scholarly journals Environmental regulation, Industrial structure upgrading and Economic growth in Beijing Tianjin Hebei region

2021 ◽  
Vol 235 ◽  
pp. 02021
Author(s):  
Menglu Li
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Environmental Regulation ◽  
Industrial Structure ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model ◽  
The Relationship ◽  
Industrial Structure Upgrading

This paper selects the panel data of 13 cities in Beijing Tianjin Hebei region from 2008 to 2016, and uses the fixed effect model to study the relationship between environmental regulation, industrial structure upgrading and economic growth in Beijing Tianjin Hebei region. The results show that: strengthening environmental regulation can promote the upgrading of industrial structure in Beijing Tianjin Hebei region by reducing the emission of pollutants; the upgrading of industrial structure is conducive to promoting the economic development of Beijing Tianjin Hebei region.

scholarly journals Analysis on the influencing factors of industrial structure upgrading in Northeast China

2021 ◽  
Vol 292 ◽  
pp. 03034
Author(s):  
Dapeng Dong ◽  
Yan Xu ◽  
Guiyan Zhao ◽  
Yihui Qi
Keyword(s):  
Quantile Regression ◽  
Influencing Factors ◽  
Northeast China ◽  
Industrial Structure ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model ◽  
The Government ◽  
Quantile Regression Method ◽  
Industrial Structure Upgrading

Based on the panel data of 34 cities in Northeast China, this paper uses fixed-effect model and quantile regression method to empirically test the influencing factors of industrial structure upgrading. The results show that the government has led the upgrading of the industrial structure in Northeast China, economic growth and investment in fixed assets has inhibitory effect on industrial structure upgrade, the level of opening to the outside world, the financial sector development and the increase of human capital in the northeast has obvious role in promoting industrial structure upgrade. The quantile regression results show that the coefficient of each factor are basically consistent with the estimated results of ordinary panel fixed effect model, which further verifies the robustness of the research conclusions in this paper.

scholarly journals PENERAPAN REGRESI DATA PANEL PADA ANALISIS PENGARUH INFRASTRUKTUR TERHADAP PRODUKTIFITAS EKONOMI PROVINSI-PROVINSI DI LUAR PULAU JAWA TAHUN 2010-2014

2018 ◽  
Vol 11 (1) ◽  
pp. 1-15
Author(s):  
Yosephine Magdalena Sitorus ◽  
Lia Yuliana
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Seemingly Unrelated Regression ◽  
Total Output ◽  
Economic Productivity ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

There is inequality between the economic growth of provinces in Java and outside of Java. The total area of Java  is only 6,77% from total area of Indonesia but the Growth Domestic Product (GDP) based on constant price in 2014, Java contributed 57,8% of the GDP total Indonesia. One cause that made this disparity is the development of infrastructure in outside Java is still weak. The development of infrastructure is a basic element for increasing total output production that later will increase the economic growth. However, there are so many problems that occur in developing the infrastructure in outside of Java. This study aimed to analyze the condition of infrastructure provinces outside Java in 2010-2014. The data used is the secondary data for 27 provinces outside of Java 2010-2014 from BPS. The analytical method used is panel data regression with fixed effect model and Seemingly Unrelated Regression (SUR) Model. Based on the results, the infrastructure that affects economic productivity significantly and positively is road infrastructure, health, and budget. Infrastructure that affects economic productivity significantly and negatively is the educational infrastructure. Water and electricity infrastructure did not significantly affect economic productivity.Keywords: Infrastructure, Economic productivity, Panel Data Regression, Fixed Effect Model

scholarly journals PENENTUAN KARAKTERISTIK PARIWISATA DAN MODEL JUMLAH WISATAWAN UNTUK KABUPATEN/KOTA DI PROVINSI ACEH

2016 ◽  
Vol 16 (1) ◽  
pp. 43-50
Author(s):  
Nurhasanah Nurhasanah ◽  
Nany Salwa ◽  
Nelva Amelia
Keyword(s):  
Panel Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Regional Government ◽  
Tourist Attractions ◽  
Tourist Destinations ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Relationship

Tourism is one of the primary sectors that is expected to increase the regional government income. Therefore there is a need to observe the factors that affect the successfulness of tourism factors and products offered. Tourism products can be tourist destinations, where the characteristics of that particular destination can affect the decisions made by the tourist to return the place again. The characteristics of tourism in Aceh can be analyzed by using biplot analysis. Meanwhile, the effects of tourism characteristics on the number of tourists in Aceh from the year 2008 until 2013 is analyzed using panel data regression analysis that is approached by Fixed Effext Model (FEM). Based on the biplot graph, the cities that are superior in their number of all tourism products are Sabang and Banda Aceh. Cities other than these two cities tend to have a lower number of their tourism products. The biplot graph can explain the relationship between the variables of tourism products by 83.8%. Based on the model of fixed effect panel data, Aceh tourism products that affect the number of tourists in Aceh is the number of accommodations, restaurants, and tourist attractions. Fixed effect model explain correlation between the variables of tourism products to the number of tourists in Aceh by 78.8%.

scholarly journals Daya Saing dan Pertumbuhan Ekonomi Negara Berkembang ASEAN

2020 ◽  
Vol 9 (1) ◽  
pp. 37-44
Author(s):  
Fadeli Yusuf Afif ◽  
Ukhti Ciptawaty
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Panel Data ◽  
Direct Investment ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Labor Participation ◽  
Effect Model ◽  
Asean Countries

The purpose of this study is to look at the condition of the country's competitiveness and its influence on ASEAN economic growth. The data used consists of panel data consisting of time series data for 2009 - 2019 and a cross section of five ASEAN countries with the highest level of competitiveness. The variables used are economic growth, competitiveness, labor participation, and foreign direct investment. The analysis tool used is panel data regression, the Fixed Effect Model (FEM). The results show that competitiveness, labor participation, and foreign direct investment have a positive and significant effect on economic growth in the five developing ASEAN countries.   Keywords: ASEAN, Competitiveness, Economic Growth, and Fixed Effect Model (FEM).

scholarly journals Multidimensional Innovation, Heterogeneity of Property Rights and Enterprise Productivity

2020 ◽  
Vol 214 ◽  
pp. 02045
Author(s):  
Shujun Wang
Keyword(s):  
Panel Data ◽  
Property Rights ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Factor Productivity ◽  
Effect Model ◽  
Almost All ◽  
The Relationship

This paper constructed a fixed effect model of panel data, taking the full factor productivity as a measure of enterprise productivity. This paper empirically studies the effect of multi-dimensional innovation on enterprise productivity, examining the relationship between multi-dimensional innovation level and enterprise productivity of different ownership enterprises. This paper finds that the multidimensional innovation of almost all types of enterprises take a notable promotion role on their productivity on the whole, while the specific dimensions have different effects. In the end, this paper analyzes the causes of this situation, which also proposes the corresponding suggestions.

The impact of institutions on economic growth in selected developing countries: An analysis based on Bayesian panel estimation

2020 ◽  
Vol 4 (4) ◽  
pp. 251-272
Author(s):  
Qasim Shah ◽  
Seema Zubair ◽  
Sundus Hussain
Keyword(s):  
Economic Growth ◽  
Developing Countries ◽  
Panel Data ◽  
Fixed Effect Model ◽  
Data Models ◽  
Fixed Effect ◽  
Estimation Methods ◽  
Panel Data Models ◽  
Effect Model ◽  
The Impact

This paper presents an empirical analysis of the impact of institutions on the economic growth of 27 developing countries during the period 1990-2014. Many creative models of panel data allow variations in slope coefficients both across time and cross-sectional units. All models were established in a Bayesian structure and their performance was tested by using an interesting application of the effect of institution on GDP. Technical details of all these models are given and tools are presented to compare their performance in the Bayesian system. Besides, panel data models and posterior model pools are provided for an insight into the institution's relationship with economic development. The derivation of Bayesian panel data models is included. The previous data has been used in this study and normal gamma prior is used for the models of panel data. 2SLS estimation technique has been used to analyze the classical estimation of panel data models. In the paper, developing countries were viewed as a whole. The study's evaluated results have shown that panel data models are valid Bayesian methodology models. In the Bayesian approach, the results of all independent variables affect the dependent variable significantly and positively. Based on all model standard defects, it is necessary to say that the Fixed Effect Model is the best in Bayesian panel data estimation methods. It was also shown that in comparison to other models, the fixed-effect model has the lowest standard error value.

scholarly journals DETERMINAN PERTUMBUHAN EKONOMI DI PROPINSI ACEH

2015 ◽  
Vol 4 (2) ◽  
Author(s):  
Nujma Faradisi
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Urban District ◽  
Independent Variables ◽  
Urban Districts ◽  
Effect Model ◽  
Aceh Province

This research aims to analyze the effect of own-source revenue, general allocation grant, special allocation fund, and special autonomy fund to economic growth in Aceh district/urban district from 2008 to 2011. To estimate economic growth, this research used the rate of RGDP  growth  for dependent  variable. While own-source revenue, general allocation grant, special allocation fund, and special autonomy funds are research’s  independent  variables.  This study took panel data with Fixed Effect Model (FEM) for the method and seven districts and three urban districts in Aceh Province for the sample. The result shows that economic growth explained by own-source revenue, general allocation grant, special allocation fund, and special autonomy fund by 87,30 percent (Adjusted R2). Then, economic growth able to be effected by own- source revenue, general allocation  grant, special allocation  fund, and  special autonomy fund by 21,64 percent (f-statistic).DOI: 10.15408/sjie.v4i2.2303

scholarly journals The Relationship between Environmental Regulation and Green Total Factor Productivity in China: An Empirical Study Based on the Panel Data of 177 Cities

2020 ◽  
Vol 17 (15) ◽  
pp. 5287 ◽  
Author(s):  
Mingliang Zhao ◽  
Fangyi Liu ◽  
Wei Sun ◽  
Xin Tao
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Inflection Point ◽  
Factor Productivity ◽  
Positive Effects ◽  
Development Level ◽  
The Mean ◽  
The Relationship

Promoting the coordinated development of industrialization and the environment is a goal pursued by all of the countries of the world. Strengthening environmental regulation (ER) and improving green total factor productivity (GTFP) are important means to achieving this goal. However, the relationship between ER and GTFP has been debated in the academic circles, which reflects the complexity of this issue. This paper empirically tested the relationship between ER and GTFP in China by using panel data and a systematic Gaussian Mixed Model (GMM) of 177 cities at the prefecture level. The research shows that the relationship between ER and GTFP is complex, which is reflected in the differences and nonlinearity between cities with different monitoring levels and different economic development levels. (1) The relationship between ER and GTFP is linear and non-linear in different urban groups. A positive linear relationship was found in the urban group with high economic development level, while a U-shaped nonlinear relationship was found in other urban groups. (2) There are differences in the inflection point value and the variable mean of ER in different urban groups, which have different promoting effects on GTFP. In key monitoring cities and low economic development level cities, the mean value of ER had not passed the inflection point, and ER was negatively correlated with GTFP. The mean values of ER variables in the whole sample, the non-key monitoring and the middle economic development level cities had all passed the inflection point, which gradually promoted the improvement of GTFP. (3) Among the control variables of the different city groups, science and technology input and the financial development level mainly had positive effects on GTFP, while foreign direct investment (FDI) and fixed asset investment variables mainly had negative effects.

scholarly journals Do Carbon Emissions and Economic Growth Decouple in China? An Empirical Analysis Based on Provincial Panel Data

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2411 ◽  
Author(s):  
Yu Hao ◽  
Zirui Huang ◽  
Haitao Wu
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Carbon Emissions ◽  
Environmental Kuznets Curve ◽  
Kuznets Curve ◽  
Ekc Hypothesis ◽  
Capita Gross Domestic Product ◽  
Level Of Economic Development ◽  
The Relationship

Global warming has emerged as a serious threat to humans and sustainable development. China is under increasing pressure to curb its carbon emissions as the world’s largest emitter of carbon dioxide. By combining the Tapio decoupling model and the environmental Kuznets curve (EKC) framework, this paper explores the relationship between China’s carbon emissions and economic growth. Based on panel data of 29 provinces from 2007 to 2016, this paper quantitatively estimates the nexus of carbon emissions and economic development for the whole nation and the decoupling status of individual provinces. There is empirical evidence for the conventional EKC hypothesis, showing that the relationship between carbon emissions and per capita gross domestic product (GDP) is an inverted U shape and that the inflection point will not be attained soon. Moreover, following the estimation results of the Tapio decoupling model, there were significant differences between individual provinces in decoupling status. As a result, differentiated and targeted environmental regulations and policies regarding energy consumption and carbon emissions should be reasonably formulated for different provinces and regions based on the corresponding level of economic development and decoupling status.

scholarly journals Analisis Regresi Panel pada Pemodelan Tingkat Kematian Bayi di Provinsi Sulawesi Selatan

2020 ◽  
Vol 2 (2) ◽  
pp. 115
Author(s):  
Syafruddin Side ◽  
S. Sukarna ◽  
Raihana Nurfitrah
Keyword(s):  
Panel Data ◽  
Infant Mortality ◽  
Regression Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Penelitian ini membahas mengenai estimasi parameter model regresi data panel pada pemodelan tingkat kematian bayi di Provinsi Sulawesi Selatan dari tahun 2014 sampai dengan 2015. Data yang digunakan adalah data sekunder dari Dinas Kesehatan Provinsi Sulawesi Selatan yang berupa jumlah kematian bayi, berat bayi lahir rendah, persalinan yang ditolong oleh tenaga kesehatan, penduduk miskin, bayi yang diberi ASI ekslusif dan rumah tangga berperilaku bersih sehat di seluruh Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2014-2016. Analisis data dilakukan dengan menggunakan penghitungan manual dan dengan menggunakan software EViews 9. Pembahasan dimulai dari melakukan estimasi parameter model regresi data panel, menentukan model regresi data panel terbaik, , menguji asumsi model regresi data panel, pengujian signifikansi parameter dan interpretasi model regresi. Dalam penelitian ini diperoleh kesimpulan yaitu estimasi model regresi data panel terbaik dengan pendekatan fixed effect model.Kata kunci:Regresi Data Panel, Kematian Bayi, Fixed Effect Model, Least Square Dummy Variable. This research discusses about parameter estimation of panel data regression model of infant mortality level modelling in South Sulawesi from 2014 to 2015. The data used were secondary data from Dinas Kesehatan Provinsi Sulawesi Selatan in the form of number of infant mortality, low weight of infant, childbirth rescued by health workers, poor population, infants who were given exclusive breast milk and household that behaves well in the whole district/town in South Sulawesi year 2014-2016. Data analysis was performed using the calculation manually and by using EViews 9 software. The discussion started from doing parameter estimation of panel data regression model, determining the best panel data regression model, testing the assumption of panel data regression model, testing the signification of parameter and interpretation of regression model. Conclusion of this research are the estimation of regression model is the best panel data regression model with fixed effects model approach.Keywords:Panel Data Regression, Infant Mortality, Fixed Effect Model, Least Square Dummy Variable.

Sign in / Sign up

Export Citation Format

Share Document