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A Bayesian analysis of multiple-output production frontier |
0 |
0 |
0 |
16 |
0 |
0 |
1 |
447 |

A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve |
0 |
1 |
3 |
82 |
0 |
3 |
8 |
163 |

A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve |
0 |
1 |
1 |
60 |
0 |
1 |
3 |
103 |

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models |
0 |
0 |
0 |
52 |
0 |
0 |
1 |
80 |

A Comparison of Forecasting Procedures For Macroeconomic Series: The Contribution of Structural Break Models |
0 |
0 |
0 |
178 |
0 |
0 |
1 |
216 |

A Comparison of Forecasting Procedures for Macroeconomic Series: the Contribution of Structural Break Models |
0 |
0 |
0 |
83 |
0 |
0 |
1 |
143 |

A Decision Theoretic Analysis of the Unit Root Hypothesis Using Mixtures of Elliptical Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
352 |

A New Index of Financial Conditions |
0 |
0 |
3 |
141 |
0 |
0 |
9 |
714 |

A New Index of Financial Conditions |
0 |
0 |
1 |
74 |
0 |
2 |
5 |
699 |

A New Model Of Trend Inflation |
0 |
0 |
1 |
76 |
0 |
0 |
1 |
181 |

A New Model of Inflation, Trend Inflation, and Long-Run Inflation Expectations |
0 |
1 |
1 |
147 |
0 |
2 |
10 |
230 |

A New Model of Trend Inflation |
0 |
0 |
0 |
112 |
0 |
1 |
5 |
229 |

A New Model of Trend Inflation |
0 |
0 |
1 |
99 |
0 |
0 |
2 |
207 |

A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
3 |

A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies |
0 |
0 |
0 |
15 |
0 |
0 |
1 |
51 |

A comparison of Forecasting Procedures for Macroeconomic Series: The Contribution of Structural Break Models |
0 |
1 |
1 |
59 |
0 |
1 |
1 |
151 |

A comparison of forecasting procedures for macroeconomic series: the contribution of structural break models |
0 |
0 |
1 |
61 |
0 |
0 |
2 |
75 |

A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |

A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
24 |

A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models |
0 |
0 |
0 |
1 |
1 |
2 |
4 |
33 |

A flexible approach to parametric inference in nonlinear and time varying time series models |
0 |
0 |
0 |
11 |
0 |
1 |
2 |
62 |

A flexible approach to parametric inference in nonlinear time series models |
0 |
0 |
0 |
184 |
0 |
0 |
1 |
382 |

A new index of financial conditions |
0 |
0 |
1 |
59 |
1 |
2 |
3 |
149 |

A new index of financial conditions |
0 |
1 |
3 |
111 |
0 |
2 |
7 |
379 |

A new look at variation in employment growth in Canada |
0 |
0 |
0 |
39 |
0 |
0 |
1 |
152 |

A new model of trend inflation |
0 |
0 |
0 |
38 |
0 |
0 |
3 |
108 |

Alternative efficiency measures for multiple-output production |
0 |
0 |
0 |
8 |
0 |
0 |
2 |
367 |

An Investigation of Thresholds in Air Pollution-Mortality Effects |
0 |
0 |
0 |
176 |
0 |
0 |
1 |
837 |

Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs |
0 |
1 |
5 |
40 |
1 |
4 |
14 |
47 |

Are apparent findings of nonlinearity due to structural instability in economic time series? |
0 |
0 |
0 |
146 |
0 |
0 |
0 |
456 |

Bayesian Analysis of Endogenous Delay Threshold Models |
0 |
0 |
0 |
99 |
1 |
1 |
3 |
301 |

Bayesian Analysis of Long Memory and Persistence using ARFIMA Models |
0 |
0 |
0 |
330 |
0 |
1 |
1 |
1,384 |

Bayesian Analysis of Long Memory and Persistence using ARFIMA Models |
0 |
0 |
0 |
11 |
0 |
0 |
0 |
383 |

Bayesian Analysis of Long Memory and Persistence using ARFIMA Models |
0 |
1 |
2 |
731 |
0 |
1 |
5 |
2,315 |

Bayesian Analysis of Stochastic Frontier Models |
0 |
1 |
2 |
37 |
0 |
1 |
5 |
1,309 |

Bayesian Approaches to Cointegration |
0 |
0 |
2 |
275 |
0 |
1 |
8 |
618 |

Bayesian Compressed Vector Autoregressions |
0 |
0 |
0 |
30 |
0 |
0 |
1 |
67 |

Bayesian Compressed Vector Autoregressions |
0 |
0 |
2 |
231 |
0 |
1 |
6 |
426 |

Bayesian Compressed Vector Autoregressions |
0 |
0 |
0 |
27 |
0 |
0 |
1 |
45 |

Bayesian Compressed Vector Autoregressions |
0 |
1 |
1 |
38 |
0 |
2 |
3 |
92 |

Bayesian Econometric Methods |
0 |
0 |
0 |
4 |
3 |
8 |
30 |
624 |

Bayesian Efficiency Analysis through Individual Effects: Hospital Cost Frontiers |
0 |
0 |
0 |
32 |
0 |
0 |
1 |
729 |

Bayesian Forecasting in the 21st Century: A Modern Review |
2 |
20 |
71 |
71 |
2 |
7 |
33 |
33 |

Bayesian Forecasting using Stochastic Search Variable Selection in a VAR Subject to Breaks |
0 |
1 |
1 |
64 |
0 |
2 |
8 |
66 |

Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations |
1 |
1 |
3 |
34 |
1 |
1 |
4 |
50 |

Bayesian Inference in a Cointegrating Panel Data Model |
1 |
1 |
1 |
270 |
2 |
2 |
2 |
637 |

Bayesian Inference in a Cointegrating Panel Data Model |
0 |
0 |
2 |
15 |
0 |
0 |
3 |
59 |

Bayesian Inference in a Time Varying Cointegration Model |
0 |
0 |
0 |
58 |
0 |
0 |
2 |
153 |

Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
36 |

Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
2 |
31 |
2 |
2 |
17 |
139 |

Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
1 |
9 |
0 |
0 |
3 |
62 |

Bayesian Inference in the Time Varying Cointegration Model* |
0 |
0 |
1 |
80 |
0 |
0 |
2 |
190 |

Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
11 |
0 |
0 |
2 |
65 |

Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
141 |
0 |
0 |
3 |
282 |

Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
29 |
0 |
0 |
2 |
126 |

Bayesian Model Averaging in the Instrumental Variable Regression Model* |
0 |
0 |
0 |
39 |
0 |
0 |
2 |
84 |

Bayesian Modeling of Time-Varying Parameters Using Regression Trees |
0 |
76 |
78 |
78 |
0 |
11 |
13 |
13 |

Bayesian Modeling of Time-varying Parameters Using Regression Trees |
1 |
3 |
106 |
106 |
1 |
3 |
30 |
30 |

Bayesian Multivariate Time Series Methods for Empirical Macroeconomics |
3 |
19 |
86 |
2,539 |
18 |
61 |
259 |
5,903 |

Bayesian Multivariate Time Series Methods for Empirical Macroeconomics |
0 |
2 |
12 |
580 |
0 |
6 |
32 |
1,429 |

Bayesian Semiparametric Inference in Multiple Equation Models |
0 |
0 |
0 |
144 |
0 |
0 |
0 |
524 |

Bayesian Variants of Some Classical Semiparametric Regression Techniques |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
402 |

Bayesian Variants of Some classical Semiparametric Regression Techniques |
0 |
1 |
1 |
112 |
0 |
1 |
2 |
273 |

Bayesian analysis of long memory and persistence using ARFIMA models |
0 |
0 |
0 |
2 |
0 |
0 |
2 |
25 |

Bayesian approaches to cointegratrion |
0 |
0 |
0 |
31 |
0 |
0 |
1 |
97 |

Bayesian dynamic variable selection in high dimensions |
0 |
0 |
0 |
9 |
0 |
0 |
3 |
33 |

Bayesian dynamic variable selection in high dimensions |
1 |
1 |
8 |
94 |
1 |
2 |
32 |
173 |

Bayesian dynamic variable selection in high dimensions |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
4 |

Bayesian efficiency analysis through individual effects: Hospital cost frontiers |
0 |
0 |
1 |
5 |
0 |
1 |
5 |
32 |

Bayesian efficiency analysis with a flexible cost function |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
13 |

Bayesian efficiency analysis with a flexible form: The aim cost function |
0 |
0 |
0 |
8 |
0 |
0 |
1 |
49 |

Bayesian efficiency analysis with a flexible form: The aim cost function |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |

Bayesian inference in models based on equilibrium search theory |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
193 |

Bayesian long-run prediction in time series models |
0 |
0 |
1 |
6 |
0 |
1 |
3 |
33 |

Bayesian modelling of catch in a Northwest Atlantic Fishery (first version) |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
155 |

Comparing the Performance of Baseball Players: A Multiple Output Approach |
0 |
0 |
0 |
143 |
0 |
0 |
0 |
436 |

Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility |
0 |
0 |
0 |
18 |
0 |
0 |
0 |
26 |

Composite likelihood methods for large Bayesian VARs with stochastic volatility |
0 |
0 |
1 |
57 |
0 |
0 |
2 |
63 |

Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs |
0 |
0 |
2 |
30 |
1 |
2 |
6 |
58 |

Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs |
0 |
0 |
1 |
5 |
0 |
0 |
1 |
17 |

Cross-sectoral patterns of efficiency and technical change in manufacturing: A stochastic frontier analysis |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
181 |

Domestic Violence and Football in Glasgow: Are Reference Points Relevant? |
0 |
0 |
1 |
96 |
1 |
4 |
17 |
346 |

Domestic Violence and Football in Glasgow: Are Reference Points Relevant? |
0 |
0 |
0 |
28 |
0 |
1 |
1 |
73 |

Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods |
0 |
0 |
0 |
29 |
0 |
2 |
3 |
34 |

Dynamic asymmetries in US unemployment |
0 |
0 |
0 |
45 |
0 |
1 |
2 |
399 |

Dynamic probabilities of restrictions in state space models: An application to the Phillips curve |
0 |
0 |
0 |
10 |
0 |
0 |
0 |
45 |

Efficient Posterior Simulation for Cointegrated Models with Priors On the Cointegration Space |
0 |
0 |
1 |
158 |
0 |
1 |
3 |
442 |

Estimating Phillips Curves in Turbulent Times using the ECBs Survey of Professional Forecasters* |
0 |
0 |
1 |
94 |
0 |
0 |
1 |
192 |

Estimating Phillips Curves in Turbulent Times using the ECBâ€™s Survey of Professional Forecasters |
0 |
1 |
1 |
38 |
0 |
1 |
1 |
94 |

Estimating Phillips curves in turbulent times using the ECB's survey of professional forecasters |
0 |
1 |
1 |
103 |
0 |
1 |
1 |
194 |

Estimating the Impact on Efficiency of the Adoption of a Voluntary Environmental Standard: An Empirical Study of the Global Copper Mining Industry |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
79 |

Estimating the Impact on Efficiency of the Adoption of a Voluntary Environmental Standard: An Empirical Study of the Global Copper Mining Industry |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
88 |

Estimating the Impact on Efficiency of the Adoption of a Voluntary Environmental Standard: An Empirical Study of the Global Copper Mining Industry |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
36 |

Exchange rate predictability and dynamic Bayesian learning |
0 |
0 |
0 |
29 |
0 |
2 |
10 |
80 |

Exchange rate predictability and dynamic Bayesian learning |
0 |
0 |
0 |
117 |
0 |
3 |
7 |
253 |

Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models |
0 |
0 |
2 |
55 |
1 |
4 |
6 |
52 |

Forecasting Inflation Using Dynamic Model Averaging |
0 |
4 |
14 |
586 |
2 |
10 |
37 |
1,167 |

Forecasting Inflation Using Dynamic Model Averaging |
0 |
0 |
0 |
88 |
1 |
2 |
7 |
115 |

Forecasting Inflation Using Dynamic Model Averaging |
0 |
0 |
0 |
19 |
2 |
2 |
2 |
109 |

Forecasting Inflation Using Dynamic Model Averaging* |
1 |
1 |
1 |
170 |
1 |
1 |
6 |
337 |

Forecasting Low Frequency Macroeconomic Events with High Frequency Data |
0 |
1 |
2 |
58 |
0 |
1 |
8 |
93 |

Forecasting Substantial Data Revisions in the Presence of Model Uncertainty |
0 |
0 |
0 |
100 |
0 |
0 |
0 |
327 |

Forecasting Substantial Data Revisions in the Presence of Model Uncertainty |
0 |
0 |
0 |
68 |
0 |
0 |
0 |
301 |

Forecasting US Inflation Using Bayesian Nonparametric Models |
0 |
0 |
12 |
16 |
0 |
1 |
15 |
21 |

Forecasting US Inflation Using Bayesian Nonparametric Models |
0 |
7 |
30 |
118 |
5 |
15 |
65 |
95 |

Forecasting With High Dimensional Panel VARs |
0 |
1 |
6 |
333 |
1 |
2 |
10 |
553 |

Forecasting and Estimating Multiple Change-point Models with an Unknown Number of Change-points |
1 |
1 |
2 |
383 |
1 |
2 |
3 |
989 |

Forecasting and estimating multiple change-point models with an unknown number of change points |
0 |
0 |
0 |
251 |
0 |
0 |
1 |
804 |

Forecasting in Large Macroeconomic Panels using Bayesian Model Averaging |
0 |
0 |
1 |
190 |
0 |
1 |
7 |
581 |

Forecasting in large macroeconomic panels using Bayesian Model Averaging |
0 |
0 |
0 |
271 |
0 |
1 |
2 |
650 |

Forecasting the European Carbon Market |
0 |
1 |
1 |
167 |
0 |
1 |
6 |
462 |

Forecasting the European Carbon Market |
0 |
0 |
0 |
33 |
0 |
0 |
0 |
82 |

Forecasting with High-Dimensional Panel VARs |
1 |
3 |
14 |
272 |
2 |
7 |
27 |
592 |

Forecasting with High-Dimensional Panel VARs |
0 |
2 |
3 |
118 |
1 |
3 |
9 |
117 |

Forecasting with High-Dimensional Panel VARs |
0 |
0 |
2 |
21 |
0 |
0 |
3 |
54 |

Forecasting with Medium and Large Bayesian VARs |
0 |
1 |
2 |
95 |
0 |
4 |
14 |
121 |

Forecasting with Medium and Large Bayesian VARs |
0 |
2 |
8 |
146 |
2 |
7 |
37 |
364 |

Forecasting with Medium and Large Bayesian VARs |
1 |
1 |
3 |
139 |
2 |
3 |
6 |
236 |

Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
2 |
5 |
123 |
1 |
3 |
12 |
308 |

Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
0 |
0 |
4 |
0 |
0 |
2 |
28 |

Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
0 |
1 |
40 |
0 |
0 |
1 |
128 |

Hierarchical shrinkage in time-varying parameter models |
0 |
0 |
2 |
250 |
0 |
0 |
5 |
444 |

Hierarchical shrinkage in time-varying parameter models |
0 |
0 |
0 |
121 |
0 |
0 |
1 |
166 |

Hospital efficiency analysis through individual effects: A Bayesian approach |
0 |
0 |
1 |
14 |
0 |
0 |
1 |
33 |

Hospital efficiency analysis through individual effects: A Bayesian approach |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |

Identifying Noise Shocks |
1 |
1 |
3 |
52 |
1 |
2 |
8 |
95 |

Inducing Sparsity and Shrinkage in Time-Varying Parameter Models |
0 |
0 |
0 |
65 |
0 |
1 |
2 |
94 |

Inducing Sparsity and Shrinkage in Time-Varying Parameter Models |
0 |
0 |
1 |
10 |
0 |
0 |
1 |
39 |

Inducing sparsity and shrinkage in time-varying parameter models |
0 |
0 |
0 |
7 |
1 |
1 |
2 |
13 |

Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model |
1 |
1 |
6 |
32 |
2 |
3 |
14 |
39 |

Large Bayesian VARMAs |
0 |
0 |
1 |
19 |
0 |
0 |
1 |
45 |

Large Bayesian VARMAs |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
19 |

Large Bayesian VARMAs |
0 |
0 |
0 |
44 |
0 |
0 |
0 |
87 |

Large Bayesian VARMAs |
0 |
0 |
0 |
88 |
0 |
0 |
2 |
93 |

Large Order-Invariant Bayesian VARs with Stochastic Volatility |
1 |
3 |
4 |
64 |
1 |
3 |
9 |
38 |

Large Time-Varying Parameter VARs |
0 |
0 |
1 |
103 |
0 |
0 |
2 |
213 |

Large Time-Varying Parameter VARs |
0 |
2 |
3 |
60 |
0 |
2 |
4 |
155 |

Large time-varying parameter VARs |
1 |
5 |
16 |
814 |
1 |
5 |
29 |
1,447 |

Large time-varying parameter VARs |
0 |
1 |
2 |
39 |
0 |
2 |
7 |
138 |

Learning About Heterogeneity in Returns to Schooling |
0 |
0 |
0 |
0 |
2 |
2 |
7 |
387 |

Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs |
0 |
0 |
5 |
38 |
0 |
1 |
15 |
52 |

Measuring the Sources of Output Growth in a Panel of Countries |
0 |
0 |
0 |
23 |
0 |
0 |
0 |
327 |

Model Switching and Model Averaging in Time- Varying Parameter Regression Models |
0 |
0 |
0 |
35 |
0 |
0 |
0 |
53 |

Model Switching and Model Averaging in Time-Varying Parameter Regression Models |
0 |
0 |
0 |
128 |
0 |
0 |
1 |
254 |

Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
27 |
0 |
0 |
2 |
64 |

Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
71 |
0 |
0 |
2 |
60 |

Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
48 |

Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
110 |
0 |
0 |
0 |
117 |

Model uncertainty in panel vector autoregressive models |
0 |
1 |
4 |
254 |
3 |
4 |
11 |
413 |

Model uncertainty in panel vector autoregressive models |
0 |
0 |
0 |
38 |
0 |
0 |
1 |
84 |

Modeling the Dynamics of Inflation Compensation |
1 |
1 |
1 |
36 |
1 |
1 |
1 |
103 |

Modeling the Evolution of Distributions: An Application to Major League Baseball |
0 |
0 |
0 |
85 |
0 |
0 |
0 |
186 |

Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables |
1 |
1 |
2 |
47 |
2 |
2 |
3 |
105 |

Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables |
0 |
0 |
1 |
18 |
0 |
0 |
1 |
59 |

Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables |
0 |
0 |
0 |
23 |
0 |
0 |
0 |
38 |

Modelling breaks and clusters in the steady states of macroeconomic variables |
0 |
0 |
0 |
12 |
0 |
0 |
0 |
53 |

Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture |
0 |
0 |
0 |
423 |
0 |
1 |
3 |
1,047 |

Multiple-output production with undesirable output: An application to nitrogen surplus in agriculture |
0 |
0 |
2 |
4 |
1 |
1 |
4 |
447 |

Nowcasting 'true' monthly US GDP during the pandemic |
0 |
1 |
6 |
59 |
0 |
2 |
17 |
80 |

Nowcasting Scottish GDP Growth |
0 |
0 |
0 |
4 |
0 |
0 |
3 |
42 |

Nowcasting Scottish GDP Growth |
0 |
0 |
0 |
29 |
0 |
0 |
2 |
105 |

Nowcasting Scottish GDP growth |
0 |
0 |
0 |
22 |
0 |
0 |
4 |
78 |

Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs |
0 |
1 |
5 |
56 |
3 |
4 |
21 |
131 |

Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs |
0 |
1 |
1 |
77 |
0 |
1 |
5 |
64 |

Nowcasting in a pandemic using non-parametric mixed frequency VARs |
0 |
0 |
1 |
50 |
1 |
1 |
6 |
58 |

On Identification of Bayesian DSGE Models |
0 |
0 |
1 |
52 |
0 |
1 |
2 |
178 |

On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
36 |
0 |
0 |
0 |
91 |

On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
93 |
0 |
0 |
0 |
181 |

On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
210 |
0 |
0 |
2 |
361 |

On Identification of Bayesian DSGE Models* |
0 |
0 |
1 |
70 |
0 |
0 |
2 |
168 |

On the Evolution of Monetary Policy |
0 |
4 |
4 |
10 |
0 |
4 |
8 |
34 |

Parametric and Nonparametric Inference in Equilibrium Job Search Models |
0 |
0 |
0 |
40 |
0 |
0 |
2 |
179 |

Posterior Analysis of Stochastic Frontier Models using Gibbs Sampling |
0 |
0 |
1 |
124 |
0 |
0 |
3 |
319 |

Posterior analysis of stochastic frontier models using Gibbs sampling |
0 |
0 |
1 |
24 |
0 |
0 |
2 |
78 |

Posterior inference on long-run impulse responses |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
15 |

Prior Elicitation in Multiple Change-point Models |
0 |
0 |
0 |
92 |
0 |
0 |
0 |
360 |

Prior Elicitation in Multiple Change-point Models |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
15 |

Prior elicitation in multiple change-point models |
0 |
0 |
0 |
103 |
1 |
1 |
1 |
489 |

Re-examining the Consumption-Wealth Relationship: The Role of Model Uncertainty |
0 |
0 |
1 |
214 |
0 |
0 |
1 |
491 |

Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty |
0 |
0 |
0 |
51 |
0 |
0 |
0 |
200 |

Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty |
0 |
0 |
0 |
146 |
0 |
1 |
4 |
549 |

Reconciled Estimates of Monthly GDP in the US |
0 |
1 |
8 |
43 |
0 |
3 |
22 |
104 |

Reconciled Estimates of Monthly GDP in the US |
0 |
0 |
2 |
8 |
0 |
0 |
6 |
17 |

Reconciled Estimates of Monthly GDP in the US |
0 |
0 |
1 |
57 |
1 |
2 |
10 |
157 |

Reexamining the consumption-wealth relationship: the role of model uncertainty |
0 |
0 |
0 |
76 |
1 |
2 |
2 |
317 |

Regime-Switching Cointegration |
0 |
0 |
0 |
45 |
0 |
0 |
0 |
62 |

Regime-Switching Cointegration |
0 |
0 |
0 |
9 |
0 |
1 |
1 |
42 |

Regime-Switching Cointegration |
0 |
0 |
0 |
118 |
1 |
2 |
6 |
300 |

Regime-Switching Cointegration* |
0 |
0 |
1 |
176 |
0 |
0 |
5 |
367 |

Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017 |
1 |
1 |
3 |
58 |
1 |
1 |
5 |
90 |

Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017 |
0 |
2 |
7 |
93 |
1 |
4 |
15 |
126 |

Semiparametric Bayesian Inference in Multiple Equation Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
255 |

Semiparametric Bayesian Inference in Smooth Coefficient Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
168 |

Semiparametric Bayesian inference in smooth coefficient models |
0 |
0 |
0 |
116 |
0 |
0 |
2 |
474 |

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy |
0 |
0 |
1 |
89 |
0 |
0 |
1 |
212 |

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy |
0 |
0 |
0 |
28 |
1 |
1 |
3 |
107 |

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy |
0 |
0 |
1 |
6 |
1 |
1 |
3 |
36 |

Stochastic frontier models: a bayesian perspective |
0 |
0 |
4 |
37 |
1 |
2 |
10 |
107 |

Subspace Shrinkage in Conjugate Bayesian Vector Autoregressions |
0 |
2 |
3 |
23 |
0 |
3 |
11 |
26 |

Tail Forecasting with Multivariate Bayesian Additive Regression Trees |
0 |
0 |
6 |
75 |
1 |
3 |
21 |
77 |

Technical Appendix to: Understanding Liquidity and Credit Risks in the Financial Crisis |
0 |
0 |
0 |
27 |
0 |
0 |
0 |
88 |

Technical appendix to: a new look at variation in employment growth in Canada |
0 |
0 |
0 |
21 |
0 |
0 |
2 |
54 |

Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach |
0 |
0 |
0 |
117 |
0 |
0 |
0 |
643 |

Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach |
0 |
0 |
1 |
99 |
0 |
0 |
2 |
327 |

Testing for integration using evolving trend and seasonal models: A Bayesian approach |
0 |
0 |
1 |
8 |
0 |
0 |
1 |
97 |

The Components of Output Growth: A Croos-Country Analysis |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
718 |

The Components of Output Growth: A Cross-Country Analysis |
0 |
0 |
0 |
17 |
1 |
1 |
1 |
104 |

The Contribution of Structural Break Models to Forecasting Macroeconomic Series |
0 |
1 |
1 |
373 |
0 |
1 |
5 |
673 |

The Contribution of Structural Break Models to Forecating Macroeconomic Series |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
40 |

The Dynamics of UK and US Inflation Expectation |
0 |
0 |
0 |
17 |
0 |
0 |
2 |
65 |

The Dynamics of UK and US Inflation Expectations |
0 |
1 |
1 |
47 |
1 |
3 |
3 |
123 |

The Dynamics of UK and US Inflation Expectations |
0 |
0 |
0 |
5 |
1 |
1 |
2 |
59 |

The Dynamics of UK and US Inflation Expectations |
0 |
0 |
0 |
57 |
0 |
0 |
0 |
53 |

The Dynamics of UK and US Inflation Expectations* |
0 |
0 |
0 |
76 |
0 |
0 |
0 |
181 |

The Known Unknowns of Governance |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
46 |

The Vector Floor and Ceiling Model |
0 |
0 |
0 |
77 |
1 |
1 |
1 |
1,050 |

The components of output growth: A cross-country analysis |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
36 |

The components of output growth: A cross-country analysis |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |

The known unknowns of governance |
0 |
0 |
0 |
22 |
0 |
0 |
0 |
60 |

The valuation of IPO, SEO and Post-Chapter 11 firms: A Stochastic Frontier Approach |
0 |
0 |
0 |
230 |
1 |
2 |
6 |
2,250 |

Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada |
0 |
0 |
0 |
23 |
0 |
0 |
1 |
90 |

Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
20 |

Time Varying Dimension Models |
0 |
0 |
0 |
117 |
0 |
0 |
8 |
424 |

Time Varying Dimension Models |
0 |
0 |
0 |
51 |
2 |
2 |
4 |
281 |

Time Varying Dimension Models |
0 |
0 |
0 |
29 |
0 |
0 |
1 |
120 |

Time Varying Dimension Models |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
23 |

Time Varying Dimension Models |
0 |
0 |
2 |
66 |
0 |
0 |
3 |
207 |

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? |
0 |
0 |
0 |
41 |
0 |
0 |
1 |
68 |

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? |
0 |
0 |
1 |
112 |
0 |
0 |
3 |
230 |

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? |
0 |
0 |
0 |
281 |
0 |
0 |
1 |
606 |

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?* |
0 |
0 |
2 |
64 |
0 |
0 |
3 |
152 |

UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model |
0 |
0 |
0 |
116 |
0 |
3 |
7 |
90 |

UK regional nowcasting using a mixed frequency vector autoregressive model |
1 |
2 |
3 |
66 |
1 |
2 |
6 |
108 |

Understanding Liquidity and Credit Risks in the Financial Crisis |
0 |
0 |
0 |
82 |
0 |
1 |
4 |
193 |

Understanding Liquidity and Credit Risks in the Financial Crisis |
0 |
0 |
0 |
132 |
2 |
8 |
29 |
232 |

Understanding Liquidity and Credit Risks in the Financial Crisis* |
0 |
0 |
0 |
250 |
0 |
5 |
20 |
433 |

Using VARs and TVP-VARs with Many Macroeconomic Variables |
0 |
1 |
1 |
74 |
1 |
4 |
7 |
144 |

Using VARs and TVP-VARs with Many Macroeconomic Variables |
0 |
0 |
1 |
142 |
1 |
3 |
7 |
199 |

Using hierarchical aggregation constraints to nowcast regional economic aggregates |
0 |
2 |
17 |
17 |
1 |
3 |
17 |
17 |

Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates |
0 |
2 |
6 |
50 |
0 |
3 |
17 |
32 |

Variational Bayes inference in high-dimensional time-varying parameter models |
0 |
0 |
2 |
360 |
0 |
2 |
13 |
728 |

Variational Bayes inference in high-dimensional time-varying parameter models |
0 |
1 |
7 |
50 |
1 |
5 |
26 |
175 |

Variational Bayes inference in high-dimensional time-varying parameter models |
0 |
0 |
0 |
16 |
0 |
0 |
0 |
42 |

Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage |
0 |
0 |
1 |
13 |
0 |
0 |
2 |
48 |

Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage |
0 |
1 |
1 |
24 |
0 |
1 |
6 |
74 |

Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage |
0 |
0 |
1 |
101 |
0 |
0 |
2 |
218 |

What is the Environmental Performance of Firms Overseas?: An Empirical Investigation of the Global Gold Mining Industry |
0 |
0 |
0 |
7 |
0 |
1 |
3 |
50 |

Total Working Papers |
21 |
203 |
687 |
22,660 |
102 |
351 |
1,534 |
64,563 |