Session 15: Frontiers of Macroeconomic Research

We use a unique high-frequency micro-dataset to estimate the slope of the primitive form of the New Keynesian Phillips curve, which features marginal cost as the relevant real activity variable. Our dataset encompasses product-level prices, costs, and output within the Belgian manufacturing sector over twenty years, recorded at a quarterly frequency. Leveraging the richness of the data, we adopt a “bottom-up” approach that identifies the Phillips curve’s slope by estimating the primitive parameters that govern firms’ pricing behavior, including the degrees of price rigidity and strategic complementarities in price setting. Our estimates indicate a high slope for the marginal cost-based Phillips curve, which contrasts with the low estimates of the conventional unemployment or output gap-based formulations in the literature. We reconcile the difference by showing that, although the pass-through of marginal cost into inflation is substantial, the elasticity of marginal cost in relation to the output gap is low. Furthermore, through an examination of the transmission of oil shocks, we illustrate how the marginal cost-based Phillips curve offers a transparent means of capturing the impact of supply shocks on inflation.

How do the sources of worker learning change over the lifecycle, and how do these changes affect human capital accumulation and wage growth? We use worker qualification data from Germany and the US to document that internal learning (learning from colleagues) decreases with workers' experience, whereas external learning (on-the-job training) has an inverted U-shape in workers' experience. To shed light on these findings, we build a quantitative search model featuring a two-source learning technology where firms and workers jointly choose learning investments, and the incentives to learn from each of the two sources evolve throughout the lifecycle as the worker's position in the human capital distribution of the firm changes. The calibrated model replicates our empirical findings and suggests that more productive firms provide better learning environments by offering a wider variety of learning options. Quantitative results indicate that internal learning plays a key role in driving the lifecycle increase in wage growth and dispersion due to compensation for the learning spillovers high-skill workers trigger for their colleagues; and that the disruption to internal learning triggered by remote work not only impacts the human capital acquisition of young workers but also depresses the wages of more senior workers since part of their compensation is tied to their ability to teach younger coworkers.

The Moving to Opportunity program, implemented in the 1990s in five US cities, offered vouchers to low income people living in high poverty neighborhoods to move to richer neighborhoods. Such a policy significantly improved the outcomes of the children who, as a result, grew up in a better neighborhood than the one where they were born. The original policy targeted a small number of families. But could it be scaled up? Would the positive effects of the policy extend to the case in which the policy is implemented on a larger scale? We use a general equilibrium model with three neighborhoods, residential choice, and endogenous local spillovers to explore the effects of scaling up this type of voucher programs. We show that, as we scale up the policy, the income gain for the kids of the voucher receivers first increases, but then decreases as a function of the scale because of general equilibrium effects. We explore the effects of the policy, both on impact and over time, on local spillovers, rental rates, inequality, and segregation. We also compare voucher policies with place-based type of policies and show that, while place-based policies may be more effective in reducing income inequality, they would be much less effective in reducing residential segregation by income. We conclude by showing that a place based policy that instead of offering transfers to people invests in the overall quality of the neighborhood is the most likely to improve overall welfare both on impact and over time.

We develop a simple model of relationship lending where lenders have incentives for evergreening loans by offering better terms to firms that are close to default. We detect such lending behavior using loan-level supervisory data for the United States. Banks that own a larger share of a firm’s debt provide distressed firms with relatively more credit at lower interest rates. Building on this empirical validation, we incorporate the theoretical mechanism into a dynamic heterogeneous-firm model to show that evergreening affects aggregate outcomes, resulting in lower interest rates, higher levels of debt, and lower productivity.

Does a rise in temperature decrease the level of GDP in affected countries or the permanent growth rate of their GDP? Differing answers to this question lead prominent estimates of climate damages to diverge by an order of magnitude. This paper combines indirect evidence on economic growth with new empirical estimates of the dynamic effects of temperature on GDP to argue that warming has persistent, but not permanent, effects on growth. We start by presenting a range of evidence that technology flows tether country growth rates together, preventing temperature change from causing them to diverge permanently. We then use data from a panel of countries to show that temperature shocks have large and persistent effects on GDP, driven in part by persistence in temperature itself. These estimates imply projected future impacts that are three to five times larger than level effect estimates and two to four times smaller than permanent growth effect estimates, with larger discrepancies for initially hot and cold countries

This paper develops a new approach to make welfare assessments based on the notion of Dynamic Stochastic weights, or DS-weights for short. We leverage DS-weights to characterize three sets of results. First, we develop an additive decomposition of aggregate welfare assessments that satisfies desirable properties. We show that, for a large class of dynamic stochastic economies with heterogeneous individuals, welfare assessments can be exactly decomposed into four components: i) aggregate efficiency, ii) risk-sharing, iii) intertemporal-sharing, and iv) redistribution. Second, we introduce the notion of normalized welfarist planners, which allows us to revisit how welfarist (e.g., utilitarian) planners make interpersonal welfare comparisons in consumption units. Third, we use DS-weights to systematically formalize new welfare criteria that are exclusively based on one or several of the components of the aggregate decomposition.

This paper explores the positive and normative consequences of government bond issuances in a New Keynesian model with heterogeneous agents, focusing on how the stock of government bonds affects the cross-sectional allocation of resources in the spirit of Samuelson (1958). We characterize the Pareto optimal levels of government bonds and the associated monetary policy adjustments that should accompany Pareto-improving bond issuances. The paper introduces a simple phase diagram to analyze the global equilibrium dynamics of inflation, interest rates, and labor earnings in response to changes in the stock of government debt. The framework also provides a tractable tool to explore the use of fiscal policy to escape the Effective Lower Bound (ELB) on nominal interest rates and the resolution of the 'forward guidance puzzle.' A common theme throughout is that following the monetary policy guidance from the standard Ricardian framework leads to excess fluctuations in income and inflation.

Our central banks set interest rate targets and do not even pretend to control money supplies. How do interest rates affect inflation? We finally have a complete theory of inflation under interest rate targets and unconstrained liquidity. Its long-run properties mirror those of monetary theory: Inflation can be stable and determinate under interest rate targets, including a peg, analogous to a k-percent rule. The zero-bound era is confirmatory evidence. Uncomfortably, stability means that higher interest rates eventually raise inflation, just as higher money growth eventually raises inflation. Sticky prices generate some short-run non-neutrality as well: Higher nominal interest rates can raise real rates and lower output. A model in which higher nominal interest rates temporarily lower inflation, without a change in fiscal policy, is a harder task. I exhibit one such model, but it paints a much more limited picture than standard beliefs. We either need a model with a stronger effect, or to accept that higher interest rates have quite limited power to lower inflation. Empirical understanding of how interest rates affect inflation without fiscal help is also a wide-open question.

We study the power of state-dependent unemployment insurance (UI) to stabilize short-run fluctuations, allowing for arbitrary deviations from full information and rational expectations. Expectations are critical because higher UI generosity raises consumption, to a large extent, by lowering precautionary savings. If UI generosity is indexed to the unemployment rate, households must forecast the unemployment rate to anticipate the policy stance. We estimate unemployment expectations in response to identified aggregate shocks. We quantify the consequences of these imperfect expectations through the lens of a Heterogeneous Agent New Keynesian model. First, we work directly with the estimated forecast errors. Our methodological contribution is to use the non-parametric history of forecast errors and forecast revisions to solve dynamic decisions of optimizing agents. By doing so, we sidestep the need to choose a particular model of belief formation. The estimated model implies that imperfect anticipation substantially affects the stimulative power of UI extensions. Second, we compare alternative ways of implementing UI policies. To run counterfactuals, we estimate a structural model of belief formation. We show that a combination of noisy information and diagnostic expectations fits the data best among a large set of popular alternatives. A UI extension that is announced directly is more stimulative in the very short run than one that is indexed to the unemployment rate.

I develop a tractable sticky-price model, where input-output linkages are formed endogenously. The model delivers cyclical properties of networks that are consistent with those I estimate using sectoral and firm-level data, conditional on identified real and nominal shocks. A novel source of state dependence in nominal rigidities arises: the strength of complementarities in price setting and monetary non-neutrality increase in the number of suppliers that firms optimally choose to have. As a result, the model simultaneously rationalizes the following observed non-linearities in monetary transmission. First, the model produces cycle dependence: the magnitude of real GDP’s response to a monetary shock is procyclical. This occurs because in expansions, the level of productivity is high, encouraging cost-minimizing firms to connect to more suppliers, which makes pricing decisions more coordinated and monetary non-neutrality stronger. Second, there is path dependence: non-neutrality of real GDP is higher following previous periods of loose monetary policy. This happens as under nominal rigidities, higher supply of money makes prices charged by suppliers cheap relative to the cost of in-house labor, encouraging more connections and strengthening pricing complementarities. Third, there is size dependence: larger monetary expansions make the network denser and have a disproportionately larger effect on GDP than smaller expansions. On the other hand, larger monetary contractions shrink the network and generate a disproportionately smaller decrease in GDP. Such size dependence holds even if the probability of price adjustment is state-independent.

We conduct a randomized controlled trial to study the consumption response of French households to unanticipated one-time money transfers of 300 Euros. Using prepaid debit cards, we consider three implementation designs: (i) a transfer without restrictions; (ii) a transfer where any unspent value expires after three weeks; (iii) a transfer subject to a 10% negative interest rate every week. We observe participants’ main bank accounts, such that we can compute the impact of the transfer on their overall spending. We establish five facts about MPCs in this setting. First, we find that participants in the baseline treatment group have an average marginal propensity to consume (MPC) of 22 percent over one month. Second, we find that implementation design matters: the MPC is substantially higher for treatment groups where any remaining balance becomes unusable after three weeks (60%) or where remaining balances are subject to the 10% negative interest rate every week (36%). Third, we document that the cumulative consumption responses are concentrated in the first weeks following the transfer and are flat thereafter. Fourth, we find that there is significant MPC heterogeneity by observed household characteristics, including by liquid wealth, current income, proxies for permanent income, gender, and age. Fifth, we estimate the unconditional distribution of MPCs across households and find that a large fraction of households have high MPCs. These facts are difficult to reconcile with the consumption response in standard Heterogeneous Agent New Keynesian (HANK) models. Furthermore, we observe that households in the treatment groups with a short expiry date or a negative interest rate frequently use other means of payment while still having a sufficient balance on the prepaid card to cover their expenses, indicating that participants see money as non-fungible. Our finding that households consume more when presented with an urgent spending need lends support to theories where the salience of treatments affects economic choices. We conclude that the implementation design and the targeting of transfers can greatly alter the effectiveness of short-run stimulus policies.

In this paper, I build a flexible theoretical model of sovereign borrowing, default, and renegotiation with borrower reputation. There is asymmetric information about the government’s "type", and reputation is the market belief that it is "responsible" and therefore less likely to default. I calibrate the model using data on how countries' credit histories affect the prices they face and validate its predictions about the effects of borrowing on interest rate spreads in the data. Using the model, I show that countries that have recently defaulted have poor reputations because they rapidly run up their debts prior to default, not because the default decision itself is revealing. I also show that, for countries facing non-trivial levels of default risk, the reputational benefits of repayment are less than 0.5 basis points of consumption. Policies that disrupt the signaling motives induced by asymmetric information, such as transparency initiatives or fiscal rules, can have substantial negative implications for welfare (losses of 0.23% − 0.85% of permanent consumption) because they lead to increased overborrowing by the government.

We identify a shock that explains the bulk of fluctuations in the equity risk premium, and show that the shock also explains a large fraction of the business-cycle comovements of output, consumption, employment, and investment. Recessions induced by the shock are associated with reallocation away from full-time labor positions, and towards part-time and flexible contract workers. We develop a novel real model with labor market frictions and fluctuations in risk appetite, where a “flight-to-safety” reallocation from riskier to safer factors of production precipitates a recession that can explain the data, since the safer factors offer lower marginal products in equilibrium.