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FRICTIONS AND THE CONTRIBUTION OF INVENTORY TO SHAREHOLDER WEALTH Charles F. Beauchamp Middle Tennessee State University William G. Hardin III Florida International University Matthew D. Hill University of Southern Mississippi Chris M. Lawrey University of Mississippi Abstract Shareholder wealth effects associated with inventory are examined. Initial results indicate a positive and signicant relation between shareholder wealth and inventory. Additional ndings suggest that operating conditions, nancial constraints, and working capital behavior inuence the value of inventory. These ndings are consistent with tactical and strategic decisions inuencing managers to hold inventory. Overall, the results suggest that shareholders price the strategic advantages accompanying inventory. JEL Classification: G31, G32 I. Introduction This study investigates the shareholder wealth effects associated with inventory after conditioning on operating frictions, access to nancing, and working capital behavior. These research questions are of interest as effective and efcient inventory management is a key component of both working capital and liquidity management. Illustrating the economic importance of inventory policy, during scal year 2012 public rms held over $375 billion worth of inventory, which comprised 6% of total assets. Concurrently, inventory investment is equal to about 33% of total equity for the typical rm. Hence, the costs associated with holding inventory are a critical concern for managers. 1 Despite the We are grateful to Drew Winters (editor) and Mark Grifths (associate editor) for valuable suggestions that greatly improved the paper. We also thank seminar participants at the University of Memphis and University of Mississippi. All remaining errors are the responsibility of the authors. 1 Marginal costs of inventory include storage expenses, shipping fees, and nancing costs. Also, the supply chain management/logistics literatures note the shrinkage and obsolescence risks associated with carrying inventory. The Journal of Financial Research Vol. XXXVII, No. 3 Pages 385403 Fall 2014 385 © 2014 The Southern Finance Association and the Southwestern Finance Association RAWLS COLLEGE OF BUSINESS, TEXAS TECH UNIVERSITY PUBLISHED FOR THE SOUTHERN AND SOUTHWESTERN FINANCE ASSOCIATIONS BY WILEY-BLACKWELL PUBLISHING

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Page 1: FRICTIONS AND THE CONTRIBUTION OF INVENTORY TO SHAREHOLDER WEALTH

FRICTIONS AND THE CONTRIBUTION OF INVENTORY TOSHAREHOLDER WEALTH

Charles F. BeauchampMiddle Tennessee State University

William G. Hardin IIIFlorida International University

Matthew D. HillUniversity of Southern Mississippi

Chris M. LawreyUniversity of Mississippi

Abstract

Shareholder wealth effects associated with inventory are examined. Initial resultsindicate a positive and significant relation between shareholder wealth and inventory.Additional findings suggest that operating conditions, financial constraints, and workingcapital behavior influence the value of inventory. These findings are consistent withtactical and strategic decisions influencing managers to hold inventory. Overall, theresults suggest that shareholders price the strategic advantages accompanying inventory.

JEL Classification: G31, G32

I. Introduction

This study investigates the shareholder wealth effects associated with inventory afterconditioning on operating frictions, access to financing, and working capital behavior.These research questions are of interest as effective and efficient inventorymanagement isa key component of both working capital and liquidity management. Illustrating theeconomic importance of inventory policy, during fiscal year 2012 public firms held over$375 billion worth of inventory, which comprised 6% of total assets. Concurrently,inventory investment is equal to about 33% of total equity for the typical firm. Hence, thecosts associated with holding inventory are a critical concern for managers.1 Despite the

We are grateful to Drew Winters (editor) and Mark Griffiths (associate editor) for valuable suggestions thatgreatly improved the paper. We also thank seminar participants at the University of Memphis and University ofMississippi. All remaining errors are the responsibility of the authors.

1Marginal costs of inventory include storage expenses, shipping fees, and financing costs. Also, the supplychain management/logistics literatures note the shrinkage and obsolescence risks associated with carryinginventory.

The Journal of Financial Research � Vol. XXXVII, No. 3 � Pages 385–403 � Fall 2014

385

© 2014 The Southern Finance Association and the Southwestern Finance Association

RAWLS COLLEGE OF BUSINESS, TEXAS TECH UNIVERSITYPUBLISHED FOR THE SOUTHERN AND SOUTHWESTERN

FINANCE ASSOCIATIONS BY WILEY-BLACKWELL PUBLISHING

Page 2: FRICTIONS AND THE CONTRIBUTION OF INVENTORY TO SHAREHOLDER WEALTH

costs associated with holding inventory, a direct link exists between firm value andinventory management since the proper integration of inventory and trade credit policiescan generate incremental revenues, profits, and cash flows (Kieschnick, LaPlante, andMoussawi 2013).

Baseline regressions using a sample of publicly traded firms from 1981 to 2010provide robust evidence of a positive and significant relation between shareholderwealth and inventory. Consistent with theory and practice, the value that shareholdersplace on inventory is lower than for cash and trade receivables. Inferences from thebaseline model are insensitive to alternative model specification and numerous robustnesschecks.

The shareholder wealth effects associated with inventory exhibit significantcross‐sectional variation with respect to firm characteristics. Operating conditions affectthe excess returns to inventory relation through suppliers’ variability in revenues andmarket share. Further results indicate a significantly stronger relation between shareholderwealth and inventory for financially constrained firms. This finding suggests thatshareholders support the accumulation of inventory by managers of constrained firms, asreported by Caglayan, Maioli, and Mateut (2012). The last set of results suggests that therelation between shareholder wealth and inventory is significantly influenced by variousaspects of working capital policy.

This study provides novel contributions to the working capital literature. Anextensive body of research examines the determinants of inventory investment, leavingthe relation between shareholder wealth and inventory relatively unexamined. Anexception to this is research by Chen, Frank, and Wu (2005), where the authors findreduced returns for firms with abnormally high inventories. Their evidence supports theview that excess investment in inventory reduces shareholder wealth. In contrast, thecurrent study focuses on the relation between shareholder wealth and inventory forthe typical firm. The studies also differ with respect to econometric method; a multivariateapproach comprises the present valuation framework, allowing for stronger statisticalinferences on the relation between shareholder wealth and inventory, relative to theportfolio sort approach used by Chen, Frank, and Wu.

This article also contributes to the literature by examining the conditional natureof the relation between shareholder wealth and inventory. The observed variation in thisrelation with respect to operating conditions, financing frictions, and working capitalbehavior is consistent with the strategic dimensions that motivate managers to holdinventory. Hence, the study links managerial motives for carrying inventory toshareholder assessment of these motives.

II. Empirical Model

The valuation framework from Kieschnick, LaPlante, and Moussawi (2013) is used toestimate the market value of inventory. The model accounts for firm‐specific risk byspecifying excess returns as the dependent variable, while the independent variablescontrol for unexpected changes in financial characteristics. The baseline specificationfollows:

386 The Journal of Financial Research

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ExReti;t ¼ g0 þ g1DInvi;tM i;t�1

þ g2DInvi;t�1

Mi;t�1þ g3

DCi;t

M i;t�1þ g4

Ci;t�1

Mi;t�1þ g5

DTRi;t

M i;t�1

þg6TRi;t�1

Mi;t�1þ g7

DTPi;t

M i;t�1þ g8

DTPi;t�1

Mi;t�1þ g9

DEi;t

M i;t�1þ g10

DNAi;t

M i;t�1

þg11DRDi;t

M i;t�1þ g12

DI i;tM i;t�1

þ g13DDi;t

M i;t�1þ g14Li;t þ g15

NFi;t

M i;t�1

þg16SalesGi;t þ g jT ime and Ind Ef f ectsj;t þ 2i;t;

ð1Þ

where DX represents a change in X from years t–1 to t.Excess returns (ExReti,t) equal annual raw returns, calculated as the sum of the

change in market value of equity and dividends scaled by lagged market equity, minus thebenchmark return.2 Fama and French’s (1993) 5� 5 size and book‐to‐market portfoliosorts (formed at the end of June in year t) provide the benchmark returns.3 The size sortuses market value of equity from the end of June in year t, while the book‐to‐market sortuses the ratio of book value of equity at fiscal year‐end in calendar year t–1 and marketvalue of equity at the end of December in calendar year t–1.

Equation (1) isolates the value implications associated with inventory byaccounting for profitability, investment, and financing policy. Earnings beforeextraordinary items (Et) and sales growth (SalesGt) proxy profitability.4 Noninventorycontrols for investment include research and development expense (R&Dt) and netassets (NAt), calculated as total assets minus cash, inventory, and trade receivables.Proxies for financial policy include cash (Ct), trade receivables (TRt), trade payables(TPt), interest expense (It), dividends (Dt), market leverage (Lt), and net financing(NFt). Equation (1) also includes fixed effects for time and industry (Fama and French1997).

The pertinent variable for our study is DInvt, defined as the change in totalinventory scaled by the laggedmarket value of equity.5 Because the annual raw return andthe change in inventory are scaled by the lagged market value of equity, g1 represents themarket value of an additional $1 invested in inventory. Including the lagged inventory

2Stock returns are adjusted for dividends and stock splits.3Ken French graciously provides data on the book‐to‐market and size portfolio breakpoints and returns (http://

mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html).4Compustat variable names and calculations follow. The market value of equity, MVE, is number of shares

multiplied by share price at fiscal year‐end. Inv is inventory. C is cash and marketable securities. TR is tradereceivables. TP is trade payables. E is earnings before extraordinary items plus interest expense, deferred tax credits,and investment tax credits. RD is research and development expenditures. NA is net assets, defined as total assetsminus cash, inventory, and trade receivables. I is interest expense.D is common dividends paid. L is market leverage,defined as long‐term debt plus debt in current liabilities divided by the sum ofmarket value of equity, long‐term debt,and debt in current liabilities.NF is net financing, calculated as equity issuanceminus repurchases plus debt issuanceminus debt redemption. SalesG is calculated as the percentage change in net sales. Following Faulkender andWang(2006), we set deferred tax credits, investment tax credits, and research and development expenditures equal to 0 ifmissing.

5For brevity, the scaling of the independent variables is suppressed throughout the remainder of the article. Forexample, DInvt refers to

DInvi;tMi;t�1

and Invt–1 refers toDInvi;t�1

Mi;t�1.

Frictions and the Contribution of Inventory 387

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ratio (Invi,t–1) clarifies the reaction of shareholders to a given change in inventory, holdingall else constant.6

Variants of equation (1) are used to test several hypotheses. The first hypothesisand its corollary involve the baseline relation between shareholder wealth and inventory.The theoretical link between firm value and inventory management is largely attributableto inefficiencies between production and sales. Anand, Anupindi, and Bassok (2008)argue that inventory allows suppliers to hedge uncertainty in (1) customer demand (stock‐out risk), (2) future input prices, and (3) shortages in the supply of necessary inputs(production buffering). In addition to these benefits, the liquidity and low adjustmentcosts of inventory enhance its value to shareholders (Shleifer and Vishny 1992;Williamson 1988). Furthermore, Kieschnick, LaPlante, and Moussawi (2013) linkworking capital components, including inventory, to shareholder wealth by explainingtheir effect on future revenues and cash flows. The aforementioned benefits of inventorylead to the following hypothesis.

H1: Shareholder wealth is directly related to inventory.

Predicting the value that shareholders ascribe to an additional $1 held ininventory is difficult because of the marginal costs associated with holding inventory.Such costs include borrowing costs, opportunity costs, risk of obsolescence, insurancepremiums, and storage expenses. The uncertainty of sales and collection further reducethe expected market value of inventory. The costs accompanying inventory lead to theexpectation that g1 will be less than $1 and lower than the marginal value of an additionaldollar of cash and/or receivables, as stated in the following corollary to H1.

H1a: The shareholder wealth effects associated with inventory are weaker thanthe wealth effects of cash and trade receivables.

Along with establishing the relation between shareholder wealth and inventory,variation is examined with respect to the influence of operating frictions, financingconstraints, andworking capital policy. The second hypothesis regards operating frictionsfaced by suppliers and shed light on whether supply chain characteristics provideadvantages in creating shareholder value via inventory management.

H2: The shareholder wealth effects of inventory are conditional on operatingfrictions.

Examples of operating frictions examined include demand uncertainty,negotiating leverage, and industry competition. Caglayan, Maioli, and Mateut (2012)show that managers respond to demand variability for products by increasing inventorylevels. This suggests that the relation between shareholder wealth and inventorystrengthens for firms with less predictable demand due to mitigated stock‐out risk.However, it is plausible that demand uncertainty may reduce inventory value due to

6Faulkender and Wang (2006) include the lagged cash ratio to isolate the value implications accompanying achange in cash holdings.

388 The Journal of Financial Research

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shareholder concern over excess inventory. Hence, the effect of demand uncertainty onthe wealth effects of inventory is ambiguous. Demand uncertainty (SalesCVt) is measuredas the standard deviation of annual revenues divided by average revenue (i.e., thecoefficient of variation). Both statistics are calculated using trailing firm‐level revenues.Observations are included in the sample for a given year if the firm makes at least threepanel appearances during the previous sample years.

The customer–supplier relationship may also influence the relation betweenshareholder wealth and inventory. Managers with weaker negotiating leverage are lesslikely to receive favorable purchasing terms without ordering in bulk. Concurrently,managers with superior negotiating ability may realize discounts that generallyaccompany bulk orders, thereby reducing the benefit of economies of scale in inventoryorders. In addition, Blazenko and Vandezade (2003) postulate that less influential firmsreceive less favorable delivery schedules and have greater stock‐out risk, suggesting astronger relation between shareholder wealth and inventory for firms with weakernegotiating power. Such effects may stem from firm‐level market power and/or industry‐level competition. Hence, H2 is tested by conditioning DInvt on proxies for both marketshare and industry concentration. The first measure of firm‐level market power isMktSharet, defined as individual firm revenues scaled by total industry revenues earned ina given year. In separate regressions, indicator variables differentiate high‐ and low‐market‐share firms. The variableMedMktShareDVt (P75MktShareDVt) equals 1 if marketshare exceeds a respective industry’s median (75th percentile), and 0 otherwise. Theinitial proxy for degree of industry competitiveness is the Herfindahl index (HFIt),calculated as the sum of squared market shares in an industry for a given year. Greatervalues for HFIt imply less competitive industries. Dummy variables are created at themedian and 75th percentile of HFIt (MedConcenDVt and P75ConcenDVt).

The third hypothesis concerns the impact of financing frictions on the marketvalue of inventory.

H3: The shareholderwealth effects of inventory strengthenwith financial constraint.

Research suggests that financing conditions affect inventory investment. Caglayan,Maioli, and Mateut (2012) find that managers of financially constrained firms hold moreinventory than unconstrained firms. Financial constraints make it more difficult to hedgeinput prices and mitigate the risk of stock‐outs attributable to positive demand shocks.Managers of unconstrained firms, meanwhile, can more readily raise capital to mitigateadverse conditions that motivate inventory holdings. For example, unconstrainedmanufacturing firms can react to positive demand shocks by purchasing raw materialswith funds from commercial paper or lines of credit. Consequently, the wealth effects ofinventory should be stronger for financially constrained firms.

The primary measure of financial constraint involves commercial paper, asinventory is generally funded with short‐term financing.7 Specifically, firm‐years with

7Credit lines also provide a typical source of financing for inventory. Data constraints prevent accounting forcredit lines in the current setting. Sufi (2009) discusses data constraints related to the coverage of credit line data forlarge samples of publicly traded firms.

Frictions and the Contribution of Inventory 389

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commercial paper ratings and positive debt levels comprise the financially unconstrainedgroup.8 Meanwhile, the constrained cohort consists of observations with positive debtlevels and no commercial paper rating. The underlying intuition is that firms withcommercial paper ratings have superior access to debt at lower marginal transactionscosts. Furthermore, Faulkender and Wang (2006) mention that firms with ratedcommercial paper are considered among the least risky of publicly traded firms.

For robustness, other proxies for financial constraint include the payout ratio,firm size, and bond ratings. Larger dividend payout ratios, defined as the sum of commondividends and repurchases divided by earnings, imply financial flexibility (Fazzari,Hubbard, and Petersen 1988). Firms are sorted based on annual payout ratios and firm‐

years with ratios less (greater) than or equal to the payout ratio at the 30th (70th)percentile for a given year are assigned to the constrained (unconstrained) group. Interms of firm size as a measure of financial constraint, larger firms tend to be older withreduced informational asymmetries and enhanced access to public and private capitalmarkets. After rank‐ordering all firms by their sales at the end of the previous fiscal year,firm‐years with sales less (greater) than or equal to the sales in the bottom (top) threedeciles of the annual size distribution are classified as constrained (unconstrained). Thefinal financial constraint measure is based on bond ratings. Firm‐years with (without)Compustat bond ratings and positive debt levels comprise the unconstrained(constrained) group.

As a final test, the influence of working capital policy on the relationbetween shareholder wealth and inventory is assessed. Sartoris and Hill (1983) arguethat working capital management requires a holistic focus because of the inter-dependencies among cash holdings, trade credit policies, and inventory levels. As aconsequence, working capital accounts are inherently related and must be managedsimultaneously. Therefore, sales growth and prior‐period working capital levels mayinfluence the relation between shareholder wealth and inventory, as stated in thefollowing hypothesis.

H4: The shareholder wealth effects attributable to inventory are conditional onworking capital policy.

Sales growth may influence the value effects of inventory. Growth in sales is animportant aspect of working capital management because additional sales trigger a chainreaction throughout the various working capital accounts. In terms of the impact oninventory value, firms with higher sales growth will need periodic increases in inventoryto satisfy customer demand. Consequently, investors should more highly value additionalinventory held by firms with more rapidly growing sales. Comparable to this view, Hill,

8The existence of rated commercial paper will not indicate the degree of financial constraint across all firms.Specifically, firms in industries with less volatile cash flows may be less reliant on the use of debt for ongoingliquidity needs (e.g., resource‐based companies). Still, the financial constraint measures used in this study areconsistent with those employed in the existing cash and working capital literatures (Almeida, Campello, andWeisbach 2004; Faulkender and Wang 2006; Denis and Sibilkov 2010; Hill, Kelly, and Lockhart 2012). We thankan anonymous reviewer for this clarification.

390 The Journal of Financial Research

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Kelly, and Lockhart (2013) find that the wealth effects of access to trade credit increasewith the buyer’s sales growth.

In terms of the effects of prior‐period working capital levels, it is difficult topredict the impact of lagged cash and trade payables on the wealth effects of inventory.Higher cash levels imply lower opportunity costs and reduced interest expenseassociated with financing additional inventory. Alternatively, because cash canmitigate the strategic benefits of inventory (Caglayan, Maioli, and Mateut 2012),shareholders may discount the value of inventory for firms with more cash. Given theseconflicting views, the effect of cash on the wealth effects of inventory is an openempirical question.

Schiff and Lieber (1974) and Kieschnick, LaPlante, and Moussawi (2013) positthat inventory management is linked to the receipt of trade credit. There is, however,ambiguity regarding the impact of trade payables on inventory value due to unobservedvariation in the cost of trade credit. Petersen and Rajan (1994, 1997) argue that trade creditis one of the most expensive forms of financing, suggesting that investors discountinventory held by firms that extensively use payables. Conversely, a growing literaturefinds that the cost of trade credit is exaggerated (Giannetti, Burkart, and Ellingsen 2011;Klapper, Laeven, and Rajan 2012).

In terms of trade credit extended (i.e., receivables), shareholders will likelydiscount inventories held by firms with higher levels of prior‐period receivables. Higherreceivables restrict cash flow and may signal collection problems, reducing the ability tofinance additional inventory. Similar to the impact of receivables, the interaction betweenthe prior‐period inventory level and the current‐period change in inventory should benegatively signed. That is, an additional dollar invested in inventory should provide lessbenefit to firms with higher lagged inventory stock. Furthermore, accumulatinginventory in the current period conditional on a high prior‐period inventory level sendsa negative signal regarding revenue and cash flow growth to shareholders. Accumulatinginventory presents two major problems. First, additional inventory may result inobsolescence, thereby reducing future sales. More likely, overstocked inventory in thecurrent period could force managers to develop sales strategies more conducive to thebuyer such as reduced prices and/or financing discounts, resulting in reduced profits andcash flow.

Many of the aforementioned hypotheses are tested by including in equation (1)interactions between DInvt and the aforementioned variables. For example, the impact ofmarket share on the relation between shareholder wealth and inventory is estimated byincluding the interaction term DInvt�MktSharet within the valuation model. Afterdifferentiating the expanded version of equation (1) with respect to DInvt, the interactionprovides the difference in g1 associated with the level of the firm’s market share. Theremaining interactions provide similar marginal effects.

III. Sample and Summary Statistics

The initial sample includes Compustat firms, excluding firms in the financial, service, andutility industries. Nonconsecutive firm‐years and observations with negative values for

Frictions and the Contribution of Inventory 391

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market value of equity, net assets, and dividends are excluded from the sample. Eachvariable is truncated at the 1% level to mitigate the effect of outliers. The sample used forthe baseline results consists of an unbalanced panel of 34,351 firm‐year observations for5,292 unique firms from 1981 to 2010.

Table 1 presents descriptive statistics. As in Faulkender andWang (2006), ExRettis positively skewed. The mean change in total inventory as a percentage of laggedmarketvalue of equity (DInvt) is negatively signed. In dollar terms, the average annual change ininventory implies an approximate reduction of inventory equal to $1.2 million per year.These statistics indicate that the sample firms have reduced their investment in inventoryover the period in question, consistent with contemporaneous improvements in inventorymanagement techniques. Despite this reduction, inventory remains an economicallysignificant aspect of corporate investment; inventory comprises 33% of the market valueof equity for the typical sample firm (Invt–1). The remaining variables are comparable insign and magnitude to those reported by recent studies using variants of equation (1) tovalue changes in working capital policies.

For brevity, pairwise correlations are not tabulated, but a direct and signi-ficant univariate correlation exists between ExRett and DInvt. This positive associationprovides preliminary support for shareholders valuing the benefits accompanyinginventory.

TABLE 1. Descriptive Statistics.

Variables N Mean 25th % Median 75th % StdDev

ExReti,t 34,351 0.024 �0.341 �0.083 0.218 0.628DInvi,t 34,351 �0.011 �0.018 0.000 0.019 0.131Invi,t�1 34,351 0.333 0.031 0.152 0.399 0.509DCi,t 34,351 0.006 �0.034 0.000 0.037 0.144Ci,t�1 34,351 0.174 0.033 0.091 0.212 0.235DTRi,t 34,351 0.002 �0.023 0.002 0.030 0.125TRi,t�1 34,351 0.321 0.078 0.182 0.388 0.415DTPi,t 34,351 0.001 �0.013 0.001 0.018 0.086TPi,t�1 34,351 0.160 0.030 0.076 0.176 0.241DEi,t 34,351 0.023 �0.040 0.005 0.047 0.273DNAi,t 34,351 �0.014 �0.058 0.002 0.057 0.308DRDi,t 34,351 0.001 �0.000 0.000 0.003 0.027DIi,t 34,351 �0.002 �0.004 �0.000 0.003 0.030DDi,t 34,351 �0.000 0.000 0.000 0.000 0.006Li,t 34,351 0.234 0.029 0.167 0.372 0.234NFi,t 34,351 0.029 �0.035 0.000 0.051 0.225SalesGi,t 34,351 0.086 �0.074 0.036 0.164 0.366

Note: This table shows the sample characteristics of the 34,351 firm‐year observations for 5,292 unique firms from1981 to 2010. Variables are reported in decimal form. DXi,t represents the one‐year change in X, Xi,t�Xi,t�1. Withthe exception of L and SalesG, all control variables are scaled by the lagged market value of equity. ExRet is excessreturn, where the Fama and French (1993) size and book‐to‐market portfolio matched returns comprise thebenchmark portfolio. Inv is total inventory. C is cash and marketable securities. TR is trade receivables. TP is tradepayables. E is earnings, defined as earnings before extraordinary items. NA is net assets, calculated as total assetsminus cash, inventory, and trade receivables. RD is research and development expenditures. I is interest expense. Dis common dividends. L is the market leverage ratio. NF is net new financing. SalesG is the percentage change insales.

392 The Journal of Financial Research

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IV. Results

Baseline Results

Table 2 displays results after estimating versions of equation (1) using pooled ordinaryleast squares (OLS) with standard errors that are corrected for heteroskedasticity and firm‐

level clustering.9 The baseline model explains roughly 27% of the variation in excessreturns.

Results suggest that shareholders value incremental investments in cash holdingsand trade receivables. The marginal value of cash ($0.90) exceeds the marginal value ofreceivables ($0.72). In terms of the nonworking capital controls, the findings show thatExRett is directly and significantly related to increased earnings, net assets, research anddevelopment expenditures, dividends, net financing, and sales growth. Suggesting thatexcess leverage is detrimental to shareholders, the coefficients on the change in interestexpense and market leverage are negatively signed, consistent with findings from Hill,Kelly, and Lockhart (2012) and Kieschnick, LaPlante, and Moussawi (2013).

The parameter estimate of interest is g1, representing shareholders’ valuation ofan incremental $1 invested in inventory. Supporting H1, the relation between shareholderwealth and inventory is positive and statistically significant at the 1% level or stronger.10

The importance of inventory to shareholders is distinct from the effect of anticipated salesgrowth, due to the inclusion of SalesGt in equation (1). Untabulated results suggest thatthe significance of the relation between excess returns andDInvt is robust after accountingfor firm‐level heterogeneity.

The initial coefficient estimate on DInvt implies that shareholders of the typicalsample firm value an additional $1 of inventory at $0.37. Consistent with H1a,comparisons of the coefficient estimates for the individual components of working capitalsuggest that shareholder value varies directly with the liquidity of the short‐term asset.Specifically, the marginal values of cash and trade receivables are significantly higherthan the marginal value of inventory. The lower value for inventory is attributable to thereduced liquidity andmarginal costs associated with inventory holdings. Furthermore, thedifference in the value of receivables and inventory is consistent with asset‐based lendingpractices.

The positive relation between equity values and inventory supports the view thatshareholders recognize the strategic benefits accompanying inventory. The finding alsoprovides a market value explanation for the economic magnitude of inventory held oncorporate balance sheets: managers carry inventory because it enhances shareholderwealth. The present results differ from findings by Chen, Frank, and Wu (2005) showinglower returns for portfolios of firms holding abnormally greater inventory. The differencein inferences may be attributable to their focus on extreme inventory behavior and theiruse of a portfolio sort approach. Alternatively, the present study focuses on typical

9The baseline results are unchanged after clustering the standard errors by industry.10The positive and significant value of inventory is consistent with the last set of results presented by

Kieschnick, LaPlante, and Moussawi (2013), in which the authors estimate the individual components of netoperating working capital.

Frictions and the Contribution of Inventory 393

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TABLE 2. Wealth Effects of Inventory.

Independent Variables (1) (2) (3)

DInvi,t 0.367��� 0.303��� 0.385���(.000) (.000) (.000)

DInvi,t�90sDV 0.182���(.004)

DInvi,t�00sDV �0.069(.377)

DInvi,t�CrisisDV �0.623���(.001)

CrisisDV 0.102���(.000)

Invi,t�1 0.119��� 0.119��� 0.112���(.000) (.000) (.000)

DCi,t 0.896��� 0.905��� 0.899���(.000) (.000) (.000)

Ci,t�1 0.280��� 0.296��� 0.289���(.000) (.000) (.000)

DTRi,t 0.722��� 0.706��� 0.706���(.000) (.000) (.000)

TRi,t�1 0.266��� 0.269��� 0.266���(.000) (.000) (.000)

DTPi,t �0.024 �0.028 �0.025(.727) (.675) (.711)

TPi,t�1 0.132��� 0.126��� 0.134���(.000) (.000) (.000)

DEi,t 0.360��� 0.362��� 0.359���(.000) (.000) (.000)

DNAi,t 0.111��� 0.111��� 0.111���(.000) (.000) (.000)

DRDi,t 0.359�� 0.312� 0.307�(.035) (.069) (.073)

DIi,t �1.591��� �1.548��� �1.600���(.000) (.000) (.000)

DDi,t 2.319��� 2.131��� 2.267���(.000) (.000) (.000)

Li,t �0.905��� �0.887��� �0.892���(.000) (.000) (.000)

NFi,t 0.083��� 0.078��� 0.078���(.002) (.004) (.004)

SalesGi,t 0.185��� 0.177��� 0.182���(.000) (.000) (.000)

Observations 34,351 34,351 34,351R2 0.266 0.259 0.260

Note: This table presents ordinary least squares regressions examining the wealth effects of inventory. Thedependent variable is excess return, where the Fama and French (1993) size and book‐to‐market portfolio matchedreturns comprise the benchmark index.DXi,t represents the one‐year change inX (Xi,t�Xi,t�1).With the exception ofL and SalesG, the baseline control variables are scaled by the lagged market value of equity. Inv is total inventory.Cis cash and marketable securities. TR is trade receivables. TP is trade payables. E is earnings, defined as earningsbefore extraordinary items. NA is net assets, calculated as total asset minus cash, inventory, and trade receivables.RD is research and development expenditures. I is interest expense.D is common dividends. L is the market leverageratio.NF is net new financing. SalesG is the percentage change in sales. 90sDV and 00sDV represent decade dummyvariables. CrisisDV is an indicator variable equal to 1 for observations occurring in 2008 or 2009, and 0 otherwise.All models include dummies for time and industry affiliation (Fama and French 1997). Unreported standard errorsare robust to heteroskedasticity and are clustered at the firm level. The p‐values appear in parentheses. For brevity,the annual time dummies and industry dummies are not presented.���Significant at the 1% level.��Significant at the 5% level.�Significant at the 10% level.

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inventory holdings and uses a multivariate approach for valuation. The latter provides amore rigorous test for the value relevance of inventory.

The remainder of this section examines variation in the relation betweenshareholder wealth and inventory throughout the sample period and across industryaffiliation. The former issue is of interest because equation (1) assumes a constant valueover the sample period, which may be inappropriate given the length of the panel data set.To address this concern, DInvt is interacted with decade dummy variables (column 2),where observations occurring in the 1980s represent the base case. Findings suggestthat an additional $1 of inventory held in the 1990s is worth $0.18 more than in theprevious decade. The wealth effects of inventory from 2000 to 2010 are statisticallyindistinguishable from those in the 1980s.

In the next column, the wealth effects of inventory during the recent financialcrisis are evaluated by interacting DInvt with CrisisDVt, a dummy variable identifyingobservations occurring in 2008 or 2009. Suggesting a reduced value of inventory duringthe financial crisis, the interaction term DInvt�CrisisDVt is negatively signed andsignificant at the 1% level. This result is consistent with the view that shareholdersperceived negative demand shocks during the crisis, which would reduce the need foradditional inventory.

Further evidence on time‐series variation in the wealth effects of inventory isprovided by Figure I, which presents estimates of g1 after estimating equation (1)separately for each sample year. Figure I suggests variation in the annual estimates for g1over the sample period. Eighteen of the 30 annual estimates for g1 are positive andstatistically significant; the relation between shareholder wealth and inventory is notsignificantly different from $0 in the years in which g1 is negatively signed. Of thestatistically significant values, the mean value for g1 equals $0.42, and the maximum andminimum point estimates equal $1.00 and $0.26 in 1993 and 1984, respectively. Overall,the results in Figure I indicate substantial decreases in inventory value during periods of

$0.00

$0.20

$0.40

$0.60

$0.80

$1.00

$1.20

1981 1982 1984 1985 1986 1988 1992 1993 1994 1995 1996 1997 1998 2000 2001 2002 2004 2007

γ Ind

ustr

y

Year

Figure I. Time‐Series Variation in the Wealth Effects of Inventory.

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equity market turbulence, such as the market crash in 1987, the tech bubble, the recessionin 2001–2002, and the recent financial crisis in 2008.

Variation in g1 across industries is examined by estimating equation (1) for eachindustry. Table 3 presents the sample size for each industry, the excess risk premium foreach industry (aInd), and the industry estimates for the wealth effects of inventory (gInd).The results indicate substantial variation in gInd. The relation between shareholder wealthand inventory is statistically insignificant for half of the sample industries. The wealtheffects of inventory are positive and significant for 20 of the sample industries. In general,the results suggest that shareholders value the inventory held by firms (1) requiringaggressive inventory management (e.g., food companies), (2) providing inelasticconsumer goods (e.g., health care), (3) supplying consumer durables (e.g., automobiles),and (4) that are manufacturers (e.g., fabricated products).

As a specific example, consider the wealth effects of inventory for the restaurantindustry; shareholders value an additional $1 of inventory for these firms at $1.25. Apossible rationale for this result is that managers of corporate restaurant chains tend to useaggressive inventory policies to satisfy consumer demand while balancing the risk ofspoilage. An aggressive inventory policy coupled with high markups on the cost of goodssold result in shareholders viewing inventory in a favorable manner.

Operating Conditions

Table 4 presents results on the relation between excess returns and inventory afterconditioning on operating frictions (H2). Space constraints limit the presented results toonly the variables of interest. Column 1 results indicate that excess returns are positivelyrelated to inventory and that demand uncertainty (SalesCVt) significantly reduces equityvalues. The coefficient for the interaction term DInvt�SalesCVt is negatively signed andmarginally significant, which suggests that equity holders discount the inventory held byfirms with more volatile sales. The reduced value of inventory for firms with less certaindemand contrasts with results from Caglayan, Maioli, and Mateut (2012) showing thatmanagers of firms with less predictable sales hold more inventory. Although managersfocus on the precautionary motive of inventory, it appears that shareholders discount thismotive and are concerned with lower than expected customer demand, as opposed toexcess demand, which leads to an accumulation of inventory.

Another aspect of operating conditions that may affect the wealth effects ofinventory is negotiating ability. Models 2 to 4 suggest a positive relation betweenshareholder wealth and negotiating ability as proxied by market share. Results for thecontinuous definition of market share in column 2 show a negative and statisticallysignificant coefficient estimate forDInvt�MktSharet. This interaction implies a weakeningrelation between excess returns and inventory for firms with stronger negotiating ability.This result is consistent with diminished benefits from economies of scale in purchases forfirms that likely already receive favorable delivery schedules, pricing, and credit terms(i.e., high‐market‐share firms). The statistical significance of this interaction is lost oncemarket share is measured usingMedMktShareDVt. However, results in column 4 indicatea reduced inventory value for firms with market share equaling or exceeding the75th percentile of the respective industry‐year market share. In terms of economic

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TABLE 3. Wealth Effects of Inventory by Industry Affiliation.

Industry N aIndustry gIndustry

Agriculture 53 �0.414 �0.549Food products 799 0.110�� 0.403��

Candy and soda 128 0.158 1.540Beer and liquor 189 0.086 1.119�

Tobacco products 60 0.222 1.672���

Recreation 420 �0.172 0.316Entertainment 393 �0.094 �1.072Print. & publishing 419 0.234�� 0.646�

Consumer goods 1,368 �0.002 0.562���

Apparel 961 0.240��� 0.295���

Healthcare 517 0.198 0.972�

Medical equip. 1,954 �0.081 0.091Pharmaceuticals 2,243 0.220 0.223Chemicals 991 �0.053 0.109Rubber & plastic 727 �0.005 0.054Textiles 555 0.241��� 0.479���

Const. materials 1,492 0.065 0.329��

Construction 212 �0.194 0.252Steel works 796 0.058 0.157Fabricated prod. 272 �0.117 0.642��

Machinery 2,271 �0.002 0.315���

Electrical equip. 973 �0.128 0.870���

Autos & trucks 885 �0.053 0.265��

Aircraft 362 0.037 0.878��

Shipbuilding 124 �0.172 0.187Defense 95 �0.507 0.902Precious metals 82 0.228 �0.630Mining 131 0.018 �0.299Coal 41 �1.173 �4.326Oil and nat. gas 1,446 �0.218��� �0.127Communication 929 0.235 0.608Computers–hardware 1,592 �0.106� 0.610���

Computers–software 2,594 0.019 0.074Electronic equipment 3,652 �0.128 0.305��

Measuring equipment 1,697 �0.039 0.555���

Business supplies 822 0.054 0.359�

Shipping cont. 150 0.082 0.607Transportation 508 0.142 0.320Wholesale 851 0.020 0.365���

Retail 373 �0.018 0.462Restaurants, etc. 183 0.197 1.250��

Other 41 �0.086�� �4.053���

No. of observations 34,351

Note: This table provides results examining the wealth effects of inventory by industry (gIndustry). Industryclassifications follow the Fama–French (1997) 48‐industry classification system. Utilities, banking, insurance, realestate, and trading firms are omitted. aIndustry is the risk‐adjusted excess return for each industry. The sample consistsof 34,351 firm‐years across 5,292 unique companies from 1981 to 2010.���Significant at the 1% level.��Significant at the 5% level.�Significant at the 10% level.

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TABLE 4. Wealth Effects of Inventory and Operating Conditions.

Independent Variables (1) (2) (3) (4) (5) (6) (7)

DInvi,t 0.437��� 0.401��� 0.382��� 0.404��� 0.367��� 0.340��� 0.359���

(.000) (.000) (.000) (.000) (.000) (.000) (.000)DInvi,t�SalesCVi,t �0.219�

(.065)DInvi,t�MktSharei,t �5.645���

(.000)DInvi,t�MedMktShareDVi,t �0.031

(.594)DInvi,t�P75MktShareDVi,t �0.182��

(.018)DInvi,t�HFIInd,t 0.002

(.996)DInvi,t�MedConcenDVInd,t 0.054

(.328)DInvi,t�P75ConcenDVInd,t 0.038

(.559)SalesCVi,t �0.040���

(.002)MktSharei,t 0.642���

(.000)MedMktShareDVi,t 0.057���

(.000)P75MktShareDVi,t 0.060���

(.000)HFIInd,t 0.088

(.226)MedConcenDVInd,t 0.005

(.629)P75ConcenDVInd,t 0.029���

(.010)Full set of controls? Yes Yes Yes Yes Yes Yes YesNo. of observations 34,351 34,351 34,351 34,351 34,351 34,351 34,351R2 0.266 0.267 0.267 0.268 0.266 0.266 0.266

Note: This table presents ordinary least squares regressions examining the wealth effects of inventory afterconditioning on operating conditions. The dependent variable is excess return, where the Fama and French (1993)size and book‐to‐market portfolio matched returns comprise the benchmark index. DXi,t represents the one‐yearchange in X (Xt�Xt�1). DInv is scaled by the lagged market value of equity. Inv is total inventory. SalesCV is thecoefficient of variation for firms’ annual sales. MktShare is the firm’s annual revenues divided by the total annualrevenues earned in the firm’s industry.MedMktShareDV (P75MktShareDV) is an indicator variable equal to 1 if thefirm’s market share exceeds the median (75th percentile) market share in the firm’s industry in a given year, and 0otherwise. HFI is the annual of sum of squared market shares across all firms in a given industry. MedConcenDV(P75ConcenDV) is an indicator variable equal to 1 if an industry’sHFI exceeds the sample median (75th percentile)HFI in a given year, and 0 otherwise. The models account for other financial characteristics (as shown in Table 3), aswell as indicator variables for time and industry affiliation (Fama and French 1997). Unreported standard errors arerobust to heteroskedasticity and are clustered at the firm level. The p‐values appear in parentheses. For brevity,results for the intercept and the other controls are omitted.���Significant at the 1% level.��Significant at the 5% level.�Significant at the 10% level.

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implications, an additional $1 in inventory is discounted by $0.18 for firms in the fourthquartile of industry‐year market share.

The impact of industry‐level competition on the excess returns–inventoryrelation is also tested. The coefficient estimates for g1 are relatively stable and statisticallysignificant across columns 5–7, and all but one of the measures of industry competition(P75ConcenDVt) are insignificant. Results for the inventory–competition interactionssuggest that the value of inventory is unconditional on the degree of competition in anindustry.

Results in Table 4 suggest that operating conditions affect the wealth effects ofinventory, as stated in H2. Specifically, the operating condition effects appear mainlythrough firm‐level channels, not an industry‐level channel.

Financial Constraints

Table 5 presents estimates for inventory wealth effects after accounting for financialconstraint (H3). The sample sizes depend on the constraint measure. Potential collinearityprecludes inclusion of multiple interactions between the constraint measures andinventory, cash, and receivables. Consequently, equation (1) is estimated separately forconstrained and unconstrained firm‐years. Consistent with prior research, the observedmarginal values of cash and receivables are generally higher for the financiallyconstrained subsamples.

TABLE 5. Wealth Effects of Inventory and Financial Constraints: Robustness.

Independent Variables

Comm. Paper Rating Payout Ratio Firm Size Bond Ratings

C U C U C U C U

DInvi,t 0.391��� �0.103 0.401��� �0.047 0.480��� 0.016 0.382��� �0.900���

(.000) (.446) (.000) (.654) (.000) (.853) (.000) (.000)p‐value (C – U 6¼ 0) .000 .000 .000 .000DCi,t 0.936��� 0.280�� 0.969��� 0.613��� 1.021��� 0.424��� 0.897��� 0.743���

(.000) (.010) (.000) (.000) (.000) (.000) (.000) (.000)p‐value (C – U 6¼ 0) .000 .000 .000 .347DTRi,t 0.677��� 0.616��� 0.800��� 0.673��� 0.980��� 0.385��� 0.674��� 0.421�

(.000) (.000) (.000) (.000) (.000) (.000) (.000) (.093)p‐value (C – U 6¼ 0) .496 .395 .000 .000Full set of controls? Yes Yes Yes Yes Yes Yes Yes YesNo. of observations 28,393 1,290 15,935 9,317 11,525 8,028 26,630 1,633R2 0.295 0.303 0.288 0.231 0.295 0.250 0.295 0.237

Note: This table presents ordinary least squares regressions across groups of financially constrained (C) andunconstrained (U) firms. The dependent variable is excess return, where the Fama and French (1993) size and book‐to‐market portfolio matched returns comprise the benchmark index. DXi,t represents the one‐year change in X (Xt –

Xt–1). DInv is scaled by the lagged market value of equity. Inv is total inventory. C is cash and marketable securities.TR is trade receivables. All models include indicator variables for time and industry affiliation (Fama andFrench 1997). Unreported standard errors are robust to heteroskedasticity and are clustered at the firm level. The p‐values appear in parentheses. For brevity, results for the intercept and the other controls are omitted.���Significant at the 1% level.��Significant at the 5% level.�Significant at the 10% level.

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Results in column 1 indicate a positive and significant relation between excessreturns and inventory for financially constrained firms without a commercial paper rating.However, the relation between excess returns and inventory is insignificant for firm‐yearswith rated commercial paper (column 2). The coefficient estimates for g1 in columns 1 and2 are significantly different at the 1% level. The finding of a significant value premium forinventory held by firms without rated commercial paper is consistent with financiallyconstrained firms having difficulty in mitigating adverse price movements in input pricesand managing demand shocks. When adverse conditions in product markets materialize,managers of constrained firms, absent inventory, forgo sales. Results in Table 5complement findings from Caglayan, Maioli, andMateut (2012) indicating that managersof constrained firms respond to financing constraints by accumulating inventory. Thepresent results suggest that shareholders value this practice.

The influence of financial constraint on the relation between shareholder wealthand inventory is further examined with respect to dividend policy, firm size, and bondrating. Implying that equity holders assign a greater market value to inventory held byfinancially constrained firms, the relation between excess returns and inventory issignificantly higher for the constrained subsamples for each measure of financialconstraint. In fact, the results indicate that inventory reduces shareholder wealth for firmswith bond ratings (column 6). Overall, the results in Table 5 suggest that the influence offinancial constraint on the relation between excess returns and inventory is robust (1) tothemeasurement of financial constraint and (2) after accounting for the impact of financialconstraint on cash and receivables.

Working Capital Behavior

Results in Table 6 provide some evidence of variation in the wealth effects of inventoryafter conditioning on working capital policies (H4). The interaction between DInvt andsales growth is examined first. Shareholder wealth is directly and significantly related toDInvt and SalesGt. Likewise, the interaction DInvt�SalesGt is positively signed andstatistically significant. This finding is consistent with the view that shareholders morehighly value inventory accumulated by firms with rapid sales growth.

Column 2 results indicate a weaker shareholder wealth–inventory relation forfirms with higher lagged cash levels. This finding is consistent with firms with higherprior‐period cash having an improved ability to use internal liquidity to mitigate demandand price shocks that motivate managers to hold inventory. Column 3 results suggest thatthe wealth effects of inventory decrease with prior‐period trade credit obligations. A onestandard deviation increase in TPt–1 reduces the value of an additional $1 of inventory by$0.035 [–0.144�0.241]. The negatively signed coefficient estimate on TPt–1�DInvt isplausible as Petersen and Rajan (1994, 1997) argue that trade credit is a costly source offinancing. A higher receivables balance reduces the value of inventory, which isconsistent with the view that larger balances of uncollected sales coupled with additionalinventory is viewed unfavorably by shareholders.

As expected, the interaction Invt–1�DInvt is negatively signed and statisticallysignificant. This interaction suggests that shareholders discount the value of inventory forfirms with higher prior‐period inventory levels. Given that the average beginning‐of‐year

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inventory‐to‐market‐value‐of‐equity ratio (Invt–1) equals 33%, the coefficient onthe interaction indicates that the value of an additional $1 of inventory is $0.034(–0.102�0.333) lower for the mean firm after conditioning on Invt–1.

An important remaining issue involves whether the efficiency of inventorymanagement influences the relation between shareholder wealth and inventory.11

Managers can reduce operating and financing costs by implementing policies thatimprove inventory cycle times. Subsequently, shareholders may ascribe differentvaluations to inventory conditional on the efficiency with which inventory is managed.Supporting this conjecture, Deloof (2003) finds that operating performance is inverselyrelated to the average number of days inventory outstanding (DIO).

TABLE 6. Wealth Effects of Inventory and Working Capital Behavior.

Independent Variables (1) (2) (3) (4) (5)

DInvi,t 0.368��� 0.424��� 0.447��� 0.458��� 0.514���

(.000) (.000) (.000) (.000) (.000)DInvi,t�SalesGi,t 0.234���

(.008)DInvi,t�Ci,t�1 �0.224�

(.057)DInvi,t�TPi,t�1 �0.144�

(.074)DInvi,t�TRi,t�1 �0.094�

(.056)DInvi,t�Invi,t�1 �0.102���

(.005)SalesGi,t 0.176��� 0.184��� 0.181��� 0.181��� 0.179���

(.000) (.000) (.000) (.000) (.000)Ci,t�1 0.277��� 0.273��� 0.280��� 0.280��� 0.279���

(.000) (.000) (.000) (.000) (.000)TPi,t�1 0.128��� 0.132��� 0.121��� 0.132��� 0.133���

(.000) (.000) (.000) (.000) (.000)TRi,t�1 0.268��� 0.265��� 0.266��� 0.260��� 0.265���

(.000) (.000) (.000) (.000) (.000)Invi,t�1 0.115��� 0.118��� 0.118��� 0.118��� 0.109��

(.000) (.000) (.000) (.000) (.000)Full set of controls? Yes Yes Yes Yes YesNo. of observations 34,351 34,351 34,351 34,351 34,351R2 0.266 0.266 0.266 0.266 0.266

Note: This table presents ordinary least squares regressions examining the wealth effects of inventory afterconditioning on working capital behavior. The dependent variable is excess return, where the Fama and French(1993) size and book‐to‐market portfolio matched returns comprise the benchmark index. DXi,t represents the one‐year change in X (Xt�Xt�1).DInv is scaled by the lagged market value of equity. Inv is total inventory.C is cash andmarketable securities. TR is trade receivables. TP is trade payables. SalesG is the percentage change in sales. Allmodels include indicator variables for time and industry affiliation (Fama and French 1997). Unreported standarderrors are robust to heteroskedasticity and are clustered at the firm level. The p‐values appear in parentheses. Forbrevity, results for the intercept and the other controls are omitted.���Significant at the 1% level.��Significant at the 5% level.�Significant at the 10% level.

11Appreciation is owed to an anonymous reviewer for suggesting this extension to the analysis.

Frictions and the Contribution of Inventory 401

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In untabulated results that are available upon request, this study measuresinventory efficiency by benchmarking the firm’s DIO against breakpoints in the industry‐year distribution of DIO, including the 1st, 5th, 10th, 25th, and 50th percentiles. Indicatorvariables are created with respect to these breakpoints. To assess the impact of inventoryefficiency on the value of inventory, the respective DIO dummy is interacted with DInv.

For each model, the results suggest a direct and significant relation betweenshareholder wealth and DInvt, similar to earlier findings. In general, the inventoryefficiency dummies are not significantly related to excess returns.12 A similar pattern ofinsignificance emerges with respect to the interactions between DInvt and the inventoryefficiency measures. However, the results indicate that shareholders discount the value ofan additional $1 of inventory held for firms with DIO below the industry‐year medianDIO. This finding lends limited support for the view that shareholders value inventoryconditionally on the efficiency of inventory management.

V. Conclusion

This study examines the relation between shareholder wealth and inventory. This relationis of interest because of the benefits and costs associated with inventory. Additional testsprovide evidence on cross‐sectional variation in the relation between shareholder wealthand inventory.

The results are robust and show a direct and statistically significant relationbetween shareholder wealth and inventory. In terms of economic significance, theestimated value of an additional dollar in inventory is less than for a marginal dollar incash and/or receivables, which is consistent with shareholders acknowledging differencesin liquidity across short‐term asset type.

Further evidence suggests substantial cross‐sectional variation in inventorywealth effects. With respect to operating conditions, the relation between excess returnsand inventory is sensitive to industry affiliation, sales variability, and market share. Thewealth effects of inventory are also conditional on financing frictions, as the resultssuggest that shareholders more highly value inventory held by financially constrainedfirms. Last, working capital policies also influence the relation between shareholderwealth and inventory. Overall, the conditional nature of inventory value is consistent withshareholder recognition of frictions that encourage inventory holdings.

The results have implications for managers, shareholders, and lenders, as it iscommonly accepted that minimizing inventory holdings is an optimal working capitalstrategy. However, this strategy is only optimal in a perfect business environment. In thepresence of operating or financing frictions, managers will find some degree of inventorya necessary aspect of working capital policy. The overall finding that shareholders ascribedifferential values to inventory with respect to the frictions faced by the supplier suggeststhat the target level of inventory varies across firms.

12An exception is the DIO dummy that signifies whether a firm has DIO that is less than the industry‐yearmedian. This dummy is positively and significantly related to excess returns.

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Given the observed variation in inventory value, spurious inferences may bedrawn by benchmarking the efficiency of inventory management based solely onindustry‐year comparisons. Consequently, operating conditions, financing frictions, andworking capital levels should be considered when evaluating inventory practices. That is,the appropriate inventory level is conditional on firm characteristics. Ignoring theconditional nature of inventory value may cause suboptimal (1) working capital strategiesto be undertaken by managers, (2) investing decisions by shareholders, and (3) lendingdecisions by financial institutions.

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