Sacrifice Ratio and Inflation Forecasting: A Case Study of Pakistan

Abstract

It is a debatable issue that high and variable inflation causes the welfare loss while on the other hand reducing inflation generally has some cost and the amount of that cost is measured by the sacrifice ratio. Therefore inflation output trade - off is important for central banks when formulating policy. Sacrifice ratio is the main indicator to measure the real cost of disinflation, calculated as the ratio of the cumulative percentage output loss (the difference between actual and potential output) to the size of disinflation. Thus, the sacrifice ratio measures the real output cost per unit of permanent decrease in inflation. Sacrifice ratio is basically divided into two main categories: time invariant sacrifice ratio and episode specific sacrifice ratio. In time invariant sacrifice ratio we took Philips Curve, structural VAR and the New Philips Curve and in episode specific ratio we took Ball method of sacrifice ratio and Zhang method of sacrifice ratio .This study covers all these methods in detail and the main objective of this study is to calculate the sacrifice ratio at aggregate level as well at disaggregated level. We disaggregate data into three sectors namely the agriculture sector, the manufacturing sector and the services sector. At aggregate level we found a positive sacrifice ratio in almost all the methods but the magnitude of the sacrifice ratio is not large .At disaggregated level the results validate that different sectors have different nature and the sectors which are less sensitive to monetary policy have less sacrifice ratio and vice versa. Inflation forecasting is the important input in formulating Monterey policy to maintain the price stability and fighting against the inflation evils. Keeping the importance of forecasting, the other objective of this study is to forecast inflation using real time data and end of sample data