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Estimating the Missing Intercept

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Abstract

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).

Suggested Citation

  • Christian Matthes & Naoya Nagasaka & Felipe Schwartzman, 2025. "Estimating the Missing Intercept," Working Paper 25-12, Federal Reserve Bank of Richmond.
    • Handle: RePEc:fip:fedrwp:102112
    DOI: 10.21144/wp25-12
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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • H50 - Public Economics - - National Government Expenditures and Related Policies - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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