true or false and give a brief explanation on why its correct or wrong. a) To correct for seasonality in daily data, we add seven dummy variables for each day of the week  to the model. b) In time series models, OLS estimators are consistent under the contemporaneous exogeneity assumption.  c)Suppose yt  is an I(1) process. Does This means that yt is a stationary process.

Write first-order model relating E(y) to four quantitative independent variables.

You are given a sample of 600 working individuals, with data on their location and earnings. You construct the following model: wage=Bo+Binorth+u, where the dependent variable is the annual earnings (wage) in $1,000. The explanatory variable is north (which equals one if a worker lives in the north, and equals zero otherwise). An OLS regression yields B 24.8. B₁ = 2.1. = As we have learned in class, education matters a lot in explaining wages-more years of education lead to higher wages. In the above econometric model, education belongs to the error term, u. We also know that in our population of interest, workers in the north have lower drop-out rates than workers in the south. These facts imply that B₁ is biased and inconsistent because the estimation is subject to omitted variable bias. The correct model should be: wage Bo+Binorth + B₂educ + e, where educ denotes the number of years of education. The OLS estimate of B1 from our incorrect model presented at the beginning of this…

What conditions must non-linear time series models, such as vector autoregressive models, satisfy in order to use impulse response functions

1. Suppose output (Q) is related to labor (L) and capital (K) in the following nonlinear way: Q = albKc When taking log to this equation, it is transformed into a linear LnQ = Ina + b In(L) + c Ln (K) One hundred twenty-three observations are used to obtain the following regression results: Dependant Variable: Observations: Variable Intercept L K Q 123 5.5215 Parameter Standard Estimate error 0.650 R-square 0.350 0.7547 0.9750 0.2950 0.1450 F-ratio 184.56 t-ratio 5.66 2.20 2.41 p-value on F 0.00001 p-value 0.0001 0.0295 0.0173 a. Write the regression equation based on the output either in the transformed linear form or the original non-linear form.

MULTIPLE CHOICE Let yt = 12.50 be the natural logarithm of Real GDP in year t. Suppose that gt = 12.45 is the trend for yt in year t. Then: (1) the cyclical component of Real GDP in year t is 5%. (2) the cyclical component of Real GDP in year t is −5%. (3) the cyclical component of Real GDP in year t is 0.05%. (4) the cyclical component of Real GDP in year t is −0.05%.

number 1 please

Describe the recommended approach towards determining model specification.How does the R2 help in determining an appropriate model? Is theideal model the one with the highest R2? Should a regressor be included in the model if it increases the model R2?

We have a pooled cross section of data with data from 2009 and 1999 on women’s wages and their years of education. We consider the model: wage = β0 + β1Year2009 + β2educ + β3Year2009 × educ + u where wage is the hourly wage and educ is the years of education. Year2009 is a dummy variable equal to 1 in the year 2009 and 0 otherwise. Which of the following measures the change in the effect of education on the wage between 1999 and 2009?  a) β0 b) β1 + β2 + β3 c) none of these answers d) β1 + β3 e) β3