Article 3 - Assessing Benefits

• Slum formation is occurring at unprecedented rates, with over 1 billion slum dwellers worldwide (32% of global urban population)
• Slum dwellers represent a significant proportion of urban populations in various regions, with the highest percentages in sub-Saharan Africa and South-central Asia
• The UN warns that without serious action, the number of slum dwellers could rise to 2 billion in the next 30 years
• Governments and international institutions are working on programs to reduce slum formation and improve the lives of slum dwellers
• The World Bank has invested $14.3 billion in shelter lending across 278 projects over the past 30 years
• The UN Millennium Development Goals include "Cities without Slums" as a target to improve the lives of 100 million slum dwellers by 2020
• Strategies for slum improvement


  • Sites and services programs
  • Resettlement
  • Land titling
  • Slum upgrading projects
• Slum upgrading


  Providing basic services like clean water, sewage disposal, housing, roads, lighting, schools, and health posts
• A key focus of slum upgrading is on regularizing property tenure and enabling shelter improvements
• Assessing the impact of slum upgrading programs faces challenges due to pre-existing distortions in land and credit markets
• Cost-benefit analyses often overlook these distortions, leading to potential inaccuracies in estimating net benefits
• The effectiveness of interventions depends on how well complementary policy initiatives are implemented to address these distortions
• Dynamic general equilibrium model

  A model that compares the effectiveness of different interventions in improving the welfare of slum dwellers, accounting for decision-making agents such as households, developers, financial institutions, and government
• The model examines how land and credit market distortions impact the ranking of different policy instruments
• Examples from three Brazilian cities are used to illustrate the analytical problem, but the strategy can apply to various cities
• Findings indicate that pre-existing distortions change the benefits and rank ordering of interventions, consistent with research in environmental economics and public finance
• The presence of market distortions can change the perceived effectiveness of slum upgrading programs
• Correcting these distortions is critical for maximizing the impact of interventions on the welfare of slum dwellers
• Addressing slum issues


  • Requires a multi-faceted approach involving infrastructure, housing, and regularizing property tenure
  • Effective interventions must account for pre-existing market distortions to accurately assess the impact and benefit-cost ratios
  • General equilibrium models provide a comprehensive analysis of how different interventions interact with land and credit market conditions
• Baseline model assumptions


  • Monocentric-closed city with no population growth
  • Four economic agents: households, developers, financial intermediaries, and the city government
• Households


  • Aim to maximize their lifetime utility by balancing consumption of non-housing and housing goods
  • Decide their optimal demand for housing based on their preferences and budget constraints, aiming to improve the quality of their housing over time
• Developers


  • Supply housing by transforming land and building materials into residential units, incurring costs in the process
  • Housing production follows a constant return to scale function, and developers aim to maximize profits in a perfectly competitive market
• Financial intermediaries


  • Banks act as financial intermediaries, converting household deposits into loans for developers
  • The credit market may experience imperfections such as default risk and expected recovery costs, leading to credit rationing
• Government


  • Derives revenue from infrastructure facilities and exogenous funding from higher government levels
  • Transfers to households are made to cover the cost of intervention programs such as housing quality enhancements
• Equilibrium


  Achieved when the prices, allocations, stock of financial assets, and policy variables balance
• The model is quantified using data from three municipalities in Brazil: Brasilia, Curitiba, and Recife
• The analysis helps identify the best possible intervention for achieving optimal housing quality while considering costs and welfare gains
• Slum upgrading


  Improving the quality of life in current locations without relocation
• Relocation strategies


  Moving people away from the city center and comparing the outcome to in-situ upgrading
• Shifts from in-situ to relocation drastically decrease the social benefit-cost ratio
• When land supply is constrained, building and infrastructure development must compensate for the lack of available land
• Stringent credit rationing distorts other resource markets, particularly affecting land and housing markets
• Slum upgrading


  • Improves housing quality and therefore quality of life
  • Different strategies work better depending on the city's context and the severity of the issue being addressed
• For effective slum upgrading, addressing pre-existing market distortions is crucial
• Dynamic general equilibrium model

  • Considers supply side bottlenecks in slum upgrading
  • Uses a social benefit-cost framework
  • Allows for an assessment of how various decision-makers (households, government, and financial institutions) react to policy changes
• Social benefit-cost ratios decline significantly when households are relocated from their original locations
• Distortions in one market (e.g., credit market) can affect another market (e.g., land market)
• Effective upgrading interventions are more successful when accompanied by institutional and regulatory reforms to address market distortions