a more variable income for both rural and urban households.<sup>10</sup> We assume that seasonal rainfall variation produces shocks to income through its effect on income diversification and transitory income variability, but has no direct effect on current per capita consumption.<sup>11</sup>

# **7.  Results**

Before discussing the results, we address the econometric specification issues. Since income diversification could be a choice variable, we test if it suffers from endogeneity problems when estimating household welfare. As suspected, the test result reported in table 12 strongly rejects that hypothesis that S is exogenous in the structural equation (4). A common econometric fix for endogeneity concerns is to use instrumental variables estimation such as a two-stage least squares regression (2SLS). 2SLS presupposes that appropriate instruments exist, i.e., the instruments are relevant in the sense that they are correlated with suspected endogenous variable and uncorrelated with error term in the structural equation.

Table 12 presents several specification tests for the instrumental variables approach. The relevance test (Bound et al., 1995), which tests the hypothesis that the coefficients on these instruments in the first stage regressions are jointly zero are soundly rejected (the F statistic meets the rule of thumb threshold of 10 established in Bound et al. (1995)). The instruments also satisfy the over-identification test proposed by Davidson and MacKinnon (1993) on the joint hypothesis that the instruments are uncorrelated with the error term and that the second stage regression is correctly specified. The standard Durban-Hausman-Wu test also shows that OLS estimates are inconsistent in all cases, justifying the use of an instrumental variables approach.

Tables 7a & b present instrumental variables (IV) estimates of per capita consumption expenditures for rural areas. We also report the accompanying OLS estimates of income diversification. Tables 9a & b contain the corresponding results for urban areas. Table 8 presents the estimates of obtained by using non-farm income share (NF) as a measure of diversification for rural areas. The results of tables 7a & b and 8 are used to compare the estimates obtained by using our measures of income diversification against those obtained by using NF.

# **Determinants of Income Diversification**

10 Extension of rainfall variables as instruments to urban areas assumes strong urban-rural linkages in developing countries such as Zimbabwe through food markets and other factors (see, for instance, Ravallion and Datt, 1996 on India). In order to make the rainfall variables better instruments we use national average rainfall information for major urban areas instead of regional rainfall figures. Our empirical results (not reported, but available upon request) indicate that rainfall variability indeed significantly affects welfare in urban Zimbabwe, both before and after economic changes. 11 This is in line with permanent income hypothesis. See Paxson (1992) who, in studying the savings behavior of Thai farm households, makes a similar assumption and uses time-series information on regional rainfall in conjunction with cross-sectional data on farm household income to obtain estimates of components of household income attributed to rainfall shocks. Alderman (1996) applies a similar technique to Pakistani households. We test the validity of our instruments (see table 10).

9