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In Table 3, coetticients of predictors revealed that change in one unit of sole predictor could cause change in the construction projects implementation, given that all other variables in the model are held constant. Thus, we would expect a decrease of 0.207 in the extent of the construction projects implementation for every one unit increase in lack of bureaucratic quality holding all other predictors stable in the model. In the same way, a decline of 0.207 in the construction projects implementation score for every one unit amplifies in inefficient and effective bureaucracy in Ethiopia. So, the study finalized that the lack of bureaucratic quality was considerably impaired the construction project activities in Ethiopia. The ANOVA outcome provided that the variance among the variables in the model were statistically significant at F-value of 18.66 and P-value of 0.000. Therefore the model was fitted and properly measured factors influenced construction projects implemented in a country. In the same way, the variance in the model wa constant; its mean value was 4.18 and F value was 18.60. Then, from Table 2, it can be observed that the p-value of F statics is statistically considerable, whic means with a p-value of.000, the model is statistically meaningful.

Table 3 In Table 3, coetticients of predictors revealed that change in one unit of sole predictor could cause change in the construction projects implementation, given that all other variables in the model are held constant. Thus, we would expect a decrease of 0.207 in the extent of the construction projects implementation for every one unit increase in lack of bureaucratic quality holding all other predictors stable in the model. In the same way, a decline of 0.207 in the construction projects implementation score for every one unit amplifies in inefficient and effective bureaucracy in Ethiopia. So, the study finalized that the lack of bureaucratic quality was considerably impaired the construction project activities in Ethiopia. The ANOVA outcome provided that the variance among the variables in the model were statistically significant at F-value of 18.66 and P-value of 0.000. Therefore the model was fitted and properly measured factors influenced construction projects implemented in a country. In the same way, the variance in the model wa constant; its mean value was 4.18 and F value was 18.60. Then, from Table 2, it can be observed that the p-value of F statics is statistically considerable, whic means with a p-value of.000, the model is statistically meaningful.

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INDEX 1: POLITICAL RISK SERVICE GROUP INDEX The other variables of Political Risk Service group index relevant to the level of project finance given is socioeconomic conditions of country affect the government: actions by fuelling dissatisfaction or social unrest based on poverty, unemployment or consumer dissatisfaction. Such unrest could potentially lead to changes ir policies, which may harm the project; e.g. the government poses a new environmental law to increase consumer confidence, a new labor law to lower unemploy: ment or it may demand the project sponsors to build new schools or roads to help the development of the country in exchange for giving permits. The other enc of the scale may be civil unrest that eventually leads to more violent measures that may lead to total discontinuation of the project. Or it may be that unrest focusing negatively on foreign operations, may lead to expropriation of such projects/investments.
INDEX 1: POLITICAL RISK SERVICE GROUP INDEX The other variables of Political Risk Service group index relevant to the level of project finance given is socioeconomic conditions of country affect the government: actions by fuelling dissatisfaction or social unrest based on poverty, unemployment or consumer dissatisfaction. Such unrest could potentially lead to changes ir policies, which may harm the project; e.g. the government poses a new environmental law to increase consumer confidence, a new labor law to lower unemploy: ment or it may demand the project sponsors to build new schools or roads to help the development of the country in exchange for giving permits. The other enc of the scale may be civil unrest that eventually leads to more violent measures that may lead to total discontinuation of the project. Or it may be that unrest focusing negatively on foreign operations, may lead to expropriation of such projects/investments.
SOUrce: TESCOMDE (2ZUUZ}) IN sala \ZUUO}. Smith (1997), divided the political risk into three categories, which are very sound based on what was found under project finance and the events that can mak a project fail. These are traditional political risks such as expropriation, currency convertibility and transferability, political violence (war, sabotage, and terrorism) Regulatory risk such as risk from unanticipated regulatory changes (taxation, foreign inv. laws (output price)), and Quasi-commercial risks that include risks whe! having state-owned supplier or customer with the questionable willingness to fulfilled obligations. Sara (2008) divided the whole ICRG's political risk index variable into three namely quality of Institutions (bureaucratic quality, corruption, democratic accounta bility, social conditions, law and order, military in politics); conflicts and tensions (ethnic tension, religious tension, external conflict and internal conflict) and polic quality (government stability and investment Profile). Sara (2008) found that “changing legislation”, “war and conflicts” and “legal system and property rights were the main political risks to a project. Further, the researcher stated that the inadequacy of institutions does lead to more project finance loans, which lead to the conclusion that such syndicated loan types can help deter some of those risks. Tension and conflict have no effect on whether project finance loans ar preferred to full-recourse syndicated loans. The Hainz and Kleimeier (2006) model of double moral hazard disclosed that firm moral hazard (managerial influence on the probability of success, firm effor costs, the economic health of the country, and country corporate governance) and bank morla hazard (Bank influence on the probability of success and Bank effor cost). Yescombe (2002) the commercial risks, which relates to a project’s construction and operational phase, are covered by variables such as bureaucratic quality in relation to obtaining permits and keeping them even though the government might change. The same risk is also related to the level of corruption in government, as it will be an indication of whether the government or sub-levels or the government might grant favorable terms to local competitors to the project which may hurt the operation of the project. The external and internal conflicts cover for war and conflict risks found in Yescombe’s (2002) investment risk component. The investment risk consisting of war and conflict along with currency convertibility and risk of expropriation namely all those relating to conflicts and tensions while the investment profile covers “change of law” component from Yescombe’s (2002) risk matrix, is mainly covered by bureaucratic quality, as it deals with policy uncertainty and the ability of the government to make predictable policies that do not change when government change. This could also be related to government stability, as it covers the government's ability to carry out its declared program(s). This would suggest whether the policies made, will be somewhat predictable, as they have declared in the program and hence should not suddenly pose new laws that could alter the profitability of the project. The last component of Yescombe’s (2002) political risk is the quasi-political risk which is taken into account through the two variables “Rule of Law” that looks at the effectiveness of the legal system and "Investment Profile". The former is highly important in project finance due to the many contacts made, and the latter includes the viability of contracts and thus the likelihood of government breach of contract and also the applicability of the contracts. This is often necessary as the loan taken on the project is denominated in other currencies than the one of the host countries. Developing markets often have poor financial markets that are not capable of providing the funds needed for the project, in which case the loan is denominated in foreign currency (Sara, 2008).
SOUrce: TESCOMDE (2ZUUZ}) IN sala \ZUUO}. Smith (1997), divided the political risk into three categories, which are very sound based on what was found under project finance and the events that can mak a project fail. These are traditional political risks such as expropriation, currency convertibility and transferability, political violence (war, sabotage, and terrorism) Regulatory risk such as risk from unanticipated regulatory changes (taxation, foreign inv. laws (output price)), and Quasi-commercial risks that include risks whe! having state-owned supplier or customer with the questionable willingness to fulfilled obligations. Sara (2008) divided the whole ICRG's political risk index variable into three namely quality of Institutions (bureaucratic quality, corruption, democratic accounta bility, social conditions, law and order, military in politics); conflicts and tensions (ethnic tension, religious tension, external conflict and internal conflict) and polic quality (government stability and investment Profile). Sara (2008) found that “changing legislation”, “war and conflicts” and “legal system and property rights were the main political risks to a project. Further, the researcher stated that the inadequacy of institutions does lead to more project finance loans, which lead to the conclusion that such syndicated loan types can help deter some of those risks. Tension and conflict have no effect on whether project finance loans ar preferred to full-recourse syndicated loans. The Hainz and Kleimeier (2006) model of double moral hazard disclosed that firm moral hazard (managerial influence on the probability of success, firm effor costs, the economic health of the country, and country corporate governance) and bank morla hazard (Bank influence on the probability of success and Bank effor cost). Yescombe (2002) the commercial risks, which relates to a project’s construction and operational phase, are covered by variables such as bureaucratic quality in relation to obtaining permits and keeping them even though the government might change. The same risk is also related to the level of corruption in government, as it will be an indication of whether the government or sub-levels or the government might grant favorable terms to local competitors to the project which may hurt the operation of the project. The external and internal conflicts cover for war and conflict risks found in Yescombe’s (2002) investment risk component. The investment risk consisting of war and conflict along with currency convertibility and risk of expropriation namely all those relating to conflicts and tensions while the investment profile covers “change of law” component from Yescombe’s (2002) risk matrix, is mainly covered by bureaucratic quality, as it deals with policy uncertainty and the ability of the government to make predictable policies that do not change when government change. This could also be related to government stability, as it covers the government's ability to carry out its declared program(s). This would suggest whether the policies made, will be somewhat predictable, as they have declared in the program and hence should not suddenly pose new laws that could alter the profitability of the project. The last component of Yescombe’s (2002) political risk is the quasi-political risk which is taken into account through the two variables “Rule of Law” that looks at the effectiveness of the legal system and "Investment Profile". The former is highly important in project finance due to the many contacts made, and the latter includes the viability of contracts and thus the likelihood of government breach of contract and also the applicability of the contracts. This is often necessary as the loan taken on the project is denominated in other currencies than the one of the host countries. Developing markets often have poor financial markets that are not capable of providing the funds needed for the project, in which case the loan is denominated in foreign currency (Sara, 2008).
As indicated in the above table, the model was fitted at a significant level of 0.05 as its F and the Durbin-Watson test were 0.000 and 1.90, respectively. Similarly, it can be seen from Table1 that the model was statistically considerable at P-value of F statics of 0.000 as compared to that of the critical level of 0.05. Therefore, the predictors dependably predict the outcome variable, construction projects implementation. Evermore, as the P-value was less than 0.05, the study stressed that the collection of predictors indicate the momentous correlation with the endogenous variable, or that the group of independent variables consistently predict the construction projects implementation. In this part, the study discussed the findings on the political risk that affected the construction project activities such as finance and implementation in Ethiopia.
As indicated in the above table, the model was fitted at a significant level of 0.05 as its F and the Durbin-Watson test were 0.000 and 1.90, respectively. Similarly, it can be seen from Table1 that the model was statistically considerable at P-value of F statics of 0.000 as compared to that of the critical level of 0.05. Therefore, the predictors dependably predict the outcome variable, construction projects implementation. Evermore, as the P-value was less than 0.05, the study stressed that the collection of predictors indicate the momentous correlation with the endogenous variable, or that the group of independent variables consistently predict the construction projects implementation. In this part, the study discussed the findings on the political risk that affected the construction project activities such as finance and implementation in Ethiopia.
gious tensions. The adjusted R2 depicts that 72.30 per cent of the unpredictability of Project Finance and its implementation in Ethiopia is accounted for the model, even afte taking in to account the number of independent variables in the constructed model. The R2 of political factors indicated that the degree lack of democrat accountability, internal and external conflicts, military enterprises participation in the construction project, investment profile, socio-economic conditions, corrut tion, internal conflict, external conflict, law and order, ethical and religious tensions significantly affected the construction projects implementation in the countr It further indicated that the predictive power of the model construct was greater and suggested that there was a considerable combined effect of political ris factors on the construction projects implementation in Ethiopia. These figures were adequate and in fact, meet the rule suggested by previous literature. These results suggested that political predictors similar to bureaucratic quality, democratic accountability; internal conflict, military politics, investment profil: socio-economic conditions, corruption, external conflict and ethnical and religious tensions had highly impaired the construction project activities for examp! project finance and implementation in Ethiopia. Also, the findings revealed that other political factors might describe 23.60 per cent of the variance in the cor ctructed model.
gious tensions. The adjusted R2 depicts that 72.30 per cent of the unpredictability of Project Finance and its implementation in Ethiopia is accounted for the model, even afte taking in to account the number of independent variables in the constructed model. The R2 of political factors indicated that the degree lack of democrat accountability, internal and external conflicts, military enterprises participation in the construction project, investment profile, socio-economic conditions, corrut tion, internal conflict, external conflict, law and order, ethical and religious tensions significantly affected the construction projects implementation in the countr It further indicated that the predictive power of the model construct was greater and suggested that there was a considerable combined effect of political ris factors on the construction projects implementation in Ethiopia. These figures were adequate and in fact, meet the rule suggested by previous literature. These results suggested that political predictors similar to bureaucratic quality, democratic accountability; internal conflict, military politics, investment profil: socio-economic conditions, corruption, external conflict and ethnical and religious tensions had highly impaired the construction project activities for examp! project finance and implementation in Ethiopia. Also, the findings revealed that other political factors might describe 23.60 per cent of the variance in the cor ctructed model.
INTERNATIONAL JOURNAL OF RESEARCH IN COMMERCE & MANAGEMENT
INTERNATIONAL JOURNAL OF RESEARCH IN COMMERCE & MANAGEMENT
Related topics:
Taxation in developing countriesProject ManagmentSocial and Enviromental Accounting
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