Adoptive expectation refers to an expectation developed by the decision maker based on past information or experience. It means individuals or society expect their consumption and income based on past experience or information.
So, using the historical data on consumption and income, we can predict their expected consumption and income at present. Similarly, the current information can be used to predict the expected future income and consumption if there is adaptive expectation.
Friedman was the first to include adoptive expectation in consumption in his permanent income hypothesis, where the permanent consumption and permanent income are positive and proportional. The permanent income and consumption are both expected, and as there is adaptive expectation, the permanent income and consumption can be estimated using the time series data of them.
i.e. Ct P = K.YtP
Ct P and YtP are the expected permanent consumption and expected income, respectively, and they are not actual. Under the adoptive expectation, they can be estimated as
Ct P = f(Ct-1, Ct-2, …….Ct-n)
YtP = f (Yt-1, Yt-2, …… Yt-n)
This shows that the permanent or expected consumption and income depend on the past level. So, if we have past information on consumption and income, we can predict the expected consumption and income of the current period.
The expectation is said to be rational if it is based on the current relevant information that is perfectly available and such expectations are fully realized. It means the information is perfectly available, and a rational individual uses such relevant information to develop an expectation, and they are 100% fulfilled.
So, under rational expectation, the current behavior of the decision maker can not be predicted from the past behavior or information. As they are rational, their current decision depends on the current situation. It means the past information can not predict the current, and the current information can not predict the future because it is full of uncertainty.
If there is rational expectation in consumption, we can not predict the current consumption from the past information on consumption. Because the current consumption decision not only depends on the current income but also on the current situation, which is not known earlier.
Robert Hall (1976) introduced rational expectations in consumption, arguing that consumption under rational expectations follows the ‘Random Walk’. It means consumption depends on the situation, which is not known earlier and the individual adjusts the current consumption given the current situation. So, the simple consumption function can be given as
Ct = α Yt + et
Where = α is the marginal propensity to consume, 0< α<1
- et = error term at ‘t’
- Ct = current consumption\
- Yt = Income at ‘t’
Here, et is the error term which represents all the uncertainties, including other explanatory factors of consumption besides the current income. Such factors create uncertainty, which makes the consumption function a random walk and unpredictable. Because the consumption decision at any period depends on the situation of the same period, and such situations are unpredictable. So, under the rational expectation, consumption can not be predicted from past information.
Implications of consumption theories
1) To identify the determinant of aggregate consumption. Such as
- AIH = disposable personal income of the same period
- RIH = demonstration effect, Ratchet effect
- PIH/LCIH = income from assets and labor
2) To analyze the behavior of short-run and long-run consumption
Short run – positive and non-proportional
Long run – positive and proportional
3) To design appropriate stabilization policy tools
e.g., during an inflationary situation (AD>AS),
- Increase the tax on the disposable personal income
- Discourage the demonstration effect on consumption by restricting the quantity/volume.
- Tax incentives for future income and promote current savings.