Teknoloji ve İşsizlik: Sistem GMM Tahminlerinden Ampirik Kanıtlar

Abstract

Çalışmada, teknolojik ilerlemenin iş kayıplarına ve işsizliğe neden olup olmadığı sorusuna odaklanılmaktadır. Ürün ve süreç yenilikle ortaya çıkan teknolojik ilerleme, bir yandan yeni iş alanları ortaya çıkarırken diğer yandan da mevcut işlerde ihtiyaç duyulan nitelikleri değiştirmektedir. Bu durum ise makinelerin insan emeğini ikame etmesiyle sonuçlanabilmektedir. Ortaya çıkan yeni iş alanları ve verimlilik artışları önemli birer fırsat olsa da bu fırsatların kaybolan meslekleri ve açığa çıkan işgücü arzını telafi etmekte yeterli olup olmadığı konusu gerek kuramsal gerekse ampirik olarak üzerinde fikir birliğine varılmış bir konu değildir. Nihai etkinin belirsizliği, yöntemsel gelişmeler ve veri setlerinin çeşitlenmesi konunun farklı boyutlarıyla ele alınması için önemli bir motivasyon kaynağıdır. Çalışmada, 1995-2021 dönemi ve 91 ülke kapsamında, işsizlik oranının geçmiş değerinin gelecek değerini etkilemesi eğiliminden hareket edilerek dinamik bir panel model çerçevesinde analizler yapılmıştır. Modeller iki aşamalı sistem Genelleştirilmiş Momentler Yöntemi (2SGMM) kullanılarak tahmin edilmiştir. Çalışmanın bulguları, işsizliğin kalıcılığını doğrulamakta ve sabit sermaye yatırımına dahil edilen somutlaştırılmış süreç yeniliğin emek tasarruf edici niteliğine işaret etmektedir. Ürün yeniliğin bir ölçüsü olarak modele dahil edilen ekonomik karmaşıklık endeksinin ise alternatif modeller kapsamında işsizlik oranını azaltıcı etkisinin olduğu tespit edilmiştir. Bir diğer model kapsamında ürün yeniliği temsil etmek üzere analize dahil edilen patent sayısının gecikmeli olarak işsizliği etkilediği bulunmuştur. Buna göre patent sayılarındaki artış, gecikmeli olarak azalan işsizlik oranlarıyla ilişkilidir.

Keywords

• İşsizlik
• Yenilik
• Teknoloji

Technology and Unemployment: Empirical Evidence from System GMM Estimates

Abstract

The study concentrates on whether technological progress causes job losses and unemployment. While technological progress, embodied in product and process innovation, creates new jobs, it also changes the qualifications required by existing jobs and causes machines to substitute human labour. The emergence of new jobs and productivity gains are opportunities, but whether these opportunities are sufficient to compensate for jobs lost and the resulting labour surplus is disputable. The uncertainty of the ultimate impact, methodological developments, and diversification of data sets are essential motivations for addressing the issue with different dimensions. In this study, analyses are conducted within the framework of a dynamic panel model considering the effect of the past value of the unemployment rate on its future value for the period 1995-2021 and 91 countries. The models are estimated using the two-step system Generalised Method of Moments (2SGMM). The findings of the study confirm the persistence of unemployment. Moreover, the embodied process included in gross fixed capital formation points to the labour-saving nature of innovation. Under alternative models, the economic complexity index, a measure of product innovation, is found to reduce unemployment. The number of patents included in the analysis to represent product innovation within the scope of another model affects unemployment in lagged terms. Accordingly, the increased number of patents results in a lagged decrease in unemployment rates.

Keywords

• Unemployment
• Innovation
• Technology

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