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Wyszukujesz frazę "Shoko, Roy" wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
Agricultural supply response and price risk of maize and sorghum in South Africa
Autorzy:
Shoko, Roy
Belete, Abenet
Mongale, Itumeleng Pleasure
Powiązania:
https://bibliotekanauki.pl/articles/2033363.pdf
Data publikacji:
2021-12-28
Wydawca:
Uniwersytet Przyrodniczy w Poznaniu. Wydawnictwo Uczelniane
Tematy:
ARDL-ECM
supply response
price risk
sorghum
maize
Opis:
The study used the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM) approach to estimate the responsiveness of South African maize and sorghum producers to price risk, price incentives and non-price incentives. The price risk variable was incorporated in the supply models to examine its impact on maize and sorghum production decisions. The study used annual historical time series data of 49 observations for the period 1970 to 2018 was used in the analysis. The empirical results reveal that maize and sorghum producers' response to own price is reasonably low. The study further shows that both maize and sorghum crops demonstrate a high speed of adjustment to the long-run equilibrium, which means that in the event of a shock to the system, grain output will quickly re-establish itself at a faster rate. The findings underscore the relevance of price risk in determining production output in South Africa.
Źródło:
Journal of Agribusiness and Rural Development; 2021, 62, 4; 435-445
1899-5241
Pojawia się w:
Journal of Agribusiness and Rural Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Efficient planning of sorghum production in South Africa – Application of the Box-Jenkin’s method
Autorzy:
Shoko, Rangarirai Roy
Belete, Abenet
Powiązania:
https://bibliotekanauki.pl/articles/952111.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Przyrodniczy w Poznaniu. Wydawnictwo Uczelniane
Tematy:
arima
sorghum production
forecasting
south
africa
Opis:
Estimation and forecasting of crop production are crucial in supporting policy decisions regarding food security and development issues. The present study examines the current status of sorghum production in South Africa. Univariate time series modelling using ARIMA model was developed for forecasting sorghum production. Box and Jenkins linear time series model, which involves autoregression, moving average, and integration, also known as ARIMA (p, d, q) model was applied. The annual production series of sorghum from 1960 to 2014 exhibited a decreasing trend while prediction of sorghum production between 2017 and 2020 showed an increasing trend. The study has shown that the best-fitted model for sorghum production series is ARMA (1, 0, 4). The model revealed a good performance in terms of explaining variability and forecasting power. This study has also shown that sorghum could contribute to the household and national food security because of its drought-tolerant properties.
Źródło:
Journal of Agribusiness and Rural Development; 2017, 46, 4; 836-841
1899-5241
Pojawia się w:
Journal of Agribusiness and Rural Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Maize yield sensitivity to climate variability in South Africa: application of the ardl-ecm approach
Autorzy:
Shoko, Rangarirai Roy
Belete, Abenet
Chaminuka, Petronella
Powiązania:
https://bibliotekanauki.pl/articles/1911913.pdf
Data publikacji:
2019-12-28
Wydawca:
Uniwersytet Przyrodniczy w Poznaniu. Wydawnictwo Uczelniane
Tematy:
maize
climate variability
ARDL model
cointegration
Opis:
Climate affects crop production decisions and outcomes in agriculture. From very short-term decisions about which crops to grow, when to plant or harvest a field, to longer-term decisions about farm investments, climate can positively or negatively affect agricultural systems. Although the general effects of climate change on agriculture are broadly understood, there are limited studies that model the relationship between specific crops and climate variables. The study uses the Autoregressive Distributed Lag (ARDL) model to analyze the sensitivity of maize yield to climate variables, fertilizer use and other non-climate variables. This paper uses annual time-series data of 47 observations spanning from 1970 to 2016. The results reveal that rainfall and temperature are important maize yield drivers in South Africa. However, if excessive, they will produce negative effects. The findings of this analysis are relevant for designing long-term interventions to mitigate the effects of climate change on maize production.
Źródło:
Journal of Agribusiness and Rural Development; 2019, 54, 4; 363-371
1899-5241
Pojawia się w:
Journal of Agribusiness and Rural Development
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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