We conduct research about
Regional Inequality Regional Growth The Geography of Development Economic and Social Convergence Economic Growth and Structural Change

Quantitative Regional and Computational Science

Research Projects and Outcomes

ABOUT US

In the QuaRCS network, we conduct research on quantitative regional and computational science. We exploit the integration of spatial data science, econometrics, and machine learning to understand and inform the process of sustainable development across subnational regions and countries.

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

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Activities

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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