Journal of Monetary Economics最新文献

In OECD countries, the labor market features a coexistence of open-ended, permanent jobs subject to strict employment protection and fixed-term, temporary jobs. This paper studies a search-and-matching model with risk-averse workers and dynamic employment contracts subject to limited commitment. In equilibrium, permanent and temporary jobs coexist when the match quality is sufficiently dispersed: firing costs generate insurance gains implying that permanent contracts are optimal for high-quality matches. Consistent with recent empirical evidence, quantitative analysis of the model shows that temporary contracts crowd out permanent jobs and do not generate employment gains.

We develop a core–periphery model with financial frictions and cross-border banking to assess the magnitude of regulatory spillovers and the gains from macroprudential policy coordination. A core global bank lends to its affiliates in the periphery and banks in both regions are subject to risk-sensitive capital regulation. Following an expansionary monetary policy in the core, a countercyclical response in capital requirements in that region induces the global bank to increase cross-border lending. We calculate welfare gains associated with countercyclical capital buffers under a range of policy regimes, including independent policymaking, full coordination, and reciprocity—a regime in which capital ratios set in the core are imposed on the global bank’s affiliates abroad. One of our key results is that, even when regulatory spillovers are strong, reciprocity can make all parties better off if regulators attach a sufficient weight to financial stability considerations. With a standard, utility-based welfare criterion, reciprocity may also perform better than independent policymaking when regulatory spillovers are weak.

The proposed blended approach combines identification via heteroskedasticity with sign/narrative restrictions, and instrumental variables. Since heteroskedasticity can point identify shocks, its use results in a sharp reduction of the potentially large identified sets stemming from other approaches. Conversely, sign/narrative restrictions or instrumental variables offer natural solutions to the labeling problem and can help when conditions for point identification through heteroskedasticity are not met. Blending these methods together resolves their respective key issues and leverages their advantages. We illustrate the benefits of the approach in Monte Carlo experiments, and apply it to several examples taken from the literature.

Is excessive risk-taking in credit cycles driven by incentives or biased beliefs? I propose a framework suggesting that the two are actually related and, specifically, that procyclical overoptimism can arise rationally from risk-taking incentives. I show that when firms and banks have a limited liability payoff structure, they have lower incentives to pay attention to the aggregate conditions that generate risk. This leads to systematic underestimation of the accumulation of risk during economic booms and overoptimistic beliefs. As a result, agents lend and borrow excessively, further increasing downside risk. Credit cycles driven by this new “uninformed” risk-taking are consistent with existing evidence such as high credit and low-risk premia predicting a higher probability of crises and negative returns for banks. My model suggests that regulating incentives can decrease overoptimistic beliefs and thus mitigate boom-and-bust cycles.

Surprise changes in monetary policy rates have a causal impact on credit risk measures, which display a significant post-FOMC drift. I employ a tight identification strategy to decompose the influence of firm-specific and creditor-specific factors across horizons. Firms with narrower income gaps and lower Tobin’s Q ratios exhibit heightened sensitivity at both short and long horizons. Bonds predominantly held by bond funds demonstrate only temporarily more sensitivity, indicating that credit market segmentation fails to account for the observed drift. Aggregate broker dealer capital scarcity is linked to an amplified response in the drift component. A large portion of the drift remains unexplained, revealing the limitations of cross-sectional characteristics in explaining the transmission mechanism.

We employ a nonlinear vector autoregression and a non-recursive identification strategy to show that an equal-sized uncertainty shock generates a larger contraction in real activity when growth is low (as in recessions) than when growth is high (as in expansions). An estimated New Keynesian model with recursive preferences replicates these state-contingent responses when approximated to third order around its risky steady state due to a stronger upward nominal pricing bias in recessions than in expansions. Empirical evidence supports this state-contingent channel, and we show that it can greatly reduce the ability of systematic monetary policy to stabilize output during recessions.

Recent survey evidence reveals misaligned inflation expectations among economic agents. While households associate higher expected inflation with lower output growth, professional forecasters link higher future inflation to higher output growth. Firms’ expectations display neither negative nor positive correlations. We explain such patterns jointly in a general equilibrium New Keynesian framework. Asymmetric information arises naturally as (i) households and firms receive imperfect, asymmetric information about supply and demand shocks, and (ii) the central bank learns from equilibrium outcomes (i.e., output and inflation) as opposed to the private sector. Survey data help uncover the magnitudes of information frictions among economic agents.

The empirical literature often uses disagreement (dispersion in forecasts) as a proxy for uncertainty, yet disagreement and uncertainty behave differently throughout the business cycle. The difference is especially salient in non-crisis periods, in which measures of disagreement are positively correlated with growth, while measures of uncertainty are negatively correlated with it. I explain this finding using a noisy information model with endogenous learning. In the model, agents observe noisy private information, but only when they are active. Holding uncertainty fixed, a rise in activity introduces noisy information to the market, and agents’ beliefs diverge, i.e., disagreement rises.

Using the Spanish Christmas lottery as a natural experiment, the impact of geographically clustered lottery winnings on consumer sentiment and intended durable consumption is analyzed. Albeit not receiving lottery prizes, consumers in winning provinces become significantly more optimistic about the Spanish macroeconomic conditions than those living elsewhere. This variation in sentiment is shown to be orthogonal to changes in regional fundamentals and leads to a rise in spending intentions. Young, less educated, low-income, and unemployed individuals react stronger to the lottery shock. At the regional level, lottery wins significantly increase car licenses, reduce unemployment, and intensify job creation and prices.

How effective are forward-guidance and make-up strategies? Standard models find them extremely effective, but by assuming households’ inflation expectations respond much more strongly than in the data. Models where households discount the future find them much less effective and match the small reaction of inflation expectations, but not the actual large reaction of asset prices. We build a model that rationalizes both. Households cognitively discount the future, but more forward-looking financial market professionals incorporate their expectations of future policy into the long-term nominal rates faced by all. We find that make-up strategies have sizably better stabilization properties than inflation targeting.