The Model of Per-Capita Expenditure Figures in Sumatera Selatan uses a Geographically Weighted Panel Regression

The Geographically Weighted Panel Regression (GWPR) is a development of a global regression model where the basic idea is taken from a combination of panel data and GWR. The GWPR model is built from the point approach method, which is based on the position of the coordinates of latitude and longitude. The parameters for the regression model at each location will produce different values. GWPR can accommodate spatial effects, so that it can better explain the relationship between response variables and predictors. The purpose of this study is to compare the GWPR model with the Fixed Gaussian and Adaptive Bisquare weighting functions based on the AIC value. The data used in this study is secondary data taken from the website of the Central Statistics Agency (BPS) in the form of Per-Capita Expenditure Figures in South Sumatra in 2013-2019. This research results that in the case of the Per-Capita Expenditure Rate (AP), it is better to use the GWPR method with a fixed gaussian weighting function in the modeling, where the resulting coefficient of determination is 95.81% rather than adaptive bisquare with a determination coefficient of 93.3%. The factors that influence the Per-Capita Expenditure Rate (AP) in South Sumatra on the fixed gaussian weighting are divided into 6 groups, while the adaptive bisquare is divided into 2 groups.

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MODEL GEOGRAPHICALLY WEIGHTED PANEL REGRESSION (GWPR) DENGAN FUNGSI KERNEL FIXED GAUSSIAN PADA INDEKS PEMBANGUNAN MANUSIA DI JAWA TIMUR

Jurnal Matematika Thales ◽

10.22146/jmt.49230 ◽

2020 ◽

Vol 2 (1) ◽

Author(s):

Dia Cahya Wati ◽

Herni Utami

Keyword(s):

Human Development ◽

Human Development Index ◽

Weighting Function ◽

Average Length ◽

Local Linear Regression ◽

Coefficient Of Determination ◽

Model Parameters ◽

Panel Regression ◽

Spatial Effects ◽

Development Index

The Geographically Weighted Panel Regression (GWPR) model is a com-bination of panel data and GWR. The GWPR model is a development of the globalregression model where ideas are taken from non-parametric regression. This model is alinear regression model that is local (local linear regression) which produces an estima-tor of the model parameters that affects local for each point or location where the datais collected. The purpose of this study is form a GWPR model with a fixed gaussiankernel weighting function in overcoming the problem of spatial effects and geographicalfactors that affect an area to another region. The data used in this study is secondarydata taken from the Central Statistics Agency (BPS) website consisting of the HumanDevelopment Index in East Java 2013-2016. This study produces data for the making ofthe Human Development Index using the GWPR method in the formation of the model,where the coefficient of determination generated is 98,74%.Factors that increase HDI es-pecially Mojokerto Regency are average length of school (RLS), life expectancy (AHH),and the construction expensiveness index (IKK). Keywords: GWPR, Fixed Gaussian, Human Development Index, East Java.

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The Step Construction of Geographically Weighted Panel Regression in Air Polluter Standard Index (APSI) Data

E3S Web of Conferences ◽

10.1051/e3sconf/20187312006 ◽

2018 ◽

Vol 73 ◽

pp. 12006

Author(s):

Budi Warsito ◽

Hasbi Yasin ◽

Dwi Ispriyanti ◽

Arief Rachman Hakim

Keyword(s):

Regression Model ◽

Weighting Function ◽

Weighted Least Squares ◽

Fixed Effect Model ◽

Fixed Effect ◽

Local Linear Regression ◽

Coefficient Of Determination ◽

Panel Regression ◽

Standard Index ◽

Effect Model

Geographically Weighted Panel Regression or GWPR is a local linear regression model that combines GWR model and panel data regression model with considering spatial effect, especially spatial heterogeneity problem. This article is focused on the soft computation of GWPR model using Fixed Effect Model (FEM). Parameter estimation in GWPR is obtain by Weighted Least Squares (WLS) methods and the resulting model for each location will be different from one to another. This study will compare the fixed-effect GWPR model with several weighting functions. The best model is determined based on the biggest coefficient of determination (R2) value. In this study, the model is applied in the Air Polluter Standard Index (APSI) in Surabaya City, East Java. The results of this study indicate that Fixed Effect GWPR model with a fixed exponential kernel weighting function is the best model to describe the APSI because it has the smallest AIC.

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AN EVALUATION OF FINANCIAL PERFORMANCE OF MUNICIPAL CORPORATIONS IN KARNATAKA WITH REFERENCE TO MYSURU AND MANGALURU CITY CORPORATIONS

YMER Digital ◽

10.37896/ymer20.12/54 ◽

2021 ◽

Vol 20 (12) ◽

pp. 569-528

Author(s):

Mahesha N M ◽

◽

Dr. K Nagendrababu ◽

Keyword(s):

Financial Performance ◽

State Government ◽

Capita Income ◽

Secondary Data ◽

Per Capita Income ◽

Secondary Sources ◽

Capita Expenditure ◽

Significant Difference ◽

Development Expenditure ◽

Per Capita

The research study attempts to evaluate the financial performance of Mysuru and Mangaluru City Corporations in Karnataka. The study is based on secondary data, which will be collected through secondary sources of financial statements of Mysuru and Mangaluru city corporation. The data so collected will be tabulated appropriately to achieve the objectives set. Required statistical tools will also be used to test the hypotheses formulated in the study. The per capita income and per capita expenditure were increased in all selected Municipal corporations during the study period 2010-11 to 2019-20. There is no significant difference in per capita income between Mysuru CC and Mangaluru CC, which means per capita income is almost equal in selected Municipal Corporations. The per capita expenditure is also equivalent to Mysuru CC and Mangaluru CC. It also found that the expenditure of selected Municipal Corporation is high compared to their income, which means the selected Municipal Corporation depends on State Government grants and loans. There is a significant difference between the development and non -development expenditure on revenue account of both Mysuru and Mangaluru City Corporations. The Mysuru CC had the highest development expenditure in 2017-18 and became 262.64 crores and lowest by 50.04 crores of Mangaluru CC in 2012-13. The Mysuru CC has the highest non-development expenditure in 2019-20 and became 199.52 crores and lowest by 16.73 crores of Mangaluru CC in 2010-11.

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PENGARUH TENAGA KERJA, INFRASTRUKTUR, PENDAPATAN PERKAPITA DAN INVESTASI INDUSTRI DI KABUPATEN MERAUKE PERIODE TAHUN 2001-2017

Musamus Journal of Economics Development ◽

10.35724/feb.v1i2.1670 ◽

2019 ◽

Vol 1 (2) ◽

pp. 69-79

Author(s):

Romualdus Turu Putra Maro Djanggo ◽

Marthen A I Nahumury

Keyword(s):

Data Processing ◽

Capita Income ◽

Secondary Data ◽

Infrastructure Investment ◽

Coefficient Of Determination ◽

Per Capita Income ◽

Per Capita ◽

Official Data ◽

Research Show ◽

Industrial Investment

The research aims to analyse whether the labour, infrastructure and Percapita income factors influence industrial investments in Merauke District in 2001-2017. The data used in this study is secondary data. The method of collecting data using secondary data from the official data is issued by the Department of Migration and Employment of Merauke District and the official data from the Central Statistics agency of Merauke District. For data processing is done using SPSS 21 program. The results of this research show that labor variables, infrastructure, and per capita income simultaneously affect the value of industrial investment. The result of the coefficient of determination (R²) 25.6% showed that labor, infrastructure, and per capita income variables had no significant effect on increasing industrial investments. The results of this study also showed that the infrastructure variables were influential for the change in the value of industrial investments in Merauke district but the influence gained only on the level of 10% of its siknification. Keywords: Labour, infrastructure, investment value

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ANALISIS FAKTOR YANG BERPENGARUH TERHADAP IPM MENGGUNAKAN REGRESI LINEAR BERGANDA

Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika ◽

10.46306/lb.v2i3.86 ◽

2021 ◽

Vol 2 (3) ◽

pp. 282-291

Author(s):

Zakiyatul Fitriyah ◽

Syafira Irsalina ◽

Aditya Rizq Herlandy K ◽

Edy Widodo

Keyword(s):

Research Method ◽

Secondary Data ◽

Significant Positive Effect ◽

West Java ◽

Capita Expenditure ◽

Study Results ◽

Per Capita ◽

The Republic ◽

Measuring Tool ◽

Positive Effect

Development becomes a tool to achieve the goals of a nation. Meanwhile, economic growth is used as an indicator to determine the success of a country's development. HDI is a measuring tool to determine the level of development. Indonesia's HDI is included in the high category, including West Java and Banten provinces. There are allegations that the Covid-19 pandemic in 2020 affected the factors that formed the HDI. This study aims to determine the description of HDI and the influence of factors forming HDI consisting of AHH, RLS, HLS, and per capita expenditure. The secondary data used is sourced from the Central Statistics Agency (BPS) of the Republic of Indonesia. This research method is multiple regression analysis. Based on the study results, the partial test showed that the variables AHH, RLS, HLS, and per capita expenditure had a significant positive effect on the Regency/City HDI variable in the Provinces of West Java and Banten in 2020

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DETERMINANTS OF PRIVATE DOMESTIC SAVINGS IN NIGERIA (1981- 2015).

International Journal for Innovation Education and Research ◽

10.31686/ijier.vol6.iss2.938 ◽

2018 ◽

Vol 6 (2) ◽

pp. 21-40 ◽

Cited By ~ 1

Author(s):

Otiwu K. ◽

Peter A Okere ◽

Uzowuru L.N

Keyword(s):

Capita Income ◽

Secondary Data ◽

Financial Inclusion ◽

Coefficient Of Determination ◽

Small Scale ◽

Per Capita Income ◽

Long Run ◽

Domestic Savings ◽

Private Savings ◽

Per Capita

This study empirically evaluates the determinants of private domestic savings in Nigeria (1981- 2015). Secondary data were sourced from CBN statistical bulletin and bureau of statistics. Hypotheses were formulated and tested using vector error correction model (VECM) and the test for stationarity proves that the variables are integrated in 1(1) order which implies that unit roots do not exist among the variables. There is also long-run equilibrium relationship between the variables and the result also confirms about 29 percent short-run adjustment speed from long-run disequilibrium. The coefficient of determination indicates that about 78 percent of the variations in private domestic savings are explained by changes in its determinants in Nigeria. The results show that per capita income and financial inclusion are major determinants of private domestic savings in Nigeria. The study therefore recommends that concerted and well articulated efforts should be made to make available and affordable credits to productive investments like small scale industries/businesses as they constitute an integral part of the growth and transformation process of an agro based economy like that of Nigeria this will induce employment, increase financial access and income of the various economic agents which will have a spillover effect on private savings. Secondly, since Per capita income and financial inclusion are the important factors that influence private savings in Nigeria, policy makers can promote growth of per capita income by improving productivity of workers and greater effort should be geared towards sustaining or improving on the financial inclusion strategies.

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The Impact of Village Fund Program on Improving Well-being

JEJAK ◽

10.15294/jejak.v13i2.24395 ◽

2020 ◽

Vol 13 (2) ◽

pp. 345-366

Author(s):

Bagoes Joetarto ◽

Agung Setiawan ◽

Farida Farida

Keyword(s):

Economic Growth ◽

Secondary Data ◽

Well Being ◽

Positive Influence ◽

High Poverty ◽

Capita Expenditure ◽

Before And After ◽

Per Capita ◽

The Impact ◽

The Village

Laws no. 6 of 2014 concerning villages has placed villages at the forefront of development and improvement of community welfare. Villages have been given adequate authority and availability of Village Funds, so that it can manage the village’s potential, solve problems, economic growth, and improve welfare in the village. Researchers will measure changes in expenditu re per capita of the population before and after the implementation of the Village Fund program by conducting statistical analysis on secondary data from 432 districts as a research sample. From the results of analysis using regression panel data, it shows that the intervention of the Village Fund has a positive influence on the increase in expenditure per capita of the rural population. In addition, this study also found that the magnitude of the influence of the Village Fund intervention on per capita expenditure varies by region type. First, an increase in per capita expenditure was found to be grater with better village infrastructure conditions compared to areas with poor village infrastructure. Second, same pattern was also found in regions with low poverty rates compared to regions with high poverty rates. Expenditures per capita rates found higher in regions with low poverty rates compared to regions with high poverty rates.

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PENENTUAN MODEL REGRESI TERBAIK DENGAN MENGGUNAKAN METODE STEPWISE (STUDI KASUS : IMPOR BERAS DI SULAWESI UTARA)

JURNAL ILMIAH SAINS ◽

10.35799/jis.17.2.2017.16834 ◽

2017 ◽

Vol 17 (2) ◽

pp. 80

Author(s):

Selfina Clara Wohon ◽

Djoni Hatidja ◽

Nelson Nainggolan

Keyword(s):

Regression Model ◽

Stepwise Regression ◽

Agricultural Land ◽

Secondary Data ◽

Coefficient Of Determination ◽

North Sulawesi ◽

The People ◽

Stepwise Method ◽

The Government

PENENTUAN MODEL REGRESI TERBAIK DENGAN MENGGUNAKAN METODE STEPWISE (STUDI KASUS : IMPOR BERAS DI SULAWESI UTARA)ABSTRAKIndonesia memiliki lahan pertanian yang cukup besar dan tentulah mampu memenuhi kebutuhan beras masyarakatnya, tetapi pada kenyataan produksi beras di Indonesia belum dapat memenuhi permintaan masyarakat sehingga pemerintah mengambil kebijakkan untuk mengadakan impor beras agar kebutuhan terpenuhi. Penelitian ini bertujuan untuk mengetahui variabel-variabel yang mempengaruhi impor beras di Sulawesi Utara dan menentukan model regresi terbaiknnya. Penelitian dilakukan di Kota Manado, Sulawesi Utara dan berlangsung selama 5 bulan sejak November 2016 sampai April 2017. Data yang digunakan adalah data sekunder tahunan Badan Pusat Statistik yang diolah dari buku Sulawesi Utara dalam Angka 2008-2016. Data yang diperoleh dianalisi dengan Metode regresi Stepwise. Variabel-variabel yang mempengaruhi impor beras di Sulawesi Utara yaitu penerimaan beras dari dalam negeri (X4) dan devisa impor unpaid pada bea dan cukai Bitung (X8) yang membentuk model regresi terbaik Yduga = 26322,228- 0,626X4 + 0.001X8, dengan nilai R-sqr = 93,7% dan R-adj = 91,8%. Variabel-variabel tersebut cukup baik untuk menduga besar jumlah impor beras di Sulawesi Utara.Kata Kunci: Metode Stepwise, koefisien determinasi, beras, Sulawesi Utara. DETERMINING THE BEST REGRESSION MODEL USING STEPWISE METHOD (CASE STUDY: RICE IMPORTS IN NORTH SULAWESI)ABSTRACTIndonesia has a large agricultural land and certainly able to supply for people, but in reality the rice production in Indonesia has not been able to complete the demands of the people, so the government took the policy to import rice. The purpose of this research is to determine the variables that affecting rice imports in North Sulawesi and determine the best regression model. The research was held in Manado City, North Sulawesi and lasted for five months from November 2016 to April 2017. The data used is secondary data of Statistics Indonesia and processed from book North Sulawesi in Figures 2008-2016. The data were analyzed by Stepwise Regression Method. The variables that influence rice import in North Sulawesi are the receipt of domestic rice (X4) and unpaid import devisa at excise Bitung customs and excise office (X8) which make the best regression model Ypredict = 26322,228- 0,626X4 + 0.001X8, with R-sqr = 93,7% and R-adj = 91,8%. These variables are good to estimate the number of rice imports in North Sulawesi.Keywords: Stepwise method, coefficient of determination, rice, North Sulawesi

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PENGARUH PENDUDUK, PDRB PERKAPITA DAN HOTEL TERHADAP PENERIMAAN PAJAK DAERAH KABUPATEN/KOTA DI SUMATERA BARAT

Jurnal Kajian Ekonomi dan Pembangunan ◽

10.24036/jkep.v2i4.10386 ◽

2020 ◽

Vol 2 (4) ◽

Author(s):

Tomo Pramana Putri ◽

Alianis Alianis

Keyword(s):

Regression Model ◽

Total Population ◽

T Test ◽

Gdp Per Capita ◽

Tax Revenue ◽

Panel Regression ◽

The West ◽

Tax Revenues ◽

West Sumatra ◽

Per Capita

Abstract : This study aims to analyze the effect of population, GDP per capita and hotelson local tax revenues in districts / cities in West Sumatra. The data used are secondarydata in the form of panel regression in 19 districts / cities in West Sumatra province. Thesource of this data is the West Sumatra Central Statistics Agency (BPS). The variablesused in this study are population (X1), GDP per capita (X2) and hotels (X3). Themethods used in this research are: (1) Panel Regression Model (2) Classical AssumptionTest (3) t test (4) f test. The results of this study indicate that (1) total population has anegative and significant effect on local tax revenues in regencies / cities in WestSumatra. (2) PDRB Per capita has a positive and significant effect on local tax revenuesin districts / cities in West Sumatra. (3) The number of hotels has a positive andsignificant effect on local tax revenues in districts / cities in West Sumatra.Keywords: Tax Revenue, Population, PDRB Per capita, Hotel.

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Analysis of Dynamic Model of Cigarette Consumption Reduces First Goal of SDGs in Indonesia

KnE Social Sciences ◽

10.18502/kss.v3i26.5386 ◽

2019 ◽

Author(s):

Nur Aini ◽

Roosita Melani Dewi ◽

Adi Musharianto

Keyword(s):

High Performance ◽

System Analysis ◽

Secondary Data ◽

Medium Term ◽

Capita Expenditure ◽

Expenditure Data ◽

Performance System ◽

Per Capita ◽

Input Variables

This research aims to see the extent to which the real conditions of society can be separated from the trap of poverty due to consuming cigarettes. This research uses secondary data which taken from various sources of publication. The variables used are input variables and output variables. Input variables are in the form of community income. Output variables used are average per capita expenditure. Data analysis using Dynamic System Analysis with software of ITHINK ® Ver. 6.01 from the High Performance System (2000). The result of this research indicate that in the condition of the community consuming 1 cigarette per day shows that groups of community are difﬁcult to escape from the trap of poverty until the end of Medium Term and Long Term Development Plan is poor society, almost poor society and middle to lower society. While middle to middle society, middle to upper society and rich society still have an income balance from the beginning of the research year to the next 20 years. While the result of the scenario of consumption of 2 packs of cigarettes per day show besides poor society, almost poor society and middle to lower society are difﬁcult to escape from the trap of poverty, middle to middle society are in poverty for the next 20 years as well. Therefore the goal of the ﬁrst SDGs in Indonesia to eliminate poverty is difﬁcult to achieve.

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