Public policy, innovation and total factor productivity: An application to Taiwan’s manufacturing industry. (English) Zbl 1177.90123

Summary: This paper analyses the impact of innovation on productivity in Taiwan. Using a panel of 48,794 firms observed over the 1997-2003 period and distributed across 23 industries, we compute total factor productivity (TFP) by estimating Translog production functions with \(C, L, E, M\) inputs. We evaluate the impact of being an innovator on TFP using propensity score matching. The rationale is that, over the period, innovating firms are likely to have benefited from one of many innovation policy measures known as statute for upgrading industry (SUI) (until 1999) or “New SUI” (after 1999). Our results show a significantly negative effect of being an innovator on TFP in most industries, both before and after 1999. This suggests that firms having innovation expenditures either perform less well than the others because of unobserved factors, or are further away from the production frontier. Therefore, innovation in Taiwan seems to be associated with catching-up strategies.


90B30 Production models


mhbounds; Stata
Full Text: DOI


[1] Aakvik, A., Building a matching estimator: the case of a Norwegian training program, Oxford bull. econ. stat., 63, 115-143, (2001)
[2] Aakvik, A.; Heckman, J.J.; Vytlacil, E.J., Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs, J. econ., 125, 15-51, (2005) · Zbl 1334.62203
[3] Basant, R.; Fikkert, B., The effects of R&D, foreign technology purchase, and domestic and international spillovers on productivity in Indian firms, Rev. econ. stat., 78, 187-199, (1996)
[4] Beason, R.; Weinstein, D.E., Growth, economies of scale, and targeting in Japan (1995-1990), Rev. econ. stat., 78, 286-295, (1996)
[5] Becker, S.O.; Caliendo, M., Sensitivity analysis for average treatment effects, Stata J., 7, 71-83, (2007)
[6] Berndt, E.; Christensen, L., The translog function and the substitution of equipment, structures, and labor in US manufacturing, 1929-1968, J. econ., 1, 81-114, (1973) · Zbl 0276.90010
[7] M. Caliendo, S. Kopeinig, Some Practical Guidance for the Implementation of Propensity Score Matching, DIW Discussion Papers, No. 485, 2005, DIW, Berlin.
[8] Caves, R.E.; Uekusa, M., Industrial organization in Japan, (1976), The Brookings Institution Washington, D.C., pp. 124-140
[9] Chan, M.W.L.; Mountain, D.C., Economies of scale and the Törnqvist discrete measure of productivity growth, Rev. econ. stat., 70, 663-667, (1983)
[10] Chang, C.-L.; Robin, S., Choosing R&D and/or imported technologies: the critical importance of firm size in Taiwan’s manufacturing industries, Rev. ind. organ., 29, 253-278, (2006)
[11] Drukker, D.M., Testing for serial correlation in linear panel-data models, Stata J., 3, 168-177, (2003)
[12] Heckman, J.J.; Ichimura, H.; Todd, P., Matching as an econometric evaluation estimator: evidence from evaluating a job training programme, Rev. econ. stud., 64, 605-654, (1997) · Zbl 0887.90039
[13] Heckman, J.J.; Ichimura, H.; Todd, P., Matching as an econometric evaluation estimator, Rev. econ. stud., 65, 261-294, (1998) · Zbl 0908.90059
[14] Hou, C.M.; Gee, S., National systems supporting technical advance in industry: the case of Taiwan, ()
[15] Kumbhakar, S.C.; Lovell, C.A.K., Stochastic frontier analysis, (2000), Cambridge University Press Cambridge · Zbl 0968.62080
[16] Luo, Y.-L., National innovation system of Taiwan, (2001), STIC-National Science Council Taiwan
[17] Odagiri, H., R&D expenditures, royalty payments, and sales growth in Japanese manufacturing corporations, J. ind. econ., 32, 61-71, (1983)
[18] Rosenbaum, P.R.; Rubin, D.B., Constructing a control group using multivariate matched sampling methods that incorporate the propensity score, Am. stat., 39, 33-38, (1985)
[19] Rosenbaum, P.R., Observational studies, (2002), Springer New York · Zbl 0985.62091
[20] Rosenbaum, P.R.; Rubin, D.B., The central role of the propensity score in observational studies for causal effects, Biometrika, 70, 41-55, (1983) · Zbl 0522.62091
[21] Scherer, F.M., Firm size, market structure, opportunity, and the output of patented inventions, Am. econ. rev., 55, 1097-1125, (1965)
[22] Scherer, F.M., Statistical evidence on antitrust decree effects, (), 207-221
[23] Scherer, F.M., Corporate size, diversification and innovative activity, (), 222-238
[24] Scott, J.T., Purposive diversification and economic performance, (1993), Cambridge University Press Cambridge, Chapter 7, pp. 84-90; Chapter 10, pp. 133-147
[25] Scott, J.T., Corporate social responsibility and environmental research and development, Struct. change econ. dyn., 16, 313-331, (2005)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.