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Dr. Martina Zanella
Assistant Professor, Economics

Biography

I completed a BSc and MSc in Economics and Social Sciences at Bocconi University in 2011 and 2013 respectively, and a PhD in Economics at the London School of Economics and Political Science in March 2022. I joined the staff of the Department of Economics in 2022 as Assistant Professor. I am affiliated at the Trinity Impact Evaluation Unit (TIME) and the Trinity Research in Social Sciences (TRISS).

During the years of the Master and PhD, I worked as Research Assistant for Professors Eliana La Ferrara, Oriana Bandiera, Nava Ashraf, and Sandra Sequeira, as Analyst in the Consulting and Advanced Analytics Team at IQVIA in Milan, Intern in the Research Unit of BRAC in Kampala, Uganda, and as Graduate Teaching Assistant and Teaching Fellow at the LSE.

Publications and Further Research Outputs

Non-Peer-Reviewed Publications

Martina Zanella, Stereotypical Selection, 2024 Working Paper, 2024 URL

Jay Euijung Lee and Martina Zanella, Learning about Women's Competence: the Dynamic Response of Political Parties to Gender Quotas in South Korea, 2024 Working Paper, 2024 URL

Jay Euijung Lee, Minhyuk Nam, and Martina Zanella, Republic of Korea Municipal Councils Decision-Making and Functioning, Data not available yet, 2023 Dataset, 2023

Martina Zanella, Essays in Applied Microeconomics, London School of Economics and Political Science, 2022 Thesis, 2022 URL

Jay Euijung Lee, Minhyuk Nam, and Martina Zanella, Group Composition and Group Decision-Making: Evidence from Municipal Council Meetings in South Korea, London School of Economics and Political Science, 2022 Working Paper, 2022

Martina Zanella, LSE Undergraduate Students Online Survey, Personal Dataset, 2022 Dataset, 2022

Martina Zanella, LSE Students and Staff, Personal Data, 2022 Dataset, 2022 URL

Jay Euijung Lee and Martina Zanella, Republic of Korea Municipal Elections Dataset, Personal Dataset, 2021 Dataset, 2021

Research Expertise

Description

I am an applied micro-economist with a cutting-edge, interdisciplinary, and policy-relevant research program. My research explores the causes and consequences of inequality in education, the labour market, and political bodies, drawing insights from psychology and sociology to provide evidence-based suggestions for policy. My ongoing research spans collaborations with private and public institutions, and my work exploits different methodologies. Some of my projects constitute observational studies, where I exploit quasi-experimental methods and natural experiments to get rigorous identification of causal effects while studying individuals in real-world settings. However, I also firmly believe in the value of qualitative methods, such as in-depth surveys, focus groups, and interviews, to shed light on underlying mechanisms or inform the design of experiments. Moreover, I also have experience in designing field experiments. Lastly, in some of my projects, I make use of text, topic and sentiment analysis, web scraping, and supervised/unsupervised learning techniques to collect and analyze data. Machine learning can be an invaluable tool in support of policy-making.

Projects

  • Title
    • Automation, Unemployment and Re-envisioning the Nature of Work
  • Summary
    • As automation and technological change gather pace within the workplace, so too do skill obsolescence and unemployment. A proactive approach to reskill and retrain workers, particularly from the private sector, is crucial for avoiding sharp increases in unemployment and inequality as the magnitude of the estimated labour market changes is such that public sector policies alone will not adequately mitigate the risks (Card et al. 2018, Greenberg et al. 2003). In this direction, we propose an intervention, embedded within a multinational consumer goods company, that fosters a "purposeful change" by reorienting blue-collar workers who could potentially be affected by restructuring towards a growth mindset and an active approach to change. The intervention entails a combination of reflective workshops and experiential learning through community volunteering. This project will be able to inform policy on a sustainable and responsible automation process that meets the needs not only of the organization and the people directly impacted but also of the local community.
  • Funding Agency
    • Nuffield Foundation
  • Date From
    • 09/2021
  • Date To
    • 09/2023
  • Title
    • Group Composition and Group Decision-Making: Evidence from Municipal Council Meetings in South Korea
  • Summary
    • Does having a seat at the table translate into influence in the decision-making process? In this paper, we study how group interactions change when quotas introduce females into South Korean municipal councils, shocking a status quo where women were nearly completely absent. Our key contribution is that we can study how group composition affects dynamics in a setting outside the lab with real consequences, by analyzing rich transcripts of data spanning >250,000 meetings, and by tracking the behavior of a councilor over 4 years of their term within the same group of councilors. Preliminary findings show that women introduced by quotas start out their term much less vocal than men, even when compared to rookie men equally lacking councilor experience. However, the gap between rookie men and rookie women nearly fully closes by the end of the term, suggesting that it is not differences in inherent talent that cause women to be less vocal and that rookie women gradually gain influence as councilors work together during the years. N.B. This paper constitutes the first step of a more ambitious initiative: to dissect the mechanisms behind how greater female representation in politics changes policy outcomes, focusing our field of vision on the decision-making process.
  • Funding Agency
    • STICERD
  • Date From
    • 2023
  • Title
    • Working together: Gender segregation across firms
  • Summary
    • Despite the mounting support for workplace diversity and the more developed understanding of the benefits for both equality and productivity, most economies exhibit stark gender segregation across industries, occupations, and firms. Whilst segregation along industry and occupational lines has garnered much attention, gender segregation across firms within industries remains poorly understood. Studies that have looked at this phenomenon have shown that gender segregation across firms accounts for a substantial share of gender gaps in wages and workplace satisfaction. The literature has shown that peers and the characteristics of the environment affect behaviours, however, it remains unclear how much of this relationship can be attributed to different types of people self-selecting into firms with a higher share of same-gender peers. If workplace gender composition is internalized in occupational choices, different gender representation might bring along a different workforce composition, with implications for workplace dynamics and employees" outcomes. To do so, we leverage a matched employer-employee dataset representative of the universe of firms in Switzerland between 1994 and 2021 and the cross-sectional heterogeneity in the density of firms within by sector/occupation across locations to identify self-selection.
  • Title
    • Gender Differences in Confidence: Evidence from The Irish Economics Association Annual Conference
  • Summary
    • In this project, we explore the existence of a gender gap in evaluations regarding other people"s work among economists " a crucial and common task in academics" day-to-day work. We examine reviewing decisions in the Irish Economic Association (IEA) Conference from 2017-2023 by exploiting a crucial characteristic of the revision process - reviewers are asked to provide an evaluation of the paper as well as a score about their confidence regarding their expertise in the field. We coupled this data with rich information regarding referees, authors, and papers that we collected from personal and institutional websites, CVs, and Google Scholar to document whether reviewers display a gender confidence gap and whether this depends on the reviewer"s or the paper"s characteristics. In a second step, we assess whether this confidence gap affects the likelihood of paper acceptance at the conference and, ultimately, whether it is correlated with the paper"s long-term outcomes - publication status and citations. This allows us to derive considerations regarding whether reviewers are accurate in their evaluations and how this accuracy depends on their confidence.

Keywords

Econometric and statistical analysis; Economic policy making; Economics; Identity politics and social change; Politics and Gender

Recognition

Awards and Honours

Trinity Excellence in Teaching Award (Nomination), TCD 2023

ISWE Prize - IEA Conference 2023 May 2023

Arts and Social Sciences Benefactions Fund Feb 2023

Nuffield Foundation Grant (joint with Nava Ashraf, Oriana Bandiera, Virginia Minni) 2021-2024

STICERD PhD Research Grant (joint with Jay Euijung Lee) 2017-2023

Excellence in Education Award, School of Public Policy, LSE 2022, 2021, 2020

LSE Class Teacher Award , School o f Public P olicy , LSE (Highly Commended) 2022, 2021

LSE SU Teaching Award for Sharing Subject Knowledge (Nominated by students) 2020

LSE Teaching Bonus , Department of Economics, LSE 2019

LSE Full Departmental Scholarship 2017-2019

Crivelli Europe Scholarship, UniCredit & Universities Foundation 2014-2016

Full Bocconi Merit Award, Bocconi University 2011-2013

Memberships

Royal Economic Society 2023

European Economic Association 2022