Testing investment forecast efficiency with textual data
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DOI: 10.18452/21651
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References listed on IDEAS
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Cited by:
- Alexander Foltas & Christian Pierdzioch, 2022.
"Business-cycle reports and the efficiency of macroeconomic forecasts for Germany,"
Applied Economics Letters, Taylor & Francis Journals, vol. 29(10), pages 867-872, June.
- Foltas, Alexander & Pierdzioch, Christian, 2020. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Working Papers 22, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
- Foltas, Alexander & Pierdzioch, Christian, 2020. "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers 21, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
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More about this item
Keywords
Forecast Efficiency; Investment; Random Forest; Topic Modeling;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
- E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2020-09-21 (Big Data)
- NEP-CMP-2020-09-21 (Computational Economics)
- NEP-MAC-2020-09-21 (Macroeconomics)
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