@misc{eprints85526,
           month = {Juli},
           title = {PANEL DATA REGRESSION MODEL PARAMETER ESTIMATION
RANDOM EFFECT MODEL USING THE GENERALIZED LEAST
SQUARE METHOD ON HUMAN DEVELOPMENT INDEX DATA

JAKARTA PROVINCE IN 2019-2023},
          author = {ANDIANA PUTRI SINTA },
         address = {UNIVERSITAS LAMPUNG},
       publisher = {FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM},
            year = {2024},
             url = {http://digilib.unila.ac.id/85526/},
        abstract = {Regression analysis on panel data is a regression technique that utilizes the panel
data structure, which combines information from time series and cross section data.
Panel data regression analysis in economics is usually used for Human
Development Index (HDI) data. HDI is a measure used to assess the success of a
region in developing the quality of life of its population. In panel data regression,
there are three estimation models, namely CEM, FEM and REM. The CEM method
assumes that the intercept and slope in the cross section and time series units are
the same, the FEM method assumes that the intercept is different between cross
section units, while the slope between cross section units remains the same, while
the REM method assumes that differences in unit characteristics and time periods
are accommodated in the residual model. As a result of this study, the best panel
data regression model is using the Random Effect Model (REM) with individual
effects. The variables of life expectancy, school expectancy, number of poor people
and per capita expenditure are able to explain HDI in DKI Jakarta Province by
95.45\%. The panel data regression equation is:
Yit = ?30.607 + 1.2131X1it + 1.0541X2it + 0.001445X3it + 0.00046209X4it

Keywords: Panel Data Regression, HDI, Random Effect Model

ABSTRAK

ESTIMASI PARAMETER MODEL REGRESI DATA PANEL
RANDOM EFFECT MODEL MENGGUNAKAN METODE GENERALIZED
LEAST SQUARE PADA DATA INDEKS PEMBANGUNAN MANUSIA

PROVINSI DKI JAKARTA TAHUN 2019-2023

OLEH

SINTA ANDIANA PUTRI

Analisis regresi pada data panel merupakan suatu teknik regresi yang
memanfaatkan struktur data panel, yang menggabungkan informasi dari data time
series dan cross section. Analisis regresi data panel dalam bidang ekonomi biasanya
digunakan untuk data Indeks Pembangunan Manusia (IPM). IPM adalah ukuran
yang digunakan untuk menilai keberhasilan suatu daerah dalam membangun
kualitas hidup penduduknya. Dalam regresi data panel terdapat tiga estimasi model,
yakni CEM, FEM dan REM. Metode CEM berasumsi bahwa intercept dan slope
pada unit cross section dan time series adalah sama, metode FEM mengasumsikan
bahwa intercept berbeda antar unit cross section, sedangkan slope antar unit cross
section tetap sama, sedangkan metode REM berasumsi bahwa perbedaan
karakteristik unit dan periode waktu diakomodasi pada residual model. Hasil
penelitian ini, model regresi data panel terbaik ialah menggunakan Random Effect
Model (REM) dengan efek individu. Variabel umur harapan hidup, harapan lama
sekolah, jumlah penduduk miskin dan pengeluaran per kapita mampu menjelaskan
IPM di Provinsi DKI Jakarta sebesar 95,45\%. Persamaan regresi data panelnya
adalah:
Yit = ?30.607 + 1.2131X1it + 1.0541X2it + 0.001445X3it + 0.00046209X4it

Kata Kunci: Regresi Data Panel, IPM, Random Effect Model}
}