Econometric versus Traditional Approaches to Housing Planning: Lessons from the CLG Affordability Model Geoff Meen March 4, 2010 University of Reading 2006 www.reading.ac.uk
Issues Affordability and household projections Housing supply and the impact on affordability Supply targets and the implied price elasticities The role of migration in inter-regional adjustment Supply targets at the sub-regional level Building in the South or North differential effects & housing based regional policy Housing supply and the roles of planning/history/geography Aspirations for owner-occupation Effects of the credit crunch Housing quality versus numbers of units International migration and the effects on prices, domestic household formation and inter-regional migration Migrant household formation and tenure patterns Regional variations in response to national policy shocks To put Regional your footer correlations here go to View in housing > Header supply. and Footer 2
. Concentrate on: Affordability and household projections Housing supply and the impact on affordability Supply targets at the sub-regional level Building in the South or North differential effects & housing based regional policy Housing supply and the roles of planning/history/geography Aspirations for owner-occupation Housing quality versus numbers of units International migration and the effects on prices, domestic household formation and inter-regional migration Regional variations in response to national policy shocks To put your footer here go to View > Header and Footer 3
. Affordability & Household Projections Official projections are trend based, but: (i) (ii) historically they have over-predicted (see Andrew and Meen 2008), recent LFS data indicate lower headship rates than census projections would suggest, (iii) how much of this is due to worsening affordability? (iv) do trend projections really reflect need? Should we pay so much attention to them? (v) Economic-based projections suggest a rise in the average household size. But is this really an indicator of over-crowding or is it something we accept in a market system? To put your footer here go to View > Header and Footer 4
. Affordability & Household Projections In the southern regions, household size would rise somewhat (2.5 in GL), but hardly a return to the C19th. Do we care about more sharing/staying with parents in London? 2.60 2.50 GL SE 2.40 E 2.30 2.20 SW EM WM 2.10 YH 2.00 1.90 NW NE 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 To put your footer here go to View > Header and Footer 5
Housing Supply and Affordability Perhaps the most controversial (and most important result) is that changes in supply have to be large and long lasting to have a major effect on affordability. Cannot be used for short-run stabilisation. Simulation below shows effect of 50% increase in private construction (all regions for 17 years) 0-2 -4-6 -8-10 -12-14 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 GL SE E SW EM WM YH NW NE To put your footer here go to View > Header and Footer 6
Supply Targets at the Sub-regional Level Not unreasonably, most regions would argue that construction targets at the regional scale are too broad for example any region may include a number of travel-to-work areas. However, the narrower the spatial scale of analysis, the more difficult it becomes for an economic (or any other) model to say anything useful, because an increase in construction generates an almost equal increase in migration flows with no effect on affordability. This is particularly true in the SE (Reading), but less so in the most deprived areas of the NW. Standardising for differences in neighbourhood conditions, price changes across the Thames Gateway and Thames Valley between 2003 and 2006 were driven primarily by region-wide/national factors. There is little individual local authorities can do. To put your footer here go to View > Header and Footer 7
Building in the South and North A housing based regional policy? Building in the South has positive spill-overs to the Midlands/North, but 0-2 -4-6 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 GL SE E SW EM building in the Midlands/North has smaller -8-10 -12 WM YH NW NE effects on the South. 1 0-1 -2-3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 GL SE E SW -4 EM -5 WM -6-7 -8 YH NW NE -9 To put your footer here go to View > Header and Footer 8
Housing Supply & Planning, History, Geography Attempted to test conventional wisdoms: Weak housing price elasticities of supply are due to the planning system. But Could weak supply elasticities be due to other factors? If so, basis of policy is undermined. To put your footer here go to View > Header and Footer 9
Geography & History At the local level, one reason for low supply elasticities could be the historical pattern of land use (property rights built up over centuries) and physical geography (hard to build on water, marshes, mountains). Therefore low supply elasticities in particular areas could simply reflect differences in land-use patterns. If so, unfair to impose common targets on local authorities. To put your footer here go to View > Header and Footer 10
Housing Change To put your footer here go to View > Header and Footer 11
Results Despite common national planning policies, local supply responses to market pressures vary considerably, because of differences in historical land uses. Due to differences in historical land use and geography, the price elasticity in the least constrained area is approximately six times higher than the most constrained. Given the considerable local variations, a question arises whether it is reasonable to expect all local authorities to meet the same targets. But the conventional wisdom still seems to be correct planning policies lower price elasticities. To put your footer here go to View > Header and Footer 12
Flat Plains To put your footer here go to View > Header and Footer 13
Aspirations for Owner-Occupation Sometimes forgotten but not so long ago, government had an aspiration to raise homeownership rates to 75%. In fact the rate has remained around 70% for the past 10 years. To put your footer here go to View > Header and Footer 14
Ownership/Renting Probabilities Table 5. Ownership Probabilities for Previous Renters and Previous Owners (South East, 2003) Female Head, Aged 30-34, Single, No Children Previous Owner Previous Renter Income Quartile 2 0.936 0.023 Income Quartile 4 0.961 0.040 Male Head, Aged 35-39, Partner, With Children Previous Owner Previous Renter Income Quartile 2 0.982 0.078 Income Quartile 4 0.991 0.120 Table 6. Social Renting Probabilities for Previous Social Renters and Non-Previous Social Renters (South East, 2003) Female Head, Aged 30-34, Single, No Children Previous Social Renter Not Previous Social Renter Income Quartile 1 0.899 0.167 Income Quartile 4 0.473 0.010 Male Head, Aged 35-39, Partner, With Children Previous Social Renter Not Previous Social Renter Income Quartile 1 0.980 0.428 Income Quartile 4 0.763 0.064 To put your footer here go to View > Header and Footer 15
Effects of Deposit Requirements on ownership (prior to credit crunch) Table 7 Years in which the Deposit Constraint Ceases to Bind (Male, 30-34, partner and children) Region Quartile 1 Quartile 2 Quartile 3 Quartile 4 London - - 2025 2016 South East - - 2019 2012 East - - 2016 2011 South West - - 2017 2011 East Midlands - 2018 2011 2008 West Midlands - 2021 2011 2009 Yorkshire and - 2014 2009 2007 Humberside North West - 2014 2009 2007 North East 2017 2010 2007 2005 To put your footer here go to View > Header and Footer 16
Housing numbers versus housing quality Traditional approach has been to match numbers of households and numbers of units. But this does not take account of the increase in housing demand from existing households wishing to trade up. This stock effect has a bigger effect on prices than demand from new households (high income elasticity). It follows that concentrating constructing only on starter homes is not appropriate. Improving the quality of the housing stock has bigger price effects. To put your footer here go to View > Header and Footer 17
International migration & effects on prices etc. General view seems to be that international migration raises house prices, although the evidence is rather weak. The model suggests that the impacts are slightly more subtle because of the induced impacts on household formation and migration of domestic residents. 6.00 5.00 4.00 3.00 2.00 1.00 0.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Figure 3a. Effects of 50,000 pa Increase in Migrants House Prices (% differences from a base scenario) GL SE E SW EM WM YH NW NE 50000 45000 GL 4000 40000 SE 2000 GL 35000 30000 25000 20000 15000 10000 5000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 E SW EM WM YH NW NE 0-2000 -4000-6000 -8000-10000 -12000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 SE E SW EM WM YH NW NE Figure 3c. Effects of 50,000 pa Increase in Migrants Household Formation (differences from base scenario) Figure 3b. Effects of 50,000 pa Increase in Migrants Net Regional Flows (differences from base scenario) To put your footer here go to View > Header and Footer 18
Regional variations in response to national policy shocks A change in interest rates has bigger effects in London and the South than in the Midlands and North. This is one of the factors that contributes to the ripple effect. 4.00 2.00 0.00-2.00-4.00-6.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 GL EM NW -8.00-10.00 Figure 6. Mortgage Rate Shock (% changes in house prices from base scenario) To put your footer here go to View > Header and Footer 19