Rwanda is a landlocked country and it is far from the maritime ports having the nearest port of Dar Es-Salaam approximately 1400 km away.
The country lacks a link to regional railway and Inland Water Transport, which means most trades are conducted by road. Moreover, the country is fully depending on imported fuel for transport. Consequently, transport costs of imports and exports are high and these have negative impacts on the economic growth and development of the country. Transport is therefore considered as a strategic sector to enable the expansion of the Rwandan economic base from predominantly agriculture based into the secondary and the tertiary sectors.
Transport infrastructure in Rwanda is comprised of the following Road transport with a network about 14,000 km, Air transport where Rwanda counts one international airport and six aerodromes with average 1.4 million passengers, Lake transport limited only on Lake Kivu. The transport service sector in Rwanda is rather informal and uncoordinated. Although at present there are 41 companies and cooperatives, the major market share of vehicles comes from individual operators. In terms of total available seat capacity, the individual operators provide 70% of the supply.
Rwandan economy is dominated by subsistence agriculture where 79% of the population is engaged in agriculture. The economy’s trade balance is negative where exports are dominated by imports. The country’s vision 2020/2050 through its national strategy for transformation one and 2035 agenda is to transform the economy in the lower middle income and upper middle-income economies by 2024 and 2035 respectively .
For the country to achieve its target, it requires all sectors of the economy to be more productive. All the sectors of the economy are exposed to the oil price shocks and transportation in general. Policy makers need evidences to inform policies about the economic sectors especially transport sector and how other sectors react to the change in transportation sector.
In general, the research aims at Econometric Analysis of Transport Sector on Economic Growth in Rwanda (1999-2018) in order to identify the contribution of Transport services, Gross Capital formation (Transport infrastructures), and Trade balance on Rwandan economic growth.
To achieve the purpose mentioned, this paper is organized into five sections. Following this introduction, there is Section 2 which focuses on review of related literatures while methodology is discussed in Section 3. Section 4 presents the results and discussions of findings. Conclusion and recommendations are in the last Section 5.
1.1. Research Problem
Transport is a key in economy of a country as all economic activities depend on transport facilities such as people and commodities movement. Level of infrastructure and oil price affect the economy of a country, in 2007, almost twenty percent of World Bank lending was allocated to transportation infrastructure projects, a larger share than that of education, health and social services combined . Previous researcher analysed the relationship between transport infrastructure and per capita income and job creation. Literature of  and  found a neutral relationship among infrastructure investment, job creation and per capita income.
Findings of previous research did not analyse impact of transport sector on economic growth. However this sector is subject to oil price shock causing an increase in price level for other commodities. This research aims at analysing the relationship between transport services and economic growth in Rwanda and indicates at which level transport sector is contributing to economic growth.
1.2. Research Objectives
The study focuses on the following specific objectives:
1) To analyse the influence of Gross Capital formation in terms of transport infrastructures on Economic growth of Rwanda
2) To determine the influence of trade balance on Economic growth of Rwanda as it may be affected by the quality of transport system
3) To determine the level of contribution of transport services to economic growth of Rwanda
This research is guided by the following null hypotheses as tentative possible answers that finally at the end we count to confirm or reject:
Ho1: Gross Capital formation in terms of transport infrastructures does not have any influence on the economic growth in Rwanda.
Ho2: Trade balance does not have any influence on economic growth in Rwanda.
Ho3: Transport services do not have any influence on economy of Rwanda.
2. Literature Review
There are views about transport infrastructures investment and its relation with jobs creation. The first view suggests a positive relationship between infrastructure investment and jobs creation . The second view finds a neutral relationship among infrastructure investment, jobs creation and an increase in per capita income . The third view argues that public investments, such as roads, airport, ports, enhance income per capita and create jobs . , however, noted that the change in infrastructure stock, such as roads, did not significantly create new employment opportunities. In contrast to the above two views,  found that there was an extremely impact of infrastructure investment, including roads, on income per capita and jobs creation. Generally, transportation infrastructures carry societal costs, such as public health and safety, which are often ignored in analysing their costs and benefits in the decision-making process .
Studies on the Nigerian economy  indicate that transportation costs form a significant proportion of the final price of goods.  found that there is a positive relationship between transportation infrastructure and economic growth in sub-Saharan Africa. In his research,  found that transport facilities were a major differentiating factor in explaining growth gaps. With Combination of panel data and cross sectional,  found that transport capital contributes to economic growth for Africa countries.
The  panel causality analysis shows the feedback effect of transport energy consumption and transport infrastructure with economic growth. The empirical results add a new dimension to the importance of investing in modern infrastructure that facilitates the use of more energy-efficient modes and alternative technologies that positively affect the economy with minimizing negative externalities.
Principles of development (increasing well-being and equity) as well as sustainability (preserving natural and man-made capital) should be inherent in sustainable transport policies and manifested in transport trends .
We lack a rigorous empirical understanding of the extent to which transportation infrastructure projects actually reduce the costs of trading, and how the resulting trade cost reductions affect welfare.
In Figure 1, Gross Capital formation is used in this model as transport infrastructures where government provide Roads, airports, railways, and ports to increase transport service, the more the quality of transport infrastructures, the more investors will likely to invest in transport, the more transport cost decreases and rate of unemployment decrease, the more the cost of transport of commodities decrease, the more trade will be facilitated. Trade balance is the difference between export and import, transport service represents air transport, land transport and water transport.
3. Research Methodology
3.1. Data and Data Source
Secondary data on gross domestic product, gross capital formation, transport services and trade balance were extracted from the national institute of statistics of Rwanda (NISR) from 1999 up to 2018. This study has a sample of 19 annual periods from 1999-2018.
Figure 1. Conceptual frameworks.
3.2. Model1: Long Run Regression Model
where GDP denote gross domestic product, GROSS_CAP denote gross capital formation, transport services to denote income from transport activities and trade balance is the total export minus total import.
3.3. Model 2: Error Correction Model
where D(GDP) denote change in gross domestic product, D(GROSS_CAP) denote change in gross capital formation, D(transport services) to denote change income from transport activities, D(trade balance) is change in total export minus total import and U(−1) denote the error correction term of lag one.
This chapter presents the result of empirical analysis of transport sector on economic growth in Rwanda. This result produced using Eviews7 are presented as below.
4.1. Unit Root Test
The result of unit root test presented in Table 1 shows that GDP, gross capital formation and trade balance are integrated at first difference (“I(1)”order one) whereas transport services is integrated at second difference (“I(2)”order two). This means that each variable under study has a time trend.
To proceed, the researcher conducted cointegration test to see if the linear combination of the variables under study is stationary. The result of cointegration presented in Table 2 shows that the linear combination is stationary indicating that there is cointegrating relationship among the variables under study, or the error term is stationary.
4.3. Granger Causality
The result of granger causality in Table 3 shows that gross capital formation,
Table 1. Unit root test results computed with Eviews7.
(*), (**) and (***) denotes Stationary at 10%, 5% and 1% levels of significance respectively.
Table 2. Cointegration test results computed with Eviews7.
(*), (**) and (***) denotes Stationary at 10%, 5% and 1% levels of significance respectively.
Table 3. Granger causality test results computed with Eviews7.
trade balance and transport services significantly granger causes GDP. This means that the variation of GDP is explained by gross capital formation, trade balance and transport services as the probability calculated is greater than critical probability therefore the null hypothesis is rejected.
4.4. Regression Results
4.4.1. Long Run Regression Results
The result of long-run regression model in Table 4 shows that all the coefficients are significant, calculated probabilities are less than critical probability, this means that an increase of gross capital formation, trade balance and transport services by one unit is associated with an increase of GDP by 2.841260, 0.826272 and 11.03252 respectively.
Table 4. Long run regression results.
Transport services has a significant strong positive relationship with GDP, this is in line with economic theories which predict a positive relationship between GDP and transport services (an increase of transport services is associated with an increase of GDP). This is because of sensitivity of transport mainly oil prices on the other sectors of the economy.
A small change in oil prices lead to change in transport cost, through transport price of other commodities (goods and services) respond to oil price changes. This means that an increase of oil price raise the cost transport and raw materials increase and end up with high commodity prices.
4.4.2. Error Correction Results
The error correction result in Table 5 shows a quick recovery after a shock happen, in one-year GDP return to its original path at 81.3% after the oil price shock. This gives signal for policy makers, in the case of an increase of oil price both transport cost and cost of raw material rise rapidly but if policies are taken it shows its impact quickly. All the slopes of the model are significant, calculated probabilities are less than critical probability of 10% indicating a short run relationship of variables in the model. An increase of gross capital formation, trade
Table 5. Error correction results.
balance and transport services by one Percent lead to an increase of GDP by 1.689529, 0.781311 and 14.68661 Percent in short run.
Durbin Watson for both the error correction model and the long run regression model of 1.967291 and 1.535361 are closer to 2, this indicates that there is no autocorrelation in the result of the above mentioned two models.
4.5. Normality Test
The probability of Jarque-Berra of 0.219470 is greater than 10% critical probability, so the null hypothesis is rejected. This means that the results are normally distributed as it is shown by Normality test in Figure 2.
4.6. Stability Test
In Table 6, the probabilities calculated of the Ramsey Rest test are less than probability critical indicating that it is statistically significant, so the regression results of the model are stable.
Econometric analysis of transport sector on economic growth in Rwanda for the period of 1999 up to 2018 is an empirical analysis study which used econometric approach.
This research used the long run regression model and the error correction
Table 6. Stability test results.
Figure 2. Normality test results.
model to evaluate the relationship among variables under study. The result show a statistically significant positive relationship between transport services and gross domestic product for both short run and short run. The result showed a strong statistically significant relationship between GDP and transport sector as measured by transport services for both short run and long run as it is shown by R-squared of 0.997316 and 0.782009 of the long run regression model and error correction model respectively.
Adequate, efficient, and effective transport systems are important for access to markets, employment, education and basic services critical to poverty alleviation; at the same time, transportation is expected to be a major driving force behind a growing world demand for energy and it has a significant environmental footprint. Therefore, integrated approaches to policy making should be promoted, including policies/planning for land use, infrastructure development, public transport systems and goods delivery networks, with a view to providing affordable, efficient and safe transportation, increasing energy efficiency, and reducing pollution and congestion effects.
Transport accidents (fatalities or injuries) lead to substantial social and economic losses for families and society. In order to evaluate transport safety, the current situation, trends and controlling factors (e.g. speeding and drink-driving) of transport accidents should be controlled. Finally, transportation affects the environment negatively through the consumption of non-renewable fuels, Carbon emissions, noise and ecosystem degradation. At the same time, transport infrastructure and services are impacted by the environmental conditions and their variability.
Infrastructure, particularly transport infrastructure, play a key role in Adam Smith’s vision of economic development, No roads, no transport, no trade, no specialization, no economies of scale, no productivity progress, and no development.
Econometric analysis of transport sector on economic growth in Rwanda for the period of 1999 up to 2018 is an empirical analysis study which used econometric approach. This research used the long run regression model to evaluate the relation between variables under this study. Results show a statistically significant positive relationship between transport services and gross domestic product for both short run and long run. The result showed a strong statistically significant relationship between GDP and transport sector as measured by transport services for both short run and long run as it is shown by R-squared of 0.997316 and 0.782009 of the long run regression model and error correction model respectively. These results imply that the effect of Transportation infrastructure is slow to occur but long lived: an increase in infrastructure has little short run impact on output but leads to a higher growth rate and higher output in the long run.
The policy implication that can be deduced from this study is that, policies to increase gross capital formation, improve trade balance, facilitate transport sector through expansion of road network and maintenance of existing road network coupled with revitalization of alternative mode of transportation such as rail system and waterways will significantly improve the growth of the economy. Businesses are subject to oil price shock, hence a slow economic growth. Policy makers should take actions on using vehicles which use electricity or Gas where possible to reduce dependence on oil. Transport Infrastructure and National Development should improve the quality and reliability of transport infrastructure and services to reduce transport costs and attract domestic and foreign investment in Rwanda. An efficient transport system intends to contribute to poverty reduction by facilitating rural communities’ access to economic activities such as markets and social and other support services.
I would like to thank Nation Bank of Rwanda and Nation statistic Institute of Rwanda for data provided. I wish to thank my supervisor Dr. Twesige Daniel for his constructive advice and encouragement over this research. I would like also to thank my family, friends and to whom my success is their pride.
BNR, http://www.bnr.rw/, retrovied in July 2016
http://www.sciencedirect.com, journal of monetary economics
http://www.minecofin.rw, retroviewed in July 2016
Reports and Other Documentations
BNR, Annual Reports, (2001-2015)
MINECOFIN Report, (2001-2015)
World Bank Report, 2010
IMF, October 2012: Statistics on the Growth of the Global Gross Domestic Product (GDP)
CIA World Fact book (February 2015)
U.S. Dept. of State Country Background Notes (February 2015)
 Duffy-Deno, K.T. and Eberts, R.W. (1991) Public Infrastructure and Regional Economic Development: A Simultaneous Equations Approach. Journal of Urban Economics, 30, 329-343.
 Dalenberg, D.R. and Partridge, M.D. (1995) The Effects of Taxes, Expenditures, and Public Infrastructure on Metropolitan Area Employment. Department of General Studies the Federal Polytechnic. Journal of Regional Science, 35, 617-640.
 Uddin, W., Boriboonsomsin, K. and Garza, S. (2005) Transportation Related Environmental Impacts and Societal Costs for Life-Cycle Analysis of Costs and Benefits. International Journal of Pavements, 4, 92-104.
 Njoh, A.J. (2012) Impact of Transportation Infrastructure on Development in East Africa and the Indian Ocean Region. Journal of Urban Planning and Development, 138, 1-9.
 Demurger, S. (2001) Infrastructure Development and Economic Growth: An Explanation for Regional Disparities in China? Journal of Comparative Economics, 29, 95-117.