We analytically characterize optimal monetary policy in a multisector economy with menu costs and show that inflation and output should move inversely following sectoral shocks. That is, after negative productivity shocks, inflation should be allowed to rise, and vice versa. In a baseline parameterization, optimal policy stabilizes nominal wages. This nominal wage targeting contrasts with inflation targeting, the optimal policy prescribed by the textbook New Keynesian model in which firms are permitted to adjust their prices only randomly and exogenously. The key intuition is that stabilizing inflation causes shocks to spill over across sectors, needlessly increasing the number of firms that must pay the fixed menu cost of price adjustment compared to optimal policy. Finally, we show in a quantitative model that moving from inflation to nominal wage targeting improves welfare by 0.32% in consumption-equivalent terms.

We study how financial market prices can be used to forecast the likelihood of transformative artificial intelligence. Transformative AI is a double-edged sword: while advanced AI could lead to rapid economic growth, some researchers argue that superintelligence misaligned with human values could pose an existential risk to humanity. Theoretically, we show that either possibility would predict a large increase in long-term real interest rates, due to consumption smoothing. We then use rich cross-country data on real rates and growth expectations to show that, contrary to other recent findings, higher long-term growth expectations do indeed cause higher long-term real interest rates.

I make five conceptual points about optimal monetary and fiscal policy at the zero lower bound (ZLB) in representative agent New Keynesian models, using the simplest possible version of such a model.

1. Monetary policy is typically described as facing a time consistency problem at the zero lower bound; but if ZLB episodes are a repeated game rather than a one-shot game – as is empirically realistic – then the time consistency problem can be easily overcome by reputational effects.
2. The ZLB is not special, in terms of the constraint it creates for monetary policy: an intratemporal rigidity, such as the minimum wage or rent control, creates exactly the same kind of constraint on monetary policy as the intertemporal rigidity of the ZLB.
3. Austerity is stimulus: in the representative agent New Keynesian model, fiscal stimulus works through the change in government spending. Promising to cut future spending – committing to austerity – has precisely the same effect on inflation and the output gap as a decision to raise spending today.
4. Fiscal stimulus can be contractionary, when targeted heterogeneously: if fiscal spending is targeted at certain sectors, this can in fact lower inflation and deepen the output gap.
5. Fiscal policy faces a time consistency problem at the ZLB, just as monetary policy does.

Overall, I suggest that – in this class of models – the power of monetary policy at the ZLB has been underrated, and the power of fiscal policy has been overrated.

We use survey data on macroeconomic expectations, across 89 countries and going back to 1989, to establish four facts about how forecast biases depend on the time horizon of the forecast. The data cover average expectations and horizons from 0 to 10 years. (1) Expectations underreact at a horizon of one year or less. (2) Expectations overreact at horizons of two years or more. (3) Expectations are “too extreme” at all horizons. (4) Overreaction and over-extremity increase with forecast horizon. These four patterns hold across advanced and emerging economies, and across multiple macroeconomic variables. They are inconsistent with several popular models of overreaction, where the degree of overreaction is independent of forecast horizon. Finally, although long-term expectations exhibit stronger overreaction, it is short-term expectations that are most strongly associated with fluctuations in GDP, investment, and the stock market.

We use a theory of apologies to analyze a nationwide field experiment involving 1.5 million Uber ridesharing consumers who experienced late rides. Several insights emerge. First, apologies are not a panacea: the efficacy of an apology and whether it may backfire depend on how the apology is made. Second, across treatments, money speaks louder than words – the best form of apology is to include a coupon for a future trip. Third, in some cases sending an apology is worse than sending nothing at all, particularly for repeated apologies. For firms, caveat venditor should be the rule when considering apologies.

Monetary economics traditionally does not consider a market-based benchmark: when we study trade, we start with a benchmark of free trade; when we study monetary economics, however, we start with a benchmark of central banking. This paper aims to fill that gap. We study competition among unbacked, costless (“fiat”) moneys. First, under flexible prices and perfect competition, there is a first welfare theorem for money: When producers of such moneys have commitment technology — such as blockchain technology — then competition implements the optimum quantity of money. Second, under nominal rigidities where the competing moneys also serve as competing units of account, then competition can also implement the equivalent of “optimal monetary policy” to avoid macroeconomic fluctuations, if the competing moneys pay interest. We show how these results are suitably modified when competition is imperfect, and we also extend the model to consider the cases of backed or costly-to-produce moneys.

We decompose the post-1973 productivity growth slowdown into three causes: structural change (Baumol’s cost disease), input misallocation, and pure productivity effects. We do this by constructing sector-level productivity from 1947 to 2016, using the recent BEA-BLS Integrated Level Production Accounts (Eldridge et al. 2020) adjusted with our own industry-specific markup estimates. We find that Baumol’s cost disease explains ~25% of the productivity slowdown. The magnitude of the input misallocation channel is sensitive to methodology, reflecting uncertainty about whether or not aggregate markups have risen: input misallocation can account for between 0-20% of the productivity slowdown.

Inflation targeting is strictly suboptimal when economic actors have incomplete information about the state of the economy. Nominal income targeting is approximately optimal, and exactly optimal under certain parameterizations. We derive this result in a “Lucas islands” monetary misperceptions model built from, unlike prior work, explicit microfoundations. Agents have knowledge of local productivity and money supply conditions, but must perform a signal extraction problem each period to estimate the aggregate productivity shock and the aggregate money supply shock. Without full information, agents cannot perfectly distinguish between relative price shocks and aggregate shocks, causing monetary policy to affect the real economy. Since the model is built from agents optimizing from first principles, we are able to take a second-order welfare approximation and ask what monetary policy rule is optimal. In contrast to sticky price or sticky information models, inflation and price level targeting are always suboptimal, as price level variation provides useful information to agents. Under log utility, nominal income targeting is optimal.