3 citations · 5 across the 3 of their papers we have counts for
3 papers
stat.ML2022★ 3 cited
Benchmarking Econometric and Machine Learning Methodologies in Nowcasting
Daniel Hopp
Nowcasting can play a key role in giving policymakers timelier insight to data published with a significant time lag, such as final GDP figures. Currently, there are a plethora of…
stat.ML2022
Performance of long short-term memory artificial neural networks in nowcasting during the COVID-19 crisis
Daniel Hopp
The COVID-19 pandemic has demonstrated the increasing need of policymakers for timely estimates of macroeconomic variables. A prior UNCTAD research paper examined the suitability o…
econ.EM2021★ 2 cited
Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)
Daniel Hopp
Artificial neural networks (ANNs) have been the catalyst to numerous advances in a variety of fields and disciplines in recent years. Their impact on economics, however, has been c…