Determinants of Manufacturing Concentration Patterns in Mercosur

Over the last fifteen years, Argentina, Brazil, Paraguay and Uruguay have implemented major economic reforms including unilateral trade liberalization programs and the constitution of a regional trade bloc, Mercosur. This trade policy change has led to a reallocation of resources across sectors and space. The impact of the trade liberalization on industrial production structures in Mercosur countries has been little investigated so far. How concentrated /dispersed are manufacturing activities? Have patterns of manufacturing concentration changed? What are the determinants of manufacturing concentration patterns? This paper identifies and explains relative concentration patterns of manufacturing activities in three Mercosur member countries, namely, Argentina, Brazil, and Uruguay, over the period 1970-1998. In particular, using econometric techniques, we analyse inter-industry and across-time differences in manufacturing concentration patterns and explain their main determinants over this period. Our research results suggest that some industries, such as Beverages, Tobacco and Leather are highly concentrated in relative terms, while industries such as Glass, Textiles, and Fabricated metal products are dispersed. We find that on average, relative manufacturing concentration has increased over the above mentioned period. While industries, such as, Non-electrical machinery, Electrical machinery and Professional and scientific instruments have experienced significant monotonic increases, other industries, such as Printing and publishing, Rubber products, and Non-ferrous metals have registered a reversal of their relative concentration levels. Our econometric analysis indicates that localization of demand and comparative advantage factors are the main driving forces of the observed relative manufacturing concentration patterns.

Unbiased taxonomic annotation of metagenomic samples

The classification of reads from a metagenomic sample using a reference taxonomy is usually based on first mapping the reads to the reference sequences and then classifying each read at a node under the lowest common ancestor of the candidate sequences in the reference taxonomy with the least classification error. However, this taxonomic annotation can be biased by an imbalanced taxonomy and also by the presence of multiple nodes in the taxonomy with the least classification error for a given read. In this article, we show that the Rand index is a better indicator of classification error than the often used area under thereceiver operating characteristic (ROC) curve andF-measure for both balanced and imbalanced reference taxonomies, and we also address the second source of bias by reducing the taxonomic annotation problem for a whole metagenomic sample to a set cover problem, for which a logarithmic approximation can be obtained in linear time and an exact solution can be obtained by integer linear programming. Experimental results with a proof-of-concept implementation of the set cover approach to taxonomic annotation in a next release of the TANGO software show that the set cover approach further reduces ambiguity in the taxonomic annotation obtained with TANGO without distorting the relative abundance profile of the metagenomic sample.Peer ReviewedPostprint (published version

A Corpus-Based Investigation of Definite Description Use

We present the results of a study of definite descriptions use in written texts aimed at assessing the feasibility of annotating corpora with information about definite description interpretation. We ran two experiments, in which subjects were asked to classify the uses of definite descriptions in a corpus of 33 newspaper articles, containing a total of 1412 definite descriptions. We measured the agreement among annotators about the classes assigned to definite descriptions, as well as the agreement about the antecedent assigned to those definites that the annotators classified as being related to an antecedent in the text. The most interesting result of this study from a corpus annotation perspective was the rather low agreement (K=0.63) that we obtained using versions of Hawkins' and Prince's classification schemes; better results (K=0.76) were obtained using the simplified scheme proposed by Fraurud that includes only two classes, first-mention and subsequent-mention. The agreement about antecedents was also not complete. These findings raise questions concerning the strategy of evaluating systems for definite description interpretation by comparing their results with a standardized annotation. From a linguistic point of view, the most interesting observations were the great number of discourse-new definites in our corpus (in one of our experiments, about 50% of the definites in the collection were classified as discourse-new, 30% as anaphoric, and 18% as associative/bridging) and the presence of definites which did not seem to require a complete disambiguation.Comment: 47 pages, uses fullname.sty and palatino.st