Business and Economic Forecasting - Research Paper Example

Question The impact of the wages and the transportation costs will be eventually negative on the output level, as both factors will increase thecost of production and will eventually affect the overall output level. Hence, the slopes of both variables will be negative. As the increase in the wage rates will increase the cost of production which will lead to increase in the prices of products and eventually decrease in the demand of the products, hence the production will decrease. Same is true for the transportation costs (Hoshmand, 2009).

However, it is important to note here that increase in wage rates will also results in increase in the spending power of the consumers and consumers will be willing to pay more for the products, thus it can have some positive effect on the economy. On the other hand the increase in the transportation costs will have double fold negative impact on the economy as the consumers will have to also bear the increased in the transportation costs. Hence, there can be different economic scenarios during different economic times.

For instance, during the economic boom the increase in wage rates will not have strong negative impact on the economy, as the people will be ready to pay more for the products. However, the increase in the transportation costs will negatively influence the economy. But the increase in wages will have greater overall effect on the economy.On the other hand during recession the increase in the wages will have less positive and more negative impact, as still people will be more inclined towards saving and hence will be reluctant to pay more for the products.

Similarly the increase in the transportation costs will have negative influence on the economy. Hence, it can be said that the wages will have more effect on the state of the economy in different time periods. So the slope value of wages will be high as compared to that of the transportation costs in the multiple regression formula (Hoshmand, 2009).Question # 2:During regression analysis and evaluating regression models it is important to check that whether the regression model is efficient or not.

For this purpose different tests and methods are used by the researchers. One method used in this regard is the R2 test. The researchers use The R2 test in order to check whether the forecasted values are closely related and associated with the original values or not. This means that the high value of R2 depicts that there are less or few errors and residuals in the regression model. If the value of R2 is closer to one it means that the regression model is efficient and the forecasted values are more closed to the original values and the forecasted values are more close to the liner line.

In the other hand if the value of R2 is closer to zero it means that the regression model is not efficient and the forecasted values are not close to the original values.Hence, R2 test can be beneficial for testing and evaluating the efficiency of the regression models. If the value of the R2 is closer to the one that the forecasted values will fit the linear line and the regression model will be more effective and efficient and there will be less or few errors or residuals values (Wilson, Keating, & John Galt Solutions, Inc. 2009).ReferencesHoshmand, A. (2009). Business forecasting: a practical approach.

NY: Routledge.Wilson, J.H., Keating, B., & John Galt Solutions, Inc. (2009). Business forecasting with ForecastXTM (6th ed.). Boston: McGraw-Hill Irwin.