Position Analysis of the Relationship Between the Naira Exchange Rate, Gb Pounds, Euro and US-Dollars

Authors

Keywords:

Position Analysis, exchange rate, vector error correction, causal relationship, cointegration

Abstract

Kingsley Uchendu Chinaegbomkpa Umezurike and David, Friday Adiele

The main objective of this research is to investigate the true position of the causal relationship between the Nigeria Naira exchange rate against the Euro, GBP and Dollars on the long and short run. We considered the structural break which is believed to be as a result of the government deliberate devaluation of the Naira. Unit root test indicated stationarity at the first difference for all the variables. The result of the vector error correction model reveals that the position of the relationship on long run pair wise test between NGNUSD, NGGBP and NGNEUR shows unidirectional causality running from NGNUSD→NGNGBP→ and NGNUSD→NGNEUR. This implies that NGNUSD affects NGNGBP and NGNEUR in the long run. It is observed that NGNUSD is useful to forecast NGNGBP and NGNEUR, but the converse is not true. Moreover, it is observed that there is bi-directional causality between NGNGBP and NGNEUR, which implies that all the series affect each other in the long run. On the other hand, the position of the relationship in the short run using the Wald test reveals a unidirectional causality running from NGNEUR to NGNGBP, which means NGNEUR affects NGNGBP in the short-run. We observed that NGNEUR is useful to forecast NGNGBP in the short-run but the converse is not true. This reveals that the position of the relationship between the Naira, Dollar, Euro and GB-pound is responsible for the constant price hike in Nigeria, making the living condition of Nigeria, making living condition of Nigerians  harshly unbearable.

Author Biographies

  • Kingsley Uchendu, Michael Okpara University of Agriculture Umudike, Nigeria.

    Department of Statistics

  • Chinaegbomkpa Umezurike, Michael Okpara University of Agriculture Umudike, Nigeria

    Department of Statistics

  • David, Friday Adiele, Michael Okpara University of Agriculture Umudike, Nigeria

    Department of Statistics

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Published

2022-09-28

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