Alternate input output matrix updating formulations

Linden JA, Dietzenbacher E (2000) The determinants of structural change in the European Union: a new application of RAS. Li L, Zhang N, Willett TD (2011) A survey of measurements of interdependence.

LATEC—document de travail—economie (1991–2003) 2000-01, LATEC, Laboratoire d’Analyse et des Techniques Economiques, CNRS UMR 5118, Université de Bourgogne.

A new method is presented for the finite element model updating of structures at the element level utilizing Frequency Response Function data.

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The main finding of this section is that, on one hand, the I-O coefficients are volatile, but on the other, they are serially correlated. 3—Attractor hypothesis—examines a possible presence of attractors in corresponding statistical series. Sawyer JA (1992) Forecasting with input–output matrices: are the coefficients stationary? European Commission Directorate General Economic and Financial Affairs, October. Schirwitz B, Wälde K (2004) Synchronization of business cycles in G7 and EU14 countries. The paper describes a methodology to approximate these using new indicators obtained by summation—in columns and rows—of the technical coefficients (colsums scaj and rowsums srai). The RAS method is involved as a connecting technique between these indicators and sectoral data. Bevilacqua F, van Zon A (2001) Random walks and non-linear paths in macroeconomic time series: some evidence and implications. Management School of Graduate University, Chinese Academy of Sciences. Working paper 1221/July, European Central Bank, Eurosystem. Paper presented at the 14th international conference on input–output techniques, Montréal, Canada, October 10–15, 2002. Jian X, Jing H, Yanyun Z (2007) Assessment study for the RAS method based on China’s input–output tables. Kalemli-Ozcan S, Papaioannou E, Peydró J-L (2010) Financial regulation, financial globalization and the synchronization of economic activity. Kratena K, Zakarias G (2002) Technical coefficients change by bi-proportional econometric adjustment functions. Lahr ML, de Mesnard L (2004) Biproportional techniques in input–output analysis: table updating and structural analysis. Moloney K, Raghavendra S (2011) Testing for nonlinear dependence in the credit default swap market. Nelson CR, Plosser CI (1982) Trends and random walks inmacroeconomic time series: some evidence and implications. Nguyen T (2007) Determinants of business cycle synchronization in East Asia: an extreme bound analysis. Ngoc Toan/Determinants_of_Business_Cycle_Synchronization_in_East_Asia-rv2_ In: Colander D (ed) Complexity and the teaching of economics. National Commission for Prognosis, Romania (2012) Data base of the macromodel-Dobrescu from the project strengthening the institutional capacity in evaluating and formulating of macroeconomic policies for economic convergence with EU within the National Commission for Prognosis, SMIS code 27153 34. Rosser JB Jr, Kramer KL Jr (2000) Integrating the complexity vision into mathematical economics. Section 4—Conclusions—presents the main conclusions of the research and outlines several possible future developments. The database and econometric analysis are presented in Statistical and Econometric Appendix. Afonso A, Furceri D (2007) Business cycle synchronization and insurance mechanisms in the EU. Belaire-Franch J, Contreras-Bayarri D (2002) The BDS test: a practitioner’s guide.

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