In our case, as illustrated in Figure 3 , all roots lie inside the unit circle which is an indication that our VECM is stable. The residuals were also examined for the normality, autocorrelation and heteroscedasticity and the results are reported in Table 5. Table 5 shows that the results do not suffer from autocorrelation, non-normality and heteroscedasticity. The results obtained from the analysis are therefore robust.
This article focused on interpreting the results of models estimated. This article began with analysing the time series properties of the data using three methods of testing for unit root. All three methods confirmed that the variables are integrated of order one, I 1. Having determined the order of integration of the variables, the lag length used in the estimation for the Johansen cointegration was determined empirically. This, therefore, implied that there is a long-term relationship between ED and its determinants.
The VECM was also estimated to analyse both the long-run and the short-run interaction between the variables. The long-run equation showed that all the variables employed in the model are significant and carried the correct signs. The results also observed all the assumptions which underlie the classical linear regression model. The strength of this article lies in reaffirming the established relationships of road transport infrastructural investment with ED. Taking into cognisance the significance and the challenges confronting road transport infrastructure investment in South Africa, this article argued that ROTI is pivotal to ED.
Stretching from an introduction to empirical review, where other studies demonstrated similar tendencies around the world, in Africa and in South Africa as well, outlining the studies of Perkins, Fedderke and Luiz, and Fedderke and Bogeti conducted in South Africa, it stretches the discussion even further by providing an analysis between and using the VECM AR Roots Johansen cointegration in assessing the relationship. As it is common that macroeconomic time series are trended, in most cases the variables are nonstationary and using a non-stationary data may lead to invalid results and conclusion.
For this reason, before conducting the cointegration test, the study first conducted the stationarity test for all variables under investigation using both the informal and formal tests. For the informal test, graphical inspections were used, while PP and ADF tests were applied in order to formally test for stationarity. Having found that the variables are stationary after first differencing and are integrated of the same order, the study further conducted a cointegration test to check if there exists a long-run relationship between the two variables.
The results revealed that there is cointegration among the variables under examination.
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With the first model, the trace statistics suggested three cointegrating vectors, whereas the maximum eigenvalue suggested two cointegrated vectors. With the latter, the trace statistics suggest two cointegrating vectors, whereas the maximum eigenvalue indicates that there is no cointegration. The presence of at least one cointegrating vector allowed for estimation of the VECM, which was followed by diagnostic checks through autocorrelation serial correlation , heteroscedasticity and normality of the residuals, the results from these tests are positive.
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These results are in accordance with most of the studies such as Peter et al. Also, the nature of the relationship is in accordance with the a-priori expectations as presented in this article. It is interesting to find that the ROTI, as sophisticated as it is, contributes this more towards growth. Given the results above, the study makes the following policy recommendations: The South African government should develop policies that encourage the incorporation of the ROTI into the economic system.
Policy makers Fiscal and Monetary should embark on economic activities that enhance the link between ROTI and ED, such as, stimulating savings which in turn improves the level of investment. The use of data from mainly the South African Reserve Bank would limit the effect of the study to only the Reserved Bank analysis.
Variables that were converted from annual to quarter might also result in the frequency disparities. This adjustment might have contributed to some of the challenges experienced in the study. Using the short vector error correction alone might portend another limitation on the contrary. The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article. Arrow, K. Aschauer, D. Ashipala, J. Barro, R.
Economic growth , 2nd edn. ISBN Brooks, C. Domar, E. As reprinted in Domar Engle, R. Fedderke, B.
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Ncanywa, T. Tsheola eds. Perkins, P. Pesaran, H. Pradhan, R. Sheshinski, E. Shell ed. Solow, R. JSTOR The MIT Press 39 3 , — Sturm, J. Swan, T. Richard J.
spamivadodcruz.ml Stiglitz, David Aschauer, Melo, Patricia C. Thisse ed. Whinston, Daniel J. Graham, Edward L. Gottlieb, Audretsch, David B.
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Harald Badinger, Daniel J Graham, You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:trapol:vyi:c:p See general information about how to correct material in RePEc. For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dana Niculescu. A New Proposal for Project Appraisal - A major criticism with the national level analysis is the conclusion that finding a rate of GDP growth from a certain increase of total capital accumulation actually tells us little about the contribution of the next infrastructure project.
That is, some projects have a high and positive impact on GDP growth whereas others may not. All that the national level analysis says is about the average contribution of capital accumulation. But since infrastructure investments are carried out on an individual project basis, we need to analyse each separately where the general rate of return or rate of GDP growth from total public capital formation may at best serve as a kind of a guideline.
A further issue to contemplate is that analysis of all planned infrastructure investment projects is done ex-ante with little certain information about future trends and development. Hence there is a need to consider specific issues that may affect the potential impact of this investment on economic development through ex-post analysis. First is the need to consider each transport project within the framework of a local, regional or even national networks.
For development to occur, it must be the result of improvements at the network level and not at the single project level. The effect of a given investment on development can be dramatically different when it links, for example, two disjoint networks rather than being only an additional link in an established network. This was a clear conclusion form the EU COST Action on Integrated Strategic Infrastructure Networks in Europe , where the value added from individual links to the network formed the basis for developing evaluation processes that linked projects to programmes and policies, as well as determining critical success factors and the necessary decision making processes for implementation to take place.
Prioritising objectives and criteria for project appraisal constitutes a second set of issues: 1. The majority of benefits need to be transport related, since otherwise why invest in transport facilities in the first place; 2.
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