Abstract:
Most free market economies worldwide depend heavily on demand and
supply, which is influenced by exchange rates. As a developing country, Sri
Lanka should emphasise exchange rates more than other factors to maintain
its economic sustainability. It is important to study the characteristics and
behaviour of exchange rates to maintain sustainability. Studies show that
monetary and non-monetary factors affect the exchange rate. As a result,
currency exchange rates frequently exhibit nonlinear trends, including sharp
fluctuations induced by events such as the recent scenario of the sudden
devaluation of the Sri Lankan rupee in early 2022. Modelling exchange rate
data under these nonlinear tendencies is difficult, and this difficulty is made
challenging by the abrupt shifts in the overall trend brought on by unforeseen
disruptions. On that account, the combination of semi-parametric and
interrupted time series models was proposed to develop a flexible model that
describes the exchange rate movement in Sri Lanka. The Bayesian approach
was employed for model fitting with R2Winbugs because it enables rigorous
handling of uncertainty. The next value of the exchange rate was obtained by
applying first-order bivariate Taylor series approximation to the mean
response of the model. The result from the posterior predictive evaluation
shows that the developed model accurately captured the trends and variability
of the exchange rate. Furthermore, all model parameters are significant,
indicating that the monetary (inflation, trade balance, tourist arrivals) and nonmonetary
(sudden devaluation of Sri Lankan rupee) variables are important
for studying exchange rate variabilities. The findings suggest that the
developed model provides information about predicting and forecasting the
future exchange rate movement in Sri Lanka. These predictions and forecast
values would help to balance the economic sustainability in Sri Lanka.
