are constructed to account for these potential issues, but they are used parsimoniously in the empirical modeling process.

All variables entering the inflation models are tested for their order of integration and are found to be integrated of order 1 in levels (and stationary in first differences), with the exception of the output gap variable which is stationary in levels. The results are presented in Table A2 in the Appendix. The output gap is extracted from cereal production series using a Hodrick-Prescott filter. The use of the cereal output gap is motivated by the fact that the Ethiopian economy is highly dependent on agriculture, so agricultural production is a better measure of output trend than GDP.

Time series econometric modeling is used to estimate four models (cereals, food, non-food, and all-item inflation) through a two-step process. The first step establishes long-run relationships in the monetary and fiscal sectors as well as in the external food and non-food sectors. After specifying the long-run relationship in each sector, the existence of cointegrating vectors is established using the Johansen methodology. One cointegrating vector is uncovered for each sector. Next, the estimation of the cointegrating relationship provides coefficients of the cointegrating vector used to compute deviations from equilibrium. The error correction residuals are then tested to verify that they are stationary. Indeed, all the cointegration models produce stationary residuals. The equations of the residuals—representing deviations from equilibria— are then included in the error correction models. The results of the cointegration tests are presented in Table A3 in the Appendix.

In the second step of the empirical analysis, error correction models are estimated for cereals, food, non-food, and CPI inflation. Applying the general-to-specific methodology, the analysis starts with over-parameterized models where short-term variables have 12 lags each. Parsimonious models of inflation are derived through a process of model reduction. Ultimately, the number of significant lags varies by regressor.

Each model considers three groups of inflation determinants: long-run determinants, short-run domestic factors, and short-run external factors. Long-run determinants are represented by the cointegrating vectors derived through cointegration analysis in the first step. Short-run determinants are lags of first differences of the variables of interest, which are all stationary. Dummy variables capturing shocks to prices and seasonal effects associated with the main harvest season ( _Meher_ ) are included in the relevant models as appropriate.

# 6. Discussion of empirical results

## **Discussion of empirical results from the baseline model**

The empirical results confirm that inflation in Ethiopia is determined by several long-term and short-term factors (Table 1). Long-term determinants are associated with the monetary sector and the external food and non-food sectors, while short-run effects are associated with the monetary sector, external and domestic food prices, oil prices, output gap, and exchange rate market premium. The results are discussed thematically below. Similar to the point mentioned earlier, even though estimated coefficients may appear small, they represent monthly effects— this should be kept in mind in making inferences on the economic significance of the relationships between inflation and its determinants.

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