|
on Technology and Industrial Dynamics |
| By: | Douglas Cumming; Randall Morck; Zhao Rong; Minjie Zhang |
| Abstract: | Because corporate limited liability protects founder’s personal assets, creditors often require founders of new, small and risky firms to contract around limited liability by pledging their personal assets as collateral for loans to their firms. This makes personal bankruptcy law (PBL) relevant to corporate finance. We find that pro-debtor PBL reforms increase the number of patents filed, citations to those patents, and début patents by firms with no previous patents. These reforms also redistribute innovation across industries in closer alignment to its distribution in the U.S., which we take to approximate industry innovative potential. These effects are driven by firms without histories of high-intensity patenting, and are damped in countries that impose minimum capital requirements on new firms. Firms with largescale legacy technology may avoid radical innovations that devalue that technology. Consequently, new, initially small and risky firms often develop the disruptive innovations that contribute most to economic growth. Consistent with this, we also find pro-debtor PBL reforms increasing value-added growth rates across all industries, and by larger margins in industries with more innovation potential. Our difference-in-differences regressions use patents and PBL reforms for 33 countries from 1990 to 2002, with subsequent years used to measure citations to patents in this period. |
| JEL: | G33 G5 K35 O3 O4 P1 P50 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:32826 |
| By: | Yao Lu; Gordon M. Phillips; Jia Yang |
| Abstract: | We examine the rise of cloud computing and AI in China and their impacts on industry dynamics after the shock to the cost of Internet-based computing power and services. We find that cloud computing is associated with an increase in firm entry, exit and the likelihood of M&A in industries that depend more on cloud infrastructure. Conversely, AI adoption has no impact on entry but reduces the likelihood of exit and M&A. Firm size plays a crucial role in these dynamics: cloud computing increases exit rates across all firms, while larger firms benefit from AI, experiencing reduced exit rates. Cloud computing decreases industry concentration but AI increases concentration. On the financing side, firms exposed to cloud computing increase equity and venture capital financing, while only large firms increase equity financing when exposed to AI. |
| JEL: | D25 G3 G34 L20 L23 L25 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:32811 |
| By: | Preißner, Stephanie; Raasch, Christina; Schweisfurth, Tim |
| Abstract: | This study investigates the sources of disruptive innovation. The disruptive innovation literature suggests that these do not originate from existing customers, in contrast to what is predicted by the user innovation literature. We compile a unique content-analytical dataset based on 60 innovations identified as disruptive by the disruptive innovation literature. Using multinomial and binomial regression, we find that 43% of the sample disruptive innovations were originally developed by users. Disruptive innovations are more likely to originate from users (producers) if the environment has high turbulence in customer preferences (technology). Disruptive innovations that involve high functional (technological) novelty tend to be developed by users (producers). Users are also more likely to be the source of disruptive process innovations and to innovate in environments with weaker appropriability. Our article forges new links between the disruptive and the user innovation literatures, and offers guidance to managers on the likely source of disruptive threats. |
| Keywords: | appropriability regime, disruptive innovation, environmental turbulence, functional novelty, radical innovation, user innovation |
| Date: | 2023 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ifwkie:293964 |
| By: | Bastani, Spencer (Uppsala University); Waldenström, Daniel (Research Institute of Industrial Economics, Stockholm) |
| Abstract: | This paper examines the implications of Artificial Intelligence (AI) and automation for the taxation of labor and capital in advanced economies. It synthesizes empirical evidence on worker displacement, productivity, and income inequality, as well as theoretical frameworks for optimal taxation. Implications for tax policy are discussed, focusing on the level of capital taxes and the progressivity of labor taxes. While there may be a need to adjust the level of capital taxes and the structure of labor income taxation, there are potential drawbacks of overly progressive taxation and universal basic income schemes that could undermine work incentives, economic growth, and long-term household welfare. Some of the challenges posed by AI and automation may also be better addressed through regulatory measures rather than tax policy. |
| Keywords: | AI, automation, inequality, labor share, optimal taxation, tax progressivity |
| JEL: | H21 H30 O33 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izapps:pp212 |
| By: | Mr. Daniel Garcia-Macia; Alexandre Sollaci |
| Abstract: | When and how should governments use industrial policy to direct innovation to specific sectors? This paper develops a framework to analyze the costs and benefits of industrial policies for innovation. The framework is based on a model of endogenous innovation with a sectoral network of knowledge spillovers (Liu and Ma 2023), extended to capture implementation frictions and alternative policy goals. Simulations show that implementing sector-specific fiscal support is only preferable to sector-neutral support under restrictive conditions—when externalities are well measured (e.g., greenhouse gas emissions), domestic knowledge spillovers of targeted sectors are high (typically in larger economies), and administrative capacity is strong (including to avoid misallocation to politically connected sectors). If any of these conditions are not fully met, welfare impacts of industrial policy quickly become negative. The optimal allocation of support entails greater subsidies to greener sectors, but other factors such as cross-sector knowledge spillovers matter. For a sample of technologically advanced economies, existing industrial policies seem to be directing innovation to broadly the right sectors, but to an excessive degree in most economies, including China and the United States. |
| Keywords: | Industrial policy; innovation; knowledge spillovers; climate policy; AI |
| Date: | 2024–08–16 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2024/176 |
| By: | Mons Chan; Guangbin Hong; Joachim Hubmer; Serdar Ozkan; Sergio Salgado |
| Abstract: | Do larger firms have more productive technologies or are their technologies more scalable, or both? We use administrative data on Canadian and US firms to estimate flexible nonparametric production functions. Our estimation results in a joint distribution of output elasticities of capital, labor, and intermediate inputs---therefore, returns to scale (RTS)---along with total factor productivity (TFP). We find significant heterogeneity in both RTS and TFP across firms. Larger firms operate technologies with higher RTS, both across and within industries. Higher RTS for large firms are entirely driven by higher intermediate input elasticities. Descriptively, these align with higher intermediate input revenue shares. We then incorporate RTS heterogeneity into an otherwise standard incomplete markets model with endogenous entrepreneurship that matches the observed heterogeneity in TFP and RTS. In this model, we find that the efficiency losses of financial frictions are more than twice as large relative to the conventional calibration that loads all heterogeneity on TFP and imposes a common RTS parameter. |
| Keywords: | production function heterogeneity; returns to scale; misallocation |
| JEL: | E22 L11 |
| Date: | 2024–07–11 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedlwp:98702 |
| By: | Nicola Gagliardi; Elena Grinza; François Rycx |
| 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 |
| JEL: | D24 J24 Q54 |
| Date: | 2024–08–22 |
| URL: | https://d.repec.org/n?u=RePEc:sol:wpaper:2013/377135 |
| By: | Key, Tomas (Bank of England); Lenney, Jamie (Bank of England) |
| Abstract: | In this paper, we examine the response of earnings and employment to fluctuations in aggregate economic activity (GDP) across the income distribution. Using data from the UK’s Labour Force Survey, we present evidence that aggregate fluctuations have economically significant but heterogeneous impacts across the income distribution. Sensitivity is greatest at the very bottom (first decile) of the income distribution and smallest in the upper middle (seventh and eight deciles) of the distribution. The transmission of GDP fluctuations also differs across the income distribution. Changes to hours worked and employment explain the majority of the labour earnings response in the bottom half of the distribution, whereas changes to the hourly wage are more important in the top half. In a further decomposition, we show that the changes to employment are largely due to fluctuations in the employment to unemployment transition rate. We also find that GDP fluctuations are positively correlated with job switching in the bottom half of the distribution. |
| Keywords: | Distributional effects; business cycles; income dynamics; labour markets |
| JEL: | E24 E32 J31 |
| Date: | 2024–08–06 |
| URL: | https://d.repec.org/n?u=RePEc:boe:boeewp:1083 |