Paper uses machine learning to nowcast GDP in Lebanon
Analysis is a ‘distinct challenge’ in the country on account of data lags
A working paper published by the International Monetary Fund explores the potential for two machine learning techniques to help assess economic conditions in Lebanon, where it says analysis is a "distinct challenge".
Andrew Tiffin notes GDP data in Lebanon are compiled on an annual basis with a publication lag of between one and two years. "So to gauge the true state of the economy in 2015, policy makers may have to wait until 2017," he notes, in Seeing in the dark: a machine-learning approach
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@centralbanking.com or view our subscription options here: http://subscriptions.centralbanking.com/subscribe
You are currently unable to print this content. Please contact info@centralbanking.com to find out more.
You are currently unable to copy this content. Please contact info@centralbanking.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@centralbanking.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@centralbanking.com
More on Economic modelling
SNB researchers develop ‘more precise’ LLM-based risk predictor
New model allows for “more nuanced understanding” of types of uncertainty, researchers say
The Netherlands Bank overhauls nowcasting model
Economic dynamics have become more complicated since the pandemic, economists say
Machine learning can improve inflation forecasts – IMF paper
Model for Japan is “easily interpretable” and overcomes some drawbacks of standard models
NBER paper seeks ‘canonical Hank model’
Early attempts at heterogeneous agent modelling led to implausible results, authors say
North Macedonia develops new DSGE model
Analytical tool to supplement existing models built in conjunction with CNB and IMF
‘Beveridge threshold’ can explain US soft landing – study
Gauti Eggertson tells Jackson Hole attendees why many economists were too gloomy about growth
‘State-dependent’ model sheds light on inflation surge
Bank of Spain’s Galo Nuño says changing key pricing assumption helps explain “immaculate disinflation”
Central Bank of Kenya upgrades nowcasting platform
Package of forecasting reforms is part of ongoing policy “modernisation”