Determining optimal location of new growth centers based on LGP–IRIO model to reduce regional disparity in Indonesia

Pribadi, Didit Okta; Putra, Andi Syah; Rustiadi, Ernan

doi:10.1007/s00168-014-0647-8

Cited by 9 publications

(9 citation statements)

References 13 publications

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“…This creates a challenge on how to manage food demands in various geographical regions of Indonesia. Therefore, considering regional diversity becomes an important factor [55], as stated by Grigg [61], food consumption based on geographical differences factors needs to be studied.…”

Section: Research Areamentioning

confidence: 99%

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Spatial Analysis of Socio-Economic Driving Factors of Food Expenditure Variation between Provinces in Indonesia

2020

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Food security has become one of the global challenges; therefore, monitoring food consumption is required. As food consumption is a resultant of food availability at an affordable price, food expenditure actually is a key indicator to assess food security policy. Particularly, the link of food expenditure with socio-economic factors based on the perspective of spatial connectivity should be understood as nowadays food supply and demand between regions are increasingly connected. This study aims to define socio-economic driving factors of food expenditure that considering spatial connectivity between provinces in Indonesia. Data of household food expenditure and socio-economic factors by province including urbanization level, economic growth, gross domestic regional product (GDRP) per capita, poverty severity index, and unemployment rate were used. The preliminary test on the spatial correlation of food expenditure showed a significant result; thus, a spatial regression approach was employed. The results showed that declining food expenditure did not simply indicate increasing prosperity. Larger income disparity among the poor has become crucial to detect lower food expenditure caused by a lack of income. In addition, the increasing unemployment rate was followed by increasing food expenditure. Despite economic growth, increasing GDRP per capita and urbanization contributing to declining food expenditure, both poverty and unemployment are the main issues that threaten household's ability to afford food. Furthermore, the effect of food expenditure in the neighboring region is also significant, but it shows a contradictory relationship as food expenditure in a region is decreasing when food expenditure in its neighbors is increasing, and vice versa. Therefore, reducing disparities in economic growth, GDRP per capita, urbanization, poverty, and unemployment rate between provinces is also crucial to support more equal food expenditure as well as to achieve the second goal of SDG's (Sustainable Development Goals) in improving food security.

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Section: Research Areamentioning

confidence: 99%

“…It has been planned since 2009 that increasing the flow of goods and services between provinces should be pushed to increase economic growth and equity simultaneously [54]. This is an important matter for Indonesia as an archipelagic country with a high disparity in regional development [55].…”

Section: Introductionmentioning

confidence: 99%

Spatial Analysis of Socio-Economic Driving Factors of Food Expenditure Variation between Provinces in Indonesia

2020

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“…Meskipun model neoklasik yang digagas oleh Solow pada 1956 dimana pertumbuhan supply dalam jangka panjang ditentukan oleh tingkat konsumsi, pertumbuhan modal, tenaga kerja dan kemajuan teknologi (Cheshire & Malecki 2004;Blanchard 2007;Steindl & Tichy 2009) telah mendapatkan berbagai kritik karena tidak mempertimbangkan eksistensi keterkaitan spasial antarwilayah (Cheshire & Malecki 2004), namun model tersebut masih menjadi landasan dalam perumusan kebijakan dan program pembangunan di berbagai negara berkembang (Adisasmita 2008;Priyarsono 2016). Eksistensi keterkaitan spasial antarwilayah dibuktikan oleh berbagai penelitian yang telah dilakukan dengan menggunakan metode pendekatan yang beragam, baik di bidang ekonomi (SAC et al 2005;Suparta 2009;Junaidi et al 2012;Veneri & Ruiz 2013;Pribadi et al 2014;Berdegue et al 2015;Lehtonen et al 2015;Pasaribu et al 2015;Wardhana fet al 2015;Arman et al 2017) maupun di bidang non ekonomi (Pertiwi et al2012;Maggioni et al 2014;Pravitasari et al 2016). Salah satu model pertumbuhan ekonomi wilayah yang terkenal dengan eksistensi keterkaitan spasialnya yaitu model kutub pertumbuhan yang digagas oleh Perroux.…”

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Spillover Spasial Negatif Pertumbuhan Ekonomi Antar Kabupaten/Kota Di Provinsi Jawa Timur

2018

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Various studies have been conducted to conceive the factors of regional economic growth and its nature in order to obtain the right formulation of regional development policy. The main aim of this research is exploring the spatial influence of economic growth in East Java Province. The result of Lagrange Multiplier test shows that the regencies/cities economic growth affects each other in the long term. Parameters estimation on spatial lag model shows that the spatial influence of economic growth inter regencies/cities is negative. These indicate that development activities in East Java Province have not been get synergistic yet.

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“…Resosudarmo and Vidyattama (2006), Akira and Alisjahbana (2002), and Akira and Lukman (1995) discovered regional disparities. Pribadi et al (2015) suggest that regional inequalities are the product of economic policies geared towards growth and generate reverse washing rather than reversal effects in areas. As a strategic strategy for fostering regional equity, they propose new growth poles in Medan, Palembang, Balikpapan, Gorontalo, Makassar, and Ternate.…”

Section: Introductionmentioning

confidence: 99%

Regional Disparity in Western and Eastern Indonesia

Achmad¹,

Prayitno²

2020

IJEBA

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Purpose: This study aims to analyze the regional disparity trend of Indonesia's in 2007-2015 and the factors affecting it. The study aims to encourage the gap to be reduced by appropriate development policies in Indonesia. Approach/Methodology/Design: The study uses panel data from 33 provinces from 2007 to 2015, so 297 observations. The analytical method uses two approaches, descriptive analysis with graphical comparison and panel regression analysis with a fixed-effect model. Findings: The results showed that inequality in the West is higher than inequality in the East. The results also found differences in factors affecting inequality in Western Indonesia Region (WIR) and Eastern Indonesia Region (EIR). The increase in electricity distribution and investment has a significant effect on reducing inequality at the WIR. Meanwhile, the development of road infrastructure has increased inequality in the WIR. There are similarities with different strengths that increasing investment can play a role in reducing regional disparity. Practical Implications: Thus, to reduce regional inequality, the Indonesian government and related parties need to encourage increased investment to develop electricity infrastructure in Western Indonesia and encourage employment in Eastern Indonesia. Originality/Value: There are diverse contributions in each region to the formation of GDP growth nationally. So, it is suspected of having occurred regional inequality in Indonesia. For this reason, research is needed to analyze whether disparities in regional development have occurred.

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Determining optimal location of new growth centers based on LGP–IRIO model to reduce regional disparity in Indonesia

Cited by 9 publications

References 13 publications

Spatial Analysis of Socio-Economic Driving Factors of Food Expenditure Variation between Provinces in Indonesia

Spatial Analysis of Socio-Economic Driving Factors of Food Expenditure Variation between Provinces in Indonesia

Spillover Spasial Negatif Pertumbuhan Ekonomi Antar Kabupaten/Kota Di Provinsi Jawa Timur

Regional Disparity in Western and Eastern Indonesia

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