Does financial development cause economic growth in the ASEAN-4 countries

This paper empirically examines the short- and long-run finance-growth nexus during the post-1997 financial crisis in the ASEAN-4 countries (i.e., Indonesia,Malaysia, Thailand and the Philippines) by employing battery of times series techniques such as autoregressive distributed lag (ARDL) model, vector error correction model (VECM), variance decompositions (VDCs) and impulseresponse functions (IRFs). Based on the ARDL models, the study documents a long-run equilibrium between economic growth, finance depth, share of investment and inflation. The study also finds that the common sources of economic progress/regress among the countries are price stability and financial development. Granger causality tests based on the VECM further reveals that there are: (i) no causality between finance-growth in Indonesia; the finding in favour of “the independent hypothesis” of Lucas (1988); (ii) a unidirectional causality running from finance to growth in Malaysia, thus supporting “the finance-growth led hypothesis” or “the supply-leading view”; (iii) a bidirectional causality between finance-growth in Thailand, the finding accords with “the feedback hypothesis” or “bidirectional causality view”; and (iv) a unidirectional causality stemming from growth to finance in the Philippines, the finding echoes with “the growth-led finance hypothesis” or “the demand following view” of Robinson (1952). Based on the VDCs and IRFs, the study discovers that the variations in the economic growth rely very much on its own innovations. If policy makers want to promote growth in the ASEAN-4 countries, priority should be given for long run policies, i.e., the enhancement of existing financial institutions both in the banking sector and stock market

Blind image separation based on exponentiated transmuted Weibull distribution

In recent years the processing of blind image separation has been investigated. As a result, a number of feature extraction algorithms for direct application of such image structures have been developed. For example, separation of mixed fingerprints found in any crime scene, in which a mixture of two or more fingerprints may be obtained, for identification, we have to separate them. In this paper, we have proposed a new technique for separating a multiple mixed images based on exponentiated transmuted Weibull distribution. To adaptively estimate the parameters of such score functions, an efficient method based on maximum likelihood and genetic algorithm will be used. We also calculate the accuracy of this proposed distribution and compare the algorithmic performance using the efficient approach with other previous generalized distributions. We find from the numerical results that the proposed distribution has flexibility and an efficient resultComment: 14 pages, 12 figures, 4 tables. International Journal of Computer Science and Information Security (IJCSIS),Vol. 14, No. 3, March 2016 (pp. 423-433