结构与就业增长:来自印度KLEMS数据的证据

IF 0.8 Q4 DEVELOPMENT STUDIES
S. Aggarwal, B. Goldar
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引用次数: 8

摘要

目的本研究旨在分析1980-8081年至2015-2016年间印度经济的就业结构和趋势。设计/方法/方法使用印度KLEMS数据集。使用“点”就业弹性来估计就业增长率并讨论就业前景。发现尽管自1991年改革以来,印度的GDP增长率一直令人印象深刻,但就业增长率,尤其是2003-2015年的就业增长率,就业增长模式也不平衡,制造业就业增长缓慢,建筑业就业增长迅速。印度现在的劳动力参与率也很低,非正规就业在经济中所占比例很大。研究局限性/含义局限性在于缺乏近期可靠的就业数据。实际含义由于就业弹性总体较低,印度将不得不探索可以创造更多就业机会的部门。社会影响印度不仅要创造更多的就业机会,还要创造“好”的就业机会。原创性/价值印度KLEMS数据提供了就业的时间序列,本文使用该时间序列来寻找就业的“点”弹性,而不是弧弹性,这是对现有就业弹性估计的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structure and growth of employment: evidence from India KLEMS data
Purpose This study aims to analyze the structure and trend in employment in the Indian economy between 1980-8081 and 2015-2016. Design/methodology/approach Use of India KLEMS data set. Estimate growth rate of employment and discuss employment prospects using “Point” employment elasticity. Findings Whilst India’s GDP growth rate has been quite impressive since the reforms of 1991, the rate of employment growth, especially in the recent period of 2003-2015, has been quite slow (1 per cent) with low employment elasticity (0.1). The pattern of employment growth has also been imbalanced with slow rate of employment growth in manufacturing and rapid growth rate in the construction sector. India now also has low labour force participation rate and a large share of informal employment in the economy. Research limitations/implications The limitation is the lack of reliable data on employment for the recent period. Practical implications With overall low employment elasticity, India would have to explore sectors where more employment opportunities could be created. Social implications India has to create not only more jobs but also “good” jobs. Originality/value The India KLEMS data provide a time series for employment, which has been used in this paper to find “Point” elasticity instead of arc elasticity of employment and is an improvement over existing employment elasticity estimates.
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CiteScore
2.80
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发文量
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