Heterogeneity in speed of adjustment using finite mixture models

C-Tier
Journal: Economic Modeling
Year: 2022
Volume: 107
Issue: C

Authors (4)

Durand, Robert B. (not in RePEc) Greene, William H. (not in RePEc) Harris, Mark N. (Curtin University) Khoo, Joye (not in RePEc)

Score contribution per author:

0.251 = (α=2.01 / 4 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Many empirical analyses of firms' speed of leverage adjustment (SOA) impose a strong constraint: an average SOA is estimated for all firms in a sample. We demonstrate the usefulness of finite mixture models (FMM) in corporate finance by analysing estimates of firms' SOA. Applying FMM to a sample of US firms during 1972–2017, we find five distinct types of firm behaviours, each with its own SOA. Moreover, the same explanatory variables can have quite differing effects across the groups. We also offer the applied researcher a battery of validation techniques that can be used in a FMM context. FMM should be a standard part of finance researchers’ tool-kits.

Technical Details

RePEc Handle
repec:eee:ecmode:v:107:y:2022:i:c:s0264999321003023
Journal Field
General
Author Count
4
Added to Database
2026-01-25