Luca Looser

PhD Candidate in Economics · Universitat Pompeu Fabra

Macro Development · Economic Geography · Family Economics

I study how families and geography shape structural transformation and economic development. My work combines large-scale data, quasi-experimental evidence and quantitative spatial models.

I am on the 2026–27 academic job market.

Advisors: Elisa Giannone and Dávid Krisztián Nagy.

luca.looser@upf.edu
Luca Looser
JOB MARKET PAPER

Dynastic Structural Change

Kinship can slow structural change by tying workers to existing sectors and places, but development also reshapes what those ties connect workers to. I study this feedback during U.S. structural transformation from 1880 to 1950.

Using new data on extended family relationships covering 32 million individuals, I show that relatives shape sector entry and migration while worker reallocation creates new connections for later generations. A dynamic spatial model quantifies how changes in kinship connections affect the pace of structural change.

Abstract Paper
Evidence from Dynastic Structural Change
OTHER RESEARCH

Research

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Working Paper

Unequal Global Convergence

with Shoumitro Chatterjee, Elisa Giannone, Tatjana Kleineberg and Kan Kuno

We study how structural transformation toward high-skill services changes regional convergence around the world.

Draft →
Working Paper

The Intergenerational Consequences of a Temporary Shock

with Chanont Banternghansa and Elisa Giannone

We use temporary import restrictions in Thailand to study persistent sectoral reallocation and intergenerational responses.

Abstract →
Work in Progress

Inheriting Geography

Marriage and the Intergenerational Spatial Transmission of Opportunity

Marriage reshapes family geography by changing where households settle and which destinations are connected to the next generation. Using linked U.S. families from 1880 to 1950, I show that marriage expands family-connected geography, affects where couples settle and creates destination connections that persist into the next generation.

Abstract →