arXiv subjects

Penny Mealy

Publications and source records attributed to Penny Mealy.

4 recordsLinked to original sources

arXiv2025

Skill and spatial mismatches for sustainable development in Brazil

Structural change is necessary for all countries transitioning to a more environmentally sustainable economy, but what are the likely impacts on workers? Studies often find that green transition scenarios result in net positive job creation numbers overall but rarely provide insights into the more granular dynamics of the labour market. This paper combines a dynamic labour market simulation model with development scenarios focused on agriculture and green manufacturing. We study how, within the context of a green transition, productivity shifts in different sectors and regions, with differing environmental impacts, may affect and be constrained by the labour market in Brazil. By accounting for labour market frictions associated with skill and spatial mismatches, we find that productivity shocks, if not well managed, can exacerbate inequality. Agricultural workers tend to be the most negatively affected as they are less occupationally and geographically mobile. Our results highlight the importance of well-targeted labour market policies to ensure the green transition is just and equitable.

econ.GN↗

arXiv2020

Supply and demand shocks in the COVID-19 pandemic: An industry and occupation perspective

We provide quantitative predictions of first order supply and demand shocks for the U.S. economy associated with the COVID-19 pandemic at the level of individual occupations and industries. To analyze the supply shock, we classify industries as essential or non-essential and construct a Remote Labor Index, which measures the ability of different occupations to work from home. Demand shocks are based on a study of the likely effect of a severe influenza epidemic developed by the US Congressional Budget Office. Compared to the pre-COVID period, these shocks would threaten around 22% of the US economy's GDP, jeopardise 24% of jobs and reduce total wage income by 17%. At the industry level, sectors such as transport are likely to have output constrained by demand shocks, while sectors relating to manufacturing, mining and services are more likely to be constrained by supply shocks. Entertainment, restaurants and tourism face large supply and demand shocks. At the occupation level, we show that high-wage occupations are relatively immune from adverse supply and demand-side shocks, while low-wage occupations are much more vulnerable. We should emphasize that our results are only first-order shocks -- we expect them to be substantially amplified by feedback effects in the production network.

econ.GN↗

arXiv2020

Automation and occupational mobility: A data-driven network model

The potential impact of automation on the labor market is a topic that has generated significant interest and concern amongst scholars, policymakers, and the broader public. A number of studies have estimated occupation-specific risk profiles by examining the automatability of associated skills and tasks. However, relatively little work has sought to take a more holistic view on the process of labor reallocation and how employment prospects are impacted as displaced workers transition into new jobs. In this paper, we develop a new data-driven model to analyze how workers move through an empirically derived occupational mobility network in response to automation scenarios which increase labor demand for some occupations and decrease it for others. At the macro level, our model reproduces a key stylized fact in the labor market known as the Beveridge curve and provides new insights for explaining the curve's counter-clockwise cyclicality. At the micro level, our model provides occupation-specific estimates of changes in short and long-term unemployment corresponding to a given automation shock. We find that the network structure plays an important role in determining unemployment levels, with occupations in particular areas of the network having very few job transition opportunities. Such insights could be fruitfully applied to help design more efficient and effective policies aimed at helping workers adapt to the changing nature of the labor market.

econ.GN↗

arXiv2018

Interpreting Economic Complexity

Two network measures known as the Economic Complexity Index (ECI) and Product Complexity Index (PCI) have provided important insights into patterns of economic development. We show that the ECI and PCI are equivalent to a spectral clustering algorithm that partitions a similarity graph into two parts. The measures are also related to various dimensionality reduction methods and can be interpreted as vectors that determine distances between nodes based on their similarity. Our results shed a new light on the ECI's empirical success in explaining cross-country differences in GDP/capita and economic growth, which is often linked to the diversity of country export baskets. In fact, countries with high (low) ECI tend to specialize in high (low) PCI products. We also find that the ECI and PCI uncover economically informative specialization patterns across US states and UK regions.

econ.GN↗