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Estimation Of Parameter Regression Panel Data Model Using Least Square Dummy Variable Method

Estimasi Parameter Model Regresi Data Panel Menggunakan Metode Least Square Dummy Variable

Jurnal Matematika, Statistika dan Komputasi · Vol. 20 No. 1 (2023) · pp. 221–228

DOI
10.20956/j.v20i1.27530
ISSN
2614-8811, 1858-1382
Published
2023-09-06
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

English

Panel data regression is a set of techniques for modeling the effect of independent variable on the dependent variable of panel data. The parameter estimation in the panel data regression model used the least squares method, but the difference between the intercept and the slope could not be known between time and between cross-section. One of the methods used is the Least Square Dummy Variable method (LSDV). The LSDV method is a method that has the same stages as the least squares method, but uses dummy variable to get different intercept score. This research uses the LSDV method to explain the differences in intercept between cross-sections using balanced panel data, namely the Human Development Index (HDI) data in South Sulawesi 2011-2017 to get fixed effect panel data regression model parameters on that data and the regencies with Average Length of School (ALS) and Life Expectancy (LE) variable that has the most influence on HDI based on the coefficient of determination criteria. According to the results of this research, the score of the coefficient of determination in the panel data regression model using the fixed effect model in each cross-section (regency), there are also three regencies with the highest coefficient of determination, respectively, Gowa, Pare-pare and Bantaeng regency that ALS and LE are able to explain the HDI variables 98.942%, 98.089% and 97.444%.

Bahasa Indonesia

Regresi data panel merupakan sekumpulan teknik untuk memodelkan pengaruh variabel bebas terhadap variabel terikat data panel. Estimasi parameter pada model regresi data panel digunakan metode kuadrat terkecil akan tetapi tidak dapat diketahui perbedaan intersep dan slope baik antar waktu maupun antar cross-section. Salah satu metode yang digunakan ialah Metode Least Square Dummy Variable. Metode LSDV merupakan metode yang tahapannya sama dengan metode kuadrat terkecil, tetapi menggunakan variabel dummy untuk mendapatkan nilai intersep yang berbeda. Penelitian ini menggunakan metode LSDV untuk menjelaskan adanya perbedaan intersep antar cross-section dengan menggunakan data panel seimbang yaitu data Indeks Pembangunan Manusia di Sulawesi-Selatan tahun 2011-2017 untuk mendapatkan penaksi parameter model regresi data panel efek tetap pada data tersebut dan kabupaten mana yang variabel RRL dan AHH yang paling berpengaruh terhadap IPM berdasarkan kriteria koefisien determinasi. Berdasarkan hasil penelitian ini, nilai dari koefisien determinasi pada model regresi data panel menggunakan model efek tetap pada masing-masing cross-section (kabupaten) terdapat juga tiga kabupaten dengan koefisien determinasi tertinggi berturut-turut, kabupaten Gowa, Pare-pare dan Bantaeng yang menunjukkan bahwa RLS dan AHH mampu menjelaskan variabel IPM 98,942%, 98,089% dan 97,444%.

Keywords

Collaboration network of the authors

36 authors · 98 co-authorship links · 1 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Sultan Ageng Tirtayasa University
  • Institut Agama Islam Negeri Kendari
  • STKIP Taman Siswa Bima
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anisa AnisaSultan Ageng Tirtayasa University6
Anna IslamiyatiAffiliation unknown5
A.Muthiah Nur AngrianyAffiliation unknown4
Nirwan IlyasAffiliation unknown3
Siswanto SiswantoAffiliation unknown2
Nurtiti SunusiAffiliation unknown2
Zhazha Alifkhamulki RamdhaniAffiliation unknown1
Samsul ArifinAffiliation unknown1
Andi Sitti Fahmi Riyanti HufainiAffiliation unknown1
Dwicahyo Ramadhan PriyatnaAffiliation unknown1
La Podje TalangkoAffiliation unknown1
Vieri KoerniawanAffiliation unknown1
Dewi Rahma EnteAffiliation unknown1
Andi Kresna JayaAffiliation unknown1
Andi Tenri Riski AmaliaAffiliation unknown1
Sitti SahrimanAffiliation unknown1
Fitri AnnisaAffiliation unknown1
Muhammad FadilAffiliation unknown1
Asnidar AsnidarAffiliation unknown1
Nurul HikmahInstitut Agama Islam Negeri Kendari1
Nasrah SirajangAffiliation unknown1
Fauziah NurhidayahAffiliation unknown1
Anni Ivoni ParapaAffiliation unknown1
Bambang Widjanarko OtokAffiliation unknown1
M. Sjahid AkbarAffiliation unknown1
Nurmiati Nurmiati NurdinAffiliation unknown1
Saleh AFAffiliation unknown1
Hasruni Satya TarumaAffiliation unknown1
Try Widyaiswara HairilAffiliation unknown1
Hasrina HasrinaAffiliation unknown1
Ilyas IlyasSTKIP Taman Siswa Bima1
Georgina Maria TinungkiAffiliation unknown1
Georgina M. TinungkiAffiliation unknown1
Andi Atirah ArumtiwiAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Estimation Of Parameter Regression Panel Data Model Using Least Square Dummy Variable Method</dc:title>
	<dc:title xml:lang="id">Estimasi Parameter Model Regresi Data Panel Menggunakan Metode Least Square Dummy Variable</dc:title>
	<dc:creator xml:lang="en">AHMAD, NUR AMINAH</dc:creator>
	<dc:creator xml:lang="en">Raupong, Raupong</dc:creator>
	<dc:subject xml:lang="en">Panel Data Regression</dc:subject>
	<dc:subject xml:lang="en"> Least Square Dummy Variable Method</dc:subject>
	<dc:subject xml:lang="en">Human Development Index </dc:subject>
	<dc:description xml:lang="en">Panel data regression is a set of techniques for modeling the effect of independent variable on the dependent variable of panel data. The parameter estimation in the panel data regression model used the least squares method, but the difference between the intercept and the slope could not be known between time and between cross-section. One of the methods used is the Least Square Dummy Variable method (LSDV). The LSDV method is a method that has the same stages as the least squares method, but uses dummy variable to get different intercept score. This research uses the LSDV method to explain the differences in intercept between cross-sections using balanced panel data, namely the Human Development Index (HDI) data in South Sulawesi 2011-2017 to get fixed effect panel data regression model parameters on that data and the regencies with Average Length of School (ALS) and Life Expectancy (LE) variable that has the most influence on HDI based on the coefficient of determination criteria. According to the results of this research, the score of the coefficient of determination in the panel data regression model using the fixed effect model in each cross-section (regency), there are also three regencies with the highest coefficient of determination, respectively, Gowa, Pare-pare and Bantaeng regency that ALS and LE are able to explain the HDI variables 98.942%, 98.089% and 97.444%.</dc:description>
	<dc:description xml:lang="id">Regresi data panel merupakan sekumpulan teknik untuk memodelkan pengaruh variabel bebas terhadap variabel terikat data panel. Estimasi parameter pada model regresi data panel digunakan metode kuadrat terkecil akan tetapi tidak dapat diketahui perbedaan intersep dan&amp;nbsp; slope baik antar waktu maupun antar cross-section. Salah satu metode yang digunakan ialah Metode Least Square Dummy Variable. Metode LSDV merupakan metode yang tahapannya sama dengan metode kuadrat terkecil, tetapi menggunakan variabel dummy untuk mendapatkan nilai intersep yang berbeda. Penelitian ini menggunakan metode LSDV untuk menjelaskan adanya perbedaan intersep antar cross-section dengan menggunakan data panel seimbang yaitu data Indeks Pembangunan Manusia di Sulawesi-Selatan tahun 2011-2017 untuk mendapatkan penaksi parameter model regresi data panel efek tetap pada data tersebut dan kabupaten mana yang variabel RRL dan AHH yang paling berpengaruh terhadap IPM berdasarkan kriteria koefisien determinasi. Berdasarkan hasil penelitian ini, nilai dari koefisien determinasi pada model regresi data panel menggunakan model efek tetap pada masing-masing cross-section (kabupaten) terdapat juga tiga kabupaten dengan koefisien determinasi tertinggi berturut-turut, kabupaten Gowa, Pare-pare dan Bantaeng yang menunjukkan bahwa RLS dan AHH mampu menjelaskan variabel IPM 98,942%, 98,089% dan 97,444%.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2023-09-06</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/27530</dc:identifier>
	<dc:identifier>10.20956/j.v20i1.27530</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 20 No. 1 (2023): SEPTEMBER, 2023; 221- 228</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/27530/10279</dc:relation>
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	<dc:rights xml:lang="en">Copyright (c) 2023 Author and publisher</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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