Abstract
Using a logit model and quarterly data from 1962 to 2021, we test the forecasting power of the yield spread, a popular leading indicator, and show that forecasting models that include the entirety of the term structure of interest rates provide more accurate estimates of future economic downturns. We also show that models that only include the yield spread are implicitly imposing restrictions in the coefficients of the model resulting in lower predictive power and omitted variable bias issues.
Highlights
Whether the recession of 2020 was caused by changing macroeconomic conditions or as an unintended consequence of deliberate government action, a popular leading indicator of downturns in economic activity signaled a recession in the U.S economy within its range of influence of 18 months
We show that models that only include the yield spread are implicitly imposing restrictions in the coefficients of the model resulting in lower predictive power and omitted variable bias issues
Three different models were estimated for each forecasting period: a base model where the conditioning set was an indicator variable of an inversion of the curve, M0, a ‘spread’ model that included only the yield spread as defined in Estrella and Hardouvelis (1991), M1, and a model that included the entirety of the term structure of interest rates, M2
Summary
Whether the recession of 2020 was caused by changing macroeconomic conditions or as an unintended consequence of deliberate government action, a popular leading indicator of downturns in economic activity signaled a recession in the U.S economy within its range of influence of 18 months. Forecasting models based on the yield curve, on the other hand, require a more succinct econometric specification, where no a-priori structural form must be derived and calibrated, and seem to remain impervious to structural changes in the economy This is of special importance during times of increased uncertainty in both the short-run and long-run path of fundamental economic variables. We draw from the most salient features of competing yield curve models to produce forecasts for real GDP while delineating a framework for the assessment of the reliability of the proposed model We accomplish this by estimating a statistically adequate logistic regression that uses the spread of the long-run versus the short-run interest rates but rather the entirety of the term structure of interest rates, commonly known as the yield curve.
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