Estimating the Missing Intercept

Cross-sectional data have proven to be increasingly useful for macroeconomic research. However, their use often leads to the 'missing intercept' problem in which aggregate general equilibrium effects and policy responses are absorbed into fixed effects. We present a statistical approach to jointly estimate aggregate and idiosyncratic effects within a panel framework, leveraging identification strategies coming from both cross-sectional or time-series settings. We then apply our methodology to study government spending multipliers (Nakamura and Steinsson, 2014) and wealth effects from stock returns (Chodorow-Reich et al., 2021).