Household Spending Analysis (Colombia)

Overview

This project analyzes household spending based on purchase receipts to understand consumption patterns, category behavior, and the impact of inflation in Colombia (2025–early 2026). Using cleaned receipt-level data, the analysis explores how prices and spending evolved over time and contrasts observed behavior with economic theory (mechanical inflation effect).

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Research Questions

• How did total household spending evolve over the period analyzed?
• Which categories contributed most to spending changes?
• How does inflation mechanically affect spending when quantities are held constant?
• Do observed patterns align with theoretical expectations?

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Data

• Source: Manually collected household purchase receipts
• Granularity: Receipt-level transactions
• Frequency: Bi-weekly purchases
• Geography: Colombia
• Time span: 2025

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Methodology

1. Manual data entry and validation of receipt-level purchases in spreadsheets
2. Data cleaning and standardization of product categories using Excel / Google Sheets
3. Aggregation of nominal spending by period and category
4. Integration of inflation context as a theoretical benchmark
5. Interpretation of observed trends using economic theory, with explicit assumptions and limitations

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Key Insight

• Nominal spending decreased despite inflation, implying that quantity reductions and substitution effects dominated price-driven pressures

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Reproducibility

This project follows a spreadsheet-based reproducibility approach. All transformations, aggregations, and calculations were performed in Google Sheets and are reflected in the processed dataset.

To reproduce the analysis:

1. Review the raw dataset in data/raw/
2. Follow documented cleaning and categorization logic to obtain the processed dataset
3. Review the analytical report in docs/, which references the cleaned data

Key assumptions and methodological decisions are explicitly documented in the report.

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Repository Structure

├── data/
│ ├── processed/
│ │ └── household_goods_2025_cleaned.xlsx
│ ├── raw/
│ │ └── household_goods_2025_raw.xlsx
├── docs/
│ └── household_spending_patterns_under_inflation.pdf
├── README.md

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Tools & Skills

• Microsoft Excel / Google Sheets
• Data cleaning & validation
• Descriptive analysis and aggregation
• Economic reasoning (inflation & consumer behavior)
• Documentation & analytical reporting

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Author

Kevin Pelaez Bilingual (Spanish–English) Customer Support Specialist transitioning into Data Analytics