ONGOING PROJECTS

 

The cost of Civil conflict in low-to-middle income countries.

IP: Hannes Mueller

Open Philanthropy

2022


The project will produce a literature review and new research to produce a common framework for the literature . Emphasis will be on collating different prominent estimates for civil wars in terms of (a) the growth costs (b) the costs in terms of lives lost (or DALYs generated), as well as (c) possibly estimates on refugees/IDPs generated by conflict. 

This research “the research will be financed by Open Philanthropy, a nonprofit public benefit corporation organized and operated exclusively for the purpose of promoting social welfare. A report will be delivered at the end of the Project.

Dynamic Early Warning and Action Model

IP: Hannes Mueller

FCDO-UK Goverment

2021-2022


Armed conflicts pose significant challenges for the international community. Predicting conflict outbreaks and escalation, and assessing the best timing and nature of interventions is fundamental for policy makers to reduce death tolls and economic costs of armed violence. Policies to address armed conflict should thus be developed within a framework that integrates forecasts of future events into a dynamic model of optimal decision making. While such models are regular tools of the economics literature and have been applied to financial crisis, debt burdens, pandemics and climate change, they haven’t been used to study conflicts. This project fills this gap.


The contribution of this project is two-fold. First, we will develop a forecast framework which is able to track the entire conflict cycle, from forecasting new outbreaks, escalation of conflict, de-escalations out of conflict to the re-emergence of conflict in the post-conflict phase in which countries are particularly fragile. We will do this through a cutting-edge machine learning model which integrates a text-based forecast of conflict outbreaks with geo-spatial and temporal forecast of conflict dynamics during conflict. The estimated risks will be made accessible through the webpage: conflictforecast.org. Second, we will build a theoretical framework for optimal interventions which embeds the forecasting module and can be used as a laboratory to study costs and benefits of different intervention strategies and locations, from pre-conflict prevention, to de-escalation and post-conflict stabilization. 

AXA POSTDOCTORAL FELLOWSHIP

2021-2023


Ursulla Mello has been awarded an AXA post-doctoral fellowship for two years, in order to support her project "Public Policies for Tackling Inequality" at the Fundació d’Economia Analítica and IAE-CSIC. She will study how governmental policy could reduce inequality in access to higher education. The AXA Fellowship is a funding scheme aiming at supporting young promising researchers on a priority topic aligned with AXA and the Society. This support should be transformative for the researcher and the advancement of her research field.


https://www.axa-research.org/

Aggregation and acquisition of information in markets: positive and normative aspects

PI: Jordi Brandts and Xavier Vives

IESE

2021-2023


IESE and the Fundació d’Economia Analíta have signed a collaboration agreement for the development of research on positive and regulatory aspects of the aggregation and acquisition of information in markets. The aim of the project is to analyze the incentives of economic agents to acquire information when subsequently they have to compete and trade in the market, analyze information acquisition and trading strategies, and the welfare impact on all market participants. The welfare analysis will follow in order to prescribe policy measures. The project aims to contrast the predictions of the theoretical models with experimental evidence in simplified scenarios. In particular, it would aim to validate in the laboratory the derived behavior taxonomy obtained in the theoretical analysis. The results of the research will serve as a basis for the publication of articles on this subject.

Development of indicators of economic, political and economic policy risk, with a global perspective, based on textual analysis, through the use of "machine learning" techniques

PI: Hannes Mueller

Banco de EspaƱa

2020-2023


Political risks are key problem for developing countries and has recently also affected countries in Europe indirectly through forced migration and directly through political challenges to their political order. This has triggered several initiatives in the international donor community that aim at reducing State fragility. The Covid-19 crisis is bound to re-enforce these problems in the mid-term. In the social sciences, research on fragility has long received a lot of attention and, most recently, the issue has also been taken up by researchers outside the social science and, specifically, in machine learning.


This project has three objectives:


1.- Use the developed tools in Mueller and Rauh (2018, 2019) on the full text of millions of newspaper articles that are updated constantly to provide monthly updates of political risk to the Banco de España (BdE) and other public actors and interested researchers.

2.- Tailor the index to needs of the BdE by developing and providing additional forecasts of political and economic risks.

3.- Evaluate the ability of the framework to provide true out-of-sample forecasts.


In relation to this project, the web page https://conflictforecast.org/, has been created with the aim of helping preventive efforts and make the method accessible to a wider audience through state-of-the-art data visualization tools, as well as to make forecasts available to professionals and research teams from all over the world. The researchers involved on the project have produced a paper on “Conflict, social unrest and policy uncertainty measures are useful for macroeconomic forecasting”  where they generate monthly measures of “institutional instability” for Brazil, Colombia and Mexico and use them to predict quarterly GDP using standard methods of macroeconomics. The results clearly indicate that the institutional instability measure used is very useful for making predictions.