[4_1]_2003_Anderson_et_al_Are_selling,_general_and_administrative_costs_sticky

Support the sticky costs hypothesis and the reversal

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Unformatted text preview: equations to ensure identification of the system. The results of estimating this model, ˆ ˆ β 1 = 0.4671 (t -statistic = 11.49) and β 2 = −0.2207 (t -statistic = −4.93), support the sticky costs hypothesis and the reversal of stickiness in subseˆ quent periods (β 4 = 0.0839, t -statistic = 3.54). The coefficients on the contemporaneous and lagged changes in SG&A costs in the second equation ˆ ˆ are significantly positive, γ1 = 1.5285 (t -statistic = 131.53) and γ2 = 0.2284 (t -statistic = 18.27), suggesting SG&A costs positively influence sales. Advertising is a specific discretionary expenditure included with SG&A costs that influences the level of revenue activity. For firms that reported advertising costs separately, we estimated a model that related changes in nonadvertising SG&A costs to changes in revenue in one equation and changes in revenue to changes in advertising costs in a second equation. Results of ˆ estimating this model support the sticky costs hypothesis, β 1 = 0.6298 > 0 ˆ2 = −0.1232 < 0 (t -statistic = −6.56), and the re(t -statistic = 68.77) and β ˆ versal of stickiness in subsequent periods (β 4 = 0.1142, t -statistic = 6.11). Significant and positive coefficients on the contemporaneous and lagged ˆ ˆ advertising change terms, γ1 = 0.2214 (t -statistic = 51.69) and γ2 = 0.1007 (t -statistic = 24.05) support the effect advertising has on current and future sales. 4. Variation in the Degree of Stickiness Hypotheses 3a through 4b describe conditions and circumstances that would affect the degree of stickiness across firms and over time under the STICKY COSTS 59 alternative model of cost behavior. The coefficient on the sticky costs term, β2 in model (I), may be expanded to include the various economic factors described in hypotheses 3a through 4b as follows: β2 = γ0 + γ1 ∗ Successive Decrease i,t + γ2 ∗ Growth i,t + γ3 ∗ log + γ4 ∗ log Employees i,t Revenue i,t Assets i,t Revenue i,t . The Successive Decrease i,t dummy is activated for firm-year observations when revenue declined in the preceding period. The Growth i,t variable is the percentage growth in real gross national product (GNP) during year t . Substituting this relation into model (I) gives: log SG&Ai,t Revenue i,t = β0 + β1 log + γ0 + γ1 ∗ Successive Decrease i,t SG&Ai,t −1 Revenue i,t −1 Assets i,t Revenue i,t + γ2 ∗ Growth i,t + γ3 ∗ log + γ4 ∗ log ∗ log Employees i,t Revenue i,t ∗ Decrease Dummyi,t Revenue i,t + εi,t . Revenue i,t −1 This is restated as model (III), where βk = γk −2 in the expanded version of model (I), k = 2, 3, 4, 5, and 6. Model (III): log SG&Ai,t SG&Ai,t −1 = β0 + β1 log Revenue i,t Revenue i,t + β2 ∗ Decrease Dummyi,t ∗ log Revenue i,t −1 Revenue i,t −1 + β3 ∗ Decrease Dummyi,t ∗ log Revenue i,t ∗ Successive Decrease i,t Revenue i,t −1 + β4 ∗ Decrease Dummyi,t ∗ log Revenue i,t ∗ Growth i,t Revenue i,...
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