摘要
Inf<span style="font-family:Verdana;">lation has </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">substantial impact on an economy because it affects the financial value of money and stability in the economy. Government </span><span style="font-family:Verdana;">and non-govern</span><span style="font-family:Verdana;">- </span><span style="font-family:Verdana;">ment policies might be hindered due to the excessive rate of inflation. This paper aims to model and forecast inflation by the Box-Jenkins autoregressive integrated moving average (ARIMA) technique using annual time series data on inflation from 1987 to 2017 in Bangladesh. It is found that ARIMA (2, 1, 0) model is the best optimal to forecast inflation for a period of up to eight years. Graphical tools</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> as well as theoretical tests such as Ljung-Box, Shapiro-Wilk, and runs tests have been used in the model diagnostics.</span>
Inf<span style="font-family:Verdana;">lation has </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">substantial impact on an economy because it affects the financial value of money and stability in the economy. Government </span><span style="font-family:Verdana;">and non-govern</span><span style="font-family:Verdana;">- </span><span style="font-family:Verdana;">ment policies might be hindered due to the excessive rate of inflation. This paper aims to model and forecast inflation by the Box-Jenkins autoregressive integrated moving average (ARIMA) technique using annual time series data on inflation from 1987 to 2017 in Bangladesh. It is found that ARIMA (2, 1, 0) model is the best optimal to forecast inflation for a period of up to eight years. Graphical tools</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> as well as theoretical tests such as Ljung-Box, Shapiro-Wilk, and runs tests have been used in the model diagnostics.</span>
