ENHR Housing Economics Workshop

1. ENHR Housing Economics Workshop Housing Mobility and Tenure Choice with varying constraints and rationing: a model for English regions built from micro household transition dataProf Glen Bramley(Heriot-Watt University, Edinburgh, UKContact: g.bramley@hw.ac.uk; +44 (0)131 451 4605)with Prof Michael White (Nottingham Trent University)July 2011

2. Overview of Paper • Paper is about housing tenure choice and outcomes in England • Reviews literature • Describes general approach and data sources- micro estimation on BHPS transitions over 7 pairs of waves- macro regional simulation model built on S.E.H., LFS, etc. • Findings on drivers of mobility, moves to buy and social rent • Simulation model features • Baseline and alternative scenarios • Conclusions

3. Previous Literature • Fundamentals of ‘choice’ to buy or rent • Embedded within wider housing demand – also hhld formation, quantity/quality of housing services • Affordability & income; permanent income; relative ‘user costs’ • Transaction costs & mobility (length of stay) • Econometric issues around identification • Credit constraints – savings & wealth/age of purchase/ • Demographics – age, family type, ethnicity • Tax & inflation effects • Subsidies e.g. Housing Allowances/Benefits • Location – region, market area, labour market conditions - migration interactions

4. Our Approach • While taking much from previous literature, we see some limitations, esp in British context • Better to focus on flows – active decision making households - path dependence • Hierarchical sequential approach (Form/move – Buy – Soc Rent) • Mobility models generate flows & also affect ‘expected length of stay’ • Household formation modelled on similar drivers • Social rented lettings clearly rationed • Market rents, prices, unemployment etc linked at subregional HMA levelplus, in simulation stage, • Recognition of physical limits to stock-> feedback Vacs->HHFm, PRS • Recognition of (re-emergence of ) credit rationing post 2007

5. Hierarchical Choice Model

6. Mobility Rates

7. Household Formation • Reviewed theory and past research, and highlighted trends from data since early 1990s • Base period ‘profile’ of new households from S.E.H. & BHPS • Modelled propensity to form new household using BHPS linked to local/subregional market variables • Key demographic drivers include age (younger), migrancy, marriage, childbirth • Key economic factors include prices (-0.27) incomes (0.31), unemp (-0.24) • Social lettings supply (0.26) • Smaller effects from prev tenure, ethnicity, qualifs, hsg type • Model is consistent with previous research including Reading model but adds some extra elements

8. Mobility Models • Logistic regression to predict 1-year moves by origin tenure • Young are more mobile, esp in rental tenures • Larger households less mobile, tho children & crowding may trigger moves • Higher (current & perm) income increases mobility in private market; wealth mixed • Unemployment mixed but mainly positive • Rates in private renting 4-5x other tenures

11. Mobility and Tenure Choice • Logistic regression fitted to pooled BHPS data on 1-year transitions • Movers Buying related to mobility (-, via user cost), age (young -), hhd size (-), children (+), working (+), students (-), unemployment (-), income (+), wealth (+), house prices & int rates (-, via user cost), private rents (+ for PR), soc rents (mixed) • Movers Social renting related to similar factors, but usually with reverse sign (except students; user cost omitted);migrants (-), young (-), sick/disabled (+); low income (+); crowding (+); supply of social lettings signif (+); priv rents (+ for PR); soc rents (?)

12. Forward Forecast • Model now simulates system forward year-by-year from 2009 to 2021 • Takes inputs from parallel run of Reading Affordability model • Model is recursive – endogenous variables calculated sequentially with some use of lagged values • Forecasts of household formation and tenure flows and stocks by household age-type and region • Stock-household reconciliation, affecting vacancies, new household formation and concealed/sharing households • Model to predict private rents – simple reduced form regression • Social lettings rationing constraint, now formularised • 9 categories of specific need incl homelessness forecast each period, based on models for each need

14. Stock-Household Reconciliation • Ex poste, system must satisfy identity relationship:Households=Stock-Vacancies-2nd homes+Sharing Households-Shared Dwellings • ‘Natural’ vacancy rate (3.5%) in private sector; if a region goes below this, adjustments are made to new household formation by (younger) singles in PRS (equiv to half the difference) • With corresponding increase in multi-adult households, and also in concealed households and sharing (specific needs) • Argue that concealed effects bigger than sharing under current conditions

15. Private Rents Equation In simulation model, vacancy relationship imposed, raising rents where vacancies below natural rate

16. Baseline Scenario • Modified version of Reading model baseline • Income growth curtailed in this period, leading to incomes nearly 10% lower than trend by 2014 • New private build reduced sharply in 2008-2010, (95,000 comps in 2010) recovering to 150,000 by 2012 & 185,000 by 2015 • New social output static at 17,000 pa. • Altho prices and HPIR fall sharply in 2008-9, we apply a ‘shadow price of credit rationing’ in model to represent ‘effective affordability’ (1.9 in 2009, tapering off to 1.10 by 2015). • Populations are as per Sept 2009 Reading model, but household growth is endogenous

17. Baseline Forecast

18. Components of Change in Owner Occupation and User Cost

19. Comments on Baseline • 2004-09 unusual for seeing decline in OO and large rise in PRS • This will reverse, particularly up to 2016, but later growth of OO slows again as user cost rises • Net growth quite sensitive to moderate changes in gross flows • Some regional differences e.g. more persistent shift from OO to PR in poorer regions

20. Differing Supply Policy Scenarios

21. Differing Financial Contextual Scenarios

22. Backlog Need

23. Scenario Impacts • Overall new build supply makes relatively little difference to tenure outcomes; somewhat counter-intuitive • Priv renting mainly mirror image • Main reason is effective quantity rationing in private sector, suppressing marginal household growth at expense of private rental sector • Providing more subsidised housing does impact on tenure, e.g. more LCHO->more OO, but quite small impact even in medium term; more social renting would displace private renting. • Contextual financial conditions, esp credit rationing, would have bigger effect – persistent CR would see OO stalled or falling • Inequality – not big effect at level modelled • Rents – effects shown may be too strong (?)

24. Concluding comments • Findings of both stages of modelling support need take account of institutional & quantity rationing effects • Nature and extent of recent changes go beyond conditions observed in base period (2003-07); hence estimated functions not sufficient to deal realistically with some of strains on system; need for additional feedback mechanisms in simulation • General need to measure & model credit rationing & operation of private rented sector more effectively • General supply policies have less impact on tenure than expected, although they do help to reduce need (gradually) • Credit rationing has bigger effects on both tenure and need • Maybe governments should be more concerned with need outcomes than with tenure per se