ISS (Statistical Services) Statistics Paper III: Questions 84  89 of 96
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Question number: 84
» Econometrics » AutoCorrelation
Appeared in Year: 2014
Describe in Detail
Describe the problem of ‘multicollinearity’ in econometrics and explain how will you detect it.
Explanation
Multicollinearity may arise for various reasons, they are:
There is a tendency of economic variables to move together over time. In time series data, growth and trend factors are the main causes for multicollinearity problem. For example, in period of booms or rapid economic growth the basic economic magnitudes grow. The income, consumption, savi
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Question number: 85
» Applied Statistics » Index Numbers » Laspeyre
Appeared in Year: 2014
Describe in Detail
Define Laspeyres’ and Paasche’s index numbers. It is sometimes stated that Laspeyres’ price index number tends to overestimate price changes while Paasche’s price index number tends to underestimate them. Justify or refute the above statement giving reasons.
Explanation
Laspeyre’s Index Number:
Laspeyre’s index number is a index number where the base year quantities are taken as weights. Under this method, we get the weighted index on the basis of aggregative expenditure, assuming that the quantities consumed in the base year are also the quantities consumed in the current year.
where
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Question number: 86
» Econometrics » AutoCorrelation
Appeared in Year: 2014
Describe in Detail
Explain the term ‘autocorrelation’. What are the consequences of autocorrelation? Explain how the Durbin Watson d statistic is used to detect the presence of autocorrelation.
Explanation
Autocorrelation:
Autocorrelation refers to the correlation of a time series with its own past and future values.
It is a measurement of the degree of similarity between a given time series and a lagged version of the same time series.
It can be considered as a special case of correlation, except that the same time series is used twice: once in
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Question number: 87
» Applied Statistics » Time Series Analysis » Illustration, Additive and Multiplicative Models
Appeared in Year: 2014
Describe in Detail
What are the two mathematical models employed for time series analysis? Can one model be considered as a particular type of the other one? Which one of the two models is considered to be more useful and why? Discuss each of the above aspects.
Explanation
The two mathematical models employed for time series analysis:
(i) Additive model
(ii) Multiplicative Model
Additive model:
According to the additive model the time series can be expressed as
where
is the time series value at time T
Represents the Trend value
Represents the Seasonal value
Represents the Cyclic value
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Question number: 88
» Econometrics » Heteroscedastic Disturbances
Appeared in Year: 2014
Describe in Detail
Discuss the problem of Heteroscedasticity in GLM. Describe Glejser test for detecting hetroscadasticity. What are the difficulties in using Glejser test? How do you overcome these difficulties?
Explanation
Problem of Hetroscadasticity:

One of the sources of Heteroscedasticity is grouping. data from large scale surveys are often in grouped form with an different number of entities in different groups. Working with group averages in such cases give rise to Heteroscedasticity disturbance.

There may be certain outlying observations in the data wh
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Question number: 89
» Applied Statistics » Index Numbers » Price Relatives and Quantity or Volume Relatives
Appeared in Year: 2014
Describe in Detail
Discuss how you will proceed for constructing a cost of living index number for a given expenditure group in a city.
Explanation
Steps involved in the construction of cost of living index number.
i) Scope and coverage: Since it is always constructed for a particular community, first step is to specify the particular class of people for which the index number is going to be constructed. such class may be industrial workers of a particular locality, government employees of a
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