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One of the disadvantages of using the Laspeyre index is that as prices rise, quantities purchased tend to fall of (which is true) if there are alternatives available. This decrease is not reflected in the Laspeyre index which tends to overstate the effect of rising prices.
I don’t understand this last statement
Laspeyre assumes that the quantities purchased stay the same.
However if prices go up people are likely to buy less of the things that go up the most and therefore the overall effect on the cost of their shopping basket is likely to be smaller than is shown by Laspeyre.
When the trend is increasing or decreasing, additive seasonal components change in their importance relative to the trend whereas multiplicative components remain in the same proportion to the trend.
What does this mean and why exactly is the multiplicative model preferred when the trend is sharply increasing ?
Also, if the trend is increasing sharply, under the multiplicative model, the seasonal variation is also unexpected to increase in proportion to the trend unlike the additive model. However, what is the logic that if the trend increases, the seasonal variation should change too?
This is a question about time series analysis, not about Laspeyre. If it is a new topic, then in future please start a new thread.
Suppose this year we have a trend of 100 and an actual of 110 – so a seasonal variation of 10.
Suppose next year the trend is100. Although it is not a rule, it is surely quite likely that if sales are so much bigger then the seasonal variation is likely to be bigger as well?
(Have you watched the free lecture on time series analysis?)
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