The local labour market effects of decline in public sector employment BIS Analyst Conference 24 November 2011 Frank Bowley Thank you for coming, you’re just in time to settle an argument Back in April, Mike and I started arguing about the likely impact of any public sector cuts across the country Mike thinks that there will be places which will see a significant shock to the economy I, like a proper supply-side economist, feel that where the public sector is a significant employer, it crowds out the private sector So as the public sector contracts, the private sector should grow to pick up the spare workers Since April, this question has had some political traction, so we have been able to spend some time gather evidence as opposed to wide speculation So this presentation is based on work from a number of people: Heather Holt, James Beeson, Sarah Hamilton and Alistair Griffiths

OBR forecast highlights 2 OBR forecast highlights Year Growth (%) Output gap (%) Employment level (m) Unemploy Rate (%) Public Private 2009/10 -4.9 -4.2 7.6 2010/11 1.3 -3.4 5.7 23.2 7.9 2011/12 1.7 -3.9 8.2 2012/13 2.5 -3.6 5.6 23.4 8.1 2013/14 2.9 -3.0 23.7 2014/15 -2.2 5.4 24.1 7.0 2015/16 2.8 -1.4 5.3 24.5 6.4 Source: OBR March 2011 forecast

Bank of England growth forecast Source: Inflation Report – Nov 2011

Policy question Based on OBR forecasts, the national impact of public sector cuts will be muted. But, Are there any places in England were the cuts will be significant? Will the private sector be able to grow quick to absorb redundant public sector workers? What areas are the most vulnerable?

Public sector data Among the areas which show biggest differences: Whitehaven (Sellafield); Cambridge, Canterbury and Lancaster (universities) Previously used ABI data with the sectors Public Administration and Defence; Education and Health Private sector jobs in health and education included (e.g. universities) Public Sector jobs in post and telecommunications excluded

Spatial unit of analysis 6 Spatial unit of analysis What is a local labour market? An area where supply and demand of labour interact But available data areas have problems overlapping areas commuting (supply and demand in different areas) Proportion of population commuting in or out (2008)   Percentile Commuting 10th 25th 50th 75th 90th Local authorities Out 15.8 40.7 61.9 80.4 In 21.3 42.3 64.4 82.8 Travel to work 5 21.7 38.7 56.9 8.6 25.4 42.9 68.8 Region 4.8 5.8 8.8 12.8 18 3.3 6.5 7.7 10.4 10.6

Public sector distribution 7 Public sector distribution Source: BIS calculations from ABI, LFS and DWP data 7

Public sector distribution Spearman rank correlation of public sector dependency metric Jobs Workforce Population ρ = 0.998 ρ = 0.818 ρ = 0.827 Source: BIS calculations on ABI and LFS data

Public Sector Proportions by English TtWA, 2008

Public sector size & private sector growth 10 Public sector size & private sector growth Source: BIS calculations of ABI data

Public sector crowding out ? One key issue is whether changes in public sector employment affect the private sector, as: supply-side – extra supply from public sector may allow a constrained private sector to grow. demand-side – less public sector employment reduces aggregate demand, reducing private sector employment.

Public sector pay premium – high skill

Public sector pay premium – medium skill

Public sector pay premium – low skill

Searching for crowding out - strategy At the most basic, change in one sector may cause a change in the other: negative correlation denotes supply-side effects positive correlation denotes demand-side effects But public sector may not be randomly distributed Government may put public sector in poor areas; Public sector growth may be counter-cyclical. Other sources of labour supply (e.g. unemployment) other than public sector

Searching for crowding out - model Influence of surplus labour? Fixed effects pi,t private sector employees in area i at time t si,t public sector employees in area i at time t Ui,t (workbased) unemployment rate in area i at time t i area fixed effect of area i t time fixed effect for time t Re-run with independent variable j private sector including self-employed Unemployment rate lagged to avoid any identity relationship Lags of all variables included to model delayed effects

Searching for crowding out - data Private and public sector employees from ABI Self-employed and unemployed from LFS microdata Change in Private Public Private (inc. self-emp) Unemp rate Minimum -22,800 -11,400 -36,800 0.0% Percentile 10th -3,300 -2,800 -4,600 3.0% 25th -1,100 -700 -1,800 3.7% 50th 800 300 900 4.7% 75th 3,800 1,500 5,300 6.2% 90th 7,700 2,800 9,600 7.7% Maximum 40,600 15,700 59,900 13.1%

Searching for crowding out - results Dependent variable Employee jobs (pi,t) Total jobs including self-employment (ji,t) NUTS 3 I II III IV V VI pi,t-1 -0.340** -0.325** ji,t-1 -0.352** -0.338** si,t 0.335** 0.055 -1.000** 0.455* -0.012 -1.036* si,t-1 -0.162 -1.290** -0.152 -2.231** si,t.Ui,t-1 24.87** 24.72* si,t-1.Ui,t-2 25.76** 47.49** Observations 635 508 464 591 Adj. R2 11.0% 34.7% 37.0% 7.1%% 32.1% 35.5% Note: area and time fixed effects, and U coefficients not shown * denotes probability of coefficient equal to zero is < 5%, ** denotes probability < 1%

Unemployment and crowding out 19 Unemployment and crowding out

Conclusions National impacts maybe muted, but: Number of areas with high public sector dependency and low private sector growth Crowding out is not an issue: crowding out can occur in tight labour market at typical unemployment rates, no crowding out High public sector / high unemployment / low private sector growth vulnerable These areas predominantly in North, South West and coastal areas. Regional Growth Fund focused on these places

Vulnerability Index 1 (average rank of all three variables) Areas ranked according to all variables, average rank calculated. Bottom quartile taken as most vulnerable. Problems: automatically, a quartile is most vulnerable; does not weight towards public sector

Vulnerability Index 2 (must be greater than English average public sector proportion to be vulnerable) Restriction- must be greater than the English average (20.2%) of public sector proportions and one other variable Bishop Aukland and Barrand Castle: public sector proportion= 19.1% Problems- areas just below English average and poorly performing on other two variables