nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2018‒08‒20
fifteen papers chosen by

  1. Estimating Input-Mix Efficiency in a Parametric Framework: Application to State-Level Agricultural Data for the United States By Shabbir Ahmad
  2. Productivity of Slovenian Firms By Polona Domadenik; Bojan Ivanc; Denis Marinšek
  3. When losses turn into loans: the cost of undercapitalized banks By Francisca Rebelo; Laura Blattner; Luísa Farinha
  4. Performances management when modelling internal structure By Pinto, Claudio
  5. Technical Efficiency of Cassava's Producers in the Hinterland of Kinshasa, Democratic Republic of Congo By Kabibu Henry Muayila; Alain Kapemba Mujinga
  6. Firm Performance and Macro Forecast Accuracy By Mari Tanaka; Nicholas Bloom; Joel M. David; Maiko Koga
  7. Reflections on Agricultural R&D, Productivity, and the Data Constraint: Unfinished Business, Unsettled Issues By Alston, Julian M.
  8. Every cloud has a silver lining: micro-level evidence on the cleansing effects of the portuguese financial crisis By Daniel A. Dias; Carlos Robalo Marques
  9. Technical Efficiency and Its Determinants of the State-owned Enterprises in the Indonesian Manufacturing Industry By Maman Setiawan; Erni Tisnawati Sule
  10. Fear the walking dead: zombie firms, spillovers and exit barriers By Christian Osterhold; Ana Fontoura Gouveia
  11. Differences in Efficiency between Banks in Financial Conglomerates and other Banks in the Banking Sectors in Visegrad Countries By Iveta Palečková
  12. Does Outward Foreign Investment Matter for Canadian Productivity? Evidence from Greenfield Investments By Naveen Rai; Lena Suchanek; Maria Bernier
  13. Estimation of Dynamic Stochastic Frontier Model using Likelihood-based Approaches By Lai, Hung-pin; Kumbhakar, Subal C.
  14. Factor productivity in EU agriculture: A microeconometric perspective By Kloss, Mathias
  15. A Novel Approach to Verifying Evaluation of Agricultural Products with Productive Efficiency: An Empirical Study By Rouf, Abdur

  1. By: Shabbir Ahmad
    Abstract: This paper contributes to the productivity literature by demonstrating novel econometric methods to estimate input-mix efficiency (IME) in a parametric framework. Input-mix efficiency is defined as the potential improvement in productivity with change in input mix. Any change in input-mix (e.g., land to labor ratio) will result in change in productivity. We minimize a nonlinear input-aggregator function (e.g., Constant Elasticity of Substitution) to derive an expression for input-mix efficiency. We estimate a Bayesian stochastic frontier for obtaining mix efficiency using US state-level agricultural data for the period 1960 – 2004. We note significant variation in input-mix efficiency across the states and regions, attributable to diverse topographic, geographic and infrastructure conditions. Furthermore, comparisons of allocative and mix efficiencies provide insightful policy implications. For example, the production incentives such as taxes and subsidies could help farmers in adjusting their input mix in response to changes in input prices, which can affect the US agricultural productivity significantly. We provide a simple way of estimating mix efficiency in an aggregate-input, aggregate-output framework. This framework can be extended by i) using flexible functional forms; ii) introducing various time- and region-varying input aggregators; and iii) defining more sophisticated weights for input aggregators.
    Keywords: Agribusiness, Production Economics, Productivity Analysis
    Date: 2017–09–14
  2. By: Polona Domadenik; Bojan Ivanc; Denis Marinšek
    Abstract: We analyse productivity differences across non-financial Slovenian firms over the period 1994-2015. In particular, we investigate the impact of different factors (including size, ownership, investment activity and industry characteristics) on firms' total factor productivity (TFP), competitiveness and internationalisation. Large corporates appear to have the highest level of TFP, more than 50% above the average, and show stronger TFP growth. Exporting firms also show higher TFP growth than other firms, particularly after the recent crisis. Using a complete database of R&D subsidies over 1998-2015, the paper identifies R&Dintensive firms and investigates the impact of R&D investment on productivity and profitability. It is found that subsidies did not significantly increase firm-level productivity, once size, industry and year effects are taken into account. This could be because, during the recession (2009-2015), subsidies were granted to firms in difficulties.
    JEL: D22 D24 L25
    Date: 2018–03
  3. By: Francisca Rebelo; Laura Blattner; Luísa Farinha
    Abstract: We provide evidence that a weak banking sector has contributed to low productivity growth following the European sovereign debt crisis. An unexpected increase in capital requirements for a subset of Portuguese banks in 2011 provides a natural experiment to study the effects of reduced bank capital adequacy on productivity. Affected banks respond not only by cutting back on lending but also by reallocating credit to firms in financial distress with prior underreported loan loss provisioning. We develop a method to detect when banks delay loss reporting using detailed loan-level data. We then show that the credit reallocation leads to a reallocation of production factors across firms. A partial equilibrium exercise suggests that the resulting increase in factor misallocation accounts for 20% of the decline in productivity in Portugal in 2012.
    JEL: D24 E51 G21 G38 O47
    Date: 2018
  4. By: Pinto, Claudio
    Abstract: The performances management is a key issue for public as well as private organizations. The core of the performances management in the DEA context are essentially the relative efficiency measurement for organizations considered as a “black box” that use inputs to produce two or more outputs. In reality, organizations/ production process are comprised of a number of divisions/stages which performs different functions/tasks interacting among them. For these reasons modelling internal structures of organizations/production process allow to discover the inefficiency of individual divisions/stages. In this paper we estimate the relative efficiency of a production process once modelling its internal structure with a network structure of three divisions/stages interrelated among them. To outline the differences in the performances management in the two cases (“black box” vs network structure) we compare they empirical cumulative distribution functions.
    Keywords: network data envelopment analysis, modelling internal structure, performance management, private and public organizations
    JEL: C14 C67 D20 L0
    Date: 2018–07–14
  5. By: Kabibu Henry Muayila (Université Protestante au Congo); Alain Kapemba Mujinga (Université Protestante au Congo)
    Abstract: This study aims at identifying the main determinants of efficiency of cassava producers in the hinterland of Kinshasa. Data used were from a sample 202 farm-household survey randomly selected. The Data Envelopment Analysis was applied to compute the efficiency score. The truncated regression model was used to identify factors associated with the efficiency score distribution. The results of estimations revealed that only few farm-households have reached the frontier of best practice and therefore can be viewed as technically efficient. The results of truncated regression showed that landholding property, associations, formal education of household head and farm size are the key drivers of technical efficiency differentials between producers.
    Abstract: Ce papier se propose de mesurer l'efficacité technique des producteurs de manioc dans l'hinterland de Kinshasa d'une part ; et d'autre part, d'identifier ses principaux déterminants. Les données utilisées proviennent d'une enquête administrée auprès de 202 producteurs. La méthode d'enveloppement de données est appliquée pour mesurer les scores d'efficacité technique sous les hypothèses de rendements d'échelle constants (REC) et rendements d'échelle variables (REV). Par ailleurs, le modèle de régression tronquée intervient pour expliquer la variance de scores d'efficacité. Les résultats révèlent un niveau élevé d'inefficacité des producteurs de manioc. En effet, le score moyen d'efficacité est 0.318 et 0.272 respectivement sous REV et REC. Cela suggère que l'efficacité technique des producteurs de manioc de l'hinterland de Kinshasa peut être améliorée de 0.73 sous l'hypothèse REC et de 0.68 sous l'hypothèse REV. Le score moyen de l'efficacité d'échelle est largement supérieur au score moyen d'efficacité technique sous REC et REV, soit 0.902. Ce résultat implique que l'inefficacité dans la production de manioc observée dans cette étude est davantage liée à la mauvaise allocation de ressource qu'à la taille de la culture. Les résultats issus du modèle de régression tronquée révèlent que le niveau d'instruction du producteur, la possession de terres arables en propriété et la taille de la ferme affectent positivement la distribution des scores d'efficacité technique.
    Keywords: Productivity,Efficiency,Farm-household,Agriculture,Productivité,Efficacité,Ménages
    Date: 2018
  6. By: Mari Tanaka; Nicholas Bloom; Joel M. David; Maiko Koga
    Abstract: Ever since Keynes’ famous quote about animal spirits, there has been an interest in linking firms’ expectations and actions. However, empirical evidence has been limited due to a lack of firm-level panel data on expectations and outcomes. In this paper, we build such a dataset by combining a unique survey of Japanese firms’ GDP forecasts with company accounting data for 25 years for over 1,000 large Japanese firms. We find four main results. First, firms’ GDP forecasts are positively associated with their employment, investment, and output growth in the subsequent year. Second, both optimistic and pessimistic forecast errors lower profitability. Third, while over-optimistic forecasts lower measured productivity, over-pessimistic forecasts do not tend to have an effect on productivity. Overall, these results are stronger for firms whose performance is more sensitive to the state of macroeconomy. We show that a simple model of firm input choice under uncertainty and costly adjustment can rationalize there results. Finally, larger and more cyclically sensitive firms make more accurate forecasts, presumably reflecting a higher return to accuracy for these firms. More productive, older, and bank-owned firms also make more accurate forecasts, suggesting that forecasting ability is also linked to management ability, experience, and governance. Collectively, our results highlight the importance of firms’ forecasting ability for micro and macro performance.
    JEL: E0 M0
    Date: 2018–06
  7. By: Alston, Julian M.
    Abstract: Sixty years ago, T.W. Schultz introduced the idea of the productivity “residual” to agricultural economics. His main message was that growth in conventional inputs accounted for little of the observed growth in agricultural output, and that there was work to be done by agricultural economists to understand and ultimately eliminate this unexplained residual called “productivity.” Thus was launched the economics of agricultural productivity as a sub-field within agricultural economics, along with the economics of agricultural R&D and innovation and related government policy. Much progress has been made in the decades since. Still, critical issues remain unresolved. This matters because agricultural innovation and productivity matter, and so do the related policies that rest to some extent on our established understanding of the economic relationships. In this paper, I review some unsettled issues related to economic models and measures applied to agricultural R&D and productivity, and some unfinished business in terms of economic and policy questions that are not yet well answered. Before doing that, I present some evidence on agricultural productivity and why it matters. Next, with a nod to “factology,” I present available productivity measures from USDA and InSTePP, and compare them in the context of translog cost function models. In subsequent sections I use these and other data to develop new evidence related to two contentious questions: (1) Do farmers benefit from public agricultural R&D? (2) Has U.S. agricultural productivity growth slowed in recent decades? The answers are revealed within.
    Date: 2017–08–24
  8. By: Daniel A. Dias; Carlos Robalo Marques
    Abstract: Using firm level data, we show that the Portuguese financial crisis had, overall, a cleansing effect on productivity. During the crisis, aggregate productivity gains, both in manufacturing and services, came from relatively higher contributions of entry and exit of firms and from reallocation of resources between surviving firms. At the microlevel, we find that the crisis reduced the probability of survival for high and low productivity firms, but hit low productivity firms disproportionately harder, in line with the cleansing hypothesis. The correlation between productivity and employment growth in manufacturing and services strengthened, but the correlation between productivity and capital growth in the service sector weakened. We attribute this result in part to structural sectoral differences, but mainly to the large negative demand and credit shocks that affected mainly the nontradable services sub-sector. We also find that the probability of exit increased disproportionately for firms operating in more financially dependent industries, but there is no evidence of a scarring effect on productivity stemming from changing credit conditions.
    JEL: D24 E32 L25 O47
    Date: 2018
  9. By: Maman Setiawan (Faculty of Economics and Business, University of Padjadjaran); Erni Tisnawati Sule (Faculty of Economics and Business, University of Padjadjaran)
    Abstract: This research investigates technical efficiency and its determinants of the state-owned enterprises (SOEs) in the Indonesian manufacturing industry. This study applies bootstrapped data envelopment analysis to calculate the technical efficiency score at the first stage and panel data technique to estimate the effects of the determinants on the technical efficiency at the second stage. This research uses firm-level survey data classified at the five-digit International Standard Industrial Classification (ISIC) level to estimate the technical efficiency score. This research finds that the SOEs in the Indonesian manufacturing are technically inefficient. The technical efficiency is affected by the firm size, location, level of technology, export engagement and economic and financial crisis.
    Keywords: Indonesian state-owned enterprises, manufacturing industry, technical efficiency, bootstrapped data envelopment analysis.
    JEL: L0
    Date: 2018–08
  10. By: Christian Osterhold; Ana Fontoura Gouveia
    Abstract: Productivity growth is slowing down among OECD countries, coupled with increased misallocation of resources. A recent strand of literature focuses on the role of non-viable firms ("zombie firms") to explain these developments. Using a rich firm-level dataset for one of the OECD countries with the largest drop in barriers to firm exit and restructure, we assess the role of zombies on firm dynamics, both in the extensive and intensive margins. We confirm the results on the high prevalence of zombie firms, significantly less productive than their healthy counterparts and thus dragging aggregate productivity down. Moreover, while we find evidence of positive selection within zombies, with the most productive restructuring and the least productive exiting, we also show that the zombies' productivity threshold for exit is much lower than that of non-zombies, allowing them to stay in the market, distorting competition and sinking resources. Zombie prevalence curbs the growth of viable firms, in particular the most productive, harming the intra-sectoral resource reallocation. We show that a reduction in exit and restructuring barriers promotes a more effective exit channel and fosters the restructuring of the most productive, highlight the role of public policy in addressing zombies' prevalence, fostering a more efficient resource allocation and enabling productivity growth.
    JEL: D24 E22 E24 G33 J24 L25
    Date: 2018
  11. By: Iveta Palečková (Department of Finance and Accounting, School of Business Administration, Silesian University)
    Abstract: The aim of this paper is to estimate the differences in efficiency between banks in four financial conglomerates and other banks in the banking sectors in Visegrad countries within the period 2005-2015. In line with the aim of the paper, the research question is stated as follows: Are banks that belong to financial conglomerates more efficient than other banks in the banking sectors in the Visegrad countries? We analysed banks from four financial conglomerates: Erste Group, Société Généralé Group, UniCredit Group and KBC Group. Moreover we estimated the efficiency of commercial banks in the Visegrad countries using the Dynamic Data Envelopment Analysis (DEA) approach. We did not find the statistical significant differences in efficiency between banks that belong to a financial conglomerate and other banks in the banking sectors in the Visegrad countries.
    Keywords: efficiency, Dynamic Data Envelopment Analysis, banking sector, financial conglomerate, propensity score matching, Visegrad countries
    JEL: G21
    Date: 2018–07–30
  12. By: Naveen Rai; Lena Suchanek; Maria Bernier
    Abstract: This paper seeks to understand how outward foreign direct investment (FDI) affects the productivity of Canadian firms. We estimate the impact of outward greenfield investment on measures of firm-level productivity using FDI data from roughly 2,000 Canadian firms and more than 4,000 outward FDI projects over the 2003–14 period. Combining matching techniques with a difference-in-difference approach, we find that firms that invest abroad tend to see more important productivity gains one to two years after the investment, compared with firms that are otherwise similar but remain domestic, suggesting that outward investment has beneficial implications for investing firms. Further, panel regression analysis at the provincial level shows that an increase in the number of outward investment projects is found to be associated with higher productivity growth, particularly for investments in OECD countries. The result suggests that learning or technological spillover effects are particularly important when investing in countries close to the home country’s technological frontier.
    Keywords: Firm dynamics; Productivity
    JEL: D24 F21 F23
    Date: 2018
  13. By: Lai, Hung-pin; Kumbhakar, Subal C.
    Abstract: Almost all the existing panel stochastic frontier models treat technical efficiency as static. Consequently there is no mechanism by which an inefficient producer can improve its efficiency over time. The main objective of this paper is to propose a panel stochastic frontier model that allows the dynamic adjustment of persistent technical inefficiency. The model also includes transient inefficiency which is assumed to be heteroscedastic. We consider three likelihood-based approaches to estimate the model: the full maximum likelihood (FML), pairwise composite likelihood (PCL) and quasi-maximum likelihood (QML) approaches. Moreover, we provide Monte Carlo simulation results to examine and compare the finite sample performances of the three above-mentioned likelihood-based estimators. Finally, we provide an empirical application to the dynamic model.
    Keywords: Technical inefficiency, panel data, copula, full maximum likelihood estimation, pairwise composite likelihood estimation, quasi-maximum likelihood estimation
    JEL: C23 C24 C51
    Date: 2018–04–10
  14. By: Kloss, Mathias
    Abstract: Measuring factor productivity has been important in economics since its early days as a scientific discipline for a number of reasons. The first is the availability of systematically collected agricultural data after World War I, which allowed researchers to motivate and test newly developed methods. This data was collected to fulfill the societal need to learn more about the farming sector, which was stuck in a deep economic crisis at that time. In addition, economists stressed that agricultural technologies approximate the key assumptions of production theory particularly well. To measure agricultural productivity the analyst must deal with tangible (land, labour, and capital) as well as intangible (e.g., management abilities or unexpected weather shocks) production factors. Separating these two types of inputs and appropriately accounting for the latter is at the core of understanding agricultural production. Recent developments such as rising food prices and the decline in global productivity growth indicate that there is a societal need to understand and raise agricultural productivity again. Interestingly, these trends are accompanied by a new debate among econometricians about basic methodological issues in measuring firm level productivity. [...] Following my analyses, a number of policy implications unfold. As it turned out, materials is the most important input in European field crop farming. Hence, improving the availability of working capital is the most promising way to increase agricultural productivity. This finding is also underlined by the shadow price analysis, which indicated that in a number of countries the estimated return on working capital is much above observed market interest rates. Therefore, policy reforms should aim to ease access to short-term credit. With regards to agricultural labour markets the results indicate for France, West Germany and Italy that hired workers perform the highly specialised tasks leading to an increase in agricultural productivity. Consequently, policy makers should focus on creating incentives for farms to hire such specialised labour. For instance, programs to qualify and hire specialised labour could improve their inflow into agricultural labour markets.
    Keywords: Agricultural Finance, Labor and Human Capital, Productivity Analysis
    Date: 2017–12–18
  15. By: Rouf, Abdur
    Keywords: Productivity Analysis, Research Methods/ Statistical Methods
    Date: 2018–02–06

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.