Testing for the bias in the estimation of business structure indexes from different data sources

A crucial question faced by statistical authorities is how the use of different data sources, namely surveys and administrative files, affects the compilation of specific statistics. This paper analyzes aggregated data from Greek structural business statistics (2014–2018), comprising 8 indexes across 140 business branches originated from two sources, survey and administrative files. Analysis reveals whether computed indexes differ by data source, repeated for each index. The structure of the data is that of repeated measures. The statistical testing was performed using two parametric statistical tests, the two-way repeated measures ANOVA and the linear mixed models, as well as the respective bootstrap tests (wild bootstrap for the linear mixed models). The consistency of the parametric and bootstrap tests was first assessed on simulated data, using the data setting of the real data but determining different scenarios for the dependence of the statistic on each factor. The simulation study concluded that, even for strong deviations of the data from normality, the parametric and bootstrap tests result to the correct test decisions. Real data analysis confirms agreement between parametric and bootstrap tests, with two indexes showing statistically significant data source effects. The findings suggest that the data source may have an impact on the derived statistics.