Public policy, innovation and total factor productivity: An application to Taiwan's manufacturing industry
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DOI: 10.1016/j.matcom.2008.01.005
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- Chia-Lin Chang & Stéphane Robin, 2008. "Public policy, innovation and total factor productivity : An application to Taiwan's manufacturing industry," Post-Print hal-03691878, HAL.
References listed on IDEAS
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- Kancs, d’Artis & Siliverstovs, Boriss, 2016.
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- d'Artis Kancs & Boriss Siliverstovs, 2012. "R&D and Non-Linear Productivity Growth of Heterogeneous Firms," JRC Working Papers on Corporate R&D and Innovation 2012-06, Joint Research Centre.
- d'Artis Kancs & Boriss Siliverstovs, 2012. "R&D and Non-Linear Productivity Growth of Heterogeneous Firms," JRC Research Reports JRC77247, Joint Research Centre.
- D'Artis Kancs & Boriss Siliverstovs, 2012. "R&D and Non-linear Productivity Growth of Heterogeneous Firms," KOF Working papers 12-315, KOF Swiss Economic Institute, ETH Zurich.
- Mohamad Yunus, Norhanishah & Said, Rusmawati & Law, Siong Hook, 2014. "Do Cost of Training, Education Level and R&D Investment Matter towards Influencing Labour Productivity?," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 48(1), pages 133-142.
- Wei Wei & Qiao Fan & Aijun Guo, 2022. "China’s Industrial TFPs at the Prefectural Level and the Law of Their Spatial–Temporal Evolution," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
- Dimitrios Giokas & Nicolaos Eriotis & Ioannis Dokas, 2015. "Efficiency and productivity of the food and beverage listed firms in the pre-recession and recessionary periods in Greece," Applied Economics, Taylor & Francis Journals, vol. 47(19), pages 1927-1941, April.
- Xiao Xiang & Qiao Fan, 2024. "Advancing Green TFP Calculation: A Novel Spatiotemporal Econometric Solow Residual Method and Its Application to China’s Urban Industrial Sectors," Mathematics, MDPI, vol. 12(9), pages 1-33, April.
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Keywords
Newly industrialized countries; Total factor productivity; Computation propensity score matching; Firm-level panel data; Manufacturing industry;All these keywords.
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