
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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If a constant c is added to each possible value of a discrete random variable X, then the
Prove that statement using an
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- Consider the following panel model to examine the effect of retirement on consumption expenditure, consit, of individual i over years t=1,…,3: (B1) log(consit) = β0 + β1retiredit + β2ageit + β3marriedit + β4healthit + δ1Yr2t + δ2Yr3t + ai + uit Where: retiredit is a dummy variable equal to 1 if individual i is retired on year t and 0 otherwise ageit is the individual's age in years marriedit is an indicator variable for whether the individual is married (1) or not (0) in year t healthit is an indicator variable equal to 1 if the individual is in 'good health' and 0 otherwise Yr2 is a dummy variable equal to 1 in year t=2 and 0 otherwise Yr3 is a dummy variable equal to 1 in year t=3 and 0 otherwise Using the information above, answer the following 3 questions. [i] Give two (2) examples of the kind of variables captured by the term ai in Model (B1). [ii] What is the crucial assumption we must make so that the random effects (RE) estimator is consistent? Under this assumption, why is…arrow_forwardConsider the residuals from regressing the daily closing value of the S&P 500 against daily volume of shares traded: CLOSE, Bo + B₁VOLUME + u = spe & -100 02001 Ja 01apr2001 012001 Da These residuals appear to be characterized by Positive autocorrelation Negative autocorrelation paraply No autocorrelation. 01002001 01j200arrow_forwardConsider an economy where each worker is employed in either agriculture or services. Assume that log earnings of a worker are wo = 4o + €o if she is employed in agriculture and wi = µ1+€1 if she is employed in services, where µo and H1 are constants, ɛo ~ N(0, o3), and e1 - N(0, o?). Assume also that the correlation between earnings in the two sectors is p = g01 where oo1 = Cov(Eo, E1). Workers can be employed in agriculture at no cost, but they incur a cost C = T exp(wo) if they choose to work in services. Finally, assume that workers maximize their net earnings. Each worker knows all the parameters relevant to her decision. (a) Derive a linear approximation of the equation that determines whether an individual chooses services or agriculture. Assume that C is small compared to exp(wo), so you can ignore the error involved in this approximation. (b) Define v = €1 chosen worker is employed in services as a function of z, where z = (Ho – H1 +7)/0,. (c) How does this probability change…arrow_forward
- If the slope of a regression line (b1) is 1.5, then a) for every unit of change in x, there is a change of 1.5 units in y b) for every unit of change in y, there is a change of 1.5 in x. c) the score of each case is 1.5 times higher on yt han on x d)y causes Xarrow_forwardConsider the following population model for household consumption: cons = a + b1 * inc+ b2 * educ+ b3 * hhsize + u where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on educ, inc, and hhsize. Which of the following choice is correct and please explain why. A) be certain that R^2 = 1 B) be certain that R^2 = 0 C) be certain that R^2 is less than 1 but greater than 0. D) not be certainarrow_forwardThe subsets of {1,2} are Φ, {1}, {2} and {1,2}. So there are four possible potential models when deciding on a regression with a choice of inputs from a dataset containing two potential input variables. Your friend tells you this is nonsense and there are three possible models because the empty set Φ is just an imaginary concept concocted by some mathematician. What should you say to your friend? You should explain that the empty set corresponds to the model y = β + ε, where β is some constant and ε is a residual term. In this model, the output predictions are always equal to the output's sample average. You should explain that the empty set corresponds to the model y = ε, where ε is a residual term. In this model, the output predictions are totally random. You should indeed agree. Your friend is spot on and one cannot have a regression with no input variables. You should partially agree. Your friend is spot on that there are three models and not…arrow_forward
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