Macroeconomic Policy Analysis for the 21st Century

3 apr, 2016

År: 2017
Projektledare: Kurt Mitman
Medsökande: Alexandre Kohlhas, Kathrin Schlafmann, Tobias Broer
Anslagsförvaltare: Stockholms universitet
Område: Ekonomi
Belopp: 7 440 601 kr

Vår forskning

Hur påverkas samhället av penning- och finanspolitiken? Vad driver kraftiga uppgångar och nedgångar i bostadspriserna och de effekter detta får på samhället? Hur ska den ekonomiska politiken utformas för att förhindra ännu en finanskris? För att besvara dessa frågor behöver regeringar och centralbanker stiliserade framställningar, eller modeller, av makroekonomin. Genom sin natur abstraherar dessa mycket från komplexiteten i dagens samhällen. De flesta modeller som för närvarande används för policyanalys saknar komponenter som är avgörande för att utforma en bra politik. Detta projekt syftar till att skapa bättre modeller för policyanalys genom att berika dem i tre empiriskt relevanta dimensioner. Först ersätter vi den representativa konsumenten med heterogena hushåll som skiljer sig åt vad gäller inkomst, förmögenhet och sysselsättningsstatus. Detta är avgörande, inte minst för att analysera politikens fördelningspolitiska konsekvenser. Vidare beskriver vi arbets- och bostadsmarknaderna på ett mer realistiskt sätt. Istället för perfekta marknader där säljare och köpare kostnadsfritt och omedelbart möts modellerar vi en tids- och resurskrävande sök- och matchningsprocess på dessa marknader. Slutligen introducerar vi heterogena och inte nödvändigtvis korrekta förväntningar hos hushållen om den framtida utvecklingen av ekonomiska variabler. Vi tror att vårt rikare och mer realistiska ramverk kommer göra det möjligt att bättre vägleda den ekonomiska politiken i Sverige och annorstädes.

Research

How do monetary and fiscal policy affect the economy? What drives booms and busts in house prices, and their impact on the economy? How should macro-prudential policies be designed to prevent another financial crisis? The recent Global Financial Crisis and ensuing Great Recession have brought these questions to the forefront of policy analysis and revealed the serious shortcomings of the prevailing paradigm at the heart of macroeconomics. The field of macro has been dominated for the past several decades by representative-agent dynamic stochastic general equilibrium (DSGE) models–models whose main elements are derived from microeconomic theory, but that are inconsistent with vast empirical micro evidence on consumer behaviour. We can do better.
All changes in policy differentially affect households. Whether based on income, wealth or employment status, most policies have non-trivial distributional consequences. Representative-agent DSGE models, by construction, are unable to speak to issues of inequality, limiting their usefulness for any meaningful policy evaluation. To make progress in positive and normative analysis in macro requires methodological innovations and moving beyond representative-agent DSGE to models that explicitly allow for households to differ.

To that end, the aim of this proposal is to develop rich macroeconomic models that are not only micro-founded, but also micro-consistent–that is consistent with empirical microeconomic evidence on household behaviour, expectations and outcomes. We are by no means the first to propose or develop macroeconomic models with household heterogeneity (e.g., seminal contribution by Huggett 1993). The first generation of heterogeneous-agent models introduced one friction: incomplete financial markets. The models were primarily focused on the transmission from macro to micro–how aggregate shocks or policy changes differentially affected households based on their characteristics. The transmission from micro to macro, in contrast, turned out not to be very important. The model economy in Krusell and Smith (1998), for example, behaved much like a model with a representative household. However, very recent work suggests that it is the interaction of multiple frictions in heterogeneous agent models that gives rise to micro-consistent behaviour that significantly affect aggregate outcomes. For example, our own work, Krueger, Mitman and Perri (2016), found that the combination of empirically observed wealth inequality and increased unemployment risk led to significant amplification of the consumption decline during recessions. Importantly, the starting point was the observation made from household micro data that low wealth households increase their savings rate the most in recessions. That led to building a model that could explain those micro facts, which in the macro context implied significant amplification.

To build micro-consistent macro models requires starting from the ground up with micro data on household decisions. Insights from empirical micro studies are crucial for determining the types of frictions that need to be included. The extent to which these various frictions interact ultimately determines the magnitude of the transmission from micro to macro, but micro evidence suggests a potentially important role. Take, for example, the analysis of fiscal policy when the economy is in a liquidity trap. The question is inherently a macro one, requiring a model of the entire economy. However, for such a model to be credible it has to be built with households that behave in a way that is consistent with the large micro literature on consumption responses to transfer payments (e.g., Johnson, Parker and Souleles 2006). That literature finds large consumption responses–much larger than implied by representative agent models–suggesting that a model that is consistent with that micro behaviour will behave very differently than current models. Our key innovation is identifying the relevant micro consumer behaviour that relates to the macro question being asked, and then building the aggregate economy around the core partial-equilibrium model that can explain the micro facts. To do so will require introducing a combination of empirically motivated frictions–from incomplete markets to unemployment risk to search in the housing market to default on debt–and potential departures from full information rational expectations at the household level. Our richer model environments will enable us to take a fresh look at the questions raised above and hopefully provide answers that can guide policy analysis in the 21st century.