Alignment of the Quarterly Financial Statistics to the Annual Financial Statistics data

Pillay, Sagaren and de Beer, Joe (2016): Alignment of the Quarterly Financial Statistics to the Annual Financial Statistics data.

Abstract

Statistical data are often compiled at different frequencies. When analysing high and low frequency data on the same variable one often encounters consistency problems. In particular, the lack of consistency between quarterly and annual data makes it very difficult for time series analysis. This paper discusses the processes and challenges for the alignment of the quarterly and annual financial statistics surveys by industry. The process consists of three phases, the initial editing, to deal with large inconsistencies, a presentation of the methodology using the quarterly related series to interpolate the annual series, and an analysis of the results. In the initial editing phase the large differences are resolved by manually editing the input data and imputing for missing data. The temporal disaggregation/benchmarking technique used are based on the Fernandez optimisation method of allowing random drift in the error process. The main characteristic of this method is that quarter- to- quarter movements are preserved while quarterly-annual alignment is achieved. The diagnostics performed indicate that the Fernandez random walk model method produces plausible results.

• Item Type: MPRA Paper
• Language: English
• Keywords: disaggregation, benchmarking, optimisation, Fernandez random walk model 1
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C18 - Methodological Issues: General

References

Denton, F.T.,(1971).Adjustment of monthly or quarterly series to annual totals: An approach based on quadratic minimization. Journal of the American Statistical Association 66(333), 99-102.

Chen, B., (2007).An Empirical Comparison for Temporal Distribution and Interpolation at National Accounts. Bureau of Economic Analysis. Washington, DC.

Chow, G.C., Lin, A.L. (1971).Best linear unbiased interpolation, distribution and extrapolation of time series by related series. The review of Economics and Statistics 53,372-375.

Eurostat (1999).Handbook on Quarterly National Accounts, Office for Official Publications of the European Communities.

Fernadez, R.B., (1981).A methodological note on the estimation of time series.The Review of Economics and Statistics 63(3),471-476.

Litterman, R.B., (1983).A random walk, Markov model for the distribution of time series.Journal of Business and Statistics, 1,169-173.