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Total Spending Equation of St. Louis Model: A Causality Analysis for Turkish Economy
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作者 Mert Topcu Ayhan Kuloglu 《Chinese Business Review》 2012年第4期368-376,共9页
Andersen and Jordan (1968) aimed to measure efficiency of monetary and fiscal actions on real GDP by employing a time-series model which was called as St. Louis Model afterwards. Although the model is performed in m... Andersen and Jordan (1968) aimed to measure efficiency of monetary and fiscal actions on real GDP by employing a time-series model which was called as St. Louis Model afterwards. Although the model is performed in many countries similarly, the results differ from each other in accordance with the economic structure of relevant country In this regard, the aim of this paper is to investigate the effectiveness of monetary and fiscal policies on real activity and to find out causal relationship among questioned variables using OLS and causality methodologies in Turkish economy over the period 1998:1-2010: IV. Empirical findings indicate that only monetary policy has a significant positive effect on economic activity in the short run, Nonetheless, neither monetary nor fiscal policy has significant impact on real output in the long run. Causality analysis shows that there exists a unidirectional causality running from real output and money stock to government expenditures. Moreover, not surprisingly, it is also found that crisis experiences of Turkey in sample period have highly adverse impact on real activity. Causality analysis suggests us considering government expenditures as explained variable instead of real output. Hence, it can be concluded that St. Louis Model total spending equation is not applicable for Turkish economy during 1998-2010 periods 展开更多
关键词 St. Louis model monetary policy fiscal policy Turkish economy causality
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A Novel Fractal-Based Real Time Video Encoder
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作者 WU Meng (Department of Telecommunications Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, P.R.China) 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2000年第3期53-59,共7页
Fractal encoding technique possesses some particular properties which make it as an attractive approach to video sequences compression. In this paper, we propose a novel fractal based encoding method for video signal... Fractal encoding technique possesses some particular properties which make it as an attractive approach to video sequences compression. In this paper, we propose a novel fractal based encoding method for video signals, which, based on Self Transformation Systems( STS ), is combined with Motion Compensation as well as nonlinear transformation. Experiment of results of realtime image sequences show that the proposed method can achieve a very fast encoding speed and acceptable tradeoff between compression ration and decoding quality. 展开更多
关键词 visual communication fractal block encoding Motion Compensation sts model
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Over-Smoothing Algorithm and Its Application to GCN Semi-supervised Classification
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作者 Mingzhi Dai Weibin Guo Xiang Feng 《国际计算机前沿大会会议论文集》 2020年第2期197-215,共19页
The feature information of the local graph structure and the nodes may be over-smoothing due to the large number of encodings,which causes the node characterization to converge to one or several values.In other words,... The feature information of the local graph structure and the nodes may be over-smoothing due to the large number of encodings,which causes the node characterization to converge to one or several values.In other words,nodes from different clusters become difficult to distinguish,as two different classes of nodes with closer topological distance are more likely to belong to the same class and vice versa.To alleviate this problem,an over-smoothing algorithm is proposed,and a method of reweighted mechanism is applied to make the tradeoff of the information representation of nodes and neighborhoods more reasonable.By improving several propagation models,including Chebyshev polynomial kernel model and Laplace linear 1st Chebyshev kernel model,a new model named RWGCN based on different propagation kernels was proposed logically.The experiments show that satisfactory results are achieved on the semi-supervised classification task of graph type data. 展开更多
关键词 GCN Chebyshev polynomial kernel model Laplace linear 1st Chebyshev kernel model Over-smoothing Reweighted mechanism
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