Review of Economics and Development Studies Vol. I, No 2, December 2015 73 Volume and Issues Obtainable at Center for Sustainability Research and Consultancy Review of Economics and Development Studies ISSN:2519-9692 ISSN (E): 2519-9706 Volume 1: Issue 2 December 2015 Journal homepage: www.publishing.globalcsrc.org/reads Increasing Supply of Tradable Goods in the Common Market for Eastern and Southern Africa (COMESA) Macleans Mzumara Department of Economics, Bindura University of Science Education, 1020, Bindura, Zimbabwe. macmzumara@yahoo.com ARTICLE DETAILS ABSTRACT History Revised format: Nov 2015 Available online: Dec 2015 The author investigated the nature of institutional quality in the Common Market for Eastern and Southern Africa (COMESA) on the basis of voice and accountability political stability, government effectiveness, regulatory quality, rule of law and control of corruption. The author further investigated the existence of a link between institutional quality and factors of production. The results show that capital, entrepreneurship and foreign direct investment are the major determinants of production of tradable goods in COMESA. In exception of Mauritius and Namibia (currently no longer a member) the rest of COMESA member states have very poor institutional quality. This affects their ability to attract foreign direct investment hence production of tradable goods. Voice and accountability, government effectiveness, rule of law and political stability play a major role in increasing production of tradable goods in COMESA. Foreign direct investment is affected by voice and accountability, rule of law and political stability than any other factors. Availability of raw material is affected by government effectiveness, regulatory quality, political stability, voice and accountability and control of corruption. Capital is very sensitive to issues of voice and accountability and control of corruption and regulatory quality. © 2015 The authors, under a Creative Commons Attribution- NonCommercial 4.0 Keywords Governance indicators, foreign direct investment, institutional quality, production, business JEL Classification G30, G20, L23, M10 Corresponding author’s email address: macmzumara@yahoo.com Recommended citation: Mzumara, M. (2015). Increasing Supply of Tradable Goods in the Common Market for Eastern and Southern Africa (COMESA). Review of Economics and Development Studies, 1 (2) 73-117 DOI: https://doi.org/10.26710/reads.v1i2.117 1. Introduction It is essential that supply of tradable goods in the Common Market for Eastern and Southern Africa (COMESA) increases so that it can become a significant player in the global trading arena. Increasing supply of tradable goods is one of the solutions of increasing intra-regional trade in COMESA. The current state of affairs shows that the volume of intra-COMESA trade is 7% of total trade. This means http://www.publishing.globalcsrc.org/reads mailto:macmzumara@yahoo.com mailto:macmzumara@yahoo.com 74 74 that extra-regional trade is substantial compared to intra-regional trade. The fact that member countries trade more with non-member countries than other partners simply means tradable goods are in short supply in member countries and can only be sought outside the grouping. However, increasing the production of tradable goods requires that an investment be made for their production. Sometimes domestic investment alone cannot help a country to succeed in increasing production. That then calls for the assistance of external investors. Foreign direct investment (FDI) through the transnational firms have the ability to transfer technology, superior management techniques to developing countries which can lead to increased production at a low cost and then boost exports thereby altering the terms of trade (Lipsey 1995). However, for external investors to invest in a particular country, they analyse governance indicators of a particular country before making their decision. This paper intends to investigate the nature of institutional quality on the basis of voice and accountability, political stability, government effectiveness, regulatory quality, rule of law and control of corruption. The paper further investigates any existence of a link between institutional quality and factors of production. 2. Background The COMESA was previously known as the Preferential Trade Area for Eastern and Southern African States (PTA). The Preferential Trade Area was established in 1984. In the 1990s the PTA was transformed to the Common Market for Eastern and Southern Africa. The following countries are members of COMESA: Burundi, Comoros, DR Congo, Djibouti, Egypt, Eritrea, Ethiopia, Kenya, Libya, Madagascar, Malawi, Mauritius, Rwanda, Seychelles, Sudan, Swaziland, Uganda, Zambia and Zimbabwe. COMESA region has a population of 430 million people (COMESA 2011, Mzumara 2013). COMESA launched a customs union (CU) on 7-8 June 2009. The member states agreed to the establishment of a common external tariff (CET) and a three year transitional period before the implementation was also agreed upon (ZimTrade 2010, Mzumara 2013). Due to multiple membership by COMESA member states in two or three sub-regional organizations and duplicity of the activities of the COMESA, the east African Community (EAC) and the Southern African Development Community (SADC) a tripartite agreement was reached by the Heads of State of the three sub-regional groupings. On 12 June 2011, the COMESA-EAC-SADC Free Trade Area was launched (Trade Marks of Southern Africa 2013, Mzumara 2013). Table 1.1: Intra-COMESA total trade 1997-2003 in US$ (million) Member States 1997 1998 1999 2000 2001 2002 2003 Angola 57 65 57 70 98 197 337 Burundi 26 31 23 25 59 33 52 Comoros 6 5 4 5 4 3 5 Congo DR 106 113 99 141 113 349 321 Djibouti 71 74 64 78 83 85 129 Egypt 175 156 179 238 305 620 321 Eritrea 3 9 5 8 2 2 8 Ethiopia 317 338 273 263 222 247 186 Kenya 697 658 612 673 817 945 943 Madagascar 57 52 69 83 50 48 120 Malawi 154 123 132 94 137 115 154 Mauritius 130 150 140 156 186 189 209 Review of Economics and Development Studies Vol. I, No 2, December 2015 75 Namibia* 65 157 59 75 99 200 348 Rwanda 129 90 80 64 172 31 37 Seychelles 15 12 16 15 15 27 14 Sudan 24 42 25 277 312 346 494 Swaziland 34 36 34 71 52 103 121 Uganda 364 334 222 230 394 381 425 Zambia 174 272 189 240 227 211 380 Zimbabwe 341 327 258 256 153 365 186 Total 2,945 3,044 2,540 3,061 3,499 4,498 4,790 Source: COMESA (2004) * Namibia is no longer a member of COMESA Table 1.2 extra-COMESA imports 1997-2003 in US $(millions) Member States 1997 1998 1999 2000 2001 2002 2003 Angola 2,542 2,020 3,054 2972 3082 3603 3983 Burundi 112 170 122 180 133 86 126 Comoros 50 43 31 31 31 34 34 Congo DR 1036 1119 1013 813 1016 1271 1355 Djibouti 145 173 192 197 181 209 232 Egypt 13099 16777 15878 13873 11615 17880 10749 Eritrea 524 503 506 463 535 531 598 Ethiopia 965 1329 1262 1154 1685 1450 2583 Kenya 3637 3706 3106 3342 3815 3273 3450 Madagascar 571 583 707 905 566 386 1008 Malawi 690 490 530 479 505 590 621 Mauritius 2021 2202 2008 2058 1955 2092 2229 Namibia* 1582 1954 1292 1398 1481 1287 1386 Rwanda 270 280 199 112 107 64 91 Seychelles 326 372 419 254 424 395 341 Sudan 142 259 161 1735 1535 1994 2374 Swaziland 1164 1144 1008 1045 836 912 1391 Uganda 529 647 646 546 613 649 919 Zambia 784 880 888 1056 1687 1129 1314 Zimbabwe 2508 2294 1948 1741 1471 2268 2069 Total 32,697 36,545 34,972 34,357 33,311 40,104 36,854 Source: COMESA(2004). Table 1.1 above shows intra-COMESA total trade from 1997 to 2003. total intra-COMESA trade was 76 76 US$2.9 billion in 1997, US$3 billion in 1998, US$2.5 million in 1999, US$3 billion in 2000, US$3.5 billion in 2001, US$4.5 billion in 2002 and US$4.7 billion in 2003. during the same period extra- COMESA imports only (table 1.2) were US$32.7 billion in 1997, US$36.5 billion in 1998, US$35 billion in 1999, US$34.3 billion in 2000, US$33.3 billion in 2001, US$40 billion in 2002 and US$39.9 billion in 2003. this implies that if the goods were available in the region all the above amounts could have been spent within the region. Taking one country such as Egypt, her total trade was US$17.2 billion in 1997, US$19.7 billion in 1998, US$19.6 million in 1999, US$18.8 billion in 2000, US$15.7 billion in 2001 and US$22.6 billion in 2002. During the same period her total intra-COMESA trade was US$175 million in 1997, $156 million in 1998, US$179 million in 1999, US$238 million in 2000, US$305 million in 2001, US$620 million in 2002. This gives Egypt total extra-COMESA as US$17 billion in 1997, US$19.6 billion in 1998, US$19.4 billion in 1999, US$18.5 billion in 2000, US$15.4 billion in 2001 and US$22 billion in 2002. It can be seen from the above statistics that trade is heavily titled towards extra-COMESA. Since extra- COMESA imports are substantial, it would appear that member countries would have imported the same goods from partner countries where tariffs have been eliminated or are extremely low. Businesspersons would definitely import from member countries so as to enjoy the advantages of free trade. However, they are not doing so instead they are importing from countries whose goods are subject to higher tariffs. It is clear judging from the statistics that much sought imports are not available in partner countries in COMESA. This shows a serious picture of supply constrain in production of tradable goods in COMESA. Unless capacity to produce tradable goods is improved intra-COMESA trade will continue to remain low while member countries continue to source their requirements elsewhere. 3. Literature on Institutional Economics This paper is an effort to address the issue of supply of tradable goods in COMESA. The increasingly importance of new institutional economics with its dynamism becomes the most appropriate framework to address the issue of supply of tradable goods in COMESA. According to Nomvete (1992), majority African states face unstable political conditions as well as regional tensions and instability. Effective and successful cooperation framework can only occur if there is an existence of health and democratic conditions in which economic management is both transparent and accountable. Apart from political and economic prerequisites the availability of indigenous institutional capacity is also important. A viable institutional mechanism at regional and national levels is essential. However, very little attention has been given to the institutional framework for regional integration and interface levels. Muntharika (1990) acknowledged that the primary responsibility for effective regional integration cooperation depends on governments and their people of the countries concerned. However taking in account problems and the meager resources of the majority African states, substantial international support is required to augment national efforts. Bach (1993) and Barad (1990) both agree that despite continuing verbal commitments to regional integration in Africa, in reality very little has been done. The reasons advanced for no action are: historic, political, economic and institutional. Seghor (1990) put forward the same views that the problem of many African states in regional integration is lack of participation by their people in discussion on regional agendas. Bach (1993) posed a question how Africa can bridge the implementation gap and move from away from rhetoric to action without neglecting important decisions to be taken regionally, policies and institutional needs for cooperation must and foremost be addressed at a national level. A national initiative should include strengthening institutional capacities. Adedeji (2002) points out that many Africans states carried out import substitution strategy. To manufacture goods for example, they imported capital goods, the skills and the professional labor. One would therefore on the onset assume that the raw materials would come from African states themselves but in many cases they had to be imported too. So really the manufacturing Review of Economics and Development Studies Vol. I, No 2, December 2015 77 plants became just locations of assembly. They were vulnerable and bound to fail. Most of the shortcomings are institutional. Linn (2003) supports better local policies, governance and institutional building. In the absence of such measures regional integration will not be successful in the long term. The New Partnership for Africa’s Development (NEPAD) articulate the need to promote democracy, good governance and respect for human rights through appropriate security sector policy and institutional reform. Increasing physical integration through infrastructure development, implementation of NEPAD programs need to be done through establishing of a workable policy, regulatory and institutional framework especially creating a suitable conditions for investment, capacity building program to empower particularly the implementing agencies. NEPAD further states that the critical need is to achieve a purposeful programming and effective implementation of development oriented investment flow and effective intervention in the agencies of global governance. According to the World Bank (2000), market cannot operate without effective and efficient institutional framework. The needed institutional infrastructure includes the rules and regulations of market economy such as property rights, contract enforcements and regulatory mechanisms for anti competitive behavior. It also includes social and political systems that reduce risk and manage social conflict through proper governance. It further states that a key factor that has constrained Africa’s integration process is the continent’s small markets which do not permit the economies of scale that allow an economy to function effectively. Governments must monitor and enforce rules and regulations effectively and equitably. Regional integration has an advantage of promoting diversification and export to the regional market helps the countries concern gain confidence before entering the global market. Mattli (1999) came up with a model of a rational approach to behavior. He argued that two types of requirements need to be satisfied if integration is to succeed. First, there must be demand by market players for greater integration. Market players must anticipate a significant potential for economic gains, perhaps because regional economics lack complement or because a small size of the regional market does not offer important economies of scale, the process of integration will eventually wither away. The author emphasizes on commitment to improve compliance with the rules of cooperation. Rodlaver (2004) shows empirical evidence that points to clear link between the quality of institutions on one hand and economic growth on the other. He further points out that continued progress in building governance, transparency and the rule of law is essential in attracting private investment and sustaining citizens confidence in the government and the regional coordination can make a major contribution on this. Functioning judicial systems, secure property rights, fighting corruption are important issues for a region to emerge as a strong competitor in the globalized market place. 4. Conceptual Development: Factors of Production in COMESA Mainstream economics single out the following factors of production, land, labor capital and entrepreneurship. In order to produce goods resources are needed. These can be called factor inputs, which are normally available in the production of products. Land is an endowment that mankind can use to produce products. Dale (1997) comments that of the three factors of production that are said to underpin the creation of goods – capital, labor and land – it is the land that is least well understood and defined. Labor is human input that is also needed in the production process. It is not just the statistics of people; it refers to human capital that is the quality of labor inputs. These resources can be improved through investment in education, training and health. The third resource of capital simply means to investment in goods which can be used to produce other goods such as machines. Capital goods can further be divided into fixed and working capital. Fixed capital may include things like plant and equipment. Working capital includes stock of finished or semi-finished goods. The presence of the above factors may mean nothing if there are no risk takers to organize such other productive resources. These are referred to as entrepreneurs. A French economist Cantillna (1725) described entrepreneur as the agent who purchase the means of production for combination into 78 78 marketable products and takes the risk. In order to produce tradable goods in the Common Market for Eastern and Southern Africa (COMESA) the four factors of production namely, land, labor, capital and entrepreneurship must exist. This is a necessary condition to produce goods but not sufficient as we will observer in the later part of this paper. For the purpose of this paper the author has expanded the factors of production to include; foreign direct investment (FDI), capital, raw materials, utilities, infrastructure, land, human capital and entrepreneurship. Theory reveals that in order to increase supply of tradable goods in a regional grouping the above factors should be abundant and available. However, according to Muntharika (1990) governments and the people in all regional groupings in Africa and other developing world need international support to augment their meager resources. Foreign direct investment can be seen as an international community response in this regard. This means that the Common Market for Eastern and Southern Africa can augment its limited resources by tapping on FDI in its effort to increase production of tradable goods. FDI is non-resident investment in a domestic such as branch plant. Such an investment can increase the capacity to produce tradable goods in COMESA and other regional settings. If the flow of FDI is good in the region, it may also be an indicative that there is conducive macroeconomic environment that encourages investment. Since domestic resources are limited in COMESA countries, FDI becomes crucial in determining the capacity to produce tradable goods. Foreign direct investment also transfers technology to the recipient country. Technology is key in reducing the cost of production and enabling a country to enjoy economies of scale (Lipsey 1995). COMESA needs technology in order to increase production of tradable goods. This can be achieved through attracting FDI. FDI offers much more. Foreign direct investment involves much more than just transfer of capital or the establishment of a local factory in a developing country. They carry with them technologies of production, tastes and styles of living, managerial service and various business practices including cooperative arrangements (Todaro 1997). FDI generates rents to transnational corporation by virtue of their possession of superior technology, management and/or access to global markets. According to economic theory, host communities get ‘spillovers’ benefit of the superior assets. Indeed ‘effective spillovers’, which occur through the transfers of technologies and management practices, are increasingly seen as the primary benefit of FDI. These are dubbed a ‘contagion’ effect knowledge is diffuses to domestic firms and workers, thereby raising their efficiency and productivity (Gallanger & Zarsky 2005). The variables which influence FDI are domestic policies, capacities and institutions (Zarsky 2005). In this section, the author discusses capital in general. Capital is required in COMESA if production and capacity to produce tradable goods is to be improved. This supported by (Muntharika 1990, Cook and Sach 1999). Here emphasis is given to domestic capital. To increase production in COMESA countries, domestic capital is required. Investment is the function of savings. Research has shown that countries with high rates of savings have high rates of investments (Lipsey 1995). Those countries with low rates of savings have low investments. The question that can be posed is how can a COMESA country increase the rate of savings? This question can be answered by looking at tax structures of individual COMESA countries. Most of COMESA countries have very high tax structures. These leave the residents of these countries with less disposable income. Generally the major portion of disposable income is spent on consumption while little is converted into savings. So if the disposable income is very little it is likely that there will be little or no savings at all. Some of COMESA countries such as Zimbabwe have experienced unusual high rates of inflation. In such countries it is hard to save with a severely eroded purchasing power. In such countries people live hand to mouth with nothing in the bank. There are also very high interest rates which discourage borrowings in some COMESA countries. This Review of Economics and Development Studies Vol. I, No 2, December 2015 79 means those who want to expand production and those who want to start to produce are discouraged by high costs of borrowing. In the process of capital formation there is also the issue of intermediaries and these are lacking in COMESA countries to harness savings and their allocation to productive sector. In order for COMESA to produce tradable goods the above issues have to be addressed by individual countries. The issue of investment has to seriously be looked into by each COMESA country. Investment is of particular importance to the marginalized people. Through investment in the productive capacities – knowledge, skills technology and institutions for collective action – stagnant patterns of poverty and marginalisation can be changed into robust patterns of economic development and social inclusion (Zarsky 2005). Whilst most of developing countries are gifted with natural resources such as minerals and others, they need capital to exploit such resources. COMESA is no exception. It has a lot of natural resources but incapable of fully exploiting them because of lack of capital. Capital is also required to add value so that COMESA countries do not just export primary products. Primary products are vulnerable to commodity price falls. This could also substitute the importation of capital goods from outside the region. Supply of tradable goods can also be increased in COMESA if there is availability of raw material. Production in the manufacturing requires raw materials. If there is no raw material, no product can be produced. Raw materials can be sourced within a country or within partner countries or outside the region itself. To produce and acquire raw materials requires land, infrastructure, labor, transport and funding. In some COMESA countries production is now below capacity due to lack of foreign currency to import raw materials. COMESA could reconsider promoting the clearing house once again. That meant that COMESA countries could use their domestic currencies to purchase goods from other COMESA countries. During the trading period, accounts were settled in the United States Dollar. However, when most of the countries embarked on trade liberalization it was felt that they would generate sufficient foreign currency hence there was no need of using the clearing house. As it is now, countries such as Malawi, which is experiencing severe shortage of foreign currency could benefit through the revival of the clearing house to remain and increase its productive capacity. Utilities such as water, electricity, gas, and so on are essential to produce a product in a factory or on a farm. To increase its production of tradable goods, COMESA member countries need to have adequate resources of water, power supply and gas. If electricity power is not constantly available it may interfere with the production. To increase production of tradable goods it requires constant supply o electricity. Countries such as Uganda and Zimbabwe face constant shortages of electricity. In the case of Zimbabwe it imports electricity from South Africa, Mozambique and Democratic Republic of Congo to augment its domestic supplies. However, sever shortage of foreign currency frequently affects the importation. A number of COMESA countries therefore, electricity supply limits their capacity to produce. This means they need to find long-term solutions of expanding generation of electricity for them to expand production. Infrastructure is also required to support production of tradable goods in COMESA. Roads, railway, ports and so on are required to transport raw materials or finished goods. If there is no adequate infrastructure it may affect the production of tradable goods. Cook and Sach (1999) recognize the importance of infrastructure in the supply of tradable goods. They lament that transitional cost in creating institutions to manage regional public goods are under funded and frequently incapacitated and concluded that there is an important role for international donors to support their provision. This is in agreement with Muntharika (1990). Business environment risk intelligence (BERI) indicators used by Knack and Keefer (1995) include infrastructure quality. A strong index of infrastructure is associated with higher investments. Investors tend to invest in countries with infrastructure. Human capital is the next, which is referred to as knowledge and skills embodied in an individual are required in the 80 80 production process. COMESA can increase the production of the tradable goods if it has adequate human capital not just the big size of human population. This requires provision of education and skills and substantial investments in tertiary and vocational systems. COMESA may have land and other resources but if it doesn't have high quality human resource, production of tradable goods may just be a dream. In COMESA to increase production of tradable goods land is required. Land is required where to farm or where to build a factory. If there is constraint in either of the two uses of land, production of tradable goods cannot be increased. Firms and individuals in COMESA should have access to land where they can produce crops that can be exported or used as inputs in further production and also used as a factory or a warehouse. It is not just land but good quality land that can lead to higher productivity. COMESA needs those who can take risks to organize other productive resources in order to increase tradable goods. They cannot increase themselves unless there are individuals in the region or outside investing in COMESA. Entrepreneurs are required to initiate projects in COMESA. Ireland (2001) defines entrepreneurship in the context-dependent social process through which individuals create value by bringing together a peculiar package of endowments to exploit an opportunity in the market place. Two important entrepreneurial skills are ability to gain access to a variety of endowments and knowing how to leverage them effectively. Covin and Stevin (2001) describe entrepreneurship as the prosperity of a firm to take calculated risks, to be innovative and to demonstrate pro-activeness. To establish whether the above factors are perceived to be determinant of increasing supply and capability of tradable goods in the Common Market for Eastern and Southern Africa (COMESA) statistically, the following hypothesis is developed. HI There is no relationship between foreign direct investment (FDI) raw materials, utilities, infrastructure, land, human capital, entrepreneurship and production of tradable goods in COMESA. 5. Institutional Framework The mere presence of factors of production may not lead to increased production of tradable goods. This calls for institutional framework set of institutions or rules of the game. These are the formal or informal rules governing individual’s behavior or rules of the game may severely constraint the proper functioning and the availability of factors of production in regional grouping. North (1993) describes institutions as humanly devised constraints that structure human interaction. They are made of formal constraints (rules, laws, constitution) informal constraints (norms of behavior, conventions and self imposed codes of conducts) and their enforcement characteristic. Their combination defines the initiative structure of societies and specifically economic activities. Institutions and the technology used influences the transaction and transformation costs which add up to the costs of production. When it is costly to transact then institution matters and it becomes increasingly costly to transact. A viable institutional mechanism at regional and national levels is needed (Nomvete 1992). The most significant decisions to be taken regionally are policies and institutional needs for cooperation must and the key to be addressed at national level (Batch 1993). Regional integration can accomplish its objectives only if there is commitment of concerned governments and their people (Muntharika 1990). Groot, Linders, Rietveld and Subramana (2003) emphasized that a better quality of institutional framework decreases uncertainty about contract enforcement and general economic governance. It in turn reduces transactional costs associated with uncertainty by increasing confidence in the process of economic transactions both at national and regional levels. COMESA countries can be in a serious trouble if within the group or outside the group perceives that to do Review of Economics and Development Studies Vol. I, No 2, December 2015 81 business with a particular COMESA country requires bribes to get a license, land is not available and at the same time there is no rule of law to protect investment. It may negatively affect such a country. Investors would be calculating on additional transactional costs and find that it may not be profitable to invest or do business with that particular COMESA country. They may go to the countries where here are no additional transactional costs arising out of poor policies. Even though the factors of production may be abundant the institutional environment may not permit the increased supply of tradable goods. This may call for the regional grouping strengthening its member countries capability to produce tradable goods by changing their behavior of doing business and policies, which may be, referred as institutional change as advocated by North (1990). Institutional quality and governance matter if trade and production can be increased both at national and regional levels. The bank: gives the following as component of institutional quality [constructed from Kaufman, Kraay and Zoida - Lobaton (1999) and other sources] voice and accountability, political stability, government effectiveness, regulatory quality / burden, rule of law and control of corruption. These affect institutional environment and arrangements (World Bank 2000). Kaufman, Kraay and Zoida - Lobaton (1999) constructed six aggregate indexes from numerous indicators collected from 14 different sources including ICRG, BERI, Freedom House and others. The aggregate indexes are rule of law "graft", voice and accountability, government effectiveness, political instability and violence and regulatory burden affect institutional quality. If the people in a particular COMESA country do not have a voice they may not actively participate in the regional integration. They may not become entrepreneurs. The issue of accountability on the part of a particular COMESA government may be crucial in increasing production of tradable goods. Outside investors are keen to see whether a particular COMESA government is accountable and transparent. If these attributes exist they may find it safer to put their money in that country. Investors tend weigh the decision to invest with the performance of a particular government on attributes of voice and accountability. Konnend and Meiguire (1985) used civil liberties index as a proxy for economic rights, such as freedom from expropriation or the enforceability of property rights and private contracts. They found that civil liberties were positively associated with investment rates through increasing investment growth rates. Where there is no political stability, land and raw material may be available but no one can produce because of the risk associated with political instability. There is a lot of uncertainty in dealing with a country that is politically unstable. How do you deal with the issue of property protection and others such as enforcement of agreements? An example on point of time was Somalia where could an investor go with a dispute when there was no government? Investors and business people will shun away a country highly volatile politically even though it may have abundant natural resources hence it may not be expected to increase production of tradable goods. Wars destroy infrastructure, production concerns and so on. This has been the case in Democratic Republic of Congo (DRC) where civil war in that country has destroyed infrastructure. Although DRC is endowed with natural resources production has gone down due to political instability. Angola was also affected for a very long time until recently when peace returned so was Mozambique. A country politically stable can expect to attract investors holding other factors constant. It can therefore contribute to increase in production of tradable goods in the region hence contribute to increased intra-regional trade. Government effectiveness is crucial in the institutional framework. It ensures that there is no corruption in issuing licenses, land and other things. It also has the ability to regulate the rules and policies how business is done. It enforces the agreements between business people and between itself and business people. If a particular COMESA government is effective it may raise the institutional quality by making the rules of the game better. In contrast, if the government is ineffective it may impact the institutional quality and this may affect foreign direct investment, proper production of raw material provision of 82 82 utilities, infrastructure, human capital, land, capital and entrepreneurship. This would drastically affect the production of the tradable goods. With an ineffective government there is great uncertainty among investors and business. Trading at the stock exchange becomes volatile due to uncertainty. This makes it hard neither to raise capital nor to venture in production. Effective government gives an assurance to investors and others. Regulatory quality is an important as other factors governing the institutional quality. In developing countries many regulatory entities have been established. There are available in member countries of a particular regional integration grouping. How they perform their duties is considerable importance to business people both investors and traders. If the rules or regulations are not clear they may impact on business people. If they regard policies to be unrealistic it may also impact their decision to invest or trade with a particular country. If there are favoritisms in granting licenses this may also have a negative impact. If competition is suppressed it may also impact on the proper functioning of the economy. If the regulatory quality is credible other things being equal may create a conducive atmosphere to do business hence remove uncertainty and transactional costs. Production of tradable goods can increase. COMESA member countries need to adhere to the rule of law. Rule of law includes where there is a dispute between the government and a private company and then the government does not follow legal procedure to settle the dispute. It may also include the general decline in exercising rule of law in protection of property and their owners. If the rule of law does not exists in a particular COMESA country investors and traders may not be keen to enter agreements and contracts with other business people if they perceive that there is no rule of law. This has a tendency of increasing transactional costs associated with uncertainty in dealing with the concerned country. This can therefore affect negatively the production of the tradable goods through investment being not forth coming. Generally in countries where a policy of nationalization of production concerns have been exercised, such countries have seen drastic reduction of private investment due to fear that if they establish in such countries they could lose the investment altogether. Knack and Keefer (1995) include nationalization risk in their indicators that investors are concerned with. According to Collier and Pattilo (2000) in their research have shown that investment behavior in the in total depends on measurements of country’s risk. Member countries will have to enforce rule of law to create the environment for both investment and trade. Consequently, where there is rule of law, it is not risky to invest in such a country. There are minimal transactional costs due to absence of uncertainty. Investors and traders would feel safe to trade with counter parts in COMESA countries knowing that the agreements and contracts entered would be honored in the court of law in that country. The rule of law hence affects the provision of factors of production. The quality of institutions in COMESA is affected if there is rule of law or no rule of law. The quality of institutions depends also on how a particular country controls corruption. Since COMESA is made up of member countries, its success in having high quality institutions depends heavily on the ability to deal with corruption. Corruption renders policies, procedures, regulations a mockery. Corruption brings disorders in the system thereby affecting the institutional costs. It is hard to deal with countries, which are corrupt because there are a lot of uncertainties in dealing with such countries. World Bank (1997) showed the following as main indicators that inhibit investment, production and trade both at national and regional levels. These are policy unpredictability, quality of government service, corruption and red tape and judicial unpredictability. The survey was conducted in 67 countries involving actual investors. World Competitive Year Book (WCY) has used bribing and corruption as part of its indicators that investors look at. International Country Risk Guide (ICRG) - Knack and Keefer (1995) have used ICRG indicators corruption in government enforceability of contract, the rule of law, expropriation risk, and repudiation of contracts by governments and quality of Review of Economics and Development Studies Vol. I, No 2, December 2015 83 bureaucracy as significance to the determination of institutional quality. In looking at the quality of institutions in the Common Market for Eastern and Southern Africa (COMESA) on the basis of voice and accountability, political stability, government effectiveness, regulatory quality, rule of law and control of corruption a specific research question is developed. 1: What is the nature of institutional quality in COMESA member countries with respect to the following variables; voice and accountability, political stability, government effectiveness, regulatory quality, rule of law and control of corruption? 6. The Link Between Institutional Quality and Factors of Production in COMESA In this section the author intends to establish the link between institutional quality and factors of production in COMESA. The mere existence of natural resources may not lead to increased production of tradable goods. In order for COMESA to increase the supply of tradable goods requires that there should not be high transactional costs arising from institutional quality, uncertainty in contract enforcement in the use and provision of factors of production. World Bank (2000) institutional quality and governance matter if trade and production can be improved both at national and regional levels. Low trade and investment affect nations and regions with poor institutional quality. Investment for example is highly sensitive to corruption, accountability, transparency, regulatory quality and rule of law. Investors will tend to invest in countries that show no corruption, high accountability and transparency regulatory quality that is fair and not corrupt and existence of rule of law. When a bribe is demanded before the approval of the project, the project costs increase by the amount of the bribe yet such money simply goes to an official associated with the process. If the money had gone into the project it would have increased production. According to BERI indicators as used by Knack and Keefer (1995) contract enforceability, nationalization risk, bureaucratic delays and infrastructure quality have effect on investment. A strong index is associated with higher investments. Human resources may be poor if there are no regulatory measures that improve standards. Corruption may also affect the quality of human resources. Corruption in providing training and also in recruitment. Both anomalies lead to poor human resources. Political instability may lead to exodus of skilled people out of a particular country. The rule of law may also affect human resources as skilled manpower feel insecure and may seek to move to other countries where they perceive to have the rule of law. Land is critical to production of tradable goods. The institutional quality may affect its accessibility. If corruption exists in the provision of land it may affect the production of tradable goods. Regulatory quality may also affect land available for production. The delays in land allocation may affect production of tradable goods. Poor land policies may affect production. Utilities are needed in the process of creating a product. To establish a business you need water, electricity, phone and so on. If corruption exists in member countries the provision of these utilities may affect production. They may be available to those who have paid the bribe but are not producing or may increase transactional costs to those who are producing and that would lead to the limit of their capacity. In contrast if utilities are facilitated by a high institutional quality they may facilitate production. A high institutional quality can lead to a better provision of raw material. Rule of law that guarantees contract enforcement may encourage suppliers from one country to supply to another without facing a risk of uncertainty arising from the transaction. This can lead to the increase in production in the recipient country. Political stability may also affect the provision of raw material outside or within that country. Generally where there is political instability production of both final goods and intermediate goods are affected. Countries and regions with low institutional quality have poor infrastructure. Infrastructure supports 84 84 production of tradable goods. To address the issue of tradable goods in COMESA requires that there be adequate infrastructure. Where there is no transparency and where there is corruption provision of infrastructure may be negatively affected. Corrupt officials may build a substandard infrastructure and pocket the remaining funds. Since infrastructure supports production, it may be affected with such an act. Private individuals may not invest in infrastructure development if property rights are not respected. High quality institutions are positively associated with high quality infrastructure. High quality institutions may encourage and facilitate the development of entrepreneurship through which COMESA can increase tradable goods. Entrepreneurs are frustrated if there is a problem with licensing their ventures due to corruption bureaucratic delays, no support from government and policies that make their operations difficult. Entrepreneurs may not find confidence if there is political instability in a particular country. The absence of rule of law may discourage them also. To establish whether in the Common Market for Eastern and Southern Africa (COMESA) there is a link between institutional quality and factors of production, the following hypothesis is tested. H2 There is no relationship between voice and accountability, political stability, government effectiveness, rule of law, control of corruption, regulatory quality and production of tradable goods in COMESA. H3 There is no relationship between voice and accountability, political stability, government effectiveness, rule of law, control of corruption, regulatory quality and individual dependent variables individually FDI, raw material, utilities, infrastructure, capital, labor, entrepreneurship. H4 There is no differences in the views of stakeholders on the influence of voice and accountability, political stability, government effectiveness, rule of law, control of corruption, regulatory quality and production of tradable goods. 7. Methodology The paper used stepwise regression analysis to treat the data. The data was collected using a self administered questionnaire to 61 actual exporters, importers, investors, chambers of industries and commerce and others in Zimbabwe by random sampling. Due to constraints in resources the author did not administer in other member states. . In total there were eighty-one questions under the heads; voice and accountability political stability, government effectiveness, rule of law, control of corruption and regulatory quality. Another section of the questionnaire asked the respondents how they perceived; foreign direct investment, raw material, utilities, infrastructure, human capital, land, capital and entrepreneurship as determinants of supply of tradable goods in COMESA. Further data was collected and develop from the World Bank index on institutional quality indicators related to each COMESA country in respect of the following variables; voice and accountability, political stability, government effectiveness, rule of law, control of corruption and regulatory quality. The following were measurements on the scale 1-5 in respects of the data collected in the questionnaire. Evaluation of scoring of the questionnaire on voice and accountability, political stability, government effectiveness, rule of law, control of corruption and regulatory quality. Table 1.3: Scale for evaluation for governance indicators Scale Response Mean interval Verbal interpretation Review of Economics and Development Studies Vol. I, No 2, December 2015 85 5 Strongly agree 4.50 -5.00 Very high 4 Agree 3.50 - 4.49 High 3 Neutral 2.50 - 3.49 Undecided 2 Disagree 1.50 - 2.49 Low 1 Strongly agree 1.00 - 1.49 Very low Source: Authors’ own table. Evaluation of scoring of the questionnaire on supply constraints Table 1.4 Scale for supply constraints Scale Response Mean interval Verbal interpretation 5 Strongly agree 4.50 -5.00 Very high 4 Agree 3.50 - 4.49 High 3 Neutral 2.50 - 3.49 Undecided 2 Disagree 1.50 - 2.49 Low 1 Strongly agree 1.00 – 1.49 Very low Source: Authors’ own table Results And Analysis HI There is no relationship between Foreign Direct Investment (FDI), raw material, utilities, infrastructures, land, human capital, entrepreneurship, and production of tradable goods in COMESA. Regressing by stepwise regression production of tradable goods on Foreign Direct Investment, raw material, capital, entrepreneurship, labor, land, utility and infrastructure. Stepwise regression returned capital as the most significant contributor to production of tradable goods in COMESA. Production of tradable goods = 6.79 + 1.62 capital Table1.5 Predictor Coef StDev t ratio p Constant -6.794 3.546 -1.92 0.151 Capital 1.62182 0.0561 28.91 0.000 Source: Results of stepwise regression analysis S= 4.979 R-sq = 99.6% R-sq (adj) = 99.5% Table 1.5 shows that capital is related to the production of tradable goods in COMESA. With t ratio = 28.91 and p value = 0.000 both are significant at 5% level of significance. R-sq = 99.6% and R-sq (adj) == 99.5% are both high and there is no variation between the two. With R-sq = 99.6%, capital alone explains 99.6% of variations in tradable goods in COMESA .This gives capital as 86 86 major determinant of tradable goods in COMESA. Table 1.6: The regression equation is production of tradable goods = -20.2 + 1.28 Entrpre Table 1.6 predictor coef StDev t-ratio p Constant -20.21 12.56 -1.61 0.206 Enterpre 1.2804 0.1427 8.97 0.003 Source: Results of stepwise regression analysis Table 1.6 shows stepwise regression showing entrepreneurship to be second most significant in the production of tradable goods in COMESA. Both t-ratio = 8.97 and p-value = 0.003 are significant showing a strong relationship between entrepreneurship and production of tradable goods in COMESA with R-sq = 96.4 it indicates that entrepreneurship explains 96.4% of variations in tradable goods in COMESA. Table 1.7 Production of tradable goods in COMESA = -24.2+0.575 FDI Table 1.7 predictor coef StDev t-ratio p Constant -24.23 22.24 -1.09 0.356 FDI 0.5753 0.114 5.16 0.014 Source: Results of stepwise regression analysis S= 26.47 R-sq = 89.9% R-sq (adj) = 86.5% Table 1.7 shows that FDI is related to the production of tradable goods in COMESA. It becomes third from capital and entrepreneurship. With R-sq =89.9%, FDI explains 89.9% of the variations. Table 1.8 Production of tradable goods in COMESA = -30.5 + 1.42 labor Table 1.8 Predicto Coeff StDev t-ratio p Constant -30.52 24.13 -1.26 0.295 Labour 1.4181 .2848 4.98 0.016 Source: Results of stepwise regression analysis S= 27.36 R-sq = 89.2% R-sq (adj) = 85.6% In table 1.8, t = 4.98. This is above 2 showing a significant relationship between labor and production of tradable goods in COMESA. Table 1.9 Production of tradable goods in COMESA (p/goods) = -8.417 + 1. 4 7 capital +0.127 entrepreneur Table 1.9 Review of Economics and Development Studies Vol. I, No 2, December 2015 87 predictor coef StDev t-ratio p constant -8.417 5.273 -1.6 0.252 capital 1.4663 0.3238 4.53 0.045 Source: Results of stepwise regression analysis In table 1.9, t-ratio of 0.49 in respect of entrepreneurship is very low. Capital t-ratio of 4.53 is very significant but p-value is medium significant. Table 1.10 Production of tradable goods in COMESA (pi goods) = 14.7+3.31 capital -2.12 enterpre + 1.08 raw material. Table 1.10 predictor coef StDev t-ratio p constant -14.739 4.761 -3.1 0.199 capital 3.3104 0.9824 3.37 0.184 enterpre -2.122 1.182 -1.79 0.324 raw material 1. 0809 0.5623 1.92 0.305 Source: Results of stepwise regression analysis Table 1.10 shows that capital is highly correlated with other predictor variables. Entrepreneurship is also correlated with other predictor variables. Raw material is highly correlated with other predictor variables. There was presence of multicollinearity. It may explain also why raw material was left out of stepwise regression. Generally there was multicollinearity among the predictor variables. The other variables such as land, utility and infrastructures labor were also left out due to multicollinearity of predictor variables HI is therefore rejected. There is relationship between Foreign Direct Investment (FDI), raw material, utilities, infrastructure, land, human capital (labor), entrepreneurship and production of tradable goods in COMESA. Of all the above variables, capital is the most important factor that influences production of tradable goods in COMESA followed by entrepreneurship and then FDI. Research Question 1 What is the nature of institutional quality in COMESA member countries with respect to the following variables~ voice and accountability, political stability, government effectiveness, regulatory quality, rule of law and control of corruption? Table 1.11 Relating to 2004 Table 1.11 Country Voice and Political Government Regulatory Rule Control of Accountability Stability Effectiveness Quality of law Corruptio n 88 88 Angola -1.02 -0.95 -1.14 -1.40 -1.33 -1.12 Comoros -0.14 -0.3 -1.45 -1. 06 -1.04 -1.14 DRC -1. 64 -2.27 -1.41 -1.80 -1.74 -1.31 Djibouti -0.85 -0.44 -0.76 -0.76 -0.61 -0.94 Egypt -1. 04 -0.72 0.20 -0.58 -0.02 -0.21 Eritrea -1.96 -0.14 -1.05 -1.29 -0.78 -0.64 Ethiopia -1.11 -0.98 -0.96 -1.19 -1.00 -0.85 Madagascar +0.07 -0.02 -0.43 +0.10 -0.30 -0.83 Mauritius +0.94 +0.91 +0.60 +0.33 0.84 +0.33 Namibia +0.47 +0.46 +0.29 +0.45 0.22 +0.18 Rwanda -1. 09 0.92 0.56 0.42 0.90 -0.36 Seychelles -0.04 +0.84 -0.31 -1.21 -0.1,7 +0.01 Sudan -1.81 -2.08 -1.28 -1. 04 -1.59 -1.30 Swaziland -1.45 +0.23 -0.60 -0.36 -0.95 -0.95 Uganda -0.64 -1.27 -0.43 +0.07 -0.79 -0.71 Zambia -0.36 -0.16 -0.84 -0.49 -0.54 -0.74 Zimbabwe -1.48 -1.86 -1.20 -2.15 -1.53 -1.01 Source: World Bank The results presented in table 1.11 have been extracted from World Bank (2000): index on institutional quality indicators. These were computed and constructed from Kaufman Kraay and Zoida- Lobaton (1999). The World Bank: survey was conducted in 67 countries. Actual investors were surveyed. These have been refined with the inclusion of Kaufmann, Kray and Zoido - Lobation using the six aggregate indexes from numerous indicators collected from 14 different sources including; International Country Risk Guide (ICRG) Business Environment Risk Intelligence (BERI), Freedom House and others. The indicators of institutional quality as presented in table 1.11 are negative in most of COMESA countries except Mauritius and Namibia (which is no longer COMESA member) The negativity of the results indicates poor institutional quality while positivity indicat6that the institutional quality is good. Although Mauritius and Namibia are positive the positivity is very low. Madagascar scored positive on Voice and accountability (+0.07) and regulatory quality (+0.10) and scored negative on political stability (-0.02), government effectiveness (-0.43») Rule of law (-0.30) and Control of corruption (-0.83). Egypt Review of Economics and Development Studies Vol. I, No 2, December 2015 89 scored positive on government effectiveness (0.20) and negative on voice and accountability (-1.04), political stability (-0.72), regulatory quality (-0.58), rule of law (-0.02) and control of corruption (-0.21). Rwanda scored a positive on political stability (+0.92), government effectiveness (-0.56), Regulatory quality (+0.42), and rule of law (+0.90) but negative on Voice and accountability (-1.09) and control of corruption (-0.36). Seychelles has a positive on political stability (+0.84) and control of corruption (+0.01). Swaziland has a positive on Political stability (+0.23) and negative scores on Voice and accountability (- 1.45), government effectiveness (-0.60), regulatory quality (-0.36), rule of law (-0.95) and control of corruption (-0.95). Uganda has a positive on regulatory quality (+0.07) and negative scores on voice and accountability (-0.64) political stability (-1.27), government effectiveness (-0.43), rule of law (-0.79) and control of corruption (-0.71). Malawi scored positive on regulatory quality (+0.57) and negative on voice and accountability (-0.50), political stability (-0.53), government effectiveness (-0.81), rule of law (-0.29) and control of corruption (-0.83). The civil war tom country DRC scored all negative such as voice and accountability (-1.64), political stability (-2.27), government effectiveness (-1.41), regulatory quality (-1.80), rule of law (-1.74) and control of corruption (-1.31). Angola, Comoros, Djibouti, Eritrea, Ethiopia, Kenya, Sudan, Zambia and Zimbabwe have negative scores in all indicators. The nature of institutional quality in COMESA is therefore very poor. H2 There is no relationship between voice and accountability, political stability, government effectiveness, rule of law, control of corruption, regulatory quality and production of tradable goods in COMESA. Stepwise supply 'voice ac ' 'politic' 'gvt effe' 'r-of-Iaw' 'c-corrup' 'r-qualit' Table 1.12 step 1 2 constant 0.09977 43.24222 gvt-effe 0.8 2.8 t-ratio 5.6 3.23 voice ac -2.12 t-ratio -2.32 Source: Results of stepwise regression analysis R-sq = 91.27% R-sq (adj) =97.63 When stepwise regression was used voice and accountability and government effectiveness were the best in influencing production of tradable goods in COMESA. The two accounted for 91.27% of variation in tradable goods in COMESA. The best alternative was voice and accountability and rule of law with t-ratio = 4.17 and -2.00 respectively. Another alternative was rule of law and political stability with t-ratio = 3.99 and - 1.60 respectively. 90 90 Table 1.13 The regression equation was supply of tradable goods = -21.4 + 1.88 r-of- law 1.01 politic Table 1.13 Predicator Coef StDev t-ratio P Constant -21.38 24.13 -0.89 0.469 r-of-law 1.8781 0.5714 3.29 0.081 Politic -1.0104 0.5218 -1.94 0.192 Source: Results of stepwise regression analysis S = 28.56 R-sq = 94.5% R-sq (adj) = 89.0% Table 1.13 shows that R-sq = 94.5. This is very high. Rule of law and in political stability. Political stability has a role to play. It also shows that rule of law has a role to play. H2 is rejected in respect of voice and accountability, government effectiveness, rule of law and political stability and accepted in respect of control of corruption and regulatory quality. Voice and accountability, government effectiveness, rule of law and political stability have a role to play in the production of tradable goods in COMESA. Control of corruption and regulatory quality has no significant role in the production of tradable goods in COMESA. H3 There is no relationship between voice and accountability, political stability, Government effectiveness, rule of law, control of corruption, regulatory quality and the following dependant variables individually, FDI, raw material, utilities, infrastructure, capital, labor, land and entrepreneurship. Table 1.14 FDI =32.1 + 1.14 gvt-eff Table 1.14 Predicto Coef StDev t- P Constant 32.12 20.12 1.60 0.209 Gvt – eff 1.1368 0.1330 8.55 0.003 Source: Results of stepwise regression analysis S =27.25 R-sq = 96.1% R-sq (adj)=94.7% In table 1.14, government effectiveness has significant relationship with FDI judging from t -ratio of 8.55 and significant p value (0.003) government effectiveness explains 96.1 % of variations. Table 1.15 FDI = 8.6 + 1.20 voice and accountability Table 1.15 Predicto Coef StDev t- P Constant 8.60 22.73 0.38 0.730 Voice ac 1.1970 0.1423 8.41 0.004 Source: Results of stepwise regression analysis S =27.66 R-sq = 95.9% R-sq (adj)=94.6% In table 1.15 voice and accountability's t-ratio is significant (8.41) and p-value (0.004) is significant showing relationship exists between voice and accountability and FDI. Table 1.16 FDI = 24.5 + 1.18 r-of-law Table 1.16 Review of Economics and Development Studies Vol. I, No 2, December 2015 91 predictor coef StDev t-ratio p constant 24.49 24.85 0.99 0.397 r-of-Iaw 1.1845 0.1657 7.15 0.006 Source: Results of stepwise regression analysis S =32.31 R-sq = 94.5% R-sq (adj)=92.6% In table 1.16, rule of law affects FDI as evidenced by high t-ratio (7.15) and a significant p-value (0.006) relationship exists between rule of law and FDI. This is also strengthened by R 2 = (94.5%). Table 1.17 FDI = 56.6 + 1.02 politic Table 1.17 predictor coef StDev t-ratio p constant 56.62 37.13 1.152 0.225 Politic 1.0216 0.2549 4.01 0.028 S = 54.43 R-sq = 84.3% R-sq (adj)=79.0% Political stability is related to FDI. The p – value is significant and t-ratio (4.01) is also significant. FDI is affected by political stability. H3 is rejected in respect of government effectiveness and accountability, rule of law and political stability. H3 is however accepted in respect of control of corruption and regulatory quality. There is significant relationship between government effectiveness voice and accountability, rule of law, political stability and FDI. There is no significant relationship between control of corruption, regulatory quality and FDI. Table 1.18 Raw material = 4.20 +0.368 gvt-effe +0.149 R-quality Table 1.18 Predic Coef StDev t-ratio P Consta 44.200 3.043 1.38 0 Gvt-eff 0.3676 0.0146 25.04 0 r 0.1487 0.0157 9.45 0 Source: Results of stepwise regression analysis In table 1.18 both the government effectiveness and regulatory quality have significant relationship with raw material with p-values of 0.002 and 0.011 respectively. The two explain 99.8% of variations in raw material. Table 1.19 Raw material = 13.2 + 0.976 R-of-Iaw -0.535 politic Table 1.19 predictor coef StDev t-ratio p constant 13.17 12.12 1.09 0.391 92 92 r-of law 0.9765 0.2871 3.40 0.077 Politic -0.5354 0.2622 -2.04 0.178 Source: Results of stepwise regression analysis S =14.35 R-sq = 94.6% R-sq (adj)=89.2% Analysis of variance Table 1.20 Source DF SS MS F P Regression 2 7241.4 3620.7 17.59 0.054 Error 2 411.8 205.9 Total 4 7653.2 Source: Results of stepwise regression analysis The p – value (0.054) is marginal significant. Political stability and rule of law affect raw materials. Political stability has an inverse relationship with raw material, which means that political stability has a negative effect on raw material. Table 1.21 Raw Material = 17.7 + 0.416 voice and accountability Table 1.21 predictor coef StDev t-ratio p constant 17.67 15.81 1.12 0.345 Voice ac 0.41591 0.09897 4.20 0.025 Source: Results of stepwise regression analysis S = 19.25 R – sq = 85.5 R – sq(adj) = 80.6 Table 1.22 raw material = 5.5 + 0.380 voice acc + 0.139 c – corrup Table 1.22 predictor coef StDev t-ratio p constant -5.51 14.44 -0.38 0.739 Voice acc 0.37984 0.06595 5.76 0.029 C – corrup 0.13936 0.06129 2.27 0.151 Source: Results of stepwise regression analysis Review of Economics and Development Studies Vol. I, No 2, December 2015 93 S = 12.45 R – sq = 95.9% R – sq (adj) = 91.9% Analysis of variance Table 1.23 Source DF SS MS F P Regression 2 7343.2 3671.6 2369 0.041 Error 2 310.0 155.0 Total 4 7653.2 Source: Results of stepwise regression analysis Table 1.23 indicates that there is marginal significant relationship between raw material and voice accountability and control of corruption. H3 was rejected in respect of government effectiveness, regulatory quality, political stability, and rule of law, voices and accountability and control of corruption. Rule of law was accepted. There is significant relationship between effectiveness, regulatory quality, political stability, voice accountability, rule of law, control of corruption and raw material. Regressing capital on 6 predictors Table 1.24 Step 1 2 3 constant 3.8965 0.7490 29.2242 Politic 0.412 0.287 0.614 t-ratio 12.72 5.99 5.44 gvt-effe 0.140 1.046 t-ratio 2.81 3.40 voice ac -1.29 t-ratio -2.95 Source: Results of stepwise regression analysis Voice and accountability is highly correlated with other predictor variables. Political stability was highly correlated with other predictor variables. Government effective was highly correlated with other predictor variable. There was an existence of multicollinearity. Table 1.25 Capital = 29.2 – 1.29 voice & acc + 0.614 politic + 1.05 gvt – effe Table 1.25 94 94 predictor coef StDev t-ratio p constant 29.224 9.723 3.01 0.204 Voice & acc -1.2948 0.4383 -2.95 0.208 Politic 0.6140 0.1128 5.44 0.116 gvt-effe 1. 0460 0.3074 3.40 0.182 Source: Results of stepwise regression analysis S = 1.727 R – sq = 100.0% R – sq(adj) = 99.8% Analysis of variance Table 1.26 Source DF SS MS F P Regression 3 7875.8 2625.3 880.45 0.025 Error 1 3.0 3.0 Total 4 7878.8 Source: Results of stepwise regression analysis Table 1.25 shows that voice and accountability, political stability and government effectiveness explain very well capital with R 2 = 100 %. However voice and accountability has negative relationship with capital. The regression equation is capital = -2.00+0.463 voice accountability -0.0542 c-corrup Table 1.27 predictor coef StDev t-ratio p constant -2.000 9.026 -0.22 0.845 Voice&acc 0.46339 0.04123 11.24 0.008 c-corrup -0.05420 0.03831 -1.41 0.293 Source: Results of stepwise regression analysis S = 7.782 R –sq = 98.5% R – sq (adj) = 96.6% Analysis of variance Review of Economics and Development Studies Vol. I, No 2, December 2015 95 Table 1.28 Source DF SS MS F P Regression 2 7757.7 3878.8 64.05 0.015 Error 2 121.1 60.6 Total 4 7878.8 Source: Results of stepwise regression analysis Table 1.27 shows that voice and accountability and control of corruption have a lot to explain about capital. A significant relationship exists between them and capital. Control of corruption has inverse relationship with capital. The regression equation is capital = 2.47 + 0.460 r-of-law –0.0560 r-quality Table 1.29 predictor coef StDev t-ratio p constant 2.474 7.076 0.35 0.760 r-of-Iaw 0.45989 0.03389 13.57 0.0005 r-quality -0.05597 0.03459 -1.62 0.247 Source: Results of stepwise regression analysis S =6.489 R-sq = 98.9% R-sq (adj)=97.9% Analysis of variance Table 1.30 Source DF SS MS F P Regression 2 7794.6 3897.3 92.56 0.011 Error 2 84.2 42.1 Source: Results of stepwise regression analysis Table 1.29 shows that rule of law and regulatory quality explained 98.9% of the variation in capital. Regulatory quality has negative relationship with capital. H3 is rejected. There is significant relationship between voice and accountability, political stability, rule of law government effectiveness, control of corruption, regulatory quality and capital. Regressing entrepreneurship with voice and accountability, political stability, governmental effectiveness, rule of law, control of corruption, regulatory quality. 96 96 Table 1.31 predictor coef StDev t-ratio p constant -8.047 2.603 -3.09 0.091 Voice &acc 0.56023 0.01189 47.13 0.000 c-corup 0.02874 0.01105 2.60 0.121 Source: Results of stepwise regression analysis S =2.244 R-sq = 99.9% R-sq (adj) =99.8% Analysis of variance Table 1.32 Source DF SS MS F P Regression 2 12220.7 6110.4 1213.58 0.001 Error 2 10.1 5.0 Total 4 12230.8 Source: Results of stepwise regression analysis In table 1.31 voice and accountability and corruption show significant relationship with entrepreneurship accounting 99.9% of variation when the two independent variables are regressed with the dependent variable. Entrepre = 3.89 + 0.565 r-of-law Table 1.32 predictor coef StDev t-ratio p constant 3.891 4.429 0.88 0.444 r-of-Iaw 0.56482 0.02953 19.12 0.000 Source: Results of stepwise regression analysis S = 5.759 R – sq = 99.2% R – sq (adj) = 98.9% Table 1.32 indicates that there is significant relationship between entrepreneurship and rule of law this was confirmed by a very high t – ration (19.12) and p – value (0.000) was significant. Rule of law explained 99.2% of variation on entrepreneurship, when regressed with it. This would mean that in a COMESA country without rule of law entrepreneurship may be suppressed and this can also lead to exodus of entrepreneurs to other countries, which have rule of law. Review of Economics and Development Studies Vol. I, No 2, December 2015 97 Table 1.33 entrepre = 8.8 + 0.536 gvt – effe – 0.0031 r – quality Table 1.33 predictor coef StDev t-ratio p constant 8.77 10 .44 0.84 0.490 gvt -effe 0.53615 0.05041 10.64 0.009 r-quality -0.00311 0.05407 -0.06 0.959 Source: Results of stepwise regression analysis S =9.946 R-sq = 98.4% R-sq (adj)=96.8% Table 1.34 Source DF SS MS F P Regression 2 12032.9 6016.5 60.82 0.016 Error 2 197.9 98.9 Total 4 12230.8 Source: Results of stepwise regression analysis Table 1.33 indicates that there is a significant relationship between government effectiveness, regulatory quality and entrepreneurship. Regulatory quality has an inverse relationship with entrepreneurship. Entrepreneur = 9.25 + 0.399 gvt-effe + 0.141 politic Table 1.34 predictor coef StDev t-ratio p constant 9.255 4.454 2.08 0.173 gvt -effe 0.39867 0.07857 5.07 0.037 politic 0.141432 0.07538 1.87 0.202 Source: Results of stepwise regression analysis S =5.995 R-sq = 99.4% R-sq(adj) =98.8% Table 1.35 Source DF SS MS F P 98 98 Regression 2 12158.9 6079.5 169.17 0.006 Error 2 71.9 35.9 Total 4 12230.8 Source: Results of stepwise regression analysis In table 1.34, government effectiveness and political stability have significant relationship with entrepreneurship. They explain 99.4% of the variation in entrepreneurship when the two are regressed with entrepreneurship. H3 is rejected. There is a significant relationship between voice and accountability, government effectiveness, rule of law, regulatory quality, control of corruption and entrepreneurship. Regressing labor with voice and accountability, political stability, government effectiveness, rule of law, control of corruption, regulatory quality. Table 1.36 predictor coef StDev t-ratio p constant 14.255 1.343 10.61 0.060 gvt -effe 0.67266 0.04615 14.58 0.044 r-of-Iaw -0.22782 0.04755 -4.79 0.131 r-quality 0.033113 0.006364 5.20 0.121 Source: Results of stepwise regression analysis S =0.8939 R-sq = 100.0% R-sq(adj) =100.0% Table 1.37 Source DF SS MS F P Regression 3 9225.2 3075.1 3848.58 0.012 Error 1 0.8 0.8 Total 4 9226.0 Source: Results of stepwise regression analysis In table 1.36, government effectiveness, rule of law and regulatory quality have significant relationship with labor. Rule of law has negative relationship with labor, government effectiveness, rule of law and regulatory quality explain 100% of variation. This is very high. Review of Economics and Development Studies Vol. I, No 2, December 2015 99 Labor = 8.92 + 1.46 voice & acc –0.686 r-of-law –0.276 politic Table 1.38 Predictor Coef StDev t-ratio p Constant -8.916 2.447 -3.64 0.171 Voice & acc 1.4621 0.1996 7.33 0.086 r-of-law -0.6858 0.2137 -3.21 0.192 politic -0.27581 0.02515 -10.97 0.058 Source: Results of stepwise regression analysis S = 1.186 R-sq = 100.0% R-sq(adj) = 99.9% Analysis of Variance Table 1.39 Source DF SS MS F P Regression 3 9225.2 3075.1 3848.58 0.012 Error 1 0.8 0.8 Total 4 9226.0 Source: Results of stepwise regression analysis Table 1.38 indicates that voice and accountability, rule of law and political stability have significant relationship with labor. They account 100% variation in labor when regressed with it. Rule of law and political stability have negative relationship with labor. H3 is rejected in respect of government effectiveness, rule of law, regulatory quality, voice and accountability and political stability but accepted in respect of control of corruption. There is therefore significant relationship between government effectiveness and rule of law, regulatory quality, and voice and accountability political stability with labor. There is no significant relationship between control of corruption and labor. Regression utility on voice and accountability, political stability, government effectiveness, rule of law, control of corruption and regulatory quality. Utility = -2.83 + 0.436 c – corrup –0.0994 r-of-law Table 1.40 Predictor coef StDev t-ratio p Constant -2.831 1.367 -2.07 0.174 100 100 c-corrupt 0.435614 0.005842 74.57 0.000 r-of-law -0.099408 0.006269 -15.56 0.004 Source: Results of stepwise regression analysis S =1.195 R-sq = 100.0% R-sq (adj) =99.9% Table 1.41 Source DF SS MS F P Regression 2 7938.3 3969.2 2779.99 0.000 Error 2 2.9 1.4 Total 4 7941.2 Source: Results of stepwise regression analysis Control of corruption and rule of law affect the provision of utilities significantly than any other factor. Rule of law has a negative relationship with provision of utilities. This means that if there is no control of corruption the provision of utilities will be very poor. Similarly where there is no rule of law private investment in utilities may be affected negatively. Utility = 6.7 + 0.462 r-quality –0.0861 voice & acc Table 1.42 Predictor Coef StDev t-ratio p Constant 6.71 17.89 0.38 0.744 r-quality 0.46194 0.08656 5.34 0.033 Voice -0.08606 0.8503 -1.01 0.418 Source: Results of stepwise regression analysis S = 16.13 R-sq = 93.4% R-sq (adj) = 86.9% Table 1.43 Source DF SS MS F P Regression 2 7420.6 3710.3 14.25 0.066 Error 2 520.6 260.3 Total 4 7941.2 Source: Results of stepwise regression analysis Table 1.43 above p – value (0.066) is marginally significant. There is also a big difference between R 2 and adjusted R 2 showing this marginally significant relationship. Review of Economics and Development Studies Vol. I, No 2, December 2015 101 H3 is rejected in respect of control of corruption, rule of law, regulatory quality and voice and accountability. There is a significant relationship between control of corruption and rule of law, regulatory quality, voice and accountability and utility. Utility has no significant relationship with government effectiveness and political stability. Regressing infrastructure on voice and accountability, political stability, government effectiveness, rule of law, control of corruption and regulatory quality. Table 1.44 Predictor Coef StDev t-ratio p constant -6.865 4.343 -1.58 0.25 Gvt-effe 0.37337 0.02096 17.81 0.00 r-quality 0.17131 0.02248 7.62 0.01 Source: Results of stepwise regression analysis S = 4.135 R-sq = 99.6% R-sq (adj) = 99.2% Analysis of Variance Table 1.45 Source DF SS MS F P Regression 2 8272.6 4136.3 241. 87 0.004 Error 2 34.2 17.1 Total 4 8306.8 Source: Results of stepwise regression analysis Government effectiveness and regulatory quality show significant relationship with infrastructure. They affect both quality and availability of infrastructure. P-vale (0.004) and t-ratios are significant. Table 1.46 infrastr = 18.2 + 0.386 voice & acc + 0.016 c-corrup Table 1.46 predictor coef StDev t-ratio p constant -18.25 12.08 -1.51 0.270 Voice&acc 0.38592 0.05519 6.99 0.020 c-corrup 0.16584 0.05129 3.23 0.084 Source: Results of stepwise regression analysis S = 10.42 R – sq = 97.4 R – sq (adj) = 94.8% Analysis of variance 102 102 Table 1.47 Source DF SS MS F P Regression 2 8272.6 4136.3 241.87 0.004 Error 2 34.2 17.1 Total 4 8306.8 Source: Results of stepwise regression analysis Voice and accountability and control of corruption show that they contribute to infrastructure development. They explain about 97.4% of variation in infrastructure when they are regressed with it. Infrastructure = 15.4 + 0.421 r-of-law Table 1.48 predictor coef StDev t-ratio p constant 15.42 17.54 0.88 0.444 r-of-Iaw 0.4212 0.1170 3.60 0.037 Source: Results of stepwise regression analysis S = 22.81% R – sq = 81.2% R – sq(adj) = 74.9% P – value (0.037) is marginally significant. There is marginally significant relationship between rule of law and infrastructure. H3 is rejected in respect of government effectiveness, regulatory quality, voice and accountability, control of corruption and rule of law. H3 is accepted in respect of political stability. There is a significant relationship between government effectiveness, regulatory quality and accountability, control of corruption, rule of law and infrastructure. There is no significant relationship between political stability and infrastructure probably due to multicollinearity. Regressing land on voice and accountability, political stability, government effectiveness, rule of law, control of corruption and regulatory quality. Land = -47.8 + 5.72 voice & acc –0.657 politic –4.41 r-of-law Table 1.49 predictor coef StDev t-ratio p constant -47.769 8.812 -5.42 0.116 Voice & acc 5.7215 0.7186 7.96 0.080 Review of Economics and Development Studies Vol. I, No 2, December 2015 103 politic -0.65703 0.09055 -7.26 0.087 r-of-Iaw -4.4053 0.7696 -5.72 0.0110 Source: Results of stepwise regression analysis S = 4.271 R – sq = 99.9% R – sq (adj) = 99.9% Voice and accountability, political stability and rule of law explain 99.9% of the variations in land when they are regressed with it. Land = 20.0 + 1.48 government – effe + 0.178 r-quality – 0.975 r-o-law Table 1.50 predictor coef StDev t-ratio p constant 19.984 7.852 2.55 0.238 gvt-effe 1.4806 0.2698 5.49 0.115 r-quality 0.17819 0.03721 4.79 0.131 .. r-of-Iaw -0.9747 0.2780 -3.57 0.177 Source: Results of stepwise regression analysis S = 5.226 R – sq = 99.8% R – sq = 99.4% Government effectiveness, regulatory quality and rule of law explain 99.8% of variation in land. Rule of law is negatively associated with land. H3 is accepted in respect of control of corruption, but rejected in all others. There is a significant relationship between voice and accountability, political stability, rule of law, government effectiveness, regulatory quality and land. There is no significant relationship between control of corruption and land. H4 there are no differences in the views of shareholders on the influence of voice and accountability, Political stability, government effectiveness, rule of law, control of corruption, regulatory quality and production of tradable goods. Table 1.51 Analysis of variance for control of corruption One-Way analysis of variant Table 1.51 Source DF SS MS F P Regression 60 5557.56 9.29 8.97 0.000 Error 1408 1459.18 1.04 104 104 Total 1468 2016.74 Source: Results of stepwise regression analysis Individual 95% CIs for mean Based on pooled StDev Table 1.52 Level n Mean StDev Cl 24 4.292 1.083 C2 25 4.52 0.714 C3 24 4.75 0.532 C4 25 3.28 0.936 C5 24 2.75 1.894 C6 24 2.083 0.776 C7 25 4.16 0.688 C8 24 4.083 0.881 C9 25 4.64 0.569 ClO 25 3.4 0.957 C11 9 3.333 1. 000 C12 25 3.4 1.258 C13 25 3.182 1. 097 C14 25 3.6 0.816 C15 24 3.417 0.929 C16 24 3.458 1.103 C17 25 3.04 1.399 C18 25 3.56 0.821 C19 25 3.44 0.507 C20 25 3.08 0.277 C21 25 2.6 1.555 C22 24 3.458 1.414 C23 25 3.2 0.816 C24 25 3.64 0.81 C25 25 4.44 0.507 C26 25 4.52 0.51 C27 25 4.08 0.702 C28 25 3.2 0.737 C29 24 2.667 1.341 C30 25 1.56 0.961 C31 24 3.458 1.103 C32 24 2.792 0.833 C33 24 3.5 1.063 C34 24 3.25 0.737 C35 24 4.042 0.624 C36 24 3.292 1.429 C37 24 2.542 1.793 C38 25 3.16 0.987 C39 24 3.417 1.139 C40 24 3.75 0.794 C41 24 3.917 0.974 C42 24 3.833 0.565 C43 24 3.333 1.167 C44 25 3.8 0.816 C45 24 4.292 1.042 Review of Economics and Development Studies Vol. I, No 2, December 2015 105 C46 25 3.88 0.971 C47 24 2.833 0.963 C48 24 3.5 1.18 C49 24 3.458 0.588 C50 24 3.375 0.875 C51 24 3.417 0.881 C52 24 3.708 1.628 C53 24 3.125 0.947 C54 24 4.25 0.737 C55 24 3.5 0.511 C56 24 3.375 1.135 C57 23 2.348 1.434 C58 24 3.958 1.301 C59 24 4.208 1.141 C60 24 3.792 1.25 C61 25 3.92 0.759 Source: Results of stepwise regression analysis H4 is rejected in respect of control of corruption. There are differences in the views of stakeholders. Majority was in agreement. Our decision to trade and invest in a particular COMESA country is based on whether that country controls corruption. Analysis of variance for government effectiveness One-way analysis of variance Table 1.53 Source DF SS MS F P Regression 59 340.457 5.770 9.78 0.000 Error 537 317.000 0.590 Total 596 657.457 Source: Results of stepwise regression analysis INDIVIDUAL 95% CIS FOR MEAN BASED ON POOL STDEV Table 1.54 LEVEL N MEAN STDEV Cl 10 2.9 1.3703 C2 10 4.1 000 0.9944 C3 10 4.9 0.3162 C4 10 3.7 0.8233 C5 10 2.6 0.5164 C6 10 1. 9000 0.8756 C7 10 4.3 0.6749 C8 9 4.4444 0.527 106 106 C9 10 5 0 C1O 10 4.3 0.6749 C11 9 3.5556 1.236 C12 10 4.6 0.5164 C13 10 2.4 1.1738 C14 10 3.4 1.075 C15 10 4.1 0.3162 C16 10 4.4 0.5164 C17 9 4.2222 1.0929 C18 10 4.7 0.483 C19 10 4 0 C20 10 3.1 0.3162 C21 10 4.1 1.1005 C22 10 4.5 0.7071 C23 10 3.4 0.6992 C24 10 4 0 C25 10 4.8 0.4216 C26 10 4.5 0.527 C27 10 4.6 0.5164 C28 10 4.5 0.527 C29 10 4.2 0.9189 C30 10 150000 0.7071 C31 10 4.6 0.5164 C32 10 3.4 0.8433 C33 10 4.8 0.4216 C34 10 4.2 0.6325 C35 10 4 0.8165 C36 10 4.8 0.4216 C37 10 4.3 0.483 C38 10 4.4 0.8433 C39 10 3.6 1.075 C40 10 4.3 0.8233 C41 10 4.2 0.7888 C42 10 3.9 0.7379 C43 10 4.5 0.9718 C44 10 3.9 0.8756 C45 10 4.5 1.2693 C46 10 4 0.6667 C47 10 3.8 0.6325 C48 10 4.8 0.4216 C49 10 3.4 0.6992 C50 10 5 0 C51 10 3.6 0.8433 Review of Economics and Development Studies Vol. I, No 2, December 2015 107 C52 10 C53 10 3.7 0.6749 C54 10 4 1.1547 C55 10 3.9 0.7379 C56 10 4.9 0.3162 C57 10 3.6 1.3499 C58 10 2.5 1.354 C59 10 5 0 C60 10 4.5 0.9718 C61 10 5 0 Source: Results of stepwise regression analysis H4 is rejected in respect of government effectiveness. There are differences in the views of stakeholders. Overall mean was above 4. Majority was in agreement. Questions on government effectiveness 22. Government effectiveness affects foreign direct investment in COMESA countries 23. Our decision to invest and trade with a COMESA country is based on whether the government is effective. 24. The provision of raw material for producing goods is constrained by government effectiveness. 25. The availability and quality of infrastructure is affected by government effectiveness. Analysis Of Variance For Political Stability One-way analysis of variance Table 1.55 Source DF SS MS F P Regression 60 359.276 5.688 8.21 0.000 Error 485 353.750 0.729 Total 545 713.026 Source: Results of stepwise regression analysis INDIVIDUAL 95% CIS FOR MEAN BASED ON POOL STDEV Table 1.56 LEVEL N MEAN STDEV C1 9 3.3333 1.3229 C2 9 4.6667 0.7071 C3 9 4.2222 0.8333 C4 9 4.375 0.5175 C5 9 2.1111 1.0541 C6 9 1.3333 0.5 C7 9 3.6667 1.6583 108 108 C8 9 4.5556 0.527 C9 9 4.7778 0.6667 C10 9 4.4444 0.8819 C11 9 3.625 1.4079 C12 9 4.7778 0.441 C13 9 3.5556 1.424 C14 9 3.8889 1.1667 C15 9 4.5 0.5345 C16 9 4.3333 0.5 C17 9 4 1.3229 C18 9 4.3333 0.866 C19 9 4 0 C20 9 3.2222 0.441 C21 9 3.4444 1.0138 C22 9 5 0 C23 9 3.1111 0.928 C24 9 4.1111 0.7817 C25 9 4.7778 0.441 C26 9 4.4444 527 C27 9 4.8889 0.03333 C28 9 4.4444 0.527 C29 9 3.8889 1.453 C30 9 1.2222 0.441 C31 9 4.5556 0.441 C32 9 4.2222 0.9718 C33 9 4.1111 1.2693 C34 9 4.1111 0.06009 C35 9 4.6667 0.7071 C36 9 4.8889 0.3333 C37 9 4.4444 0.527 C38 9 3.6667 1 C39 9 3.8889 1.2693 C40 9 4.4444 0.7265 C41 9 4.4444 7265 C42 9 3.7778 0.6667 C43 9 4.4444 0.7265 C44 9 4.4444 0.7265 C45 9 4.5556 1.3333 C46 9 4.6667 0.7071 C47 9 3.7778 0.6667 C48 9 4.4444 0.8819 C49 9 4.7778 0.441 Review of Economics and Development Studies Vol. I, No 2, December 2015 109 C50 9 5 0 C51 9 4.5556 0.527 C52 9 1.8889 1.0541 C53 9 4.3333 0.7071 C54 9 4.2222 1.3017 C55 9 4.7778 0.441 C56 9 5 0 C57 9 4.111 1.453 C58 9 3.889 1.453 C59 9 5 0 C60 9 4.7778 0.441 C61 9 4.889 0.3333 Source: Results of stepwise regression analysis H4 is rejected in respect of political stability. There are differences in the views of stakeholders. The majority was strongly in agreement. Questions 13. Political stability affects the supply of tradable goods in COMESA. 14. Our decision to trade and invest in COMESA country is based on political stability of that country Table 1.57 Source DF SS MS F P Regression 59 315.385 5.346 5.90 0.000 Error 766 693.714 0.906 Total 825 1009.099 Source: Results of stepwise regression analysis INDIVIDUAL 95% CIs FOR MEAN BASED ON POOL STDEV Table 1.58 LEVEL N MEAN STDEV C1 14 3.8571 1.1673 C2 14 4.0006 0.8771 C3 14 4.7143 0.4688 C4 14 3.1429 0.7703 C5 14 1.7857 1.3114 C6 14 1.9286 0.73 C7 14 3.6429 0.9288 C8 14 3.8571 0.8644 110 110 C9 14 4.6429 0.7449 CIO 14 3.3571 0.4972 C11 14 C12 14 3.7857 0.6993 C13 14 2.9286 0.4746 C14 14 3.5714 0.8516 C15 14 2.8571 0.8644 C16 14 3.1429 0.663 C17 14 3 0.8771 C18 14 3.6429 0.9288 C19 14 3.5 0.6504 C20 14 3 0 C21 14 2.7143 1.1387 C22 14 2.7143 0.9139 C23 14 3.5714 0.6462 C24 14 3.4286 0.6462 C25 14 4.1429 0.663 C26 14 3.8571 0.9493 C27 14 4.1429 0.7703 C28 14 3.2143 0.8018 C29 14 2.7143 1.069 C30 14 1.3571 0.9288 C31 14 3.5 0.7071 C32 14 2.92286 0.6157 C33 14 3.5714 0.8516 C34 14 2.7143 1.069 C35 14 3.5714 0.7559 C36 14 3.7143 1.1387 C37 14 3 1.9612 C38 14 2.2857 0.4688 C39 14 3.1429 1.0995 C40 14 3.7143 0.6112 C41 14 3.2143 1.1217 C42 14 3.1429 1.0271 C43 14 3.2857 1.4373 C44 14 3.6429 0.4972 C45 14 3.3571 1.2774 C46 14 4 0.7845 C47 14 3 0.7845 C48 14 3.6429 1.0082 C49 14 2.6429 0.6333 C50 14 3.5 0.7596 C51 14 3.9286 0.8287 Review of Economics and Development Studies Vol. I, No 2, December 2015 111 C52 14 3.0714 1.2067 C53 14 2.9286 0.9972 C54 14 3.2857 0.9945 C55 14 3.1429 0.3631 C56 14 2.7857 0.8018 C57 14 2.4286 1.2225 C58 14 3.2857 1.7289 C59 14 3.7857 1.3688 C60 14 3.871 1.4064 C61 12 3.5 1.0871 Pooled StDev = 0.9516 Source: Results of stepwise regression analysis H4 is rejected in respect of regulatory quality. There are differences between the views of the stakeholders. Stakeholders responded between neutral and agreement. Questions 68. Our decision to trade and invest in a COMESA country is based on the regulatory quality of that country. 69. There are delays in receiving a license in COMESA. 70. Regulatory provisions are unclear in COMESA ANALYSIS OF VARIANCE FOR RULE OF LAW One-way analysis of variance Table 1.59 Source DF SS MS F P Regression 60 398.729 6.645 9.89 0.000 Error 539 362.256 0.672 Total 599 760.985 Source: Results of stepwise regression analysis INDIVIDUAL 95% CIs FOR MEAN BASED ON POOL STDEV Table 1.60 LEVEL N MEAN STDEV Cl 10 4.1 1.1005 C2 10 3.8 1.0328 C3 10 4.3 0.6749 C4 10 3.1 1.1972 C5 10 2.2 0.6325 C6 10 1.9 0.9944 C7 10 3.8 1.3984 112 112 C8 10 4.4 0.5164 C9 10 5 0 CIO 10 4.2 0.6325 C11 9 2.7778 1.3017 C12 10 4.8 0.4216 C13 2 4.5 0.7071 C14 10 3.7 1.0593 C15 10 4.1 0.5676 C16 10 4.3 0.483 C17 10 3.7 1.7029 C18 10 4.7 0.483 C19 10 4 0 C20 9 3 0 C21 10 3.2 1.3166 C22 10 4.7 0.6749 C23 10 3.4 0.8433 C24 10 4.4 0.5164 C25 10 5 0 C26 10 4.5 0.527 C27 10 4.5 0.527 C28 10 4.7 0.483 C29 10 4.1 0.5676 C30 10 1.2 0.4216 C31 10 4.8 0.4216 C32 10 3.6 1.075 C33 10 4.8 0.4216 C34 10 3.6 0.9487 C35 10 4.8 0.527 C36 10 3.3 0.7071 C37 10 4.7 0.483 C38 10 4.1 0.8756 C39 10 4.1 0.8756 C40 10 4.7 0.483 C41 10 4.2 0.9189 C42 10 3.6 0.8433 C43 10 4.4 0.6992 C44 10 4.6 0.5164 C45 10 4.7 0.483 C46 10 4.7 0.483 C47 10 3.8 0.4216 C48 10 4.4 1.2649 C49 10 3.5 0.7071 C50 10 5 0 Review of Economics and Development Studies Vol. I, No 2, December 2015 113 C51 10 3.7 1.2517 C52 10 3.3 1.7029 C53 10 3.9 0.8756 C54 10 4.6 0.5164 C55 10 4.2 0.4216 C56 10 4.6 0.5164 C57 10 3.3 0.9487 C58 10 1.9 1.4491 C59 10 5 0 C60 10 3.9 1.3703 C61 10 5 0 Pooled StDev = 0.8198 Source: Results of stepwise regression analysis H4 is rejected in respect of rule of law. There are differences in the view of stakeholders. Their views were between agreements and strongly in agreement Questions 32. Our decisions to trade and invest in a COMESA country are based on whether that particular country has a rule of law to protect property and agreements. 33. Foreign direct investment is affected by rule of law. ANALYSIS OF VARIANCE FOR VOICE AND ACCOUNT ABILITY One-way analysis of variance Table 1.61 Source DF SS MS F P Regression 60 332.198 5.537 5.73 0.000 Error 603 582.164 0.965 Total 663 914.361 INDIVIDUAL 95% CIs FOR MEAN BASED ON POOL STDEV Table 1.62 LEVEL N MEAN SIDEV Cl 11 3.6364 1.2863 C2 11 4.2727 0.9045 C3 11 4.5455 0.6876 C4 10 4 0.9428 C5 11 1.2727 0.4671 C6 10 1.5 1.0801 C7 11 4.3636 1.0269 114 114 C8 11 4.5455 0.5222 C9 11 5 0 ClO 10 4 0.8165 C11 10 4 0.8165 C12 11 4 0.6325 C13 11 3.1818 1.4013 C14 11 3.9091 0.8312 C15 10 4.4 0.5164 C16 11 4.1818 0.7508 C17 11 3.3636 1.2863 C18 11 4.4545 0.5222 C19 11 2.7273 1.0091 C20 11 3.3636 0.5045 C21 10 3.9 1.1005 C22 11 4.6364 0.6742 C23 11 3.8182 0.603 C24 11 4 0.7746 C25 11 4.2727 0.6467 C26 11 3.9091 0.8312 C27 11 4.5455 0.5222 C28 11 3.9091 0.5394 C29 11 4.0909 0.9439 C30 11 2.7273 1.7373 C31 11 3.6364 1.5015 C32 11 4 1.1832 C33 11 4.2727 0.9045 C34 11 4.3636 0.5045 C35 11 4.0909 0.6742 C36 11 4.6364 1.1362 C37 11 4.0909 0.5045 C38 11 4.6364 1.2721 C39 11 3.7273 1.4206 C40 11 3.7273 0.6742 C41 11 4.0909 1.1362 C42 11 2.5455 1.2136 C43 11 2.9091 0.9439 C44 11 4.3636 0.5045 C45 11 3.4545 1.0357 C46 11 4.2727 1.2721 C47 11 3.8182 0.603 C48 11 3.9091 1.5783 C49 11 3.9091 0.7006 C50 11 3.3636 1.4334 Review of Economics and Development Studies Vol. I, No 2, December 2015 115 #C51 10 4 0.8165 C52 11 2.4545 1.3685 C53 11 4 0.7746 C54 11 3.6364 1.0269 C55 11 4 1. 0000 C56 11 4.4545 0.5222 C57 11 4.0909 1.6404 C58 11 3.5455 1.5076 C59 11 5 0 C60 11 4.0909 1.221 C61 11 4.6364 0.9244 Pooled StDev = 0.9826 Source: Results of stepwise regression analysis H4 is rejected in respect of voice and accountability. There are differences between the views of stakeholders. The majority was in agreement. Questions 2. Voice and accountability is important in increasing supply of tradable goods in COMESA 3. Our decision to invest in COMESA is largely based on voice and accountability of a particular COMESA country. 5. Foreign direct investment is very sensitive to the issue of voice and accountability of a particular country. Views provided by respondents In an additional open question stakeholders were asked in their opinion what was needed to increase supply of tradable goods in COMESA. The following were their responses. 1. Favorable macroeconomics environment and curtailment of corruption. 2. Political and economic stability, governments driven economics. 3. Raw materials, skills and capital. 4. Availability of raw material, skilled manpower coupled with working capital supply at moderate rate. 5. Honesty good business practice. 6. Political stability, zero corruption, free trade and low taxes. 7. Removal of trade barriers and unnecessary bureaucracy. 8. Loan capital from World Bank. 9. Very clever people. 10. Political unity. 11. Enterprises. 12. Entrepreneurship. 13. Skilled manpower. 14. Capital. 15. Affordable tariffs 16. Free trade zone. 17. Infrastructure. 18. Capital 19. Capital and raw material 20. Rule of law. 21. Infrastructure and transparency 116 116 22. Maximum utilization of available resources including land 23. Stable political environment 24. Protection and tariffs. 25. Raw material and infrastructure 26. Free Trade (barriers to entry and political stability) 27. Capital formation 28. Favorable trade conditions 29. Removal of all trade barriers 8. Conclusions and Recommendations The results are indicative of perception of investors and others. The quality of institution indicators index is applicable to all COMESA countries show poor performance by individual member states. Capital, entrepreneurship and foreign direct investment are the major determinants of production of tradable goods in COMESA. Institutional quality in COMESA countries is very poor. Except Mauritius and Namibia (now no longer a member) the rest of COMESA member states have poor institutional quality. This affects their ability to attract foreign investment hence production of tradable goods. Voice and accountability, government effectiveness, rule of law and political stability play a very important role in increasing production of tradable goods in COMESA. Foreign direct investment is affected by voice and accountability, rule of law and political stability than any other factors. Availability of raw material is affected by government effectiveness, regulatory quality, political stability, voice and accountability and control of corruption. 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