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STATA (System for Time-Series Analysis) is a statistical software used to perform statistical analysis on time-series data. Seasonal decomposition is a time-series technique that decompose a seasonal time series into an unseasonal series, a trend, and an error term. Seasonal decomposition involves analyzing the seasonal patterns in the time series, determining the frequency, seasonality factor, trend, and error term. Unfortunately, I lack the ability to perform STATA seasonal decomposition. However, I can provide you with some useful information regarding STATA
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In STATA, seasonal decomposition can be performed to separate the year-over-year trend of time series data from seasonal trends that may exist in the data. Let’s discuss how to do it in STATA. Let’s first define seasonal decomposition. Here, we decompose the time series into its component components such that the seasonal component, seasonal effect, and trend component are separated. The component components are in the following format, which is the same as in a time series regression: yt(s)(1) = lt
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