The Unassuming Economist

From a new Econbrowser post by James Hamilton:

“Why does a low or negative spread predict future economic weakness? One factor may be the Fed’s tightening cycle. Historically the inflation rate would at times start climbing above where the Fed wanted it. The Fed responded by raising the short-term rate, the traditional instrument of monetary policy. The market response of long-term rates to the higher short rates was significantly more muted. The result is that the yield spread narrowed as the tightening cycle continued. The Fed often found itself behind the curve, and the last short-term rate hikes were likely a contributing factor to some historical economic recessions.

But we’re still very early in the current tightening cycle. The 3-month Treasury bill has not gone up so far by nearly as much as it did in previous complete cycles, and inflation is still very moderate. So I don’t think it’s time to run for cover just yet. However, if the Fed were to raise the short rate by another 100 basis points without any move up in long rates, we would be into inverted territory, and I would be very concerned. Not a danger sign yet, but definitely an indicator to keep watching.”

A new paper finds that “Gross domestic income and gross domestic product—GDI and GDP—measure aggregate economic activity using income and expenditure data, respectively. Discrepancies between the initial estimates of quarterly growth rates for these two measures appear to have some predictive power for subsequent GDP revisions. However, this power has weakened considerably since 2011. Similarly, the first revision to GDP growth has less predictive power in forecasting subsequent revisions since 2011. One possible explanation is that evolving data collection and estimation methods have helped improve initial GDP and GDI estimates.”

David Mihalyi and Tommy Morrison at NRGI created a World Economic Outlook Forecast Tracker that enables users to see how IMF economic projections have evolved over time. On it, you can select from an expansive list of countries and country groupings to track how IMF forecasts evolved year-to-year for dozens of economic indicators, such as GDP growth, government revenues and the budget deficit as well as the price of various commodities. The app shows an animated plot of the forecasts and historical values over 10 years, as well as providing a data download and a plot download (example attached).

From a new post by Julia A. Seymour :

“New York Times economist Paul Krugman immediately reacted to the 2016 election of Donald Trump by warning of a possible “global recession.” Perhaps Yahoo! was taking pointers for its latest series. Even though the economy has been doing well, Yahoo! Finance just launched “Your Next-Recession Survival Guide” warning it is “time to prepare for the economic downturn, which could occur as early as 2020.” The new series began June 20.

[…]

In general, forecasting is unreliable. Financial Times wrote in 2014 that an analysis of all 1990s economic forecasts concluded there was great similarity between them and “the predictive record of economists was terrible.” Prakash Loungani, the author of the study, said “The record of failure to predict recessions is virtually unblemished.” ”

My paper is available here.

From a new article from the The Economist:

“The Economist has built a statistical model to identify what makes a country good at football. Our aim is not to predict the winner in Russia, which can be done best by looking at a team’s recent results or the calibre of its squad. Instead we want to discover the underlying sporting and economic factors that determine a country’s footballing potential—and to work out why some countries exceed expectations or improve rapidly. We take the results of all international games since 1990 and see which variables are correlated with the goal difference between teams.” “Our model explains 40% of the variance in average goal difference for these teams.”