Today we are pleased to present a guest contribution written by Filippo Natoli Other Fabrizio Venditti of the Directorate General for the Economy, Statistics and Research of the Bank of Italy. The views presented in this note represent those of the author and do not necessarily reflect those of the Bank of Italy.
A negative reading for the early estimate of US GDP growth in the second quarter surprised private forecasters, contributing to recession talks. Using a standard forecast model, we show that, taking into account high CPI inflation and tight labor markets, an impending recession seemed to be extremely likely even a month ago, both in the US and the UK.
The second quarter of 2022 saw a sharp deterioration in the momentum of the global business cycle as global trade remains stifled by persistent supply bottlenecks, commodity prices are strengthened by the war in Ukraine and high inflation continues to erode consumer purchasing power. Meanwhile, financial conditions have tightened considerably as central banks reacted aggressively to stubborn inflationary pressures. Against this backdrop, the US economy recorded a second consecutive negative GDP footprint, following the decline in economic activity in the first quarter. Equally worrying are the prospects for other advanced economies, especially energy importers, whose terms of trade have rapidly deteriorated following the invasion of Ukraine. Meteorologists have taken these headwinds into account and scaled back their expectations for global growth in 2022 and 2023 (see, for example, IMF) and the question seems to be when rather than Self a recession is about to occur: the search for the word “recession” on Google has flared up since last March (Figure 1).
Figure 1: Google search intensity for the word “recession”
(number of hits classified between 0 and 100 in the considered period). Source: Google Trends
In recent works (Natoli and Venditti, 2022), We contribute to this debate by jointly assessing the relevance of financial and macroeconomic factors in anticipating recessions in the United States and the United Kingdom since the late 1990s. In our analysis we rely on the standard probit forecasting framework introduced by Estrella and Hardouvelis (1991),
where the dependent variable is a dummy equal to one (zero) if the economy is (is not) in recession at a time t + h, H. is the forecast horizon, x is the set of regressors, F (.) is the normal standard cumulative distribution function and is a normally distributed error.
The standard specification in the literature, which we take as a reference, considers the slope of the government bond yield curve – the difference between 10-year and 3-month yields – as a unique predictor. The ability of this minimalist model to predict recessions, however, has recently been questioned in the literature (Karnizova and Li, 2014; Ercolani and Natoli, 2020; Kiley, 2022, among others). We then start by adding market stress indicators – financial conditions and stock market volatility – to the baseline specification, according to the view that the slope of the yield curve alone may not be able to fully capture the deterioration in funding conditions that lead to a crisis. A Financial Condition Index (FCI) is constructed as an unweighted average of 10-year returns, monthly equity returns and corporate bond yield spreads, in the spirit of Arrigoni et al. (2022), while stock market volatility is captured by the VIX. In a third specification we also add two variables that summarize the macroeconomic environment: CPI inflation and the unemployment rate. Figure 2 shows the coefficient estimates for the United States over different forecast horizons (1 to 12). They confirm that financial indicators and macroeconomic conditions provide additional forecasting power. In particular, they show that periods of (i) flat yield curves are likely to have followed (ii) strained financial conditions (iii) high financial market uncertainty (iv) high inflation and (v) low unemployment (which largely resembles current economic environment) from a recession. Estimates for the UK are very similar.
Figure 2: Average marginal effects, US model
When specifications based on the slope of the yield curve are enriched with key financial and macroeconomic indicators, forecast performance improves significantly and, in the current environment, the probability of an impending recession jumps to values very close to 1. Figure 3 shows the time series of the predicted recession probability (6 months ahead) of the model based only on the slope of the yield curve (blue lines), the intermediate specification including VIX and FCI (green line) and the full model which also introduces inflation and unemployment (red line). According to standard fit measurements, the latter model performs best. All models are estimated with data ranging from January 1998 to May 2022, which is already available around mid-June. It turns out that, historically, financial conditions have played a more important role than inflation and unemployment in predicting the recessions of the early 2000s; Furthermore, they were very tight before the pandemic shock that eventually overtook the global economy in 2020. In the case of the Great Recession of 2008, both financial and real factors played a role. At the moment, however, the strongest signs of recession come from record inflation and rigid labor markets, in line with what was found in Domash and Summers (2022). An interesting observation is that the sample period includes years of anchored inflation expectations and credible monetary policy: our results indicate that, even in such an environment, an aggressive monetary response – aggressive enough to generate a recession – would be needed to tame inflation. All in all, our results indicate that, in the current juncture, a soft landing – engineered disinflation without causing a recession – is very unlikely. The actual combination of hot labor markets, high inflation and difficult financial conditions has generally been followed by a recession.
Figure 3: Probability of recession six months ahead, time series
Note: Economy-specific recession bands are based on OECD recession indicators
Source: Natoli, F. and Venditti F. (2022). The role of financial and macroeconomic conditions in forecasting the recession (29 July 2022). Available on SSRN: https://ssrn.com/abstract=4176581
This post written by Filippo Natoli Other Fabrizio Venditti.