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24-09-2024 | Original Research

Growing pains: geographic expansion and labor investment efficiency

Authors: Anh-Tuan Le, Henry Hongren Huang, Tzu-Chang Forrest Cheng

Published in: Review of Quantitative Finance and Accounting

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Abstract

This research examines the impact of geographic dispersion on firm-level labor investment efficiency. We find that geographically-dispersed firms exhibit lower labor investment efficiency, and that the negative association between geographic dispersion and labor investment efficiency takes form in both overinvestment and underinvestment. Further analyses suggest information asymmetry as the underlying mechanism for the efficiency loss. We also present that geographic dispersion leads to greater labor investment inefficiency in those firms operating in soft information environments and those employing more skilled labor. Finally, our results indicate that labor investment inefficiency accounts for the value discount of geographically-dispersed firms, highlighting the role of human capital investment in firm valuation for firms pursuing geographic diversification.

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Appendix
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Footnotes
1
10-K form is an annual report required by the U.S. Securities and Exchange Commission (SEC) that presents a comprehensive summary of a company’s financial performance. Besides financial information, 10-K forms also give information related to firm operations such as organizational structure, properties, subsidiaries, and executive compensation. Though 10-K forms are mentioned herein, we also collect and employ data from two other types of forms, 10-KSB or 20-F, if 10-K forms are not available. It is known that 10-KSB and 20-F correspond to small businesses and foreign issuers, respectively. This approach is similar to Bernile et al. (2015).
 
2
The Union Membership and Coverage Database (Hirsch and Macpherson 2003) can be retrieved at the website UNIONSTATS (www.​unionstats.​com).
 
3
We also replicate all regression models with 2% and 3% winsorized samples and find that the key research findings persist.
 
4
Results are quantitatively similar when we use 2-digit SIC industry codes. For robustness check, we also use firm or state fixed effects for this model to estimate abnormal net hiring.
 
5
Our statistics are quite similar to those reported in previous studies. For example, the mean of NET_HIRE in our sample is 5.9%, compared to 5.4% in Pinnuck and Lillis (2007) and 5.9% in Jung et al. (2014). Overall, our estimation is in line with other findings (Biddle et al. 2009; Jung et al. 2014; Ben-Nasr and Alshwer 2016), where NET_HIRE is negatively associated with changes in return on assets (DROA), size rank (SIZE_RANK), leverage ratio (LEV), sales ratio (AUR), and small reported losses (LOSSBIN) as well. However, we find a positive relation between actual net hiring (NET_HIRE) and sale growth and ratio (SALESGROWTH, AUR), return on assets (ROA), annual stock return (RETURN), and liquidity ratio and its change (QUICK, DQUICK).
 
6
We appreciate Diago García for sharing the geographic dispersion data for the period 1994-2007 to support this paper.
 
7
7 We thank a referee for this suggestion.
 
8
In unreported regressions, we also incorporate firm fixed effects into the model. The results remain consistent with the baseline findings.
 
9
9 The marginal effect is obtained as follows: 0.029 = (0.005*0.806)/0.139, where the denominator is the mean of abnormal net hiring.
 
10
The 0.2 percentage point increase in AB_NET_HIRE is calculated by: 0.005* ln((2 + 1)/2) = 0.002.
 
11
We would like to thank an anonymous referee for bringing this issue to our attention.
 
12
We are grateful to an anonymous referee for suggesting this measure.
 
13
We do not tabulate them in this table to save space, but they are available from the authors upon request.
 
14
We appreciate Scott D. Dyreng for sharing the data with our paper.
 
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Metadata
Title
Growing pains: geographic expansion and labor investment efficiency
Authors
Anh-Tuan Le
Henry Hongren Huang
Tzu-Chang Forrest Cheng
Publication date
24-09-2024
Publisher
Springer US
Published in
Review of Quantitative Finance and Accounting
Print ISSN: 0924-865X
Electronic ISSN: 1573-7179
DOI
https://doi.org/10.1007/s11156-024-01355-4

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