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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.



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

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Using a Regression Model: Predictive Equations In Home Prices

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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:

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Analyze and interpret the given results.

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Data Analysis with Stata

I am failing to use STATA to read and analyse the data in the attached file. May I please have a detailed analysis as per attached problem?

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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

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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:

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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

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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

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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

1. Using the following equation, what is the demand equation as a function of Ps if the price of other pastas (Po) is $2, the individual's income (Y) in thousands is $25, and tastes (Z) are represented by 20? What happens if the individual's income increases to $30? Qd= 500 - 10Ps + 5Po + 20Y +40Z 2. Given the regression e

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

Use regression analysis to explain the relationship between the two variables. Assignment #4: Interpreting Macroeconomic Conditions Supplement to Assignment 4 and Guidelines The table below shows the year (first column), the real GDP in billions of chained 2005 dollars (second column), and the domestic exchange rate for

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

Applied Problems

The director of marketing at Vanguard Corporation believes that sales of the company's Bright Side Laundry detergent (S) are related to Vanguard's own advertising expenditure (A), as well as the combined advertising expenditures of its three biggest rival detergents (R). The marketing director collects 36 weekly observations of


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Ordinary least squares (OLS) and Heteroskedasticity

1) If I suspect that heteroskedasticity is present in the following model .ie., we don't believe that the variance of women's earnings would be the same as the variance in men's earnings, what am I suspecting to be true (i.e. define heteroskedasticity)? What OLS assumption is violated if this were true? What are the repercussion

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.