OECD Adult education level data analysis 7 - Time series analysis, serial correlation, cochrane-orcutt estimation using R

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This post is following of the above post. In the previous post, I did time-series regression with differenced data and found these models are not valid. So, I will do with level data and time trend.

p-value is almost 0 and TRY is statistically significant. The Estimate of TRY is 0.0167.

If men_women and trend is fixed, one point TRY increase associates 0.0167 l_usd_cap inclease.

For time- series regression, it is better to check serial correlation. So, let's check it.

L(residual) is statistically significant. So, there is serial correlation of residuals.

If there is serial correlation, Cochrane-Orcutt estimation is betther than OLS estimation.

I use cochrane.orcutt() frunction from orcutt package.

p-value is almost 0 and this mdel is valid. But TRY is not statisitically significant.

So, with USA time series data, I cannot say TRY and men_women are associated with l_usd_cap.

That's it. Thank you!

Next post is



To read from the 1st post,