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.

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.

scholarly journals Spatial hedonic pricing models for the valuation of irrigation water

2013 ◽  
Vol 11 (4) ◽  
pp. 575-582 ◽  
Keyword(s):  
Irrigation Water ◽  
Spatial Dependence ◽  
Hedonic Pricing ◽  
Error Model ◽  
Hedonic Model ◽  
Spatial Error Model ◽  
Pricing Models ◽  
Spatial Error ◽  
Lagged Dependent Variable ◽  
Value Of Irrigation Water

The main objective of this work is to apply the hedonic pricing method using the methodology of spatial econometrics in order to assess the economic value of irrigation water, as one of the individual attributes of the value of agricultural land parcels. Most of the agricultural land’s value attributes, like neighbor characteristics as well as the availability of irrigation water, exhibit a spatial variability. This means that the application of a conventional hedonic pricing model, which is based on the assumption of spatial stationarity, may be inefficient and probably introduce bias in the estimation of several parameters. In fact, the spatial effect, and in particular the spatial dependence is a determinant of the efficiency and consistency of the hedonic model. Therefore, two spatial hedonic pricing models and a conventional one are formulated and implemented. Spatial dependence is incorporated in the modeling in two ways: a) by including a spatially lagged dependent variable (spatial lag model) and b) by including the spatial dependence of the error term (spatial error model). The two spatial econometric models together with a conventional model of multiple regression are applied in a typical rural area of Greece. A key feature of the proposed approach is that a GIS analysis of land parcels is a basic component of the modeling procedure. Results from this application show that the spatial methods increase the efficiency and consistency and reduce the bias of the parameter estimates. Moreover, the spatial error model provides better results and it is, therefore, preferred in order to estimate the value of irrigation water.

scholarly journals The Contribution of Technology Finance to the Quality of Economic Growth - Empirical Analysis Based on Spatial Econometric Model

2019 ◽  
Author(s):  
Yuming Xu ◽  
Xu Zhou ◽  
Zhiqiang Li
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Econometric Model ◽  
Entropy Method ◽  
Eastern Region ◽  
Promoting Effect ◽  
Spatial Econometric ◽  
Spatial Econometric Model ◽  
The Relationship

(1) Background: Most of the existing studies focus on the evaluation of technology finance; the relationship between technology finance and technology innovation. But there are few studies on the development of technology finance and the quality of economic development in our country; (2) Methods: Based on the panel data of 30 provinces in China, this paper constructs an index system to measure the development of technology finance through the improved entropy method, and tests the spatial correlation of the development of technology finance in China by Moran'I index. According to the test results, this paper constructs a spatial econometric model to empirically analyze the promoting effect of scientific, technological and financial development on high-quality economic development, and analyzes its promoting effect in different regions and different time periods; (3) Results: The results show that the quality of China's economic growth is spatially dependent, and the development of science, technology and finance can significantly promote the quality economic development in China. And the promotion coefficient of the central region is the largest, as well as the coefficient of the eastern region is the smallest. The promotion coefficient was small and not significant before 2015, and was significantly positive after 2015; (4) Conclusions: this paper puts forward the corresponding policy recommendations according to the research results.

scholarly journals Spatial Distribution of Cardio-Vascular Diseases in India

2021 ◽  
Author(s):  
Ayantika Biswas ◽  
Shri Kant Singh ◽  
Jitendra Gupta
Keyword(s):  
Spatial Autocorrelation ◽  
Spatial Dependence ◽  
Vascular Diseases ◽  
Error Model ◽  
Moran’S I ◽  
Spatial Error Model ◽  
Cvd Risk ◽  
Spatial Error ◽  
Moran's I ◽  
Cardio Vascular

Abstract Objective: Cardio-vascular Diseases (CVDs) are a leading cause of death and disease burden across the world, and the burden is only expected to increase as the population ages. The objective of this paper is to explore the patterns of CVD risk factors among women in the late reproductive ages (35-49 years) across 640 districts in India, and investigate the association between area-level socioeconomic factors and CVD risk patterns., using a nationally representative sample of 239,729 women aged 35–49 years from all 36 States/UTs under NFHS-4 (2015–16). Methods: Age-standardized prevalence of CVDs have been calculated, along with 95% CI among women in their late reproductive ages (35–49 years) in India. The spatial dependence and clustering of CVD burden has been examined by Moran's I indices, bivariate Local Indicator of Spatial Autocorrelation (LISA) cluster and significance maps. Ordinary Least Square (OLS) regression has been employed with CVD prevalence as the outcome variable. To consider for spatial dependence, Spatial Autoregressive (SAR) models have been fitted to the data. Diagnostic tests for spatial dependence have also been carried out to identify the best fit model. Results: Higher values of Moran's I imply high spatial autocorrelation in CVD among districts of India. Smoking, alcohol consumption, hailing from a Scheduled Caste background, more than 10 years of schooling, as well as urban places of residence appeared as significant correlates of CVD prevalence in the country. The spatial error model and the spatial lag model are a marked improvement over the OLS model; among the two, the spatial error model emerging to be the most improved of the lot. Conclusions: A broader course of policy action relating to social determinants can be a particularly effective way of CVD risk addressal. Social policy interventions related to health like reduction in inequalities in factors like education, poverty, unemployment, access to health-promoting physical or built-environments are crucial in tackling the long-term effects of CVD inequalities between geographical areas.

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