The Response of Ethiopian Grain Markets to Liberalization



5.


RESULTS


Descriptive Analysis of Grain Market Response to Liberalization

Changes in price levels and volatility

Summary statistics of real prices of grains for several markets in Ethiopia for the pre- and post-
market liberalization periods are provided in Table 2.
6 Average grain prices increased for all
markets in nominal terms (See Figure 1, 2 and 3 ). However, the average real price for maize,
white teff and white wheat increased after liberalization for the cereal-surplus areas of
Shashamane, Bako, Jimma, and Hosaenna, and decreased in the cereal-deficit markets of Addis
Ababa, Mekele, and Dire Dawa, with one exception (maize in Dire Dawa). Across all
commodities, real cereal prices increased in the grain-surplus areas in 7 of 7 cases. By contrast,
real prices in the grain-deficit areas declined in 8 of 9 cases. Prices in the surplus-producing areas
have risen by 12% to 48%, while prices in deficit regions have declined by 6% to 36% in eight
of nine cases. An unexpected result is observed for Dire Dawa market in that real maize prices
increased by 10% in the post-liberalization period.

The variability of monthly real price of maize for different markets as measured by the standard
deviation (SD) and coefficient of variation (CV) is presented in Table 2.7 The volatility of
wholesale cereal prices has generally declined since liberalization. This is especially true for the
deficit markets, where the SD declined in all 9 cases across maize, teff and wheat. In the surplus
markets, the SD actually increased from 1% to 11% in 5 cases, and declined in only 2 cases.
Similar results obtain for the CV measure of instability.

The above analyses indicate that the wholesale prices in the surplus producing markets increased
since liberalization, but became slightly more variable. Higher cereal prices in these areas have
most likely contributed to production growth and incentives to use productivity-enhancing inputs
in these areas.

However, it is not clear that price increases at wholesale level automatically translate into higher
prices to producers. Conclusive evidence on the extent to which producer and wholesale prices
move together requires time series information on producer prices, which unfortunately are only
sparsely available. However, using limited data from CSA and EGTE, data presented in Tables
3 and 4 are used to derive the producer share of the value of selected cereals at retail level.
Before liberalization under the fixed price system, the producers’ share of consumers’ price
ranged from 44% to 61% (Table 3). On the other hand, the limited data for the period after
market liberalization suggests that the producers’ share of the retail price increased slightly from

6 Within-year monthly price variability for different grains over the years from 1985 to 1996 is also
given in Appendices 2 to 4. The changes in monthly price variability from year to year is very dramatic for
most of the grains and markets.

7 The standard deviation is a measure of absolute price variability while the coefficient of variation is
a measure of price variability relative to the mean level of prices. While both measures are relevant, the
measure of absolute price variability (SD) may be most relevant for comparing the level of instability in
the pre-liberalization and post-liberalization periods.

-9-



More intriguing information

1. Short report "About a rare cause of primary hyperparathyroidism"
2. Recognizability of Individual Creative Style Within and Across Domains: Preliminary Studies
3. The name is absent
4. Barriers and Limitations in the Development of Industrial Innovation in the Region
5. Anti Microbial Resistance Profile of E. coli isolates From Tropical Free Range Chickens
6. The name is absent
7. Investment in Next Generation Networks and the Role of Regulation: A Real Option Approach
8. Legal Minimum Wages and the Wages of Formal and Informal Sector Workers in Costa Rica
9. Commuting in multinodal urban systems: An empirical comparison of three alternative models
10. Migration and employment status during the turbulent nineties in Sweden
11. The name is absent
12. Can a Robot Hear Music? Can a Robot Dance? Can a Robot Tell What it Knows or Intends to Do? Can it Feel Pride or Shame in Company?
13. BARRIERS TO EFFICIENCY AND THE PRIVATIZATION OF TOWNSHIP-VILLAGE ENTERPRISES
14. Studying How E-Markets Evaluation Can Enhance Trust in Virtual Business Communities
15. Evaluating the Impact of Health Programmes
16. Public-Private Partnerships in Urban Development in the United States
17. The name is absent
18. The name is absent
19. Weather Forecasting for Weather Derivatives
20. LIMITS OF PUBLIC POLICY EDUCATION