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Intra-Country Wage Inequality in the OECD Countries

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  • Manuel Carlos Nogueira
  • Óscar Afonso

Abstract

Two reasons are mainly brought to explain the recent increase in intra-country wage inequality in favour of high-skilled labour: Skill-Biased Technological Change (SBTC) and International Trade Liberalisation (IT). Since few empirical studies have attempted to assess both interpretations across a comprehensive sample of countries, we have analysed the impact of both and added some new variables within a unified framework and across 30 OECD countries, between 2001 and 2015. Using panel data, results show that both explanations are crucial. However, considering all 30 OECD countries, the IT argument dominates. Further, we show that seven clusters must be considered in which at least one theory influence the wage gap. Key words: Skill-biased technological change, International trade, Immigration, Education, Wage inequality, Cluster analysis. JEL: C23, F41, J31, O33, O50. Dva razloga uglavnom objašnjavaju rastuće povećanje nejednakosti zarada unutar zemalja u korist visoko-kvalifikovanih radnika: tehnološke promene zasnovane na veštinama (SBCT) i međunarodna trgovinska liberalizacija (IT). Budući da je nekoliko empirijskih studija pokušalo da proceni oba tumačenja preko sveobuhvatnog uzorka zemalja, mi smo analizirali oba uticaja i dodali neke nove varijable u jedinstveni okvir od 30 zemalja OECD-a, između 2001. i 2015. godine. Koristeći podatke panela, rezultati pokazuju da su oba objašnjenja od presudnog značaja. Međutim, posmatrajući svih 30 zemalja OECD-a, IT argumenti dominiraju. Dalje, pokazujemo da sedam klastera mora da se razmatra u kojima najmanje jedna teorija utiču na razliku u zaradama. Ključne reči: Tehnološke promene zasnovane na veštinama, međunarodna trgovina, imigracije, obrazovanje, nejednakost zarada, klaster analiza.

Suggested Citation

  • Manuel Carlos Nogueira & Óscar Afonso, 2018. "Intra-Country Wage Inequality in the OECD Countries," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 65(3), pages 339-362.
  • Handle: RePEc:voj:journl:v:65:y:2018:i:3:p:339-362:id:517
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    More about this item

    Keywords

    Skill-biased technological change; International trade; Immigration; Education; Wage inequality; Cluster analysis;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O50 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - General

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