Getting Government Involved
How Costly Is Permitting in Housing Development?
Evan Soltas & Jonathan Gruber
Princeton Working Paper, February 2026
Abstract:
Permitting costs are widely cited, but little analyzed, as a key burden on housing development in leading U.S. cities. We measure them using an implicit market for “ready-to-issue” permits in Los Angeles, where landowners can prepay permitting costs and sell preapproved land to developers at a premium. Using a repeat-listing difference-in-differences estimator, we find developers pay 50 percent more ($48 per square foot) for preapproved land. Comparing similar proposed developments, preapproval raises the probability of completing construction within four years of site acquisition by 10 percentage points (30 percent). Permitting can explain one third of the gap in Los Angeles between home prices and construction costs.
Distributional Effects of Residential Zoning Policies: Insights from the Greater Boston Area
Dongyang He
Pennsylvania State University Working Paper, February 2026
Abstract
This paper quantifies the distributional effects of zoning regulations through a dwelling production model that endogenizes floor area ratio (FAR) and density — capturing how regulations prohibit specific housing types rather than simply reducing aggregate supply. The model generates a "minimum dwelling cost" — the price of the cheapest available housing in each location — and quantifies how zoning raises this affordability barrier. This housing supply model is embedded in a spatial equilibrium framework with heterogeneous households. Applied to the Greater Boston Area using property-level housing data and parcel-level zoning information across 530 census tracts, structural estimates indicate that zoning increases the minimum dwelling cost approximately fivefold. Counterfactual simulations reveal substantial distributional effects: removing zoning from the 2018 baseline would increase welfare for the lowest-income decile of renters by 34.5%, while higher-income groups (approximately 80% of residents) experience losses of 1.4-2.6%. Property values would decline 2.6% on average, with substantial spatial heterogeneity: 60% of tracts would experience gains, while 18% would face declines exceeding 10%. These patterns — with most current residents losing from reform — help explain the political persistence of restrictive zoning.
The Impact of Short-Term Rental Regulations on Urban Spending: Evidence from Transactional Data
Kaihang Zhao, Tal Shoshani & Davide Proserpio
University of Southern California Working Paper, March 2026
Abstract:
We examine the effects of short-term rental (STR) regulations on urban service markets, focusing on the restaurant industry. Our setting is New York City’s 2023 STR regulation, which took effect in September 2023 and is among the most restrictive policies in the United States. The regulation triggered a sharp contraction in the supply of Airbnb listings across the city. Using restaurant-month-level credit and debit card transaction data, combined with a matched difference-in-differences design, we find that the policy led to an 8.7% decline in total restaurant spending, a 7.1% reduction in transaction volume, and a 1.3% decrease in average spending per customer. These effects are consistent with a mechanism in which restricting STR supply raises accommodation costs, reducing tourist inflows, and lowering discretionary spending among visitors who continue to travel despite higher prices. We provide further support for this interpretation through three complementary analyses. First, the negative effect is significantly larger for higher-priced restaurants and establishments catering to tourists, consistent with a contraction in discretionary and tourism-driven demand. Second, we document a 3.5% to 4.3% decline in passenger arrivals at New York City’s major airports following the regulation, indicating a reduction in overall tourist inflows. Third, we show that neighboring markets — most notably New Jersey — experience increased restaurant spending, suggesting spatial displacement of tourism activity. Taken together, our findings highlight that STR regulations can have economically meaningful consequences beyond the housing market, underscoring the importance of accounting for downstream impacts on local service industries when designing urban housing policies.
The redistribution of housing wealth caused by rent control
Kenneth Ahern & Marco Giacoletti
Journal of Urban Economics, March 2026
Abstract:
This paper studies the effects of rent control on the housing wealth of renters, landlords, and homeowners. Following the passage of rent control in St. Paul, Minnesota in 2021, average property values fell by 4.0% to 5.5%. Leveraging parcel-level data, we show that in the aggregate, renters gained and landlords lost, though upper-income renters gained more than lower-income renters, while small landlords lost the same as large landlords. Owner-occupants’ wealth also fell significantly from direct capitalization effects and negative externalities. These results provide the first evidence on the heterogeneous wealth effects of a wave of new rent control laws.
Minimum Resale Price Maintenance Can Reduce Prices
Jacob Burgdorf & Michael Sacks
U.S. Department of Justice Working Paper, February 2026
Abstract:
Theories suggesting that minimum resale price maintenance (RPM) are pro-competitive typically rely on inducing costly investments by downstream firms that are valued by consumers. We present a model in which minimum RPM can be implemented by an upstream monopolist with many downstream retailers that benefits consumers independent of the provision of complementary services or inventory effects. Minimum RPM disrupts coordination by downstream firms that sustains the monopoly price, leading to lower retail prices and higher retail quantities. Counter-intuitively, therefore, a binding minimum resale price can reduce retail prices, which increases consumer surplus and can also increase aggregate producer surplus.
Chaos and Misallocation under Price Controls
Brian Albrecht, Alex Tabarrok & Mark Whitmeyer
George Mason University Working Paper, February 2026
Abstract:
Price controls kill the incentive for arbitrage. We prove a Chaos Theorem: under a binding price ceiling, suppliers are indifferent across destinations, so arbitrarily small cost differences can determine the entire allocation. The economy tips to corner outcomes in which some markets are fully served while others are starved; small parameter changes flip the identity of the corners, generating discontinuous welfare jumps. These corner allocations create a distinct source of cross-market misallocation, separate from the aggregate quantity loss (the Harberger triangle) and from within-market misallocation emphasized in prior work. They also create an identification problem: welfare depends on demand far from the observed equilibrium. We derive sharp bounds on misallocation that require no parametric assumptions. In an efficient allocation, shadow prices are equalized across markets; combined with the adding-up constraint, this collapses the infinite-dimensional welfare problem to a one-dimensional search over a common shadow price, with extremal losses achieved by piecewise-linear demand schedules. Calibrating the bounds to station-level AAA survey data from the 1973-74 U.S. gasoline crisis, misallocation losses range from roughly 1 to 9 times the Harberger triangle.
Watchdog or Showdog? Spotlight Chasing in Antitrust Enforcement
Tianshu Lyu & Zunda Winston Xu
Stanford Working Paper, December 2025
Abstract:
We study how an acquirer's public visibility affects antitrust enforcement in mergers and its real economic consequences. Using a novel dataset linking FTC and DOJ inspection outcomes to news coverage of merger parties, we find that a 10 percent increase in the acquirer's share of industry news coverage raises the likelihood of being flagged by 1.5 to 3 percent. We establish causality using geographical proximity to media outlets as an exogenous source of variation in news coverage. We interpret these results through a political‐accountability framework: higher visibility raises the reputational stakes of enforcement, leading regulators to challenge more visible acquirers. Consistent with this accountability framework, the visibility gradient strengthens during congressional appropriations hearings and disappears in lame-duck periods. It is also substantially stronger in consumer-facing industries, where accountability pressures are highest. Finally, visibility-driven scrutiny has real effects: overlooked low-visibility deals gain market power, while flagged acquirers expand inefficiently and face a higher financial burden. Our results highlight how public salience distorts merger review and generates persistent post-merger inefficiencies.
The Demand for Bullshit and Its Improbable Legal Solutions
Jane Bambauer & Lila Greenberg
University of Florida Working Paper, February 2026
Abstract:
Americans consume a lot of bullshit. Verifiable falsehoods and intentional disinformation are in the mix, but the biggest contributors to the pile are sloppy, vague, and cherrypicked content that reinforces preexisting beliefs. Policymakers typically blame supply: new media outlets that fail to meet journalistic standards or social media platforms that amplify clickbait and extreme content. As a result, legal responses have attempted to reduce bullshit by managing supply through competition policy, must-carry rules, and consumer protection laws. These interventions are flawed because they stem from a misdiagnosis. Bullshit is primarily a problem of consumer demand. News consumers prioritize social belonging, stability, and intellectual ease over truth-seeking, and media organizations must oblige if they want to survive. This Article reorients the policy discussion of misinformation around audience capture and demand-side factors. It distinguishes bullshit from misinformation, critiques supply-side theories, and advances a demand-side account that better explains our democratic and epistemic predicament. It then evaluates legal reforms, showing why many are ineffective, counterproductive, or unconstitutional, and concludes by sketching three alternative approaches that the government could take: (1) treating media as a widely-shared vice, (2) helping to make truth-seeking more financially or socially rewarding, and (3) fostering a culture of critical thinking.
Open Code, Unequal Access: How Complementary Skills and Local Talent Shape Responses to Open-Source Releases
Manav Raj & Anavir Shermon
University of Pennsylvania Working Paper, February 2026
Abstract:
While open-source technologies lower the cost of accessing advanced tools, it remains unclear which establishments are particularly likely to act on these opportunities. Such cost reductions could democratize investment by making it easier for less-endowed establishments to find and invest in technology-related human capital or instead amplify existing advantages if establishments with complementary capabilities or in talent-rich markets are best positioned to respond. We study how U.S. high-tech establishments responded to Google's unexpected open-source release of TensorFlow, which sharply reduced the cost of acquiring AI-related skills. Using data from Revelio Labs and a matched difference-in-differences design, we show that establishments with complementary skills and those in talent-rich labor markets increased AI human-capital investments the most following the open-source release of TensorFlow. These factors also shaped how establishments invested in AI human capital, with complementary skills associated with internal redeployment and external hiring, and local talent driving external hiring alone. The findings reveal that while open sourcing enables widespread access to advanced tools, it does not necessarily democratize establishments' investment in them.
Patent Privateering
Jinhwan Kim et al.
Stanford Working Paper, December 2025
Abstract:
In a patent privateering strategy, firms sell patents to a non-practicing entity (NPE) with the expectation that the NPE sues the seller's rivals for patent infringement. We examine whether firms under competitive pressure and facing barriers to direct litigation engage in privateering. We find that firms facing technological competition and retaliation risk sell more patents to NPEs, and that these patents are disproportionately asserted against the original owner's competitors. Privateering sales are especially pronounced among firms in technology areas characterized by frequent litigation or extensive collaboration. Contrary to the view that small firms use NPEs to enforce patent rights, privateering-motivated sales are concentrated among well-resourced firms. Following privateering sales, peers reduce both their patenting activity and participation in the technology space, suggesting that privateering reshapes the competitive landscape. Our findings highlight an overlooked player in the policy debate over patent trolls: the firms that "feed" the trolls in the first place.
An Audit of Social Science Survey Experiments
Tamkinat Rauf et al.
Public Opinion Quarterly, Winter 2025, Pages 1063-1086
Abstract:
Survey experiments have become a popular methodology for causal inference across the social sciences. We study the efficacy of survey experiment designs by analyzing 100 social science experiments — entailing more than 1,000 hypothesis tests — that were selected by experts via a competitive process and fielded on probability samples of US adults between 2012 and 2020. Inclusion in the analysis is only conditional on the experiment qualifying for data collection, and not in any way on study results or publication. Results show that less than a third of proposed hypotheses were supported by the data, implying many more null findings than ostensibly appear in the published literature. We find that the largest predictor of positive experimental results was sample size. This is somewhat surprising, given that experimental studies typically take power considerations into account prior to data collection. In our data, the importance of sample size stemmed from small effect sizes across studies (perhaps smaller than researchers may have anticipated), highlighting a tension between commonly used power calculi and determining what constitutes a “meaningful effect.” We also find that moderation hypotheses were rarely significant, and that using multiple items for outcome measures did not affect results as expected. But indicators of research experience predicted higher rates of positive results, suggesting that there may be some room for optimizing experiment outcomes by minimizing design errors.
GPT as a Measurement Tool
Hemanth Asirvatham, Elliott Mokski & Andrei Shleifer
NBER Working Paper, February 2026
Abstract:
We present the GABRIEL software package, which uses GPT to quantify attributes in qualitative data (e.g. how “pro innovation” a speech is). GPT is evaluated on classification and attribute rating performance against 1000+ human annotated tasks across a range of topics and data. We find that GPT as a measurement tool is accurate across domains and generally indistinguishable from human evaluators. Our evidence indicates that labeling results do not depend on the exact prompting strategy used, and that GPT is not relying on training data contamination or inferring attributes from other attributes. We showcase the possibilities of GABRIEL by quantifying novel and granular trends in Congressional remarks, social media toxicity, and county-level school curricula. We then apply GABRIEL to study the history of tech adoption, using it to assemble a novel dataset of 37,000 technologies. Our analysis documents a tenfold decline of time lags from invention to adoption over the industrial age, from ~50 years to ~5 years today. We quantify the increasing dominance of companies and the U.S. in innovation, alongside characteristics that explain whether a technology will be adopted slowly or speedily.