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E-raamat: Macroeconomic Survey Expectations

  • Formaat: EPUB+DRM
  • Sari: Palgrave Texts in Econometrics
  • Ilmumisaeg: 31-Dec-2018
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319972237
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Macroeconomic Survey ExpectationsSuurem pilt
  • Formaat: EPUB+DRM
  • Sari: Palgrave Texts in Econometrics
  • Ilmumisaeg: 31-Dec-2018
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319972237
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Why should we be interested in macroeconomic survey expectations? This important book offers an in-depth treatment of this question from a point of view not covered in existing works on time-series econometrics and forecasting. Clements presents the nature of survey data, addresses some of the difficulties posed by the way in which survey expectations are elicited and considers the evaluation of point predictions and probability distributions. He outlines how, from a behavioural perspective, surveys offer insight into how economic agents form their expectations.
1 Introduction
1(6)
References
4(3)
2 The Nature of Survey Expectations
7(18)
2.1 Survey Expectations Data Sources
9(1)
2.2 Forecast Horizons and Targets
10(2)
2.3 Individual and Aggregate Expectations
12(4)
2.4 Means and Combining Information
16(4)
2.5 Which Survey Data?
20(1)
References
21(4)
3 Working with the Forecast Data
25(12)
3.1 Calculating Moments from the Histograms
26(3)
3.2 Fitting Continuous Distributions to the Histograms
29(3)
3.3 Empirical Illustration: The US SPF Inflation Histograms
32(2)
References
34(3)
4 Assessing the Point Predictions
37(28)
4.1 Assessing the Accuracy of Point Forecasts
38(4)
4.1.1 Survey Expectations
38(2)
4.1.2 Model Forecasts
40(2)
4.2 Tests of Forecast Optimality or Rationality
42(4)
4.3 Tests in the Presence of Instabilities
46(2)
4.4 A Panel of Forecasters
48(5)
4.4.1 Testing Consensus Forecasts When Agents Are Rational
48(2)
4.4.2 Testing Consensus Forecasts When Agents Are Irrational
50(1)
4.4.3 Pooling or Individual Regressions?
51(2)
4.5 Testing for Optimality Under Asymmetric Loss
53(4)
4.6 A Brief Review of the Empirical Evidence
57(3)
4.6.1 Testing for Optimality
57(1)
4.6.2 Testing Allowing for Instabilities
57(1)
4.6.3 Testing Using a Panel of Forecasters
58(1)
4.6.4 Rationality and Asymmetric Loss
58(2)
References
60(5)
5 Assessing the Accuracy of the Probability Distributions
65(32)
5.1 Density Evaluation
66(2)
5.2 Density Comparison
68(3)
5.3 Evaluating Regions of the Densities
71(1)
5.4 Alternative Density Scoring Rules
72(1)
5.5 Benchmark Density Forecasts
73(5)
5.6 Empirical Results
78(15)
5.6.1 The Aggregate Distributions
78(7)
5.6.2 The Individual Distributions
85(5)
5.6.3 Robustness of the Results to the Assumptions
90(3)
5.7 Conclusion
93(1)
References
93(4)
6 Consistency of the Point Forecasts and Probability Distributions
97(26)
6.1 Calculating Bounds on the Central Moments of Histograms
99(3)
6.2 Inconsistency and Asymmetric Loss
102(6)
6.3 Rounding and the Reporting of Probability Forecasts
108(12)
6.3.1 The SPF Probabilities of Decline and Rounding
109(6)
6.3.2 The Consistency of the Decline Probability Forecasts and the Probability Distributions
115(2)
6.3.3 The Consistency of the Decline Probability Forecasts and the Probability Distributions Allowing That the Decline Probability Forecasts Have Been Rounded
117(1)
6.3.4 Rounding of Probability Forecasts and the Histogram Forecasts
118(2)
6.4 Conclusions
120(1)
References
121(2)
7 Macroeconomic Uncertainty: Surveys Versus Models?
123(22)
7.1 Measuring Survey Uncertainty
125(8)
7.1.1 Empirical Results
128(3)
7.1.2 Are Survey Forecasters Targeting True Values?
131(2)
7.2 Models for Inflation and Output Growth Uncertainty
133(5)
7.2.1 MIDAS Specification
134(4)
7.3 Empirical Results
138(2)
7.4 Conclusions
140(2)
References
142(3)
8 Behavioural Models of Expectations Formation
145(28)
8.1 Evidence of Disagreement Among Forecasters
147(2)
8.2 Adaptive Learning
149(3)
8.3 Models of the Expectations Formation Process: Sticky Information
152(3)
8.4 Models of the Expectations Formation Process: Noisy Information
155(2)
8.5 Extensions to Basic IR Models
157(3)
8.5.1 Heterogeneous Beliefs About Long-Run Outcomes
157(1)
8.5.2 Heterogeneous Precision of Signals
158(1)
8.5.3 Asymmetric Loss Functions
159(1)
8.6 Empirical Evidence
160(3)
8.7 Individual Forecasters
163(6)
References
169(4)
9 Expectations Shocks and the Macroeconomy
173(14)
9.1 Short-Run and Long-Run Identification Schemes in Structural VARs
174(4)
9.2 Identification by Maximizing the Contribution of a Shock to the Forecast-Error Variance Decomposition
178(3)
9.3 Expectations and Non-fundamental Shocks
181(1)
9.4 Expectations Shocks and Macroeconomic Fluctuations: Empirical Evidence
182(2)
9.5 Uncertainty Shocks
184(1)
References
185(2)
10 Postscript
187(4)
References
189(2)
Index 191
Michael Clements is Professor of Econometrics at the ICMA Centre, Henley Business School, University of Reading, UK. He is Series Editor of Palgrave Texts in Econometrics and Palgrave Advanced Texts in Econometrics, and has published extensively on time series econometrics, modelling and forecasting. 
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