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.

Appendix A provides firm-level and industry-level evidence that is consistent with several key features of our model, including the predictions that rates of return increase with a firm’s intangible investments and foreign affiliate rates of return increase with age and with their parents’ R&D intensity. Appendix B provides details for the computation of our model’s equilibrium paths, the construction of model national and international accounts, and the sensitivity of our main findings to alternative parameterizations of the model. We demonstrate that the main finding of our paper—namely, that the mismeasurement of capital accounts for roughly 60 percent of the gap in FDI returns—is robust to alternative choices of income shares, depreciation rates, and tax rates, assuming the same procedure is followed in setting exogenous parameters governing the model’s current account. Appendix C demonstrates that adding technology capital and locations to an otherwise standard two-country general equilibrium model has a large impact on the predicted behavior of labor productivity and net exports.

Concerns about constructing and maintaining good reputations are known to reduce borrowers’ excessive risk-taking. However, I find that the self-discipline induced by these concerns is fragile, and can break down without obvious changes in economic fundamentals. Furthermore, in the aggregate, breakdowns are clustered among borrowers with intermediate and good reputations, which can exacerbate an economy’s weakness and contribute to a broad economic crisis. These results come from an aggregate dynamic global game analysis of reputation formation in credit markets. The selection of a unique equilibrium is accomplished by assuming that borrowers have incomplete information about economic fundamentals.

In this paper, we construct a parsimonious overlapping-generations model of human capital accumulation and study its quantitative implications for the evolution of the U.S. wage distribution from 1970 to 2000. A key feature of the model is that individuals differ in their ability to accumulate human capital, which is the main source of wage inequality in this model. We examine the response of this model to skill-biased technical change (SBTC), which is modeled as an increase in the trend growth rate of the price of human capital starting in the early 1970s. The model displays behavior that is consistent with several important trends observed in the US data, including the rise in overall wage inequality; the fall and subsequent rise in the college premium, as well as the fact that this behavior was most pronounced for younger workers; the rise in within-group inequality; the stagnation in median wage growth; and the small rise in consumption inequality despite the large rise in wage inequality. We consider different scenarios regarding how individuals’ expectations evolve during SBTC. Specifically, we study the case where individuals immediately realize the advent of SBTC (perfect foresight), and the case where they initially underestimate the future growth of the price of human capital (pessimistic priors), but learn the truth in a Bayesian fashion over time. Lack of perfect foresight appears to have little effect on the main results of the paper. Overall, the model shows promise for explaining a diverse set of wage distribution trends observed since the 1970s in a unifying human capital framework.

We study the effects of large transportation costs on economic development. We argue that the Midwest and the Northeast of the U.S. is a natural case because starting from 1840 decent data is available showing that the two regions shared key characteristics with today’s developing countries and that transportation costs were large and then came way down. To disentangle the effects of the large reduction in transportation costs from those of other changes that happened during 1840–1860, we build a model that speaks to the distribution of people across regions and across the sectors of production. We find that the large reduction in transportation costs was a quantitatively important force behind the settlement of the Midwest and the regional specialization that concentrated agriculture in the Midwest and industry in the Northeast. Moreover, we find that it led to the convergence of the regional per capita incomes measured in current regional prices and that it increased real GDP per capita. However, the increase in real GDP per capita is considerably smaller than that resulting from the productivity growth in the nontransportation sectors.

This paper studies the impact of cross-country variation in financial market development on firms’ financing choices and growth rates using comprehensive firm-level datasets. We document that in less financially developed economies, small firms grow faster and have lower debt to asset ratios than large firms. We then develop a quantitative model where financial frictions drive firm growth and debt financing through the availability of credit and default risk. We parameterize the model to the firms’ financial structure in the data and show that financial restrictions can account for the majority of the difference in growth rates between firms of different sizes across countries.

We study the U.S. sugar manufacturing cartel that was created during the New Deal. This was a legal-cartel that lasted 40 years (1934-74). As a legal-cartel, the industry was assured widespread adherence to domestic and import sales quotas (given it had access to government enforcement powers). But it also meant accepting government-sponsored cartel-provisions. These provisions significantly distorted production at each factory and also where the industry was located. These distortions were reflected in, for example, a declining industry recovery rate, that is, the pounds of white sugar produced per ton of beets. It declined from about 310 pounds in 1934 to 240 pounds in 1974. The cartel provisions also distorted the location of industry. For example, it kept production in California and the Far West. Since the cartel ended in 1974, California's share of sugar production has dropped dramatically.

In standard approaches to monetary policy, interest rate rules often lead to indeterminacy. Sophisticated policies, which depend on the history of private actions and can differ on and off the equilibrium path, can eliminate indeterminacy and uniquely implement any desired competitive equilibrium. Two types of sophisticated policies illustrate our approach. Both use interest rates as the policy instrument along the equilibrium path. But when agents deviate from that path, the regime switches, in one example to money; in the other, to a hybrid rule. Both lead to unique implementation, while pure interest rate rules do not. We argue that adherence to the Taylor principle is neither necessary nor sufficient for unique implementation with pure interest rate rules but is sufficient with hybrid rules. Our results are robust to imperfect information and may provide a rationale for empirical work on monetary policy rules and determinacy.

We conduct a systematic empirical study of cross-sectional inequality in the United States, integrating data from the Current Population Survey, the Panel Study of Income Dynamics, the Consumer Expenditure Survey, and the Survey of Consumer Finances. In order to understand how different dimensions of inequality are related via choices, markets, and institutions, we follow the mapping suggested by the household budget constraint from individual wages to individual earnings, to household earnings, to disposable income, and, ultimately, to consumption and wealth. We document a continuous and sizable increase in wage inequality over the sample period. Changes in the distribution of hours worked sharpen the rise in earnings inequality before 1982, but mitigate its increase thereafter. Taxes and transfers compress the level of income inequality, especially at the bottom of the distribution, but have little effect on the overall trend. Finally, access to financial markets has limited both the level and growth of consumption inequality.

I document that cross-country productivity differences in retail trade, which employs around 20% of workers, are accounted for in large part by compositional differences. In richer countries, most retailing is done in modern stores, with high measured output per worker, whereas in developing countries, retail trade is dominated by less-productive traditional stores. I hypothesize that developing countries rationally adopt few modern stores since car ownership rates are low. A simple quantitative model of home production supports the role of cars in determining the composition of retail technologies used and retail-sector productivity differences across countries.