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Spatial convergence clubs and innovation persistence: a country-group comparison of international spatial spillover of innovation capabilities

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Abstract

This study aims to determine whether cross-country spatial effects of innovation capabilities result into global convergence clubs. The spatial econometric modelling is applied on a panel of three groups of countries covering a period from 2007 to 2017. The analysis provides strong evidence on the existence of international diffusion of innovation capabilities among member countries of EU and APEC, but such relationship does not hold true for SWA countries. The trade share also contributes significantly for EU and APEC countries. The SWA group of countries firstly need to build their indigenous resources that can complement the knowledge adoption from abroad. The spillover benefits occur only if a country is in proximity with high innovation performance country with greater economic integration and higher trade share among themselves. There is presence of spatial convergence club among group of high innovating countries which is an outcome of knowledge globalization through well integrated economic cooperation.

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Fig. 1
Fig. 2

Source: Author’s own compilation using datasets from WIPO and WITS. *Not a member of EU

Fig. 3

Source: Author’s own compilation using datasets from WIPO and WITS. Note: Luxembourg has a missing value of patent count in the dataset for the year 2013

Fig. 4

Source: Author’s own compilation using datasets from WIPO and WITS. Common maritime border is considered for an island country

Fig. 5

Source: Author’s own compilation using datasets from WIPO and WITS

Fig. 6

Source: Author’s own compilation using datasets from WIPO and WITS. Note: Common maritime border is considered for an Island country

Fig. 7

Source: Author’s own compilation using datasets from WIPO and WITS

Fig. 8

Source: Author’s own compilation using datasets from WIPO and WITS. Note: Sri-Lanka has a missing value of patent count in the dataset for the year 2014. Common maritime border is considered for an island country

Fig. 9

Source: Author’s own compilation using datasets from WIPO and WITS

Fig. 10

Source: Authors’ own conceptualization

Fig. 11

Source: Author’s compilation from Lesage and Pace (2009) combined with extensions provided by Elhorst (2014) and Floch and Saout (2018)

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Notes

  1. It is a fixed parameter to measure the unobserved heterogeneity and also called fixed effect/within-group estimator. Elhorst (2010a) calls it spatial specific effect.

  2. The variables are explained in the functional form presented in Eq. 1.

  3. Manski (1993, pp. 532–533) explains three types of interaction effects i.e. endogenous, exogenous and correlated effects.

  4. Where N indicates the total number of cross-sections.

  5. The countries are classified by income group as per the definition of The World Bank (https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups).

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  1. Department of Economics, Government College University Lahore, Lahore, Pakistan

    Alvina Sabah Idrees & Saima Sarwar

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Idrees, A.S., Sarwar, S. Spatial convergence clubs and innovation persistence: a country-group comparison of international spatial spillover of innovation capabilities. Qual Quant 57, 4121–4152 (2023). https://doi.org/10.1007/s11135-022-01545-z

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