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

机译：使用宏集成技术解决荷兰统计局的大数据一致性问题

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摘要

The generalized multivariate Denton model for achieving consistency between large accounting frameworks developed at Statistics Netherlands (SN) is originally intended for benchmarking of supply and use (SU) tables of national accounts. The success of this application in the production process triggered using the model for other processes within the office. Currently, at SN, many production processes of national accounts, but also other departments, use the modifications of this optimization model for achieving consistency of data obtained from different sources. These include reconciliation and benchmarking of SU tables and of institutional sector accounts, ESA (European system of accounts),1 revisions of SU tables, benchmarking of gross fixed capital formation, Population Census tables, and energy statistics figures. The mathematical model is based on a quadratic optimization function and combines different features, such as linear constraints, ratio constraints, weights, soft and hard constraints, and inequalities. The optimization problems we deal with can be very large, consisting of 500,000 variables and over 100,000 constraints. This optimization problem is solved using the commercially available software tool XPRESS and the free software tool R. For the reconciliation of trade and transport statistics, similar optimization techniques are used. In this paper, we give an overview of production processes at SN using macro-integration techniques.
机译：荷兰统计局（SN）开发的用于在大型会计框架之间实现一致性的广义多元Denton模型最初旨在对国民账户的供应和使用（SU）表进行基准测试。该应用程序在生产过程中的成功触发了在办公室中使用其他过程的模型。当前，在SN中，国民账户的许多生产过程以及其他部门都使用此优化模型的修改，以实现从不同来源获得的数据的一致性。其中包括SU表和机构部门账户的对账和基准，ESA（欧洲账户系统），SU表的修订，固定资本形成总额的基准，人口普查表以及能源统计数字。数学模型基于二次优化函数，并结合了不同的特征，例如线性约束，比率约束，权重，软约束和硬约束以及不等式。我们要处理的优化问题可能非常大，其中包含500,000个变量和超过100,000个约束。使用市场上可买到的软件工具XPRESS和自由软件工具R解决了此优化问题。为了调节贸易和运输统计数据，使用了类似的优化技术。在本文中，我们概述了使用宏集成技术的SN生产过程。

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