Can Professional Forecasters Predict Uncertain Times?
Economic surveys are very popular these days and for a good reason. They tell us how the folks being surveyed—professional forecasters, households, firm managers—feel about the economy. So, for instance, the New York Fed’s Survey of Consumer Expectations (SCE) website displays an inflation uncertainty measure that tells us households are more uncertain about inflation than they were pre-COVID, but a bit less than they were a few months ago. The Philadelphia Fed’s Survey of Professional Forecasters (SPF) tells us that forecasters believed last May that there was a lower risk of negative 2024 real GDP growth than there was last February. The question addressed in this post is: Does this information actually have any predictive content? Specifically, I will focus on the SPF and ask: When professional forecasters indicate that their uncertainty about future output or inflation is higher, does that mean that output or inflation is actually becoming more uncertain, in the sense that the SPF will have a harder time predicting these variables?
Are Professional Forecasters Overconfident?
The post-COVID years have not been kind to professional forecasters, whether from the private sector or policy institutions: their forecast errors for both output growth and inflation have increased dramatically relative to pre-COVID (see Figure 1 in this paper). In this two-post series we ask: First, are forecasters aware of their own fallibility? That is, when they provide measures of the uncertainty around their forecasts, are such measures on average in line with the size of the prediction errors they make? Second, can forecasters predict uncertain times? That is, does their own assessment of uncertainty change on par with changes in their forecasting ability? As we will see, the answer to both questions sheds light of whether forecasters are rational. And the answer to both questions is “no” for horizons longer than one year but is perhaps surprisingly “yes” for shorter-run forecasts.
On the Distributional Consequences of Responding Aggressively to Inflation
This post discusses the distributional consequences of an aggressive policy response to inflation using a Heterogeneous Agent New Keynesian (HANK) model. We find that, when facing demand shocks, stabilizing inflation and real activity go hand in hand, with very large benefits for households at the bottom of the wealth distribution. The converse is true however when facing supply shocks: stabilizing inflation makes real outcomes more volatile, especially for poorer households. We conclude that distributional considerations make it much more important for policy to take into account the tradeoffs between stabilizing inflation and economic activity. This is because the optimal policy response depends very strongly on whether these tradeoffs are present (that is, when the economy is facing supply shocks) or absent (when the economy is facing demand shocks).
The Post‑Pandemic r*
The debate about the natural rate of interest, or r*, sometimes overlooks the point that there is an entire term structure of r* measures, with short-run estimates capturing current economic conditions and long-run estimates capturing more secular factors. The whole term structure of r* matters for policy: shorter run measures are relevant for gauging how restrictive or expansionary current policy is, while longer run measures are relevant when assessing terminal rates. This two-post series covers the evolution of both in the aftermath of the pandemic, with today’s post focusing especially on long-run measures and tomorrow’s post on short-run r*.
The New York Fed DSGE Model Forecast— June 2023
This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since March 2023.
Measuring the Financial Stability Real Interest Rate, r**
Comparing our financial stability real interest rate, r** (“r-double-star”) with the prevailing real interest rate gives a measure of how vulnerable the economy is to financial instability. In this post, we first explain how r** can be measured, and then discuss its evolution over the last fifty years and how to interpret the recent banking turmoil within this framework.
Financial Stability and Interest Rates
In a recent research paper we argue that interest rates have very different consequences for current versus future financial stability. In the short run, lower real rates mean higher asset prices and hence higher net worth for financial institutions. In the long run, lower real rates lead intermediaries to shift their portfolios toward risky assets, making them more vulnerable over time. In this post, we use a model to highlight the challenging trade-offs faced by policymakers in setting interest rates.
Financial Vulnerability and Macroeconomic Fragility
What is the effect of a hike in interest rates on the economy? Building on recent research, we argue in this post that the answer to this question very much depends on how vulnerable the financial system is. We measure financial vulnerability using a novel concept—the financial stability interest rate r** (or “r-double-star”)—and show that, empirically, the economy is more sensitive to shocks when the gap between r** and current real rates is small or negative.
The New York Fed DSGE Model Forecast—March 2023
This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since December 2022. Note that this forecast was produced on February 27, and hence should be viewed as reflecting the state of the economy before the current banking sector turmoil.
Is the Green Transition Inflationary?
Are policies aimed at fighting climate change inflationary? In a new staff report we use a simple model to argue that this does not have to be the case. The model suggests that climate policies do not force a central bank to tolerate higher inflation but may generate a trade-off between inflation and employment objectives. The presence and size of this trade-off depends on how flexible prices are in the “dirty” and “green” sectors relative to the rest of the economy, and on whether climate policies consist of taxes or subsidies.