House Prices and Consumer Spending

Berger, David; Guerrieri, Veronica; Lorenzoni, Guido; Vavra, Joseph

doi:10.3386/w21667

Cited by 112 publications

(169 citation statements)

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“…36 This effect is variously referred to as a wealth effect, an endowment income effect or an endowment effect. Berger et al (2017) distinguish between an endowment income (wealth) effect, an ordinary income effect, a substitution effect and a collateral effect in the transmission of house prices to consumption. Year of the boom.…”

Section: Consumptionmentioning

confidence: 99%

The Housing Boom and Bust: Model Meets Evidence

Kaplan

Mitman

Violante³

2017

109

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We thank numerous seminar participants and discussants for useful comments. In particular, we are grateful to ABSTRACTWe build a model of the U.S. economy with multiple aggregate shocks (income, housing finance conditions, and beliefs about future housing demand) that generate fluctuations in equilibrium house prices. Through a series of counterfactual experiments, we study the housing boom and bust around the Great Recession and obtain three main results. First, we find that the main driver of movements in house prices and rents was a shift in beliefs. Shifts in credit conditions do not move house prices but are important for the dynamics of home ownership, leverage, and foreclosures. The role of housing rental markets and long-term mortgages in alleviating credit constraints is central to these findings. Second, our model suggests that the boom-bust in house prices explains half of the corresponding swings in non-durable expenditures and that the transmission mechanism is a wealth effect through household balance sheets. Third, we find that a large-scale debt forgiveness program would have done little to temper the collapse of house prices and expenditures, but would have dramatically reduced foreclosures and induced a small, but persistent, increase in consumption during the recovery.3 It follows that, if foreclosure had very large externalities on house prices (which is not the case in our model), the principal reduction program might have a larger effect on prices. The empirical literature mostly estimates economically small and extremely localized effects (Anenberg and Kung, 2014;Gerardi, Rosenblatt, Willen, and Yao, 2015). See, however, Guren and McQuade (2015) for an alternative view. 4 In either case, it is essential that the shock is to future housing preferences or buildable land, rather than current housing preferences or buildable land. Otherwise, consumption or residential investment, respectively, would counterfactually fall during the boom and rise during the bust.

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Section: Consumptionmentioning

confidence: 99%

The Housing Boom and Bust: Model Meets Evidence

Kaplan

Mitman

Violante³

2017

109

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“…10 The empirical value of Mian et al's estimates is that they are quite informative about the "consumption block" of macroeconomic models. They strongly reject simple complete markets models of consumption such as the influential model of Sinai and Souleles (2005)-in which the elasticity of consumption to house prices is zero-in favor of models with life-cycle effects, uninsurable income risk, borrowing constraints, and in which households can substitute away from housing when its price rises (see, e.g., Berger et al (2017) for a discussion of such a model). This latter class of models has quite different implications about the effects of macroeconomic policies such as fiscal and monetary policy-but also housing policy-than the former class of models.…”

Section: Causal Effects As Identified Momentsmentioning

confidence: 99%

Identification in Macroeconomics

Nakamura¹,

Steinsson²

2017

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This paper discusses empirical approaches macroeconomists use to answer questions like: What does monetary policy do? How large are the effects of fiscal stimulus? What caused the Great Recession?Why do some countries grow faster than others? Identification of causal effects plays two roles in this process. In certain cases, progress can be made using the direct approach of identifying plausibly exogenous variation in a policy and using this variation to assess the effect of the policy. However, external validity concerns limit what can be learned in this way. Carefully identified causal effects estimates can also be used as moments in a structural moment matching exercise. We use the term "identified moments" as a short-hand for "estimates of responses to identified structural shocks," or what applied microeconomists would call "causal effects". We argue that such identified moments are often powerful diagnostic tools for distinguishing between important classes of models (and thereby learning about the effects of policy). To illustrate these notions we discuss the growing use of cross-sectional evidence in macroeconomics and consider what the best existing evidence is on the effects of monetary policy.

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“…As a final note, while Berger, Guerrieri, Lorenzoni, and Vavra (2015) use a fully rational framework to derive equation 6, it is useful to note that marginal propensities to consume may vary across the population due to behavioral biases such as hyperbolic discounting in addition to borrowing constraints (see Harris and Laibson (2001)). …”

Section: Models Most Closely Related To These Factsmentioning

confidence: 99%

Who Bears the Cost of Recessions? The Role of House Prices and Household Debt

Mian¹,

Sufi²

2016

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This chapter reviews empirical estimates of differential income and consumption growth across individuals during recessions. Most existing studies examine the variation in income and consumption growth across individuals by sorting on ex ante or contemporaneous income or consumption levels. We build on this literature by showing that differential shocks to household net worth coming from elevated household debt and the collapse in house prices play an underappreciated role. Using zip codes in the United States as the unit of analysis, we show that the decline in numerous measures of consumption during the Great Recession was much larger in zip codes that experienced a sharp decline in housing net worth. In the years prior to the recession, these same zip codes saw high house price growth, a substantial expansion of debt by homeowners, and high consumption growth. We discuss what models seem most consistent with this striking pattern in the data, and we highlight the increasing body of macroeconomic evidence on the link between household debt and business cycles. Our main conclusion is that housing and household debt should play a larger role in models exploring the importance of household heterogeneity on macroeconomic outcomes and policies.

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House Prices and Consumer Spending

Cited by 112 publications

References 20 publications

The Housing Boom and Bust: Model Meets Evidence

The Housing Boom and Bust: Model Meets Evidence

Identification in Macroeconomics

Who Bears the Cost of Recessions? The Role of House Prices and Household Debt

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