shock pushes households’ utility below this level, they enter poverty. Conversely, if they are lifted above this level of utility, they are no longer in poverty.

The framework of Hertel et al (2004, 2009b), and that which this paper adopts, uses the AIDADS system to represent consumer preferences. This choice is based on AIDADS’ strength in capturing food expenditure patterns across the income spectrum (Verma et al, 2009), and for its ability to perform well out of sample when compared to other demand systems (see Cranfield et al, 2002, 2003)<sup>8</sup> . Reflecting its suitability for poverty analysis is that AIDADS devotes two‐thirds of its parameters to characterizing consumer behavior at very low levels of income. Estimation of this demand system is undertaken using the 80 country, per capita consumption data set offered by Version 6.1 of the GTAP database, also following Hertel et al (2004). For each commodity, we have estimates of subsistence quantities of consumption, from which we may infer (for average prices), budget shares at the subsistence level of income.

The poverty line in Tanzania is set to match the observed national poverty headcount ratio reported by the World Bank (2006) and this in turn dictates the poverty level of utility in the initial equilibrium. So, in the wake of a change in climate, commodity prices and wages will adjust, household incomes will change, as will the consumption profile of households at the poverty line, thereby resulting in new utility level. If household utility rises above the poverty level of utility, then it is lifted out of poverty. Conversely, if the household utility level falls below the poverty utility threshold, then it has become impoverished.

Equations (2) to (4) describe how the model can then be used to predict the change in the national poverty rate – the percentage of the population living below the poverty line in 2001 – in percentage points of poverty. Equation (2) details how we compute the percentage change in the poverty headcount ratio in Tanzania,<sup>ˆH</sup> r<sup>, in the wake of a shock to the prices and</sup> wages in the economy (Hertel et al, 2009b): The term in parentheses on the right hand side of the equation reports the change in the real after tax wage rate for endowment _j_ in region _r_ (Tanzania in this case) _,_ by deducting the percentage change in the cost of living at the poverty line,<sup>ˆC</sup> pr<sup>, from the percentage change in</sup> the after‐tax ˆWrjp . This real earnings term is pre‐multiplied by three important poverty‐ parameters which deserve additional discussion<sup>9</sup> .

> The first, Ωprsj , is the share of earnings type _j_ in total income of households in the neighborhood of the poverty line in stratum _s_ of Tanzania. By definition, the earnings shares in a given stratum sum to one and serve to determine the impact of a change in wages on household income. For example, if there is a 10 percent increase in the wages of unskilled agricultural labor, and imputed unskilled wages represents 70 percent of the agricultural stratum’s

> 8 Please see Appendix C for details of AIDADS formulation and parameterization.

> 9 Please see Appendix D for more details on the poverty parameters.

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