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on Big Data |
| By: | Koski, Heli; Luukkonen, Juha |
| Abstract: | This paper empirically analyzes how markets value personal data related innovation in four prominent domains, in which firms’ potential to exploit value from data is identified to be considerable: finance, health, location-based services and artificial intelligence. We link the innovation economics literature to psychology-grounded financial economics theories of investor attention and salience theory. Our data from 117 large technology companies active in the ICT sector from the years 2007–2014 suggest that firms’ personal data related innovations and knowledge stocks in technology domains of location-based services and artificial intelligence contributed substantially to firm value. The premiums gained from personal data related innovation were particularly significant for data giants holding knowledge stocks in the location-based service domain. Our empirical results indicate that a strong positive relationship between personal data related knowledge stocks of the location-based services domain and firm value relates primarily to investor attention intensified during periods of media hype. Our data provide new insights into the market valuation of intangible assets: investors seem to overweight more salient right tails of firms’ knowledge stocks of emerging technologies while neglecting salient left tails. |
| Keywords: | Firm value, innovation, personal data, investor attention, saliency theory, technology salience |
| JEL: | D22 L2 O3 |
| Date: | 2018–05–25 |
| URL: | http://d.repec.org/n?u=RePEc:rif:wpaper:59&r=big |
| By: | Koski, Heli |
| Abstract: | Personal data is increasingly used in business value creation. Data from the years 2007–2014 suggest that firms’ personal data related innovations and knowledge stocks in technology domains of location-based services and artificial intelligence contributed substantially to firm value. The premiums gained from personal data related innovation were particularly significant for data giants holding knowledge stocks in the location-based service domain. Empirical findings indicate that a strong positive relationship between personal data related knowledge stocks of the location-based services domain and firm value relates primarily to investor attention intensified during periods of media hype. The data provide new insights into the market valuation of intangible assets: investors seem to overweight more salient right tails of firms’ knowledge stocks of emerging technologies while neglecting salient left tails. |
| Keywords: | Firm value, data economy, personal data, innovation, investor attention, technology salience |
| JEL: | D22 L2 O3 |
| Date: | 2018–05–25 |
| URL: | http://d.repec.org/n?u=RePEc:rif:briefs:66&r=big |
| By: | Fabien Labondance (Observatoire français des conjonctures économiques); Paul Hubert (Observatoire français des conjonctures économiques) |
| Abstract: | We explore empirically the theoretical prediction that optimism or pessimism have aggregate effects, in the context of monetary policy. First, we quantify the tone conveyed by FOMC policymakers in their statements using computational linguistics. Second, we identify sentiment as the unpredictable component of tone, orthogonal to fundamentals, expectations, monetary shocks and investors’ sentiment. Third, we estimate the impact of FOMC sentiment on the term structure of private interest rate expectations using a high-frequency methodology and an ARCH model. Optimistic FOMC sentiment increases policy expectations primarily at the one-year maturity. We also find that sentiment affects inflation and industrial production beyond monetary shocks. |
| Keywords: | Animal spirits; Optimism; Confidence; FOMC; Interest rate expectations; Central Bank Communication; Eurpean Central Bank; Aggregate Effects |
| JEL: | E43 E52 E58 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/64veevce0i99oav223j3pkv1hf&r=big |
| By: | HAMAGUCHI Nobuaki; KONDO Keisuke |
| Abstract: | This study investigates employment risk caused by new technology, such as artificial intelligence (AI) and robotics, using the probability of computerization by Frey and Osborne (2017) and Japanese employment data. The new perspective of this study is the consideration of regional heterogeneity in labor markets due to the uneven geographical distribution of occupations, which is especially observed between male and female workers. This study finds that female workers are exposed to higher risks of computerization than male workers, since they tend to be engaged in occupations with a high probability of computerization. This tendency is more pronounced in larger cities. Our results suggest that supporting additional human capital investment alone is not enough as a risk alleviation strategy against new technology, and policymakers need to address structural labor market issues, such as gender biases for career progression and participation in decision-making positions, in the AI era to mitigate unequal risk of computerization between workers. |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:18032&r=big |
| By: | Andrew Berg; Edward F Buffie; Luis-Felipe Zanna |
| Abstract: | We may be on the cusp of a “second industrial revolution” based on advances in artificial intelligence and robotics. We analyze the implications for inequality and output, using a model with two assumptions: “robot” capital is distinct from traditional capital in its degree of substitutability with human labor; and only capitalists and skilled workers save. We analyze a range of variants that reflect widely different views of how automation may transform the labor market. Our main results are surprisingly robust: automation is good for growth and bad for equality; in the benchmark model real wages fall in the short run and eventually rise, but “eventually” can easily take generations. |
| Date: | 2018–05–21 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:18/116&r=big |