Research Database

Common statistical measures of bond risk premia are volatile and countercyclical. This paper uses survey data on interest rate forecasts to construct subjective bond risk premia. Subjective premia are less volatile and not very cyclical; instead they are high, only around the early 1980s. The reason for the discrepancy is that survey forecasts of interest rates are made as if both the level and the slope of the yield curve are more persistent than under common statistical models. The paper then proposes a consumption based asset pricing model with learning to explain jointly the difference between survey and statistical forecasts, and the evolution of subjective premia. Adaptive learning gives rise to inertia in forecasts, as well as changes in conditional volatility that help understand both features.

This paper is an extension of Monika Piazzesi's and Martin Schneider's work while they were in the Research Department of the Federal Reserve Bank of Minneapolis.

In this paper, we employ both calibration and modern (Bayesian) estimation methods to assess the role of neutral and investment-specific technology shocks in generating fluctuations in hours. Using a neoclassical stochastic growth model, we show how answers are shaped by the identification strategies and not by the statistical approaches. The crucial parameter is the labor supply elasticity. Both a calibration procedure that uses modern assessments of the Frisch elasticity and the estimation procedures result in technology shocks accounting for 2% to 9% of the variation in hours worked in the data. We infer that we should be talking more about identification and less about the choice of particular quantitative approaches.

Macroeconomics is evolving from the study of aggregate dynamics to the study of the dynamics of the entire equilibrium distribution of allocations across individual economic actors. This article reviews the quantitative macroeconomic literature that focuses on household heterogeneity, with a special emphasis on the “standard” incomplete markets model. We organize the vast literature according to three themes that are central to understanding how inequality matters for macroeconomics. First, what are the most important sources of individual risk and cross-sectional heterogeneity? Second, what are individuals’ key channels of insurance? Third, how does idiosyncratic risk interact with aggregate risk?

I study asset prices in a two-agent macroeconomic model with two key features: limited stock market participation and heterogeneity in the elasticity of intertemporal substitution in consumption (EIS). The model is consistent with some prominent features of asset prices, such as a high equity premium; relatively smooth interest rates; procyclical stock prices; and countercyclical variation in the equity premium, its volatility, and in the Sharpe ratio. In this model, the risk-free asset market plays a central role by allowing non-stockholders (with low EIS) to smooth the fluctuations in their labor income. This process concentrates non-stockholders’ labor income risk among a small group of stockholders, who then demand a high premium for bearing the aggregate equity risk. Furthermore, this mechanism is consistent with the very small share of aggregate wealth held by non-stockholders in the US data, which has proved problematic for previous models with limited participation. I show that this large wealth inequality is also important for the model’s ability to generate a countercyclical equity premium. When it comes to business cycle performance the model’s progress has been more limited: consumption is still too volatile compared to the data, whereas investment is still too smooth. These are important areas for potential improvement in this framework.

Studying the experience of countries that have experienced great depressions during the twentieth century teaches us that massive public interventions in the economy to maintain employment and investment during a financial crisis can, if they distort incentives enough, lead to a great depression.

It is well known that movements in lending rates are asymmetric; they rise quickly and sharply, but fall slowly and gradually. Not known is the fact that the asymmetry is stronger the less developed a country’s financial system is. This new fact is here documented and explained in a model with an endogenous flow of information about economic conditions. The stronger asymmetry in less developed countries stems from their greater financial system frictions, such as monitoring and bankruptcy costs, which first magnify jumps of lending rates and then delay their recoveries by restricting the generation of information after the crisis. A quantitative exploration of the model shows the data are consistent with this explanation.

The U.S. Bureau of Economic Analysis (BEA) estimates the return on investments of foreign subsidiaries of U.S. multinational companies over the period 1982–2006 averaged 9.4 percent annually after taxes; U.S. subsidiaries of foreign multinationals averaged only 3.2 percent. Two factors distort BEA returns: technology capital and plant-specific intangible capital. Technology capital is accumulated know-how from intangible investments in R&D, brands, and organizations that can be used in foreign and domestic locations. Used abroad, it generates profits for foreign subsidiaries with no foreign direct investment (FDI). Plant-specific intangible capital in foreign subsidiaries is expensed abroad, lowering current profits on FDI and increasing future profits. We develop a multicountry general equilibrium model with an essential role for FDI and apply the BEA’s methodology to construct economic statistics for the model economy. We estimate that mismeasurement of intangible investments accounts for over 60 percent of the difference in BEA returns.