implicitly that household expenditure is roughly equivalent to household income, so that a decline in net sales income would be reflected in the same absolute decline in household expenditure, all other things equal). What we find, however, is that among food crop households the ratios are quite close between the bottom 40 percent and top 60 percent of the population, and they are relatively small (table 42). So while this explanation does not seem promising to account for the adverse redistribution effect, it may also be that the surveys do not do a very good job of estimating marketed sales of food crops.

**Table 42 Net Revenue From Staple Food Crops of Rural Food Crop Farmers')**

||_Ne_<br>_19_<br>|_t staple food crop reve_<br>_93_<br>|_nue/household expendit_<br>_19_<br>|_ure_<br>_95_<br>|
|---|---|---|---|---|
|_Region_|_Bottom 40% of_<br>_population_|_Top 60% of_<br>_population_|_Bottom 40% of_<br>_population_|_Top 60% of_<br>_population_|
|East Forest|2.5|2.3|0.9|1.0|
|West Forest|7.7|7.0|-2.3|-1.1|
|Savannah|9.1|8.6|6.0|1.7|

**a)** Net revenue is crop revenue less purchases. The staple crops are maize, manioc, millet and yam.

b) Population is ranked by household expenditure per capita.

Furthermore, as explained above, the used of a single inflation rate to deflate the expenditures of poor and non-poor households may also bias the results slightly towards an adverse redistribution pattern. Another partial explanation may relate to the housing variable. The estimating equation for housing cost yields large negative dummies for the 1995 regional dummies. Since housing as a share of expenditure declines as expenditure increases, the use of a single dummy would result in a larger decrease, relative to total expenditure, of total per capita expenditure among poorer households. All other things being equal, this would tend to yield an adverse redistribution effect.

# _Conclusion_

In the short run, the devaluation accompanied by the increased in export taxation did not appear to alter the pattern of poverty that took shape prior to the devaluation, assuming that the results of the 1993 and 1995 surveys are roughly accurate, about which there is considerable cause for doubt. Abidjan experienced the largest increase in poverty between 1993 and 1995. Food crop farmers in rural areas got absolutely poorer. And depending on whether or not one accepts the 1995 West Forest results, export crop farmers got slightly worse off or remained about the same. The increase in poverty among food crop farmers is likely linked to the downward trend in real food crop prices evident in the pre-devaluation period 1987-1993 , which continued after the devaluation. As producers of nontradables, it would be expected that food crop farmer would not have benefited from the devaluation in the short term unless a substantial part of their income comes from wage labor or off-farm sources. Unfortunately we know very little about the sources of income of food crop farmers. The failure of export crop farmers to show a more important decline in poverty is due to several things: first the survey took place relatively soon after the devaluation, so that coffee and cocoa farmers had little time to respond to higher crop prices. A second reason, particularly relevant for cocoa, is that the government taxed away much of the benefit of the devaluation and the price increase. Only for coffee was there a real price increase of any appreciable magnitude between the devaluation and the time of the 1995 survey. And curiously, among the households in East Forest and West Forest whose major source of income is coffee, there was little if any growth in household expenditure per capita.

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