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on Efficiency and Productivity |
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Issue of 2019‒01‒07
seven papers chosen by |
| By: | Nicolas Lampach; Phu Nguyen-Van; Nguyen To-The |
| Abstract: | Agricultural extension services have been dominated by development programs to improve the productivity of crops and to increase farmers’ income. The virtues and limitations of these programs ignite a debate among scholars from distinct strands of research. How effective are agricultural extension services in improving the productivity level of the agricultural output? We examine the key determinants driving systematic variations in the obtained technical efficiency estimates from all relevant crop farming studies. A weighted least square meta-regression analysis is conducted by using 193 observations from 96 farm level studies to evaluate the estimates of technical efficiency in crop farming and to review the relationship between agricultural extension services and farm performance. Evidence for the absence of a publication bias in the farm studies used in the meta-analysis is identified. The empirical results manifest that there is a positive and significant effect of extension services on technical efficiency estimates. Farm productivity is significantly influenced by country level characteristics, sample size of farm studies and type of crops. Our empirical findings are robust when replacing missing observations with imputed values applying the multiple imputation method. |
| Keywords: | Agricultural extension; Crop farming; Meta-analysis; Multiple Imputation; Publication bias; Technical efficiency; Weighted Least Square Estimation. |
| JEL: | Q16 O18 C14 C29 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ulp:sbbeta:2018-48&r=all |
| By: | Thanasis Bouzidis (Department of Economics, University of Macedonia) |
| Abstract: | In this paper, we apply for the first time the connected network Data Envelopment Analysis (DEA) model to assess the on-field performance of football clubs during a league season. Specifically, we separately measure football clubs’ technical efficiency in offense, defense, and points’ earning by using their: (i) attacking and defending moves as the inputs of offense and defense, respectively; (ii) goals scored and goals conceded as the intermediate measures that simultaneously serve as both: (a) the single outputs of offense and defense, respectively; and (b) the inputs of the points’ earning process; (iii) points earned as the single output of the points’ earning process. To illustrate the usefulness of our theoretical framework, we make use of aggregate match statistics from the 2013-2014 Greek premier football league. |
| Keywords: | Football Clubs; Offense; Defense; Points’ Earning; League Season; Efficiency; DEA. |
| JEL: | C14 C61 L83 |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:mcd:mcddps:2018_12&r=all |
| By: | Cindy Cunningham; Lucia Foster; Cheryl Grim; John Haltiwanger; Sabrina Wulff Pabilonia; Jay Stewart; Zoltan Wolf |
| Abstract: | Productivity measures are critical for understanding economic performance. The official Bureau of Labor Statistics (BLS) productivity statistics, which are available for major sectors and detailed industries, are useful for understanding the sources of aggregate productivity growth. A large volume of research shows that within-industry variation in productivity provides important insights into productivity dynamics. This research has revealed large and persistent productivity differences across businesses even within narrowly-defined industries. These differences vary across industries and over time and are related to productivity-enhancing reallocation. Dispersion in productivity across businesses may provide information about the nature of competition and frictions within sectors and about the sources of rising wage inequality across businesses. There are currently no official statistics that provide this level of detail. To fill this gap in the official statistics, the BLS and the Census Bureau are collaborating to create measures of within-industry productivity dispersion with the goal of publishing dispersion statistics to complement the official aggregate and industry-level productivity growth statistics produced by the BLS and thereby improve our understanding of the rich productivity dynamics in the U.S. economy. We are also developing restricted-use datasets for use by researchers in the Federal Statistical Research Data Center (FSRDC) network. |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:cen:wpaper:18-49&r=all |
| By: | Bertoni, Fabio; Colombo, Massimo G.; Quas, Anita |
| Abstract: | This paper provides a policy-oriented summary of the econometric study commissioned by the European Court of Auditors, in the context of its audit of EU-funded loan guarantee instruments.2 The study assesses the real performance effects of EU-guaranteed loans to SMEs disbursed in France during the years 2002 to 2016. The study estimates the average treatment effect of guaranteed loans over a 10-year period around disbursement, using a combination of difference-in-difference estimation, coarsened exact matching and propensity score analysis. On average, French SMEs benefitting from EU-guaranteed loans experienced additional 9% asset growth, 7% sales growth, and 8% employment growth compared to the control group. The economic significance of the effect is typically stronger for smaller and younger firms. Beneficiary SMEs also experienced 5% lower default rates. The study also estimates the effects of guaranteed loans on SME productivity. Consistent with earlier works, the analysis finds a short-run dip in productivity, accompanied by a medium-run recovery and a long-run positive effect, signalling the presence of adjustment costs in the production function following loan-induced investments. The study concludes by discussing potential implications for policy makers and further research. |
| Keywords: | EIF,credit guarantees,credit constraints,real effects,small and medium-sized enterprises |
| JEL: | G2 H25 O16 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:eifwps:201852&r=all |
| By: | Brekke, Kurt R. (Dept. of Economics, Norwegian School of Economics and Business Administration); Canta, Chiara (Toulouse Business School); Straume, Odd Rune (University of Bergen, Department of Economics and University of Minho, Department of Economics/NIPE); Siciliani, Luigi (University of York) |
| Abstract: | We study the impact of exposing hospitals in a National Health Service (NHS) to non-price competition by exploiting a patient choice reform in Norway in 2001. The reform facilitates a difference-in-difference research design due to geographical variation in the scope for competition. Using rich administrative data covering the universe of NHS hospital admissions from 1998 to 2005, we find that hospitals in more competitive areas have a sharper reduction in AMI mortality, readmissions, and length of stay than hospitals in less competitive areas. These results indicate that competition improves patient health outcomes and hospital cost efficiency, even in the Norwegian NHS with large distances, low fixed treatment prices, and mainly public hospitals. |
| Keywords: | Patient Choice; Hospital Competition; Quality; Cost-efficiency |
| JEL: | I11 I18 L13 |
| Date: | 2018–12–06 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:nhheco:2018_028&r=all |
| By: | Tsionas, Efthymios G.; Tran, Kien C.; Michaelides, Panayotis G. |
| Abstract: | In this paper, we generalize the stochastic frontier model to allow for heterogeneous technologies and inefficiencies in a structured way that allows for learning and adapting. We propose a general model and various special cases, organized around the idea that there is switching or transition from one technology to the other(s), and construct threshold stochastic frontier models. We suggest Bayesian inferences for the general model proposed here and its special cases using Gibbs sampling with data augmentation. The new techniques are applied, with very satisfactory results, to a panel of world production functions using, as switching or transition variables, human capital, age of capital stock (representing input quality), as well as a time trend to capture structural switching |
| Keywords: | Stochastic frontier Regime switching Efficiency measurement Bayesian inference Markov Chain Monte Carlo |
| JEL: | C11 C13 |
| Date: | 2017–12–15 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:86848&r=all |
| By: | James Harrigan; Ariell Reshef; Farid Toubal |
| Abstract: | We study the impact of firm level choices of ICT, R&D, exporting and importing on the evolution of productivity and its bias towards skilled occupations. We use a novel measure of the propensity of a firm to engage in technology investment and adoption: its employment of workers with STEM (science, technology, engineering and math) skills and experience who we call “techies”. We develop a methodology for estimating firm level productivity that allows us to measure both Hicks-neutral and skill-augmenting technology differences, and apply this to administrative data on French firms in the entire private sector from 2009 to 2013. We find that techies and importing of intermediate inputs raise skill-biased productivity, while imports also raise Hicks-neutral productivity. We also find that higher firm-level skill biased productivity raises low-skill employment even as it raises the ratio of skilled to unskilled workers. This is because of the cost-reducing effect of higher productivity. The techie and trade effects are large, and can account for much of the aggregate increase in skilled employment from 2009 to 2013. |
| Keywords: | Productivity;Skill Bias;Skill Augmenting;Labor Demand;Outsourcing;Globalization;R&D;ICT |
| JEL: | D24 F16 J24 |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:cii:cepidt:2018-21&r=all |