Economists have studied the potential effects of shifts in the age distribution on the unemployment rate for more than 50 years. Most of this analysis uses a "shift-share" method, which assumes that the demographic structure has no indirect effects on age-specific unemployment rates. This paper uses state-level data to revisit the influence of the age distribution on unemployment in the United States. We examine demographic effects across the entire age distribution rather than just the youth share of the population -- the focus of most previous work -- and extend the date range of analysis beyond that which was available for previous research. We find that shifts in the age distribution move the unemployment rate in the direction that a mechanical shift-share model would predict. But these effects are larger than the mechanical model would generate, indicating the presence of amplifying indirect effects of the age distribution on unemployment.
In this paper, we use two comprehensive micro datasets to study the evolution of the distribution of mortgage debt during the 2000s housing boom. We show that the allocation of mortgage debt remained stable, as did the distribution of real estate assets. We propose that any theory of the boom must replicate this fact. Using a general equilibrium model, we show that this requires two elements: (1) an exogenous shock to the economy that increases expected house price growth or, alternatively, reduces interest rates and (2) financial markets that endogenously relax constraints in response to the shock. The role played by subprime mortgage debt provides additional empirical evidence that this narrative mirrors reality.
The application of information technology to finance, or “fintech,” is expected to revolutionize many aspects of borrowing and lending in the future, but technology has been reshaping consumer and mortgage lending for many years. During the 1990s computerization allowed mortgage lenders to reduce loan-processing times and largely replace human-based assessment of credit risk with default predictions generated by sophisticated empirical models. Debt-to-income ratios at origination add little to the predictive power of these models, so the new automated underwriting systems allowed higher debt-to-income ratios than previous underwriting guidelines would have typically accepted. In this way, technology brought about an exogenous change in lending standards, which helped raise the homeownership rate and encourage the conversion of rental properties to owner-occupied ones, but did not have large effects on housing prices. Technological innovation in mortgage underwriting may have allowed the 2000s housing boom to grow, however, because it enhanced the ability of both borrowers and lenders to act on optimistic beliefs about future house-price growth.