Negative autocorrelation in the change of a variable implies that: a. the data is negatively trended. b. the series is not stationary. c. the variable contains only negative values. d. an increase in the variable in one period is, on average, associated with a decrease in the next.
Question
Negative autocorrelation in the change of a variable implies that:
a. the data is negatively trended.
b. the series is not stationary.
c. the variable contains only negative values.
d. an increase in the variable in one period is, on average, associated with a decrease in the next.
Solution
The correct answer is:
d. an increase in the variable in one period is, on average, associated with a decrease in the next.
Explanation:
Autocorrelation refers to the degree of correlation between the values of the same variables across different observations in the data. The term 'negative autocorrelation' or 'inverse autocorrelation' refers to the situation where higher-than-average values of a variable are followed by lower-than-average values, and vice versa.
So, if we have negative autocorrelation in the change of a variable, it implies that an increase in the variable in one period is, on average, associated with a decrease in the next. This is because the negative autocorrelation is indicating that the values of the variable are alternating in a regular pattern between periods.
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