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Urban dynamics: learning from integrated models and big data

Objective

City growth is driven by a combination of systematic determinants and shocks. Random growth models predict realistic city size distributions but ignore, for instance, the strong empirical association between human capital and city growth. Models with systematic determinants predict degenerate size distributions. We will develop an integrated model that combines systematic and random determinants to explain the link between human capital, entrepreneurship and growth, while generating relevant city size distributions. We will calibrate the model to quantify the contribution of cities to aggregate growth.
Urban growth also has a poorly understood spatial component. Combining gridded data of land use, population, businesses and roads for 3 decennial periods we will track the evolution of land use in the US with an unprecedented level of spatial detail. We will pay particular attention to the magnitude and causes of “slash-and-burn” development: instances when built-up land stops meeting needs in terms of use and intensity and, instead of being redeveloped, it is abandoned while previously open space is built up.
Job-to-job flows across cities matter for efficiency and during the recent crisis they have plummeted. We will study them with individual social security data. Even if there have only been small changes in mismatch between unemployed workers and vacancies during the crisis, if workers shy away from moving to take a job in another city, misallocation can increase substantially.
We will also study commuting flows for Spain and the UK based on anonymized cell phone location records. We will identify urban areas by iteratively aggregating municipalities if more than a given share of transit flows end in the rest of the urban area. We will also measure the extent to which people cross paths with others opening the possibility of personal interactions, and assess the extent to which this generates productivity-enhancing agglomeration economies.

Fields of science (EuroSciVoc)

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

ERC-ADG - Advanced Grant

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2015-AdG

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Host institution

FUNDACION CENTRO DE ESTUDIOS MONETARIOS Y FINANCIEROS
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 292 586,25
Address
CASADO DEL ALISAL 5
28014 Madrid
Spain

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Research Organisations
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 292 586,25

Beneficiaries (1)

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