Amavilah, Voxi (2019): A simple time-insensitive index of instability as a proxy for the “Africa dummy” variable – A Note.
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Abstract
This paper calculates a simple time-insensitive index of instability using discrete series of events. The calculation of the index does not require complex statistical analysis of event series, discrete-event systems analysis, or categorical analysis. It uses a simple, single-equation regression to estimate the effects of instability on Africa’s per capita GDP over the 1961-2018 period. The results are mixed, with some showing that instability has constrained Africa’s performance and others implying it has helped. The findings are not quite econometrically pure, but reasonable given that many relevant variables are missing from the regression. Hence, I resist the temptation to comment further until at least conventional factors like capital are included in this regression, while I insist that the index itself is sound.
Item Type: | MPRA Paper |
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Original Title: | A simple time-insensitive index of instability as a proxy for the “Africa dummy” variable – A Note |
English Title: | A simple time-insensitive index of instability as a proxy for the “Africa dummy” variable – A Note |
Language: | English |
Keywords: | Index of instability, Africa dummy, economic performance, single-equation regression |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C49 - Other O - Economic Development, Innovation, Technological Change, and Growth > O5 - Economywide Country Studies > O55 - Africa Z - Other Special Topics > Z0 - General |
Item ID: | 96295 |
Depositing User: | Voxi Heinrich Amavilah |
Date Deposited: | 03 Oct 2019 07:40 |
Last Modified: | 03 Oct 2019 07:40 |
References: | Amavilah, Voxi Heinrich (2018) Endogenous constraints, coefficients of economic distance, and economic performance of Africa countries – An exploratory essay. MPRA Paper No. 90065. https://mpra.ub.uni-muenchen.de/90065/1/MPRA_paper_90065.pdf. Barro, Robert (1991) Economic growth in a cross-section of countries. Quarterly Journal of Economics, CBI(2): 407-443. Einstein, Albert (1952) Relativity and the problem of space (English translation 1954). http://www.relativitybook.com/resources/Einstein_space.html.Accessed on September 5, 2019. Englebert, Pierre (2000) Solving the mystery of the Africa dummy. World Development, 28(10): 1821-1835. European Commission (2008) Handbook on constructing composite indicators: Methodology and user guide. Pp.12-20; 28-32. Jerven, Morten (2011) The quest for the Africa dummy. Explaining African post-colonial economic performance revisited, Journal of International Development, 23(2): 288-307. Mazziotta, Mateo and Pareto, Addriano (2013) Methods for constructing composite indices: One for all or all for one? Revista Italiana di Economica Demografia e Statistica, LXVII (2): 67-80. United Nations Development Programmr – UNDP (2014) “Technical notes” in Sustaining human progress, reducing vulnerabilities and building resilience. Human Development Report 2014. Varian, Hall (2016) How to build an economic model in your spare time. American Economist, 61(1): 81-90. World Bank Group (Undated) “GDP per capita growth (annual %) – Sub-Saharan Africa,” in World Bank National Accounts Data and OECD National Accounts Data Files. ID: NY.GDP.PCAP.KD.ZG. https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG?locations=ZG |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/96295 |
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