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This work presents a new technique for temporally benchmarking a time series according to the growth rates preservation principle (GRP) by Causey and Trager (1981). A procedure is developed which (i) transforms the original constrained problem into an unconstrained one, and (ii) applies a Newton's method exploiting the analytic Hessian of the GRP objective function. We show that the proposed technique is easy to implement, computationally robust and efficient, all features which make it a plausible competitor of other benchmarking procedures (Denton, 1971; Dagum and Cholette, 2006) also in a data-production process involving a considerable amount of series.

Time-series analysis. --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Intelligence (AI) & Semantics --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- Optimization Techniques --- Programming Models --- Dynamic Analysis --- Methodology for Collecting, Estimating, and Organizing Macroeconomic Data --- Data Access --- Technological Change: Choices and Consequences --- Artificial intelligence --- Technology --- United States