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Reconciliation of systems of time series according to a growth rates preservation principle

机译:根据增长率保留原理对时间序列系统进行对帐

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We propose new simultaneous and two-step procedures for reconciling systems of time series subject to temporal and contemporaneous constraints according to a growth rates preservation (GRP) principle. The techniques exploit the analytic gradient and Hessian of the GRP objective function, making full use of all the derivative information at disposal. We apply the new GRP procedures to two systems of economic series, and compare the results with those of reconciliation procedures based on the proportional first differences (PFD) principle, widely used by data-producing agencies. Our experiments show that (1) the nonlinear GRP problem can be efficiently solved through an interior-point optimization algorithm, and (2) GRP-based procedures preserve better the growth rates than PFD solutions, especially for series with high temporal discrepancy and high volatility.
机译:我们提出了一种新的同时和两步程序,用于根据增长速率保留(GRP)原理调和受时间和同期约束的时间序列系统。该技术利用了GRP目标函数的解析梯度和Hessian,充分利用了所有可利用的派生信息。我们将新的GRP程序应用于两个经济系列系统,并根据数据产生机构广泛使用的比例优先差(PFD)原理将结果与对帐程序的结果进行比较。我们的实验表明,(1)非线性GRP问题可以通过内点优化算法来有效解决;(2)基于GRP的过程比PFD解决方案保留了更好的增长率,特别是对于具有高时间差异和高波动性的序列。

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