scholarly journals Pengaruh Dana Desa Dan Alokasi Dana Gampong Terhadap Kemiskinan Di Kecamatan Makmur Kabupaten Bireuen

2020 ◽  
Vol 3 (1) ◽  
pp. 11
Author(s):  
Aida Fitri ◽  
Khairil Anwar
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Panel Data ◽  
Cross Section ◽  
Time Series Data ◽  
Panel Data Analysis ◽  
Series Data ◽  
Analysis Method ◽  
Fund Allocation ◽  
Data Analysis Method

This study aims to determine how much Influence funds and village fund allocation have on poverty in Makmur District, Bireuen Regency. This study uses the panel data analysis method. Which is a combination of time-series data from 2015 to 2019, and a cross-section involving 27 villages and results in 135 observations. The results show that village funds have a negative and significant effect on poverty in the Makmur sub-district. Meanwhile, the allocation of village fund has no significant effect on poverty in the Makmur sub-district.Keywords:Village Fund, VillageFund Allocation, Poverty.

scholarly journals Fuzzy panel data analysis

2021 ◽  
Vol 48 (3) ◽  
Author(s):  
Muhammet O. Yalçin ◽  
◽  
Nevin Güler Dincer ◽  
Serdar Demir ◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Panel Data ◽  
Cross Section ◽  
Time Series Data ◽  
Panel Data Analysis ◽  
Series Data ◽  
Percentage Error ◽  
Cross Sectional ◽  
Statistical Assumptions

In statistical and econometric researches, three types of data are mostly used as cross-section, time series and panel data. Cross-section data are obtained by collecting the observations related to the same variables of many units at constant time. Time series data are data type consisted of observations measured at successive time points for single unit. Sometimes, the number of observations in cross-sectional or time series data is insufficient for carrying out the statistical or econometric analysis. In that cases, panel data obtained by combining cross-section and time series data are often used. Panel data analysis (PDA) has some advantages such as increasing the number of observations and freedom degree, decreasing of multicollinearity, and obtaining more efficient and consistent predictions results with more data information. However, PDA requires to satisfy some statistical assumptions such as “heteroscedasticity”, “autocorrelation”, “correlation between units”, and “stationarity”. It is too difficult to hold these assumptions in real-time applications. In this study, fuzzy panel data analysis (FPDA) is proposed in order to overcome these drawbacks of PDA. FPDA is based on predicting the parameters of panel data regression as triangular fuzzy number. In order to validate the performance of efficiency of FPDA, FPDA, and PDA are applied to panel data consisted of gross domestic production data from five country groups between the years of 2005-2013 and the prediction performances of them are compared by using three criteria such mean absolute percentage error, root mean square error, and variance accounted for. All analyses are performed in R 3.5.2. As a result of analysis, it is observed that FPDA is an efficient and practical method, especially in case required statistical assumptions are not satisfied.

scholarly journals Sub Sektor Pariwisata terhadap Pembangunan Daerah di Kabupaten Lumajang

2019 ◽  
Vol 9 (1) ◽  
pp. 51-56
Author(s):  
Herman Diartho Cahyo
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Analysis Method ◽  
Local Revenue ◽  
Descriptive Research ◽  
Data Analysis Method ◽  
Tourism Sector

This research is a Descriptive research which aims to find out how much the level of labor elasticity of tourism subsector in Lumajnag regency, to know contribution of tourism subsector to local revenue (PAD) in Lumajang Regency, and to know the growth of labor absorption in tourism sector in Lumajang regency. The type of data used in this research is secondary data in the form of time series data with the object of research on the tourism subsector in Lumajang District and data obtained from the Department of Tourism, Department of Manpower and Dinas revenue Lumajang District in 2011-2017. Data analysis method used in this research is elasticity and proportion analysis. The results of this study indicate that the ability of the tourism subsector is not much in the absorption of labor that is equal to -1.49 percent of the number of workers who have worked or categorized as inelastic. In addition, the tourism subsector also did not contribute a considerable amount during the period of 2011-2017 to the Regional Original Income of Lumajang Regency which averaged only 1.41 percent. Overall contribution or contribution given by the tourism sector from year to year during the period 2011-2017 tends to decrease.

scholarly journals Determinant of Car Demand in Java Island

2019 ◽  
Vol 8 (1) ◽  
pp. 1-8
Author(s):  
Dyah Candra Kirana ◽  
Prasetyo Ari Bowo
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Cross Section ◽  
Time Series Data ◽  
Panel Data Analysis ◽  
Least Square ◽  
Series Data ◽  
Cross Section Data ◽  
Section Data ◽  
Per Capita

The purpose of this research is to examine factors that affect car demand in Java Island in 2012-2016. The research method used in this research is panel least square The data used in this research is panel data. The panel data consists of time series data (2012-2106) and cross section data (six province in Java Island, those are DKI Jakarta, Jawa Barat, Jawa Tengah, DI Yogyakarta, Jawa Timur, and Banten). Data were obtained from Central Bureau of Statistic Republic of Indonesia (BPS). Data analysis used is panel data analysis. The results showed that income per capita, population, and inflation have simultan effect on car demand in Java Island in 2012-2016. Per capita income has a positive and significant effect on car demand in Java Island in 2012-2016. Population has a positive and significant effect on car demand in Java Island in 2012-2016. Inflation has positive and insignificant effect on car demand in Java Island in 2012-2016.

scholarly journals Determinan Pengangguran Terdidik Lulusan Universitas di Pulau Jawa

2021 ◽  
Vol 10 (3) ◽  
pp. 178-187
Author(s):  
Leni Anjarwati ◽  
Whinarko Juliprijanto
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Cross Section ◽  
Quantitative Methods ◽  
Negative Impact ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Series Data ◽  
Cross Section Data ◽  
Section Data

This study aims to determine the factors that influence educated unemployment in Java. The data used in this study is secondary data using quantitative methods. Data analysis uses panel data analysis which is a combination of time series and cross-section data. The time-series data uses data for the 2015-2019 period and cross-section data from 6 provinces on the island of Java. The results showed that simultaneously all variables had a significant effect on the level of educated unemployment. While partially shows that the variable level of education and PMDN have a significant positive impact on educated unemployment, and the UMR variable has a significant negative impact on educated unemployment.

WHY PANEL DATA?

2005 ◽  
Vol 50 (02) ◽  
pp. 143-154 ◽  
Author(s):  
CHENG HSIAO
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Section ◽  
Human Behavior ◽  
Time Series Data ◽  
Data Modeling ◽  
Data Availability ◽  
Series Data ◽  
Single Cross Section ◽  
Single Cross

We explain the proliferation of panel data studies in terms of (i) data availability; (ii) the heightened capacity for modeling the complexity of human behavior than a single cross-section or time series data can possibly allow; and (iii) challenging methodology. Advantages and issues of panel data modeling are also discussed.

scholarly journals ANALYSIS OF FACTORS AFFECTING COMPANY VALUE (Emperical Study Of Mining Companies Listed On The Indonesia Stock Exchange)

2020 ◽  
Vol 8 (2) ◽  
pp. 185-196
Author(s):  
Mega Silvia Febriana ◽  
Dahlia Br Pinem ◽  
Ardhiani Fadila
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Firm Value ◽  
Stock Exchange ◽  
Panel Data Analysis ◽  
Secondary Data ◽  
Analysis Method ◽  
Significance Level ◽  
Mining Companies ◽  
Data Analysis Method

This research is a quantitative study that examines the factors that affect the value of the company in mining companies listed on the Indonesia Stock Exchange. The dependent variable in this study is firm value. While the independent variables in this study are profitability, leverage, and size. The population in this study are mining companies listed on the Indonesia Stock Exchange in th 2015-2018 period with a total of 47 companies. The sample selection in this study used purposive sampling. The type of data used is secondary data and data analysis method used is panel data analysis method using e-views program 10. The sample used in this study amounted to 18 mining companies listed on the stock exchange. The results of the evaluation panel data analysis using a significance level of 0.05 indicate profitabilits has effect on firm value, while leverage and size have no effectt on firm value.  

scholarly journals Pengaruh Ekspor Ikan Tongkol/Tuna Indonesia Ke Jepang Terhadap Pertumbuhan Ekonomi Di Indonesia Dengan Model Dinamis Regression

2021 ◽  
Vol 4 (1) ◽  
pp. 15
Author(s):  
Devi Andriyani ◽  
Try Wahyu Syahputra
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Variance Decomposition ◽  
Series Data ◽  
Response Analysis ◽  
Large Contribution ◽  
Analysis Method ◽  
One Year

This study aimed to determine the effect of Tuna exports from Indonesia to Japan on the economic growth in Indonesia. This study used time series data during 2002-2015 obtained from the Central Bureau of Statistics. The data analysis method used in this study was the Vector Autoregression (VAR) approach. The results showed that the Indonesian Tuna exports to Japan had a negative and insignificant effect on economic growth. While the results based on the impulse response analysis can be said that when a shock occurs in economic growth, it takes one year so that Tuna exports can return to reach its equilibrium or equilibrium point. Based on the analysis of variance decomposition, it can be concluded that the exports of Tuna make a large contribution to economic growth.Keywords:Economic Growth, Tuna Exports from Indonesia

scholarly journals GRANGER CAUSALITY AND STRUCTURAL CAUSALITY IN CROSS-SECTION AND PANEL DATA

2016 ◽  
Vol 33 (2) ◽  
pp. 263-291 ◽  
Author(s):  
Xun Lu ◽  
Liangjun Su ◽  
Halbert White
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Section ◽  
Conditional Independence ◽  
Time Series Data ◽  
Structural Heterogeneity ◽  
Series Data ◽  
Direct Link ◽  
Structural Effects ◽  
Definition Of

Granger noncausality in distribution is fundamentally a probabilistic conditional independence notion that can be applied not only to time series data but also to cross-section and panel data. In this paper, we provide a natural definition of structural causality in cross-section and panel data and forge a direct link between Granger (G–) causality and structural causality under a key conditional exogeneity assumption. To put it simply, when structural effects are well defined and identifiable,G–non-causality follows from structural noncausality, and with suitable conditions (e.g., separability or monotonicity), structural causality also impliesG–causality. This justifies using tests ofG–non-causality to test for structural noncausality under the key conditional exogeneity assumption for both cross-section and panel data. We pay special attention to heterogeneous populations, allowing both structural heterogeneity and distributional heterogeneity. Most of our results are obtained for the general case, without assuming linearity, monotonicity in observables or unobservables, or separability between observed and unobserved variables in the structural relations.

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