Amine Charles-Louis Ouazad
Associate Professor in the Department of Economics at HEC Montreal, Canada.
I am Associate professor at HEC Montréal‘s Department of Economics. My research was cited in Congressional hearings, in the Financial Times, Wall Street Journal, New York Times, CBS, Bloomberg, Politico, etc. I serve on the scientific and awards committees of the American Real Estate and Urban Economics Association, and the scientific committee of the Urban Economics Association. Previously I was an associate professor at Ecole polytechnique, France, an associate professor at Rutgers Business School, New Jersey, and an assistant professor at INSEAD, Fontainebleau. In April 2020, I was appointed DLA Piper Distinguished Visiting Professor of Economics at Johns Hopkins University. I was a Senior Fellow of Johns Hopkins’ 21st Century Cities Initiative. Email me
Speaking at the MIT Center for Real Estate with Bill Wheaton and Jacques Gordon
My research interests span finance, climate risk, urban economics, real estate, social justice.
The most recent research:
New! Adaptation Using Financial Markets: Climate Risk Diversification through Securitization Link to the paper. In the face of rising climate risk, financial institutions may adapt by transferring such risk to securitizers that have the skill and expertise to build diversified pools, such as Mortgage-Backed Securities. In diversified pools, exposure to climate risk may be a drop in the ocean of cash flows. This paper builds a data set of the entire securitization chain from mortgage-level to MBS deal-level cash flows, and observes the prices of the tranches at monthly frequency. Wildfires lead to higher rates of prepayment and foreclosure at the mortgage level, and larger losses during foreclosure sales. At the MBS deal level, a lower spatial concentration of dollar balances (lower spatial dollar Herfindahl), a lower spatial correlation in wildfire events (within-deal correlation), leads to a lower exposure to wildfire events. These quantifiable metrics of diversification identify those existing deals whose design makes them resilient to climate change. This paper builds optimal deals by finding the portfolio weights in an asset demand system that targets return and risk. Extrapolating wildfire risk using a granular wildfire probability model and temperature projections in 2050, we build climate resilient MBSs whose returns are minimally impacted by wildfire risk even as they supply mortgage credit to wildfire prone areas. Finally, we test whether the market prices the sensitivity of each deal’s cash flow to wildfire risk.
New! Equilibrium Multiplicity in Quantitative Spatial Models, with an Application to Chicago Link to the paper. Discrete choice models with social interactions or spillovers may exhibit multiple equilibria. This paper provides a systematic approach to enumerating them for a quantitative spatial model with discrete locations, social interactions, and elastic housing supply. The approach relies on two homotopies. A homotopy is a smooth function that transforms the solutions of a simpler city where solutions are known, to a city with heterogeneous locations and finite supply elasticity. The first homotopy is that, in the set of cities with perfectly elastic floor surface supply, an economy with heterogeneous locations is homotopic to an economy with homogeneous locations, whose solutions can be comprehensively enumerated. Such an economy is epsilon close to an economy whose equilibria are the zeros of a system of polynomials. This is a well-studied area of mathematics where the enumeration of equilibria can be guaranteed. The second homotopy is that a city with perfectly elastic housing supply is homotopic to a city with an arbitrary supply elasticity. In a small number of cases, the path may bifurcate and a single path yields two or more equilibria. By running the method on thousands of cities, we obtain a large number of equilibria. Each equilibrium has different population distributions. We provide a method that is computationally feasible for economies with a large number of locations choices, with an empirical application to the City of Chicago. There exist multiple “counterfactual Chicagos” consistent with the estimated parameters. Population distribution, prices, and welfare are not uniquely pinned down by amenities. The paper’s method can be applied to models in trade and IO. Further applications of algebraic geometry are suggested.
New! “Do Investors Hedge Against Physical Disaster Risk? Option-Implied Risk Aversion to Wildfires” Link to the Paper. Measuring beliefs about natural disasters is challenging. Deep out-of-the-money options allow investors to hedge at a range of strikes and time horizons, thus the 3-dimensional surface of firm-level option prices provides information on (i) skewed and fat-tailed beliefs about the impact of natural disaster risk across space and time dimensions at daily frequency; and (ii) information on the covariance of wildfire-exposed stocks with investors’ marginal utility of wealth. Each publicly-traded company’s daily surface of option prices is matched with its network of establishments and wildfire perimeters over two decades. First, wildfires affect investors’ risk neutral probabilities at short and long maturities; investors price asymmetric downward tail risk and a probability of upward jumps. The volatility smile is more pronounced. Second, comparing risk-neutral and physical distributions reveals the option-implied risk aversion with respect to wildfire-exposed stock prices. Investors’ marginal utility of wealth is correlated with wildfire shocks. Option-implied risk aversion identifies the wildfire-exposed share of portfolios. For risk aversions consistent with Barro (2012), equity options suggest (i) investors hold larger shares of wildfire-exposed stocks than the market portfolio; or (ii) investors may have more pessimistic beliefs about wildfires’ impacts than what observed returns suggest, such as pricing low-probability unrealized downward tail risk. We calibrate options with models featuring both upward and downward risk. Results are consistent a significant pricing of downward jumps.
In Mortgage Finance and Climate Change: Securitization Dynamics in the Aftermath of Natural Disasters, joint with Matthew E Kahn, we show that mortgage lenders may have an incentive to securitize their flood risk, selling the risk to the Government Sponsored Enterprises Fannie Mae and Freddie Mac. The paper was featured in the New York Times, in the Wall Street Journal, on CBS News. We outlined our policy proposals in a Bloomberg oped. Our work was the focus of Rep. McHenry’s questions to FHFA’s director Mark Calabria during a congressional hearing on October 22, 2019.
In City Equilibrium with Borrowing Constraints: Structural Estimation and General Equilibrium Effects, in the International Economic Review (May 2019), I provide a fine-grained neighborhood-level model that estimates the impact of banks’ lending policies on house prices in the San Francisco Bay Area. The papers shows that (i) the distribution of house prices contracted during the boom of 2000-2006 in the San Francisco Bay area, and that (ii) part of this contraction is due to banks’ lending policies.
In Credit Standards and Segregation, published in the Review of Economics and Statistics, I ask whether mortgage credit supply increases lead to greater segregation by race. The paper is based on the 900+ core based statistical areas (metro areas) of the US.
In Blockbusting: Brokers and the dynamics of segregation paper, published in the Journal of Economic Theory, I show whether and how market intermediaries can shift the market equilibrium – and how competition among market intermediaries prevents such tactics. Blockbusting is prohibited in the US under the Fair Housing Act.
In The Higher Moments of Future Earnings, published in the Accounting Review, we use US S&P 1500 data to show how historical data can help us predict tail events. Authors have long emphasized that assuming normally distributed returns leads us to underestimate the probability of extreme events. We show that fundamental firm-level accounting data helps us predict such extreme events (skewness and kurtosis at the firm-level).
In Balance-Sheet Diversification in General Equilibrium: Identification and Network Effects (NBER working paper 23574), I show how financial shocks propagate through banks’ networks, using security-level and bank-level data.
In Job Displacement and Crime: Evidence from Danish Microdata and Reforms, published in the Journal of the European Economic Association I analyze the impact of plant closures on workers’ criminal activity. A substantial part of such plant closures was driven by the Nordic Financial Crisis, a series of bank failures that constrained the activity of firms most reliant on external funding.
My previous research on the economics of education has helped me teach very diverse classrooms. I taught (and perhaps mostly learnt from !) over 2,000 executives across Canada, the United Kingdom, France, Singapore, South Africa, and the United Arab Emirates.
Previously I was an associate professor at HEC Montréal, Ecole polytechnique, Paris, an assistant professor at INSEAD, where I taught on the Asia, Europe, and Middle East campuses, in the EMBA, MBA, PhD programs.