Guido Pialli

Welcome! I am a Postdoctoral Research Fellow at UCL, based at CASA, contributing to an ESRC funded project.

I obtained a PhD in Economics from the University of Torino and Maastricht University in December 2022.

I am an applied economist. My research broadly falls under the area of the economics of knowledge and innovation. I also work on topics related to labor and migration.

I am currently working on: i) the drivers and direction of firm and regional innovation; ii) the economics of diversity; iii) the role of intangible capital in the knowledge economy.

Here you can find my CV

Contacts:

g.pialli@ucl.ac.uk;

guido.pialli@unito.it

Here are some of my ongoing projects:

Intangible intensity and between-firm wage inequality (with Olga Tcaci). Accepted with revision at Economica.

Abstract: A substantial portion of the recent increase in wage inequality in advanced economies is attributed to the rise in between-firm wage inequality. At the same time, growing empirical evidence shows a rising reliance on intangible assets in the production process. We demonstrate that these two trends are related. Using industry-level data for European countries for the period 2000-2020, we show that intangible intensity positively affects between-firm wage inequality. When decomposing overall intangible capital into subcategories, we find that the effect is mainly driven by innovative property assets, such as R&D, licenses, and designs. Robustness checks and an instrumental variable strategy provide further support for these results. We interpret these findings as the outcome of technology-based effects arising from the distinctive characteristics of intangible assets and R&D, including their scalability and critical role in competitive advantage, which favour large and frontier firms.

Population diversity and entrepreneurial motivation: evidence from second-generation Americans (with Olga Tcaci).

Abstract. This article examines how population diversity, proxied by the distance from East Africa of the ancestral populations, shapes contemporary entrepreneurial spirit. We propose that greater population diversity can foster stronger social comparison effects, motivating individuals to pursue entrepreneurial activities. By adopting an epidemiological approach, we examine this channel among US second-generation immigrants and use the corresponding migratory distance from East Africa of the parents' country of origin as a proxy for variation in ancestral population diversity. Our empirical results indicate a positive relationship between population diversity and entrepreneurial disposition: individuals whose ancestral origins are geographically closer to East Africa, thus more diverse, exhibit higher likelihood of entrepreneurship. Consistent with our conceptual framework, we further document that ancestral groups geographically closer to East Africa are characterized by greater income dispersion and a wider distribution of productive traits, both of which are positively associated with entrepreneurial participation.

A new matched employer-employee dataset for UK firms (with Max Nathan, Tom Kemeny, Ceren Ozgen, Anna Rosso, Mateo Serè and Anna Valero).

Abstract available upon request.

Migration, diversity and productivity in UK firms (with Max Nathan, Tom Kemeny, Ceren Ozgen, Anna Rosso, Mateo Serè and Anna Valero).

Abstract. We look at the effects of skilled migrants and migrant diversity on firm productivity, using a novel worker-firm dataset – leveraging millions of online profiles – to identify impacts and mechanisms. In theory, migration can boost firms’ productivity through improving human capital, improved task specialisation, or via diverse teams’ role in ideas generation/scrutiny. Conversely, discrimination or lack of trust may lead to sub-optimal task allocation or workplace frictions, respectively. Urban location may amplify these effects, via compositional channels and/or interaction with agglomeration economies. A growing body of evidence finds support for migration-productivity effects, although effect sizes vary considerably across countries, industries and workflows. Two major challenges here are the lack of employer-employee datasets in many countries, and limitations in coverage / dimensionality in those that do exist. Data from online platforms and the web may help meet these challenges. We sample individual education/career histories from the Diffbot knowledge graph to the UK company register, alongside financial data from Orbis Historical, 2007-2023. Focusing on larger firms across a range of sectors, we define migrants through name, language and countries of education, using panel fixed effects and GMM/IV settings for identification. We then explore the contributions of seniority, migrant human capital, task specialisation and migrant diversity. Results suggest a U-shaped link from migrant workforce share to firm TFP, which is more pronounced for senior staff, and for a minority of skill- and STEM-intensive firms. Migrant human capital and migrant worker specialisation into technical roles help explain our results.