I am a senior research fellow at the Department of Economics of University College London and at The Alan Turing Institute. I enjoy studying problems that involve economic behavior and institutions. Currently, I am working on topics related to firm-labor dynamics, political behavior, economic development and inequality. My main interest lies in building models with explicit social mechanisms that can be used to inform policy. Usually, this involves computational simulations of multi-agent systems, complex networks and analysis of big data. My aim is to advance the computational social sciences and make them an integral part of the toolbox of every social scientist.

Contact:
oguerrero@turing.ac.uk
@guerrero_oa

SELECTED PAPERS

How do governments determine policy priorities? Studying development strategies through networked spillovers.

Uncovering Vote Trading Through Networks and Computation

Diffusing Workers in a Multiplex World

The Network Composition of Aggregate Unemployment

Understanding Unemployment in the Era of Big Data: Policy Informed by Data-Driven Theory

Labor Flows and the Aggregate Matching Function: A Network-Based Test Using Employer-Employee Matched Records

Employment Growth through Labor Flow Networks

Víctor L. Urquidi Prize in Economics

I am grateful to the outstanding Mexican social science and humanities research institute El Colegio de México for awarding me the Víctor L. Urquidi Economics Prize. Together with Professor Gonzalo Castañeda, I combine agent-based modelling, network science and behavioural economics to estimate government policy priorities. The latter has been identified as a challenging problem in Development Economics literature because, on one hand, development goals are multi-dimensional and, on the other, the policies to achieve them are not independent of each other. Find more in our latest pre-print.

 

Paid Summer Internships for PhD Students

Uncovering Hidden Cooperation in Democratic Institutions
The Alan Turing Institute’s Summer Internship Programme
 
I am looking for two PhD students for a paid summer internship in Computational Social Science at The Alan Turing Institute. The Turing is running a 12-week Internship Programme for students to work on one of the projects during summer 2018, between 25 June and 14 September. Interns will be based at the Turing headquarters in the British Library, London. The application deadline is Wednesday 31st of January at 12:00 (GMT).
 
Eligibility criteria:
  • Applicants must currently be studying for a PhD at a university within the UK.
  • Applicants must be eligible to work in the UK and be available for the duration of the internship project.

Further information about the Turing’s internship programme and the application process can be found here: http://bit.ly/2CaxMKQ.

Project Specifics

The goal of the internship is generalising the method of Vote-Trading Networks (http://bit.ly/2CCcU02), previously developed to study hidden cooperation in the US Congress, to a wider set of democratic institutions, developing a research programme in the measurement and characterisation of hidden cooperation on a large scale.

 
The project aims at improving our understanding of cooperation in democratic institutions. In particular, it will shed new light on cooperative behaviour that is intentionally ‘hidden’. An example of such hidden cooperation is when two legislators agree to support each other’s favourite bills, despite their ideological preferences, and/or despite such support being disapproved by their respective voters or campaign donors. This kind of behaviour is key to the passage or blockage of critical legislation; however, we know little about it due to its unobservable nature. The objective of this project is to exploit newly available big data on voting behaviour from different institutional contexts and state-of-the-art methods from data science in order to develop two distinct research papers with clear policy implications for the design and evaluation of political institutions.
 
Political institutions, such as parliaments and congresses, shape the life of every democratic society. Hence, understanding how legislative decisions arise from hidden agreements has direct implications on the guidelines that governments follow when conducting policy interventions. Moreover, decision making by voting is common in other areas than legislative law-making. It is prevalent in courts, international organisations, as well as in board rooms of private enterprises.
 
The internship is structured in two projects, each looking to a specific institution: the United States Supreme Court, and the United Nations (UN) General Assembly. It is organised in three phases. As part of the internship, the students will receive an introduction to the topic of cooperation in social systems, with a particular focus on political institutions and situations in which cooperation is intentionally hidden, such as vote trading, and, hence, unobservable in real-world data. Some specifics about this phase are the following:
  • Introduction to vote trading in democratic institutions, its societal relevance, evidence, measurements and challenges.
  • Introduction to web scraping and text mining.
  • Tutorial on network science.
  • Tutorial on stochastic and agent-based models.
  • Tutorial on the Vote-Trading Networks framework.