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Statistical Tools for Program Evaluation: Methods and Applications to Economic Policy, Public Health, and Education 1st ed. 2017 [Hardback]

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  • Formāts: Hardback, 531 pages, height x width: 235x155 mm, weight: 9339 g, 86 Illustrations, color; 53 Illustrations, black and white; X, 531 p. 139 illus., 86 illus. in color., 1 Hardback
  • Izdošanas datums: 06-Jun-2017
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319528262
  • ISBN-13: 9783319528267
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Statistical Tools for Program Evaluation: Methods and Applications to Economic Policy, Public Health, and Education 1st ed. 2017Palielināt
  • Formāts: Hardback, 531 pages, height x width: 235x155 mm, weight: 9339 g, 86 Illustrations, color; 53 Illustrations, black and white; X, 531 p. 139 illus., 86 illus. in color., 1 Hardback
  • Izdošanas datums: 06-Jun-2017
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319528262
  • ISBN-13: 9783319528267
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783319528267.html
Keywords:
This book provides a self-contained presentation of the statistical tools required for evaluating public programs, as advocated by many governments, the World Bank, the European Union, and the Organization for Economic Cooperation and Development. After introducing the methodological framework of program evaluation, the first chapters are devoted to the collection, elementary description and multivariate analysis of data as well as the estimation of welfare changes. The book then successively presents the tools of ex-ante methods (financial analysis, budget planning, cost-benefit, cost-effectiveness and multi-criteria evaluation) and ex-post methods (benchmarking, experimental and quasi-experimental evaluation). The step-by-step approach and the systematic use of numerical illustrations equip readers to handle the statistics of program evaluation.





It not only offers practitioners from public administrations, consultancy firms and nongovernmental organizations the basic tools and advanced techniques used in program assessment, it is also suitable for executive management training, upper undergraduate and graduate courses, as well as for self-study.
1 Statistical Tools for Program Evaluation: Introduction and Overview
1(14)
1.1 The Challenge of Program Evaluation
1(3)
1.2 Identifying the Context of the Program
4(2)
1.3 Ex ante Evaluation Methods
6(3)
1.4 Ex post Evaluation
9(2)
1.5 How to Use the Book?
11(4)
Bibliography
12(3)
Part I Identifying the Context of the Program
2 Sampling and Construction of Variables
15(30)
2.1 A Step Not to Be Taken Lightly
15(1)
2.2 Choice of Sample
16(6)
2.3 Conception of the Questionnaire
22(5)
2.4 Data Collection
27(6)
2.5 Coding of Variables
33(12)
Bibliography
43(2)
3 Descriptive Statistics and Interval Estimation
45(44)
3.1 Types of Variables and Methods
45(2)
3.2 Tabular Displays
47(7)
3.3 Graphical Representations
54(10)
3.4 Measures of Central Tendency and Variability
64(5)
3.5 Describing the Shape of Distributions
69(8)
3.6 Computing Confidence Intervals
77(12)
References
87(2)
4 Measuring and Visualizing Associations
89(48)
4.1 Identifying Relationships Between Variables
89(3)
4.2 Testing for Correlation
92(7)
4.3 Chi-Square Test of Independence
99(6)
4.4 Tests of Difference Between Means
105(8)
4.5 Principal Component Analysis
113(13)
4.6 Multiple Correspondence Analysis
126(11)
References
135(2)
5 Econometric Analysis
137(52)
5.1 Understanding the Basic Regression Model
137(10)
5.2 Multiple Regression Analysis
147(6)
5.3 Assumptions Underlying the Method of OLS
153(3)
5.4 Choice of Relevant Variables
156(8)
5.5 Functional Forms of Regression Models
164(3)
5.6 Detection and Correction of Estimation Biases
167(7)
5.7 Model Selection and Analysis of Regression Results
174(6)
5.8 Models for Binary Outcomes
180(9)
References
187(2)
6 Estimation of Welfare Changes
189(46)
6.1 Valuing the Consequences of a Project
189(2)
6.2 Contingent Valuation
191(9)
6.3 Discrete Choice Experiment
200(11)
6.4 Hedonic Pricing
211(5)
6.5 Travel Cost Method
216(5)
6.6 Health-Related Quality of Life
221(14)
References
230(5)
Part II Ex ante Evaluation
7 Financial Appraisal
235(34)
7.1 Methodology of Financial Appraisal
235(3)
7.2 Time Value of Money
238(6)
7.3 Cash Flows and Sustainability
244(5)
7.4 Profitability Analysis
249(6)
7.5 Real Versus Nominal Values
255(2)
7.6 Ranking Investment Strategies
257(6)
7.7 Sensitivity Analysis
263(6)
References
266(3)
8 Budget Impact Analysis
269(22)
8.1 Introducing a New Intervention Amongst Existing Ones
269(2)
8.2 Analytical Framework
271(4)
8.3 Budget Impact in a Multiple-Supply Setting
275(2)
8.4 Example
277(4)
8.5 Sensitivity Analysis with Visual Basic
281(10)
References
288(3)
9 Cost Benefit Analysis
291(34)
9.1 Rationale for Cost Benefit Analysis
291(3)
9.2 Conceptual Foundations
294(5)
9.3 Discount of Benefits and Costs
299(7)
9.4 Accounting for Market Distortions
306(5)
9.5 Deterministic Sensitivity Analysis
311(2)
9.6 Probabilistic Sensitivity Analysis
313(8)
9.7 Mean-Variance Analysis
321(4)
Bibliography
324(1)
10 Cost Effectiveness Analysis
325(60)
10.1 Appraisal of Projects with Non-monetary Outcomes
325(3)
10.2 Cost Effectiveness Indicators
328(8)
10.3 The Efficiency Frontier Approach
336(6)
10.4 Decision Analytic Modeling
342(9)
10.5 Numerical Implementation in R-CRAN
351(6)
10.6 Extension to QALYs
357(1)
10.7 Uncertainty and Probabilistic Sensitivity Analysis
358(13)
10.8 Analyzing Simulation Outputs
371(14)
References
382(3)
11 Multi-criteria Decision Analysis
385(34)
11.1 Key Concepts and Steps
385(3)
11.2 Problem Structuring
388(2)
11.3 Assessing Performance Levels with Scoring
390(5)
11.4 Criteria Weighting
395(3)
11.5 Construction of a Composite Indicator
398(3)
11.6 Non-Compensatory Analysis
401(9)
11.7 Examination of Results
410(9)
References
416(3)
Part III Ex post Evaluation
12 Project Follow-Up by Benchmarking
419(24)
12.1 Cost Comparisons to a Reference
419(4)
12.2 Cost Accounting Framework
423(3)
12.3 Effects of Demand Structure and Production Structure on Cost
426(7)
12.4 Production Structure Effect: Service-Oriented Approach
433(3)
12.5 Production Structure Effect: Input-Oriented Approach
436(4)
12.6 Ranking Through Benchmarking
440(3)
References
441(2)
13 Randomized Controlled Experiments
443(46)
13.1 From Clinical Trials to Field Experiments
443(5)
13.2 Random Allocation of Subjects
448(5)
13.3 Statistical Significance of a Treatment Effect
453(10)
13.4 Clinical Significance and Statistical Power
463(8)
13.5 Sample Size Calculations
471(3)
13.6 Indicators of Policy Effects
474(6)
13.7 Survival Analysis with Censoring: The Kaplan-Meier Approach
480(3)
13.8 Mantel-Haenszel Test for Conditional Independence
483(6)
References
487(2)
14 Quasi-experiments
489
14.1 The Rationale for Counterfactual Analysis
489(3)
14.2 Difference-in-Differences
492(6)
14.3 Propensity Score Matching
498(14)
14.4 Regression Discontinuity Design
512(7)
14.5 Instrumental Variable Estimation
519
References
530
Jean-Michel JOSSELIN is professor of economics at the University of Rennes 1 (France). His research and teaching interests include law and economics, public policy evaluation, with a focus on public health (cost effectiveness analysis, decision analytic modelling in oncology and chronic diseases). He is researcher at the French National Center for Scientific Research (CREM-CNRS and Condorcet Center for Political Economy), affiliated with the health research chair Hospinnomics (AP-HP and Paris School of Economics), member since 2012 of the Health Economics and Public Health Committee (CEESP) of the French National Authority for Health (HAS).







Benoīt Le Maux is associate professor of economics at the University of Rennes 1 (France). His research and teaching relate to public policy evaluation and democracy, with a special emphasis on public expenditures (microeconomic analysis of collective decision-making, econometrics, quasi-experimental techniques). He is researcher at the French National Center for Scientific Research (CREM-CNRS and Condorcet Center for Political Economy) and currently in charge of coordinating a master program in public finance and management at the Faculty of Economics of the University of Rennes 1.