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Abstract Views |
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12 months |
Total |
Last month |
3 months |
12 months |
Total |
| 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 |
4 |
66 |
1 |
2 |
11 |
121 |
| A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve |
0 |
1 |
2 |
85 |
0 |
2 |
5 |
172 |
| A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models |
0 |
0 |
0 |
52 |
0 |
0 |
1 |
81 |
| A Comparison of Forecasting Procedures For Macroeconomic Series: The Contribution of Structural Break Models |
0 |
0 |
0 |
178 |
0 |
0 |
1 |
217 |
| A Comparison of Forecasting Procedures for Macroeconomic Series: the Contribution of Structural Break Models |
0 |
0 |
0 |
83 |
0 |
1 |
4 |
147 |
| 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 |
1 |
2 |
143 |
0 |
2 |
10 |
730 |
| A New Index of Financial Conditions |
0 |
0 |
2 |
77 |
1 |
5 |
13 |
720 |
| A New Model Of Trend Inflation |
0 |
1 |
1 |
77 |
0 |
1 |
1 |
183 |
| A New Model of Inflation, Trend Inflation, and Long-Run Inflation Expectations |
0 |
0 |
0 |
152 |
0 |
0 |
4 |
245 |
| A New Model of Trend Inflation |
0 |
0 |
0 |
99 |
1 |
1 |
1 |
209 |
| A New Model of Trend Inflation |
0 |
0 |
0 |
114 |
0 |
0 |
0 |
232 |
| A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies |
0 |
0 |
0 |
15 |
0 |
1 |
1 |
53 |
| A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
| 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 |
1 |
1 |
76 |
| A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models |
0 |
0 |
0 |
1 |
0 |
2 |
3 |
38 |
| A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
| A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
26 |
| A flexible approach to parametric inference in nonlinear and time varying time series models |
0 |
0 |
0 |
11 |
0 |
0 |
2 |
65 |
| A flexible approach to parametric inference in nonlinear time series models |
0 |
0 |
0 |
184 |
1 |
1 |
3 |
389 |
| A new index of financial conditions |
0 |
0 |
1 |
61 |
0 |
0 |
2 |
156 |
| A new index of financial conditions |
0 |
0 |
3 |
114 |
0 |
1 |
5 |
387 |
| A new look at variation in employment growth in Canada |
0 |
0 |
0 |
39 |
0 |
0 |
0 |
153 |
| A new model of trend inflation |
0 |
0 |
0 |
38 |
0 |
0 |
1 |
111 |
| Alternative efficiency measures for multiple-output production |
0 |
0 |
1 |
9 |
0 |
1 |
2 |
369 |
| An Investigation of Thresholds in Air Pollution-Mortality Effects |
0 |
0 |
0 |
176 |
0 |
0 |
2 |
842 |
| Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs |
0 |
0 |
1 |
41 |
0 |
1 |
5 |
52 |
| Are apparent findings of nonlinearity due to structural instability in economic time series? |
0 |
0 |
0 |
146 |
0 |
0 |
0 |
458 |
| Bayesian Analysis of Endogenous Delay Threshold Models |
0 |
0 |
0 |
100 |
1 |
3 |
4 |
308 |
| Bayesian Analysis of Long Memory and Persistence using ARFIMA Models |
0 |
0 |
0 |
11 |
0 |
0 |
2 |
385 |
| Bayesian Analysis of Long Memory and Persistence using ARFIMA Models |
0 |
0 |
1 |
331 |
0 |
0 |
3 |
1,388 |
| Bayesian Analysis of Long Memory and Persistence using ARFIMA Models |
0 |
0 |
1 |
732 |
0 |
0 |
3 |
2,319 |
| Bayesian Analysis of Stochastic Frontier Models |
0 |
1 |
4 |
42 |
1 |
3 |
7 |
1,319 |
| Bayesian Approaches to Cointegration |
0 |
0 |
2 |
280 |
0 |
1 |
6 |
631 |
| Bayesian Compressed Vector Autoregressions |
0 |
0 |
1 |
28 |
0 |
0 |
1 |
46 |
| Bayesian Compressed Vector Autoregressions |
0 |
0 |
1 |
232 |
0 |
0 |
1 |
428 |
| Bayesian Compressed Vector Autoregressions |
0 |
0 |
0 |
31 |
0 |
1 |
1 |
70 |
| Bayesian Compressed Vector Autoregressions |
0 |
0 |
0 |
38 |
0 |
0 |
0 |
92 |
| Bayesian Econometric Methods |
0 |
0 |
0 |
4 |
2 |
5 |
20 |
661 |
| Bayesian Efficiency Analysis through Individual Effects: Hospital Cost Frontiers |
0 |
0 |
0 |
32 |
0 |
1 |
3 |
733 |
| Bayesian Forecasting in Economics and Finance: A Modern Review |
1 |
1 |
3 |
79 |
1 |
2 |
15 |
72 |
| Bayesian Forecasting in the 21st Century: A Modern Review |
0 |
1 |
5 |
75 |
0 |
4 |
14 |
66 |
| Bayesian Forecasting using Stochastic Search Variable Selection in a VAR Subject to Breaks |
0 |
0 |
0 |
66 |
0 |
1 |
2 |
71 |
| Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations |
0 |
0 |
0 |
37 |
2 |
2 |
2 |
55 |
| Bayesian Inference in a Cointegrating Panel Data Model |
0 |
0 |
0 |
16 |
0 |
1 |
1 |
63 |
| Bayesian Inference in a Cointegrating Panel Data Model |
0 |
0 |
0 |
272 |
1 |
1 |
2 |
644 |
| Bayesian Inference in a Time Varying Cointegration Model |
0 |
0 |
1 |
59 |
0 |
1 |
3 |
157 |
| Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
1 |
10 |
0 |
0 |
2 |
66 |
| Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
1 |
6 |
0 |
0 |
1 |
38 |
| Bayesian Inference in the Time Varying Cointegration Model |
0 |
0 |
1 |
33 |
2 |
2 |
5 |
149 |
| Bayesian Inference in the Time Varying Cointegration Model* |
0 |
0 |
2 |
82 |
0 |
1 |
4 |
196 |
| Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
11 |
0 |
0 |
1 |
67 |
| Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
141 |
0 |
1 |
4 |
289 |
| Bayesian Model Averaging in the Instrumental Variable Regression Model |
0 |
0 |
0 |
29 |
1 |
3 |
5 |
132 |
| Bayesian Model Averaging in the Instrumental Variable Regression Model* |
0 |
0 |
1 |
41 |
0 |
0 |
2 |
87 |
| Bayesian Modeling of TVP-VARs Using Regression Trees |
0 |
1 |
3 |
111 |
1 |
6 |
12 |
54 |
| Bayesian Modeling of Time-Varying Parameters Using Regression Trees |
0 |
1 |
4 |
89 |
0 |
1 |
9 |
40 |
| Bayesian Modelling of TVP-VARs Using Regression Trees |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
53 |
| Bayesian Multivariate Time Series Methods for Empirical Macroeconomics |
1 |
3 |
23 |
619 |
4 |
10 |
57 |
1,540 |
| Bayesian Multivariate Time Series Methods for Empirical Macroeconomics |
12 |
27 |
120 |
2,742 |
28 |
68 |
278 |
6,418 |
| Bayesian Semiparametric Inference in Multiple Equation Models |
0 |
0 |
0 |
144 |
0 |
2 |
3 |
527 |
| 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 |
1 |
2 |
28 |
| Bayesian approaches to cointegratrion |
0 |
1 |
1 |
33 |
0 |
1 |
1 |
100 |
| Bayesian dynamic variable selection in high dimensions |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
7 |
| Bayesian dynamic variable selection in high dimensions |
0 |
1 |
1 |
10 |
0 |
1 |
2 |
35 |
| Bayesian dynamic variable selection in high dimensions |
0 |
0 |
0 |
94 |
0 |
1 |
3 |
180 |
| Bayesian efficiency analysis through individual effects: Hospital cost frontiers |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
34 |
| Bayesian efficiency analysis with a flexible cost function |
0 |
0 |
0 |
2 |
0 |
1 |
1 |
16 |
| Bayesian efficiency analysis with a flexible form: The aim cost function |
0 |
0 |
0 |
8 |
0 |
0 |
1 |
50 |
| Bayesian efficiency analysis with a flexible form: The aim cost function |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
3 |
| Bayesian inference in models based on equilibrium search theory |
0 |
0 |
0 |
6 |
0 |
1 |
3 |
196 |
| Bayesian long-run prediction in time series models |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
37 |
| Bayesian modelling of VAR precision matrices using stochastic block networks |
1 |
1 |
14 |
14 |
1 |
3 |
12 |
12 |
| Bayesian modelling of catch in a Northwest Atlantic Fishery |
0 |
0 |
0 |
0 |
0 |
3 |
4 |
159 |
| Comparing the Performance of Baseball Players: A Multiple Output Approach |
0 |
0 |
2 |
145 |
0 |
1 |
7 |
447 |
| Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility |
0 |
0 |
0 |
18 |
1 |
1 |
1 |
28 |
| Composite likelihood methods for large Bayesian VARs with stochastic volatility |
1 |
1 |
1 |
58 |
2 |
3 |
3 |
66 |
| Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs |
0 |
0 |
0 |
30 |
0 |
0 |
1 |
61 |
| Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
17 |
| Cross-sectoral patterns of efficiency and technical change in manufacturing: A stochastic frontier analysis |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
184 |
| Decision Synthesis in Monetary Policy |
0 |
0 |
3 |
3 |
0 |
1 |
11 |
11 |
| Decision synthesis in monetary policy |
0 |
1 |
18 |
18 |
1 |
3 |
46 |
46 |
| Domestic Violence and Football in Glasgow: Are Reference Points Relevant? |
0 |
0 |
1 |
98 |
1 |
1 |
5 |
355 |
| Domestic Violence and Football in Glasgow: Are Reference Points Relevant? |
0 |
0 |
0 |
28 |
0 |
1 |
1 |
75 |
| Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods |
0 |
1 |
1 |
30 |
0 |
1 |
2 |
38 |
| Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
5 |
| Dynamic asymmetries in US unemployment |
0 |
0 |
0 |
45 |
0 |
1 |
2 |
403 |
| Dynamic probabilities of restrictions in state space models: An application to the Phillips curve |
1 |
1 |
1 |
13 |
1 |
1 |
2 |
51 |
| Efficient Posterior Simulation for Cointegrated Models with Priors On the Cointegration Space |
0 |
0 |
0 |
162 |
0 |
1 |
3 |
449 |
| Estimating Phillips Curves in Turbulent Times using the ECBs Survey of Professional Forecasters* |
0 |
0 |
0 |
94 |
0 |
0 |
2 |
194 |
| Estimating Phillips Curves in Turbulent Times using the ECB’s Survey of Professional Forecasters |
0 |
0 |
0 |
38 |
0 |
0 |
0 |
95 |
| Estimating Phillips curves in turbulent times using the ECB's survey of professional forecasters |
0 |
0 |
0 |
104 |
0 |
0 |
3 |
200 |
| 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 |
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 |
11 |
0 |
0 |
0 |
80 |
| Exchange rate predictability and dynamic Bayesian learning |
0 |
0 |
0 |
117 |
0 |
2 |
4 |
262 |
| Exchange rate predictability and dynamic Bayesian learning |
0 |
0 |
0 |
29 |
0 |
1 |
3 |
89 |
| Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models |
0 |
0 |
0 |
56 |
0 |
9 |
12 |
70 |
| Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks |
0 |
1 |
1 |
1 |
1 |
4 |
6 |
13 |
| Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks |
0 |
0 |
0 |
29 |
0 |
2 |
3 |
20 |
| Fast, Order-Invariant Bayesian Inference in VARs using the Eigendecomposition of the Error Covariance Matrix |
0 |
0 |
1 |
12 |
1 |
2 |
7 |
17 |
| Forecasting Inflation Using Dynamic Model Averaging |
0 |
0 |
1 |
20 |
0 |
1 |
3 |
115 |
| Forecasting Inflation Using Dynamic Model Averaging |
0 |
0 |
1 |
92 |
1 |
2 |
3 |
125 |
| Forecasting Inflation Using Dynamic Model Averaging |
1 |
3 |
9 |
612 |
1 |
3 |
20 |
1,218 |
| Forecasting Inflation Using Dynamic Model Averaging* |
0 |
0 |
2 |
178 |
1 |
3 |
8 |
356 |
| Forecasting Substantial Data Revisions in the Presence of Model Uncertainty |
0 |
0 |
0 |
100 |
0 |
2 |
3 |
331 |
| Forecasting Substantial Data Revisions in the Presence of Model Uncertainty |
0 |
0 |
0 |
68 |
0 |
0 |
1 |
303 |
| Forecasting US Inflation Using Bayesian Nonparametric Models |
1 |
1 |
5 |
30 |
1 |
1 |
10 |
56 |
| Forecasting US Inflation Using Bayesian Nonparametric Models |
0 |
0 |
2 |
122 |
0 |
0 |
5 |
109 |
| Forecasting With High Dimensional Panel VARs |
0 |
0 |
0 |
340 |
1 |
2 |
6 |
575 |
| Forecasting and Estimating Multiple Change-point Models with an Unknown Number of Change-points |
0 |
0 |
0 |
383 |
0 |
1 |
2 |
991 |
| Forecasting and estimating multiple change-point models with an unknown number of change points |
0 |
1 |
1 |
252 |
0 |
1 |
3 |
809 |
| Forecasting in Large Macroeconomic Panels using Bayesian Model Averaging |
0 |
0 |
1 |
191 |
0 |
1 |
2 |
583 |
| Forecasting in large macroeconomic panels using Bayesian Model Averaging |
0 |
0 |
0 |
273 |
0 |
0 |
2 |
656 |
| Forecasting the European Carbon Market |
0 |
0 |
0 |
167 |
0 |
7 |
9 |
475 |
| Forecasting the European Carbon Market |
0 |
0 |
0 |
33 |
0 |
0 |
0 |
83 |
| Forecasting with High-Dimensional Panel VARs |
0 |
2 |
11 |
295 |
0 |
5 |
23 |
636 |
| Forecasting with High-Dimensional Panel VARs |
0 |
0 |
0 |
119 |
0 |
1 |
3 |
127 |
| Forecasting with High-Dimensional Panel VARs |
0 |
0 |
0 |
21 |
0 |
1 |
2 |
59 |
| Forecasting with Medium and Large Bayesian VARs |
1 |
1 |
2 |
151 |
2 |
2 |
6 |
382 |
| Forecasting with Medium and Large Bayesian VARs |
1 |
1 |
2 |
99 |
1 |
4 |
7 |
136 |
| Forecasting with Medium and Large Bayesian VARs |
2 |
2 |
3 |
143 |
2 |
3 |
5 |
245 |
| Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
1 |
1 |
41 |
0 |
2 |
4 |
135 |
| Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
0 |
2 |
127 |
1 |
2 |
9 |
323 |
| Hierarchical Shrinkage in Time-Varying Parameter Models |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
31 |
| Hierarchical shrinkage in time-varying parameter models |
0 |
0 |
0 |
121 |
0 |
0 |
0 |
166 |
| Hierarchical shrinkage in time-varying parameter models |
0 |
1 |
4 |
260 |
0 |
2 |
6 |
458 |
| Hospital efficiency analysis through individual effects: A Bayesian approach |
0 |
0 |
0 |
14 |
0 |
2 |
2 |
35 |
| Hospital efficiency analysis through individual effects: A Bayesian approach |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
4 |
| Identifying Noise Shocks |
0 |
0 |
0 |
54 |
0 |
0 |
0 |
97 |
| Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting |
0 |
0 |
1 |
8 |
0 |
1 |
4 |
17 |
| Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting |
0 |
3 |
6 |
28 |
1 |
7 |
12 |
26 |
| Inducing Sparsity and Shrinkage in Time-Varying Parameter Models |
0 |
0 |
0 |
65 |
0 |
2 |
3 |
101 |
| Inducing Sparsity and Shrinkage in Time-Varying Parameter Models |
0 |
0 |
1 |
12 |
0 |
0 |
1 |
42 |
| Inducing sparsity and shrinkage in time-varying parameter models |
0 |
0 |
0 |
7 |
0 |
2 |
4 |
21 |
| Investigating Economic Uncertainty Using Stochastic Volatility in Mean VARs: The Importance of Model Size, Order-Invariance and Classification |
0 |
0 |
0 |
0 |
0 |
4 |
15 |
32 |
| Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
8 |
| Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model |
0 |
1 |
2 |
36 |
0 |
2 |
5 |
51 |
| Large Bayesian VARMAs |
0 |
0 |
0 |
2 |
1 |
1 |
1 |
20 |
| Large Bayesian VARMAs |
0 |
0 |
0 |
44 |
0 |
0 |
0 |
87 |
| Large Bayesian VARMAs |
0 |
0 |
1 |
20 |
0 |
1 |
3 |
48 |
| Large Bayesian VARMAs |
0 |
0 |
0 |
88 |
0 |
0 |
2 |
95 |
| Large Order-Invariant Bayesian VARs with Stochastic Volatility |
0 |
0 |
1 |
66 |
0 |
0 |
1 |
43 |
| Large Time-Varying Parameter VARs |
0 |
1 |
2 |
63 |
0 |
2 |
4 |
164 |
| Large Time-Varying Parameter VARs |
0 |
1 |
3 |
112 |
0 |
3 |
9 |
233 |
| Large time-varying parameter VARs |
0 |
3 |
9 |
832 |
1 |
4 |
15 |
1,488 |
| Large time-varying parameter VARs |
0 |
0 |
0 |
41 |
0 |
1 |
8 |
152 |
| Learning About Heterogeneity in Returns to Schooling |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
393 |
| Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs |
0 |
0 |
0 |
39 |
0 |
1 |
2 |
59 |
| Measuring the Sources of Output Growth in a Panel of Countries |
0 |
0 |
0 |
23 |
0 |
0 |
1 |
332 |
| Model Switching and Model Averaging in Time- Varying Parameter Regression Models |
0 |
0 |
0 |
35 |
0 |
1 |
1 |
54 |
| Model Switching and Model Averaging in Time-Varying Parameter Regression Models |
0 |
0 |
0 |
128 |
0 |
0 |
0 |
257 |
| Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
1 |
28 |
0 |
1 |
3 |
68 |
| Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
71 |
0 |
0 |
0 |
61 |
| Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
110 |
0 |
1 |
1 |
120 |
| Model Uncertainty in Panel Vector Autoregressive Models |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
50 |
| Model uncertainty in panel vector autoregressive models |
0 |
0 |
5 |
270 |
0 |
1 |
13 |
442 |
| Model uncertainty in panel vector autoregressive models |
0 |
0 |
0 |
38 |
0 |
0 |
1 |
85 |
| Modeling the Dynamics of Inflation Compensation |
0 |
0 |
0 |
36 |
1 |
1 |
1 |
104 |
| Modeling the Evolution of Distributions: An Application to Major League Baseball |
0 |
0 |
1 |
86 |
0 |
1 |
2 |
189 |
| 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 |
1 |
1 |
39 |
| Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables |
0 |
0 |
0 |
19 |
0 |
0 |
1 |
61 |
| Modelling breaks and clusters in the steady states of macroeconomic variables |
0 |
0 |
0 |
12 |
1 |
2 |
3 |
56 |
| Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture |
0 |
0 |
0 |
424 |
0 |
0 |
1 |
1,051 |
| Multiple-output production with undesirable output: An application to nitrogen surplus in agriculture |
0 |
0 |
1 |
6 |
0 |
0 |
1 |
449 |
| Nowcasting 'true' monthly US GDP during the pandemic |
0 |
0 |
0 |
60 |
0 |
0 |
3 |
86 |
| Nowcasting Scottish GDP Growth |
0 |
0 |
0 |
4 |
0 |
2 |
3 |
48 |
| Nowcasting Scottish GDP Growth |
0 |
0 |
0 |
30 |
0 |
1 |
2 |
111 |
| Nowcasting Scottish GDP growth |
0 |
0 |
0 |
23 |
0 |
0 |
2 |
83 |
| Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs |
0 |
0 |
0 |
58 |
0 |
1 |
3 |
142 |
| Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs |
0 |
0 |
0 |
78 |
0 |
2 |
2 |
75 |
| Nowcasting in a pandemic using non-parametric mixed frequency VARs |
0 |
0 |
0 |
50 |
2 |
4 |
5 |
63 |
| On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
210 |
0 |
0 |
1 |
362 |
| On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
93 |
0 |
0 |
0 |
181 |
| On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
38 |
0 |
0 |
1 |
94 |
| On Identification of Bayesian DSGE Models |
0 |
0 |
1 |
54 |
0 |
1 |
4 |
183 |
| On Identification of Bayesian DSGE Models* |
0 |
0 |
0 |
70 |
0 |
0 |
1 |
170 |
| On the Evolution of Monetary Policy |
1 |
1 |
2 |
12 |
2 |
2 |
5 |
41 |
| Parametric and Nonparametric Inference in Equilibrium Job Search Models |
0 |
0 |
0 |
40 |
0 |
3 |
6 |
185 |
| Posterior Analysis of Stochastic Frontier Models using Gibbs Sampling |
0 |
1 |
2 |
126 |
2 |
9 |
14 |
334 |
| Posterior analysis of stochastic frontier models using Gibbs sampling |
0 |
0 |
2 |
27 |
0 |
2 |
8 |
90 |
| Posterior inference on long-run impulse responses |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
17 |
| Predictive Density Combination Using a Tree-Based Synthesis Function |
0 |
0 |
0 |
17 |
0 |
1 |
4 |
15 |
| Predictive Density Combination Using a Tree-Based Synthesis Function |
0 |
0 |
0 |
9 |
1 |
1 |
5 |
10 |
| Predictive Density Combination Using a Tree-Based Synthesis Function |
0 |
0 |
0 |
10 |
1 |
3 |
4 |
18 |
| Prior Elicitation in Multiple Change-point Models |
0 |
0 |
0 |
4 |
0 |
2 |
3 |
18 |
| 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 |
104 |
0 |
0 |
0 |
491 |
| Re-examining the Consumption-Wealth Relationship: The Role of Model Uncertainty |
0 |
0 |
1 |
216 |
0 |
2 |
3 |
496 |
| Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty |
0 |
0 |
0 |
52 |
0 |
1 |
1 |
203 |
| Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty |
0 |
0 |
0 |
147 |
0 |
1 |
1 |
551 |
| Reconciled Estimates of Monthly GDP in the US |
0 |
0 |
0 |
9 |
0 |
1 |
5 |
26 |
| Reconciled Estimates of Monthly GDP in the US |
0 |
0 |
0 |
47 |
2 |
2 |
4 |
115 |
| Reexamining the consumption-wealth relationship: the role of model uncertainty |
0 |
0 |
0 |
76 |
0 |
1 |
2 |
320 |
| Regime-Switching Cointegration |
0 |
0 |
1 |
11 |
0 |
1 |
5 |
51 |
| Regime-Switching Cointegration |
0 |
0 |
1 |
120 |
0 |
0 |
3 |
305 |
| Regime-Switching Cointegration |
0 |
0 |
0 |
45 |
0 |
0 |
1 |
63 |
| Regime-Switching Cointegration* |
0 |
0 |
1 |
178 |
0 |
0 |
4 |
376 |
| Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017 |
1 |
2 |
3 |
104 |
1 |
3 |
13 |
153 |
| Semiparametric Bayesian Inference in Multiple Equation Models |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
256 |
| Semiparametric Bayesian Inference in Smooth Coefficient Models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
169 |
| Semiparametric Bayesian inference in smooth coefficient models |
0 |
0 |
0 |
116 |
0 |
0 |
2 |
477 |
| Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy |
0 |
0 |
0 |
89 |
0 |
2 |
2 |
214 |
| 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 |
28 |
0 |
0 |
0 |
108 |
| Stochastic frontier models: a bayesian perspective |
0 |
0 |
1 |
40 |
0 |
0 |
1 |
114 |
| Subspace Shrinkage in Conjugate Bayesian Vector Autoregressions |
0 |
0 |
0 |
23 |
0 |
0 |
0 |
27 |
| Tail Forecasting with Multivariate Bayesian Additive Regression Trees |
0 |
0 |
0 |
4 |
0 |
3 |
9 |
17 |
| Tail Forecasting with Multivariate Bayesian Additive Regression Trees |
0 |
0 |
0 |
78 |
1 |
2 |
3 |
90 |
| Technical Appendix to: Understanding Liquidity and Credit Risks in the Financial Crisis |
0 |
0 |
1 |
28 |
0 |
0 |
2 |
90 |
| 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 |
0 |
719 |
| The Components of Output Growth: A Cross-Country Analysis |
0 |
0 |
0 |
17 |
0 |
0 |
0 |
105 |
| The Contribution of Structural Break Models to Forecasting Macroeconomic Series |
0 |
0 |
5 |
382 |
1 |
3 |
9 |
686 |
| The Contribution of Structural Break Models to Forecating Macroeconomic Series |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
44 |
| The Dynamics of UK and US Inflation Expectation |
0 |
0 |
0 |
17 |
0 |
0 |
0 |
66 |
| The Dynamics of UK and US Inflation Expectations |
0 |
0 |
0 |
47 |
0 |
0 |
1 |
126 |
| 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 |
1 |
7 |
0 |
0 |
1 |
61 |
| The Dynamics of UK and US Inflation Expectations* |
0 |
0 |
0 |
76 |
0 |
0 |
0 |
182 |
| The Known Unknowns of Governance |
0 |
0 |
0 |
6 |
0 |
1 |
3 |
49 |
| 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 |
1 |
0 |
0 |
0 |
8 |
| The components of output growth: A cross-country analysis |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
37 |
| 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 |
13 |
2,264 |
| Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada |
0 |
0 |
0 |
23 |
0 |
0 |
2 |
93 |
| 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 |
67 |
1 |
1 |
2 |
210 |
| Time Varying Dimension Models |
0 |
0 |
0 |
51 |
0 |
0 |
7 |
296 |
| Time Varying Dimension Models |
0 |
0 |
1 |
118 |
0 |
0 |
1 |
427 |
| Time Varying Dimension Models |
0 |
0 |
0 |
29 |
1 |
1 |
1 |
122 |
| Time Varying Dimension Models |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
23 |
| UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? |
0 |
0 |
2 |
283 |
0 |
1 |
4 |
610 |
| UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? |
0 |
0 |
3 |
119 |
0 |
4 |
8 |
246 |
| UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So? |
0 |
0 |
0 |
42 |
0 |
0 |
3 |
72 |
| UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?* |
0 |
0 |
1 |
67 |
0 |
1 |
2 |
157 |
| UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model |
0 |
0 |
1 |
119 |
0 |
0 |
3 |
98 |
| UK regional nowcasting using a mixed frequency vector autoregressive model |
0 |
0 |
1 |
68 |
0 |
0 |
4 |
114 |
| Understanding Liquidity and Credit Risks in the Financial Crisis |
1 |
1 |
1 |
83 |
1 |
1 |
3 |
202 |
| Understanding Liquidity and Credit Risks in the Financial Crisis |
0 |
0 |
0 |
132 |
0 |
0 |
0 |
244 |
| Understanding Liquidity and Credit Risks in the Financial Crisis* |
0 |
0 |
0 |
250 |
3 |
4 |
7 |
449 |
| Using VARs and TVP-VARs with Many Macroeconomic Variables |
0 |
0 |
0 |
75 |
1 |
1 |
2 |
151 |
| Using VARs and TVP-VARs with Many Macroeconomic Variables |
0 |
1 |
1 |
143 |
1 |
3 |
5 |
207 |
| Using hierarchical aggregation constraints to nowcast regional economic aggregates |
0 |
0 |
0 |
18 |
0 |
0 |
4 |
26 |
| Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates |
0 |
0 |
1 |
52 |
0 |
1 |
2 |
35 |
| Variational Bayes inference in high-dimensional time-varying parameter models |
0 |
1 |
1 |
361 |
0 |
3 |
4 |
732 |
| Variational Bayes inference in high-dimensional time-varying parameter models |
0 |
3 |
6 |
59 |
0 |
4 |
13 |
200 |
| Variational Bayes inference in high-dimensional time-varying parameter models |
0 |
0 |
1 |
18 |
0 |
0 |
4 |
49 |
| Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage |
0 |
1 |
1 |
27 |
0 |
1 |
1 |
77 |
| Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage |
1 |
1 |
3 |
19 |
2 |
2 |
7 |
60 |
| Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage |
0 |
0 |
0 |
101 |
1 |
3 |
6 |
224 |
| What is the Environmental Performance of Firms Overseas?: An Empirical Investigation of the Global Gold Mining Industry |
0 |
0 |
0 |
7 |
0 |
1 |
3 |
54 |
| Total Working Papers |
27 |
81 |
364 |
23,364 |
99 |
379 |
1,257 |
66,769 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| 'Objective' Bayesian Unit Root Tests |
0 |
0 |
0 |
147 |
0 |
0 |
1 |
453 |
| A Bayesian analysis of a variance decomposition for stock returns |
0 |
0 |
0 |
91 |
0 |
1 |
1 |
268 |
| A Bayesian analysis of multiple-output production frontiers |
0 |
0 |
0 |
138 |
0 |
0 |
4 |
336 |
| A Bounded Model of Time Variation in Trend Inflation, Nairu and the Phillips Curve |
0 |
1 |
7 |
42 |
0 |
1 |
14 |
132 |
| A Decision-Theoretic Analysis of the Unit-Root Hypothesis Using Mixtures of Elliptical Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
184 |
| A New Model of Inflation, Trend Inflation, and Long‐Run Inflation Expectations |
1 |
3 |
13 |
44 |
4 |
7 |
23 |
131 |
| A New Model of Trend Inflation |
2 |
4 |
6 |
128 |
2 |
4 |
16 |
430 |
| A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies |
0 |
1 |
1 |
320 |
1 |
6 |
9 |
1,112 |
| A flexible approach to parametric inference in nonlinear and time varying time series models |
0 |
0 |
1 |
54 |
0 |
0 |
3 |
210 |
| A new index of financial conditions |
1 |
2 |
8 |
279 |
7 |
14 |
54 |
1,513 |
| A new look at variation in employment growth in Canada: The role of industry, provincial, national and external factors |
0 |
0 |
1 |
15 |
0 |
0 |
4 |
70 |
| APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs |
0 |
0 |
1 |
3 |
2 |
5 |
7 |
14 |
| Aggregate Shocks and Macroeconomic Fluctuations: A Bayesian Approach |
0 |
1 |
2 |
154 |
0 |
1 |
2 |
329 |
| Alternative efficiency measures for multiple-output production |
0 |
0 |
0 |
74 |
0 |
0 |
3 |
245 |
| An Empirical Investigation of Wagner's Hypothesis by Using a Model Occurrence Framework |
0 |
0 |
0 |
1 |
0 |
1 |
2 |
10 |
| An empirical assessment of recent challenges in today's financial markets |
0 |
0 |
0 |
13 |
0 |
0 |
1 |
35 |
| An objective Bayesian analysis of common stochastic trends in international stock prices and exchange rates |
0 |
0 |
0 |
73 |
0 |
0 |
1 |
250 |
| Are apparent findings of nonlinearity due to structural instability in economic time series? |
0 |
0 |
0 |
6 |
0 |
0 |
1 |
307 |
| BAYESIAN DYNAMIC VARIABLE SELECTION IN HIGH DIMENSIONS |
0 |
1 |
1 |
1 |
0 |
2 |
4 |
6 |
| Bayes factors and nonlinearity: Evidence from economic time series1 |
0 |
0 |
2 |
71 |
0 |
0 |
3 |
195 |
| Bayesian Analysis of Endogenous Delay Threshold Models |
0 |
0 |
0 |
2 |
0 |
1 |
1 |
293 |
| Bayesian Analysis, Computation and Communication Software |
0 |
0 |
1 |
187 |
0 |
1 |
2 |
650 |
| Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
353 |
| Bayesian Methods for Empirical Macroeconomics |
0 |
0 |
1 |
20 |
1 |
4 |
12 |
90 |
| Bayesian Multivariate Time Series Methods for Empirical Macroeconomics |
1 |
6 |
21 |
539 |
9 |
24 |
87 |
1,438 |
| Bayesian Semi-nonparametric ARCH Models |
0 |
0 |
0 |
72 |
0 |
0 |
0 |
232 |
| Bayesian analysis of logit models using natural conjugate priors |
0 |
0 |
1 |
189 |
1 |
1 |
5 |
419 |
| Bayesian analysis of long memory and persistence using ARFIMA models |
0 |
0 |
0 |
96 |
0 |
0 |
2 |
457 |
| Bayesian compressed vector autoregressions |
0 |
0 |
0 |
36 |
1 |
1 |
3 |
115 |
| Bayesian efficiency analysis through individual effects: Hospital cost frontiers |
0 |
0 |
1 |
258 |
1 |
1 |
6 |
646 |
| Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks |
0 |
0 |
0 |
46 |
0 |
2 |
2 |
182 |
| Bayesian inference in a time varying cointegration model |
1 |
3 |
4 |
69 |
1 |
5 |
13 |
198 |
| Bayesian inference in models based on equilibrium search theory |
0 |
0 |
0 |
36 |
0 |
0 |
1 |
134 |
| Bayesian long-run prediction in time series models |
0 |
1 |
2 |
61 |
1 |
2 |
5 |
196 |
| Bayesian model averaging in the instrumental variable regression model |
1 |
1 |
1 |
41 |
1 |
2 |
5 |
133 |
| Bayesian variants of some classical semiparametric regression techniques |
0 |
0 |
0 |
60 |
0 |
0 |
1 |
174 |
| Carbon dioxide emissions and economic growth: A structural approach |
0 |
0 |
1 |
161 |
0 |
0 |
2 |
553 |
| Choosing between identification schemes in noisy-news models |
0 |
0 |
1 |
2 |
0 |
0 |
2 |
9 |
| Cointegration tests in present value relationships: A Bayesian look at the bivariate properties of stock prices and dividends |
0 |
0 |
0 |
36 |
0 |
0 |
1 |
122 |
| Comparing the Performance of Baseball Players: A Multiple-Output Approach |
0 |
0 |
0 |
33 |
0 |
1 |
1 |
121 |
| Composite likelihood methods for large Bayesian VARs with stochastic volatility |
0 |
0 |
0 |
3 |
1 |
2 |
2 |
25 |
| Computationally efficient inference in large Bayesian mixed frequency VARs |
0 |
0 |
0 |
15 |
0 |
0 |
2 |
55 |
| Correction [Posterior Properties of Long-Run Impulse Responses] |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
109 |
| Cross-Sectoral Patterns of Efficiency and Technical Change in Manufacturing |
0 |
0 |
0 |
46 |
0 |
2 |
2 |
235 |
| Current developments in productivity and efficiency measurement |
0 |
0 |
0 |
144 |
0 |
0 |
0 |
333 |
| Do environmental regulations affect the location decisions of multinational gold mining firms? |
0 |
0 |
0 |
29 |
0 |
1 |
5 |
131 |
| Do recessions permanently change output? |
0 |
1 |
1 |
552 |
0 |
2 |
3 |
1,149 |
| Domestic Violence and Football in Glasgow: Are Reference Points Relevant? |
0 |
1 |
2 |
7 |
0 |
2 |
5 |
71 |
| Dynamic Asymmetries in U.S. Unemployment |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
604 |
| Dynamic Probabilities of Restrictions in State Space Models: An Application to the Phillips Curve |
0 |
0 |
0 |
42 |
2 |
3 |
3 |
176 |
| Dynamic Shrinkage Priors for Large Time-Varying Parameter Regressions Using Scalable Markov Chain Monte Carlo Methods |
0 |
1 |
2 |
2 |
1 |
2 |
4 |
4 |
| Econometric estimation of proportional hazard models |
0 |
0 |
0 |
63 |
0 |
0 |
0 |
147 |
| Editorial Introduction of the Special Issue of Studies in Nonlinear Dynamics and Econometrics in Honor of Herman van Dijk |
0 |
0 |
3 |
3 |
0 |
0 |
3 |
3 |
| Editorial: The Scottish Journal of Political Economy's 60th Birthday Issue |
0 |
0 |
0 |
15 |
0 |
0 |
1 |
62 |
| Editors' Introduction to the Special Issue of Econometric Reviews on Bayesian Dynamic Econometrics |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
90 |
| Efficient Posterior Simulation for Cointegrated Models with Priors on the Cointegration Space |
1 |
2 |
3 |
58 |
1 |
4 |
7 |
155 |
| 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 |
8 |
0 |
0 |
0 |
49 |
| Estimation and Forecasting in Models with Multiple Breaks |
0 |
0 |
9 |
121 |
1 |
3 |
17 |
342 |
| Exchange rate predictability and dynamic Bayesian learning |
1 |
1 |
2 |
20 |
2 |
4 |
13 |
134 |
| FORECASTING INFLATION USING DYNAMIC MODEL AVERAGING |
3 |
4 |
6 |
72 |
6 |
7 |
15 |
267 |
| Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models |
0 |
1 |
1 |
6 |
0 |
1 |
2 |
10 |
| Forecasting Substantial Data Revisions in the Presence of Model Uncertainty |
0 |
0 |
0 |
24 |
0 |
0 |
0 |
255 |
| Forecasting Substantial Data Revisions in the Presence of Model Uncertainty |
0 |
0 |
0 |
1 |
0 |
1 |
2 |
6 |
| Forecasting in dynamic factor models using Bayesian model averaging |
0 |
0 |
0 |
252 |
1 |
1 |
5 |
716 |
| Forecasting the European carbon market |
0 |
0 |
0 |
15 |
0 |
0 |
1 |
81 |
| Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage |
0 |
1 |
3 |
4 |
0 |
1 |
6 |
13 |
| Forecasting with High‐Dimensional Panel VARs |
0 |
1 |
2 |
20 |
0 |
4 |
8 |
54 |
| Forecasting with Medium and Large Bayesian VARS |
0 |
0 |
0 |
0 |
2 |
3 |
10 |
234 |
| Forecasting with dimension switching VARs |
0 |
0 |
0 |
9 |
0 |
1 |
2 |
45 |
| Go climb a mountain: an application of recreation demand modelling to rock climbing in Scotland |
0 |
0 |
0 |
18 |
0 |
8 |
9 |
97 |
| Hierarchical Shrinkage in Time‐Varying Parameter Models |
0 |
1 |
2 |
38 |
2 |
4 |
6 |
143 |
| Identifying noise shocks |
0 |
0 |
0 |
13 |
0 |
0 |
4 |
49 |
| Impulse response analysis in nonlinear multivariate models |
7 |
14 |
76 |
3,105 |
17 |
37 |
187 |
6,346 |
| Incomplete models and reweighting |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
28 |
| Inducing Sparsity and Shrinkage in Time-Varying Parameter Models |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
21 |
| Intertemporal Properties of Real Output: A Bayesian Analysis |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
113 |
| Is there an environmental Kuznets curve for deforestation? |
0 |
3 |
7 |
515 |
0 |
5 |
13 |
2,045 |
| Large Bayesian VARMAs |
0 |
0 |
0 |
14 |
0 |
1 |
3 |
99 |
| Large Order-Invariant Bayesian VARs with Stochastic Volatility |
1 |
2 |
6 |
6 |
2 |
6 |
14 |
14 |
| Large time-varying parameter VARs |
1 |
1 |
3 |
235 |
3 |
9 |
19 |
616 |
| Learning about the across-regime correlation in switching regression models |
0 |
0 |
1 |
70 |
0 |
0 |
3 |
171 |
| Measuring differential forest outcomes: A tale of two countries |
0 |
0 |
1 |
21 |
0 |
0 |
2 |
88 |
| Measuring the health effects of air pollution: to what extent can we really say that people are dying from bad air? |
1 |
1 |
3 |
144 |
1 |
1 |
4 |
519 |
| Model uncertainty in Panel Vector Autoregressive models |
0 |
0 |
2 |
80 |
0 |
1 |
9 |
234 |
| Modeling the Sources of Output Growth in a Panel of Countries |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
396 |
| Modeling the dynamics of inflation compensation |
1 |
1 |
1 |
50 |
1 |
1 |
1 |
171 |
| Modeling the relationship between European carbon permits and certified emission reductions |
0 |
0 |
0 |
22 |
0 |
2 |
8 |
102 |
| Modelling Recreation Demand Using Choice Experiments: Climbing in Scotland |
0 |
0 |
0 |
119 |
0 |
0 |
0 |
340 |
| Modelling breaks and clusters in the steady states of macroeconomic variables |
0 |
0 |
0 |
5 |
0 |
1 |
2 |
33 |
| Modelling the evolution of distributions: an application to Major League baseball |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
94 |
| Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture |
0 |
0 |
0 |
55 |
0 |
0 |
2 |
161 |
| NOWCASTING ‘TRUE’ MONTHLY U.S. GDP DURING THE PANDEMIC |
0 |
0 |
0 |
9 |
0 |
0 |
2 |
23 |
| Nowcasting Using Mixed Frequency Methods: An Application to the Scottish Economy |
0 |
0 |
0 |
6 |
0 |
1 |
5 |
34 |
| Nowcasting in a pandemic using non-parametric mixed frequency VARs |
0 |
1 |
1 |
11 |
0 |
3 |
6 |
33 |
| On Identification of Bayesian DSGE Models |
0 |
0 |
0 |
98 |
1 |
2 |
3 |
254 |
| On the evolution of the monetary policy transmission mechanism |
1 |
2 |
12 |
392 |
1 |
4 |
23 |
823 |
| On the sensitivity of unit root inference to nonlinear data transformations |
0 |
0 |
0 |
14 |
0 |
0 |
2 |
80 |
| One size does not fit all… panel data: Bayesian model averaging and data poolability |
0 |
1 |
2 |
11 |
0 |
2 |
7 |
55 |
| PRIOR ELICITATION IN MULTIPLE CHANGE-POINT MODELS |
0 |
0 |
0 |
32 |
0 |
0 |
1 |
168 |
| Parameter uncertainty and impulse response analysis |
0 |
0 |
0 |
143 |
0 |
0 |
3 |
342 |
| Posterior Properties of Long-Run Impulse Responses |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
150 |
| RECONCILED ESTIMATES AND NOWCASTS OF REGIONAL OUTPUT IN THE UK |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
4 |
| Rank-Ordered Logit Models: An Empirical Analysis of Ontario Voter Preferences |
0 |
0 |
0 |
627 |
0 |
0 |
4 |
1,882 |
| Re-Examining the Consumption-Wealth Relationship: The Role of Model Uncertainty |
0 |
0 |
0 |
55 |
1 |
2 |
2 |
169 |
| Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty |
0 |
1 |
1 |
61 |
0 |
1 |
1 |
204 |
| Recent Progress in Applied Bayesian Econometrics |
0 |
0 |
0 |
0 |
0 |
2 |
4 |
391 |
| Reconciled Estimates of Monthly GDP in the United States |
0 |
0 |
0 |
1 |
0 |
1 |
2 |
12 |
| Regime-switching cointegration |
0 |
0 |
0 |
41 |
0 |
0 |
3 |
131 |
| Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970 |
0 |
0 |
2 |
24 |
1 |
1 |
5 |
77 |
| Review of PCBRAP |
0 |
0 |
0 |
21 |
0 |
0 |
0 |
170 |
| Re‐Examining the Consumption–Wealth Relationship: The Role of Model Uncertainty |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
13 |
| Semiparametric Bayesian inference in multiple equation models |
1 |
1 |
2 |
102 |
1 |
1 |
2 |
381 |
| Semiparametric Bayesian inference in smooth coefficient models |
0 |
0 |
0 |
34 |
0 |
0 |
0 |
121 |
| Should we care about the uncertainty around measures of political-economic development? |
0 |
0 |
0 |
8 |
0 |
1 |
9 |
66 |
| Stochastic frontier models: A Bayesian perspective |
1 |
1 |
2 |
489 |
1 |
2 |
11 |
896 |
| Stochastic search variable selection in vector error correction models with an application to a model of the UK macroeconomy |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
61 |
| Subspace shrinkage in conjugate Bayesian vector autoregressions |
0 |
0 |
1 |
2 |
0 |
0 |
2 |
10 |
| TAIL FORECASTING WITH MULTIVARIATE BAYESIAN ADDITIVE REGRESSION TREES |
0 |
1 |
3 |
8 |
0 |
2 |
7 |
25 |
| TIME VARIATION IN THE DYNAMICS OF WORKER FLOWS: EVIDENCE FROM NORTH AMERICA AND EUROPE |
0 |
0 |
0 |
5 |
0 |
1 |
1 |
40 |
| Testing for integration using evolving trend and seasonals models: A Bayesian approach |
0 |
0 |
0 |
57 |
0 |
0 |
3 |
227 |
| Testing for optimality in job search models |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
255 |
| The Components of Output Growth: A Stochastic Frontier Analysis |
0 |
0 |
1 |
5 |
1 |
1 |
3 |
19 |
| The Contribution of Structural Break Models to Forecasting Macroeconomic Series |
1 |
1 |
1 |
35 |
2 |
2 |
5 |
117 |
| The dynamics of UK and US inflation expectations |
0 |
0 |
1 |
30 |
0 |
0 |
1 |
90 |
| The valuation of IPO and SEO firms |
0 |
0 |
0 |
184 |
0 |
0 |
2 |
868 |
| Time Varying Dimension Models |
0 |
0 |
0 |
29 |
1 |
3 |
5 |
145 |
| Time varying VARs with inequality restrictions |
0 |
0 |
1 |
88 |
0 |
2 |
9 |
238 |
| To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: A Comment |
0 |
0 |
0 |
39 |
0 |
1 |
1 |
210 |
| UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so? |
1 |
1 |
3 |
68 |
2 |
7 |
19 |
216 |
| UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting |
0 |
0 |
1 |
9 |
0 |
2 |
6 |
31 |
| Understanding liquidity and credit risks in the financial crisis |
0 |
0 |
1 |
41 |
0 |
0 |
1 |
159 |
| Using VARs and TVP-VARs with Many Macroeconomic Variables |
0 |
0 |
0 |
49 |
0 |
3 |
7 |
192 |
| What is the environmental performance of firms overseas? An empirical investigation of the global gold mining industry |
0 |
0 |
0 |
30 |
0 |
0 |
0 |
129 |
| Total Journal Articles |
28 |
70 |
248 |
12,553 |
87 |
256 |
888 |
39,691 |
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