Dummy Variable Regression

Case Study: Analyzing the effects of population and poverty indicators on GRDP in East Java Province

EconometricsDummy RegressionData Analysis

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Dummy Variable Regression | Toriqul Muchlissin

Project Overview

This project explores the use of dummy variable regression to analyze the impact of population and poverty indicators on Gross Regional Domestic Product (GRDP) in East Java Province. The analysis aims to understand how various socio-economic factors influence regional economic performance and whether there are significant differences between regency and city areas in contributing to GRDP.

Using a dataset sourced from the Badan Pusat Statistik (BPS) Jawa Timur 2022, the study includes several independent variables, such as:

Population Distribution
Poverty Depth Index (P1)
Poverty Severity Index (P2)
Percentage of Poor Population (PPM)
Poverty Line
Real Expenditure per Capita
Regency/City Dummy Variable

The dependent variable is GRDP, which measures the total value of goods and services produced in a region.

This regression analysis aims to:

Determine the relationship between population-poverty indicators and GRDP, and
Identify whether the type of region (regency or city) significantly affects GRDP.

The findings of this study are expected to inform policymakers by identifying key socio-economic factors that contribute to regional economic growth and evaluating disparities between urban and rural regions in East Java.