Reconciliation of National Income and Expenditure
Balanced Estimates of National Income for the United Kingdom, 1920–1990

Describes method of testing economic data reliability using long run UK statistics.

James Sefton (Author), Martin Weale (Author)

9780521496353, Cambridge University Press

Hardback, published 18 January 1996

344 pages
23.5 x 15.6 x 2.4 cm, 0.63 kg

"This book is number seven in the distinguished series Studies in the National Income and Expenditure of the United Kingdom, founded by the late Sir Richard Stone. Fortunately, the authors have maintained the high standards of their illustrious predecessors." Journal of Economic History

This book was first published in 1995. The problem of disparities between different estimates of GDP is well known and widely discussed. Here, the authors describe a method for examining the discrepancies using a technique allocating them with reference to data reliability. The method enhances the reliability of the underlying data and leads to maximum-likelihood estimates. It is illustrated by application to the UK national accounts for the period 1920–1990. The book includes a full set of estimates for this period, including runs of industrial data for the period 1948–1990, which are longer than those available from any other source. The statistical technique allows estimates of standard errors of the data to be calculated and verified; these are presented both for data in levels and for changes in variables over 1-, 2- and 5-year periods.

Part I. The Theory of Data Reconciliation: 1. The reconciliation of national accounts
2. Basic issues in data reconciliation
3. Reconciliation without knowledge of data reliabilities
Part II. Application to UK National Accounts: 4. Patterns of autocorrelation
5. The data and their reliability, 1920–48
6. The data and their reliability, 1948–90
7. Sectoral income/expenditure and capital accounts
8. The results of the balancing exercise
Part III. Balanced National Accounts for the United Kingdom: 1920–1990
Bibliography
Index.

Subject Areas: Econometrics [KCH]