In a time of unprecedented economic uncertainty, this book provides empirical guidance to the economy and what to expect in the near and distant future. Beginning with a historic look at major contributions to economic indicators and business cycles starting with Wesley Clair Mitchell (1913) to Burns and Mitchell (1946), to Moore (1961) and Zarnowitz (1992), this book explores time series forecasting and economic cycles, which are currently maintained and enhanced by The Conference Board. Given their highly statistically significant relationship with GDP and the unemployment rate, these relationships are particularly useful for practitioners to help predict business cycles.
Author(s): John B. Guerard
Publisher: Palgrave Macmillan
Year: 2022
Language: English
Pages: 665
City: Cham
Preface
Contents
About the Author
List of Figures
List of Tables
1 Economic Growth and Business Cycles in the U.S
1.1 Depression in the Late Nineteenth-Century U.S. Economy
1.1.1 The Panic of 1873
1.1.2 The Cycle of 1879–1885
1.1.3 The Cycle of 1885–1888
1.1.4 The Panic of 1893 and the Cycle of 1894–1897
1.1.5 Monetary Policy and Prices, 1890–1909
1.2 Mr. Fisher and the Purchasing Power of Money and Depressions
1.3 Post-War Economic History and Measuring U.S. Economic Growth
1.4 Our Path Ahead
2 Wesley Clair Mitchell: The Advent of U.S. And NBER Business Cycle Research
2.1 Mitchell’s Early Business Cycles Analysis: What Investors Needs to Know About the Cumulation of Prosperity
2.1.1 Mitchell’s Early Business Cycles Analysis: Prosperity Breeding Crisis
2.1.2 Mitchell’s Early Business Cycles Analysis: Crisis
2.1.3 Mitchell’s Early Business Cycles Analysis: Business Depression
2.1.4 Mitchell’s Early Business Cycles Analysis: Wider Aspects of Business Cycles
2.2 Mr. Mitchell and His Business Cycles and Unemployment
2.3 Mitchell’s Business Cycles Analysis at the NBER: Volume 1
2.4 Summary and Conclusions of Mr. Mitchell and His Business Cycles and His Business Cycles
3 Measuring Business Activity: An Introductions to the Contributions of Mr. Persons, Mr. Schumpeter, Mr. Haberler, and Mr. Eckstein
3.1 Mr. Persons and the General Business Conditions Index
3.2 Mr. Schumpeter and His Business Cycles
3.3 Mr. Haberler and Prosperity and Depression
3.3.1 Mr. Haberler and the Prosperity and Depression Phases
3.3.2 Mr. Haberler and His the Expansion and Contraction Phases
3.3.3 Mr. Haberler on Crisis and Revival
3.4 Econometric Modelling and Mr. Eckstein and His DRI Model
3.4.1 Mr. Eckstein: The DRI Model and the Business Cycle
3.5 Summary and Conclusions to the Contributions of Mr. Persons, Schumpeter, Haberler, and Eckstein
4 Mr. Burns and Mr. Mitchell on Measuring Business Cycles
4.1 Comments on Measuring Business Cycles
4.2 Mr. Burns on Mr. Mitchell and the Progress on Business Cycle Research
4.3 Summary and Conclusions of the Mr. Burns and Mr. Mitchell Business Cycle Research
References
5 Mr. Geoffrey Moore and NBER Business Cycle Research
5.1 Mr. Moore and his Business Cycles Indicators (1961)
5.2 Mr. Moore and his Business Cycles, Inflation, and Forecasting (1983)
5.3 What is a Recession?
5.3.1 Mr. Moore and His Leading Group Indicators
5.3.2 Unemployment
5.3.3 The Money Supply and Stock Prices
5.4 Mr. Moore and the Mildness and Shortness of Postwar Recessions
5.5 Mr. Moore and his Leading Indicators for the 1990s
5.6 Mr. Moore and Mr. Lahiri and Their Leading Economic Indicators (1991)
5.7 Mr. Zarnowitz and his Tribute to Mr. Moore: The Ms. Dua Volume
5.8 Summary and Conclusions
6 Mr. Victor Zarnowitz and Economic Forecasting, and NBER Business Cycle Research
6.1 Forecast Rationality
6.2 Absolute and Relative Forecast Accuracy
6.3 Extending the Mincer-Zarnowitz Forecasting Benchmark
6.4 Mr. Zarnowitz, the NBER, and Business Cycle Research in 1992
6.4.1 Mr. Zarnowitz and the Lists of Leading Indicators, 1950–1989
6.4.2 Econometric Model Simulations and Business Cycles
6.5 Mr. Zarnowitz and The Major Market Economies during the Post-World War II Period
6.5.1 Estimated Dimensions of Business Cycles in Eight Countries
6.5.2 Growth Cycles
6.5.3 Mr. Zarnowitz and Exogenous Business Cycle Variables: Money
6.5.4 Mr. Zarnowitz, Business Cycles and Expectational Shocks
6.5.5 What is a Business Cycle: Some General Conclusions
6.6 Summary and Conclusions
Appendix 6.1: Exponential Smoothing
References
7 Regression and Time Series Modeling of Real GDP, the Unemployment Rate, and the Impact of Leading Economic Indicators on Forecasting Accuracy
7.1 Estimating an Ordinary Least Square Regression Line
7.2 Estimating Multiple Regression Lines
7.3 Influential Observations and Possible Outliers and the Application of Robust Regression
7.4 Estimating Simple and Multiple Regression Models in SAS
7.4.1 Estimating OLS and Robust Regression Real GDP Models in SAS
7.4.2 Estimating OLS and Robust Regression Models of the Unemployment Rate in SAS
7.4.2.1 Estimation Six: The Unemployment Rate and WkUNCL OLS Model, 1959–2018
7.5 Estimating Robust Regression Simple and Multiple Regression Model in SAS
7.6 Estimating Automatic Time Series Models and Forecasting
7.6.1 Automatic Time Series Model Selection Using OxMetrics
7.6.2 Automatic Time Series Modeling of Real GDP Using Leading Economic Indicators (LEI), 1959–2020
7.7 Automatic Time Series Modeling of the Unemployment Rate Using Leading Economic Indicators (LEI)
7.8 Forecasting the Unemployment Series with Leading Indicators and Adaptive Learning
7.9 Concluding Remarks and Extensions
Appendix: OxMetrics Modeling in the COVID Period
BOLD Notes the Statistically Significant AR1 and LEI Coefficients and the WkUNCL Component Variables
BOLD Denotes Statistically Significant Coefficients on the AR1 and LEI and Its WkUNCL Components
References
8 Granger Causality Testing and LEI Forecasting of Quarterly Mergers and the Unemployment Rate
8.1 Causal Analysis for Economic Policy
8.2 Regression Modeling of Quarterly Mergers, Stock Prices, and the LEI
8.3 Time Series Model Selection and Granger Causality Modeling
8.4 Granger Causality Testing in the SCA System
8.5 Rolling Forecast Windows Modeling Efficiency
8.5.1 Rolling Windows and Real GDP with the LEI and Money Supply
8.6 Summary and Conclusions
References
9 Active Management in Portfolio Selection and Management Within Business Cycles and Present-Day COVID
9.1 The Risk-Return Trade-Off Work of Markowitz, Sharpe, and Elton and Gruber
9.1.1 Markowitz Optimization Analysis
9.1.1.1 A General Form of Portfolio Optimization
9.1.2 Multi-Beta Risk Control Models
9.1.3 The BARRA Model: The Primary Institutional Risk Model
9.2 Implementing Optimal Portfolio Selection
9.2.1 What We Knew in 1991 Tests of Fundamental Data
9.2.2 What We Learned After 1993
9.2.3 Markowitz Risk Modeling with Barra and Axioma Risk Models: Constructing Mean-Variance Efficient Frontiers
9.2.4 The Stone Mathematical Assignment Program Trade-off Curve
9.3 The Existence and Continued Persistence of Financial Anomalies, 2003–2108
9.3.1 Portfolio Selection Through Much of COVID
9.4 Summary and Conclusions
References
10 Testing and Forecasting the Unemployment Rate with the Most Current Data, TCB LEI, Data as of 11/05/2021
10.1 OLS Modeling of the PJD Unemployment Rate, TCB LEI 11052021 in 1959–11/2021
10.2 Robust Regression of the Modeling the PJD Unemployment Rate, TCB LEI 11052021
10.3 Robust Regression Estimations of the DUE, DLLEIL1, and DkWkUNCLL1 Relationships Using M, S, and MM-Estimations
10.4 OLS Modeling of the PJD Unemployment Rate, TCB LEI 11052021 in 1999–11/2021
10.5 Robust Regression of the Modeling the PJD Unemployment Rate, TCB LEI 11052021, 1999–11/2021
10.6 Automatic Time Series Modeling and Forecasting the PJD Unemployment Rate, the Application of OxMetrics to TCB LEI 11052021
10.7 Automatic Time Series Modeling and Forecasting the PJD Unemployment Rate, the Application of OxMetrics to TCB LEI 11052021 to the MZTT Post-publication Period, 1999–11/2021
10.8 Concluding Remarks and Extensions
References
11 Conclusions and Summary
11.1 Where Do We Go from Here?
Appendix: The Theory and Estimation of Regression, Time Series Analysis, and Causality Modeling of the Unemployment Rate and the Leading Economic Indicators (LEI)
Estimating an Ordinary Least Square Regression Line
Estimating Multiple Regression Lines
Influential Observations and Possible Outliers and the Application of Robust Regression
Time Series Modeling and the Forecasting Effectiveness of Transfer Functions
Basic Statistical Properties of Economic Series
The Autoregressive and Moving Average Processes
ARMA Model Identification in Practice
Forecasting Effectiveness of Time Series Modelling Using AutoMetrics to Estimate Breaks with Saturation Variables
Granger-Causality Modeling and Testing
Influential Observations and Outlier Detection
The U.S. Leading Economic Indicators
Identifying Influential Observations in a Regression
Selected References
Index
