Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 18th May 2024, 06:26:48am BST

 
 
Session Overview
Session
Labour markets, (income) inequality and mobility
Time:
Friday, 21/July/2023:
8:30am - 10:00am

Session Chair: Natalie J Yang, Columbia University, United States of America;
Location: Jesus College, Sibilla room

Breakout room

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Presentations

Locked-in, far away from workplace? Effects of public housing subsidies on moving and commute

Kananoja, Lauri Markus; Saarimaa, Tuukka; Falkenbach, Heidi; Ala-Mantila, Sanna

Aalto University/School of Engineering, Finland;

Discussant: Hao, Yang (The People’s Bank of China)

This paper examines the lock-in effect of public housing. We focus

on the capital region of Finland and estimate the effects of public hous-

ing subsidies on moving propensity and commuting distance of public

housing tenants. Our panel ranges from 2010 to 2020. Using hedo-

nic models, we estimate the public housing tenants' subsidies for the

city-owned units and find them considerable. Using linear probability

and fixed effects models, estimated subsidies and household micro data,

we find that the average moving propensity of public housing tenants

decreases by 14 percent. Furthermore, we find that the average com-

muting distance of public housing tenants increases by 12 percent. For

both moving and commuting distance, the size of subsidy strengthens

the effect. These suggest that public housing tenants may be willing to

lock-in to keep their subsidy.



Homeownership, Polarization, and Inequality

Parkhomenko, Andrii

University of Southern California, United States of America;

Discussant: Kananoja, Lauri Markus (Aalto University/School of Engineering)

The rise of income inequality and job polarization have been more pronounced in large U.S. cities. I offer a new explanation: when price-rent and price-wage ratios grow faster in large cities, middle-income households increasingly cannot afford to own a house there. They move to smaller cities and the middle of the income distribution in large cities hollows out, making them more polarized and unequal. I document that (1) commuting zones with higher price growth experienced larger polarization and increase in inequality since 1980 and (2) middle-income households migrate more often to cheaper states for housing-related reasons than low- or high-income households. Using a quantitative spatial equilibrium model with tenure choice and skill heterogeneity, I find that disproportionate growth of prices relative to incomes and rents in large cities accounts for about one-half of the gap in inequality growth and polarization between large and small cities.



Human Capital and Productivity across U.S. Cities

Fu, Yuming1; Hao, Yang2; Yang, Shangming3

1National University of Singapore, Singapore; 2The People’s Bank of China, China; 3Zhongfang Information Technology;

Discussant: Parkhomenko, Andrii (University of Southern California)

Using the generalized division-of-labor (GDL) human capital productivity (HCP) accounting (Jones, AER 2014 and 2019), we show that urban productivity divergence across cities must be reflected by skill divergence rather than wage divergence. We find that, among US cities, the skill divergence is driven by skill complementarity among high-skill workers. Thus, the concentration of high-skill workers generates a positive spillover effect on the HCP of high-skill workers but a negative spillover effect on that of middle-skill and low-skill workers. In contrast, urban productivity generates a pecuniary externality that raises the wage of all skill types equally. The variation in the skill premium reflects the differences in compensating wage differential across cities (or labor supply elasticity) between high-skill and low-skill workers.



 
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