naureen karachiwalla university of oxford albert park hkust n.
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Naureen Karachiwalla , University of Oxford Albert Park, HKUST. Promotion Incentives in the Public Sector: Evidence from Chinese Schools. Motivations. Teachers are central to the learning process Often undermotivated in developing countries Exclusive focus on incentive pay (bonuses)

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Presentation Transcript
motivations
Motivations
  • Teachers are central to the learning process
    • Often undermotivated in developing countries
    • Exclusive focus on incentive pay (bonuses)
    • China ideal case to study use of promotions to provide incentives—sophisticated system, good performance
  • Incentives for civil servants, puzzle of governance and rapid growth in China?
  • Empirical evidence on promotion incentives
    • Previous evidence mostly on use of incentives (by studying wage patterns) in US companies
    • Little direct evidence on effort/performance (Gibbs, 1995; Campbell 2008, Kwon 2006)
outline
Outline
  • Motivations
  • Promotion of teachers in China
  • Data
  • Model of Promotions as Incentives
  • Empirical model
  • Results
  • Conclusion
promotion of teachers in china
Promotion of Teachers in China
  • Four ranks in both primary and middle school
  • To apply for a promotion, need:
    • To wait a certain number of years (depending on education)
    • Favourable annual evaluation scores (one ‘excellent’ or two ‘good’) in the last 5 years
  • Promotion depends on the number of spaces available in a township
  • Wages are higher at higher rank levels
teacher evaluations
Teacher evaluations
  • Annual evaluations on a four point scale: excellent, good, pass, fail. Set proportions.
  • Based on four criteria: student test scores, attendance, preparation and ‘attitude’. Committee chooses weights.
  • Classroom observation, questionnaires to teachers and students, principal reports. Points for each component.
  • Points added, teachers are ranked. Top 10% get ‘excellent’, next 10% get ‘good’ scores. Rest get a ‘pass’.
  • Results of ‘excellent’ and ‘good’ evaluation scores announced at annual meetings
slide10
Data
  • Gansu Survey of Children and Families (GSCF), focussed on rural schools
  • 3 waves, we use 2007. Child, teacher, principal etc.
  • Sampled 100 villages in 42 townships in 20 counties
  • Sampled the main primary and middle school in each village
  • Sample of 2,350 teachers
literature theory
Literature – Theory
  • Promotions as tournaments, Lazear and Rosen (1981). Wage gap that can induce first best effort exists.
  • Macleod and Malcolmson (1988) model of skill and effort as private information. Employees sort into ranks according to ability.
  • Fairburn and Malcolmson (1994) sorting into different jobs. Promotions can be made incentive compatible.
  • Gibbs (1989) multi-person tournaments with heterogeneous competitors. Predictions on ability, number of competitors, time after promotion, beliefs on ability etc.
model of promotions as incentives
Model of Promotions as Incentives
  • School offers promotions, teachers hired in lowest rank, n teachers compete for k promotion slots at each rank level
  • School offers ΔEU  (W2 - W1)*tenure after promotion
  • Teachers have different skill, s with B(s) and b(s), E(s)=0
  • Cost of effort (e) is C(e) where C’ , C’’ >0
  • p(e, s, e) is probability of promotion
model of promotions as incentives1
Model of Promotions as Incentives
  • Teacher solves:
  • First order condition:
  • dp/de is marginal probability of promotion (MPE)
model of promotions as incentives2
Model of Promotions as Incentives
  • qi = si + ei + πi where πi = εi + μ, CDF R(q) PDF r(q)
  • E(πi)=E(εi)=E(μ)=0, CDF F(ε), PDF f(ε)
  • Probability teacher i beats teacher g:

pr(qi > qg) = pr(ei + si + εi + μ > eg + sg + εg + μ) = pr(eg + sg + εg + < ei + si + εi) = R(ei + si + εi)

  • Probability of promotion:
predictions
Predictions
  • Incentives higher with higher wage increases when promoted
  • Incentives decline with age
  • Incentive highest when skill percentile = 1 – p*, and declines with distance from 1-p*
  • When n increases but p* stays the same, incentives increase for those close with skill percentile close to 1 - p* (and decrease for those with very high or very low skill)
multiperiod model
Multiperiod Model
  • Teachers have careers of T periods, eligible for promotion in year t = X
  • Probability of promotion, pt is based on performance in past 5 years
  • Normalize per period utility before promotion to zero, define Uh > 0 utility from wages after promotion
  • In year j, lifetime expected discounted utility is:
  • Prior belief on skill, s1, 1/N ≤ s1 ≤ 1. True relative rank s.
  • Teachers update beliefs on skill rank st, adjust stdownward when passed over for promotion
more predictions
More Predictions
  • Predictions on teacher performance over time
    • If t ≤ X – 5 effort is zero
    • Effort is increasing from t=X – 4 to X
    • Teachers update beliefs on s based on whether or not they are promoted. When teachers are not promoted, s is revised downwards, effort is decreasing for every year of non-promotion
empirical specification
Empirical Specification
  • From the one-period model’s FOC:
  • Estimate as:
  • We will estimate with fixed effects so w and p will drop out. We will also add in the time dimension.
empirical specification1
Empirical specification
  • ev = evaluation scores for t = 2003, 2004, 2005, 2006
  • a = ability index, dummies for top and bottom 10%
  • n = number of teachers, also interacted with ability in top and bottom 10%
  • w = fixed effect
  • D – dummies for:
    • t = X – 5 or greater
    • t = X – 4, t = X – 3, t = X – 2, t = X – 1 , t=X
    • t > after half the other teachers are promoted (dummies from one to ten years after half of colleagues are promoted)
empirical results
Empirical results
  • Evaluation scores increase with higher expected wage increases
  • Evaluation scores increase in the years preceding promotion eligibility and decrease after not being promoted (inverted U) or reaching the highest rank
  • Evaluation scores increase with competition (number of teachers) for those in the middle of the skill distribution but do not for those in the tails of the skill distribution
  • Promotion probability positively affected by high evaluation scores
results x 5 to x
Results – X-5 to X

X-5 X-4 X-3 X-2 X-1 X

primary high
Primary High

Theory predicts no effort incentive after achieving highest rank, decline suggests older

teachers slowing down (rising cost of effort?)

evaluations as a proxy for effort
Evaluations as a proxy for effort
  • One could argue that the evaluation scores capture both ability and effort
  • However, the use of the fixed effect and the ability index mitigate this problem
  • A regression was also run of the probability of obtaining an ‘excellent’ or ‘good’ evaluation score on measures of teacher time use
    • This was done for 2006 only since that is what we have data on
    • Coefficient on number of hours (spent with students, preparing lesson plans, marking homework etc.) is positive and significant
robustness
Robustness
  • What if principals are just awarding high scores to teachers who are nearing eligibility for promotion?
    • Again, evaluation scores are related to time use
    • Restricted the sample to counties that have high correlations between time use and evaluation scores and the effect remains
    • Ranks strongly predict test scores (other studies)
  • Or, teachers could be learning and that would also produce an upward trend pre-eligibility
    • The teachers in the sample have already been teaching for many years (average experience is 12 years)
conclusion
Conclusion
  • Effort responds to promotion incentives
  • Implications for design
    • Optimal contest size and promotion rate?
    • Incentivizing teachers falling behind
    • Combining pay for performance (within-rank incentives) with promotion incentives

(happening in China!)