Economic Fluctuations and Growth Research Meeting

February 5, 2010
Andrew Atkeson and Harald Uhlig, Organizers

Ricardo Lagos, New York University, Guillaume Rocheteau, UC, Irvine, and Pierre-Olivier Weill, UC, Los Angeles and NBER
Crises and Liquidity in Over-the-Counter Markets

Lagos, Rocheteau, and Weill study the efficiency of dealers’ liquidity provision and the desirability of policy intervention in over-the-counter (OTC) markets during crises. Their theory emphasizes two key frictions in OTC markets: that finding counterparties takes time, and that trade is bilateral, with quantities and prices determined by bargaining. The researchers model a crisis as a negative shock to investors’ asset demands that lasts until a random recovery time. In this context, dealers can provide liquidity to outside investors by acting as counterparties in trades and by accumulating asset inventories. The authors find that, when frictions are severe, even well capitalized dealers may not find it optimal to accumulate inventories, given that investors choose asset positions that require small re-allocations. In such circumstances, welfare can increase if the government steps in, purchases private assets on its own account, and resells them when the economy recovers.

Francois Gourio,Boston University and NBER
Disaster Risk and Business Cycles

Gourio proposes a tractable business cycle model with large, volatile, and countercyclical risk premia. Risk premia are driven by a small, exogenously time-varying risk of economic disaster, and macroeconomic aggregates respond to this time-varying risk. The model is consistent with the second moments of quantities and of asset returns, and matches well the relations between quantities and asset prices. An increase in the probability of disaster leads to a collapse of investment and a recession, with no current or future change in productivity. Demand for precautionary savings increases, leading yields on safe assets to fall, while spreads on risky securities increase. To assess the empirical validity of the model, Gourio infers the probability of disaster from observed asset prices and feeds it into the model. The variation over time in this probability appears to account for a signi?ficant fraction of business cycle dynamics, especially the sharp downturns in investment and output such as in the last quarter of 2008. This is consistent with the then-widespread fear of a repeat of the Great Depression.

Veronica Guerrieri, University of Chicago and NBER, Daniel Hartley, Federal Reserve Bank of Cleveland, and Erik Hurst, University of Chicago and NBER

Endogenous Gentrification and Housing Price Dynamics

Guerrieri, Hartley, and Hurst explore differential changes in house prices across neighborhoods within a city to better understand the nature of house price dynamics across cities. They do this by proposing a previously unexplored mechanism through which individual utility is increasing in the income of one's neighbors. Instead of proximity to jobs, it is proximity to "richer" people that drives differences in land prices within and across cities. In the model, segregation by income occurs: richer households are concentrated together with poorer households living in the periphery. In response to a positive increase in housing demand (for example, a decrease in the interest rate, an increase in city-wide income, or an influx of richer households), richer households expand into adjacent poorer neighborhoods. This is what we term "endogenous gentrification". As richer households expand into poorer neighborhoods, land values in those neighborhoods increase, which drives house prices up. The model also predicts that the city-wide responsiveness of house prices to a given demand shock will depend on the income distribution within the city. As a result, richer cities are predicted to respond more to the housing demand shock, even if housing supply is perfectly elastic, because they experience a higher degree of gentrification. Using a variety of different data sources, the autjprs show that the data are consistent with many predictions of their model. In particular, they find that those neighborhoods whose house values increase the most during city-wide housing booms are the poor neighborhoods that are in close proximity to the richer neighborhoods. This pattern is robust to controlling for distance to jobs. Additionally, they find that the neighborhoods that experience the highest price increases also show strong evidence of gentrification (large increases in income, large reductions in the poverty rate, and an influx of new residents). The authors formally assess the mechanism of the model by showing that house prices increase substantially in a poorer neighborhood when the surrounding neighborhoods receive a positive shock to income. Finally, they assess how much of cross-city differences in price appreciation rates during the 1990s and the 2000s can be explained by their mechanism.

Jack Favilukis, London School of Economics, Sydney Ludvigson, New York University and NBER, and Stijn Van Nieuwerburgh, New York University and NBER
The Macroeconomic Effects of Housing Wealth, Housing Finance, and Limited Risk-Sharing in General Equilibrium

Favilukis, Ludvigson, and Van Niewuwerburgh study a two-sector general equilibrium model of housing and non-housing production in which heterogeneous households faced with aggregate and idiosyncratic risks have limited risk-sharing opportunities because of incomplete financial markets. The model generates large variability in national house price-rent ratios, both because they fluctuate endogenously with the state of the economy and because they rise in response to a relaxation of credit constraints and a decline in housing transaction costs (that is, financial market liberalization). When the authors add to this an influx of foreign capital into domestic bond markets that is calibrated to match the increase in foreign ownership of U.S. Treasury and agency debt from 2000-7, their model generates an increase in national price-rent ratios comparable to that observed in U.S. data over this period. Moreover, in a simulated transition for the period 2000-9, the model generates a sharp decline in national house price-rent ratios starting in 2007, driven by the economic contraction and a presumed reversal of the financial market liberalization. A financial market liberalization drives down risk premia in both the housing and equity market , shifts the composition of wealth towards housing for all age and income groups, and leads to a short-run boom in aggregate consumption but to a short-run bust in investment. The model also implies that an influx of foreign capital into the domestic bond market plays a central role in reducing interest rates, but only a modest role in raising home prices. Finally, the model implies that pro-cyclical increases in equilibrium price-rent ratios reflect expectations of lower future housing returns, not higher future rents.

Christopher Erceg, Federal Reserve Board, and Jesper Linde, Federal Reserve Board
Is There a Fiscal Free Lunch in a Liquidity Trap?

Erceg and Linde examine the effects of an expansion in government spending in a liquidity trap. If the liquidity trap is very prolonged, the spending multiplier can be much larger than under normal circumstances, and the budgetary costs will be minimal. But given this “fiscal free lunch,” it is unclear why policymakers would want to limit the size of fiscal expansion. This paper addresses the question in a model environment in which the duration of the liquidity trap is determined endogenously, and depends on the size of the fiscal stimulus. The authors show that even if the multiplier is high for small increases in government spending, it may decrease substantially at higher spending levels; thus, it is crucial to distinguish between the average and marginal multiplier.

YiLi Chien, Purdue University, Harold Cole, University of Pennsylvania and NBER, and Hanno Lustig, UC, Los Angeles and NBER
Is the Volatility of the Market Price of Risk due to Intermittent Portfolio Re-Balancing?

Chien, Cole, and Lustig examine whether intermittent portfolio re-balancing on the part of some stock market investors can help to explain the counter-cyclical volatility of aggregate risk compensation in financial markets. To answer this question, they set up an incomplete markets model in which CRRA-utility investors are subject to aggregate and idiosyncratic shocks and have heterogeneous trading technologies. In the model, a large mass of passive investors do not re-balance their portfolio shares in response to aggregate shocks, while a smaller mass of active investors adjust their portfolio each period to respond to changes in the investment opportunity set. The researchers find that intermittent re-balancers amplify the effect of aggregate shocks on the time variation in risk premia by a factor of four in a calibrated version of their model.

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