This study investigates the determinants of the fertility transition in the United States from 1850 to the end of the 20th century. We find a robust negative relation between years of schooling and fertility. The magnitude of our baseline estimate suggests that the rise in schooling accounts for about 60% of the US fertility decline. In contrast, we find no evidence of a robust relation between income per capita and fertility. This pattern corroborates theories stressing the importance of human capital investments in generating a transition from high to low fertility.

Grazing by large herbivores is well-known to influence plant communities, while much fewer studies have been carried out on grazing effects on invertebrates. In Norway, some 2.2 million sheep graze on outlying pastures during summer, most of them in the alpine zone, but no study has reported the relative impact of sheep grazing on invertebrate communities relative to other environmental factors such as the plant community and altitude. A fully replicated landscape-scale experiment (2.7 km2) was performed with no, low (25 per km2) and high (80 per km2) sheep densities in an alpine habitat of Norway (1050–1300 m a.s.l.). The increased vulnerability hypothesis (H1) predicts that the more folivorous invertebrates, the higher the grazing pressure by sheep, as large herbivore grazing may stress the plants so they are more vulnerable to insect herbivory. The increased defence hypothesis (H2) predicts increased levels of general anti-herbivore defences, and thus a lower abundance of invertebrates with increasing sheep densities. Contrary to both predictions, no evidence was found that sheep grazing affected invertebrate richness, or abundance of folivorous, predatory or detritivore invertebrates – in a community dominated by Diptera and Hemiptera. Demonstrating an effect will always be a function of sample size, but at least our study shows that other environmental variables (such as plant species richness and functional plant richness) are more important determinants than sheep grazing for the selected invertebrate groups. Our study was short-term (first year of grazing) mainly designed to test specific hypotheses related to induced plant defences; long-term effects are probably owing to the impact sheep may have on vegetation composition, primary production, litter cover and soil properties.

We develop and apply bootstrap methods for diffusion models when fitted to the long run as characterized by the stationary distribution of the data. To obtain bootstrap refinements to statistical inference, we simulate candidate diffusion processes. We use these bootstrap methods to assess measurements of local mean reversion or “pull” to the center of the distribution for short-term interest rates. We also use them to evaluate the fit of the model to the empirical density.

Christopher Sims is a well-known intellectual leader in time-series econometrics and applied macroeconomics. Among his many honors and distinctions, he has been the President of the Econometric Society and he is a member of the National Academy of Sciences. He has made fundamental contributions to both statistical theory of time series and empirical macroeconomics. Sims' work is influential precisely because it was motivated by important problems in macroeconomics. Not only did Sims study questions of statistical approximation in abstract environments, he showed how to apply the resulting apparatus to a variety of specific problems confronting applied researchers. The applications include seasonality in economic time series, aggregation over time, and approximation in formulating statistical models with economic underpinnings. Moreover, Sims' contributions to causality in time series and to the development of vector autoregressive methods were complemented by an important body of empirical research. Sims has served as an effective advocate and critic of the extensively used vector autoregressive statistical methods. Motivated by his own and related empirical research, Sims is one of the leaders in rethinking how monetary policy should be modeled and reconsidering the channels by which monetary policy influences economic aggregates. This interview with Chris Sims gives an opportunity to explore further the context of many of these contributions. Sims typically has a unique perspective on many economic problems, a perspective that is articulated in his answers to a variety of questions.