arXiv 7 Jun 2026 · Econometrics
arXiv:2606.08398 · PDF · DOI · OpenAlex · Extracted main text
We show analytically and via simulation that cross-sectional aggregation can substantially attenuate regime-switching signals in time-series data, making regime switches harder to detect. Building on this, we develop regime-switching models and an estimation algorithm which allow for autoregressive dynamics and grouped heterogeneity. We apply the approach to a U.S. macroeconomic dataset of 94 series, covering components of real gross domestic product, industrial production, capacity utilization, employment, and hours worked. The estimates give sharper business cycle classifications than those typically found in the literature. Monte Carlo simulations show that the computation is practical for datasets with a few hundred time series.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Hamilton (1989) A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle | 0.928 | 5 | 4 | 80% |
| 2 | Kim and Nelson (1998) Business Cycle Turning Points, a New Coincident Index, and Tests of Duration Dependence Based on a Dynamic Factor Model with Reg… | 0.874 | 5 | 2 | 100% |
| 3 | Kim and Nelson (1999) State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications | 0.737 | 5 | 2 | 60% |
| 4 | Chauvet and Hamilton (2006) Dating Business Cycle Turning Points | 0.511 | 2 | 1 | 100% |
| 5 | Ang and Bekaert (2002) International Asset Allocation With Regime Shifts | 0.405 | 1 | 1 | 100% |
| 6 | Ang and Bekaert (2002) Regime Switches in Interest Rates | 0.405 | 1 | 1 | 100% |
| 7 | Ang and Timmermann (2012) Regime Changes and Financial Markets | 0.405 | 1 | 1 | 100% |
| 8 | Barigozzi and Massacci (2025) Modelling Large Dimensional Datasets with Markov Switching Factor Models | 0.405 | 1 | 1 | 100% |
| 9 | Botev (2017) The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting | 0.405 | 1 | 1 | 100% |
| 10 | Chauvet, Juhn, and Potter (2002) Markov switching in disaggregate unemployment rates | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 32 scored citations.