U.S. international transactions in 1996

After stabilizing in 1995, the U.S. current account deficit widened in 1996 to $165 billion. The deficit increased sharply in the first three quarters of the year, but, because of strong export growth, narrowed significantly in the fourth quarter. The widening of the deficit by$17 billion was the net result of moderate-to-strong growth in all the key components of the current account: exports and imports of goods and services, income from U.S. and foreign portfolio and direct investments, and net unilateral transfers.Investments, Foreign ; International economic relations ; International trade

Interactions between Domestic and Foreign Investment

We present a model of portfolio allocation by noise traders who form incorrect expectations about the variance of the return distribution of a particular asset. We show that for many types of misperceptions, as long as such noise traders do not affect prices, they earn higher expected returns than do rational investors with similar degrees of risk aversion. Moreover, many such noise traders survive and dominate the market in terms of wealth in the long run, in the sense that the probability that noise traders will eventually have a high share of the economy's wealth is arbitrarily close to one. Noise traders come to dominate the market despite the fact that they take excessive risk that skews the distribution of their long run wealth and despite their excessive consumption. We conclude that the theoretical case against the long run viability of noise traders is by no means as clear cut as is commonly supposed.

Artificial intelligence in steam cracking modeling : a deep learning algorithm for detailed effluent prediction

Chemical processes can benefit tremendously from fast and accurate effluent composition prediction for plant design, control, and optimization. The Industry 4.0 revolution claims that by introducing machine learning into these fields, substantial economic and environmental gains can be achieved. The bottleneck for high-frequency optimization and process control is often the time necessary to perform the required detailed analyses of, for example, feed and product. To resolve these issues, a framework of four deep learning artificial neural networks (DL ANNs) has been developed for the largest chemicals production process-steam cracking. The proposed methodology allows both a detailed characterization of a naphtha feedstock and a detailed composition of the steam cracker effluent to be determined, based on a limited number of commercial naphtha indices and rapidly accessible process characteristics. The detailed characterization of a naphtha is predicted from three points on the boiling curve and paraffins, iso-paraffins, olefins, naphthenes, and aronatics (PIONA) characterization. If unavailable, the boiling points are also estimated. Even with estimated boiling points, the developed DL ANN outperforms several established methods such as maximization of Shannon entropy and traditional ANNs. For feedstock reconstruction, a mean absolute error (MAE) of 0.3 wt% is achieved on the test set, while the MAE of the effluent prediction is 0.1 wt%. When combining all networks-using the output of the previous as input to the next-the effluent MAE increases to 0.19 wt%. In addition to the high accuracy of the networks, a major benefit is the negligible computational cost required to obtain the predictions. On a standard Intel i7 processor, predictions are made in the order of milliseconds. Commercial software such as COILSIM1D performs slightly better in terms of accuracy, but the required central processing unit time per reaction is in the order of seconds. This tremendous speed-up and minimal accuracy loss make the presented framework highly suitable for the continuous monitoring of difficult-to-access process parameters and for the envisioned, high-frequency real-time optimization (RTO) strategy or process control. Nevertheless, the lack of a fundamental basis implies that fundamental understanding is almost completely lost, which is not always well-accepted by the engineering community. In addition, the performance of the developed networks drops significantly for naphthas that are highly dissimilar to those in the training set. (C) 2019 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company

Monetary Policy Goals for Inflation in Australia

This paper outlines the inflation objective for monetary policy in Australia, which we describe as seeking to achieve a broad central tendency for inflation of between 2 and 3 per cent over the long run – a “thick point” – rather than a narrow target band. It also provides a more detailed rationale for this objective. In doing so, the paper discusses the issues relevant in determining the appropriate mean inflation rate at which policy should aim, the degree of variation of inflation around that central point, and how policy should respond to shocks. A simple model of the economy is presented which attempts to address these issues in a consistent framework.

Simple cuspidal representations of symplectic groups: Langlands parameter

Let $F$ be a non-archimedean local field of odd residual characteristic. We compute the Jordan set of a simple cuspidal representation of a symplectic group over $F$, using explicit computations of generators of the Hecke algebras of covers reflecting the parabolic induction under study. When $F$ is a $p$-adic field we obtain the Langlands parameter of the representation.Comment: 33 page

REFGEN and TREENAMER: automated sequence data handling for phylogenetic analysis in the genomic era.

Published onlineJournal ArticleThe phylogenetic analysis of nucleotide sequences and increasingly that of amino acid sequences is used to address a number of biological questions. Access to extensive datasets, including numerous genome projects, means that standard phylogenetic analyses can include many hundreds of sequences. Unfortunately, most phylogenetic analysis programs do not tolerate the sequence naming conventions of genome databases. Managing large numbers of sequences and standardizing sequence labels for use in phylogenetic analysis programs can be a time consuming and laborious task. Here we report the availability of an online resource for the management of gene sequences recovered from public access genome databases such as GenBank. These web utilities include the facility for renaming every sequence in a FASTA alignment file, with each sequence label derived from a user-defined combination of the species name and/or database accession number. This facility enables the user to keep track of the branching order of the sequences/taxa during multiple tree calculations and re-optimisations. Post phylogenetic analysis, these webpages can then be used to rename every label in the subsequent tree files (with a user-defined combination of species name and/or database accession number). Together these programs drastically reduce the time required for managing sequence alignments and labelling phylogenetic figures. Additional features of our platform include the automatic removal of identical accession numbers (recorded in the report file) and generation of species and accession number lists for use in supplementary materials or figure legends.Leverhulm