ESRC Seminar on Neighbourhood Effects: Discussion of Day 2

1. ESRC Seminar on Neighbourhood Effects: Discussion of Day 2 Geoff Meen

2. A Reminder of 19th Century Urban Housing Conditions (Gustave Dore)

3. Points • I believe that neighbourhood effects in the C19th were important – average age of death about 30 in worst areas and there was a case for place-based policies. • But it would still be difficult to demonstrate that the worst areas were not self-selecting. They “choose” the worst areas because they were poor (but didn’t have much choice because they had to be close to work). Government policy was hardly to improve labour market skills (not a feature of the Poor Law Amendment Act). Victorian view that they were impoverished because of their own failures. Raises a number of points: • Social reformers tried place-based reforms, but largely failed. • Threshold effect: Because of high absolute poverty levels, place more likely to be important then than now. • But do results transfer across time and place? Implications for current research.

4. Lessons from the papersand points for discussion • Issues from economic theory • Empirical/technical issues in econometric studies (including data) – many of these raised yesterday. • Policy questions.

5. Economic Theory (1) • As Cheshire’s paper points out, different strands of literature all suggest that segregation is the most likely outcome and spatial structures appear to be resilient over centuries (despite policy). These strands include: • Standard residential location theory, extensions by Brueckner et al (multiple equilibria, but still segregated), Schelling and later social interactions models, self organisation models of complex systems, long-term work on random walks by Davis and Weinstein (and others). • Segregation appears to be a stochastically stable state (checkerboard patterns easily breakdown – e.g. Krugman). • Therefore policy is fighting against deep-seated forces. Even if mixing is desirable, it may not be achievable.

6. Economic Theory (2) • However, just because segregation is generated by market processes, the outcomes may or may not be optimal because of implied externalities. • The poor may “ choose” to live in the worst areas or be outbid for the best areas by the rich (if the supply of some characteristics is inelastic, as the hedonic research suggests), but Schelling type models indicate that the degree of segregation may be sub-optimal. Even if households want a small percentage of households to be the same type as themselves, this leads to a very high degree of segregation. • Message might be that we have to be careful of claims that segregated residential patterns is what households want (even for the rich).

7. Empirical Issues (1) • Data and estimation methods – (until we heard from George) most would appear to agree that experimental data is best, but most countries do not have that luxury. • Second (or first) best choices: • Longitudinal data sets – (e.g. Van Ham & Manley – Scottish data 1991 and 2001 from sub-set of censuses looking at probability of changed labour market status, conditional on individual characteristics and tenure). • Role of fixed effects estimators to control for unobserved individual characteristics • Role of IV estimation • Identification through non-linearities.

8. Empirical Issues (2) • Spatial scale of analysis for the neighbourhood: • Van Ham and Manley use Output Areas and CATTs. • Bernelius uses school catchment areas. • Tampubolon uses LSOAs. • Is there an optimum choice or are we always bound by administrative geographies? • Does the choice of inappropriate geographies bias findings away from the significance of neighbourhood effects?

9. Empirical Issues (3) • Causality. Perhaps the key issue. Cheshire view that deprived neighbourhoods are simply those where the poor choose to live, rather than the other way round. Therefore, policy should be based on improving inequality (see latest John Hills report), rather than places. • Can longitudinal studies help overcome the problem. Van Ham and Manley do not support the neighbourhoods view strongly. But is tenure capturing other effects e.g. area stability – owners stay in one place longer?

10. Empirical Issues (4) • Omitted variable problems: • Van Ham and Manley show what happens to the neighbourhood (tenure) effects when individual characteristics are added  implies neighbourhood effects are biased unless all relevant individual characteristics can be included . But that is generally not possible. • In Bernelius study, could omitted individual characteristics account for some of the more unexpected findings (P24: in privileged schools, the range of performances are relatively narrow, despite differences in background. Those from poor backgrounds perform well).

11. Empirical Issues (5) • Question: • In countries where there are no experimental data (MTO equivalents) and longitudinal data at fine spatial scales are not available, can any useful research be conducted? Yesterday suggests that the data position is not quite as bleak as I thought (Sweden, Netherlands). But still the case that the data sets were designed primarily for different purposes. • One possible approach might be to bring together a variety of different pieces of evidence, none of which is entirely convincing individually. • For example: (i) evidence of non-linearities at fine spatial scales in conventional models: (ii) micro simulation models with social interactions terms (estimated [Tampubolon] or imposed). Can these match observed spatial patterns? (iii) studies of long-run change and persistence e.g. since C19th and Industrial Revolution. Have spatial structures changed? What are the effects of slum clearance programmes? Do areas change gradually or in discrete jumps?

12. Policy Issues (1) • Are research results transferable internationally? E.g. for Finland, the degree of inequality is less than in US, UK, therefore, less likely to find threshold effects. Similarly Swedish, Netherlands. What about developing economies? • Are results transferable over time? A priori neighbourhood effects more likely to occur in C19th. • Is there empirical evidence that agglomeration economies are important for the disadvantaged i.e. gains from segregation? Or is this just speculation?

13. Policy Issues (2) • Even if mixed neighbourhoods are desirable, are they achievable? If not no point wasting public money. • Type 1 and Type 2 errors: if the government has a null that mixed communities improve performance and T1 (reject the null when true) errors are considered particularly important, what are the appropriate significance levels for our tests? Therefore, have to be careful about concluding neighbourhood effects are unimportant, based on conventional significance levels. But these have to be measured against the costs of the policies (local community initiatives are not necessarily very expensive).

14. Policy Issues (3) • The alternative to place-based initiatives are individual-based policies e.g. skills/education improvements. But the evidence appears to suggest that these factors can only explain a part of the income distribution. Do we want to put all our policy eggs in one basket?