Skip to main content

Trinity College Dublin, The University of Dublin

Menu Search


Trinity College Dublin By using this website you consent to the use of cookies in accordance with the Trinity cookie policy. For more information on cookies see our cookie policy.

      
Profile Photo

Dr. Martina Zanella

Assistant Professor (Economics)

 


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.
  Econometric and statistical analysis   Economic policy making   Economics   Identity politics and social change   Politics and Gender
 Automation, Unemployment and Re-envisioning the Nature of Work
 Group Composition and Group Decision-Making: Evidence from Municipal Council Meetings in South Korea
 Working together: Gender segregation across firms
 Gender Differences in Confidence: Evidence from The Irish Economics Association Annual Conference

Language Skill Reading Skill Writing Skill Speaking
English Fluent Fluent Fluent
French Basic Basic Basic
Italian Fluent Fluent Fluent
Spanish Basic Basic Basic
Details Date From Date To
European Economic Association 2022
Royal Economic Society 2023
  

Martina Zanella, Stereotypical Selection, 2024, Working Paper, PUBLISHED
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, PUBLISHED
Jay Euijung Lee, Minhyuk Nam, and Martina Zanella, Republic of Korea Municipal Councils Decision-Making and Functioning, Data not available yet, 2023, Dataset, PRESENTED
Martina Zanella, LSE Students and Staff, Personal Data, 2022, Dataset, PRESENTED
Martina Zanella, LSE Undergraduate Students Online Survey, Personal Dataset, 2022, Dataset, PRESENTED
Martina Zanella, Essays in Applied Microeconomics, London School of Economics and Political Science, 2022, Thesis, PUBLISHED
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, PRESENTED
Jay Euijung Lee and Martina Zanella, Republic of Korea Municipal Elections Dataset, Personal Dataset, 2021, Dataset, PRESENTED

  

Award Date
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
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.