Index
Essays in Honor of Cheng Hsiao
ISBN: 978-1-78973-958-9, eISBN: 978-1-78973-957-2
ISSN: 0731-9053
Publication date: 15 April 2020
This content is currently only available as a PDF
Citation
(2020), "Index", Li, T., Pesaran, M.H. and Terrell, D. (Ed.) Essays in Honor of Cheng Hsiao (Advances in Econometrics, Vol. 41), Emerald Publishing Limited, Leeds, pp. 445-457. https://doi.org/10.1108/S0731-905320200000041017
Publisher
:Emerald Publishing Limited
Copyright © 2020 Emerald Publishing Limited
INDEX
Index
Note: Page numbers followed by “n” indicate notes.
A + B auctions
, 288
Ad position auctions, application to
, 331
click-through curve
, 332
data
, 331–332
estimation results
, 333–335
model specification
, 332–333
Advanced placement (AP)
, 367
AIC criterion
, 74, 76, 78–80, 84–85, 87, 89
Allocation
, 324
latent Dirichlet
, 435
observed
, 326
optimal
, 325–328
American Express Inc. (AXP)
, 133
Arellano–Bond type GMM
, 2
dynamic panel model and
, 3
estimation and asymptotical bias
, 3–6
JIVE estimation
, 6–7
JIVE for Arellano–Bond GMM estimation
, 19–24
Artificial intelligence (AI)
, 414, 416–417, 425, 431
big data and growing engagement of economics with
, 425
Asymptotic bias of Arellano–Bond GMM
, 3–6, 17n2
Asymptotic theory
, 75
of indirect inference estimator
, 83
Augmented Dickey-Fuller specification (ADF specification)
, 230
Automatic differentiation
, 435
Autoregressive coefficient (AR coefficient)
, 75
Autoregressive fractionally integrated moving average (ARFIMA)
, 106
Autoregressive model (AR)
, 107
Average pairwise housing return correlations
, 387
Average partial effects (APEs)
, 365
Average treatment effect (ATE)
, 344, 348
Backward sequential testing procedure
, 111
Bagging
, 433–434
Bailey, Kapetanios, and Pesaran approach (BKP approach)
, 155
Barro regressions
, 222
Bartlett–Newey–West estimator
, 32, 58
Baumeister and Hamilton model (BH model)
, 162
Bayesian approach
, 223
Bayesian deep learning
, 435
Bayesian equilibrium
, 292
Bayesian estimation
, 326
likelihood of optimal allocation and equilibrium prices
, 326–328
MCMC algorithm
, 328–331
Bayesian framework
, 145
Bayesian Gaussian semiparametric model
, 231
Bayesian model averaging (BMA)
, 218, 434
Bayesian neural networks
, 435
Bayesian semiparametric model
growth model
, 219
with random coefficients
, 222–224
Bayesian variable selection technique
, 434
Beta distribution
, 333
Beta selection
, 328
β-convergence
, 26
Bias
asymptotic
, 3–6, 17n2
simple alternative of estimating
, 280–281
Bias-corrected tail-trimmed estimator
, 262–265
interquartile range against simulation size
, 268
sampling distributions
, 270
BIC
, 74, 76, 78–80, 84, 87, 89
Bidders’ cost
function
, 298
inefficiency distribution
, 298
Bidding firms
, 289
Bidding strategies
, 295–298, 304, 319n6
rewriting
, 299–300
Big data (BD)
, 413, 431
econometrics and
, 414–419, 425–429, 431–438
and growing engagement of economics with AI
, 425
interaction between economic or financial theory and
, 414–415
Binary Logit Model
, 368
Binary models for college attendance
, 365–371
Bivariate truncated normal distribution
, 393–394
Block approach
, 417
Boosting
, 433–434
Bootstrapped nonparametric
specification test for RCM_CT against OWEC_CST
, 253
test for common trends
, 251–253
Bootstrapping
, 433–434
procedure for global shock effects
, 181–182
Borrower defaults
, 393–394
Break-adjusted forecasting method 132–133
Buyer
benefit function
, 298
decision rule
, 289
private
, 292–294
public
, 294–295
Buyer’s optimal mechanism
, 290–291
firm’s IC and IR constraints
, 291–292
private buyer
, 292–294
public buyer
, 294–295
Calibration
calibrated polynomial function
, 205–206
estimates of calibrated trending functions
, 213–214
of semiparametric estimated trends
, 199–200
Causality testing
, 426
CD statistic
, 387, 391
Censored normal distributions
, 407–411
Censored variables
, 393
Choice sets
, 363
Citigroup system (C system)
, 133
Classification and regression trees (CART)
, 432, 434
Click-through curve
, 332
Cobb–Douglas aggregate production function
, 218–219
Coefficient estimation
, 201–203
estimation results of coefficients
, 203
panel data unit root test statistics
, 202
Column standardization
, 362
Common correlated effect (CCE)
, 194
estimates of βi
, 210–211
estimator
, 197
Computer-Assisted Personal Interviewing (CAPI)
, 343
Computer-Assisted Telephone Interviewing (CATI)
, 343
Conditional mean independence
, 301
Conventional HAC methods
, 28
Conventional structural break tests
, 107
Conventional t-statistic
, 29
Convergence
, 362
studies
, 26
Coordinate ascent variational inference
, 435
Correlation
, 410
average pairwise housing return
, 387
latent
, 384
matrix
, 406
Correlograms
, 391
Cost function
, 301
multiplicative separability of
, 289, 300
Cost inefficiency
, 289
Country-specific effects of global shocks
, 157–159
Country-specific models
, 144, 182
Covariance matrix
, 133, 397
Covariogram
, 391–392
CPR
, 155, 157
Cross-section (CS)
augmentation
, 165
averages
, 144
Cross-sectional augmented IPS test (CIPS test)
, 230
unit root tests
, 231
Cross-sectional dependence (CSD)
, 155, 195, 197, 201, 384
empirical measures
, 390
exponent
, 389
weak vs. strong
, 387–391
Cross-validation
, 432
CS-MSAs
, 385–387, 403n1, 405–406
Cubic B-splines
, 227
interpolation
, 240n18
Cubic O’Sullivan splines
, 240n10
Cultures
, 428–429
in statistics
, 426–427
Data analysis in econometrics
, 432
Data driven method
, 416
Data generating processes (DGPs)
, 2, 76, 112, 131
Debt
accumulation
, 145–146
debt-generating fiscal policy
, 146
elasticities
, 163–165
and growth
, 146–148
monetization
, 172n12
Debt-to-GDP series
, 150, 183
Deep learning
, 426
Deep mixture model
, 438
Defaulted loan
, 394
Density function
, 272n1
Determinants of HCE
, 193–194
data
, 200–201
models
, 194–200
results
, 201–207
Deterministic utility component
, 363
Digital single-lens reflexive camera (DSLR camera)
, 334
Dimension reduction
, 417–418
Direct effect (DE)
, 360, 362
Discrete choice models
, 256
Distribution free
, 194
Double selection problem
, 345
Dual problem (DP) (see also Linear sum assignment problems (LSAP))
, 326–327, 331, 338
Dynamic panel model
, 2
JIVE for Arellano–Bond GMM estimation
, 19–24
model and Arellano–Bond GMM estimation
, 3–7
model with exogenous variables
, 7–10
Monte Carlo simulation
, 10–16
Dynamic spatio-temporal data
, 437
Easy-to-implement method
, 107
Econometric(s)
, 431
analysis
, 417
approaches
, 132
BD
, 425–429, 431–438
BD and
, 414–419
combining data of different sources and time frequencies
, 418
data analysis in
, 432
dimension reduction
, 417–418
functional dynamics
, 418
incorporating AI and machine learning techniques
, 416–417
methodological challenges
, 416–419
modeling interactions among individuals, multiple equilibrium
, 419
multi-dimensional asymptotics
, 417
one stage modeling or multistage modeling
, 419
one-dimensional asymptotics
, 417
reduced form vs. structured equation approach
, 419
of scoring auctions
, 288–318
techniques
, 26
Economic
decision-making
, 428
efficiency
, 222
efficiency change (see Technical innovation change)
shock
, 398–399
theory
, 146, 414–415
Elastic nets
, 432
Elasticity
, 203
Empirical analysis
, 26
Empirical assignment model
, 324–326
Empirical rejection frequency (ERF)
, 15
Equilibrium prices
, 324–326, 338
Error cross-sectional dependencies
, 147
Error-correction models
, 418
Evidence lower bound (ELBO)
, 225–226, 235, 240n13
variational
, 248–250
Exchangeability
, 307
Exogenous quality
, 289–290
Exogenous variables, dynamic panel model with
, 7–10
Expansionary fiscal policies
, 146
shock
, 147
Expected returns
, 397
Explosive models, model selection for
limit properties based on indirect inference estimator
, 82–86
limit properties based on OLS estimator
, 76–82
models, information criteria, and literature review
, 75–76
Monte Carlo study
, 87–89
proof for theorems
, 92–103
UR behavior
, 74
Explosive roots (EXs)
, 74
Exponent of cross-sectional dependence
, 389
External debt
, 146
Extreme bounds approach
, 426
Factor
approach
, 417
augmented regressions
, 434
mixture analysis
, 438
mixtures of factor analyzers
, 437–438
models
, 434
Factor-augmented panel
VaR models
, 148–150
vector error-correcting model
, 144
Factor-augmented regressions
, 218–219
Federal Housing Finance Agency (FHFA)
, 385
Fee-for-service (FFS)
, 193
Financial crisis (2007–2008)
, 144
Financial theory
, 414–415
Firewall principle
, 432
Firm’s IC and IR constraints
, 291–292
Fiscal policy shocks (see also National shocks)
country-specific effects of global shocks
, 157–159
estimated global shocks
, 157
evidence on CS dependence
, 155–157
expansionary fiscal policy shock
, 147
FEVDs and IRFs of global shocks
, 159–160
global output and fiscal policy shocks and effects
, 154
robustness of global shocks analysis
, 160–161
Fiscal shock
contemporaneous effects of
, 165–170
priors used for estimating effects of
, 182–183
Fitted model
, 32
Fixed effect (FE)
, 192, 194, 202, 240n9
Fixed-b
approach
, 49n1
lag truncation rule
, 28
variance estimation
, 33
Florida procurements
, 290
Forecast error variance decomposition (FEVD)
, 159
of global shocks
, 159–160
for sets of global and national shocks
, 181
Forecasting methods
, 112
comparison break occurs at end of sample
, 131–132
comparison of forecasting methods
, 115
optimal weighting averaging approach
, 114
post-break approach
, 112
simulation design I
, 115–129
simulation design II
, 129–131
VAR approximation approach
, 114
VNV method
, 113–114
VNVNO method
, 112–113
Forecasting multivariate realized volatility
, 132
break-adjusted forecasting method
, 132–133
h-step ahead forecasts
, 133
out-of-sample forecast evaluation
, 135–136
relative root mean squared forecast errors
, 134
Forecasting univariate time series
, 106
Forward chaining
, 433
Fraternal twins
, 414
French National Space Agency (CNES)
, 318
Full Bayesian model
, 224
Functional dynamics
, 418
Functional principal component analysis (FPCA)
, 437
Functional regression analysis
, 418
Functional time series
analysis
, 418
theme of
, 436–437
Gamma function
, 250
Gaussian distribution
, 269
Gaussian kernel function
, 196, 198
Gaussian mixture models
, 438
GDP per capita
, 201–202, 218
MCMC results for growth rate model for
, 234
MFVB results for growth rate model for
, 234
time means of MFVB spline fit of growth rate
, 236
General Electric (GE)
, 133
Generalized cost
, 294
Generalized method of moments (GMM)
, 2
Generalized Pareto distribution
, 257–258
Generalized social cost
, 295
Generic sequentially adaptive Bayesian learning algorithm
, 435
Genetic factors
, 414
Gibbs sampling
, 219, 224
Global business
, 147
Global factor-augmented error-correcting model
, 175–181
Global growth shock
, 145
Global shocks
, 144–145
bootstrapping procedure for effects
, 181–182
country-specific effects of
, 157–159
estimation
, 157
FEVDs
, 159–160, 181
IRFs
, 159–160
robustness of global shocks analysis
, 160–161
Global value at risk (GVAR)
, 144, 419
additional result tables and figures
, 184–185
bootstrapping procedure for global shock effects
, 181–182
comparison of parameters across countries in models
, 189
data
, 183–184
estimates of long-run relationships between real GDP and public debt
, 186–187
estimating effects of national fiscal and technology shocks
, 182–183
FEVDs for sets of global and national shocks
, 181
global output and fiscal policy shocks and effects
, 154–161
global shocks
, 144–145
literature on debt and growth
, 146–148
long-run perspective on public debt and output
, 150–154
national shocks
, 161–170
representation of factor-augmented panel VaR models
, 148–150
representation using global factor-augmented error-correcting model
, 175–181
SEs of reduced-form shocks
, 188
Gross domestic product (GDP)
, 144, 147, 192, 203, 218
country means of the growth rate
, 228
Growth empirics
, 239n1
Bayesian semiparametric model with random coefficients
, 222–224
data
, 227–231
mean field variational Bayes approximation
, 224–227
model
, 219–222
results
, 231–238
Guerre, Perrigne, and Vuong approach (GPV approach)
, 289
Half-Cauchy priors
, 240n10
Health care
, 192
Health care expenditure (HCE) (see also Determinants of HCE)
, 192–193
Heterogeneity
, 203
cross-country
, 218
Heteroskedastic and autocorrelation consistent (HAC)
, 27
Heteroskedastic and autocorrelation robust estimators (HAR estimators)
, 27
assumptions
, 52
convergence
, 27–28
generating mechanism under null hypothesis
, 53–72
Monte Carlo simulations and empirical example
, 42–48
preliminaries on robust inference concerning trend
, 28–29
robust testing
, 32–42
testing convergence
, 29–32
High speed rail projects in China
, 416
High-dimensional asymptotic theorems
, 417
High-dimensional asymptotics
, 436
High-impact journals
, 431–432
Historical Public Debt database
, 183
Holdout cross-validation
, 432
Home Depot Inc. (HD)
, 133
House price indices (HPIs)
, 385–386
HQIC
, 74, 76, 78–80, 84, 87
Hsiao’s volumunus work on random coefficient models
, 239n5
Hyperparameters
, 432–433
Hypothesis tests
, 426, 432
Hysteresis
, 146
IBM/SPSS Modeler
, 427
Identical twins
, 414
Identification argument
, 304
Idiosyncratic shocks
, 161, 361
Importance sampling
, 256–257
bias-corrected tail-trimmed estimator
, 262–265
density
, 257
future research
, 271–272
illustration
, 269–271
Monte Carlo experiments
, 265–268
tail-trimmed estimator
, 259–262, 268
testing for existence of variance
, 257–259
Importance sampling estimator
, 257
interquartile range against simulation size
, 268
sampling distributions
, 266–267, 270, 284–285
Incentive compatibility (IC)
, 291–292
Income
, 193
Income elasticity (IE)
, 192
Independent component analysis
, 437
Indirect effect (IE)
, 360, 362
Indirect inference estimator
, 82–86
Individual rationality (IR)
, 291–292
condition
, 326
Inequality
, 241n30
Inferential robustness
, 27
Infinite dimensional functions
, 437
Information criteria
, 87
for model selection
, 74–76
Instrument matrix
, 19
Integer programming problem
, 325
Intermediate order sequence
, 260
International Business Machines (IBM)
, 133
International Conference on Machine Learning (ICML)
, 428
International Monetary Fund (IMF)
, 183
FAD
, 183
Interpretability of ML model results
, 427–428
IRFs of global shocks
, 159–160, 165
Jackknife instrumental variables estimation (JIVE)
, 2, 6–7
for Arellano–Bond GMM estimation
, 19–24
JPMorgan Chase & Co. (JPM)
, 133
k-fold
, 432
cross-validation or bootstrapping
, 427
Kalman filter
, 270
Kernel methods
, 416
Kernel-based nonparametric estimators
, 289
Kronecker product
, 195
Kullback–Leibler divergence
, 225
L’Hopital’s rule
, 275, 277, 319n6, 408
Labor augmenting technical progress
, 220
Lagrange multipliers
, 326
λ estimation
, 315–316
Language information
, 432
LARS
, 432
LASSO
, 432, 434, 436–437
Latent correlation
, 384
Latent Dirichlet allocation
, 435
Latent structure approach
, 417
Least squares (LS)
, 107
estimators
, 199
Lee and Wand’s approach
, 221
Likelihood
of optimal allocation and equilibrium prices
, 326–328
ratio framework
, 172n20
Limit theory
, 59
under alternative of convergence
, 36–42
under null
, 34–35
Linear discriminant analysis
, 437
Linear programming relaxation
, 325
Linear regression model
, 427
Linear stochastic frontier panel models
, 221
Linear sum assignment problems (LSAP)
, 323–324
application to Ad position auctions
, 331–335
Bayesian estimation
, 326–331
empirical assignment model
, 324–326
Linear trend regression method
, 27
Linear-mixed Gaussian specification
, 223
model-based penalized spline specification
, 226
Loans
mortgage
, 384
risk of
, 385
Local-currency-denominated debt
, 172n6
Local-to-unity explosive (LTUE)
, 75, 85
Log-likelihood
, 362
Long memory models
, 106
Long run variance (LRV)
, 30
Long-run perspective on public debt and output
, 150–154
Loss function
, 196, 417
Lovell rule
, 426
Machine learning (ML)
, 426, 431, 435
algorithms
, 432
interpretability of ML model results
, 427–428
tool of elastic nets
, 426
Machine learning techniques
, 416–417
Markov Chain Monte Carlo methods (MCMC methods)
, 218–219, 221, 224, 233, 240, 269, 271, 323–324
approximate posterior density functions
, 235
results for growth rate model for GDP per capita
, 234
Markowitz mean-variance scheme
, 415
Matrix completion approach
, 434–435
Maximand
, 293
Maximum likelihood estimation (MLE)
, 106
Mean field variational Bayes
algorithm
, 248–250
approximation
, 224–227
Mean field variational Bayesian approach (MFVB approach)
, 219, 225, 233, 240
approximate posterior density functions
, 235
flexibilities
, 238
results for growth rate model for GDP per capita
, 234
Methods-of-Payment survey (MOP survey)
, 343–344, 349
factual/objective
, 353
recall
, 353–354
subjective
, 354
Mildly explosive model (ME model)
, 75
Mixed-mode surveys
, 342
Model primitives
, 289
Model selection approach
, 417
Model uncertainty
, 438
Model-based multivariate time-series clustering algorithm
, 437
Moment matching estimators
, 324
Monte Carlo experiments
, 265–268
Monte Carlo simulations
, 10–16, 42–44, 107, 363
and empirical example
, 42, 44
state unemployment rates
, 44–48
Monte Carlo study
, 87–89, 256
Mood test
, 427
Mortgage loans
, 384
Mortgage portfolio diversification
, 384
average pairwise housing return correlations
, 387
data
, 385
empirical dependence
, 385–393
housing return correlations
, 388
portfolio implications
, 397–399
simulations
, 399–401
theory
, 393–397
Mulinomial models for post high school choice
, 371–379
Multi-dimensional asymptotics
, 417
Multicollinearity
, 418
Multinomial choice
model
, 289, 301
probability
, 306
Multinomial Logit Model
, 372
Multiple testing estimator
, 434
Multiplicative separability of cost function
, 289, 300
Multistage modeling
, 419
Multivariate case
, 276–279
Multivariate GARCH models
, 132
Multivariate long memory models
, 106–108
Multivariate LS coefficient estimator
, 107
Multivariate volatility forecasting
, 132
“Naïve-no break” method (VNVNO method)
, 112–113, 124, 129
National shocks
, 161
debt elasticities
, 163–165
demand-supply model
, 162–163
effects of fiscal and technology shocks
, 165–170
FEVDs for sets of
, 181
Negative Hessian
, 270
Nested propensity score
, 345
No-blocking-pair condition
, 326
Non-nested propensity scores
, 345
Non-transferable utility matching models
, 324
Nonlinearities
, 146
Nonparametric
approaches of nearest neighbor matching
, 416
estimation methods
, 239n6
strategy
, 302
studentization
, 33–34
Nonspatial models
, 369
Nonstationarity
, 74
Normal density function
, 407
Null and alternative hypotheses
, 32–33
Numerical integration
, 363
Observed allocation
, 326
OLS estimator
, 74, 84–85, 87, 90, 96
limit properties based on
, 76–82
One covariate at time multiple testing (OCMT)
, 434
One stage modeling
, 419
One-dimensional asymptotics
, 417
Optimal allocation
, 325
Optimal discriminant analysis
, 433
Optimal q-densities
, 225
Optimal scoring rule
, 290–291, 295–298
Optimal transport problems
, 324
Optimal weighting averaging approach
, 114
Optimal-in-sample goodness-of-fit
, 111
Organization of Economic Cooperation and Development countries (OECD countries)
, 192
Orthogonalized LS
, 149
Out-of-sample forecasts
, 207–209
Overfitting problem
, 432
p-values of “final” regression model
, 426
Paradata
, 342–343
Parameter instability
, 433
Parametric
equilibrium selection rule
, 327
estimation
, 194
fitting
, 212
Partial effects evaluated at sample averages (PEA)
, 365
Partially linear models
, 194
Peer effects
, 360
accounting for
, 367
evidence
, 365
measuring
, 360–361
Penalized models
, 432
Penalized splines
, 240n8
Policymakers
, 415
Pooled common correlated effect (CCEP)
, 202–203
Pooled semiparametric profile likelihood dummy variable method (PPLE)
, 194–198, 202–204
Pooling
, 310–313
Portfolio loss
, 398
Position auctions
calculating volume of Equilibrium CPC
, 339
characterizing set of equilibrium CPC
, 338–339
implementation details in empirical study of
, 338–339
Post-break method (PB method)
, 112
Post-break model
, 107
Postal Self-Administered Questionnaires (Postal SAQs)
, 343
Pre-break observations
, 433
Predata
, 342–343
identification with
, 344–349
Prediction
, 415, 432, 436
Predictor importance measures
, 427–428
Price vector
, 326
Price-per-quality rules
, 289
ratio rule
, 288
Primal problem (P problem)
, 327
Primary data
, 342
Principal component (PC)
, 144, 388
Principal coordinates analysis
, 437
Private buyers
, 288, 292–294
Private effect (see Direct effect (DE))
Probabilistic computation tree logic models
, 437
Probabilistic principal component analysis
, 437
Probability kernel function
, 198
Procurement auctions
, 288
Pseudo maximum likelihood estimates
, 363
Public buyer
, 294–295
Public debt
accumulation
, 147
crisis
, 172n6
long-run perspective on
, 150–154
Public financing (PF)
, 192
Public procurements
, 288
Purchasing power parity (PPP)
, 155, 227
Qualitative information
, 417
Quantile approach
, 416
Quantile treatment effect (QTE)
, 344, 348
Quasi-Bayesian form of cross-validation
, 433
Quasi-linear rules
, 289
Quasi-linear scoring rule
, 288
R-continuously differentiable
, 306–307
Random coefficients
, 222–224, 417
Random effect
, 240n9
Random forest algorithm
, 416
Random intercept and slope coefficients with common trends (RCM_CT)
, 232–233
bootstrapped nonparametric specification test against OWEC_CST
, 253
Random intercept and slope coefficients with country-specific trends (RCMCST)
, 232
Random utility
, 361
Realized covariance methods
, 132
Regional science
, 385
Regressions
, 27
errors
, 28
Relative RMSFE
, 122–124, 134
Repeat-sales framework
, 386
Research Data Centers (RDCs)
, 425
Residual sum of squares (RSS)
, 106
Response time
, 415
Reward point balance
, 350–351
Risky loan
, 394
Robo-advising
, 432
Robo-investors
, 432
Robust optimal weight averaging method
, 107
Robust optimal weighting forecasting procedure (ROW)
, 112, 132
Robust structural break test
, 106
Robust testing
, 32
limit theory under alternative of convergence
, 36–42
limit theory under null
, 34–35
null and alternative hypotheses
, 32–33
test statistics and alternative nonparametric studentization
, 33–34
Robustness
, 348–349
checks
, 284–285
of global shocks analysis
, 160–161
Rolling window forecast technique
, 207
Rolling-origin (see Forward chaining)
Root mean squared forecast errors (RMSFE)
, 122–124
Row standardization
, 362
S&P 500 index
, 269
Satellite data
, 431–432
Scoring auctions, econometrics of
, 288–289
estimation
, 305–316
extensions
, 316–318
identification
, 298–305
model
, 290–298
Scoring rules
, 288
Selection effects
, 342
(Semi-)strong dependence
, 388
(Semi-)variogram
, 391–393
Seminonparametric estimator
, 315
Seminonparametric strategy
, 302
Semiparametric estimation
, 194, 239n6
calibration of
, 199–200
of trends
, 198–199
Semiparametric models
, 221, 239n6
Semiparametric nonlinear errors-in-variables models
, 239n6
Semiparametric one-way error component models with common trends (OWEC_CT)
, 232
Semiparametric one-way error component models with country-specific trends (OWEC_CST)
, 232
bootstrapped nonparametric specification test for RCM_CT against
, 253
Semiparametric panel data models
, 239n6
Semiparametric VAR(k) model
, 121
Series methods
, 416
Shapley–Shubik model
, 324
σ-convergence
, 26–27, 31
Simple linear trend regressions
, 29–30
Simulations
, 399–401
Skew-normal models
, 438
Skew-t mixture models
, 438
Slow variation
, 272n1
Smooth vs. abrupt changes
, 418
Smoothed function
, 232
Smoothness assumptions
, 306
Social effect (see Indirect effect (IE))
Social programs, evaluating or simulating impacts of
, 416
Social surplus
, 325
Solow residual (see Total factor productivity (TFP))
Spatial approach
, 419
Spatial Binary Logit Model
, 369–370
Spatial dependence (see also Cross-sectional dependence)
, 384, 391–393
Spatial econometrics
, 385
approach
, 361
models
, 161
Spatial models
, 369
Spatial multinomial logit choice model
, 360
data
, 364–365
direct and indirect impacts
, 363
estimation
, 362–363, 365–379
model
, 360–362
Spatial random utility
, 361–362
Spatial weight matrix
, 361
Spherical model
, 391
Spherical semivariogram
, 392
Spike-and-slab priors
, 437
Spike-and-slab regression (see Bayesian variable selection technique)
Stable matching
, 326
Stationarity
, 192
Statistical inference
, 417
Statistical modeling
, 426
Stochastic gradient descent
algorithm
, 435
computational technique
, 416–417
Stochastic volatility
, 256
model
, 269
Structural breaks
, 106–108, 113, 118, 121, 131–133, 433
Structural econometric model
, 305–307
Structured equation approach
, 419
Subjective survey questions
, 342
Summarization
, 432
Sup–Wald test
, 130
Survey design
, 342
identification with predata
, 344–349
MOP survey
, 349–354
Symmetric matrix
, 4
square matrix
, 361
Tail-trimmed estimator
, 259–262, 268
bias-corrected
, 262–265
Tax ratio
, 222
Technical innovation change
, 221
Technology shock
contemporaneous effects of
, 165–170
priors used for estimating effects of
, 182–183
Test statistics
, 252
Testing convergence using HAR inference
, 29–32
Texas Higher Education Opportunity Project (THEOP)
, 360, 364
Threshold approach
, 417
Time series
, 106
of cross-sectional averages
, 389
model specification
, 198
Total effect (TE)
, 363
Total factor productivity (TFP)
, 218–219, 237
regression-based estimation
, 239n5
Traditional “hill climbing” computational approach
, 417
Traditional cross-validation
, 433
Traditional econometric models
, 414
Traditional location prediction models
, 437
Training-testing-validation methodology
, 432
Trends
regression misspecification
, 27
semiparametric estimation of
, 198–199
study of trending functions
, 203–207
Tri-diagonal matrix
, 6
Trimmed estimated cost inefficiencies
, 309
Truncated normal distributions
, 407–411
Two-fold dimension reduction approach
, 437
Two-sided matching
markets
, 323
models
, 324
Two-stage approach
, 387
Type I Extreme Value distribution (TIEV distribution)
, 361
Uniform distribution
, 333
Uniform selection
, 328
Unit-root behavior (UR behavior)
, 74
Univariate AR approximation-based forecast
, 133
Univariate framework
, 106
Univariate long memory process
, 140–141, 275
Urban economics
, 385
Valuation matrix
, 324
Value at Risk approach (VaR approach)
, 398
approximation approach
, 107, 114
comparison of forecasting methods
, 115–132
forecasting methods
, 112–115
forecasting multivariate realized volatility
, 132–136
model and theoretical insights 108–112
multivariate long memory models
, 106–108
proof of Lemma
, 141
simulation and empirical support
, 140–141
VAR(k) approximation-based forecasting
, 138
Vandermonde determinant
, 303
VAR-RV-Break model (VRB model)
, 133
VARFIMA-based forecast method (VNV method)
, 112–114
Variables
, 250–251
Variance, testing for existence of
, 257–259
Variational Bayesian inference
, 224
Variational evidence lower bound
, 248–250
Variational inference algorithms
, 227
Variogram measure
, 391–392
Vector autoregressive fractionally integrated moving average (VARFIMA)
, 106–107, 109
Virtual cost
, 289, 294, 302
Weak σ-convergence
, 26, 30–31, 36
Web Self-Administered Questionnaires (Web SAQs)
, 343–344
Weighted linear scoring rule
, 290
Wilcoxon–Mann–Whitney test
, 427
Winning probability
, 307, 317
- Prelims
- Chapter 1: Correction for the Asymptotical Bias of the Arellano-Bond type GMM Estimation of Dynamic Panel Models
- Chapter 2: Testing Convergence Using HAR Inference
- Chapter 3: Model Selection for Explosive Models
- Chapter 4: A VAR Approach to Forecasting Multivariate Long Memory Processes Subject to Structural Breaks
- Chapter 5: Identifying Global and National Output and Fiscal Policy Shocks Using a GVAR
- Chapter 6: The Determinants of Health Care Expenditure and Trends: A Semiparametric Panel Data Analysis of OECD Countries
- Chapter 7: Growth Empirics: a Bayesian Semiparametric Model With Random Coefficients for a Panel of OECD Countries
- Chapter 8: Robust Estimation and Inference for Importance Sampling Estimators with Infinite Variance
- Chapter 9: Econometrics of Scoring Auctions
- Chapter 10: Bayesian Estimation of Linear Sum Assignment Problems
- Chapter 11: The Mode is the Message: Using Predata as Exclusion Restrictions to Evaluate Survey Design
- Chapter 12: Estimating Peer Effects on Career Choice: A Spatial Multinomial Logit Approach
- Chapter 13: Mortgage Portfolio Diversification in the Presence of Cross-Sectional and Spatial Dependence
- Chapter 14: An Econometrician’s Perspective on Big Data
- Chapter 15: Comments on “an Econometrician’s Perspective on Big Data” by cheng hsiao
- Chapter 16: Comments on “An Econometrician’s Perspective on Big Data” by Cheng Hsiao
- Index