The Experts below are selected from a list of 75777 Experts worldwide ranked by ideXlab platform
Vincent Labhard - One of the best experts on this subject based on the ideXlab platform.
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a state space approach to extracting the signal from uncertain Data
Journal of Business & Economic Statistics, 2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain—they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions is first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
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a state space approach to extracting the signal from uncertain Data
2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain - they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions are first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
Alastair Cunningham - One of the best experts on this subject based on the ideXlab platform.
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a state space approach to extracting the signal from uncertain Data
Journal of Business & Economic Statistics, 2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain—they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions is first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
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a state space approach to extracting the signal from uncertain Data
2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain - they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions are first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
Jana Eklund - One of the best experts on this subject based on the ideXlab platform.
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a state space approach to extracting the signal from uncertain Data
Journal of Business & Economic Statistics, 2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain—they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions is first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
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a state space approach to extracting the signal from uncertain Data
2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain - they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions are first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
Christopher Jeffery - One of the best experts on this subject based on the ideXlab platform.
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a state space approach to extracting the signal from uncertain Data
Journal of Business & Economic Statistics, 2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain—they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions is first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
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a state space approach to extracting the signal from uncertain Data
2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain - they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions are first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
George Kapetanios - One of the best experts on this subject based on the ideXlab platform.
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a state space approach to extracting the signal from uncertain Data
Journal of Business & Economic Statistics, 2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain—they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions is first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
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a state space approach to extracting the signal from uncertain Data
2009Co-Authors: Alastair Cunningham, Jana Eklund, Christopher Jeffery, George Kapetanios, Vincent LabhardAbstract:Most Macroeconomic Data are uncertain - they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain Data. It describes a two-step estimation procedure in which the history of past revisions are first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the Macroeconomic variable.
