To solve this problem, a second approach was proposed by Decaluwé, Dumont and Savard (1999) and applied by Cogneau and Robilliard (2000), Gørtz et al. (2000) and Cockburn (2001), namely the CGE integrated multi-household approach (CGE-IMH). This method incorporates a large number of households from a household survey (and sometimes all of them) into the CGE model. The approach takes into account within-group distributional effects and has the further advantage of providing coherence between the micro and macro parts of the model, but at a cost. First, data reconciliation can be very problematic (Rutherford, Tarr and Shepotylo, 2005); second, numerical resolution can be challenging (Chen and Ravallion, 2004).

The third approach is referred to as the CGE micro-simulation sequential method (MSS) and could be subdivided into two variants. The first, micro-accounting, was formally presented by Chen and Ravallion (2004) and has been extensively applied in recent years.<sup>13</sup> The second variant, proposed by Bourguignon, Robilliard and Robinson (2005), consists of integrating, at an individual level, rich micro behavior observed at a household level such as consumption or labor supply. This version introduces more heterogeneity between households with the application of a microeconometric model. The general idea of the MSS approach is that a CGE module feeds market and factor price changes into a microsimulation household model. The main criticism leveled at this approach is that the microfeedback effect is not fully taken into account; the question has been raised in two literature reviews of macro-micro modeling for poverty analysis (Hertel and Reimer (2005) as well as Bourguignon and Spadaro (2006)). However, Bourguignon and Savard (2008) found that the loss of information associated with using the MSS approach can be relatively small and policy conclusions were robust between the two approaches.<sup>14</sup> In this paper we apply the micro-accounting version of the MSS approach.<sup>15</sup> The last two approaches (IMH, MSS) allow for rich analysis of income distribution and poverty because they include a large number of households in the modeling exercise. This in turn allows the modeler to apply poverty and income distribution measures and indexes following policy simulations. As already mentioned, the IMH approach is the soundest on a theoretical basis. However, with this approach, it is necessary to construct a balanced submatrix for household accounts in a standard social accounting matrix. On the other hand, with the CGE-MSS approach, the household income and expenditure do not require balancing. This gain in flexibility comes from the fact that the micro module is solved sequentially and that we use price percentage changes to link the CGE module to the micro household module. This constraint is one of the two reasons behind our choice to select the CGE-MSS approach for our analysis. The second argument for this approach is that some households will increase their labor supply and land use. This will involve in some cases

> 13 Among early applications of this approach are Vos and De Jong (2003) and King and Henda (2003).

> 14 Bourguignon and Savard’s (2008) comparative analysis of the IMH and MSS approaches was applied to the Filipino economy. In this study, the labor supply was endogenous and the largest portion of the gap in the results obtained from the two approaches came from the labor supply. In our application, the labor supply will be held constant.

> 15 The main reason for selecting this approach is the lack of adequate data to apply the microeconometric approach.

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