Quality assurance in the SLSA

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The product balancing technique is one of several key data quality assurance practices and procedures undertaken in SUT compilation. Others include:

Ensuring enterprise coherence

• In a statistical system, large companies are generally divided into operating segments whose data are collected from different sources (e.g. surveys). Aggregate survey data can be cross-checked with corporate tax filings or a company’s annual reports to ensure that the trends and levels are coherent and that they conform to expectations concerning the trends.

Confirming industry dynamics

• When company financial information is aggregated and converted to national accounting concepts, the ratios of inputs to outputs can be compared in either real or nominal terms. The expectation is that these ratios should not change dramatically over a one-year period (certainly in real terms) without a significant economic event accounting for the change (e.g., exit or entry of a significantly different firm, technological change, large variations in relative prices of inputs or outputs).

Analyzing time series

• Since the SUTs are compiled with tremendous detail, one can compare many different series over time. Do total outputs change dramatically from one year to the next? Can price fluctuations account for these changes? Does a certain input or output product change over time? If so, have the production processes of the dominant companies changed? Do output volumes follow a trend similar to that of export volumes? In all cases, viewing each of these elements independently, then cross-checking against secondary sources, greatly enhances confidence in the underlying data.

Comparing with external information

• All the above checks can be done with reference to external information as well. Annual reports, company websites, association websites and news articles all describe the economic events of a given year and can help shed light on the trends presented by source data.