Macro-Integration for Solving Large Data Reconciliation Problems

Abstract

Macro-integration technique is a well established method for<br />reconciliation of large, high-dimensional tables, especially applied to macroeconomic data at national statistical oces (NSO). This technique is mainly used when data obtained from dierent sources should be reconciled on a macro level. New areas of applications for this technique arise as new data sources become available to NSO's. Often these new data sources cannot be combined on a micro level, while macro integration could provide a solution for such problems. Yet, more research should be carried out to investigate if in such situations macro integration could indeed be applied. In this paper we propose two applications of macro-integration techniques in other domains than the traditional macro-economic applications. In particular: reconciliation of tables of a virtual census and reconciliation of monthly series of short term statistics gures with the quarterly gures of structural business statistics.

Solving large‐data consistency problems at Statistics Netherlands using macro‐integration techniques

“…Boonstra et al () showed that the GREG‐estimator used for repeated weighting is equivalent to a weighted least squares estimate, where consistency under linear constraints should be achieved. The repeated weighting solution can be obtained as a solution to a specific quadratic optimization problem as in (1), after choosing a particular specification for the weights; see, for example, the work of Mushkudiani, Daalmans, and Pannekoek ().…”