Centre for Market and Public Organisation

1. Centre for Market and Public Organisation Can pay regulation kill? Panel data evidence on the effect of labor markets on hospital performance Emma Hall, Carol PropperJohn Van Reenen Feb 2008

2. Motivation • Unintended consequences of wage regulation • Pay setting (e.g. public sector) often has “geographical equity” despite different local labor markets. Implies problems of labour supply - and poor performance - when outside labour mkts strong • How do labour markets affect firm performance? • Hard to identify as wages reflect equilibrium outcomes of demand and supply shocks. • In our design, pay regulation help identification • Policy issue in hospital performance • What are causes of large performance variation (note also large productivity dispersion in other industries)

3. Our Design • Wages for nurses (and doctors) in UK National Health Service centrally set by National Pay Review Body. NPRB “Mandates” wage rates for doctors and nurses by grade. Uprated each year. • Very little local variation in regulated pay despite substantial local variation in total private sector • E.g. 65% private sector pay gap between North-East England and Inner London but only 11% in NPRB regulated pay • Use exogenous variation in “outside wage” and examine impact on hospital outcomes (quality, prody) • Institutional setting one in which selection of patients to hospitals is limited

4. Our Results • Main Finding:Hospitals in high outside wage areas have lower hospital quality (higher AMI death rates) and lower output per head. • Not result of general UK labour market conditions • Placebo experiments on similar sectors: no evidence of negative effect of outside wages on productivity • One mechanism: greater reliance on lower quality temporary/agency staff.

5. Geographical variation in: In-hosp AMI deaths Outside wages Agency nurses

6. OUTLINE • Models: What is the effect of pay regulation? • Empirical models • Data • Results • Conclusions

7. 1. Effects of high outside wage relative to regulated wage • Employers • try to circumvent by “over-promoting” (grade drift) and increasing non-wage benefits. Limited by regulation/union enforcement • Substitution to other factors: health care assistants, maybe capital. But limited due to nature of needed expertise. • Substitute temporary agency staff. Lower job-specific human capital so less productive/lower quality (cf Autor & Houseman, 2006) • Employees • Lower participation, higher vacancies for permanent staff • More likely to become agency staff. • Permanent staff also less motivated, lower relative quality compared to low outside wage areas Implication: Worse hospital performance in high outside wage areas

8. Implications • In high outside wage areas • Problems of labour supply for permanent staff • higher vacancies • lower participation in nursing • Greater reliance on agency nurses • Worse health outcomes • Lower quality (AMI death rate) • Lower productivity • See this in raw data at regional level

9. 2. Empirical Models 1. Hospital quality equation For hospital i in year t: d = 30 day death rate from emergency AMI admission for 55+ year olds SPHYS = share of clinical workforce who are physicians SNURSES= share of clinical workforce who are nurses (and AHPs) (base group is health care assistants) wO = ln(outside wage) Z = controls for casemix, area mortality rates, hospital size, teaching status w = ln(inside wage) η = hospital dummies τ = time dummies, r=regional dummies

10. 2. Hospital productivity equation Ln(Y/L) = ln(Finished Consultant Episodes per clinical worker) SPHYS = share of clinical workforce who are physicians SNURSES= share of clinical workforce who are nurses (and AHPs) (base group is health care assistants) wO = ln(outside wage) Z = controls for casemix, area mortality rates, hospital size, teaching status w = ln(inside wage) r = regional dummies τ = time dummies η = hospital dummies

11. 3. Placebo productivity equation Ln(R/L) = ln(revenues/worker) SQUAL = share of workforce who are qualified(nursing homes: with nursing quals; ln (cap/labor) ratio other industries) wO = ln(outside wage) Z = total staffing (+ gender mix, age of staff for nursing homes) w = ln(inside wage) r = regional effects τ = time dummies η = firm fixed effect Run for 42 industries + nursing homes

12. Issues • Unobserved heterogeneity: OLS, long differences and “System GMM” • Endogeneity of wages and shares: • Outside wage: hospitals are a small % of local labor market • Skill shares: GMM-SYS (Blundell-Bond,2000; Bond and Soderbom, 2006) • Standard errors allow for heteroscedacity, autocorrelation and clustering by region

13. Issues • Endogeneity of patient quality • Selection of hospitals • Association of illhealth and economic activity • Hospital selection limited by inst. structure • AMI patients sent to nearest hosp. • Hospitals not monitored on quality; in theory financial incentives exist but no systems to implement • Upswings less associated with increase in hrs (due to higher labor protection); also undertake extensive checks to ensure no rel. between community health and ‘good times’

14. 3. Data • Hospital level panel data • 3 groups of clinical workers: Physicians, nurses (AHPs) and Health Care Assistants. Total employment. From Medical Workforce Statistics • Agency staff – hospital financial returns • Hospital quality: 30 day in-hospital death rates for Emergency admissions for Acute Myocardial Infarction (AMI) for over 55 year olds. From HES (Hospital Episode Statistics). • Productivity: Finished Consultant Episodes (HES) per worker

15. Wage Data • Outside wage • New Earnings Survey (NES) 1% sample of all workers • Use travel to work area (78 in England) • Compare results with 9 main regions • Female non-manual wage • Inside Wage • Average wage in hospital (but can just reflect grades) • Predicted wage based on NPRB regulation including regional allowances (Gosling-Van Reenen, 2006)

16. Final Dataset • 211 hospitals between 1996-2001 • 907 observations

17. OUTLINE • Models: What is the effect of pay regulation? • Empirical models • Data • Results • Conclusions

18. Table 2: Death Rates from AMI

19. Magnitudes (col 3) • From 90th to 10th percentile of area outside wage difference is a fall of 33%. Associated with • a 14% fall in death rates (a quarter of the 62% 90-10 spread) • Increase in physician share from 10th to 90th percentile is 7 percentage points. Associated with • 37% fall in AMI death rates (60% of 90-10 diff) • Effect on AMI death rates of outside wage not dissimilar magnitude to drug based medical interventions (aspirin, beta blockers) • 10% increase in outside wages leads to 1 pp increase in AMI fatality • Heidenrich and McClellan (2001) increase use of aspirins by 70% resulted in 3.3 p.p fall in AMI mortality

20. Table 3: Productivity (FCEs per employee)

21. Placebo tests • Nursing homes • Provide medical care and other care services to elderly • Wages not regulated • 649 randomly selected homes: data for 1998 and 1999 • No evidence from OLS regression that outside pay associated with lower output (beds) per hour of staff time

22. Other placebo tests • 42 service industries • Dependent variable ln(revenues/worker) • Only in 7/126 regression was outside wage neg. and significant • Inside wage significant in almost all • Suggests our finding of neg. effect of outside wages is a result of regulated pay maxima

23. A possible mechanism: Agency nurses • Higher outside wages associated with significantly greater use of agency staff • Doubling of agency staff increases AMI death rates by 5%; no remaining effect of outside wages • Agency nurses disproportionately in A and E wards • Less effect on outside wages in productivity equation, but agency use still significant • Use of agency staff related to MRSA rates (for 2001-2002)

24. Robustness checks Upswings lead to poorer health in local labour market (e.g. Ruhm) • Case-mix and local wages • AMI severity (HRG category) not related to outside wages • controls for HRG not significant for AMI deaths; total case-mix not significant for prody • Are outside wages associated with higher community death rates? • Our model implies weakly so • Ruhm type argument – strong positive relationship • We find weak n.s. positive relationship • Also find no relationship between two key drivers of poor health-upswing relationship (pollution, smoking)

25. Robustness checks Outside labor market affecting ambulance care • More economic activity – slower road speeds (‘floor to door’) • Control for ambulance speeds • Poorer quality of ambulance crew (door to needle time’) • Ambulance crew have no autonomy over which hospital to go to; administration of reperfusion (to stop clotting) by crews under 0.6%. Other tests • Financial pressure • Dynamics • Regional heterogeneity in impact outside wage

26. Conclusions • Regulated pay costs lives (and productivity) in high outside wage areas • Higher death rates (and lower productivity) in areas where labour markets are tight • Some of this affect seems to operate through greater reliance on temporary agency staff • Not a feature of other UK service industries where (maximum) pay regulation does not operate • Labour markets important for health on supply side of medical care as well as demand side • Policy solution – allow wages to reflect local labour market conditions?

27. Back Up Slides

28. Next Steps • Other explanations – e.g. technology adoption (Acemoglu and Finkelstein, 2006)?

29. Underlying structural model • Hospitals choose mix of factors depending on environment and adjustment costs • Factor with high adjustment costs changed more slowly • Implies that lagged values predict future values • Empirical identification requires that adjustment costs be sufficiently different across the factors to avoid weak instruments problems

30. System GMM Equation of interest 1) Difference equation eliminates firm fixed effects Moment conditions allow use of suitably lagged levels of the variables as instruments for the first differences (assuming levels error term serially uncorrelated, see Arellano and Bond, 1991) for s > 1 when uit~ MA(0), and for s > 2 when uit ~ MA(1), etc. Test assumptions using autocorrelation test and Sargan Problem of weak instruments with persistence series…..

31. System GMM 2) Use lagged differences as instruments in the levels equation additional moment conditions (Arellano and Bover, 1998; Blundell and Bond, 2000): for s = 1 when uit ~ MA(0), and for s = 2 when uit ~ MA(1) Requires first moments of x to be time-invariant, conditional on common year dummies Can test the validity of the additional moment conditions We combine both sets of moments for difference and levels equations to construct “System GMM” estimator We assume all firm level variables are endogenous, while industry level variables are exogenous in main specifications (relax in some specifications)

32. Alternative to regulation • Avoiding permanent pay increases (Houseman et al, 2003) • Pay more observable than in US • Differences in pay and quality across regions are persistent

33. Big spread in productivity between hospitals (Fig 3) Note: productivity measured by finished consultant episodes per worker

34. Sample characteristics

35. Sample characteristics cont

36. Large spread in death rates from AMI between hospitals Worst 10% Best 10% • Improvements over time (cf. TECH Investigators) • 1996: 10 percentage point (60%) difference between top and bottom (90th =27%,10th =17%)

37. Simple model • 2 areas: high outside wage “South” and low outside wage “North” • Regulated wage the same in both areas • Regulated wage lower than equilibrium wage

38. Wages Labour Supply, South Labour Supply, North Labor Demand Regulated Wage NSOUTH N, employment NNORTH

39. Wages Labour Supply, South Labor Demand Regulated Wage NSOUTH N, employment

40. Wages Labour Supply, South Labor Demand Agency Wage Regulated Wage Agency staff NPERMANENT N, employment NTOTAL

41. Table 4: Controls for inside wages

42. Table 6: Placebo experiments: nursing homes

43. A possible mechanism: Agency nurses

44. Figure 5: Agency Nurses, outside wages and AMI death rates All regressions include hosp fixed effects, region dummies, year effects.

45. Robustness checks: coefficient on outside wage

46. Cost effectiveness • Effect on AMI death rates of outside wage not dissimilar magnitude to drug based medical interventions (aspirin, beta blockers) • 10% increase in outside wages leads to 1 pp increase in AMI fatality; Heidenrich and McClellan (2001) increase use of aspirins by 70% resulted in 3.3 p.p fall in AMI mortality • Cost of a life year saved by an 1% increase in (inside) nurse wages to all staff and an 1 p.p. increase in physician and nurses skill shares • Increasing inside wages: $100,000 • physician share: $60,000 • nurse share: $36,000 • Value of QALY c $60,000 • Comparison with greater use of drug based medical technology, increasing wages for nurses and skill shares in hospitals expensive, but cheaper than the current cost of AMI treatment in the US (Skinner et al 2006)

47. Higher nurse vacancy rates1 in stronger labor markets (fig 4) 1 Percentage of nurse posts that have been vacant for 3 months or more

48. Higher use of agency nurses in stronger labor markets (Fig 6)

49. Higher death rate from AMI admissions in stronger labor markets (fig 7)

50. Changes in AMI death rates and changes in outside wages