Technology shocks and the business cycle

Technology ; Business cycles

Why has home ownership fallen among the young?

We document that home ownership of households with 'heads' aged 25-44 years fell substantially between 1980 and 2000 and recovered only partially during the 2001-2005 housing boom. The 1980-2000 decline in young home ownership occurred as improvements in mortgage opportunities made it easier to purchase a home. This paper uses an equilibrium life-cycle model calibrated to micro and macro evidence to understand why young home ownership fell over a period when it became easier to own a home. Our findings indicate that a trend toward marrying later and the increase in household earnings risk that occurred after 1980 account for 3/5 to 4/5 of the decline in young home ownership.Housing, home ownership, tenure choice, first-time home-buyers, marriage, income risk

Why has home ownership fallen among the young?

We document that home ownership of households with "heads" aged 25 - 44 years fell substantially between 1980 and 2000 and recovered only partially during the 2001-2005 housing boom. The 1980-2000 decline in young home ownership occurred as improvements in mortgage opportunities made it easier to purchase a home. This paper uses an equilibrium life-cycle model calibrated to micro and macro evidence to understand why young home ownership fell over a period when it became easier to own a home. Our findings indicate that a trend toward marrying later and the increase in household earnings risk that occurred after 1980 account for 3/5 to 4/5 of the decline in young home ownership.Home ownership ; Marriage

In search of a robust inflation forecast

It is difficult to consistently improve upon forecasts of inflation based solely on the most recent data on inflation. In this article, we show how to do so. Our main finding is that the most robust forecasts combine information from several different forecasting models, each of which incorporates the information in the available inflation indicators in different ways.Inflation (Finance)

The great turn-of-the-century housing boom

This article explains the recent high levels of residential investment and rates of homeownership.Home ownership ; Housing - Finance ; Housing - Prices

First-time home buyers and residential investment volatility

Like other macroeconomic variables, residential investment has become much less volatile since the mid-1980s (recent experience notwithstanding.) This paper explores the role of structural change in this decline. Since the early 1980s there have been many changes in the underlying structure of the economy, including those in the mortgage market which have made it easier to acquire a home. We examine how these changes affect residential investment volatility in a life-cycle model consistent with micro evidence on housing choices. We find that a decline in the rate of household formation, increased delay in marriage, and an increase in the cross-sectional variance of earnings drive the decline in volatility. Our findings provide support for the view that the “Great Moderation” in aggregate fluctuations is not just due to smaller aggregate shocks, but is driven at least in part by structural change.Home ownership ; Mortgages

Mortgage choices and housing speculation

We describe a rational expectations model in which speculative bubbles in house prices can emerge. Within this model both speculators and their lenders use interest-only mortgages (IOs) rather than traditional mortgages when there is a bubble. Absent a bubble, there is no tendency for IOs to be used. These insights are used to assess the extent to which house prices in US cities were driven by speculative bubbles over the period 2000-2008. We find that IOs were used sparingly in cities where elastic housing supply precludes speculation from arising. In cities with inelastic supply, where speculation is possible, there was heavy use of IOs, but only in cities that had boom-bust cycles. Peak IO usage predicts rapid appreciations that cannot be explained by standard correlates and this variable is more robustly correlated with rapid appreciations than other mortgage characteristics, including sub-prime, securitization and leverage. Where IOs were popular, their use does not appear to have been a response to houses becoming more expensive. Indeed, their use anticipated future appreciation. Finally, consistent with the reason why lenders prefer IOs, these mortgages are more likely to be repaid earlier or foreclose. Combined with our model, this evidence suggests that speculative bubbles were an important factor driving prices in cities with boom-bust cycles.Mortgage loans ; Mortgage-backed securities ; Housing - Prices

Using stock returns to identify government spending shocks

This paper explores a new approach to identifying government spending shocks which avoids many of the shortcomings of existing approaches. The new approach is to identify government spending shocks with statistical innovations to the accumulated excess returns of large US military contractors. This strategy is used to estimate the dynamic responses of output, hours, consumption and real wages to a government spending shock. We find that positive government spending shocks are associated with increases in output, hours, and consumption. Real wages initially decline after a government spending shock and then rise after a year. We estimate the government spending multiplier associated with increases in military spending to be about 0.6 over a horizon of 5 years.Fiscal policy ; Government spending policy ; Stocks

What are the implications of rising commodity prices for inflation and monetary policy?

The recent run-ups in oil and other commodity prices and their implications for inflation and monetary policy have grabbed the attention of many commentators in the media. Clearly, higher prices of food and energy end up in the broadest measures of consumer price inflation, such as the Consumer Price Index. Since the mid-1980s, however, sharp increases and decreases in commodity prices have had little, if any, impact on core inflation, the measure that excludes food and energy prices.Inflation (Finance) ; Monetary policy ; Consumer price indexes