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"Rotterdam Econometrics": an analysis of publications of the econometric institute 1956-2004 |
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7 |
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33 |
"Rotterdam econometrics": publications of the econometric institute 1956-2005 |
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4 |
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34 |
A BAYESIAN ANALYSIS OF THE UNIT ROOT HYPOTHESIS |
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1 |
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12 |
A BAYESIAN ANALYSIS OF THE UNIT ROOT IN REAL EXCHANGE RATES |
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2 |
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1 |
21 |
A Bayesian Analysis of the PPP Puzzle using an Unobserved Components Model |
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97 |
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1 |
433 |
A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance |
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7 |
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28 |
A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance |
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1 |
3 |
46 |
1 |
4 |
10 |
87 |
A Bayesian analysis of the PPP puzzle using an unobserved components model |
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0 |
0 |
7 |
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0 |
2 |
53 |
A Class of Adaptive EM-based Importance Sampling Algorithms for Efficient and Robust Posterior and Predictive Simulation |
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0 |
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25 |
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0 |
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95 |
A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation |
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24 |
0 |
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1 |
100 |
A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihood |
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32 |
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134 |
A Simple Strategy to prune Neural Networks with an Application to Economic Time Series |
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83 |
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1 |
215 |
A product of multivariate T densities as upper bound for the posterior kernel of simultaneous equation model parameters |
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2 |
0 |
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13 |
A product of multivariate T densities as upper bound for the posterior kernel of simultaneous equation model parameters |
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0 |
0 |
0 |
0 |
0 |
1 |
38 |
A reconsideration of the Angrist-Krueger analysis on returns to education |
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1 |
98 |
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1 |
9 |
491 |
A simple strategy to prune neural networks with an application to economic time series |
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16 |
0 |
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1 |
50 |
ADAPTIVE POLAR SAMPLING WITH AN APPLICATION TO A BAYES MEASURE OF VALUE-AT-RISK |
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0 |
0 |
0 |
0 |
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422 |
AN ALGORITHM FOR THE COMPUTATION OF POSTERIOR MOMENTS AND DENSITIES USING SIMPLE IMPORTANCE SAMPLING |
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0 |
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2 |
0 |
0 |
0 |
14 |
Adaptive Mixture of Student-t distributions as a Flexible Candidate Distribution for Efficient Simulation: the R Package AdMit |
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0 |
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41 |
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0 |
0 |
192 |
Adaptive Polar Sampling |
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0 |
0 |
0 |
0 |
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162 |
Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk |
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6 |
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86 |
Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk |
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182 |
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1,004 |
Adaptive Polar Sampling: A New MC Technique for the Analysis of Ill-behaved Surfaces |
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24 |
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516 |
Adaptive polar sampling with an application to a Bayes measure of value-at-risk |
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10 |
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530 |
Adaptive polar sampling, a class of flexibel and robust Monte Carlo integration methods |
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6 |
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64 |
Adaptive polar sampling: a new MC technique for the analysis of ill behaved surfaces |
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49 |
Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods |
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16 |
Adaptive radial-based direction sampling; Some flexible and robust Monte Carlo integration methods |
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19 |
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0 |
106 |
BAYESIAN ESTIMATES OF EQUATION SYSTEM PARAMETERS An Application of Integration by Monte Carlo |
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2 |
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2 |
33 |
BAYESIAN ESTIMATES OF EQUATION SYSTEM PARAMETERS An Unorthodox Application of Monte Carlo |
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8 |
BAYESIAN SPECIFICATION ANALYSIS AND ESTIMATION OF SIMULTANEOUS EQUATION MODELS USING MONTE CARLO METHODS |
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0 |
0 |
0 |
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838 |
Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann |
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81 |
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2 |
105 |
Bayes Estimates of Markov Trends in possibly Cointegrated Series: An Application to US Consumption and Income |
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128 |
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542 |
Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income |
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17 |
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0 |
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98 |
Bayes estimates of multimodal density features using DNA and Economic Data |
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2 |
13 |
1 |
1 |
9 |
35 |
Bayes estimates of the cyclical component in twentieth centruy US gross domestic product |
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42 |
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104 |
Bayes model averaging of cyclical decompositions in economic time series |
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13 |
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0 |
47 |
Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank |
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1 |
52 |
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0 |
1 |
33 |
Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo |
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0 |
0 |
41 |
1 |
1 |
2 |
198 |
Bayesian Approaches to Cointegration |
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2 |
279 |
1 |
1 |
5 |
626 |
Bayesian Averaging over Many Dynamic Model Structures with Evidence on the Great Ratios and Liquidity Trap Risk |
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55 |
0 |
0 |
1 |
134 |
Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index |
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0 |
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45 |
0 |
0 |
1 |
149 |
Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data |
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0 |
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49 |
0 |
0 |
1 |
72 |
Bayesian Forecasting of Value at Risk and Expected Shortfall using Adaptive Importance Sampling |
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0 |
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84 |
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2 |
252 |
Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan |
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0 |
2 |
59 |
0 |
1 |
8 |
216 |
Bayesian Model Selection with an Uninformative Prior |
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1 |
1 |
254 |
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1 |
1 |
920 |
Bayesian Simultaneous Equations Analysis using Reduced Rank Structures |
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124 |
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1 |
454 |
Bayesian Simultaneous Equations Analysis using Reduced Rank Structures |
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23 |
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0 |
1 |
119 |
Bayesian analysis of boundary and near-boundary evidence in econometric models with reduced rank |
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28 |
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1 |
32 |
Bayesian approaches to cointegratrion |
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1 |
32 |
0 |
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1 |
99 |
Bayesian model averaging in vector autoregressive processes with an investigation of stability of the US great ratios and risk of a liquidity trap in the USA, UK and Japan |
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20 |
1 |
1 |
2 |
96 |
Bayesian model selection for a sharp null and a diffuse alternative with econometric applications |
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4 |
0 |
0 |
0 |
61 |
Bayesian near-boundary analysis in basic macroeconomic time series models |
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1 |
89 |
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0 |
4 |
176 |
Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods |
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0 |
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0 |
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77 |
Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods |
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0 |
0 |
7 |
0 |
0 |
0 |
28 |
Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation |
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0 |
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50 |
0 |
0 |
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99 |
Combination Schemes for Turning Point Predictions |
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0 |
0 |
67 |
0 |
0 |
0 |
146 |
Combination schemes for turning point predictions |
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1 |
1 |
58 |
0 |
1 |
3 |
116 |
Combination schemes for turning point predictions |
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19 |
0 |
0 |
2 |
128 |
Combined Density Nowcasting in an Uncertain Economic Environment |
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0 |
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13 |
0 |
0 |
3 |
91 |
Combined Density Nowcasting in an uncertain economic environment |
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1 |
1 |
50 |
0 |
1 |
2 |
97 |
Combined Forecasts from Linear and Nonlinear Time Series Models |
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0 |
1 |
267 |
0 |
0 |
1 |
708 |
Combined forecasts from linear and nonlinear time series models |
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0 |
0 |
11 |
0 |
0 |
0 |
77 |
Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data |
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0 |
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41 |
0 |
0 |
0 |
87 |
Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data |
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0 |
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16 |
0 |
0 |
0 |
68 |
Combining predictive densities using Bayesian filtering with applications to US economic data |
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0 |
0 |
55 |
0 |
0 |
0 |
167 |
Combining predictive densities using Bayesian filtering with applications to US economics data |
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0 |
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67 |
0 |
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1 |
113 |
Comparison of the Anderson-Rubin test for overidentification and the Johansen test for cointegration |
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0 |
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51 |
0 |
0 |
4 |
305 |
Cyclical Components in Economic Time Series: a Bayesian Approach |
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0 |
0 |
374 |
0 |
0 |
1 |
1,226 |
Cyclical components in economic time series |
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1 |
1 |
98 |
0 |
1 |
2 |
198 |
Cyclical components in economic time series: A Bayesian approach |
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0 |
0 |
160 |
0 |
0 |
1 |
569 |
Daily Exchange Rate Behaviour and Hedging of Currency Risk |
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0 |
0 |
516 |
0 |
0 |
1 |
2,409 |
Daily Exchange Rate Behaviour and Hedging of Currency Risk |
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0 |
0 |
168 |
0 |
0 |
0 |
495 |
Daily Exchange Rate Behaviour and Hedging of Currency Risk |
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0 |
1 |
480 |
0 |
0 |
2 |
1,648 |
Daily exchange rate behaviour and hedging of currency risk |
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0 |
0 |
21 |
0 |
0 |
0 |
101 |
Daily exchange rate behaviour and hedging of currency risk |
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0 |
0 |
27 |
0 |
0 |
1 |
112 |
Distributional Dynamics using Quartic-based State-Space models |
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0 |
0 |
0 |
0 |
0 |
1 |
17 |
Distributional Dynamics using Quartic-based State-Space models |
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0 |
0 |
0 |
0 |
0 |
1 |
10 |
Distributional Dynamics using Quartic-based State-Space models |
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0 |
0 |
0 |
0 |
0 |
1 |
5 |
Distributional Dynamics using Quartic-based State-Space models |
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0 |
0 |
0 |
0 |
0 |
1 |
8 |
Divergent Priors and well Behaved Bayes Factors |
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0 |
0 |
33 |
0 |
0 |
1 |
144 |
Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance |
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0 |
0 |
76 |
0 |
0 |
3 |
164 |
Dynamic predictive density combinations for large data sets in economics and finance |
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0 |
3 |
37 |
0 |
0 |
5 |
109 |
EXPERIMENTS WITH SOME ALTERNATIVES FOR SIMPLE IMPORTANCE SAMPLING IN MONTE CARLO INTEGRATION |
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0 |
2 |
25 |
0 |
0 |
13 |
102 |
Editors' introduction. First Riverboat conference on Bayesian econometrics and statistics |
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0 |
0 |
0 |
0 |
1 |
1 |
19 |
Efficient Sampling from Non-Standard Distributions Using Neural NetworkApproximations |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
154 |
Evidence on Features of a DSGE Business Cycle Model from Bayesian Model Averaging |
0 |
0 |
0 |
57 |
0 |
0 |
0 |
128 |
Evidence on a DSGE Business Cycle model subject to Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging |
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0 |
0 |
52 |
0 |
0 |
0 |
115 |
Evidence on a Real Business Cycle Model with Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging |
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1 |
1 |
36 |
0 |
1 |
2 |
79 |
Evidence on a Real Business Cycle model with Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging |
0 |
0 |
0 |
63 |
1 |
1 |
3 |
123 |
Exceptions to Bartlett’s Paradox |
0 |
0 |
1 |
155 |
1 |
1 |
6 |
689 |
Explaining Adaptive Radial-Based Direction Sampling |
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0 |
0 |
7 |
1 |
1 |
1 |
59 |
FURTHER EXPERIENCE IN BAYESIAN ANALYSIS USING MONTE CARLO INTEGRATION |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
13 |
Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights |
0 |
0 |
1 |
99 |
0 |
0 |
1 |
250 |
Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies |
0 |
0 |
0 |
14 |
0 |
0 |
0 |
43 |
Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies |
0 |
0 |
0 |
31 |
0 |
0 |
1 |
50 |
Forecast Density Combinations with Dynamic Learning for Large Data Sets in Economics and Finance |
0 |
0 |
0 |
48 |
0 |
0 |
0 |
72 |
Forecast accuracy and economic gains from Bayesian model averaging using time varying weight |
0 |
0 |
0 |
96 |
0 |
0 |
2 |
162 |
Forecast density combinations with dynamic learning for large data sets in economics and finance |
0 |
0 |
0 |
32 |
0 |
0 |
0 |
54 |
Functional approximations to posterior densities: a neural network approach to efficient sampling |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
39 |
Gibbs sampling in econometric practice |
0 |
0 |
2 |
60 |
0 |
0 |
2 |
178 |
Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14 |
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0 |
1 |
17 |
0 |
0 |
5 |
91 |
Improper priors with well defined Bayes Factors |
0 |
0 |
0 |
261 |
0 |
0 |
1 |
953 |
Improper priors with well defined Bayes Factors |
0 |
0 |
0 |
20 |
0 |
0 |
0 |
93 |
Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo |
0 |
0 |
0 |
56 |
0 |
0 |
0 |
199 |
Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model |
0 |
0 |
1 |
27 |
0 |
0 |
2 |
107 |
Interactions between eurozone and US booms and busts: A Bayesian panel Markov-switching VAR model |
0 |
0 |
0 |
69 |
0 |
0 |
0 |
197 |
Interactions between eurozone and US booms and busts: A Bayesian panel Markov-switching VAR model |
0 |
0 |
2 |
62 |
0 |
0 |
4 |
194 |
Interactions between eurozone and US booms and busts: A Bayesian panel Markov-switching VAR model |
0 |
0 |
1 |
47 |
0 |
0 |
2 |
170 |
Interconnections between Eurozone and US Booms and Busts using a Bayesian Panel Markov-Switching VAR Mode |
1 |
1 |
2 |
96 |
1 |
2 |
4 |
121 |
Jan Tinbergen (1903-1994) |
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0 |
0 |
29 |
0 |
0 |
2 |
132 |
LIKELIHOOD DIAGNOSTICS AND BAYESIAN ANALYSIS OF A MICRO-ECONOMIC DISEQUILIBRIUM MODEL FOR RETAIL SERVICES |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
15 |
Learning to Average Predictively over Good and Bad: Comment on: Using Stacking to Average Bayesian Predictive Distributions |
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0 |
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36 |
0 |
0 |
0 |
33 |
MONTE CARLO ANALYSIS OF SKEW POSTERIOR DISTRIBUTIONS: AN ILLUSTRATIVE ECONOMETRIC EXAMPLE |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
6 |
Model Uncertainty and Bayesian Model Averaging in Vector Autoregressive Processes |
1 |
1 |
1 |
191 |
1 |
1 |
2 |
462 |
Model uncertainty and Bayesian model averaging in vector autoregressive processes |
0 |
0 |
0 |
8 |
0 |
0 |
2 |
52 |
Modelling option prices using neural networks |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
278 |
Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data |
0 |
0 |
0 |
24 |
0 |
0 |
0 |
92 |
Neural network analysis of varying trends in real exchange rates |
1 |
1 |
1 |
20 |
1 |
1 |
2 |
52 |
Neural network approximations to posterior densities: an analytical approach |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
38 |
Neural network based approximations to posterior densities: a class of flexible sampling methods with applications to reduced rank models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
54 |
Neural networks as econometric tool |
1 |
1 |
1 |
47 |
1 |
1 |
2 |
127 |
Neural networks as econometric tool |
0 |
0 |
1 |
206 |
1 |
1 |
6 |
658 |
Note on neural network sampling for Bayesian inference of mixture processes |
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0 |
0 |
3 |
0 |
0 |
0 |
44 |
Oil Price Shocks and Long Run Price and Import Demand Behavior |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
115 |
On Bayesian routes to unit roots |
0 |
0 |
0 |
52 |
0 |
0 |
1 |
280 |
On Bayesian structural inference in a simultaneous equation model |
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0 |
0 |
9 |
0 |
0 |
1 |
48 |
On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling |
0 |
0 |
0 |
139 |
1 |
2 |
3 |
485 |
On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14 |
0 |
0 |
0 |
268 |
0 |
0 |
3 |
461 |
On the Variation of Hedging Decisions in Daily Currency Risk Management |
0 |
0 |
0 |
281 |
0 |
0 |
0 |
938 |
On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks |
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0 |
0 |
21 |
0 |
0 |
1 |
146 |
On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks |
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0 |
0 |
2 |
0 |
0 |
0 |
23 |
On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks |
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0 |
0 |
3 |
0 |
0 |
0 |
52 |
On the variation of hedging decisions in daily currency risk management |
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0 |
0 |
13 |
0 |
0 |
2 |
81 |
POSTERIOR ANALYSIS OF KLEIN'S MODEL |
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0 |
0 |
1 |
0 |
0 |
0 |
11 |
POSTERIOR ANALYSIS OF POSSIBLY INTEGRATED TIME SERIES WITH AN APPLICATION TO REAL GNP |
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0 |
1 |
2 |
0 |
0 |
1 |
13 |
POSTERIOR MOMENTS COMPUTED BY MIXED INTEGRATION |
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0 |
0 |
0 |
0 |
0 |
0 |
5 |
POSTERIOR MOMENTS COMPUTED BY MIXED INTEGRATION |
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0 |
0 |
1 |
0 |
0 |
0 |
13 |
POSTERIOR MOMENTS OF THE KLEIN-GOLDBERGER MODEL |
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0 |
0 |
2 |
0 |
0 |
0 |
9 |
PREDICTIVE MOMENTS OF SIMULTANEOUS ECONOMETRIC MODELS A Bayesian Approach |
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0 |
0 |
0 |
0 |
0 |
0 |
7 |
Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo Matlab Toolbox |
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0 |
0 |
119 |
0 |
0 |
0 |
479 |
Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox |
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0 |
0 |
79 |
0 |
0 |
0 |
177 |
Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox |
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0 |
0 |
34 |
0 |
0 |
0 |
120 |
Parallelization Experience with Four Canonical Econometric Models using ParMitISEM |
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16 |
0 |
0 |
0 |
56 |
Parallelization experience with four canonical econometric models using ParMitISEM |
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0 |
0 |
9 |
0 |
0 |
0 |
50 |
Partially Censored Posterior for Robust and Efficient Risk Evaluation |
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0 |
0 |
20 |
0 |
0 |
0 |
33 |
Partially Censored Posterior for robust and efficient risk evaluation |
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0 |
0 |
2 |
0 |
0 |
0 |
17 |
Possibly Ill-behaved Posteriors in Econometric Models |
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0 |
0 |
45 |
0 |
0 |
0 |
262 |
Posterior-Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models with Non-filtered Data |
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0 |
0 |
37 |
0 |
0 |
1 |
120 |
Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data |
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0 |
0 |
60 |
0 |
0 |
1 |
217 |
Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series |
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0 |
0 |
83 |
0 |
0 |
0 |
255 |
Predictive gains from forecast combinations using time-varying model weights |
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0 |
1 |
29 |
0 |
0 |
1 |
109 |
Quantifying time-varying forecast uncertainty and risk for the real price of oil |
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0 |
0 |
25 |
1 |
1 |
7 |
42 |
Quantifying time-varying forecast uncertainty and risk for the real price of oil |
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0 |
0 |
9 |
1 |
2 |
10 |
38 |
Quantifying time-varying forecast uncertainty and risk for the real price of oil |
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0 |
0 |
11 |
1 |
3 |
3 |
17 |
Return and Risk of Pairs Trading using a Simulation-based Bayesian Procedure for Predicting Stable Ratios of Stock Prices |
0 |
0 |
0 |
40 |
1 |
1 |
2 |
174 |
Robust Optimization of the Equity Momentum Strategy |
0 |
0 |
0 |
106 |
0 |
0 |
0 |
362 |
SOME ADVANCES IN BAYESIAN ESTIMATION METHODS USING MONTE CARLO INTEGRATION |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
Simulation based Bayesian econometric inference: principles and some recent computational advances |
0 |
0 |
0 |
29 |
1 |
1 |
2 |
99 |
Simulation based bayesian econometric inference: principles and some recent computational advances |
0 |
0 |
0 |
18 |
0 |
0 |
1 |
59 |
Some advances in Bayesian estimations methods using Monte Carlo Integration |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
6 |
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 |
0 |
99 |
0 |
0 |
0 |
327 |
Testing for integration using evolving trend and seasonal models: A Bayesian approach |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
97 |
The AdMit Package |
0 |
0 |
0 |
11 |
0 |
0 |
0 |
71 |
The Evolution of Forecast Density Combinations in Economics |
1 |
2 |
3 |
135 |
1 |
3 |
10 |
221 |
The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation |
0 |
0 |
0 |
45 |
0 |
0 |
0 |
199 |
The R package MitISEM: Efficient and robust simulation procedures for Bayesian inference |
0 |
0 |
0 |
28 |
0 |
0 |
0 |
38 |
The R package MitISEM: efficient and robust simulation procedures for Bayesian inference |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
151 |
The R-package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference |
0 |
0 |
0 |
8 |
0 |
1 |
3 |
53 |
The Value of Structural Information in the VAR Model |
0 |
0 |
0 |
77 |
0 |
0 |
0 |
267 |
The Value of Structural Information in the VAR Model |
0 |
0 |
0 |
69 |
0 |
0 |
0 |
307 |
The value of structural information in the VAR model |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
68 |
Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies |
0 |
0 |
0 |
62 |
1 |
1 |
3 |
89 |
Time-varying Combinations of Predictive Densities using Nonlinear Filtering |
0 |
0 |
0 |
79 |
0 |
0 |
3 |
144 |
To Bridge, to Warp or to Wrap? A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods |
1 |
1 |
1 |
52 |
2 |
2 |
2 |
197 |
Trends and cycles in economic time series: A Bayesian approach |
0 |
0 |
4 |
224 |
0 |
0 |
8 |
427 |
Twentieth century shocks, trends and cycles in industrialized nations |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
48 |
Valuing structure, model uncertainty and model averaging in vector autoregressive processes |
0 |
0 |
0 |
19 |
0 |
0 |
0 |
52 |
Weakly informative priors and well behaved Bayes factors |
0 |
0 |
0 |
10 |
0 |
0 |
0 |
81 |
Total Working Papers |
7 |
14 |
50 |
9,720 |
23 |
42 |
249 |
35,327 |