LABOUR PRODUCTIVITY ANALYSIS OF MANUFACTURING SECTOR IN TURKEY AGAINST EU

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Dursun Balkan, G. Akyuz
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引用次数: 0

Abstract

This study offers an in-depth analysis of labour productivity of manufacturing sector in Turkey and provides a comparison with EU27 and EA19 countries utilizing Eurostat time series data of 63 quarters covering 2005/first quarter-2020/third quarter time interval. Productivity trends are identified and interpreted by relating them with the key macroeconomic events and factors. Multiple linear and non-linear regression equations, and ARIMA model with different parameters are applied to the time series data considering the periods with and without covid effect. Future projections are made for the periods 2020–2023 for Turkey manufacturing sector based on the best fitting regression and ARIMA solutions and they are compared. Findings revealed that extreme covid conditions of even two quarters of data have significant impact on the forecasted values for Turkey, EU27 and EA19 countries. ARIMA analysis with 12 different parameter settings provided accurate results, supported by Thiel’s inequality coefficients and standard error measures. Analysis has shown consistent patterns between EA19 and EU27 countries. ARIMA results represent better compatibility with the regression results for Turkey. Study is valuable by providing comprehensive and comparative analysis, revealing future forecasts and covid effect and degree of recovery from the pandemic.
土耳其制造业劳动生产率对欧盟的影响分析
本研究对土耳其制造业的劳动生产率进行了深入分析,并利用欧盟统计局2005年/第一季度-2020年/第三季度的63个季度的时间序列数据,与欧盟27国和EA19国进行了比较。生产率趋势是通过将其与关键的宏观经济事件和因素联系起来来确定和解释的。采用多元线性和非线性回归方程以及不同参数的ARIMA模型,对考虑有无冠状病毒效应的时间序列数据进行分析。根据最佳拟合回归和ARIMA解决方案,对2020-2023年土耳其制造业的未来进行了预测,并对其进行了比较。调查结果显示,即使是两个季度的数据,极端的covid条件也会对土耳其、欧盟27国和EA19国家的预测值产生重大影响。在蒂尔不等式系数和标准误差测量的支持下,ARIMA分析提供了12种不同参数设置的准确结果。分析显示东亚19国和欧盟27国之间的模式是一致的。ARIMA结果与土耳其的回归结果具有较好的兼容性。研究的价值在于提供全面和比较的分析,揭示未来的预测和covid效应以及从大流行中恢复的程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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