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

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  • Nino Mushkudiani
  • Jacco Daalmans
  • Reinier Bikker

Abstract

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), 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.

Suggested Citation

  • Nino Mushkudiani & Jacco Daalmans & Reinier Bikker, 2018. "Solving large‐data consistency problems at Statistics Netherlands using macro‐integration techniques," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 553-573, November.
    • Handle: RePEc:bla:stanee:v:72:y:2018:i:4:p:553-573
    DOI: 10.1111/stan.12158
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    1. Tommaso di Fonzo & Marco Marini, 2005. "Benchmarking Systems of Seasonally Adjusted Time Series," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(1), pages 89-123.
    2. Magnus, Jan R & van Tongeren, Jan W & de Vos, Aart F, 2000. "National Accounts Estimation Using Indicator Ratios," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 46(3), pages 329-350, September.
    3. Baoline Chen, 2007. "An Empirical Comparison of Methods for Temporal Distribution and Interpolation at the National Accounts," BEA Papers 0077, Bureau of Economic Analysis.
    4. Reinier Bikker & Jacco Daalmans & Nino Mushkudiani, 2013. "Benchmarking Large Accounting Frameworks: A Generalized Multivariate Model," Economic Systems Research, Taylor & Francis Journals, vol. 25(4), pages 390-408, December.
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