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6.0. METHODOLOGY
6.1. Research Framework
The research framework of this study is shown in Figure 6-1. There are two models used in
this study; the GTAP model, and micro-simulation. Firstly, the GTAP model is used to
analyze the impact of trade liberalization on macro-economic variables. Secondly, the results
of the GTAP model (prices and wages) are used in micro-simulation to analyze the impact of
trade liberalization on poverty
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.
Figure 6-1. The research framework of this study
6.2.GTAP Model and Data Base
Computable equilibrium (CGE) model which called the Global Trade Analysis Project
(GTAP) model was used for our analysis. Computable General Equilibrium (CGE) model
combine economic theory and empirical data to create economic tool for policy analysis such
as changes in tariffs and their effects on whole economic systems .CGE model present the
behavior of economic agents (producers, consumers, and government), sectors (industry,
agriculture, and services) and factors of production (labor, capital and land). CGE model are
of two basic types: a multi-regional computable equilibrium (CEG) model and single
country-CGE model.
The Global Trade Analysis Project (GTAP) model, a multi-region computable equilibrium
(CGE) model, is one of the most popular models for analyzing the impact of trade policies
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.
There are various advantages to the GTAP model. Firstly, since it is a multi-regional model
of world production and trade, it can take into account the overall trade implications of AFTA
as well as third-party countries. Secondly, it contains a database for different sectors and thus
can explore the trade implications for various sectors of interest
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.
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Here, it is important to note that there are other approaches to assessing the impact of trade liberalization on
poverty. The first one is to link the GTAP model with the single country model (with multi-household). The
import and export prices from the GTAP model can be used to shock to the single country model. This approach
can estimate the change in household welfare as a result of trade liberalization. The second approach links the
three models (GTAP model and micro-simulation).The import and export price changes from the GTAP model
can be used to shock into the single country CGE model, then used to shock in the micro-simulation model.
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The origin of GTAP model is based on ORANI model, a single country CGE model, a first CGE model for
Australian economy (Dixon, Parmenter, Sutton, and Vincent, 1997). GTAP model extended ORANI model for
allowing international trade which introduced a global transportation sector and savings institution.
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For more details, see Hertel (ed), 1997. A graphic presentation of the GTAP model, with particular emphasis
on the accounting relationships, is given by Brockmeier (1996).
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The GTAP model assumes perfectly competitive markets, where the zero profit condition
holds, and that all the markets are cleared. The regional household allocates expenditure
across three categories: private household, government, and savings. It derives income from
the ‘sale’ of primary factors to the producers, which combine them with domestically
produced and imported intermediate composites to produce final goods. These final goods are
in turn sold both domestically to private households and the Government, and exported to the
rest of the world. Both the Government and private households also import consumer goods
from the rest of the world. A global bank intermediates between global savings and regional
investments by assembling a portfolio of regional investment goods and selling shares in this
portfolio to regional households in order to meet their savings demands. Finally, a global
transport sector assembles regional exports of trade, transport and insurance services and
produces composite goods used to move merchandise trade among regions (Hertel eds,
1997). The flowchart of the GTAP model and production structure in the GTAP model is
illustrated in Figure 6-2.
The latest version of the GTAP database, version 8, is used for this study. To facilitate our
analysis, regions have been aggregated into 21 separate sub-regions (see Appendix 1). All 57
sectors remain as delineated in the GTAP database (Appendix 2).
Figure 6-2. Production structure in the GTAP model
The model closure and free parameters are important factors to influence the simulation result
in CGE model. Macro closure is important factors to influence the simulation result from
GTAP model. Closure is divided the variables in model to endogenous or exogenous
variables. Endogenous model are determined by the model but exogenous variables are from
outside the model. Macro closure is based on mainly characteristics of economy in the
country which we focus. The closure of GTAP model has various elements such as
population growth, capital accumulation, industrial capacity, technical changes, and policy
variable (tax and subsidies). However, in order to simplify the closure, we use the standard
GTAP closure which called “Neo-classical” closure. This closure assumed that all prices are
flexible; perfect competition (all firm earn zero pure profits); full employment and factor
mobility within regions; investment expenditure is determined by savings rate; tax rates are
fixed.
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Parameters are one of the most important considerations in a CGE model. Some studies have
found that different parameters lead to different policy results (Abler et al, 1999).
International trade is linked thought Armington substitution among goods differentiated by
country of origin. Trade liberalization simulation can produce positive or negative impact
depend on the Armington elasticities (Zhan, 2006). Basically, some parameters for this study
are calibrated from SAM. However, some parameters for the CGE model are not available in
Laos. As there is not estimation of free parameter in Laos. We used free parameter from
Warr (2008) .
6.3. Measuring Welfare Impacts
Household welfare is affected by four factors: changes in revenue, changes in expenditure,
changes in inputs, and changes in wages (see equation below). As mentioned in the research
framework, the measurement of welfare changes due to trade liberalization uses the top-down
approach linked to the GTAP model and micro-simulation. There are two steps to estimating
the effect of trade liberalization on household welfare. Firstly, we estimate producer and
consumer price changes, and factor production price changes from the GTAP model.
Secondly, the price and output changes from the GTAP model are used for micro-simulation
(Figure 6-3). Household welfare change is calculated using the formula in Chen and
Ravallion (2004) and Ravallion and Lokshin (2008).
The results of the GTAP model indicate that the four factors are influenced by changes in
consumer and producer prices, and wages. The changes in the price and production of
particular food and non-food items alter household welfare, which is based on a share of
revenue from these items. Changes in international demand for particular goods affect
household incomes, which depend on a proportion of their marketed production of goods.
Wage changes influence household income according to the share of waged income received.
Price changes also affect household consumption, with an increase in prices decreasing
household welfare. The welfare impacts from trade liberalization in the monetary value of the
change in utility for household income can be expressed as follows
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:
gi
= The monetary value of the change in utility for household
= The revenue (selling value) from household production activities in sector
= Quantity supplied from household i in production activities in sector j
he (negative) weight for demand price changes
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The measurement of welfare impacts from trade liberalization has data constraints because initial data of price
and wage levels are not included. Nevertheless, this problem can be overcome by calculating a first-order
approximation of the welfare impact in a neighborhood of the household’s optimum (Chen and Ravallion, 2004;
Ravallion and Lokshin, 2008).
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= Demand price from household i in production activities in sector j
Commodities used as production inputs, of which
is used for production goods in
sector
= The weight for changes in the wage rate for activity
Household’s “external” labor supply to activity
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