We conduct research about
Regional Inequality Regional Growth Geography of Development Economic and Social Convergence Labor markets and macroeconomic shocks Economic growth and structural change

Quantitative Regional and Computational Science

Research Projects and Outcomes


In the QuaRCS lab, we exploit the integration of econometrics, data science, and machine learning methods to understand and inform the process of economic growth and development of countries, regions, and industries.

The QuaRCS lab is also a member of the UN Sustainable Development Solutions Network (SDSN). As such, it helps mobilize scientific knowledge and technological expertise to promote global sustainable development.



Research methods

Modern data science

To conduct research across all our projects, we use a modern data science workflow.

Applied econometrics

To conduct research across all our projects, we implement the latest advances in applied econometrics.

Machine learning

To conduct research acroos various projects, we use various clustering algorithms from the unsupervised manchine learning literature.

Spatial econometrics

Exploratory spatial data analysis (ESDA), exploratory space-time data analysis (ESTDA), spatial dependence, spatial heterogoenity.

Nonparametric econometrics

Nonparametric density estimation, mixture densities.

Bayesian econometrics

Bayesian model averaging.

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