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on Efficiency and Productivity |
| By: | Olga Kutnohorská (University of Chemistry and Technology, Prague); Dana Strachotová (University of Chemistry and Technology, Prague); Marek Botek (University of Chemistry and Technology, Prague); Stanislava Grosová (University of Chemistry and Technology, Prague) |
| Abstract: | This study analyses the productivity of selected chemical industry companies in the Czech Republic through Data Envelopment Analysis (DEA). The selection of companies for analysis was based on the amount of turnover and also according to the field of business. The enterprises were grouped into 4 groups. The first group A represents qualified chemistry, followed by group B (commodity inorganic and organic chemistry), group C (processing of plastics or rubbers) and group D (distribution of raw materials). The Malmquist productivity index (MPI) was used to analyse changes in the productivity of companies, and the statistical significance of these indices was tested using. This procedure helped identify the influence of various factors on the efficiency and productivity of companies, including the influence of the area of business. The study showed other possibilities of using this procedure. E.g., in the case of inclusion of environmental costs or investments in the field of the environment. |
| Keywords: | Field of business of chemical industry company, Data envelopment analysis, Malmquist productivity index, Financial statements |
| JEL: | C10 D20 |
| URL: | https://d.repec.org/n?u=RePEc:sek:iefpro:14716504 |
| By: | Francesco Filippucci; Peter Gal; Matthias Schief |
| Abstract: | The paper studies the expected macroeconomic productivity gains from Artificial Intelligence (AI) over a 10-year horizon. It builds a novel micro-to-macro framework by combining existing estimates of micro-level performance gains with evidence on the exposure of activities to AI and likely future adoption rates, relying on a multi-sector general equilibrium model with input-output linkages to aggregate the effects. Its main estimates for annual aggregate total-factor productivity growth due to AI range between 0.25-0.6 percentage points (0.4-0.9 pp. for labour productivity). The paper discusses the role of various channels in shaping these macro-level gains and highlights several policy levers to support AI's growth-enhancing effects. |
| Keywords: | Artificial Intelligence, Productivity, Technology adoption |
| JEL: | E1 O3 O4 O5 |
| Date: | 2024–11–22 |
| URL: | https://d.repec.org/n?u=RePEc:oec:comaaa:29-en |
| By: | Ariel Burstein; Javier Cravino; Marco Rojas |
| Abstract: | We leverage a comprehensive dataset of electronic invoices from Chilean firms to document new facts on price dispersion across buyers of manufactured intermediate goods. Over half of firm-to-firm manufacturing sales are accounted for by products that are purchased by more than one buyer in the same month. Price dispersion across buyers is pervasive, with a price range across buyers of 46 percentage points for the average product. Price gaps are highly persistent over time and strongly correlated across different products purchased by the same buyer. While price disparities comove with observable characteristics of buyer-seller pairs—such as size of the buyer and the transaction—these factors account for a small portion of the overall variation in price gaps. We use a workhorse model of production networks to quantify the productivity gains from eliminating observed dispersion in prices across buyers of the same product, under the assumption that this dispersion is driven by buyer-product specific markups. The increase in aggregate productivity (normalized by the sales share of treated multi-buyer firms) ranges from 2 to 7 percent, depending on the calibration of elasticities of substitution. The gains from eliminating markup dispersion across buyers are as large as those of eliminating markup dispersion across products. |
| JEL: | D22 D24 D4 E02 O4 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33128 |
| By: | James Bono; Justin Grana; Alec Xu |
| Abstract: | We measure the association between generative AI (GAI) tool adoption and security operations center productivity. We find that GAI adoption is associated with a 30.13% reduction in security incident mean time to resolution. This result is robust to several modeling decisions. While unobserved confounders inhibit causal identification, this result is among the first to use observational data from live operations to investigate the relationship between GAI adoption and security worker productivity. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.03116 |
| By: | Leonardo Bortolan; Atreya Dey; Luca Taschini |
| Abstract: | We establish the financial materiality of temperature variability by demonstrating its impact on US firms and investors. A long-short strategy that sorts firms based on exposure earns a market-adjusted alpha of 39 basis points per month. This variability metric is related to aggregate decreases in firm profitability, with asymmetric effects across industries. These outcomes are driven by reductions in consumer demand and labor productivity coupled with changes in media and investor attention. The geographically scalable statistical framework provides a reference for assessing the quantitative effects of climate-related physical risks, offering a metric for improving the disclosure of material climate risks. |
| Keywords: | corporate climate reporting, climate attention, temperature variability, stock returns, firm performance |
| JEL: | C21 C23 G12 G32 Q54 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11438 |
| By: | Thomas Licht; Klaus Wohlrabe |
| Abstract: | This paper examines the adoption of Artificial Intelligence (AI) among German firms, leveraging firm-level data from the ifo Business Survey. We analyze the diffusion of AI across sectors and firm sizes, showing a significant increase in AI usage from 2023 to 2024, particularly in manufacturing and services. The survey data allows us to explore not only sectoral patterns of adoption but also the drivers and barriers that firms face, including firm-specific characteristics and industry dynamics. Additionally, we investigate the role of managerial traits, such as risk tolerance and patience, in shaping AI adoption decisions. Finally, we assess the potential pro-ductivity impacts of AI at the firm level, with a focus on the expected long-term benefits of AI for different sectors of the German economy. Our findings contribute to the growing body of research on AI adoption by providing new evidence from a non-US context, offering valuable insights for both academia and politics. |
| Keywords: | artificial intelligence, AI, ifo business survey, productivity |
| JEL: | M15 O30 C83 L20 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11459 |
| By: | Scur, Daniela; Ohlmacher, Scott W.; Van Reenen, John; Bennedsend, Morten; Bloom, Nick; Choudhary, M. Ali; Foster, Lucia; Groenewegen, Jesse; Grover, Arti; Hardemanh, Sjoerd; Iacovone, Leonardo; Kambayashi, Ryo; Laible, Marie-Christine; Lemos, Renata; Li, Hongbin; Linarello, Andrea; Maliranta, Mika; Medvedevi, Denis; Mengo, Charlotte; Touya, John Miles; Mandirola, Natalia; Ohlsbom, Roope; Ohyamas, Atsushi; Patnaik, Megha; Pereira-López, Mariana; Sadun, Raffaella; Senga, Tatsuro; Qian, Franklin; Zimmermann, Florian |
| Abstract: | A country’s national income broadly depends on the quantity and quality of workers and capital. But how well these factors are managed within and between firms may be a key determinant of a country’s productivity and its GDP. Although social scientists have long studied the role of management practices in shaping business performance, their primary tool has been individual case studies. While useful for theory-building, such qualitative work is hard to scale and quantify. We present a large, scalable dataset measuring structured management practices at the business level across multiple countries. We measure practices related to performance monitoring, target-setting, and human resources. We document a set of key stylized facts, which we label “the international empirics of management”. In all countries, firms with more structured practices tend to also have superior economic performance: they are larger in scale, are more profitable, have higher labor productivity and are more likely to export. This consistency was not obvious ex-ante, and being able to quantify these relationships is valuable. We also document significant variation in practices across and within countries, which is important in explaining differences in the wealth of nations. The positive relationship between firm size and structured management practices is stronger in countries with more open and free markets, suggesting that stronger competition may allow firms with more structured management practices to grow larger, thereby potentially raising aggregate national income. |
| Keywords: | management practices; productivity; firm performance; misallocation |
| JEL: | J1 J50 |
| Date: | 2024–11–05 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:125967 |
| By: | Francesco Giffoni; Emanuela Sirtori; Louis Colnot |
| Abstract: | This paper addresses how to assign a monetary value to scientific publications, particularly in the case of multi-author papers arising from large-scale research collaborations. Contemporary science increasingly relies on extensive and varied collaborations to tackle global challenges in fields such as life sciences, climate science, energy, high-energy physics, astronomy, and many others. We argue that existing literature fails to address the collaborative nature of research by overlooking the relationship between coauthorship and scientists productivity. Using the Marginal Cost of Production (MCP) approach, we first highlight the methodological limitations of ignoring this relationship, then propose a generalised MCP model to value co-authorship. As a case study, we examine High-Energy Physics (HEP) collaborations at the Large Hadron Collider (LHC) at CERN, analysing approximately half a million scientific outputs by over 50, 000 authors from 1990 to 2021. Our findings indicate that collaborative adjustments yield monetary valuations for subsets of highly collaborative papers up to 3 orders of magnitude higher than previous estimates, with elevated values correlating with high research quality. This study contributes to the literature on research output evaluation, addressing debates in science policy around assessing research performance and impact. Our methodology is applicable to authorship valuation both within academia and in large-scale scientific collaborations, fitting diverse research impact assessment frameworks or as self-standing procedure. Additionally, we discuss the conditions under which this method may complement survey-based approaches. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.10278 |
| By: | Tacsir, Ezequiel; Pereira, Mariano; Favata, Federico; Leone, Julian |
| Abstract: | Using a multilevel analysis and the new Harmonized Latin American Innovation Surveys Database (or LAIS database) augmented with indicators from the U.S. Census Bureau's Survey of Business Owners (SBO) and the World Banks World Integrated Trade Solution (WITS), this paper presents estimates of the effects of import competition and distance to the technological frontier on firm innovation in Latin American countries. Although innovation is recognized as a multilevel phenomenon, with investment decisions not solely affected by the firm characteristics but also by the context in which each firm is embedded, the empirical literature adopting a multilevel design is still nascent and scarce. Using a two-level random slope model allows us to overcome some of the pitfalls of traditional regression models when dealing with the hierarchical structure of data while allowing us to capture the influence of contextual factors. The results suggest that the fostering effect of foreign competition depends on the firms distance to the technological frontier. The estimates suggest that the lower the foreign competition and the greater the productivity gap, the lower the probability of firms engaging in innovation. In contrast, when a firm operates in a sector that is relatively closer to the technological frontier, firms invest in innovative activities to remain at the top. These results offer a clear and useful guide for designing policies in Latin America regarding innovation among firms. While it is important to promote and stimulate innovation efforts by firms, these factors should not be overlooked as considerations: sectoral characteristics associated with the economies, sectoral openness to foreign competition, and firms distance to the technological frontier. |
| Keywords: | innovation;Latin America;multilevel modeling;LAIS database;Productivity;Competition |
| JEL: | O31 O32 C21 C25 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:13833 |
| By: | Saul Estrin; Andrea Herrmann; Moren Levesque; Tomasz Mickiewicz; Mark Sanders |
| Abstract: | We present a Schumpeterian growth model with new venture creation, under uncertainty, which explains the tradeoff between speed-to-breakeven, revenue-at-breakeven and relates this to the level of innovation. We then explore the tradeoffs between these outcomes empirically in a unique sample of 331 information and communication technology (ICT) ventures using a multi-input, multi-output stochastic frontier model. We estimate the contribution of financial capital and labor input to the outcomes and the tradeoffs between them, as well as address heterogeneity across ventures. We find that more innovative (and therefore more uncertain) ventures have lower speed-to-breakeven and/or lower revenue-at-breakeven. Moreover, for all innovativeness levels, new ventures face a tradeoff between speed-to-breakeven and revenue-at-breakeven. Our results suggest that it is the availability of proprietary resources (founder equity and labor) that helps ventures overcome bottlenecks in the innovation process, and we propose a line of research to explain the (large) unexplained variation in venture creation efficiency. Plain English Summary. This study examines how new businesses deal with uncertainty, focusing on the tradeoff between how quickly they become profitable (speed-to-breakeven) and how much revenue they generate when they do. We analyze data from 331 ICT ventures to understand these tradeoffs better, considering factors like financial resources and labor inputs. We find that more innovative ventures, which tend to be more uncertain, often take longer to reach profitability and may earn less when they do. Moreover, regardless of their level of innovation, all new ventures face a tradeoff between speed-to-breakeven and revenue. The study highlights that unique resources, such as founder equity and founder labor, help businesses overcome challenges in the innovation process. It also suggests further research to understand why some ventures are more efficient than others in the early stage of creating new businesses. |
| Keywords: | entrepreneurship, innovation, new venture creation, proprietary resources, stochastic frontier analysis, Schumpeterian growth model |
| Date: | 2024–11–15 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2054 |
| By: | Yuan, Boning |
| Abstract: | Using panel data from 35 listed banks' annual reports and corporate social responsibility reports from 2009 to 2022 as a sample, this study empirically examines the impact of green credit on the performance of commercial banks and takes China Merchants Bank as the case analysis object. Based on the theory of green finance, this paper discusses the function mechanism of the effect of green credit on commercial banks by empirical method, heterogeneity analysis and robustness test. Then, using the specific business data of China Merchants Bank in the field of green credit and its business performance data, the paper further reveals the specific impact of green credit on the business performance of the bank. The research shows that commercial banks have improved their asset income ability through green credit, significantly enhanced their operating efficiency in social responsibility and risk control, and positively impacted the overall operating effect. Finally, this paper suggests that green credit can positively promote commercial banks' performance and point out a new path for the sustainable development and social responsibility of commercial banks. This research has not only contributed to theory but also provided important reference for practice. |
| Date: | 2024–11–03 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:xk6ew |