1. Carlos Garriga and Aaron Hedlund: Housing Finance, Boom-Bust Episodes and the Macroeconomy
Discussion by Andrew Coleman
University of Otago and New Zealand Productivity Commission

2. A wealth of detail (1) Infinite-lived agents with income uncertainty
Multiple housing types
Elastically supplied (small) rentals
Variable-sized houses for owner-occupancy
A matching function for house sales and purchase
Households sometimes wish to upgrade
Liquidity issues arise from volume of sales

3. A wealth of detail (2) 4. Different types of mortgage contracts
Fixed rate mortgages with option clauses allowing households to renegotiate terms when interest rates fall
Fixed rate mortgage rates price in forward looking interest rates
Adjustable rate mortgages that reflect short wholesale rates
Loan-to-value ratios restrict the ability of people to borrow more to buy bigger houses (as do payment-to-income constraints)
Mortgages have option to default
Banks charge a premium to cover option costs and default costs

4. Question: when are which bits most important?
The role of liquidity in the sales process is most impressive
Can explain correlation between sales volumes and price movements
The rental market seems unimportant
The role of the responsiveness of the new construction market to interest rate changes seems opaque.
How important is the infinitely lived agent assumption (rather than a finitely lived lifecycle model assumption) - for the housing ladder and for the distribution of mortgages
Non-Americans are baffled that US banks offer fixed rate mortgages with option to renegotiate interest rates downwards

5. Things to wonder about.
At the heart of the application of the model is a desire for agents to upgrade housing when interest rates fall.
This leads to the aggregation problem identified by Rosen (1974) and Sweeney (1974)
Rosen, S Hedonic prices and implicit markets: product differentiation in pure competition. Journal of Political Economy, 82(1),
Sweeney, J. L “A commodity hierarchy model of the rental housing market.” Journal of Urban Economics, 1(3),

6. When interest rates fall, many people want to upgrade to a better house
In aggregate this can only occur by building new, bigger houses
Builders build bigger houses to overcome the shortfall
In the short run, the building industry cannot upgrade the quality distribution fast enough so prices for bigger houses rise
Adjustment can take a long time and prices rise during the transition, depending on expectations – there is price backwardation
The extent prices increase depends on long run costs of supplying different sized houses and the dynamics of price adjustment over the whole quality distribution.

7. What is the distribution of new building size and mortgage size implied by the model??
In the data, new houses got a lot bigger as interest rates fell
The relatively- increased demand for large houses continued after even though total demand collapsed
The change was quite different in the North east and Midwest relative to the South and West – can this be explained by the model, or is this due to
Immigration and age distribution differences
Finite-lifecycle model considerations.

9. All new houses are big

10. New construction collapses across the size distribution

11. New construction collapses across the size distribution

13. Fewer small houses and more big houses during the boom

14. Fewer small houses and more big houses during the collapse

15. Is the model consistent with these data?
(a) Could you present the model implications about the size of new construction?
(b) Are these data important – is the size distribution of new construction a key part of the mechanism?
(c ) What is the role of capacity constraints in the building sector - are they a major reason why prices rise when interest rates fall, as the quality distribution cannot be changed all at once?
(d) After the boom, does the continued decline in small house construction reflect low interest rates (demand factors) or credit restrictions

16. Regional Variation

17. Regional Variation
Is it important that there seems to be differences in the construction activity in the South and West, and the north and mid-west?
Is this accounted for by population growth (doesn’t explain the differences in the booms and busts)
Does it suggest that the boom-bust cycle depends on the elasticity of supply of houses during the boom and credit markets during the bust?

20. Summary
Ambitious model, seems to have a very good mechanism for explaining how liquidity endogenously leads to the decline in market volumes and the rise in default
The implications for the distribution of house size could be made more explicit
It would be nice to know if the implications for mortgage size are consistent with the data or whether a lifecycle model may provide additional insight.