| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Bayesian Local Likelihood Method for Modelling Parameter Time Variation in DSGE Models |
0 |
0 |
0 |
3 |
0 |
0 |
8 |
70 |
| A Bootstrap Invariance Principle for Highly Nonstationary Long Memory Processes |
0 |
0 |
0 |
3 |
0 |
1 |
5 |
18 |
| A Bootstrap Procedure for Panel Datasets with Many Cross-Sectional Units |
0 |
0 |
0 |
23 |
1 |
1 |
13 |
59 |
| A Comparison of Estimation Methods for Dynamic Factor Models of Large Dimensions |
0 |
0 |
0 |
5 |
0 |
1 |
15 |
44 |
| A Dynamic Factor Analysis of Financial Contagion in Asia |
0 |
0 |
0 |
1 |
0 |
0 |
10 |
18 |
| A Generalised Fractional Differencing Bootstrap for Long Memory Processes |
0 |
0 |
0 |
26 |
0 |
0 |
10 |
39 |
| A New Approach for Detecting Shifts in Forecast Accuracy |
0 |
0 |
0 |
53 |
0 |
0 |
9 |
97 |
| A New Method for Determining the Number of Factors in Factor Models with Large Datasets |
0 |
0 |
0 |
12 |
0 |
0 |
13 |
44 |
| A New Nonparametric Test of Cointegration Rank |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
9 |
| A New Test for Market Efficiency and Uncovered Interest Parity |
0 |
0 |
1 |
25 |
0 |
1 |
10 |
63 |
| A New Test for Market Efficiency and Uncovered Interest Parity |
0 |
0 |
0 |
10 |
0 |
2 |
10 |
29 |
| A New Test forMarket Efficiency and Uncovered Interest Parity |
0 |
0 |
1 |
9 |
0 |
0 |
12 |
43 |
| A Nonlinear Approach to Public Finance Sustainability in Latin America |
0 |
0 |
0 |
2 |
1 |
2 |
8 |
29 |
| A Nonlinear Panel Data Model of Cross-Sectional Dependence |
0 |
0 |
0 |
132 |
0 |
0 |
14 |
296 |
| A Nonlinear Panel Model of Cross-sectional Dependence |
0 |
0 |
0 |
2 |
0 |
1 |
11 |
27 |
| A Note on Covariance Stationarity Conditions for Dynamic Random Coefficient Models |
0 |
0 |
0 |
0 |
0 |
1 |
11 |
12 |
| A Note on Joint Estimation of Common Cycles and Common Trends in Nonstationary Multivariate Systems |
0 |
0 |
0 |
0 |
0 |
0 |
6 |
10 |
| A Note on an Iterative Least Squares Estimation Method for ARMA and VARMA Models |
0 |
0 |
1 |
4 |
0 |
0 |
12 |
34 |
| A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models |
0 |
1 |
3 |
50 |
0 |
4 |
20 |
96 |
| A Parametric Estimation Method for Dynamic Factor Models of Large Dimensions |
0 |
0 |
1 |
189 |
0 |
0 |
8 |
626 |
| A Radial Basis Function Artificial Neural Network Test for ARCH |
0 |
0 |
0 |
104 |
0 |
2 |
9 |
1,059 |
| A Residual-based Threshold Method for Detection of Units that are Too Big to Fail in Large Factor Models |
0 |
0 |
0 |
29 |
0 |
0 |
7 |
76 |
| A Review of Forecasting Techniques for Large Data Sets |
0 |
0 |
0 |
2 |
0 |
0 |
11 |
23 |
| A Shrinkage Instrumental Variable Estimator for Large Datasets |
0 |
0 |
0 |
3 |
1 |
1 |
13 |
30 |
| A Shrinkage Instrumental Variable Estimator for Large Datasets |
0 |
0 |
0 |
8 |
0 |
0 |
15 |
55 |
| A Similarity-based Approach for Macroeconomic Forecasting |
0 |
0 |
1 |
63 |
1 |
1 |
18 |
121 |
| A State Space Approach To The Policymaker's Data Uncertainty Problem |
0 |
0 |
0 |
65 |
0 |
0 |
7 |
187 |
| A State Space Approach to Extracting the Signal from Uncertain Data |
0 |
0 |
0 |
5 |
0 |
0 |
6 |
53 |
| A Stochastic Variance Factor Model for Large Datasets and an Application to S&P Data |
0 |
0 |
0 |
1 |
0 |
1 |
9 |
17 |
| A Test for Serial Dependence Using Neural Networks |
0 |
0 |
0 |
5 |
0 |
0 |
7 |
34 |
| A Test of M Structural Breaks Under the Unit Root Hypothesis |
0 |
0 |
0 |
63 |
1 |
1 |
8 |
373 |
| A Testing Procedure for Determining the Number of Factors in Approximate Factor Models with Large Datasets |
1 |
1 |
1 |
14 |
1 |
1 |
16 |
48 |
| A Time Varying DSGE Model with Financial Frictions |
0 |
0 |
0 |
8 |
0 |
1 |
17 |
58 |
| A UK Financial Conditions Index Using Targeted Data Reduction: Forecasting and Structural Identification |
0 |
0 |
0 |
35 |
0 |
0 |
9 |
110 |
| A UK financial conditions index using targeted data reduction: forecasting and structural identification |
0 |
0 |
0 |
24 |
0 |
0 |
8 |
103 |
| A UK financial conditions index using targeted data reduction: forecasting and structural identification |
0 |
0 |
0 |
33 |
0 |
1 |
14 |
78 |
| A new approach for detecting shifts in forecast accuracy |
0 |
0 |
1 |
76 |
0 |
0 |
13 |
109 |
| A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models |
0 |
0 |
0 |
59 |
0 |
0 |
7 |
178 |
| A state space approach to extracting the signal from uncertain data |
0 |
0 |
0 |
72 |
0 |
1 |
7 |
291 |
| A time varying parameter structural model of the UK economy |
0 |
0 |
1 |
122 |
1 |
2 |
22 |
157 |
| Adaptive Forcasting in the Presence of Recent and Ongoing Structural Change |
0 |
0 |
0 |
33 |
1 |
2 |
9 |
168 |
| Adaptive Forecasting in the Presence of Recent and Ongoing Structural Change |
0 |
0 |
0 |
0 |
1 |
1 |
4 |
27 |
| Adaptive forecasting in the presence of recent and ongoing structural change |
0 |
0 |
0 |
60 |
0 |
0 |
8 |
133 |
| Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns |
0 |
0 |
1 |
2 |
0 |
1 |
13 |
34 |
| Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns |
0 |
0 |
0 |
135 |
1 |
1 |
8 |
317 |
| Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns |
0 |
0 |
0 |
157 |
0 |
0 |
4 |
500 |
| An Automatic Leading Indicator of Economic Activity: Forecasting GDP Growth for European Countries |
0 |
0 |
0 |
282 |
0 |
0 |
11 |
1,624 |
| An Investigation of Current Account Solvency in Latin America Using Non Linear Stationarity Tests |
0 |
0 |
0 |
4 |
0 |
0 |
2 |
15 |
| An automatic leading indicator, variable reduction and variable selection methods using small and large datasets: Forecasting the industrial production growth for euro area economies |
0 |
0 |
0 |
31 |
0 |
0 |
10 |
54 |
| Are more data always better for factor analysis? Results for the euro area, the six largest euro area countries and the UK |
0 |
0 |
0 |
112 |
1 |
1 |
10 |
277 |
| Assessing the economy-wide effects of quantitative easing |
0 |
0 |
5 |
510 |
2 |
5 |
43 |
1,383 |
| Big Data Analytics: A New Perspective |
0 |
0 |
0 |
35 |
0 |
0 |
14 |
111 |
| Big Data Analytics: A New Perspective |
0 |
0 |
0 |
23 |
0 |
1 |
7 |
98 |
| Big Data Econometrics: Now Casting and Early Estimates |
1 |
1 |
2 |
211 |
1 |
2 |
25 |
309 |
| Big data analytics: a new perspective |
0 |
0 |
0 |
219 |
0 |
0 |
17 |
309 |
| Block Bootstrap and Long Memory |
0 |
0 |
0 |
6 |
1 |
2 |
9 |
32 |
| Boosting Estimation of RBF Neural Networks for Dependent Data |
0 |
0 |
0 |
1 |
1 |
1 |
7 |
22 |
| Bootstrap Statistical Tests of Rank Determination for System Identification |
0 |
0 |
0 |
1 |
0 |
0 |
7 |
17 |
| Breaks in DSGE models |
0 |
0 |
0 |
45 |
0 |
0 |
6 |
116 |
| Choosing between persistent and stationary volatility |
0 |
0 |
2 |
59 |
2 |
2 |
8 |
99 |
| Cluster Analysis of Panel Choosing the Optimal Set of Instruments from Large Instrument Setsusing Non-Standard Optimisation of Information Criteria |
0 |
0 |
0 |
0 |
1 |
1 |
13 |
23 |
| Cluster Analysis of Panel Datasets using Non-Standard Optimisation of Information Criteria |
0 |
0 |
0 |
7 |
0 |
0 |
8 |
21 |
| Cointegrating VAR models with endogenous I(0) variables: theoretical extensions and an application to UK monetary policy |
0 |
0 |
0 |
166 |
0 |
0 |
5 |
659 |
| Common correlated effect cross-sectional dependence corrections for non-linear conditional mean panel models |
0 |
0 |
3 |
73 |
2 |
4 |
23 |
164 |
| Cross-sectional Averaging and Instrumental Variable Estimation with Many Weak Instruments |
0 |
0 |
0 |
6 |
0 |
0 |
12 |
38 |
| Deep Neural Network Estimation in Panel Data Models |
1 |
1 |
2 |
10 |
2 |
3 |
22 |
47 |
| Deep Neural Network Estimation in Panel Data Models |
0 |
0 |
0 |
26 |
0 |
1 |
19 |
52 |
| Detecting Network Instability via Multiscale Detrended Cross-Correlations and MST Topology |
0 |
0 |
6 |
6 |
1 |
2 |
2 |
2 |
| Determining the Poolability of Individual Series in Panel Datasets |
0 |
0 |
0 |
4 |
0 |
0 |
7 |
36 |
| Determining the Stationarity Properties of Individual Series in Panel Datasets |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
12 |
| Dynamic Factor Extraction of Cross-Sectional Dependence in Panel Unit Root Tests |
0 |
0 |
0 |
0 |
0 |
0 |
6 |
17 |
| Estimating Deterministically Time-Varying Variances in Regression Models |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
14 |
| Estimating Time-Variation in Measurement Error from Data Revisions: An Application to Forecasting in Dynamic Models |
0 |
0 |
0 |
1 |
0 |
1 |
7 |
20 |
| Estimating Time-Varying DSGE Models Using Minimum Distance Methods |
0 |
0 |
0 |
10 |
0 |
0 |
10 |
79 |
| Estimating the rank of the spectral density matrix |
0 |
0 |
0 |
129 |
1 |
1 |
15 |
447 |
| Estimating time-variation in measurement error from data revisions; an application to forecasting in dynamic models |
0 |
0 |
0 |
52 |
0 |
0 |
12 |
267 |
| Estimating time-varying DSGE models using minimum distance methods |
0 |
0 |
0 |
119 |
0 |
1 |
10 |
174 |
| Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets |
0 |
0 |
0 |
159 |
0 |
2 |
19 |
177 |
| Estimation and Inference for Multi-dimensional Heterogeneous Panel Datasets with Hierarchical Multi-factor Error Structure |
0 |
0 |
0 |
85 |
0 |
0 |
8 |
139 |
| Estimation and Inference in a Non-Linear State Space Model: Durable Consumption |
0 |
0 |
0 |
193 |
0 |
1 |
8 |
457 |
| Estimation of time-varying covariance matrices for large datasets |
0 |
0 |
0 |
1 |
0 |
1 |
11 |
21 |
| Evaluating macroeconomic models of the business cycle |
0 |
0 |
0 |
69 |
0 |
0 |
4 |
238 |
| Evolving UK and US macroeconomic dynamics through the lens of a model of deterministic structural change |
0 |
0 |
0 |
52 |
0 |
0 |
9 |
139 |
| Expansionary and contractionary fiscal multipliers in the U.S |
0 |
0 |
2 |
9 |
0 |
0 |
18 |
27 |
| Exponent of Cross-sectional Dependence for Residuals |
0 |
0 |
0 |
34 |
1 |
2 |
17 |
96 |
| Exponent of Cross-sectional Dependence: Estimation and Inference |
0 |
0 |
0 |
74 |
0 |
0 |
10 |
239 |
| Exponent of Cross-sectional Dependence: Estimation and Inference |
1 |
2 |
3 |
57 |
2 |
16 |
35 |
258 |
| Exponent of Cross-sectional Dependence: Estimation and Inference |
0 |
0 |
0 |
148 |
0 |
0 |
24 |
337 |
| Exponent of cross-sectional dependence for residuals |
0 |
0 |
0 |
11 |
1 |
1 |
10 |
56 |
| Factor Analysis Using Subspace Factor Models: Some Theoretical Results and an Application to UK Inflation Forecasting |
0 |
0 |
0 |
1 |
0 |
0 |
12 |
23 |
| Factor based identification-robust inference in IV regressions |
0 |
1 |
3 |
50 |
0 |
1 |
9 |
102 |
| Factor-GMM Estimation with Large Sets of Possibly Weak Instruments |
0 |
0 |
0 |
23 |
0 |
0 |
14 |
123 |
| Factor-GMM Estimation with Large Sets of Possibly Weak Instruments |
0 |
0 |
1 |
5 |
1 |
2 |
14 |
39 |
| Forecast combination and the Bank of England’s suite of statistical forecasting models |
0 |
0 |
1 |
330 |
0 |
2 |
18 |
966 |
| Forecasting Exchange Rates with a Large Bayesian VAR |
0 |
0 |
0 |
174 |
0 |
0 |
11 |
431 |
| Forecasting Exchange Rates with a Large Bayesian VAR |
0 |
0 |
0 |
11 |
2 |
3 |
8 |
49 |
| Forecasting Exchange Rates with a Large Bayesian VAR |
0 |
0 |
1 |
76 |
0 |
0 |
23 |
290 |
| Forecasting Financial Crises and Contagion in Asia Using Dynamic Factor Analysis |
0 |
0 |
0 |
2 |
0 |
1 |
17 |
36 |
| Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis |
0 |
0 |
0 |
227 |
2 |
3 |
26 |
532 |
| Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis |
0 |
0 |
0 |
203 |
0 |
0 |
18 |
539 |
| Forecasting Government Bond Yields with Large Bayesian VARs |
0 |
0 |
1 |
11 |
1 |
2 |
14 |
60 |
| Forecasting Government Bond Yields with Large Bayesian VARs |
0 |
0 |
1 |
39 |
0 |
0 |
15 |
156 |
| Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models |
0 |
0 |
0 |
63 |
1 |
2 |
16 |
230 |
| Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models |
0 |
0 |
0 |
144 |
1 |
3 |
22 |
332 |
| Forecasting Large Datasets with Reduced Rank Multivariate Models |
0 |
0 |
0 |
0 |
1 |
1 |
12 |
24 |
| Forecasting UK GDP growth with large survey panels |
0 |
0 |
2 |
43 |
2 |
4 |
27 |
103 |
| Forecasting UK inflation bottom up |
0 |
0 |
1 |
113 |
3 |
4 |
69 |
486 |
| Forecasting Using Predictive Likelihood Model Averaging |
0 |
0 |
0 |
1 |
0 |
0 |
8 |
28 |
| Forecasting Value-at-Risk using deep neural network quantile regression |
0 |
0 |
3 |
69 |
1 |
3 |
34 |
108 |
| Forecasting euro area inflation using dynamic factor measures of underlying inflation |
0 |
0 |
0 |
103 |
0 |
1 |
13 |
272 |
| Forecasting in the Presence of Recent Structural Change |
0 |
0 |
0 |
78 |
0 |
1 |
7 |
159 |
| Forecasting in the presence of recent structural change |
0 |
0 |
1 |
178 |
0 |
0 |
11 |
349 |
| Forecasting in the presence of recent structural change |
0 |
0 |
0 |
31 |
0 |
0 |
10 |
123 |
| Forecasting using Bayesian and Information Theoretic Model Averaging: An Application to UK Inflation |
0 |
0 |
0 |
3 |
0 |
0 |
6 |
40 |
| Forecasting using Bayesian and information theoretic model averaging: an application to UK inflation |
0 |
0 |
0 |
138 |
0 |
1 |
10 |
395 |
| Forecasting using Bayesian and information theoretic model averaging: an application to UK inflation |
0 |
0 |
0 |
16 |
0 |
1 |
15 |
70 |
| Forecasting with Dynamic Models using Shrinkage-based Estimation |
0 |
0 |
0 |
3 |
0 |
0 |
20 |
37 |
| Forecasting with Measurement Errors in Dynamic Models |
0 |
0 |
0 |
0 |
0 |
1 |
9 |
29 |
| Forecasting with measurement errors in dynamic models |
0 |
0 |
0 |
116 |
0 |
0 |
10 |
422 |
| Forecasting with measurement errors in dynamic models |
0 |
0 |
0 |
143 |
1 |
1 |
21 |
525 |
| GLS Detrending for Nonlinear Unit Root Tests |
0 |
0 |
0 |
1 |
0 |
1 |
12 |
20 |
| GLS Detrending-Based Unit Root Tests in Nonlinear STAR and SETAR Frameworks |
0 |
0 |
0 |
272 |
0 |
0 |
19 |
782 |
| Generalised Density Forecast Combinations |
0 |
0 |
0 |
119 |
0 |
2 |
10 |
189 |
| Generalised density forecast combinations |
0 |
0 |
1 |
45 |
0 |
1 |
12 |
116 |
| Getting PPP Right: Identifying Mean Reverting Real Exchange Rates in Panels |
0 |
0 |
0 |
59 |
0 |
1 |
12 |
234 |
| Getting PPP Right: Identifying Mean-Reverting Real Exchange Rates in Panels |
0 |
0 |
0 |
1 |
0 |
3 |
13 |
35 |
| Getting PPP Right: Identifying Mean-Reverting Real Exchange Rates in Panels |
0 |
0 |
0 |
8 |
2 |
3 |
15 |
46 |
| Heterogeneous Exposures to Systematic and Idiosyncratic Risk across Crypto Assets: A Divide-and-Conquer Approach |
0 |
0 |
0 |
3 |
0 |
1 |
27 |
34 |
| Heterogeneous Exposures to Systematic and Idiosyncratic Risk across Crypto Assets: A Divide-and-Conquer Approach |
0 |
0 |
2 |
5 |
3 |
3 |
16 |
20 |
| Heterogeneous Grouping Structures in Panel Data |
0 |
0 |
2 |
13 |
0 |
1 |
42 |
61 |
| Hierarchical Time Varying Estimation of a Multi Factor Asset Pricing Model |
0 |
0 |
0 |
44 |
0 |
0 |
6 |
76 |
| High Dimensional Generalised Penalised Least Squares |
0 |
0 |
1 |
29 |
0 |
2 |
15 |
62 |
| How Puzzling is the PPP Puzzle? An Alternative Half-Life Measure of Convergence to PPP |
0 |
0 |
0 |
1 |
1 |
2 |
11 |
36 |
| How Puzzling is the PPP Puzzle? An Alternative Half-Life Measure of convergence to PPP |
0 |
0 |
0 |
124 |
1 |
3 |
15 |
414 |
| Import prices and exchange rate pass-through: theory and evidence from the United Kingdom |
0 |
0 |
0 |
783 |
0 |
0 |
14 |
2,103 |
| Impulse Response Functions from Structural Dynamic Factor Models: A Monte Carlo Evaluation |
0 |
0 |
0 |
144 |
0 |
0 |
10 |
539 |
| Impulse Response Functions from Structural Dynamic Factor Models:A Monte Carlo Evaluation |
0 |
0 |
0 |
348 |
0 |
0 |
20 |
1,071 |
| Incorporating lag order selection uncertainty in parameter inference for AR models |
0 |
0 |
0 |
48 |
0 |
1 |
9 |
334 |
| Inference for Impulse Response Coefficients From Multivariate Fractionally Integrated Processes |
0 |
0 |
0 |
39 |
0 |
0 |
10 |
42 |
| Inference on Multivariate Heteroscedastic Time Varying Random Coefficient Models |
0 |
0 |
1 |
3 |
0 |
1 |
14 |
29 |
| Information Criteria, Model Selection Uncertainty and the Determination of Cointegration Rank |
0 |
0 |
0 |
64 |
0 |
0 |
7 |
454 |
| Investor behavior and multiscale cross-correlations: Unveiling regime shifts in global financial markets |
0 |
0 |
0 |
6 |
0 |
0 |
11 |
19 |
| Inward investment and technical progress in the United Kingdom manufacturing sector |
0 |
0 |
0 |
105 |
0 |
1 |
7 |
344 |
| Jumps in Option Prices and Their Determinants: Real-time Evidence from the E-mini S&P 500 Option Market |
0 |
0 |
0 |
8 |
1 |
1 |
29 |
72 |
| Large Time-Varying Parameter VARs: A Non-Parametric Approach |
0 |
0 |
0 |
87 |
0 |
1 |
17 |
144 |
| Large time-varying parameter VARs: a non-parametric approach |
0 |
0 |
0 |
123 |
1 |
2 |
12 |
197 |
| Making a Match: Combining Theory and Evidence in Policy-Oriented Macroeconomic Modelling |
0 |
0 |
0 |
91 |
0 |
3 |
12 |
203 |
| Making a match: combining theory and evidence in policy-oriented macroeconomic modelling |
0 |
0 |
0 |
130 |
0 |
0 |
17 |
442 |
| Making text count: economic forecasting using newspaper text |
0 |
1 |
6 |
111 |
1 |
6 |
54 |
281 |
| Mean Group Instrumental Variable Estimation of Time-Varying Large Heterogeneous Panels with Endogenous Regressors |
0 |
0 |
0 |
17 |
0 |
0 |
16 |
35 |
| Measurement of Factor Strenght: Theory and Practice |
1 |
1 |
2 |
45 |
2 |
4 |
23 |
130 |
| Measurement of Factor Strength: Theory and Practice |
0 |
0 |
0 |
30 |
0 |
0 |
11 |
71 |
| Measuring Conditional Persistence in Time Series |
0 |
0 |
0 |
0 |
0 |
0 |
10 |
18 |
| Model Selection Uncertainty and Dynamic Models |
0 |
0 |
0 |
55 |
0 |
1 |
8 |
272 |
| Model Selection in High-Dimensional Linear Regression using Boosting with Multiple Testing |
0 |
0 |
20 |
20 |
0 |
1 |
11 |
11 |
| Model Selection in Threshold Models |
0 |
0 |
0 |
692 |
0 |
0 |
10 |
2,314 |
| Model selection criteria for factor-augmented regressions |
0 |
0 |
0 |
105 |
1 |
2 |
20 |
425 |
| Modelling Core Inflation for the UK Using a New Dynamic Factor Estimation Method and a Large Disaggregated Price Index Dataset |
0 |
0 |
0 |
4 |
1 |
1 |
10 |
27 |
| Multivariate Methods for Monitoring Structural Change |
0 |
0 |
0 |
1 |
0 |
1 |
13 |
46 |
| Multivariate methods for monitoring structural change |
0 |
0 |
0 |
55 |
0 |
0 |
12 |
162 |
| Network Effects in Corporate Emissions: Evidence from a Data-Dependent Spatial Panel Model |
0 |
0 |
25 |
25 |
0 |
1 |
6 |
6 |
| Non-Nested Models and the Likelihood Ratio Statistic: A Comparison of Simulation and Bootstrap Based Tests |
0 |
0 |
1 |
5 |
0 |
0 |
12 |
43 |
| Non-nested Models and the likelihood Ratio Statistic: A Comparison of Simulation and Bootstrap-based Tests |
0 |
0 |
0 |
400 |
0 |
1 |
11 |
1,439 |
| Nonlinear Autoregressive Models and Long Memory |
0 |
0 |
0 |
1 |
1 |
2 |
8 |
19 |
| Nonlinear Modelling of Autoregressive Structural Breaks in a US Diffusion Index Dataset |
0 |
0 |
0 |
3 |
0 |
0 |
9 |
27 |
| Nonlinear Models with Strongly Dependent Processes and Applications to Forward Premia and Real Exchange Rates |
0 |
0 |
0 |
0 |
0 |
0 |
16 |
28 |
| Nonparametric Time Varying IV-SVARs: Estimation and Inference |
0 |
0 |
4 |
25 |
0 |
4 |
25 |
50 |
| On Robust Inference in Time Series Regression |
0 |
1 |
2 |
126 |
0 |
3 |
21 |
64 |
| On Robust Inference in Time Series Regression |
0 |
0 |
0 |
20 |
1 |
3 |
17 |
65 |
| On Robust Inference in Time Series Regression |
0 |
0 |
1 |
5 |
0 |
2 |
15 |
55 |
| On Testing for Diagonality of Large Dimensional Covariance Matrices |
0 |
0 |
0 |
0 |
0 |
0 |
11 |
16 |
| Panels with Nonstationary Multifactor Error Structures |
0 |
0 |
0 |
52 |
0 |
1 |
16 |
239 |
| Panels with Nonstationary Multifactor Error Structures |
0 |
0 |
0 |
0 |
0 |
2 |
16 |
43 |
| Panels with Nonstationary Multifactor Error Structures |
0 |
0 |
0 |
233 |
0 |
0 |
23 |
666 |
| Panels with Nonstationary Multifactor Error Structures |
0 |
0 |
0 |
78 |
0 |
0 |
24 |
334 |
| Panels with nonstationary multifactor error structures |
0 |
0 |
0 |
17 |
0 |
1 |
15 |
113 |
| Parsimonious estimation with many instruments |
0 |
0 |
0 |
30 |
0 |
0 |
4 |
94 |
| Partial Time-Varying Regression Modelling under General Heterogeneity |
0 |
0 |
0 |
16 |
1 |
6 |
20 |
37 |
| Rational expectations and fixed-event forecasts: an application to UK inflation |
0 |
0 |
0 |
150 |
0 |
2 |
18 |
604 |
| Regression Modelling under General Heterogeneity |
0 |
0 |
1 |
36 |
1 |
2 |
14 |
42 |
| Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting |
0 |
0 |
0 |
2 |
0 |
0 |
16 |
41 |
| Revisiting useful approaches to data-rich macroeconomic forecasting |
0 |
0 |
0 |
147 |
0 |
0 |
14 |
357 |
| Semiparametric Sieve-Type GLS Inference in Regressions with Long-Range Dependence |
0 |
0 |
0 |
3 |
0 |
1 |
12 |
25 |
| Sieve Bootstrap for Strongly Dependent Stationary Processes |
0 |
0 |
0 |
2 |
0 |
0 |
7 |
26 |
| Spectral based methods to identify common trends and common cycles |
0 |
0 |
0 |
181 |
1 |
2 |
12 |
589 |
| State-level wage Phillips curves |
0 |
0 |
0 |
3 |
0 |
0 |
9 |
21 |
| State-level wage Phillips curves |
0 |
0 |
0 |
20 |
0 |
1 |
11 |
58 |
| State-level wage Phillips curves |
0 |
0 |
0 |
9 |
1 |
3 |
27 |
58 |
| Statistical Tests of the Rank of a Matrix and Their Applications in Econometric Modelling |
1 |
1 |
1 |
1 |
1 |
2 |
11 |
26 |
| Statistical tests and estimators of the rank of a matrix and their applications in econometric modelling |
0 |
0 |
0 |
66 |
0 |
0 |
8 |
143 |
| Stochastic Volatility Driven by Large Shocks |
0 |
0 |
0 |
2 |
0 |
0 |
5 |
24 |
| Stock Returns Predictability with Unstable Predictors |
0 |
0 |
1 |
12 |
0 |
2 |
8 |
24 |
| Stock returns predictability with unstable predictors |
0 |
0 |
0 |
74 |
0 |
0 |
7 |
64 |
| Structural Analysis with Multivariate Autoregressive Index Models |
0 |
0 |
0 |
87 |
1 |
2 |
12 |
134 |
| Structural Breaks in Inflation Dynamics |
0 |
0 |
0 |
0 |
1 |
1 |
11 |
505 |
| Testing for ARCH in the Presence of Nonlinearity of Unknown Form in the Conditional Mean |
0 |
0 |
0 |
0 |
0 |
2 |
8 |
15 |
| Testing for Cointegration in Nonlinear STAR Error Correction Models |
0 |
0 |
0 |
3 |
1 |
1 |
13 |
40 |
| Testing for Correlated Factor Loadings in Cross Sectionally Dependent Panels |
0 |
0 |
0 |
53 |
0 |
2 |
14 |
116 |
| Testing for Exogeneity in Nonlinear Threshold Models |
0 |
0 |
0 |
0 |
0 |
2 |
15 |
19 |
| Testing for Neglected Nonlinearity in Cointegrating Relationships |
0 |
0 |
0 |
1 |
0 |
0 |
4 |
12 |
| Testing for Neglected Nonlinearity in Long Memory Models |
0 |
0 |
1 |
1 |
0 |
2 |
15 |
22 |
| Testing for Nonstationary Long Memory against Nonlinear Ergodic Models |
0 |
0 |
0 |
0 |
0 |
1 |
30 |
34 |
| Testing for Strict Stationarity |
0 |
0 |
0 |
3 |
0 |
2 |
10 |
34 |
| Testing for Structural Breaks in Nonlinear Dynamic Models Using Artificial Neural Network Approximations |
0 |
0 |
2 |
5 |
2 |
2 |
11 |
34 |
| Testing for a Linear Unit Root against Nonlinear Threshold Stationarity |
0 |
0 |
0 |
109 |
1 |
4 |
24 |
345 |
| Testing for a Unit Root against Nonlinear STAR Models |
1 |
1 |
1 |
162 |
1 |
2 |
17 |
339 |
| Testing for a unit root against nonlinear star models |
0 |
0 |
0 |
182 |
0 |
2 |
21 |
666 |
| Testing for nonlinear cointegration between stock prices and dividends |
0 |
0 |
0 |
193 |
0 |
0 |
5 |
431 |
| Testing the Martingale Difference Hypothesis Using Neural Network Approximations |
0 |
0 |
0 |
1 |
0 |
0 |
11 |
21 |
| Testing the rank of the Hankel matrix: a statistical approach |
0 |
0 |
0 |
108 |
0 |
0 |
8 |
605 |
| Tests for Deterministic Parametric Structural Change in Regression Models |
0 |
0 |
0 |
1 |
1 |
1 |
10 |
16 |
| Tests of Rank in Reduced Rank Regression Models |
0 |
0 |
0 |
61 |
1 |
1 |
7 |
610 |
| The Elusive Persistence: Wage and Price Rigidities, the Phillips Curve, and Inflation Dynamics |
0 |
0 |
0 |
5 |
1 |
2 |
17 |
34 |
| The Forecasting Performance of the OECD Composite Leading Indicators for France, Germany, Italy |
0 |
0 |
0 |
183 |
0 |
0 |
13 |
1,046 |
| The Impact of Large Structural Shocks on Economic Relationships: Evidence from Oil Price Shocks |
0 |
0 |
1 |
5 |
0 |
0 |
10 |
24 |
| The Role of Search Frictions and Bargaining for Inflation Dynamics |
0 |
0 |
0 |
41 |
1 |
2 |
9 |
184 |
| The Yen Real Exchange Rate May Be Stationary after All: Evidence from Nonlinear Unit-Root Tests |
0 |
0 |
0 |
2 |
0 |
1 |
17 |
60 |
| The yen real exchange rate may be stationary after all: evidence from non-linear unit root tests |
0 |
0 |
0 |
167 |
0 |
1 |
17 |
747 |
| Threshold Models for Trended Time Series |
0 |
0 |
0 |
843 |
1 |
1 |
6 |
2,470 |
| Time Varying Cointegration and the UK Great Ratios |
0 |
0 |
0 |
36 |
1 |
2 |
15 |
94 |
| Time Varying Three Pass Regression Filter |
0 |
0 |
4 |
16 |
0 |
0 |
16 |
41 |
| Time varying cointegration and the UK Great Ratios |
0 |
0 |
0 |
30 |
0 |
0 |
13 |
58 |
| Time-Varying Instrumental Variable Estimation |
0 |
0 |
0 |
40 |
0 |
1 |
9 |
108 |
| Time-Varying Instrumental Variable Estimation |
0 |
0 |
0 |
50 |
0 |
2 |
22 |
95 |
| Time-varying cointegration and the UK great ratios |
0 |
0 |
0 |
30 |
0 |
1 |
13 |
62 |
| Unconventional monetary policies and the macroeconomy: the impact of the United Kingdom's QE2 and Funding for Lending Scheme |
0 |
0 |
1 |
128 |
2 |
3 |
28 |
331 |
| Unit Root Testing against the Alternative Hypothesis of up to m Structural Breaks |
0 |
0 |
2 |
11 |
1 |
3 |
13 |
37 |
| Unit Root Tests in Three-Regime SETAR Models |
0 |
0 |
0 |
0 |
0 |
1 |
16 |
39 |
| Unit Root Tests in Three-Regime SETAR Models |
0 |
0 |
0 |
240 |
1 |
3 |
12 |
671 |
| Unlocking the Regression Space |
0 |
0 |
36 |
36 |
1 |
2 |
23 |
23 |
| Using Extraneous Information and GMM to Estimate Threshold Parameters in TAR Models |
0 |
0 |
0 |
0 |
0 |
0 |
9 |
19 |
| Variable Selection using Non-Standard Optimisation of Information Criteria |
0 |
0 |
0 |
3 |
2 |
3 |
8 |
21 |
| Total Working Papers |
7 |
12 |
171 |
15,579 |
86 |
265 |
3,116 |
49,314 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Generalised Fractional Differencing Bootstrap for Long Memory Processes |
0 |
0 |
0 |
5 |
0 |
0 |
11 |
32 |
| A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models |
0 |
0 |
2 |
33 |
1 |
2 |
22 |
136 |
| A SHRINKAGE INSTRUMENTAL VARIABLE ESTIMATOR FOR LARGE DATASETS |
0 |
0 |
0 |
1 |
0 |
0 |
9 |
57 |
| A State Space Approach to Extracting the Signal From Uncertain Data |
0 |
0 |
0 |
14 |
0 |
0 |
8 |
74 |
| A Testing Procedure for Determining the Number of Factors in Approximate Factor Models With Large Datasets |
0 |
0 |
0 |
62 |
0 |
0 |
11 |
179 |
| A UK financial conditions index using targeted data reduction: Forecasting and structural identification |
0 |
0 |
1 |
27 |
0 |
0 |
14 |
150 |
| A bootstrap procedure for panel data sets with many cross-sectional units |
0 |
0 |
0 |
237 |
0 |
1 |
21 |
831 |
| A comprehensive evaluation of macroeconomic forecasting methods |
0 |
0 |
3 |
38 |
2 |
4 |
23 |
165 |
| A factor approach to realized volatility forecasting in the presence of finite jumps and cross-sectional correlation in pricing errors |
0 |
0 |
0 |
22 |
0 |
1 |
7 |
77 |
| A new approach for detecting shifts in forecast accuracy |
0 |
0 |
0 |
4 |
1 |
1 |
14 |
46 |
| A new approach to multi-step forecasting using dynamic stochastic general equilibrium models |
0 |
0 |
0 |
16 |
1 |
2 |
9 |
82 |
| A new summary measure of inflation expectations |
0 |
0 |
0 |
34 |
1 |
1 |
10 |
87 |
| A new test for market efficiency and uncovered interest parity |
0 |
0 |
2 |
4 |
0 |
1 |
14 |
23 |
| A nonlinear panel data model of cross-sectional dependence |
0 |
0 |
1 |
91 |
0 |
0 |
21 |
270 |
| A note on an iterative least-squares estimation method for ARMA and VARMA models |
0 |
0 |
0 |
56 |
1 |
2 |
9 |
143 |
| A note on modelling core inflation for the UK using a new dynamic factor estimation method and a large disaggregated price index dataset |
0 |
0 |
0 |
51 |
0 |
2 |
9 |
132 |
| A parametric estimation method for dynamic factor models of large dimensions |
0 |
0 |
1 |
65 |
0 |
0 |
14 |
166 |
| A radial basis function artificial neural network test for ARCH |
0 |
0 |
0 |
28 |
0 |
1 |
5 |
150 |
| A radial basis function artificial neural network test for neglected nonlinearity |
0 |
0 |
0 |
219 |
0 |
1 |
15 |
1,262 |
| A real time evaluation of Bank of England forecasts of inflation and growth |
0 |
1 |
1 |
91 |
3 |
7 |
32 |
293 |
| A review of forecasting techniques for large datasets |
0 |
1 |
1 |
3 |
0 |
2 |
11 |
19 |
| A review of forecasting techniques for large datasets |
0 |
1 |
1 |
32 |
0 |
2 |
9 |
85 |
| A similarity‐based approach for macroeconomic forecasting |
0 |
1 |
2 |
30 |
0 |
2 |
13 |
119 |
| A stochastic variance factor model for large datasets and an application to S&P data |
0 |
0 |
0 |
33 |
0 |
1 |
20 |
131 |
| A time varying DSGE model with financial frictions |
0 |
0 |
2 |
47 |
2 |
7 |
17 |
174 |
| A time-varying parameter structural model of the UK economy |
0 |
0 |
0 |
17 |
0 |
0 |
5 |
76 |
| Adaptive forecasting in the presence of recent and ongoing structural change |
1 |
1 |
2 |
96 |
3 |
9 |
22 |
386 |
| Amazingly versatile Durbin regressions with persistent and nonlinear errors: HAC comparisons |
0 |
0 |
0 |
0 |
1 |
1 |
5 |
5 |
| An Investigation of Current Account Solvency in Latin America Using Non Linear Nonstationarity Tests |
0 |
0 |
0 |
97 |
0 |
1 |
29 |
327 |
| An LM Test for the Conditional Independence between Regressors and Factor Loadings in Panel Data Models with Interactive Effects |
0 |
0 |
1 |
1 |
0 |
0 |
11 |
13 |
| An automatic leading indicator of economic activity: forecasting GDP growth for European countries |
0 |
0 |
0 |
51 |
0 |
0 |
8 |
1,414 |
| Are more data always better for factor analysis? Results for the euro area, the six largest euro area countries and the UK |
0 |
0 |
1 |
41 |
0 |
2 |
10 |
127 |
| Assessing the Economy‐wide Effects of Quantitative Easing |
0 |
0 |
0 |
425 |
2 |
5 |
29 |
1,356 |
| Bandwidth selection by cross-validation for forecasting long memory financial time series |
0 |
0 |
0 |
8 |
0 |
0 |
13 |
51 |
| Bootstrap Neural Network Cointegration Tests Against Nonlinear Alternative Hypotheses |
0 |
0 |
0 |
140 |
0 |
2 |
7 |
374 |
| Bootstrap-based tests for deterministic time-varying coefficients in regression models |
0 |
0 |
0 |
22 |
1 |
1 |
9 |
78 |
| Choosing the optimal set of instruments from large instrument sets |
0 |
0 |
0 |
4 |
0 |
1 |
12 |
54 |
| Cluster analysis of panel data sets using non-standard optimisation of information criteria |
0 |
0 |
0 |
211 |
0 |
0 |
10 |
596 |
| Common correlated effect cross‐sectional dependence corrections for nonlinear conditional mean panel models |
0 |
0 |
3 |
17 |
0 |
1 |
19 |
57 |
| Comparing logit-based early warning systems: Does the duration of systemic banking crises matter? |
0 |
0 |
0 |
46 |
0 |
2 |
10 |
188 |
| Correction to: Exponent of Cross-sectional Dependence for Residuals |
0 |
1 |
2 |
3 |
0 |
2 |
10 |
16 |
| Corrigendum to “A Generalised Fractional Differencing Bootstrap for Long Memory Processes” Journal of Time Series Analysis 40: 467‐492 (2019) DOI: 10.1111/jtsa.12460 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
14 |
| Credit market freedom and cost efficiency in US state banking |
0 |
0 |
0 |
15 |
0 |
1 |
7 |
106 |
| Cross-sectional averaging and instrumental variable estimation with many weak instruments |
0 |
0 |
0 |
34 |
0 |
0 |
30 |
130 |
| Detection of units with pervasive effects in large panel data models |
0 |
0 |
1 |
4 |
1 |
1 |
9 |
36 |
| Dynamic factor extraction of cross-sectional dependence in panel unit root tests |
0 |
0 |
1 |
89 |
0 |
0 |
10 |
310 |
| ELUSIVE PERSISTENCE: WAGE AND PRICE RIGIDITIES, THE NEW KEYNESIAN PHILLIPS CURVE AND INFLATION DYNAMICS |
0 |
0 |
0 |
0 |
1 |
3 |
25 |
182 |
| ESTIMATION OF TIME-VARYING COVARIANCE MATRICES FOR LARGE DATASETS |
0 |
0 |
0 |
3 |
1 |
1 |
10 |
18 |
| Erratum |
0 |
0 |
0 |
6 |
1 |
1 |
7 |
105 |
| Estimating deterministically time-varying variances in regression models |
0 |
0 |
0 |
9 |
0 |
0 |
11 |
54 |
| Estimating the Dynamics and Persistence of Financial Networks, with an Application to the Sterling Money Market |
0 |
0 |
0 |
18 |
2 |
3 |
9 |
66 |
| Estimating the Rank of the Spectral Density Matrix |
0 |
0 |
0 |
23 |
0 |
1 |
14 |
110 |
| Estimating time variation in measurement error from data revisions: an application to backcasting and forecasting in dynamic models |
1 |
1 |
1 |
60 |
1 |
2 |
13 |
338 |
| Estimation and forecasting in vector autoregressive moving average models for rich datasets |
0 |
0 |
0 |
19 |
1 |
1 |
17 |
129 |
| Estimation and inference for impulse response functions from univariate strongly persistent processes |
0 |
0 |
0 |
5 |
0 |
1 |
11 |
43 |
| Estimation and inference for multi-dimensional heterogeneous panel datasets with hierarchical multi-factor error structure |
1 |
1 |
1 |
14 |
1 |
6 |
14 |
58 |
| Evolving UK and US macroeconomic dynamics through the lens of a model of deterministic structural change |
0 |
0 |
0 |
6 |
1 |
1 |
15 |
40 |
| Expansionary and Contractionary Fiscal Multipliers in the United States |
1 |
1 |
2 |
2 |
2 |
3 |
6 |
6 |
| Exponent of Cross-sectional Dependence for Residuals |
0 |
1 |
4 |
14 |
1 |
3 |
17 |
64 |
| Exponent of Cross‐Sectional Dependence: Estimation and Inference |
0 |
0 |
1 |
31 |
0 |
2 |
26 |
175 |
| Factor-GMM estimation with large sets of possibly weak instruments |
0 |
0 |
0 |
104 |
2 |
3 |
35 |
270 |
| Factor‐Based Identification‐Robust Interference in IV Regressions |
0 |
0 |
2 |
13 |
0 |
2 |
18 |
58 |
| Financial Econometrics and Realized Volatility/Vast Data |
0 |
0 |
0 |
7 |
0 |
1 |
3 |
29 |
| Forecast combination and the Bank of England's suite of statistical forecasting models |
0 |
0 |
1 |
99 |
1 |
2 |
16 |
269 |
| Forecasting UK inflation bottom up |
0 |
0 |
3 |
9 |
4 |
12 |
43 |
67 |
| Forecasting Using Bayesian and Information-Theoretic Model Averaging: An Application to U.K. Inflation |
0 |
0 |
0 |
89 |
0 |
0 |
9 |
297 |
| Forecasting Value-at-Risk Using Deep Neural Network Quantile Regression* |
0 |
2 |
6 |
9 |
5 |
12 |
56 |
78 |
| Forecasting euro area inflation using dynamic factor measures of underlying inflation |
0 |
0 |
0 |
18 |
0 |
0 |
15 |
126 |
| Forecasting exchange rates with a large Bayesian VAR |
1 |
2 |
4 |
291 |
2 |
5 |
21 |
809 |
| Forecasting financial crises and contagion in Asia using dynamic factor analysis |
0 |
0 |
0 |
122 |
0 |
2 |
24 |
370 |
| Forecasting government bond yields with large Bayesian vector autoregressions |
0 |
0 |
1 |
141 |
2 |
3 |
23 |
378 |
| Forecasting in factor augmented regressions under structural change |
0 |
1 |
3 |
5 |
0 |
1 |
13 |
23 |
| Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods |
0 |
0 |
4 |
28 |
0 |
0 |
10 |
84 |
| Forecasting large datasets with Bayesian reduced rank multivariate models |
0 |
0 |
0 |
0 |
0 |
1 |
13 |
157 |
| Forecasting using predictive likelihood model averaging |
0 |
0 |
0 |
47 |
1 |
1 |
8 |
172 |
| Forecasting with measurement errors in dynamic models |
0 |
0 |
0 |
35 |
1 |
1 |
9 |
131 |
| GLS detrending-based unit root tests in nonlinear STAR and SETAR models |
0 |
0 |
0 |
54 |
0 |
0 |
9 |
144 |
| Generalised density forecast combinations |
0 |
0 |
1 |
49 |
1 |
3 |
19 |
159 |
| Getting PPP right: Identifying mean-reverting real exchange rates in panels |
1 |
1 |
1 |
189 |
1 |
1 |
21 |
676 |
| HOW PUZZLING IS THE PPP PUZZLE? AN ALTERNATIVE HALF‐LIFE MEASURE OF CONVERGENCE TO PPP |
0 |
0 |
0 |
0 |
0 |
1 |
14 |
112 |
| Hierarchical Time-Varying Estimation of Asset Pricing Models |
0 |
0 |
1 |
3 |
0 |
2 |
8 |
12 |
| How did consumers react to the COVID‐19 pandemic over time? |
0 |
0 |
1 |
8 |
0 |
1 |
9 |
36 |
| Incorporating lag order selection uncertainty in parameter inference for AR models |
0 |
1 |
1 |
11 |
0 |
1 |
14 |
53 |
| Inference for impulse response coefficients from multivariate fractionally integrated processes |
0 |
0 |
0 |
1 |
0 |
0 |
8 |
30 |
| Inference on Multivariate Heteroscedastic Time Varying Random Coefficient Models |
0 |
0 |
2 |
6 |
0 |
1 |
15 |
30 |
| Inference on stochastic time-varying coefficient models |
0 |
0 |
1 |
177 |
3 |
4 |
15 |
402 |
| Investigating the predictive ability of ONS big data‐based indicators |
0 |
0 |
1 |
4 |
0 |
1 |
14 |
22 |
| Jumps in option prices and their determinants: Real-time evidence from the E-mini S&P 500 options market |
0 |
0 |
0 |
1 |
1 |
2 |
17 |
42 |
| Kernel-based Volatility Generalised Least Squares |
0 |
0 |
0 |
11 |
0 |
1 |
13 |
43 |
| Large time‐varying parameter VARs: A nonparametric approach |
0 |
0 |
0 |
17 |
0 |
1 |
17 |
103 |
| Level shifts in stock returns driven by large shocks |
0 |
0 |
0 |
11 |
0 |
0 |
8 |
62 |
| Liquidity creation through efficient M&As: A viable solution for vulnerable banking systems? Evidence from a stress test under a panel VAR methodology |
0 |
0 |
0 |
21 |
2 |
2 |
27 |
138 |
| MULTIVARIATE METHODS FOR MONITORING STRUCTURAL CHANGE |
0 |
0 |
0 |
0 |
1 |
1 |
11 |
64 |
| Machine Learning for Economic Policy |
0 |
1 |
10 |
18 |
0 |
3 |
49 |
71 |
| Making a match: Combining theory and evidence in policy-oriented macroeconomic modeling |
0 |
0 |
1 |
185 |
1 |
4 |
19 |
484 |
| Making text count: Economic forecasting using newspaper text |
1 |
3 |
15 |
43 |
1 |
6 |
48 |
130 |
| Mean group instrumental variable estimation of time-varying large heterogeneous panels with endogenous regressors |
0 |
0 |
0 |
0 |
2 |
3 |
12 |
12 |
| Measurement of factor strength: Theory and practice |
0 |
0 |
1 |
5 |
2 |
4 |
17 |
49 |
| Measuring Conditional Persistence in Nonlinear Time Series* |
0 |
0 |
0 |
11 |
1 |
1 |
10 |
55 |
| Model Selection Criteria for Factor-Augmented Regressions-super- |
0 |
0 |
0 |
12 |
1 |
1 |
6 |
57 |
| Model Selection in Threshold Models |
0 |
0 |
0 |
2 |
0 |
0 |
11 |
20 |
| Modeling structural breaks in economic relationships using large shocks |
0 |
0 |
2 |
70 |
1 |
2 |
18 |
242 |
| Modified information criteria and selection of long memory time series models |
0 |
0 |
0 |
8 |
1 |
1 |
9 |
44 |
| Nonlinear Alternatives to Unit Root Tests and Public Finances Sustainability: Some Evidence from Latin American and Caribbean Countries* |
0 |
0 |
0 |
40 |
0 |
1 |
4 |
126 |
| Nonlinear autoregressive models and long memory |
0 |
0 |
0 |
13 |
0 |
0 |
5 |
45 |
| Nonlinear mean reversion in real exchange rates |
0 |
0 |
0 |
64 |
0 |
0 |
6 |
173 |
| Nonlinear models for strongly dependent processes with financial applications |
0 |
0 |
0 |
40 |
0 |
0 |
8 |
138 |
| On robust inference in time-series regression |
0 |
0 |
1 |
2 |
1 |
1 |
20 |
21 |
| On the estimation of short memory components in long memory time series models |
0 |
0 |
0 |
18 |
1 |
1 |
13 |
75 |
| Panels with non-stationary multifactor error structures |
0 |
0 |
1 |
269 |
0 |
4 |
32 |
766 |
| Prediction from ARFIMA models: Comparisons between MLE and semiparametric estimation procedures |
0 |
0 |
0 |
15 |
0 |
1 |
11 |
74 |
| Pure Significance Tests of the Unit Root Hypothesis Against Nonlinear Alternatives |
0 |
0 |
0 |
43 |
0 |
1 |
6 |
243 |
| Rational expectations and fixed-event forecasts: An application to UK inflation |
0 |
0 |
0 |
45 |
0 |
0 |
10 |
162 |
| Reducing labour market flexibility: A causal inference study on reform in The Netherlands |
0 |
0 |
1 |
2 |
0 |
1 |
18 |
25 |
| Resuscitating real interest rate parity: new evidence from panels |
0 |
0 |
0 |
4 |
0 |
0 |
4 |
27 |
| Revisiting useful approaches to data-rich macroeconomic forecasting |
0 |
0 |
0 |
37 |
1 |
2 |
12 |
123 |
| Robust Forecast Methods and Monitoring during Structural Change |
0 |
0 |
0 |
20 |
1 |
2 |
19 |
130 |
| Semiparametric Sieve-Type Generalized Least Squares Inference |
0 |
1 |
1 |
5 |
0 |
1 |
5 |
32 |
| Shifts in volatility driven by large stock market shocks |
0 |
0 |
0 |
8 |
0 |
1 |
10 |
94 |
| Small sample properties of the conditional least squares estimator in SETAR models |
0 |
0 |
0 |
50 |
0 |
1 |
10 |
190 |
| State-level wage Phillips curves |
0 |
0 |
1 |
6 |
0 |
2 |
14 |
38 |
| Statistical Tests and Estimators of the Rank of a Matrix and Their Applications in Econometric Modelling |
0 |
0 |
1 |
15 |
0 |
0 |
11 |
79 |
| Structural analysis with Multivariate Autoregressive Index models |
0 |
0 |
2 |
46 |
0 |
2 |
16 |
220 |
| TESTING FOR COINTEGRATION IN NONLINEAR SMOOTH TRANSITION ERROR CORRECTION MODELS |
1 |
1 |
1 |
131 |
3 |
4 |
22 |
328 |
| TESTING FOR EXOGENEITY IN THRESHOLD MODELS |
0 |
0 |
0 |
21 |
0 |
0 |
5 |
70 |
| TESTS OF THE MARTINGALE DIFFERENCE HYPOTHESIS USING BOOSTING AND RBF NEURAL NETWORK APPROXIMATIONS |
0 |
0 |
1 |
19 |
0 |
0 |
12 |
84 |
| THE ASYMPTOTIC DISTRIBUTION OF THE COINTEGRATION RANK ESTIMATOR UNDER THE AKAIKE INFORMATION CRITERION |
0 |
0 |
0 |
11 |
0 |
0 |
6 |
65 |
| Testing for ARCH in the presence of nonlinearity of unknown form in the conditional mean |
0 |
0 |
0 |
21 |
0 |
0 |
12 |
88 |
| Testing for Neglected Nonlinearity in Cointegrating Relationships* |
0 |
0 |
0 |
15 |
0 |
0 |
8 |
59 |
| Testing for Neglected Nonlinearity in Long-Memory Models |
0 |
0 |
0 |
12 |
0 |
1 |
13 |
52 |
| Testing for a unit root in the nonlinear STAR framework |
2 |
4 |
14 |
856 |
3 |
7 |
58 |
1,971 |
| Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects |
0 |
0 |
0 |
0 |
0 |
1 |
13 |
17 |
| Testing for strict stationarity in financial variables |
0 |
0 |
1 |
34 |
0 |
0 |
7 |
141 |
| Testing the Null Hypothesis of Nonstationary Long Memory Against the Alternative Hypothesis of a Nonlinear Ergodic Model |
0 |
0 |
0 |
36 |
0 |
0 |
10 |
156 |
| The Fifth Special Issue on Computational Econometrics |
0 |
0 |
0 |
32 |
0 |
0 |
6 |
130 |
| The Yen Real Exchange Rate may be Stationary after all: Evidence from Non‐linear Unit‐root Tests |
0 |
0 |
0 |
87 |
0 |
2 |
8 |
433 |
| Threshold models for trended time series |
0 |
0 |
0 |
22 |
0 |
1 |
10 |
86 |
| Time-varying Lasso |
0 |
0 |
1 |
88 |
1 |
3 |
17 |
223 |
| Time-varying cointegration with an application to the UK Great Ratios |
0 |
0 |
1 |
9 |
0 |
1 |
13 |
48 |
| Time-varying instrumental variable estimation |
0 |
0 |
5 |
24 |
1 |
2 |
19 |
79 |
| Unconventional monetary policies and the macroeconomy: The impact of the UK's QE2 and funding for lending scheme |
0 |
0 |
4 |
39 |
0 |
1 |
29 |
159 |
| Unit root tests in three-regime SETAR models |
0 |
0 |
0 |
52 |
0 |
3 |
24 |
370 |
| Unit‐root testing against the alternative hypothesis of up to m structural breaks |
0 |
0 |
1 |
88 |
0 |
1 |
13 |
267 |
| Variable selection in regression models using nonstandard optimisation of information criteria |
0 |
0 |
0 |
52 |
1 |
1 |
12 |
154 |
| Yes! uncovered interest parity does hold in the long run |
1 |
1 |
2 |
2 |
4 |
7 |
46 |
46 |
| Total Journal Articles |
11 |
28 |
138 |
7,101 |
86 |
246 |
2,163 |
26,402 |
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