Abstract:
The study analysed the result of exchange rate’s effect on export performance in
Tanzania whereby time series data in quarterly statistical form employed from 2001 to
2016. The study used Pearson correlation analysis for Casual relationship, unit source
test for stationary assessment, cointegration test to show if cointegration is present.
Also, the study employed Vector error correction model to show either short run or
long run. Similarly, this study engaged the Vector autoregressive model to capture
linear interdependencies (optimal lag) between the variables from the data. The study
findings revealed that exchange rate, , gross domestic product as well as industrial
production index show to have the strong positive relationship with export
performance.
Furthermore, all variables became stationary after being differenced once (at order 1).
Then, both “max” statistic and “trace” statistic supports the existence of cointegration
and the total of cointegrating calculations is single. Moreover, all the variables found
that exchange rate at lag 1, 2 and 3 jointly influence export performance in a short run.
Also, it was found that industrial production index at lag 1, 2 and 3 jointly influence
export performance in a short run. Likewise, gross domestic product at lag 1, 2 and 3
jointly found to influence performance on export in a short run. This implies that there
is a short run relationship between exchange rate, industrial production index and
gross domestic product to export performance..
Therefore, there is a positive trend of export performance and hence, with these results,
deliberate devaluation of shilling can do well towards boosting exports; this is in line
with Marshall-Lerner Condition.
