Abstract
This paper investigates the impact of economic policy uncertainty (EPU) on firm value and examines corporate diversification's role between EPU and firm value. We employ firm-level data for twenty-two countries from 2000 through 2020, which covers 364,433 firm-year observations of 29,709 unique firms and use index-based measures for EPU and corporate diversification. The results illustrate that EPU negatively impacts the firm value. However, corporate diversification positively moderates the adverse impact of EPU on the firm value by efficiently mitigating the effect of financial constraints. Further, the additional analysis shows that related and unrelated corporate diversification can be instrumental in alleviating the negative impact of high EPU on firm value in developed economies. In emerging economies, only unrelated diversification effectively deals with high EPU. The results are robust to subsampling, sensitivity, and endogeneity issues. Our study suggests a potential policy recommendation from a managerial perspective, that diversification helps to sustain the firm's value during uncertainty. Furthermore, Policymakers should recognize high policy uncertainty as a threat to business environment stability and take measures to reduce uncertainty and provide a more favorable environment for businesses.
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Notes
Apart from the moderating channels between EPU-firm value relationship, various other studies use the moderating channels to conduct studies. Like, Usman et al. (2022) examined the financial development role between pollution concern and globalization mode relationship using financially rich countries data. Also, Sadiq et al. (2022), conducted a study to see the role of external debt and financial globalization on the relationship between human development, nuclear energy, and carbon emission in BRICS countries. Another study done by Ke et al. (2022) examines the nexus between information, telecommunication, and technology (ICTs), globalization, foreign direct investment, and carbon emission based on 77 develo** countries' data.
The data for EPU is collected from www.policyuncertainty.com.
For more detail about the construction of the index. See, Baker et al. (2016) and visit www.policyuncertainty.com.
For brevity, regression results for control variables are not reported in all the results except for baseline results.
In unreported results, following (Jumah et al. 2022; Suh and Yang 2021), we rerun our baseline results using data sample after excluding financial crisis years (year excluded 2007–2009), sample after financial crises years (2010–2020) and sample excluding Covid-19 years (2000–2018). Also, we rerun the baseline results by clustering the robust standard errors at the firm level. In all the specifications, our results align with the baseline findings.
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Appendix: Variable definition
Appendix: Variable definition
Variables Name | Variable | Symbol | Description | Source |
|---|---|---|---|---|
Firm value | Dependent | Q | (Market value of equity − Book value of equity + Book value of total assets)/(Book value of total assets) following the study (Gulen and Ion 2016) | Refinitiv DataStream |
Excess value | Dependent (Alternate Measure) | E.V | We measured the Excess value based on the natural logarithm of the firm's excess value following the study of (Berger and Ofek 1995). A diversified firm’s excess value is the ratio of the actual market value of the firm to the sum of its imputed value of each business segment. Each firm segment's imputed value is based on its sales multiplied by the corresponding industry-median capital-to-sales ratio | Same as above |
Firm size | Control | Size | Firm size is measured by taking the natural logarithm of the firm's total assets at time t | Same as above |
Debt ratio | Control | Debt | The debt ratio is calculated by dividing the firm's total debt by its total assets at time t | Same as above |
Capital expenditure | Control | Capex | Firm investment is calculated by dividing the total capital expenditure of the firm by its total assets at time t | Same as above |
Dividend | Control | Div | The dividend ratio is a common share dividend to total assets at time t | Same as above |
Operating cash flow | Control | OperCF | The firm's operating cash flow is calculated by dividing the operating cash flow by total assets at time t | Same as above |
Sales growth | Control | SGrowth | The sales growth of the firm is a dummy measure with a value of ‘1’ where a firm has positive growth and ‘0’ otherwise. This measure adjusted the firms' sales growth by the median sales growth of its respective industry based on 4-digit SIC codes in the same country and year | Same as above |
EPU | Independent | LnEPU | Economic policy uncertainty is measured using the natural logarithm of the equally-weighted arithmetic mean of the monthly EPU index for the 12 months of the year, developed by (Baker et al. 2016). The equation is as follows \({LN(EPU}_{t})=LN({\sum }_{m=1}^{12}{EPU}_{m}/12)\) where, EPUt denotes the economic policy uncertainty at time t = year, EPUm denotes the monthly value of the U.S. EPU index and 12 denotes 12 months of the year | Data gathered from the website; www.policyuncertainty.com |
EPU3 | Independent (Alternate Measure) | LnEPU3 | Instead of 12 months, equally-weighted arithmetic mean, we use the last three months' EPU index arithmetic mean and take the natural logarithm of it as an alternate measure of EPU following the study of (Hong and Quang 2022; Nguyen and Phan 2017) \({LN(EPU}_{t})=LN({\sum }_{m=1}^{3}{EPU}_{m}/3)\) where, EPUt denotes the economic policy uncertainty at time t = year, EPUm denotes the monthly value of the U.S. EPU index and 3 denotes last three months of the year | Same as above |
EPU6 | Independent (Alternate Measure) | LnEPU6 | Instead of 12 months, equally-weighted arithmetic mean, we use the last six months EPU index arithmetic mean and take the natural logarithm of it as an alternate measure of EPU following the study of (Hong and Quang 2022; Nguyen and Phan 2017) \({LN(EPU}_{t})=LN({\sum }_{m=1}^{6}{EPU}_{m}/6)\) where, EPUt denotes the economic policy uncertainty at time t = year, EPUm denotes the monthly value of the U.S. EPU index and 6 denotes last six months of the year | Same as above |
Diversification dummy | Moderator | CDDum | Diversification measure based on dummy variable takes the value ‘1’ for the firms with two or more business segments and ‘0’ otherwise | Refinitiv DataStream |
Diversification index (Entropy) | Moderator | CDENindex | Diversification proxy using Entropy Index, measured as follows \(CDENindex={\sum }_{{\varvec{i}}=0}^{{\varvec{N}}{\varvec{S}}}{{\varvec{P}}}_{{\varvec{i}}}\boldsymbol{ }\mathbf{l}\mathbf{n}(\frac{1}{{{\varvec{P}}}_{{\varvec{i}}}})\) Where NS is many business segments in the conglomerate. Pi shows the income proportion from individual segment i in the total income of the conglomerate. The greater value of the index shows a high diversification level and vice-versa | Same as above |
Diversification index (Caves) | Moderator (Alternate Measure) | CDCavesindex | This Caves diversification measure captures the diversification in terms of relatedness and unrelatedness from its base industry. We measure the Caves index as follows \({\varvec{C}}.{\varvec{I}}=\boldsymbol{ }{\sum }_{{\varvec{K}}=1}^{{\varvec{K}}}{{\varvec{P}}}_{{\varvec{k}}}\times {{\varvec{D}}}_{{\varvec{k}}{\varvec{H}}}\) where k is the total product segments of the firm, Pk is the sales percentage of k product to the firm's total sales. \({{\varvec{D}}}_{{\varvec{k}}{\varvec{H}}}\) takes the value ‘0’ if the segment N belongs to the same four-digit SIC as its based product H and takes the value ‘1’ if the segment N has a different four-digit SIC from its base product H but the same three-digit SIC as the based product H, and takes the value ‘2’ if the segment N has different two-digit SIC from its base product H. The higher the value, shows greater the unrelated diversification level. See (Bae et al. 2011) for extensive detail on Caves-index measurement | Same as above |
Diversification index (Modified Herfindahl) | Moderator (Alternate Measure) | CDHFindex | Diversification measure based on the modified Herfindahl index is calculated as follows \({\varvec{M}}.\mathbf{H}.\mathbf{I}\mathbf{n}\mathbf{d}\mathbf{e}\mathbf{x}=1-{\sum }_{{\varvec{i}}=1}^{{\varvec{Z}}}\boldsymbol{ }({\varvec{S}}{\varvec{i}}\boldsymbol{ }/{\sum }_{{\varvec{i}}=1}^{{\varvec{Z}}}{\varvec{S}}{\varvec{i}})^2\) We measure across Z business segments of the firm, taking the sum of the square of each business segment i’s sales, \(Si,\) as a ratio of the total sale of the firm. After this, the value of the Herfindahl index is subtracted from 1 to get the modified Herfindahl index as a measure of diversification. If the value is close to ‘0’, the less diversified the firm is, and vice-versa. There is no defined standard for SIC code levels, and we use three- and four-digit codes to measure the caves index | Same as above |
Financial constraints | Mechanism analysis channel | F.C | Financial constraints measured as FC = {(− 0.737 × firm size) + (0.043 × (firm size)2) − (0.040 × firm age)}, following the study of (Hadlock and Pierce 2010) | Same as above |
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Jumah, Z., Safdar, N., Younas, Z.I. et al. Economic policy uncertainty, corporate diversification and firm value: the global evidence. Qual Quant 58, 2677–2707 (2024). https://doi.org/10.1007/s11135-023-01768-8
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DOI: https://doi.org/10.1007/s11135-023-01768-8