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Regression

Regressions are used to compare variables to determine how strong the nature of the correlation and causation between variables. Variables in regression analysis are separated into explanatory variables and endogenous variables. Explanatory variables are usually seen as policy instruments, which are variables that economists and policy makers can control or change¹. An example of a policy instrument is the supply of money, which is controlled by the Federal Reserve. The Federal Reserve must collect data on a periodic basis and the statistics will tell the Federal Reserve if there is a problem in the economy, such as inflation¹.

Regression analysis is present in almost all fields of economics. An example would be a family’s consumption expenditure being represented by the dependent variable and the family’s income, number of family members, and other factors being represented by the independent variable. A basic regression technique is the ordinary least squared regression.

 

References:

1. Naghshpour, Shahdad. Statistics for Economics. New York, NY: Business Expert, LLC, 2012. 

Using a Regression Model: Predictive Equations In Home Prices

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Forecasting for Personal Computers and Printers Sold

I need some assistance in completing the following assignment: Infoworks is a large computer discount store that sells computers and ancillary equipment and software in the town where State University is located. Infoworks has collected historical data on computer sales and printer sales for the past 10 years, as follows:

Residual Plot in Regression: Homoskedasticity/Heteroskedasticity

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Properties of R-Square and Adjusted R-Square

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Regression on Stock Returns

I need some help with the calculations below: Estimate a regression of the form given by the below ri = β0 +β1Si + β2Mβi+ β3PEi+ β4βETAi +Ui In order to evaluate the effect of various firm -specific factors on the returns of a sample of firms . You run a cross -sectional regression with 200 firms Where ri= perce

Analyze and interpret the given results.

Chez Henri is a restaurant chain that operates in 40 different cities. It hired an economist to estimate the factors affecting the demand for its sales. The following equation was estimated using cross sectional data from each of its 40 restaurants. Y : Annual restaurant sales (in thousands) X1 : Disposable per capital inc

Regression Analysis: Sales and Total Variable Costs

Over the past 12 months the Four Winds Novelty Company firm has recorded its internet sales (equals monthly output levels) and its monthly total variable costs (TVC) for a particular novelty item as shown in the following table. Sales have grown over this period with relatively few shocks due to uncontrollable weather, political

The Beta for Colgate-Palmolive

The Beta for Colgate-Palmolive 1. Go to finance.yahoo.com and download the ending monthly stock prices for Colgate-Palmolive for the last 60 months. Use the adjusted closing price, which adjusts for dividend payments and stock splits. Next, download the ending value of the S&P 500 index over the same period. For the historica

Demand Analysis Trends and Forecasting

A linear trend equation for sales of the form Qt = a + bt was estimated using annual sales data for the period 2000 - 2007 (i.e., t = 2000, 2001, ..., 2007). The results of the regression are as follows: DEPENDENT QT R Square F Ratio P-Value on F VARIABLE: OBSERVATIONS:

How to estimate and evaluate a demand function

1.) Given the data set in the Excel spreadsheet,write the theoretical demand equation using the appropriate variable names.These variable names must be very short and in capital letters.For example,QTY for Y,PRPIZZA for X1,PRDRK for X3. For example,if you used QTY for quantity,use QTY in the estimating demand equation (in your e

Managerial Economics - Estimated Demand Equation

Please help me with these questions! 1. Write the theoretical demand equation using the appropriate variable names you created when you prepared data for analysis. The variable names should be very short and must be in capital letters. For instance, QTY for Y, PRPIZZA for X1, and PRSDRK for X3. For example, if you used QTY fo

Interpreting the Given Regression Results.

A multiplicative demand function of the form: Qd = a*P^b1*Y^b2*Po^b3 is estimated using cross-sectional data and 224 observations. The regression results were as follows: Constant (a) Price(P) Income(Y) Price of other good (Po) Coefficient 0.02248 -0.2243 1.3458

Surveying Buying Intentions

May Brothers Department Store has conducted a survey to learn the buying intentions of a sample of 62 department store customers. The survey asked each customer their household gross income (in thousands of $'s), the number of people living in the household, and the number of shopping trips they take per year. The regression re

Solving for Coffee Demand Using Regression Analysis

This is a portion of the solution. Please see attachment for full problem and solution: In their article, "The Demand for Coffee in the United States: 1963-1977" (Quarterly Review of Economics and Business, Summer 1980 pp.36-50), C.J. Huang, J.J. Siegfried, and F. Zardoshty estimated the following regression equation using qu

Measuring Correlations of Variables with Money Spent

Refer to Column 3 of Table 1 on p. 31 of the following journal paper (see reference below). The dependent variable is the amount of money spent on conservation so the table measures the correlations between this variable and a variety of independent variables from the model. a. Describe the correlation with the independent va

Transportation Economics Questions

Please see the attached files. 1. Use the data from the table to estimate a demand equation for Union Atlantic rail service using regression analysis. Round the coefficients you obtain from the regression equation to the nearest whole number (e: 10.56 rounds to 11). Use your regression results to answer the following question

Multiple least squares are analyzed.

Please explain and show a detailed calculations. 1. Suppose that the true relationship between y, x, and z is yi = β0 + β1xi + β2zi + ui, where economic theory predicts β0 > 0, β1 < 0, and β2 < 0. Ui is a random error with an expected value of zero. The following sample model has been proposed: Answer the following

Demand Equations

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Compute the percentage change of the values of output and exchange rate

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Derive demand equation.

Suppose that John Smith, the manager of the marketing division of Chevrolet at GM, estimated the following regression equation for Chevrolet automobiles: Qc=100,000 - 100 Pc + 2,000N + 50I + 30Pf - 1,000 Pg + 3A + 40,000P1 Where Qc= quantity demanded per year of Chevrolet automobiles Pc= Price of Chev. automobiles in do

Econometrics

This question refers to the estimated regressions in table 1 computed using data for 1988 from the U.S. Current Population Survey. The data set consists of information on 4000 full-time full-year workers. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's age

Ordinary least squares (OLS) and Heteroskedasticity

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estimated regression line

PLEASE SEE THE ATTACHED DOCUMENT FOR CHART (a) Complete the above table, putting the sums in the last row. What are mean of X(X(bar)) and mean of Y(Y(bar))? (b) Assume our estimated regression line is Y(hat)i = b0 + b1Xi and calculate b0 and b1 from this chart and provide an interpretation of each.

Assess the given demand equation.

Assume your research staff used regression analysis to estimate the industry demand curve for Product X. Qx = 10,000 - 100 Px + 0.5 Y - 1000 r (3,000) (25) (0.12) (900) Where Qx is the quantity demanded of Product X, Px is the price of X, Y is income, and r is the prime interest rate (given in decim

Multiple Regression

Do you suppose that when applying the multiple regression in the formula Y = b1X1 and b2X2 + E that X1 represents wages and X2 represents transportation costs? Discuss how X1 and X2 b slopes could create several different economic scenarios during different economic times of the year, or even during several different years, an

Calculate the sample regression line.

A company's sales (in million units), selling expenses (in $million), and price (in $/unit) data are provided in the table below. (A) Calculate the sample regression line, where sales is the dependent variable and selling expenses and price are the independent variable (B) Forecast the company's sales if the company inc

forecasted sales for Quarter I, Quarter II, Quarter III, and Quarter IV of 2011

A forecaster used the following regression equation: Qt = a + bt + c1D1 + c2D2 + c3D3 + e. Where, Qt is quarterly sales, D1, D2 and D3 are seasonal dummy variables for quarters I, II, and III, and e is the error term. The model was estimated using quarterly sales data for the period 2002II -2010IV (t = 1 for 2002II, ..., 35) a