The danger of high home ownership: Greater unemployment Andrew Oswald (Warwick and CAGE)

1. The danger of high home ownership: Greater unemployment Andrew Oswald (Warwick and CAGE) Joint work with Danny Blanchflower

2. The background since WW2

3. OECD unemployment was 3% and is now 10%+

4. OECD unemployment was 3% and is now 10%+ Standard explanations: • trade unions became too powerful • unemployment benefits too generous • labour markets too inflexible.

5. We want to consider something different

6. We want to consider something different – that economists and policy-makers need to focus on the way the housing market works.

7. Often-forgotten facts

8. Often-forgotten facts • In 1950, most British citizens were private renters.

9. Often-forgotten facts • In 1950, most British citizens were private renters. • Today, nearly 70% of Swiss people are private renters.

10. Friedman (1968)

11. Friedman (1968) • “The ‘natural rate of unemployment’ ... is the level that would be ground out by the Walrasian ... equations, provided there is embedded in them the actual ... characteristics of the labour and commodity markets, ... market imperfections, the costs of gathering information, the costs of mobility, and so on.”

12. Let’s start

13. Let’s start ... with some simple correlations

15. Euro area alone

16. Over half a century in the US

17. Long time-differences in US state data

18. Long time-differences for Swiss cantons

19. Is there any quasi-experimental evidence?

20. Is there any quasi-experimental evidence? • Yes. Recently released in Finland. “Home-ownership and the Labour Market: Evidence from Rental Housing Market Deregulation” Jani-Petri Laamanen

21. In our own work

22. In our own work • Movements in the unemployment rate in state j are explained in large part by movements in the home-ownership rate in state j some years earlier. • The ‘elasticity’ is huge. It exceeds 1.

23. Is this pattern robust across different time periods and different parts of the USA?

24. Is this pattern robust across different time periods and different parts of the USA? Yes, if we split the data at year 2001.

25. Is this pattern robust across different time periods and different parts of the USA? Yes, if we split the data at year 2001. Yes, if we split the data into different areas of the USA.

26. What might be going on?

27. Home ownership leads to: • Lower geographical mobility • Longer commuting times • Fewer new businesses

28. Why? It is not that being a home owner is ‘making’ me unemployed.

29. Why?

30. Why? It is hard to see how this could be in some sense Keynesian or all about ‘aggregate demand’.

31. Idea 1 • High home-ownership encourages greater commuting, and that increases congestion costs for other workers and their employers.

32. Idea 2 • High home-ownership reduces mobility, and that has deleterious knowledge-flow ‘externalities’ on everyone’s productivity.

33. Idea 3 • High home-ownership tends to block new business development (zoning and NIMBY pressures).

34. The main finding There is a profound link between high home ownership and later high unemployment.