A Computational Model for Assessing the Impact of Policies on Reducing Gender Disparity in Land Ownership and Tenure Security

Core Concepts

A computational model to quantify the impact of government policies and agency actions on minimizing the gender disparity in land acquisition and tenure security, accounting for cultural and socioeconomic factors.

Abstract

The content introduces the Sarafina score, a metric to evaluate the effectiveness of policies aimed at addressing the gender asset gap, particularly in the context of land acquisition and tenure security. The key points are:

1. Gender disparity in land ownership is a significant issue globally, with cultural and social norms playing a major role in limiting women's access to land. While some regions have made progress, the problem persists in many parts of the world.

2. Current approaches to measuring gender asset gap often fail to capture the nuances of cultural differences and the impact of governmental/corporate policies. The Sarafina score aims to fill this gap by incorporating these factors.

3. The Sarafina score rewards the enactment of new policies that address the gender disparity problem, proportional to their effectiveness. It accounts for the time-delayed impact of policies, assigning a penalty based on the gap between the observed and projected reduction in the gender asset gap.

4. The policy impact is estimated using a probabilistic model that leverages a set of proxy indicators, such as economic GDP, education gender ratio, domestic violence, and judicial effectiveness, to predict the expected reduction in the gender asset gap.

5. The authors demonstrate the application of the Sarafina score to assess the impact of policies in Brazil and Mexico, showing how it can be used to track the progress of interventions over time.

Stats

Women's land ownership in Brazil:

2000: 11%
2006: 10.2%
2017: 14.8%
Women's land ownership in Mexico:

1984: 13%
1996: 22%
2002: 22.4%

Quotes

"Essentially, the impact of policy in addressing the gender disparity problem is uneven i.e., similar policies might have varying effectiveness in different geographical regions. As such, a framework for subjective policy impact quantification is needed."
"The Sarafina score is designed to predict policy performance and weigh the effects of governmental and corporate action favorably against the gender gap problem even when the nominal values do not yet reflect strongly in that regard."

Key Insights Distilled From

A computational model for gender asset gap management with a focus on gender disparity in land acquisition and land tenure security

by Oluwatosin O... at arxiv.org 04-16-2024

https://arxiv.org/pdf/2404.09164.pdf

Deeper Inquiries

How can the Sarafina score be extended to incorporate intersectional factors beyond gender, such as race, class, and ethnicity, to provide a more comprehensive assessment of asset disparities?

To extend the Sarafina score to incorporate intersectional factors beyond gender, such as race, class, and ethnicity, a multi-dimensional approach is necessary. This would involve identifying key indicators specific to each intersectional factor that contribute to asset disparities. For race, indicators could include historical discrimination in land ownership, access to financial resources, and systemic barriers. Class-related indicators may encompass income levels, educational attainment, and employment opportunities that impact asset acquisition. Ethnicity-related factors could involve cultural norms, traditional land tenure systems, and representation in decision-making processes.
By integrating these intersectional factors into the Sarafina score framework, a more nuanced and comprehensive assessment of asset disparities can be achieved. This expanded model would require data collection and analysis specific to each factor, allowing for a more holistic understanding of the complexities surrounding asset ownership and control. Additionally, weighting these factors appropriately based on their significance in different contexts would ensure a balanced evaluation of asset disparities across various dimensions.

What are the potential limitations or biases in the selection of proxy indicators used to estimate policy impact, and how can these be addressed to ensure the model's robustness?

The selection of proxy indicators to estimate policy impact may be subject to limitations and biases that could affect the robustness of the model. Some potential limitations include:

Data Availability: Proxy indicators rely on available data, which may be limited or incomplete, leading to gaps in the assessment of policy impact.
Correlation vs. Causation: Proxy indicators may show correlation with policy outcomes but not necessarily causation, leading to inaccurate estimations of impact.
Contextual Specificity: Proxy indicators may not capture the unique contextual factors that influence policy effectiveness in different settings, resulting in a lack of generalizability.

To address these limitations and biases, several strategies can be implemented:

Validation Studies: Conducting validation studies to ensure that selected proxy indicators accurately reflect policy impact and are not influenced by external factors.
Sensitivity Analysis: Performing sensitivity analysis to assess the robustness of the model to variations in proxy indicators and their weights.
Expert Consultation: Involving domain experts to review and validate the selection of proxy indicators, ensuring their relevance and reliability in estimating policy impact.
Continuous Monitoring: Regularly updating and refining the selection of proxy indicators based on new data and insights to enhance the model's accuracy and reliability.

By addressing these limitations and biases, the model's robustness can be strengthened, leading to more accurate estimations of policy impact on asset disparities.

Given the complex and deeply rooted cultural and social norms that contribute to gender asset disparities, what complementary approaches beyond policy interventions could be explored to drive more transformative change in land ownership and tenure security?

Beyond policy interventions, complementary approaches can be explored to drive transformative change in land ownership and tenure security, considering the complex cultural and social norms at play:

Community Empowerment Programs: Implementing community-led initiatives that educate and empower marginalized groups, particularly women, on their land rights and legal protections.
Capacity Building: Providing training and resources to enhance the financial literacy and entrepreneurship skills of women to enable them to actively participate in land ownership and management.
Cultural Sensitization Campaigns: Conducting awareness campaigns to challenge traditional gender roles and stereotypes that perpetuate unequal access to land, promoting gender equality and social inclusion.
Collaborative Partnerships: Engaging with local organizations, NGOs, and grassroots movements to advocate for gender-inclusive land policies and support marginalized communities in securing land rights.
Research and Data Collection: Conducting in-depth research and data collection on gender asset disparities to inform evidence-based interventions and monitor progress towards achieving gender equality in land ownership.

By adopting a multi-faceted approach that combines policy interventions with community engagement, capacity building, cultural sensitization, and collaborative partnerships, transformative change can be fostered to address gender asset disparities and promote equitable land ownership and tenure security.