Türkiye’de İnovasyonun İstihdama Etkisi

Bu makale 1991-2021 yılları arasında Türkiye işgücü piyasasında inovasyonun istihdam üzerindeki etkisini aylık patent tescilleri ve yıllık AR-GE harcamaları istatistiklerini kullanılarak incelemektedir. Ampirik teknik olarak ARDL yaklaşımı kullanılmıştır. Bu yaklaşımın tercih edilmesinin nedeni bu yöntemin uzun dönem ve kısa dönem sonuçlarını ayırması ve diğer yöntemlere göre daha az gözlem sayısı ile analizlerde daha iyi sonuçlar vermesidir. Bu çalışmanın sonuçlarının literatürden farklılığı analizin iki farklı zaman diliminde, iki farklı temsili değişken ile yapılması ve sonuçlarının sağlamlılığının kanıtı olarak bunların aynı sonucu vermesidir. Uzun dönem modeli ve kısa dönem modeli ayrı ayrı incelendiğinde inovasyonun istihdam üzerindeki etkisinin kısa dönemde negatif olduğu, uzun dönemde ise pozitif olduğu görülmektedir. Böylece, 1991-2021 döneminde Türkiye işgücü piyasasında inovasyon kısa vadede istihdam düzeylerini bir ölçüde olumsuz etkileyebilirken, uzun vadede inovasyon istihdam düzeyleri üzerinde daha yapısal ve sürdürülebilir bir pozitif etki gösterebilecektir. Kısa dönemde inovasyonun istihdama negatif etkisi bir nevi yaratıcı yıkım gibi karşılanabilir ancak uzun dönemde etkinin pozitife dönmesi inovasyonun sağladığı kar ve verimlilikle birlikte işçilerin eğitim ve öğretim seviyelerindeki artışın onları inovasyona adapte ederek istihdamın arttığı hipotezini desteklemektedir. Bu çalışmanın amacı makro veri setleri ile çıkarım yapmaktır ancak mikro düzeyde firma verileri kullanılarak inovasyonun istihdam üzerindeki etkisine ilişkin önemli sonuçlar elde edilebilir.

Anahtar Kelimeler:

ARDL Yaklaşımı, İnovasyon, Patent tescilleri, AR-GE harcamaları, İstihdam, Türkiye

The Effect of Innovation on Employment in Türkiye

This study examines the impact of innovation on employment in the Turkish labor market between the years 1991-2021, using monthly patent grants and annual R&D expenditure statistics. As for empirical technique, ARDL (autoregressive distributed lag) approach is used. The reason for choosing this approach is that it separates the long-term and short-term results and gives better results in analysis with a lower number of observations than other methods. The difference between the results of this study from the literature is that the analysis was performed in two different time periods, with two different proxy variables, and they gave the same result as proof of the robustness of the results. When the long-run model and the short-run model are investigated separately, it is found that while the effect of innovation on employment is negative in the short-run, it turns out to be positive in the long-run. Thus, during the period 1991-2021 in the Turkish labor market, while innovation might negatively affect employment levels to some extent in the short run, innovation could exert a more structural and sustainable positive impact on employment levels in the long run. In the short-run, the negative effect of innovation on employment can be seen as a kind of creative destruction, but in the long-run, the positive effect of innovation supports the hypothesis that the increase in the education and training levels of workers along with the profit and productivity provided by innovation increases employment by adapting workers to innovation. The aim of this study is to make an inference with macro data sets but, using micro-level, firm data may provide significant results on the effect of innovation on employment.

Keywords:

ARDL Approach, Innovation, Patent grants, R&D expenditures, Employment, Türkiye,

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