Work in progress

Land Subsidence: Environmental risk in housing markets in Mexico City with Carolina Rodríguez Zamora
Presented at: LSE Environment week, AERE summer meeting, LACEA Urban workshop
Abstract

We study the costs of and the housing market response to subsidence, the sinking of land areas due to groundwater over-extraction, in Mexico City. We propose an equilibrium model of the housing market that features housing re-development in the face of an evolving environmental hazard that has both realized and expected future impacts to home quality. Guided by model-derived estimating equations for key parameters of the model, we exploit quasi-random variation in sinking intensity to estimate the impact of both realized and future subsidence on home values. We find that realized subsidence imposes substantial costs, which are driven by physical degradation to the structure, increased maintenance investment, and impacts to public infrastructure. However, prices are unresponsive to measures of expected future sinking, and novel survey evidence on residents' beliefs and information about sinking suggest that information frictions affect the ability of homebuyers to capitalize predictable future risk. Consistent with model predictions, units that have experienced more sinking are more likely to be redeveloped, as these have lower opportunity cost of being re-built. Evaluating welfare using our parameter estimates implies that subsidence costs Mexico City $34.2 billion USD in economic costs, 12% of which are due to information frictions that inefficiently increase the housing stock in risky areas. Our findings show that groundwater depletion imposes a costly externality on the built environment, and that frictions affecting the capitalization of environmental hazards in the housing market exacerbate these costs by putting more value in harm's way.

Estimating the Gains from Water Trade: A Systematic Evaluation of Modeling Considerations with Nell Green Nylen, Ellen Bruno, Andrew Ayers, Michael Kiparsky, Josué Medellín-Azuara, and Sarah Null

Abstract

The gains from water trading can vary significantly depending on local conditions as well as the specifics of market design and implementation. However, models of water trading necessarily rely on assumptions that simplify the social, institutional, and environmental landscape within which a water market operates. We systematically evaluate peer-reviewed papers that estimate the gains from water trading to assess how models of water markets take this local context into account. Our results demonstrate that whether and how models incorporate key considerations varies widely, with implications for the accuracy of results. We find that estimates of the economic impacts of water trading in the published literature are more likely to consider distributional effects and incorporate features of the legal and regulatory environment than to account for third-party impacts, transaction costs, the consequences of trading for the economy at large, or the administrative costs associated with setting up and operating a market. Understanding what features a model takes into account is important for interpreting its policy implications. Researchers modeling the gains from trade could better support local decision makers by explicitly articulating their models’ capabilities and limitations.

Draft available upon request.

Differential subsidence, damages, and fragility: Evidence from a systematic analysis of structural vulnerability in Mexico City with Enrique Fernández-Torres

Abstract

Understanding the structural vulnerability of buildings and public infrastructure to differential subsidence is crucial for evaluating the risks and costs that subsidence poses in urban areas. We combine novel estimates of plot-specific differential subsidence in Mexico City with a representative survey of structural issues in both private residences and public infrastructure to estimate structural fragility curves and damage thresholds. We then extrapolate these findings from micro-data to a city-wide analysis, calculating damages and vulnerability at a city block level.