House Prices, Debt Burdens, and the Heterogeneous Effects of Mortgage Rate Shocks

Gary Cornwall and Marina Gindelsky

No 2024-003, Working Papers from The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting

Abstract: Inequality statistics are usually calculated from high-quality, comprehensive survey or administrative microdata. Naturally, this data is typically available with a lag of at least 9 months from the reference period. In turbulent times, there is interest in knowing the distributional impacts of observable aggregate business cycle and policy changes sooner. In this paper, we use an elastic net, a generalized model that incorporates lasso and ridge regressions as special cases, to nowcast the overall Gini coefficient and quintile level income shares. National accounts data, published by the Bureau of Economic Analysis, are used (starting in 2000) as features instead of the underlying microdata to produce a series of distributional nowcasts for 2020–2022. These nowcasts predict turning points with at least 85 percent accuracy across all metrics and minimal errors relative to na¨ıve models. We find we could plausibly create advance inequality estimates approximately one month after the end of the calendar year, reducing the present lag by almost a year.

Keywords: inequality; income distribution; national accounts; nowcasting; machine learning (search for similar items in EconPapers)
JEL-codes: C52 C53 D31 E01 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2024-09
New Economics Papers: this item is included in nep-big, nep-ipr and nep-ure
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