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Book Details
Abstract
Benchmarking is essential for those developing and implementing water policy. If decision-makers do not know where they have been or where they are, it would seem to be impossible to set reasonable targets for future performance. Information on water/sewerage system (WSS) operations, investments, and outputs is essential for good management and oversight. This book is designed to help decision makers identify the data required for performance comparisons over time and across water utilities, to understand the strengths and limitations of alternative benchmarking methodologies, and to perform (or commission) benchmark studies.
This book provides an overview of the strengths and limitations of different methodologies for making performance comparisons over time and across water utilities (metric benchmarking). In addition, it identifies ways to determine the robustness of performance rankings. Current benchmarking activities in Latin America, Asia, Africa, Central Europe/Asia, and OECD nations are summarized.
Five basic approaches to benchmarking characterize current studies: Core indicators and a summary or overall performance Indicator (partial metric method), Performance scores based on production or cost estimates (“total” methods), Performance relative to a model company (engineering approach), Process benchmarking, and Customer survey benchmarking.
This volume is of interest to the water professionals, water utility managers and senior staff of regulatory agencies, professionals in related government agencies, and consultants.
Visit the IWA WaterWiki to read and share material related to this title: http://www.iwawaterwiki.org/xwiki/bin/view/Articles/InfrastructureRegulationStateOwnedEnterprisesVsInvestor-ownedInfrastructureOperators
"The Associação Brasileira de Agências de Regulação – ABAR, recognizes and applauds the merits of this book. We welcome the way Sanford Berg’s underscores the critical need for key information about how service is affected by the efficiency of water and sewerage operations, investments, and incentives. Without benchmarking methodologies, policy-makers, regulators and managers do not know where they have been nor where they are, and it is impossible for them to establish feasible performance targets to be reached by operators. This book explains how water and sewerage services can be offered at affordable cost to all consumers—the main objective for citizens andpolicymakers." RICARDO PINTO PINHEIRO, President of Agência Reguladora de Águas, Energia e Saneamento Básico do Distrito Federal (ADASA), Brasil; and President of the Associação Brasileira de Agências de Regulação (ABAR) 2010.
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Half Title | 1 | ||
| Title | 3 | ||
| Copyright | 4 | ||
| Table of Contents | 5 | ||
| Preface | 7 | ||
| Acknowledgements | 10 | ||
| Acronyms and Abbreviations | 11 | ||
| Chapter 1: Introduction | 13 | ||
| 1.1 Basic Definitions | 16 | ||
| 1.2 Five Methodologies | 18 | ||
| 1.3 Measurement and Data Sources | 25 | ||
| 1.4 Operational and Accounting Data | 27 | ||
| 1.5 Illustrative Functions: Model Specification | 31 | ||
| 1.5.1 Production functions | 31 | ||
| 1.5.2 Cost functions | 32 | ||
| 1.6 Company Comparisons | 36 | ||
| Chapter 2: Checklist for Conducting Benchmarking Studies | 39 | ||
| 2.1 Identify Objectives, Select Methodology and Gather Data (Step 1) | 41 | ||
| 2.1.1 Organize benchmarking team | 43 | ||
| 2.1.2 Identify study objectives | 43 | ||
| 2.1.3 Select methodology and refine study objectives | 44 | ||
| 2.1.4 Selection of timeframe and peer comparison group | 45 | ||
| 2.1.5 Gather raw data: collection issues | 46 | ||
| Technical and operational problems | 47 | ||
| Commercial and financial concerns | 47 | ||
| Human capital and personnel issues | 48 | ||
| Regulatory governance and incentives issues | 49 | ||
| 2.2 Screen and analyze data (Step 2) | 50 | ||
| 2.2.1 Investigate the raw data and evaluate data quality | 51 | ||
| 2.2.2 Assemble benchmarking dataset | 55 | ||
| 2.2.3 Analyze the data and conduct performance benchmarking study | 55 | ||
| 2.3 Utilize Specific Analytic Techniques (Step 3) | 60 | ||
| Partial indicators | 61 | ||
| Total factor productivity | 61 | ||
| Nonparametric | 61 | ||
| Parametric | 61 | ||
| 2.4 Sensitivity Tests (Step 4) | 62 | ||
| 2.4.1 Robustness of results | 62 | ||
| 2.4.2 Three levels of sensitivity tests | 65 | ||
| 2.4.3 Analyze the scores and rankings and explore the potential determinants of inefficiency | 66 | ||
| 2.5 Develop Policy Implications (Step 5) | 66 | ||
| 2.5.1 Explore the potential determinants of inefficiency | 66 | ||
| 2.5.2 Summarize the results: formats for presenting comparisons | 68 | ||
| 2.5.3 Suggestions/Strategies for potential improvement | 72 | ||
| 2.5.4 Follow-up benchmarking studies | 73 | ||
| 2.6 Recent Institutional Developments | 73 | ||
| Chapter 3: Overview of Metric Benchmarking Concepts | 77 | ||
| 3.1 Production Concepts | 77 | ||
| 3.2 Statistical Estimate of a Production Function | 82 | ||
| 3.3 Cost Concepts | 85 | ||
| 3.4 Efficiency Scores Reflecting Outputs and Inputs | 88 | ||
| 3.4.1 Efficiency frontier | 90 | ||
| 3.4.2 Calculating technical efficiency | 91 | ||
| 3.4.3 Calculating allocative efficiency | 92 | ||
| 3.5 Outputs and Costs | 95 | ||
| 3.5.1 Scale efficiency: the concept | 95 | ||
| 3.5.2 Measuring scale efficiency | 97 | ||
| 3.6 Statistical Estimates of a Linear Cost Function | 98 | ||
| 3.7 Specification of a Nonlinear Relationship | 100 | ||
| Chapter 4: Strengths and Limitations of Different Methodologies: Technical Considerations | 103 | ||
| 4.1 Criteria for Selecting Performance Measures | 103 | ||
| 4.2 Specific Core Indicators (Partial Metric Methods) | 104 | ||
| 4.3 Aggregating Partial Indices into an Overall Performance Indicator (OPI) | 105 | ||
| 4.4 Performance Scores Based on Production and Cost Estimates (‘‘Total’’ Methods) | 109 | ||
| 4.4.1 Index methods (Total Factor Productivity) | 109 | ||
| 4.4.2 Estimation using mean and average methods | 110 | ||
| Ordinary least squares (OLS) | 111 | ||
| Corrected ordinary least squares (COLS) | 111 | ||
| 4.4.3 Frontier methods | 112 | ||
| 4.5 Examples of Empirical Studies | 116 | ||
| Chapter 5: Summary and Conclusions | 123 | ||
| 5.1 Potential Impacts of Benchmarking Studies | 124 | ||
| 5.1.1 Network expansion | 124 | ||
| 5.1.2 Poverty reduction | 125 | ||
| 5.1.3 Organizational incentives | 126 | ||
| 5.1.4 International support and national commitment | 126 | ||
| 5.2 Concluding Observations | 127 | ||
| 5.2.1 Comparing performance | 128 | ||
| 5.2.2 Using performance scores | 130 | ||
| 5.2.3 Promoting public acceptance | 130 | ||
| Appendix 1: Variable Definitions and Explanations | 133 | ||
| Output Variables | 133 | ||
| Output Variables for Water Services | 134 | ||
| Output Variables for Sewerage Services | 135 | ||
| Output Variables for Both Services | 136 | ||
| Variable Conversions | 136 | ||
| Quality Variables | 137 | ||
| Input Variables: Quantities and Prices | 139 | ||
| Accounting/Financial Variables | 143 | ||
| Conditioning/Environmental Variables | 144 | ||
| Weather and Topographical Variables | 146 | ||
| Macroeconomic Variables | 147 | ||
| Governance Structure Variables | 147 | ||
| Concluding Remarks about Variables | 152 | ||
| Appendix 2: Annotated Bibliography of Water Benchmarking Studies | 153 | ||
| Appendix 3: Technical Features of Benchmarking Methodologies | 161 | ||
| Partial Indicators (Specific Core Indicators) | 161 | ||
| Total Factor Productivity (TFP) Index | 162 | ||
| Tornqvist index | 162 | ||
| Malmquist index | 162 | ||
| Non-parametric Methods | 162 | ||
| Parametric Methods | 164 | ||
| Stochastic Production Frontier Model | 165 | ||
| Stochastic Cost Frontier Model | 165 | ||
| Stochastic Frontier Distance Function Model | 165 | ||
| Corrected Ordinary Least Squares | 166 | ||
| Fixed or Random Effects Models (Distribution Free Methods) | 166 | ||
| Appendix 4: Benchmarking in Regions of the World | 169 | ||
| Latin America: ADERASA⊃1 | 170 | ||
| Africa: WUP | 172 | ||
| Asia: SEAWUN⊃6 | 173 | ||
| OECD⊃7 | 175 | ||
| Index | 177 |