Maximum likelihood estimation framework for table‐balancing adjustments. (29th August 2018)

• Record Type: Journal Article
• Authors: Brent, Geoffrey
• Other Names: Chen Baoline guestEditor.; Di Fonzo Tommaso guestEditor.; Mushkudiani Nino guestEditor.
• Is Part Of: Statistica Neerlandica. Volume 72:Number 4(2018)
• Page Start: 520
• Page End: 532
• Publication Date: 2018-08-29
• Subjects: balancing -- benchmarking -- maximum likelihood estimation -- national accounts -- optimization; Statistics -- Periodicals; 519.5; 314.92
• DOI: 10.1111/stan.12159
• Languages: English
• ISSNs: 0039-0402

Abstract

Abstract : Balancing problems in national accounts and similar applications may be addressed by optimization methods that aim to maximize preservation of specific characteristics of the unadjusted data, for example, levels or time‐series movements. However, published methods do not always indicate the assumptions that underpin these methods, making it hard to identify when those assumptions might be violated or how to generalize them to complex cases. Previous authors have observed that least‐squares estimation methods correspond to maximum likelihood estimation (MLE) under normality assumptions. This paper explores this relationship in the context of published "movement preservation"/"level preservation" methods, showing how the MLE interpretation identifies implicit assumptions made by these methods and, hence, helps inform decisions about their use. It also notes a case where the MLE and "preservation" approaches diverge, and gives a framework for generalizing MLE approaches to complex scenarios.