Data: What Was Measured

Every conclusion in this report rests on two primary datasets:

  1. The USD/MRU exchange rate
  2. The Mauritanian Consumer Price Index (CPI)

Nothing else is introduced without documentation.

1. Exchange Rate (USD/MRU)

Source

Central Bank of Mauritania (BCM)
Daily official USD/MRU exchange rate file (Excel format)

Coverage

  • Start: 2020-02-01
  • End: 2025-12-19
  • Frequency: Daily
  • Currency: US Dollar vs Mauritanian Ouguiya (MRU)

1.1 Monthly Aggregation

Daily rates are converted into monthly averages:

\[ FX_{month} = \text{mean of daily USD/MRU during month} \]

Monthly percent change:

\[ \Delta FX_t = \frac{FX_t - FX_{t-1}}{FX_{t-1}} \]

This aligns frequency with CPI.

2. Consumer Price Index (CPI)

Country

Mauritania, Islamic Republic of

Observations in raw file

150 total series for Mauritania

These include: - Monthly - Quarterly - Annual - Index levels - Percent changes - Weights - Multiple COICOP categories

We strictly filter.

2.1 Baseline Selection Rules

To avoid mixing incompatible series, baseline CPI uses:

  • FREQUENCY: Monthly
  • TYPE_OF_TRANSFORMATION: Standard reference period (2010=100), Index
  • COICOP_1999: All Items

Selected headline series:

MRT.CPI._T.SRP_IX.M

This is the official monthly headline CPI index.

2.2 Inflation Calculation

We compute inflation manually.

Monthly inflation:

\[ \pi_t = \frac{CPI_t - CPI_{t-1}}{CPI_{t-1}} \]

Year-over-year inflation:

\[ \pi^{YoY}_t = \frac{CPI_t - CPI_{t-12}}{CPI_{t-12}} \]

No precomputed percent changes are used.

3. COICOP Breakdown

Mauritania CPI is divided into 13 categories:

  • Food and non-alcoholic beverages
  • Housing, water, electricity, gas and fuels
  • Transport
  • Health
  • Education
  • Communication
  • Recreation and culture
  • Clothing and footwear
  • Restaurants and hotels
  • Alcoholic beverages, tobacco and narcotics
  • Furnishings and household maintenance
  • Miscellaneous goods and services
  • All Items

Each category has:

  • Monthly index
  • Weight series (monthly and annual)

These are used to measure:

  • Category-specific pass-through
  • Category-specific persistence
  • Contribution to headline inflation

4. Time Coverage

Final merged dataset:

  • Start: 2020-02
  • End: 2025-12
  • Total months: 71

This window includes:

  • COVID supply shock
  • Global commodity spike (2022)
  • BCM institutional transition (2022–2023)
  • FX platform modernization (2023)
  • Presidential re-election (2024)
  • Prime Minister transition (2024)
  • Initial gas export phase (2025)

5. Processed Output

Merged dataset stored at:

analysis/outputs/merged_fx_cpi_2020_2025.csv

Contains:

  • date
  • fx_usd_avg
  • fx_mom_pct
  • cpi_index
  • infl_mom_pct
  • infl_yoy_pct
  • category indices (Food, Transport, etc.)
  • category inflation rates
  • rolling volatility
  • rolling persistence estimates
  • rolling pass-through estimates

6. Why This Matters

The integrity of macroeconomic research depends on:

  • Frequency alignment
  • Series consistency
  • Avoiding transformation mixing
  • Transparent filtering

This dataset follows those principles.

The findings are not rhetorical.

They are mechanical.

The next section shows how those mechanics change over time.