Warning: Undefined array key 1 in /home/acaproso/public_html/._System/._Template/.Main.php on line 116
Econometrics questions.

Econometrics questions.

Find Econometrics university examination questions in acaproso.com

# Question
1

Many analysts feel that it is inappropriate to use the ordinary least squares(OLS) methods to model time series data. List three consequences of using OLS methods to model time series data.


Short answers
2

If you are to collect data, what are the three things you have to consider before you decide on the type of dataset you need to collect/use?


Short answers
3

If a consultant gives you a dataset containing information on the total number of accidents per 120 workers at Tanzania Breweries for the year 2014.

  1. What type of dataset will this be?
  2. What three things might the company be interested in analysing or what kind of information (three) can the company get from such a dataset.

Short answers
4

Briefly define the following

  1. Longitudinal data
  2. Econometric model
  3. Binary variables
  4. Autocorrelation
  5. Random variable

Short answers
5

One of the assumptions underlying the use of ordinary least squares(OLS) is that errors in an econometric model should not be correlated.

  1. What is the technical name for such a problem?
  2. Describe the method that is appropriate to test its presence
  3. In an event you detect this problem what should be done to make results of an econometric model realistic?
  4. There could also be problems when other assumptions are violeted. Mention two other assumptions which should not be violated?
  5. Explain the consequences of violating any of the assumptions mentioned in part (d).

Long answers
6
  1. What is ANOVA
  2. Using your knowledge of ANOVA complete all missing values in Table below.
Source of variation Sum of square(SS) Degree of freedom (df) Mean square (MS)=(SS/df) F-statistic
Regression(ESS) 250.75   250.75  
Residual (RSS)        
Total(TSS) 575.40 15    
  1. Explain why the test statistic used in ANOVA should be F-statistic.
  1. Given this F-test what are numerator`s and denominator`s degree of freedom?

Mathematical Calculation
7

Read the data presented in the table below carefully:

Sample data on maize prices(TZS/Kg) and inflation rate

Maize price (Y) 1200 1300 1350 1350 1400 1460 1500 1700
Inflation rate(x) 3.5 3.9 4.0 4.3 4.7 4.8 5.0 6.2

r=frac{nsum xy-sum xsum y}{sqrt{[n(sum x^{2})-(sum x^{2})][n(sum y^{2})-(sum y)^{2}]}}

t=frac{r}{sqrt{frac{1-r^{2}}{n-2}}}

  1. Using data presented above, calculate the sample correlation between maize price and inflation rate
  2. Interpret the correlation coefficient
  3. State the null and alternative hypothesis to test whether there is a significant linear association between maize price and inflation rate.
  4. What conclusion will you make? Note that  t(6)=2.4469.

Mathematical Calculation
8
  1. Describe the linear probability model (LPM) and give an example of its use in agriculture or any other sector of the economy.
  2. Describe the difference between the ordinary least squares (OLS) model and LPM
  3. In a logit model what is the interpretation of a slope coefficient for a particular variable in the model?

Short answers
9

Read the data presented in the table below.

Average maize yield in Kg/Ha among farmers in Mbozi District, Mbeya region.

Farmer`s ID 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Yield(kg/Ha) 30 64 30 29 40 52 67 29 64 37 40 67 29 37
Farmer`s ID 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Yield(kg/Ha) 67 29 64 37 64 30 64 30 29 40 52 67 29 64
Farmer`s ID 29 30 31                      
Yield(kg/ha) 37 40 67                      

Using the data presented in the table above answer the following questions:

  1. Find the sample variance and standard deviation of maize yield.
  2. Find the 95% confidence interval (C.I) for the true mean
  3. Based on this interval test whether the mean yield is less that 50Kg/Ha.

Mathematical Calculation
10

The following table shows data on the number of visitors (v) to Serengeti National Park and the amount of money they spent (m).

Number of visitors v(1000) 2450 2480 2540 2420 2350 2290 2400 2460
Amount of money spent m(1000 US $) 1370 1350 1400 1330 1270 1210 1330 1350
  1. Find the correlation coefficient between m and v
  2. Give a reason to support fitting a regression model of the form m=alpha +eta v+ mu to these data.
  3. FInd the estimator of eta correctly to two decimal places
  4. Find the equation of the regression line
  5. Interpret the value obtained in part (c)

Mathematical Calculation