- ISBN: 9781119691969 | 1119691966
- Cover: Paperback
- Copyright: 6/2/2021
Advanced Engineering Economics, Second Edition, provides an integrated framework for understanding and applying project evaluation and selection concepts that are critical to making informed individual, corporate, and public investment decisions. Grounded in the foundational principles of economic analysis, this well-regarded reference describes a comprehensive range of central topics, from basic concepts such as accounting income and cash flow, to more advanced techniques including deterministic capital budgeting, risk simulation, and decision tree analysis.
Fully updated throughout, the second edition retains the structure of its previous iteration, covering basic economic concepts and techniques, deterministic and stochastic analysis, and special topics in engineering economics analysis. New and expanded chapters examine the use of transform techniques in cash flow modeling, procedures for replacement analysis, the evaluation of public investments, corporate taxation, utility theory, and more. Now available as interactive eBook, this classic volume is essential reading for both students and practitioners in fields including engineering, business and economics, operations research, and systems analysis.
About the Authors vii
Preface ix
Part 1 Basic Concepts and Tools in Economic Analysis
1 Accounting Income and Cash Flow 3
1.1 What Is Investment? 3
1.2 The Corporate Investment Framework 4
1.2.1 The Objective of the Firm 4
1.2.2 The Functions of the Firm 4
1.2.3 The Analysis Framework 6
1.2.4 Accounting Information 6
1.3 The Balance Sheet 7
1.3.1 Reporting Format 7
1.3.2 Cash versus Other Assets 10
1.3.3 Liabilities versus Stockholders’ Equity 10
1.3.4 Inventory Valuation 11
1.3.5 Depreciation 12
1.3.6 Working Capital 12
1.4 The Income Statement 13
1.4.1 Methods of Reporting Income 13
1.4.2 Reporting Format 13
1.4.3 Measurement of Revenue 15
1.4.4 Measurement of Expenses 16
1.4.5 Retained Earnings, Cash Dividends, and Earnings per Share 16
1.4.6 Return on Common Equity (ROE) 17
1.5 The Funds Flow Statement 18
1.5.1 The Cash Flow Cycle 19
1.5.2 Basic Relationship 20
1.5.3 Funds Statement on a Cash Basis 21
1.5.4 Funds Statement as Working Capital 23
1.6 Net Income Versus Cash Flows 24
1.6.1 Deferred Income Taxes 24
1.6.2 Computing Deferred Income Taxes 24
1.6.3 Estimating Cash Flows from Income Statement 26
1.6.4 Use of Cash Flows in Evaluating Investments 26
1.7 Investment Project and Its Cash Flows 27
1.7.1 The Project Cash Flow Statement 28
1.7.2 Cash Flows over the Project Life 29
Summary 31
Problems 32
2 Interest Rates and Valuing Cash Flows 36
2.1 Cash Flow Diagram 36
2.2 Time Preference and Interest 36
2.2.1 Time Preference 37
2.2.2 Types of Interest 37
2.2.3 Nominal and Effective Interest Rates 39
2.3 Discrete Compounding 42
2.3.1 Comparable Payment and Compounding Periods 42
2.3.2 Noncomparable Payment and Compounding Periods 53
2.4 Continuous Compounding 55
2.4.1 Discrete Payments 56
2.4.2 Continuous Cash Flows 58
2.5 Equivalence of Cash Flows 60
2.5.1 Concepts of Equivalence 61
2.5.2 Equivalence Calculations with Several Interest Factors 62
2.6 Effect of Inflation on Cash Flow Equivalence 65
2.6.1 Measure of Inflation 65
2.6.2 Explicit and Implicit Treatments of Inflation in Discounting 66
2.6.3 Case Study—Home Ownership Analysis during Inflation 71
Summary 74
Problems 75
3 Advanced Cash Flow Modeling Techniques 80
3.1 Z-Transforms and Discrete Cash Flows 80
3.1.1 The Z-Transform and Present Value 80
3.1.2 Properties of the Z-Transform 82
3.2 Development of Discrete Present Value Models 87
3.2.1 Extensive Present Value Models 87
3.2.2 Simplified Present Value Model 90
3.2.3 Applications of Z-Transforms 90
3.3 Laplace Transforms and Continuous Cash Flows 96
3.3.1 Laplace Transform and Present Value 96
3.3.2 Properties of Laplace Transforms 97
3.4 Development of Continuous Present Value Models 102
3.4.1 Extensive Present Value Models 102
3.4.2 Present Values of Impulse Cash Flows 105
3.4.3 Extension to Future and Annual Equivalent Models 106
3.5 Application of the Laplace Transform 107
Summary 109
Problems 110
4 Developing Project Cash Flows 113
4.1 Corporate Tax Rates 113
4.1.1 Tax Structure for Corporations 113
4.1.2 Depreciation and Its Relation to Income Taxes 113
4.1.3 Use of Effective and Marginal Income Tax Rates in Project Evaluations 115
4.2 Depreciation Methods 116
4.2.1 Depreciation Regulations and Notation 116
4.2.2 Book Depreciation Methods 117
4.2.3 Tax Depreciation Method 121
4.2.4 Multiple-Asset Depreciation 126
4.3 Capital Gains and Adjustments to Income Taxes 126
4.4 After-Tax Cash Flow Analysis 128
4.4.1 Income Statement Approach 128
4.4.2 Generalized Cash Flows 129
4.4.3 Effects of Depreciation Methods 131
4.4.4 Effects of Financing Costs 134
4.4.5 Effects of Inflation 137
4.4.6 Cash Flow Analysis for Tax-Exempt Corporations 139
Summary 140
Problems 140
5 Selecting a Discount Rate for Project Evaluation 144
5.1 Investment and Borrowing Opportunities 144
5.1.1 Future Investment Opportunities 144
5.1.2 Financing Sources 146
5.1.3 Capital Rationing 147
5.2 Costs of Capital from Individual Sources 147
5.2.1 Debt Capital 147
5.2.2 Equity Capital 154
5.3 Use of a Weighted-Average Cost of Capital 157
5.3.1 Net Equity Flows 158
5.3.2 After-Tax Composite Flows 160
5.4 Specifying the Weighted-Average Cost of Capital 161
5.4.1 Basic Valuation Forms 161
5.4.2 Valuation with Debt and Taxes 163
5.4.3 The Firm’s Capitalization Rate 163
5.4.4 Obtaining a Cutoff Rate 166
5.4.5 Other Issues 167
5.4.6 Effect of Inflation 168
Summary 168
Problems 169
Part 2 Deterministic Analysis
6 Measures of Investment Worth—Single Project 175
6.1 Initial Assumptions 175
6.2 The Net Present Value Criterion 176
6.2.1 Mathematical Definition 176
6.2.2 Economic Interpretation Through Project Balance 180
6.3 Internal Rate-of-Return Criterion 182
6.3.1 Computational Methods 182
6.3.2 Classification of Investment Projects 185
6.3.3 IRR and Pure Investments 188
6.3.4 IRR and Mixed Investments 190
6.3.5 Modified Internal Rate of Return 194
6.4 Benefit–Cost Ratios 197
6.4.1 Benefit–Cost Ratios Defined 198
6.4.2 Equivalence of B/C Ratios and PV 199
6.5 Payback Period 200
6.5.1 Payback Period Defined 200
6.5.2 Popularity of the Payback Period 201
6.6 Time-Dependent Measure of Investment Worth 202
6.6.1 Areas of Negative and Positive Balances 202
6.6.2 Investment Flexibility 203
Summary 205
Problems 207
7 Decision Rules for Selecting among Multiple Alternatives 213
7.1 Formulating Mutually Exclusive Alternatives 213
7.2 Project Ranking Based on Total Investment Approach 216
7.2.1 Total Investment Approach 216
7.2.2 Consistency Within Groups 217
7.2.3 Modification of Criteria to Include Unspent Budget Amounts 219
7.3 Incremental Analysis 220
7.3.1 Irrelevance of Ordering for PV, FV, AE, and PBN 220
7.3.2 Agreement on Increments Between PV and Other Relative Measures 221
7.3.3 Alternative Derivations 221
7.3.4 Decision Rules for IRR 222
7.3.5 A Comprehensive Example for Incremental Analysis 224
7.4 Reinvestment Issues 228
7.4.1 Net Present Value 228
7.4.2 Internal Rate of Return 230
7.4.3 Benefit–Cost Ratio 231
7.5 Comparison of Projects with Unequal Lives 232
7.5.1 Common Service Period Approach 232
7.5.2 Estimating Salvage Value of Longer-Lived Projects 235
7.5.3 Reinvestment Issues When Revenues Are Known 239
7.5.4 Summary Treatment of Unequal Lives 239
7.6 Decisions on the Timing of Investments 239
Summary 240
Problems 242
8 Deterministic Capital Budgeting Models 247
8.1 The Use of Linear Programming Models 247
8.1.1 Description of a Basic Capital Budgeting Problem 248
8.1.2 Criterion Function to Be Optimized 248
8.1.3 Multiple Budget Periods 249
8.1.4 Project Limits and Interdependencies 249
8.1.5 LP Formulation of Lorie–Savage Problem 250
8.1.6 Duality Analysis 250
8.2 Pure Capital Rationing Models 253
8.2.1 Criticisms of the PV Model 254
8.2.2 Consistent Discount Factors 255
8.3 Net Present Value Maximization with Lending and Borrowing 258
8.3.1 Inclusion of Lending Opportunities 258
8.3.2 Inclusion of Borrowing Opportunities 259
8.4 Weingartner’s Horizon Model 259
8.4.1 Equal Lending and Borrowing Rates 259
8.4.2 Lending Rates Less than Borrowing Rates 265
8.4.3 Inclusion of Borrowing Limits Supply Schedule of Funds 267
8.4.4 Dual Analysis with Project Interdependencies 271
8.5 Bernhard’s General Model 272
8.5.1 Model Formulation 272
8.5.2 Major Results 273
8.6 Discrete Capital Budgeting 276
8.6.1 Number of Fractional Projects in LP Solution 276
8.6.2 Branch-and-Bound Solution Procedure 277
8.6.3 Duality Analysis for Integer Solutions 279
8.7 Capital Budgeting with Multiple Objectives 281
8.7.1 Goal Programming 281
8.7.2 Interactive Multiple-Criteria Optimization 283
Summary 284
Problems 285
Part 3 Stochastic Analysis
9 Utility Theory 295
9.1 The Concept of Risk 295
9.1.1 Role of Utility Theory 297
9.1.2 Alternative Approaches to Decision Making 298
9.2 Preference and Ordering Rules 298
9.2.1 Bernoulli Hypothesis 298
9.3 Properties of Utility Functions 301
9.3.1 Risk Attitudes 301
9.3.2 Relationship between Certainty Equivalent and Risk Premium 304
9.3.3 Types of Utility Functions 304
9.4 Empirical Determination of Utility Functions 307
9.4.1 General Procedure 307
9.4.2 Sample Results 309
9.5 Mean–Variance Analysis 310
9.5.1 Indifference Curves 310
9.5.2 Coefficient of Risk Aversion 312
9.5.3 Justification of the Mean and Variance Criterion 312
9.5.4 Justification of Certainty Equivalent Method 314
Summary 317
Problems 318
10 Probabilistic Cash Flow Analysis—Single Project 322
10.1 Measures of Project Risk 322
10.1.1 Downside Risk 322
10.1.2 How Businesspeople Perceive Risk in Project Evaluation 323
10.2 Estimating Values in Probabilistic Terms 324
10.2.1 Statistical Moments of a Single Random Variable 325
10.2.2 Statistical Moments of Linear Combinations of Random Variables 328
10.2.3 Products of Random Variables 332
10.2.4 Quotients of Random Variables 334
10.2.5 Powers of Independent Random Variables 335
10.2.6 General Approximation Formulas 338
10.3 Statistical Moments of Discounted Cash Flows 339
10.3.1 Expected Net Present Value 339
10.3.2 Variance of Net Present Value 340
10.3.3 Mixed Net Cash Flows 343
10.3.4 Net Cash Flows Consisting of Several Components 344
10.3.5 Cash Flows with Uncertain Timing: Continuous Case 345
10.3.6 Cash Flows with Uncertain Timing: Discrete Case 352
10.4 Probability Distributions of Net Present Value 355
10.4.1 Discrete Cash Flows Described by a Probability Tree 355
10.4.2 Use of the First Two Statistical Moments 357
10.4.3 Use of the First Four Statistical Moments 358
10.5 Estimating Risky Cash Flows 359
10.5.1 Beta-Function Estimators for Single Cash Flows 359
10.5.2 Hiller’s Method for Correlated Cash Flows 365
10.6 Measure of Operational Risk 367
10.6.1 Value at Risk—Downside Risk Measurements 367
10.6.2 How to Calculate the Value at Risk? 367
10.6.3 Conditional Value at Risk (CVaR) 371
Summary 373
Problems 375
11 Comparing Risky Projects and Portfolio Optimization Theory 386
11.1 Comparative Measures of Investment Worth 386
11.1.1 Mean–Variance, E–V 386
11.1.2 Mean–Semivariance, E–Sh 388
11.1.3 Safety First 391
11.2 Stochastic Dominance 392
11.2.1 First-Degree Stochastic Dominance 392
11.2.2 Second-Degree Stochastic Dominance 395
11.2.3 Third-Degree Stochastic Dominance 399
11.2.4 Relationship Between Dominance and Mean–Variance Criterion 402
11.3 Portfolio Theory 403
11.3.1 Efficiency Frontier 404
11.3.2 Diversification of Risk 406
11.3.3 Full Covariance Model 407
11.3.4 Index Model 408
11.3.5 Capital Market Theory 409
11.4 Discrete Capital-Rationing Models Under Risk 412
11.4.1 Hillier’s Method for Correlated Projects 413
11.4.2 Stochastic Programming 414
11.5 Multiperiod Index Model for Project Portfolio 415
11.5.1 Model Structure and Assumptions 415
11.5.2 Procedure 417
11.6 Uncertainty Resolution 419
Summary 421
Problems 423
12 Risk Simulation 430
12.1 An Overview of the Logic of Simulation 430
12.1.1 Monte Carlo Sampling 431
12.1.2 Using the Simulation Output 431
12.2 Selecting Input Probability Distributions 432
12.2.1 Selecting a Distribution Based on Observed Data 432
12.2.2 Selecting a Distribution in the Absence of Data 439
12.3 Sampling Procedures for Independent Random Variables 441
12.3.1 Inverse Transformation Techniques 441
12.3.2 Other Frequently Used Random Deviates 444
12.4 Sampling Procedures for Dependent Random Variables 446
12.4.1 Assessment of Conditional Probabilities 446
12.4.2 Sampling a Pair of Dependent Random Samples 447
12.4.3 Sampling Based on Regression Equation 450
12.4.4 Conditional Sampling in the Absence of Data 455
12.4.5 Normal Transformation Method 457
12.5 Output Data Analysis 460
12.5.1 Replication and Precision of Results 460
12.5.2 Comparison of Two Projects 462
12.6 A Simple Risk Simulation Example 465
12.6.1 Decision Problem 465
12.6.2 Replication Results 468
Summary 469
Problems 470
13 Decision Analysis and Value of Information 474
13.1 Sequential Decision Process 474
13.1.1 Structuring the Decision Tree 474
13.1.2 Expected Value as a Decision Criterion 478
13.2 Obtaining Additional Information 478
13.2.1 The Value of Perfect Information 479
13.2.2 Determining Revised Probabilities 481
13.2.3 Expected Monetary Value after Receiving Sample Information 486
13.2.4 Value of the Market Survey 486
13.3 Decision Tree and Risk 487
13.3.1 Sensitivity Analysis 487
13.3.2 Decision Based on Certainty Equivalents 488
13.4 Investment Decisions with Replication Opportunities 490
13.4.1 The Opportunity to Replicate 490
13.4.2 Experiment Leading to Perfect Information 490
13.4.3 A Case Example—Flexible Cellular Manufacturing Operation 491
13.4.4 Sampling Leading to Imperfect Information 494
13.5 Bayesian Inference and Value of Sampling 495
13.5.1 Bayesian Inference 495
13.5.2 Bayesian Update with a Discrete Prior Distribution 497
13.5.3 Bayesian Update with a Continuous Prior Probability Distribution 500
13.6 Conjugate Prior Distributions 503
13.6.1 Types of Sampling 503
13.6.2 Conjugate Distribution for Bernoulli Process 505
13.6.3 Conjugate Distribution for Poisson Process 507
13.6.4 Conjugate Distribution for Normal Process 509
13.6.5 Lognormal Process 512
13.7 Terminal Analysis: Opportunity Loss and Value of Perfect Information 513
13.7.1 Opportunity Loss Function 513
13.7.2 The Expected Value of Sample Information 515
13.7.3 Optimal Sample Size 517
Summary 518
Problems 519
14 Basic Options Theory 527
14.1 Financial Options Concepts 527
14.1.1 Call Options 528
14.1.2 Put Options 529
14.2 Stochastic Process of Asset Dynamics 530
14.2.1 Underlying Asset Price Movement—Geometric Brownian Motion 531
14.2.2 Simulated Stock Prices Based on Brownian Motion 534
14.2.3 Discrete-Time Price Movement 535
14.2.4 How to Determine the Binomial Parameters 537
14.3 Upper and Lower Bounds for Option Prices 539
14.3.1 Upper and Lower Bounds 539
14.3.2 Put–Call Parity 540
14.4 Binomial Option Pricing Model 541
14.4.1 Option Pricing for a Single-Period Model 541
14.4.2 Risk-Neutral Probabilities 543
14.4.3 Properties of Option Attributes 544
14.4.4 Effects of Dividends 545
14.5 Option Pricing for the Multi-Period Binomial Model 546
14.6 Pricing an American Option 548
14.6.1 Early Exercise for an American Call Option 550
14.7 Black–Scholes Model 550
14.7.1 Call and Put Options Formulas 551
14.7.2 Components of the Black–Scholes Model 552
14.7.3 Formal Derivation of the Black–Scholes Formula 553
14.7.4 Relationship Between the Binomial Lattice Model and the Black–Scholes Model 555
14.8 Dividends and Black–Sholes Model 556
14.8.1 Known Dividend Yield 556
14.8.2 Known Dollar Dividend 556
14.9 Pricing Exotic Options 557
14.9.1 Exchange Options—Margrabe Model 557
14.9.2 The Geske Model—Compound Option 558
14.10 Estimating Volatility for Traded Financial Assets 560
Summary 563
Problems 564
15 Real Options Analysis 567
15.1 A New Way of Thinking of Investment Strategy under Uncertainty 567
15.1.1 Identify the Level of Uncertainty 567
15.1.2 Analytic Tools and Strategies to Resolve Uncertainty 568
15.2 What Is the Investment Flexibility? 572
15.3 Real Options Valuation with Financial Option Framework 575
15.3.1 Basic Modeling Concept 575
15.3.2 SNPV Calculation with Black–Scholes Formula 576
15.4 Real Call Options Models 577
15.4.1 Option to Wait—Delay Options 577
15.4.2 Option to Expand—Growth Options 579
15.4.3 Research and Development 580
15.4.4 Scale-Up Options by Binomial Lattice 582
15.4.5 Exchange Option—Delay Options with Stochastic Investment Cost 584
15.5 Real Put Options Models 586
15.5.1 Option to Abandon 586
15.5.2 Option to Switch 589
15.5.3 Option to Scale Down 590
15.6 Option to Choose 591
15.7 Compound Real Options 594
15.7.1 Geske Model 594
15.7.2 Compound Options with Changing Volatility 598
15.7.3 A Four-Phased Compound Option with Varying Volatility—A Case Example 599
15.8 Estimating the Implied Project Volatility 605
15.9 An Alternative Real Options Valuation Based on the Loss Function Approach 606
15.9.1 The Concept of Opportunity Loss Function 607
15.9.2 Valuing Real Call Option with the Standardized Loss Function Approach 607
15.9.3 Valuing Real Put Option with the Standardized Loss Function Approach 612
15.9.4 Determining the Correct Amount of Premium to Pay for Real Options 614
Summary 618
Problems 619
15A Bayesian Real Options Analysis 625
15A.1 Real Options Premium and Value of Information 625
15A.1.1 Real Options Valuation Based on Linear Payoff Analysis 625
15A.1.2 Expected Value of Perfect Information and Its Relation to Option Premium 626
15A.2 Option Valuation with Opportunity to Replicate 628
15A.2.1 Option Value with Imperfect Information 629
15A.2.2 Revised Option Values 631
15A.3 Bayesian Compound Option—Delay Real Options with Learning 632
15A.3.1 A Conceptual Modeling Framework 632
15A.3.2 Effects of Learning 634
15A.3.3 Decision to Invest in Phase 1 with Upstream Learning 634
15A.3.4 Development of a Learning Real Options Framework 635
15A.3.5 Incorporating Bayesian Learning 636
15A.3.6 Posterior Properties 638
15A.4 A Case Study—Learning Options in Aerospace Industry 638
15A.4.1 Background 638
15A.4.2 Applying the Decision Model 639
15A.4.3 Option Value Based on Posterior Information 640
15A.4.4 Economic Interpretation 641
Summary 642
Part 4 Special Topics in Engineering Economic Analysis
16 Evaluation of Public Investments 647
16.1 The Nature of Public Activities 647
16.2 The Procedure of Benefit–Cost Analysis 648
16.2.1 Valuation of Benefits and Costs 649
16.2.2 Decision Criteria 651
16.3 The Benefit–Cost Concept Applied to a Mass Transit System 654
16.3.1 The Problem Statement 655
16.3.2 Users’ Benefits and Disbenefits 656
16.3.3 Sponsor’s Costs 662
16.3.4 Benefit–Cost Ratio for Project 665
16.4 Cost–Benefit/Cost-Effectiveness Analyses 666
16.4.1 Cost–Benefit Analysis 666
16.4.2 Cost-Effectiveness Analysis 667
16.5 Risk and Uncertainty in Benefit–Cost Analysis 667
16.5.1 Exact Distribution of Benefit–Cost Ratio 668
16.5.2 Exact Distribution of Incremental Benefit–Cost Ratio 669
16.5.3 Computer Simulation Approach 673
Summary 676
Problems 677
17 Economic Analysis in Public Utilities 681
17.1 Utility Firms and Fair Returns 681
17.2 Capital Costs for Public Utilities 682
17.2.1 Debt and Equity Financing for Public Utilities 682
17.2.2 Weighted After-Tax Cost of Capital 682
17.2.3 Capital Recovery Cost Based on Book Depreciation Schedule 683
17.3 The Revenue Requirement Method 685
17.3.1 Assumptions of the Revenue Requirement Method 685
17.3.2 Determination of Annual Revenue Requirements 686
17.3.3 Effect of Inflation in Revenue Requirements 689
17.4 Equivalence of the Present Value and Revenue Requirement Methods 692
17.4.1 The A/T Equity Cash Flows and Revenue Requirement Series 692
17.4.2 Important Results Regarding the Equivalence of the PV and RR Methods 694
17.5 Flow-Through and Normalization Accounting 696
17.5.1 Flow-Through Method 696
17.5.2 Normalizing Method 698
Summary 704
Problems 704
18 Procedures for Replacement Analysis 708
18.1 Quantifying Obsolescence and Deterioration 708
18.2 Forecasting Future Data 713
18.3 Basic Concepts in Replacement Analysis 715
18.3.1 Sunk Costs 715
18.3.2 Outsider Point of View 716
18.4 Economic Life of an Asset 721
18.5 Infinite Planning Period Methods 724
18.5.1 No Technology or Cost Changes, AE Method 724
18.5.2 Geometric Changes in Purchase Costs and O&M Costs, PV Method 727
18.6 Finite Planning Period Methods 730
18.6.1 Sensitivity Analysis of PV with Respect to Inflation 730
18.6.2 Dynamic Programming Method 732
18.7 Building a Data Base 738
18.8 Recent Advances in Fleet Replacement Studies 740
Summary 741
Problems 742
Appendix A Discrete Interest Compounding Tables A-1
Appendix B Statistical Tables A-29
Table B.1 Cumulative Standard Normal Distribution A-29
Table B.2 Percentage Points of the χ2 Distribution A-30
Table B.3 Standard Normal Distribution Loss Function A-31
Index I-1
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