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

A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve |
0 |
1 |
3 |
63 |
0 |
2 |
7 |
111 |

A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve |
0 |
0 |
1 |
83 |
0 |
1 |
4 |
167 |

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

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

A Comparison of Forecasting Procedures for Macroeconomic Series: the Contribution of Structural Break Models |
0 |
0 |
0 |
83 |
0 |
0 |
0 |
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 |
0 |
141 |
0 |
2 |
4 |
720 |

A New Index of Financial Conditions |
0 |
1 |
1 |
75 |
1 |
2 |
8 |
708 |

A New Model Of Trend Inflation |
0 |
0 |
0 |
76 |
0 |
0 |
1 |
182 |

A New Model of Inflation, Trend Inflation, and Long-Run Inflation Expectations |
0 |
0 |
2 |
152 |
1 |
4 |
10 |
243 |

A New Model of Trend Inflation |
0 |
0 |
0 |
99 |
0 |
0 |
1 |
208 |

A New Model of Trend Inflation |
0 |
0 |
2 |
114 |
0 |
1 |
3 |
232 |

A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
4 |

A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies |
0 |
0 |
0 |
15 |
0 |
0 |
1 |
52 |

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

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

A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
25 |

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 |
1 |
0 |
0 |
1 |
35 |

A flexible approach to parametric inference in nonlinear and time varying time series models |
0 |
0 |
0 |
11 |
1 |
1 |
1 |
64 |

A flexible approach to parametric inference in nonlinear time series models |
0 |
0 |
0 |
184 |
0 |
0 |
2 |
386 |

A new index of financial conditions |
0 |
0 |
0 |
111 |
0 |
0 |
3 |
382 |

A new index of financial conditions |
0 |
0 |
1 |
60 |
0 |
0 |
5 |
154 |

A new look at variation in employment growth in Canada |
0 |
0 |
0 |
39 |
0 |
0 |
1 |
153 |

A new model of trend inflation |
0 |
0 |
0 |
38 |
0 |
0 |
1 |
110 |

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

An Investigation of Thresholds in Air Pollution-Mortality Effects |
0 |
0 |
0 |
176 |
0 |
1 |
3 |
841 |

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

Are apparent findings of nonlinearity due to structural instability in economic time series? |
0 |
0 |
0 |
146 |
0 |
0 |
1 |
458 |

Bayesian Analysis of Endogenous Delay Threshold Models |
0 |
1 |
1 |
100 |
1 |
2 |
4 |
305 |

Bayesian Analysis of Long Memory and Persistence using ARFIMA Models |
0 |
0 |
0 |
330 |
0 |
0 |
1 |
1,385 |

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 |
0 |
0 |
731 |
0 |
0 |
1 |
2,316 |

Bayesian Analysis of Stochastic Frontier Models |
0 |
1 |
2 |
39 |
0 |
1 |
4 |
1,313 |

Bayesian Approaches to Cointegration |
0 |
0 |
2 |
278 |
0 |
0 |
6 |
625 |

Bayesian Compressed Vector Autoregressions |
0 |
0 |
0 |
231 |
0 |
0 |
1 |
427 |

Bayesian Compressed Vector Autoregressions |
0 |
0 |
0 |
31 |
0 |
0 |
1 |
69 |

Bayesian Compressed Vector Autoregressions |
0 |
0 |
0 |
38 |
0 |
0 |
0 |
92 |

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

Bayesian Econometric Methods |
0 |
0 |
0 |
4 |
2 |
7 |
17 |
646 |

Bayesian Efficiency Analysis through Individual Effects: Hospital Cost Frontiers |
0 |
0 |
0 |
32 |
0 |
0 |
1 |
730 |

Bayesian Forecasting in Economics and Finance: A Modern Review |
0 |
1 |
5 |
77 |
0 |
4 |
19 |
59 |

Bayesian Forecasting using Stochastic Search Variable Selection in a VAR Subject to Breaks |
0 |
0 |
2 |
66 |
0 |
1 |
4 |
70 |

Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations |
0 |
0 |
3 |
37 |
0 |
0 |
3 |
53 |

Bayesian Inference in a Cointegrating Panel Data Model |
0 |
0 |
1 |
16 |
0 |
0 |
3 |
62 |

Bayesian Inference in a Cointegrating Panel Data Model |
0 |
1 |
2 |
272 |
0 |
2 |
5 |
643 |

Bayesian Inference in a Time Varying Cointegration Model |
0 |
0 |
0 |
58 |
0 |
1 |
2 |
155 |

Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
1 |
32 |
0 |
0 |
4 |
144 |

Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
0 |
9 |
0 |
1 |
2 |
65 |

Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
37 |

Bayesian Inference in the Time Varying Cointegration Model* |
0 |
2 |
2 |
82 |
0 |
2 |
3 |
194 |

Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
141 |
0 |
0 |
3 |
285 |

Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
29 |
0 |
2 |
2 |
128 |

Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
11 |
0 |
1 |
1 |
67 |

Bayesian Model Averaging in the Instrumental Variable Regression Model* |
1 |
2 |
2 |
41 |
1 |
2 |
2 |
86 |

Bayesian Modeling of TVP-VARs Using Regression Trees |
1 |
1 |
3 |
109 |
3 |
3 |
14 |
45 |

Bayesian Modeling of Time-Varying Parameters Using Regression Trees |
1 |
2 |
6 |
86 |
3 |
6 |
17 |
35 |

Bayesian Multivariate Time Series Methods for Empirical Macroeconomics |
2 |
4 |
15 |
598 |
3 |
9 |
53 |
1,489 |

Bayesian Multivariate Time Series Methods for Empirical Macroeconomics |
6 |
19 |
85 |
2,636 |
22 |
57 |
237 |
6,183 |

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 |
0 |
0 |
112 |
0 |
0 |
0 |
273 |

Bayesian analysis of long memory and persistence using ARFIMA models |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
26 |

Bayesian approaches to cointegratrion |
0 |
0 |
1 |
32 |
0 |
0 |
2 |
99 |

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

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

Bayesian dynamic variable selection in high dimensions |
0 |
0 |
0 |
94 |
1 |
1 |
3 |
178 |

Bayesian efficiency analysis through individual effects: Hospital cost frontiers |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
34 |

Bayesian efficiency analysis with a flexible cost function |
0 |
0 |
0 |
2 |
0 |
0 |
2 |
15 |

Bayesian efficiency analysis with a flexible form: The aim cost function |
0 |
1 |
1 |
1 |
0 |
1 |
1 |
2 |

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

Bayesian inference in models based on equilibrium search theory |
0 |
0 |
0 |
6 |
0 |
2 |
2 |
195 |

Bayesian long-run prediction in time series models |
0 |
0 |
1 |
7 |
0 |
0 |
4 |
37 |

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

Comparing the Performance of Baseball Players: A Multiple Output Approach |
1 |
1 |
1 |
144 |
2 |
2 |
5 |
442 |

Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility |
0 |
0 |
0 |
18 |
0 |
0 |
1 |
27 |

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

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

Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs |
0 |
0 |
0 |
30 |
0 |
0 |
2 |
60 |

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

Domestic Violence and Football in Glasgow: Are Reference Points Relevant? |
0 |
0 |
0 |
28 |
0 |
0 |
1 |
74 |

Domestic Violence and Football in Glasgow: Are Reference Points Relevant? |
0 |
0 |
1 |
97 |
0 |
0 |
3 |
350 |

Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods |
0 |
0 |
0 |
29 |
0 |
0 |
2 |
36 |

Dynamic asymmetries in US unemployment |
0 |
0 |
0 |
45 |
0 |
0 |
2 |
401 |

Dynamic probabilities of restrictions in state space models: An application to the Phillips curve |
0 |
0 |
1 |
12 |
0 |
0 |
3 |
49 |

Efficient Posterior Simulation for Cointegrated Models with Priors On the Cointegration Space |
0 |
0 |
4 |
162 |
0 |
0 |
4 |
446 |

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

Estimating Phillips Curves in Turbulent Times using the ECBâ€™s Survey of Professional Forecasters |
0 |
0 |
0 |
38 |
0 |
0 |
1 |
95 |

Estimating Phillips curves in turbulent times using the ECB's survey of professional forecasters |
0 |
0 |
1 |
104 |
0 |
0 |
3 |
197 |

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 |
0 |
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 |
0 |
36 |

Estimating the Impact on Efficiency of the Adoption of a Voluntary Environmental Standard: An Empirical Study of the Global Copper Mining Industry |
0 |
0 |
1 |
11 |
0 |
0 |
1 |
80 |

Exchange rate predictability and dynamic Bayesian learning |
0 |
0 |
0 |
117 |
0 |
2 |
4 |
260 |

Exchange rate predictability and dynamic Bayesian learning |
0 |
0 |
0 |
29 |
0 |
0 |
2 |
86 |

Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models |
0 |
0 |
0 |
56 |
0 |
1 |
5 |
59 |

Forecasting Inflation Using Dynamic Model Averaging |
0 |
0 |
0 |
19 |
0 |
1 |
4 |
113 |

Forecasting Inflation Using Dynamic Model Averaging |
1 |
4 |
15 |
605 |
1 |
4 |
28 |
1,200 |

Forecasting Inflation Using Dynamic Model Averaging |
0 |
1 |
3 |
91 |
0 |
1 |
7 |
122 |

Forecasting Inflation Using Dynamic Model Averaging* |
1 |
3 |
7 |
177 |
1 |
3 |
12 |
349 |

Forecasting Low Frequency Macroeconomic Events with High Frequency Data |
0 |
0 |
1 |
60 |
1 |
1 |
4 |
98 |

Forecasting Substantial Data Revisions in the Presence of Model Uncertainty |
0 |
0 |
0 |
68 |
0 |
0 |
1 |
302 |

Forecasting Substantial Data Revisions in the Presence of Model Uncertainty |
0 |
0 |
0 |
100 |
0 |
0 |
1 |
328 |

Forecasting US Inflation Using Bayesian Nonparametric Models |
0 |
1 |
1 |
120 |
0 |
2 |
8 |
105 |

Forecasting US Inflation Using Bayesian Nonparametric Models |
0 |
2 |
8 |
26 |
0 |
5 |
21 |
48 |

Forecasting With High Dimensional Panel VARs |
0 |
2 |
6 |
340 |
0 |
3 |
11 |
570 |

Forecasting and Estimating Multiple Change-point Models with an Unknown Number of Change-points |
0 |
0 |
0 |
383 |
0 |
1 |
1 |
990 |

Forecasting and estimating multiple change-point models with an unknown number of change points |
0 |
0 |
0 |
251 |
0 |
0 |
1 |
806 |

Forecasting in Large Macroeconomic Panels using Bayesian Model Averaging |
1 |
1 |
1 |
191 |
1 |
1 |
1 |
582 |

Forecasting in large macroeconomic panels using Bayesian Model Averaging |
0 |
0 |
2 |
273 |
0 |
1 |
3 |
655 |

Forecasting the European Carbon Market |
0 |
0 |
0 |
33 |
0 |
0 |
1 |
83 |

Forecasting the European Carbon Market |
0 |
0 |
0 |
167 |
2 |
2 |
6 |
468 |

Forecasting with High-Dimensional Panel VARs |
0 |
0 |
1 |
119 |
0 |
0 |
6 |
124 |

Forecasting with High-Dimensional Panel VARs |
0 |
0 |
0 |
21 |
0 |
0 |
2 |
57 |

Forecasting with High-Dimensional Panel VARs |
2 |
2 |
12 |
286 |
3 |
4 |
21 |
617 |

Forecasting with Medium and Large Bayesian VARs |
0 |
0 |
0 |
97 |
0 |
1 |
1 |
129 |

Forecasting with Medium and Large Bayesian VARs |
0 |
0 |
2 |
149 |
1 |
4 |
9 |
379 |

Forecasting with Medium and Large Bayesian VARs |
0 |
0 |
0 |
140 |
1 |
1 |
2 |
241 |

Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
0 |
1 |
125 |
0 |
0 |
4 |
314 |

Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
0 |
2 |
6 |
0 |
0 |
3 |
31 |

Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
0 |
0 |
40 |
0 |
0 |
3 |
131 |

Hierarchical shrinkage in time-varying parameter models |
0 |
0 |
5 |
256 |
0 |
0 |
7 |
452 |

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

Hospital efficiency analysis through individual effects: A Bayesian approach |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
3 |

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

Identifying Noise Shocks |
0 |
0 |
0 |
54 |
0 |
0 |
0 |
97 |

Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting |
0 |
1 |
12 |
23 |
0 |
2 |
14 |
15 |

Inducing Sparsity and Shrinkage in Time-Varying Parameter Models |
0 |
0 |
0 |
65 |
0 |
0 |
4 |
98 |

Inducing Sparsity and Shrinkage in Time-Varying Parameter Models |
0 |
0 |
1 |
11 |
0 |
0 |
1 |
41 |

Inducing sparsity and shrinkage in time-varying parameter models |
0 |
0 |
0 |
7 |
0 |
1 |
4 |
17 |

Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model |
1 |
1 |
3 |
35 |
3 |
3 |
10 |
49 |

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

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

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

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

Large Order-Invariant Bayesian VARs with Stochastic Volatility |
0 |
0 |
0 |
65 |
0 |
0 |
3 |
42 |

Large Time-Varying Parameter VARs |
1 |
3 |
7 |
110 |
1 |
4 |
11 |
226 |

Large Time-Varying Parameter VARs |
1 |
1 |
2 |
62 |
1 |
1 |
5 |
161 |

Large time-varying parameter VARs |
1 |
6 |
11 |
826 |
2 |
9 |
25 |
1,477 |

Large time-varying parameter VARs |
0 |
0 |
2 |
41 |
0 |
0 |
5 |
144 |

Learning About Heterogeneity in Returns to Schooling |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
391 |

Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs |
0 |
1 |
1 |
39 |
1 |
2 |
5 |
58 |

Measuring the Sources of Output Growth in a Panel of Countries |
0 |
0 |
0 |
23 |
0 |
0 |
4 |
331 |

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 |
1 |
3 |
257 |

Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
71 |
0 |
0 |
1 |
61 |

Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
110 |
0 |
0 |
2 |
119 |

Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
1 |
5 |
0 |
0 |
2 |
50 |

Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
27 |
0 |
0 |
1 |
65 |

Model uncertainty in panel vector autoregressive models |
0 |
2 |
10 |
265 |
1 |
4 |
14 |
431 |

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

Modeling the Dynamics of Inflation Compensation |
0 |
0 |
0 |
36 |
0 |
0 |
0 |
103 |

Modeling the Evolution of Distributions: An Application to Major League Baseball |
0 |
0 |
0 |
85 |
0 |
0 |
0 |
187 |

Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables |
0 |
0 |
0 |
47 |
0 |
0 |
0 |
105 |

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 |
1 |
19 |
0 |
0 |
1 |
60 |

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 |
1 |
424 |
0 |
0 |
2 |
1,050 |

Multiple-output production with undesirable output: An application to nitrogen surplus in agriculture |
0 |
1 |
1 |
5 |
0 |
1 |
1 |
448 |

Nowcasting 'true' monthly US GDP during the pandemic |
0 |
0 |
1 |
60 |
1 |
1 |
4 |
84 |

Nowcasting Scottish GDP Growth |
0 |
0 |
1 |
30 |
0 |
2 |
4 |
109 |

Nowcasting Scottish GDP Growth |
0 |
0 |
0 |
4 |
0 |
1 |
3 |
45 |

Nowcasting Scottish GDP growth |
0 |
0 |
1 |
23 |
0 |
2 |
3 |
81 |

Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs |
0 |
0 |
2 |
58 |
1 |
1 |
7 |
140 |

Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs |
0 |
0 |
1 |
78 |
0 |
2 |
6 |
73 |

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

On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
38 |
0 |
1 |
1 |
94 |

On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
53 |
0 |
0 |
0 |
179 |

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

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

On Identification of Bayesian DSGE Models* |
0 |
0 |
0 |
70 |
0 |
0 |
1 |
169 |

On the Evolution of Monetary Policy |
0 |
0 |
0 |
10 |
0 |
0 |
2 |
36 |

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

Posterior Analysis of Stochastic Frontier Models using Gibbs Sampling |
0 |
0 |
0 |
124 |
0 |
0 |
1 |
320 |

Posterior analysis of stochastic frontier models using Gibbs sampling |
0 |
1 |
2 |
26 |
2 |
3 |
5 |
85 |

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

Predictive Density Combination Using a Tree-Based Synthesis Function |
0 |
0 |
9 |
9 |
2 |
2 |
7 |
7 |

Predictive Density Combination Using a Tree-Based Synthesis Function |
0 |
0 |
17 |
17 |
0 |
0 |
11 |
11 |

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 |
104 |
0 |
0 |
0 |
491 |

Re-examining the Consumption-Wealth Relationship: The Role of Model Uncertainty |
0 |
0 |
1 |
215 |
0 |
0 |
1 |
493 |

Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty |
0 |
0 |
1 |
147 |
0 |
0 |
1 |
550 |

Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty |
0 |
0 |
1 |
52 |
0 |
0 |
2 |
202 |

Reconciled Estimates of Monthly GDP in the US |
0 |
0 |
1 |
9 |
0 |
2 |
4 |
21 |

Reconciled Estimates of Monthly GDP in the US |
0 |
0 |
1 |
47 |
1 |
1 |
5 |
112 |

Reconciled Estimates of Monthly GDP in the US |
1 |
1 |
2 |
60 |
1 |
1 |
4 |
164 |

Reexamining the consumption-wealth relationship: the role of model uncertainty |
0 |
0 |
0 |
76 |
0 |
0 |
0 |
318 |

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

Regime-Switching Cointegration |
0 |
0 |
0 |
119 |
1 |
1 |
1 |
303 |

Regime-Switching Cointegration |
0 |
0 |
1 |
10 |
0 |
1 |
4 |
46 |

Regime-Switching Cointegration* |
0 |
0 |
1 |
177 |
0 |
2 |
6 |
373 |

Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017 |
0 |
0 |
7 |
101 |
2 |
2 |
14 |
142 |

Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017 |
0 |
0 |
1 |
60 |
1 |
1 |
4 |
95 |

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 |
1 |
1 |
169 |

Semiparametric Bayesian inference in smooth coefficient models |
0 |
0 |
0 |
116 |
0 |
1 |
2 |
476 |

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

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

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy |
0 |
0 |
0 |
28 |
0 |
0 |
1 |
108 |

Stochastic frontier models: a bayesian perspective |
0 |
0 |
1 |
39 |
0 |
0 |
4 |
113 |

Subspace Shrinkage in Conjugate Bayesian Vector Autoregressions |
0 |
0 |
0 |
23 |
0 |
0 |
1 |
27 |

Tail Forecasting with Multivariate Bayesian Additive Regression Trees |
0 |
0 |
1 |
78 |
0 |
0 |
8 |
87 |

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 |
0 |
54 |

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

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 seasonal models: A Bayesian approach |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
97 |

The Components of Output Growth: A Croos-Country Analysis |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
719 |

The Components of Output Growth: A Cross-Country Analysis |
0 |
0 |
0 |
17 |
0 |
0 |
1 |
105 |

The Contribution of Structural Break Models to Forecasting Macroeconomic Series |
0 |
2 |
4 |
379 |
0 |
2 |
4 |
679 |

The Contribution of Structural Break Models to Forecating Macroeconomic Series |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
42 |

The Dynamics of UK and US Inflation Expectation |
0 |
0 |
0 |
17 |
0 |
0 |
1 |
66 |

The Dynamics of UK and US Inflation Expectations |
0 |
0 |
1 |
6 |
0 |
0 |
1 |
60 |

The Dynamics of UK and US Inflation Expectations |
0 |
0 |
0 |
47 |
0 |
0 |
2 |
125 |

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 |
1 |
182 |

The Known Unknowns of Governance |
0 |
0 |
0 |
6 |
0 |
1 |
1 |
47 |

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

The components of output growth: A cross-country analysis |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
37 |

The components of output growth: A cross-country analysis |
0 |
0 |
1 |
1 |
0 |
0 |
3 |
8 |

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 |
0 |
1 |
2 |
2,252 |

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

Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada |
0 |
0 |
0 |
23 |
0 |
0 |
1 |
91 |

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

Time Varying Dimension Models |
0 |
0 |
0 |
51 |
0 |
3 |
7 |
290 |

Time Varying Dimension Models |
0 |
0 |
0 |
29 |
0 |
0 |
1 |
121 |

Time Varying Dimension Models |
0 |
0 |
0 |
117 |
0 |
0 |
1 |
426 |

Time Varying Dimension Models |
0 |
0 |
1 |
67 |
0 |
0 |
1 |
208 |

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? |
0 |
0 |
0 |
42 |
0 |
1 |
1 |
70 |

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? |
0 |
0 |
3 |
116 |
1 |
1 |
8 |
239 |

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

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?* |
1 |
1 |
2 |
67 |
1 |
1 |
3 |
156 |

UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model |
0 |
0 |
2 |
118 |
0 |
0 |
5 |
95 |

UK regional nowcasting using a mixed frequency vector autoregressive model |
0 |
0 |
1 |
67 |
1 |
2 |
4 |
112 |

Understanding Liquidity and Credit Risks in the Financial Crisis |
0 |
0 |
0 |
132 |
0 |
0 |
2 |
244 |

Understanding Liquidity and Credit Risks in the Financial Crisis |
0 |
0 |
0 |
82 |
1 |
2 |
4 |
200 |

Understanding Liquidity and Credit Risks in the Financial Crisis* |
0 |
0 |
0 |
250 |
1 |
2 |
3 |
444 |

Using VARs and TVP-VARs with Many Macroeconomic Variables |
0 |
0 |
0 |
75 |
0 |
1 |
4 |
150 |

Using VARs and TVP-VARs with Many Macroeconomic Variables |
0 |
0 |
0 |
142 |
1 |
1 |
3 |
203 |

Using hierarchical aggregation constraints to nowcast regional economic aggregates |
0 |
0 |
1 |
18 |
0 |
1 |
6 |
23 |

Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates |
0 |
0 |
1 |
51 |
0 |
0 |
1 |
33 |

Variational Bayes inference in high-dimensional time-varying parameter models |
0 |
0 |
1 |
17 |
0 |
0 |
1 |
45 |

Variational Bayes inference in high-dimensional time-varying parameter models |
0 |
1 |
3 |
54 |
1 |
3 |
11 |
189 |

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

Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage |
0 |
0 |
3 |
16 |
0 |
0 |
5 |
53 |

Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage |
0 |
0 |
1 |
26 |
0 |
0 |
1 |
76 |

Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage |
0 |
0 |
0 |
101 |
1 |
1 |
1 |
219 |

What is the Environmental Performance of Firms Overseas?: An Empirical Investigation of the Global Gold Mining Industry |
0 |
0 |
0 |
7 |
0 |
0 |
1 |
51 |

Total Working Papers |
23 |
76 |
352 |
23,092 |
81 |
238 |
1,028 |
65,832 |