Effects of private investment on economic growth in Ethiopia

Table of Contents

Abstract

CHAPTER ONE

INTRODUCTION

CHAPTER TWO
LETERATURE REVIEW
Conceptual Issues
2.1 Overview of Historical Development
2.1.1 Trends of Private Investment in Ethiopia
2.1.2 Performance of private investment in Ethiopia
2.1.3. Opportunities of private investment in Ethiopia
2.1.3.1 Strategic Sectors for Foreign Investment in Ethiopia
2.1.4. Challenge of private investment in Ethiopia
2.1.4.1. Land Expropriation
2.1.4.2. Environmental Pollution
2.2 THEORETICAL FRAMEWORK
2.2.1 The Neoclassical Growth Model
2.3. Empirical Literature

CHAPTER THREE
Research Methodology
3.1. Data Source
3.2. Expected Sign of the variable
3.3. Estimation Method
3.3.1 Unit roots
3.3.2. Long run Autoregressive Distributed Lag (ARDL) Model
3.3.3 Short run ARDL Model
3.3.4 Long Run Diagnostic and Stability Tests
3.4 Model Specification
3.4.1 Autoregressive Distributed Lag (ARDL) Model

4.2. Unit Root Test
4.3. Testing for Bounds Test or Co-Integration
4.4. Diagnostic test Checking
4.4. Long run model
4.5 Short Run/Error Correction Model

CHAPTER FIVE
CONCLUSION AND POLICY IMPLICATIONS
5.1 Introduction
5.2 Conclusion
5.3 Recommendation

References

LIST OF TABLES

Table 1.1: Number of Projects, Capital and Jobs Created by Operational Investment(Capital in millions of Birr) .

Table 1. 2: Description and Measurement of Variables Studied

Table 1.3: Descriptive Statistics

Table 1.4: Unit Root Tests of the Variables at Level and First Difference

Table 1.5: ARDL Bounds Test for Cointegration

Table 1.6: Serial correlation test

Table 1.7: Heteroskedasticity test

Table 1.8: Estimated Long Run Coefficients

Table 1.9: Estimated Short Run Coefficients (ECM)

LISTS OF FIGURES

Figure 1.1:Trends of private investment as a percentage share of GDP(1986-2014)

Figure 1.2:Normality test

Figure 1.3:CUSUN and CUSUMSQ test

Acronym

Abbildung in dieser Leseprobe nicht enthalten

Abstract

The main objective of this study is to investigate the effect of private investment on economic growth in Ethiopia for utilizes annual time-series data from 1986 to 2020. To achieve the goal of this study, Autoregressive Distributed Lag (ARDL) Approach to Bounds test and Error Correction Model. Data was collected from National Bank of Ethiopia (NBE). The finding of the Bounds test shows that there is a stable long run relationship in all variables. The empirical results suggest that lag private investment and bank credit exerts a positive and statistically significant effect on private investments, in the long run, real effective exchange rate, import, inflation rate and real lending rate a negative and statistically significant effect on private investment in the long run. The estimate of the speed of adjustment coefficient found in this study indicates that about 84.9 percent of the variation in the economic growth from its equilibrium level is corrected within a year. Based on the findings of the empirical analysis, the study recommends that private investment have a positive effect on economic growth; as for credit, time should be effort towards ensuring a fair distribution of credit among different sectors so that some sectors do not reap all the benefit or incentives alone. This implies that government should consist to control as distribute credit to sector where it is mostly need. This will enhance the less developed sector and enable them have a chance to avail themselves to credit for investment which will in turn stimulate economic growth.

Keywords : private investment, economic growth; ARDL Co-Integration, Ethiopia

CHAPTER ONE INTRODUCTION

Economic growth and development are largely dependent on a country's capacity to invest and use its resources efficiently and productively. In truth, growth is impossible without significant and high-quality investment. As a result, according to Bayraktar (2003), investment is both the result and the cause of economic growth. The private sector's contribution to the quantity of gross domestic investment, as well as its capacity to allocate and deploy resources efficiently, is critical. Private sector investment has been a driving force behind the creation of jobs and income, as well as the provision of infrastructure and social services. The role of the private sector in improving economic growth in underdeveloped countries has also been recognized by international organizations. The European Commission (EU) (2014), for example, stated that the private sector in developing countries has the ability to generate inclusive and sustainable growth. The fast growth of FDI over the last decade has intrigued prominent economists and policymakers to examine FDI's impact on economic growth. Empirical findings for the effect of FDI on economic growth show a positive result for most recipient countries. The main benefits include spillover knowledge such as packages of capital, technical skills, managerial and organizational knowhow (Astatike & Assefa, 2005). FDI is a crucial component to developing countries and provides access to resources and technology that otherwise would not be available. Investment is an important component of aggregate demand and a leading source of economic growth. Change in investment not only affect aggregate demand but also enhance the productive capacity of an economy. The function of investment in extending the economy's productive capacity and promoting long-term economic growth is critical (Jongwanich and Kohpaiboon, 2008). Faster economic growth is triggered by higher investment rates.

In Ethiopia, attracting Private investment is one of the government's main priorities for economic growth. Businesses in the poorest developing countries, such as Ethiopia, usually operate in investment climates that deter them from investing and growing. Ethiopian investors complain about weak infrastructure, including power outages, bad transportation, poor telecom connectivity of commercial locations, and ineffective tax administration in this context (Mima and David, 2012; World Bank, 2004). The Ethiopian economy has been deteriorated by prolonged internal and external wars, wrong policies and recurrent drought coupled with ever­rising population resulting into economic stagnation, image deterioration and unattractiveness to investment expansion in spite of the recent revival. Therefore, examining the effect of private investment on economic growth in Ethiopia has its importance. Private investment has played an essential role in Ethiopian economic growth and attracted multinational companies. Studies about the contribution of private investment inflows and their relationship to economic growth are not well explored in Ethiopia. Therefore, this study assumes to fill this gap and better understand the relationship between private investment and Ethiopia's economic growth.

The paper is organized as follows. After this introduction, the following section reviews the relevant literature, both theoretical and empirical. After this review, the methodological framework is presented. A series of test are show to assess the sensibility of the model. The discussion of the results is presented. Finally, some concluding remarks are shown.

CHAPTER TWO

LETERATURE REVIEW

The purpose of this chapter is to review the related literature on the area of the effects of private investment on economic growth. This establishes a framework that guides the study. Theoretical and empirical literature will address the key sections of the section. The first part deals with theoretical literature, and empirical study is analyzed in the second part.

Conceptual Issues

2.1 Overview of Historical Development

2.1.1 Trends of Private Investment in Ethiopia

Private investment as a percentage share of GDP Exhibit different trends in Ethiopia from 10.40% of GDP in 1986GC to the end of period specified in this study 21.78 % of GDP in 2015GC. In the period the maximum amount 67.99% registered in 2008, while the minimum 6.50% in 1997GC. In the study period on average the percentage share of private investment to GDP is 17.34%, the Ethio-Eritrean war period (1998-1999) registered a smallest while the Ethiopian millennium year (2008) largest share of private investment exhibited. The higher inflation rate after 2008 deteriorates the rate of private investment.

When we see the total employment creation of total implemented 1775 private investment projects reached to 95,206 in the period 1992-2008.while the implemented private projects and job opportunity creation reached 1157 and 102,158 respectively during 2009-2015GC.

Figure 1.1: Trends of private investment as a percentage share of GDP(1986-2014

Abbildung in dieser Leseprobe nicht enthalten

Source: Author computation; NBE, MoFED, CSA, macro-economic and social indicators (adjusted at GDP current market price) various years' report

In General, the above figure 1indicates that in the early stage of the study period private investment as a percentage share of GDP had a lower share to GDP around 10% and between 10% to 18% for the long period and registered a record share of 67.9% in 2008 and stay above 50% in 2007 and 2008 and stared to decline until 2011 and stay above 20% for the last four Years. The last four years record is a minimum benchmark for developing counters to achieve sustainable development for the nation.

2.1.2 Performance of private investment in Ethiopia

In this portion the status of private investment in Ethiopia investigated country base in different aspects. The Ethiopian Investment Commission (EIC) and regional investment offices licensed a total of 84 projects during 2019/20, all of which were operational. The projects started operation with investment capital of Birr 1.3 billion. All of the Private investment projects licensed were private. Of the total investment projects, 47 (56 percent) were domestic with investment capital of Birr 675.5 million; whereas 37 projects were Foreign owned with total capital of Birr 644.9 million capital. Average capital per project for domestic investment projects was Birr 14.4 million while that of foreign investment projects was Birr 17.4 million, implying that the foreign investment projects were more of capital intensive than domestic investment projects. Job opportunity created by these investment projects was estimated at 3,211 permanent and 1,634 casual (Table 1.1).

Table 1.1: Number of Projects, Capital and Jobs Created by Operational Investment(Capital in

Abbildung in dieser Leseprobe nicht enthalten

2.1.3. Opportunities of private investment in Ethiopia

2.1.3.1 Strategic Sectors for Foreign Investment in Ethiopia

The strategic sectors for investment, as identified by the government, are agriculture, textile and apparel, leather and leather products, pharmaceuticals, agro-processing, ICT, power, mining, and tourism. Ethiopia‘s natural and various riches such as vast arable land, favorable climate, diverse agro-ecological zones that make it possible to grow almost everything, cheapest electricity per kilowatt hours, and trained and affordable human power combine to make it an incredible hub for investment. The country has 74.3 million hectares of arable land, and over 3-million-hectares of land has been made available for investment. Ethiopia offers one of the largest and most diverse agricultural investment opportunities in the continent.

In the path to industrialize Ethiopia, textile and garment industry are given prominent position in boosting export and creating job opportunities. The recent surge in Ethiopia's textile and apparel production and export to the global markets shows that the country has the potential to become one of the leading textiles and Apparel hubs of Africa, with the bold vision of transforming the country into compelling new apparel sourcing hub for brand, retails and their suppliers.

In agro-processing sector, investment opportunities include processing of meat and meat products, fish and fish products, fruits and vegetables, manufacturing of edible oil, processing of milk and/manufacturing of dairy products, baby food, animal feed, macaroni and pasta, alcohol and soft drinks, etc.

The country, as a Land of Origins, commands a large and untapped potential for the tourism and hospitality sectors. The potential for interested investors to tap into the construction of star rated hotels and lodges around the destinations will offer a wide opportunity as the tourism infrastructure has huge room to grow.

In sum, the sectorial varieties coupled with potential for backward and forward linkages, Key geographic location, and duty-free access to the EU and U.S. markets through the Everything but Arms (EBA) and African Growth and Opportunity Act (AGOA) respectively, Put Ethiopia as an attractive place for FDI (https://perspectives-cblacp.eu/investment-opportunities-in-ethiopia/).

2.1.4. Challenge of private investment in Ethiopia

2.1.4.1. Land Expropriation

Government of Ethiopia is providing land for investment with a variety of incentives such as repatriation of profits, hiring expats, custom duty exemption, income tax exemption and etc. It believes that investment is a crucial way to fight poverty among other approaches, is to make use of available natural resources. However, this exercise is not positively viewed in all corners and which benefits investors at the expense of the people. (http://www.conscientiabeam.com/pdf-files/eco/35/JSER-2019-6(2)-150-168.pdf).

2.1.4.2. Environmental Pollution

Some industries generating liquid wastes, solid wastes (especially the under composed materials, plastics), etc. Polluting the environment is a serious problem in Sebeta town. During the field visit, I observed that animals drink Sebeta River which carries wastes of factories alongside to the river. One informant during focus group discussion said that “I lost one milking cow in 2018. It drank this river and passed away”. Other participant of the interview also share this problem and added that, had it not been the situation improving we could have lost many animals.

Most of the high water consuming industries in the awash basin area draw water for production purposes from water supply sources and discharge their by-product wastes in to streams and rivers without any kind of treatment. Besides this, there is no restriction on industrial plants discharging their waste water into the rivers and water courses. For example, Ayka Addis can be an example (http://www.conscientiabeam.com/pdf-files/eco/35/JSER-2019-6(2)-150- 168.pdf).

2.2 THEORETICAL FRAMEWORK

2.2.1 The Neoclassical Growth Model

The Solow (1956) and Swan (1956) economic growth models, which are generally referred to as the Neoclassical model, are based on a Cobb-Douglas aggregate production function and a capital accumulation equation. These models ignore technical advancement and anticipate that the pace of population growth and investment will determine the amount of per capital income. As a result, economic growth is only temporary and only lasts until capital per capita reaches a steady state level. Solow's second model, introduced in 1957, uses exogenous technology.

The important implications of the neoclassical growth model are the level of per capita output is determined by the level of technology, investment rate and population growth rate. While sustained growth rate of per capita output overtime is determined by technological changes. Other temporary shocks such as policy changes can affect growth only temporarily just until a new steady state level is reached. Hence, according to Solow‘s model, per capita output differences across countries and overtime are explained by the country‘s population growth, investment rate and technology (Jones 1998, Romer 1996).

The other implication of the dynamic analysis of the Neoclassical model is that the initial capital stock is far below the steady state rate of accumulation (until a new steady state is restored) is fast and accordingly output grows fast but at a lower rate as it approaches steady state level where growth ceases. This implies that poor economies with a lower stock of capital and output tend to catch up with the initially rich ones. The prediction, hence, is that poor economies grow faster than rich ones (Barro, 1997).

In this model, in the absence of technological progress, steady state per capita output does not grow and it depends on exogenous factors (that is technological progress and population growth). In this framework, in the short run, an increase in the savings rate raises per capita economic growth. However, due to diminishing returns to capital, per capita output in the long run grows at the rate of exogenously given technological progress. Although economic policies can affect the level of output (growth rate) when the economy is in transition from one steady state to another, they do not affect steady state economic growth.

2.2.2 Endogenous Growth Model

The failure of the Neoclassical Growth Model to be consistent with empirical evidence in predicting that the output level of countries with similar technologies should converge to a given level in steady state and the inability of the model to show the mechanisms through which government policies can potentially influence the growth process, led to the development of endogenous growth theory that avoids the assumption of exogenous advance in technology. This new growth model addresses the limitations of the neoclassical model by proposing a variety of channels through which steady-state growth arises endogenously. Two broad approaches have been followed in the New Growth literature to relax the assumption of diminishing returns to capital imposed in the basic neoclassical model. The first consists of viewing all production inputs as some 11 form of reproducible capital including physical capital and human capital (Lucas 1988) or the state of knowledge (Romer 1986). The second approach to generate growth endogenously consists of introducing spillover effects or externalities in the growth process.

Romer (1986) models technology growth (he termed it knowledge growth) as the outcome of competitive firms that invest in knowledge generation. The central idea that allowed this was that while individual firms face diminishing returns to invest in knowledge, at the social level returns to knowledge can be increasing that is knowledge is a function of the entire capital stock of the economy. The fact that knowledge can have positive externalities is at the center of the growth process. Romer (1986) develops these ideas into a competitive equilibrium model which yields long-run positive growth. The model also suggests that the competitive growth rate is below the socially optimal level due to the presence of knowledge externalities; large countries may grow faster and shocks to a country‘s growth may have permanent effects.

One particular source of externalities that has been emphasized in the growth literature is the accumulation of human capital and its effect on the productivity of the economy. Lucas (1988) provides one of the best known tempts to incorporate the spillover impacts of human capital accumulation, in a model built upon the idea that individual workers are pre productive, regardless of their skill level, if other workers have more human capital. The important implication of the external effect captured in the model presented by Lucas's (1988) is that under a purely competitive equilibrium its presence leads to an under investment in human capital because private agents do not take into account the external benefits of human capital accumulation. The equilibrium growth rate is thus lower than the optimal growth rate due to the existence of these externalities. Equilibrium growth rate depends on the rate of investment in human capital the externality implies that growth would be higher with more investment in human capital. This leads to the conclusion that government policies (subsidies) are necessary to increase the equilibrium growth rate up to the level of the optimal growth rate. A government subsidy to human capital 12 formation or schooling could potentially result in a substantial increase in the rate of economic growth.

2.3. Empirical Literature

An enormous number of researchers have drawn attention to the effects of private investment on economic growth, and there has been a wide and growing body of literature.

Most growth studies began their framework of analysis with the most influential works of Solow (1956 and 1957) in economic growth theory, which ignored the role of any capital formation to economic growth and took technical productivity as the only source of economic growth. In this analysis technical progress was explained outside the model and considered as manna from heaven. Following this work there have been various studies by different researchers that attempted to trace the possible source of a growth of nation. In these studies, a variable that is taken as a determinant of growth in one study is considered as a controlling variable in another study. Most of these growth analyses tried to show the relative contribution of various factors of production to the growth process. Cross country analysis and time series were used in all attempts to show possible sources of growth. Usually, growth related analyses are undertaken by using cross section and panel data evidence. Such data sets are criticized for taking samples of varies countries 15 differing widely in social, political and institutional characteristics on a common surface.

Since the reappearance of growth theory in economic literature following Solow‘s pioneering work, various, empirical and theoretical studies relating investment to economic growth have been conducted. These studies show the different role of aggregate investment in the long run growth and convergence across countries (De Long and Summer, 1991 and Levine et al). are some to mention. De Long and summer (1991), Levine and Renelt (1992) et al . found that investment to GDP ratio has a strong influence of income growth.

The good performance of economies, which were governed by the state led economics in post war Europe and other socialist countries motivated most LDCs in Africa and Latin America to implement similar types of policy to public sector investment in 1950s. These LDCs invested scarce capital of their economy in large and medium scale industries, farming, mining, trade etc. However, excessive involvement of the public sector in every sector of the economy caused great crisis to these economies. Consequently, there have been frequent calls towards private investment especially since late 1970s. Following the structural Adjustment Program of the International Monetary fund and the world bank for newly liberalized market economies of LDCs most of these countries adopted privatization and private sector led growth as an alternative development strategy to boost economic growth. In this regard, the role of the state is limited to the formulation of policies and infrastructure investments like road, communication and energy whose service are essential since they tend to generate positive externalities for the private sector.

It is now widely accepted that the expansion of private investment should be the main impetus for economic growth, allowing public investment resources 16 gradually to focus on social areas including alleviation of poverty and the upgrading of social capital and services (Chiber, 1990).

Empirical studies addressing the impact of private investment on economic growth in developing countries started to appear in economic literature following the 1980s and 1990s structural adjustment program. The robustness of investment to GDP ratio in explaining economic growth and economic policy through investment variables led most studies to focus their analysis from economic policy towards explaining cross-country differences in investment level Mankiw et al (1992) using the augmented Solow model, which includes accumulation of human as well as physical capital in the growth regression found that 80% of the cross country growth variation in the model is explained by these variables. That is international variation in per capita income can well be explained using just these three variables.

Haque, S. T. (2013) adopting the new neo-classical growth model of Cobb Doglous Production Function utilizing the error correction model (ECM), found that the variables are stationary in first difference and the co-integration tests also confirm the existence of long term relationship between the variables. The findings of the study concluded that there exist a short-run and long- run relationship between public and private investment and economic growth in Bangladesh. The study revealed that public and private investment impact positively on economic growth in the short and long run process. In addition it confirms that private investment is more effective in the long run than public investment.

Nguyen and Trinh (2018) examined both short and long-term influences of public investment on private investment and economic growth.

Hetsavong and Ichihashi (2012) investigate the impact of FDI, public investment, and private domestic investment using a sample of 15 Asian developing countries from 1984 to 2009.

According to the traditional view expressed in De Long and Summers (1991 and 1992), fixed investment in nonresidential sectors, especially in equipment investment, is the key to economic growth. Blomstrom et al (1996), however, showed that the causal link between growth and investment runs in the opposite direction. They thus suggested that the source of economic growth ought to be found somewhere else outside capital accumulation. Wen (2001) findings do not conform to either of these views about the cause of economic growth. What he has found, surprisingly, is that capital formation in the residential sector Granger-causes economic growth, which in turn Granger causes capital formation in the business sector. This perhaps explains the slowdown of U.S. economic growth for the 80s and the early 90s, because residential investment as shares of GDP has been falling while non-residential investment as share of GDP has been rising during that period. Hailu et al (2015), Results suggest that private investment is positively and significantly influenced in the short-run by public investment, money supply, and a real output but negatively and significantly by real exchange rate while, real interest rate is found to have insignificant and has a negative sign in line with macro-economic theory.

Changes in the volume of bank credit to the private sector are suggested to have a positive impact on private investment activity among developing countries (Oshikoya et al 2000). The basic idea is that some business agents are unable to get financing directly from the debt market, hence these agents are strongly dependent on bank credit (Lounging and Rush, 1995: 517), which has remained the most important source of investment financing among private enterprises in developing countries (Oshikoya, 1994). Additionally this is based on the argument that availability of loanable funds may affect the investment decisions irrespective of the cost of capital (Chirinko, 1993:1899).

CHAPTER THREE

Research Methodology

3.1. Data Source

Data for this empirical study are secondary data collect from the National Bank of Ethiopia (NBE) annual time series data over the period of 1986 to 2020.

3.2. Expected Sign of the variable

Table 1. 2: Description and Measurement of Variables Studied

Abbildung in dieser Leseprobe nicht enthalten

3.3. Estimation Method

3.3.1 Unit roots

Testing stationary is pre-estimation of data that will help to gauge the relevance of different theories and possible data problems. It is important for estimating and forecasting the variable and it tells us what kind of processes we will have to build into our models in order to make accurate prediction, otherwise misleading parameter estimation and spurious regressions relationship between the variables. There are several tests for stationary checking but especially Augmented Dickey-Fuller (ADF) unit root test proposed by Dickey and Fuller (1979, 1981) is most frequently used as well as acceptable different economic literature. Therefore, we used ADF test to perform our data.

As ADF unit root test (non-stationary) hypothesis are stated as given below: - H0: y = 0 (not stationary) against H1: y 0 (stationary).

If our time series data are non-stationary we will have to make stationary by differencing and de­trending the data. Therefore Augmented Dickey-Fuller (ADF) test has an estimation equation form as follows:-

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Where, 5 and 0 are intercept and coefficient on trend respectively yt is the relevant time series variable, A is a difference operator, t is a linear trend and & is the error term. Then if absolute value of the ADF test statistic is greater than the critical values, we reject the null hypothesis of non-stationary and conclude that the series is stationary. On the other wise, we fail to reject the null hypothesis and conclude that the series is non-stationary

3.3.2. Long run Autoregressive Distributed Lag (ARDL) Model

Before finding the long- and short-run relations that exist between variables, it is important to use the ARDL bound test (Pesaran et al., 2001) for the confirmation of co-integration. In this test there are two set of asymptotic values which assume that all variables are I (1) in one set and I (0) in other. These two sets provide critical value bonds for co-integration for both I (1) and I (0) data sets. To apply ARDL model three steps are required:

1) . Applying bounds testing procedure for detecting co-integration ranks between
variables
2) . Estimating long run relationship coefficients with respect to co-integration relations
estimated in first step and
3) . Estimating short run dynamic coefficients.

Testing the null hypothesis of co-integration is done through an F-statistics using the critical values calculated by (Pesaran et al., 2001) as follows:

1) . If the computed F-statistics is less than lower bound critical values, the null hypothesis of co-integration is rejected and that there is no long run relationship between variables.
2) . If the computed F-statistics is greater than the upper bound value, it could be claimed that variables used in the model are co-integrated.
3) . If the computed F-statistic falls between the lower and upper bound values, then the test results are inconclusive.

3.3.3 Short run ARDL Model

The ECM (Error Correction Mechanism) version of modified ARDL is used to investigate the short run dynamic relationships. All this will be done through the ECM applied through the Ordinary Least Square (OLS) estimation method.

3.3.4 Long Run Diagnostic and Stability Tests

The model that has been used for testing the long run relationship and coefficients is further checked with diagnostic tests of Serial autocorrelation, Hetroskedasticity and Normality tests. The stability of the model and stability of coefficients are checked through the CUSUM and CUSUMQ, graphical presentation of the recursive coefficients and recursive cumulative sum squares is used to judge the stability of the coefficients and residuals.

3.4 Model Specification

3.4.1 Autoregressive Distributed Lag (ARDL) Model

In regression analysis if model includes both current and lagged values of independent variables it is called distributed lags model and if model also includes lagged values of dependent variables it is called autoregressive distributed lag model (Gujarati, 2004) Autoregressive distributed lag model allows us to express co-integrated behavior of variables which have different order of integration. ARDL is appropriate for the independent variable in the model which is I (0), I (1) or a mix of I(0) and I(1), but it fails in the presence I (2) in any variables (Frimpong et al., 2006). ARDL model is the more appropriate method to determine the co­integration relation in small samples ((Pesaran et al., 2001).

In ARDL approach it is possible that different variables have different number of optimal lags. The other advantage is both long run and short run parameters are determined simultaneously. This approach involves two stages, at the first stage it examines if there is long run relationship between the variables under investigation. Second stage estimates the long run and short run coefficients. To find the relationship between endogenous and exogenous variables, the following log linear model was stated as follows:

LnPIt = p 0 + p1 LnREER+ p 2 LnBC + P3INFR+ LnM + p 5 RLR + st 1

The log linear form of Equation ( EQ2 ) can be rewrite in ARDL model form as follows:

15

k m s

A ta PI, = P t E PJ ln PI , + X P, 'nREER.-, + Z P, ’A 'nBCt

j =1 j =1 j =1

l p q

+ t Pi , + £ A [5] A lnM. _, + £ p, [6] ARL . _, +

j =1 j =1 j =1 R

0 [1] ln PI, . + 0[2] ln REER, . + 0[3] ln BC, . + 0 [4]INFR, . + 0 [5] ln M, . + 0[6] RLR t_, + sipEQ!

After finding the long-run association existing between variables, the study uses the error correction model (ECM) to find the short-run dynamics. ECM shows the speed of adjustment in the long-run equilibrium after a shock in the short run. The ECM general form of Equation ( EQ2 ) is specified in Equation ( EQ3 ):

k m s l

A ln PI,= p[0]+ ^p ln PI t + £ P. [2]A InMZR_J + £ p, [3]A In BC, + J p,[4]MNFR

p

+ E P. [5]A ln M, - J j =1

q

+ Y P. [6] A RL j =1 R

+ SECM t _j + St

EQ 3

Where, ECMt is the error correction term, defined as:

k m s

ECM , = A ln PI , _{p X £ p J ln PI ,, + £ P, ln REERt_ , + £ A ln BCt_ ,

j =1 , =1 , =1

l p q

+ YP, [4]A ln INFR+ YP, [5]A ln M,+ £ p, [6]A ln RLR, ] EQ 4

j =1 j =1 j =1

Where; PI private investment, REER real effective exchange rate, BC bank credit, INFR

inflation rate, M money supply, RLR real lending interest rate, A is first difference operator, ln stands for natural logarithmic transformation. P ,'(i = 1,2,3,,6) are short run coefficients on ?

variable i at lag j, 0[1] (i = 1,2,3,,6) are long-run coefficients on variable i and k, m, s, l, p and q indicate optimum lag length of the variable under study and & the coefficient of speed of adjustment.

16

CHAPTER FOUR

Estimated Results and Interpretation

4.1. Summary Statistics

Before going to provide a complete econometric analysis, the study gives brief interpretation of statistical analysis. Descriptive statistics shows that basic feature of the data. They represent quantitative descriptions in a manageable form and provide simple summaries about the data. It differs from inferential statistics. Descriptive statistics describe what is or what the data shows while inferential statistics is used to reach conclusion that extend beyond the immediate data alone.

Table 1.3: Descriptive Statistics

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Table 1.3 interprets the average of LRGDP, LREER, LPI, LM, LBC, IR and RLR as 12.91, 4.98, 10.20, 8.72, 9.45,9.85 and 1.51 while standard deviation as 0.99, 0.31, 1.96, 1.49, 2.12. Descriptive statistics shows that maximum value of LRGDP, value of during sample period was 14.50 in 2020 and minimum value of LRGDP was 11.63 in 1986. Maximum value of LREER during sample period was 5.84 in 2020 and minimum value of LREER was 4.54 in 1986. Maximum value of LPI during sample period was 13.63 in 2020 and minimum value of LPI was 7.60 in 1986. Maximum value of LM during sample period was 11.80 in 2020 and minimum value of LM was 6.51 in 1986. Maximum value of LBC during sample period was 13.05 in 2020 and minimum value of LBC was 6.2 in 1986. Maximum value of IR during sample period was 55.24 in 2020 and minimum value of IR was -11.82 in 1986.

Skewness is a measure of departure from symmetry. The skewness of a symmetric distribution is zero. Therefore, according to the following table the data of Real GDP (LRGDP, 0.12), Real Effective Exchange Rate (LREER, 0.77 ), Private investment (LPI , 0.39), and import (LM, 0.51) showed that these four variables are nearly normally distributed. And the variable inflation (IR, 1.38) is positively skewed, real lending rate (RLR, -1.39) and bank credit (LBC, - 0.18 ) is negatively skewed, and then we can say that their distribution has long right tail. Kurtosis measures the peakdness or flatness of the data relative to the normal distribution. The kurtosis of normal distribution is 3 whereas the Kurtosis of Real GDP(RGDP,1.53), private investment (LPI,1.84), Import (LM, 2.13), and bank credit(BC,2.00) are less than three, which show platykurtic distribution this small kurtosis is an indication for having a flatted curve distribution. The Kurtosis of real effective exchange rate (REER, 3.36), inflation (IR, 5.52) and (RLR, 5.63) is more right value (peaked curve) so it has positive kurtosis which show leptokurtic distribution.

4.2. Unit Root Test

The first step in time series econometric analysis is to carry out a unit root test on the variables of interest. The test examines whether the data series is stationary or not. To conduct the test, the conventional Augmented Dickey-Fuller (ADF) test was employed with and without a trend. The results of the test for the variables at a level and first difference are presented in Table 4.2. As reported in Table 4.2 two variable with an intercept at the level is stationary at a 5% level of significance and three variables with intercept and trend at the level are stationary and six variables with intercept at first differences and five variables with intercept and trend at first differences are stationary at 5% level of significance.

Table 1.4: Unit Root Tests of the Variables at Level and First Difference

Abbildung in dieser Leseprobe nicht enthalten

Denotes rejection of null hypothesis at 1, 5 and 10 percent level of significance. Source: Researcher summarized from E-views 10 outputs

4.3. Testing for Bounds Test or Co-Integration

In order to check for the existence of long run relationship, co integration, in the model bound co integration test was used to check whether have a long run relation among the variable's or not.

The results of the ARDL bounds testing approach are also shown in Table 4.3

Table 1.5: ARDL Bounds Test for Cointegration

Abbildung in dieser Leseprobe nicht enthalten

Source: Computed by authors using E-views 10 software

From Table 1.5, the calculated F statistics (7.89) is higher than both the Pesaran et al. (2001) and Narayan (2004) upper bound critical values at a 5% level of significance. This implies that the null hypothesis of no long-run relationship is rejected; rather accept the alternative hypothesis (there is a long-run relationship) based on the Pesaran et al. (2001) and Narayan (2004) critical values at a 5% level of significance. Therefore, there is a co-integration relationship among the variables in long run.

4.4. Diagnostic test Checking

Table 1.6: Serial correlation test

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As shown in Table 1.6, all versions of the Breusch-Godfrey serial correlation LM test statistic (F statistic, Chi-Square) gave the same conclusion that there was no evidence for the presence of autocorrelation in this particular study. Since the p-values of 0.5993 and 0.4454 for F-statistic and Chi-Square respectively were more than 0.05, the null hypothesis should not be rejected. Table 1.7: Heteroskedasticity test

Abbildung in dieser Leseprobe nicht enthalten

As shown in Table 1.7, all versions of the white test statistic (F-statistic and Chi-Square) gave the same conclusion that there was no evidence for the presence of heteroscedasticity in this particular study. Since the p-values of 0.1554 and 00.1458 for F-statistic and Chi-Square respectively were more than 0.05, the null hypothesis should not be rejected.

Figure 1.2: Normality test

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Here we have the probability associated with the Jarque-Bera statistic has a P-value of normality test is 0.547437 which is greater than the 5% significance level so we cannot reject Ho rather accept Ho & conclude that the residuals are normally distributed.

Figure 1.3: CUSUN and CUSUMSQ test

The results of both CUSUM and CUSUMSQ test given below as depicted in the first figure; the plot of CUSUM test did not cross the critical limits. Similarly, the CUSUMSQ test shows that the graphs do not cross the lower and upper critical limits. Therefore, we can conclude that long and short runs estimates are stable and there is no any structural break. Hence, the results of the estimated model are reliable and efficient.

Abbildung in dieser Leseprobe nicht enthalten

| CUSUM of Squares 5% Significance |

As shown from the above, the diagnostic test recommends good fit of the model. The model does not suffer from the problems of non-normality of the errors, serially correlated errors, heteroskedasticity and stability which further affirm that the estimation is BLUE. Therefore, the entire diagnostic test of the residual and as observed all test are pass the model we need.

4.4. Long run model

Table 1.8: Estimated Long Run Coefficients

Estimated long run coefficients for the selected ARDL model Selected Model: ARDL (2, 0, 2, 1, 0, 2, 2) selected based on Akaki information criterion.

Abbildung in dieser Leseprobe nicht enthalten

Source: Computed by authors using E-views 10 software. The long-run model of the corresponding ARDL (2, 0, 2, 1, 0, 2, 2) for the economic growth can be written as follows:

LRGDP = -0.361 LREER + 0.229 LPI (-2) - 0.291 /.M (-1) + 0.239LBC - 0.059 IR (-2) - 0.061 RLR (-2) + 9.294

The result shows that import of goods and services (M) is negative and statistically significant at 5% level of significance, indicating that an increase in import of goods and services (M) by 1 percent will lead to decrease economic growth by 0.291%. This implies that the increase in long run import of goods and services (M) has a negative impact on economic growth. As shown on the table 4.6, Importing goods and services (M) hurts economic growth, confirming the results of studies such as in his study untitled “Performance Evaluation of Foreign Trade and Economic Growth in Nigeria” Usman(2011) reported that imports and exports are negatively related to GDP. The study by Kartikasari, D. (2017) shows a negative relationship between imports and economic growth, which is obvious since when a country imports things, it buys them from foreign producers, and hence imports send money out of the country and reduce economic growth.

The coefficient of Real Effective Exchange Rate (REER) is negative and statistically significant at 5% level of significance, indicating that increase in real effective exchange rate by 1 percent will lead to decrease economic growth by 0.361%. This implies that an increase in REER implies that exports become more expensive and imports become cheaper; therefore, an increase indicates a loss in trade competitiveness and the countries of economic growths are decrease. As shown on the table 4.6, confirming the results of Razin and Collins (1997) studied the relationship between economic growth and real exchange rate, considering investments and tradable products sector as channels through which the REER deviation may affect economic growth. They came to the conclusion that only a very high overvaluation seems to be associated with slower economic growth, while moderate to high (but not too high) undervaluation of real exchange rate appears to stimulate economic growth. Aguirre and Calderon (2005) analyzed the misalignment of REER and growth effect of misalignment for 60 countries over the period 1965­2003. In contrast Williamson, J. (2000) is on the view that undervaluation leads to high inflation. They found that the deviations from equilibrium hinder economic growth, but the effect is non­linear: growth declines are larger, the larger the size of the misalignments. Although large undervaluation's hurt growth, small to moderate undervaluation's enhance growth. They suggested that growth is hampered by highly volatile REER misalignments.

The coefficient of private investment (PI) is positive and statistically significant at 5% level of significance, indicating that an increase in private investment by 1 percent will lead to increase economic growth by 0.229%. This implies that the increase in long run private investment has a greater positive impact on economic growth. General by implication, an increase in private investment will enhance economic growth. Private investment provides the basis for sustained long-term economic growth. Khan and Kumar (1997) using pooled time series cross section data, which has a relatively larger number of country coverage (95 developing countries including Ethiopia) and a long time period (1970-1990) came up with similar positive contribution of private investment to economic growth. Their result reveals that there is a substantial difference in impact of private and public investment on economic growth. Ramirez and Nazmi (2003) also suggested that both public and private investment positively contribute to economic growth for nine major Latin American countries.

The coefficient of bank credit (BC) is positive and statistically significant at 5% level of significance, indicating that an increase in bank credit by 1 percent will lead to increase economic growth by 0.239%. This implies that the increase in long run bank credit has a greater positive impact on economic growth. General by implication, an increase in bank credit will enhance economic growth. Bank credit provides the basis for sustained long-term economic growth. As shown on the table 4.6, bank credit has a positive impact on private investment, confirming the results of (Blejer, M. I., & Khan, M. S. (1984) who argued that increase bank credit leads to high rates of investment and vice versa. Joseph, E. (2020) in the long run, bank credit has a significant positive effect on economic growth. Policies towards enhancing growth of financial sector should be emphasized to enable increase in credit provision and promote economic growth through investment in different sectors of the economy. Dey & Flaherty (2005) examined the impact of bank credit and stock market liquidity on GDP growth using two-stage least squares regression model and found that bank credit is not a consistent determinants of GDP growth.

The coefficient of inflation rate (IR) is negative and statistically significant at 5% level of significance, indicating that an increase in inflation rate by 1 percent will lead to decrease economic growth by 0.059%. This implies that the increase in long run inflation rate has a greater negative impact on economic growth. General by implication, an increase in inflation rate will decrease economic growth. Inflation rate provides the basis for sustained long-term economic growth. As shown on the table 4.6, inflation rate has a negative impact on economic growth, confirming the results of Hayat et al. (2018) the low inflation would help achieve sustainable real economic growth. Kiat (2018) inflation has a negative impact on economic growth. Ilyas et al. (2014) inflation negatively and significantly affects economic growth. High inflation and hyperinflation in Latin American countries in the 1980s caused the emergence of view that inflation has a negative impact on economic growth, contrary to the prevailing view that inflation has a positive impact on the economic growth (Erbaykal and Okuyan, 2008). Fisher (1993) investigated the role of macroeconomic factors, such as inflation on growth using a panel data of 93 countries. He found that economic growth is negatively associated with inflation and that inflation reduces economic growth by reducing the growth in productivity and investment. Barro (1995) studied the effects of inflation on economic growth by using panel data for around 100 countries for the period of 1960-1990. From the empirical analysis, he found that the estimated impact of inflation on economic growth is significantly negative.

The coefficient of real lending rate (RLR) is negative and statistically significant at 5% level of significance, indicating that an increase in real lending rate by 1 percent will lead to decrease real GDP by 0.00242%. This implies that the increase in long run real lending rate has a negative impact on economic growth. As shown on the table 4.6, real lending rate has a negative impact on economic growth, confirming the results A negative effect of interest rates on economic grown in Kenya was obtained in the study conducted by Mutinda (2014) who collected data from the Central Bank of Kenya using the period 2003-2012.

Ifeanyi and Chukwu (2014) examined the impact of interest rate deregulation on economic growth in Nigeria, using secondary data collected from Central Bank of Nigeria Statistical Bulletin for the period 1986 to 2010. The study employed OLS technique based on the E-View statistical package to analyses data, and found that low interest rate stimulates and increase growth in real domestic product. This result shows that negative relationship between lending rate and economic growth. Eregha (2010) examined variations in interest rate and investment determination in Nigeria. The study employed dynamic model of two equations using instrumental variable technique of estimation on data from the World Development Indicator. The study revealed that variation in interest rate played a negative and highly significant role in investment decision in the economy and demand for credit also had negative and significant influence on interest rate variations in both the short run and long run.

4.5 Short Run/Error Correction Model

Table 1.9: Estimated Short Run Coefficients (ECM)

Abbildung in dieser Leseprobe nicht enthalten

Table 1.9 error correction model result represents the short run ARDL estimated model. The error correction coefficient, the estimated value at -0.85 is highly significant and has the correct negative sign. The absolute value of the coefficient ECM (-1) 85% is high, and this imply a high speed of adjustment to equilibrium. The short run shocks about 85% of the disequilibrium, caused by previous period shocks, converge back to the long run equilibrium. Or the coefficient of the error term ECM(-1) implies that the deviation from long run equilibrium level of dependent variable private investment of the current period is corrected by 85 in the next period to bring back equilibrium.

CHAPTER FIVE

CONCLUSION AND POLICY IMPLICATIONS

5.1 Introduction

This chapter is divided into four sections, section 5.1 conclusion of the study and section 5.2 presents policy implications.

5.2 Conclusion

Private sector investment and development has become a more important engine for Ethiopia's government in fostering economic growth and employment creation.

Based on the empirical findings obtained in the long-run and short run showed that there is no doubt that private investment is a key and can be considered as engine for the progress of economic growth in Ethiopia. This paper employs the co-integrated ARDL model to examine the effects private investment on economic growth.

Before applying the ARDL model, all the variables are tested for their time series properties (stationarity properties) using the ADF tests. ADF tests results show us, Inflation Rate and real lending rate variable with intercept and with intercept and trend at level are stationary at 5% level of significance and bank credit, inflation rate and real lending rate with intercept and trend at level are stationary at 5% level of significance. Real GDP, real effective exchange rate, private investment, inflation rate and real lending rate variables with intercept and with intercept and trend at first differences are stationary at 5% level of significance except bank credit. Next to testing for time series property, the model stability was done by testing the diagonal testing techniques. The result revealed that no evidence of serial correlation, the residual is normally distributed and no evidence of heteroscedasticity problem and no evidence of stability problem. As we discussed above, this study applied the methodological approach called ARDL model also known as bound test approach. As the result indicted the bound test (F-statistic) value is larger than the upper bound critical value both for Pesaran et al. (2001) and Narayan (2004), which indicates there is a long run relationship between economic growth and its determinants (real effective exchange rate, private investment, bank credit, inflation rate and real lending rate) in long run during the study period. In establishing a long-run analysis, real effective exchange rate, private investment, import goods, bank credit, inflation rate and real lending rate for economic growth turned out to be statistically significant in long-run relationship model. Final, ECM

28

coefficient is negative and significant, and this model represents the dynamic of the short-term to long-term, error correction process in terms of adjustment speed is 85%. The ECM coefficient shows how quickly variables converge to equilibrium and it should have a statistically significant coefficient with negative sign.

5.3 Recommendation

The findings of the study lead to the following policy recommendations necessary to ensure steady and sustainable increase in economic growth. Based on the findings of the study the following policy implications are suggested:

-If a country's imports exceed its exports, the net exports would be negative. This economic context of a country is known as the trade deficit. It will negatively affect the market economy of a country. Therefore, Import goods according to the country's foreign currency and appreciate foreign currency earn.
-To promote growth and keep inflation low, the government needs to control budget deficits.
-As for credit, time should be effort towards ensuring a fair distribution of credit among different sectors so that some sectors do not reap all the benefit or incentives alone. This implies that government should consist to control as distribute credit to sector where it is mostly need. This will enhance the less developed sector and enable them have a chance to avail themselves to credit for investment which will in turn stimulate economic growth.
-In the long run, countries with higher private investment experience higher rates of growth. Therefore, good public policies that encourage permanent increases in private investment rates lead to increases in long-term economic growth and welfare.

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