Table 4 |
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|
Results of regression for advertising time or space |
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|
Number of observations = 214 |
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|
Adjusted r2 = 0.6116 |
F statistic = 56.90 |
P of F statistic < 0.0001 |
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|
Variable |
Coefficient |
SE (Robust)* |
T (Robust)* |
P (Robust)* |
|
|
||||
|
ln GDP per capita |
-0.592 |
0.0967 (0.1310) |
-6012 (-4.52) |
0.000 (0.000) |
|
ln of population in service area |
0. 425 |
0.0461 (0.0482) |
9.20 (8.81) |
0.000 (0.000) |
|
Dummy if costs are for TV |
2.215 |
0.2559 (0.2705) |
8.66 (8.19) |
0.000 (0.000) |
|
Dummy if costs are for newspaper |
2.055 |
0.2286 (0.2093) |
8.99 (9.82) |
0.000 (0.000) |
|
Dummy for Eastern Europe |
-8.668 |
4.1304 (4.1141) |
-2.10 (-2.11) |
0.037 (0.039) |
|
Dummy for Eastern Europe * ln GDP per capita |
1.0670 |
0.4688 (0.4673) |
2.28 (2.28) |
0.024 (0.026) |
|
Constant |
-5.1640 |
1.1805 (1.4728) |
-4.37 (-3.51) |
0.000 (0.001) |
|
|
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|
*The results as reported after a robust and country clustering are reported in the parenthesis. Dependent variable: log ratio of price of media and advertising to GDP per capita Breusch-Pagan test of heteroskedasticity: 1.91 (p = 0.1667 (Chi2)). VIF test for multicollinearity is not appropriate for this model due to the inclusion of interaction variables. |
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|
Johns et al. Cost Effectiveness and Resource Allocation 2006 4:8 doi:10.1186/1478-7547-4-8 |
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