Oil, Power, and Poverty in Angola

García‐Rodríguez, José León; García‐Rodríguez, Francisco J.; Castilla‐Gutiérrez, Carlos; Major, Silvério Adriano

doi:10.1017/asr.2015.8

Cited by 16 publications

(7 citation statements)

References 15 publications

(16 reference statements)

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“…Angola is one of the largest exporters of primary commodities in SSA. If affected by the Dutch disease, the economic situation of Angola can mirror that of a resource-curse-country, where natural resource abundance is associated with deteriorated standards of living [28,29]. However, other scholars note that although the Dutch disease has been prevalent in oil-intensive countries, Angola can be an exception because of the positive correlation between oil export intensity and the growth of Angola's non-oil sectors [29].…”

Section: Introductionmentioning

confidence: 99%

Effects of Agricultural, Manufacturing, and Mineral Exports on Angola’s Economic Growth

Zayone¹,

Henneberry

Radmehr

2020

Energies

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This study investigates the effects of Angola’s agricultural, manufacturing, and mineral exports on the country’s economic growth using data from 1980 to 2017. An Autoregressive Distributed Lag (ARDL) model is employed to estimate the effect of sectoral exports on economic growth. The estimation results show that while exports from all three sectors (manufacturing, mineral, and non-mineral) have driven Angola’s economic growth in the long-run; only non-manufacturing (agricultural and mineral) exports have led its growth in the short-run. Moreover, growth in non-export GDP was driven by mineral exports in the long-run and agricultural exports in the short-run. Considering the statistically significant and positive impact of mineral exports on the Angolan GDP as well as on its non-export GDP, this study points to a lack of evidence supporting the Dutch disease phenomenon in Angola.

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Section: Introductionmentioning

confidence: 99%

Effects of Agricultural, Manufacturing, and Mineral Exports on Angola’s Economic Growth

Zayone¹,

Henneberry

Radmehr

2020

Energies

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“…All in all, the country performs poorly in all of the BBI proxies, i.e., assuming a threshold of 70 th percentile, with the exception of their performance in the proxies for 'Poor Savings' (SAV) and 'CO2 Emissions Per Capita' (CO2E). According to Munslow (1999) & García-Rodríguez et al (2015, Angola is poorly developed despite the abundance of natural oil resources is due to corruption and the unequal distribution of wealth. Hammond (2011) on the other hand, argues that Angola's poor development could be attributed to the resource curse thesis developed by Auty (1995), arguing that high dependence on external rent leads to unsustainable development which fuels corruption.…”

Section: Angola and The Bbi: Leading The Rankingsmentioning

confidence: 99%

The 'Bad Behavior Index': A Composite Measure of the Development Hindering Behavior of Individuals and Institutions

Fozaie

2023

Sci. Ann. Econ. Bus.

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Composite indices have become a popular tool for providing a quantitative, simplified, and visualized representation of complex phenomena. An example of such is the Human Development Index (HDI) which ranks countries by their level of development. The primary limitation of the HDI is its narrow scope, which hinders its effectiveness at explaining why some nations are more developed than others. The discussion as to why some nations are more developed than others goes back as far as the 14th century, where Ibn Khaldun developed a theory which aims to explain why civilizations rise and fall. Some of the hypotheses which seek to answer this question point to the importance of economic freedoms, absence of corruption, high investment in human capital, and the importance of institutions etc. to development. One hypothesis which has not been properly studied regards the culpability of individual and institutional behavior. The purpose of this study is to introduce a composite measure of the development hindering behavior of individuals and institutions, i.e., the Bad Behavior Index (BBI). The methodology of this study is influenced by the Mazziotta & Pareto framework for composite indices. The index weights have been computed by integrating expert opinion with the Fuzzy Analytic Hierarchy Process (FAHP). The findings of this study suggest that African countries engage in the highest level of bad behavior, which subsequently leads to their poor socio-economic development, whereas Northern countries engage in the least level of bad behavior. The study also finds that the most important drivers for socio-economic development are low levels of corruption, high levels of knowledge creation, strict application of the rule of law, high levels of social cohesion, and high levels of political stability.

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“…However, contrary to what findings revealed about other developing regions, this is not so in African developing countries, as export and services have not led to substantial economic growth in the region. Notably, the exportation of primary minerals or commodities has been, over the years, connected with negative or non-beneficiary trade (Garc ıa-Rodr ıguez et al, 2015;Harvey et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Impact of non-oil sectors on GDP/capita in selected African countries: evidence from panel analysis

Adeosun

Gbadamosi

2021

WJSTSD

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PurposeThe purpose of this paper is to investigate the impact or contribution of non-oil sectors on economic growth (GDP/capita) of some selected African countries using panel data analysis.Design/methodology/approachThe paper focused on secondary data for the period 1991–2019 for macro parameters, including agriculture, industry, export and service, and GDP/capita received from World Development Indicators (WDI). Panel unit root tests like Levin, Lin and Chu test and Im, Pesaran and Shin test, Johansen co-integration test, Granger causality test and an error correction model were also applied to the data for analysis.FindingsThe study reveals no causality from agriculture to economic growth, which implies most of the African countries (used in this study) have neglected agriculture as a source of economic growth. The industry independent variable was of no effect on these countries’ economic growth, whereas the findings reveal that industry has causality on economic growth. Economic growth has no causality on the industry, which means the industry is not contributing to economic growth. The study also shows no causality from export and service to economic growth, but a causality runs from economic growth to export and service.Originality/valueThe paper examines the contribution of the non-oil sectors to economic growth in selected African countries.

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Oil, Power, and Poverty in Angola

Cited by 16 publications

References 15 publications

Effects of Agricultural, Manufacturing, and Mineral Exports on Angola’s Economic Growth

Effects of Agricultural, Manufacturing, and Mineral Exports on Angola’s Economic Growth

The 'Bad Behavior Index': A Composite Measure of the Development Hindering Behavior of Individuals and Institutions

Impact of non-oil sectors on GDP/capita in selected African countries: evidence from panel analysis

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