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On Friday, February 25, Yuriy Gorodnichenko will join Markus’ Academy for a lecture on Inflation Expectations. Gorodnichenko is the inaugural Quantedge Presidential Chair in Economics at UC Berkeley.

Watch the full presentation below. You can also watch all Markus’ Academy webinars on the Markus’ Academy YouTube channel.


[0:00] Introductory remarks

[8:30] Role of inflation expectations over time

[16:34] How do we measure inflation expectations?

[29:55] Predicted economic activity

[39:41] Forces driving inflation expectations

[45:41] Much of the country remains poorly informed

[1:07:53] Lessons for economists and policy implications

Executive Summary

  • [0:00] Introductory remarks: Inflation expectations are anchored if households, firms, bond traders believe that inflation returns to its target. Anchored inflation allowing the central bank to smooth out shocks, and resilience to bounce back; overstretching it will lead to the anchor breaking, and a need to rebuild trust. The inflation anchor is a focal point and coordinates also higher order beliefs, i.e. beliefs about others’ beliefs. In a New Keynesian perspective, price adjustments are staggered due to strategic complementarities.
  • [8:30] Role of inflation expectations over time: Inflation and inflation expectations are very high by historical standards, but does this mean a repeat of the 1970s? Leaders including Bernanke, Yellen, and Powell have all highlighted the importance of inflation expectations, but the way in which we calculate expectations has changed. In the ‘70s, we assumed that peoples’ expectations were non-rational and backward looking, and when that failed, we assumed that people made full-information rational expectations (FIRE), which also was not a perfect model; it seems to work in the long run, but not the short or medium term as much.
  • [16:34] How do we measure inflation expectations? One year inflation expectations of households, firms, and professional forecasters differ tremendously. The professional forecasters typically estimate around 2%, while households estimate around 5-6%; firms have oscillated from acting like households to acting like forecasters, back to households again.
  • [29:55] Predicted economic activity: the perception of firms throughout the Covid crisis was that expected inflation and GDP growth was positively correlated. However, among households, the opposite was true: as expected inflation increased, GDP growth decreased. This suggests a serious stagflationary fear in U.S. households, as the data shows they are highly sensitive to salient prices, and pay little attention to monetary and fiscal policy– overall, different from the FIRE model.
  • [39:41] Forces driving inflation expectations: Hard to say exactly, but the correlation of inflation expectations with gasoline prices suggests that people use gas prices too much to calculate their inflation beliefs. Gas prices make up about 5% of a consumption basket in the U.S., but consumers believe that it makes up 25% of the shifts in inflation. In other countries, exchange rates or certain other goods are often used by households to calculate inflation. Perhaps as a shift to renewable energy occurs, gasoline prices will play less of a major role in the U.S.
  • [45:41] Much of the country remains poorly informed: Most CEOs (firms) and households do not have a good understanding of the perceived inflation target of the Fed. This means that people generally do not understand the Flexible Average Inflation Targeting framework, and it did not affect consumer’s expectations. By running experiments on how people react to information about inflation targets, inflation forecasts, forward guidance, and fiscal policy; data shows that increased inflation expectations stimulates spendings on nondurables. This is not consistent with FIRE, because all information is already available. However, this leads to a decrease in spending on durables, which does not make as much sense.
  • [1:07:53] Lessons for economists and policy implications: FIRE overall useful, though deviations in survey data; alternatives allow some degree of rationality. Monetary policy needs to be focused, and recognize potential for misinformation and heterogeneity in beliefs. Monetary policy needs to be simple, provide a holistic perspective, focus on targets, and have sustained information campaigns.