PEMODELAN INDEKS HARGA KONSUMEN NEGARA-NEGARA ASEAN DENGAN REGRESI DATA PANEL DINAMIS MENGGUNAKAN METODE ESTIMASI GMM ARELLANO-BOND DAN GMM BLUNDELL-BOND

Dinda Sofiatun Laila, NIM.: 20106010024 (2024) PEMODELAN INDEKS HARGA KONSUMEN NEGARA-NEGARA ASEAN DENGAN REGRESI DATA PANEL DINAMIS MENGGUNAKAN METODE ESTIMASI GMM ARELLANO-BOND DAN GMM BLUNDELL-BOND. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

Preview	Text (PEMODELAN INDEKS HARGA KONSUMEN NEGARA-NEGARA ASEAN DENGAN REGRESI DATA PANEL DINAMIS MENGGUNAKAN METODE ESTIMASI GMM ARELLANO-BOND DAN GMM BLUNDELL-BOND) 20106010024_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf - Published Version Download (3MB) | Preview
	Text (PEMODELAN INDEKS HARGA KONSUMEN NEGARA-NEGARA ASEAN DENGAN REGRESI DATA PANEL DINAMIS MENGGUNAKAN METODE ESTIMASI GMM ARELLANO-BOND DAN GMM BLUNDELL-BOND) 20106010024_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf - Published Version Restricted to Registered users only Download (3MB) | Request a copy

Abstract

Dynamic panel data regression analysis plays an important role in understanding economic phenomena over time, where a variable is influenced by its own value both in the same period and the previous period. The research objective is to evaluate the efficiency of both methods in modeling the Consumer Price Index (CPI) and determine the factors that significantly affect the movement of the ASEAN countries' CPI. This study compares two well-known dynamic panel data estimation methods, namely Generalized Method of Moment Arellano-Bond (GMM Arellano-Bond) and Generalized Method of Moment Blundell-Bond (GMM Blundell-Bond). The data used are secondary data from the World Bank and Trading Economics websites for the period 2013 to 2022. The dependent variable is the CPI, while the independent variables include Gross Domestic Product (GDP), Labor Force Participation Rate (TPAK), and Exports (EKS). The results of the analysis show that the Arellano-Bond GMM tends to be more efficient than the Blundell-Bond GMM, with GDP and ESC as influential variables. The smaller standard error value in the Arellano-Bond GMM estimation method indicates that this method is better in modeling the dynamic relationship between CPI and its influencing factors in ASEAN countries. Although according to Baltagi (2005) the Blundell-Bond GMM is generally considered more efficient for samples with short time periods, the results of this analysis show that for longer periods, the Arellano-Bond GMM provides more efficient results.

Share this knowledge with your friends :

Actions (login required)

View Item