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M/XMix Effects
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2 percent to EUR 685 (522) million, mainly on the back of positive volume and mix effects as well as optimized product costs.
Operating profit in the first half-year rose to EUR 299 (268) million year-on-year as a result of mix effects.
For Louisiana and Montana the industry mix effects were negative, indicating that their exports were relatively more concentrated in industries whose exports were rising less than the national average for all manufacturing exports.
Generally speaking, the destination and industry mix effects were equally important but not necessarily in the ways one might expect.
In classic shift-share models a state's net relative change is separated into an industry mix effect and a competitive effect.
Using the classic shift-share model, the change in a state's manufacturing exports is separated into a national growth effect, an industry mix effect, and a competitive effect.
The purpose of the shift-share analysis is to dissect the year-to-year change in the female-male differential into three components: national share effect, industry mix effect, and employment shift effect.
If employment in female-male-dominated industries, as appears indicated in table 1, the industry mix effect will reduce the unemployment rate of women relative to that of men.
It is assumed that men and women who "enter" employment as a result of the industry mix effect come from the unemployment pool and from outside the labor force in the same proportions as they actually did during the previous year.
The industry mix effect shows how differing industry growth rates affect the female-male unemployment rate differential when there are different percentages of men and women in each industry.