With Panel Data, if we assume that the individual effects vi are correlated with the regressors Xit (i.e. E(vi|Xit) ≠ 0), which one of the following statements is correct: The Fixed Effects estimator is not consistent. Both the OLS and the Random Effects estimators are not consistent. The OLS estimator is not consistent, but the Random Effects estimator is consistent. The OLS estimator is consistent, but the Random Effects estimator is not consistent. All of the above. None of the above.

Introduction - Panel data - In pane data , individuals are observed at several points in time .This…

Answered: With Panel Data, if we assume that the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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7.55 The following variables were recorded for several counties in Minnesota in 1977: y = average rent paid per acre of land with alfalfa X₁ = - average rent paid per acre for all land x₂ = average number of dairy cows per square mile x3 = proportion of farmland in pasture The data for 34 counties are given in Table 7.5 (Weisberg 1985, p. 162). Can rent for alfalfa land be predicted from the other three variables? (a) Find 3 and ². (b) Find , and ß using Sex and sx as in (7.46) and (7.47). (c) Find R² and R2.
1) A researcher wants to know whether the number of hours students spent on social networking sites (e.g., Facebook, Instagram) is correlated with how long they study for final exams. The researchers asks 5 students at UCI to report their scores on these two continuous variables: Time on Social Networking Sites Time Spent Studying for Finals (hours) 2 5 7 3 9 (hours) 10 5 4 8 2 a) Create a scatter diagram for this correlation with Time on Social Networking Sites along the x-axis. b) Describe the pattern of the data points in terms of the strength and direction of the correlation.
Please assist with the following questions with the answers.
A weight-loss program wants to test how well their program is working. The company selects a simple random sample of 51 individual that have been using their program for 15 months. For each individual person, the company records the individual's weight when they started the program 15 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (205, 190) would be for a specific person and it would indicate that the individual started the program weighing 205 pounds and currently weighs 190 pounds. In other words, they lost 15 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.707. This clearly shows there is strong correlation, which got the company excited. However, when they showed their data to a statistics professor, the professor pointed out that correlation was not the right tool to show that their program was effective. Correlation will NOT show whether or not there is…
Which of the following is not a cause of perfect multicollinearity? Select all that apply. One of the explanatory variables is equal to half of another explanatory variable for 100% of the observations in the sample. The correlation between two of the explanatory variables is 1.00. One of the explanatory variables is equal to half of another explanatory variable for 20% of the observations in the sample. A dummy variable for male is included at the same time as a dummy variable for non-male. One of the regressors is X and another regressor is X².
q56.1
Which of the following is true regarding weak correlation coefficients? a. They indicate a slight causation between variables. b. They are found only with Pearson r coefficients. c. They may be the result of restricted range for one of the variables. d. They are rarely found in social science research.
1
Five observations taken for two variables follow. xi 4 5 12 4 13 yi 50 50 30 50 20 Compute the sample covariance (to 1 decimal and enter negative value as negative figure). Compute the sample correlation coefficient (to 3 decimals and enter negative value as negative figure)
For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of five types of automobile, the linear correlation coefficient is found and the P-value is 0.033. Write a statement that interprets the P-value and includes a conclusion about linear correlation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is nothing%, which is ▼ high, low, so there ▼ is not is sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles.
Which of the following is not a property of the product moment correlation coefficient? it is independent of sample size and units of measurement. it is a measure of association between two variables. it always lies between 1 and -1. it implies a causal relationship between two variables.
Which of the following is the research hypothesis of one-tailed dependent t-test expecting to see a significant decrease in the observed scores? A. mean(posttest) < mean(pretest) B. mean(posttest) = mean(pretest) C. mean(posttest) > mean(pretest) D. mean(posttest) ≠ mean(pretest)

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		The Fixed Effects estimator is not consistent.
		Both the OLS and the Random Effects estimators are not consistent.
		The OLS estimator is not consistent, but the Random Effects estimator is consistent.
		The OLS estimator is consistent, but the Random Effects estimator is not consistent.
		All of the above.
		None of the above.