| Registro completo |
| Provedor de dados: |
31
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| País: |
United States
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| Título: |
The information theoretic foundations of a probabilistic and predictive micro and macro economics
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| Autores: |
Judge, George G.
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| Data: |
2012-04-20
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| Ano: |
2012
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| Palavras-chave: |
Information theoretic methods
State space models
First order Markov processes
Inverse problems
Dynamic economic systems
Research Methods/ Statistical Methods
C40
C51
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| Resumo: |
Despite the productive efforts of economists, the disequilibrium nature of the economic system and imprecise predictions persist. One reason for this outcome is that traditional econometric models and estimation and inference methods cannot provide the necessary quantitative information for the causal influence-dynamic micro and macro questions we need to ask given the noisy indirect effects data we use. To move economics in the direction of a probabilistic and causal based predictive science, in this paper information theoretic estimation and inference methods are suggested as a basis for understanding and making predictions about dynamic micro and macro economic processes and systems.
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| Tipo: |
Working Paper
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| Idioma: |
Inglês
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| Identificador: |
http://purl.umn.edu/122890
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| Relação: |
University of California, Berkeley>Department of Agricultural and Resource Economics>CUDARE Working Papers
CUDARE Working Papers
1123
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| Formato: |
22
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