Centre for Market and Public Organisation

1. Centre for Market and Public Organisation Evidence on the impact of pay regulation on hospital quality and productivityor Can pay regulation kill? Emma Hall, Carol Propper John Van Reenen (Preliminary)

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 labor supply and poor hospital performance when outside labor mkts strong • How do labor markets affect firm performance? • Hard to identify as wages reflect equilibrium outcomes of demand and supply shocks. Regulated pay helps identification. • Policy issue in hospital performance • What are causes of large performance variation (note also large productivity dispersion in other industries).

3. Large spread in death rates from AMI between hospitals (Fig 2) Worst 10% Best 10% • Improvements over time (cf. TECH Investigators) • 1996: 10 percentage point (60%) difference between top and bottom (90th =27%,10th =17%)

4. 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) • Main Finding:Hospitals in high outside wage areas have lower hospital quality (higher AMI death rates) and lower output per head. One mechanism: greater reliance on lower quality temporary/agency staff.

5. Geographical variation in Outside wages Highest outside wage Manchester Birmingham Lowest outside wage London

6. Geographical variation in use of agency nurses High intensity of agency nurses Low intensity of agency nurses London

7. Geographical variation in emergency AMI death rates High AMI death rates Low AMI death rates London

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

9. 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

10. 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

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

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

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

14. Implications • In high outside wage areas • Problems of labor 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 • What do we see in data?

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

16. Lower nurse participation rate in stronger labor markets (fig 5) Note: participation rate is the % of women with nursing qualifications who are working as nurses

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

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

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

20. 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, region dummies, etc w = ln(inside wage) η = hospital fixed effect τ = time dummies

21. 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, area, etc w = ln(inside wage) η = hospital fixed effect τ = time dummies

22. Issues • Unobserved heterogeneity: compare OLS, long differences and “System GMM” • Endogeneity: • 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

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

24. 3. Data • New 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

25. Casemix • AMI • Do not have co-morbidity • Demographics of those admitted for AMI (14 gender age-bands) • Control for hospital fixed effects • Mortality rate in area • Drop hospitals with under 150 AMI cases per year • Productivity • 36 age-gender groups • Type of admission • Control for fixed effects • Experiment with conditioning on relative cost index

26. Wage Data • Outside wage • New Earnings Survey (NES) 1% sample of all workers • Use travel to work area (100 in England) • Compare results with 9 main regions • Female non-manual wage • Robustness: all females, all non-manuals, average wage, unemployment rates • Labor Force Survey (like CPS) “corrected” spatial wages taking nurse characteristics into account • Inside Wage • Average wage in hospital (but can just reflect grades) • Predicted wage based on NPRB regulation including regional allowances (Gosling-Van Reenen, 2006)

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

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

29. Table 2: Death Rates from AMI All columns include controls for area mortality rates, year dummies, casemix control, region dummies, hospital size (employment). HCA (Health Care Assistants) is base skill group

30. 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)

31. Table 3: Productivity (FCEs per employee) All columns include controls for area mortality rates, year dummies, casemix control, region dummies, hospital size (employment). HCA is base skill group

32. Magnitudes • From 90th to 10th of area outside wage difference is a fall of 33%, associated with: • a 16% increase in productivity (a quarter of the 90-10 productivity difference) • Increase in physician share from 90th to 10th is 7 percentage points • 35% increase in productivity (58% of the 90-10 diff)

33. A possible mechanism: Agency nurses • High outside wages associated with significantly greater use of agency staff • Greater use of agency staff associated with lower hospital quality • Quantitatively, agency staff appear to account for c.70% of the effect of outside wages on AMI death rates • Agency staff also lowers productivity (maybe 10%+ of outside wage effect)

34. Figure 5: Agency Nurses, outside wages and AMI death rates All columns include all controls in Table 2 (skills, year dummies, casemix control, region dummies, area mortality, etc.). Estimation by GMM-SYS.

35. Figure 5 – cont.: Agency Nurses, outside wages and Productivity All columns include all controls in Table 2 (skills, year dummies, casemix control, region dummies, etc.)

36. Robustness (Table 6) • Internal Market (pre-1997 more flexibility). Row 2 • High outside wages implies higher costs (e.g. rents), financial distress and worse outcomes. Row 3 • Not regulation? Houseman et al (2003) US case studies: (i) buffer, (ii) “hidden” monopsony, (iii) screening. BUT long-run effects in our data (figures and dynamics row 4) • Model implies effects should be stronger in South – drop London (row 5)

37. Table 6: Robustness Checks

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

39. Conclusions • Regulated pay costs lives (and productivity) in high outside wage areas • Higher death rates (and lower productivity) in areas where labor markets are tight • Much of this affect seems to operate through greater reliance on temporary agency staff • Also find that skill mix matters for hospital outcomes • Labor markets important for health on supply side of medical care as well as demand side • Policy solution – allow wages to reflect local labor market conditions?

40. Back Up Slides

41. Next Steps • Policy simulations • What is it about agency staff that is the problem? • Other explanations – e.g. technology adoption (Acemoglu and Finkelstein, 2006)?

42. Table 4: Inside Wage controls All columns include controls for area mortality rates, year dummies, casemix control, region dummies, hospital size (employment). HCA is base skill group

43. Single Regulated Wage in areas of differential outside wage

44. 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

45. 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…..

46. 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)

47. 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

48. Table A: Productivity (FCEs per employee) – Controlling for relative costs index All columns include controls for nurses share, area mortality rates, year dummies (1999-2002), casemix control, region dummies, hospital size

49. Table B: Productivity (FCEs per employee) – Show effect of adding inside wage and skill mix sequentially All columns include controls for nurses share, area mortality rates, year dummies (1999-2002), casemix control, region dummies, hospital size

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