nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2022‒02‒28
seven papers chosen by

  1. Return of the Solow-paradox in AI? AI-adoption and firm productivity By Bäck, Asta; Hajikhani, Arash; Jäger, Angela; Schubert, Torben; Suominen, Arho
  2. Data sharpening for improving CLT approximations for DEA-type efficiency estimators By Nguyen, Bao Hoang; Simar, Léopold; Zelenyuk, Valentin
  3. Firm Productivity and Immigrant-Native Earnings Disparity By Aslund, Olof; Bratu, Cristina; Lombardi, Stefano; Thoresson, Anna
  4. Cost-benefit analysis of bank regulation: Does size matter? By Mulindi, Hillary
  5. Does Group-Based Incentive Pay Lead To Higher Productivity? Evidence from a Complex and Interdependent Industrial Production Process By Frederiksen, Anders; Hansen, Daniel Baltzer Schjødt; Flaherty Manchester, Colleen
  6. The impact of management on hospital performance By Asaria, Miqdad; Mcguire, Alistair; Street, Andrew
  7. Working from a Distance: Productivity Dispersion and Labor Reallocation By Dongya Koh; Jingping Gu; Andrew Liu

  1. By: Bäck, Asta (VTT); Hajikhani, Arash (VTT); Jäger, Angela (Fraunhofer Institute for Systems and Innovation Research ISI); Schubert, Torben (CIRCLE, Lund University); Suominen, Arho (VTT)
    Abstract: AI-related technologies have become ubiquitous in many business contexts. However, to date empirical accounts of the productivity effects of AI-adoption by firms are scarce. Using Finnish data on job advertisements between 2013 and 2019, we identify job advertisements referring to AI-related skills. Matching this data to productivity data from ORBIS, we estimate the productivity effects of AI related activities in our sample. Our results indicate that AI-adoption increases productivity, with three important qualifications. Firstly, effects are only observable for large firms with more than 499 employees. Secondly, there is evidence that early adopters did not experience productivity increases. This may be interpreted as technological immaturity.Thirdly, we find evidence of delays of least three years between the adoption of AI and ensuing productivity effects (investment delay effect). We argue that our findings on the technological immaturity and the investment delay effect may help explain the so-called AI-related return of the Solow-paradox: I.e. that AI is everywhere except in the productivity statistics.
    Keywords: Recruiting personnel; AI related jobs; Artificial Intelligence; Job Market; Text Mining; Firm performance; Productivity
    JEL: D22 D24 O31 O32
    Date: 2022–02–15
  2. By: Nguyen, Bao Hoang (University of Queensland); Simar, Léopold (Université catholique de Louvain, LIDAM/ISBA, Belgium); Zelenyuk, Valentin (University of Queensland)
    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: 2021–09–08
  3. By: Aslund, Olof (Uppsala University); Bratu, Cristina (Aalto University); Lombardi, Stefano (VATT, Helsinki); Thoresson, Anna (IFAU)
    Abstract: We study the role of firm productivity in explaining earnings disparities between immigrants and natives using population-wide matched employer-employee data from Sweden. We find substantial earnings returns to working in firms with higher persistent productivity, with greater gains for immigrants from non-Western countries. Moreover, the pass-through of within-firm productivity variation to earnings is stronger for immigrants in low-productive, immigrant-dense firms. But immigrant workers are underrepresented in high-productive firms and less likely to move up the productivity distribution. Thus, sorting into less productive firms decreases earnings in poor-performing immigrant groups that would gain the most from working in high-productive firms.
    Keywords: firm productivity, immigrant-native earnings gaps, wage inequality
    JEL: J15 J31 J62
    Date: 2021–12
  4. By: Mulindi, Hillary
    Abstract: This study investigates the trade-off between costs and benefits of bank regulation in Kenya. Using the Stochastic Frontier Analysis (SFA) and Annual data for the period 2003 - 2019, extracted from KBA Financial Database and KNBS macroeconomic data, the study models Industry-level and cluster level relationship between bank regulation and cost inefficiency of banks. The industry-level analysis indicates that stringent capital requirement has a positive and significant effect on the cost-efficiency of banks, while tighter liquidity requirements hurt cost efficiency. Further, the bank tier-level analysis established that the double-layered regulatory framework creates Cost inefficiencies amongst middle-tier banks. The key policy implication would be to consider reviewing, identifying, and amending the regulatory provisions that are creating inefficiencies among the listed middle-tier banks
    Keywords: Bank Regulation,Cost-Benefit Analysis,Stochastic Frontier Analysis
    JEL: G28 D61 C24
    Date: 2021
  5. By: Frederiksen, Anders (Aarhus University); Hansen, Daniel Baltzer Schjødt (Aarhus University); Flaherty Manchester, Colleen (University of Minnesota)
    Abstract: Group-based incentive pay is attractive in contexts where production is complex and interdependent, yet freeriding is a paramount concern. We assess the introduction of group-based performance pay in a modern industrial production setting using difference-in-difference estimation. Performance increased by 19 percent, with three quarters coming from increased performance of existing workers and the remaining from selection; workers became more efficient and were absent less often. We find little evidence of freeriding; quantile regressions show increased performance throughout the distribution of workers. Features of the design and implementation process created trust, a common goal, and a shared identity, which limited freeriding.
    Keywords: difference-in-differences, performance pay, group-based incentive, freeriding, incentive effects, selection effects, absenteeism, efficiency, performance, productivity, trust
    JEL: M5 J33 L23
    Date: 2022–01
  6. By: Asaria, Miqdad; Mcguire, Alistair; Street, Andrew
    Abstract: There is a prevailing popular belief that expenditure on management by health-care providers is wasteful, diverts resources from patient care, and distracts medical and nursing staff from getting on with their jobs. There is little existing evidence to support either this narrative or counter-claims. We explore the relationship between management and public sector hospital performance using a fixed effects empirical econometric specification on a panel data set consisting of all 129 non-specialist acute National Health Service (NHS) hospitals in England for the financial years 2012/13 to 2018/19. Measures of managerial input and quality of management practice are constructed from NHS Electronic Staff Records and NHS Staff Survey data. Hospital accounts and Hospital Episode Statistics data are used to construct five measures of financial performance and of timely and high-quality care. We find no evidence of association either between quantity of management and management quality or directly between quantity of management and any of our measures of hospital performance. However, there is some evidence that higher-quality management is associated with better performance. NHS managers have limited discretion in performing their managerial functions, being tightly circumscribed by official guidance, targets, and other factors outside their control. Given these constraints, our findings are unsurprising.
    Keywords: personnel management; analysis of health care markets; firm performance; size; diversification and scope; panel data models; labor force and employment; structure; Visiting Research Fellowship
    JEL: C33 I11 J21 L25 M12
    Date: 2021–12–09
  7. By: Dongya Koh; Jingping Gu; Andrew Liu
    Abstract: Following the shocks of the COVID-19 pandemic, the economy may be significantly changed relative to the pre-pandemic world. One critical shift induced by the COVID-19 pandemic is a need for physical distance (at least 6 feet apart) between workers and customers. In this study, we examine the impacts of social distancing in the workplace on employment and productivity across industries. Using our constructed measure of adaptability to social distancing, we empirically find that industries that are more adaptive to social distancing had less decline in employment and productivity during the pandemic. Using this empirical evidence, our model predicts that employment and productivity dispersion would induce labor reallocation across sectors, while imperfect labor mobility may result in a long road to economic recovery.
    Date: 2022–02

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