Item-level transactions data yield cost-of-living indices that can account for quality change and consumer substitution. Transactions data require confronting the rapid turnover of items because prices of new and existing products are interrelated in equilibrium. This paper evaluates multiple approaches to measuring quality change at scale. It shows that a hedonic superlative approach—using econometrics or machine learning for hedonic estimation combined with index formulas that require simultaneous observation of item-level price and expenditure—yields improved measures of the cost of living. Accounting for ubiquitous quality change and for consumer substitution yields lower measures of inflation than traditional, official methods

Lack of market transparency can impair the liquidity provision of nonstandard liquidity suppliers and make liquidity demand increasing in illiquidity. This can yield strategic complementarities and induce multiple equilibria. Then an initial dearth of liquidity may degenerate into a liquidity rout (as in a “flash crash”), and traders faced with the largest cost of trading are those trading more intensely at equilibrium. An increase in order flow transparency and/or in the mass of dealers who are in the market at all times has a positive impact on total welfare.

We show remote work led to large drops in lease revenues, occupancy, and market rents in the commercial office sector. We revalue New York City office buildings, taking into account both the cash flow and discount rate implications of these shocks, and find a 46 percent decline in long-run value. For all US office markets combined, we find a $556.8 billion value destruction. Higher-quality buildings were buffered against these trends due to a flight to quality, while lower-quality offices are at risk of becoming a stranded asset. These valuation changes have repercussions for financial stability and local public finances

We show that subjective assessments of employee “potential” contribute to gender gaps in promotion and pay. Using data on 29,809 management-track employees from a large retail chain, we find that women receive substantially lower potential ratings despite receiving higher performance ratings. Differences in potential ratings account for approximately half of the gender promotion gap. Women’s lower potential ratings do not reflect accurate forecasts of future performance: Women subsequently outperform male colleagues, both on average and on the margin of promotion. We highlight two mechanisms driving the gender potential gap: strategic retention and stereotyping.

This paper estimates the effects of improving public transit infrastructure on city structure and welfare. It develops a quantitative urban model with multiple worker groups and transit modes, and derives a special case yielding sufficient statistics for aggregate welfare in a broad class of models. The paper estimates reduced-form elasticities to implement the approach using data spanning construction of the world’s largest Bus Rapid Transit system in Bogotá, Colombia. This class of models explains observed adjustments in economic activity. Standard value-of-time calculations capture only 52 percent of welfare gains. Accounting for reallocation and general equilibrium effects, distributional impacts are modest

What is the optimal response of a resource exporter when a price cap is imposed on its main export? This paper develops a dynamic framework incorporating stochastic prices, financial frictions, and market power to study this novel tool of statecraft. With the right design, a price cap can incentivize increased extraction, stabilizing prices in the global market. But the stabilizing effects diminish when there is leakage outside the cap. Consequently, weak enforcement of the policy worsens the trade-off faced by the sanctioning policymaker. We provide a systematic approach to setting and enforcing an optimal cap level in these circumstances

We study optimal monetary policy during times of global scarcity of tradable goods. The optimal monetary response entails a surge in inflation, which helps rebalance production toward the tradable sector. While the inflation costs are fully borne domestically, however, the gains in terms of higher supply of tradable goods partly spill over to the rest of the world. National central banks may thus fall into a coordination trap and implement an excessively tight monetary policy causing an unnecessarily sharp global contraction.

We develop a simple multilayer network model in which agents allocate effort across layers with heterogeneous structures, subject to an aggregate effort constraint. Incentives are shaped by agents’ network positions within each layer, and equilibrium behavior reflects both within- and cross-layer interactions. We analyze how shocks propagate through the network and characterize optimal targeting interventions. Our results show that effective policy design must account for effort allocation across layers. We also demonstrate that predictions from monolayer models can diverge sharply from those of multilayer models, underscoring the importance of accounting for network complexity in both empirical and policy analyses.

Digitization reforms have been hailed as an effective way of strengthening state capacity. However, digitization can also fundamentally reshape the organization of bureaucracies. Using a unique administrative dataset on agricultural taxation and surveys of local bureaucrats from Punjab, Pakistan, we show that digitization reforms can have unintended consequences for state capacity. We exploit the staggered rollout of the digitization of land records in Punjab to show that digitization had a negative effect on tax collection. The fall in taxes was not due to a decrease in the tax base. Instead, digitization affected the bureaucrats’ capacity to collect taxes.

We revisit the role of temporary layoffs in the business cycle. While some have emphasized a stabilizing effect due to recall hiring, we quantify from the data an important countercyclical destabilizing effect due to “loss-of-recall,” whereby workers in temporary-layoff unemployment lose their job permanently. We develop a quantitative model allowing for endogenous flows of workers across employment and both temporary-layoff and jobless unemployment. The model captures both pre- and post-pandemic unemployment dynamics, including the contractionary role of loss-of-recall. We use our structural model to show that the Paycheck Protection Program generated sizable employment gains, in part by significantly reducing loss-of-recall.