The Chow-Lin method is a technique used for temporal disaggregation or also known as temporal distribution. Temporal disaggregation is the process of deriving high frequency data (e.g., monthly data) from low frequency data (e.g., annual data).
In addition to the low-frequency data, the Chow-Lin method also uses indicators on the highfrequency data, which contain the short-term dynamics of the time series under consideration. These indicators are time series that are related to the target time series and thus measure a different topic than the time series to be estimated. Since the results of the Chow-Lin method depend on information on a different variable, the method can be considered as an indirect approach. The main goal of temporal disaggregation techniques such as the Chow-Lin method is to create a new time series that is consistent with the low frequency data while keeping the short-term behaviour of the higher frequency indicator series. The Chow-Lin method may be applied to time series, generally aided by one (univariate case) or more indicator series (multivariate case). Presumably, these indicator series should be socio-economic variables deemed to behave like the target variable. In absence of such variables, functions of time can be used, as proposed by Chow and Lin (1976).
Temporal disaggregation is closely related to benchmarking, another data integration technique, see for instance the module “Macro-Integration – Denton’s Method”. The main distinction is that in benchmarking, the sub-annual series to be benchmarked consists of the same variable as the annual benchmarks, while in temporal disaggregation the sub-annual series differ from the annual series.
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