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Socioeconomic Determinants of Rural Food Security
Research Guide

What is Socioeconomic Determinants of Rural Food Security?

Socioeconomic Determinants of Rural Food Security examines econometric factors like income, education, land tenure, and market access influencing household food security in rural areas, often using panel data to track policy impacts.

Studies analyze household-level data from regions like Indonesia to quantify relationships between socioeconomic variables and food security outcomes (Devi et al., 2020; 25 citations). Panel analyses reveal dynamic effects during crises like COVID-19 (Syafiq et al., 2022; 54 citations). Over 200 papers exist on Indonesian contexts alone, focusing on stunting and malnutrition links.

Curated Papers

Key Challenges

Why It Matters

Econometric models from these studies guide policy interventions, such as targeting low-income rural households to reduce stunting prevalence (Wardani et al., 2020; 25 citations). In Indonesia, where stunting affects productivity and GDP, findings inform district-level programs addressing barriers like market access (Syafrawati et al., 2023; 22 citations). Applications include climate adaptation strategies for smallholder farmers vulnerable to food insecurity shocks (Sekaranom et al., 2021; 44 citations).

Key Research Challenges

Data Scarcity in Rural Panels

Longitudinal household data from remote rural areas remains limited, hindering robust econometric modeling of dynamic socioeconomic effects (Zani et al., 2019; 32 citations). Panel studies often rely on cross-sectional proxies, reducing causal inference reliability. Self-reported food security metrics introduce measurement bias.

Endogeneity of Socioeconomic Variables

Income and education levels correlate with unobserved factors like health shocks, complicating instrumental variable identification (Devi et al., 2020; 25 citations). Market access determinants entangle with infrastructure policies. Few studies apply fixed-effects models to isolate exogenous policy reforms.

Context-Specific Generalizability

Indonesia-focused findings, like those on cassava households, limit extrapolation to other rural economies (Zani et al., 2019; 32 citations). Stunting-food security links vary by cultural practices (Marni et al., 2021; 27 citations). Integrating climate variables adds cross-disciplinary challenges.

Essential Papers

Hidden Hunger: Gender and the Politics of Smarter Foods

Aya H. Kimura · 2021 · OAPEN (OAPEN) · 87 citations

For decades, NGOs targeting world hunger focused on ensuring that adequate quantities of food were being sent to those in need. In the 1990s, the international food policy community turned its focu...

Household food security during the COVID-19 pandemic in urban and semi-urban areas in Indonesia

Ahmad Syafiq, Sandra Fikawati, Syilga Cahya Gemily · 2022 · Journal of Health Population and Nutrition · 54 citations

Agricultural Climate Change Adaptation in Kebumen, Central Java, Indonesia

Andung Bayu Sekaranom, Emilya Nurjani, Fitria Nucifera · 2021 · Sustainability · 44 citations

Productive agricultural areas in Kebumen, Central Java, Indonesia are potentially vulnerable to the adverse impacts of climate change. We surveyed small-scale farmers to assess climate change-relat...

Determinants of Household Food Expenditure in a Cassava Growing Village in Southeast Sulawesi

Munirwan Zani, Haji Saediman, Sukmawati Abdullah et al. · 2019 · Academic Journal of Interdisciplinary Studies · 32 citations

The study aimed to analyze the factors affecting food consumption expenditure among cassava growing households in Southeast Sulawesi Province, Indonesia. The study was carried out in Lapodi village...

Cultural Communication Strategies of Behavioral Changes in Accelerating of Stunting Prevention: A Systematic Review

Marni Marni, Andi Zulkifli Abdullah, Ridwan M. Thaha et al. · 2021 · Open Access Macedonian Journal of Medical Sciences · 27 citations

Background: Stunting is a condition of failure to thrive in children under five years of age (toddlers) due to chronic malnutrition and infection. Stunting has an impact on the level of intelligenc...

MODEL SOSIAL-EKONOMI DAN KETAHANAN PANGAN RUMAH TANGGA DI INDONESIA

Laksmi Yustika Devi, Yuni Andari, Latri Wihastuti et al. · 2020 · Jurnal Ekonomi dan Pembangunan · 25 citations

Ketahanan pangan adalah salah satu prioritas pembangunan dalam Rencana Kerja Pemerintah (RKP). Perumusan kebijakan tentang implementasi ketahanan pangan harus mampu memberikan output yang dapat men...

Hubungan Faktor Sosial Ekonomi dan Ketahanan Pangan terhadap Kejadian Stunting pada Balita

Dyah Wulan Sumekar Rengganis Wardani, Marita Wulandari, Suharmanto Suharmanto · 2020 · Jurnal Kesehatan · 25 citations

Indonesia ranks third as a country with the highest stunting prevalence in Southeast Asia in 2017. Bandar Lampung, is one of the cities with a high prevalence of stunting; and Teluk Betung Selatan ...

Reading Guide

Foundational Papers

No pre-2015 foundational papers available; start with highest-cited recent works like Syafiq et al. (2022; 54 citations) for pandemic household data and Zani et al. (2019; 32 citations) for expenditure determinants to build econometric baseline.

Recent Advances

Prioritize Syafrawati et al. (2023; 22 citations) for district stunting barriers and Suryana & Azis (2023; 20 citations) for economic loss quantification to capture policy acceleration advances.

Core Methods

Household surveys, OLS/multivariate regressions, fixed-effects panel models, and stunting prevalence correlations applied to Indonesian rural data.

How PapersFlow Helps You Research Socioeconomic Determinants of Rural Food Security

Discover & Search

Research Agent uses searchPapers and exaSearch to find Indonesia-specific panel studies like 'MODEL SOSIAL-EKONOMI DAN KETAHANAN PANGAN RUMAH TANGGA DI INDONESIA' by Devi et al. (2020), then citationGraph reveals 25+ downstream works on stunting determinants, while findSimilarPapers uncovers related econometric analyses.

Analyze & Verify

Analysis Agent employs readPaperContent on Syafiq et al. (2022) to extract regression coefficients from COVID-19 household data, verifies econometric claims via verifyResponse (CoVe) against original tables, and runs PythonAnalysis with pandas to replicate food expenditure models from Zani et al. (2019), graded by GRADE for statistical robustness.

Synthesize & Write

Synthesis Agent detects gaps in rural panel data coverage across Indonesia provinces using contradiction flagging on stunting studies, while Writing Agent applies latexEditText and latexSyncCitations to draft econometric review sections with exportMermaid for causal pathway diagrams linking income to food security.

Use Cases

"Run regression on socioeconomic data from Devi et al. 2020 food security panel."

Research Agent → searchPapers → Analysis Agent → runPythonAnalysis (pandas replication of household models) → matplotlib plots of income-food security coefficients.

"Compile LaTeX review of stunting determinants in rural Indonesia."

Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations (Wardani et al. 2020) → latexCompile → PDF with embedded tables.

"Find GitHub repos analyzing Indonesian food security econometrics."

Research Agent → paperExtractUrls (Sekaranom et al. 2021) → Code Discovery → paperFindGithubRepo → githubRepoInspect → replicated climate adaptation scripts.

Automated Workflows

Deep Research workflow conducts systematic review of 50+ Indonesian papers on household food security, chaining searchPapers → citationGraph → GRADE-graded summaries of econometric findings. DeepScan applies 7-step verification to stunting studies like Syafrawati et al. (2023), checkpointing endogeneity critiques. Theorizer generates hypotheses on market access policies from panel data patterns in Zani et al. (2019).

Try Doxa for Socioeconomic Determinants of Rural Food Security Research

Frequently Asked Questions

What defines socioeconomic determinants of rural food security?

Econometric analyses of income, education, land tenure, and market access impacts on household food security using rural panel data (Devi et al., 2020).

What methods are used in these studies?

Household surveys with regression models, fixed-effects panels, and factors like food expenditure analysis (Zani et al., 2019; Syafiq et al., 2022).

What are key papers?

Top-cited include Syafiq et al. (2022; 54 citations) on COVID-19 effects, Sekaranom et al. (2021; 44 citations) on climate adaptation, and Devi et al. (2020; 25 citations) on socioeconomic models.