Index
Essays in Honour of Fabio Canova
ISBN: 978-1-80382-636-3, eISBN: 978-1-80382-635-6
ISSN: 0731-9053
Publication date: 16 September 2022
This content is currently only available as a PDF
Citation
(2022), "Index", Dolado, J.J., Gambetti, L. and Matthes, C. (Ed.) Essays in Honour of Fabio Canova (Advances in Econometrics, Vol. 44A), Emerald Publishing Limited, Leeds, pp. 211-215. https://doi.org/10.1108/S0731-90532022000044A008
Publisher
:Emerald Publishing Limited
Copyright © 2022 Juan J. Dolado, Luca Gambetti and Christian Matthes
INDEX
Note: Page numbers followed by “n” indicate notes.
Adaptive expectations (see Backward-looking expectations)
Adjustment costs
, 125–126
Aruoba–Diebold–Scotti Index (ADS Index)
, 6
business conditions
, 6–7
chronology
, 21–24
Asymmetric co-kurtosis conditions
, 170
Asymmetric risks on forecasting distributions
, 198–202
Asymptotic efficiency of ML estimation
, 70
Autoregressive-moving-average model (ARMA model)
, 26
Auxiliary assumptions
, 118–119
Average continuous ranked probability scores (ACRPS)
, 40–41
Average log predictive scores (ALPS)
, 40–41
B-model
, 168
BAA-AAA spread
, 159
Backward-looking expectations
, 28
Bayes’ rule
, 32, 38
Bayesian algorithm for linear models
, 183
Bayesian estimation
methods
, 32
of skewed SVAR model
, 183–186
Bayesian inference
, 34
posterior analysis
, 34–39
Bayesian structural vector autoregressive model
, 183
Big data approaches
, 6
Brinca et al. (2016) multi-country BCA analysis
, 96–97
Business cycle
, 8
Business cycle accounting (BCA)
, 56 (see also Monetary business cycle accounting (MBCA))
economic relevance
, 93–97
estimated parameters
, 64–66
with investment adjustment costs
, 106–113
Iskrev (2010) test for strict and weak identification
, 68–71
Komunjer and Ng (2011) test for strict identification
, 66–67
methodology
, 57, 61–71
results
, 71–93
state space form
, 63–64
statistics for practitioners
, 97–102
Chari et al. (2007) BCA model
, 72–75, 79–85, 95–96, 106–107
Cholesky decomposition
, 39
Cholesky factorization
, 39
Cholesky identification scheme
, 181
Collinearity factor
, 63
Composite Indicator of Systemic Stress (CISS)
, 178
Consumption
, 159
Corporate bonds
, 149
spreads
, 140
Correlation
, 47–48
Counterfactual
, 191, 193
economies
, 94
Cramér-Rao lower bounds (CRLBs)
, 78
Cramér-Rao theorem
, 70
Density function
, 69
Disturbance smoothing
, 38–39
Disturbance-based parametrization
, 37
Dot plot
, 12–13
Durables spending
, 148–150
Dynamic equilibrium models, estimation of
, 2
Dynamic factor models
, 6
Dynamic stochastic general equilibrium (DSGE)
, 57, 62, 66, 98
Economic relevance
, 93
Brinca et al. (2016) multi-country BCA analysis
, 96–97
Chari et al. (2007) BCA model
, 95–96
Empirical distance
between DSGE models
, 101
measures
, 98–102
Estimated parameters
, 64–66
Euler equation
, 140
Euler method
, 101
Expectations hypothesis (EH)
, 140
of interest rates
, 146–148
FAVAR models
, 4
Financial variables
, 148–150
First-order necessary conditions
, 115–117
Fisher information matrix
, 63, 68–70
Folded normal distribution
, 182
Forecast metrics
, 40–41
Forecasting
, 27
function
, 32–34
Forward-Filtering-Backward-Smoothing recursions (FFBS recursions)
, 34
Forward-looking expectations
, 28
Forward-looking variables
, 160–161
Full path plot
, 12–13
Functional forms
, 118–119
Gaussian kernel
, 38
Gaussianity of structural shocks
, 167
GDP growth
, 178–179
GDP risks
, 178
Generalized method of moments (GMM)
, 166, 169–171
Gensys state space
, 123
adjustment costs
, 125–126
log-linearized equilibrium conditions
, 123–125
MBCA model
, 126–127
representation
, 127–135
Gibbs sampler
, 178
Granger’s lemma
, 29, 33
Great Financial Crisis
, 180
Great Recession
, 10, 161
exit
, 14–17
Hessian matrix
, 69
Historical shock decomposition
, 190–195
Hourly wage
, 159
Identification
, 62, 66–67
general principles of identification analysis
, 68–70
strength
, 70–71
Impulse response functions (IRFs)
, 143, 195–198
Industrial Production (IP)
, 19n14
Inflation expectations
, 47–48, 150–152
Inflation gap
, 29
Inflation risks
, 178
International Association of Applied Econometrics (IAAE)
, 1
Intratemporal optimality condition
, 116
Investment adjustment costs, BCA and MBCA model with
, 106–113
Iskrev (2010) test for strict and weak identification
, 68, 77, 110–113
Chari et al. (2007) BCA model
, 79–85
general principles of identification analysis
, 68–70
identification strength
, 70–71
preliminaries
, 68
Šustek (2011) MBCA model
, 85–93
J-test
, 170–171
Jarque-Bera test statistic
, 174n2
Jensen’s inequality
, 69
Kalman filter
, 68
Kalman smoother
, 19n11
Komunjer and Ng (2011) test for strict identification
, 66–67, 71, 106
Chari et al. (2007) BCA model
, 72–75, 106–107
Šustek (2011) MBCA model
, 75–77, 107–110
Kullback–Leibler distance (KL distance)
, 101
Lagrangian function
, 115
Later-vintage path
, 10–11
Left-invertibility
, 67
Leverage effect models
, 49–50n4
Local identifiability
, 98
Log-likelihood function of sample
, 68–69
Log-linearized equilibrium conditions
, 123–125
Long-term interest rates
, 145–146
Manufacturing and Trade Sales (MTS)
, 19n14
Markov Chain Monte Carlo algorithm (MCMC algorithm)
, 28
Maximum likelihood estimation (ML estimation)
, 57
Minimality
, 67
Model equations
, 118
Monetary business cycle accounting (MBCA)
, 57, 126–127
description
, 58–60
equilibrium conditions
, 60
with investment adjustment costs
, 106–113
operational model
, 60–61
prototype (M) BCA economy
, 58–61
Monetary policy
, 150–152
changes in conduct of
, 152
Multiple source of error (MSOE)
, 27, 30, 34
Multivariate skewed normal distribution (MSN distribution)
, 181
NBER recession chronology
, 19n10
News shocks
, 140
alternative news shock identification
, 162–164
data and VAR model
, 142–143
data sources and time-series construction
, 158–159
results
, 143–152
Nominal variables
, 159
Non-Gaussian distributions
, 171
Nowcasting
, 6
Nowcasts
, 27
construction, characteristics, and assessment
, 7
construction and updating
, 7–8
ex post characteristics
, 8
performance assessment
, 8–10
‘One-wedge-off’ economies
, 94
‘One-wedge-on’ economies
, 94
Operational model
, 119–120
Optimization problem of household
, 114
Orthogonal innovations
, 49n1
Out-of-sample results
, 41–46
Pandemic Recession
, 19n4
entry and exit
, 10
later-vintage path
, 10–11
real economic activity and COVID-19
, 14
real-time vintages
, 11–13
Parameters
, 122
Perfect collinearity
, 70
Personal consumption expenditure (PCE)
, 40
Point forecasts
, 40
Population
, 62
Posterior analysis
, 34–39
Precision-based algorithms
, 50n14
Precision-based samplers
, 28
Price index measure
, 29
Rational expectations (see Forward-looking expectations)
Real economic activity
, 6
great recession exit
, 14–17
nowcast construction, characteristics, and assessment
, 7–10
pandemic recession entry and exit
, 10–14
Real interest rates
, 148–150
Real variables
, 159
Real-time vintages
, 11–13
Recession
, 8
Reduced source of error (RSOE)
, 27, 30, 34, 49n2
Relevant moment selection criterion (RMSC)
, 170
Representative consumer
, 114
first-order necessary conditions
, 115–117
Lagrangian function
, 115
optimization problem of household
, 114
Representative producer
, 117
optimization problem of firm
, 117
Robustness
, 48
Root mean square forecast errors (RMSFE)
, 40
s-lag M-variable SVAR model
, 180
Sensitivity, lack of
, 69
Sensitivity factor
, 63
Short-run response
, 143–144
Short-term interest rates
, 145–146
Single source of error (SSOE)
, 27, 30, 34
Skewed shocks
Bayesian estimation of skewed SVAR model
, 183–186
SVAR model with
, 179–186
Skewness
, 178
Small-data approaches
, 6
Snapshots
, 11
State correlation
, 32–34
State space form
, 63–64
States
, 27, 29
Statistics for practitioners
, 97
empirical distance measures
, 98–102
Steady state
, 120–121
Stepsize
, 136–138
Structural shocks
, 185
Structural vector autoregressive models (SVAR models)
, 2, 165, 178
additional figures
, 207–210
application to US labour market
, 169–172
estimated monthly real GDP growth
, 206
model
, 167–169
sign-identified
, 166
with skewed shocks
, 179–186
tracking macroeconomic tail risks in Euro area
, 186–202
Survey of Professional Forecasters (SPF)
, 48
Šustek (2011) MBCA model
, 75–77, 107–110
Symmetric co-kurtosis condition
, 170
Taylor-type nominal interest rate setting rule
, 57
Three-equation system
, 29
Time-varying coefficients VAR models
, 2
Tobin’s Q
, 159
Total factor productivity (TFP)
, 140–141
Tracking macroeconomic tail risks in Euro area
, 186
data and model specification
, 186–188
evolution of skewness in
, 188–190
macroeconomic impact of time varying skewness
, 190–202
Trend inflation
, 27
Trend inflation
, 47–48
Unobserved components models (UC models)
, 26–30
Bayesian inference
, 34–39
evaluation
, 40–49
modelling state correlation
, 30–32
state correlation and forecasting function
, 32–34
and state correlation assumptions
, 31
US Pandemic Recession
, 17
Variables
, 122
Vector autoregression model (VAR model)
, 140
specification for Minnesota prior in
, 159–160
Vector moving average (VMA)
, 98
Wedges
, 56
Workhorse nowcasting approaches
, 6
Wu-Xia shadow rate
, 159
Zero-impact response of TFP
, 154n11
- Prelims
- Introduction
- Chapter 1: Real-Time Real Economic Activity: Entering and Exiting the Pandemic Recession of 2020
- Chapter 2: State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models
- Chapter 3: On Identification Issues in Business Cycle Accounting Models
- Chapter 4: The Effect of News Shocks and Monetary Policy
- Chapter 5: Statistical Identification of Economic Shocks by Signs in Structural Vector Autoregression
- Chapter 6: Skewed SVARs: Tracking the Structural Sources of Macroeconomic Tail Risks
- Index