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Thesis on the relationship between finance and economic growth
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An Empirical Investigation of the Financial Development - Economic Growth Nexus:
The case of Zimbabwe (1990 – 2008)
Jecheche Petros:
Business Studies Department
Faculty of Commerce
University of Zimbabwe
Abstract
The study examines the relationship between financial development and economic growth in Zimbabwe
for the period 1990-2008. The method of principal components is employed to construct a financial sector
development index (FSDI) used to proxy development in the sector. Using the autoregressive distributed
lag (ARDL) approach, the study finds a unique cointegrating relationship among real GDP, financial
development, investment and real deposit rate. The results suggest that financial development exerts a
positive and statistically significant effect on economic growth and investment is an important channel
through which financial development feeds economic growth.
Keywords: Financial Development, Economic Growth, Principal Components, ARDL
Approach,
1
1 Introduction
In recent years the relationship between financial development and economic growth has become
an issue of extensive analysis. The question is whether financial development precedes or simply
follows economic growth. A general proposition states that the development of the financial
sector is expected to have a positive impact on economic growth.
The theoretical relationship between financial development and economic growth goes back to
the study of Schumpeter (1911) who focuses on the services provided by financial intermediaries
and argues that these are essential for innovation and development. The Mckinnon – Shaw
school examines the impact of government intervention on the development of the financial
system. Their main proposition is that government restrictions on the banking system such as
interest rate ceilings and direct credit programs have negative effects on the development of the
financial sector and, consequently, reduce economic growth (Mckinnon 1973, Shaw 1973).
The endogenous growth theory has reached similar conclusions by explicitly modeling the
services provided by financial intermediaries such as risk-sharing and liquidity provision. This
theory also suggests that financial intermediation has a positive effect on steady-state growth and
that government intervention in the financial system has a negative effect on economic growth
(Ghali 1999).
While some economists have generally emphasized the central role of financial markets in
economic growth, the empirical evidence on the relationship between financial development and
economic growth is apparently inconclusive. Several authors have shown a positive link between
financial development and economic growth (see for instance, King and Levine, 1993b; Neusser
and Kugler, 1998; Rousseau and Wachtel, 1998; Levine et al., 2000; Khan and Senhadji, 2003;
Chistopoulos and Tsionas, 2004; Khan et al, 2005; and Khan and Qayyum, 2006).
Robinson (1952) argues that financial development follows economic growth as a result of
higher demand for financial services. On the other hand, some studies show a bi-directional
relationship between financial development and economic growth (Demetriades and Hussein,
2
1996; Luintel and Khan, 1999) while others reject the existence of a finance-growth relationship
(Lucas, 1988).
Empirically, studies that have used cross-section and panel data generally support the positive
effect of financial development on economic growth. On the contrary, the studies based on time
series data give contradictory results (Khan et al, 2005 and Kiran et al, 2009). However,
empirical studies based on cross-sectional data may not satisfactorily address country-specific
effects as these countries could be at different stages of financial and economic development (see
Odhiambo, 2009). According to Badun (2009), differences in financial sector development may
reflect different institutional characteristics, different policies, and differences in their
implementation. Therefore, there is need to investigate the finance-growth relationship on a
country case basis. Establishing this relationship is crucial because it has significantly different
implications for development policy (Calderon and Liu, 2003; and Kiran et al, 2009).
However, despite the prominent role of the financial sector in influencing economic growth,
Zimbabwe is still characterized by underdeveloped financial markets which constrain resource
mobilization and hinder economic growth. Financial sector reform policies were adopted in the
1990s as part of a structural adjustment programme to ensure a competitive and efficient
financial sector to support development of the economy. Despitethe gradual improvement in the
mobilization of financial savings following the reform process the level of mobilized financial
savings and hence private sector credit allocation has not been enough to stimulate private
investment and growth.
Although there has been extensive empirical studies testing the views on the finance-
growthnexus, few studies have investigated this relationship in Zimbabwe. In particular, the
general observation from previous studies is that such a relationship has been examined using
either a single indicator of financial development (Sakutukwa, 2008) or different indicators
separately (Ahmed, 2009). Given the rudimentary nature of the financial sector in Zimbabwe, it
is unlikely that the use of one or more indicators separately will reflect the developmental level
of the sector. As the choice of the financial development indicator may influence the ultimate
findings of the study, it will be more appropriate to combine the indicators together as they tend
3
to complement each other, to generate a financial sector development index as a proxy for
government policy in the sector.
The objective of this paper is to examine the relationship between financial development and
economic growth in Zimbabwe. The Autoregressive Distributed Lag (ARDL) approach is
applied using annual data over the period 1990-2008. This paper makes an empirical contribution
to existing literature on Zimbabwe by employing a composite index of financial sector
development constructed by principal components analysis to establish the finance-growth
relationship.
The rest of the paper is organized as follows. Section 2 reviews the theoretical and empirical
literature on the finance-growth nexus. Section 3 describes the model, ARDL approach and data.
The analysis is given in section 4, while section 5 concludes the paper.
4
2 Review of Theoretical and Empirical Literature
2.1 Theoretical Literature
The relationship between financial development and economic growth has been the subject of
much debate both at the theoretical and empirical levels. Financial systems have long been
recognized to play an important role in economic growth and development. Following
Schumpeter (1911), and more recently McKinnon (1973) and Shaw (1973), the relationship
between financial development and economic growth has been extensively studied.
Generally, the literature has documented four views on the finance-growth nexus; supply
leading, demand following, mutual impact of finance and growth and those that suggest that the
role of finance in promoting economic growth is overemphasized. Patrick (1966) identified two
possible directions of causality between financial development and economic growth. These
relationships were labeled as the supply-leading and demand following.
The supply leading view postulates a positive impact of financial development on economic
growth, which means that creation of financial institutions and markets increases the supply of
financial services and thus leads to economic growth. Patrick advocated for a supply leading
strategy that ensures the creation of financial institutions and the supply of their assets, liabilities
and related services in advance of demand forthem. The supply-leading finance performs two
functions: to transfer resources from traditional (non-growth) sectors to modern high-growth
sectors, and to promote and stimulate an entrepreneurial response in these modern sectors. He
argues that supply leading finance would exert a positive influence on capital by improving the
composition of the existing stock of capital, allocate efficiently new investments among
alternative uses, and raise the rate of capital formation by providing incentives for increased
saving and investment. The supply-leading finance will cause economic development through
the transfer of scarce resources from savers to investors according to the highest rates of return
on investment.
The McKinnon-Shaw hypothesis supports the supply-leading argument of Patrick (1966).
5
McKinnon (1973) suggests a complementarity relationship between the accumulation of money
balances (financial assets) and physical capital accumulation in developing countries. He
considers an outside model of money demand. The author argues that due to underdeveloped
financial markets in most developing countries, there are limited opportunities for external
finance and all firms are confined to self-finance. Given that investment expenditures are lumpier
than consumption expenditure, potential investors must first accumulate money balances prior to
undertaking relatively expensive and indivisible investment projects.
The ‘debt-intermediation’ view proposed by Shaw (1973) is based on an inside money model.
Shaw (1973) argues that high interest rates are essential in attracting more saving. With more
supply of credit, financial intermediaries promote investment and raise output growth through
borrowing and lending.
However, in the early 1980s the theoretical underpinnings of the financial liberalization theory
were criticized by some economists notably, the neo-structuralists, led by Van Wijnbergen
(1983) and Taylor (1983) who predicted that financial liberalization would slow down economic
growth. The demand -following view postulates a causal relationship from economic growth to
financial development. Patrick (1966) argues that the creation of modern financial institutions,
their financial assets and liabilities and related financial services are a response to the demand for
these services by investors and savers in the real economy. Thus,economic growth creates a
demand for developed financial institutions and services.
Robinson (1952) had earlier pointed out that finance does not exert a causal impact on growth.
Instead financial development follows economic growth as a result of higher demand for
financial services. As such, an increasing demand for financial services might induce an
expansion in the financial sector as the real economy grows (i.e. financial sector responds
positively to economic growth). This line of reasoning is also supported by Gurley and Shaw
(1967), Goldsmith (1969) and Jung (1986).
Patrick (1966) however argues that the causal relationship between financial development and
economic growth varies according to the stages of the development process. He suggests that the
supply-leading pattern dominates during the early stages of economic development. As financial
6
development and economic development proceed, the supply-leading characteristics of financial
development diminish gradually and are eventually dominated by demand followingfinancial
development.
Recent literature on the endogenous growth theory has rekindled the debate on the relationship
between financial development and economic growth. Since the 1990s, several authors have
incorporated financial institutions in the analysis of endogenous growth models (for instance,
Greenwood and Jovanovic, 1990; and King and Levine, 1993b).
These models show that economic growth performance is related to financial development,
technology and income distribution (Caporale et al, 2003). Greenwood and Jovanovic
(1990) consider a model that allows examining the relation between growth and income
distribution, as well as between financial structure and economic development. The authors
assume a positive two-way causal relationship between financial development and growth.
On the one hand, financial institutions collect and analyze information in order to find the
investment opportunities with the highest return. They channel funds to the most productive
uses, thereby increasing the efficiency of investment and growth. On the other hand, growth
provides the means needed to implement and develop a costly financial structure.
King and Levine (1993 b) identify innovation as the engine of growth, which accords with the
line of reasoning of Schumpeter. They argue that an efficient allocation of funds fromfinancial
intermediaries to entrepreneurs is able to lower the cost of investing in productivity enhancement
and stimulates economic growth. Financial intermediaries and securities markets enable
particular entrepreneurs to undertake innovative activity, which affects growth through
productivity enhancement. Financial systems can influence the decision of entrepreneurs to
invest in productivity enhancing activities by evaluating entrepreneurs, pooling resources,
diversifying risk and valuing the expected profits from innovative activities. Therefore, financial
markets help the efficient allocation of resources which increase the probability of successful
innovation. The rate of innovation is reduced with the existence of distortions like deposit rate
ceilings or high reserve requirements.
7
On the contrary, Lucas (1988) rejects the existence of a finance-growth relationship. Theauthor
argues that economists tend to over-emphasize the role of financial factors in the process of
growth. Development of the financial markets may well turn out to be an impediment to
economic growth when it induces volatility and discourage risk-averse investors from investing
(Singh, 1997). Besides, the introduction of certain financial tools that allow individuals to hedge
against risks may lead to a reduction in the precautionary saving and hence lowers economic
growth (Mauro, 1995).
2.2 Empirical Literature
The evidence on the relationship between financial development and economic growth suggests
enormous heterogeneity across countries, regions, financial factors, and directions of causality
(Eschenbach, 2004). Several empirical findings support the supply leading hypothesis. King and
Levine (1993b) used cross-section analysis to examine the relationship between financial
development and economic growth during the period 1960-89. The measures of financial
development used are the ratio of liquid liabilities of banks and nonbank institutions to GDP,
ratio of bank credit to the sum of bank and central bank credit, ratio of private credit to domestic
credit and ratio of private credit to GDP. The study found that the level of financial development
predicts future economic growth and future productivity advances. The authors have interpreted
it as evidence of a causal relationship that runs from financial development to economic growth.
Odedokun (1996) used time-series regression analysis for 71 developing countries withvarying
periods from 1960-1980 and found that financial intermediation promotes economic growth in
roughly eighty five percent of the countries. The results further indicated that the growth-
promoting patterns of financial intermediation do not vary across countries and regions.
Neusser and Kugler (1998) examined the finance-growth relationship for 13 Organization for
Economic Cooperation and Development (OECD) countries for the period 1970-1991. Using
time series analysis, the study showed a positive correlation between financial development and
growth. Unlike Odedokun (1996), the authors found that the causal structure underlying the
relationship varies widely across countries. By employing time series analysis, Rousseau and
.
8
Levine et al. (2000) conducted the study on 71 countries for the period 1960 to 1995. The ratio
of liquid liabilities to GDP, ratio of deposit money banks domestic assets to deposit money banks
domestic assets plus central bank domestic assets and ratio of credit issued to private enterprises
to nominal GDP were used as financial indicators. The findings supported the positive
correlation between financial system and economic growth. Theauthors suggested that legal and
accounting reforms should be undertaken to strengthencreditor rights, contract enforcement and
accounting practices in order to boost financial intermediary development and thereby accelerate
economic growth.
Allen and Ndikumanu (2000) used various indicators of financial development to examine the
role of financial intermediaries in promoting economic growth in Southern Africa. The results
found evidence of the positive relationship between financial development and economic growth.
Khan and Senhadji (2003) examined the relationship between financial development and
economic growth for 159 countries over the period 1960-1999 using cross-section data. To
address the problem of potential endogeneity in the underlying relationship, the two-stage least
squares (2SLS) was employed. The study found that financial development has a positive and
statistically significant effect on economic growth.
Chistopoulos and Tsionas (2004) conducted the study on 10 developing countries toexamine the
relationship between financial development and economic growth using panel analysis. The
authors used the ratio of total bank deposits liabilities to nominal GDP as a measure of financial
depth and included the ratio of investment to GDP and inflation rate as control variables. The
results showed the presence long-run causality running from financial development to economic
growth but there was no evidence of bi-directional causality. Also, the study did not find any
short-run causality between financial deepening and output. The study suggests that improving
financial markets will have an effect on growth that is delayed but nevertheless significant.
Fatima (2004) examined the causal relationship between financial development and economic
growth in Morocco for the period 1970-2000. The ratio of liquid liabilities (M3) to GDP, ratio of
9
domestic credit provided by the banking sector to GDP and domestic credit to the private sector
to GDP were the financial depth indicators used. Using the
Granger causality test, the study found a short-run relationship between financial development
and economic growth.
The study by Ndebbio (2004) was conducted on selected Sub-Saharan African countries (SSA).
Using the ratio of M2 to GDP and growth rate in per capita real money balances as indicators of
financial development, the study found positive and statistically significant impact of growth rate
in per capita real money balances on real per capita GDP growth.
Khan et al (2005) investigated the link between financial development and economic growth in
Pakistan over the period 1971-2004. By employing the autoregressive distributed lag approach,
the study found that financial depth exerted positive impact on economic growth in the long run
but the relationship was insignificant in the short-run. The ratio of investment to GDP exerted
positive influence on economic growth in the short-run but alsoinsignificant in the long run. The
study also showed a positive impact of real deposit rateon economic growth. The authors
recommended that policy makers should focus attention on long run policies to promote
economic growth, for example, the creation of modern financial institutions, in the banking
sector and the stock market.
10
3 Methodology
3.1 Model Specification
The theoretical literature discussed above predicts that real income, financial development and
real interest rate are positively correlated. The positive relationship between the level of output
and financial depth is derived from the complementarity between the accumulation of money
balances (financial assets) and physical capital accumulation (Mckinnon, 1973). McKinnon
(1973) argues that investment in a typical developing country is lumpy and self-financedand
hence cannot be materialized unless adequate savings are accumulated in the form of bank
deposits.
Shaw (1973), on the other hand, postulates that financial intermediaries promote investment
which, in turn, raises the level of output. A positive real interest rate increases financial depth
through the increased volume of financial saving mobilization and promotes growth through
increasing the volume of productivity of capital. High real interest rates exert a positive effect on
the average productivity of physical capital by discouraging investors from investing in low
return projects (World Bank, 1989; Fry, 1997).
Based on these theoretical views and following Christopoulos and Tsionas (2004), Ang and
McKibbin (2005), Khan et al (2005) and Khan and Qayyum (2006), the relationship between
economic growth and financial development can be specified as:
LRGD Pt=α 0+α1 LFSD I t+α2 LINV Gt+α3 RI Rt+α4 INF+α 5 FSLD+εt (1)
Where RGDP is real GDP, FSDI is a measure of financial depth, INVG is the ratio ofinvestment
to GDP, RIR is real deposit rate, INF is a dummy variable introduced to capture the effect of the
hyper inflationary period, FSLD is an interactive term to account for financial liberalization
effect and ε tis an error term. Real GDP, INVG and FSDI are expressed in natural logarithm.
11
From the literature, the coefficients of financial depth, investment and real deposit rate
areexpected to be positive. The inclusion of the share of investment in GDP as a conditioning
variable allows us to test the channel through which financial development affects economic
growth, through increasing productivity or through increasing savings resources and therefore
investment (Abu-Bader and Abu-Qarn, 2006). The interactive term is also expected to exert
positive effect on real GDP. However, the coefficient of hyperinflation dummy is expected to be
negative since the hyperinflation inhibited the mobilization of financial savings and generally
created an environment that was not conducive for investment.
3.2 Estimation Procedure
Since the focus of this paper is to establish the relationship between financial developmentand
economic growth, an appropriate technique is to adopt cointegration analysis and error correction
modeling. Therefore, the Autoregressive Distributed Lag (ARDL)approach (i.e. the bounds
testing approach to cointegration) popularized by Pesaran and Pesaran (1997), Pesaran and Shin
(1999) and Pesaran et al (2001) is used in the study. This approach has some econometric
advantages over the Engle-Granger (1987) and maximum likelihood based approach proposed by
Johansen and Juselius (1990) and Johansen (1991) cointegration techniques.
Firstly, the bounds test does not require pre-testing of the series to determine their order of
integration since the test can be conducted regardless of whether they are purely I(1), purely I(0),
or mutually integrated. Second, the ARDL modeling incorporates sufficient number of lags to
capture the data generating process general to specific modeling framework (Laurenceson and
Chai, 2003 quoted in Shrestha and Chowdhury, 2005; and Jalil, et. al, 2008).
In addition, endogeneity problems are addressed in this technique. According to Pesaranand Shin
(1999), modeling the ARDL with the appropriate lags will correct for both serial correlation and
endogeneity problems. Jalil et al (2008) argue that endogeneity is less of a problem if the
estimated ARDL model is free of serial correlation. In this approach, all the variables are
assumed to be endogenous and the long run and short run parameters of the model are estimated
simultaneously (Khan el al, 2005). The issue of endogeneity is particularly relevant since the
causal relationship between financial development andeconomic growth cannot be ascertained
12
beforehand. The literature suggests that a bidirectional relationship could exist between financial
development and economic growth.
This implies that the proxy for financial sector development is a potentially endogenousvariable
in equation 1, which justifies the use of the bounds technique. The ARDL has superior small
sample properties as compared to the Johansen and Juselius(1990) cointegration test (Pesaran
and Shin, 1999). Therefore, the approach is considered to be very suitable for analyzing the
underlying relationship and has been increasingly used in empirical research in recent years. An
ARDL representation of equation (1) can be specified as follows:
∆ LRGD Pt=β0+∑i=1
ρ
β1 i∆ LRGDPt−i∑i=1
ρ
β2 i ∆ LFSD I t−i+∑i=1
ρ
β3 i❑ ∆ LINV Gt−i+∑i=1
ρ
β4 i∆ RI R t−i+δ 1 LRGDPt−1+σ 2 LINV Gt−1+σ3 LFSD I t−1+σ4 RI Rt−1+γ1 INF+γ2 FSLD+V t
(2)
Where ∆is a difference operator, ρis the lag length andVtis assumed to be seriallyuncorrelated.
The approach involves the following steps. In the first stage, the null hypothesis of no
cointegration relationship which is defined as H0: σ1 = σ2 = σ3 = σ4 = 0is tested against the
alternative hypothesis H1: σ1≠ σ2≠ σ3≠σ4 ≠0of the existence of cointegrating relationship.
Thecointegration test is based on the F-statistics or Wald statistics. The F-test has a nonstandard
distribution. Thus, Pesaran and Pesaran (1997) and Pesaran et al (2001) have provided two sets
of critical values for the cointegration test. The lower critical bound assumes that all the variables
are I(0), meaning that there is no cointegration among the variables, while the upper bound
assumes that all the variables are I(1). If the computed F statistic is greater than the upper critical
bound, then the null hypothesis will be rejected suggesting that there exists a cointegrating
relationship among the variables. If the F-statistic falls below the lower critical bounds value, it
implies that there is no cointegration relationship.
However, when the F-statistic lies within the lower and upper bounds, then the test is
inconclusive. In this context, the unit root tests should be conducted to ascertain the orderof
integration of the variables. If all the variables are found to be I(1), then the decision istaken on
13
the basis of the upper critical value. On the other hand, if all the variables are I(0), then the
decision is based on the lower critical bound value.
Once cointegrating relationship is ascertained, the long run and error correction estimatesof the
ARDL model are obtained. The diagnostic test statistics of the selected ARDL model can be
examined from the short run estimates at this stage of the estimation procedure. Similarly, the
test for parameter stability of the model can be performed. The error correction representation of
the series can be specified as follows:
∆ LRGD Pt=β0+∑i=1
ρ
β1 i∆ LRGDPt−i∑i=1
ρ
β2 i ∆ LFSD I t−i+∑i=1
ρ
β3i ∆ LINV Gt−i+∑i=1
ρ
β4 i ∆ RI R t−i+ξEC M t−1+γ1 INF+γ2 FSLD+μt
(3)
Where ξ is the speed of adjustment parameter and ECM is the residuals obtained fromequation 1
(i.e. the error correction term). The coefficient of the lagged error correction term (ξ) is expected
to be negative and statistically significant to further confirm the existence of a cointegrating
relationship.
3.3 Data Description
Choosing an appropriate measure of financial development is crucial in analyzing therelationship
between financial development and economic growth. Construction of financial development
indicators is an extremely difficult task due to the diversity of financial services catered for in the
financial system (Ang and McKibbin, 2005). Due to underdeveloped financial markets in
Zimbabwe and consequently lack of data on stock market development, the indicators of
financial development used in the study only reflect developments in the banking sector.
Several indicators of financial depth have been used in the empirical literature as proxy for
development of the financial sector. However, in this paper three financial development
indicators are used- ratio of banking deposit liabilities to GDP, ratio of private sector credit to
GDP, and the ratio of private sector credit in domestic credit. The ratio of broad money (M2) to
GDP is considered to be a standard measure of financialdevelopment (World Bank, 1989).
14
However, this ratio measures the extent of monetization rather than financial development (Khan
and Qayyum, 2006). In most developing countries, a higher ratio of money to GDP may not
necessarily reflect increased financial depth as money is used as a store of value in the absence
of other more attractive alternatives (see Khan and Senhadji, 2003). Hence, the ratio of banking
deposit liabilities toGDP is used as the first proxy for financial development, which is calculated
by subtractingcurrency in circulation from M2 and dividing by nominal GDP.
The second measure of financial development is the ratio of domestic credit to the private sector
to GDP. This ratio excludes the public sector and therefore reflects more efficient resource
allocation in the economy since the private sector is able to utilize funds in more efficient and
productive manner as compared to the public sector. The next ratio, private sector credit to
domestic credit shows the share of credit to the private sector in total domestic credit and also
measures the extent to which the banking system channels funds to the private sector to facilitate
investment and growth.
Using all three indicators of financial development separately in the same model can cause the
problems of multicolinearity and over-parameterization. Since the literature does not explicitly
specify the most effective measure of financial development, an appropriate technique to avoid
these problems is to generate an index comprising all three indicators. Thus, a financial sector
development index (FSDI) is constructed to represent government policy in the financial sector
(following Khan and Qayyum, 2006).
Real GDP is measured by dividing nominal GDP by the consumer price index (CPI 1990=
100). The share of investment is proxied by the ratio of gross fixed capital formation to nominal
GDP. Real deposit rate is calculated by subtracting the rate of inflation from the nominal deposit
rate of commercial banks. Data on all the variables were obtained from the International
Financial Statistics (IFS) CD ROM and the Reserve Bank of Zimbabwe. The dummy variable
INF takes the value of 1 in period of the hyperinflation (2000-2008) and zero otherwise.
The interactive term (FSLD) is computed as a dummy for financial liberalization (with 1 during
the liberalization period, 1991-1996 and 0 otherwise) multiplied by the financial sector
development index (FSDI).
15
3.4 Construction of Financial Sector Development Index
Following the expositions of Ang and McKibbon (2005) and Khan and Qayyum (2006), the
principal component analysis (PCA) is used to construct a financial sector development index
from three proxies of financial development. This avoids the potentially high correlation among
the different measures of financial development. According to Sricharoen and Buchenrieder
(2005: p.2), “PCA is an indicator reduction procedure to analyze observed variables that would
result in a relatively small number of interpretable components (group of variables), which
account for most of the variance in a set of observed variables”. The eigenvalues are calculated
for each component. The size of an eigenvalue indicates the amount of variance in the principal
component explained by each component. The first principal component reflects the largest
proportion of the total variability in the set of indicators used. The second component accounts
for the next largest amount of variability not accounted by the first component, and so on.
16
4 Empirical Analysis
4.1 Unit Root Test
Even though the bounds test for cointegration does not require pre-testing of the variables for
unit root, it is imperative that this test is conducted to ensure that the series are not integrated of
an order higher than one. This approach is necessary to avoid the problem of spurious results.
The Augmented Dickey-Fuller (ADF) test is employed. The Schwartz- Bayesian Criterion (SBC)
and Akaike Information Criterion (AIC) are used to determine the optimal number of lags
included in the test. The results of the ADF test are reported in Table 1. The results suggest that
all the variables are integrated of order one i.e. stationary after first difference except real deposit
rate which is stationary in level. This result gives support to the use of ARDL bounds approach
to determine the long-run relationships among the variables.
Table 1: Unit Root Test
Variable Lag
ADF test statistic (intercept with no trend)
ADF test statistic (intercept with trend)
Level First difference Level First differenceLRGDP 1 -1.49 -4.0075 -0.52158 -4.5256LFSDI 1 -1.6042 -4.2134 -0.51149 -4.9017LINVG 1 -1.656 -5.1895 -1.3885 -5.2097RIR 0 -3.99 -4.3114
4.2 Cointegration Analysis
Given a relatively small sample size (39) and the use of annual data, a lag length of 2 is used in
the bounds test. For annual data, Pesaran and Shin (1999) suggest a maximum of 2 lags (also
Narayan, 2004; and Narayan and Siyabi, 2005). The results of the bound test are given in table 2.
17
Table 2: Bounds Test Results
Test statistic Value Lag
Bound critical values (Restricted intercept and no trend
F- statistic 4.4373 2 I(0) I(1)
1% 4.434 5.642
5% 3.116 4.094
10% 2.596 3.474
FLFSDI (.) = 1.4414, FLINVIG (.) = 2.8142, FRIR (.) = 1.7746
The F-statistic for the model is 4.4373, which is greater than the upper critical bound (4.094) at
the 5 percent significance level. This suggests that there is a long-run relationship among real
GDP, financial development index, ratio of investment to GDP and real deposit rate. When the
financial development index is taken as dependent variable, there is no evidence of the existence
of a cointegrating relationship as the calculated F-statistic (1.4414) falls below the lower critical
bound (3.116). Similarly, no long run relationship is found when other variables are taken as
dependent variables. Thus, the results imply that there is a unique cointegrating relationship
among real GDP and the explanatory variables.
4.3 Static Long-Run Results
The existence of a long run relationship among real GDP and its explanatory variables suggests
the estimation of long run coefficients and short run dynamic parameters. The estimation of the
ARDL model is based on the Akaike Information Criterion (AIC). The static long-run results and
the diagnostic test statistics of the estimated model based on short run estimates are reported in
table 3.
The financial development index, investment and real deposit rate have the expected positive
sign and exert statistically significant effects on real GDP. An increase in real deposit rate
facilitates financial savings and increases real income. The positive impact agrees with the
supply leading view of the relationship between financial development and economic growth in
18
accordance with the prediction by McKinnon- Shaw hypothesis. The coefficient of the financial
development index implies that a 1% increase in the index increases real GDP by 0.46 percent.
The result accords with the findings by Khan and Qayyum (2006) for Pakistan but contradicts
the findings by Esso (2009) and Ahmed (2009) for Zimbabwe. Ahmed (2009) found negative but
significant relationship for Zimbabwe when private sector credit was used, and the relationship
was positive but insignificant when domestic credit was employed.
Financial development raises the capacity of financial intermediaries to supply funds and feeds
economic growth through the channel of increased investment. This is confirmed by the positive
and statistically significant effect of the ratio of investment to GDP at the 10 percent level. The
result agrees with the findings by Sanusi and Salleh (2007) for Malaysia. The magnitude of the
coefficient implies that a 1 percent increase in investment to GDP ratio increases real GDP by
0.26 percent.
Similarly, real deposit rate exerts a positive effect on real GDP and it is statistically significant at
the 1 percent level. A 1 percent rise in real deposit rate increases real GDP by 0.31 percent. The
positive and significant impact is consistent with the findings by Khan et al (2005) and Khan and
Qayyum (2006). The interactive term for financial liberalization is not significant. The dummy
variable for hyperinflationary period (INF) was dropped because it was insignificant although it
had the expected negative sign.
Table 3: Long-run Estimates based on AIC- ARDL (1,0,0,0,2) Dependent Variable is LRGDP
Variable Coefficient Standard error T- ratioLFSDI 0.46399 0.082506 5.6237***LINVG 0.25566 0.12854 1.9890*RIR 0.0030791 0.0010465 2.9421***FSLD -0.0085177 0.0086905 -0.98011INPT 8.5935 0.22146 38.8037***
Note: ***,* imply significant at the 1 and 10 percent levels respectively.
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4.4 Short-Run Dynamics
The results of the short-run dynamics associated with the ARDL (1,0,0,0,2) are reported in table
4. The coefficient of the lagged error correction term (-0.73796) is negative and statistically
significant at the 1 percent level. The negative and significant coefficient is an indication of
cointegrating relationship among real GDP, financial development, investment and real deposit
rate (see Hossein, 2007; and Dara and Sovannroeun, 2008). The magnitude of the coefficient
implies that 74 percent of the disequilibrium caused by previous year’s shocks converges back to
the long-run equilibrium in the current year.
The results of short-run dynamic coefficients indicate that the variables have the expected signs
as in the long run. Short run changes in financial development index have positive and
statistically significant effect on economic growth at the 1 percent level. The coefficient of short
run change in the share of investment in GDP is also positive and statistically significant at the
10 percent level. The positive and significant effect of investment is consistent with the results
by Khan et al (2005) for Pakistan. The results further suggest that a rise in real deposit rate in the
short run will exert a positive effect on economic growth.
This result agrees with the findings by Khan et al (2005) and Khan and Qayyum (2006) for
Pakistan. However, the interactive term for financial liberalization exerts a negative and
significant impact on economic growth, suggesting that further financial sector reforms are
needed to facilitate financial development for economic growth.
Table 4: Short Run Dynamic Results
Variable Coefficient Standard error T- ratiodLFSDI 0.34241 0.0926 3.6977***dLINVG 0.18867 0.1109 1.7012*dRIR 0.0022722 0.0007487 3.0350***dFSLD -0.026604 0.011561 -2.3013**dFSLD1 -0.01625 0.011299 -1.4382dINPT 6.3417 1.4903 4.2554***Ecm(-1) -0.73796 0.17394 -4.2426***
Note: ***,** ,* imply significant at the 1, 5 and 10 percent levels respectively.
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5 Conclusions and Policy Recommendations
The paper has examined the relationship between financial development and economic growth in
Zimbabwe over the period 1990-2008. The bounds testing approach to cointegration was adopted
to estimate the long run relationship and short run dynamic parameters of the model. The test
suggests that there exists a unique cointegrating relationship among real GDP, financial
development, investment and real deposit rate.
In both the short run and long run, financial development index, ratio of investment to
GDP and real deposit rate exerted positive effects on economic growth. The positive and
statistically significant effect of financial development is supportive of the supply leading
hypothesis in accordance with the predictions by McKinnon (1973) and Shaw (1973). The results
imply that financial development feeds economic growth through the channel of increased
investment. In the short-run, the interactive term to control for financial liberalization has a
negative sign, suggesting that further financial sector reform measures need to be implemented to
facilitate development of the sector for economic growth.
The coefficient of the lagged error correction term is negative and statistically significant, further
confirming the existence of a long run relationship among real GDP and its determinants. The
magnitude of the coefficient implies that 74 percent of the disequilibrium caused by previous
year’s shocks converges back to the long-run equilibrium in the current year.
The study has underscored the importance of the financial sector in influencing economic growth
in Zimbabwe. The findings indicate that economic growth can be stimulated by the adoption of
both short run and long run policies to ensure development of the financial sector.
Therefore, the policy suggestions for enhanced economic growth will be for policy makers to
facilitate the establishment of financial institutions to increase credit delivery to the private
sector especially in rural areas which have limited access to financial services; create the
enabling legal environment for efficient allocation of credit to the private sector through the
adoption of reforms to strengthen creditors rights and enforce commercial contracts; and
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strengthen the operations of the Zimbabwe Stock Exchange, which serves as a source of medium
and long term finance for investment.
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