## CHECK THESE SAMPLES OF Financial Econometrics

...?**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

...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

...Question 1.A. Hedge ratio could be computed by given information as follows: Given that: Then Given: , and x= 10, y= 30 Then it is possible to calculate hedge ratio from given information
1.B.
----- Equation (1)
----- (2)
The minimum hedge ratio required is 5.88%
= 299.4117 ----- (3)
Therefore by substituting (2) and (3) in (1)
1.C. Estimating Hedge Ratio by Regression:
Linear regression could be used to estimate the minimum-variance hedge ratio. The following approach has been extensively applied in the literature. The independent variable is the future return and the dependent variable the spot return to construct the following model:
Spot return = Constant + β future return + residuals.
β would provide... 1.A. Hedge ratio...

8 Pages(2000 words)Essay

...**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 2....

16 Pages(4000 words)Essay

...IG segment.
Selection Bias
The Possible selection bias in this study may be the restriction of our sample to managers with an MBA degree.
Identification Strategy
The main strategy used to identify the managers as investment grade and high yield is based on skill and focuses on the following:
Holders of master’s in Business Administration
Non holders of Masters in Business Administration
Holders of Certified **Financial** Analysts
Other Qualifications
Experience in the field
Endogeneity Problem
The fund family has to decide how to assign the managers to two funds: operating in the inefficient market segment and operating in the more efficient segment. To maximize its profit, the fund family allocates managers to funds so...

2 Pages(500 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 -20.
Question 2
The...

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: 15:24
Sample: 2002M01... Question 3...

1 Pages(250 words)Assignment

...**Econometrics** Log of Real Personal Disposable Income (Lrpdi) The graph above is a time series plot for the log of real personal disposable income. This series shows an upward trend. This implies that this variable has an upward trend across the years. This data is non-stationary since it is increasing with the change of time.
The graph above shows autocorrelation of Lrpdi. ACF is significant across the years. However, at year 1 it is quite high but it has a decreasing uniform trend across the years; implying that the data is not stationary.
The above plot shows the partial autocorrelation of Lrpsi. PACF is generally small in most of the years. Thus, the series has a significant autocorrelations across the years. However,...

2 Pages(500 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... Econometrics...

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