-Carlo experiments, due to the curse of dimensionality, the accuracy of the normal approximation is disappointing when the sample size is not large enough. Simar & Zelenyuk (2020) have suggested a simple way to improve the approximation by using a more appropriate estimator of the variances. In this paper we suggest another way to improve the approximation, by smoothing out the spurious values of efficiency estimates when they are in a neighborhood of 1. This results in sharpening the data for observations near the estimated efficient frontier. The method is very easy to implement and does not require more computations than the original method. We compare our approach using Monte-Carlo experiments, both with the basic method and with the improved method suggested in Simar & Zelenyuk (2020) and in both cases we observe significant improvements. We show also that the Simar & Zelenyuk (2020) idea can also be adapted to our sharpening method, bringing additional improvements. We illustrate the method with some real data sets.
    Keywords: Data Envelopment Analysis (DEA), Free Disposal Hull (FDH), Production Efficiency, Statistical Inference
    Date: 2021–09
  4. By: Mike Tsionas (Montpellier Business School Université de Montpellier, Montpellier Research in Management and Lancaster University Management School); Christopher F. Parmeter (Miami Herbert Business School, University of Miami, Miami FL); Valentin Zelenyuk (School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia)
    Abstract: The literature on firm efficiency has seen its share of research comparing and contrasting Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), the two workhorse estimators. These studies rely on both Monte Carlo experiments and actual data sets to examine a range of performance issues which can be used to elucidate insights on the benefits or weaknesses of one method over the other. As can be imagined, neither method is universally better than the other. The present paper proposes an alternative approach that is quite flexible in terms of functional form and distributional assumptions and it amalgamates the benefits of both DEA and SFA. Specifically, we bridge these two popular approaches via Bayesian Artificial Neural Networks. We examine the performance of this new approach using Monte Carlo experiments. The performance is found to be very good, comparable or often better than the current standards in the literature. To illustrate the new techniques, we provide an application of this approach to a recent data set of large US banks.
    Keywords: Simulation; OR in Banking; Stochastic Frontier Models; Data Envelopment Analysis; Flexible Functional Forms.
    Date: 2021–06
  5. By: Marijn Bolhuis; Swapnika Rachapalli; Diego Restuccia
    Abstract: We exploit substantial variation in land-market institutions across Indian states and detailed micro household-level panel data to assess the effect of distortions in land rental markets on agricultural productivity. We provide empirical evidence that states with more rental-market activity feature less misallocation and reallocate land more efficiently over time. We develop a model of heterogeneous farms and land rentals to estimate land-market distortions in each state. Land rentals have substantial positive effects on agricultural productivity: an efficient reallocation of land increases agricultural productivity by 38 percent on average and by more than 50 percent in states with highly distorted rental markets. Both farm and state-level land market distortions are quantitatively important, with state-level wedges accounting for a significant fraction of rental market participation differences across states. Land market distortions contribute about one-third to the large differences in agricultural total factor productivity across Indian states.
    Keywords: Productivity, agriculture, distortions, land rentals, states, India.
    JEL: O4 O5 O11 O14 E01 E13
    Date: 2021–10–05
  6. By: Christopher F. Parameter (Miami Herbert Business School, University of Miami); Léopold Simar (Institut de Statistique, Biostatistique et Sciences Actuarielles, Université Catholique de Louvain.); Ingrid Van Keilegom (Institut de Statistique, Biostatistique et Sciences Actuarielles, Université Catholique de Louvain.); Valentin Zelenyuk (School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia)
    Abstract: This paper is the first in the literature to discuss in detail how to conduct various types of inference in the stochastic frontier model when it is estimated using nonparametric methods. We discuss a general and versatile inferential technique that allows for a range of practical hypotheses of interest to be tested. We also discuss several challenges that currently exist in this framework in an e ort to alert researchers to potential pitfalls. Namely, it appears that when one wishes to estimate a stochastic frontier in a fully nonparametric framework, separability between inputs and determinants of ineciency is an essential ingredient for the correct empirical size of a test. We showcase the performance of the test with a variety of Monte Carlo simulations.
    Keywords: Stochastic Frontier Analysis, Efficiency, Productivity Analysis, Local-Polynomial Least-Squares
    JEL: C1 C14 C13
    Date: 2021–09
  7. By: Fernando Aragon; Diego Restuccia; Juan Pablo Rud
    Abstract: This paper shows that using yields may not be informative of the relationship between farm size and productivity in the context of small-scale farming. This occurs because, in addition to productivity, yields pick up size-dependent market distortions and decreasing returns to scale. As a result, a positive relationship between farm productivity and land size may turn negative when using yields. We illustrate the empirical relevance of this issue with microdata from Uganda and show similar findings for Peru, Tanzania, and Bangladesh. In addition, we show that the dispersion in both measures of productivity across farms of similar size is so large that it renders farm size an ineffective indicator for policy targeting. Our findings stress the need to revisit the empirical evidence on the farm size-productivity relationship and its policy implications.
    Keywords: Farm size, productivity, yields, land markets, distortions, agriculture, policy.
    JEL: O12 O13 Q12 Q15
    Date: 2021–10–01
  8. By: Georg Duernecker; Miguel Sanchez-Martinez
    Abstract: This paper studies the effect of structural change on the historical path of aggregate labor productivity growth for a large sample of European countries, and it builds a quantitative multi-sector growth model to analyze the potential impact that structural change may have on future productivity growth. We document that the observed reallocation of economic activity since the 1970s towards the service sector has exerted a strongly negative effect on aggregate productivity growth in most European countries. Moreover, we perform a quantitative analysis to show that the expected path of structural change might continue to have a sizable dent on future productivity growth in Europe. By contrast, the impact in the U.S. is expected to rapidly diminish. We show that this differential result can be explained by the large expansion, in Europe, of certain service sub-sectors characterized by stagnant productivity.
    Keywords: structural change, productivity growth, Baumol’s cost disease, service sector, European Union
    JEL: O41 O47 O52
    Date: 2021
  9. By: Matthieu Belarouci (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR1 - Université de Rennes 1 - UNIV-RENNES - Université de Rennes - CNRS - Centre National de la Recherche Scientifique, ANTHROPO-LAB - Laboratoire d'Anthropologie Expérimentale - ICL - Institut Catholique de Lille - UCL - Université catholique de Lille)
    Abstract: This paper uses a DEA bad-output framework to assess the efficiency of court settlement activities and examine how efficiency depends on both the characteristics of the conciliators and on institutional factors. The empirical analysis relies on court level data of conciliation activities in French civil magistrate courts between 2010 and 2017. Results show that efficiency is positively related to factors that foster the demand for settlement. More efficient courts are more prone to involving conciliation in the judicial circuit. Finally, the professional background and previous experience of conciliators are positively related to efficiency.
    Keywords: Efficiency of justice,conciliation,data envelopment analysis
    Date: 2021–01–20
  10. By: Lindgren, Charlie (Dalarna University, 791 88 Falun, Sweden); Li, Yujiao (Dalarna University, 791 88 Falun, Sweden); Rudholm, Niklas (Institute of Retail Economics (Handelns Forskningsinstitut))
    Abstract: This paper investigates how firm entry into a price comparison website marketplace affects firm productivity, profits, and wages. We want to answer the key research question: Why do firms compete on price comparison websites? A substantial literature indicates that competition in such marketplaces is fierce, leading to lower prices for products sold. We suggest that participation in these marketplaces also leads to increased productivity, i.e., output increases when holding constant the level of inputs used. This leads to increased profits, motivating firms to enter price comparison websites despite fierce competition. Our results indicate that for the full sample of firms, PriceSpy participation increases output by almost 12% when holding the level of inputs constant. Also, investigation of who gains from the increased productivity shows that, for entering firms, operating profits increase by 9% and gross wages by 14% when studying the full sample of firms. That labor gains more from PriceSpy participation is even clearer when studying the impact on wholesale and retail firms separately. For those firms, gross wages increased by 16–17% after entry, while no statistically significant impact was found regarding operating profits.
    Keywords: Online retailing; e-commerce; price comparison websites; productivity; value added.
    JEL: D22 D24 D33 L81
    Date: 2020–09–01
  11. By: Charles A. Taylor; Wolfram Schlenker
    Abstract: We assess the CO 2 fertilization effect on US agriculture using spatially-varying CO 2 data from NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite covering the majority of US cropland under actual growing conditions. This study complements the many CO 2 enrichment experiments that have found important interactions between CO 2 and local environmental conditions in controlled settings. We use three empirical strategies: (i) a panel of CO 2 anomalies and county yields, (ii) a panel of spatial first-differences between neighboring counties, and (iii) a cross-sectional spatial first-difference. We find consistently high fertilization effects: a 1 ppm increase in CO 2 equates to a 0.5%, 0.6%, and 0.8% yield increase for corn, soybeans, and wheat, respectively. Viewed retrospectively, 10%, 30%, and 40% of each crop's yield improvements since 1940 are attributable to rising CO 2 .
    JEL: N52 Q11 Q54
    Date: 2021–10
  12. By: Safa El Kefi
    Abstract: This article presents a Benchmarking methodology to support decision-making for international market selection (IMS). In order to do so, we will be using an output-oriented Data Envelopment Analysis (DEA) model. This methodology considers multiple variables validated with a correlation analysis. The methodology is applied to all of the products directly exported from Spain, it takes into consideration different Inputs variables and returns us the efficient and regions generating higher benefits to access international markets with the lowest costs possible.
    Date: 2021–09
  13. By: D. LASHKARI (Boston College); A. BAUER (Insee - Crest); J. BOUSSARD (Commission européenne - Crest)
    Abstract: Relying on a novel dataset on hardware and software investments in the universe of French firms, we document a robust within-industry correlation between firm size and the intensity of IT demand. To explain this fact, we argue that the relative marginal product of IT inputs may rise with firm scale, since IT helps firms deal with organizational limits to scale. We propose a general equilibrium model of industry dynamics that features nonhomothetic production functions compatible with this mechanism. Estimating this production function, we identify the nonhomotheticity of IT demand and find an elasticity of substitution between IT and non- IT inputs that falls below unity. Under the estimated model parameters, the cross-sectional predictions of the model match the observed relationship of firm size with IT intensity (positive) and labor share (negative). In addition, in response to the fall in the relative price of IT inputs in post-1990 France, the model explains about half of both the observed rise in market concentration and the market reallocations toward low-labor-share firms.
    Keywords: information technology, labor share, competition, production function, nonhomotheticity.
    JEL: E10 E23 E25
    Date: 2020

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