US CapEx & Growth Analysis
Budget: $250 – $750 USD
I need a clear, data-driven study that shows how capital expenditures have affected economic growth in the United States during the last 10 years. All numbers must come from authoritative government databases such as BEA, FRED, BLS or similar federal sources; no industry reports or paywalled third-party estimates are to be used.
The job involves gathering and cleaning the raw series, creating summary tables and visuals, and running an econometric investigation—regression, VAR, or another defensible model—to test both correlation and causality between CapEx and GDP (and, where relevant, employment, productivity, or related macro indicators). The analysis should clearly state assumptions, any transformations applied, and statistical significance levels so the results are fully replicable.
Deliverables
• Clean, well-documented dataset and code (Python, R, Stata, or similar)
• Jupyter notebook / script that reproduces every figure and test
• Written report (~10 pages) interpreting the findings and policy takeaways
• Brief slide deck summarising key points for non-technical stakeholders
Flag any data gaps or definitional issues as you find them, and tell me up front which modelling framework you prefer so we can agree on variables before you dive in.
The job involves gathering and cleaning the raw series, creating summary tables and visuals, and running an econometric investigation—regression, VAR, or another defensible model—to test both correlation and causality between CapEx and GDP (and, where relevant, employment, productivity, or related macro indicators). The analysis should clearly state assumptions, any transformations applied, and statistical significance levels so the results are fully replicable.
Deliverables
• Clean, well-documented dataset and code (Python, R, Stata, or similar)
• Jupyter notebook / script that reproduces every figure and test
• Written report (~10 pages) interpreting the findings and policy takeaways
• Brief slide deck summarising key points for non-technical stakeholders
Flag any data gaps or definitional issues as you find them, and tell me up front which modelling framework you prefer so we can agree on variables before you dive in.