Managerial economics

2. Please describe the method of least squares regression. Please show two graphs that represent relationships between Y and X, one that has uncertainty or forecast error and one that does not. Please show an example model from economics or finance that could be estimated with least squares. Please discuss and diagnose the two sets of regression results of the estimated demand functions for gasoline on Table 2 of the gas demand paper for the basic model: linear. Can you get the price and elasticity from these results? Please explain. IGNORE ALL REGRESSIONS EXCEPT THE RESULTS FOR THE TWO REGRESSIONS ON THE LEFT OF THE TABLE: BASIC MODEL LINEAR: 1975- 1980 and 2001 - 2006. The data used in the analysis are U.S. aggregate monthly data reported by several U.S. government agencies for the period from January 1975 to March 2006. Gasoline consumption is approximated as monthly "product supplied" reported by the U.S. Energy Information Administration (2006), which is calculated as domestic production plus imports, less exports and changes to stocks. Real gasoline prices are U.S. city average prices for unleaded regular fuel from the U.S. Bureau of Labor Statistics (2006), CPI-Average Price Data. Personal disposable income is from the U. S. Bureau of Economic Analysis (2006), National Economic Accounts. Prices and income are converted to constant 2000 dollars using GDP implicit price deflators from the Bureau of Economic Analysis (2006). B, is the intercept and the values below the estimated slopes are the standard errors of each slope. Also ignore In(Y) and In(P) as they are ot used in the first two regressions. Desktop O