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Taylor & Francis
Business Forecasting, Second Edition: A Practical Approach / Edition 2

Business Forecasting, Second Edition: A Practical Approach / Edition 2

by A. Reza Hoshmand
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Product Details

ISBN-13: 9780415988568
Publisher: Taylor & Francis
Publication date: 11/23/2009
Edition description: New Edition
Pages: 384
Product dimensions: 6.00(w) x 8.90(h) x 0.70(d)

About the Author

A. Reza Hoshmand is associate dean of graduate studies and chair of the Business and Management Division at Daniel Webster College. He holds a Ph.D. in resource economics from the University of Maryland and has published nearly a dozen books and manuals, including Design of Experiments for Agriculture and the Natural Sciences, 2nd Edition (Chapman and Hall\CRC Press, 2006), Business and Economic Forecasting for the Information Age: A Practical Approach (Quorum, 2002) and, Statistical Methods for Environmental and Agricultural Sciences, Second Edition (CRC Press, 1997.) He has also written more than two dozen journal articles, technical reports and other papers.

Recently named a Fulbright Scholar to research foreign direct investment in China, Professor Hoshmand has garnered numerous other honors and awards including being nominated for the "Excellence in Teaching Award" by the University of Hawaii Board of Regents and being included in Who’s Who in the West, 26th edition. Prior to coming to Daniel Webster in 2001, Professor Hoshmand was a Professor of Economics and Finance at Lesley University’s School of Management. He has been a faculty member at the University of Hawaii, and with the California State University at Pomona. At Cal Poly Pomona, he was the interim director, International Center, and associate dean, College of Agriculture. He also held numerous other academic appointments during his career, including economics lecturer at Harvard and Tufts Universities. In 1991 Professor Hoshmand, was a visiting lecturer, economics, at the University of Hong Kong.

Table of Contents

Preface xi

1 Forecasting for Management Decisions: An Introduction 1

1.1 Forecasting and Decision Making 2

1.2 The Art and Science of Forecasting 4

1.3 The Forecasting Process 5

References and Suggested Reading 8

2 Data Patterns and Choice of Forecasting Techniques 9

2.1 Data Patterns 9

2.2 Forecasting Methodologies 17

2.3 Technique Selection 19

2.4 Model Evaluation 22

Chapter Summary 30

Review Questions 31

References and Suggested Reading 34

3 The Macroeconomy and Business Forecasts 36

3.1 Phases of the Business Cycle 36

3.2 Macroeconomic Models and Forecasting 39

3.3 Use of Macroeconomic Models at the Industry and Firm Level 40

Chapter Summary 42

References and Suggested Reading 44

4 Data Collection and Analysis in Forecasting 46

4.1 Preliminary Adjustments to Data 46

4.2 Data Transformation 52

4.3 Patterns in Time Series Data 58

4.4 The Classical Decomposition Method of Time Series Forecasting 60

Chapter Summary 91

Case Study 92

Review Questions 94

References and Suggested Reading 100

5 Forecasting with Smoothing Techniques 101

5.1 Naïve Model 102

5.2 Forecasting with Averaging Models 105

5.3 Exponential Smoothing Models 112

5.4 Higher Form of Smoothing 118

Chapter Summary 134

Case Study 135

Review Questions 140

References and Suggested Reading 144

Appendix: Use of Excel 146

6 Adaptive Filtering as a Forecasting Technique 149

Chapter Summary 158

Review Questions 160

References and Suggested Reading 163

7 Forecasting with Simple Regression 164

7.1 Regression Analysis: The Linear Model 166

7.2 The Standard Error of Estimate 173

7.3 Correlation Analysts 176

7.4 InferencesRegarding Regression and Correlation Coefficients 182

7.5 An Application Using Excel 185

7.6 The Assumptions of the Regression Model 190

7.7 Curvilinear Regression Analysis 194

Chapter Summary 200

Review Questions 200

References and Suggested Reading 204

8 Forecasting with Multiple Regression 206

8.1 Estimating the Multiple Regression Equation-The Least Squares Method 207

8.2 The Standard Error of Estimate 212

8.3 Multiple Correlation Analysis 213

8.4 Inferences Regarding the Regression and Correlation Coefficients 217

8.5 Validation of the Regression Model for Forecasting 222

8.6 Curvilinear Regression Analysis 237

8.7 Application to Management 239

Chapter Summary 240

Review Questions 241

References and Suggested Reading 244

9 Advanced Regression Methodologies in Forecasting 246

9.1 Proxy and Dummy Variables 246

9.2 Selection of Independent Variables 253

9.3 Lagged Variables 257

Chapter Summary 264

Review Questions 266

References and Suggested Reading 268

10 The Box-Jenkins Method of Forecasting 270

10.1 The Box-Jenkins Models 211

10.2 Forecasting with Autoregressive (AR) Models 271

10.3 Forecasting with Moving Average (MA) Models 219

10.4 Autoregressive Integrated Moving Average (ARIMA) Models 281

10.5 Trends and Seasonality in Time Series 281

Chapter Summary 300

Case Study 303

Review Questions 305

References and Suggested Reading 307

11 Communicating Forecasts to Management 309

11.1 Forecasts and Their Use in Managerial Decisions 309

11.2 Presentation of Forecasts to Management 309

11.3 The Future of Business Forecasting 313

Chapter Summary 314

References and Suggested Reading 314

Appendices 316

A Student t Distribution 316

B Critical Values for the F Distribution 318

C The Durbin-Watson Statistic 323

D Chi-Square (x2) Distribution 326

E Minitab Guide 328

Index 363

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