Marco van der Leij

Economics: An Emerging Small World?

We study the evolution of social distance among economists over the period 1970–2000. While the number of economists has more than doubled, the distance between them, which was already small, has declined significantly. The key to understanding the short average distances is the observation that economics is spanned by a collection of interlinked stars. A star is an economist who writes with many other economists, most of whom have few coauthors and generally do not write with each other.

Social Networks and Research Output

We study how knowledge about the social network of an individual researcher, as embodied in his coauthor relations, helps us in developing a more accurate prediction of his or her future productivity. We find that incorporating information about coauthor networks leads to a modest improvement in the accuracy of forecasts on individual output, over and above what we can predict based on the knowledge of past individual output. Second, we find that the informativeness of networks dissipates over the lifetime of a researchers career. This suggests that the signaling content of the network is quantitatively more important than the flow of ideas.

A Social Network Analysis of Occupational Segregation

This paper proposes a simple social network model of occupational segregation, generated by the existence of inbreeding bias among individuals of the same social group. If network referrals are important in getting a job, then expected inbreeding bias in the social structure results in different career choices for individuals from different social groups, which further translates into stable occupational segregation equilibria within the labour market. Our framework can be regarded as complementary to existing discrimination or rational bias theories used to explain persistent observed occupational disparities between various social groups.

Identifying Booms and Busts in House Prices under Heterogeneous Expectations

We introduce heterogeneous expectations in a standard housing market model linking housing rental levels to fundamental buying prices. Using quarterly data we estimate the model parameters for eight different countries, US, UK, NL, JP, CH, ES, SE and BE. We find that the data support heterogeneity in expectations, with temporary endogenous switching between fundamental mean-reverting and trend-following chartists beliefs based on their relative performance. For all countries we identify temporary house price bubbles, amplified by trend extrapolation, and crashes reinforced by fundamentalists. The qualitative predictions of such non-linear models are very different from standard linear benchmarks, with important policy implications. The fundamental price becomes unstable, e.g. when the interest rate is set too low or mortgage tax deductions too high, giving rise to multiple non-fundamental equilibria and/or global instability.

The Formation of a Core Periphery Structure in Heterogeneous Financial Networks

Recent empirical evidence suggests that financial networks exhibit a core-periphery network structure. This paper aims at giving an explanation for the emergence of such a structure using network formation theory. We propose a simple model of the overnight interbank lending market, in which banks compete for intermediation benefits. Focusing on the role of bank heterogeneity, we find that a core-periphery network cannot be unilaterally stable when banks are homogeneous. A core-periphery network structure can form endogenously, however, if we allow for heterogeneity among banks in size. Moreover, size heterogeneity may arise endogenously if payoffs feed back into bank size.

Complex Methods in Economics: An Example of Behavioral Heterogeneity in House Prices

We show how simple statistical techniques for capturing critical transitions used in natural sciences, fail to capture economic regime shifts. This implies that we need to use model-based approaches to identify critical transitions. We apply a heterogenous agents model in a standard housing market model to show that these family of models generate non-linear responses that can capture such transitions. We estimate this model for the United States and the Netherlands and find that first, the data does capture the heterogeneity in expectations and, second, that the qualitative predictions of such nonlinear models are very different to standard linear benchmarks. It would be important to identify which approach can serve best as an early warning indicator.

Social Networks and Labor Market Inequality between Ethnicities and Races

This paper analyzes the relationship between unexplained racial/ethnic wage differentials on the one hand and social network segregation, as measured by inbreeding homophily, on the other hand. Our analysis is based on both U.S. and Estonian surveys, supplemented with Estonian telephone communication data. In case of Estonia we consider the regional variation in economic performance of the Russian minority, and in the U.S. case we consider the regional variation in black-white differentials. Our analysis finds a strong relationship between the size of the differential and network segregation: regions with more segregated social networks exhibit larger unexplained wage gaps.

Competing Transport Networks

In a circular city model, I consider network design and pricing decisions for a single fast transport connection that faces competition from a slower but better accessible transport mode. To access the fast transport network individuals have to make complementary trips by slow mode. This fact has interesting implications on the location decisions. I show that in the presence of competition the profit-maximizing and socially optimal decision would be to cluster the two stations. By contrast, in the absence of competition both a profit-maximizing firm and a social planner would locate the two stations on opposite sides of the circle.