Analysis of Correlation Between Working Time Duration and Productivity Index in EU and OECD Countries

Context and Methodology: This dataset was created as part of the research project "Analysis of Correlation Between Working Time Duration and Productivity Index in EU and OECD Countries".

The purpose of this dataset is to investigate the statistical relationship between average weekly working hours and labour productivity (GDP per hour worked) across selected European and OECD countries. The analysis tests the hypothesis that longer working hours correlate with lower productivity.

Creation Process: The dataset was generated by processing and fusing two external, publicly available statistical sources:

1. Eurostat: Hours worked per week of full-time employment (Table: tps00071).

2. OECD: Level of GDP per hour worked (Dataset: Productivity and ULC).

The data were filtered for the period 2014–2024, harmonized using Purchasing Power Parities (PPP) to ensure valid cross-country comparison, and merged into a single analytical table using Python.

Technical Details and Structure: The deposit follows a flat file structure containing the following machine-actionable data and results:

• final_data_for_analysis.csv: The fused, cleaned dataset containing Country, Year, Working Hours, and Productivity values.

• analysis_code.ipynb: The Jupyter Notebook containing the Python source code used for data ingestion, fusion, and Pearson correlation analysis.

• statistical_report.pdf: A formal report summarizing the methodology and statistical findings.

• scatter_plot.png: A visualization of the correlation results.

• requirements.txt: List of Python libraries required to reproduce the analysis.

• README.md: Detailed documentation of the project structure and sources.

Software Requirements: To reuse the CSV data, any spreadsheet software (Excel, LibreOffice) or statistical tool is sufficient. To run the source code (.ipynb), a Python 3 environment with Jupyter Notebook and libraries listed in requirements.txt (Pandas, SciPy, Matplotlib) is required.