scholarly journals Regression Models for Spatial Data: An Example from Gross Domestic Regional Bruto in Province Central Java

2017 ◽  
Vol 18 (2) ◽  
pp. 213
Author(s):  
Abdul Karim ◽  
Akhmad Faturohman ◽  
Suhartono Suhartono ◽  
Dedy Dwi Prastyo ◽  
Budi Manfaat
Keyword(s):  
Economic Growth ◽  
Spatial Data ◽  
Spatial Modeling ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Error Model ◽  
Transportation Infrastructure ◽  
Spatial Error ◽  
Central Java ◽  
Transportation Infrastructures

The important role of a region's transportation infrastructure strongly affects the economic growth of the region and tends to affect the surrounding areas. The effect is called spillover effect. The aim of the research was to recognize the direct effect and spillover effect (indirect) of transportation infrastructure on the economic growth in Central Java. To identify the spillover effects, it is necessary to recognize the different characteristics of each region which have the implications on the various transportation infrastructures at each region in Central Java. Therefore, the spatial modeling was conducted. In this study, the spatial modeling employed was Spatial Durbin Error Model (SDEM). The SDEM is another form of Spatial Error Model (SEM). It does not allow for lag effects of endogenous variables, but it allows for spatial error and spatial lag on exogenous variables in which it simplifies the interpretations on direct effects and spillover effect. According to SDEM estimates, the transportation infrastructures at the districts/municipalities in Central Java had no significant effect on the outputs at each region where the infrastructures were located and their neighboring districts/cities

Transportation and Urban Development

2018 ◽  
pp. 283-305
Author(s):  
Mehmet Akif Kara
Keyword(s):  
Spillover Effect ◽  
Error Model ◽  
Transportation Infrastructure ◽  
Spatial Error Model ◽  
Test Statistic ◽  
Spatial Econometric ◽  
Spatial Error ◽  
Infrastructure Investments ◽  
Regional Economic Performance ◽  
The Impact

It is noteworthy that there is a substantial literature review that examines the impact of transportation infrastructure on urban and regional economic performance. It is observed that such infrastructure investments are focused on the economic growth as well as the spillover effect in applied studies carried out in this respect. In this study, in which the effects of highway transportation infrastructure on urban output and the spillover effect of these investments are determined using the spatial econometric method, 81 cities in Turkey have been taken into consideration, and according to the results of the study, transportation infrastructure investments in Turkey have been found to contribute positively to urban output. Also, while the Moran's I test statistic reveals the spatial dependence of such investments, the Lagrange multiplier test results also determine the need to use the spatial error model. The spatial error model results reveal the existence of the positive spillover effect of transportation infrastructure investments.

Effects of tourism development on economic growth: An empirical study of China based on both static and dynamic spatial Durbin models

2021 ◽  
pp. 135481662110211
Author(s):  
Honghong Liu ◽  
Ye Xiao ◽  
Bin Wang ◽  
Dianting Wu
Keyword(s):  
Economic Growth ◽  
Spillover Effect ◽  
Tourism Development ◽  
Spillover Effects ◽  
Policy Implications ◽  
Long Term Effects ◽  
Spatial Spillover ◽  
Domestic Tourism ◽  
Inbound Tourism ◽  
Spatial Spillover Effect

This study applies the dynamic spatial Durbin model (SDM) to explore the direct and spillover effects of tourism development on economic growth from the perspective of domestic and inbound tourism. The results are compared with those from the static SDM. The results support the tourism-led-economic-growth hypothesis in China. Specifically, domestic tourism and inbound tourism play a significant role in stimulating local economic growth. However, the spatial spillover effect is limited to domestic tourism, and the spatial spillover effect of inbound tourism is not significant. Furthermore, the long-term effects are much greater than the short-term impact for both domestic and inbound tourism. Plausible explanations of these results are provided and policy implications are drawn.

scholarly journals Spatial Interaction Spillover Effects between Digital Financial Technology and Urban Ecological Efficiency in China: An Empirical Study Based on Spatial Simultaneous Equations

2021 ◽  
Vol 18 (16) ◽  
pp. 8535
Author(s):  
Yaya Su ◽  
Zhenghui Li ◽  
Cunyi Yang
Keyword(s):  
Economic Growth ◽  
Spatial Interaction ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Simultaneous Equations ◽  
Ecological Efficiency ◽  
Core Component ◽  
Coordinated Development ◽  
Three Stage Least Squares ◽  
Financial Technology

As a core component of the digital economy, digital financial technology has a complex interactive and interdependent relationship with ecological efficiency. From the holistic spatial interaction perspective, this paper uses spatial simultaneous equations and generalized spatial three-stage least squares (GS3SLS) to analyze the spatial interaction spillovers between digital financial technology and urban ecological efficiency based on data from 284 Cities in China from 2008 to 2018. The results show that: (1) Digital financial technology and urban ecological efficiency promote each other, and the latter is relatively dominant. (2) Both digital financial technology and urban ecological efficiency have significant spatial spillover effects. (3) Digital financial technology in surrounding cities has a restraining effect on local ecological efficiency, and the improvement of ecological efficiency in surrounding cities has a siphon effect on local digital financial technology. (4) There is spatial and period heterogeneity in the intensity of the spatial interaction spillover effect between the two. With resources and environment increasingly becoming rigid constraints on economic growth, these findings help identify new drivers of regional ecological efficiency and promote the coordinated development of digital finance and green ecology.

scholarly journals Spatial Regression Models: A Systematic Comparison of Different Model Specifications Using Monte Carlo Experiments

2019 ◽  
pp. 004912411988246 ◽  
Author(s):  
Tobias Rüttenauer
Keyword(s):  
Monte Carlo ◽  
Spatial Data ◽  
Regression Models ◽  
Spatial Regression ◽  
Spillover Effects ◽  
Spatial Error ◽  
Monte Carlo Experiments ◽  
Spatial Autoregressive ◽  
Spatial Regression Models ◽  
Variable Bias

Spatial regression models provide the opportunity to analyze spatial data and spatial processes. Yet, several model specifications can be used, all assuming different types of spatial dependence. This study summarizes the most commonly used spatial regression models and offers a comparison of their performance by using Monte Carlo experiments. In contrast to previous simulations, this study evaluates the bias of the impacts rather than the regression coefficients and additionally provides results for situations with a nonspatial omitted variable bias. Results reveal that the most commonly used spatial autoregressive and spatial error specifications yield severe drawbacks. In contrast, spatial Durbin specifications (SDM and SDEM) and the simple spatial lag of X (SLX) provide accurate estimates of direct impacts even in the case of misspecification. Regarding the indirect “spillover” effects, several—quite realistic—situations exist in which the SLX outperforms the more complex SDM and SDEM specifications.

scholarly journals Pengaruh Human Capital Spillover Effects terhadap Produktivitas Industri Pengolahan Kawasan Kedungsepur

2018 ◽  
Vol 5 (2) ◽  
pp. 226-234 ◽  
Author(s):  
Sessa Anata Salam ◽  
Bambang Prishardoyo
Keyword(s):  
Higher Education ◽  
Human Capital ◽  
Manufacturing Industry ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Ordinary Least Squares ◽  
Industrial Workers ◽  
Level Of Education ◽  
Central Java ◽  
Lower Education

Tujuan dari penelitian ini untuk mengetahui terdapat atau tidaknya pengaruh human capital spillover effects terhadap produktivitas industri pengolahan di Kawasan Kedungsepur. Industrialisasi sejak masa orde baru periode 1967-1997 telah mengubah struktur perekonomian Indonesia. Kawasan Kedungsepur menjadi lokasi penelitian dikarenakan terdapatnya potensi dalam bidang industri dibandingkan dengan 8 (delapan) kawasan strategis lainnya di Provinsi Jawa Tengah. Pada tahun 2007-2012 perkembangan PDRB sektor industri pengolahan cenderung mengalami penurunan. Salah satu yang mempengaruhi produktivitas ialah SDM yang berkualitas, sehingga peneliti ingin melihat apakah terdapat pengaruh Human Capital Spillove Effects serta pengaruh dari faktor lainnya seperti tenaga kerja industri dengan tingkat pendidikan rendah dan tingkat pendidikan tinggi, modal industri serta upah terhadap produktivitas industri pengolahan pada Kawasan Kedungsepur. Penelitian ini menggunakan fungsi produksi Cobb-Douglas. Metode analisis yang digunakan berupa Ordinary Least Squares dengan menggunakan regresi data panel. Berdasarkan hasil penelitian tidak ditemukan adanya pengaruh dari tenaga kerja industri dengan tingkat pendidikan rendah. Kesimpulan penelitian ini ialah, ditemukan Human Capital Spillover Effect terhadap produktivitas industri pengolahan pada kawasan Kedungsepur. Tenaga kerja industri pendidikan rendah tidak berpengaruh secara nyata, angkatan kerja di luar industri dengan tingkat pendidikan tinggi, tenaga kerja industri dengan tingkat pendidikan tinggi, modal industri dan upah berpengaruh secara nyata dan positif terhadap produktivitas industri kawasan Kedungsepur. The purpose of this research to determine whether or not the influence of human capital spillover on the productivity of processing industries in the Area Kedungsepur. Industrialization since the ner order during the period 1967-1997 has changed the structure of economic in Indonesia. Kedungsepur became the location of the research because have a potential of manufacturing industry than 8 (eight) other strategic areas in the Province of Central Java. In 2007-2012 GDP growth of manufacturing industry tends to drop in. one of which affect the productivity are qualified human resource, so the researcher wanted to see wether there are affected of human capital spillover effects an the influence of another factors such as industrial workers with low level of education and high level of education levels, industrial capital and wages on the productivity of the manufacturing industry in the region of Kedungsepur.  Based on the result, the industry labor with lower education hasn’t influenced the productivity of manufacturing industry. The conclusion of this research, human capital spillover has effects the productivity of manufacturing industry at Kedungsepur. The industry labor with lower education takes no affect, in other hands the force labor with higher education, the industry labor higher education, capital, and wages have influenced the productivity of manufacturing industry at Kedungsepur with positive.

Fiscal Decentralisation, Provincial Economic Growth and Spillover Effects: A Spatial Panel Data Analysis

2016 ◽  
Vol 55 (4I-II) ◽  
pp. 743-760
Author(s):  
Qasim Raza ◽  
Hafsa Hina
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Spatial Dependence ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Provincial Government ◽  
Data Set ◽  
Spatial Panel ◽  
Fiscal Decentralisation ◽  
Spatial Panel Data

This study examines the spatial dependence, direct and indirect effects of fiscal decentralisation on the provincial economic growth of Pakistan. Due to spatial dependence, spatial econometric technique is applied on the augmented growth of Mankiw, et al. (1992) by incorporating the fiscal decentralisation variable in the theoretical framework. The empirical analysis is based on the spatial panel data set, which is used from 1990 to 2011 of provinces. Model is selected on basis of specific to general and general to specific approach, and decided two-way fixed effects Spatial Durbin model (SDM) is appropriate for our data. We have estimated the SDM by maximum likelihood (bias corrected and random effect) estimation technique, otherwise, if we applied OLS and ignore the spillover effect which makes our estimated parameters biased and inconsistent. Results show that revenue decentralisation has positive, while expenditure decentralisation has negative effect to provincial economic growth. Spillover effects are found to be significant in case of revenue decentralisation and insignificant in case of expenditure. Negative and insignificant spillover effect of expenditure decentralisation is due to weak institutions, lack of intra governmental competition, and absence of political vision which may increase the level of corruption and less accountability. On the basis of econometric analysis, it may be suggested that federal government should transfer the resources to provinces as determined in the 18th amendment, and it is the responsibility of provincial government to train their officials in the area of professional ethics, technical and administrative skills by different programmes. JEL Classification: C31, C33, H3, H50 Keywords: Fiscal Decentralisation, Spatial Econometrics, Revenue, Expenditure

scholarly journals Study of the Spillover Effect on Sport to Chinese Regional Economic Development

2019 ◽  
Vol 10 (5) ◽  
pp. 487
Author(s):  
Huijun Jiang ◽  
Myeong Cheol Choi ◽  
Xinke Leng
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Data Model ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Regional Economic Growth ◽  
Panel Data Model ◽  
Regional Economic ◽  
Incentive Effect

Sports development can lead to the emergence of external economies, which forms part of the spillover effects on regional economic growth under certain conditions. This study uses a sample of 31 provinces in China from 2008–2012 to construct a panel data model to examine the role of sports development in the regional economic growth in the C-D function. The results indicate that sports development indeed brings a good incentive effect to the economy in all areas, which suggests a spillover effect of Chinese sports development that stimulates regional economic growth, but this spillover effect reflects a greater difference between different regions. Overall, Hebei, Jiangxi, Henan, Hubei, Hunan, and Sichuan have the highest coefficient of sports investment on economy, but Jilin is relatively weak.

scholarly journals Spatial Econometric Model on Economic Growth in West Nusa Tenggara

Jurnal Varian ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 153-158
Author(s):  
Siti Soraya ◽  
Baiq Candra Herawati ◽  
Muttahid Shah ◽  
Syaharuddin Syaharuddin
Keyword(s):  
Economic Growth ◽  
Spatial Dependence ◽  
Econometric Model ◽  
Error Model ◽  
Spatial Error Model ◽  
Spatial Econometric ◽  
Spatial Error ◽  
Response Variable ◽  
Spatial Econometric Model ◽  
Capital Value

Gross Regional Domestic Product (GRDP) is a reflection of a region's economic growth. West Nusa Tenggara (NTB) is one of the provinces that contributes to good GRDP for Indonesia. The purpose of this research is to modeling GRDP in NTB using spatial econmetrics. The data used is the GRDP data of each district / city in NTB Province as a response variable and factors that affect the number of workers, capital value and electrification ratio as predictor variables. The results showed that there is a spatial dependence on the district / city GRDP in NTB Province on the error model so that the model formed is the Spatial Error Model (SEM) with a rho of 71.1% and an AIC value of 173.34.

scholarly journals Spatial Modeling for Poverty: The Comparison of Spatial Error Model and Geographic Weighted Regression

2021 ◽  
Vol 12 (1) ◽  
pp. 237-251
Author(s):  
Achi Rinaldi ◽  
Yuni Susianto ◽  
Budi Santoso ◽  
Wahyu Kusumaningtyas
Keyword(s):  
Spatial Modeling ◽  
Spatial Regression ◽  
Evaluation Criteria ◽  
Spatial Models ◽  
Error Model ◽  
Weighted Regression ◽  
Spatial Error Model ◽  
Spatial Error ◽  
Explanatory Variables ◽  
The Relationship

This study aims to analyze poverty using spatial models. The researchers also compared the Spatial Error Model (SEM) and Geographically Weighted Regression (GWR). The comparison of the two models was based on the estimation evaluation criteria and the constructed spatial associations. Spatial regression is considered very appropriate to be used to model the relationship pattern between poverty and explanatory variables when the observed data has a spatial effect caused by the proximity between the observation areas. The spatial dependence of errors on observational data can be overcome using SEM, while the effect of heterogeneity of spatial variance can overcome using GWR.

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