2015
DOI: 10.1007/s40888-015-0013-z
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Business cycles, technology and exports

Abstract: This article shows-on both conceptual and empirical grounds-the importance of business cycles in affecting key relationships between innovation and international performance. While periods of upswing are characterised by a well documented "virtuous circle" between innovation inputs, new products and export success, during downswings most of the positive relationships and feedbacks tend to break down. The findings of Guarascio et al. (2014) on the long-term relationships between R&D, new products and exports ar… Show more

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Cited by 23 publications
(9 citation statements)
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“…In several studies on the employment impact of technology, demand-proxied by value added and by its components-has emerged as a key driver [83][84][85][86][87]; in particular, an expanding demand at the industry level is a necessary condition for allowing the job creation effects of product innovation to emerge.…”
Section: The Econometric Estimationmentioning
confidence: 99%
See 1 more Smart Citation
“…In several studies on the employment impact of technology, demand-proxied by value added and by its components-has emerged as a key driver [83][84][85][86][87]; in particular, an expanding demand at the industry level is a necessary condition for allowing the job creation effects of product innovation to emerge.…”
Section: The Econometric Estimationmentioning
confidence: 99%
“…We then compare the resulting coefficients in order to understand how the business cycle affects the relationships documented above, following the approach proposed in [93]; see also [84]. Table 5 shows the results.…”
Section: The Estimation For Business Cyclesmentioning
confidence: 99%
“…This sectoral classification extends the Pavitt's (1984) taxonomy to service industries, allowing us to appropriately distinguish between high-tech and low-tech industries according to the structure of the market and the nature, sources and appropriability of knowledge. On this basis, we classify Science based and Specialised supplier industries as high-tech sectors, while Scale and information intensive and Supplier dominated industries are included in the low-tech sectoral cluster (Bramucci et al 2017;Coveri and Pianta 2019;Guarascio et al 2015;Guarascio and Pianta 2016;Reljic et al 2019). 3 Once stated our technology-based classification of sectors and took stock of the extant conceptual and empirical literature on technological regimes, we finally have all the ingredients to formulate our second hypothesis:…”
Section: Heterogeneity In the Effects Of Nswmentioning
confidence: 99%
“…In this context, it is just worth noting the inclusion of the variable related to the foreign sourcing of high-tech intermediate inputs, which allows to account for the modern international fragmentation of production (Milberg and Winkler 2013) while also capturing its technological dimension. In particular, we took advantage of the offshoring indicator proposed by Feenstra and Hanson (1996) as amended by Guarascio et al (2015) to discriminate imported intermediate inputs according to their technological content. By exploiting the World Input-Output Tables (WIOT) provided by WIOD (Timmer et al 2015), we thus built this indicator by computing the ratio between the sum of the expenditure devoted by each industry to the acquisition of intermediate inputs from foreign high-tech industries over the expenditure for the total (domestically produced and foreign) intermediate inputs used for production by each sector.…”
Section: The Sid Databasementioning
confidence: 99%
“…The specification in (3) constitutes an enhancement with respect to the previous models exploring the determinants of innovation in industries. In particular, we follow the contributions examining jointly the impact on industries' innovative performance in technology-push and demand-pull factorssee, among the others, Crespi and Pianta (2007), Guarascio et al (2015 and , by adding variables that explicitly account for PP and import penetration of PP.…”
Section: The Modelmentioning
confidence: 99%