26 research outputs found
Data-intensive innovation and the State: evidence from AI firms in China
Artificial intelligence (AI) innovation is data-intensive. States have historically collected large amounts of data, which is now being used by AI firms. Gathering comprehensive information on firms and government procurement contracts in China’s facial recognition AI industry, we first study how government data shapes AI innovation. We find evidence of a precise mechanism: because data is sharable across uses, economies of scope arise. Firms awarded public security AI contracts providing access to more government data produce more software for both government and commercial purposes. In a directed technical change model incorporating this mechanism, we then study the trade-offs presented by states’ AI procurement and data pro-vision policies. Surveillance states’ demand for AI may incidentally promote growth, but distort innovation, crowd-out resources, and infringe on civil liberties. Government data provision may be justified when economies of scope are strong and citizens’ privacy concerns are limited
AI-tocracy
Can frontier innovation be sustained under autocracy? We argue that innovation and autocracy can be mutually reinforcing when: (i) the new technology bolsters the autocrat's power; and (ii) the autocrat's demand for the technology stimulates further innovation in applications beyond those benefiting it directly. We test for such a mutually reinforcing relationship in the context of facial recognition AI in China. To do so, we gather comprehensive data on AI firms and government procurement contracts, as well as on social unrest across China during the last decade. We first show that autocrats benefit from AI: local unrest leads to greater government procurement of facial recognition AI, and increased AI procurement suppresses subsequent unrest. We then show that AI innovation benefits from autocrats' suppression of unrest: the contracted AI firms innovate more both for the government and commercial markets. Taken together, these results suggest the possibility of sustained AI innovation under the Chinese regime: AI innovation entrenches the regime, and the regime's investment in AI for political control stimulates further frontier innovation
Data-intensive innovation and the state: evidence from AI firms in China
Developing AI technology requires data. In many domains, government data far exceeds in magnitude and scope data collected by the private sector, and AI firms often gain access to such data when providing services to the state. We argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses. We gather comprehensive information on firms and public security procurement contracts in China’s facial recognition AI industry. We quantify the data accessible through contracts by measuring public security agencies’ capacity to collect surveillance video. Using a triple-differences strategy, we find that data-rich contracts, compared to data-scarce ones, lead recipient firms to develop significantly and substantially more commercial AI software. Our analysis suggests a contribution of government data to the rise of China’s facial recognition AI firms, and that states’ data collection and provision policies could shape AI innovation
Regional Heterogeneity and the Refinancing Channel of Monetary Policy
We argue that the time-varying regional distribution of housing equity influences the aggregate consequences of monetary policy through its effects on mortgage refinancing. Using detailed loan-level data, we show that regional differences in housing equity affect refinancing and spending responses to interest rate cuts, but these effects vary over time with changes in the regional distribution of house price growth. We build a heterogeneous household model of refinancing with mortgage borrowers and lenders and use it to explore the monetary policy implications arising from our regional evidence. We find that the 2008 equity distribution made spending in depressed regions less responsive to interest rate cuts, thus dampening aggregate stimulus and increasing regional consumption inequality, whereas the opposite occurred in some earlier recessions. Taken together, our results strongly suggest that monetary policy makers should track the regional distribution of equity over time
Replication Data for: 'Regional Heterogeneity and the Refinancing Channel of Monetary Policy'
The programs replicate tables and figures from "Regional Heterogeneity and the Refinancing Channel of Monetary Policy", by Beraja, Fuster, Hurst, and Vavra
Government as venture capitalists in AI
Venture capital plays an important role in funding and shaping innovation outcomes, characterized by investors’ deep knowledge of the technology, industry, and institutions, as well as their long-running relationships with the entrepreneurship and innovation community. China, in its pursuit of global leadership in AI innovation and technology, has set up government venture capital funds so that both national and local governments act as venture capitalists. These government-led venture capital funds combine features of private venture capital with traditional government innovation policies. In this paper, we collect comprehensive data on China’s government and private venture capital funds. We draw three important contrasts between government and private VC funds: (i) government funds are spatially more dispersed than private funds; (ii) government funds invest in firms with weaker ex-ante performance signals but these firms exhibit growth rates exceeding those of firms in which private funds invest; and (iii) private VC funds follow government VC investments, especially when hometown government funds directly invest on firms with weaker ex-ante performance signals. We interpret these patterns in light of VC funds’ traditional role overcoming information frictions and China’s unique institutional environment, which includes important frictions on mobility and information
AI-tocracy
Recent scholarship has suggested that artificial intelligence technology and autocratic regimes may be mutually reinforcing. We test for such a mutually reinforcing relationship in the context of facial recognition AI in China. To do so, we gather comprehensive data on AI firms and government procurement contracts, as well as on social unrest across China during the last decade. We first show that autocrats benefit from AI: local unrest leads to greater government procurement of facial recognition AI as a new technology of political control, and increased AI procurement indeed suppresses subsequent unrest. We then show that AI innovation benefits from autocrats’ suppression of unrest: the contracted AI firms innovate more both for the government and commercial markets, and are more likely to export their products; and non-contracted AI firms do not experience detectable negative spillovers. Taken together, these results suggest the possibility of sustained AI innovation under the Chinese regime: AI innovation entrenches the regime, and the regime’s investment in AI for political control stimulates further frontier innovation
Replication Data for: 'From Hyperinflation to Stable Prices: Argentina's Evidence on Menu Cost Models'
The data and programs replicate tables and figures from "From Hyperinflation to Stable Prices: Argentina's Evidence on Menu Cost Models", by Alvarez, Beraja, Gonzalez-Rozada, and Neumeyer. Please see the Readme file for additional details