Do a Small Open Economy DSGE Model Characterizes Correctly
the Cyclicality in the African Least Developed Countries?
Jean-Paul K. Tsasa Vangu
February 14, 2014
Abstract
This article reviews the recent literature on Dynamic and Stochastic General Equilibrium Models,
with the objective (i) to document the empirical regularities characterizing African economies; (ii)
to discuss the usefulness of the DSGE approach to the analysis of macroeconomic implications of
monetary, fiscal, real and external impulses in African economies. So We consider the theoretical
framework of a standard New Keynesian DSGE model for a small open economy with an array of
financial frictions, nominal and real rigidities that have been identified in the standard
macroeconomic literature to explain observed business cycle.
JEL Code: E32, E58, E62, N17.
Keywords: DSGE; Small Open Economies; Stylized facts; Least Developed Countries; Africa
Introduction
This article reviews the recent literature on the applications of dynamic stochastic general
equilibrium (DSGE) models in African economies. In the macroeconomic literature, there are
several papers that document the stylised facts of US economy or the advanced economies using
DSGE approach (King and Watson 1996; Chari and Kehoe 2006; Fernndez-Villaverde 2010;
Milani 2012; etc.). But, for African Developing countries, the article of Naoussi and Tripier
(2012) is probably the only that proposes a detailed reading of different DSGE models applied to
sub-Saharan Africa. Indeed, the general objective of Naoussi and Tripier (2012) was essentially
twofold: (i) document the specific factors that may explain the high volatility characterizing the
economies of sub-Saharan Africa; (ii) assess the adequate response to these factors monetary and
fiscal policies.
Following the same logic, this article aims to contribute to enrich this documentation in three
ways. We propose: (i) first, to extend the investigation to the African level because Naoussi and
Tripier (2012) consider only the case of sub-Saharan economies; (ii) to characterize the empirical
regularities like in the literature on the macroeconomics of development, and compare them with
the stylized facts ofadvanced economies; (iii) to discuss the value and usefulness of the DSGE
approach to the analysis of macroeconomic implications of monetary, fiscal, real and external
impulses in the least developed countries.
2
We consider the theoretical framework of a simple NK-DSGE model for small open economy to
address main issues on the business cycle fluctuations in the African least developed countries
(LDCs). The conceptual framework is an economy that produces tradable goods for domestic
consumption (households), government consumption and export (rest of world). Monetary policy
is conducted by a central bank with a management based on a simple Taylor rule. We suppose
that the small open economy is vulnerable to exogenous and price taker on world market. Indeed,
based on Monacelli (2003), and Gali and Monacelli (2004), we propose an analyze to extend the
DSGE models of Christiano, Eichenbaum and Evans (2005) by incorporating in the theoretical
analyze several small open economy features and an array of financial frictions, nominal and real
rigidities that have been identified in the standard macroeconomic literature to explain observed
business cycle and that have proven to be important for the empirical fit of models for
development countries. Following Lind (2003).
This paper is organised as follows. In section 2, the African least developed countries are
identified and characterized and Section 3 contains an explanation of the theoretical model. In
section 4, we analyze the usefulness of DSGE approach both in the understanding of cyclical and
in the conduct of macroeconomic policy in Africa.
2. Identification of African Least Developed Countries
The least developed countries (LDCs) are a group of the poorest economies in the world
identified by the United Nations based three criteria: [i] a per capita income criterion; [ii] a human
asset criterion; [iii] an economic vulnerability criterion. Forty-nine countries are currently
designated as LDCs by the UNCTAD report in 2013 with thirty-four African countries; nine
Asian countries; five countries in the Pacific and countries in the Caribbean (Haiti).
Figure 1: Location of the Least Developed Countries
Source: United Nations Conference on Trade and Development (UNCTAD), 2013.
3
According to the spatial and geographical location of individual LDCs:
14 of 18 to the east are LDCs i.e. on the eighteen countries located in East Africa, fourteen
are classified LDCs;
12 of 16 in West Africa are LDCs;
6 of 9 in Central Africa;
1 of 5 in Southern Africa;
1 of 6 in North Africa.
It appears that in Africa the LDCs are mainly located in the western, eastern, and central regions.
Table 1: Identification of African LDCs by region
African By % compared to the Weighting By % compared to the
LDCs African regional location total
East 78 0,33 41
West 75 0,30 35
Central 67 0,17 18
Southern 20 0,09 3
North 17 0,11 3
We can also focus on the identification of LDCs by community. Thus, considering eleven African
communities, we note that:
11 of 15 countries that constitute the Economic Community of West African States
(ECOWAS) are LDCs;
7 of 10 countries for the Economic Community of Central African States (ECCAS);
3 of 6 countries for the Economic and Monetary Community of Central Africa (CEMAC);
20 of 28 countries for the Community of Sahel-Saharan States (CEN-SAD);
All three countries members of the Economic Community of the Great Lakes Countries
(ECGLC);
12 of 20 countries for Common Market for Eastern and Southern Africa (COMESA);
4 of 5 countries for the East African Community (EAC);
6 of 7 countries for the Intergovernmental Authority on Development (IGAD);
8 of 15 countries for the Southern African Development Community (SADC);
1 of 5 countries of the Arab Maghreb Union (AMU);
7 of 8 countries de West African Economic and Monetary Union (UMEAO).
From this list its clear that LDCs are prominent in every community, regardless of location,
except for the case of CEMAC and AMU.
3. Characterization of LDCs and DSGE Paradigm
Before focusing on some stylized facts of developing countries, it is worth note two important
facts characterizing LDCs: the institutional uncertainty and the political instability.
Fundamentally these two factors distort governance and have a direct and negative impact on the
effectiveness of macroeconomic policy. In this environment the issue of credibility and
Jean-Paul K. Tsasa Vangu
@Mail: jeanpaultsasa@lareq.com [February 2014 Larq: www.lareq.com]
4
dependence of institutions vis--vis the political and governmental lobbying constrains the
implementation of objective and sound macroeconomic policies (Kaufmann, Kraay and Zoido-
Lobaton 1999, 2002; Kaufmann, Kraay and Mastruzzi 2003).
Figure 1: Political instability by regions
Source: Economist Intelligence Unit, 2007 2012.
Thus, macroeconomic performances are strongly biased by political instability, e.g. the D.R.
Congo in Central Africa, the Ivory Coast in Western Africa, Egypt in North Africa, Somalia in
Eastern Africa or Zimbabwe in Southern Africa. Indeed, the risk associated with political
instability substantially affects the governance, efficiency of public investment and objectivity in
the strategic choices (fight against corruption, rule of law, regulations, etc.).
Subsequently, it would be more prudent to include the issue of credibility and dependence of the
institutions in the characterization of the macroeconomic dynamics in LDCs. In addition to the
institutional problems, it is also important to note that the implementation of a standard DSGE
model for African LDCs means we characterize the macroeconomic dynamics without
considering the implication of:
The predominance of the informal sector (Charmes 2009; OECD 2009; Yatta 2006):
Table 2: Informal Sector by Region
Informal Sector Informal Sector (% of GDP)
[% of GDP] [Excluding agriculture]
Sub-Saharan Africa 54,7 23,7
North Africa 37,7 26,3
Asia 23,9 21,5
Latin America 30,6 23,4
Caribbean 22,2 19,7
Transition economy 21,7 11,8
5
The preponderance of foreign currency bank deposits and the weak development of the
banking sector:
Graph 1: Percentage of banking by region
44
28 27
24
18
Europe & Central Latin America & the Pacific & East Asia Middle East & North Sub-Saharan Africa
Asia Caribbean Africa
Source: PERIOU C. (eds) [2013.
The existence of a large primary sector with high export orientation (Mendoza 1995).
Moreover, the analysis of the correlation reveals that there is no robust relationship between
macroeconomic performance and the number of communities of belonging.
Graph 2: Correlation macroeconomic performance and number of communities belonging
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Jean-Paul K. Tsasa Vangu
@Mail: jeanpaultsasa@lareq.com [February 2014 Larq: www.lareq.com]
6
The African LDCs that have the level of high per capita incomes are those who take advantage of
their natural resources.
Table 3: African LDCs, Per Capita Income and Growth rate
GDP per capita Growth rate GDP per capita Growth rate
(2009-12, US $) (2009-12, en %) (2009-12, US $) (2009-12, en %)
Angola 4 055,0 4,13 Equat. Guinea 12 022,5 1,63
Benin* 722,5 3,55 Rwanda* 535,0 7,40
Burkina Faso* 610,0 6,15 Sudan*** 1 300,0 -1,68
Congo, DR* 200,0 24,10 Chad ** 907,5 6,70
Source: WDI, World Bank, 2014. Note: The asterisk (*) indicates countries that have reached the
completion point of the Heavily Indebted Poor Countries (HIPC) initiative in late 2012; (**) a
country in interim phase; (***) a country not having reached the decision point of the HIPC
initiative.
The level of inflation in the LDCs is not only high but also very volatile and persistent, implying
the setting of interest rates higher values.
Table 5: African LDCs, Real GDP per capita (2009-2013) and Growth rate (2009-2013)
Inflation rate Real interest rate Government budget balance
(%, 2009-13) (%, 2009-12) (% of GDP, 2009-12)
Angola 12,16 8,13 2,00
Congo, DR 7,30 25,65 2,10
Rwanda 5,78 10,15 -0,70
Source : WDI, World Bank, 2014.
Moreover, the strategies or economic policies that are implemented by combining for example,
governance of natural resources or by providing a security framework and the legal and a political
environment have enabled some LDCs such as Angola, Burkina Faso and Benin to stand out from
other countries.
Table 4: African LDCs, World Peace Index (2013) and Political stability (1999-2004)
World Peace Political World Peace Political
Index (ranking stability Index (ranking stability
of 162 countries) (Rank 1 100) of 162 countries) (Rank 1 100)
1999 2004 1999 2004
Angola 102 18 Equat. Guinea 89 37
Benin 104 35 Rwanda 135 19
Burkina Faso 87 36 Sudan 158 2
Congo, DR 156 1 Chad 138 13
Source: Governance Matters IV: Governance Indicators for 1996-2004.
7
Ceteris paribus, in a politically stable and institutionally regulated environment, the empirical
regularities in advanced economies and low-income countries seem to get closer. This is the case
for example in emerging economies, such as South Africa.
Indeed, failure to satisfy all these contextual conditions, the stylized facts in industrialized
countries appear more uniform, whereas this is not the case for LDCs, where they differ by
country and by region. Below, we identify some features of interest in DSGE modelling in an
African context. Referring Hoffmaister et al. (1998); Agnor et al. (2000); Rand and Tarp (2002);
Pallage and Robe (2001); Bulir and Hamann (2001); Neumeyer and Perri (2005); Jaguar and
Gopinath (2007); Male (2010), the following stylized facts characterize LDCs:
The economic cycles are generally shorter and more volatile for the LDCs than those for
developed countries;
The output is more volatile in LDCs than in developed countries, but there is an almost
similar degree of persistence in output fluctuations in both groups of countries;
The consumption is more volatile than output in LDCs;
The economic activities developed countries, measured by the global output and the real
interest rate have a positive relationship and significant impact on production in most LDCs;
The prices are not always cyclical as for developed countries;
The inflation is not always pro-cyclical in LDCs;
The consumption, investment, real wages, monetary aggregates are generally procyclical in
LDCs. However, their correlations are generally lower than those observed in developed
countries;
The real interest rates are slightly procyclical in developed countries, but they are generally
contracyclical in LDCs, and moreover lead the cycle;
The real interest rates are more volatile in LDCs than in developed countries;
There is no clear relationship in terms of public expenditure, nominal effective exchange rate,
real effective exchange rate, terms of trade and production in LDCs;
The shock of terms of trade that explains on average about half the volatility of GDP is
significantly more volatile in LDCs, and this impact is at the origin of the higher volatility of
production, consumption and trade balance;
The shock of international finance doesn't appear to play a decisive role in economic cycles
for LDCs, however the constraints of access to international finance are a powerful
propagation mechanism.
Thus, in a next paper we will then attempt to characterize these facts using a DSGE model, before
discussing the need to integrate the Schumpeterian foundations in this exercise.
4. Discussions and Conclusion
As illustrated above, a common practice in modern macroeconomics, following the seminal
contributions of Lucas (1972, 1976); Sargent and Wallace (1975); Barro (1976); Kydland and
Prescott (1977, 1982); Hansen and Sargent (1980), is to construct rational expectations models
with micro-foundations to document and characterize the stylized facts observed in the data
provided by the national accounts. Concerning this paradigm we note the main features:
By construction, the various assumptions underlying most canonical DSGE models are more
suited to the realities of the American economy, those of OECD economies or of the Euro
zone;
Jean-Paul K. Tsasa Vangu
@Mail: jeanpaultsasa@lareq.com [February 2014 Larq: www.lareq.com]
8
Despite serious attempts of Aiyagari et al. [1992]; Baxter and King [1993]; McGrattan
(1994); Chari et al. (1996); McGrattan et al. (1997); Chari and Kehoe (1999]; Gal et al.
(2004, 2007), or recently Drautzburg and Uhlig (2011); Christiano et al. (2011); Ravn et al.
(2012), It is apparent that in this class of models, fiscal policy does not seem to care enough
places in the debates (Solow 2002; Linnemann and Schabert 2003; Uhlig 2010);
In addition, the inclusion of fiscal policy in the standard model typically involves ambiguous
effects on the variables of interest such as private consumption and hours of work (Cogan et
al. 2009).
Therefore, such a configuration does not facilitate proper application of the canonical DSGE
models in developing countries or in African economies.
In parallel, it should be noted nonetheless major advances in the effort to make DSGE models
more realistic in both academic and professional program. For example, according to Campbell
and Mankiw (1989), Mankiw (2000) is proposed to improve the foundations supporting
framework for analysing macroeconomic implications of fiscal impulses.
This seminal, contribution Erceg et al. (2006), Gal et al. (2004, 2007) and Ratto et al. (2009)
have developed DSGE models, shiny consumer agent in Ricardian households and non-Ricardian
households to generate the observed effects including consumption or hours, in response to the
impact of public spending.
Also, models taking into account the assumption of a small open economy have also been
developed in recent years. This specification facilitates e.g. the transposition models in the case of
developing countries.
These advances, several institutions are proposed to incorporate the assumption of economic
openness, modelling fiscal policy and monetary policy in a single framework or take into account
the non-Ricardian households in the analysis models. This is the case of the IMF (GIMF Global
Integrated Monetary and Fiscal Model, see Laxton and Pesenti 2003); Federal Reserve (SYGMA
model, see Erceg, Guerrieri and Gust 2006); the European Central Bank (NAWM, New Area-
Wide Model); European Commission (QUEST III, see Ratto, Roeger and Veld 2009); etc.
Moreover, although some variables socio-economic malaise, e.g. unemployment, corruption or
credit constraints, have been included in DSGE models (Gertler et al 2008; Blanchard and Gali
2010; Christiano et al 2011; Gali et al 2012, etc.), it follows that so far, institutional frictions and
parameters specific to developing countries macroeconomic vulnerability are not sufficiently
taken into account or both, remain virtually absent in the canonical models. At the same time, the
macroeconomic literature reveals the existence of a considerable number of studies on African
economies, using the DSGE paradigm. In most cases, the main contribution of these models is the
use of data from African economies to estimate the canonical DSGE models, originally designed
for the advanced economies. Indeed, on the one hand, it is clear that these models are essentially:
(i) duplication of existing canonical models, (ii) transpositions in the context of developing
countries, models designed for advanced economies such as the United States, Canada, the
Eurozone or OECD countries.
9
On the other hand, these models focus on the analysis of monetary policy, fiscal policy or
economic openness, while isolating the issue of the impact of the credibility of the institutions on
the effectiveness of policy macroeconomic. Accordingly, since it follows that advanced
economies and developing countries stand the existence of endogenous factors affecting the
propagation mechanisms of macroeconomic impulses, therefore it is necessary to take more
seriously the proposal Acemolu (2010) mentioned above, with the aim to build DSGE models
with equations painting appropriately enough the African context. So instead of addressing only
on reading and the validity of simulation results after calibration or estimation, it is especially
important to revisit the "foundations".
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