Replication materials for "Monetary Policy and Oil-Shock Pass-Through: Evidence from Morocco, 2020-2025"
Description
This dataset accompanies the article "Monetary Policy and Oil-Shock Pass-Through: Evidence from Morocco, 2020–2025" by Otmane Lahrizi and Meriem Demdoumi (ENCG, Université Ibn Tofaïl, Morocco), submitted to Energy Economics. RESEARCH QUESTION ; The dataset was assembled to test whether Bank Al-Maghrib's 2022–2024 monetary tightening cycle was associated with a smaller pass-through of global oil-price shocks to Moroccan inflation than the prior loose regime. Morocco is an analytically clean setting: it imports the entirety of its refined petroleum since the 2015 SAMIR refinery closure, fuel retail prices follow a bi-monthly indexation formula tied to international quotations, and BAM ran a complete tightening cycle (1.50% to 3.00% to 2.25%) within the sample. WHAT THE DATA CONTAINS ; 66 monthly observations from January 2020 to June 2025: Moroccan year-on-year CPI inflation (peak 10.1% in February 2023, highest in three decades); Brent crude price (USD 18 in April 2020 to USD 123 in June 2022); BAM policy rate; MAD/USD exchange rate; Eurozone HICP as global control; CPI sub-components CP04 (energy and fuels) and CP07 (transport); and a binary tight-regime dummy = 1 for September 2022 to June 2024. SOURCES ; Morocco CPI from Haut-Commissariat au Plan via IMF IFS; Brent from FRED (DCOILBRENTEU); BAM rate from published Monetary Policy Committee communiqués; MAD/USD from FRED (DEXMAUS); Eurozone HICP from Eurostat; energy import bill from Office des Changes (CVS-CJO series). Daily Brent prices were converted to monthly arithmetic averages before log-differencing. NOTABLE FINDINGS ; Using the included Python code, the state-dependent Local Projection interaction coefficient gamma_h is negative at 12 of 13 horizons, reaching −10.2 percentage points at horizon 8 months. A joint test rejects the null of no interaction (sign-test p < 0.001; Wald chi-squared(13) = 25.84, p = 0.018). The finding survives five robustness exercises: continuous-rate specification, wild bootstrap, Brent realized volatility, a 9-cell lag-sensitivity grid, and exclusion of the COVID acute period. HOW TO INTERPRET ; Inflation, BAM rate, and HICP are in percentage points. Δlog Brent and Δlog MAD/USD are monthly log-differences (0.01 = 1% monthly change). The tight dummy is binary. CPI sub-components follow HCP COICOP classification. HOW TO USE ; The script run_lp_estimation.py reproduces every quantitative result in the paper. make_figures.py regenerates the three main figures. Run time under 30 seconds. Requires Python 3.10+, numpy, pandas, openpyxl, scipy, matplotlib. LIMITATIONS ; The tight-regime sub-sample is small (22 months), limiting horizon-by-horizon precision; joint inference is the appropriate reading. The reduced-form Brent shock conflates supply, demand, and uncertainty components. Substantial fiscal compensation (Caisse de Compensation expenditure rising from ~12.5 to 42 billion dirhams in 2021–2022) operated concurrently with the monetary tightening.