Disaggregated Analysis Of Phillips Curve In Pakistan - ASJED, ROOMA; ALAM, Dr. SHAISTA (The journal of contemporary issues in business and government, 2021)
This study has estimated disaggregated Phillips Curve (PC) in case of Pakistan for food, nonfood and core inflation using annual time series data. The main objective of the study is to compare traditional and open economy Phillips curves using global output gap as external determinant of inflation. The study has estimated global slack hypothesis by augmenting traditional PC with global output gap as measures of global determinant. The accurate measurement of slope of PC has significant role in effective monetary policy formulation to control inflation through managing aggregate demand. There is abundant literature investigating whether Phillips curve still holds, weakened or strengthened as it used to be before 1990. Although less focused in case of Pakistan, for other countries the literature shows evidence of flattening of PC due to many reasons mainly globalization. The results of this study indicate existence of global slack hypothesis where both domestic and global output gaps affect overall inflation in Pakistan positively and significantly. However, when estimated for food and nonfood inflation separately for the period 1976-2019, domestic output gap in presence of global output gap does not affect nonfood inflation in Pakistan. Similarly, for core inflation domestic output gap in presence of global output gap does not affect core inflation in Pakistan. This finding is consistent with existing literature arguing that central banks’ monetary policy intervention significantly affects relation between domestic output gap and core inflation. The results have also indicated that global economic crisis 2008 positively affected overall, food, nonfood and core inflation in Pakistan. The main policy implication of the study is that demand management policies in Pakistan need to be accompanied with supply side price controlling measures considering global economic factors.