Pemodelan PDRB Di Provinsi Jawa Tengah Dengan Regresi Panel Dinamis Pendekatan GMM Arrelano-Bond dan Blundell-Bond

Setiadi, Aryo Rachman (2026) Pemodelan PDRB Di Provinsi Jawa Tengah Dengan Regresi Panel Dinamis Pendekatan GMM Arrelano-Bond dan Blundell-Bond. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pertumbuhan ekonomi merupakan indikator utama keberhasilan pembangunan suatu daerah. Di Provinsi Jawa Tengah, masih terdapat ketimpangan Produk Domestik Regional Bruto (PDRB) yang signifikan antar kabupaten/kota. Penelitian ini bertujuan untuk memodelkan pertumbuhan ekonomi (PDRB ADHK) di Provinsi Jawa Tengah menggunakan regresi data panel dinamis dengan pendekatan Generalized Method of Moment (GMM) Blundell-Bond, serta membandingkannya dengan pendekatan GMM Arellano-Bond. Data yang digunakan merupakan data sekunder dari 35 kabupaten/kota di Provinsi Jawa Tengah selama periode tahun 2020 hingga 2024. Variabel prediktor yang digunakan meliputi Penanaman Modal Dalam Negeri (PMDN), Penanaman Modal Asing (PMA), Angka Harapan Hidup (AHH), Rata-rata Lama Sekolah (RLS), dan Tingkat Partisipasi Angkatan Kerja (TPAK). Hasil penelitian menunjukkan bahwa model terbaik yang diperoleh adalah model regresi data panel dinamis dengan pendekatan GMM Blundell-Bond. Variabel yang berpengaruh secara signifikan dan bernilai positif terhadap PDRB adalah PMA, PMDN, dan RLS dengan nilai koefisien determinasi sebesar 99,66%. Berdasarkan model terbaik tersebut, diperoleh nilai short-term effect untuk PMA sebesar 0,0037%, PMDN sebesar 0,0165%, dan RLS sebesar 0,0091%. Sedangkan nilai long-term effect untuk PMA adalah 0,2305%, PMDN adalah 1,2846%, dan RLS adalah 0,5644%.
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Economic growth is a key indicator of a region’s development success. In Central Java Province, there are still significant disparities in Gross Regional Domestic Product (GRDP) between regencies and cities. This study aims to model economic growth (GRDP at constant prices) in Central Java Province using dynamic panel data regression with the Blundell-Bond Generalised Method of Moments (GMM) approach, and to compare this with the Arellano-Bond GMM approach. The data used are secondary data from 35 regencies and cities in Central Java Province covering the period from 2020 to 2024. The predictor variables used include Domestic Investment (PMDN), Foreign Investment (PMA), Life Expectancy (AHH), Average Years of Schooling (RLS), and Labour Force Participation Rate (TPAK). The research results indicate that the best model obtained is a dynamic panel data regression model using the Blundell-Bond GMM approach. The variables that significantly and positively affect GRDP are PMA, PMDN, and RLS, with a coefficient of determination of 99.66%. Based on the best model, the short-term effect values obtained are 0.0037% for PMA, 0.0165% for PMDN, and 0.0091% for RLS. Meanwhile, the long-term effect values are 0.2305% for PMA, 1.2846% for PMDN, and 0.5644% for RLS.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Pertumbuhan Ekonomi, PDRB, Regresi Data Panel Dinamis, GMM Arellano-Bond, GMM Blundell-Bond, Economic Growth, GRDP, Dynamic Panel Data Regression, Arellano-Bond GMM, Blundell-Bond GMM.
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis. H Social Sciences > HA Statistics > HA31.7 Estimation H Social Sciences > HB Economic Theory Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Aryo Rachman Setiadi
Date Deposited:	31 Jul 2026 07:55
Last Modified:	31 Jul 2026 07:57
URI:	http://repository.its.ac.id/id/eprint/140914

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