scholarly journals Convergence in Sub-Saharan Africa: a nonstationary panel data approach

2002 ◽  
Vol 34 (7) ◽  
pp. 819-829 ◽  
Author(s):  
Suzanne K. McCoskey
Keyword(s):  
Panel Data ◽  
Sub Saharan Africa ◽  
Sub Saharan ◽  
Nonstationary Panel Data

scholarly journals The Nexus between Financial Development and Economic Growth: Panel Data Evidence from Developing Countries

2021 ◽  
Vol 14 (10) ◽  
pp. 489
Author(s):  
E. M. Ekanayake ◽  
Ranjini Thaver
Keyword(s):  
Economic Growth ◽  
Developing Countries ◽  
Panel Data ◽  
Least Squares ◽  
Financial Development ◽  
Panel Cointegration ◽  
Sub Saharan Africa ◽  
Explanatory Variables ◽  
Cointegration Tests ◽  
Sub Saharan

The objective of this study is to investigate the nexus between financial development (FD) in economic growth (GROWTH) in developing countries. The study uses panel data from 138 developing countries during the period 1980–2018. The relationship between financial development and economic growth is investigated using four explanatory variables that are commonly used to measure the level of financial development and several other control variables, including a dummy variable representing the financial and banking crises. The sample of 138 developing countries is also classified into six geographic regions. We have carried out panel unit-root tests and panel cointegration tests before estimating the specified models using both Panel Least Squares (Panel LS) and Panel Fully Modified Least Squares (FMOLS) methods. In addition, panel Granger causality tests have been conducted to identify the direction of causality between FD and GROWTH for each of the regions. The results of the study provide evidence of a direct relationship between FD and GROWTH in developing countries. Furthermore, there is evidence of bi-directional causality running from FD to GROWTH and from GROWTH to FD in samples of Europe and Central Asia, South Asia, and all countries, but not in East Asia and Pacific, Latin America and the Caribbean, Middle East and North Africa, and Sub-Saharan Africa.

Stochastic Evaluation of Capacity and Demand Management of the Airline Industry

2021 ◽  
pp. 85-106
Author(s):  
Yohannes Yebabe Tesfay
Keyword(s):  
Panel Data ◽  
North Africa ◽  
Airline Industry ◽  
Demand Management ◽  
Sub Saharan Africa ◽  
Load Factor ◽  
Sub Saharan ◽  
And Performance ◽  
Periodic Autocorrelation ◽  
Dynamic Time

In the airline industry, the term load factor defined as the percentage of seats filled by revenue passengers and is used to measure efficiency and performance. This metric evaluates the airlines capacity and demand management. This paper applies stochastic models to analyse the load factor of the Association European Airlines (AEA) for flights of Europe - North Africa and Europe- Sub Saharan Africa. The estimation result prevails that the airlines have better demand management in the flights of Europe- Sub Saharan Africa than in the flight of Europe - North Africa. However, the capacity management of the airlines is poor for both regional flights. The autocorrelation structures for the load factor for both regional flights have both periodic and serial correlations. Consequently, the use of ordinal panel data models is inappropriate to capture the necessary variation of the load factor of the regional flights. Therefore, in order to control for the periodic autocorrelation, the author introduces dynamic time effects panel data regression model. Furthermore, in order to eliminate serial correlation the author applies the Prais–Winsten methodology to fit the model. Finally, the author builds realistic and robust forecasting model of the load factor of the Europe- North Africa and Europe-Sub Saharan Africa flights.

Stochastic Evaluation of Capacity and Demand Management of the Airline Industry

2016 ◽  
Vol 3 (2) ◽  
pp. 1-20 ◽  
Author(s):  
Yohannes Yebabe Tesfay
Keyword(s):  
Panel Data ◽  
North Africa ◽  
Airline Industry ◽  
Demand Management ◽  
Sub Saharan Africa ◽  
Load Factor ◽  
Sub Saharan ◽  
And Performance ◽  
Periodic Autocorrelation ◽  
Dynamic Time

In the airline industry, the term load factor defined as the percentage of seats filled by revenue passengers and is used to measure efficiency and performance. This metric evaluates the airlines capacity and demand management. This paper applies stochastic models to analyse the load factor of the Association European Airlines (AEA) for flights of Europe - North Africa and Europe- Sub Saharan Africa. The estimation result prevails that the airlines have better demand management in the flights of Europe- Sub Saharan Africa than in the flight of Europe - North Africa. However, the capacity management of the airlines is poor for both regional flights. The autocorrelation structures for the load factor for both regional flights have both periodic and serial correlations. Consequently, the use of ordinal panel data models is inappropriate to capture the necessary variation of the load factor of the regional flights. Therefore, in order to control for the periodic autocorrelation, the author introduces dynamic time effects panel data regression model. Furthermore, in order to eliminate serial correlation the author applies the Prais–Winsten methodology to fit the model. Finally, the author builds realistic and robust forecasting model of the load factor of the Europe- North Africa and Europe-Sub Saharan Africa flights.

The nexus between economic institutions and unemployment: evidence from sub-Saharan Africa

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdullahi Abdulhakeem Kilishi ◽  
Hammed Adesola Adebowale ◽  
Sodiq Abiodun Oladipupo
Keyword(s):  
Panel Data ◽  
Private Investment ◽  
Developed Countries ◽  
Sub Saharan Africa ◽  
Economic Institutions ◽  
Male And Female ◽  
Content Type ◽  
Long Run ◽  
Sub Saharan ◽  
Ssa Countries

Purpose This paper aims to investigate the nexus between economic institutions (EI) and unemployment in sub-Saharan African (SSA) countries. Specifically, the paper examines the impact of aggregate EI and ten different components of institutions on total, male and female unemployment in SSA. Design/methodology/approach The paper used unbalanced panel data of 37 SSA countries covering the period between 1995 and 2018. A dynamic heterogenous panel data model is specified for the study. Two alternative estimation techniques of dynamic fixed effect and pool mean group methods were used to estimate the models. The choice of appropriate method is based on Hausman specification test. Findings The findings reveal that aggregate EI and institutions related to the monetary system, trade flows, government spending and fiscal process significantly lead to less unemployment in the long-run. However, there is no evidence of a significant relationship between EI and unemployment in the short-run. These findings are consistent for total, male and female unemployment, respectively. Practical implications To reduce unemployment significantly in the long run, policymakers in SSA need to build more market-friendly institutions that will incentivize private investment, allow free movement of labour and goods, as well as guarantee a stable macroeconomic environment and efficient fiscal system. Originality/value Most of the existing studies focused on the influence of labour market institutions on unemployment ignoring the effects of other forms of institutions. While available studies on the link between institutions and unemployment used either OECD or other developed countries sample, with scanty evidence from Africa. However, the effects of EI could vary across regions. Thus, generalizing the findings from developed countries for SSA countries and other developing countries may be misleading. Hence, this paper contributes to the existing literature by examining the nexus between different types of EI and unemployment using the SSA sample.

scholarly journals The Effect of Financial Sector Development on Economic Growth of Selected Sub-Saharan African Countries

2020 ◽  
Vol 23 (2) ◽  
Author(s):  
Dagim Tadesse Bekele ◽  
Adisu Abebaw Degu
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Private Sector ◽  
Financial Institutions ◽  
Adult Population ◽  
Financial Sector ◽  
Dynamic Panel Data ◽  
Sub Saharan Africa ◽  
Financial Sector Development ◽  
Sub Saharan

Finance-growth nexus is among the main debatable issue in economics and policymaking. So, this research tried to look at the effect of financial sector development on the economic growth of 25 sub-Saharan Africa countries by using panel data for time 2010-2017. Precisely, three dynamic panel data models which look the effect of financial sector depth, access and efficiency on economic growth were estimated by two-step system GMM estimation. In this research, credit extended to the private sector per GDP, commercial bank branch per 100,000 adult population, and Return to assets were used as a proxy for financial sector depth, access, and efficiency, respectively. Accordingly, the results revealed financial sector depth, access, and efficiency have a positive and statistically significant effect on the economic growth of these countries.  It is therefore recommended for the concerned bodies that broadening the depth of financial institutions by giving more credit for the private sector is essential. Besides, the financial institutions will have to be expanded to increase their accessibility to the mass and have to take some measures which promote their efficiency. 

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