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on Business Economics |
| By: | Julian Di Giovanni (Federal Reserve Bank of New York, CEPR - Center for Economic Policy Research - CEPR); Andrei A Levchenko (University of Michigan System, NBER - National Bureau of Economic Research [New York] - NBER - The National Bureau of Economic Research, CEPR - Center for Economic Policy Research - CEPR); Isabelle Mejean (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique, CEPR - Center for Economic Policy Research - CEPR) |
| Abstract: | This paper uses a dataset covering the universe of French firm-level value added, imports, and exports over the period 1995-2007 and a quantitative multi-country model to study the international transmission of business cycle shocks at both the micro and the macro levels. Because the largest firms are the most likely to trade internationally, foreign shocks are transmitted to the domestic economy primarily through the large firms. We first document a novel stylized fact: larger French firms are significantly more sensitive to foreign GDP growth. We then implement a quantitative framework calibrated to the full extent of the observed heterogeneity in firm size, exporting, and importing. We simulate the propagation of foreign shocks to the French economy and report one micro and one macro finding. At the micro level heterogeneity across firms predominates: 45 to 75% of the impact of foreign fluctuations on French GDP is accounted for by the "foreign granular residual"-the term capturing the larger firms' greater responsiveness to the foreign shocks. At the macro level, firm heterogeneity attenuates the impact of foreign shocks, with the GDP responses 10 to 20% larger in a representative firm model compared to the baseline model. |
| Keywords: | granularity, shock transmission, aggregate fluctuations, input linkages, international trade |
| Date: | 2023–04–27 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-04208350&r=bec |
| By: | IKEUCHI Kenta; INUI Tomohiko; KIM YoungGak |
| Abstract: | The use of Artificial Intelligence (AI) in business has been expanding in recent years, and there is growing interest in the mechanisms and extent to which AI affects firm performance. In this study, we analyze the impact of firms’ introduction of AI on their performance using the "Basic Survey of Japanese Business Structure and Activities" of the Ministry of Economy, Trade and Industry (METI), Japan, TSR's business-to-business transaction data, press release data from NIKKEI, and IIP patent database 2020. In addition to the introduction of AI-related patents generated by a company's own R&D activity, we also try to analyze the impact of the introduction of AI within their trading partners (suppliers and customers). In addition to the efficiency gains in production processes (process innovation), the study analyzes the creation of new products and improvements in existing products (product innovation). The main results from the analyses are as follows. (1) AI-related patents positively correlate with firm productivity and have a stronger relationship with productivity than non-AI patents. (2) The relationship between AI-related patents and firm productivity strengthened even after 2009 when the number of patent applications began to decline. (3) AI-related patents mainly contribute to the productivity of firms with productivity in middle or higher status within the industry, while AI-related patents have a negative impact on the productivity of firms with low productivity. (4) We cannot confirm that the introduction of AI by a firm's business partner has a positive or negative spillover effect on the productivity of that firm. (5) AI-related patents are strongly related to product innovation, process innovation, and technological innovation of the firms, and especially high-quality AI-related patents have a mid-term and important impact on innovation. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:eti:rdpsjp:23034&r=bec |
| By: | Tomohiro Ara |
| Abstract: | This paper develops a dynamic industry model to study the effect of search frictions on industry structure and aggregate welfare. We consider a search-theoretic setting with two types of agents, firms and suppliers. To customize inputs, each firm needs to find a supplier but search is costly and does not always end in success. Matched firms use customized inputs obtained from matched suppliers to enhance production efficiency, while unmatched firms use generic inputs obtained from a competitive input market. In equilibrium the number of unmatched and matched firms is endogenous. We use this model to contrast the implications of two forms of economic integration: integration of final-good markets allowing firms to export varieties to another market, and integration of matching markets allowing firms to seek suppliers from another market. We show that the former form of integration can amplify the welfare gains from trade by improving firms’ matching frequency associated with resource reallocations from unmatched firms to matched firms. In contrast, the latter might cause welfare losses by hindering the resource-reallocation process of firms. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:toh:tupdaa:42&r=bec |
| By: | Ahmed, Rafayal; Shopp, Colin |
| Abstract: | We analyze firms’ incentives to acquire information about market demand in a differentiated goods duopoly setting. We find two distinct benefits of having better information. Firstly, with better information, each firm can better match its price to demand. This benefit is decreasing in the level of market competition. Secondly, better information allows each firm to coordinate their prices with each other in different states, and each firm can make better use of its own information if the other firm acquires better information. This benefit is inverse u-shaped in the level of competition. Based on which effect dominates, each firm’s total benefit from information can either be decreasing, or inverse u-shaped in the level of competition. Given endogenous information acquisition decisions by firms, the effect of competition on consumer welfare is ambiguous. |
| Keywords: | Information acquisition, Bertrand duopoly, signals, competition. |
| JEL: | D43 D81 D84 L13 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:118311&r=bec |
| By: | Dominik Jurek |
| Abstract: | Do patents facilitate market entry and job creation? Using a 2014 Supreme Court decision that limited patent eligibility and natural language processing methods to identify invalid patents, I find that large treated firms reduce job creation and create fewer new establishments in response, with no effect on new firm entry. Moreover, companies shift toward innovation aimed at improving existing products consistent with the view that patents incentivize creative destruction. |
| Keywords: | intellectual property rights, creative destruction, entry, job creation, Alice decision, natural language processing |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:cen:wpaper:23-45&r=bec |
| By: | Orlando Gomes (Lisbon Accounting and Business School); Roxana Mihet (University of Lausanne, Swiss Finance Institute and CEPR); Kumar Rishabh (University of Basel and University of Lausanne) |
| Abstract: | In this paper, we formulate a growth model of the data economy, highlighting data's dual role as a business optimization tool and a cybercrime target. We investigate the impact of cybercrime on firm innovation and economic growth, finding that it unequivocally leads to reduced knowledge stocks, decreased productivity, and slower overall economic growth for all firms. However, there is a silver lining: cybercrime risk prompts data-intensive companies to pursue digital innovation, enhancing productivity in other domains. We observe increased R&D, patenting, and patent diversity in response to higher cyber risk, especially among data-intensive firms. Non-data-intensive firms do not exhibit increased general innovation in response to cyber risk. Notably, in-house cybersecurity innovation sustains this cycle, while third-party cybersecurity delegation lacks the same innovation benefits. |
| Keywords: | Data economy, data theft, data breaches, cyber-risk, growth, artificial intelligence, innovation |
| JEL: | D8 O3 O4 G3 L1 L2 M1 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp2386&r=bec |
| By: | Catalina Amuedo-Dorantes; Esther Arenas-Arroyo; Parag Mahajan; Bernhard Schmidpeter (Economics, Johannes Kepler University Linz) |
| Abstract: | We examine how migrant workers impact firm performance using administrative data from the United States. Exploiting an unexpected change in firms' likelihood of securing low-wage workers through the H-2B visa program, we find limited crowd-out of other forms of employment and no impact on average pay at the firm. Yet, access to H-2B workers raises firms' annual revenues and survival likelihood. Our results are consistent with the notion that guest worker programs can help address labor shortages without inflicting large losses on incumbent workers. |
| Keywords: | guest workers, migrants, employment, firm dynamics, H-2B visa |
| JEL: | J23 F22 J61 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:jku:econwp:2023-10&r=bec |
| By: | Cusato, Antonio; Castillo, José Luis; IDB Invest |
| Abstract: | We exploit the staggered expansion of the internet broadband network to firms and bank branches locations in Peru during the last decade to study non-financial firm performance and bank credit dynamics. Access to broadband unleashes firm growth, increases the chances of entry of firms and reduces the probability of exit in benefited locations. For those firms that had a borrowing relation with a bank before the expansion of broadband, the increase in sales serves as a signal to banks about their profitability, which in turn respond by providing more credit. Entry and exit from the credit market follows a similar pattern as in the case of firms, but the results take longer to materialize after the shock. We can disentangle supply and demand effects, since there is a group of firms and bank branches with different locations and asymmetrical timing for the availability of the technology. Our analysis highlights the importance of the demand channel in the reduction of the observed interest rates, which is consistent with the fact that our credit market results are concentrated among micro and small firms, and firms with thin credit files, which are often perceived as riskier. |
| Keywords: | Compliance;accountability;Norms;Sanctions;Argentina |
| JEL: | O33 L86 G21 |
| Date: | 2023–06 |
| URL: | http://d.repec.org/n?u=RePEc:idb:brikps:12922&r=bec |
| By: | Arnaud Dupuy (Department of Economics and Business Economics, University of Luxembourg); John Kennes (Department of Economics and Business Economics, Aarhus University); Ran Sun Lyng (Tampere University) |
| Abstract: | We use a two-sided multidimensional matching model with imperfect transferable utility to estimate how CEOs/firms trade off preferred firm/CEO qualities against salary. These preferences are identifiable with data on CEO pecuniary compensation and assignment. We estimate the model with high-quality Danish data through maximum likelihood, accounting for CEO and firm fixed effects. The estimates reveal that CEOs have strong preferences for non-monetary job amenities that account for several puzzling features of the market for CEOs. The central role of CEO job preferences is also illustrated by several counterfactual experiments. |
| Keywords: | Job amenities, CEO compensation, Assignment Models, CEO-firm matching, Multidimensional matching |
| JEL: | G30 M12 G34 J32 C78 C35 |
| Date: | 2023–09–25 |
| URL: | http://d.repec.org/n?u=RePEc:aah:aarhec:2023-08&r=bec |
| By: | Kristina McElheran; J. Frank Li; Erik Brynjolfsson; Zachary Krof; Emin Dinlersoz; Lucia Foster; Nikolas Zolas |
| Abstract: | We study the early adoption and diffusion of five AI-related technologies (automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition) as documented in the 2018 Annual Business Survey of 850, 000 firms across the United States. We find that fewer than 6% of firms used any of the AI-related technologies we measure, though most very large firms reported at least some AI use. Weighted by employment, average adoption was just over 18%. Among dynamic young firms, AI use was highest alongside more-educated, more-experienced, and younger owners, including owners motivated by bringing new ideas to market or helping the community. AI adoption was also more common in startups displaying indicators of high-growth entrepreneurship, such as venture capital funding, recent innovation, and growth-oriented business strategies. Adoption was far from evenly spread across America: a handful of “superstar” cities and emerging technology hubs led startups’ use of AI. These patterns of early AI use foreshadow economic and social impacts far beyond its limited initial diffusion, with the possibility of a growing “AI divide” if early patterns persist. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:cen:wpaper:23-48&r=bec |