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,

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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,

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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

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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.

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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).

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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

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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.

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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

.

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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

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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.

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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.

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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

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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

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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).

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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).

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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.

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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.

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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

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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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