<p>The most obvious answer is: What is the alternative? To do nothing? If you do the best you can - with the best knowledge you have at the time, it is hard to fault people for wanting to change something they think can be done better. </p>

<p>Second part - When the Lucas critique was published - it was part of a movement towards micro-economic models - which is great. However, these models where all/mostly based on an assumption of rationality. As behavioural economics have show - homo economicus is a horrible way to model actual human behaviour. </p>

<p>Basically, You should use rational assumptions to see how your model behaves in the most simple settings. Then see what happens - stepwise - when you let real-world behaviour influence your models. </p>

<p>This was not the aim of the Lucas critique. But it should have been. </p>

<p>Also, there is so much inertia in the economic world. It seems that most of the current professors where educated in the 70-80's, and most economic students have to study many years before they meet something else than strict rational assumptions. Or actual just have to stumble out into the real world :) </p>

<p>And in the real world there is pressure from the politicians to actual do something about the economy - probably the real answer to your question. </p>

CC BY-SA 3.0
2015-09-21T09:08:08.053Z
2015-09-21T13:03:30.243Z
2015-09-21T13:03:30.243Z
Thorst
<p>The response to the Lucas Critique was the emergence of RBC and DSGE models. Using microeconomic foundations of macro models we can simulate how behavior changes when policy changes and only estimate "deep" structural paramateres that are not policy variant. Before microfoundations we were estimating models where the estimation included the actions of people. With microfounded models today we try to seperate the actions. This was not possible in older models as we actually did not consider how people act or react, whereas microfoundations tell you how people would react.</p>

<p>However this is a difficult task as once you introduce agents that actively think about their actions you must take into acount their future expectations, which are unknown. One way to deal with this are rational expectations.</p>

<p>A further issue is that such models predict reactions that are quicker than in the data. If agents are perfectly rational, have perfect foresight and all information, they react quickly and perfectly. The solution to this today is to add frictions that slow these reactions down. However old models that we used to estimate (think about IS-LM and especially AS-AD models) also have the huge issue that people are too stupid (only adaptive (backward looking) expectations, do not take information into account when forming expectations, don't think about what may come in the future) and this is partially a piece of the Lucas Critique. Now we have the problem that people are too smart or super-rational. Some models (see models where some fraction of agents are "Rule of Thumb Consumers") now also assume that some agents are fully rational (many indeed are) while some just are backward looking (as in the normal IS-LM or AS-AD model), as a balance of the two things to generate a more realistic picture.</p>

<p>As for the critique of rationality: In many experimental micro studies rationality fails. However this does not tell us how many small deviations from rationality aggregate, which is what macro is interested in. It may occur that from many different deviations in different directions that in aggregate rationality is still a good approximation.</p>

<p>Furthermore approaches have been developed now to deviate from rational expectations. These are very difficult to solve though. One interesting way is to assume people are rational, but do not have all the information, which is a reason most people make mistakes. These are models of information frictions. Key words: Rational Inattention (e.g. Sims) and Inattentiveness (e.g. Reis). Another related approach includes Learning Models.</p>

<p>To summarize: we try to have models that are immune to the Lucas Critique. These often require rational expectations to be solved, but other approaches are also being developed.</p>

CC BY-SA 3.0
2015-09-21T18:37:10.917Z
2015-09-21T22:09:42.787Z
2015-09-21T22:09:42.787Z
BB King
<p>With high probability this question is duplicate, and I tried to find one already in the community, but I was unsuccessful. </p>

<p>According to the <a href="https://en.wikipedia.org/wiki/Lucas_critique">Lucas Critique, in its more general terms,</a> the problem with empirical macroeconomic models is that they are not invariant to policy changes, and hence we cannot take any policy conclusions out of them. </p>

<p>My question then is why do we still use them? </p>

<p>Any help would be appreciated. </p>

<macroeconomics><microeconomics><statistics>
Why use empirical macroeconomic models when they are not policy invariant (Lucas Critique)?
An old man in the sea.
# Why use empirical macroeconomic models when they are not policy invariant (Lucas Critique)?

(Asked by: username_0 on 2015-09-19)

With high probability this question is duplicate, and I tried to find one already in the community, but I was unsuccessful.

According to the [Lucas Critique, in its more general terms,](https://en.wikipedia.org/wiki/Lucas_critique) the problem with empirical macroeconomic models is that they are not invariant to policy changes, and hence we cannot take any policy conclusions out of them.

My question then is why do we still use them?

Any help would be appreciated.

**Tags:** macroeconomics, microeconomics, statistics

---

## 2 answers

### Answer by username_2 on 2015-09-21. Score: 5 | Accepted answer

The response to the Lucas Critique was the emergence of RBC and DSGE models. Using microeconomic foundations of macro models we can simulate how behavior changes when policy changes and only estimate "deep" structural paramateres that are not policy variant. Before microfoundations we were estimating models where the estimation included the actions of people. With microfounded models today we try to seperate the actions. This was not possible in older models as we actually did not consider how people act or react, whereas microfoundations tell you how people would react.

However this is a difficult task as once you introduce agents that actively think about their actions you must take into acount their future expectations, which are unknown. One way to deal with this are rational expectations.

A further issue is that such models predict reactions that are quicker than in the data. If agents are perfectly rational, have perfect foresight and all information, they react quickly and perfectly. The solution to this today is to add frictions that slow these reactions down. However old models that we used to estimate (think about IS-LM and especially AS-AD models) also have the huge issue that people are too stupid (only adaptive (backward looking) expectations, do not take information into account when forming expectations, don't think about what may come in the future) and this is partially a piece of the Lucas Critique. Now we have the problem that people are too smart or super-rational. Some models (see models where some fraction of agents are "Rule of Thumb Consumers") now also assume that some agents are fully rational (many indeed are) while some just are backward looking (as in the normal IS-LM or AS-AD model), as a balance of the two things to generate a more realistic picture.

As for the critique of rationality: In many experimental micro studies rationality fails. However this does not tell us how many small deviations from rationality aggregate, which is what macro is interested in. It may occur that from many different deviations in different directions that in aggregate rationality is still a good approximation.

Furthermore approaches have been developed now to deviate from rational expectations. These are very difficult to solve though. One interesting way is to assume people are rational, but do not have all the information, which is a reason most people make mistakes. These are models of information frictions. Key words: Rational Inattention (e.g. Sims) and Inattentiveness (e.g. Reis). Another related approach includes Learning Models.

To summarize: we try to have models that are immune to the Lucas Critique. These often require rational expectations to be solved, but other approaches are also being developed.


---

### Answer by username_1 on 2015-09-21. Score: 2

The most obvious answer is: What is the alternative? To do nothing? If you do the best you can - with the best knowledge you have at the time, it is hard to fault people for wanting to change something they think can be done better.

Second part - When the Lucas critique was published - it was part of a movement towards micro-economic models - which is great. However, these models where all/mostly based on an assumption of rationality. As behavioural economics have show - homo economicus is a horrible way to model actual human behaviour.

Basically, You should use rational assumptions to see how your model behaves in the most simple settings. Then see what happens - stepwise - when you let real-world behaviour influence your models.

This was not the aim of the Lucas critique. But it should have been.

Also, there is so much inertia in the economic world. It seems that most of the current professors where educated in the 70-80's, and most economic students have to study many years before they meet something else than strict rational assumptions. Or actual just have to stumble out into the real world :)

And in the real world there is pressure from the politicians to actual do something about the economy - probably the real answer to your question.


---

