Real business-cycle theory

Last updated

Real business-cycle theory (RBC theory) is a class of new classical macroeconomics models in which business-cycle fluctuations are accounted for by real (in contrast to nominal) shocks. [1] Unlike other leading theories of the business cycle,[ citation needed ] RBC theory sees business cycle fluctuations as the efficient response to exogenous changes in the real economic environment. That is, the level of national output necessarily maximizes expected utility, and governments should therefore concentrate on long-run structural policy changes and not intervene through discretionary fiscal or monetary policy designed to actively smooth out economic short-term fluctuations.

Contents

According to RBC theory, business cycles are therefore "real" in that they do not represent a failure of markets to clear but rather reflect the most efficient possible operation of the economy, given the structure of the economy.

RBC theory is associated with freshwater economics (the Chicago School of Economics in the neoclassical tradition).

Business cycles

If we were to take snapshots of an economy at different points in time, no two photos would look alike. This occurs for two reasons:

  1. Many advanced economies exhibit sustained growth over time. That is, snapshots taken many years apart will most likely depict higher levels of economic activity in the later period.
  2. There exist seemingly random fluctuations around this growth trend. Thus given two snapshots in time, predicting the latter with the earlier is nearly impossible.
FIGURE 1 Businesscycle figure1.jpg
FIGURE 1

A common way to observe such behavior is by looking at a time series of an economy's output, more specifically gross national product (GNP). This is just the value of the goods and services produced by a country's businesses and workers.

Figure 1 shows the time series of real GNP for the United States from 1954–2005. 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.

FIGURE 2 Businesscycle figure2.jpg
FIGURE 2

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. 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.

FIGURE 3 Businesscycle figure3.jpg
FIGURE 3

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.e. what people buy and use at any given period. Observe how the peaks and troughs align at almost the same places and how the upturns and downturns coincide.

FIGURE 4 Businesscycle figure4.jpg
FIGURE 4

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.

FIGURE 5 Businesscycle figure5.jpg
FIGURE 5
FIGURE 6 Businesscycle figure6.jpg
FIGURE 6

Stylized facts

By eyeballing the data, we can infer several regularities, sometimes called stylized facts. One is persistence. 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. The capital stock is the least volatile of the indicators.

TABLE 1 Businesscycle table1.jpg
TABLE 1

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. 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. They are not quite as productive when the economy is experiencing a slowdown. Similar explanations follow for consumption and investment, which are strongly procyclical. Labor is also procyclical while capital stock appears acyclical.

Observing these similarities yet seemingly non-deterministic fluctuations about trend, the question arises as to why any of this occurs. Since people prefer economic booms over recessions, it follows that if all people in the economy make optimal decisions, these fluctuations are caused by something outside the decision-making process. So the key question really is: what main factor influences and subsequently changes the decisions of all factors in an economy?

Economists have come up with many ideas to answer the above question. The one which currently dominates the academic literature on real business cycle theory[ citation needed ] was introduced by Finn E. Kydland and Edward C. Prescott in their 1982 work Time to Build And Aggregate Fluctuations. They envisioned this factor to be technological shocks—i.e., random fluctuations in the productivity level that shifted the constant growth trend up or down. Examples of such shocks include innovations, bad weather, imported oil price increase, stricter environmental and safety regulations, etc. The general gist is that something occurs that directly changes the effectiveness of capital and/or labour. This in turn affects the decisions of workers and firms, who in turn change what they buy and produce and thus eventually affect output. RBC models predict time sequences of allocation for consumption, investment, etc. given these shocks.

But exactly how do these productivity shocks cause ups and downs in economic activity? Consider a positive but temporary shock to productivity. This momentarily increases the effectiveness of workers and capital, allowing a given level of capital and labor to produce more output.

Individuals face two types of tradeoffs. One is the consumption-investment decision. Since productivity is higher, people have more output to consume. An individual might choose to consume all of it today. But if he values future consumption, all that extra output might not be worth consuming in its entirety today. Instead, he may consume some but invest the rest in capital to enhance production in subsequent periods and thus increase future consumption. This explains why investment spending is more volatile than consumption. The life-cycle hypothesis argues that households base their consumption decisions on expected lifetime income and so they prefer to "smooth" consumption over time. They will thus save (and invest) in periods of high income and defer consumption of this to periods of low income.

The other decision is the labor-leisure tradeoff. Higher productivity encourages substitution of current work for future work since workers will earn more per hour today compared to tomorrow. More labor and less leisure results in higher output today. greater consumption and investment today. On the other hand, there is an opposing effect: since workers are earning more, they may not want to work as much today and in future periods. However, given the pro-cyclical nature of labor, it seems that the above substitution effect dominates this income effect.

Overall, the basic RBC model predicts that given a temporary shock, output, consumption, investment and labor all rise above their long-term trends and hence formulate into a positive deviation. Furthermore, since more investment means more capital is available for the future, a short-lived shock may have an impact in the future. That is, above-trend behavior may persist for some time even after the shock disappears. This capital accumulation is often referred to as an internal "propagation mechanism", since it may increase the persistence of shocks to output.

A string of such productivity shocks will likely result in a boom. Similarly, recessions follow a string of bad shocks to the economy. If there were no shocks, the economy would just continue following the growth trend with no business cycles.

To quantitatively match the stylized facts in Table 1, Kydland and Prescott introduced calibration techniques. Using this methodology, the model closely mimics many business cycle properties. Yet current RBC models have not fully explained all behavior and neoclassical economists are still searching for better variations.

The main assumption in RBC theory is that individuals and firms respond optimally over the long run. It follows that business cycles exhibited in an economy are chosen in preference to no business cycles at all. This is not to say that people like to be in a recession. Slumps are preceded by an undesirable productivity shock which constrains the situation. But given these new constraints, people will still achieve the best outcomes possible and markets will react efficiently. So when there is a slump, people are choosing to be in that slump because given the situation, it is the best solution. This suggests laissez-faire (non-intervention) is the best policy of government towards the economy but given the abstract nature of the model, this has been debated.

A precursor to RBC theory was developed by monetary economists Milton Friedman and Robert Lucas in the early 1970s. They envisioned the factor that influenced people's decisions to be misperception of wages —that booms and recessions occurred when workers perceived wages higher or lower than they really were. This meant they worked and consumed more or less than otherwise. In a world of perfect information, there would be no booms or recessions.

Calibration

Unlike estimation, which is usually used for the construction of economic models, calibration only returns to the drawing board to change the model in the face of overwhelming evidence against the model being correct; this inverts the burden of proof away from the builder of the model. In fact, simply stated, it is the process of changing the model to fit the data. Since RBC models explain data ex post, it is very difficult to falsify any one model that could be hypothesised to explain the data. RBC models are highly sample specific, leading some[ who? ] to believe that they have little or no predictive power.

Structural variables

Crucial to RBC models, "plausible values" for structural variables such as the discount rate, and the rate of capital depreciation are used in the creation of simulated variable paths. These tend to be estimated from econometric studies, with 95% confidence intervals. [ citation needed ] If the full range of possible values for these variables is used, correlation coefficients between actual and simulated paths of economic variables can shift wildly, leading some to question how successful a model which only achieves a coefficient of 80% really is. [ citation needed ]

Criticisms

The real business cycle theory relies on three assumptions which according to economists such as Greg Mankiw and Larry Summers are unrealistic: [2]

1. The model is driven by large and sudden changes in available production technology.

Summers noted that Prescott is unable to suggest any specific technological shock for an actual downturn apart from the oil price shock in the 1970s. [3] Furthermore there is no microeconomic evidence for the large real shocks that need to drive these models. Real business cycle models as a rule are not subjected to tests against competing alternatives [4] which are easy to support.( Summers 1986 )

2. Unemployment reflects changes in the amount people want to work.

Paul Krugman argued that this assumption would mean that 25% unemployment at the height of the Great Depression (1933) would be the result of a mass decision to take a long vacation. [5]

3. Monetary policy is irrelevant for economic fluctuations.

Nowadays it is widely agreed that wages and prices do not adjust as quickly as needed to restore equilibrium. Therefore most economists, even among the new classicists, do not accept the policy-ineffectiveness proposition. [5]

Another major criticism is that real business cycle models can not account for the dynamics displayed by U.S. gross national product. [6] As Larry Summers said: "(My view is that) real business cycle models of the type urged on us by [Ed] Prescott have nothing to do with the business cycle phenomena observed in the United States or other capitalist economies." —( Summers 1986 )

See also

Related Research Articles

Macroeconomics Study of an economy as a whole

Macroeconomics is a branch of economics dealing with performance, structure, behavior, and decision-making of an economy as a whole. For example, using interest rates, taxes, and government spending to regulate an economy’s growth and stability. This includes regional, national, and global economies. According to a 2018 assessment by economists Emi Nakamura and Jón Steinsson, economic "evidence regarding the consequences of different macroeconomic policies is still highly imperfect and open to serious criticism."

New Keynesian economics

New Keynesian economics is a school of macroeconomics that strives to provide microeconomic foundations for Keynesian economics. It developed partly as a response to criticisms of Keynesian macroeconomics by adherents of new classical macroeconomics.

This aims to be a complete article list of economics topics:

Business cycle Fluctuation in the degree of utilization of the production potential of an economy

Business cycles are intervals of expansion followed by recession in economic activity. They have implications for the welfare of the broad population as well as for private institutions. Typically business cycles are measured by applying a band pass filter to a broad economic indicator such as Real Gross Domestic Production. Here important problems may arise with a commonly used filter called the "ideal filter". For instance if a series is a purely random process without any cycle, an "ideal" filter, better called a block filter, a spurious cycle is produced as output. Fortunately methods such as [Harvey and Trimbur, 2003, Review of Economics and Statistics] have been designed so that the band pass filter may be adapted to the time series at hand.

Aggregate demand Total demand for final goods and services in an economy at a given time

In macroeconomics, aggregate demand (AD) or domestic final demand (DFD) is the total demand for final goods and services in an economy at a given time. It is often called effective demand, though at other times this term is distinguished. This is the demand for the gross domestic product of a country. It specifies the amount of goods and services that will be purchased at all possible price levels. Consumer spending, investment, corporate and government expenditure, and net exports make up the aggregate demand.

Accelerator effect

In economics, the acceleration effect is defined as the positive effect of market economic growth on private fixed investment, for example, compared with the total change in domestic output. More GDP makes society more prosperous as businesses see profits rise. This change manifests itself in an increase in sales and earnings that now maximizes the benefits of capacity. This usually manifests itself in desirable profits and an increase in the profits of the business. It also entices firms to build more factories and other buildings, spending known as fixed investment. In addition, it will attract more customers to consume, which is called the multiplier effect in economics. This change has an excellent improvement to the social economy.

Edward C. Prescott American economist

Edward Christian Prescott is an American economist. He received the Nobel Memorial Prize in Economics in 2004, sharing the award with Finn E. Kydland, "for their contributions to dynamic macroeconomics: the time consistency of economic policy and the driving forces behind business cycles". This research was primarily conducted while both Kydland and Prescott were affiliated with the Graduate School of Industrial Administration at Carnegie Mellon University. According to the IDEAS/RePEc rankings, he was the 19th most widely cited economist in the world in 2013. In August 2014, Prescott was appointed as an Adjunct Distinguished Economic Professor at the Australian National University (ANU) in Canberra, Australia.

Harrod–Domar model

The Harrod-Domar model is a Keynesian model of economic growth. It is used in development economics to explain an economy's growth rate in terms of the level of saving and of capital. It suggests that there is no natural reason for an economy to have balanced growth. The model was developed independently by Roy F. Harrod in 1939, and Evsey Domar in 1946, although a similar model had been proposed by Gustav Cassel in 1924. The Harrod–Domar model was the precursor to the exogenous growth model.

Procyclical and countercyclical variables are variables that fluctuate in a way that is positively or negatively correlated with business cycle fluctuations in gross domestic product (GDP). The scope of the concept may differ between the context of macroeconomic theory and that of economic policy–making.

Robert Ernest "Bob" Hall is an American economist and a Robert and Carole McNeil Senior Fellow at Stanford University's Hoover Institution. He is generally considered a macroeconomist, but he describes himself as an "applied economist".

Economic stability is the absence of excessive fluctuations in the macroeconomy. An economy with fairly constant output growth and low and stable inflation would be considered economically stable. An economy with frequent large recessions, a pronounced business cycle, very high or variable inflation, or frequent financial crises would be considered economically unstable.

Dynamic stochastic general equilibrium modeling is a macroeconomic method which is often employed by monetary and fiscal authorities for policy analysis, explaining historical time-series data, as well as future forecasting purposes. DSGE econometric modeling applies general equilibrium theory and microeconomic principles in a tractable manner to postulate economic phenomena, such as economic growth and business cycles, as well as policy effects and market shocks.

New classical macroeconomics School of thought in macroeconomics

New classical macroeconomics, sometimes simply called new classical economics, is a school of thought in macroeconomics that builds its analysis entirely on a neoclassical framework. Specifically, it emphasizes the importance of rigorous foundations based on microeconomics, especially rational expectations.

The Kiyotaki–Moore model of credit cycles is an economic model developed by Nobuhiro Kiyotaki and John H. Moore that shows how small shocks to the economy might be amplified by credit restrictions, giving rise to large output fluctuations. The model assumes that borrowers cannot be forced to repay their debts. Therefore, in equilibrium, lending occurs only if it is collateralized. That is, borrowers must own a sufficient quantity of capital that can be confiscated in case they fail to repay. This collateral requirement amplifies business cycle fluctuations because in a recession, the income from capital falls, causing the price of capital to fall, which makes capital less valuable as collateral, which limits firms' investment by forcing them to reduce their borrowing, and thereby worsens the recession.

Great Moderation Phenomenon in economies of developed nations since the mid-1980s

The Great Moderation is a period starting from the mid-1980s until 2007 characterized by the reduction in the volatility of business cycle fluctuations in developed nations compared with the decades before. It is believed to be caused by institutional and structural changes, particularly in central bank policies, in the second half of the twentieth century.

Demand-led growth

Demand-led growth is the foundation of an economic theory claiming that an increase in aggregate demand will ultimately cause an increase in total output in the long run. This is based on a hypothetical sequence of events where an increase in demand will, in effect, stimulate an increase in supply. This stands in opposition to the common neo-classical theory that demand follows supply, and consequently, that supply determines growth in the long run.

The Goodwin model, sometimes called Goodwin's class struggle model, is a model of endogenous economic fluctuations first proposed by the American economist Richard M. Goodwin in 1967. It combines aspects of the Harrod–Domar growth model with the Phillips curve to generate endogenous cycles in economic activity unlike most modern macroeconomic models in which movements in economic aggregates are driven by exogenously assumed shocks. Since Goodwin's publication in 1967, the model has been extended and applied in various ways.

History of macroeconomic thought Aspect of history

Macroeconomic theory has its origins in the study of business cycles and monetary theory. In general, early theorists believed monetary factors could not affect real factors such as real output. John Maynard Keynes attacked some of these "classical" theories and produced a general theory that described the whole economy in terms of aggregates rather than individual, microeconomic parts. Attempting to explain unemployment and recessions, he noticed the tendency for people and businesses to hoard cash and avoid investment during a recession. He argued that this invalidated the assumptions of classical economists who thought that markets always clear, leaving no surplus of goods and no willing labor left idle.

In macroeconomics, the cost of business cycles is the decrease in social welfare, if any, caused by business cycle fluctuations.

New neoclassical synthesis

The new neoclassical synthesis (NNS), which is now generally referred to as New Keynesian economics, and occasionally as the New Consensus, is the fusion of the major, modern macroeconomic schools of thought - new classical macroeconomics/real business cycle theory and early New Keynesian economics - into a consensus view on the best way to explain short-run fluctuations in the economy. This new synthesis is analogous to the neoclassical synthesis that combined neoclassical economics with Keynesian macroeconomics. The new synthesis provides the theoretical foundation for much of contemporary mainstream economics. It is an important part of the theoretical foundation for the work done by the Federal Reserve and many other central banks.

References

  1. Helgadóttir, Oddný (2021). "How to make a super-model: professional incentives and the birth of contemporary macroeconomics". Review of International Political Economy. doi:10.1080/09692290.2021.1997786. ISSN   0969-2290.
  2. Cencini, Alvaro (2005). Macroeconomic Foundations of Macroeconomics . Routledge. p.  40. ISBN   978-0-415-31265-3.
  3. Summers, Lawrence H. (Fall 1986). "Some Skeptical Observations on Real Business Cycle Theory" (PDF). Federal Reserve Bank of Minneapolis Quarterly Review. 10 (4): 23–27.
  4. George W. Stadler, Real Business Cycles, Journal of Economics Literatute, Vol. XXXII, December 1994, pp. 1750–1783, see p. 1772
  5. 1 2 Kevin Hoover (2008). "New Classical Macroeconomics", econlib.org
  6. George W. Stadler, Real Business Cycles, Journal of Economics Literatute, Vol. XXXII, December 1994, pp. 1750–1783, see p. 1769

Further reading