Lec-8A - Business Cycle.ppt

112/04/19Intermediate Macroeconomic Theory

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Business Cycle Measurement

IU – Main Campus

A. Z. Warsi

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Regularities in GDP Fluctuations• Business Cycles:

Fluctuations about trend in real GDP.

• Peak (Trough): A relatively large positive (negative) deviation from trend.

• Peaks and troughs are referred to as turning points.

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Regularities in GDP Fluctuations• Amplitude: The

maximum deviation from trend.

• Frequency: The number of peaks in real GDP that occur per year.

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Observations from the U.S. Data• Consider the

percentage deviations from trend in real GDP over the period 1947 - 2006.

• 3 main observations:– Persistency– Irregularities– Comovement

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Observations from the U.S. Data• Persistency: the

deviations from trend are persistent in the sense that when real GDP is above (below) trend, it tends to stay above (below) trend.

• This is important for making economic forecast over the short run.

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Observations from the U.S. Data• Irregularities:

– Irregularities in the amplitude and frequency of fluctuations in real GDP about trend.

– These imply that forecasting is difficult for longer term.

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Observations from the U.S. Data• Macroeconomic variables usually fluctuate together in

patterns that exhibit strong regularities: Comovement• 3 ways of describing comovement relative to real GDP:

– Procyclical, countercyclical, acyclical– Leading, lagging, coincident– Variability relative to GDP

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Observations from the U.S. Data• Procyclical variable: If

its deviations from trend are positively correlated with the deviations from trend in real GDP.

• Examples:– Real consumption, real

investment, real imports, money supply, employment and real wage.

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Observations from the U.S. Data• Countercyclical variable:

If its deviations from trend are negatively correlated with the deviations from trend in real GDP.

• Example:– Price level

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Observations from the U.S. Data• Acyclical variable: If it

is neither procyclical or countercyclical.

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Observations from the U.S. Data• Degree of correlation between two variable x and y is

measured by the correlation coefficient ,

takes on values between –1 (perfectly negatively correlated) and 1 (perfectly positively correlated).

)var()var(),(yx

yxCov

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Leading and Lagging• Leading variable: Its

peaks and troughs tend to precede those of real GDP.

• This kind of variable tends to aid in predicting the future path of real GDP.

• Example: Money supply

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Leading and Lagging• Lagging variable: Its

peaks and troughs tend to lag before those of real GDP.

• Contrary, real GDP helps to predict the future path of such a variable.

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Leading and Lagging• Coincident variable:

One that is neither leads nor lags real GDP.

• Examples:– Real consumption– Real investment– Price level

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Variability relative to GDP• Variables that are more volatile than real GDP:

– Real investment, real imports

• Variables that are less volatile than real GDP:– Real consumption, price level, money supply and

employment

• Cyclical variability is measured by the standard deviation of the percentage deviations from trend.