publications

 

WORKING PAPERS

In order of most recent revision

  • “Security Audits in DeFi” With Francisco Sesto

    Abstract

    Decentralized Finance (DeFi) is an innovation with the potential to address fundamental issues in modern finance. However, in practice, its technology has also demonstrated susceptibility to various problems, including security vulnerabilities and coding errors, which have led to an increasing number of exploits and hacks. In response, protocols have adopted security audits as a means to mitigate these issues. In this study, we collected original data on security audits and explored their potential signaling effects. Our findings indicate that protocols are audited more frequently than previously documented, including audits when contracts are already managing funds. Generally, the release of security audits results in modest increases in the returns of the protocols’ own currencies. Contrary to findings in other studies, we did not observe significant increases in the amount of liquidity attracted by protocols or in their operating volume as the number of audits increased. Therefore, our preliminary results do not support the notion that audit releases generally serve as a signaling mechanism.

  • “Quadratic Funding and Matching Funds Requirements” Arxiv

    Abstract

    In this paper we examine the mechanism proposed by Buterin, Hitzig, and Weyl (2019) for public goods financing, particularly regarding its matching funds requirements, related efficiency implications, and incentives for strategic behavior. Then, we use emerging evidence from Gitcoin Grants, to identify stylized facts in contribution giving and test our propositions. Because of its quadratic design, matching funds requirements scale rapidly, particularly by more numerous and equally contributed projects. As a result, matching funds are exhausted early in the funding rounds, resulting in some allocative inefficiencies. Empirically, there is also a tendency by contributors to give small amounts, scattered among multiple projects, which accelerates this process. Among other findings, we also identify a significant amount of reciprocal backing, which could be consistent with the kind of strategic behavior we discuss.

  • “Optimal allocation of limited funds in quadratic funding” Arxiv

    Abstract

    We examine the allocation of a limited pool of matching funds to public good projects using Quadratic Funding. In particular, we consider a variation of the capital constrained quadratic funding (CQF) proposed by Buterin, Hitzig and Weyl (2019), which tends to generate a socially optimal allocation of limited funds.

  • Subsidized government credits and households' financial distress: Estimating the effect of Créditos Argenta

    Abstract

    In this paper we examine the effects of a large-scale, state-provided, subsidized credit program on the financial distress of vulnerable households. The Argentine government expanded Créditos Argenta to recipients of poverty alleviation, cash transfer allowances in 2017. One of the motivations of this credit program was to crowd-out a growing and high interest rate credit market that targeted cash transfer allowances recipients. We carry out this analysis using an original data panel constructed by geo-referencing data from the CENDEU credit bureau. The resulting data includes 4.2 million households, tracked monthly during four years, and mapped at the census tract scale. We then estimate the intention-to-treat effect on households’ financial distress by proposing a differences-in-differences identification strategy. Our preliminary results suggest that the program allowed only temporary relief, followed by a worsening in their relative financial conditions.Keywords: households indebtedness, financial inclusion, conditional cash transfer programs

  • Transcending census boundaries: Using user-generated geographic information to predict gentrification and displacement, With Karen Chapple, Emmanuel Lopez and Maria Emilia Pérsico. Github repository

    Abstract

    Researchers have long struggled in using secondary census data to measure neighborhood change, specifically in the form of gentrification and displacement. Though some researchers have devised typologies of neighborhood change that predict future transformation, for instance using machine learning to assign gentrification risk to neighborhoods, their predictive power remains questionable, perhaps in part because of the use of census data that is out-of-date or unreliable at a fine geographic scale (Chapple and Zuk, 2016; Reades, De Souza and Hubbard, 2018). In this project we are studying the potential of sources of user-generated, real-time, social media generated data, such as Twitter, to develop early warning systems of gentrification and displacement. Keywords: Gentrification and Displacement, Early Warning Systems, Machine learning, Big data

 

REFEREED PUBLICATIONS

  • 2023 “Do land use regulations help give rise to informal settlements? Evidence from Buenos Aires” With Cynthia Goytia and Eric J Heikkila Land Use Policy, Volume 125, 2023, 106484, ISSN 0264-8377

    Abstract

    Increasingly, scholars are drawing causal linkages between urban land use regulations and the presence of informal settlements, especially in the global South. To date, however, the empirical evidence has been scant, in part due to the intrinsic difficulty of gathering reliable data on informal settlements. In this paper, we review recent theoretical perspectives on the linkages between formal and informal housing sectors, and we develop and apply empirical tests of some key tenets from this literature. Our approach entails two distinct yet complementary datasets for the Metropolitan Area of Buenos Aires (MABA). First, we collected a survey of 550 representative households living in informal settlements and in nearby formal areas, specifically for this purpose. The other data set is derived from a Census matching technique applied to the National Expenditure Survey (ENGH) of Argentina, yielding a database with 399,000 households. Although these datasets, and therefore the underlying empirical approaches, are quite different from each other, several key findings emerge. Both methods confirm the existence of a rent premium for accessing the formal housing sector. Likewise, both show that restrictive land use regulations compel lower income households in the formal sector to over-consume housing. Both of these findings support a causal link between restrictive land use regulations and the emergence of informal housing settlements. Our results also show a strong interconnection between infrastructure provision and housing outcomes, and this linkage needs to be explored further.

  • 2021 “Effects of Regulating the Brokerage Commission in the Rental Market: Geographic RD Evidence from Buenos Aires” Journal of Housing Economics Volume 54, December 2021, 101793 https://doi.org/10.1016/j.jhe.2021.101793 SSRN WP version

    Abstract

    In the rental market, one of the measures that governments take to benefit tenants is to exempt them from their obligation to pay the real estate commission, transferring this obligation to landlords. Recent experience in the city of Buenos Aires from the sanction of a law of this type has characteristics of a natural experiment, allowing the study of the causal effects of this policy on rental prices. In identifying this effect I propose an extension of the Geographic Discontinuity Design, exploiting before and after differences along the city limit. I find an increase in average rents of a magnitude consistent with the theoretical idea that owners transfer the value of the commission to tenants, but distributed throughout the contract. In other words, it is consistent with a financing effect, where owners finance tenants in the payment of the commission. I also find suggestive evidence indicating owners have changed their security deposit requirements. *Keywords: Rental Market; Brokerage Commission; Geographic Regression Discontinuity Design; Differences-in-Differences, Causal inference*

  • 2021 “Impact of Accelerators, as Education & Training Programs, on Female Entrepreneurs”. With Carolina Dams, Virginia Sarría Allende, Magdalena Cornejo and Gabriela Robiolo. Entrepreneurship Research Journal. Pre-published online by De Gruyter July 1, 2021 https://doi.org/10.1515/erj-2020-0306

 

Previous Work by Topic

Urban Economics

  • “Mitigating the displacement impact of special districts in Latin American cities: How to promote urban inclusion via land policy instruments” With Cynthia Goytia, Sergio Montero, Karen Chapple, Manuel Santana Palacios, Diego Silva Ardila, Lina Gonzalez, Donna Leong and Jose Carpio-Pinedo. Lincoln Institute of Land Policy Working Paper, 2019

    Abstract

    Latin American cities are increasingly using urban redevelopment plans (URP) and special districts (SD) in order to attract firms and middle-income residents in less developed areas of their cities. Broadly speaking, SD policies refer to government efforts to enhance the economic performance of underperforming areas, such as deteriorating downtown industrial districts, transformed into vibrant work and living environments. As a place-based policy intended to generate employment and local economic development, these policy interventions have led to new interest in understanding neighborhood change, gentrification, displacement and segregation, when instruments to promote inclusion have proven elusive. This paper analyzes the impacts of SDs in both Buenos Aires and Bogotá. First, we analyze and provide evidence on SD policies effects in Buenos Aires, analyzing in depth the case of the Technology District in the southern area of the city, including its effects on land use changes and real estate prices. In a context of displacement and vulnerability, we find high increases in land value and apartment prices, consistent with an anticipation of district policies and related interventions by the market. Secondly, we explore how land policy instruments can lay a foundation for more inclusive urban development, throughout a simulation of the potential impacts of approaches such as inclusionary zoning, and/or land base and fiscal instruments, in promoting or mitigating displacement. Our simulation shows the effects of land policies in land values and displacement, relative to a business-as-usual scenario. In contrast, in the case of Bogotá, we find that the implementation of the Triangulo de Fenicia plan has actually stabilized land values relative to the surrounding area. Qualitative analysis reveals the role of community organizing in the co-creation of more inclusive land policy. We conclude with a call for revisiting special district policies in Latin American cities in order to ensure they are equitable and inclusive. Keywords: Gentrification, Displacement, Land and Real Estate Markets, Land Use Planning, Land Regulation, Special Districts, Urban Revitalization, Latin America & The Caribbean, Spatial Segregation

 

Entrepreneurial Finance

  • “The Added-Value of Network Connections in Entrepreneurial Finance” With Gabriela Robiolo

    Abstract

    Summary: Entrepreneurs are usually exhorted to attract the best networked investors. We provide further insights into this advice by estimating network effects in the performance of entrepreneurial ventures. We show dimensions that are critical in this estimation, such as the consideration for startups’ connections, common connections among investors, and the decreasing returns to network centrality, and estimate their relative importance. We estimate networks effects using an original database of connections among startups, investors and individuals with relevant roles in California, collected from web-based sources, resulting in a network of nearly 1 million connections. Keywords: Entrepreneurial Finance, Investor’s value added, Networks JEL Classification: G24,L14, M13

  • “Random Network Formation in Entrepreneurial Finance: A Simple Model and Evidence”. With Virginia Sarria Allende (IAE Business School).

    Abstract

    We propose a simple two-mode random network formation model aimed to mimic the properties of an entrepreneurial finance network, and calibrate it with data of a network of startups and investors in California. In the model investors match with startups at random, and find about other investment opportunities by other investors by invitations. This model helps explains features of the observed network such as its degree distribution, average distance, and clustering. Keywords: Entrepreneurial Finance, Networks, Random Models of Network Formation, Empirical Network Structure, Syndicates, Serial-Investors JEL Classification: D85, G01, G24, L14, M13

  • 2017 “Tanchella: una herramienta para la recolección de datos de la Web” With Gabriela Robiolo, Javier Isoldi, Martín Salaberri, Kevin Stenssens, Carolina Dams, Virginia Sarria-Allende Proceedings of CIbSE 2017@ICSE 2017

Finance