Global Journal of Management and Business Research, D: Accounting and Auditing, Volume 21 Issue 2

Table 4: Parameter Estimates Relating Overhead Costs to Multiple Cost Drivers (Daily Data) (White's adjusted statistics in parentheses) Model 2: ILCOST t = γ 0 + γ 1 DLCOST t + γ 2 NUMSETUPS t + γ 3 NUMPARTS t Variable Sheet Metal (n=1365) Machine Shop (n=1423) Brush & Steel Wool (n=1314) Paint Shop (n=1302) Component Assembly (n=1368) Welding (n=1327) Final Assembly (n=1391) Intercept 47.06 (22.22) ** 22.75 (0.58) 12.28 (1.54) 114.28 (48.91) ** 86.64 (6.00) ** 72.42 (7.54) ** 24.84 (0.34) DLCOST 0.09 (34.52) ** 0.11 (55.85) ** 0.05 (9.26) ** 0.11 (95.69) ** 0.08 (33.29) ** 0.07 (62.96) ** 0.06 (33.53) ** NUMSETUPS 3.40 (222.64) ** 6.99 (31.49) ** 6.66 (108.43) ** 1.10 (1.38) 5.41 (32.70) ** 2.33 (29.76) ** 2.62 (9.75) ** NUMPARTS 0.78 (4.90) * 1.66 (1.01) 8.07 (26.10) ** 0.67 (13.98) ** 1.38 (1.55) 3.02 (27.72) ** 4.73 (7.39) ** Adj. R 2 0.78 0.51 0.33 0.15 0.18 0.30 0.09 P(Model) P(Multiple Drivers: γ 2= γ 3=0 ) 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 Durbin-Watson Statistic Before Prais-Winsten Correction After Prais-Winsten Correction 1.67 * 2.01 1.43 ** 1.98 1.07 ** 2.11 1.62 * 2.01 1.64 ** 2.02 1.69 * 2.01 1.65 * 2.04 ILCOST = Indirect Labor Cost DLCOST = Direct Labor Cost NUMSETUPS = Number of Setups NUMPARTS = Number of Distinct Parts * indicates significant at the 5% level. ** indicates significant at the 1% level. a) Sensitivity Analysis Models 1 and 2 are misspecified if their maintained assumption of linearity (albeit, weaker than the testable assumption of proportionality) is not valid. In addition, as in Noreen and Soderstrom (1994), our linear models are likely to have heteroskedastic residuals. Furthermore, tests based on the Box-Cox (1964) transformation (Greene 2011) reject the linear specification, but not the loglinear specification, of both models for all seven departments. Therefore, in keeping with Noreen and Soderstrom (1994) and Banker et al. (1995), we also estimated loglinear model after logarithmic transformation of the variables. 5 We employed Belsley, Kuh and Welsch (1980) collinearity diagnostics to examine multicollinearity between independent variables. Both the condition index and VARPROP are above the cutoffs suggested by Belsley, Kuh and Welsch (1980) for all seven regressions, indicating a very high degree of Consistent with the linear model (results not shown here), NUMSETUPS is significant for six and NUMPARTS for all seven departments. 5 We also estimated two other models: one linear and the other loglinear, with labor hours instead of costs as the two variables. The results (not shown here) remain qualitatively the same multicollinearity. As a result, coefficient estimates are sensitive to small model changes, although they are unbiased. Since collinearity is a data problem, we examined the robustness of our results with different subsets of sample data. We re-estimated both models separately for each of the five years covered by our data set for each of the seven departments. DLCOST has a significant and positive coefficient in 27, NUMSETUPS in 28, and NUMPARTS in 20 out of the 35 estimated regressions. The joint test of γ 2= γ 3=0 is rejected in only 3 of the 35 regressions. These results provide additional support for the significance of multiple cost drivers. We also examined the impact of extreme and influential observations using the criteria outlined in Belsley, Kuh and Welsch (1980). We computed the RSTUDENT, COV, DFFITS and h metrics. We classified observations as influential if two or more of the computed metrics exceeded the cutoff values suggested by Belsley, Kuh and Welsch (1980), deleted them from the sample and re-estimated both models for all departments. This procedure did not lead to any appreciable change in the results. b) Aggregating Costs and Activities on a Monthly Basis Because our focus is on indirect labor costs within each production department, and because production cycle times in all departments are 9 Global Journal of Management and Business Research Volume XXI Issue II Version I Year 2021 ( ) D © 2021 Global Journals Cost Hierarchy: Evidence and Implications