Business cycle measurement Flashcards

1
Q

Regularities in GDP fluctuations

A

Business Cycles are persistent fluctuations about trend in real GDP.

  • The turning points in the deviations of real GDP from trend are peaks and troughs.
  • Persistent positive deviations from trend are booms and persistent negative deviations from trend are recessions.

Amplitude is the maximum deviation from trend

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2
Q

Deviations From Trend in Real GDP are Irregular

A
  • The fluctuations in GDP about trend are quite choppy.
  • There is no regularity in the amplitude of fluctuations in real GDP about trend.
  • There is no regularity in the frequency of fluctuations in real GDP about trend.
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3
Q

Comovement

A
  • Macroeconomic variables fluctuate together in patterns that exhibit strong regularities
  • These patterns in fluctuations are referred to as comovement
  • We measure macroeconomic variables as time series
  • Positive correlation when variable x is high at the same time as variable y and vice versa
  • Negative correlation when variable x is high when variable y is low and vice versa
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4
Q

Scatter plot

A
  • Variable x on x-axis and Variable y on y-axix
  • If two time series are perfectly positively (negatively) correlated, then a scatter plot will be a positively (negatively) sloped straight line
  • Otherwise, correlation is determined by the slope of a straight line that is best fit to the data
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5
Q

Correlation with Real GDP

A
  • If the deviations from trend in a macroeconomic variable are positively (negatively) correlated with the deviations from trend in real GDP, then that variable is procyclical (countercyclical).
  • If a macroeconomic variable is neither procyclical nor countercyclical, it is acyclical.
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6
Q

Imports and real GDP

A
  • Procyclical
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7
Q

Correlation coefficient

A
  • Measure of the degree of correlation between two variables
  • Takes on values between -1 and 1
  • (1) = perfectly positively correlated
  • (-1) = perfectly negatively correlated
  • (0) uncorrelated
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8
Q

Leading variables

A
  • A macroeconomic variable that tends to aid in predicting the future path of real GDP
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9
Q

Lagging variables

A
  • If real GDP helps to predict the future path of that particular macroeconomic variable
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10
Q

Coincident variable

A
  • A macroeconomic variable which neither leads nor lags real GDP
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11
Q

Measure of cyclical variability

A
  • Standard deviation of the percentage deviations from trend
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12
Q

The components of GDP

A
  • Consumption = Highly positively correlated (procyclical), coincident variable. Less volatile/variable than GDP
  • Investment = Positively correlated (procyclical), coincident variable. More volatile/variable than GDP
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13
Q

The price level and GDP

A
  • The correlation of the price level with real GDP is close to zero.
  • This was not always so, as the price level tended to be negatively correlated with real GDP early in the post-World War II period.
  • However, over some periods of time in history, the price level has been procyclical.
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14
Q

The Inflation Rate and GDP

A
  • Phillips curve – Illustrates a negative relationship between the rate of change in money wages and the unemployment rate
  • If we take the unemployment rate to be a measure of aggregate economic activity, then the Phillips-curve captures a positive relationship between the rate of change in a money price and the level of aggregate activity
  • A positive correlation in the data of in the inflation rate with real GDP would be evidence of a Phillips curve relation.
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15
Q

Percentage Deviations from Trend in Employment and Real GDP

A
  • Employment is a procyclical, lagging variable, but is less variable/volatile than real GDP
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16
Q

Percentage Deviations from Trend in Average Labor Productivity and Real GDP

A
  • The behavior of average labor productivity is sometimes important in distinguishing among theories of the business cycle. In the data, average labor productivity is procyclical.
17
Q

Seasonal adjustment

A
  • Statisticians take account of the regular seasonal fluctuations in the data and try to take them out in a consistent way – Observe historical seasonal patterns and take out the extra amount we tend to observe during a particular time period
  • Sometimes there are issues with seasonal adjustment – a problem is that seasonal adjustment is purely statistical and takes no account of economic factors.