Francisco J. Buera, NBER and University of California, Los Angeles; Joseph P. Kaboski, Ohio State University; and Youngseok Shin, Washington University in St. Louis
Finance and Development: A Tale of Two Sectors
Income differences across countries primarily reflect differences in total factor productivity (TFP). In less developed economies, TFP is particularly low in sectors that produce tradable goods. Buera, Kaboski and Shin develop a quantitatively-oriented framework to explain such cross-country patterns in aggregate and sectoral TFP. They start by documenting that an important distinction between the tradable and the non-tradable sector is average establishment size: establishments in the tradable sector operate at much larger scales. Because of their larger scale of operation, tradable sector establishments have more financing needs, and hence are affected disproportionately by financial frictions. The authors quantitative exercises show that financial frictions account for a substantial part of the observed cross-country patterns in TFP, both at the aggregate and at the sectoral level. Their model also has novel implications for the impact of financial frictions on the relative scale between the tradable and the non-tradable sector, which are consistent with the data.
Diego Comin, NBER and Harvard University; Mark Gertler, NBER and New York University; and Ana Maria Santacreu, New York University
Technology Innovation and Diffusion as Sources of Output and Asset Price Fluctuations
Comin, Gertler, and Santacreu develop a model in which innovations in an economys growth potential are one important driving force for the business cycle. Their framework shares the emphasis of the recent "new shock" literature on revisions of beliefs about the future as a source of fluctuations, but it differs by tying those beliefs to fundamentals of the evolution of the technology frontier. One important feature of the model is that the process of moving to the frontier involves costly adoption of technology. In this way, news of improved growth potential has a positive effect on current hours. As the authors show, the model also has reasonable implications for stock prices. Using post-1984 data, they show that the innovations-shock explains nearly one third of the variation in output at business cycle frequencies. The estimated model also accounts reasonably well for the large gyration in stock prices over this period. Finally, the endogenous adoption mechanism plays a significant role in amplifying other shocks.
Glenn D. Rudebusch and Eric T. Swanson, Federal Reserve Bank of San Francisco
The Bond Premium in a DSGE Model with Long-Run Real and Nominal Risks
The term premium on nominal long-term bonds in the standard dynamic stochastic general equilibrium (DSGE) model used in macroeconomics is far too small and stable relative to empirical measures obtained from the data -- an example of the bond premium puzzle. However, in models of endowment economies, researchers have been able to generate reasonable term premiums by assuming that investors have recursive Epstein-Zin preferences and face long-run economic risks. Rudebusch and Swanson show that introducing Epstein-Zin preferences into a canonical DSGE model can also produce a large and variable term premium without compromising the models ability to fit key macroeconomic variables. Long-run real and nominal risks further improve the models ability to fit the data with a lower level of household risk aversion.
Eric M. Leeper, NBER and Indiana University; Todd B. Walker, Indiana University and Shu-Chun Susan Yang, Congressional Budget Office,
Fiscal Foresight and Information Flows (NBER Working Paper No. 14630)
Fiscal foresight-the phenomenon that legislative and implementation lags ensure that private agents receive clear signals about the tax rates they face in the future-is intrinsic to the tax policy process. Leeper, Walker, and Yang develop an analytical framework to study the econometric implications of fiscal foresight. Simple theoretical examples show that foresight produces equilibrium time series with non-fundamental representations, which misalign the agents and the econometricians information sets. Economically meaningful shocks to taxes, therefore, cannot generally be extracted from statistical innovations in conventional ways. Econometric analyses that fail to align information sets of agents and the econometrician can produce distorted inferences about the effects of tax policies. These researchers document the sensitivity of econometric inferences of tax effects to details about how tax information flows into the economy. They show that alternative assumptions about the information flows that give rise to fiscal foresight can reconcile the diverse empirical findings in the literature on anticipated tax changes.
Alessandra Fogli, Federal Reserve Bank of Minneapolis, and Laura Veldkamp, NBER and New York University,
Nature or Nurture? Learning and the Geography of Female Labor Force Participation (NBER Working Paper No.
One of the most dramatic economic transformations of the past century has been the entry of women into the labor force. While many theories explain why this change took place, Fogli and Veldkamp investigate the process of transition itself. They argue that transmission of local information generates changes in participation that are geographically heterogeneous, locally correlated, and smooth in the aggregate, just like those observed in our data. In their model, women learn about the effects of maternal employment on children by observing nearby employed women. When few women participate in the labor force, data is scarce and participation rises slowly. As information accumulates in some regions, the effects of maternal employment become less uncertain, and more women in that region participate. Learning accelerates, labor force participation rises faster, and regional participation rates diverge. Eventually, information diffuses throughout the economy, beliefs converge to the truth, participation flattens out, and regions become more similar again. To investigate the empirical relevance of their theory, the authors use a new county-level dataset to compare their calibrated model to the time-series and geographic patterns of participation.
James Feyrer, Dartmouth College,
Trade and Income Exploiting Time Series in Geography
Establishing a robust causal relationship between trade and income has been difficult. Frankel and Romer (1999) use geographic instruments to identify a positive effect of trade on income; Rodriguez and Rodrik (2000) show that these results are not robust to controlling for missing variables, such as distance to the equator or institutions. Feyrer solves the missing-variable problem by generating time varying geographic instruments. The quantity of world trade carried by air has been increasing over time. Estimates from a gravity model show an increase in the elasticity of bilateral trade with regard to air distance over time, while the elasticity with regard to sea distance has declined. This change has heterogeneous effects on the trade between pairs of countries depending on the relative sea and air distances between them. This heterogeneity in geography can be used to generate geography based predictions for bilateral trade that vary over time. These predictions can be aggregated and used as instruments for trade in a regression of income on trade. The time-series variation allows for controls for country fixed effects, eliminating the bias from any omitted time invariant variables, such as distance from the equator or historically determined institutions. Trade has a significant effect on income with an elasticity of roughly one half. Differences in predicted trade growth can explain roughly 17 percent of the variation in cross-country income growth between 1960 and 1995.