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: 13th Aug 2022, 09:47:20am IST

 
 
Session Overview
Session
Elasticity of Supply
Time:
Thursday, 07/July/2022:
4:15pm - 6:00pm

Session Chair: Jason Barr, Rutgers University-Newark, United States of America
Location: Room A

Room in the Arts Building, Trinity College Dublin. Exact details to be confirmed by May 31

External Resource:
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Presentations

Supply Constraints and Housing Markets: Evidence from a Spatially Matched Dataset

Yu, Xiaolun

University of Reading, Henley Business School, United Kingdom;

Supply constraints and their impacts on housing markets are understudied in China due to a lack of reliable measures. This paper first applies and extends the method proposed by Glaeser et al. (2005) to estimate ‘regulatory tax rate’ in 115 major Chinese cities. Using a unique spatially matched dataset of land plots and residential projects and combining local developer profit margin and construction cost information, I find substantial variations in regulatory restrictiveness across Chinese cities. I then explore the impacts of both regulatory constraint and geographical constraint on housing prices in China. Exploiting the exogenous variation generated from local dialects, government tax enforcement, and historical amenity, I find that housing prices respond more strongly to changes in local salaries in cities with tighter supply constraints. This finding is robust after I apply a Bartik-type predicted local employment as the demand shifter. I also find that housing construction responds less strongly to demand shocks in places with more relaxed supply conditions.



Remote Shocks, Migration, and Housing Supply in India

Dutta, Arnab1; Green, Richard1; Gandhi, Sahil2

1University of Southern California; 2University of Manchester;

Housing supply elasticity estimates for cities in large and rapidly urbanizing countries like India can tell us whether their urban housing markets' supply keeps pace with the rising demand. The case of India is particularly interesting in this regard because of its variety of housing typologies. We estimate the supply elasticity of (1) durable or formal houses made of concrete, bricks, and metal, (2) non-durable or informal houses made of thatch, mud, plastic, etc. and typically found in slums, and (3) vacant residential housing units in urban India between 2001 and 2011. We use two migration-inducing exogenous events --- negative rainfall shocks and a highway upgrade program --- occurring in distant states as demand shifters for local urban housing markets.

We estimate that the decadal supply elasticity of durable housing in urban India is 1.62. Second, we find that the supply elasticity of non-durable housing is -0.49. A negative supply elasticity value for non-durable houses is consistent with the existence of urban gentrification through the demolition and upgradating of slums. And finally, we estimate the elasticity of vacant residential housing units' supply to be 2.62.



Why have house prices risen so much more than rents in superstar cities?

Hilber, Christian A. L.1; Mense, Andreas2

1London School of Economics, United Kingdom; 2IAB;

In most countries house prices have risen much more strongly than rents over the last two decades and much more so in supply constrained superstar cities. Moreover, the price-to-rent ratio has been cyclical. These facts are consistent with spatial variation in supply constraints and serially correlated demand shocks. We test our model predictions employing panel data for England. Our instrumental variable-fixed effect estimates suggest that in Greater London auto-correlated labor demand shocks in conjunction with supply constraints explain two-thirds of the 153% increase in the price-to-rent ratio between 1997 and 2018. We can exclude competing explanations for our findings.



 
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