Problems and Questions

Briefly explain the meaning of R-squargond. A time series summary of direct tends to result In a higher R-squared than one development cross-sectional info. Why do you think this Is the case? R-squared measures the goodness of tally of a regression equation. A time series analysis of demand tends to result in a higher Required than one use cross-sectional data because data is being gathered at aggregate periods of time as opposed to one period of time when utilize cross-sectional data. II.What is the identification task? What effect will this problem scram on the regression predicts off demand function? Explain. The identification problem occurs when there Is an Inability In the principle to Identify the best estimate of values of one or more variables In regression. This problem set up regression estimates of a demand function because there is a concurrent shifting of both the supply and demand, which results in biased results. Ill. A. Why are manufacturers new orders, endogens capital goods, an set aside leading index finger?They are an clutch Indicator because they are commitments that show that economic activity will paying back place In the in store(predicate). B. Why Is the Index of Industrial production an appropriate coincident Indicator? The Index of Industrial production Is an appropriate coincident indicator because it provides information about the current state of the economy. C. Why is the middling prime rate charged by banks an appropriate lagging indicator? Its an appropriate lagging indicator because changes in the prime rate broadly trail changes in the rest of the economy.IV. You have been asked to produce a harbinger for your compacts product, bottled water. Discuss the kind of Information you would look for In order to plant this forecast. An effective forecast for bottled water would Include sales revenue, marketing, competition, Seibel issues that may airlift in the future, and information about the target demograp hic. V. One of the most tricky tasks in regression analysis is to obtain the data suitable for valued studies of this kind.Suppose you are trying to estimate the demand for home article of furniture. Suggest kinds of variables that could be used to represent the following factors, which are believed to affect the demand for any(prenominal) product. Do you anticipate any difficulty in securing such data? Explain. Determinants of Demand for Furniture Suggested Variables to use in Regression Analysis outlay Prices set for furniture at competing companies Tastes &038 Preferences % of people who like modern, rustic, traditional, contemporary, res publica, etc. Hypes of furniture Price of related products Price of accent Items (blinds, pillows, rugs) Income Average Income of buyers Cost or availability of credit % of people who purchase furniture with cash or credit Number of buyers of sales per year Future expectations Availability of products, future income of buyers Other possibl e factors Seasonal sales I do non see any problem securing this data. Most of this Information can be maker of a leading brand of low-calorie microwaveable food estimated the following rectify equation for its product using data from 26 supermarkets around the country for the month of April.