This study investigates the short- and long-term dynamic relationships between technological innovation (patent activity), R&D expenditures, industrial productivity, and industrial competitiveness in Türkiye using annual data from 1991 to 2024. Methodologically, a cointegration model and a Vector Error Correction Model (VECM) are employed to analyze long-run equilibrium associations, the Dynamic Conditional Correlation (DCC-GARCH) approach captures time-varying interactions, and a Time-Varying Parameter Vector Autoregression (TVP-VAR) model is applied to assess how the strength and direction of the innovation–competitiveness relationship evolve across sub-periods. The results confirm the existence of a long-term cointegration relationship among the variables. Industrial productivity is positively associated with competitiveness, whereas R&D expenditures exhibit a negative association within the estimated long-run relationship. Patent activity shows only a weak association with competitiveness. Short-term dynamics indicate that industrial productivity contributes most strongly to the system's return to equilibrium, while competitiveness itself displays weak self-adjustment. The DCC-GARCH analysis reveals volatile correlation patterns over time: competitiveness and industrial productivity maintain positive but fluctuating co-movements, whereas competitiveness and R&D expenditures exhibit persistently negative correlations. The TVP-VAR results further demonstrate that the marginal impact of R&D and patent activity on competitiveness is structurally unstable, alternating in sign and magnitude across different sub-periods. These findings point to potential frictions in Türkiye's innovation environment, reflected in low observable returns from R&D and patent activity during the sample period. Such patterns should not be interpreted as direct evidence of institutional failure, but rather as indicative signals of delayed commercialization processes, limited absorptive capacity, and coordination constraints between innovation inputs and industrial output. From a policy perspective, the results suggest the importance of fostering high-value-added production and improving the effectiveness of innovation diffusion mechanisms to support sustainable competitiveness.
Çetin et al. (Tue,) studied this question.