nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2019‒04‒22
thirty papers chosen by

  1. Frontier Efficiency, Capital Structure, and Portfolio Risk: An Empirical Analysis of U.S. Banks By Ding, Dong; Sickles, Robin C.
  2. Econometric Analysis of Productivity: Theory and Implementation in R By Sickles, Robin C.; Song, Wonho; Zelenyuk, Valentin
  3. Firm Performance and Agglomeration Effects: Evidence from Tunisian Firm-level Data By Mohamed Amara
  4. Productivity of the English National Health Service: 2016/17 update By Adriana Castelli; Martin Chalkley; James Gaughan; Maria Lucia Pace; Idaira Rodriguez Santana
  5. Who is an Efficient and Effective Physician? Evidence from Emergence Medicine By Saghafian, Soroush; Imanirad, Raha; Traub, Stephen J.
  6. The Limits of Lending? Banks and Technology Adoption across Russia By Bircan, Cagatay; de Haas, Ralph
  7. Market Concentration and the Productivity Slowdown By Olmstead-Rumsey, Jane
  8. Global Value Chain Integration and Productivity: The Case of Turkish Manufacturing Firms By Yilmaz Kiliçaslan; Ugur Aytun; Oytun Meçik
  9. Impacts of extreme events on technical efficiency in Vietnamese agriculture By Yoro Diallo; Sébastien Marchand; Etienne Espagne
  10. External R&D Acquisition and Product Innovation By OA Carboni; G. Medda
  11. Non-structural Analysis of Productivity Growth for the Industrialized Countries: A Jackknife Model Averaging Approach By Isaksson, Anders; Shang, Chenjun; Sickles, Robin C.
  12. Decomposing a decomposition: Within-country differences and the role of structural change in productivity growth By Escobar, Octavio; Mühlen, Henning
  13. Does International Financial Integration Increase the Standard of Living in Africa? A Frontier Approach By Gilles Dufrénot; Kimiko Sugimoto
  14. Efficiency Assessment of Tunisian Public hospitals Using Data Envelopment Analysis (DEA) By Miryam Daoud Marrakchi; Hédi Essid
  15. Why is Productivity Correlated with Competition? By Matthew Backus
  16. Resource Allocation in Multi-divisional Multi-product Firms By Gong, Binlei; Sickles, Robin C.
  17. Estimation of Industry-level Productivity with Cross-sectional Dependence by Using Spatial Analysis By Han, Jaepil; Sickles, Robin C.
  18. Overhead Labour and Skill-Biased Technological Change: The Role of Product Diversification By Choong Hyun Nam
  19. Direction Selection in Stochastic Directional Distance Functions By Ferrier, Gary D.; Johnson, Andrew L.; Layer, Kevin; Sickles, Robin C.
  20. Capital Regulation, Efficiency, and Risk Taking: A Spatial Panel Analysis of U.S. Banks By Ding, Dong; Sickles, Robin C.
  21. Off-Balance Sheet Activities, Inefficiency and Market Power of U.S. Banks By Wheelock, David C.; Wilson, Paul W.
  22. Do Hospital Closures Improve the Efficiency and Quality of Other Hospitals? By Song, Lina; Saghafian, Soroush
  23. Empirical Surveys of Frontier Applications: A Meta-Review By Daraio, Cinzia; Kerstens, Kristiaan; Nepomuceno, Thyago; Sickles, Robin C.
  24. Determinants of Manufacturing Sector Performance and Its Contribution To Gross Domestic Product In Nigeria By Kenny S, Victoria
  25. Decentralisation and performance measurement systems in health care By Ivor Beazley; Sean Dougherty; Chris James; Caroline Penn; Leah Phillips
  26. Robots and Firms By Michael Koch; Ilya Manuylov; Marcel Smolka
  27. Cost, Revenue, and Profit Function Estimates By Kutlu, Levent; Liu, Shasha; Sickles, Robin C.
  28. The performance of Islamic banks in the MENA region: Are specific risks a minor attribute? By Imène Berguiga; Philippe Adair
  29. An Overview of Issues in Measuring the Performance of National Economies By Glass, Anthony; Kenjegalieva, Karligash; Sickles, Robin C.; Weyman-Jones, Thomas
  30. Productivity, Profits, and Pay: A Field Experiment Analyzing the Impacts of Compensation Systems in an Apparel Factory By Lollo, Niklas; O’Rourke, Dara

  1. By: Ding, Dong (Rice U); Sickles, Robin C. (Rice U)
    Abstract: The measurement of firm performance is central to management research. Firms' ability to effectively allocate capital and manage risks are the essence of their production and performance. This study investigated the relationship between capital structure, portfolio risk levels and firm performance using a large sample of U.S. banks from 2001-2016. Stochastic frontier analysis (SFA) was used to construct a frontier to measure firm's cost efficiency as a proxy for firm performance. We further look at their relationship by dividing the sample into different size and ownership classes, as well as the most and least efficient banks. The empirical evidence suggests that more efficient banks increase capital holdings and take on greater credit risk while reducing risk weighted assets. Moreover, it appears that increasing the capital buffer impacts risk-taking by banks depending on their level of cost efficiency, which is a placeholder for how productive their intermediation services are performed. More cost efficient banks that are well-capitalized tend to maintain relatively large capital buffers versus banks that are not. An additional finding, which is quite important, is that the direction of the relationship between risk-taking and capital buffers differs depending on what measure of risk is used.
    Date: 2018–06
  2. By: Sickles, Robin C. (Rice U); Song, Wonho (Chung-Ang U); Zelenyuk, Valentin (U of Queensland)
    Abstract: Our chapter details a wide variety of approaches used in estimating productivity and efficiency based on methods developed to estimate frontier production using Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). The estimators utilize panel, single cross section, and time series data sets. The R programs include such approaches to estimate firm efficiency as the time invariant fixed effects, correlated random effects, and uncorrelated random effects panel stochastic frontier estimators, time varying fixed effects, correlated random effects, and uncorrelated random effects estimators, semi-parametric efficient panel frontier estimators, factor models for cross-sectional and time-varying efficiency, bootstrapping methods to develop confidence intervals for index number-based productivity estimates and their decompositions, DEA and Free Disposable Hull estimators. The chapter provides the professional researcher, analyst, statistician, and regulator with the most up to date efficiency modeling methods in the easily accessible open source programming language R.
    Date: 2018–09
  3. By: Mohamed Amara (University of Tunis)
    Abstract: Using Tunisian manufacturing data between 1998 and 2004 and by referring to multilevel approach, this paper investigates the impact of agglomeration and individual characteristics on firm’s performance. The empirical results show the importance of considering both regional and firm characteristics when examining firm performance. They also support the validity of self selection and learning-by-exporting hypotheses. Urbanization and localization effects are significant and positive for firm’s export behavior, but only localization economies have a positive effect of firm productivity. However, the results of the quantile approach show that selection, rather than agglomeration economies in larger cities, better explain spatial productivity differences
    Date: 2019
  4. By: Adriana Castelli (Centre for Health Economics, University of York, UK); Martin Chalkley (Centre for Health Economics, University of York, UK); James Gaughan (Centre for Health Economics, University of York, UK); Maria Lucia Pace (Centre for Health Economics, University of York, UK); Idaira Rodriguez Santana (Centre for Health Economics, University of York, UK)
    Abstract: This report updates the Centre for Health Economics’ time-series of National Health Service (NHS)productivity growth for the period 2015/16 to 2016/17 and reports trends in output, input and productivity since 2004/05. NHS productivity growth is measured by comparing the growth in outputs produced by the NHS to the growth in inputs used to produce them. NHS outputs include all the activities undertaken for NHS patients wherever they are treated in England, and also accounts for changes in the quality of care provided to those patients. NHS inputs include the number of doctors, nurses and support staff providing care, the equipment and clinical supplies used, and the facilities of hospitals and other premises where care is provided.
    Date: 2019–04
  5. By: Saghafian, Soroush (Harvard Kennedy School); Imanirad, Raha (Harvard Business School); Traub, Stephen J. (Mayo Clinic Arizona)
    Abstract: Improving the performance of the healthcare sector requires an understanding of the efficiency and effectiveness of care delivered by providers. Although this topic is of great interest to policymakers, researchers, and hospital managers, fair and scientific methods of measuring efficiency and effectiveness of care delivery have proven elusive. Through Data Envelopment Analysis (DEA), we make use of evidence from care delivered by emergency physicians, and shed light on scientific metrics that can gauge performance in terms of efficiency and effectiveness. We use these metrics along with Machine Learning techniques and Tobit analyses to identify the distinguishing behaviors of physicians who perform highly on these metrics. Our findings indicate a statistically significant positive relationship between a physician's effectiveness and efficiency scores suggesting that, contrary to conventional wisdom, high levels of effectiveness are not necessarily associated with low efficiency levels. In addition, we find that a physician's effectiveness is positively associated with his/her average contact-to-disposition time and negatively associated with his/her years of experience. We also find a statistically significant negative relationship between a physician's efficiency and his/her average MRI orders per patient visit. Furthermore, we find evidence of a peer effect of one physician upon another, which suggests an opportunity to improve system performance by taking physician characteristics into account when determining the set of physicians that should be scheduled during same shifts.
    Date: 2018–09
  6. By: Bircan, Cagatay; de Haas, Ralph
    Abstract: We exploit historically-determined variation in local credit markets to identify the impact of bank lending on firm innovation across Russia. We find that deeper credit markets increase firms' use of bank credit, their adoption of new products and technologies, and productivity growth. This relationship is more pronounced in industries further from the technological frontier; more exposed to import competition; and that export more. These impacts are also stronger for firms near historical R&D centers or railways, and in regions with supportive institutions. Consistent with these results, credit markets contribute to economic growth in such regions.
    Keywords: credit constraints; Firm innovation; institutions; Russia; Technological change
    JEL: D22 G21 O12 O31
    Date: 2019–04
  7. By: Olmstead-Rumsey, Jane
    Abstract: Since around 2000, U.S. aggregate productivity growth has slowed and product market (sales) concentration has risen. At the same time, productivity differences among firms in the same sector appear to have risen dramatically. In this paper I propose a rich model of competition and innovation to explain the coincidence of these three observations. In the model a key parameter governing all three phenomena is the probability that innovating firms make radical innovations. Thus one explanation for rising concentration, slower productivity growth, and wider technology differences among firms is that the incidence of radical innovations has slowed relative to the 1990s, when the internet and other information technology radically transformed production and sales technology in many sectors.
    Keywords: Endogenous growth; market concentration; market power; productivity slowdown; superstar firms
    JEL: E23 L1 O3 O4
    Date: 2019–04–10
  8. By: Yilmaz Kiliçaslan (Anadolu University); Ugur Aytun; Oytun Meçik
    Abstract: In this study, we examine how firms’ positions (supplier, consumer, or both) in both global and domestic value chains (GVC andDVC) affect their productivity. This is said to be the first attempt in exploring the impact of integration of firms to the GVCs on productivity generation in Turkish manufacturing industry at the firm level. The analysis is based on firm level data obtained from Turkish Statistical Institute (TurkStat) and covers the period from 2003 to 2015. The data used in the analysis includes all firms employing 20 or more employees in Turkish manufacturing industry. Our findings based on both fixed-effects and GMM estimations show that while supplier position on domestic chain has negative effect on productivity, the same position in GVC vanishes this effect. Consumer position in the GVC, on the other hand, provide more benefits to SMEs than to large-scale firms.
    Date: 2019
  9. By: Yoro Diallo (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique); Sébastien Marchand (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique); Etienne Espagne (CIRED - Centre International de Recherche sur l'Environnement et le Développement - CNRS - Centre National de la Recherche Scientifique - ENPC - École des Ponts ParisTech - CIRAD - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - EHESS - École des hautes études en sciences sociales - AgroParisTech, AFD - Agence française de développement, CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique)
    Abstract: The aim of this study is to examine farm household-level impacts of weather extreme events on Vietnamese rice technical efficiency. Vietnam is considered among the most vulnerable countries to climate change, and the Vietnamese economy is highly dependent on rice production that is strongly affected by climate change. A stochastic frontier analysis is applied with census panel data and weather data from 2010 to 2014 to estimate these impacts while controlling for both adaptation strategy and household characteristics. Also, this study combines these estimated marginal effects with future climate scenarios (Representative Concentration Pathways 4.5 and 8.5) to project the potential impact of hot temperatures in 2050 on rice technical efficiency. We find that weather shocks measured by the occurrence of floods, typhoons and droughts negatively affect technical efficiency. Also, additional days with a temperature above 31°C dampen technical efficiency and the negative effect is increasing with temperature. For instance, a one day increase in the bin [33°C-34°C] ([35°C and more]) lessen technical efficiency between 6.84 (2.82) and 8.05 (3.42) percentage points during the dry (wet) season.
    Keywords: Weather shocks,Technical efficiency,Rice farming,Vietnam
    Date: 2019–03–22
  10. By: OA Carboni; G. Medda
    Abstract: The outsourcing of R&D activities is considered an important way to acquire external technological information that can be integrated into a firm's own knowledge endowment. Given the complex relationship between R&D partnerships and innovation performance, it becomes of paramount importance for scholars, managers and policy-makers to understand whether and how outsourcing benefits the firm. This paper tries to assess the impact that external sources of R&D may have on product innovation, differentiating between R&D supplied by universities and other companies. The empirical analysis is based on a large and representative sample of European manufacturing companies. The analysis considers R&D an endogenous decision in investigating its effect on product innovation. An instrumental variable two-step estimation method is employed to deal with this issue. The results suggest that R&D intensity, or the share of R&D acquired from external sources, has a positive and significant effect on product innovation. Furthermore, we find evidence of an inverse U-shaped relationship between R&D outsourcing and innovation, meaning that on average, costs start to outweigh benefits as the R&D collaboration projects increase. We also estimate high returns from R&D acquired from universities on the probability to achieve product innovations, while having firms in the same group as research partners has the largest effect on innovative product sales. The results have straightforward implications for the practice of R&D managers. In order to gain advantages from partnership in research, innovation managers need to jointly exploit these different types of collaboration activities and their potential synergies. Given that the innovative firms in the sample desire additional credit which actually they do not obtain, R&D managers should also be concerned with the financing sources firms have access to. Finally, the analysis suggests that managers ought to identify the appropriate level of external acquisition in order to fully benefit on innovation.
    Keywords: External R&D;research partners;innovation performance;IV model
    Date: 2019
  11. By: Isaksson, Anders (United National Industrial Development Organization); Shang, Chenjun (Freddie Mac); Sickles, Robin C. (Rice U)
    Abstract: Various structural and non-structural models of productivity growth have been proposed in the literature. In either class of models, predictive measurements of productivity and efficiency are obtained. This paper examines the model averaging approaches of Hansen and Racine (2012), which can provide a vehicle to weight predictions (in the form of productivity and efficiency measurements) from different non-structural methods. We first describe the jackknife model averaging estimator proposed by Hansen and Racine (2012) and illustrate how to apply the technique to a set of competing stochastic frontier estimators. The derived method is then used to analyze productivity and efficiency dynamics in 25 highly-industrialized countries over the period 1990 to 2014. Through the empirical application, we show that the model averaging method provides relatively stable estimates, in comparison to standard model selection methods that simply select one model with the highest measure of goodness of fit.
    JEL: C14 C23 O40
    Date: 2018–06
  12. By: Escobar, Octavio; Mühlen, Henning
    Abstract: In this article, we investigate the relevance of structural change in country-wide productivity growth considering within-country differences. For this purpose, we propose a two-step decomposition approach that accounts for differences among subnational units. To highlight the relevance of our procedure compared to the prevalent approach in the existing development literature (which usually neglects subnational differences), we show an application with data for the Mexican economy. Specifically, we contrast findings obtained from country-sector data on the one hand with those obtained from (more disaggregated) state-sector data on the other hand. One main insight is that the qualitative and quantitative results differ substantially between the two approaches. Our procedure reveals that structural change appeared to be growth-reducing during the period from 2005 to 2016. We show that this negative effect is driven mainly by the reallocation of (low-skilled) labor within subnational units.
    Keywords: decomposition approach,economic development,labor reallocation,regional differences,structural change
    JEL: L16 O10 O18 R11
    Date: 2019
  13. By: Gilles Dufrénot (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique); Kimiko Sugimoto (Hirao School of Management - Konan University)
    Abstract: We investigate whether a higher financial integration with the rest of the world can help the African countries reduce their production inefficiency and/or push up their efficient frontier of production. We use two alternative empirical approaches based, respectively, on a stochastic frontier analysis and quantile regressions. We provide evidence of heterogeneous situations across countries and time. This paper proposes a new approach for defining, at the aggregate level, a link between financial openness and production efficiency. We show that one size does not fit all: international financial integration can increase or decrease African countries' standard of living.
    Keywords: African countries,financial openness,stochastic frontier,quantile regression
    Date: 2019–04
  14. By: Miryam Daoud Marrakchi (Université de Tunis); Hédi Essid
    Abstract: In the recent past years, Tunisia pursued a national policy on health which was directed towards the performance. Although the lack of adequate resources presents the most important constraint, efficiency in the utilization of available resources is another challenge that cannot be overlooked. The objective of this study aims to assess the technical efficiency (TE) of a sample of Tunisian public hospital using the non-parametric approach of Data Envelopment Analysis (DEA). In this perspective, we started with measuring, comparing and analyzing the TE of the three categories of the Tunisian public hospitals, then to investigate the difference in the level of efficiency by district and finally to Guide the decision and the policy makers in their decision making process through the developed decision making tools. The data were gathered from a sample of 134 public hospitals throughout Tunisia. These would cover about 80% of the total number of Tunisian public hospitals. The model estimates the technical efficiency for the whole sample as well as for each hospital. The entire sample was operating on average at 0, 78 level of technical efficiency. Only 28% of the total hospitals were found to be technically efficient in relative term while the remaining were inefficient. The Public Health Establishment (PHE), the regional hospital (RH) and the District Hospital (DH) were operating on average at 0,9; 0,74 and 0,76 level of technical efficiency respectively. Only 45% of the PHE, 23% of the RH and 25% of the DH were technically efficient while the remaining were inefficient. The study identifies the inefficient hospitals and provides the magnitudes by which specific input per inefficient hospital ought to be more managed or to be reduced. It emphasizes also the disparity by districts in term of percentage of efficient and inefficient hospitals. Therefore, the highest percentage of efficient hospitals is also in the districts of North East (NE) and Center East (CE).
    Date: 2019
  15. By: Matthew Backus
    Abstract: The correlation between productivity and competition is an oft–observed but ill–understood result. Some suggest that there is a treatment effect of competition on measured productivity, e.g. through a reduction of managerial slack. Others argue that greater competition makes unproductive establishments exit by reallocating demand to their productive rivals, raising observed average productivity via selection. I study the ready-mix concrete industry and offer three perspectives on this ambivalence. First, using a standard decomposition approach, I find no evidence of greater reallocation of demand to productive plants in more competitive markets. Second, I model the establishment exit decision and construct a semi-parametric selection correction to quantify the empirical significance of treatment and selection. Finally, I use a grouped IV quantile regression to test the distributional predictions of the selection hypothesis. I find no evidence for greater selection or reallocation in more competitive markets; instead, all three results suggest that measured productivity responds directly to competition. Potential channels include specialization and managerial inputs.
    JEL: L22 L23 L25 L61
    Date: 2019–04
  16. By: Gong, Binlei (Zhejiang U); Sickles, Robin C. (Rice U)
    Abstract: This paper is concerned with specifying and estimating the productive characteristics of multidivisional multiproduct companies at the divisional level. In order to accomplish this, we augment division-level information with inputs that are imputed based on profit-maximizing allocations within each division. This study builds on work by De Loecker, et al. (2016) as well as Olley and Pakes (1996), Levinsohn and Petrin (2003) and Ackerberg, Caves and Frazer (2015), and extends this work by lifting a key assumption that single- and multi-product/division firms have the same production technique for the same product/segment. We estimate the production function and impute input allocations simultaneously in the absence of this key assumption as well as the constant share constraint of the input portfolio. Finally, our approach is applied to estimate the division-specific productivity of firms that compete in five segments of the global oilfield market.
    JEL: C5 D2 L2 Q4
    Date: 2019–01
  17. By: Han, Jaepil (Korea Development Institute); Sickles, Robin C. (Rice U)
    Abstract: We examine aggregate productivity in the presence of inter-sectoral linkages. Cross-sectional dependence is inevitable among industries, in which each sector serves as a supplier to the other sectors. However, the chains of such interconnections cause indirect relationship among industries. Spatial analysis is one of the approaches to address cross-sectional dependence by using a priori a specified spatial weights matrix. We exploit the linkage patterns from the input-output tables and use them to assign spatial weights to describe the economic interdependencies. By using the spatial weights matrix, we can estimate the industry-level production functions and productivity of the U.S. from 1947 to 2010. Cross-sectional dependencies are the consequences of indirect effects, and they reflect the interactions among industries linked via their supply chain networks result in larger output elasticities as well as scale effects for the networked production processes. However, productivity growth estimates are reportedly comparable across various spatial and non-spatial model specications.
    JEL: C21 C23 C51 O47 R15
    Date: 2019–01
  18. By: Choong Hyun Nam (Economic Research Institute, Bank of Korea)
    Abstract: This paper tries to explain why a certain type of technology is skill-biased. In contrast with existing literature, this paper regards skilled workers as overhead labour, and presents a model wherein skilled workers constitute a fixed input, required to produce a new product. The demand for skill increases with product variety, and information technology is skill-biased because it raises product variety by lowering the fixed cost of product creation. However, skill-biased change does not necessarily raise measured productivity because product diversification reallocates resources into fixed inputs, which is consistent with the historical fact that skill-biased change did not always accompany productivity growth.
    Keywords: Skill demand, Product innovation, Inequality, Productivity
    JEL: E24 J31 L1 O3 O4
    Date: 2019–04–08
  19. By: Ferrier, Gary D. (Texas A&M U); Johnson, Andrew L. (Texas A&M U and Osaka U); Layer, Kevin (Rice U); Sickles, Robin C. (U of Arkansas)
    Abstract: Researchers rely on the distance function to model multiple product production using multiple inputs. A stochastic directional distance function (SDDF) allows for noise in potentially all input and output variables, yet when estimated, the direction selected will affect the functional estimates because deviations from the estimated function are minimized in the specified direction. Specifically, the parameters of the parametric SDDF are point identified when the direction is specified; we show that the parameters of the parametric SDDF are set identified when multiple directions are considered. Further, the set of identified parameters can be narrowed via data-driven approaches to restrict the directions considered. We demonstrate a similar narrowing of the identified parameter set for a shape constrained nonparametric method, where the shape constraints impose standard features of a cost function such as monotonicity and convexity. Our Monte Carlo simulation studies reveal significant improvements, as measured by out of sample radial mean squared error, in functional estimates when we use a directional distance function with an appropriately selected direction and the errors are uncorrelated across variables. We show that these benefits increase as the correlation in error terms across variables increases. This correlation is a type of endogeneity that is common in production settings. From our Monte Carlo simulations we conclude that selecting a direction that is approximately orthogonal to the estimated function in the central region of the data gives significantly better estimates relative to the directions commonly used in the literature. For practitioners, our results imply that selecting a direction vector that has non-zero components for all variables that may have measurement error provides a significant improvement in the estimator's performance. We illustrate these results using cost and production data from three random samples of approximately 500 US hospitals operating in 2007, 2008, and 2009, respectively, and find that the shape constrained nonparametric methods provide a significant increase in flexibility over second order local approximation parametric methods.
    Date: 2018–10
  20. By: Ding, Dong (Rice U); Sickles, Robin C. (Rice U)
    Abstract: In this study, we empirically assess the impact of capital regulations on capital adequacy ratios, portfolio risk levels and cost efficiency for U.S. banks. Using a large panel data of U.S. banks between 2001-2016, we first estimate the model using two-step generalized method of moments (GMM) estimators. After obtaining residuals from the regressions, we propose a method to construct the network based on clustering of these residuals. The residuals capture the unobserved heterogeneity that goes beyond systematic factors and banks' business decisions that impact its level of capital, risk and cost efficiency and thus represent unobserved network heterogeneity across banks. We then re-estimate the model in a spatial error framework. The comparisons of Fixed Effects, GMM Fixed Effect models with spatial fixed effects models provide clear evidence of the existence of unobserved spatial effects in the interbank network. We find a stricter capital requirement causes banks to reduce investments in risk-weighted assets, but at the same time, increase holdings of non-performing loans, suggesting the unintended effects of higher capital requirements on credit risks. We also find the amount of capital buffers has an important impact on banks' management practices even when regulatory capital requirements are not binding.
    Date: 2018–07
  21. By: Wheelock, David C. (Federal Reserve Bank of St. Louis); Wilson, Paul W. (Clemson University)
    Abstract: The Lerner index is a well-established measure of firms’ market power, but estimation and interpretation present several challenges, especially for banks. We estimate Lerner indices for U.S. banks for 2001-2016 while (i) accounting for banks’ off-balancesheet activities, (ii) estimating cost and profit functions nonparametrically to avoid mis-specification inherent in parametric estimation of translog functions on banking data, and (iii) allowing for cost and profit inefficiency that can otherwise bias index estimates. We find that banks have more market power than previous studies found, and that failure to account for off-balance-sheet activities or inefficiency can seriously bias estimates of market power.
    Keywords: banks; concentration; market power; nonparametric regression
    JEL: C12 C13 C14 G21 L13
    Date: 2019–04–16
  22. By: Song, Lina (Harvard University); Saghafian, Soroush (Harvard Kennedy School)
    Abstract: The recent trend in the U.S. hospital closures can have important impacts on the healthcare sector by changing the operational efficiency and quality of care of the remaining hospitals. We investigate the impact of hospital closures on the surrounding hospitals' efficiency and quality and shed light on mechanisms through which they can be affected. Using and combining various data sources, we find that when a hospital closes, its nearby hospitals improve their operational efficiency without expanding their resources. However, they do so via a speed-up behavior (i.e., by reducing their service durations) instead of an effort to lower their average bed idle time. Importantly, we find that this speed-up response to the increased demand by nearby hospitals negatively affects some (but not all) aspect of the care, including the 30-day patient mortality. Furthermore, hospital closures induce changes in directions that widen social disparity, as their adverse consequences fall disproportionately among hospitals or patients with limited resources. Our results have implications for both hospital administrators and policymakers who strive to improve the efficiency and quality of the healthcare system.
    Date: 2019–01
  23. By: Daraio, Cinzia (DIAG, Sapienza U of Rome); Kerstens, Kristiaan (IESEG School of Management); Nepomuceno, Thyago (Universidade Federal de Pernambuco and DIAG, Sapienza U of Rome); Sickles, Robin C. (Rice U)
    Abstract: This contribution is the first attempt to systematically review all empirical surveys that so far have been made available in the broad field of efficiency and productivity analysis using frontier estimation methodologies. We provide a systematic bibliometric review on the many empirical surveys in the field of efficiency and productivity analysis, the most relevant concepts, areas, overlaps and potentials to explore from its introduction to the most recent surveys. We combine the international ISIC taxonomy of economic activity with the JEL classification system to classify these empirical surveys and to identify the current gaps in the literature. This provides not only the most relevant/generic potential areas for applications (according to the UN's ISIC), but also the most relevant concepts that have been worked on in those applications (according to the JEL codes). We also provide some cluster analysis. This overview therefore provides an interesting guide for future work to develop the whole field.
    Date: 2019–01
  24. By: Kenny S, Victoria
    Abstract: The Manufacturing sector is regarded as a very important sector in an economy because of its capacity to foster wide and efficient backward and forward linkages among other sectors of the economy. This study examines the determinants of manufacturing sector performance and its contribution to gross domestic product in Nigeria using a time series data from 1981 to 2015 using Johansen Cointegration and the Vector Error Correction Model. The study found that while labour force, gross fixed capital formation and exchange rate showed a positive long run relationship with the manufacturing value added, the average manufacturing capacity utilisation, lending interest rate and government expenditure showed a long run negative relationship. The study recommends that policies should be geared towards making the exchange rate, lending interest rate and government capital expenditure more favourable and productive in the manufacturing sector.
    Keywords: Economy, Manufacturing, Vector Error Correction
    JEL: D00
    Date: 2019–04–13
  25. By: Ivor Beazley; Sean Dougherty; Chris James; Caroline Penn; Leah Phillips
    Abstract: Based on an OECD survey, this paper presents quantitative and qualitative data on the decentralisation of health systems, focusing on how they vary according to different institutional characteristics and what types of performance measurement systems are used in the health sector. Decision-making in health care tends to rest largely with the central government, which has considerable power across many aspects of the delivery of health services. However, sub-national governments have more control over decisions regarding the inputs, outputs and monitoring of health care services. The majority of OECD countries tends to rely on centralised performance measurement systems, especially to monitor the performance of hospital providers, focusing more on improving performance rather than reducing service costs. Less likely to be monitored under a specific performance framework are providers of ancillary services, retailers and other providers of medical goods, and providers of preventive care.
    Keywords: Health systems, intergovernmental relations, performance monitoring
    JEL: H75 I18 O43
    Date: 2019–04–18
  26. By: Michael Koch (University of Bayreuth); Ilya Manuylov (Department of Economics and Business Economics, Aarhus University, Denmark); Marcel Smolka (Department of Economics and Business Economics, Aarhus University, Denmark)
    Abstract: We study the implications of robot adoption at the level of individual firms using a rich panel data-set of Spanish manufacturing firms over a 27-year period (1990-2016). We focus on three central questions: (1) Which firms adopt robots? (2) What are the labor market effects of robot adoption at the firm level? (3) How does firm heterogeneity in robot adoption affect the industry equilibrium? To address these questions, we look at our data through the lens of recent attempts in the literature to formalize the implications of robot technology. As for the first question, we establish robust evidence that ex-ante larger and more productive firms are more likely to adopt robots, while ex-ante more skill-intensive firms are less likely to do so. As for the second question, we find that robot adoption generates substantial output gains in the vicinity of 20-25% within four years, reduces the labor cost share by 5-7%-points, and leads to net job creation at a rate of 10%. These results are robust to controlling for non-random selection into robot adoption through a difference-in-differences approach combined with a propensity score reweighting estimator. Finally, we reveal substantial job losses in firms that do not adopt robots, and a productivity-enhancing reallocation of labor across firms, away from non-adopters, and toward adopters.
    Keywords: Automation, Robots, Firms, Productivity, Technology
    JEL: D22 F14 J24 O14
    Date: 2019–04–08
  27. By: Kutlu, Levent (U of Texas, Arlington); Liu, Shasha (Rice U); Sickles, Robin C. (Rice U)
    Date: 2018–10
  28. By: Imène Berguiga; Philippe Adair
    Date: 2019
  29. By: Glass, Anthony (?); Kenjegalieva, Karligash (?); Sickles, Robin C. (Rice U); Weyman-Jones, Thomas (?)
    Date: 2019–01
  30. By: Lollo, Niklas; O’Rourke, Dara
    Abstract: Factory worker pay in global value chains remains a contentious issue. In this paper, we evaluate a two-year field experiment in an apparel factory to analyze altered compensation systems designed to increase worker pay while supporting factory goals around productivity and profitability. Using a quasi-experimental design, with unique data on wages, hours, productivity, quality, and worker engagement, we estimate the impact of three altered compensation systems on pay, productivity, and factory profits. The compensation systems can be described as: 1) an improved productivity-based scheme, 2) a scheme that brings quality and waste reduction into the calculation; and 3) a “target wage†scheme. Overall, the treatments raised wages by 4.2-11.6% and increased productivity by 7-12%-points. Management reported significant financial benefits from the experiment, including increased profits for five of six lines, and avoided costs and productivity losses due to decreased turnover. The factory workers, through focus-group interviews before, during, and after the intervention, reported improved relations with team members and managers. This study demonstrates altered factory compensation can support better factory performance and a better paid workforce, indicating a path towards advanced supply chains with improved wages.
    Keywords: Social and Behavioral Sciences, LABOR MARKETS, LOW-WAGE WORK
    Date: 2018–12–20

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.