Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy Design
ABSTRACT This paper contributes a new paradigm for international agricultural development research. It uses machine learning techniques to aid expert diagnosis of development problems in conjunction with New Structural Economics (NSE) to analyse and design policies to enable effective rural transfor...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-05-01
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| Series: | Asia & the Pacific Policy Studies |
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| Online Access: | https://doi.org/10.1002/app5.70016 |
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| author | Dong Wang Chunlai Chen Christopher Findlay Jikun Huang Justin Yifu Lin Abedullah Mohammad Jahangir Alam Abid Hussain Nunung Nuryartono Tahlim Sudaryanto David Shearer |
| author_facet | Dong Wang Chunlai Chen Christopher Findlay Jikun Huang Justin Yifu Lin Abedullah Mohammad Jahangir Alam Abid Hussain Nunung Nuryartono Tahlim Sudaryanto David Shearer |
| author_sort | Dong Wang |
| collection | DOAJ |
| description | ABSTRACT This paper contributes a new paradigm for international agricultural development research. It uses machine learning techniques to aid expert diagnosis of development problems in conjunction with New Structural Economics (NSE) to analyse and design policies to enable effective rural transformation. It conducts a multi‐country, multi‐regional, multi‐level and multi‐dimensional analysis in Bangladesh, China, Indonesia, and Pakistan to identify stage segmentations of rural transformation and examine stagewise associate policies and applicable learnings across each dimension. By presenting structured stages of rural transformation, we provide guidance on designing dynamic comparative‐advantage‐adapting policies that are able to adapt at each stage. This analytical procedure can serve other relevant agricultural development studies. |
| format | Article |
| id | doaj-art-01701c75ceb242c6a656a9ecea102862 |
| institution | OA Journals |
| issn | 2050-2680 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Asia & the Pacific Policy Studies |
| spelling | doaj-art-01701c75ceb242c6a656a9ecea1028622025-08-20T01:56:56ZengWileyAsia & the Pacific Policy Studies2050-26802025-05-01122n/an/a10.1002/app5.70016Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy DesignDong Wang0Chunlai Chen1Christopher Findlay2Jikun Huang3Justin Yifu Lin4Abedullah5Mohammad Jahangir Alam6Abid Hussain7Nunung Nuryartono8Tahlim Sudaryanto9David Shearer10Crawford School of Public Policy Australian National University Canberra AustraliaCrawford School of Public Policy Australian National University Canberra AustraliaCrawford School of Public Policy Australian National University Canberra AustraliaChina Centre for Agricultural Policy (CCAP) School of Advanced Agricultural Sciences Peking University Beijing ChinaInstitute of New Structural Economics Peking University Beijing ChinaPakistan Institute of Development Economics (PIDE) Islamabad PakistanDepartment of Agribusiness and Marketing Bangladesh Agricultural University Mymensingh BangladeshSocial Sciences Research Institute (SSRI) Pakistan Agricultural Research Council‐National Agricultural Research Centre Islamabad PakistanFaculty of Economics and Management IPB University West Java IndonesiaCentre for Behavioural and Circular Economy National Research and Innovation Agency (BRIN) Jakarta IndonesiaFenner School of Environment and Society Australian National University Canberra AustraliaABSTRACT This paper contributes a new paradigm for international agricultural development research. It uses machine learning techniques to aid expert diagnosis of development problems in conjunction with New Structural Economics (NSE) to analyse and design policies to enable effective rural transformation. It conducts a multi‐country, multi‐regional, multi‐level and multi‐dimensional analysis in Bangladesh, China, Indonesia, and Pakistan to identify stage segmentations of rural transformation and examine stagewise associate policies and applicable learnings across each dimension. By presenting structured stages of rural transformation, we provide guidance on designing dynamic comparative‐advantage‐adapting policies that are able to adapt at each stage. This analytical procedure can serve other relevant agricultural development studies.https://doi.org/10.1002/app5.70016Huang segmentationmachine learningnew structural economicsrural developmentrural transformation |
| spellingShingle | Dong Wang Chunlai Chen Christopher Findlay Jikun Huang Justin Yifu Lin Abedullah Mohammad Jahangir Alam Abid Hussain Nunung Nuryartono Tahlim Sudaryanto David Shearer Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy Design Asia & the Pacific Policy Studies Huang segmentation machine learning new structural economics rural development rural transformation |
| title | Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy Design |
| title_full | Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy Design |
| title_fullStr | Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy Design |
| title_full_unstemmed | Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy Design |
| title_short | Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy Design |
| title_sort | stage segmentation of rural transformation and comparisons among bangladesh china indonesia and pakistan combining machine learning and new structural economics to facilitate international agricultural development and policy design |
| topic | Huang segmentation machine learning new structural economics rural development rural transformation |
| url | https://doi.org/10.1002/app5.70016 |
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