What Drives Firms' Hiring Decisions? An Asset Pricing Perspective

55 Pages Posted: 30 Apr 2020 Last revised: 6 May 2022

See all articles by Frederico Belo

Frederico Belo

INSEAD; Centre for Economic Policy Research (CEPR)

Andres Donangelo

no affiliation

Xiaoji Lin

University of Minnesota

Ding Luo

City University of Hong Kong

Date Written: May 6, 2022

Abstract

In a neoclassical dynamic model of the firm with labor market frictions, optimal hiring is a forward-looking decision that depends on both discount rates and expected cash flows. Empirically, we show that: a) the aggregate hiring rate of publicly traded firms in the U.S. economy negatively predicts stock market excess returns and long-term cash flows both in-sample and out-of-sample, and positively predicts short-term cash flows; and b) through a variance decomposition, the time series variation in the aggregate hiring rate is mainly driven by changes in discount rates and short-term expected cash flows, each contributing to about 40% and 60% of the variation, respectively, with no contribution from variation in long-term expected cash flows. Through structural estimation of the model, we show that labor adjustment costs and time-varying risk are essential for the model to replicate the empirical patterns.

Keywords: Labor Hiring, Stock Returns, Dividend Growth, Simulated Method of Moments, Labor Adjustment Costs

JEL Classification: G12, E44

Suggested Citation

Belo, Frederico and Donangelo, Andres and Lin, Xiaoji and Luo, Ding, What Drives Firms' Hiring Decisions? An Asset Pricing Perspective (May 6, 2022). Available at SSRN: https://ssrn.com/abstract=3569679 or http://dx.doi.org/10.2139/ssrn.3569679

Frederico Belo (Contact Author)

INSEAD ( email )

Boulevard de Constance
77305 Fontainebleau Cedex
France

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Andres Donangelo

no affiliation ( email )

Xiaoji Lin

University of Minnesota ( email )

420 Delaware St. SE
Minneapolis, MN 55455
United States

Ding Luo

City University of Hong Kong ( email )

83 Tat Chee Avenue
Kowloon
Hong Kong

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