Innovative growth: the role of market power and negative selection

Piekkola, Hannu; Rahko, Jaana

doi:10.1080/10438599.2019.1655878

Cited by 8 publications

(7 citation statements)

References 51 publications

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“…Internationalization and, hence, trade has been shown in the literature to increase the innovation input in the form of R&D, which may help to generate new product innovations, see Keller and Shiue (2008), Piekkola and Rahko (2019). It can be seen that export intensity promotes OC -IBTC, while import intensity relates positively to R&D-IBTC.…”

Section: Estimation Resultsmentioning

confidence: 99%

“…In the survey, half of firms have 250 employees or more with full coverage and rest is a sample of SMEs. Piekkola and Rahko (2019) shows that R&D defined in this way has in their sample high coverage of over 80% of firms, while survey R&D is reported only in 24% service firms and 44% manufacturing firms.…”

Section: Data and The Measurement Of Iamentioning

confidence: 93%

“…Productivity growth or the growth of output is likely to be a less significant factor for measuring the success of intangibles among SMEs. Piekkola and Rahko (2019) explain this by the large fixed costs in innovations and access to market, which causes negative selection among the fast growing SMEs. In a "negative selection mechanism," firms with low initial productivity and profitability invest only in innovations with the highest productivity growth.…”

Section: Literaturementioning

confidence: 99%

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Intangibles and innovation-labor-biased technical change

Piekkola

2020

JIC

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PurposeThis paper analyzes the productivity effects of structural capital such as research and development (R&D) and organizational capital (OC). Innovation work also produces innovation-labor-biased technical change (IBTC) and knowledge spillovers. Analyses use full register-based dataset of Finnish firms for the period 1994–2014 from Statistics Finland.Design/methodology/approachIntangibles are derived from the labor costs of innovation-type occupations using linked employer-employee data. The approach is consistent with National Accounting and offered as one method in OECD (2010) and applied in statistical offices, e.g. in measuring software. The EU 7th framework Innodrive project 2008–2011 extended this method to cover R&D and OC.FindingsMethodology is implementable at firm-level and offers way to link personnel reporting to intangible assets. The OC-IBTC as well as total resources allocated to OC are relevant for productivity growth. The R&D stock is relatively higher but R&D-IBTC is smaller than OC-IBTC. Public policy should, besides technology policy, account for OC and OC-IBTC and related knowledge spillovers in the industries that are most important among the SMEs (low market-share-firms).Research limitations/implicationsThe data are based on remote access to Statistics Finland; the data cannot be disseminated.Originality/valueIntangible assets are measured from innovation work that encompasses not only R&D work. IBTC is proxied in production function estimation by relative compensations on IA work. The non-competing nature of IAs is captured by IA knowledge spillovers. The sample sizes are much higher than in earlier studies on horizontal knowledge spillovers (such as for SMEs,) thus bringing additional generality to the results.

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Section: Estimation Resultsmentioning

confidence: 99%

Section: Data and The Measurement Of Iamentioning

confidence: 93%

Section: Literaturementioning

confidence: 99%

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Intangibles and innovation-labor-biased technical change

Piekkola

2020

JIC

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“…Other studies (Aghion et al, 2005;Gilbert, 2006;Piekkola and Rahko, 2020) challenged Schumpeter's theory that monopoly power is more conducive to innovation. Aghion et al, (2014) for instance find that firms that have lower level of competition have a lower incentive to invest in research and development.…”

Section: Innovation and Market Structure In Oecd Countriesmentioning

confidence: 99%

“…Other studies (Aghion et al. , 2005; Gilbert, 2006; Piekkola and Rahko, 2020) challenged Schumpeter’s theory that monopoly power is more conducive to innovation. Aghion et al.…”

Section: Literature Reviewmentioning

confidence: 99%

On the role of innovation and market structure on trade performance: is Schumpeter right?

Guei

2022

EJMBE

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PurposeThe goal of the paper is to examine the dynamics between innovation, market structure and trade performance. Firstly, the author first investigates the effects of innovation on trade performance. Secondly, the author then examines how market structure affect trade by classifying industries based on their innovation intensity.Design/methodology/approachThe author uses a detailed level data set of eight OECD countries in a panel of 17 industries from the STAN and ANBERD Database. The author employs both a pooled regression and a two-stage quantile regression analysis. The author first investigates the effects of innovation at the aggregate level, and then the author assesses the effects at the disaggregated or firm level.FindingsThe author finds that at the aggregate level, innovation and market size have a positive and significant effect on competitivity in most of the specifications. However, innovation is negatively associated with trade performance in the case of bilateral trade between Spain and the Netherlands. Also, the sectoral analysis provides evidence that the innovation-trade nexus depends on technological classification. The author shows that: (1) the effect of innovation activity on trade performance economic performance is lower for the high technology and high concentration (HTHC) market compared to the low technology (LT) market; (2) the impact of innovation on economic performance is ambiguous for firms in the high technology and low concentration (HTLC) market.Research limitations/implicationsAlthough the database provides a rich data set on industrial data, it fails to provide innovation output such as patent data which may underestimate the innovation activities of firms that do not have a separate R&D records. In the current context of subdue economic growth these research results have important policy implications. Firstly, the positive impact of innovation on trade performance strengthens its role for sustainable development. The negative coefficient on innovation is an indication that research intensity in some cases has not been able to create a new demand capable to boost economic performance.Practical implicationsThe market classification analysis provides new evidence that innovation in the LT market has the potential to enhance competition. Secondly, market size supports industries that are competing in the international market. Policy makers must therefore put in place incentives to encourage firms to grow in size if they want to remain globally competitive.Social implicationsSustainable development can be supported through investment in research and development in the low technology sector.Originality/valueThe study is the first as far as the author knows, to examine the impact of innovation on bilateral trade performance using industry level data from OECD countries. Secondly, the author complements the existing literature by examining how innovation activities (classified as high technological intensive or low technological intensive) affect trade performance.

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Innovation and employment growth in developing countries: the role of market structure

Nurillaev,

Hiwatari

2024

Economics of Innovation and New Technology

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Innovative growth: the role of market power and negative selection

Cited by 8 publications

References 51 publications

Intangibles and innovation-labor-biased technical change

Intangibles and innovation-labor-biased technical change

On the role of innovation and market structure on trade performance: is Schumpeter right?

Innovation and employment growth in developing countries: the role of market structure

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