scholarly journals Assessing the performance of regional soybean prices in Ghana

2020 ◽  
Vol 23 (2) ◽  
pp. 267-282 ◽  
Author(s):  
Edward Martey ◽  
Nicolas Gatti ◽  
Peter Goldsmith
Keyword(s):  
Market Integration ◽  
Smallholder Farmers ◽  
Poor Performance ◽  
Sub Saharan Africa ◽  
Vector Error Correction ◽  
Vector Error ◽  
Local Supply ◽  
Sub Saharan ◽  
And Performance ◽  
Regional Soybean

Soybean production has been widely promoted in sub-Saharan Africa as a means of improving rural household income. Numerous studies point to poor adoption levels, low yield levels, and limited profitability among smallholder farmers. Poor performance of soybean among smallholders generates numerous hypotheses as to the root causes. One logical cause is low prices, which result from anecdotes from the field, especially among producers and policymakers. In this study, the first of its kind that we are aware of, analyzes regional soybean prices over time across six key growing and commercial regions of Ghana. We employ cointegration and multivariate vector error correction model to measure the level of international and inter-market integration and performance. The results show regional and international integration as well as Granger Causality results consistent with the local supply-demand context. Specifically, the international market Granger causes Kumasi, Bolgatanga, and Wa markets, while the Tamale and Kumasi, serve as the leading production and demand markets, respectively. The results of the study provide evidence that prices do perform well in Ghana and are not a major source of weak adoption and low levels of profitability among smallholder soybean farmers.

scholarly journals Financial Development and Energy Consumption in Sub-Saharan Africa: Evidence From Panel Vector Error Correction Model

SAGE Open ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 215824402093543
Author(s):  
Chigozie Nelson Nkalu ◽  
Samuel Chinwero Ugwu ◽  
Fredrick O. Asogwa ◽  
Mwuese Patricia Kuma ◽  
Queen O. Onyeke
Keyword(s):  
Energy Consumption ◽  
Error Correction ◽  
Granger Causality ◽  
Financial Development ◽  
Sub Saharan Africa ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Sub Saharan

This study examines the nexus between financial development and energy consumption/use in Sub-Saharan Africa (SSA) using a panel vector error correction model (VECM), cointegration, and Granger causality tests over the period ranging from 1975 to 2017. The annual panel time-series data generated from the World Bank database were tested for unit-roots processing using both the Levin–Lin–Chu and Im–Pesaran–Shin before proceeding to Johanson cointegration technique, the results of which motivated the choice of adopting the panel VECM rather than panel vector autoregression in the methodology. From the estimation result especially on the variables of interest, there exists a positive and statistically significant relationship between financial development and energy consumption in the long run, but not statistically significant in the short run. Further findings from the panel Granger causality test shows a unidirectional causality running from financial development to energy consumption, gross domestic product per capita, population growth to urbanization with no feedback. Among a series of policy recommendations, the monetary authorities in Sub-Saharan African countries should ensure optimal utilization of financial instruments and technologies available in the system to enhance more robust financial development to boost efficiency in energy consumption in the region in line with the sustainable growth theory.

scholarly journals Dividend Payout, Retention Policy and Financial Performance in Commercial Banks: Any Causal Relationship?

2018 ◽  
Vol 63 (1) ◽  
pp. 37-62 ◽  
Author(s):  
Odunayo Magret Olarewaju ◽  
Stephen Oseko Migiro ◽  
Mabutho Sibanda
Keyword(s):  
Financial Performance ◽  
Error Correction ◽  
Causal Relationship ◽  
Commercial Banks ◽  
Banking Sector ◽  
Sub Saharan Africa ◽  
Model Estimate ◽  
Vector Error Correction ◽  
Vector Error ◽  
Sub Saharan

Abstract Dividend policy remains one of the top ten unresolved issues in corporate finance including in the banking sector. Hence, this study explores data from 250 commercial banks in 30 Sub-Saharan African countries to establish the causal relationship between the use of two major dividend policies in the sector and financial performance for the period 2006 to 2015. The empirical results of the vector error correction block exogeneity Wald test and Pairwise Granger causality test reveal that only retention policies Granger cause performance (ROA), even though both major policies posit a positive relationship with performance (ROA) in the Vector Error Correction Model estimate. Therefore, commercial banks in Sub Saharan Africa and also in the entire world should use their free cash flows wisely by exploring all available viable investment opportunities. By doing this, not only owners’ profit but wealth is fully maximised such that their survival, value creation, and future growth is fully justified.

scholarly journals OIL PRICE FLUCTUATIONS AND EXCHANGE RATE IN SELECTED SUB-SAHARAN AFRICA COUNTRIES: A VECTOR ERROR CORRECTION MODEL APPROACH

2020 ◽  
Vol 10 (6) ◽  
pp. 242-249
Author(s):  
Benjamin Ighodalo Ehikioya ◽  
Alexander Ehimare Omankhanlen ◽  
Ayopo Abiola Babajide ◽  
Godswill Osagie Osuma ◽  
Cordelia Onyinyechi Omodero
Keyword(s):  
Exchange Rate ◽  
Error Correction ◽  
Oil Price ◽  
Sub Saharan Africa ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Sub Saharan ◽  
Model Approach

scholarly journals Precision Agriculture for Resource Use Efficiency in Smallholder Farming Systems in Sub-Saharan Africa: A Systematic Review

2021 ◽  
Vol 13 (3) ◽  
pp. 1158
Author(s):  
Cecilia M. Onyango ◽  
Justine M. Nyaga ◽  
Johanna Wetterlind ◽  
Mats Söderström ◽  
Kristin Piikki
Keyword(s):  
Resource Use ◽  
Precision Agriculture ◽  
Large Scale ◽  
English Language ◽  
Management Practices ◽  
Smallholder Farmers ◽  
Management Strategies ◽  
Sub Saharan Africa ◽  
Smallholder Farming ◽  
Sub Saharan

Opportunities exist for adoption of precision agriculture technologies in all parts of the world. The form of precision agriculture may vary from region to region depending on technologies available, knowledge levels and mindsets. The current review examined research articles in the English language on precision agriculture practices for increased productivity among smallholder farmers in Sub-Saharan Africa. A total of 7715 articles were retrieved and after screening 128 were reviewed. The results indicate that a number of precision agriculture technologies have been tested under SSA conditions and show promising results. The most promising precision agriculture technologies identified were the use of soil and plant sensors for nutrient and water management, as well as use of satellite imagery, GIS and crop-soil simulation models for site-specific management. These technologies have been shown to be crucial in attainment of appropriate management strategies in terms of efficiency and effectiveness of resource use in SSA. These technologies are important in supporting sustainable agricultural development. Most of these technologies are, however, at the experimental stage, with only South Africa having applied them mainly in large-scale commercial farms. It is concluded that increased precision in input and management practices among SSA smallholder farmers can significantly improve productivity even without extra use of inputs.

scholarly journals REVIEW OF SEASONAL CLIMATE FORECASTING FOR AGRICULTURE IN SUB-SAHARAN AFRICA

2011 ◽  
Vol 47 (2) ◽  
pp. 205-240 ◽  
Author(s):  
JAMES W. HANSEN ◽  
SIMON J. MASON ◽  
LIQIANG SUN ◽  
ARAME TALL
Keyword(s):  
Smallholder Farmers ◽  
Seasonal Forecast ◽  
Sub Saharan Africa ◽  
Seasonal Forecasting ◽  
Seasonal Forecasts ◽  
Climate Services ◽  
Seasonal Climate ◽  
Climate Forecasting ◽  
Probabilistic Forecasts ◽  
Sub Saharan

SUMMARYWe review the use and value of seasonal climate forecasting for agriculture in sub-Saharan Africa (SSA), with a view to understanding and exploiting opportunities to realize more of its potential benefits. Interaction between the atmosphere and underlying oceans provides the basis for probabilistic forecasts of climate conditions at a seasonal lead-time, including during cropping seasons in parts of SSA. Regional climate outlook forums (RCOF) and national meteorological services (NMS) have been at the forefront of efforts to provide forecast information for agriculture. A survey showed that African NMS often go well beyond the RCOF process to improve seasonal forecast information and disseminate it to the agricultural sector. Evidence from a combination of understanding of how climatic uncertainty impacts agriculture, model-based ex-ante analyses, subjective expressions of demand or value, and the few well-documented evaluations of actual use and resulting benefit suggests that seasonal forecasts may have considerable potential to improve agricultural management and rural livelihoods. However, constraints related to legitimacy, salience, access, understanding, capacity to respond and data scarcity have so far limited the widespread use and benefit from seasonal prediction among smallholder farmers. Those constraints that reflect inadequate information products, policies or institutional process can potentially be overcome. Additional opportunities to benefit rural communities come from expanding the use of seasonal forecast information for coordinating input and credit supply, food crisis management, trade and agricultural insurance. The surge of activity surrounding seasonal forecasting in SSA following the 1997/98 El Niño has waned in recent years, but emerging initiatives, such as the Global Framework for Climate Services and ClimDev-Africa, are poised to reinvigorate support for seasonal forecast information services for agriculture. We conclude with a discussion of institutional and policy changes that we believe will greatly enhance the benefits of seasonal forecasting to agriculture in SSA.

scholarly journals Factors That Matter for Financial Inclusion: Evidence from Sub-Sharan Africa - The Zimbabwe Case

2021 ◽  
Vol 10 (6) ◽  
pp. 48
Author(s):  
David Mhlanga
Keyword(s):  
Smallholder Farmers ◽  
Multinomial Logistic Regression ◽  
Multinomial Logit Model ◽  
Financial Inclusion ◽  
Sub Saharan Africa ◽  
Farm Income ◽  
Smallholder Farming ◽  
Hand Off ◽  
Sub Saharan ◽  
The Government

The study intended to investigate the factors that are important in influencing the financial inclusion of smallholder farming households in Sub-Saharan Africa with a specific focus on Zimbabwe. Motivated by the fact that there is an increase in the evidence of the importance of financial inclusion in fighting poverty and the fact that by merely having a bank account, financial inclusion cannot be guaranteed, the study went further to interrogate factors that influence smallholder farmers to have a transaction account, to borrow and to have insurance. Since the dependent variable of financial inclusion had more than two categories, with three unordered categories, transaction account, savings/credit account, and insurance, the multinomial logistic regression was used to estimate the determinants of financial inclusion from these three categories of the dependent variable. The multinomial logit model results, with insurance as the reference category, indicated that the size of the household, transaction costs, gender and agricultural extension service were the factors influencing the demand for a household to open a transaction account. On the other hand, off-farm income and age of the household were the only two factors significantly influencing households to borrow. Therefore, it is imperative for, the government of Zimbabwe to come up with more policies that encourage farmers to participate in the formal financial market as financial inclusion can help to fight poverty and the general developments of societies.   Received: 28 April 2021 / Accepted: 31 August 2021 / Published: 5 November 2021

scholarly journals A Multi-Phase Assessment of the Effects of COVID-19 on Food Systems and Rural Livelihoods in Zimbabwe

2021 ◽  
Author(s):  
Vine Mutyasira
Keyword(s):  
Food Systems ◽  
Smallholder Farmers ◽  
Rapid Assessment ◽  
Policy Research ◽  
Rural Livelihoods ◽  
Mitigation Strategies ◽  
Sub Saharan Africa ◽  
Response Measures ◽  
Sub Saharan ◽  
Multi Phase

The COVID-19 pandemic has continued to affect agri-food systems around the world and lay bare its fragility, worsening the welfare of millions of smallholder farmers whose livelihoods are anchored on agricultural activities. For the vast majority of sub-Saharan Africa, COVID-19 has coincided with a number of other macroeconomic shocks, which have also exacerbated the impacts of the pandemic on food security, nutrition and general livelihoods, as well curtailed policy responses and mitigation strategies. In Zimbabwe, the COVID-19 pandemic struck at a time the country was experiencing a worsening economic and humanitarian situation. This study focused more on community and household dynamics and response measures to cope with the pandemic. This paper presents a summary of findings emerging from a series of rapid assessment studies undertaken by the Agricultural Policy Research in Africa (APRA) Programme in Mvurwi and Concession areas of Mazowe District in Zimbabwe to examine how COVID-19 is affecting food systems and rural livelihoods in our research communities.

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.

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