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Firm-supplier relations and managerial compensation

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Abstract

In this paper we examine customer firms’ managerial compensation policies when they have important supplier relations. We show that firms with greater reliance on their suppliers tend to offer higher total- and equity-based pay but lower risking-taking incentives to its top executives. Our results are consistent with the argument that suppliers making firm-specific investments are concerned about the customer firm’s prospects. Therefore, firms with important supplier relations use the compensation policies of their top executives (more equity-based and less risk-taking) to signal their commitment to a stable and promising performance in the future. To address endogeneity issues arising out of time-varying omitted variables, we exploit a 2SLS procedure to supplement our baseline OLS findings. Our results are robust alternate measures of suppliers’ relationship-specific investments and econometric models. Overall, our results indicate that some of the heterogeneity in managerial compensation can be attributed to characteristics of the firm’s supply-chain relations.

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Notes

  1. In our sample, customer firms are, on average, twenty times larger than their suppliers.

  2. See Joskow (1988, 2005).

  3. Kale et al. (2012) argue that suppliers’ and customers’ RSIs will be undermined when the firm undertakes risky projects, and document a negative relation between risk-taking incentives of the CEO and RSIs.

  4. Consistent with this argument, Chen et al. (2012) find that firms with a unionized labor force undertake less risky projects and are associated with lower bond yields.

  5. Eshleman and Guo (2014) find that quarterly earnings announcements of supplier firms contain information about their customer’s earnings.

  6. As in Fee et al. (2006), we acknowledge that the 10% sales threshold and voluntary disclosure (by other reported customers) may lead to a non-random sample of customers. However, since the selection is based on the level of an exogenous explanatory variable, OLS estimates are consistent under reasonable assumptions. See Wooldridge (2010) for a discussion of exogenous sampling.

  7. We repeat our main tests using only firm-years with a single reported supplier and find qualitatively similar results.

  8. The variable Supp. Importance is constructed in almost exactly the same manner as in Banerjee et al. (2008). The only difference is that they additionally scale COGS by the industry level proportion of material cost to total cost (material + labor). We do not follow this scaling to avoid losing firms in the non-manufacturing sector.

  9. The figures are the mean (median) values of the variable Supplier Sales Dependence; See Table 2: Panel A in their paper.

  10. The variable Prop LT is in line with the “incentive” variable in Harvey and Shrieves (2001) who study the relation between incentives and corporate governance choices. Frye (2004) uses a similar measure to examine the effect of equity-based employee compensation on firm performance.

  11. We use the percentage of stock ownership at the beginning of the year for each executive to obtain the stock-based sensitivity of an executive’s equity portfolio. For option holdings, we use the number of options held by the manager at the beginning of the year, to represents option grants made in prior years. Since the proxy statement does not provide the exercise prices for these options, we follow the methodology in Core and Guay (2002) and determine an average exercise price for all previously granted options based on their year-end intrinsic value. We treat all options held at the beginning of the year as a single grant with a 5-year time to maturity. The risk-free rate is the 5-year Treasury bill constant-maturity series from the Federal Reserve Bank’s official website, and the dividend yield from ExecuComp. Stock return volatility is the annualized standard deviation of 60 monthly stock returns prior to the sample year and requires at least 12 usable consecutive monthly returns. Using the above information, we compute the average delta of prior option grants using the modified Black–Scholes formula.

  12. These figures are comparable with the mean values of supplier (7.23%) and customer (3.64%) R&D intensities reported in Table 1, Panel A by Fee et al. (2006).

  13. Implicit in our interpretation is the premise that CEOs can influence the size as well as the composition of their pay.

  14. The construction of this variable is described in the Data Appendix.

  15. Other studies examining the effect of supplier characteristics on corporate policy rely on a similar argument (Banerjee et al. 2008), Kale and Shahrur (2007), and Raman and Shahrur (2008). In all these studies, the firm policy variable is the dependent variable and supplier relation is an explanatory variable. A more recent study in this regard is Chen and Liao (2017) which explores the effect of uncertainty in the production efficiency of a firm’s customers’ and suppliers’ on its bond yield spreads.

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Author information

Authors and Affiliations

  1. D’Amore-McKim School of Business, Northeastern University, Boston, MA, 02115, USA

    Tiantian Gu & Anand Venkateswaran

  2. Indian Institute of Management - Bangalore, Bangalore, India

    Anand Venkateswaran

Authors
  1. Tiantian Gu
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  2. Anand Venkateswaran
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Corresponding author

Correspondence to Anand Venkateswaran.

Additional information

We are grateful for Tor-Erik Bakke, Olubunmi Faleye, Karthik Krishnan, Husayn Shahrur, and seminar participants at the Financial Management Association (2013) for several useful comments. We are solely responsible for any errors.

Data Appendix

Data Appendix

This Appendix defines all the variables used in the study. The data items taken from Compustat are denoted by their variable names. All returns data are from the Center for Research in Security Prices (CRSP). The Compensation related variables are from Compustat’s ExecuComp. Joint Venture and Strategic Alliance variables are from SDC’s Mergers and Acquisitions database. CEO Network data is from BoardEx. Institutional Ownership is obtained from Thomson Reuters 13F filings.

Variable

Definition

Compensation and incentives related

 Short-term compensation (ST Comp)

Salary + bonus + other annual payments

 Long-term compensation (LT Comp)

Restricted stock grants + B–S value of options granted + long-term incentive payouts + total other annual payments

 CEO Total Compensation

Short-term compensation + Long-term compensation

 CEO PPS (per $100)

(Shares owned at the beginning of the year + Average delta of prior option grants × Number of options)/Number of shares outstanding × 100

 Ln(Tot Comp)

Ln(CEO total compensation)

 Prop LT

CEO LT Comp/CEO total compensation

 OTH PPS (per $100)

Mean of (shares owned at the beginning of the year + average delta of prior option grants × number of options)/number of shares outstanding × 100), of other execs

 Ln(OTH Tot Comp)

Ln(Mean of (total compensation)), of other executives

 OTH Prop LT

Mean of (LT Comp/total compensation), of other executives

 CEO Delta

10−6 times the dollar sensitivity of CEO firm-specific wealth (option and stockholdings) to 1% change in the firm’s stock price.

 CEO Vega

10−6 times the dollar sensitivity of CEO firm-specific wealth (option and stockholdings) to 0.01 change in the firm’s stock return volatility

Relation-specific invest ments related

 Supplier R&D

Max (XRD,0)/lag (AT)

 Cust. Sale

$ value of sale by a supplier to firm

 Customer COGS

Customer firm’s cost of goods sold (COGS)

 Supp. Importance

Customer Sale/Customer COGS

 Number of Suppliers (s)

Number of reported suppliers associated with each customer firm

 Supp. RSI (Firm-Supplier Pair Level)

Supp. Importance × Supplier R&D

 Supp. RSI (Firm level)

Sum of (Supp. RSI) for each firm-year across all reported suppliers

 Supplier Industry Input Coefficient

Sale by supplier to firm’s I–O industry/total purchases by firm’s I–O industry (including Compensation of Employees and excluding purchases from its own industry)

 Industry R&D

Sum of (Max(XRD,0))/Sum of (AT) for all firms in Compustat for each I–O industry)

 Supplier Industries R&D (Industry Level)

Sum of (supplier industry input coefficient × industry R&D) across all supplier I–O industries for the firm’s I-O industry

 JV/SA Dummy (Firm-Supplier Pair Level)

Dummy = 1 if the two firms are listed as participants from the SDC strategic alliance and joint venture database during the sample period, 0 otherwise

Main Independent Variables

Definition

Ln (CEO Tenure)

Ln (Number of years as CEO up to sample year)

Chairman

Dummy = 1 if CEO is also the Chairman of the Board, 0 otherwise

New CEO

Dummy = 1 if the CEO is in her first year in that position, 0 otherwise

Lag Ln(Sales)

Ln(Lag Sales for firm)

S&P 500

Dummy = 1 if firm is in S&P 500 Index, 0 otherwise

Lag Book to Mkt.

Lag (AT/(AT − CEQ + PRCC_F × CSHO)

Stk Return

Annualized return based on 12 monthly returns prior to sample year

Variable

Definition

ROA-CGL

Return on assets (IB/AT) based on Core–Guay–Larcker (2008)

SD Returns

Std. dev. of 12 monthly returns preceding sample year

R&D to Assets

Max(XRD,0)/Lag (AT)

Missing R&D

Dummy = 1 for all obs. where missing value for XRD is replaced with 0, 0 otherwise.

Ind. Concentration

Sales based Herfindahl index calculated based on all firms in Compustat in the firm’s 2-digit SIC industry

Instrumental variables

 

 Supp. Share (a)

Cust. sale/sum of (Cust. sale), across reported suppliers for a customer

 Cust. Importance (b)

Cust. sale/supplier’s total sales

 Cust. Importance Wt. Supp.  Share (c = a × b)

Cust. importance × Supp. share

 Share Wt. Cust. Importance

Sum of (Cust. importance × Supp. share), across all reported suppliers

 Industry Mean Supp. RSI

Sum of (Average R&D/TA in each supplier’s 2-digit SIC industry × Supp. Importance), across all reported suppliers

Subsamples

 

 Wt. C–S Distance

Supp. Importance × Ln(distance between firm’s and supplier’s headquarters in miles)

 Manufacturing

All observations in the firm’s 2-Digit SIC codes (20–39)

 Market Share

Market share of customer firm’s sales in the 2-digit SIC industry

 Institutional Ownership

The average percentage of outstanding common stock held by institutional investors in the prior year. Firms in the top (bottom) quartile of Institutional Ownership in each year are classified as High and Low, respectively.

 CEO Network

The number of individuals with whom the CEO shares a common educational, employment, or social history in BoardEx excluding those individuals connected to him solely via his position as CEO of his own firm.

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Gu, T., Venkateswaran, A. Firm-supplier relations and managerial compensation. Rev Quant Finan Acc 51, 621–649 (2018). https://doi.org/10.1007/s11156-017-0683-4

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