Time series plots of differenced economic indicators, each with a p-value indicating the significance of a statistical test, likely a unit root test such as the Augmented Dickey-Fuller (ADF) test. Here’s an analysis of what each plot represents:
Differenced logan_passengers: This plot shows the changes in the number of passengers over time after differencing the data (likely to achieve stationarity). The p-value suggests that the differenced series is stationary (p < 0.05).
Differenced logan_intl_flights: Like the passengers’ plot, this shows the changes in the number of international flights. The p-value is above the common threshold of 0.05, suggesting that the series may not be stationary.
Differenced hotel_occup_rate: This graph displays the changes in the hotel occupancy rate over time. The p- value is 0.0000, which is highly significant and indicates stationarity of the differenced series.
Differenced hotel_avg_daily_rate: Shows the changes in the average daily rate for hotels. The p-value again indicates that the differenced series is stationary.
Differenced total_jobs: This represents the changes in the total number of jobs. The p-value is not below the 0.05 threshold, suggesting non-stationarity.
Differenced unemp_rate: The changes in the unemployment rate over time are plotted here. The p-value is greater than 0.05, suggesting that the series may not be stationary.
Differenced labor_force_part_rate: Shows the changes in the labor force participation rate. The p-value is close to the threshold, which could suggest marginal stationarity depending on the specific significance level you are using.
In each plot, the time series data have been different, which is a common technique to remove trends and seasonal patterns to achieve stationarity in time series analysis. Stationarity is an important assumption in many time series models, and the ADF test is often used to test for it. The low p-value (typically <0.05) in the ADF test suggests that the null hypothesis of the presence of a unit root can be rejected, implying stationarity.