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In addition, while much attention has been placed on the direct price incentives (generally producer prices), little work has included the indirect effects of macroeconomic policy distortions on agricultural growth, especially exports (balassa, 1988, has used the real exchange rate as a proxy for iLt.entives). Real exchange rates affect the competitiveness of agricultural exports by altering the relative prices of inputs and products. But inclusion of the real exchange rate - in addition to real prices - serves as a proxy for the costs -id efficiency losses associated with trade and exchange restrictions that generally occur wheh exchange rates are highly overvalued.

The analysis presented here utilizes time-series data for the 1970-87 period and for 21 countries to estimate the response of agriculture to changes in real producer prices, macioeconomic policies (specificaUy the real exchange rate), the effect of weather, and major shocks in the form of "disasters" (including war, civil strife, famine, floods, or other disruptions). L1/ The model is as follows:

# AGRICULTURAL EXPORTS = b0 + b, REAL PRODUCER PRICE +b2 REAL EFFECTIVE EXCHANGE RATE + b3 WEATHER + b4 DISASTERS + _e_

The analysis focuses on exports of agricultural commodities (cocoa, coffee, tea, etc.). For most of these commodities, nearly all production is exported so that exports are a reasonable approximation of production except in cases where domestic consumption is large relative to exports (as in the case of palm oil), or where smuggling results in a significant divergence of recorded exports from actual production. 12/ The food crop sector is, for the moment, left out of the analysis. To estimate similar supply equations for food crops would be problematic due to the lack of adequate producer price data. This results in part from the prevalence of officially announced prices for food crops which in many countries have little relation to what farmers actually receive. These official prices are often the only available price series. The interaction between food production and policy variables is addressed below.

Weather has an important impact on agricultural production in Africa, but quantifying that effect is problematic. Rainfall data is spotty and difficult to interpret correctly short of complex simulation models of soil moisture, daily rainfall, and evapotranspiration data, and different rainfall patterns will effect individual crops differently. An approximation for the general effect of weather on agriculture is derived here by estimating a regression trend line for cereal yields, and taking the _iL/_ Specification of variables and data sources can be found in Annex A.

12/ Several countries have been excluded from the anm1ysis because of obvious "border effects" and smuggling. These include Benin and Zambia where dramatic swings in agricultural exports appear to have resulted from policy changes and border closings in neighboring countries. Also, - Rwanda and Burundi are excluded due to apparent smuggling exports exceeded production by substantial amounts in several years. Ghana is often thought to have substantial smuggling but it is unclear that this accounts for a substantial share of total production.