The Quarterly National Accounts in real-time: an analysis of the revisions over the last decade
In this article, the revisions of the Portuguese Quarterly National Accounts over the last decade are analyzed. We assess the real-time behaviour of GDP estimates and corresponding expenditure and supply side components. In particular, we focus on the revisions up to one year after the release of the fi rst estimate as well as on the revisions resulting from the inclusion of the Annual National Accounts. In the case of GDP, the reliability of the fl ash estimate, more recently made available by INE, is also assessed. The results for GDP suggest that the revisions up to one year are not signifi cant although the revisions can be larger when the Annual National Accounts are included. The expenditure components related with external trade present the largest revisions while the supply side estimates are more fragile than those from the expenditure side.
A mixed frequency approach to the forecasting of private consumption with ATM/POS data
The recent worldwide development and widespread use of electronic payment systems has provided an opportunity to explore new sources of data for the monitoring of macroeconomic activity. In this paper, we analyse the usefulness of data collected from automated teller machines (ATM) and points-of-sale (POS) for nowcasting and forecasting quarterly private consumption. We take advantage of the availability of such high frequency data by using mixed data sampling (MIDAS) regressions. A comparison of several MIDAS variants proposed in the literature is conducted, and both single- and multi-variable models are considered, together with different information sets within the quarter. Given the substantial use of ATM/POS technology in Portugal, it is important to assess the information content of this data for tracking private consumption. We find that ATM/POS data display a better forecast performance than typical indicators, which reinforces the potential usefulness of this novel type of data among policymakers and practitioners.
Complexity, Network-Decisions And Alternative Risk Premia: Some New Theories Of Structural Change And Portfolio Decisions.
Structural Change is the basis for many decisions such as government fiscal and monetary policies, government interventions, corporate-expenditure decisions, corporate strategic decisions, portfolio management decisions in finance; household allocation decisions, etc.. Structural change in industries and national economies is increasingly more difficult to detect partly because of the growth and dominance of Complex Systems and “Networks” in modern industries and economies – such Networks and Complex Systems include GVCs (global value chains), retail store networks; franchising networks; internet networks; services networks; credit-chains in industries; online social networks; etc.. The relationship between Complexity and Structural Change is well established in the physics, applied math and economic dynamics literatures. Traditional definitions and modeling of structural change have erroneously focused on changes in labor, technological progress, market share, and or capital – which are grossly inadequate in the new economy and post- global financial crisis (as confirmed by changes in the global retailing and housing industries and other industries). Also the modeling of structural change seems to be constrained by the availability of data, and often omits the relationship between structural change on one hand, and globalization, financial stability and international financial contagion. This article: i) introduces the Operations Strategy Model of structural change, explains how it differs from the Lewis Model of Structural Change; and explains the often omitted relationship between operations strategy (of companies and government agencies) and structural change; ii) introduces other new Complexity-based models/theories of Structural Change in industries; iii) reviews the relationships among Operations Research, Complexity and Structural Change; iv) explains the symbiotic relationship between structural change on one hand, and economic growth, financial stability, financial contagion and globalization; v) discusses the significant gap between academic research and practice and explains some issues and factors that should be considered in the development and testing of structural change models; vi) explains how alternative risk premia can be generated from new models of Structural Change.