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on Efficiency and Productivity |
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Issue of 2022‒11‒28
twelve papers chosen by |
| By: | G. Jacob Blackwood; Cindy Cunningham; Matthew Dey; Lucia S. Foster; Cheryl Grim; John C. Haltiwanger; Rachel L. Nesbit; Sabrina Wulff Pabilonia; Jay Stewart; Cody Tuttle; Zoltan Wolf |
| Abstract: | An important gap in most empirical studies of establishment-level productivity is the limited information about workers’ characteristics and their tasks. Skill-adjusted labor input measures have been shown to be important for aggregate productivity measurement. Moreover, the theoretical literature on differences in production technologies across businesses increasingly emphasizes the task content of production. Our ultimate objective is to open this black box of tasks and skills at the establishment-level by combining establishment-level data on occupations from the Bureau of Labor Statistics (BLS) with a restricted-access establishment-level productivity dataset created by the BLS-Census Bureau Collaborative Micro-productivity Project. We take a first step toward this objective by exploring the conceptual, specification, and measurement issues to be confronted. We provide suggestive empirical analysis of the relationship between within-industry dispersion in productivity and tasks and skills. We find that within-industry productivity dispersion is strongly positively related to within-industry task/skill dispersion. |
| JEL: | C81 E23 O33 |
| Date: | 2022–11 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30620&r=eff |
| By: | Wildmer Daniel Gregori (European Commission); Maria Martinez Cillero (European Commission); Michela Nardo (European Commission) |
| Abstract: | This study empirically investigates the extent to which firms in the European Union, once acquired through a cross-border acquisition, show different productivity levels as compared to those firms that have not been acquired. Our identification strategy relies on the combination of Propensity Scores and the Staggered Difference-in-Difference estimator, using firms’ balance sheet for the years 2008-2018. We find that cross-border acquisitions decrease the productivity of the acquired firms, especially in the manufacturing sector, both high- and low-tech. We find evidence of origin and sector heterogeneity. Firms targeted by acquirers with ultimate owners originating in emerging market economies and Offshore Financial Centres also decrease productivity of target firms in high-tech manufacturing. |
| Keywords: | Cross-border M&As, TFP, European Union, Propensity Score, DiD |
| JEL: | G |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:inf:wpaper:2022.10&r=eff |
| By: | Karmakar, Sudipto (Bank of England); Melolinna, Marko (Bank of England); Schnattinger, Philip (Bank of England) |
| Abstract: | This paper studies the effects of different types of investment and levels of debt on productivity in the UK, using firm-level data. We set out a stylised model of a dynamic firm profit-maximisation problem, and augment this model with an external financing option in a novel way. We use the model to illustrate why productivity-enhancing investment differs from other uses of company funds in terms of its effects on total factor productivity (TFP), and how these positive effects can be stronger for firms that have higher indebtedness. We then examine the issue empirically with data on listed firms in the UK. Our main finding is that intangibles investment are a good proxy for productivity-enhancing investment, as they have a positive effect on TFP, and in those firms that have high debt and high levels of intangibles, these effects are even more pronounced. On the other hand, we find no consistent evidence of positive TFP effects for other uses of funds, like tangible capital expenditure or dividends and equity buybacks. The effects of debt on TFP are smaller and more tenuous, but we find no evidence of a negative TFP effect of debt in firms that have high levels of intangibles intensity. |
| Keywords: | Dynamic programming; firm-level productivity; intangible assets; panel regression |
| JEL: | C61 D22 D24 O30 |
| Date: | 2022–07–15 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0992&r=eff |
| By: | Dacic, Nikola; Melolinna, Marko (Bank of England) |
| Abstract: | We study two key characteristics of producers in a production network – size and centrality – and their relationship, which are intimately related to the extent of shock transmission in production networks, both at a macro and micro level. Our contributions are fourfold. First, we show empirically that the UK’s production network has significant asymmetries in producer centrality, varies over time, and yields an empirical size-centrality relationship that tends to be positive in and outside of steady state. Second, we set up a static multisector model with a production network which allows us to link producer size and centrality to underlying shocks in the economy. We show that as long as input substitutability is less than unitary, technology shocks tend to induce negative (positive) co-movement between real output (Domar weights) and outdegrees, unlike preference shocks which tend to induce a positive size-centrality relationship. Third, we calibrate a dynamic model featuring a production network to UK data and use it to filter out technology and demand shocks. The implied size-centrality relationship from the filtered shocks confirms the intuition from the static model. Finally, we use this model to analyse the UK’s post-2010 productivity growth slowdown from a production network perspective, distinguishing industries’ accounting contributions from the contributions of industry-specific and common shocks. We find that idiosyncratic shocks to the manufacturing sector have played a key role in driving the aggregate productivity slowdown. |
| Keywords: | Business cycle; aggregate productivity; productivity puzzle; input-output linkages; production network |
| JEL: | E23 E24 E32 |
| Date: | 2022–09–27 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0994&r=eff |
| By: | Bradley Pycroft; Aleksandar Vasilev |
| Abstract: | This study represents a new way of looking at health, by investigating the effect of aggregate cancer incidence rates on labour productivity, using a macroeconomic methodology. The health of the labour force is a key determinant of labour productivity, with poor health comes both physical and mental stresses that corrode the productive capacity of workers. Within this study, cancer was selected as an approximation of labour force health, given its ability to capture a range of lifestyle choices. Workers afflicted by cancer often face three choices: continue working, temporarily/permanently leave employment or retire early – all resulting in productivity loss. Moreover, the effect on productivity may not just be felt by the patient but also their family. This creates a negative externality, the result of which is additional productivity loss. The study used an autoregressive distributed lag (ARDL) model to assess the impact of cancer rates in the short-run and long-run. The results were clear, with cancer rates having a significant short-run one year lagged effect on labour productivity. With a 10% short-run lagged increase in cancer rates, leading to a loss of -$1711 in labour productivity per worker – using 2010 GDP per worker. In the long-run, the effect was positive suggesting cancer does not impact long-run economic growth. This research offers a new insight into the mechanics of health within the environment of macroeconomics. With this study potentially unlocking a new avenue of productivity policy framework, aimed at health improvement rather than more traditional approaches involving training and technological advancement. |
| Keywords: | Labour Productivity, Health Economics, Cancer, UK Productivity, Productivity Growth |
| JEL: | E24 E32 I10 J24 |
| Date: | 2022–09–12 |
| URL: | http://d.repec.org/n?u=RePEc:eei:rpaper:eeri_rp_2022_12&r=eff |
| By: | Clara Kögel (OCDE - Organisation de Coopération et de Développement Economiques = Organisation for Economic Co-operation and Development, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | This paper investigates the effect of air pollution on labour productivity in French establishments in both manufacturing and non-financial market services sectors from 2001 to 2018. An instrumental variable approach based on planetary boundary layer height and wind speed allows identifying the causal effect of air pollution on labour productivity. The finding shows that a 10% increase in fine particulate matter leads, on average, to a 1.5% decrease in labour productivity, controlling for firm-specific characteristics and other confounding factors. The analysis also considers different dimensions of heterogeneity driving this adverse effect. The negative effect of pollution is mainly driven by service-intensive firms and sectors with a high share of highly skilled workers. This finding is in line with the expectation that air pollution affects cognitive skills, concentration, headache, and fatigue in non-routine cognitive tasks. Compared to an estimation of the marginal abatement cost of PM 2.5 reductions by the Air Quality Directive 2008/50/EC, gains only from the labour productivity channel are equivalent to one-third of the abatement cost over the implementation period. All in all, these estimates suggest that the negative impact of air pollution is much larger than previously documented in the literature. |
| Keywords: | air pollution,labour productivity,planetary boundary layer height |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-03837884&r=eff |
| By: | Mahyar Adibi; Keun Lee |
| Abstract: | This paper analyzes the importance of investment climate (IC), international integration (II), and innovation system (IS) variables on firm productivity. These variables are measured at the firm, sector, and country levels, and the interaction effects among them are also investigated. Multilevel-mixed effect analysis is conducted using the World Bank Enterprise Survey data for 20 developing countries in 21 sectors. Results indicate that firm-level variables tend to be more robust than sector- or country-level variables, and that more II variables are shown be significant than either IC or IS variables. Specifically, sector-level II variables are significant, whereas sector-level IC variables and sector-level R&D variables are not significant. Sector-level IC and IS variables become significant only when they interact with firm-level variables. The results underscore the importance of firm-level capabilities, which can be enhanced by II (e.g., firm-level learning by exporting and Foreign Direct Investment (FDI) arrangement) and IS (e.g., firm-level education and training), as well as by spillover from sector-level II and human capital. Results also reveal the channels through which IC may affect firm productivity. IC exhibits an effect on firm productivity when it interacts with firm-level capabilities and activities. |
| Keywords: | Firm Productivity; Innovation Systems; Investment Climate; International Integration; Multilevel Analysis; Developing Country; |
| JEL: | O10 O29 O30 O57 |
| Date: | 2022–11 |
| URL: | http://d.repec.org/n?u=RePEc:snu:ioerwp:no151&r=eff |
| By: | De Haas, Ralph (European Bank for Reconstruction and Development, CEPR and KU Leuven); Sterk, Vincent (University College London and CEPR); Van Horen, Neeltje (Bank of England) |
| Abstract: | Can policymakers improve macroeconomic performance by encouraging the entry of high‑performance start‑ups? To answer this question, we construct a novel and comprehensive data set on 1.3 million start‑ups in 10 European countries. We apply cluster analysis to identify distinct start‑up types and trace their development over time. Three stylised facts transpire. First, we uncover five well‑separated start‑up types that are consistently present across countries, industries, and cohorts. We label these basic, large, capital‑intensive, cash‑intensive, and high‑leverage. Second, the initial differences between these start‑up types are persistent. Third, each start‑up type displays a characteristic life cycle in terms of productivity, employment generation, and exit rates. We feed these empirical results into an agnostic firm dynamics model to quantify how much structural policy could improve macroeconomic performance by shifting the composition of start‑ups. We find that substantial gains in aggregate employment and productivity can be made through policies that benefit high‑performance start‑ups (such as large and capital‑intensive ones) while discouraging the entry of underperforming firms (such as highly leveraged ones). |
| Keywords: | Start‑ups; firm entry; productivity; corporate tax; entrepreneurship; cluster analysis. |
| JEL: | D22 D24 G32 L11 L25 L26 O47 |
| Date: | 2022–06–17 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0986&r=eff |
| By: | David C. Chan Jr; Yiqun Chen |
| Abstract: | Professions play a key role in determining the division of labor and the returns to skilled work. This paper studies the productivity difference between physicians and nurse practitioners (NPs), two health care professions performing overlapping tasks but with stark differences in background, training, and pay. Using data from the Veterans Health Administration and quasi-experimental variation in the patient probability of being treated by physicians versus NPs in the emergency department, we find that, compared to physicians, NPs significantly increase resource utilization but achieve worse patient outcomes. We find evidence suggesting mechanisms relating to lower human capital among NPs relative to physicians and worker-task assignment responding to the lower skill of NPs. Counterfactual analysis suggests a net increase in medical costs with NPs, even when accounting for NPs’ wages that are half as much as physicians’. Despite large productivity differences between professions, we find even larger productivity differences within professions and substantial productivity overlap between professions. Yet there is little overlap in wages between NPs and physicians and, within professions, no significant correlation between productivity and wages. |
| JEL: | I11 I18 J24 J44 M53 |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30608&r=eff |
| By: | Jaretzky, Huong; Liebenehm, Sabine; Waibel, Hermann |
| Abstract: | With the increasing complexity of farming in the developing countries in Asia and the growing challenge arising from climate change, management, technical knowledge, and skills become more and more important for smallholder farmers. So far, little is known about how knowledge, skills, and cognitive abilities of farm decision-makers affect agricultural productivity. Most empirical studies lack the necessary parameters to adequately measure knowledge and skills and often rely on simple parameters like educational attainment and years of formal schooling. However, to generate a better understanding of how knowledge and skills enable farmers to meet the challenges of increasingly obstacle farming environments, more direct measures of education are needed. This paper investigates the impact of farmers’ knowledge on agricultural productivity by making use of specific agricultural knowledge questions and management tests conducted with 1,290 small-scale farmers in two provinces in Thailand and Vietnam, carried out in 2014. Applying OLS and 2SLS approaches and combining the knowledge and skills test results with productivity data of later waves allows for identifying the effect of agricultural knowledge and skills on agricultural productivity. Results show that farmers’ specific agriculture knowledge is significantly and positively associated with profits but significantly negative with yields and total input costs. Hence, better farmers may strive for optimal instead of maximum yields, are more judicious in the use of inputs, and as a result, make more money in rice production. |
| Keywords: | Education; Knowledge; Skills; Human Capital; Agricultural Productivity |
| JEL: | D83 O15 I25 |
| Date: | 2022–11 |
| URL: | http://d.repec.org/n?u=RePEc:han:dpaper:dp-702&r=eff |
| By: | Dutcher, Glenn; Saral, Krista |
| Abstract: | Remote work policies remain controversial mainly because of productivity concerns. The existing literature highlights how the remote setting affects individual productivity yet little is known about how the remote setting affects work in teams - where productivity losses are potentially higher given the additional role of beliefs over partner productivity. Our study closes this gap by examining the effort of individuals randomly assigned to work in either a remote or office setting with partners who are remote and office based. We find that remote workers contribute more effort to the team than office workers, with no differences based on the location of their partners. Office workers incorrectly believe their remote teammates' contributions will be lower and respond by contributing less effort to the team when paired with remote partners versus office partners. Hence, productivity issues in remote teams are driven by the biased beliefs of office workers rather than true productivity differences, which suggests that managerial policies should focus on correcting these incorrect beliefs rather than limiting remote work. |
| Keywords: | Telecommuting, Remote Work, Team Production, Productivity, Economic Experiments |
| JEL: | C7 C9 J0 |
| Date: | 2022–11–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:115253&r=eff |
| By: | Kyogo Kanazawa; Daiji Kawaguchi; Hitoshi Shigeoka; Yasutora Watanabe |
| Abstract: | We examine the impact of Artificial Intelligence (AI) on productivity in the context of taxi drivers. The AI we study assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI improves drivers’ productivity by shortening the cruising time, and such gain is accrued only to low-skilled drivers, narrowing the productivity gap between high- and low-skilled drivers by 14%. The result indicates that AI's impact on human labor is more nuanced and complex than a job displacement story, which was the primary focus of existing studies. |
| JEL: | J22 J24 L92 R41 |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30612&r=eff |