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Efficiency Of Public Spending

Introduction:

Governments of developing countries typically spend resources equivalent to a range between 15 and 30 percent of GDP. Hence, small changes in the efficiency with which those resources are used could have major impacts on GDP and on the attainment of the government’s objectives whichever these are. The first challenge that policymakers, outside parties or applied researchers face is the measurement of efficiency.

Empirical and theoretical measures of efficiency are based on ratios of observed output levels to the maximum that could have been obtained given the level of input utilization. This maximum constitutes the efficient frontier which is generally used as a benchmark for measuring the relative efficiency of the observations. This website presents some of the World Bank's research project in this area, provides some databases and software used, as well a summary literature and links to other websites that have been useful in our project. In this sense, this overview is far from exhaustive and should be considered as work in progress.

Papers by World Bank Staff and Consultants: 

  • Efficiency of Public Spending in Developing Countries: An Efficiency Frontier Approach: Santiago Herrera & Gaobo Pang - May 2005 [Document]
  • A Preliminary Non-Parametric Analysis of Public Education and Health Expenditures in Developing Countries: Paul Wilson [Document]
    • Annex - A Preliminary Non-Parametric Analysis of Public Education and Health Expenditures in Developing Countries [Document]
  • Measuring Efficiency in Public Expenditure: Vito Tanzi [Document]
    • Figures - Measuring Efficiency in Public Expenditure [Document]
  • Efficiency of Public Spending in Developing Countries: A Stochastic Frontier Approach: William Greene - May 2005 [Document]

Results, Datasets & Programs: (Notes on the programs to calculate efficiency scores)

The data and codes posted here accompany the paper titled "Efficiency of Public Spending in Developing Countries: An Efficiency Frontier Approach: Santiago Herrera & Gaobo Pang" by Santiago Herrera and Gaobo Pang.

Datasets

Free Disposable Hull (FDH)

The FDH program can be easily tailored to fit various efficiency comparisons by (1) replacing the data with their own dataset, in Stata format; (2) changing the variable names for input and output indicators; and (3) setting Nobs in Do-files to the corresponding number of observations. Readers are suggested to go through the first two exercises (F1 and F2) since there is detailed explanation for each step.

Quick Steps to Get Started with FDH

  1. Save EDUHEA.dta and the Do file in each exercise in the same directory.
  2. Start Stata /SE 8.0 for Windows, open and run the Do file as follows.
    1. Click Window and select Do-File Editor.
    2. Click File in the Do-File Editor and select Open to open the .DO file in the current directory.
    3. Run the whole file by clicking Do, or run part of it by highlighting and clicking Do.

FDH Exercises

  • Exercise F1. Single Input and Single Output, Input Efficiency
  • Exercise F2. Single Input and Single Output, Output Efficiency
  • Exercise F3. Multiple Inputs and Multiple Outputs, Input Efficiency
  • Exercise F4. Multiple Inputs and Multiple Outputs, Output Efficiency

Data Envelopment Analysis (DEA)

 

The DEAP software was written by Tim Coelli. This program is used to construct DEA frontiers for the calculation of technical and cost efficiencies and also for the calculation of Malmquist TFP Indices. An introduction document in PDF format is also included in the zipped package.

 

Quick Steps to Get Started with DEA

  1. Download DEAP version 2.1 from http://www.uq.edu.au/economics/cepa/deap.htm.
  2. Save all outputs and then all inputs in columns from left to right in a data file (e.g. EDU11 in Exercise D1.)
  3. Give and save instructions in the .ins file (e.g. EDU11.ins in Exercise D1.)
  4. Double click DEAP and type in the full name of instruction file at the DOS prompt (e.g. EDU11.ins in Exercise D1.)
  5. Open output file to check results (e.g. EDU11.out in Exercise D1.)

Note: All files can be edited using Notepad or other text editors.

DEA Exercises:

  • Exercise D1. Single Input (Orthogonalized Public Spending on Education) and Single Output (Gross Primary School Enrollment), Input Efficiency
  • Exercise D2. Two Inputs (Orthogonalized Public Spending on Education, Teachers per Pupil) and Two Outputs (Gross Primary and Secondary School Enrollment), Input Efficiency
  • Exercise D3. Three Inputs (Orthogonalized Public Spending on Education, Teachers per Pupil, & Literacy of Adult) and Two Outputs (Gross Primary and Secondary School Enrollment), Input Efficiency
  • Exercise D4. Three Inputs (Orthogonalized Public Spending on Education, Teachers per Pupil, & Literacy of Adult) and Three Outputs (Average Years of School, First & Second Level Complete), Input Efficiency

Note: Output efficiency can be calculated by choosing 1 output-oriented in the instruction file.

FDH and DEA : Estimated Efficiency Scores for Education and Health

  1. Input Efficiency for Single Period (1996-2002)
  2. Output Efficiency for Single Period (1996-2002)
  3. Input Efficiency for Multiple Periods (1975-80 and 1996-2002)
  4. Output Efficiency for Multiple Periods (1975-80 and 1996-2002)

Reference Materials for Efficiency Frontier Estimation:

Introduction and Theoretical Foundation of Non-parametric Estimation of Efficiency Frontier

  • Bowlin, William F. 1998. Measuring Performance: An Introduction to Data Envelopment Analysis (DEA), Journal of Cost Analysis, pp. 3-27.
  • Banker, R. 1993 “Maximum likelihood, consistency and data envelopment analysis: a statistical foundation” Management Science, Vol. 39, No. 10
  • Banker, R. D., Charnes, A. and Cooper, W. W. 1984. Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis, Management Science 30(9), pp.1078-92.
  • Charnes,  A. W. Cooperand E. Rhodes 1978“Measuring efficiency of decision-making units” European Journal of Operational Research, Vol. 2 pp.429-444.
  • Fare, R. and S. Grosskopf  1995. Non-parametric tests of regularity, Farrell efficiency, and goodness of fit. Journal of Econometrics, 69. pp.415-425.
  • Farrell, M. 1957. “The measurement of productive efficiency”, Journal of the Royal Statistical Society, Series A. Vol. 120, No. 3, pp. 253-290.
  • Murillo-Zamorano, L. 2004. “Economic efficiency and frontier techniques”  Journal of Economic Surveys, Vol. 18, No. 1, pp.33-77.
  • Varian, H. 1984. The Nonparametric Approach to Production Analysis, Econometrica, Vol. 52 No. 3, pp. 579-598
  • Varian, H. 1990. “Goodness-of-fit in optimizing models”, Journal of Econometrics, 46, pp. 125-140.

Applied FDH/DEA on Education, Health and Others

  • Afonso, A. and M. St Aubyn (2004) Non-parametric approaches to education and health: Expenditure efficiency in OECD countries. Mimeo. Technical University of Lisbon.
  • Afonso, A., L. Schuknecht and V. Tanzi (2003)Public sector efficiency: an international comparison. Working paper 242. European Central Bank.
  • Burgess, J. and P. Wilson (1998) “Variation in inefficiency in U.S. Hospitals” Canadian Journal of Operational Research and Information Processing, 36, pp.84-102.
  • Gupta, Sanjeev, and Martin Verhoeven. 2001. The efficiency of government expenditure, experiences from Africa. Journal of Policy Modeling, 23, 433-467.
  • Tanzi V. 2004 Measuring efficiency in public expenditure.  Paper presented in Conference on Public Expenditure Evaluation and Growth. The World Bank. October.
  • Worthington, A.2001 “An empirical survey of frontier efficiency measurement techniques in education” Education Economics, Vol. 9, No. 3

Efficiency and Technical Change through Time

  • Fare, R., S. Grosskopf, M. Norris, and Z. Zhang 1994. Productivity Growth, Technical Progress and Efficiency Change in Industrialized Countries. American Economic Review 84, pp.66-83.
  • Fare, R., E. Griffell-Tajte, S. Grosskopf, and C.A. Knox Lovell 1997. Biased Technical Change and Malmquist Productivity Index, Scandinavian Journal of Economics 99, 119-127.
  • Nin, A. C. Arndt, and P. Preckel 2003“Is agricultural productivity in developing countries really shrinking? New evidence using a modified nonparametric approach”  Journal of Development Economics, 71,pp.395-415

Statistical Inference and Recent Advances in Non-parametric Approach

  • Cazals, C., Florens, J. and L. Simar 2002“Non-parametric frontier estimation; A robust approach” Journal of Econometrics, 106(1) pp. 1-25
  • Cherchye, L. and T. Post 2001 . “Methodological advances in DEA: A survey and an application for the Dutch electricity sector”. ERIM Report Series Research in Management, ERS-2001-53-F&A
  • Grosskopf, S. (1996) “Statistical inference and non-parametric efficiency: a selective survey” The Journal of Productivity Analysis, 7 pp.161-176.
  • Simar, L. and P. Wilson 2000 . “Statistical inference in non-parametric frontier models: The state of the art” Journal of Productivity Analysis, 13 pp 49-78.
  • Simar, L. and P. Wilson 1998 . Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models, Management Science, Vol. 44, No. 1, pp.49-61.
  • Simar, L. and P. Wilson 2000 . A General Methodology for Bootstrapping in Non-parametric Frontier Models, Journal of Applied Statistics, Vol. 27, No. 6, pp.779-802.
  • Wheelock D. and Wilson, P. 2003“Robust  Non-parametric estimation of efficiency and technical change in U.S. Commercial Banking” Working Paper. Federal reserve Bank of St. Louis. November.

Parametric Approach: Stochastic Frontier

  • Aigner, D.J., C.A.K. Lovell, and P. Schmidt. 1977. Formulation and estimation of stochastic frontier production function models, Journal of Econometrics, Vol. 6: 21-37.
  • Bishop, P. and S. Brand 2003“The efficiency of museums: a stochastic frontier production function approach”, Applied Economics, 35, pp.1853-1858.
  • Evans, D, A. Tandon, C. JL Murray, and J. A Lauer. 2000. The comparative efficiency of national health systems in producing health: an analysis of 191 countries. World Health Organization  GPE Discussion Paper Series No. 29
  • Greene, W. 2003a. Distinguishing between heterogeneity and inefficiency: Stochastic frontier analysis of the World Health Organization’s panel data on national health cares systems". Mimeo. NYU.
  • Jayasuriya, Ruwan, and Quentin Wodon. 2002. Measuring and explaining country efficiency in improving health and education indicators. The World Bank

Useful Links

Government Applied Work on Efficiency and Expenditure Appraisal


Last updated: 2005-09-27




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