Combining job mobility patterns and vacancy data to better measure labour market opportunities and skill mismatch

结合工作流动模式和职位空缺数据，更好地衡量劳动力市场机会和技能不匹配

基本信息

批准号：
ES/X011887/1
负责人：
Fabien Postel-Vinay
金额：
$ 62.3万
依托单位：
Institute for Fiscal Studies
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2023
资助国家：
英国
起止时间：
2023 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FX011887%2F1
关键词：
Combining job mobility patterns vacancy

项目摘要

The Covid pandemic brought about an unprecedented labour market shock. Job opportunities in sectors like hospitality disappeared overnight, whilst opportunities expanded in other sectors like driving and healthcare. This radical restructuring of the economy called for a new way of measuring the labour market prospects facing individuals that captured their widely-varying ability to adapt to the shock by moving into alternative lines of available work. Motivated by this, we developed a new worker-specific measure of labour market opportunities. Our measure is based on historical patterns of job-to-job moves, which we use to infer how suitable a given worker is for different types of jobs. Combined with high-quality data on vacancy postings, this allowed us to look beyond aggregate measures of labour market performance and quantify important differences in the labour market prospects facing different types of workers over the pandemic (Costa Dias et al 2021, Joyce et al 2022). While our innovation was triggered by the pandemic, the usefulness of our method is much more general and wide-ranging. Our method links the state of the labour market in one part of the economy to the rest of the economy, meaning that it could be used to answer questions like: how do shocks in retail affect wage pressures and career progression for delivery drivers? How do changes in the wider labour market affect the ability of the social care sector to recruit and retain workers? Our method further provides insights into the extent to which workers' skills align with the skills demanded by employers - the extent of labour market 'mismatch' - which has implications for productivity and economic growth. For example, if the older workers who have recently left the labour market were to come back, to what extent could this ease labour shortages in specific occupations? Where in the economy are skills shortages most acute, and what is the economic cost of mismatch in terms of aggregate productivity?The aim of this project is to extend and refine our new method, grounding it in a theoretical search and match model, and demonstrate its applicability to substantive questions and its advantages over traditional methods. We will refine our index to capture variation in opportunities arising from competition for jobs from different types of jobseekers, as well as variation in the skills demanded by employers (captured by our current index). We will then demonstrate its utility by applying it to empirical, policy-relevant questions like the ones above - in particular, in identifying the variation in labour market opportunities across workers and over time, and in quantifying the extent and economic cost of labour market mismatch in the economy. A key part of embedding this innovation within future research and statistical practice will be dissemination and engagement with others - not only after the project is done, but during its production, helping us to maximise its usefulness. The main target audiences will include the research community, statistical practitioners (e.g. ONS), and policy-makers - since the ultimate purpose of our innovation is to better guide policy-making, and through achieving impact on policy-makers we will further highlight the potential of our innovation within future research.

联盟大流行带来了前所未有的劳动力市场冲击。酒店等部门的工作机会在一夜之间消失，而在驾驶和医疗保健等其他领域的机会则扩大。这种经济的根本性重组要求一种新的方法来衡量个人面临的劳动力市场前景，这些人通过进入可用工作的替代方案来捕捉其广泛变化的能力来适应冲击。在此激励的情况下，我们开发了针对劳动力市场机会的新工人。我们的措施基于工作与工作的历史模式，我们用来推断给定工人对不同类型的工作的合适程度。再加上有关空缺发布的高质量数据，这使我们能够超越劳动力市场绩效的总体测量，并量化了大流行的不同类型工人面临的劳动力市场前景的重要差异（Costa Dias等人2021年，Joyce等，2022年）。尽管我们的创新是由大流行触发的，但我们方法的有用性更加一般和广泛。我们的方法将经济一部分的劳动力市场状况与其他经济联系起来，这意味着它可以用来回答诸如以下问题：零售的冲击如何影响工资压力和交付驱动因素的职业发展？更广泛的劳动力市场的变化如何影响社会护理部门招募和留住工人的能力？我们的方法进一步提供了有关工人技能与雇主要求的技能（劳动力市场不匹配'的程度 - 对生产力和经济增长的影响的程度）的程度的见解。例如，如果最近离开劳动力市场的老年工人会回来，那么这种特定职业的劳动力短缺可以在多大程度上减轻劳动力短缺？在经济中，最严重的是技能短缺，从总体生产力方面，不匹配的经济成本是多少？该项目的目的是扩展和完善我们的新方法，将其扎根于理论搜索和匹配模型中，并证明其适用于实质性问题及其在传统方法上的优势。我们将完善我们的指数，以捕捉来自不同类型的求职者的工作以及雇主要求技能的差异（由我们当前的指数捕获）的差异。然后，我们将通过将其应用于上述问题（尤其是在确定工人和随着时间的时间范围内劳动力市场机会的差异，以及量化经济中劳动力市场不匹配的程度和经济成本）时，将其应用于与上述政策相关的问题。将这项创新嵌入未来的研究和统计实践中的关键部分将是与他人的传播和互动 - 不仅在项目完成之后，而且在其生产过程中，有助于我们最大程度地提高其实用性。主要的目标受众将包括研究界，统计从业人员（例如ONS）和政策制定者 - 因为我们创新的最终目的是更好地指导政策制定，并通过对政策制定者的影响，我们将进一步强调我们在未来研究中创新的潜力。