Subject Area

Economics

Description

This project estimates the Phillips curve using disaggregated US data. The panel model for this project was created using relative unemployment rates and metropolitan regional price parities for all items (RPP) for each state from 2008-2018. The relative unemployment rate was created for each state by taking the state level of unemployment and dividing it by the US national unemployment rate. The metropolitan price parity was created by taking the Consumer Price Index (CPI) for all metropolitan areas in a state and a dividing it by the US national CPI for all metropolitan areas in the US. The dependent variable is metropolitan RPP, and the independent variables are the relative unemployment rate, a lagged unemployment rate, and a lagged metropolitan RPP. During the time-period of 2008-2018, the results suggest there is an inverse relationship to the disaggregated Philips Curve. However, the aggregated Philips Curve is flat over this same time period. I discuss why a disaggregated approach allows for identification of the Phillips curve that is not found using aggregate data.

Share

Import Event to Google Calendar

COinS
 
Apr 26th, 12:00 AM Apr 26th, 12:00 AM

Disaggregated Phillips Curve Regression

This project estimates the Phillips curve using disaggregated US data. The panel model for this project was created using relative unemployment rates and metropolitan regional price parities for all items (RPP) for each state from 2008-2018. The relative unemployment rate was created for each state by taking the state level of unemployment and dividing it by the US national unemployment rate. The metropolitan price parity was created by taking the Consumer Price Index (CPI) for all metropolitan areas in a state and a dividing it by the US national CPI for all metropolitan areas in the US. The dependent variable is metropolitan RPP, and the independent variables are the relative unemployment rate, a lagged unemployment rate, and a lagged metropolitan RPP. During the time-period of 2008-2018, the results suggest there is an inverse relationship to the disaggregated Philips Curve. However, the aggregated Philips Curve is flat over this same time period. I discuss why a disaggregated approach allows for identification of the Phillips curve that is not found using aggregate data.