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Social absorption capability, systems of innovation and manufactured export response to preferential trade incentives

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  • Na-Allah, Abdelrasaq
  • Muchie, Mammo

Abstract

In many extant analyses of the impact of non-reciprocal system of trade preferences it is typical to focus on the details of market access value of tariff concessions as explanation for why export of beneficiaries may or may not respond to incentives. Very often, the role that supply related factors can, and do play in the process is relegated to the background. This paper argues that the social absorption capability of a beneficiary's economy as expressed in her incumbent systems of innovation is a crucial determinant of export performance response. The experience of sub-Sahara African countries under the US African Growth and Opportunity Act apparel trade incentive is used as a classical illustration of this proposition. It is shown that the comparative efficiency of Lesotho, despite emerging from a relatively weak trade performance potential background, in recording the highest level of export success among beneficiaries of the scheme is a function of the relative efficiency of her systems of innovation.

Suggested Citation

  • Na-Allah, Abdelrasaq & Muchie, Mammo, 2012. "Social absorption capability, systems of innovation and manufactured export response to preferential trade incentives," Research Policy, Elsevier, vol. 41(1), pages 93-101.
    • Handle: RePEc:eee:respol:v:41:y:2012:i:1:p:93-101
    DOI: 10.1016/j.respol.2011.06.002
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    References listed on IDEAS

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    Cited by:

    1. Proksch, Dorian & Haberstroh, Marcus Max & Pinkwart, Andreas, 2017. "Increasing the national innovative capacity: Identifying the pathways to success using a comparative method," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 256-270.
    2. Valeria Costantini & Francesco Crespi, 2015. "European enlargement policy, technological capabilities and sectoral export dynamics," The Journal of Technology Transfer, Springer, vol. 40(1), pages 25-69, February.
    3. Zhao, S.L. & Cacciolatti, L. & Lee, S.H. & Song, W., 2015. "Regional collaborations and indigenous innovation capabilities in China: A multivariate method for the analysis of regional innovation systems," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 202-220.

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