An Input-Output Approach to Industrial Wastes

The Statistical Distributions of Industrial Wastes: an Analysis of the Japanese Establishment Linked Input-output Data

An Input-output Approach to the Measurement of Productivity Differences*

This paper deals with the measurement of e¢ciency di¤erences among countries within a federation. The key tool is the use of a suitable interpretation of the non-substitution theorem in order to get a natural technological standard. Two alternative indices are proposed. One provides a structural productivity measure, independent of consumption and prices. The other consists of a price index ass...

An EM Approach to Grammatical Inference: Input/Output HMMs

We propose a modular recurrent connectionist architecture for adaptive temporal processing. The model is given a probabilistic interpretation and is trained using the EM algorithm. This model can also be seen as an Input/Output Hidden Markov Model. The focus of this paper is on sequence classiication tasks. We demonstrate that EM supervised learning is well suited for solving grammatical infere...

Industrial input-output analysis: implications for industrial ecology.

Industrial ecology will need to develop fundamentally new approaches to reducing, reusing, and recycling wastes. Industrial ecology will also require an analytic framework for examining the implications for the economic system as a whole of each potential web of industrial changes. A suitable framework is furnished by structural economics, which situates the economy within the physical world. T...

An Input Output HMM

We introduce a recurrent architecture having a modular structure and we formulate a training procedure based on the EM algorithm. The resulting model has similarities to hidden Markov models, but supports recurrent networks processing style and allows to exploit the supervised learning paradigm while using maximum likelihood estimation.