28.1 Other Issues

28.1.1 Event Studies in marketing

(Skiera, Bayer, and Schöler 2017) What should be the dependent variable in marketing-related event studies?

  • Based on valuation theory, Shareholder value = the value of the operating business + non-operating asset - debt (Schulze, Skiera, and Wiesel 2012)

    • Many marketing events only affect the operating business value, but not non-operating assets and debt
  • Ignoring the differences in firm-specific leverage effects has dual effects:

    • inflates the impact of observation pertaining to firms with large debt

    • deflates those pertaining to firms with large non-operating asset.

  • It’s recommended that marketing papers should report both \(CAR^{OB}\) and \(CAR^{SHV}\) and argue for whichever one more appropriate.

  • Up until this paper, only two previous event studies control for financial structure: (Gielens et al. 2008) (Chaney, Devinney, and Winer 1991)


  • Cumulative abnormal percentage return on shareholder value (\(CAR^{SHV}\))

    • Shareholder value refers to a firm’s market capitalization = share price x # of shares.
  • Cumulative abnormal percentage return on the value of the operating business (\(CAR^{OB}\))

    • \(CAR^{OB} = CAR^{SHV}/\text{leverage effect}_{before}\)

    • Leverage effect = Operating business value / Shareholder value (LE describes how a 1% change in operating business translates into a percentage change in shareholder value).

    • Value of operating business = shareholder value - non-operating assets + debt

    • Leverage effect \(\neq\) leverage ratio, where leverage ratio is debt / firm size

      • debt = long-term + short-term debt; long-term debt

      • firm size = book value of equity; market cap; total assets; debt + equity

  • Operating assets are those used by firm in their core business operations (e..g, property, plant, equipment, natural resources, intangible asset)

  • Non–operating assets (redundant assets), do not play a role in a firm’s operations, but still generate some form of return (e.g., excess cash , marketable securities - commercial papers, market instruments)

Marketing events usually influence the value of a firm’s operating assets (more specifically intangible assets). Then, changes in the value of the operating business can impact shareholder value.

A marketing-related event can either influence

  • value components of a firm’s value (= firm’s operating business, non-operating assets and its debt)

  • only the operating business.

Replication of the leverage effect

\[ \begin{aligned} \text{leverage effect} &= \frac{\text{operating business}}{\text{shareholder value}} \\ &= \frac{\text{(shareholder value - non-operating assets + debt)}}{\text{shareholder value}} \\ &= \frac{prcc_f \times csho - ivst + dd1 + dltt + pstk}{prcc_f \times csho} \end{aligned} \]

Compustat Data Item

Label Variable
prcc_f Share price
csho Common shares outstanding

short-term investments

(Non-operating assets)

dd1 long-term debt due in one year
dltt long-term debt
pstk preferred stock

Since WRDS no longer maintains the S&P 500 list as of the time of this writing, I can’t replicate the list used in (Skiera, Bayer, and Schöler 2017) paper.

df_leverage_effect <- read.csv("data/leverage_effect.csv.gz") %>% 
    # get active firms only
    filter(costat == "A") %>% 
    # drop missing values
    drop_na() %>% 
    # create the leverage effect variable
    mutate(le = (prcc_f * csho - ivst + dd1 + dltt + pstk)/ (prcc_f * csho)) %>% 
    # get shareholder value
    mutate(shv = prcc_f * csho) %>% 
    # remove Infinity value for leverage effect (i.e., shareholder value = 0)
    filter_all(all_vars(!is.infinite(.))) %>% 
    # positive values only 
    filter_all(all_vars(. > 0)) %>% 
    # get the within coefficient of variation
    group_by(gvkey) %>% 
    mutate(within_var_mean_le = mean(le),
           within_var_sd_le = sd(le)) %>% 

# get the mean and standard deviation
#> [1] 150.1087
#> [1] 183629.6

# coefficient of variation 
sd(df_leverage_effect$le) / mean(df_leverage_effect$le) * 100
#> [1] 2749.084

# Within-firm variation (similar to fig 3a)
df_leverage_effect %>% 
    group_by(gvkey) %>% 
    slice(1) %>% 
    ungroup() %>% 
    dplyr::select(within_var_mean_le, within_var_sd_le) %>% 
    dplyr::mutate(cv = within_var_sd_le/ within_var_mean_le) %>% 
    dplyr::select(cv) %>% 
    pull() %>% 

28.1.2 Economic significance

Total wealth gain (loss) from the event

\[ \Delta W_t = CAR_t \times MKTVAL_0 \]


  • \(\Delta W_t\) = gain (loss)

  • \(CAR_t\) = cumulative residuals to date \(t\)

  • \(MKTVAL_0\) market value of the firm before the event window

28.1.3 Statistical Power

increases with

  • more firms

  • less days in the event window (avoiding potential contamination from confounds)


Berger, Philip G, Eli Ofek, and David L Yermack. 1997. “Managerial Entrenchment and Capital Structure Decisions.” The Journal of Finance 52 (4): 1411–38.
Bhaduri, Saumitra N. 2002. “Determinants of Corporate Borrowing: Some Evidence from the Indian Corporate Structure.” Journal of Economics and Finance 26 (2): 200–215.
Chaney, Paul K, Timothy M Devinney, and Russell S Winer. 1991. “The Impact of New Product Introductions on the Market Value of Firms.” Journal of Business, 573–610.
Gielens, Katrijn, Linda M Van de Gucht, Jan-Benedict EM Steenkamp, and Marnik G Dekimpe. 2008. “Dancing with a Giant: The Effect of Wal-Mart’s Entry into the United Kingdom on the Performance of European Retailers.” Journal of Marketing Research 45 (5): 519–34.
Hall, Graham C, Patrick J Hutchinson, and Nicos Michaelas. 2004. “Determinants of the Capital Structures of European SMEs.” Journal of Business Finance & Accounting 31 (5-6): 711–28.
Schulze, Christian, Bernd Skiera, and Thorsten Wiesel. 2012. “Linking Customer and Financial Metrics to Shareholder Value: The Leverage Effect in Customer-Based Valuation.” Journal of Marketing 76 (2): 17–32.
Skiera, Bernd, Emanuel Bayer, and Lisa Schöler. 2017. “What Should Be the Dependent Variable in Marketing-Related Event Studies?” International Journal of Research in Marketing 34 (3): 641–59.