This article outlines an approach, based on ecosystem services, for assessing the trade-offs inherent in managing humans embedded in ecological systems. Evaluating these trade-offs requires an understanding of the biophysical magnitudes of the changes in ecosystem services that result from human actions, and of the impact of these changes on human welfare. We summarize the state of the art of ecosystem services-based management and the information needs for applying it. Three case studies of Long Term Ecological Research (LTER) sites-coastal, urban, and agriculturalillustrate the usefulness, information needs, quantification possibilities, and methods for this approach. One example of the application of this approach, with rigorously established service changes and valuations taken from the literature, is used to illustrate the potential for full economic valuation of several agricultural landscape management options, including managing for water quality, biodiversity, and crop productivity.

two referees, and participants at a number of seminars for helpful comments. The views expressed herein are those of the authors and not necessarily those of the National Bureau of Economic Research, the Federal Reserve Bank of New York, or the Federal Reserve System. A data diskette is available upon request that contains both the raw and filtered data series that are used in our empirical work.

Most advanced economies have experienced a striking decline in the volatility of aggregate economic activity since the early 1980s. Volatility reductions are evident for output and employment at the aggregate level and across most industrial sectors and expenditure categories. Inflation and inflation volatility have also declined dramatically. Previous studies offer several potential explanations for this "Great Moderation." We review evidence on the Great Moderation in conjunction with evidence about volatility trends at the micro level. We combine the two types of evidence to develop a tentative story for important components of the aggregate volatility decline and its consequences. The key ingredients are declines in firm-level volatility and aggregate volatility -- most dramatically in the durable goods sector. Surprisingly, this has occurred without a decline in household consumption volatility and individual earnings uncertainty. Our explanation for the aggregate volatility decline stresses improved supply-chain management, particularly in the durable goods sector, and, less important, a shift in production and employment from goods to services. We provide evidence that better inventory control made a substantial contribution to declines in firm-level and aggregate volatility. Consistent with this view, if we look past the turbulent 1970s and early 1980s much of the moderation reflects a decline in high frequency (short-term) fluctuations. While these developments represent efficiency gains, they do not imply (nor is there evidence for) a reduction in economic uncertainty faced by individuals and households.

No abstract

This paper presents an econometric estimation of the "rebound effect" for household vehicle travel in the United States based on analysis of survey data collected by the Energy Information Administration (EIA) at approximately three-year intervals over a 15-year period. The rebound effect measures the tendency to "take back" potential energy savings from fuel economy improvements as increased travel. Vehicle use models were estimated for one-, two-, three-, four-, and five-vehicle households. The results confirm recent estimates based on national or state-level data: a long-run "take back" of about 20 percent of potential energy savings. Consumer responses to changes in fuel economy or fuel price per gallon appear to be equal and opposite in sign. Recognizing the interdependencies among miles of travel, fuel economy and price is key to obtaining meaningful results. AbstractThis paper reports on an analysis of productivity growth and input trends in six energy intensive sectors of the Indian economy, using growth accounting and econometric methods. The econometric work estimates rates and factor price biases of technological change using a translog production model with an explicit relationship defined for technological change. Estimates of own-price responses indicate that raising energy prices would be an effective carbon abatement policy for India. At the same time, our results suggest that, as with previous findings on the U.S. economy, such policies in India could have negative long-run effects on productivity in these sectors. Inter-input substitution possibilities are relatively weak, so that such policies might have negative short-and medium-term effects on sectoral growth. Our study provides information relevant for the analysis of costs and benefits of carbon abatement policies applied to India and thus contributes to the emerging body of modeling and analysis of global climate policy. AbstractIn China, between 1978 and 1995, energy use per unit of GDP fell by 55 percent. There has been considerable debate about the major factors responsible for this dramatic decline in the energy-output ratio. In this paper we use the two most recent input-output tables to decompose the reduction in energy use into technical change and various types of structural change, including changes in the quantity and composition of imports and exports. In performing our analysis we are forced to deal with a number of problems with the relevant Chinese data and introduce some simple adjustments to improve the consistency of the input-output tables. Our mail conclusion is that between 1987 and 1992, technical change within sectors accounted for most of the fall in the energy-output ratio. Structural change actually increased the use of energy. An increase in the import of some energy-intensive products also contributed to the decline in energy intensity. Pages 93-121Abstract Technological progress, energy use, energy intensity, and carbon mitigation are tightly intertwined concepts within the worldwide climate change debate. The s...

No abstract

No abstract

Manufacturers' finished goods inventories move less than shipments over the business cycle. We argue that this requires marginal cost to be more procyclical than is conventionally measured. We construct, for six manufacturing industries, alternative measures of marginal cost that attribute high-frequency productivity shocks to procyclical work effort, and find that they are much more successful in accounting for inventory behavior. The difference is attributable to cyclicality in the shadow price of labor, not to diminishing returns-in fact, parametric evidence suggests that the short-run slope of marginal cost is close to zero for five of the six industries. Moreover, while our measures of marginal cost are procyclical relative to output price, they are too persistent for intertemporal substitution to be important. We conclude that countercyclical markups are chiefly responsible for the sluggish response of inventory stocks over the cycle.