Transcript CGE Approaches to Policy Analysis in Developing Countries: Issues

CGE Approaches to Policy Analysis
in Developing Countries: Issues and
Perspectives
Carlo Bernini Carri
Dep. of Business
University of Pavia
CGE modelling in LDCs.
-The Computable General Equilibrium (CGE) or
Applied General Equilibrium models (AGE) are used
to tackle a wide range of problems in the development
field, such as choice of development strategy, income
distribution, trade policy, structural adjustments to
external shocks, tax policy and long-term growth and
structural changes.
-Since the beginning of the 1990´s CGE modeling has
also become a widely used tool for analysis of
environmental policy and natural resource
management issues.
-Government expenditure policies including subsidies
are another area of concern in fiscal policy modelling.
-Careful consideration of the development strategies is
an essential part of the policy analysis in LDCs.
-CGE models capture both stabilization and structural
adjustment features.
-Another important area of interest concerns the
agricultural trade liberalization. Agriculture is
important in structural reforms because of the size of
the agricultural sector, and because poverty reduction
requires that agricultural investment be part of the
overall development strategy.
-In terms of the number of models, and studies based
on these models, CGE modeling has expanded very
significantly.
There are a number of different ways in
which the CGE applications can be
categorized. One way is based on the
issues that they address. In the LDCs
experience we can distinguish five
categories: a) trade policy related issues; b)
income distribution; c)issues related to
external shocks and structural adjustment;
d) government fiscal policy related issues;
e) choice of development strategy, longterm growth, structural change.
-The majority of CGE models have been
used to simulate comparative static results
of a change in a particular policy or a group
of policies.
-Some of modellers have attempted to
incorporate dynamic elements into their
models. Two distinct approaches have been
employed: myopic (recursive) and
clairvoyant (intertemporal dynamics). In
the applications in LDCs, the intertemporal
approach has been widely used.
-Another important feature of the models
applied to LDCs is the usage of different
‘closure’. Different closure of CGE models
change their qualitative characteristics. In the
majority of studies the classical closure has been
used.
-Instead of perfect competition with perfectly
flexible prices and free product and factor
mobility, applied CGE models often incorporate
structural rigidities that seek to capture nonneoclassical
behaviour,
macroeconomic
imbalances, and institutional rigidities typical of
-Another major characteristic of CGE models is
whether they are single-period models for
comparative-static analysis or dynamic models
for
multiperiod
forecasting.
-Few applications show explicit interest in, and
specification of, intertemporal aspects of the
development
process.
There is no general answer to the question about
what CGE models are good for. The usefulness
of a designed and implemented CGE model
depends on what it is intended for and what the
alternatives are.
-CGE models almost always are focused on
the real side of the economy and thus do
not include markets for financial assets.
It would seem reasonable to expect that a
more “realistic“ approach could postulate
the possibility of unemployment, informal
labour markets, financial markets for
various assets and their relation to the real
sectors.
-Some problems linked to the analysis of
agriculture in LDCs have to be underlined:
in the area of consumer demand;
substitution among intermediate inputs and
between intermediate and primary inputs;
specification of farm technology; factor
mobility, farm land in particular but also
family labour, farm structures, and some
types of capital.
Some applications in LDCs.
-The interest generated by CGE modelling
in LDCs is explained by several factors:
approach appropriate to analyse various
policy changes and external shocks which
have economy-wide effects; development
of the relevant statistical data bases in
LDCs; advances made in efficient
numerical solution techni ques that have
removed the computational constraints on
the implementation of CGE modelling.
-The numerous applications of CGE
models during the past decades can be
categorized with respect to their scope
into: • single versus multi-country
(regional) CGE models; • single-period
versus dynamic CGE models; • nonfinancial (real economy) versus financial
CGE models; • national versus village
CGE models.
Foreign
exchange
shortages,
the
vulnerability of domestic economies to
external shocks, primary commodity
dependence, continuous external debt
problems and income disparities are major
problems in LDCs; also the impacts of
trade liberalization on economic growth
and poverty reduction.
The majority of applications of CGE
models have focused on these issues.
-According to Khan, the main
analytical developments in modelling
distribution into the first and second
generation models relied on a
representative household assumption
and fixed distributional coefficients for
the household income distribution.
Therefore, the analysis of poor
households was necessarily rough
-Now we are in the third generation of CGE
models where poverty impact has been
modeled explicitly, utilizing the
information in household income and
expenditure surveys.
There are at least two aspects of any
poverty impact analysis.These are: i) the
impact on economic growth; ii) on income
and asset distribution. The growth effect on
poverty reduction is then given by some
estimated growth-poverty elasticity.
-In any case, economic modellers
apparently do not agree regarding what
elements of general equilibrium models are
essential. This is evident in the variety of
CGE models that are currently used for
policy analysis, particularly in developing
countries.
-An important question regards the relevance of
CGE analysis for agriculture. There are several
important advantages offered by this approach to
policy analysis for this sector. Traditional
agricultural economic analysis has tended to
focus on commodities, and associated factor
returns. In contrast, CGE models deals also with
households. The focus also on people, services,
resources and the environment, instead of just
commodities is increasingly important, as the
share of farm household income generated
outside of agriculture increases.
-One of the features of agricultural
policy analysis is the high degree of
public intervention in the farm and food
sector. As shown by some works, AGE
models provide a good tool for welfare
analysis in a second-best setting, and
this makes them particularly wellsuited for use in agricultural policy
analysis.
-Another important field of research
regards the analysis of interindustry
linkages that can be very important.
-CGE analysis also has an important role to
play in the political economy of reforming
agricultural and trade policies. We can
observe a large body of literature
concerning the impacts of agricultural trade
reforms in developing countries.
-Some works have focused on the
importance of “dynamic gains” from trade
liberalization. Dynamic gains include the
pro-competitive effects of trade
liberalization eliminating domestic
monopolies as well as productivity gains
that result in sectors that are more globally
integrated and so realize the benefits of
improved technology.
But these gains are likely due also to the
In any case, protection, especially in
industrialized countries, can limit
export opportunities. The impact on
special interest groups can be a very
significant fraction of their income.
Much of the focus of adjustment policy
is on compensating these losers so that
liberalization becomes politically
feasible.
-Agricultural trade reforms can also
negatively affect rural welfare in LDCs, in
the cases in which the removal of
protection has made by the LDC itself.
-Assessing rural welfare effects of
agricultural trade reforms is particularly
complex in a general equilibrium setting,
because both quantities and prices are
changing.
-Increasingly agricultural policy is being
driven by environmental considerations.
Therefore, demand for analyses of the
impact of agricultural and trade policies on
the environment has been rapidly
increasing.
-The theme of product differentiation has
come to play an increasingly important role
in analysis of agricultural trade policies
-Future research in GE modelling for
agriculture have to seek more appropriate
solutions ,among others, in these fields: a)
agriculture as a multiproduct industry;
b) producer heterogeneity; c) treatment
of land (sector-specificity of land and the
eterogeneity of farm land); d) the role of
water; e) modelling policies that affect
agriculture.
Appropriate modelling of agricultural
policies is an important, but difficult task.
Limitations of CGE modelling.
GE models have become quite popular
among policy analysts in LDCs on the
recent past. However, there is still
considerable debate regarding the value
and appropriateness of using CGE
models for such policy analysis. Bandara
outlines some of the key criticisms levelled
at CGE models in literature: unrealistic
neo-classical assumption; absence of the
role of money and so on.
This criticism is less actual now with
the incorporation, for example, of
oligopolistic pricing and economies of
scale into CGE models.
Rigidities in markets and other
“structuralist” aspects of economies
have also been incorporated into CGE
models.
Perhaps the most important
criticism is related to data and
parameter values. There are many
problems in relation to consistency,
reality and adequacy of data in the
LDCs. Therefore, one of the
frontiers of research in the CGE
modelling involves the data.
-New developments in CGE modelling can
be considered as the responses of modellers
to earlier criticisms. CGE models are now
well-suited to analyse a wide range of
policy issues in LDCs in the short-run and
the medium-run.
-However, CGE models are rather weak
in modelling long-run processes of
development and change.
Because development is a process, both
a clearly defined real time frame and an
account of how the economy shifts
forward in time are needed.
-While the comparative static approach
to the movement of the economy
through time is unsatisfactory, it is not
clear that there are more appealing
alternatives.
-Referring to money, economic
development is invariably accompanied by
increasing monetization in very poor
countries and progressively more elaborate
system of financial intermediation, markets,
and institutions. Any account of inflation
must include the role of money and other
financial assets.
-Until now, the chances of introducing
inflationary processes into these models in
a credible way are problematic.
-Referring to agricultural and rural issues other
considerations are critical when modelling
welfare effects of trade policy shocks: the
heterogeneity of rural households and the
diversification of these households’ activities
and income sources.
-In addition, rural households exhibit diversified
income sources, technologies, and demands.
Technological heterogeneity across households,
like differences in market access, is generally
absent from aggregate economy-wide models.
-Another problem with excessive sectoral
and commodity aggregation stems from the
fact that the dividing line between the
agricultural and non-agricultural economy
is not at all clear.
-Whalley emphasizes the need to move
from general to special-purpose models if
CGE analysis is to become more policy
relevant.
Perspectives for CGE modelling.
-In the developing world the leading issues
refer to the impact of factors like
globalization, adjustment policies and
debt reduction on growth and especially
poverty. The interest goes to the
connection between growth and other
phenomena including income distribution.
-In the standard CGE model the choice of
factor and household disaggregations has
an impact on the political insights that can
be obtained. If one differentiates labour
only according to the categories
skilled/unskilled, male/female, and
urban/rural for example, then it is
impossible to study the effects of policies
that discriminate between workers in
different groups, regions, or industries, and
so on.
-Therefore, complementing
microsimulation with CGE or
macroeconomic models ("micro-macro"
links) is an area of great current interest.
-Approaches and techniques are still
under development, and in some cases
(e.g. with regard to economic growth)
are in initial stages, where it is not clear
what links are most appropriate and
feasible.
-The division between the two types of
models is beginning to break down. In
some cases the different model types have
been integrated. In other cases the models
have been treated in a "layered" manner.
- In recent literature it has become clear
that different combinations of model
types are needed when dealing with
different issues.
-The integrated models may have the
advantage where the goal is to understand
the direction and relative magnitude of
distributional and other effects in terms of a
full microeconomic analysis.
-The layered models, in contrast, perhaps
have an advantage where the concern is
about short-term distributional impacts in a
setting where realism is at a premium.
-Anyway, although the interest in
microsimulation and CGE integration,
there are still only a small number of
completed studies.
-Another kind of "two-layer" model would
combine CGE and macro modelling, e.g.
when monetary and financial phenomena
play a key role in the analysis but
distributional detail is not required.
-All these can constitute paths for future
improvements in CGE modelling.
Some requirements
-In CGE modelling, data requirements
are enormous.
-The selection of parameter values for
the functional forms are extremely
important determining the results of
various policy simulation.
-The starting point for the development of
any CGE model is the construction of a
micro-consistent benchmark dataset.
-One problem with calibration is
the general unavailability of
social accounting matrices and of
econometric estimates of key
models parameters in developing
countries.
-The calibration procedure itself
determines all of the parameters
in a model.
-To overcome the obvious defects of calibration
approach, some researchers have developed
CGE models based on the econometric
approach. Although the econometric approach
has some obvious advantages, it has some
advantages, particularly in relation to LDCs.
For this approach time series data are required
and the required number of parameters rises
with the increase in number of sectors in the
model. Because of this limitations many CGE
models applied to LDCs have followed the
calibration approach.
-But when functional forms for supply and
demand sides are introduced, empirically
estimated values for elasticities are necessary to
implement a CGE model. These values cannot
be derived from the input-output or SAM data. One of the main problems that arises in LDCs is
the lack of empirically estimated elasticity
parameters. The estimation of the necessary
parameters is a difficult task due to the
unavailability of data. The most common
practice in selecting elasticities is the literature
search.
-The need of larger data set has increased
with the analysis aimed to evaluate the
impact of different policy strategies on
poverty.
-From the point of view of welfare
analysis, disaggregation of households in
the economy is probably even more
important than sectoral disaggregation.
Unfortunately, data on factor payments to
households is difficult to obtain.
-Also
a
regional
disaggregation
frequently is required to adequately
capture the impact of agricultural and
resource policies. Such disaggregation can
take place at the sub-national level. A major
challenge in such efforts at sub-national
disaggregation arises from the scarcity of
state-level social accounting matrices or
input output tables.
-
Some conclusions.
-CGE modelling has made significant
progress in terms of the size and
complexity of the models that can be
solved.
-Yet complexity should never be an end in
itself in CGE modeling. Much of the
usefulness of a CGE model stems from its
solid foundation in basic economic theory.
-The addition of non-standard features,
such as imperfect competition on product
and factor markets, price rigidities and
inter-temporal relations, may make the
model more“realistic”.
-CGE applications in LDCs lead to some
suggestions for further research and
advancements in both methodological and
analytical aspects.
-The household budget survey should be
designed as a real income-expenditure
survey and not focus only on the
expenditure pattern of households.
It should also collect detailed information
on formal and informal income.
-Future research should also include more
advanced estimation techniques for the
response parameters of the CGE model.
-Recent work has attempted to bring together
microsimulation, CGE, and macro models.
Different combinations are appropriate for
different kinds of problems.
-Income distribution issues have been a major
concern of development policy in LDCs since
the 1970s. This has given rise to studies
focusing on income distribution issues. In this
context, a growing literature is oriented on
incorporating household survey data into an
econmywide framework provided by a CGE
model.
-Another possible extension of the CGE
model, suggested by the research for
Tanzania, could exploit its microeconomic
foundation and combine it with a village
CGE model to analyse the effect of
macroeconomic policies on a village
economy and the agents involved.
-With time, the degree of integration
between micro- and macro- analyses should
tighten.
-Determining the poverty impacts of trade
policy change, some works underline the
evidence of dominance of earnings-side impacts
over consumption side effects. This is
problematic, since household surveys are
notable for their under-reporting of income. The
poverty impacts of trade reform often depend
crucially on how well the increased demand for
labour in one part of the economy is transmitted
to the rest of the economy. Further
econometric research aimed at discriminating
between
competing
factor
mobility
-There are other prospective improvements
through the introduction of non-competitive
behaviour (while agriculture and certain service
sectors are competitive, other sectors of the
economy are manifestly not so) and various
forms of rationing.
-The CGE models used in policy work vary
widely in size, complexity, and domain of
applicability but all are designed to analyse the
links between policy choices and economic
outcomes. The questions driving the policy
debate also must drive the models.
-Estimation of the numerical values of key
parameters such as elasticities is an
important area of research required for the
future development of more realistic CGE
models.
-Agriculture is a key component of
adjustment
policy
in
developing
economies.
Because of its size relative to GNP and its role
as the major employer in low income countries,
investment in agriculture should not be ignored
in development policy.
Therefore, future
research has to deepen the focus on rural areas
and the role of institutions.
-The findings of more recent works highlight the
importance of using a disaggregated modelling
approach with a focus on rural households to
explore the impacts of agricultural trade reforms
on rural welfare.
-One of the improvements in GE
analyses of agricultural policies over
the coming decade will be through
increased collaboration with
economists working on partial
equilibrium studies.
-To be useful for policy analysis, economic
models should have a number of desirable
features to have an utility in policy
debates, such as policy relevance,
transparency; up to date, validation and
estimation (model determined to achieve
accurate results for the domain of potential
policy choices under consideration in the
policy debate), diversity of approaches (to
test the robustness of the results and the
importance of assumptions made.).
-In sum, while much remains to be done to
overcome the limitations of CGE
modelling, we can expect CGE models to
play an increasingly important role in the
future.
-However, the work to compare model
performance to economic history, so
addressing the criticism that models have
little relationship to reality, should have a
high priority for future research.
-All the improvements in any CGE model
are, however, conditioned by the
availability of a consistent database.
-An attention to informational and
computational costs is also needed.
-A final comment suggested by ISTAT
contributions in the morning: in my review
of literature (only a part of it, obviously) I
did find no considerations about NOE.
Why?
Thanks.