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A Bayesian Local Likelihood Method for Modelling Parameter Time Variation in DSGE Models |
0 |
0 |
0 |
3 |
0 |
1 |
3 |
59 |

A Bootstrap Invariance Principle for Highly Nonstationary Long Memory Processes |
0 |
0 |
1 |
3 |
0 |
0 |
4 |
12 |

A Bootstrap Procedure for Panel Datasets with Many Cross-Sectional Units |
0 |
2 |
8 |
21 |
0 |
4 |
14 |
41 |

A Comparison of Estimation Methods for Dynamic Factor Models of Large Dimensions |
0 |
0 |
1 |
4 |
1 |
1 |
5 |
24 |

A Dynamic Factor Analysis of Financial Contagion in Asia |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
8 |

A Generalised Fractional Differencing Bootstrap for Long Memory Processes |
0 |
0 |
0 |
25 |
0 |
0 |
0 |
28 |

A New Approach for Detecting Shifts in Forecast Accuracy |
0 |
0 |
0 |
53 |
0 |
1 |
3 |
85 |

A New Method for Determining the Number of Factors in Factor Models with Large Datasets |
0 |
0 |
1 |
8 |
0 |
0 |
4 |
25 |

A New Nonparametric Test of Cointegration Rank |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
7 |

A New Test for Market Efficiency and Uncovered Interest Parity |
0 |
0 |
0 |
10 |
0 |
0 |
3 |
17 |

A New Test for Market Efficiency and Uncovered Interest Parity |
0 |
0 |
2 |
24 |
0 |
0 |
4 |
21 |

A New Test forMarket Efficiency and Uncovered Interest Parity |
0 |
0 |
0 |
8 |
0 |
2 |
2 |
26 |

A Nonlinear Approach to Public Finance Sustainability in Latin America |
0 |
0 |
0 |
2 |
0 |
0 |
3 |
21 |

A Nonlinear Panel Data Model of Cross-Sectional Dependence |
0 |
0 |
1 |
131 |
0 |
0 |
1 |
279 |

A Nonlinear Panel Data Model of Cross-Sectional Dependence |
0 |
0 |
0 |
22 |
0 |
0 |
0 |
79 |

A Nonlinear Panel Model of Cross-sectional Dependence |
0 |
0 |
0 |
1 |
1 |
1 |
2 |
12 |

A Note on Covariance Stationarity Conditions for Dynamic Random Coefficient Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |

A Note on Joint Estimation of Common Cycles and Common Trends in Nonstationary Multivariate Systems |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |

A Note on an Iterative Least Squares Estimation Method for ARMA and VARMA Models |
0 |
0 |
0 |
3 |
0 |
1 |
3 |
19 |

A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models |
0 |
0 |
1 |
47 |
0 |
1 |
5 |
71 |

A Parametric Estimation Method for Dynamic Factor Models of Large Dimensions |
0 |
0 |
0 |
188 |
0 |
0 |
3 |
614 |

A Quality Assessment Framework for Maintaining & Publishing New Indicators |
0 |
0 |
0 |
3 |
0 |
1 |
3 |
9 |

A Radial Basis Function Artificial Neural Network Test for ARCH |
0 |
0 |
0 |
104 |
0 |
0 |
1 |
1,049 |

A Residual-based Threshold Method for Detection of Units that are Too Big to Fail in Large Factor Models |
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0 |
1 |
29 |
0 |
0 |
2 |
67 |

A Review of Forecasting Techniques for Large Data Sets |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
12 |

A Shrinkage Instrumental Variable Estimator for Large Datasets |
0 |
0 |
1 |
7 |
0 |
0 |
1 |
37 |

A Shrinkage Instrumental Variable Estimator for Large Datasets |
0 |
0 |
0 |
3 |
0 |
1 |
1 |
17 |

A Similarity-based Approach for Macroeconomic Forecasting |
0 |
0 |
1 |
61 |
1 |
1 |
2 |
95 |

A State Space Approach To The Policymaker's Data Uncertainty Problem |
0 |
0 |
0 |
65 |
0 |
0 |
0 |
180 |

A State Space Approach to Extracting the Signal from Uncertain Data |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
47 |

A Stochastic Variance Factor Model for Large Datasets and an Application to S&P Data |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
8 |

A Test for Serial Dependence Using Neural Networks |
0 |
1 |
2 |
4 |
0 |
1 |
5 |
20 |

A Test of M Structural Breaks Under the Unit Root Hypothesis |
0 |
0 |
0 |
63 |
0 |
0 |
1 |
365 |

A Testing Procedure for Determining the Number of Factors in Approximate Factor Models with Large Datasets |
1 |
1 |
4 |
11 |
1 |
1 |
5 |
25 |

A Time Varying DSGE Model with Financial Frictions |
0 |
0 |
0 |
8 |
0 |
0 |
1 |
37 |

A UK financial conditions index using targeted data reduction: forecasting and structural identification |
0 |
0 |
0 |
30 |
0 |
0 |
2 |
59 |

A UK financial conditions index using targeted data reduction: forecasting and structural identification |
0 |
0 |
1 |
24 |
0 |
0 |
6 |
92 |

A UK financial conditions index using targeted data reduction: forecasting and structural identification |
0 |
0 |
0 |
34 |
0 |
0 |
1 |
97 |

A comprehensive evaluation of macroeconomic forecasting methods |
0 |
0 |
2 |
226 |
0 |
1 |
10 |
493 |

A new approach for detecting shifts in forecast accuracy |
0 |
0 |
0 |
74 |
0 |
1 |
1 |
93 |

A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models |
0 |
0 |
0 |
59 |
0 |
0 |
3 |
166 |

A state space approach to extracting the signal from uncertain data |
0 |
0 |
1 |
72 |
0 |
0 |
1 |
284 |

A time varying parameter structural model of the UK economy |
0 |
0 |
1 |
120 |
0 |
1 |
4 |
131 |

Adaptive Forcasting in the Presence of Recent and Ongoing Structural Change |
0 |
0 |
0 |
33 |
0 |
0 |
1 |
157 |

Adaptive Forecasting in the Presence of Recent and Ongoing Structural Change |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
19 |

Adaptive forecasting in the presence of recent and ongoing structural change |
0 |
0 |
2 |
60 |
0 |
0 |
4 |
122 |

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 |
0 |
495 |

Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns |
0 |
0 |
2 |
135 |
0 |
0 |
3 |
308 |

Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
18 |

An Automatic Leading Indicator of Economic Activity: Forecasting GDP Growth for European Countries |
0 |
0 |
0 |
282 |
1 |
2 |
6 |
1,601 |

An Evaluation Framework for Targeted Indicators Aggregates vs. Disaggregates |
0 |
0 |
0 |
6 |
0 |
0 |
2 |
7 |

An Investigation of Current Account Solvency in Latin America Using Non Linear Stationarity Tests |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
11 |

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 |
1 |
44 |

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 |
0 |
0 |
0 |
263 |

Assessing the economy-wide effects of quantitative easing |
0 |
0 |
3 |
500 |
0 |
3 |
18 |
1,325 |

Big Data & Macroeconomic Nowcasting: Methodological Review |
2 |
3 |
22 |
274 |
4 |
7 |
48 |
487 |

Big Data Analytics: A New Perspective |
0 |
0 |
0 |
35 |
1 |
2 |
2 |
96 |

Big Data Analytics: A New Perspective |
0 |
0 |
0 |
23 |
0 |
0 |
0 |
90 |

Big Data Econometrics: Now Casting and Early Estimates |
0 |
2 |
8 |
203 |
3 |
5 |
21 |
267 |

Big data analytics: a new perspective |
0 |
0 |
1 |
218 |
0 |
2 |
4 |
288 |

Block Bootstrap and Long Memory |
0 |
0 |
1 |
4 |
0 |
1 |
2 |
20 |

Boosting Estimation of RBF Neural Networks for Dependent Data |
0 |
0 |
0 |
1 |
0 |
0 |
3 |
13 |

Bootstrap Statistical Tests of Rank Determination for System Identification |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
8 |

Breaks in DSGE models |
0 |
0 |
1 |
45 |
0 |
0 |
3 |
110 |

Choosing between persistent and stationary volatility |
0 |
0 |
0 |
56 |
0 |
1 |
3 |
85 |

Cluster Analysis of Panel Choosing the Optimal Set of Instruments from Large Instrument Setsusing Non-Standard Optimisation of Information Criteria |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
9 |

Cluster Analysis of Panel Datasets using Non-Standard Optimisation of Information Criteria |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
13 |

Cointegrating VAR models with endogenous I(0) variables: theoretical extensions and an application to UK monetary policy |
0 |
0 |
0 |
166 |
0 |
0 |
0 |
654 |

Common correlated effect cross-sectional dependence corrections for non-linear conditional mean panel models |
0 |
0 |
2 |
69 |
0 |
1 |
5 |
135 |

Cross-sectional Averaging and Instrumental Variable Estimation with Many Weak Instruments |
0 |
0 |
0 |
6 |
0 |
0 |
2 |
25 |

Deep Neural Network Estimation in Panel Data Models |
0 |
0 |
1 |
26 |
1 |
2 |
13 |
24 |

Deep Neural Network Estimation in Panel Data Models |
0 |
0 |
0 |
4 |
0 |
1 |
7 |
14 |

Determining the Poolability of Individual Series in Panel Datasets |
0 |
0 |
1 |
4 |
1 |
1 |
2 |
29 |

Determining the Stationarity Properties of Individual Series in Panel Datasets |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
6 |

Dynamic Factor Extraction of Cross-Sectional Dependence in Panel Unit Root Tests |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
10 |

Estimating Deterministically Time-Varying Variances in Regression Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
8 |

Estimating Time-Variation in Measurement Error from Data Revisions: An Application to Forecasting in Dynamic Models |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
12 |

Estimating Time-Varying DSGE Models Using Minimum Distance Methods |
0 |
0 |
0 |
10 |
0 |
0 |
0 |
67 |

Estimating the rank of the spectral density matrix |
0 |
0 |
0 |
129 |
0 |
0 |
0 |
430 |

Estimating time-variation in measurement error from data revisions; an application to forecasting in dynamic models |
0 |
0 |
0 |
52 |
0 |
0 |
1 |
253 |

Estimating time-varying DSGE models using minimum distance methods |
0 |
0 |
0 |
119 |
0 |
0 |
0 |
163 |

Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets |
0 |
0 |
0 |
159 |
0 |
0 |
1 |
156 |

Estimation and Inference for Multi-dimensional Heterogeneous Panel Datasets with Hierarchical Multi-factor Error Structure |
0 |
0 |
0 |
84 |
0 |
0 |
1 |
130 |

Estimation and Inference in a Non-Linear State Space Model: Durable Consumption |
0 |
0 |
0 |
193 |
0 |
0 |
0 |
448 |

Estimation of time-varying covariance matrices for large datasets |
0 |
0 |
1 |
1 |
0 |
0 |
4 |
5 |

Evaluating macroeconomic models of the business cycle |
0 |
0 |
0 |
69 |
0 |
0 |
1 |
234 |

Evolving UK and US macroeconomic dynamics through the lens of a model of deterministic structural change |
0 |
0 |
0 |
52 |
0 |
0 |
0 |
129 |

Expansionary and contractionary fiscal multipliers in the U.S |
0 |
0 |
0 |
5 |
0 |
0 |
2 |
5 |

Exponent of Cross-sectional Dependence for Residuals |
0 |
0 |
1 |
34 |
0 |
0 |
2 |
77 |

Exponent of Cross-sectional Dependence: Estimation and Inference |
0 |
0 |
0 |
53 |
0 |
1 |
3 |
219 |

Exponent of Cross-sectional Dependence: Estimation and Inference |
0 |
0 |
1 |
74 |
0 |
0 |
1 |
227 |

Exponent of Cross-sectional Dependence: Estimation and Inference |
0 |
0 |
0 |
148 |
0 |
0 |
2 |
312 |

Exponent of cross-sectional dependence for residuals |
0 |
0 |
0 |
11 |
0 |
0 |
3 |
45 |

Factor Analysis Using Subspace Factor Models: Some Theoretical Results and an Application to UK Inflation Forecasting |
0 |
0 |
0 |
1 |
0 |
0 |
2 |
10 |

Factor based identification-robust inference in IV regressions |
0 |
0 |
1 |
47 |
1 |
1 |
2 |
90 |

Factor-GMM Estimation with Large Sets of Possibly Weak Instruments |
0 |
0 |
1 |
3 |
0 |
0 |
5 |
21 |

Factor-GMM Estimation with Large Sets of Possibly Weak Instruments |
0 |
0 |
0 |
23 |
1 |
1 |
5 |
106 |

Forecast combination and the Bank of England’s suite of statistical forecasting models |
0 |
0 |
0 |
325 |
0 |
0 |
5 |
939 |

Forecasting Exchange Rates with a Large Bayesian VAR |
0 |
0 |
0 |
10 |
1 |
4 |
8 |
36 |

Forecasting Exchange Rates with a Large Bayesian VAR |
1 |
1 |
1 |
173 |
1 |
1 |
3 |
412 |

Forecasting Exchange Rates with a Large Bayesian VAR |
1 |
2 |
2 |
74 |
1 |
2 |
5 |
265 |

Forecasting Financial Crises and Contagion in Asia Using Dynamic Factor Analysis |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
18 |

Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis |
0 |
0 |
0 |
227 |
0 |
0 |
0 |
503 |

Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis |
0 |
0 |
0 |
203 |
0 |
1 |
1 |
520 |

Forecasting Government Bond Yields with Large Bayesian VARs |
0 |
0 |
1 |
9 |
0 |
0 |
5 |
40 |

Forecasting Government Bond Yields with Large Bayesian VARs |
0 |
0 |
0 |
36 |
0 |
0 |
0 |
136 |

Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models |
0 |
0 |
0 |
62 |
0 |
0 |
1 |
209 |

Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models |
0 |
0 |
0 |
144 |
0 |
0 |
2 |
308 |

Forecasting Large Datasets with Reduced Rank Multivariate Models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
10 |

Forecasting UK GDP growth with large survey panels |
0 |
1 |
2 |
40 |
0 |
1 |
8 |
54 |

Forecasting UK inflation bottom up |
1 |
3 |
17 |
105 |
4 |
12 |
61 |
389 |

Forecasting Using Predictive Likelihood Model Averaging |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
18 |

Forecasting Value-at-Risk using deep neural network quantile regression |
0 |
1 |
7 |
63 |
0 |
4 |
21 |
58 |

Forecasting euro area inflation using dynamic factor measures of underlying inflation |
0 |
0 |
0 |
103 |
0 |
0 |
3 |
258 |

Forecasting in the presence of recent structural change |
0 |
0 |
0 |
78 |
0 |
0 |
0 |
150 |

Forecasting in the presence of recent structural change |
0 |
0 |
4 |
172 |
0 |
4 |
14 |
325 |

Forecasting in the presence of recent structural change |
0 |
0 |
0 |
31 |
0 |
0 |
0 |
110 |

Forecasting using Bayesian and Information Theoretic Model Averaging: An Application to UK Inflation |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
32 |

Forecasting using Bayesian and information theoretic model averaging: an application to UK inflation |
0 |
0 |
0 |
16 |
0 |
0 |
0 |
53 |

Forecasting using Bayesian and information theoretic model averaging: an application to UK inflation |
0 |
0 |
0 |
137 |
0 |
1 |
3 |
379 |

Forecasting with Dynamic Models using Shrinkage-based Estimation |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
15 |

Forecasting with Measurement Errors in Dynamic Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
18 |

Forecasting with measurement errors in dynamic models |
0 |
0 |
0 |
143 |
0 |
0 |
2 |
499 |

Forecasting with measurement errors in dynamic models |
0 |
0 |
0 |
116 |
0 |
0 |
0 |
412 |

GLS Detrending for Nonlinear Unit Root Tests |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
6 |

GLS Detrending-Based Unit Root Tests in Nonlinear STAR and SETAR Frameworks |
0 |
0 |
0 |
272 |
0 |
0 |
0 |
760 |

Generalised Density Forecast Combinations |
0 |
0 |
0 |
119 |
0 |
0 |
1 |
179 |

Generalised Density Forecast Combinations |
0 |
0 |
0 |
3 |
0 |
0 |
2 |
38 |

Generalised density forecast combinations |
1 |
1 |
1 |
44 |
2 |
2 |
3 |
101 |

Getting PPP Right: Identifying Mean Reverting Real Exchange Rates in Panels |
0 |
0 |
0 |
59 |
1 |
1 |
1 |
221 |

Getting PPP Right: Identifying Mean-Reverting Real Exchange Rates in Panels |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
20 |

Getting PPP Right: Identifying Mean-Reverting Real Exchange Rates in Panels |
0 |
0 |
1 |
8 |
0 |
0 |
2 |
31 |

Hierarchical Time Varying Estimation of a Multi Factor Asset Pricing Model |
0 |
0 |
0 |
44 |
0 |
0 |
0 |
69 |

High Dimensional Generalised Penalised Least Squares |
1 |
1 |
1 |
28 |
2 |
2 |
5 |
44 |

How Puzzling is the PPP Puzzle? An Alternative Half-Life Measure of Convergence to PPP |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
24 |

How Puzzling is the PPP Puzzle? An Alternative Half-Life Measure of convergence to PPP |
0 |
0 |
1 |
124 |
0 |
0 |
5 |
396 |

Import prices and exchange rate pass-through: theory and evidence from the United Kingdom |
0 |
0 |
1 |
780 |
0 |
0 |
2 |
2,081 |

Impulse Response Functions from Structural Dynamic Factor Models: A Monte Carlo Evaluation |
0 |
0 |
0 |
144 |
0 |
0 |
0 |
528 |

Impulse Response Functions from Structural Dynamic Factor Models:A Monte Carlo Evaluation |
0 |
0 |
2 |
348 |
0 |
1 |
7 |
1,050 |

Incorporating lag order selection uncertainty in parameter inference for AR models |
0 |
0 |
0 |
48 |
0 |
0 |
0 |
322 |

Inference for Impulse Response Coefficients From Multivariate Fractionally Integrated Processes |
0 |
0 |
0 |
39 |
0 |
0 |
0 |
32 |

Inference on Multivariate Heteroscedastic Time Varying Random Coefficient Models |
0 |
0 |
0 |
2 |
0 |
0 |
2 |
12 |

Information Criteria, Model Selection Uncertainty and the Determination of Cointegration Rank |
0 |
0 |
0 |
64 |
0 |
0 |
3 |
443 |

Inward investment and technical progress in the United Kingdom manufacturing sector |
0 |
0 |
0 |
105 |
0 |
0 |
0 |
335 |

Jumps in Option Prices and Their Determinants: Real-time Evidence from the E-mini S&P 500 Option Market |
0 |
0 |
2 |
8 |
0 |
0 |
6 |
37 |

Large Time-Varying Parameter VARs: A Non-Parametric Approach |
0 |
1 |
1 |
85 |
0 |
1 |
3 |
120 |

Large time-varying parameter VARs: a non-parametric approach |
0 |
0 |
2 |
121 |
1 |
2 |
8 |
177 |

Making a match: Combining theory and evidence in policy-oriented macroeconomic modelling |
0 |
0 |
0 |
91 |
0 |
1 |
3 |
189 |

Making a match: combining theory and evidence in policy-oriented macroeconomic modelling |
0 |
0 |
0 |
129 |
0 |
0 |
3 |
423 |

Making text count: economic forecasting using newspaper text |
0 |
2 |
3 |
101 |
1 |
4 |
18 |
214 |

Mean Group Instrumental Variable Estimation of Time-Varying Large Heterogeneous Panels with Endogenous Regressors |
0 |
0 |
16 |
16 |
1 |
1 |
13 |
13 |

Measurement of Factor Strenght: Theory and Practice |
0 |
0 |
1 |
43 |
1 |
1 |
3 |
105 |

Measurement of Factor Strength: Theory and Practice |
0 |
0 |
0 |
30 |
0 |
1 |
1 |
59 |

Measuring Conditional Persistence in Time Series |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
8 |

Model Selection Uncertainty and Dynamic Models |
0 |
0 |
0 |
55 |
0 |
0 |
1 |
264 |

Model Selection in Threshold Models |
0 |
0 |
1 |
692 |
0 |
1 |
2 |
2,303 |

Model selection criteria for factor-augmented regressions |
0 |
0 |
5 |
105 |
2 |
2 |
13 |
404 |

Modelling Core Inflation for the UK Using a New Dynamic Factor Estimation Method and a Large Disaggregated Price Index Dataset |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
16 |

Multivariate Methods for Monitoring Structural Change |
0 |
0 |
0 |
1 |
0 |
0 |
2 |
32 |

Multivariate methods for monitoring structural change |
0 |
0 |
0 |
55 |
0 |
0 |
0 |
147 |

Non-Nested Models and the Likelihood Ratio Statistic: A Comparison of Simulation and Bootstrap Based Tests |
0 |
0 |
0 |
2 |
0 |
0 |
4 |
28 |

Non-nested Models and the likelihood Ratio Statistic: A Comparison of Simulation and Bootstrap-based Tests |
1 |
1 |
1 |
400 |
1 |
1 |
2 |
1,426 |

Nonlinear Autoregressive Models and Long Memory |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
10 |

Nonlinear Modelling of Autoregressive Structural Breaks in a US Diffusion Index Dataset |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
16 |

Nonlinear Models with Strongly Dependent Processes and Applications to Forward Premia and Real Exchange Rates |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
11 |

On Robust Inference in Time Series Regression |
0 |
0 |
0 |
122 |
1 |
3 |
7 |
36 |

On Robust Inference in Time Series Regression |
0 |
1 |
1 |
1 |
3 |
7 |
7 |
7 |

On Robust Inference in Time Series Regression |
0 |
1 |
4 |
20 |
0 |
5 |
12 |
41 |

On Testing for Diagonality of Large Dimensional Covariance Matrices |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |

Panels with Nonstationary Multifactor Error Structures |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
27 |

Panels with Nonstationary Multifactor Error Structures |
0 |
0 |
0 |
78 |
0 |
0 |
1 |
308 |

Panels with Nonstationary Multifactor Error Structures |
0 |
0 |
0 |
52 |
0 |
0 |
1 |
220 |

Panels with Nonstationary Multifactor Error Structures |
0 |
0 |
1 |
233 |
0 |
0 |
2 |
640 |

Panels with nonstationary multifactor error structures |
0 |
0 |
0 |
16 |
0 |
0 |
2 |
95 |

Parsimonious estimation with many instruments |
0 |
0 |
0 |
30 |
0 |
0 |
0 |
88 |

Rational expectations and fixed-event forecasts: an application to UK inflation |
0 |
0 |
0 |
149 |
0 |
0 |
1 |
582 |

Real Time Indicators During the COVID-19 Pandemic Individual Predictors & Selection |
0 |
0 |
0 |
14 |
1 |
2 |
5 |
18 |

Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting |
0 |
0 |
0 |
1 |
0 |
0 |
2 |
22 |

Revisiting useful approaches to data-rich macroeconomic forecasting |
0 |
0 |
0 |
145 |
0 |
0 |
0 |
341 |

Semiparametric Sieve-Type GLS Inference in Regressions with Long-Range Dependence |
0 |
0 |
0 |
3 |
0 |
0 |
2 |
13 |

Sieve Bootstrap for Strongly Dependent Stationary Processes |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
16 |

Spectral based methods to identify common trends and common cycles |
0 |
0 |
0 |
181 |
0 |
0 |
0 |
572 |

State-level wage Phillips curves |
0 |
0 |
1 |
3 |
0 |
0 |
1 |
12 |

State-level wage Phillips curves |
0 |
0 |
0 |
20 |
0 |
0 |
0 |
45 |

State-level wage Phillips curves |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
28 |

Statistical Tests of the Rank of a Matrix and Their Applications in Econometric Modelling |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
15 |

Statistical tests and estimators of the rank of a matrix and their applications in econometric modelling |
0 |
0 |
0 |
66 |
0 |
0 |
0 |
133 |

Stochastic Volatility Driven by Large Shocks |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
18 |

Stock returns predictability with unstable predictors |
0 |
0 |
1 |
10 |
0 |
0 |
3 |
11 |

Stock returns predictability with unstable predictors |
0 |
0 |
0 |
74 |
1 |
1 |
4 |
53 |

Structural Analysis with Multivariate Autoregressive Index Models |
0 |
1 |
1 |
85 |
0 |
1 |
2 |
118 |

Structural Breaks in Inflation Dynamics |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
490 |

Testing for ARCH in the Presence of Nonlinearity of Unknown Form in the Conditional Mean |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
6 |

Testing for Cointegration in Nonlinear STAR Error Correction Models |
0 |
0 |
0 |
3 |
0 |
0 |
2 |
26 |

Testing for Correlated Factor Loadings in Cross Sectionally Dependent Panels |
0 |
0 |
1 |
52 |
0 |
0 |
2 |
101 |

Testing for Exogeneity in Nonlinear Threshold Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |

Testing for Neglected Nonlinearity in Cointegrating Relationships |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
8 |

Testing for Neglected Nonlinearity in Long Memory Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
6 |

Testing for Nonstationary Long Memory against Nonlinear Ergodic Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |

Testing for Strict Stationarity |
0 |
0 |
0 |
3 |
1 |
1 |
2 |
21 |

Testing for Structural Breaks in Nonlinear Dynamic Models Using Artificial Neural Network Approximations |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
16 |

Testing for a Linear Unit Root against Nonlinear Threshold Stationarity |
0 |
0 |
0 |
109 |
0 |
0 |
0 |
319 |

Testing for a Unit Root against Nonlinear STAR Models |
0 |
0 |
0 |
182 |
0 |
0 |
1 |
644 |

Testing for a Unit Root against Nonlinear STAR Models |
0 |
0 |
1 |
160 |
0 |
0 |
1 |
320 |

Testing for nonlinear cointegration between stock prices and dividends |
0 |
0 |
0 |
192 |
0 |
0 |
1 |
425 |

Testing the Martingale Difference Hypothesis Using Neural Network Approximations |
0 |
0 |
0 |
1 |
0 |
0 |
2 |
8 |

Testing the rank of the Hankel matrix: a statistical approach |
0 |
0 |
0 |
108 |
0 |
0 |
1 |
596 |

Tests for Deterministic Parametric Structural Change in Regression Models |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
5 |

Tests of Rank in Reduced Rank Regression Models |
0 |
0 |
0 |
61 |
0 |
0 |
2 |
602 |

The Elusive Persistence: Wage and Price Rigidities, the Phillips Curve, and Inflation Dynamics |
1 |
2 |
4 |
5 |
1 |
2 |
5 |
13 |

The Forecasting Performance of the OECD Composite Leading Indicators for France, Germany, Italy |
0 |
0 |
0 |
183 |
0 |
0 |
0 |
1,030 |

The Impact of Large Structural Shocks on Economic Relationships: Evidence from Oil Price Shocks |
0 |
0 |
0 |
4 |
1 |
1 |
2 |
13 |

The Role of Search Frictions and Bargaining for Inflation Dynamics |
0 |
0 |
0 |
41 |
0 |
1 |
3 |
174 |

The Yen Real Exchange Rate May Be Stationary after All: Evidence from Nonlinear Unit-Root Tests |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
41 |

The yen real exchange rate may be stationary after all: evidence from non-linear unit root tests |
0 |
0 |
0 |
167 |
0 |
0 |
1 |
728 |

Threshold Models for Trended Time Series |
0 |
0 |
0 |
843 |
0 |
0 |
3 |
2,463 |

Time varying cointegration and the UK Great Ratios |
0 |
0 |
0 |
30 |
0 |
0 |
1 |
44 |

Time varying cointegration and the UK great ratios |
0 |
0 |
1 |
36 |
1 |
1 |
7 |
75 |

Time-Varying Instrumental Variable Estimation |
0 |
0 |
1 |
40 |
0 |
0 |
3 |
96 |

Time-Varying Instrumental Variable Estimation |
0 |
0 |
0 |
49 |
0 |
1 |
1 |
64 |

Time-varying cointegration and the UK great ratios |
0 |
0 |
0 |
30 |
0 |
0 |
0 |
45 |

UK Economic Conditions during the Pandemic: Assessing the Economy using ONS Faster Indicators |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
13 |

Unconventional monetary policies and the macroeconomy: the impact of the United Kingdom's QE2 and Funding for Lending Scheme |
0 |
0 |
1 |
124 |
0 |
0 |
4 |
292 |

Unit Root Testing against the Alternative Hypothesis of up to m Structural Breaks |
0 |
0 |
1 |
7 |
0 |
0 |
1 |
16 |

Unit Root Tests in Three-Regime SETAR Models |
0 |
0 |
0 |
240 |
0 |
0 |
1 |
658 |

Unit Root Tests in Three-Regime SETAR Models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
15 |

Using Extraneous Information and GMM to Estimate Threshold Parameters in TAR Models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
10 |

Variable Selection using Non-Standard Optimisation of Information Criteria |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
11 |

Total Working Papers |
10 |
28 |
170 |
15,731 |
47 |
134 |
677 |
46,459 |