Dear all
Given that I have 8 years data of labor working hours variable , how can I determine the initial value of this variable in steady state?
Best
Heidar

Do you mean the actual steady state? Or the initial value for steady state finding? Also, units of time are rather arbitrary in the model, so the question is how you match the data to the model.

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yes.i mean the actual steady state (N_bar)

Then my question applies how you match the data to the model. Hours in the data are usually aggregate hours, while in the model there is a normalized time endowment.

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I have the annual data of the average weekly work hours of eight years. Based on this data, I can calculate the normalized work time of each year. I want to know how I can determine the value of these normalized work time in the steady state.

Usually, you would say that the average over the sample is the steady state.

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Is it also correct that the intercept © in the regression (x=c+r*@trend) is the value of variable x in the steady state?

Why would there be a trend in hours per capita?

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Due to the increase in employees and the lack of job opportunities for more work in the considered period, the annual data of the average weekly work hours have a decreasing trend.

Lack of job opportunities sounds like a cyclical phenomenon, not a trend.

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So it’s best to use the average according to your recommendation. Which one is most commonly used, the arithmetic mean or the geometric mean? Is there a reference for this?

If it’s not an index, use the arithmetic mean. If you think your sample average does not correctly reflect your steady state, you can only try to estimate the steady state or use economic theory to pin it down.

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Considering that the amount of weekly work time in each year is the average of weekly working time of all employees in a year. For calculate the average of annual weekly working time (8 years) should i use geometric mean?

I have never seen anyone use the geometric mean in this case, but any differences to the arithmetic one should be negligible.

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