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Effects of climate change on combined labour productivity and supply: an empirical, multi-model study

机译:气候变化对劳动生产率和供应组合的影响:实证,多模型研究

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BackgroundAlthough effects on labour is one of the most tangible and attributable climate impact, our quantification of these effects is insufficient and based on weak methodologies. Partly, this gap is due to the inability to resolve different impact channels, such as changes in time allocation (labour supply) and slowdown of work (labour productivity). Explicitly resolving those in a multi-model inter-comparison framework can help to improve estimates of the effects of climate change on labour effectiveness.MethodsIn this empirical, multi-model study, we used a large collection of micro-survey data aggregated to subnational regions across the world to estimate new, robust global and regional temperature and wet-bulb globe temperature exposure-response functions (ERFs) for labour supply. We then assessed the uncertainty in existing labour productivity response functions and derived an augmented mean function. Finally, we combined these two dimensions of labour into a single compound metric (effective labour effects). This combined measure allowed us to estimate the effect of future climate change on both the number of hours worked and on the productivity of workers during their working hours under 1·5°C, 2·0°C, and 3·0°C of global warming. We separately analysed low-exposure (indoors or outdoors in the shade) and high-exposure (outdoor in the sun) sectors.FindingsWe found differentiated empirical regional and sectoral ERF's for labour supply. Current climate conditions already negatively affect labour effectiveness, particularly in tropical countries. Future climate change will reduce global total labour in the low-exposure sectors by 18 percentage points (range ?48·8 to 5·3) under a scenario of 3·0°C warming (24·8 percentage points in the high-exposure sectors). The reductions will be 25·9 percentage points (–48·8 to 2·7) in Africa, 18·6 percentage points (–33·6 to 5·3) in Asia, and 10·4 percentage points (–35·0 to 2·6) in the Americas in the low-exposure sectors. These regional effects are projected to be substantially higher for labour outdoors in full sunlight compared with indoors (or outdoors in the shade) with the average reductions in total labour projected to be 32·8 percentage points (–66·3 to 1·6) in Africa, 25·0 percentage points (–66·3 to 7·0) in Asia, and 16·7 percentage points (–45·5 to 4·4) in the Americas.InterpretationBoth labour supply and productivity are projected to decrease under future climate change in most parts of the world, and particularly in tropical regions. Parts of sub-Saharan Africa, south Asia, and southeast Asia are at highest risk under future warming scenarios. The heterogeneous regional response functions suggest that it is necessary to move away from one-size-fits-all response functions to investigate the climate effect on labour. Our findings imply income and distributional consequences in terms of increased inequality and poverty, especially in low-income countries, where the labour effects are projected to be high.FundingCOST (European Cooperation in Science and Technology).
机译:背景,对劳动力的影响是最有形和可惜的气候影响之一,我们对这些效应的量化不足,基于弱方法。部分原因是,这种差距是由于无法解决不同的冲击通道,例如时间分配(劳动力供应)的变化和工作放缓(劳动生产率)。明确解决多模型相互比较框架的框架可以有助于改善气候变化对劳动力变化影响的估计。此类经验,多模型研究,我们使用大量的微观调查数据聚集到“区域区域”全世界估算劳动力供应的新,强大的全球和区域温度和湿灯泡全球温度暴露 - 反应函数(ERF)。然后,我们评估了现有劳动生产率响应函数的不确定性,并衍生出了增强的平均功能。最后,我们将劳动力的这两个维度与单一复合度量(有效劳动效应)组合成。这种综合措施使我们能够估计在1·5°C,2·0°C和3·0°C下工作时间在工作时间内工作时间和工人生产力的未来气候变化的效果。全球暖化。我们分别分析了低暴露(室内或户外或户外),高曝光(户外在阳光下)扇区.Findingswe发现有区别的经验区域和部门ERF用于劳动力供应。目前的气候条件已经对劳动力有效性产生负面影响,特别是在热带国家。未来的气候变化将在3·0°C的场景下减少18个百分点(范围?48·8至5·3)的全球劳动力(范围48·8至5·3)(在高曝光中为24·8个百分点行业)。在非洲的减少将是25·9个百分点(-48·8至2·7),亚洲的18·6个百分点(-33·6至5·3),10·4个百分点(-35·在低曝光部门中的美洲0到2·6)。与室内(或阴影户外)相比,这些区域效应预计在户外户外劳动力在户外劳动力较高,平均降低预计为32·8个百分点(-66·3至1·6)在非洲,亚洲25·0百分点(-66·3至7·0),美洲的16·7个百分点(-45·5至4·4)。Interpretationboth劳动力供应和生产率被预计降低在未来的气候变化,在世界大部分地区,特别是热带地区。部分撒哈拉以南非洲,南亚和东南亚的部分是在未来的温暖情景下的最高风险。异构区域响应职能表明,有必要远离一定规模的所有反应作用,以调查劳动力的气候效应。我们的研究结果意味着在增加的不平等和贫困方面,特别是在低收入国家的收入和分配后果,劳动力影响被预测为HIGHT.FundingCost(欧洲科学和技术合作)。

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