## CHECK THESE SAMPLES OF Econometrics 2

...?**Econometrics** Regression Model Question A The other hypothesis to be investigated by this regression was weather the level of education of women had an impact on their level of availability or participation in the work place. This was to be monitored using the coefficient educ. The availability and increase of other sources of income for the family was also considered to find out weather the same affected their level of commitment at work. This was done using the variable nwifeinc. The estimated coefficients had the signs as expected and were of statistical significance, this was demonstrated clearly buy the patterns displayed by the respective graphs of the variable coefficients. It therefore demonstrated beyond any...

3 Pages(750 words)Assignment

....6946349 lweight02 | -.1928427 .0676438 -2.85 0.004 -.3255582 -.0601272 lexp | .096436 .0445005 2.17 0.030 .0091272 .1837448 ltenure | .0840076 .011747 7.15 0.000 .0609602 .107055 lhours | .2658989 .0535023 4.97 0.000 .1609288 .3708689 catgov | -.0469187 .034193 -1.37 0.170 -.1140045 .0201672 female | -.2666817 .033851 -7.88 0.000 -.3330966 -.2002669 region | -.0327165 .012845 -2.55 0.011 -.0579181 -.007515 _cons | -2.270849 .4863924 -4.67 0.000 -3.225139 -1.31656 ------------------------------------------------------------------------------ **2**. Explanation of Constructed Variables logearnings = log(earnings) the ‘l’ prefixes on the independent variables indicate natural logs. For example, ls = log(s), ltenure =...

3 Pages(750 words)Essay

...in the dependent variable are explained by changes in the independent variables. Including an insignificant variable as one of the independent variables may minimize the effects of the actual variable causing the variation in the independent variable. Like in the example above, if truly age is not a determinant of income as stated in equation 1, then including it like in equations **2** and 3 will minimize the actual effects of education on income.
BIBLIOGRAPHY
Greene W. H. (2003). **Econometric** Analysis. Fifth Edition. Prentice Hall. Pearson Education International.
Anderson D. R., Sweeney D. J., Williams T. A. (2005). Statistics for Business and Economics. Ninth Edition. Thomson...

3 Pages(750 words)Essay

...method and there may be competing candidates to describe a series.
To achieve stationarity or remove trend two techniques are usually applied. The first one involves fitting either a parametric model or a spline function. In this case the ARMA model is applied to the residuals. Alternatively, Box and Jenkins recommended taking suitable differences of the process to achieve stationarity. Here the assumption is that the original series is ARIMA and the difference gives rise to the ARMA series. To determine whether the series has been reduced to a stationary series, one may look at the autocorrelations. For a stationary series, the autocorrelation sequence would converge to 0 quickly as lag increases.
The time plot given in Figure...

5 Pages(1250 words)Assignment

...**ECONOMETRICS** PART Question a) From table the correlation coefficient between health status and years of education is 0.33. When the correlation coefficient in absolute values is between 0.1 and 0.5, there is a weak correlation between the variables and when the values are between 0.5 and 0.9 there is a strong correlation. In this case, there is a weak positive correlation between the two variables. Since the coefficient is positive, there is a positive linear relationship between health status and years of education. When years in education increase, there is an improvement in health status of the individual.
Question 1 (b)
i. Number of doctor visits and gender
The results of the regression are demonstrated in table...

16 Pages(4000 words)Essay

...work Finance and Accounting **Econometrics** Question Model2 (Model **2**) read = 419.7 – 18.6 * noroom – 50.0 * noeng + 29.4 * fiction
N = 11984, R2 = 0.204
(1.7) (2.6) (3.1) (0.6)
Interpretation of the coefficient for noroom
Because noroom is one of the continuous variables, its coefficient is represented by -18.6 which is a constant. If the value of noroom increases, the model value reduces
Hypothesis test
In order to test for the hypothesis, we use t test as follows
t = (1.7-2.6)/(3.1/SQRT(18.6)) =
The t score is less than 0.5 at the 5% significance level (Dougherty, 2008). This confirms the null hypothesis, that the parameter is -20 against the alternative hypothesis that the parameter is greater than...

3 Pages(750 words)Coursework

...Question 3 Use the data set shorttbills.wf1. Limit the sample so that it begins in 2002. Regress the three month treasury bill rate (tb3ms) on the lagged three month rate and the twice lagged 6 month rate (tb6ms(-**2**)). Do the coefficients make much sense? (Okay, explain why they don’t.) Test, at the 1% level, for first-order serial correlation using the Breusch-Godfrey test. Now run the regression correcting for serial correlation by including AR(1) in the regression. Do the coefficients make sense now? Correct for second order serial correlation (add AR(1) and AR(**2**)). How about the coefficients now?
The regression output looks like
Dependent Variable: TB3MS
Method: Least Squares
Date: 09/17/12 Time:...

1 Pages(250 words)Assignment

... **Econometrics** Question Required coefficients in the estimate table become evident through writing of the needed estimates using the fitted model, μ12 will be
= (ΣkY12k)/n12
= (Σkμ)/n12 + (Σkα1)/n12 + (Σkβ2)/n12 + (Σkαβ12)/n12 + (Σkε12k)/n12
We then assume that averages of the errors in this context are zero (εijk):
= μ + α1 + β2 + αβ12
Question **2**
In the same way, the mean in table 1 will be:
μ11 = μ + α1 + β1 + αβ11
Getting the estimates of table 1 mean, add the estimates at μ, α1, β2, and αβ12.
Achieving this goes by multiplying the solution vector with a vector coefficients (e.g. Sum-product)
Solution for Coefficient estimates
Effect
a
b
Estimate
Standard Error
DF
t Value
Pr > |t|
Intercept
21.6100
0.2958
72
83.21
<.0001
a
1... ...

3 Pages(750 words)Assignment

...Lecturer’s and Number Submitted **Econometrics** In an influential article, ‘‘Hedonic Housing Prices and the Demand for Clean Air," David
Harrison and Daniel Rubinfeld study the impact of improvements in air quality on local citizens as reflected through differences in housing prices. A simplified version of their model, which is to be studied, is
ln(MVi) = β0 + β1RMi + β2 ln(DISi) +β3NOXi + β4DCHAS;i + Ɛi , (1)
where the level of observation is the census tract. Further, MVi is the median housing price (measured in $1,000) for a given census tract in the Boston metropolitan statistical area.
RM is the average number of rooms in owner occupied housing in the census tract; DIS is a weighted...

2 Pages(500 words)Assignment

...Applied **Econometric** paper s Affiliation Introduction This paper gives answers to certain questions regarding a study by Acemoglu, Johnson & Robinson (2001): Colonial Origins of Comparative Development. In their study, they claim that countries with quality institutions and secure property rights appear to have higher economic growth than their counterparts. From the **econometric** model adopted by Acemoglu, Johnson & Robinson (2001), the following questions will be answered appropriately.
Question 1
The coefficient estimate (β1) measures how economic growth increases due to the increase in institutions ` quality. Therefore, economic growth will increase by 43% whenever the quality of institution increases...

11 Pages(2750 words)Speech or Presentation