Read All About it: What happens following a technology shock

By Michelle Alexopoulos. 2011

147 citations recorded by the source corpus.

For decades economists have searched for the sources of business cycle fluctuations. Early business cycle research focused on leading and lagging indicators and, while many of these are still employed today, they fail to provide insight into the sources of the fluctuations. Despite recent advances in economic modeling, there is still much debate as to the cause of recessions and expansions. In standard real business cycle models, a large component of the fluctuations is attributable to technology shocks. Unfortunately, technology and technology shocks are notoriously difficult to measure. To identify the responses of the economy to a technology shock, I use new data from Bowker’s Publications that documents the change in the number of new titles in technology that were available for purchase in the American economy from major publishers. My findings indicate that, in response to a positive technology shock, employment, total factor productivity and capital all significantly increase. Although my findings are different from those in other recent studies, they are consistent with the predictions of standard real business cycle models.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/54f4fe882053dbcb90f30d9b2ab8aae10985f31a

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In Economics and Econometrics

Citations in the corpus

Can News About the Future Drive the Business Cycle (2009, unknown): “Since in Section 3 we consider a version of the model with investment-specific technical progress, Figure 2 shows the response to a version of the same experiment in which there is a future increase in zt instead of in At.(2) Again consumption, investment, output, hours worked, average labor product”
Technological Innovation, Resource Allocation and Growth (2017, background): “Our aggregate innovation indices capture known periods of high technological progress as well as industries participating in these waves (Field, 2003; Alexopoulos and Cohen, 2009, 2011; Alexopoulos, 2011).”
News Driven Business Cycles: Insights and Challenges (2014, unknown): “One paper that is more closely related is Alexopoulos [2011]. Alexopoulos [2011] identifies dates where there are publications of books related to new technological developments.”
Technology Diffusion: Measurement, Causes and Consequences (2014, methodology): “We conclude our discussion of the measurement of technology by mentioning one recent approach proposed by Alexopoulos (2011). Her approach consists in measuring technology by the number of books published in the field of a particular technology.”
Measuring Technological Innovation over the Long Run (2018, unknown): “Though the measure in Alexopoulos (2011) overcomes many of the shortcomings of patent counts, it is only available at the aggregate level and for only the later part of the 20-th century.”
On the Cyclicality of R&D (2011, background): “6 While the causality may run from R&D to output, empirical literature has documented that R&D has an impact on output by long time lags, and only 20% of the outcome of R&D (patents) can actually contribute to later commercialized products (Alexopoulos, 2006; Basu, Fernald, & Kimball, 2006).”
Technological Innovation, Resource Allocation, and Growth (2012, unknown): “We compare our measure of aggregate innovation with three aggregate measures proposed in the literature: the log number of total patents granted; the log R&D expenditures from the BEA; and the log number of technology books published from Alexopoulos (2011).”
Uncertain Times, uncertain measures (2009, background): “2 Also, see Alexopoulos (2008) and Alexopoulos and Cohen (forthcoming) for publication based measures of technology change.”
Technological Innovations and Aggregate Risk Premiums (2009, unknown): “Moreover, there exist other technology statistics including the number of scientific journal articles (Price, 1963), the number of scientists and engineers (Gort, 1969), and the number of books published (Alexopoulos, 2006).”
The Quantitative Importance of News Shocks in Estimated DSGE Models (2012, background): “Alternatively, agents may respond to future gains in productivity due to the commercialization of products or processes (see Alexopoulos (2011)).”