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Transportation Industry…Cost Structure, Stock Return structures, other control variables shown to be important in previous studies and returns variability measured by the firm’s beta. The variables and model are as follows. Control Variables Including controls allows their effects to be separately estimated from the effects of other independent variables and reduces the likelihood that they may be surrogates for alternative determinants of the dependent variable. The following control variables are included in this study. lnMVEit: Fama and French (1993) showed that smaller capitalization stocks outperform large capitalization stocks. Keim (1983) earlier showed, however, that most of the negative relationship between market value of equity and abnormal returns occurs in January. Although the relationship is slightly negative over the following eleven months the relationship is unstable, with even a few months in the 1963-1979 research period displaying significant positive relationships. We control for size by including the firm’s end of fiscal year market value of equity. We measure this variable as number of common shares outstanding multiplied by price per share. Since inconsistent variances violate the OLS constant variance assumption, we attempt to mitigate this outcome by using the log of market value of equity, i.e., lnMVEit. LEVit: As mentioned above financial leverage has been shown to be correlated with beta. We include financial leverage and measure this variable as each firm’s end of fiscal year total longterm debt scaled by its end of fiscal year total assets. TURNit: Denis and Kadlec (1994) showed that beta estimates are significantly related to changes in trading activity. Cremers and Mei (2007) assert that share turnover and systematic risk are related. To assess the impact of share turnover on returns variance for the firms of our study, TURNit, defined as the average daily share volume divided by the average shares outstanding, is included in the regression. lnSHOLDit: Using a CAPM framework, Amihud and Mendelson (1989) provide evidence that asset returns increase with their illiquidity as measured by the bid-ask spread. O’Hara (2003) argues that liquidity is priced by the market. Chordia, et al. (2001) showed a statistically significantly negative relationship between stock returns and variability of liquidity. Since shares which are thinly held may be subject to larger bid-ask price spreads and hence reduced liquidity, we control for this potential effect by including the log of the number of total common shareholders for each firm, at end of fiscal year t. MBit: Fama and French (1993) showed that beta and book-to-market are positively correlated and included this ratio in their model. We add market-to-book ratio to our model and measure this variable as the firm’s end of fiscal year market value divided by its end of fiscal year book value. YEAR: Campbell and Hentschel (1992) provide evidence that expected returns and stock return volatility change over time. Year dummy variables are used to control for temporal variation of betas across the years of this study. Variables of Interest BETAit: Month-end closing prices are used to measure the sensitivity of a firm’s stock price to changes in the S&P 500 index. Using monthly returns, beta is calculated for a five year time period. If less than five years of data is available then beta is calculated for as few as 24 months. ASBBS E-Journal, Volume 4, No.1, 2008 124
MacArthur, Houmes and Stranahan OLit: Two alternative measures are used as proxies for operating leverage: the ratio of changes in operating income to changes in sales and the ratio of fixed asset to total stockholders equity. Model Ordinary Least Squares is used to estimate the following model. BETAit = α0 + α1 lnMVEit + α2LEVit + α3TURNit + α4lnSHOLDit + α5MBit + α6YEAR + α7OLit + εit Results The results are shown in Table 1 except for the year dummies. TABLE 1: BETA REGRESSED ON CONTROL VARIABLES AND TWO ALTERNATIVE OPERATING LEVERAGE PROXY VARIABLES N = 121 Proxy Variables Used to Measure Degree of Operating Leverage Independent variable Regression #1 Fixed assets to total stockholders equity Regression #2 ∆ operating income / ∆ sales constant .185 .235 (.680) (.605) lnMVEit .044 .067 (.260) (.075) LEVit -.166 -.191 (.605) (.559) TURNit -.629 -1.582 (.969) (.922) lnSHOLDit .030 .022 (.336) (.487) MBit .022 -.001 OLit (.118) (.934) .014 (.019) Adjusted R 2 .071 F 1.769 p-values are in parentheses. p-values for OL are one tailed. .020 (.044) .060 1.924 Only a few of the variables are significant in these preliminary regression results. The coefficient of the size variable, lnMVE, is positive in both regressions but only in Regression #2 is there evidence of a positive relationship at the
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ASBBS eJournal Volume 4, No.1, 2008
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THE SUPREME COURT GRANTS CERTIORARI
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Deductibility of investment fees…
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Mellon Bank, N.A. v. United States,
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Browning email and document exchang
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Browning VirtualOfficeInternational
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Dhareshwar and Bacon study as it is
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Fekula and Hornyak of qualit y rese
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Fekula and Hornyak Cumulative % of
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Fekula and Hornyak 3 Figure 3 allow
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Fekula and Hornyak WA St Louis 4.1
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Fekula and Hornyak VA Commonwealth
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Grady, Maniam and Leavell economic
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Grady, Maniam and Leavell Financial
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Grady, Maniam and Leavell security
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Grady, Maniam and Leavell Berghel,
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Mining for Knowledge..Higher Ed sho
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Mining for Knowledge..Higher Ed hea
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Mining for Knowledge..Higher Ed Ano
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Mining for Knowledge..Higher Ed Sol
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Kehoe and Whitten of no trust betwe
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Kehoe and Whitten economies. So why
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Kehoe and Whitten system. Two facto
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Page 151 and 152: ABSTRACT Major trends in hotel gues
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Growth …Analysis of Harley-Davids
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FIRM EXPANSION AND REGIONAL DEVELOP
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INNOVATIVE HRM: HOW HR ACTIVITIES C
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strategy implementation best. It se
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Innovative HRM It must be noted tha
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approach to compensation does not o
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Allied Signal, Dupont, Honeywell, B
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Figure 5: General Schemata of BSC:
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Innovative HRM where open communica
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Zomorrodian, A (1999) “Learning O
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