|
on Efficiency and Productivity |
| By: | Nicola Gagliardi (CEBRIG and DULBEA, Solvay Brussels School of Economics and Management, Université Libre de Bruxelles); Elena Grinza (Department of Economics, Social Studies, Applied Mathematics and Statistics, University of Turin); François Rycx (CEBRIG and DULBEA, Solvay Brussels School of Economics and Management, Université Libre de Bruxelles. IRES (UCLouvain)) |
| Abstract: | In this paper, we investigate the impact of rising temperatures on firm productivity using longitudinal firm-level balance-sheet data from private sector firms in 14 European countries, combined with detailed weather data, including temperature. We begin by estimating firms’ total factor productivity (TFP) using control-function techniques. We then apply multiple-way fixed-effects regressions to assess how higher temperature anomalies affect firm productivity – measured via TFP, labor productivity, and capital productivity. Our findings reveal that global warming significantly and negatively impacts firms’ TFP, with the most adverse effects occurring at higher anomaly levels. Labor productivity declines markedly as temperatures rise, while capital productivity remains unaffected – indicating that TFP is primarily affected through the labor input channel. Our moderating analyses show that firms involved in outdoor activities, such as agriculture and construction, are more adversely impacted by increased warming. Manufacturing, capital-intensive, and blue-collar-intensive firms, compatible with assembly-line production settings, also experience significant productivity declines. Geographically, the negative impact is most pronounced in temperate and mediterranean climate areas, calling for widespread adaptation solutions to climate change across Europe. |
| Keywords: | Climate change, Global warming, Firm productivity, Total factor productivity (TFP), Semiparametric methods to estimate production functions, Longitudinal firm-level data |
| JEL: | D24 J24 Q54 |
| Date: | 2024–08–21 |
| URL: | https://d.repec.org/n?u=RePEc:ctl:louvir:2024010 |
| By: | Kelly Cobourn; Christopher O'Donnell; Jesús Antón; Ben Henderson |
| Abstract: | This paper proposes an analytical framework to calculate an environmentally sustainable productivity index (ESPI) to address the multiple challenges faced at present by food systems. Using this framework, an empirical analysis covering 28 countries (anonymised) over three decades examines sustainable productivity performance including three environmental externalities: greenhouse gas emissions, and nitrogen and phosphorus surpluses. The results illustrate how the framework could be used to identify trends in environmentally sustainable productivity within and across countries. While this framework is flexible and can accommodate multiple environmental variables, its application requires appropriate and comparable data on agriculture production and related environmental performance, selecting methods to measure and aggregate groups of outputs and inputs into the productivity index, and choosing a weight for environmental externalities relative to commodity outputs. Sensitivity analyses, as well as comparisons with other approaches to measure sustainable productivity can be undertaken using this framework to ensure the robustness of the measurement. By supporting cross-section comparisons, the ESPI also has the potential to be used in statistical analysis to identify the economic and policy drivers of sustainable productivity performance. |
| Keywords: | Environmental sustainability, Index theory, Total Factor Productivity |
| JEL: | C43 D24 O44 Q18 |
| Date: | 2024–10–23 |
| URL: | https://d.repec.org/n?u=RePEc:oec:agraaa:213-en |
| By: | Bertin Martens |
| Abstract: | This working paper explores the tension between rapidly increasing artificial intelligence investment costs and the slower pace of productivity growth |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:bre:wpaper:node_10375 |
| By: | Chatzistamoulou, Nikos; Koundouri, Phoebe |
| Abstract: | The European Green Deal prioritizes green growth through resource efficiency and eco-innovation to achieve the transition in a sustainable and inclusive growth orbit. To monitor progress in such endeavor the EU Resource Efficiency Scoreboard was launched. Focusing on the resource productivity, which is the main sustainability development indicator and policy evaluation tool for Europe and the eco-innovation performance of the EU-28 over a twenty-year period, from 2000 though 2019, we explore convergence patterns and club formation. Descriptive analysis via growth rates of the resource productivity and eco-innovation indicates productivity differentials among the countries giving rise to heterogeneity groups. Econometric results using convergence algorithms advocate in favor of convergence for both variables. However, convergence clubs surface highlighting that there is heterogeneity to consider when designing policies to promote sustainability transition to ensure that no one is left behind serving the priority of inclusive and sustainable growth. |
| Keywords: | Resource Productivity, Eco-Innovation, Sustainability, Convergence, Technological Heterogeneity, European Green Deal |
| JEL: | O1 O3 |
| Date: | 2022–12 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:122104 |
| By: | Busso, Matías; Fentanes, Oscar |
| Abstract: | What determines the aggregate and distributional effects of new transportation infrastructure? One key overlooked channel is the role that infrastructure policy plays in changing the incentives of firms to enter, exit, and grow--in turn generating endogenous changes in local productivity. In this paper, we document and quantify the importance of this channel by using detailed Mexican microdata and a spatial general-equilibrium model that incorporates firm dynamics. Leveraging random delays in the construction of highways, we empirically show that productivity grows in places with better transportation infrastructure. Firms play a critical role in driving these results: highways increase firms' size, entry rates, survival rates, and total factor productivity. Then, by calibrating our model on census data between 1998 and 2018, we find that new highways over this period increased welfare and income by half a percent, similar to its costs in terms of GDP. Moreover, we find substantial spatial reallocation of workers and production. Nearly half of these effects are explained by endogenous changes in local productivity, which is driven by firm dynamics. |
| Keywords: | Economic geography;firm dynamics;Infrastructure |
| JEL: | R12 D24 O18 O54 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:13759 |
| By: | Elisa Fusco (Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", Università di Firenze); Giuseppe Arbia (Dipartimento di Scienze Statistiche, Università Cattolica del Sacro Cuore, Roma); Francesco Vidoli (Dipartimento di Economia, Società , Politica (DESP), Università degli Studi di Urbino Carlo Bo); Vincenzo Nardelli (Università Cattolica del Sacro Cuore, Roma) |
| Abstract: | In the literature on stochastic frontier models until the early 2000s, the joint consideration of spatial and temporal dimensions was often inadequately addressed, if not completely neglected. However, from an evolutionary economics perspective, the production process of the decision-making units constantly changes over both dimensions: it is not stable over time due to managerial enhancements and/or internal or external shocks, and is influenced by the nearest territorial neighbours. This paper proposes an extension of the Fusco and Vidoli (2013) SEM-like approach, which globally accounts for spatial and temporal effects in the term of inefficiency. In particular, coherently with the stochastic panel frontier literature, two different versions of the model are proposed: the time-invariant and the time-varying spatial stochastic frontier models. In order to evaluate the inferential properties of the proposed es- timators, we first run Monte Carlo experiments and then present the results of an application to a set of commonly referenced data, demonstrating robustness and stability of estimates across all scenarios. |
| Keywords: | Stochastic frontier analysis, Spatio-temporal effects, Productive efficiency |
| JEL: | C21 D24 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:fir:econom:wp2024_09 |
| By: | Benoit Dostie; Genevieve Dufour |
| Abstract: | To what extent is the increase in inequality in business productivity reflected in wage inequality? The answer essentially depends on the degree to which productivity differentials are transmitted into wage differentials. In this study, the authors examine this issue using data from the Canadian Employer-Employee Dynamics Database (CEEDD) for the period 2001–2019 and identify a set of stylized facts. From 2001 to 2019, there has been an unequivocal increase in productivity inequalities between firms in Quebec, a result that is consistent with we observe in a number of other countries. This upward trend is greater in Quebec than in Ontario. It is interesting to compare this rise in productivity inequality with the decrease in income inequality. One possible explanation is that the transmission of productivity differences to income differences also decreased over the period. A number of possibilities could explain this decrease, and one of them would be a decrease in labour mobility. The authors examine this issue by decomposing productivity growth for the particular case of the manufacturing sector. They show that productivity growth in this sector is primarily driven by within-firm productivity growth. Labour reallocation and net input do not contribute much to productivity growth. Dans quelle mesure l’augmentation des inégalités dans la productivité des entreprises se reflète-t-elle dans les inégalités de salaires?? La réponse dépend essentiellement du degré de transmission des différentiels de productivité en différentiels salariaux. Dans cette étude, les auteurs examinent cette question à partir des données de la Base de données canadienne sur la dynamique employeurs-employés (BDCEE) pour la période 2001-2019 et dégagent un ensemble de faits stylisés. De 2001 à 2019, on observe une hausse sans équivoque des inégalités de productivité entre les entreprises au Québec, un résultat conforme à ce qu'on observe dans plusieurs autres pays. Cette tendance à la hausse est plus importante au Québec qu'en Ontario. Il est intéressant de contraster cette hausse des inégalités de productivité à la baisse des inégalités de revenus. Une explication possible est que la transmission des différences de productivité en différences de revenus ait aussi diminué au cours de la période. Plusieurs possibilités pourraient expliquer cette diminution et l’une d’elles serait une diminution de la mobilité de la main-d’œuvre. Les auteurs examinent cette question en effectuant des décompositions de la croissance de la productivité pour le cas particulier du secteur manufacturier. Ils montrent que la croissance de la productivité dans ce secteur provient très majoritairement de la croissance de la productivité à l’intérieur de l’entreprise. La réallocation de main-d’œuvre et l’effet net d’entrée contribuent assez peu à la croissance de la productivité. |
| Keywords: | Productivity, Inequality, Companies, Labour market, Productivité, Inégalités, Entreprises, Marché du travail |
| Date: | 2024–10–15 |
| URL: | https://d.repec.org/n?u=RePEc:cir:cirpro:2024rp-19 |
| By: | Fangchen Song; Ashish Agarwal; Wen Wen |
| Abstract: | Generative artificial intelligence (AI) has opened the possibility of automated content production, including coding in software development, which can significantly influence the participation and performance of software developers. To explore this impact, we investigate the role of GitHub Copilot, a generative AI pair programmer, on software development in open-source community, where multiple developers voluntarily collaborate on software projects. Using GitHub's dataset for open-source repositories and a generalized synthetic control method, we find that Copilot significantly enhances project-level productivity by 6.5%. Delving deeper, we dissect the key mechanisms driving this improvement. Our findings reveal a 5.5% increase in individual productivity and a 5.4% increase in participation. However, this is accompanied with a 41.6% increase in integration time, potentially due to higher coordination costs. Interestingly, we also observe the differential effects among developers. We discover that core developers achieve greater project-level productivity gains from using Copilot, benefiting more in terms of individual productivity and participation compared to peripheral developers, plausibly due to their deeper familiarity with software projects. We also find that the increase in project-level productivity is accompanied with no change in code quality. We conclude that AI pair programmers bring benefits to developers to automate and augment their code, but human developers' knowledge of software projects can enhance the benefits. In summary, our research underscores the role of AI pair programmers in impacting project-level productivity within the open-source community and suggests potential implications for the structure of open-source software projects. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.02091 |
| By: | Tomás R. Martinez; Thiago Trafane Oliveira Santos |
| Abstract: | Assessments of the role played by misallocation in shaping total factorproductivity (TFP) have been hindered by constraints in the availability of firm-level data.This paper addresses this issue by developing a static Cournot model that primarily requires standard macroeconomic data to estimate market-power-driven misallocation.We apply this framework to decompose aggregate TFP into technology and allocative efficiency components from 1950 to 2019 for up to a hundred countries from the Penn World Table10.01. Utilizing this decomposition, we revisit key facts of economic growth. On the one hand, we evaluate the world income frontier as proxied by the US, finding that changes in misallocation can significantly impact short-run growth. On the other hand, we examine the economic performance around the world. We conclude misallocation enhances our understanding of cross-country income differences, eventhough a substantial unexplained portion persists. We also find a lack of convergence in allocative efficiency, suggesting market-power-driven misallocation is linked, in the long run, to long-lasting country-specific factors such as institutions. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:bcb:wpaper:603 |
| By: | Diao, Xinshen; Jones, Eleanor; Pauw, Karl; Thurlow, James; Xu, Wenqian |
| Abstract: | Agricultural transformation, in broad terms, is the process during which the agricultural sector develops from a low-productivity, subsistence-oriented sector to a modern, commercially oriented one. It typically involves adopting advanced technologies and more sustainable and efficient production practices, and results in higher agricultural productivity per worker, agricultural diversification into high-value crops, and rising rural incomes. Importantly, agricultural transformation is also seen as a catalyst for broader economic development and a structural shift towards industrialization in developing economies. Given the central role of agricultural transformation in driving such change, as well as its contribution to development objectives such as poverty reduction, improvements in diet quality, and environmental sustainability, it is useful to measure and monitor progress on agricultural transformation. This is the purpose of the Agricultural Transformation Index (ATI), a newly developed composite index constructed from four indicators of progress on agricultural transformation: staple crop productivity, crop diversification, agricultural labor productivity, and food system expansion. Together, these indicators, which are calculated from publicly available, global datasets, can be used to examine progress over time on global, regional, and national scales. In addition to being transparent and easy to interpret, the index can be updated annually as new data is released. As demonstrated in this study, the ATI produces a plausible ranking of countries and is highly correlated with indicators of overall economic wellbeing such as GDP per capita or household-specific welfare measures such as poverty or the prevalence of undernourishment. The ATI is not only useful for identifying countries in need of support from international development partners or tracking their progress on agricultural transformation but can also highlight specific areas of agricultural transformation where technical or investment support might be directed by governments or their partners. |
| Keywords: | agricultural transformation; economic development; productivity; structural adjustment |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:ifprid:2275 |
| By: | Tony ShunTe Yuo; Tai-Hsi Wu; Yu-An Yang |
| Abstract: | The analytical model of the social-ecological system structure is designed to explore spatial environmental performance from a holistic, complex, dynamic, network-oriented, and nonlinear perspective. In this research, we employ the Social-Ecological System (SES) framework proposed by Ostrom (2009) and McGinnis and Ostrom (2014) to construct a model capturing the characteristics of Taiwan's real estate market in relation to social and ecological spatial diversity. Utilizing Dynamic Network Data Envelopment Analysis (DNDEA), we conduct performance measurements for the SES model. This framework encompasses various real estate market features, including resource systems, ecological and environmental indicators, government governance, and characteristics of real estate market sectors. The study observes dynamic interactions over multiple years. By incorporating assessments of indicators such as social, industrial, energy, ecological, pollution, and healthcare, central and local governments can optimize relevant policies based on comprehensive social and ecological characteristics in addressing the real estate market.This research is funded by the Ministry of Science and Technology: 111-2410-H-305 -055 -MY2McGinnis, M. D., & Ostrom, E. (2014). Social-ecological system framework: initial changes and continuing challenges. Ecology and Society, 19(2).Ostrom, E. (2009). A general framework for analyzing sustainability of social-ecological systems. Science, 325(5939), 419-422. |
| Keywords: | ESG in Real Estate; Human and Environment coupled; Social-Ecological System; Sustainable Development |
| JEL: | R3 |
| Date: | 2024–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:arz:wpaper:eres2024-074 |