This study examines money market and foreign exchange market dynamics in Nigeria by estimating the dynamic correlation and volatility spillovers between Nigeria Naira/US Dollar Bureau De Change (BDC) exchange rate and interbank call rate with data from January 2007 to August 2019. The study employs a dynamic conditional correlation form of GARCH model (DCC-GARCH) to access the nature of correlation, while an unrestricted bivariate BEKK-GARCH (1, 1) form of multivariate GARCH model is utilized to investigate shocks and volatility spillover of the rates. The estimated DCC-GARCH (1, 1) reveals that interest rate and exchange rate are dynamically linked negatively, suggesting that exchange rate (or interest rate) is inversely sensitive to interest rate (or exchange rate) in Nigeria. This result was substantiated by the estimated BEKK-GARCH(1, 1) model. Furthermore, the effects of news (shocks spillover) are bi-directional across the markets. However, volatility spillover is unidirectional, from exchange rate to interest rate, suggesting that, calming the volatility in foreign exchange market does guarantee moderation of volatility in the money market, whereas the reverse is not the case. The results underscore the growing influence of foreign exchange market in the financial space of the Nigerian economy. Thus, the study recommends that foreign exchange policies aimed at maintaining exchange rate stability should be sustained, having found exchange rate to be more effective in moderating interest rate volatility in Nigeria.

https://www.econstor.eu/bitstream/10419/237438/1/1767673035.pdf

Money and foreign exchange markets dynamics in Nigeria: A multivariate GARCH approach

The risks associated with exchange rate and money market indicators have drawn the attentions of econometricians, researchers, statisticians, and even investors in deposit money banks in Nigeria. The study targeted at modeling exchange rate and Nigerian deposit banks money market dynamics using trivariate form of multivariate GARCH model. Data for the period spanning from 1991 to 2017 on exchange rate (Naira/Dollar) and money market indicators (Maximum and prime lending rate) were sourced for from the central bank of Nigeria (CBN) online statistical database. The study specifically investigated; the dynamics of the variance and covariance of volatility returns between exchange rate and money market indicators in Nigeria were examine whether there exist a linkage in terms of returns and volatility transmission between exchange rate and money market indicators in Nigeria and compared the difference in Multivariate BEKK GARCH considering restrictive indefinite under the assumption of normality and that of student’s –t error distribution.  Preliminary time series checks were done on the data and the results revealed the present of volatility clustering. Results reveal the estimate of the maximum lag for exchange rate and money market indicators were 4 respectively. Also, the results confirmed that there were two co-integrating equations in the relationship between the returns on exchange rate and money market indicators.  The results of the diagonal MGARCH –BEKK estimation  confirmed  that diagonal MGARCH –BEKK in students’-t was  the best fitted and an appropriate model for modeling exchange rate and Nigerian deposit money market dynamics using trivariate form of multivariate GARCH model. Also, the study confirmed presence of two directional volatility spillovers between the two sets of variables.

/pdf/modeling-exchange-rate-and-nigerian-deposit-money-market-2ip2h4ojjj.pdf

Modeling Exchange Rate and Nigerian Deposit Money Market Dynamics Using Trivariate form of Multivariate GARCH Model

The study modeled the dynamic interaction between exchange rate, interest rate and agricultural export earnings using panel VAR Model. The specific objectives of the study include to; interdependencies in the dynamic interaction between exchange rate, interest rate and agricultural export earnings, parameters of panel VAR model using PVAR Stata code developed by Abrigo and love, determine the shocks associated with their dynamic interactions between these variables, investigate direction of causality between interest rate, exchange rate and agricultural export earnings from six African countries and make appropriate recommendations. The data used for the study was secondary data extracted from index mundi website and world data indicators for the period of 40 years (1980-2020). The data was on exchange rate, interest rate and agricultural export earnings. Geographically, the six African countries include; Algeria, Angola, Egypt, Libya, Gabon and Nigeria. The study uses vector Autoregressive model estimation results with PVAR Stata code developed by Abrigo and love. The post estimation test on the Vector Autoregressive (VAR) model shows a contemporary Co-efficient of Correlation analysis. It was found that lending interest rate and exchange rate are negatively associated with Co-efficient of Correlation of (-0.0873). Also, it was found that there exist a positive association between exchange rate and agricultural export earnings. Also, there is a positive association between lending interest rate and agricultural export earnings. The inverse roots of a characteristic polynomial of the estimated Panel VAR model satisfied the stability condition (of the diagnostic test) since no root lied outside the unit root circle. Therefore, the estimated VAR is stable. However, it was confirmed that there is no directional relationship that exist between the variables. Also, the results show that exchange rate and lending rate have positive on agricultural export earnings, whereas exchange rate is likely to reduce the level of lending interest rate slightly. Therefore, it is recommended that in estimating the dynamic interaction between variables in a panel data system, there is need for the inclusion of the lags of the response variable among the determinants to measures the dynamic interaction as well capture heterogeneities in the series and also, policies should be formulated to stabilized exchange and lending rates in order to improve and strengthen the countries’ agricultural economy amongst others

Exchange Rate, Interest Rate and Agricultural Export Earnings: An analysis Using Panel Data Vector Autoregressive Model

The study examines the effect of monetary policy on commercial bank’s lending operation in Nigeria between February, 1991 to October, 2020 using the macroeconomic time series variables of exchange rate, interest rate, maximum lending rate and prime lending rate. The vector error correction model was employed to analyze these interactions as well as the effect and pattern of causality among the variables under investigation. Monthly data spanning from February, 1991 to October, 2020 which covered a period of 29 years and 7 months (357 observations) were sourced from the Statistical Bulletin of the Central Bank of Nigeria (CBN). Preliminary statistical approach such as descriptive statistics and time plot were carried out to test if the data set obey the normality assumption and to verify if there is trend on the series. Pre-estimation diagnosis such as unit root test, lag order selection criteria and co-integration test were carried out and the results shows that at level, all variables had unit root, then, at first difference all variables were stationary. The lag order selection criteria chose lag 3 (14.7844*) of Akaike information criteria, but the vector error correction model (VECM) was done at lag 2 indicating losing a lag. The co-integration test shows the presence of long run relationship among the variables. The vector error correction model (VECM) estimated from the results obtained shows that all the variables had positive effect on commercial bank’s lending operation. The post estimation test on vector error correction model such as normality of the residuals, serial correlation and heteroscedasticity shows that the VEC model was multivariate normal, no serial correlation and homoscedastic. The inverse root of AR characteristic polynomial shows that the estimated VECM satisfy the stability condition of the diagnostic test. The variance decomposition test shows that the variables have a very weak influence in predicting one another. Recommendations were made based on the result of findings in the study

Zorle Dum Deebom

Papers

Modeling Exchange Rate and Nigerian Deposit Money Market Dynamics Using Trivariate form of Multivariate GARCH Model

Exchange Rate, Interest Rate and Agricultural Export Earnings: An analysis Using Panel Data Vector Autoregressive Model

Modeling the Effect of Monetary Policy on Commercial Bank’s Lending Operation in Nigeria using Vector Error Correction Model (1991- 2020)