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November 7, 2022
Do Freeway Lids Spur Development in Cities? Evidence from Dallas
The Federal Highway Act of 1956 connected Americas cities like never before, but the system of roads also divided and isolated existing city neighborhoods. As a result, people lost neighbors and local businesses and found themselves cut off from other parts of the city. Moreover, exposure to air and noise pollution increased, and some residents simply left the city altogether.
The recently passed Inflation Reduction Act included $3 billion in neighborhood access and equity grants, expanding on $1 billion in funding for the Reconnecting Communities Pilot grants (part of the 2021 infrastructure bill ). These funds are intended to remediate some of the ill effects of urban freeways, and the grants could fund freeway removal or other mitigation strategies. The most ambitious projects, however, are likely to put "lids" composed of parks and surface streets over sections of existing freeways. Atlanta currently has three proposed lidding projects that are likely to compete for this funding: a park over Highway 400 in Buckhead, a park over the connector (I-75/I-85) in Midtown between North Avenue and 10th Street, and a separate proposal over the connector between downtown and Midtown around Peachtree Street.
Capping a freeway with a park and surface streets could play a significant part in ameliorating the unpleasantness of an urban freeway. However, these lidding projects are expensive to construct and maintain and don't completely eliminate air and noise pollution from freeways. Whether such projects are fiscally sustainable largely depends on their ability to attract new investment and residents to the city.
One of the more celebrated recent lidding projects is Klyde Warren Park, a five-acre park spanning three city blocks of freeway in downtown Dallas. The park was partly funded with an assessment on proximate land and, at least anecdotally, attracted considerable investment to that area of Dallas. Like Atlanta, Dallas is a growing, low-density, largely auto-dependent Sunbelt city. If a freeway lid could attract new investment and residents to the city core, then such projects might have broader impact.
One challenge to evaluating any place-based project or subsidy is identifying the appropriate treatment area. Although a new park might attract investment or raise property values for immediately adjacent land, do such parks benefit the city as a whole? Or do they just redirect normal, market-driven development to a different location?
To look at whether the construction around Klyde Warren Park represented development beyond what might otherwise have happened, I looked at SupplyTrack data on new construction for six years before and after construction on the park began, both in Dallas and in a control group of six cities. I selected large southern cities not directly on the coast: Fort Worth, San Antonio, Austin, Houston, Nashville, and Atlanta. Looking before and after completion of the Dallas freeway lid and across cities, we can ask if the pace of new construction in Dallas increased relative to the control group. This is, effectively, a simple difference-in-difference estimate of the treatment effect of the freeway lid on Dallas. The table below summarizes the evidence on new construction.
Relative to its peers, Dallas experienced faster office and multifamily construction growth after lid construction began in 2012. Dallas added 1.3 million square feet of office space, a rate that is 50 percent faster than what occurred in the six prior years. Multifamily housing (apartments and condominiums in buildings with 5 or more units) grew even faster. Dallas added nearly 5,300 individual multifamily units after starting the lid, more than twice as many units as the six years before. I should note, though, that this period spans the housing market collapse of 2008. However, most large southern cities were doing well after 2012 as their economies slowly recovered from the Great Recession and developers took advantage of low interest rates. Still, compared to the control group cities, Dallas appeared to outperform. If we subtract the percentage growth in office and multifamily space from that of other large southern cities—either just in Texas or pooling all seven cities together—the growth in Dallas still looks exceptional. Compared to other Texas cities, Dallas office space grew 18 percent faster and multifamily grew 42 percent faster. In percentage growth terms Dallas's performance looks even better when we include Atlanta and Nashville in the control group, suggesting that whatever immediate growth that happened around the park did not simply divert growth from elsewhere in the city.
I also looked at the annual growth relative to 2012 for each city's hotels and retail space. Hotel room growth was weaker in Dallas than in peer cities, suggesting that new hotels built near the park might have come at the expense of other locations in the city and did not represent a net addition to supply. Perhaps parks are simply a more attractive amenity to residents than tourists, or maybe—given the relatively brief exposure—tourists were more indifferent to freeway noise and pollution ex ante. Retail growth never recovered after the Great Recession, but it didn't look particularly worse in Dallas than for the control group of cities.
Of course, none of this evidence is definitive. Cities are complex, and numerous idiosyncratic factors affect a cities labor demand, attractiveness to workers or their capacity to supply new houses and offices. Still, when looking at investment activity, Dallas's growth in multifamily and housing and office construction is at least consistent with the idea that building the Klyde Warren Park lid over the freeway in downtown Dallas made the city a more attractive place to live and work.
October 21, 2022
Viewing the Wage Growth Tracker through the Lens of Wage Levels
One of the most popular features of the Atlanta Fed's Wage Growth Tracker is its depiction of median year-over-year wage growth of four different wage levels (wage quartiles). Unfortunately, the sample size of each quartile for a month is quite small, and thus the median wage growth for each quartile is noisy. For that reason, the Tracker shows changes by wage quartile only as a 12-month moving average. However, although the averaging smooths out a lot of the month-to-month noise in the series, it also means that the series have a substantial lag in showing wage growth changes across quartiles.
Instead, I have produced a cut of the wage growth data by wage level that can show a three-month moving average, which gives a better near-term picture of wage growth trends. The restriction, however, is that rather than using four wage groups, I put the average wage-level data (that is, the average of a person's reported wage in the current month and their reported wage a year earlier) into two groups: those whose average wage is above the median and those whose average wage is below the median. Essentially, I split the distribution of average wages in half.
Chart 1 plots the resulting three-month moving average of the two groups' median wage growth.
As you can see, median wage growth has been elevated since 2020 for workers across the wage distribution. But for workers in the bottom half of the wage distribution, median growth has been especially high during the last year. High wage growth for lower-paid workers aligns with numerous anecdotal reports suggesting that worker shortages since the pandemic have been especially acute in industries that pay below-average wages, such as leisure and hospitality.
Chart 1 allows another interesting observation: in the years leading up to the pandemic, the median wage growth of those in the lower half of the wage distribution was typically a bit above those in the upper part of the distribution. This was a period when the labor market was also tight, although much less so than it is today. Chart 2, which shows the sum of employment and job openings relative to the size of the available labor force, makes clear the divergence in the degree of overall labor market tightness today versus prior to the pandemic.
By this measure, though the gap has narrowed a bit in recent months, labor demand remains well above its supply, and this gap has been putting upward pressure on wages across the spectrum.
The Wage Growth Tracker series for the two wage groups is available now in the downloadable spreadsheet here and will be updated with October data after the Current Population Survey micro data for October is released, which usually occurs about a week after the US Bureau of Labor Statistics issues its labor report.
October 20, 2022
The Atlanta Fed's Early Career Visitor Program Workshop: A Synopsis
On September 9, 2022, the Federal Reserve Bank of Atlanta hosted the Early Career Visitor Program Workshop, organized by Salome Baslandze, Simon Fuchs, Indrajit Mitra, and Veronika Penciakova. The purpose of the program is to offer early- and mid-career researchers the opportunity to spend several months visiting the department. The program, an innovative addition to the existing landscape of offerings across the Federal Reserve System, provides a unique opportunity for researchers in the early part of their careers to spend some time at a regional Reserve Bank, and for Atlanta Fed's Research Department to strengthen ties with new generations of policy-oriented economists. The program also supports our policy-making process by keeping us in touch with new theoretical, quantitative, and empirical methods in the profession. The workshop brought together participants in the Atlanta Fed's 2021 Early Career Visitor Program with an aim to foster active exchange and discussion among economists on a wide range of topics. Tao Zha from the Atlanta Fed opened the conference by welcoming the participants. He talked about our unprecedented times and the challenges policymakers face in light of high inflation, government debt, and ongoing macroeconomic shocks. He also discussed the importance of high-quality research in informing policymakers.
Yuhei Miyauchi from Boston University presented his in-progress research (coauthored with with Elisa Giannone, Nuno Paixão, Xinle Pang, and Yuta Suzuki) titled "Living in a Ghost Town: The Geography of Depopulation and Aging." This project explores the dynamics of aging and depopulation across different regions within a country and how this process affects welfare across regions and generations. Using spatially disaggregated data from Japan for the last 40 years, he documents that depopulation and aging have progressed more rapidly in less populous areas. This empirical pattern is primarily driven by the youths' net outmigration. Motivated by this evidence, the author develops a dynamic life-cycle spatial equilibrium model of migration decisions. The model matches the historical spatial population changes in Japan and projects future spatial patterns of depopulation and aging. A key take-away from this project is that abstracting from endogenous migration decisions over the life cycle and their effects on local economies substantially biases the projected spatial patterns of demographic changes and welfare.
Wookun Kim from Southern Methodist University presented his joint work with Changsu Ko and Hwanoong Lee, "Heterogeneous Local Employment Multipliers: Evidence from Relocations of Public Entities in South Korea." The authors exploit a variation in public-sector employment from an episode of the relocations of public-sector entities and estimate local employment multipliers. The estimated multiplier is positive and persistent over time: an introduction of one public sector employment increases the private sector employment by one unit, with employment growth in the services sector driving this increase in private sector employment. The authors document that the effect of public employment on private employment is highly localized. In addition to changes in private employment, the relocations of public-sector employees led to a positive net inflow of residents into the treated neighborhood. Examining the variation in the extent of public employment shock across different relocations, the paper identifies heterogeneous local employment multipliers and provides evidence that the extent of public sector shocks and different types of relocation shape this heterogeneity. Their results imply that local employment multipliers tend to be higher in areas with predetermined characteristics that allow faster and larger general equilibrium responses to take place after the public sector shock.
Maya Eden from Brandeis University presented her work titled "The Cross-Sectional Implications of the Social Discount Rate." In her research, Eden asks, how should policy discount future returns? The standard approach to this normative question is to ask how much society should care about future generations. The author establishes an alternative approach, based on the social desirability of age-based redistribution. The social discount rate is below the market interest rate only if it is desirable to increase the consumption of the young at the expense of the old. Along the balanced growth path, small deviations of the social discount rate from the market interest rate imply large welfare gains from redistributing consumption across age groups.
Boyoung Seo from Indiana University presented her work, "Racial Differences in Prices Paid for Same Goods," coauthored with Andrew Butters and Daniel Sacks. The authors document that Black non-Hispanic households pay 2.0 percent higher prices than white non-Hispanic households, and Hispanic households pay 0.8 percent higher prices for physically identical products. This difference suggests that conventional measures of racial income differences understate real racial income inequality. Differences in income, demographics, or education do not explain the racial price gap. Instead, it is entirely explained by three factors: Black non-Hispanic and Hispanic households buy smaller packages with higher unit prices, benefit less from coupons, and live in places where prices tend to be high. The place-based price differences appear driven not by supermarket presence but by differences in carrying and transportation costs.
Abdoulaye Ndiaye from New York University presented "Bonus Question: How Does Incentive Pay Affect Wage Rigidity?," a paper coauthored with Meghana Gaur, John Grigsby, and Jonathan Hazell. Wage rigidity occupies a central role in models of macroeconomic fluctuations. However, recent work shows that wage rigidity is not sustained in equilibrium with appropriately calibrated idiosyncratic shocks. Indeed, individual wages frequently adjust in response to both idiosyncratic and aggregate shocks in the data. Many of these fluctuations result from movements in nonbase compensation such as bonuses, which most existing models are ill-equipped to study. The authors study whether and how flexible incentive pay affects macroeconomic fluctuations. They develop a general model of dynamic contracting, in which firms offer contracts to workers to give them incentives to supply costly effort that is otherwise unobservable by the firm. In this class of models, the first-order response of firm value to exogenous shocks is summarized by the direct effect of the shock on firms' objective function and constraints—the envelope theorem, which examines the effects of changes in certain variables, would hold that the indirect effects of the shock on wage payments and effort are not value-relevant. The authors consider the implications of this result both theoretically and quantitatively for the two fields that most commonly rely on wage rigidity to generate macroeconomic fluctuations: labor search and New Keynesian business cycle theory.
Yu Xu from the University of Delaware presented his work, titled "Ambiguity and Unemployment Fluctuations" and coauthored with Indrajit Mitra. The authors analyze the consequences of ambiguity aversion in the Diamond-Mortensen-Pissarides (DMP) search and matching model. Their model features a cross-section of workers whose productivity is the sum of an aggregate component and a match-specific component. Firms are ambiguity averse towards match-specific productivity. The model delivers two insights. First, ambiguity aversion substantially amplifies unemployment rate volatility. Second, a part of the high value of leisure required by the canonical DMP model to generate realistic unemployment rate volatility can arise from fitting a model missing ambiguity aversion to data generated in an environment where agents are ambiguity averse.
The workshop organizers hope that participants found the diverse array of presentations thought provoking as they progress in their careers as researchers, and that the discussions contributed to their professional and intellectual development.
October 18, 2022
Decentralized Finance (DeFi): Potential and Risks
In a 2008 paper by Satoshi Nakamoto, Bitcoin was proposed as a method of making electronic payments using a blockchain without the need to go through a financial institution. In a relatively short period of time, the basic idea laid out by Nakamoto has grown into a crypto finance world that at its recent peak in November 2021 was valued by Coinmarketcap as being worth almost $3 trillion. However, contrary to Nakamoto's original vision, financial intermediaries have provided many of the financial services needed for the crypto finance world to grow to this level. Thus, it's not surprising to see the rise of an alternative method of providing many services not reliant on institutions. This method replaces centralized finance (or CeFi), which is delivered through institutions, with decentralized finance, or DeFi, which uses smart contracts (computer code) running on a blockchain.
DeFi had shown considerable growth starting in late 2020 through late 2021 (for more discussion of this growth, see here ). The standard measures of size, total value locked—saw DeFis reaching a peak of more than $180 billion in December 2021, according to one relatively broad measure (such as DeFiLlama, a total value locked data aggregator). Although these numbers may sound large, they are still a rather small part of the global financial system. For example, four US banks have total assets greater than $1.5 trillion. Moreover, the total value locked in DeFi has dropped dramatically since the start of the "crypto winter" earlier this year, reaching values below $55 billion in September 2022. Whether DeFi can become a major provider of financial services will likely depend upon the extent to which crypto finance either integrates with the existing financial system or evolves to become a parallel system for providing a wide range of financial services—or both.
Along with coauthors Francesca Carapella, Edward Dumas, Jacob Gerszten, and Nathan Swem, I recently posted an article on DeFi titled "Decentralized Finance (DeFi): Transformative Potential and Associated Risks" as part of the Atlanta Fed's Policy Hub series. (It is also available in the Board of Governors FEDS working paper series and as a working paper out of the Boston Fed's Supervisory Research and Analysis Unit.) This Policy Hub: Macroblog post summarizes some key ideas in our article.
To understand developments in DeFi, it is helpful to understand the how and why of widely accessible (public, permissionless) blockchains. A blockchain is a database where the data are entered in time-stamped blocks and the blocks are cryptographically chained together so that any change in a prior record can easily be detected. Bitcoin facilitates the avoidance of financial intermediaries by using a public, permissionless blockchain, meaning that anyone can obtain a copy of the database, read the database, and potentially write to the database. The problem that such an open database can create is that of "double spending." An example of double spending would be Joe first making a payment to Jane and then trying to make a payment to Mary using the same funds. This circumstance could happen if Joe has ability to rewrite blocks that had been previously written. That is, he could rewrite the block he had used to pay Jane so that it no longer contains that payment and—using the funds he took back—make the payment to Mary.
Nakamoto's solution to double spending is to make it very costly to try to rewrite existing blocks. The person who gets to add a new block to a blockchain must win a computationally intensive contest called proof-of-work (participants in this contest are said to be "mining" Bitcoin). As this mining process is mandatory for adding each block, attempting to rewrite a previously written block requires the miner to rewrite every block thereafter to the present, solving the computationally difficult problem for each replacement block—a very costly process. The result is that the Bitcoin blockchain is highly resistant to tampering (often spurring exaggerated claims that blockchains are "immutable"). However, Bitcoin's protocol also takes a relatively long time to ensure that a transaction has been processed.
In practice, DeFi is a relatively small part of Bitcoin because Bitcoin was not designed for sophisticated programming. The Ethereum blockchain stepped into this gap and added the ability to run programs as part of creating new blocks. Consider a simple example of such a program: one for delivery versus payment (a crypto asset is delivered from agent A to agent B, if and only if B simultaneously pays A). These programs are referred to as dapps (distributed applications). One type of dapp is the smart contract, which automates the execution of financial transactions among different parties. Although some other blockchains have since followed Ethereum in allowing dapps, Ethereum has emerged as the most important blockchain for DeFi as measured by total value locked, according to DeFiLlama's blockchain page.
Ethereum originally adopted a version of Nakamoto's proof-of-work protocol to deal with the double-spending problem. However, on September 15, Ethereum replaced proof-of-work with proof-of-stake, in which the party who gets to add the next block is randomly chosen from a group who have locked up (or staked) the blockchain's native cryptocurrency (called Ether). The winner of this contest is called a validator. The switch to proof-of-stake is part of a long-term project to allow Ethereum to process more transactions in a given period.
Our article discusses some of the most important financial services that decentralized finance is providing. Currently, one of DeFi's most important services is that of borrowing and lending. Decentralized lending platforms bring together borrowers and lenders. Borrowers incur fees (continuously accruing interest) from the time they take out the loan until its repayment. Lenders earn interest on the funds they lend.
Loans made through a DeFi are typically collateralized with other crypto assets. Participants in crypto finance are pseudonymous, meaning they are known only by their public address on the blockchain, which prevents lending based on reputation and the threat of resorting to bankruptcy courts. Moreover, because almost all the assets currently residing on blockchains are crypto assets, blockchain tokens representing off-chain assets such as equipment and real estate are generally not (yet, anyway) legally enforceable in law courts. As a result of the requirement for on-chain collateralization, borrowers take out many loans to finance off-chain consumption while retaining exposure to the crypto asset they are using as collateral—like a stock investor taking out a margin loan to buy a new car. (Another use of such loans is to increase leverage for those speculating on an increase in the value of a crypto asset—especially a cryptocurrency.)
A second important service type of DeFi service is decentralized exchanges (DEXs), which facilitate the trading of crypto assets with a centralized market maker or centralized order books. DEXs typically solicit investors to lock funds into so-called liquidity pools, rewarding these investors with fees (essentially, interest on their deposits). Users can exchange one cryptoasset for another by withdrawing a different cryptoasset than they deposited. A protocol called an "automated market maker" controls the rate at which one asset can be exchanged for another. If the price of one asset gets out of line with the views of investors or the prices on other exchanges, liquidity providers have an incentive to step in to close the price gap.
A third use of DeFi is the provision of derivatives, or claims whose value depends on (or is derived from) another asset. DeFi derivatives allow users to obtain price exposure to other assets, and this exposure is not limited to crypto assets but could include sovereign currencies, commodities, stocks, and indices. Like DEXs, DeFi derivatives connect buyers and sellers directly using collateral pools.
A fourth use of DeFi is to facilitate payments. One example discussed in our article is that of Flexa, which facilitates timely payments to merchants so that the transaction can be quickly completed despite delays inherent in the settlement of some cryptocurrencies. A second payments DeFi is the Lightning Network, which seeks to accelerate Bitcoin transactions by moving most of the work off the Bitcoin blockchain into what is called layer 2, with only the results recorded on the Bitcoin blockchain.
A third payments system our article discusses is Tornado Cash, a so-called "cryptocurrency tumbler," which is a service that obscures the relationship between the sending and receiving addresses of a cryptocurrency payment. Tornado Cash receives cryptocurrency funds from various sources and then, with some delay, distributes the funds to the intended recipient(s). The commingling of funds from various sources makes it more difficult to trace payments from one address to the intended recipient at another addresses. Tornado Cash was developed because although most cryptocurrencies are pseudonymous, everyone can nevertheless see payments sent from one address to another even though the blockchain itself does not reveal the identity of either party. However, information linking some addresses to specific parties, and some other analysis, can lead to discovery of many participants' identities. Thus, people who would prefer to send payments with reduced risk of revealing their identity might prefer to use a tumbler such as Tornado Cash. The problem is that in many cases the individuals seeking to hide their identity are engaged in illegal activities such as money laundering, ransomware schemes, and sanctions evasion. Thus, on August 8, the US Department of the Treasury's Office of Foreign Assets Control (OFAC) sanctioned Tornado Cash. Among the consequences of this sanctioning is that Americans are prohibited from using Tornado Cash unless licensed by OFAC or the transaction has an exemption. This sanctioning has resulted in a sharp drop in the total value locked in Tornado Cash, according to Defi Llama (you can see a graph of historical values here).
The last type of DeFi service that we discuss in our article is asset management. Asset-management dapps are similar to mutual funds in that they pool investor funds so that they can be efficiently invested other assets. This ability to pool assets may be useful, for example, by facilitating investment in an index of cryptocurrency values.
As noted earlier, the value of all cryptoassets and cryptoassets locked in DeFi is relatively small, given the scale of the global financial system. As such, DeFi is not yet large enough to pose a systemic risk to the financial system or to be a significant mitigant of systemic risk. Nevertheless, DeFi's potential risk implications merit careful review given its potential for growth.
In our article, we discuss how DeFi could reduce some risks but increase other risks in the financial system. Arguably the biggest potential for risk reduction is enhancing the ability of supervisors to track, in real time, major financial institutions' transactions on the blockchain, both as individual institutions and in aggregate. Having this ability would allow supervisors to respond nearly in real time. The cost, however, is that the complete record of transactions is available to everyone, and pseudo-anonymity can be broken in many circumstances. Thus, users of cryptofinance, including DeFi, have no guarantee that their transactions will remain private. This potential lack of privacy poses problems not only for individuals but also for businesses that would rather not have their financial transactions disclosed to competitors.
In terms of risks created by DeFi, many of them are like the risks that have always been part of traditional finance, including excessive leverage, maturity and liquidity transformation, and so forth. However, important operational differences exist between traditional finance and DeFi that could have significant risk implications. Some of these issues might have solutions, such as whether a blockchain can be made secure and scalable while remaining decentralized. However, many other problems are inherent in blockchains, dapps, and cryptofinance.
At the most basic level is governance of the blockchain and the individual dapps. In theory, the governance of blockchains and dapps is decentralized, with no one party exercising control. In practice, we observe a wide spectrum of governance arrangements. Some governance arrangements are de facto centralized with a small group—typically, the founders—exercising effective control (see, for example, here). Such centralized control facilitates correcting mistakes in programming and adapting to environmental changes. However, such centralization also allows those in control to change the operation of the dapp in ways that benefit themselves. At an extreme, this behavior can take the form of a "rug pull," in which the founders disappear with all the tokens locked in a smart contract. Conversely, as governance becomes more decentralized, making changes to the blockchain protocol or dapp might become more challenging, and the supervisors could have difficulty finding people to address regulatory concerns. Also, decentralization of governance does not guarantee against someone temporarily buying control to enact changes favorable to themselves, nor does it prevent a majority of the voters from taking actions that disadvantage a minority of the voters.
The process of creating new blocks introduces risks for DeFi users. New blocks typically contain multiple transactions with the miner (or validator) who "wins" the competition obtaining control over which transactions get entered in the block and in which order. One result is that the structure of blockchains allows something akin to front-running in traditional markets. The resulting profit accruing to miners (and validators) is called miner's extractable value (as discussed in detail here).
Focusing more specifically on smart contracts, this computer code is subject to two problems. First, mistakes in the programming (bugs) are common in computer code. Of course, traditional financial intermediaries' programs also have bugs. However, the resistance of blockchains to rewriting historical blocks makes reversing errors almost impossible unless the receiver of a payment agrees to reverse the transaction. Second, the code must state (explicitly or implicitly) what will happen in every possible circumstance. Yet as I have previously observed, traditional contracts are often intentionally left incomplete for a variety of good economic reasons.
A third issue related to risk is that of trust. Users of traditional financial intermediaries need to place considerable trust in their intermediary, its regulator, and the judicial system. On the other hand, cryptofinance is described as "trustless," meaning that its user can verify all transactions on a blockchain and inspect the code being used by a dapp. In practice, though, very few people would have the technical skills (or the time) needed to carefully analyze a dapp to find any programming bugs, fully understand the dapp's economic incentives, and understand how that dapp could interact with other dapps. Thus, as a practical matter, almost all users will need to trust third parties if DeFi is to become mainstream.
The issue of trust is exacerbated by something called "censorship resistance," which is a property of public, permissionless blockchains. In principle, anyone can initiate any transaction on a blockchain as long as it complies with the blockchain's protocol. This openness can have benefits, such as preventing governments from trying to financially cripple political opponents. However, it also means that the blockchain is open to every bad actor no matter where they are in the world. As a result, blockchains have been used to facilitate scams, theft, and money laundering. Although similar problems exist in traditional finance, the extent of such problems is reduced by financial intermediaries' incentive to build customer trust, regulators' ability to enforce regulations around financial conduct, and, in some cases, regulators and judicial authorities' ability to enforce the reversal of improper transactions.
One unusual feature of dapps is their interoperability, a potential advantage in that smart contract composability allows for dapps to interoperate and thus provide services and products that are not available from any single dapp. However, such interoperability also creates the risk that if a financial or operational issue arises with one dapp, the problem could spread to other parts of the DeFi ecosystem.
Another risk we discuss in the article is DeFi's interconnections with the traditional financial system. In part, this risk arises because traditional finance and DeFi simply have different mindsets and take different risk-mitigation approaches. Participants in DeFi might not appreciate the potential risks they are incurring from involvement with traditional finance, such as the risks that the investment portfolios of some stablecoins have taken. Similarly, traditional financial institutions might not fully appreciate their risks through DeFi when they interact with crypto finance. Moreover, traditional financial institutions could face greater exposure to legal risk as they—unlike almost all dapps—can be readily identified, and their deep pockets make them attractive targets.
DeFi is opening a new avenue for the provision of financial services and might provide significant benefits. However, alongside exposure to most of the risks incurred in traditional finance, DeFi introduces new risks that arise from its unique operational structure. While DeFi is still a relatively small part of the financial system, policymakers should try to get ahead of developments in this area and decide what regulatory controls would be appropriate.
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