Business Cycle Models with Indeterminacy


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While we see continuous growth of output, it is not a steady increase. There are times of faster growth and times of slower growth. Figure 2 transforms these levels into growth rates of real GNP and extracts a smoother growth trend. A common method to obtain this trend is the Hodrick—Prescott filter. The basic idea is to find a balance between the extent to which general growth trend follows the cyclical movement since long term growth rate is not likely to be perfectly constant and how smooth it is.

The HP filter identifies the longer term fluctuations as part of the growth trend while classifying the more jumpy fluctuations as part of the cyclical component. Observe the difference between this growth component and the jerkier data. Economists refer to these cyclical movements about the trend as business cycles. Figure 3 explicitly captures such deviations. Note the horizontal axis at 0. A point on this line indicates at that year, there is no deviation from the trend. All other points above and below the line imply deviations. By using log real GNP the distance between any point and the 0 line roughly equals the percentage deviation from the long run growth trend.

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Also note that the Y-axis uses very small values. This indicates that the deviations in real GNP are very small comparatively, and might be attributable to measurement errors rather than real deviations. We call large positive deviations those above the 0 axis peaks. We call relatively large negative deviations those below the 0 axis troughs. A series of positive deviations leading to peaks are booms and a series of negative deviations leading to troughs are recessions.

At a glance, the deviations just look like a string of waves bunched together—nothing about it appears consistent. To explain causes of such fluctuations may appear rather difficult given these irregularities. However, if we consider other macroeconomic variables, we will observe patterns in these irregularities. For example, consider Figure 4 which depicts fluctuations in output and consumption spending, i.

Business Cycle Models with Indeterminacy

Observe how the peaks and troughs align at almost the same places and how the upturns and downturns coincide. We might predict that other similar data may exhibit similar qualities. For example, a labor, hours worked b productivity, how effective firms use such capital or labor, c investment, amount of capital saved to help future endeavors, and d capital stock, value of machines, buildings and other equipment that help firms produce their goods. While Figure 5 shows a similar story for investment, the relationship with capital in Figure 6 departs from the story.

We need a way to pin down a better story; one way is to look at some statistics.

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By eyeballing the data, we can infer several regularities, sometimes called stylized facts. One is persistence.


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For example, if we take any point in the series above the trend the x-axis in figure 3 , the probability the next period is still above the trend is very high. However, this persistence wears out over time. That is, economic activity in the short run is quite predictable but due to the irregular long-term nature of fluctuations, forecasting in the long run is much more difficult if not impossible.

Another regularity is cyclical variability. Column A of Table 1 lists a measure of this with standard deviations. The magnitude of fluctuations in output and hours worked are nearly equal. Consumption and productivity are similarly much smoother than output while investment fluctuates much more than output.

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The capital stock is the least volatile of the indicators. Yet another regularity is the co-movement between output and the other macroeconomic variables. Figures 4 — 6 illustrated such relationship. We can measure this in more detail using correlations as listed in column B of Table 1.


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Procyclical variables have positive correlations since it usually increases during booms and decreases during recessions. Vice versa, a countercyclical variable associates with negative correlations. Acyclical, correlations close to zero, implies no systematic relationship to the business cycle. We find that productivity is slightly procyclical. This implies workers and capital are more productive when the economy is experiencing a boom.

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They are not quite as productive when the economy is experiencing a slowdown. Similar explanations follow for consumption and investment, which are strongly procyclical. The theoretical model is estimated on U. The analysis shows that the shirking model is capable of matching the stylized facts of the labor market. However, the data strongly favor a version of the artificial economy that is characterized by determinacy.

Thesis Ph. Research by publication animal spirits business cycles financial frictions indeterminacy monetary policy efficiency wage. This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses.

Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. Transitional dynamics in a two-sector non-scale growth model. Journal of Economic Dynamics and Control , January, 25 , Evans, G.

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Honkapohja and P. Romer Growth Cycles. American Economic Review , 88, Matsuyama, K. Growing Through Cycles. Econometrica , 67, Perez, Fidel Journal of Monetary Economics , 45 2 , April. Steger, Thomas M. On the Mechanics of Economic Convergence. German Economic Review , 7 3 , August, Transitional dynamics, convergence and international capital flows in a two-country model of innovation and growth. Journal of Economics , 64, Other models Greiner, A.

Semmler Multiple steady states, indeterminacy, and cycles in a basic model of endogenous growth. Journal of Economics , 63, Jones, L. Manuelli Journal of Political Economy , 98,

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Business Cycle Models with Indeterminacy Business Cycle Models with Indeterminacy
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Business Cycle Models with Indeterminacy Business Cycle Models with Indeterminacy
Business Cycle Models with Indeterminacy Business Cycle Models with Indeterminacy
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