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Technical change, EMPloyment & Inequality. A Spatial analysis of households & plant data

技术变革、就业

基本信息

批准号：
ES/N011929/1
负责人：
Maria Savona
金额：
$ 20.12万
依托单位：
University of Sussex
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FN011929%2F1
关键词：
Technical change EMPloyment Inequality.Spatial

项目摘要

According to the London Futures Deloitte report (Frey and Osborne, 2014), 35 per cent of the current workforce in the UK is at risk of being made redundant over the next two decades as a result of the introduction of digital robots that will replace their tasks. For those that manage to remain employed, it is difficult to predict whether and how they are able to adapt their skills to the changing demand for occupational tasks. One emerging trend is that, after the introduction of new digital capital, firms dismiss large shares of medium-skilled workers, while seeking either low skilled workers to perform highly routinised tasks, or very high skilled people who provide creative ideas and apply sophisticated knowledge to maximise the benefits of digital capital. The polarisation of demand for tasks and the skills required to perform them is likely to be reflected in a similar polarisation of wages. This will depend on how firms decide to increase digital mechanisation, for instance what type of hardware and software services they purchase, and what types of new occupations this new capital requires. Also, as pointed out by Piketty (2014), rising share of capital in production goes hand in hand with decreasing share of labour, favouring top income concentration. Overall, innovative firms might be responsible for increasing income inequality, both through higher concentration of capital returns in the hands of a few creative CEOs and a higher proportion of the wage bill going to a proportionally smaller share of very high-skilled workers.This research aims to provide comparative evidence on the core mechanisms behind the effects of technical change on income inequality, by looking at the actors directly involved in their occurrence: firms investing in tangible, digital capital and R&D, and households providing skilled and unskilled workforce respectively employed in un-routinised and routinised tasks, and the associated distribution of wage and non-wage income. The novel contribution of this research compared to the extant literature is in the following aspects. First, we will uniquely combine, at the spatial level, plant-level data on tangible, digital and R&D investments of firms located in a certain area, defined as Travel-To-Work-Area (TTWA) and data on occupational categories, wage and non-wage earnings of household living in the same TTWA. TTWAs are defined by the Office for National Statistics as self-contained local labour markets. Second, we will study how technical change, through creative destruction, changes top income shares, wage distribution, and capital income distribution, at the level of TTWA. Third, we will analyse the temporal and spatial associations between the level and composition of investments in tangible, digital capital and R&D in firms and (i) changes in individual's occupational choice across job categories, and (ii) changes in wages at different quantiles of the wage distribution.This research adds to a debate on pressing social and policy issues: income inequality and unemployment. It is therefore particularly relevant not only for the academic community, but also for policy makers, innovative employers, public, social and private enterprises, trade unions, training institutions and young and old members of the workforce that seek and use information on employment and investment decisions. Our dissemination plan ensures that the findings of our research reach all the above stakeholders to inform their decision-making processes.

根据伦敦未来德勤报告（Frey 和 Osborne，2014 年），由于数字机器人的引入将取代他们的工作，未来 20 年英国 35% 的现有劳动力面临被裁员的风险。对于那些设法保住工作的人来说，很难预测他们是否以及如何能够使自己的技能适应不断变化的职业任务需求。一个新兴趋势是，在引入新的数字资本后，企业解雇了大量中等技能工人，同时寻找低技能工人来执行高度常规化的任务，或者寻找提供创造性想法并应用复杂知识以最大限度地发挥数字资本效益的高技能人才。对任务和执行任务所需技能的需求的两极分化很可能反映在工资的类似两极分化中。这将取决于企业决定如何提高数字机械化，例如他们购买什么类型的硬件和软件服务，以及新资本需要什么类型的新职业。此外，正如皮凯蒂（Piketty，2014）所指出的，资本在生产中所占份额的上升与劳动力份额的下降密切相关，有利于顶层收入集中。总体而言，创新型企业可能对收入不平等的加剧负有责任，因为资本回报更加集中在少数富有创造力的首席执行官手中，而较高比例的工资支出流向了比例较小的高技能工人。本研究旨在通过观察直接参与其发生的参与者，为技术变革对收入不平等影响背后的核心机制提供比较证据：投资于有形、数字资本和资本的企业。研发、提供分别从事非常规和常规任务的熟练和非熟练劳动力的家庭，以及相关的工资和非工资收入分配。与现有文献相比，本研究的新颖贡献体现在以下几个方面。首先，我们将在空间层面上独特地将位于特定区域（定义为上班区（TTWA））的企业有形、数字和研发投资的工厂级数据与居住在同一 TTWA 的家庭的职业类别、工资和非工资收入数据结合起来。国家统计局将 TTWA 定义为独立的当地劳动力市场。其次，我们将研究技术变革如何通过创造性破坏，在 TTWA 层面上改变最高收入份额、工资分配和资本收入分配。第三，我们将分析企业有形、数字资本和研发投资的水平和构成与（i）个人跨工作类别的职业选择的变化，以及（ii）工资分布不同分位数的工资变化之间的时间和空间关联。这项研究增加了关于紧迫的社会和政策问题的辩论：收入不平等和失业。因此，它不仅对学术界特别重要，而且对政策制定者、创新型雇主、公共、社会和私营企业、工会、培训机构以及寻求和使用就业和投资决策信息的年轻和老年劳动力成员也特别重要。我们的传播计划确保我们的研究结果传达给所有上述利益相关者，为他们的决策过程提供信息。