Nber recession dating
The NBER also give a lot of attention to the two broadest measures of the economy, Gross Domestic product (GDP) and Gross Domestic Income (GDI) which are however published quarterly.We provide a separate analysis “GDPI Report” that examines these two components in detail as described in our research note “Estimating Recession Probabilities from GDP/GDI.” The aim of this research note is to apply traditional recession forecasting and probability modelling techniques to the 4 co-incident monthly indicators examined by NBER so that we can “see what the NBER are seeing.” Bear in mind, the 4 components are co-incident and thus the recession model we build is likely to be at least 1-month lagging in its determinations.When the index falls below zero (more than 2 systems are below their syndrome triggers) we call recession.The syndrome triggers were obtained from an optimization program to find the values that maximize the Area Under Curve (AUC or ROC) of the resulting recession dating model.A shorter period results in too many false positives. Syndrome Diffusion Index We have also found 4 thresholds below which each co-incident indicators’ growth shown above must respectively fall to contribute to a recession “syndrome.” They are as follows: When each indicator falls below its syndrome trigger, it means nothing on its own and merely counts a vote toward the Syndrome Index.We then take 2 and subtract the number of votes to get a Recession Syndrome Diffusion Index recession dating model.We make several remarkable discoveries from the tests.
Real Retail Sales In this instance we have found the 12-month % change (not smoothed) growth rate to work the best for signalling recession.
Rather, a recession is a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial production, and wholesale-retail sales.
They will be examining 4 monthly co-incident indicators: Less weight is given by the NBER for items 1 and 4 as they are sectoral measurements for manufacturing and retail as opposed to broad measures of the economy.
We then re-do the exercise but including data up to just before the 3rd recession.
We repeat again including data to the 4th recession, 5th recession and so on until we have of the weighted composite.
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Basically we simulate what kind of models (vintages) a Recession ALERT researcher would have built through time until present day, with a view to seeing just how varied the results would have been and how well the models performed into the future.