National Accounts ESA. Detailed tables by branch 1985-1990

See Introduction p. 14 and Table of Contents p. 13.

National Accounts ESA. Detailed tables by sector, Non-financial transactions 1985-1996. 1999 edition

See Introduction p. 12 and Table of Contents p. 11.

National Accounts ESA. Detailed tables by branch 1987

See Introduction p. 5 and Table of Contents p. 11.

Constructing internationally comparable real income aggregates by combining sparse benchmark data with annual national accounts data: A state-space approach

The importance of availability of comparable real income aggregates and their components to applied economic research is highlighted by the popularity of the Penn World Tables. Any methodology designed to achieve such a task requires the combination of data from several sources. The first is purchasing power parities (PPP) data available from the International Comparisons Project roughly every five years since the 1970s. The second is national level data on a range of variables that explain the behaviour of the ratio of PPP to market exchange rates. The final source of data is the national accounts publications of different countries which include estimates of gross domestic product and various price deflators. In this paper we present a method to construct a consistent panel of comparable real incomes by specifying the problem in state-space form. We present our completed work as well as briefly indicate our work in progress.

Portuguese National Accounts : a network approach

In recent years, the Portuguese economy has gone through a severe adjustment process, which aected almost every sector of the economy. Therefore, it is important to study how the structure of the economy changed during this period. To that end, using data on the annual output by industry and product from National Accounts, we developed a network of industries for the years 2010 and 2013. By comparing the Minimal Spanning Trees and a set of topological coecients for the years considered, we evaluate the structural evolution of the economy. In order to get a long term view, we extended the analysis to the period between 1995 and 2010. We found that the industries linked to trade activities maintained their centrality, although they decreased their importance over time. Together with construction activities, they were among the most severely aected industries.