Doctoral Degrees (Business Management)

Permanent URI for this collection

https://scholar.sun.ac.za/handle/10019.1/696

Browse

Now showing 1 - 5 of 41

The socioeconomic impacts of public and private investments in infrastructure development in Burkina Faso
(Stellenbosch : Stellenbosch University, 2023-12) Ouedraogo, Yacouba; Kibuuka, Paul; Adjasi, Charles; Stellenbosch University. Faculty of Economic and Management Sciences. Dept of Business Management.
ENGLISH SUMMARY: Under Burkina Faso’s National Plan for Economic and Social Development (PNDES), a first phase of an ambitious programme for infrastructure development was adopted for 2016-2020. PNDES acknowledges the critical role that energy, transport and telecommunication infrastructure development will play in transforming the productive base of Burkina Faso’s economy. However, in recent years, there have been repeated calls from the public and Parliament for the Government to justify the massive investments in infrastructure envisioned by the PNDES. This research informs policymakers in Burkina Faso about the extent to which an increase in investment in infrastructure would impact Burkina Faso’s economy and proposes potential priority policy changes. The study quantified the impact of public and private investment in infrastructure in Burkina Faso on sovereign macro and microeconomic and socioeconomic indicators. Furthermore, the research assessed the funding sources (debt, tax and Official development assistance (ODA)) with the highest developmental return for transport, energy and telecommunication infrastructure. The research drew on Burkina Faso’s social accounting matrix (SAM) for 2017 to develop a dynamic Computable General Equilibrium (CGE) model based on the International Food Policy Research Institute (IFPRI) standard model. Three policy simulations were performed to assess the impact of a 5% increased investment in infrastructure on economic growth in Burkina Faso. These simulations considered three financing sources, namely debt, tax and ODA. A benchmark equilibrium, which served as a baseline, was established in the first instance. The impact of the policy simulation on economic variables was then measured and compared against the baseline. Performing a simulation consisted of introducing a policy shock. In this study, the policy shock was about increased investment in infrastructure. To simulate an increase in investment, this study drew on Burkina Faso's fiscal and capital expenditure budgets to assume a 5% increase in investment to reflect the limited resources at play in Burkina Faso as well as the increasing national security budget that has become the major budget expenditure of the country over the last five years. In general, most CGE simulations would consider a 100% increase in investment in infrastructure. However, choosing any figure representing an increase would be relevant in the simulations. However, given the budgetary limitations in Burkina Faso, this study has considered an average increase of 5% in infrastructure spending. Overall, the research findings showed that increased investment in infrastructure would promote growth in Burkina Faso. As economic theory predicted and was evidenced by a wide range of empirical studies, infrastructure is a key determinant of economic growth in developing countries such as Burkina Faso. At the macroeconomic level, real gross domestic product (GDP) per capita for transport infrastructure increased, regardless of the funding source. Real GDP per capita increased by 0.64% for transport infrastructure financed through debt. It rose by 0.41% for transport infrastructure financed via tax and 1.29% for transport infrastructure funded through ODA. Imports increased irrespective of the funding source. Imports increased by 0.90% for debt-financed transport infrastructure, 0.42% for transport infrastructure financed via tax and 1.81% for transport infrastructure funded through ODA. Exports also rose, except for transport infrastructure financed through ODA. Exports rose by 0.40% and 0.78%, respectively, following an increase in investment in transport funded by debt and tax respectively. It fell by 0.28% against the baseline for transport infrastructure funded through ODA. Burkina Faso’s consumer purchasing power fell as Consumer Price Index (CPI) increased, irrespective of the funding source. CPI went up by 0.63% for increased investment in transport through debt, 0.12% for tax financing, and 0.50% for ODA financing. The balance of budget deficit further increased sharply by 13.89%.in the scenario of debt financing. However, it remained at the baseline level in the tax and ODA financing scenario of an increase in investment in transport infrastructure. Burkina Faso’s current account fell, irrespective of the infrastructure sector. The current account declined by 7.50% following increased investment in transport via debt. It also fell by 7.20% in the tax or ODA-financed scenarios. On the microeconomic side, primary, secondary, and tertiary sector production increased regardless of the funding source. The primary sector’s production rose by 0.24%, 0.11% and 1.43% for debt, tax, and ODA financing, respectively, with the latter recording the highest percentage change. Production of the secondary sector also rose. It grew by 0.38% for debt financing of transport infrastructure, 0.18% for tax-financed transport infrastructure and 1.39% for ODA financing. Similarly, the output of the tertiary sector also increased. It rose by 0.92%, 0.98% and 1.79%, respectively, for debt, tax, and ODA financing following an increase in investment in transport infrastructure. However, factor production prices generally rose except for non-agricultural labour. Agriculture labour costs rose by 0.05% for increased investment in transport infrastructure through debt. It also increased by 0.07% in the scenario of tax-financed transport infrastructure. ODA financing increased by 0.44% of the labour cost in the agricultural sector. The cost of labour outside the agricultural sector marginally fell. It went down by 0.01% if an increase in investment in transport was financed through debt. The costs decreased by 0.02% in the scenario of debt financing and by 0.27% if the increase was financed through ODA. Family labour costs also increased marginally by 0.05%, 0.07% and 0.44%, respectively, for debt, tax and ODA-financed increases in transport infrastructure. Capital costs rose by 0.18% in the case of an increase in transport infrastructure financed via debt and tax. It went up by 0.27% if the increase in transport investment was financed via ODA. Income from factor production increased irrespective of the funding source, except for labour outside the agricultural sector. Income from agriculture labour increased by 0.19%, 0.21% and 0.57%, respectively, in the scenario of an increase in investment financed through debt, tax and ODA. Family labour income also increased by 0.19% if the increase in investment was debt-financed. It rose by 0.21% in the case of debt and 0.57% in the ODA financing scenario. Capital income increased regardless of the funding source. It increased by 0.33% for debt- and tax-financed scenarios. It rose by 0.40% if the increase in transport investment was financed through ODA. Concerning socioeconomic variables, household income and consumption levels increased for poor and non-poor households, irrespective of the funding source. Household income for poor households increased by 0.61%, 0.42% and 1.26%, respectively, for debt-financed, tax-financed, and ODA-financed scenarios. Concerning non-poor households, their income would rise by 0.49% in the case of an increase in investment in transport infrastructure financed through debt. Their revenue increased by 0.35% for an increased investment financed via tax, which increased by 1.08% in the ODA-financed scenario. Poor households’ consumption levels would increase by 0.33% if an increase in transport infrastructure were financed by debt. It increased by 0.49% in the scenario of tax financing and by 1.47% for ODA financing. In the debt, tax and ODA financing scenarios, consumption levels for non-poor households rose by 0.34%, 0.39% and 1.23%, respectively. The unemployment rate reduced marginally in the case of an ODA-financed increase in transport infrastructure, while it grew by the same measure in the scenario of debt or tax financing. The unemployment rate was reduced marginally by 0.1 percentage points in the case of an ODA-financed increase in transport investment, while it grew by 0.1 percentage points in the debt or tax financing scenario. The findings of this study showed that ODA financing of the transport sector tends to be more beneficial to the economy of Burkina Faso as it would generate the highest increase in real GDP per capita (1.29%) compared to debt (0.64%) and tax (0.41%). For telecommunication infrastructure at the macroeconomic level, real GDP per capita rose above the baseline regardless of the funding source. Real GDP per capita rose as imports, sectoral output production, capital income, household income, and consumption levels increased. It increased above the baseline by 2.3%, 1.8% and 0.4%, respectively, for the telecommunications infrastructure financed through debt, tax, and ODA. CPI increased marginally by 0.1% following increased investment in telecommunication infrastructure financed through debt. Funding an increase in investment in telecommunication infrastructure via tax or ODA had no impact on CPI. Imports, similar to real GDP per capita, also rose, regardless of the funding source. Imports increased by 3.9%, 2.9%, and 0.2%, respectively, for debt, tax, and ODA financing, following increased investment in the telecommunications infrastructure. Exports, with the exception of tax financing, increased following increased investment in telecommunications. Exports rose by 0.20% and 0.30%, respectively, due to increased investment in telecommunication financed by debt and ODA. It fell by 0.5% against the baseline for telecommunication infrastructure financed through tax. The budget balance deficit increased sharply in the scenario of debt financing. Increased investment in the telecommunications infrastructure via debt also negatively impacted Burkina Faso’s budget balance, which increased by 13.89%. However, it did not have any impact on the budget balance if investment was channelled through tax and ODA. The current account declined by 8.49% in the scenario of a debt-financed increase in the telecommunications infrastructure. It fell by 7.25% for a tax-financed increase and by just 0.07% in the ODA-financed scenario of an increase in the telecommunications infrastructure. On the microeconomic side, the primary sector’s production rose by 2.5% for debt financing and 0.1% for tax and ODA financing. Similar to the primary industry, production of the secondary sector also rose nearly by the same levels. It grew by 2.5% for debt financing and 0.1% for tax and ODA financing. The output of the tertiary sector also increased. It rose by 2.5% for debt financing and 0.40% for tax and ODA financing after increased investment in the telecommunications infrastructure. Factor production prices collectively went up. Cost rose marginally by 0.2% for labour in the agricultural sector following an increase in infrastructure investment through debt and tax. In comparison, ODA financing resulted in a 0.6% increase in the cost of labour in the agricultural sector. Labour costs outside the agricultural sector marginally increased. It rose by 0.3% if an increase in investment in telecommunication was financed through debt and tax. Prices here remained stable in the case of increased investment financed through ODA. Family labour costs also rose marginally by 0.2% for debt and a tax-financed increase in the telecommunications infrastructure. Costs rose by 0.6% for ODA financing. Capital costs rose by 0.2% in the case of an increase in the telecommunications infrastructure financed via debt and tax. Costs rose by 0.3% if the increase in telecommunications investment was financed via ODA. Income from factor production increased regardless of the funding source. In the increased investment financed through debt, tax, and ODA scenario, revenue from agricultural labour increased by 0.19%, 0.21% and 0.57%, respectively. For debt and tax financing, labour income outside the agricultural sector rose by 0.3%. It did not change in the increased investment in telecommunications financed through the ODA scenario. Family labour income also rose by 0.19% if the increase in investment was debt-financed. It rose by 0.21% in the case of debt and 0.57% in the ODA financing scenario. Similarly, capital income increased by 0.33% for debt and tax-financed scenarios. It rose by 0.40% if the increased telecommunications investment was financed through ODA. Concerning socioeconomic variables, household income and consumption levels for the poor and non-poor rose, irrespective of the funding source. Income for poor households rose by 2.2%, 1.7%, and 0.4% for the debt-financed, tax-financed and ODA-financed scenarios, respectively. Non-poor household income also increased by 1.9%, 2.0%, and 0.4%, respectively, for debt, tax and ODA financing. Poor households’ consumption levels rose by 1.9% in the scenario of increased investment in telecommunication financed through debt. It increased by 2% and 0.4% for tax and ODA financing, respectively. Consumption levels for non-poor households rose by 1.8% for debt and tax financing, while it increased by 0.4% for ODA financing. The unemployment rate, following an increase in investment in telecommunication, marginally increased for all funding sources. It increased by 0.28% for ODA and tax financing. It rose by just 0.02% in the scenario of ODA financing. The results of this study also showed that in Burkina Faso, debt financing of increased investment in telecommunication infrastructure tends to be more beneficial to Burkina Faso’s economy as it would generate the highest increase in real GDP per capita (2.28%) compared to tax (1.78%) and ODA (0.39%). Concerning electricity-water-gas infrastructure, on the macroeconomic side, real GDP per capita increased, regardless of the funding source. It rose by 1.94%, 1.42%, and 0.32% for debt, tax and ODA financing for increased investment in the electricity, water, and gas infrastructure. CPI increased marginally by 0.01% for all funding sources following increased investment in the electricity, water, and gas infrastructure. Imports rose following an increase in investment in electricity-water-gas infrastructure regardless of the funding source. Imports increased above the baseline by 3.43%, 2.44%, and 0.21% for debt, tax, and ODA financing, respectively. Exports also increased following an increase in investment in electricity-water-gas, except for tax financing. It fell against the baseline for electricity-water-gas infrastructure financed through tax. Exports rose by 0.16% and 0.26% after an increase in investment in electricity, water, and gas financed by debt and ODA, respectively. However, it fell by 0.51% against the baseline for an electricity, water, and gas infrastructure funded via tax. The balance of the budget deficit increased further for debt financing of increased investment, while it did not change in the scenario of tax and ODA financing. It increased by 18.81%, meaning a significant negative impact on Burkina Faso’s budget balance. However, it does not have any impact on the budget balance if investment is channelled through tax and ODA. The current account fell for debt and tax financing while it slightly decreased for ODA financing. It declined by 7.68%, 6.37%, and 0.12%, respectively, for debt, tax and ODA-financed electricity, water, and gas infrastructure increase. At the microeconomic level, primary sector production increased regardless of the funding source. The production of the primary sector rose by 2.14%, 1.60% and 0.23% for debt, tax and ODA financing, respectively. Production of the secondary sector also rose. It grew by 2.17% for debt-financed electricity, water, and gas infrastructure, 1.70% for tax-financed electricity, water, and gas infrastructure and 0.17% for ODA financing. Similarly, the output of the tertiary sector also increased. It rose by 2.14%, 1.60%, and 0.23% for debt, tax and ODA financing, respectively, for increased investment in the electricity, water, and gas infrastructure. Costs rose for labour in the agricultural sector. Agricultural labour costs rose by 2.14% for increased infrastructure investment through debt. It also increased by 1.75% in the tax-financed scenario. ODA financing resulted in an increase of 0.12% in the agricultural sector’s labour cost. The cost of labour outside the agricultural sector marginally fell. It went down by 0.02% if an increase in electricity, water, and gas investment was financed through debt. The cost fell by 1.04% in the scenario of tax financing and by 0.28% if the increase was financed through ODA. Family labour costs also increased marginally by 2.17%, 1.70%, and 0.17%, respectively, for debt, tax, and ODA-financed increases in the electricity, water, and gas infrastructure. Capital costs rose by 2.14% in the case of an increase in the electricity, water, and gas infrastructure financed via debt. It also increased by 0.60% and 0.23%, respectively, for tax and ODA-financed increased investment in the electricity, water, and gas infrastructure. Income from factor production increased irrespective of the funding source, except for labour outside the agricultural sector, which fell by 0.21 in the scenario of ODA financing. Income from agricultural labour increased by 0.09%, 0.11% and 0.47%, respectively, in increased investment financed through debt, tax and ODA scenarios. Family labour income also increased by 0.09% if the increase in investment was debt-financed. It rose by 0.11% in the case of debt and 0.47% in the ODA financing scenario. Similarly, capital income increased by 0.16% for debt and tax-financed scenarios. It rose by 0.23% if the increase in electricity, water, and gas investment was financed through ODA. Regarding socioeconomic indicators, household income increased for poor and non-poor households, regardless of the funding source. Household income increased for poor households by 1.81%, 1.36%, and 0.32% for the debt-financed, tax-financed and ODA-financed scenarios, respectively. Non-poor household income rose by 1.57% in the scenario of increased investment in the electricity, water, and gas infrastructure financed through debt. Their revenue increased by 1.20% and 0.28% for the tax and ODA-financed scenarios, respectively. Consumption levels for the poor and non-poor households also rose in all funding scenarios. Poor households’ consumption levels would increase by 1.33% if an increase in the electricity, water, and gas infrastructure were financed by debt. It increased by 1.59% in the tax financing scenario and by 0.36% in the ODA financing scenario. Consumption levels for non-poor households rose by 1.45%, 1.36%, and 0.31% in the debt financing, tax, and ODA financing scenarios, respectively. The unemployment rate reduced marginally in the case of an ODA-financed increase in electricity-water-gas investment while it grew by the same amount in the scenario of debt or tax financing. Its rate reduced marginally by 0.17 percentage points in the case of an ODA-financed increase in electricity, water, and gas investment, while it grew by 0.07 percentage points in the debt or tax financing scenarios. Similar to the telecommunication sector, this study’s findings showed that for energy infrastructure, debt financing of an increase in investment in electricity, water and gas infrastructure tends to be more beneficial to Burkina Faso’s economy as it would generate the highest growth in real GDP per capita (1.94%) compared to tax (1.42%) and ODA (0.32%). Investment in infrastructure may have a positive or a negative impact on economic growth. Regardless of the financing source, investment in transport, telecommunications and water, electricity, and gas infrastructures positively affected real GDP per capita, imports, household income, and household consumption levels in Burkina Faso. Furthermore, an additional economic indicator, employment level, was positively affected by increased investment in telecommunications infrastructure through ODA. Tax financing of transport and debt financing positively affected the country’s exports. Similarly, ODA financing of telecommunication, water, electricity, and gas infrastructure also positively impacted Burkina Faso’s exports. Conversely, debt financing for transport had a negative impact on CPI and employment. Further, it also negatively affected exports for telecommunications and the water-electricity-gas infrastructure. Financing the transport infrastructure by ODA resulted in a negative impact on Burkina Faso’s exports. Burkina Faso’s budget balance further increased in the scenario of debt financing while the current account decreased, irrespective of the funding source and the infrastructure sector. This research provides evidence in support of the PNDES in which investment in infrastructure is a key strategic pillar. At the same time, this study calls on policymakers to carefully consider the funding source as it may negatively impact some economic variables. Moreover, this research urges policymakers to consider accounting for the wider value and benefits of infrastructure in Burkina Faso’s infrastructure investment strategic planning.
Total effects of bank credit on economic growth in Mauritius : a time-varying coefficient estimation of the quantity theory of disaggregated credit
(Stellenbosch : Stellenbosch University, 2022-12) Achameesing, Amit; Aziakpono, Meshach Jesse; Stellenbosch University. Faculty of Economic and Management Sciences. Dept of Business Management.
ENGLISH SUMMARY: The empirical literature has found mixed evidence of the effects of finance on growth. A comprehensive review by Levine (2005) found that more finance is good for the economy, and countries which have a smaller share of private sector credit to GDP should attempt to increase it to promote investment and growth. However, a part of the literature has found a non-linear relationship between ‘financial deepening’ and economic growth, suggesting that too much finance could be harmful for growth (see Deidda and Fattouh, 2002; Huang and Lin, 2009; Arcand et al., 2012, 2015; Cecchetti and Kharroubi, 2012, 2013; Law and Singh, 2014). To the best of our knowledge, none of the studies investigated the reasons for the nonlinear effects of finance on growth. Empirical studies on finance and growth in Mauritius have found a positive link between different quantitative measures of financial development (FD) such as the ratio of liquid liabilities of banks to GDP and private sector credit to GDP on investment or economic growth (see Jouan, 2005; Jankee, 2006; Seetanah, 2008; Nowbutsing et al., 2010; Muyambiri and Odhiambo, 2018). Since the empirical literature has shown that the effects of private sector credit on economic growth have been declining in many parts of the world (See Arcand et al. (2012); Cechetti et al. (2012)), this thesis investigates if the positive effects of private sector credit on economic growth still hold in Mauritius. This investigation is particularly salient as during the past three decades there has been an increase in private sector credit but economic growth has remained relatively subdued, raising questions about the efficiency of aggregate credit in promoting productive investment in the country. We start this research by performing a fixed coefficient estimation of the effects of two measures of FD: Private Sector Credit per capita1 (PSC) and Commercial Bank Credit per capita (CBC) on Real GDP per capita (RGDP). The results of the ARDL model show strong evidence of negative long-run effects of PSC or CBC on RGDP, but the effects of the former on the latter remain positive in the short-run. These results raise serious questions about the effects of aggregate credit on economic growth in the country in the long-run. We argue that the relationship between PSC or CBC and RGDP in Mauritius might have changed over time due to different economic policies adopted and structural economic changes in the country since independence in 1968, and therefore the application of a timevarying coefficient (TVC) model would be more appropriate for the analyses. In contrast to existing fixed and variable coefficient models, which ignore the indirect effects of the regressor on the dependent variable, the TVC model of Swamy and Von Zur Muehlen (2020) measure the total effects2 of PSC or CBC on RGDP from 1970 to 2019. Furthermore, as opposed to the existing empirical literature on the indirect effects of finance and growth (Sarwar et al., 2020), the TVC model uses coefficient drivers to measure more precisely the partial indirect effects3 through which finance can affect growth. The results show that the direct effects of PSC or CBC on economic growth are positive while the indirect effects measured by Private Investment (PI), Gross Fixed Capital Formation (GFCF), Private Consumption (PC) and IMPORTS are all negative which partly explains the declining effects of finance on growth in Mauritius. It is important to highlight the differences between the ARDL and TVC results. The results for the ARDL model show significant positive direct effects of PSC or CBC on RGDP in the short-run and significant negative direct effects of PSC or CBC on RGDP in the long-run. On the other hand, the results for the TVC model show that the total effects, including the direct effects of PSC or CBC on RGDP for the entire period, are always positive and in fact it is the indirect effects of PSC or CBC on RGDP which are negative. The indirect effects are significantly measured by the negative coefficient of the coefficient drivers, PI, GFCF, PC and IMPORTS which partially explains the decline in the positive total effects of private sector credit and commercial bank credit on economic growth in Mauritius over time. The ARDL model ignores the indirect effects and hence wrongly arrives at the conclusion that it is PSC or CBC which has negative direct effects on economic growth in the long-run. The TVC results suggest that banks in Mauritius have been allocating credit to sectors which are less productive during more recent times. Therefore, we introduce the Quantity Theory of Disaggregated Credit (QTDC) in Africa and provide a new theoretical framework to show the explicit link between bank credit and nominal GDP (NGDP). In particular, we use QTDC to disaggregate commercial bank credit into bank credit for GDP transactions and bank credit for non-GDP transactions, and then measure the total effects of the former on NGDP in Mauritius. The empirical results show that bank credit for GDP transactions namely proxy 104 has stronger total effects on NGDP than proxy 115 throughout the period 1970 to 2019. This result suggests that bank credit to the construction sector has had major non-GDP effects. The time path for the total effects of proxy 10 on NGDP shows that during the economic miracle period of the 1980s bank credit for GDP transactions played a significant role in stimulating GDP. However, from the late 1980s the total effects of bank credit for GDP transactions on NGDP start to decline as commercial banks gradually shifted their allocation of credit to non-GDP sectors, notably to finance and construction. Consequently, the total effects of proxy 10 on NGDP plummet and reach its minimum point in 20136. The stronger deceleration in the time path of the total effects of proxy 11 on NGDP in comparison to the time path of proxy 10 on NGDP shows that as banks increased their allocation of credit to the construction sector, the link between bank credit and NGDP weakened considerably. The indirect effects of proxy 10 and 11 on NGDP are measured by the coefficient drivers – Private Investment (PI), Gross Fixed Capital Formation (GFCF), Private Consumption (PC) and IMPORTS are all significant and negative, which partially explains the decline in NGDP during recent decades. In the final part of the empirical study, we use the proposition of Turner (2014, p. 28) and disaggregate Gross Fixed Capital Formation (GFCF) into three components: Residential and Commercial Real Estate Investment (RCREI), Investment in Machines (IM) and Investment in Infrastructure (II) to have a mesoscopic view of the indirect effects of bank credit for GDP transactions on NGDP and RGDP. We use the two disaggregated measures of bank credits for GDP transactions namely proxy 10 and proxy 11 as financing variables to measure their total effects on NGDP and RGDP. The findings show that irrespective of whether we use aggregate or disaggregate measures of investment, the total effects of proxy 10 on NGDP or RGDP outperforms the total effects of proxy 11 on NGDP or RGDP. The indirect effects of proxy 10 and proxy 11 measured by II, IM and RCREI remain always negative, which corroborates the previous findings that the uses of credit are important for strong economic performance. The high growth rates of the country during 1970s and 1980s is accurately depicted by the time path of the total effects of proxy 10 on RGDP which shows strong total effects of bank credit on economic growth through IM from 1970 to 1979 and from 1984 to 1992. From 1984 to 1992, the total effects of proxy 10 on RGDP via IM have had stronger total effects on economic growth relative to the total effects of proxy 11 on RGDP via RCREI. The period of high growth rates coincides with the imposition of the credit ceiling on non-priority sectors from 1973 to 1993. We argue that the close monitoring of the sectoral composition of bank credit and the introduction of the credit ceiling in 1973 has been an important element in explaining the high economic growth of the country in the 1970s and 1980s. However, after the removal of all forms of credit controls in July 1993, the time path of the total effects of proxy 10 and proxy 11 on RGDP experienced a sharp decline due to the gradual shift in the composition of bank credit to non-GDP transactions. In a nutshell, this study has brought to light five major findings. First, the fixed coefficient estimation of the effects of bank credit on economic growth has shown that the effects are significantly positive in the short-run but negative in the long-run. Second, the time-varying coefficient estimation shows that the effects of bank credit on economic growth are not constant but vary over time, and are non-linear which strongly challenges the findings of previous empirical studies that have used fixed coefficient models and hence assumed that the relationship between finance and growth is constant. More specifically, we find that the effect of bank credit for GDP transactions vary over time and are non-linear. This result also contrasts the findings of previous empirical studies on QTDC that have used fixed coefficient models and assumed that the positive effects of increases in bank credit for GDP transactions on NGDP growth are constant. Third, bank credit has had stronger effects on economic growth from 1970 to about 1990 but then the effects weaken due to increasing bank credit for non-GDP transactions. Fourth, proxy 10 has had stronger effects on GDP in comparison to proxy 11 because the latter includes bank credit to construction whose non-GDP effects weaken the relationship between bank credit and GDP. Fifth, the indirect effects of proxy 10 on economic growth as measured by IM give a strong channel through which bank credit can stimulate economic growth. We believe that it is possible to replicate the time path of the best model that shows sustained and strong positive total effects of proxy 10 on RGDP in Mauritius from 1973 to 1979 and notably from 1984 to 1992. Thus, we propose credit policy measures that would increase bank credit for GDP transactions and encourage investment to IM which today could include investment in agri-tech, high-tech manufacturing, renewable energy technology, information and communications technology devices and the operations of the blue economy amongst others. However, the reintroduction of a productive system of credit allocation is a necessary but not sufficient condition to reignite economic growth in the country. It should also be accompanied by an industrial policy like in 1980s which includes the production of higher value added goods mainly for the exports market.
A FOURTH INDUSTRIAL REVOLUTION INTEGRATED INTELLIGENCE TAXONOMY AND MEASUREMENT FRAMEWORK FOR TOP MANAGEMENT
(2022-12) Oosthuizen, Jacobus Hendrik; Ungerer, Marius; Volschenk, Jako
Antecedents to consumer willingness to share information with retailers
(2022-12) Koorts, Christie; Gerber, Charlene; Terblanche-Smith, Marlize
An assessment of urban land administration in Ethiopia : evidence from Mekelle City
(Stellenbosch : Stellenbosch University, 2022-12) Gebrihet, Hafte Gebreselassie; Pillay, Pregala; Stellenbosch University. Faculty of Economic and Management Sciences. Dept of Business Management.
ENGLISH SUMMARY: There has been a growing scholarly interest within the land administration community to realize fit-for-purpose land administration that meets people's needs across society. While global research into land administration is on the rise, little attention has been paid to the Ethiopia's context. The literature gap results from the problem of available data to examine questions relating to good governance, land market, and land policies. This study offers evidence from Ethiopia by providing an analysis of triangulated data while focusing on good governance, land market, and land policies. The study is based on a pragmatic research design that used surveys, interviews, secondary data, and document reviews to gather evidence on urban land administration in Mekelle City, Ethiopia. The study's first objective is generating a good governance index that fits the context of urban land administration in the Mekelle City context. The findings demonstrate that accountability, transparency, the rule of law, and public participation matter the most in urban land administration. The good governance index generated from this study is included in the survey to analyze the determinants of customer satisfaction in urban land governance. The findings of the study demonstrate that urban land administration in Mekelle City is characterized by weak governance. The regression analysis results reveal that undermining the rule of law, accountability, public participation, transparency, and rampant corruption negatively affect customer satisfaction. In addition, the study examines the determinants of the urban land lease market. As a result, this study found that plots specified for residential housing, plot grade, payment period, monthly income and plot size increases the markup price by 160.34; 5.56; 0.5; 0.056 and 0.04 percent, respectively. Plots located in Adi-Haki, Hawelti, and Ayder increase the markup price by 19.28, 16.98 and 12.89 percent, respectively. In the fourth objective, the study appraises the rhetoric and praxis of Ethiopian urban land policies. Results show that urban land legislation in Ethiopia has failed to achieve efficiency and fairness in the land lease market. These failures, in turn, contribute to increasing customer dissatisfaction. The proliferation of customer dissatisfaction was found to be influenced by weak land governance. However, the scale of the phenomenon was seen beyond weak land governance as a signal of policy failure and market failure. The land policy-making failure emanated from the complexity and under-estimation of the modalities of land lease delivery. Hence, all stakeholders must be committed to work as a team to ensure quality service delivery, improve customer satisfaction, and realize sustainable urban land administration in Mekelle City. The study contributes to Sustainable Development Goal (SDG) no. 11 by tracing the performance of urban land governance, the dynamics of the urban land market, and urban land policies towards fit-for-purpose and sustainable land use and development. It also contributes methodologically by generating a good governance framework for urban land administration and combining rhetoric informed and practice-based discourse analyses to show the whole picture of policy research.

Browse

Recent Submissions