nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2019‒02‒11
twelve papers chosen by
Angelo Zago
Università degli Studi di Verona

  1. Productivity and wage effects of firm-level collective agreements: Evidence from Belgian linked panel data By Andrea Garnero; Francois Rycx; Isabelle Terraz
  2. Labour productivity and firm-level TFP with technology-specific production functions By Michele Battisti; Filippo Belloc; Massimo Del Gatto
  3. Digitalisation and productivity: In search of the holy grail – Firm-level empirical evidence from EU countries By Peter Gal; Giuseppe Nicoletti; Theodore Renault; Stéphane Sorbe; Christina Timiliotis
  4. A Bayesian approach for correcting bias of data envelopment analysis estimators By Zervopoulos, Panagiotis; Emrouznejad, Ali; Sklavos, Sokratis
  5. Cluster externalities, firm capabilities, and the recessionary shock: How the macro-to-micro-transition shapes firm performance during stable times and times of crisis By Hundt, Christian; Holtermann, Linus; Steeger, Jonas; Bersch, Johannes
  6. Does Output Influence Productivity?-A Meta-Regression Analysis By Ludwig List
  7. What's Behind the Figures? Quantifying the Cross-Country Exporter Productivity Gap By Kozo Kiyota; Toshiyuki Matsuura; Lionel Nesta
  8. From Teacher Quality to Teaching Quality: Instructional Productivity and Teaching Practices in the US By Simon Briole
  9. Digital Dividend: Policies to Harness the Productivity Potential of Digital Technologies By Stéphane Sorbe; Peter Gal; Giuseppe Nicoletti; Christina Timiliotis
  10. Shape constrained kernel-weighted least squares: Estimating production functions for Chilean manufacturing industries By Yagi, Daisuke; Chen, Yining; Johnson, Andrew L.; Kuosmanen, Timo
  11. Robust Productivity Analysis: An application to German FADN data By Mathias Kloss; Thomas Kirschstein; Steffen Liebscher; Martin Petrick
  12. Do Financing Constraints Matter for the Direction of Technical Change in Energy R&D? By Joelle Noailly; Roger Smeets

  1. By: Andrea Garnero; Francois Rycx; Isabelle Terraz
    Abstract: How do firm-level collective agreements affect firm performance in a multi-level bargaining system? Using detailed Belgian linked employer-employee panel data, our findings show that firm agreements increase both wage costs and labour productivity (with respect to sector-level agreements). Relying on a recent approach developed by Bartolucci (2014), they also indicate that firm agreements exert a stronger impact on wages than on productivity, so that on average profitability is hampered. However, this rent-sharing effect only holds in sectors where firms are more concentrated. Firm agreements are thus mainly found to raise wages beyond labour productivity when the rents to be shared between workers and firms are relatively big. Overall, this suggests that firm-level agreements benefit both employers and employees – through higher productivity and wages – without being detrimental to firms’ gross profits.
    JEL: C33 J24 J31
    Date: 2019–02–11
  2. By: Michele Battisti; Filippo Belloc; Massimo Del Gatto
    Abstract: We investigate the technological dimension of productivity, presenting an empirical methodology based on mixture models to disentangle the labor productivity differences associated with the firm's choice of technology (BTFP) and those related to the firm's ability to exploit the adopted technology (WTFP). The estimation endogenously determines the number of technologies (in the sector) and degree of technology sharing across firms (i.e., for each firm, the probability of using a given technology). By using comparable data for about 35,000 firms worldwide distributed across 22 (two-digit) sectors, we show BTFP to be at least as important as WTFP in explaining the labor productivity gaps across firms. Intra-sectoral and inter-sectoral heterogeneity is substantial and, even in sectors in which BTFP dominates on average, we find a considerable number of firms for which labor productivity is mostly determined by the ability to use the adopted technology. Hence, dissecting the labor productivity gaps is crucial to achieving more targeted innovation policies. The estimated number of technologies ranges from one (in only three industries) to five, being three in most cases. The suggested estimation strategy takes simultaneity into account. The BTFP measure is unaffected by omitted price bias. The presence of BTFP dispersion can be associated with the action of frictions preventing firms from switching to superior and more productive technologies. Eliminating BTFP does not eliminate misallocation.
    Keywords: TFP, technology adoption, production function estimation, mixture models
    JEL: D24 O33 C29
    Date: 2019–01
  3. By: Peter Gal; Giuseppe Nicoletti; Theodore Renault; Stéphane Sorbe; Christina Timiliotis
    Abstract: This paper assesses how the adoption of a range of digital technologies affects firm productivity. It combines cross-country firm-level data on productivity and industry-level data on digital technology adoption in an empirical framework that accounts for firm heterogeneity. The results provide robust evidence that digital adoption in an industry is associated to productivity gains at the firm level. Effects are relatively stronger in manufacturing and routine-intensive activities. They also tend to be stronger for more productive firms and weaker in presence of skill shortages, which may relate to the complementarities between digital technologies and other forms of capital (e.g. skills, organisation, or intangibles). As a result, digital technologies may have contributed to the growing dispersion in productivity performance across firms. Hence, policies to support digital adoption should go hand in hand with creating the conditions to enable the catch-up of lagging firms, notably by easing access to skills.
    Keywords: cloud computing, digitalisation, high-speed internet, ICT, productivity, skills
    JEL: D24 J24 O33
    Date: 2019–02–12
  4. By: Zervopoulos, Panagiotis; Emrouznejad, Ali; Sklavos, Sokratis
    Abstract: The validity of data envelopment analysis (DEA) efficiency estimators depends on the robustness of the production frontier to measurement errors, specification errors and the dimension of the input-output space. It has been proven that DEA estimators, within the interval (0, 1], are overestimated when finite samples are used while asymptotically this bias reduces to zero. The non-parametric literature dealing with bias correction of efficiencies solely refers to estimators that do not exceed one. We prove that efficiency estimators, both lower and higher than one, are biased. A Bayesian DEA method is developed to correct bias of efficiency estimators. This is a two-stage procedure of super-efficiency DEA followed by a Bayesian approach relying on consistent efficiency estimators. This method is applicable to ‘small’ and ‘medium’ samples. The new Bayesian DEA method is applied to two data sets of 50 and 100 E.U. banks. The mean square error, root mean square error and mean absolute error of the new method reduce as the sample size increases.
    Keywords: Data envelopment analysis Super-efficiency Bayesian methods Statistical inference Banking
    JEL: C11 C18 C44 M11
    Date: 2019–01
  5. By: Hundt, Christian; Holtermann, Linus; Steeger, Jonas; Bersch, Johannes
    Abstract: In this paper, we examine the macro-to-micro-transition of cluster externalities to firms and how it is affected by the macroeconomic instability caused by the recessionary shock of 2008/2009. Using data from 16,166 manufacturing and business services firms nested in 390 German regions, we employ within-firm regression techniques to estimate the impact of cross-level interactions between firm- and cluster-level determinants on phase-related differences in firm performance between a pre-crisis (2004-2007) and a crisis period (2009-2011). The empirical results validate the existence of a macro-to-micro-transition that evolves best in the case of broad firm-level capabilities and variety-driven externalities. Furthermore, the results indicate that the transition strongly depends on the macroeconomic cycle. While the transition particularly benefits from a stable macroeconomic environment (2004-2007), its mechanisms are interrupted when being exposed to economic turmoil (2009-2011). Yet, the crisis-induced interruption of the transition is mainly restricted to the national recession in 2009. As soon as the macroeconomic pressure diminishes (2010-2011), we observe a reversion of the transmission mechanisms to the pre-crisis level. Our study contributes to the existing literature by corroborating previous findings that the economic performance of firms depends on a working macro-to-micro transition of external resources, which presupposes sufficient cluster externalities and adequate firm-level combinative capabilities. In contrast to previous studies on this topic, the transition mechanism is not modeled as time-invariant. Instead, it is coupled to the prevailing macroeconomic regime.
    Keywords: Macro-to-micro-transition, combinative capabilities, agglomeration economies, cluster-level externalities, unrelated variety, related variety, macroeconomic regimes, Great Recession, eco-nomic resilience
    JEL: C33 R11 R58
    Date: 2019–01–28
  6. By: Ludwig List (CEPN - Centre d'Economie de l'Université Paris Nord - UP13 - Université Paris 13 - USPC - Université Sorbonne Paris Cité - CNRS - Centre National de la Recherche Scientifique)
    Abstract: The goal of this paper is to conduct a meta-regression analysis (MRA hereafter) regarding the effects of the Kaldor-Verdoorn effect-the relation between output/demand and productivity. The Kaldor-Verdoorn effect has been subject to many econometric studies and while the overwhelming majority of them finds a positive overall effect, there is no consensus on its size-the results vary quite a bit, especially according to the chosen econometric specification. This MRA estimates a 'true value' of the Kaldor-Verdoorn effect without interference from potential publication selection bias via the use of multivariate MRA. A series of moderator variables is used to check for their effect of excess variation, including amongst others the year of publication, the sectors and the countries studied. This MRA study uses available data from 22 published studies with 303 estimations of the Kaldor-Verdoorn effect. When examining the primary literature as a whole, there seems to be publication bias. While there seems to exist a genuine Kaldor-Verdoorn effect, its size varies considerably depending on the specification chosen.
    Keywords: Kaldor-Verdoorn effect,Productivity,Meta-regression analysis,Effective demand,Learning by doing
    Date: 2018–11–14
  7. By: Kozo Kiyota (Keio Economic Observatory, Keio University); Toshiyuki Matsuura (Keio Economic Observatory, Keio University); Lionel Nesta (1. Universite Cote d'Azur, 2. OFCE Sciences Po. Paris, 3. SKEMA Business School)
    Abstract: We present a simple framework that allows us to examine the cross-country exporter productivity gap without accessing confidential firm-level data. This gap depends on the three readily available statistics: the productivity gap between two countries; the export participation rates; and export premia. This gap holds irrespective of the distribution underlying firm productivity and irrespective of the presence of fixed costs. Under specific conditions, allocative efficiency may affect the exporter productivity gap. The empirical analysis globally validates this exercise.
    Keywords: International productivity gap, Export premia, Competitiveness, Meta analysis
    JEL: F1 D24
    Date: 2018–12–21
  8. By: Simon Briole (PSE - Paris School of Economics, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Panthéon-Sorbonne - ENS Paris - École normale supérieure - Paris - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique)
    Keywords: test scores,education,TIMSS,teacher quality,teaching practices,instruction time
    Date: 2019–01
  9. By: Stéphane Sorbe; Peter Gal; Giuseppe Nicoletti; Christina Timiliotis
    Abstract: This paper presents a range of policies to enhance adoption of digital technologies and firm productivity. It quantifies illustratively the effect of policy changes by combining the results of two recent OECD analyses on the drivers of adoption and their productivity benefits. Increasing access to high-speed internet, upgrading technical and managerial skills and implementing product and labour market reforms to facilitate the reallocation of resources in the economy are found to be the main factors supporting the efficient adoption of a selection of digital technologies. The most productive firms have benefitted relatively more from digitalisation in the past, contributing to a widening productivity gap with less productive firms. Policies should create the conditions for efficient adoption by less productive firms, which would help them to catch up, achieving a double dividend in terms of growth and inclusiveness. Enhancing skills has a key role to play in this area since less productive firms suffer relatively more from skill shortages.
    Keywords: competition, digitalisation, dispersion, ICT, productivity, regulation, skills
    JEL: D24 J24 O33
    Date: 2019–02–12
  10. By: Yagi, Daisuke; Chen, Yining; Johnson, Andrew L.; Kuosmanen, Timo
    Abstract: In this paper we examine a novel way of imposing shape constraints on a local polynomial kernel estimator. The proposed approach is referred to as Shape Constrained Kernel-weighted Least Squares (SCKLS). We prove uniform consistency of the SCKLS estimator with monotonicity and convexity/concavity constraints and establish its convergence rate. In addition, we propose a test to validate whether shape constraints are correctly specified. The competitiveness of SCKLS is shown in a comprehensive simulation study. Finally, we analyze Chilean manufacturing data using the SCKLS estimator and quantify production in the plastics and wood industries. The results show that exporting firms have significantly higher productivity
    Keywords: Local Polynomials; Kernel Estimation; Multivariate Convex Regression; Nonparametric regression; Shape Constraints
    JEL: C1
    Date: 2018–01–23
  11. By: Mathias Kloss; Thomas Kirschstein; Steffen Liebscher; Martin Petrick
    Abstract: Sources of bias in empirical studies can be separated in those coming from the modelling domain (e.g. multicollinearity) and those coming from outliers. We propose a two-step approach to counter both issues. First, by decontaminating data with a multivariate outlier detection procedure and second, by consistently estimating parameters of the production function. We apply this approach to a panel of German field crop data. Results show that the decontamination procedure detects multivariate outliers. In general, multivariate outlier control delivers more reasonable results with a higher precision in the estimation of some parameters and seems to mitigate the effects of multicollinearity.
    Date: 2019–02
  12. By: Joelle Noailly; Roger Smeets
    Abstract: The objective of this study is to examine the impact of firms’ financing constraints on innovation activities in renewable (REN) versus fossil-fuel (FF) technologies. Our empirical methodology relies on the construction of a firm-level dataset for 1,300 European firms over the 1995-2009 period combining balance-sheet information linked with patenting activities in REN and FF technologies. We estimate the importance of the different types of financing (e.g. cash flow, long-term debt, and stock issues) on firms’ patenting activities for the different samples of firms. We use count estimation techniques commonly used for models with patent data and control for a large set of firm-specific controls and market developments in REN and FF technologies. We find evidence for a positive impact of internal finance on patenting activities for the sample of firms specialized in REN innovation, while we find no evidence of this link for other firms, such as firms conducting FF innovation or large mixed firms conducting both REN and FF innovation. Hence, financing constraints matter for firms specialized in REN innovation but not for other firms. Our results have important implications for policymaking as the results emphasize that small innovative newcomers in the field of renewable energy are particularly vulnerable to financing constraints.
    Keywords: R&D;.; Financing constraints; renewable energy
    JEL: O14 O33 Q41 Q42
    Date: 2019–01–31

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