Strength of Relation Between Gdp Growth and Other Variables

Introduction Word count: 1892

The report will firstly introduce the cyclical nature and indicator properties. After that, there is an analysis of coefficients of correlations between GDP growth and other indicators. The cyclical nature and properties of indicators will be distinguished in part 1. The part 2 will focus on the trends forecast of indicators with graphs and provide predictions of Australia’s economic.

Part 1

Table 1 is an analysis of cyclical nature and properties of indicators. Especially the table I shows the coefficients of correlation and cross-correlation between GDP growth and other indicators. All the indicators were obtained quarterly from 1996 to 2012 and are seasonal adjusted. The coefficients of correlation show the strength of relations between GDP growth and other variables. And the coefficients of cross-correlation show the strength of relations between GDP growth (in period t) and other variables within different periods such as X= t-i and X= t+i ( i= 1, 2, 3, 4, 5). The types of cyclical nature include pro-cyclical, counter-cyclical and uncorrelated. Which pro-cyclical means the variables are positive related and the coefficient is greater than 0. The counter-cyclical means the variables are negative related and the coefficient is less than 0. Uncorrelated occurs only if the coefficient equals to 0 which means there are no relation between variables. Therefore, the cyclical nature of indicators can be defined.

The properties of indicator include leading, lagging and coincident. To determine the properties of indicator, it needs to compare the absolute value of coefficients in correlation and cross-correlation for the indicator. If the largest absolute value is in the column of X= t-i, the indicator has the leading property. If the largest absolute value is in the column of X= t+i, the indicator has the lagging property. Coincident indicator occurs if the largest absolute value is in the X= t column. Therefore, following are the cyclical nature and indicator properties.

Inflation

a) As showed in Table 1, the correlation coefficient between Inflation and GDP growth is -0.3193, therefore the cyclical nature of GDP growth and inflation is counter-cyclical which means there is a negative relationship between two variables. For example, the increase in the inflation will lead GDP growth to decrease.

b) The largest absolute value in the line is 0.3193 in the X= t column. Therefore the indicator property for inflation is coincident indicator.

Exchange rate

a) As showed in Table 1, the correlation coefficient between exchange rate and GDP growth is -0.0513, therefore the cyclical nature of GDP growth and exchange rate is counter-cyclical which