Presentation on theme: "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,"— Presentation transcript:
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 Propper John 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.
6 1.Models: What is the effect of pay regulation? 2.Empirical models 3.Data 4.Results 5.Conclusions OUTLINE
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 S PHYS = share of clinical workforce who are physicians S NURSES = share of clinical workforce who are nurses (and AHPs) (base group is health care assistants) w O = 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) S PHYS = share of clinical workforce who are physicians S NURSES = share of clinical workforce who are nurses (and AHPs) (base group is health care assistants) w O = 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) S QUAL = share of workforce who are qualified (nursing homes: with nursing quals; ln (cap/labor) ratio other industries) w O = 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 1.Models: What is the effect of pay regulation? 2.Empirical models 3.Data 4.Results 5.Conclusions OUTLINE
19 Magnitudes (col 3) From 90 th to 10 th 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 10 th to 90 th 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
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?
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 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) Equation of interest for s > 1 when u it ~ MA(0), and for s > 2 when u it ~ 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): 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) for s = 1 when u it ~ MA(0), and for s = 2 when u it ~ MA(1)
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
36 Large spread in death rates from AMI between hospitals Improvements over time (cf. TECH Investigators) 1996: 10 percentage point (60%) difference between top and bottom (90 th =27%,10 th =17%) Worst 10% Best 10%
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 N, employmentN SOUTH N NORTH Labour Supply, South Labour Supply, North Labor Demand Regulated Wage
39 Wages N, employmentN SOUTH Labour Supply, South Labor Demand Regulated Wage
40 Wages N, employmentN PERMANENT Labour Supply, South Labor Demand Regulated Wage Agency Wage N TOTAL Agency staff
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 rates 1 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
51 Magnitudes From 90 th to 10 th 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 90 th to 10 th is 7 percentage points –35% increase in productivity (58% of the 90- 10 diff)
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