Hikaru Saijo

We develop theoretical and methodological framework to apply diagnostic expectations to a large class of recursive macro models, with a focus on implications of memory recall based on distant past.

We propose a new propagation mechanism based on firm-level confidence dynamics that challenges and improves upon standard New Keynesian frictions.

The interaction of ambiguity aversion and limited capital market participation magnifies the impact of fiscal uncertainty shocks on economic activity because concerns about redistribution have first-order effects.

Contrary to the aggregate evidence, labor supply responses to technology shocks at the household level indicate that the data is inconsistent with the sticky price view of the business cycle.

A dynamic general equilibrium model where agents learn about macro fundamentals through investment. The endogenously countercyclical uncertainty amplifies output fluctuations by 16%.

The common practice of estimating dynamic stochastic general equilibrium (DSGE) models using seasonally adjusted data leads to sizeable distortions in estimated parameters.

The increase in markups due to cartelization can explain a substantial fraction of Japan's weak recovery from the Great Depression.

Introducing Smooth Diagnostic Expectations (Smooth DE), featuring an intrinsic connection between uncertainty and overreaction. We provide novel survey evidence that supports the key prediction of Smooth DE: forecasts overreact more when uncertainty is high. We show Smooth DE explains additional stylized facts on surveys, and key features of business cycles.

I show that sector-specific volatility shocks propagate through input–output linkages, triggering a network precautionary pricing multiplier that amplifies their impact on the entire economy.