An effect analysis of regional research and development support policies: focused on Gyeongbuk province in Korea

• Published in: International Journal of Urban Sciences Vol. 19; no. 3; pp. 320 - 342
• Main Authors: Choi, Kyunghee, Cho, Deokho
• Format: Journal Article
• Language: English
• Published: Abingdon Routledge 02.09.2015; Taylor & Francis Ltd; 도시과학연구원
• Subjects: Commercialization; Electronics industry; Information industry; innovation and technology; propensity score matching; R&D; regional development; Research & development; research and development; Sales workers; 학제간연구
• ISSN: 1226-5934; 2161-6779
• DOI: 10.1080/12265934.2015.1043326

Regional industry policies, including regional research and development (R&D) policies, have been initiated since 1998 in Korea. Despite the need for performance evaluation, the evaluation studies of the regional R&D support policies are lacking. This study analyses the effect of regional R&D support policies on firm's innovative and economic performance, focusing on Gyeongbuk province and adopting the propensity score matching (PSM) method to deal with the problem of selection bias. The characteristics that influence the participation of the firm in the regional R&D support were analysed as age, R&D department, exports, and the electronics/information appliances industry. The government needs to encourage the firms to have an absorptive capacity by establishing R&D departments. Regional R&D support was analysed to have no significant effects on the commercialization of developed technology, patent applications, new employees, and sales of new products. Though the effect is not statistically significant, it is nonetheless not meaningless, considering the short elapsed time. We can expect that the performance will improve in the future considering the fact that the outputs of the R&D programmes are generated over many years. The regional R&D support policies are expected to contribute to strengthening the regional innovation system by improving the regional firms' innovative capacity in the long term. By adopting the PSM method, the study could potentially eliminate estimation error resulting from the simple comparison between the treatment group and the control group. It is necessary to take special note of the design of the survey in order to adopt the PSM method.