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Abstract

Markets where quality is hard to observe allocate opportunities under uncertainty. In such settings, informal mechanisms like trust, reputation, and relational information help agents screen partners when formal verification is limited. These mechanisms are central to innovation and growth, yet they are difficult to observe empirically because uncertainty seldom shifts in a clear and exogenous way. The early modern academic book market of the Low Countries provides an exceptional setting to study these dynamics. It combined dense scholarly communities with an interconnected print industry, while the secession between Northern and Southern provinces produced a sharp divergence in censorship intensity that was exogenous to the book trade and emerged across a stable geographic frontier. This generated quasi-exogenous variation in ideological uncertainty while commercial and technological fundamentals remained comparable. I construct a new dataset linking book trade records to academic affiliations, enabling reconstruction of the multilayer network connecting authors to colleagues and to printers. I develop a mean–variance framework in which printers evaluate authors under noisy signals, with relational proximity increasing signal precision and the value of precision rising when ideological risk intensifies. Finally, I identify the informational role of networks through time-to-event models of first publication and a spatial regression discontinuity design at the 1585 frontier.

Researcher(s)

• Promoter: Maes Sebastiaan
• Co-promoter: Egorov Konstantin

Research team(s)

• Economics01/10/2026 - 30/09/2029

Funding

• FWO

Project type(s)

• Research Project

Abstract

This research integrates household and spatial economics to examine how partner, labor, housing, and location choices interact to shape economic outcomes. Despite their fundamental role in individual welfare and macroeconomic patterns, these interdependent decisions remain understudied. Most existing work treats households as single decision-makers, overlooking the bargaining processes that drive family decision-making. We address this gap by developing a novel nonparametric revealed preference framework that extends the collective household model to incorporate spatial dimensions. This approach accounts for unobserved preference heterogeneity while identifying deep behavioral parameters. We construct an integrated longitudinal dataset that combines household microdata from the Panel ¶¶Òõ¶ÌÊÓƵ of Income Dynamics with high-resolution spatial data. We investigate three key questions: 1) How do spatial factors influence household bargaining, and conversely, how does household bargaining shape spatial decisions? 2) What are the implications for consumption, labor, housing, and location decisions? How does this impact inequality within households and across geographic regions? How have these patterns evolved over time? 3) What is the impact of counterfactual policy changes or economic shocks on decisions and individual and aggregate welfare?

Researcher(s)

• Promoter: Maes Sebastiaan

Research team(s)

• Economics01/05/2026 - 30/04/2030

Funding

• BOF

Project type(s)

• Research Project

Abstract

It is now widely recognised that social interactions play a crucial role in economic decision-making and outcomes. Taking such interactions into account is of first-order importance to identify the true mechanisms underlying microeconomic behaviour and to assess individual and social welfare. Almost all empirical work that studies these interactions, however, proceeds by invoking strong parametric assumptions in the econometric model. This does not only obfuscate the empirical content of the model; it also leads to biased estimates, and therefore to biased conclusions. In response to these issues, this project makes a double contribution. First, I will develop a flexible model that significantly generalises the widely-applied linear-in-means model of social interactions, in which the outcome of an individual arbitrarily depends on the characteristics and outcomes of her connections. I will subsequently show that this model can be identified and estimated with nonparametric IV techniques using the average characteristics of connections-of-connections as an instrument, extending previous results from a linear to a nonlinear context. Second, I will investigate the channels through which social interactions can arise in structural models of demand. Drawing from the literature on differential demand and revealed preferences, I will then characterise what are the testable implications of these models. An experiment will empirically validate various specifications of the model.

Researcher(s)

• Promoter: Cosaert Sam
• Fellow: Maes Sebastiaan

Research team(s)

• Economics01/10/2022 - 30/09/2025

Funding

• FWO

Project type(s)

• Research Project