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The value is said to be the trend value of the process at time t.
For example, assume that the growth of labor productivity is the same as that in the trend and that current productivity equals its trend value:
In this type of study, trend values of consumption and income are collected over a long period of time so that most cyclical fluctuations are smoothed out.
Permanent consumption and permanent income are long-run trend values of consumption and income, so the hypothesis is consistent with long-run time-series data (like that collected by Kuznets) which suggests that the apc is constant.
Therefore, we finalize our estimate for the annual mean growth rate of the previous year in March, by using the average of the most recent November-February months, corrected for the average seasonal cycle, as the trend value for January 1.
The annual mean growth during the previous year is determined by taking the average of the most recent December and January months, corrected for the average seasonal cycle, as the trend value for January 1, and then subtracting the same December-January average measured one year earlier.
A level of statistical certainty, S, may now be selected - 95% confidence is typical; 99% would be stricter, 90% looser - and the following question can be asked: what is the borderline trend value V that would result in S% of trends being between V and +V?
For this, the set of 100,000 generated series would be replaced by 100,000 series constructed by randomly shuffling the observed data series; clearly such a constructed series would be trend-free, so as with the approach of using simulated data these series can be used to generate borderline trend values V and V.