Consider the following unobserved effects model: Yit =B₁xit1+...+Bkitk + ai + Uit You plan on using fixed effects to estimate the model. Suppose you have a panel data set consisting of 10 individuals over 6 years. However, you are missing the last 3 years of data for the third, i = 3, Individual in your data set. Your panel data set has total observations. Suppose the reason individual i is missing data for certain time periods (called attrition) is correlated with the idiosyncratic error, uit. Recall that ai is assumed to be uncorrelated with the idiosyncratic error, uit. This correlation cause the fixed effects estimators to be biased.

Consider the following unobserved effects model: Yit =B₁xit1+...+Bkitk + ai + Uit You plan on using fixed effects to estimate the model. Suppose you have a panel data set consisting of 10 individuals over 6 years. However, you are missing the last 3 years of data for the third, i = 3, Individual in your data set. Your panel data set has total observations. Suppose the reason individual i is missing data for certain time periods (called attrition) is correlated with the idiosyncratic error, uit. Recall that ai is assumed to be uncorrelated with the idiosyncratic error, uit. This correlation cause the fixed effects estimators to be biased.

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4A: Problems In Applying The Linear Regression Model

Section: Chapter Questions

Problem 5E

See similar textbooks

Similar questions

Consider the binary variable version of the fixed effects model with an additional regressor, D1; that is, let Yit = β0 + β1Xit + γ1D1i + γ2D2i +...+ γnDni + ui.a) Suppose that n = 3. Show that the binary regressors and the “constant” regressor areperfectly multicollinear; that is, express one of the variables D1i , D2i, D3i, and X0it as aperfect linear function of the others, where X0it = 1 for all i,t.b) Show the result in (a) for general n.c) What will happen if you try to estimate the coefficients of the regression by OLS?
Fixed effects model with three time periods Consider the following general fixed effects model for use with a panel data set with three time periods (T = 3): yir = 51 +82 d2: +63 d31 + ẞ1x11 + ... + ẞkxisk + Vit where, for t=1, 2, 3, and time period 1 is the base year: yir = value of dependent variable y for i, in year t, in pounds d2, 1 in the second time period (t = 2), and 0 otherwise d3, =1 in the third time period (t = 3), and 0 otherwise Xirl,..., Xink value of explanatory variables for individual i at time f Vir = composite error consisting of the unobserved, time-constant effect (a) and the idiosyncratic error (uir) If there are 106 cross-sectional units in your balanced panel data set, then the total number of observations you have in your data set is For the first time period (1), the intercept is Which of the following would cause pooled OLS estimation of the model to yield biased and consistent estimators? Check all that apply. Measurement error in any explanatory variable…
When estimating the equation: i Acrimerate =B+B Aunemployment + Au, i 0 The estimate of B, is only causal if there is no correlation between Acrimerate; 1 True False and Au; i
Describe the Probabilistic Analysis?
6. Assume we draw a random sample (ri, Yi) : i = 1, ..., N from a certain population and estimate the following linear model via OLS: aAEb4jalF: OLS? Which not? Why? y = Bo + B1r1 + u (i) E[ûr1] = 0 (ii) E[r1û] = 0 hold by construction of (iii) E[ù] = 0 ialF: id:KaAEftb4jalF:
A justification for job training programs is that they improve worker productivity. Suppose that you are asked to evaluate whethe r more job training makes workers more productive. However, rather than having data on individual workers, you have access to data on manufacturing firms in Ohio. In particular, for each firm, you have information on hours of job training per worker (training) and number of nondefective items produced per worker hour (output).(iv) If you find a positive correlation between output and training, would you have convincingly established that job training makes workers more productive? Explain.
1. A study published in 1993 used US state panel data to investigate the relationshipbetween minimum wage and the employment of teenagers. The sample period was1977 to 1989 for all 50 states. The author estimated a model of the following type:ln(Eit) = β0 + β1ln(Mit/Wit) + γ2D2i + ... + γnD50i + δ2B2t + ... + δTB13t + uitwhere E is the employment to population ratio of teenagers, M is the nominalminimum wage, and W is average hourly earnings in manufacturing. In addition,other explanatory variables, such as the adult unemployment rate, the teenagepopulation share, and the teenage enrollment rate in school, were included.(a) Name some of the factors that might be picked up by time and state fixedeffects(b) The author decided to use eight regional dummy variables instead of the 49state dummy variables. What is the implicit assumption made by the author?Could you test for its validity? How?(c) The results, using time and region fixed effects only, were as follows:ˆ ln(EIT ) =…
In the December, 1969, American Economic Review (pp. 886-896), Nathanial Leff reports thefollowing least squares regression results for a cross section study of the effect of age composition onsavings in 74 countries in 1964:log S/Y = 7.3439 + 0.1596 log Y/N + 0.0254 log G - 1.3520 log D1 - 0.3990 log D2 (R2= 0.57)log S/N = 8.7851 + 1.1486 log Y/N + 0.0265 log G - 1.3438 log D1 - 0.3966 log D2 (R2= 0.96)where S/Y = domestic savings ratio, S/N = per capita savings, Y/N = per capita income, D1 = percentage ofthe population under 15, D2 = percentage of the population over 64, and G = growth rate of per capitaincome. Are these results correct? Explain..
The model initial setup is• The number of vacancies posted in the economy during a particular month is v = 100.• There were initially u = 225 unemployed workers at the beginning of the month.• Suppose that the average wage is 0.6 relative to their productivity. Unemployed workersreceive benefits that are half the wage, i.e., b = 0.3 relative to productivity.• Suppose that the number of matches between firms and workers are given by thefollowing matching functionsM = Au^0.5v^0.5• Suppose that 45 workers were able to find a job by the end of the month.Answer the following questions.a) What is the monthly job finding rate?b) What is the probability that an average vacancy is filled in a month?c) What is the job creation cost, k?d) What is the value of A?e) Explain how introducing a searching cost to this model would affect the queue length,the number of vacancy and unemployment rate, and wage.
As a manager of a small software retailing company, you are concerned with projected profit next year. While profit can be determined as the difference between sales and maintenance cost, or in symbols, P = S - M, where P is profit, S is sales, and M is maintenance cost including technical support. It is argues that when sales goes up so does maintenance cost because the cost of technical support will go up. Further, it is measured that the correlation between S and M is 0.8. Now given the figure that sales next year is expected to be $300 thousand with standard deviation of $4 thousand and maintenance cost is expected to be $150 thousand with standard deviation of $6 thousand, what would be the expected profit and its standard deviation you will include in your report?
Mr. John operates a medium size business that sells tires. He buys most of his tires from a company that is located in South America. Mr. John believes that he is stocking too much tires so he decided to look into the situation. He wants to use the Economic Order Quantity (EOQ) model to manage his stock of tires. In order to use this model, he must first of all forecast the annual demand for his tires. Using a numerical example, demonstrate to Mr. John how he can use the manual trend projection method of forecasting to forecast demand for the next two years.
Many of the survey questions focus on the used to pay for college, so the undergraduates in the sur ing for their parents. For example, each participant is asked to report how much of the parent's current income is used to pay for college. Do you think it is wise to combine responses across the parents and undergraduates? Are you fully aware of how much money your parents are spending and borrowing for college? The authors report overall averages and percents in their repon spond. Chapter 6 Introduction to Inference 350 We will also consider this a sample from one population but this is debatable certainly Average college savings fund contribution. One survey question asked ho much money from a college savings fund, such as a 529 plan, is used to pay an answer Nonresponse should ahways be considered as a source of bias. In this case, the nonresponse is very low, so we'll proceed by treating the n1593 sample as EXAMPLE 6.4 for college. Of the 1600 who were surveyed, n= 1593 provided a…