Effect of Real Exchange Rate Volatility on Agricultural Products Export in Nigeria

Alegwu, Friday Otse; Aye, Goodness C.; Asogwa, Benjamin C.

doi:10.7160/aol.2018.100301

Cited by 9 publications

(12 citation statements)

References 8 publications

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“…Farmers do not know how to and do not have the means to export their products to the market. This problem is consistent with the extant literature (Alegwu et al, 2018; Azih, 2008; Elijah et al, 2017). Asenso-Okyere and Mekonnen (2018) noted that lessons from the Asian experience could help Africa, specifically that access to market information could help rural farmers become more competitive and productive.…”

Section: Discussionsupporting

confidence: 92%

“…Some rural Nigerian farmers do not have access to market data or know how to perform strategic planning. There was a lot of evidence to support this point in the literature, namely, Alegwu et al (2018), Dauda et al (2015), Kassali et al (2018), Magbadelo (2018) and Marketline (2017). The focus group participants felt Nigerian farmers do not treat farming as a business.…”

Section: Discussionmentioning

confidence: 94%

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Urgently strategic insights to resolve the Nigerian food security crisis

2019

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The food security crisis is a serious worldwide predicament in developing countries but it is a relatively larger problem in Nigeria. We argued there was no solution for the Nigerian food security crisis because researchers had not customized theoretical models with data-driven priorities grounded on local agriculture subject matter expert knowledge. We collected data from local agriculture extension workers who had specialized knowledge of the problems. We applied the consensual qualitative research method with embedded nominal brainstorming and multiple correspondence statistical techniques at the group level of analysis to develop a proposed solution. Our final model highlighted strategically urgent ideas to increase agriculture productivity and appease the most severe constraints in rural Nigeria. The results extended what was already published in the literature and should generalize to rural farmers in Nigeria as well as to government policymakers in developing countries around the world.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 94%

Urgently strategic insights to resolve the Nigerian food security crisis

2019

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“…Using a general methods of moments model and panel data on 29 Chinese provinces for 1987-2008, Hua (2011) found that real exchange rate appreciation had a negative effect on both economic growth and employment. Alegwu et al (2017) examined the asymmetric effects of real exchange rate volatility on agricultural products export in Nigeria, using the VAR model and annual time series data for 1970-2013. Analysis using the real exchange rate volatility, measured as generalized autoregressive conditional heteroscedasticity (GARCH) (1, 1), showed that the effects of the real exchange rate volatility shock during appreciation and depreciation on most of the products were significantly different.…”

Section: Empirical Reviewmentioning

confidence: 99%

The effect of real exchange rate volatility on income distribution in South Africa

Aye¹,

Harris²

2019

WIDER Working Paper

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte.Abstract: This study investigates the effect of real exchange rate volatility on the distribution of income between labour and capital in South Africa. Both symmetric and asymmetric effects are considered. Using quarterly data for 1985:1-2018:3 and local linear projection, we find that the immediate response of labour's income share to a one standard deviation shock in exchange rate volatility is negative. Moreover, high exchange rate volatility impacts negatively on labour's income share, while low exchange rate volatility impacts positively on labour income. As the magnitude of the effect of high exchange rate volatility is greater than that of low exchange rate volatility, the study documents evidence of an asymmetric effect. A shock increase in some control variables (real gross domestic product, investment, and openness) is followed immediately by a decline in labour income, while an increase follows a positive shock in the relative price of investment. The policy implications of these findings are discussed.

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“…GARCH (1,1) was used by [28] to measure real exchange rate volatility of Nigerian currency with a view to investigate the asymmetric effects of real exchange rate volatility on agricultural products export in Nigeria. Asymmetric effects test based on the Wald statistic showed that apart from cotton exports, the effect of currency volatility on cocoa, coffee and rubber exports was significantly different.…”

Section: Literature Reviewmentioning

confidence: 99%

Unravelling the Cipher of Indian Rupee’s Volatility: Testing the Forecasting Efficacy of the Rolling Symmetric and Asymmetric GARCH Models

Talwar¹,

Bhat²

2018

TEL

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Modelling exchange rate volatility is crucially important because of its diverse implications on the profitability of corporations and decisions of policy makers. This paper empirically investigates exchange rate volatility of India's currency by applying rolling symmetric and asymmetric GARCH models to the USDINR and EURINR daily exchange rates for a period spanning April 1, 2006 through January 31, 2018, resulting in total observations of 2861. To estimate GARCH (1,1) and EGARCH (1,1) models, the data window is rolled over five years with nearly 1200 observations and one month is used as forecast period for each window. Both, in-sample criteria like the log likelihood criteria, Akaike information criterion (AIC), the Bayesian information criterion (SIC) and Hannan Quinn criterion (HQC) as well as the out-of-sample criteria like Mean Squared Error (MSE) and Mean Absolute Error (MAE) have been used to test model fit and forecast accuracy of the models. To test the robustness of the findings, Diebold-Mariano test is used to compare the predictive accuracy of both the models. Further, the forecasting accuracy of the two models has also been tested by splitting the sample period into periods of tranquility and volatility in Indian exchange rate. Results show that GARCH (1,1) model with generalized error distribution is adequate to capture the mean and volatility process of USDINR and EURINR exchange rate returns.

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Effect of Real Exchange Rate Volatility on Agricultural Products Export in Nigeria

Cited by 9 publications

References 8 publications

Urgently strategic insights to resolve the Nigerian food security crisis

Urgently strategic insights to resolve the Nigerian food security crisis

The effect of real exchange rate volatility on income distribution in South Africa

Unravelling the Cipher of Indian Rupee’s Volatility: Testing the Forecasting Efficacy of the Rolling Symmetric and Asymmetric GARCH Models

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