scholarly journals Penanganan Endogenitas Modal Sosial Pada Pemodelan Kemiskinan Rumah Tangga di Indonesia Dengan Metode Two Probit Least Square (2PLS)

2019 ◽  
Vol 8 (1) ◽  
pp. 19-26
Author(s):  
Eko Yulian
Keyword(s):  
Social Capital ◽  
Human Capital ◽  
Regression Analysis ◽  
Poverty Alleviation ◽  
Least Square ◽  
Probit Regression ◽  
Variable Size ◽  
Factors Affecting ◽  
Independent Variables ◽  
Independent Variable

Kemiskinan merupakan salah satu permasalahan mendasar yang telah menjadi perhatian utama berbagai negara di dunia termasuk Indonesia. Agar pengentasan kemiskinan berjalan efektif tentunya perlu diketahui dan diukur kuat pengaruh faktor-faktor yang mempengaruhi kemiskinan. Faktor-faktor tersebut diantaranya adalah modal SDM dan modal sosial. Untuk mengukur kontribusi faktor-faktor tersebut digunakan analisis regresi. Variabel bebas pada penelitian ini bersifat kategorik biner (1=miskin, 0=tidak) sehingga analisis regresi yang bisa digunakan adalah analisis regresi logistik dan probit. Penelitian ini menggunakan regresi probit untuk mengetahui pengaruh modal sosial dan modal SDM terhadap kemiskinan. Pada analisis regresi probit, asumsi yang harus dipenuhi adalah tidak adanya korelasi antara variabel bebas dan error pada model, apabila hal tersebut tidak terpenuhi maka akan muncul permasalahan yang disebut dengan endogenitas yang mengakibatkan hasil taksiran parameter yang dihasilkan bias. Pada penelitian ini diperoleh informasi bahwa variabel modal sosial merupakan variabel endogen sehingga digunakan metode Two Probit Least Square (2PLS) untuk mengatasi permasalahan endogenitas yang terjadi. Berdasarkan hasil regresi probit dengan menggunakan metode 2PLS diperoleh tiga variabel bebas yang berpengaruh negatif terhadap peluang rumah tangga menjadi miskin, variabel-variabel tersebut adalah modal sosial, lama sekolah dan umur. Sedangkan variabel ukuran rumah tangga berpengaruh positif terhadap peluang rumah tangga menjadi miskin di Indonesia. [Poverty is one of the fundamental problems. It has been a major concern of governments in various countries around the world, including Indonesia. In order for poverty alleviation to be effective, it is necessary to know and measured strongly the influence of factors affecting poverty. These factors include human capital and social capital. To measure the contribution of these factors is used regression analysis. The independent variables in this study are binary categorical (1=poor, 0=no) so that regression analysis that can be used is logistic and probit regression analysis. This research uses probit regression to know the influence of social capital and human capital to poverty. In the probit regression analysis, the assumption that must be met is the absence of correlation between the independent variable and error in the model, if it is not fulfilled then the problem will arise called endogeneity which can lead to bias parameter. In this study obtained information that social capital variable is an endogenous variable, so Two Probit Least Square (2PLS) method used to overcome the problem of endogeneity that happened. Based on the results of probit regression using 2PLS method obtained three independent variables that negatively affect the probability of households to be poor, these variables are social capital, school, and age. While the variable size of households positively affects the probability of households being poor in Indonesia.]

scholarly journals Assessing factors affecting FDI in developing Asian countries

2021 ◽  
Vol 9 (2) ◽  
pp. 16-28
Author(s):  
P. Gupta
Keyword(s):  
Random Effect ◽  
Least Square ◽  
Market Size ◽  
Asian Countries ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Fixed Capital Formation ◽  
Effect Regression ◽  
Independent Variable

The paper focuses on various factors that affect the inflow of Foreign Direct Investment in developing countries. The study majorly deals with Asian countries, namely India, China, Myanmar, Nepal, Pakistan, Bangladesh and Bhutan, that are progressing from being aid-dependent to trading giants. The factors affecting FDI are majorly categorised into dependent and independent variables. Here, in this study, the dependent variable considered is FDI inflow, and independent variables are market size, the value of the currency, export, import, gross fixed capital formation, GDP deflator, cost of borrowing and economic reforms. Pooled Ordinary Least Square (OLS), fixed effect and random effect regression analysis is done to ascertain the best regression model and various tests are performed to check the intensity of effect caused by each independent variable on our dependent variable.

scholarly journals Factors Affecting Students’ Decisions Choosing SMA Maitreyawira Batam

2017 ◽  
Vol 3 (2) ◽  
pp. 172
Author(s):  
Emi Lestari
Keyword(s):  
Quality Of Service ◽  
Regression Analysis ◽  
Service Quality ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Significant Influence ◽  
Factors Affecting ◽  
Independent Variables ◽  
Independent Variable

<p>This study examines the quality of service that includes variable Reliability, Responsiveness, Assurance, Empathy and Evidence Direct (Tangible) partially and simultaneously affect the decision of students to choose SMA Maitreyawira Batam. The method of multiple regression analysis used by the researcher is to know and examine how big influence of independent variable which numbers two or more. Multiple regression analysis is used to know the influence of independent variables on dependent variable. The number of samples of this research is 110 students of SMA Maitreyawira Batam. The result of the research shows that there is significant influence of service quality with variable of reliability, responsiveness, assurance, empathy and tangible to student decision to choose SMA Maitreyawira Batam.</p>

scholarly journals Analisis Masalah Heteroskedastisitas Menggunakan Generalized Least Square dalam Analisis Regresi

2019 ◽  
Vol 1 (2) ◽  
pp. 61
Author(s):  
Aditya Setyawan R ◽  
Mustika Hadijati ◽  
Ni Wayan Switrayni
Keyword(s):  
Parameter Estimation ◽  
Regression Analysis ◽  
Linear Regression ◽  
Statistical Method ◽  
Estimation Method ◽  
Least Square ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Regression Parameters ◽  
Independent Variable

Regression analysis is one statistical method that allows users to analyze the influence of one or more independent variables (X) on a dependent variable (Y).The most commonly used method for estimating linear regression parameters is Ordinary Least Square (OLS). But in reality, there is often a problem with heteroscedasticity, namely the variance of the error is not constant or variable for all values of the independent variable X. This results in the OLS method being less effective. To overcome this, a parameter estimation method can be used by adding weight to each parameter, namely the Generalized Least Square (GLS) method. This study aims to examine the use of the GLS method in overcoming heteroscedasticity in regression analysis and examine the comparison of estimation results using the OLS method with the GLS method in the case of heteroscedasticity.The results show that the GLS method was able to maintain the nature of the estimator that is not biased and consistent and able to overcome the problem of heteroscedasticity, so that the GLS method is more effective than the OLS method.

scholarly journals PENERAPAN METODE BOOTSTRAP RESIDUAL DALAM MENGATASI BIAS PADA PENDUGA PARAMETER ANALISIS REGRESI

2014 ◽  
Vol 3 (4) ◽  
pp. 130
Author(s):  
NI MADE METTA ASTARI ◽  
NI LUH PUTU SUCIPTAWATI ◽  
I KOMANG GDE SUKARSA
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Confidence Intervals ◽  
Bootstrap Method ◽  
Least Square ◽  
Prediction Tool ◽  
Analysis Method ◽  
Ordinary Least Square ◽  
Independent Variable ◽  
Parameter Estimators

Statistical analysis which aims to analyze a linear relationship between the independent variable and the dependent variable is known as regression analysis. To estimate parameters in a regression analysis method commonly used is the Ordinary Least Square (OLS). But the assumption is often violated in the OLS, the assumption of normality due to one outlier. As a result of the presence of outliers is parameter estimators produced by the OLS will be biased. Bootstrap Residual is a bootstrap method that is applied to the residual resampling process. The results showed that the residual bootstrap method is only able to overcome the bias on the number of outliers 5% with 99% confidence intervals. The resulting parameters estimators approach the residual bootstrap values ??OLS initial allegations were also able to show that the bootstrap is an accurate prediction tool.

scholarly journals IMPLIKASI PERUBAHAN UNDANG–UNDANG PERPAJAKAN TERHADAP KEPUTUSAN STRATEGI LEVERAGE BAGI PERUSAHAAN YANG TERDAFTAR DI PT. BURSA EFEK JAKARTA

2017 ◽  
Vol 12 (2) ◽  
pp. 227
Author(s):  
Sapari Sapari
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Stock Exchange ◽  
Negative Influence ◽  
Positive Influence ◽  
Independent Variables ◽  
Tax Shield ◽  
Independent Variable ◽  
Debt Tax Shield ◽  
Tax Regulation

This  research  examines the  connection between non debt tax shield and the change of leverage, between level of effective company tax and the change of leverage, and between operation income before depreciation and the change of leverage.This research takes 17 samples of  food and beverages companies listed in Jakarta Stock Exchange from 1st  January 1994 till 31st  December 1999. And this research uses data from 1994 – 1999 for the regression analysis. Multiple regression analysis is used to test hyphothesis 1 (H1), hyphothesis 2 (H2) and hyphothesis 3 (H3). Independent variables in the regression are level of effective company tax, non debt tax shield and operation income before depreciation, whilst independent variable in the regression is leverage.The result of this research proves that (1) non debt tax shield after the amendment of 1994 tax regulation (1995 – 1999) brings positive influence to the leverage change, (2) level of effective company tax after the amendment of 1994 tax regulation (1995 – 1999) brings negative influence to the leverage change, and (3) operation income before  depreciation  after the amendment of 1994 tax regulation (1995 – 1999) brings positive influence to the leverage change.

scholarly journals PENGARUH INFLASI DAN KURS TERHADAP UJRAH DALAM PEMBIAYAAN MUSYARAKAH MUTANAQISAH PADA PT. BANK MUAMALAT INDONESIA, TBK CABANG PEMATANGSIANTAR

2015 ◽  
Vol 1 (1) ◽  
pp. 86
Author(s):  
Nuri Aslami
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression Analysis ◽  
Field Research ◽  
Secondary Data ◽  
Financial Statements ◽  
Multiple Linear Regression Analysis ◽  
Independent Variables ◽  
Qualitative Approaches ◽  
Independent Variable

<p>This study aims to determine how the effects of inflation and exchange rate against <em>ujrah</em>, <em>musyarakah</em>, <em>mutanaqisah</em> PT Bank Muamalat Indonesia, Tbk Branch Pematang Siantar. This research is a field research using quantitative and qualitative approaches. The data used are secondary data, ie., data obtained from the Central Statistics Agency report, Report of Bank Indonesia, and the financial statements of PT Bank Muamalat Indonesia, Tbk Branch Pematang Siantar. The data were processed using SPSS 16. The analysis used is multiple linear regression analysis. The results showed that the inflation and the exchange rate (the independent variable) affects <em>ujrah</em> in <em>Musharaka</em>h financing <em>mutanaqisah</em> (dependent variable). The independent variables in this study could explain the change by 3.4% and the rest (96.6%) is explained by other variables beyond the variables used. Partially, the level of significant 5% and t <sub>table</sub> of 2034, inflation and exchange rate does not significantly affect the <em>Musharakah</em> financing <em>ujrah</em> <em>mutanaqisah</em>. This is demonstrated by the t <sub>value</sub> inflation of 0. 489 and t<sub>exchange</sub> rate of 0899.</p>

scholarly journals Customer Satisfaction in Retail Banking Services in Nepal

2019 ◽  
Vol 12 (1) ◽  
pp. 45-58
Author(s):  
Phul Prasad Subedi
Keyword(s):  
Regression Analysis ◽  
Customer Satisfaction ◽  
Financial Institutions ◽  
Commercial Banks ◽  
Retail Banking ◽  
Descriptive Statistics ◽  
Banking Services ◽  
Factors Affecting ◽  
Independent Variables ◽  
The Relationship

This research mainly focuses on analysing the factors affecting customer satisfaction in retail banking in Nepal. The study adopts descriptive and explorative research design to deal with the fundamental issues associated with various factors of customers’ satisfaction and retail banking. The study is based on questionnaire survey of 200 customers of 10 different “A” class financial institutions, i.e. commercial banks. Descriptive statistics, correlation coefficient and regression analysis have been applied to estimate the relationship between customer satisfaction as dependent variable and service quality variables as independent variables. The empirical evidences indicate that reliability, responsiveness, assurance and tangibles factors have positive and significant impact on customer satisfaction. It reveals that higher the level of responsiveness, reliability, assurance and tangibility higher would be the customer satisfaction.

Determinants of smallholder cattle farmers’ access to high-value cattle markets in the Ngaka Modiri Molema District, South Africa

2016 ◽  
Author(s):  
M. A. Antwi ◽  
N.V. E. Mazibuko ◽  
C. Chagwiza
Keyword(s):  
South Africa ◽  
Regression Analysis ◽  
Social Science ◽  
Regression Analyses ◽  
Probit Regression ◽  
Informal Markets ◽  
Factors Affecting ◽  
Cattle Markets ◽  
Cattle Farming ◽  
Structured Questionnaire

The objective of this study was to determine factors affecting smallholder cattle farmers’ participation in high-value cattle markets in the Ngaka Modiri Molema District, South Africa. A total of 109 smallholder cattle farmers were randomly selected and interviewed by using structured questionnaire. Descriptive and probit regression analysis were performed using the Statistical Package for Social Science. The results revealed that the majority of the farmers: were males, married, not formally educated, had less than 10years of cattle farming experience, did not participate in the most rewarding channels, used informal markets, received higher prices from the cattle markets nearer and regularly used. The statistically significant variables found to influence the cattle farmers’ participation in the high value formal markets from the probit regression analyses were number of heifers (Z=2.742: Sig. 0.006), keep farm-records (Z=2.611: Sig. 0.009), years in cattle farming (Z=-2.451: Sig. 0.014), and slaughtering cattle and selling as carcass (Z=-1.899: Sig. 0.054)

Intraprovincial trip distribution model

1986 ◽  
Vol 13 (4) ◽  
pp. 438-444 ◽  
Author(s):  
Bala Ashtakala ◽  
A. S. Narasimha Murthy
Keyword(s):  
Regression Analysis ◽  
Functional Form ◽  
Distribution Model ◽  
Trip Distribution ◽  
Individual Model ◽  
Independent Variables ◽  
Statistical Measures ◽  
Power Transformations ◽  
Independent Variable ◽  
Validity Tests

A town (or city) in a province generates external trips to other towns and cities for various purposes. A cordon origin–destination (O – D) survey shows the origin and destinations of the external trips of a town. An individual external trip distribution model is developed for a town using the cordon O – D survey data. The external trips are recognized as intra provincial trips and therefore the model is called intraprovincial trip distribution model. The data used in this study is taken from cordon O – D surveys done in Alberta.In the formulation of the model, a functional form that uses a linear relationship between the dependent and the independent variables and power transformations on the independent variable is considered. The parameters in the model are obtained by regression analysis. The models are validated by statistical measures and tests. In this paper, an individual model is developed for each of the seven cities and towns chosen for this study. The formulation and development of the model, regression analysis, and validity tests are described in detail. Key words: cordon survey, intraprovincial trips, model, power transformations, regression analysis, trip distribution.

scholarly journals Mencari Variabel-variabel Yang Mempengaruhi Sikap Mental Entrepreneural (Wirausaha)Pada Pemerintah Kabupaten Serdang Bedagai

2006 ◽  
Vol 6 (2) ◽  
pp. 155
Author(s):  
Arfan Ikhsan
Keyword(s):  
Regression Analysis ◽  
Key Words ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Mental Attitude ◽  
Independent Variables ◽  
Independent Variable

<p class="Style1">This research try to find some variables that influence entrepreneurial mental attitude at government of Serdang Bedagai Regency. independent variable which considered in this research is hierarchy, formalizes, trust, mission, ethics and regulation barriers level. Those independent variables will be able to improve society satisfaction, reduc­tion of level of bureaucracy and improvement of risking tendency. The data of this research collected from organization chart of Serdang Bedagai Regency. Amount of 68 responders participated in this research. Hereinafter this data processed by using multiple regression analysis. The result shows that formalizes, trust, mission, ethics and regulation barriers level have an effect significantly toward society satisfaction and also bureaucracy. Meanwhile risking tendency is significantly influenced by hierarchy, formalizes, mission and ethics.</p><p class="Style1" align="center">Key Words: hierarchy, formalizes, trust, mission, ethics and regulation barriers level</p>

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