Abstract
We develop a statistical testing procedure to examine whether the curve-valued time
series of interest is integrated of order d for a nonnegative integer d. The proposed procedure can distinguish between integer-integrated time series and fractionally-integrated ones, and it has broad applicability in practice. Monte Carlo simulation experiments show that the proposed testing procedure performs reasonably well. We apply our methodology to Canadian yield curve data and French sub-national age-specific mortality data. We find evidence that these time series are mostly integrated of order one, while some have fractional orders exceeding or falling below one.
series of interest is integrated of order d for a nonnegative integer d. The proposed procedure can distinguish between integer-integrated time series and fractionally-integrated ones, and it has broad applicability in practice. Monte Carlo simulation experiments show that the proposed testing procedure performs reasonably well. We apply our methodology to Canadian yield curve data and French sub-national age-specific mortality data. We find evidence that these time series are mostly integrated of order one, while some have fractional orders exceeding or falling below one.
| Original language | English |
|---|---|
| Journal | Journal of the American Statistical Association |
| Publication status | Accepted/In press - 14 Mar 2026 |
Keywords
- Functional time series
- fractional integration
- sequential testing
- maturity-specific yield curves
- age-specific mortality rates
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