Information of employee decisions and stock returns in the Korean stock market

• Published date: 01 March 2023
• Author: Jaewan Bae,Jangkoo Kang
• Date: 01 March 2023
• DOI: http://doi.org/10.1111/irfi.12394

ORIGINAL ARTICLE

Information of employee decisions and stock

returns in the Korean stock market

Jaewan Bae | Jangkoo Kang

College of Business, Korea Advanced Institute

of Science and Technology (KAIST), Seoul,

Republic of Korea

Correspondence

Jaewan Bae, College of Business, Korea

Advanced Institute of Science and Technology

(KAIST), 85 Hoegiro, Dongdaemun-Gu, Seoul

02455, Republic of Korea.

Email: jwbaem@kaist.ac.kr

Abstract

We study the role of rank-and-file employees on asset

prices in the Korean stock market using monthly labor flow

data from the national pension subscription descriptions.

We find that firms experiencing high net labor outflows

have lower future risk-adjusted returns. This return predict-

ability is found to originate mainly from gross labor out-

flows. We further show that the workers' labor market

decisions better reflect information on the firms' fundamen-

tals when firm sales are greater related to wages or when

workers can more easily transfer to better jobs. Finally, we

confirm the workers' ability to predict firm performance.

KEYWORDS

labor flows, labor market, rank-and-file employees, stock returns

JEL CLASSIFICATION

G00, G12, G14, G40, J00

1|INTRODUCTION

Labor has become one of the most important factors in production involving higher-level technology and specialized

knowledge. However, despite the rapidly growing importance of labor, relatively few studies in the finance literature

have examined the effect of labor on firm values primarily because of the empirical challenge of obtaining granular

data on employment dynamics or characteristics at the firm level. Most of the employment-related data based on

regular financial reports are annual and only report the total number of employees. Thus, identifying the number of

exits or joins at the exact period (month) becomes difficult.

A prominent work by Agrawal et al. (2021) overcomes the data issue by utilizing the vast raw data on LinkedIn,

one of the world's largest online professional networks. Their study tracks the CVs of individual users of the platform

and identifies the start and end dates of job spells to construct a sample of monthly labor flows at Russell 1000 firms.

Received: 22 January 2022 Revised: 20 June 2022 Accepted: 15 September 2022

DOI: 10.1111/irfi.12394

© 2022 International Review of Finance Ltd.

206 International Review of Finance. 2023;23:206–224.

wileyonlinelibrary.com/journal/irfi

Using the data, they could test whether the workers' labor market decisions have return predictability. They show

that firms where more workers exit and fewer workers join have low risk-adjusted returns in the near future. This

interesting empirical result reveals the critical role of rank-and-file employees in the asset pricing context. However,

their dataset has two limitations: a selection bias problem and errors in the self-reported information system of

LinkedIn. Our study complements their empirical analysis with a novel dataset.

We examine a similar empirical link between labor flows and stock returns at the firm level in the Korean stock

market, extending the study of Agrawal et al. (2021) for the US stock market but utilizing a different dataset. We col-

lect monthly firm-level labor flow data from the national pension subscription descriptions offered by the National

Pension Service of Korea. National pension data include firm names, the total number of subscribers on the national

pension, new subscribers, and terminated subscribers. As almost all employees working at Korean firms automatically

join the national pension, the number of new and terminated subscriptions effectively captures gross labor inflows

and outflows, respectively. Our labor flow data do not suffer from a selection bias problem or self-reported informa-

tion problems. In this aspect, we provide more reliable empirical analyses. Furthermore, the labor flow data are pub-

licly available, easy to access, and monthly updated, meaning that investment strategies based on the labor flows are

highly feasible. Thus, practitioners can also find benefits from our empirical analyses.

In this study, we first develop the main hypothesis that net labor outflows (defined as gross outflows minus

gross inflows) are negatively related to future stock returns, following Agrawal et al. (2021). Workers always compare

the present value of expected future wage streams from the current firm and outside firms, and they opt to quit

(stay) if the current option is less (more) attractive to the outside option. When a firm's workers detect good or bad

signals on the firm's fundamentals, they incorporate these signals into their expectation of the present value of the

future wage streams from their current firm. Thus, firms expected to underperform experience higher gross labor

outflows and lower gross labor inflows. This implies that aggregation of the labor flows (net labor outflows) contains

negative information on firms' fundamentals. If investors do not incorporate this information into valuations because

of a behavioral bias, then higher net labor outflows can predict a lower stock return.

We then explore the role of wage in the negative return predictability of net labor outflows, which is not studied

by Agrawal et al. (2021) (maybe due to data limitation). If the wage is more related to a firm's performance, workers'

exit or join decisions would be more strongly associated with the firms' future performance. As a result, the negative

link between net labor outflows and future stock returns would be stronger among firms whose wages are more sen-

sitive to firm productivity, which is our second hypothesis.

We conduct several empirical analyses for investigating the two hypotheses using firm-level labor flow data

based on national pension subscriptions. Our findings are summarized as follows. Firstly, we confirm a significant

negative relationship between net labor outflows and risk-adjusted stock returns in the Korean stock market, consis-

tent with the first hypothesis. When forming quintile portfolios based on the net labor outflows, the lowest-minus-

highest quintile portfolio generates a risk-adjusted return of 0.38% (t=2.19) and 0.84% (t=2.27) for the equal- and

value-weighted cases, respectively. Compared to the US case of Agrawal et al. (2021) showing that the counterpart

portfolio generates a risk-adjusted return of 0.25%–0.42% (depending on specifications), the value-weighted result

in the Korean stock market reveals stronger return predictability of the net labor outflows. Our analysis also shows

that the negative relationship mainly stems from gross labor outflows rather than inflows. Second, we find that the

negative link between net labor outflows and stock returns is stronger among firms with sales more related to wages,

consistent with the second hypothesis. Third, the return predictability of net labor outflows is more prominent when

workers have better outside options. Fourth, we show that higher net labor outflows are negatively associated with

firm performance (profitability). This could demonstrate workers' ability to predict the firms' fundamentals.

This study contributes to the literature as follows. Firstly, our study reveals the critical role of rank-and-file

employees, which is barely examined, in the Korean stock market. Our work is the first attempt to verify the negative

return predictability of labor flows outside the U.S. stock market studied by Agrawal et al. (2021), and provides

strong evidence reinforcing the persuasive power of their argument regarding the informativeness of labor flows.

Furthermore, our dataset based on national pension subscriptions does not suffer from self-selection or accuracy

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