Saturday, September 7, 2019

Choose an article or book chapter that has applied multivariate Essay

Choose an article or book chapter that has applied multivariate analysis to a research question. Explain the key issues that m - Essay Example Hair et al. (1994, p. 2) defined multivariate as analysis of several variables within a relationship or set of relationships. Hair et al. (1995, p. 13) explicit include multiple regression (a regression with one dependent variable and multiple independent variable) as an example of multivariate data analysis. Singh (2007, p. 177) share the same perspective of Hair et al. (1995) on a less restrictive definition of multivariate analysis. We study Kogid et al. (2010) and Shelleman et al. (2004) as illustrations of how multivariate analysis can be applied. 2.0. Kogid et al. (2010) As indicated in the abstract, the objective of the Kogid et al. (2010, p. 123) is to â€Å"investigate the factors that stimulate and maintain economic growth.† The factors investigated covered consumption expenditure, government expenditure, export, exchange rate, and foreign investments. The research focused on Malaysia and used data from 1970 to 2007. The specific multivariate statistic technique used by the Kogit et al. (2010) is technique known as â€Å"cointegration† and â€Å"causality approach†. Cointegration is discussed in Gujarati (2004, p. 822-826). Causality is discussed in Gujarati (2004, p. 696-702). One important test for causality is in Gujarati (2004, p. 696-702). According to Gujarati (2004, p. ... 822). Most tests of causations use tests of correlations. However, other tests go beyond correlation. One of such tests is the Granger causality test. Granger causality test actually test precedence and precedence is taken to be indicative of causality. Unfortunately, Gujarati (2004) does not record a capability of the Granger causality test to cover more than two variables at time (although it can be argued that the Granger causality test has that potential if a composite value covering several variables is constructed). In contrast, the Wald test as performed by Kogit et al. (2010) implies a capability of the Wald test to investigate relations of causation that involve more than two variables. Extensive search on the Wald Test conducted by this author in the books indicates that the Wald Test for causation is not yet discussed in many of the books. However, the works of Atinay and Karagol (2005), Burda (2001), No and Olatubi (2004), and Zarra and Zarea (2007) have good discussions on the Wald Test. The results of the study of Kogit et al. (2010) indicate that long-run cointegration and short-run causal relationship exists between the investigated factors and economic growth. The fundamental and important finding is all the factors investigated when combined can in their combination cause economic growth in the short-run. However, on their own, the individual regressions indicate that only consumption expenditure and export can on its own cause economic growth in the short-run. For brevity, we reproduce only the key test which is the causality test. The causality test is captured by Table 1. Table 1. Multivariate and Bivariate Causality Tests Using the Error Correction Model (ECM) Source: Table 3 of Kogit et

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