Measuring and Accounting for Innovation in the Twenty-First Century
Carol Corrado, Jonathan Haskel, Javier Miranda, Daniel Sichel
NBER Studies in Income and Wealth,
2021
Abstract
Measuring innovation is challenging both for researchers and for national statisticians, and it is increasingly important in light of the ongoing digital revolution. National accounts and many other economic statistics were designed before the emergence of the digital economy and the growing importance of intangible capital. They do not yet fully capture the wide range of innovative activity that is observed in modern economies.
This volume examines how to measure innovation, track its effects on economic activity and prices, and understand how it has changed the structure of production processes, labor markets, and organizational form and operation in business. The contributors explore new approaches to, and data sources for, measurement—such as collecting data for a particular innovation as opposed to a firm, and the use of trademarks for tracking innovation. They also consider the connections between university-based R&D and business startups, and the potential impacts of innovation on income distribution.
The research suggests potential strategies for expanding current measurement frameworks to better capture innovative activity, such as more detailed tracking of global value chains to identify innovation across time and space, and expanding the measurement of the GDP impacts of innovation in fields such as consumer content delivery and cloud computing.
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Introduction to "Measuring and Accounting for Innovation in the Twenty-First Century"
Javier Miranda
Measuring and Accounting for Innovation in the Twenty-First Century,
NBER Studies in Income and Wealth, Vol 78 /
2021
Abstract
Measuring innovation is challenging both for researchers and for national statisticians, and it is increasingly important in light of the ongoing digital revolution. National accounts and many other economic statistics were designed before the emergence of the digital economy and the growing importance of intangible capital. They do not yet fully capture the wide range of innovative activity that is observed in modern economies. This volume examines how to measure innovation, track its effects on economic activity and prices, and understand how it has changed the structure of production processes, labor markets, and organizational form and operation in business. The contributors explore new approaches to, and data sources for, measurement—such as collecting data for a particular innovation as opposed to a firm, and the use of trademarks for tracking innovation. They also consider the connections between university-based R&D and business startups, and the potential impacts of innovation on income distribution. The research suggests potential strategies for expanding current measurement frameworks to better capture innovative activity, such as more detailed tracking of global value chains to identify innovation across time and space, and expanding the measurement of the GDP impacts of innovation in fields such as consumer content delivery and cloud computing.
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Identifying Cooperation for Innovation―a Comparison of Data Sources
Michael Fritsch, Mirko Titze, Matthias Piontek
Industry and Innovation,
No. 6,
2020
Abstract
The value of social network analysis is critically dependent on the comprehensive and reliable identification of actors and their relationships. We compare regional knowledge networks based on different types of data sources, namely, co-patents, co-publications, and publicly subsidized collaborative R&D projects. Moreover, by combining these three data sources, we construct a multilayer network that provides a comprehensive picture of intraregional interactions. By comparing the networks based on the data sources, we address the problems of coverage and selection bias. We observe that using only one data source leads to a severe underestimation of regional knowledge interactions, especially those of private sector firms and independent researchers.
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Who Buffers Income Losses after Job Displacement? The Role of Alternative Income Sources, the Family, and the State
Daniel Fackler, Eva Weigt
LABOUR: Review of Labour Economics and Industrial Relations,
No. 3,
2020
Abstract
Using survey data from the German Socio‐Economic Panel (SOEP), this paper analyses the extent to which alternative income sources, reactions within the household context, and redistribution by the state attenuate earnings losses after job displacement. Applying propensity score matching and fixed effects estimations, we find that income from self‐employment reduces the earnings gap only slightly and severance payments buffer losses in the short run. On the household level, we find little evidence for an added worker effect whereas redistribution by the state within the tax and transfer system mitigates income losses substantially.
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flexpaneldid: A Stata Toolbox for Causal Analysis with Varying Treatment Time and Duration
Eva Dettmann, Alexander Giebler, Antje Weyh
IWH Discussion Papers,
No. 3,
2020
Abstract
The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) for the staggered treatment adoption design and a Stata tool that implements the approach. This flexible conditional difference-in-differences approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations. Introducing more flexibility enables the user to consider individual treatment periods for the treated observations and thus circumventing problems arising in canonical difference-in-differences approaches. The open-source flexpaneldid toolbox for Stata implements the developed approach and allows comprehensive robustness checks and quality tests. The core of the paper gives comprehensive examples to explain the use of the commands and its options on the basis of a publicly accessible data set.
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Deleveraging and Consumer Credit Supply in the Wake of the 2008–09 Financial Crisis
Reint E. Gropp, J. Krainer, E. Laderman
International Journal of Central Banking,
No. 3,
2019
Abstract
We explore the sources of the decline in household nonmortgage debt following the collapse of the housing market in 2006. First, we use data from the Federal Reserve Board's Senior Loan Officer Opinion Survey to document that, post-2006, banks tightened consumer lending standards more in counties that experienced a more pronounced house price decline (the pre-2006 "boom" counties). We then use the idea that renters did not experience an adverse wealth or collateral shock when the housing market collapsed to identify a general consumer credit supply shock. Our evidence suggests that a tightening of the supply of non-mortgage credit that was independent of the direct effects of lower housing collateral values played an important role in households' non-mortgage debt reduction. Renters decreased their non-mortgage debt more in boom counties than in non-boom counties, but homeowners did not. We argue that this wedge between renters and homeowners can only have arisen from a general tightening of banks' consumer lending stance. Using an IV approach, we trace this effect back to a reduction in bank capital of banks in boom counties.
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Identifying Cooperation for Innovation – A Comparison of Data Sources
Michael Fritsch, Matthias Piontek, Mirko Titze
Abstract
The value of social network analysis is critically dependent on the comprehensive and reliable identification of actors and their relationships. We compare regional knowledge networks based on different types of data sources, namely, co-patents, co-publications, and publicly subsidised collaborative Research and Development projects. Moreover, by combining these three data sources, we construct a multilayer network that provides a comprehensive picture of intraregional interactions. By comparing the networks based on the data sources, we address the problems of coverage and selection bias. We observe that using only one data source leads to a severe underestimation of regional knowledge interactions, especially those of private sector firms and independent researchers. The key role of universities that connect many regional actors is identified in all three types of data.
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Who Benefits from GRW? Heterogeneous Employment Effects of Investment Subsidies in Saxony Anhalt
Eva Dettmann, Mirko Titze, Antje Weyh
IWH Discussion Papers,
No. 27,
2017
Abstract
The paper estimates the plant level employment effects of investment subsidies in one of the most strongly subsidized German Federal States. We analyze the treated plants as a whole, as well as the influence of heterogeneity in plant characteristics and the economic environment. Modifying the standard matching and difference-in-difference approach, we develop a new procedure that is particularly useful for the evaluation of funding programs with individual treatment phases within the funding period. Our data base combines treatment, employment and regional information from different sources. So, we can relate the absolute effects to the amount of the subsidy paid. The results suggest that investment subsidies have a positive influence on the employment development in absolute and standardized figures – with considerable effect heterogeneity.
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Foreign Direct Investment: The Role of Institutional and Cultural Determinants
Stefan Eichler, N. Lucke
Applied Economics,
No. 11,
2016
Abstract
Using panel data for 29 source and 65 host countries in the period 1995–2009, we examine the determinants of bilateral FDI stocks, focusing on institutional and cultural factors. The results reveal that institutional and cultural distance is important and that FDI has a predominantly regional aspect. FDI to developing countries is positively affected by better institutions in the host country, while foreign investors prefer to invest in developed countries that are more corrupt and politically unstable compared to home. The results indicate that foreign investors prefer to invest in countries with less diverse societies than their own.
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