Trade Liberalisation, Growth and Poverty in Senegal: A Dynamic Microsimulation Cge Model Analysis

Abstract

Abstract:Much current debate focuses on the role of growth in alleviating poverty. However, the majority of computable general equilibrium (CGE) models used in poverty and inequality analysis are static in nature. The inability of this kind of model to account for growth (accumulation) effects makes them inadequate for long run analysis of the poverty and inequality impacts of economic policies. They exclude accumulation effects and do not allow the study of the transition path of the economy where short run policy impacts are likely to be different from those of the long run. To overcome this limitation we use a sequential dynamic CGE microsimulation model that takes into account accumulation effects and makes it possible to study poverty and inequality through time. Changes in poverty are then decomposed into growth and distribution components in order to examine whether de-protection and factor accumulation are pro-poor or not.The model is applied to Senegalese data using a 1996 social accounting matrix and a 1995 survey of 3278 households. The main findings of this study are that trade liberalisation induces small increases in poverty and inequality in the short run as well as contractions in the initially protected agriculture and industrial sectors. In the long run, it enhances capital accumulation, particularly in the service and industrial sectors, and brings substantial decreases in poverty. However, a decomposition of poverty changes shows that income distribution worsens, with greater gains among urban dwellers and the non-poor.

Agricultural Modernization, Structural Change and Pro-poor Growth: Policy Options for the Democratic Republic of Congo

“…To put it differently, a better model for agricultural modernization produces pro-poor effects where poor households gain relative to the richer ones. Several recent studies have looked at the propoor effects of policies, particularly using CGE-microsimulation model (Boccanfuso et al, 2011(Boccanfuso et al, , 2013a(Boccanfuso et al, , 2013bAnnabi et al 2008;Ravallion and Lokshin 2008). Most of the studies do not show factors behind the differences in the impacts of policy on pro-poor growth or decompose the changes in poverty into growth and distribution components, but rather show how poor benefit/lose relative to rich segments of the population.…”

“…Then I feed the changes from the CGE model into a microsimulation model, which takes into account household heterogeneity in terms of factor endowments and consumption patterns, to generate welfare gains or losses at the household level. Using these welfare changes, in the third step I apply the propoor growth framework to assess which of the agricultural modernization strategies is pro-poor and the extent to which growth and redistribution contribute to welfare changes, following Annabi et al (2008). Finally, I select a strategy that produced pro-poor welfare gains in the previous stage, and use a least square regression as in Ravallion and Lokshin (2008) to quantify the determinants of pro-poor agricultural modernization at the household level.…”

Trading for SDGs: Trade Liberalization and Human Development in the Emerging Economies

“…Major portion of the literature identified that higher trade openness increases inequality in the country for example but not limited to (Revenga, 1997;Milner and Wright, 1998;Levinsohn, 1999;Ravallion, 2001;Epifani, 2003;Lundberg and Squire, 2003;Melitz, 2003;Xu, 2003;Khondker and Raihan, 2004;Annabi et al, 2005;Milanovic, 2005;Yeaple, 2005;Bustos, 2007;Conte and Vivarelli, 2007;Meschi and Vivarelli, 2009;Barua and Chakraborty, 2010;Bergh and Nilsson, 2010;Li and Coxhead, 2011;Ezcurra and Rodriguezpose, 2013;Furusawa and Konishi, 2013;Grossman and Helpman, 2014).On the other hand, some studies concluded that trade reduces income inequality (Bourguignon and Morrisson, 1990;Wood, 1995;Calderón and Chong, 2001;Cornia and Kiiski, 2001;Ravallion, 2001;Lundberg and Squire, 2003;Wade, 2004;Milanovic and Squire, 2005;Easterly, 2006;Demir et al, 2012) and some studies found mixed results (Meschi and Vivarelli, 2009;Nissanke and Thorbecke, 2010;Castilho et al, 2012;Perera et al, 2014;Hepenstrick and Tarasov, 2015).…”

Poverty, income distribution and CGE micro-simulation modeling: Does the functional form of distribution matter?

“…The basket remains constant from one simulation to another and is the same for all subgroups of the population. 7 The endogenous poverty line post-simulation is obtained by multiplying the volume of goods in the basket of basic needs ϖ p i by their respective simulated prices Pq i , and the new poverty line is obtained by aggregating across commodities (i):…”

“…We can classify these CGE-micro-simulation approaches into three groups. The first one is generally referred to as the fully integrated multihousehold model (IMH-CGE), first proposed by Decaluwé et al [26] and later applied by Cogneau and Robilliard [18] Gørtz et al [37], Cockburn [16] and Annabi et al [7] in a dynamic framework. As mentioned above, this approach consists of using a large number of households in a CGE context, thus allowing to take into account feedback effects of micro-household behavior and to endogenize the variance of income within groups of households that will be used for poverty analysis.…”