data. It is thus reasonable to assume that a high percentage of farm output was captured during the 1990 survey. To proceed with the analysis, since the 1990 survey data do not contain information on output prices, national prices have been used to estimate the value of farm-level output for the 1990 sample.<sup>8</sup> The benefit of access to the raw data from the 1982 RHBS survey also allowed a recreation of the cluster- and household-level variables used by B&E (as contained in the processed set of 1990 data). A comparison of these variables also revealed some differences: (a) in the 1982 cluster- and farm-level control variables and (b) in the agroecological control indicators.

As with the 1990 survey data, the 1982 cluster- and farm-level production variables used in the B&E analysis were also inappropriately aggregated and had to be reconstructed.<sup>9</sup> Other problematic variables are the cluster transportation and (road) infrastructure variables. It is unclear what the coded values of these variables represent.<sup>10</sup> In fact, alternative infrastructure variables are available in the 1982 data. These are the distances from the farm to the various types of road and public transportation reported by households.

A comparison of the agro-ecological zone (AEZ) classification used for the B&E analysis with the AEZ classification variables available in the 1982 data also shows differences. In addition to the AEZ classification, B&E used indicators for the regional productivity potential (RPP) as a further control for differences in land quality. Since the 1982 data did not have comparable RPP indicators, these data were independently compiled." The RPP indicators are also substantially different from the indicators used by B&E. To determine which of the alternative sets of AEZ classification and RPP indicators to use, farm output was regressed on each set of indicators. The results show that the 1982 AEZ classification and the new RPP indicators have a higher explanatory power (R<sup>2</sup> ) for both the 1982 and 1990 farm-level production.

Finally, to maintain the focus on methodological comparability for the purpose of the present discussion, aggregate data on district agricultural output and extension costs as well as the related assumptions used to calculate the rate of return to extension are the same as used by B&E (1993).

- 8 The prices were obtained from the FAO data base and cross-checked for consistency, where feasible, with the _Economic Surveys_ for various years published by the Central Bureau of Statistics, Government of Kenya.

- 9 The quantities of crops produced, instead of their values, appear to have been summed and divided by an arbitrary factor of 12 to arrive at farm-level production used to control for household productivity differentials and for the cluster-mean values of cash and other crop production in the B&E study.

- 10 For example, in some sub-locations, all infrastructure variables (including those not included in the analysis) take the value 9, while most others take 1 or 2.

- l l Given the differences observed in the AEZ indicators, a verification of the accuracy of the RPP indicators was sought as part of the ongoing OED impact study of extension projects in Kenya. The help of the Tegemeo Institute of Egerton University, Kenya, is gratefully acknowledged for the compilation of the RPP indicators for the study areas. The new indicators are based on information gathered from the respective district annual reports and farm management handbooks for Kenya.

5