Affiliations: [a] Former Head of the National Accounts Branch, United
Nations Statistics Division, New York, USA | [b] Department of Econometrics and Operations Research,
Tilburg University, Tilburg, The Netherlands
Correspondence:
[*]
Corresponding author: Jan R. Magnus, Department
of Econometrics and OR, Tilburg University, Tiburg, The Netherlands. E-mail:
[email protected]
Abstract: We present a Bayesian estimation method applied to an extended set of national
accounts data and estimates of approximately 2500 variables. The method is based
on conventional national accounts frameworks as compiled by countries in Central
America, in particular Guatemala, and on concepts that are defined in the
international standards of the System of National Accounts. Identities between
the variables are exactly satisfied by the estimates. The method uses ratios
between the variables as Bayesian conditions, and introduces prior reliabilities
of values of basic data and ratios as criteria to adjust these values in order
to satisfy the conditions. The paper not only presents estimates and precisions,
but also discusses alternative conditions and reliabilities, in order to test
the impact of framework assumptions and carry out sensitivity analyses. These
tests involve, among others, the impact on Bayesian estimates of limited annual
availability of data, of very low reliabilities (close to non-availability) of
price indices, of limited availability of important administrative and survey
data, and also the impact of aggregation of the basic data. We introduce the
concept of 'tentative' estimates that are close to conventional national
accounts estimates, in order to establish a close link between the Bayesian
estimation approach and conventional national accounting.
Keywords: Macro accounts, system of national accounts, data frameworks, reliability, bayesian estimation, sensitivity analysis, aggregation
