Liquidations 1980-2025

During processing, the original monthly data were integrated and converted into a structured time-series format by DataFirst. Monthly variables contained in separate columns were reshaped into a long dataset in which each row represents a unique liquidation count for a specific month and classification category. A standardised reference-date variable was then constructed to ensure temporal comparability across years. Classification variables—namely business type, liquidation type, and industry—were harmonised, recoded into numeric codes, and assigned appropriate value labels to promote consistent interpretation across time. Descriptive variable labels were added to all key fields to enhance usability in statistical software environments. Text fields were standardised to lowercase to eliminate variation caused by inconsistent text formatting. After all processing steps were completed, the dataset was sorted chronologically and organised into a tidy structure suitable for producing time-series indicators, tables, and aggregated outputs. The final cleaned dataset was exported in Stata (.dta) format for analysis and dissemination.