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Housing speculation and its economic consequences

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Via VOX EU

What caused the US housing bubble in the 2000s and led to the severe economic recession after its collapse? The credit expansion to subprime households is widely regarded as a key driver (e.g. Mian and Sufi 2009, Keys et al. 2009, Justiano et al. 2017). However, housing speculation represents another potentially important, yet understudied mechanism in driving housing and economic cycles. In our recent paper (Gao et al. 2019), we find that housing speculation was largely independent of credit expansion to subprime households during the 2000s and it contributed significantly to the rising housing prices and local economic expansions during the boom period of 2004–2006 and adversely affected economic activities during the bust period of 2007–2009.

Housing speculation in the US in the 2000s

In the mid-2000s, housing speculation became a national phenomenon in the low interest rate environment of the US. We measure housing speculation by the fraction of non-owner-occupied home (second and investment homes) purchases, which conveniently proxy for the intensity of housing speculation relative to primary home demand. Figure 1 depicts the fraction of non-owner-occupied home purchases for the whole nation and three cities – New York, Las Vegas, and Charlotte – from 2000 to 2010. Non-owner-occupied home purchases accounted for a sizable fraction of mortgage originations, comprising 15.31% of all new originations in the US at its peak in 2005. Among the three cities, Las Vegas had the highest fraction of non-owner-occupied home purchases, which rose from a level 17.77% in 2000 to 29.41% in 2005, and then dropped back down to 17.77% in 2008. New York had the lowest fraction, which, while experiencing a synchronous rise and fall with the other two cities, remained below 7% during this period.  

Figure 1 Fraction of non-owner-occupied home purchases

Note: This figure plots the share of non-owner-occupied home purchases for the United States and three cities, New York, Las Vegas, and Charlotte. The fraction of non-owner-occupied home purchases in each city is computed from the ‘Home Mortgage Disclosure Act’ data set.

More importantly, housing speculation also represented a source of housing demand largely orthogonal to the widely acknowledged credit expansion to subprime households that occurred during the housing boom. Statistically, the correlation coefficient between the fraction of non-owner-occupied home purchases and that of subprime mortgages across ZIP codes in the mid-2000 is only 0.004 and is insignificant. As such, speculation may act as a complementary channel in explaining the housing and economic cycles during the 2000s.

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Figure 2 provides scatter plots of the real housing price changes during the boom period of 2004–2006 (panel A) and the bust period of 2007–2009 (panel B) against the fraction of non-owner-occupied home purchases during the boom period of 2004–2006 at the ZIP code level. These plots display a clear association between more intensive housing speculation and both greater housing price increases during the boom, and greater subsequent housing price collapses during the bust.

Figure 2 Speculation and housing price cycle

Panel A 

Panel B

Note: These figures plot the real housing price change during the boom period of 2004 to 2006 (panel A) and the bust period of 2007 to 2009 (panel B) against the fraction of non-owner-occupied home purchases in 2004 to 2006 at the ZIP code level. 

We also find that ZIP codes with a greater share of non-owner-occupied home purchases during the boom not only had more pronounced housing cycles during the boom and bust but also experienced greater swings in employment, payroll, per capital income, and the number of business establishments. 

However, as intensive purchases of non-owner-occupied homes may reflect local housing demand or other unobservable economic conditions, rather than being a cause of housing and economic cycles, we face the common endogeneity problem. To confront this challenge, we construct a novel instrument for housing speculation that takes advantage of the variation across US states in their taxation of capital gains. While homeowners can exclude capital gains from the sale of their primary residence from their income taxes, this exclusion does not cover capital gains from selling non-owner-occupied homes. As a result, housing speculation is more intensive in states with either no or low capital gains taxes.

Housing speculation, house prices, and the real economy

By instrumenting non-owner-occupied home purchases with the capital gains tax variable, our analysis shows that an increase of 9.9% (one standard deviation across ZIP codes) in the share of non-owner-occupied home purchases in 2004–2006 led to a housing price increase of 26.5% during the boom, and a drop of 37.4% during the bust. Similarly, this increase led to an increase of 13.7% in real payrolls, 8.4% in employment, 12.9% in per capita income, and 6.8% in the number of establishments in 2004–2006. During 2007–2009, in contrast, it contributed to declines of 15.4% in real payrolls, 14.6% in employment, 7.8% in income per capita, and 8.7% in the number of establishments. Furthermore, among states with lower capital gains taxes, the share of non-owner-occupied home purchases responds more strongly to past housing price increases. This finding supports extrapolative expectations as a key force of housing speculation. 

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We also examine two transmission mechanisms to understand how housing speculation during the boom propagated to the real economy during the bust. The first is the supply overhang channel. By driving up housing demand, housing speculation may have boosted the supply side of the housing market during the boom. The increased housing supply would then overhang on the housing market and the local economy during the bust, as argued by Rognlie et al. (2018). Figure 3 provides a scatter plot of the building permits in 2004–2006 relative to the number of housing units in 2000 – our measure of new housing supply – against the fraction of non-owner-occupied home purchases in the same period.1 The plot vividly illustrates a positive relation between housing speculation and new housing supply. Our empirical analysis further shows that an increase of one standard deviation in instrumented housing speculation in 2004–2006 led to an increase of 4.2% in building permits in 2004–2006, relative to the number of housing units in 2000, and decreases of 33.8% in construction-sector employment and 12.4% in non-construction sector employment in 2007–2009. These findings confirm the importance of the supply overhang channel: areas with more intensive housing speculation during the boom also had a greater increase in housing construction in the same period, which, in turn, contributed to the subsequent contraction of the construction sector during the bust. 

Figure 3 Speculation and new housing supply

Note: This figure plots building permits in 2004 to 2006 relative to the number of housing units in 2000 against the fraction of non-owner-occupied home purchases in 2004 to 2006 at the county level.

To further explain the substantial downturn experienced by non-construction sectors, we also examine a second transmission channel, local household demand (as suggested by Mian et al. 2013 and Mian and Sufi 2014), by analysing the impact of housing speculation on non-tradable sectors – and the retail and restaurant sectors more narrowly – which primarily rely on local consumption demand. We find significant real effects through this channel. An increase of one standard deviation in instrumented housing speculation in 2004–2006 led to a decrease of 15.1% in non-tradable sectors’ employment in 2007–2009, and a decline of 15.6% in the retail and restaurant sectors, specifically. In contrast, housing speculation had a more modest effect on employment in tradable sectors and in industries other than retail and the restaurant business.

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Concluding remarks

In summary, we provide evidence that housing speculation, as measured by the fraction of non-owner-occupied home purchases, represents an important mechanism, independent of the expansion of subprime credit, in explaining the cross-sectional variation in the housing and economic cycles across the US during the 2000s. Our results suggest that housing speculation had real economic consequences during the boom by increasing housing prices and fuelling local economic expansions, and during the recession by depressing residential construction employment, as a result of supply overhang, and by reducing local household demand.

References

Gao, Z, M Sockin and W Xiong (2019), “Economic consequences of housing speculation”, Review of Financial Studies, forthcoming.

Keys, B J, T Mukherjee, A Seru, and V Vig (2009), “Financial regulation and securitization: Evidence from subprime mortgage loans”, Journal of Monetary Economics 56: 700–720.

Justiano, A, G Primiceri, and A Tambolatti (2017), “Credit supply and the housing boom”, mimeo, Federal Reserve Bank of Chicago and Northwestern University.

Mian, A and A Sufi (2009), “The consequences of mortgage credit expansion: Evidence from the U.S. mortgage default crisis”, Quarterly Journal of Economics 124: 1449–96.

Mian, A, K Rao, and A Sufi (2013), “Household balance sheets, consumption, and the economic slump”, Quarterly Journal of Economics 128: 1687–726.

Mian, A and A Sufi (2014), “What explains the 2007–2009 drop in employment?”, Econometrica 82: 2197–223.

Rognlie, M, A Shleifer, and A Simsek (2018), “Investment hangover and the great recession”, American Economic Journal: Macroeconomics 10(2): 113-53.

Endnotes

1  Given that the Census Bureau provides building permit data only at the county level, we carry out the analysis by aggregating non-owner-occupied home purchases and all other controls to the county level.


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