<p><strong>To (slightly) paraphrase the OP:</strong>  </p>

<blockquote>
  <p><em>Economies</em> <strong>(Human Bodies)</strong> are extremely complex systems with many variables, not to mention the fact that they emerge from the
  interactions of complex
  <em>beings</em> <strong>(factors)</strong>. I agree that <em>economies</em> <strong>(human bodies)</strong> have certain underlying principles, but I remain skeptical of the
  overall value of <em>econometrics</em> <strong>(medicine)</strong> as a science.</p>
  
  <p>A truly useful <em>econometrics</em> <strong>(medical science)</strong> would be a
  valuable tool in predicting the future behavior of the <em>economy</em>
  <strong>(human body)</strong>, particularly in predicting shocks like <em>the recent financial crisis and Great Recession</em> <strong>(severe illnesses or near
  death)</strong>. But it did not happen.</p>
  
  <p>If <em>econometrics</em> <strong>(medical science)</strong> can't predict the future, how
  do we know it even effectively describes the past? What is the
  evidence that it has empirical value?</p>
</blockquote>

<p><strong><em>Comment:</em></strong> <strong>There is a Present that needs to be dealt with</strong>, just like with human bodies.</p>

<p><strong>To (slightly) paraphrase Milton Friedman:</strong>  </p>

<blockquote>
  <p>I don't care how I predict, as long as I predict adequately.</p>
</blockquote>

<p><strong><em>Comment:</em></strong> But what do we do when our predictions are not adequate ?</p>

<p>Econometrics is based on Mathematical Statistics on the one hand, and on the assumptions made by Economic Theory on the other, which in turn are based on (imperfect) empirical observation, and are then led to their logical conclusions. In other words, Econometrics uses rigorous mathematics, induction, deduction and all the words dear to an epistemologist. Its epistemological foundations are solid as a rock.  </p>

<p>What hangs on the balance is the <em><strong>observed</strong> validity of its abstractions</em>. So the question is not whether Econometrics is a science, in the sense of whether it follows the scientific method or not. It does, fully.  The question is whether its results are useful.  </p>

<p>But <em>what are the criteria in order to determine "useful"</em>? Is it just adequate predictions? That would be a matter of disagreement between humans.  </p>

<p>And <em>is it a matter of a "yes/no" answer</em>?  Or is it a matter of <em>degree</em> to which it is useful? In which case, we have to somehow <em>measure</em> this degree (after we have agreed on the criteria), which brings us back to where we have to collect, analyze, assess, and debate the <em>evidence</em>.</p>

CC BY-SA 3.0
2014-11-28T13:35:10.503Z
Good answer and interesting analogy. I should point out that medicine has a scientific testability that econometrics can only admire from afar: clinical trials, the daily operation of hospitals, the effects of drugs. Treatments that don't work are usually abandoned quickly. Econometrics has access to nothing even remotely comparable.
Gregory Higley
CC BY-SA 3.0
2014-11-28T13:42:56.217Z
@GregoryHigley Certainly. My main intent was to point out that "unquestionable predictive success", although perhaps the ideal final destination, cannot be a _rejection_ criterion in Social Sciences (since it is not even in medicine), but only, exactly, the "ideal final destination". Meanwhile, we have to manage with what tools we have, while trying hard to improve them.
Alecos Papadopoulos
CC BY-SA 3.0
2014-11-28T14:13:17.563Z
Fair enough. My project isn't to discredit econometrics, nor to ask for "unquestionable predictive success", though it should be obvious by now I think it has far (far, far) less utility than you do, but it's not zero. We must "manage with what tools we have," though it's as if we're trying to mine for diamonds with a feather duster. At some point we may want to ask whether we are "managing" at all, or whether it's even a tool.
Gregory Higley
CC BY-SA 3.0
2014-12-01T19:41:06.037Z
+1 Although a lot of economics is more like physical cosmology, astrophysics or climate science, where the models are similarly complex and experimentation is impossible. The predictions of these fields are frequently inaccurate, but that in and of itself doesn't invalidate the "scienciness" of their methods. Those fields also aren't always immediately "useful", but make modest improvements to generally inaccurate models over time.
jayk
CC BY-SA 3.0
2014-11-28T10:14:29.483Z
2014-11-28T10:14:29.483Z
Alecos Papadopoulos
<p>The first thing to say about this question is that it is important to look in the right places for good econometric predictions.</p>

<p>Physicists cannot reliably predict a wide-variety of quantum phenomena. Does this represent a failure of physics? No. Quite the contrary, we know (thanks to the work of a series of high profile physicists) that such phenomena are fundamentally <em>impossible</em> to predict.</p>

<p>In economics, too, there is good reason to think that certain kinds of shock or major economic event are virtually impossible to predict. Suppose that it was possible to predict the timing of the next financial crisis/recession, and that the next such event is predicted to happen tomorrow. Armed with such a prediction, firms would begin to reduce their capacity in readiness for the coming contraction in demand, traders would start to sell shares in anticipation of the coming stock market crash, households would reduce their spending in readiness for the expected contraction in their income, etc. In other words, anticipating the predicted recession tomorrow causes rational actors to take all of the actions necessary to induce a recession today: earlier than forecast! Any ability to accurately forecast the timing of such events is, therefore, to a large extent self-defeating.</p>

<p>Once one looks at variables that can realistically be predicted, virtually every field of economics is littered with examples of well-performing econometric models making predictions that are, by social science standards, excellent .</p>

CC BY-SA 3.0
2014-11-27T16:54:58.703Z
I'm interested in what you mean by "predictions that are, **by social science standards**, excellent".
Gregory Higley
CC BY-SA 3.0
2014-11-27T17:48:57.497Z
The question, which the OP chose to leave unaltered despite the suggestions that it was too broad (and enough members of this site agreed with him to re-open the question), requests _evidence_. This answer says only that "virtually every field of economics is littered with examples of well-performing econometric models..." etc (the last sentence). Is this considered _evidence_?
Alecos Papadopoulos
CC BY-SA 3.0
2014-11-27T18:49:44.520Z
@AlecosPapadopoulos No, it is not evidence. My answer should really be a comment, but it is too long. I feel like it is impossible to provide evidence unless the question is better specified. For example, take virtually any cross-sectional econometrics paper with a few thousand representative observations and you are going to get good predictions about new observations that arrive in the system so long as the structural parameters remain unchanged. That's basically tautological because all the econometric model does is produce conditional means that are very accurate in large samples.
Ubiquitous
CC BY-SA 3.0
2014-11-27T19:01:34.387Z
@Ubiquitous The comment was really addressed to the OP, in the hope that he will understand the impossibility of its question. Essentially such a question is an ideal invitation for the Chat, not for the Q&A space.
Alecos Papadopoulos
CC BY-SA 3.0
2014-11-27T19:20:07.513Z
@GregoryHigley Compare the confidence intervals we get away with, compared to hard sciences which can use real lab experiments. Its many orders of magnitudes... just look at the number of $0$s before the likelihood of the Higgs-Boson not existing.
FooBar
CC BY-SA 3.0
2014-11-27T20:15:28.590Z
One way of looking at it is that maybe econometrics has overstepped its role. The models and regressions that we have are too simplistic and yet too bold (they attempt to encompass a variety of phenomenon) to the point where our extrapolations are meaningless.
rosenjcb
CC BY-SA 3.0
2014-11-28T09:15:45.250Z
@AlecosPapadopoulos I'm sorry, Alecos, but I do not necessarily request evidence. You simply haven't grasped that I regard this as an epistemological question. It might be better phrased as, "Can econometrics conform to the scientific method?" A proper approach is not to perform a meta-analysis of its alleged successes or failures on a case-by-case basis, but rather to analyze the methodological assumptions that underlie econometrics to determine whether they conform to what one would expect of science.
Gregory Higley
CC BY-SA 3.0
2014-11-28T10:15:54.153Z
ok, I just posted then an epistemological answer.
Alecos Papadopoulos
CC BY-SA 3.0
2014-11-28T10:29:45.530Z
@GregoryHigley Ah, now it becomes clearer. I will knock-up an epistemological answer later.
Ubiquitous
CC BY-SA 3.0
2014-11-27T15:28:30.380Z
2014-11-27T16:18:29.600Z
2014-11-27T16:18:29.600Z
Ubiquitous
<p>@Alecos has already mentioned one of the two points I wanted to make, here is my extension.</p>

<p>Econometrics has no value per se, it always comes from the data we use it on. In microeconomics, with many studies that are natural experiments, quasi-experiments or where we are somewhat sure that we are not capturing endogeneity, we could estimate many interesting parameters. One of the standard references would be the many wage regressions that have delivered fairly consistent and reproducible estimates.</p>

<p>On the other hand, in Macroeconomics, we have <em>no</em> hope of getting clean identification. <em>If</em> you assume every country to be identical, all we have is a panel of around 60 panels and 30-50 periods of observations (mostly of aggregates), depending on what you want to observe. Moreover, these are often not perfectly measured, <strong>and</strong> most importantly we cannot create random variation here. 
Of course, when data fails, one can try to tweak the estimators, but even with partial identification as some VARs do it, we can only hope to get short-run identification, and still have to worry about endogeneity.</p>

<p>Yes, I agree. Economists have not consistently and univocally warned us about the financial crises and other macroeconomic shocks. But this does not necessarily mean that the structure that macroeconomic models assume are bad, nor does falsify any other section in Economics. </p>

<p>This is good news for Microeconomics: We can somewhat rely on Econometrics to reject and accept theory. It is bad news for Macro: We can almost never reject plausible models just looking at the data. </p>

CC BY-SA 3.0
2014-11-29T15:41:24.450Z
Of all the responses, this one is the closest to my view, except I think I am still more pessimistic than you. "This does not necessarily mean that the structure that macroeconomic models assume are bad." Doesn't mean they are good either. How would we know?
Gregory Higley
CC BY-SA 3.0
2014-11-30T13:26:08.047Z
It seems to me that we reject macro models all the time. Consider various consumption based asset pricing models (these are definitely "macro" in scope). They produce falsifiable predictions and the data has shown that the models are definitely wrong. Just because identification is near impossible in macro doesn't mean macro doesn't produce falsifiable hypotheses.
jmbejara
CC BY-SA 3.0
2014-11-30T15:01:31.847Z
Sure, I should probably be a bit more careful with how I phrase that. I might look into it later again. But again, also with these models, we can argue that they are right *at the core*, but they lack an extension to become *more correct*, whatever that means. For example, the preferences that include past consumption . Im not saying that that is necessarily what I think is correct, but for many falsifiable prediction your model has, you can make up a story/extension that explains it.
FooBar
CC BY-SA 3.0
2014-11-30T15:01:55.330Z
There are some predictions that are so much off-the-hook that you just outright reject the model, but its not *as easy* as it is in lab-based science, even with falsifiable micro predictions.
FooBar
CC BY-SA 3.0
2014-12-01T19:45:45.053Z
> But this does not necessarily mean that the structure that macroeconomic models assume are bad,

That's true, but it doesn't take a lot of work to show that most macroeconomic models don't hold up to real world data, and it's equally easy to point to their asinine assumptions as the culprit. Macroeconomists love to handwave away 100+ years of solid psychological and sociological research.
Nate Vomocil
CC BY-SA 3.0
2014-11-28T22:22:39.743Z
2014-11-28T22:22:39.743Z
FooBar
<p>Econometrics is nothing more than a fancy name for statistics. Namely, how do we apply statistics and economic theory together to get a clearer picture of reality?</p>

<p>Is statistics scientific? It can be when used properly. Statistics is merely a tool of science, in exactly the same way that econometrics is a tool of general economics. It is a tool that can be used for good science and for shit science.</p>

CC BY-SA 3.0
2016-05-26T11:26:03.733Z
@GregoryHigley have you ever done any econometrics? Research level, not off-the-shelf modelling? I am asking because I am curious whether your hypothesis about uselessness of econometrics (micro and especially macro) is based on personal experience, or just the impressions?
mpiktas
CC BY-SA 3.0
2014-12-01T20:18:53.073Z
No one doubts the mathematical utility of statistics. It is the inputs that are the problem: Whenever the inputs are large aggregates of conscious beings with (potentially) very different subjective preferences, possibly across times, places, cultures, etc., when the number of free variables is very large, it is an open question whether there is much to be learned, or whether the discipline of statistics is even applicable.
Gregory Higley
CC BY-SA 3.0
2014-12-01T20:34:08.080Z
Indeed, but the answer to ""Can econometrics conform to the scientific method?" is "Yes, it can."
Nate Vomocil
CC BY-SA 3.0
2014-12-01T22:10:37.717Z
If econometrics = statistics, the answer is clearly yes. But that is pretty uninteresting, almost tautological. If econometrics = statistics + "economic data as inputs", the answer is "no" at the macroeconomic level, and more muddled at the microeconomic level.
Gregory Higley
CC BY-SA 3.0
2014-12-01T19:43:45.337Z
2014-12-01T19:43:45.337Z
Nate Vomocil
<p>Economies are extremely complex systems with many variables, not to mention the fact that they emerge from the interactions of complex beings. I agree that economies have certain underlying principles, but I remain skeptical of the overall value of econometrics as a science.</p>

<p>A truly useful econometrics would be a valuable tool in predicting the future behavior of the economy, particularly in predicting shocks like the recent financial crisis and Great Recession. But it did not happen.</p>

<p>If econometrics can't predict the future, how do we know it even effectively describes the past? What is the evidence that it has empirical value?</p>

<h1>Clarification</h1>

<p>I regret any confusion this may have caused, but let me clarify what I'm looking for here. I regard this as an epistemological question. A better way to phrase it might be, "Can econometrics conform to the scientific method?" or just "Is it science?"</p>

<p>This is, at least in theory, a specific, answerable question, even if it is, as Alecos Papadopoulos noted in his answer, a matter of degree. (A view I share.)</p>

<p>This does not mean that specific examples of econometrics' successes and failures are not relevant. </p>

CC BY-SA 3.0
2014-11-27T04:12:28.743Z
I have vote to close because the question is extremely broad. At the same time, it is a very important topic. But in order to expect some fact-based, referenced-based answers, rather than opinions of the answerer or of others, that the answerer will relay, I would suggest to narrow the focus. Choose your target: Is it Crises?(Econometrics is no Oracle). Is it some particular market? (there is a _lot_ of _micro_econometrics). Is it International Economics? Etc
Alecos Papadopoulos
CC BY-SA 3.0
2014-11-27T04:21:38.800Z
Also voting to close. Econometrics does make predictive claims, especially in re job creation vis-a-vis capital investment. See RIMS II (no longer published) or IMPLAN, et al.
Jason Nichols
CC BY-SA 3.0
2014-11-27T04:32:41.573Z
I know that econometrics makes predictive claims. That is, in fact, the entire point of the question. My question is: What evidence do we have that those predictions are valid?
Gregory Higley
CC BY-SA 3.0
2014-11-27T04:36:42.863Z
So, in order to get an answer to this question, I should instead ask 10 or 15 more 'focused' questions? That would not actually answer this question. Respectfully, I consider that approach to be mildly absurd.
Gregory Higley
CC BY-SA 3.0
2014-11-27T04:54:10.460Z
Your question as it is requires an answer having the length of _a book_ (and then some), it's that simple. Otherwise, you will get opinions, and this is not an opinion site. And yes, if you want to reach an _overall_ conclusion to such a general question, you will have to break it down to more like 1,000 questions, find answers to them all, evaluate comparatively the answers, and then, see if you can answer with a "final", "overall", "all things considered", yes or no. Complex systems require complex tools and complex tools are not amenable to non-complex assessments.
Alecos Papadopoulos
CC BY-SA 3.0
2014-11-27T04:59:39.417Z
"Complex systems require complex tools and complex tools are not amenable to non-complex assessments." This is usually, but not always true. Sometimes complex systems can be explained as emerging from simple rules. And econometrics is not necessarily complex. Its content is, but not necessarily its validity, which is an epistemological question. In any case, neither of us wants to abuse the forum by arguing, even as politely as we are, so I rest my case. If it's closed, it's closed.
Gregory Higley
CC BY-SA 3.0
2014-11-27T12:40:50.210Z
@JasonNichols The way I read your comment, you vote to close, because you disagree?
FooBar
CC BY-SA 3.0
2014-11-27T12:43:36.840Z
I vote to open. A good answer could emphasize the difference between understanding the relevance of particular mechanisms in a partial equilibrium sense, something which econometrics helps us with, and predicting the whole general equilibrium with all the noise and disturbances that come with it.
FooBar
CC BY-SA 3.0
2014-11-27T14:04:51.523Z
Fair point. @FooBar. Voted to reopen.
Jason Nichols
CC BY-SA 3.0
2014-11-27T14:20:08.377Z
This remains unanswerably broad
410 gone
CC BY-SA 3.0
2014-11-27T14:33:02.393Z
I agree with @Energynmumbers but I am leaving it be. I want to see the answers to the question and whether they do answer what the question does ask -and I will comment on them.
Alecos Papadopoulos
CC BY-SA 3.0
2014-11-27T15:14:45.840Z
@GuidoJorg That's very, very close to my opinion, yes. I am preparing an answer for my own question.
Gregory Higley
<econometrics><scientific-method>
What is the evidence that econometrics has empirical value?
Gregory Higley
# What is the evidence that econometrics has empirical value?

(Asked by: username_0 on 2014-11-27)

Economies are extremely complex systems with many variables, not to mention the fact that they emerge from the interactions of complex beings. I agree that economies have certain underlying principles, but I remain skeptical of the overall value of econometrics as a science.

A truly useful econometrics would be a valuable tool in predicting the future behavior of the economy, particularly in predicting shocks like the recent financial crisis and Great Recession. But it did not happen.

If econometrics can't predict the future, how do we know it even effectively describes the past? What is the evidence that it has empirical value?

# Clarification

I regret any confusion this may have caused, but let me clarify what I'm looking for here. I regard this as an epistemological question. A better way to phrase it might be, "Can econometrics conform to the scientific method?" or just "Is it science?"

This is, at least in theory, a specific, answerable question, even if it is, as username_1 username_1 noted in his answer, a matter of degree. (A view I share.)

This does not mean that specific examples of econometrics' successes and failures are not relevant.

**Tags:** econometrics, scientific-method

> **Comments:**
> **username_1**: I have vote to close because the question is extremely broad. At the same time, it is a very important topic. But in order to expect some fact-based, referenced-based answers, rather than opinions of the answerer or of others, that the answerer will relay, I would suggest to narrow the focus. Choose your target: Is it Crises?(Econometrics is no Oracle). Is it some particular market? (there is a _lot_ of _micro_econometrics). Is it International Economics? Etc  
> **username_2**: Also voting to close. Econometrics does make predictive claims, especially in re job creation vis-a-vis capital investment. See RIMS II (no longer published) or IMPLAN, et al.  
> **username_0**: I know that econometrics makes predictive claims. That is, in fact, the entire point of the question. My question is: What evidence do we have that those predictions are valid?  
> **username_0**: So, in order to get an answer to this question, I should instead ask 10 or 15 more 'focused' questions? That would not actually answer this question. Respectfully, I consider that approach to be mildly absurd.  
> **username_1**: Your question as it is requires an answer having the length of _a book_ (and then some), it's that simple. Otherwise, you will get opinions, and this is not an opinion site. And yes, if you want to reach an _overall_ conclusion to such a general question, you will have to break it down to more like 1,000 questions, find answers to them all, evaluate comparatively the answers, and then, see if you can answer with a "final", "overall", "all things considered", yes or no. Complex systems require complex tools and complex tools are not amenable to non-complex assessments.  
> **username_0**: "Complex systems require complex tools and complex tools are not amenable to non-complex assessments." This is usually, but not always true. Sometimes complex systems can be explained as emerging from simple rules. And econometrics is not necessarily complex. Its content is, but not necessarily its validity, which is an epistemological question. In any case, neither of us wants to abuse the forum by arguing, even as politely as we are, so I rest my case. If it's closed, it's closed.  
> **username_3**: @username_2 The way I read your comment, you vote to close, because you disagree?  
> **username_3**: I vote to open. A good answer could emphasize the difference between understanding the relevance of particular mechanisms in a partial equilibrium sense, something which econometrics helps us with, and predicting the whole general equilibrium with all the noise and disturbances that come with it.  
> **username_2**: Fair point. @username_3. Voted to reopen.  
> **username_4**: This remains unanswerably broad  
> **username_1**: I agree with @Energynmumbers but I am leaving it be. I want to see the answers to the question and whether they do answer what the question does ask -and I will comment on them.  
> **username_0**: @GuidoJorg That's very, very close to my opinion, yes. I am preparing an answer for my own question.  

---

## 4 answers

### Answer by username_1 on 2014-11-28. Score: 7

**To (slightly) paraphrase the OP:**

> *Economies* **(Human Bodies)** are extremely complex systems with many variables, not to mention the fact that they emerge from the
> interactions of complex
> *beings* **(factors)**. I agree that *economies* **(human bodies)** have certain underlying principles, but I remain skeptical of the
> overall value of *econometrics* **(medicine)** as a science.
>
> A truly useful *econometrics* **(medical science)** would be a
> valuable tool in predicting the future behavior of the *economy*
> **(human body)**, particularly in predicting shocks like *the recent financial crisis and Great Recession* **(severe illnesses or near
> death)**. But it did not happen.
>
> If *econometrics* **(medical science)** can't predict the future, how
> do we know it even effectively describes the past? What is the
> evidence that it has empirical value?

***Comment:*** **There is a Present that needs to be dealt with**, just like with human bodies.

**To (slightly) paraphrase Milton Friedman:**

> I don't care how I predict, as long as I predict adequately.

***Comment:*** But what do we do when our predictions are not adequate ?

Econometrics is based on Mathematical Statistics on the one hand, and on the assumptions made by Economic Theory on the other, which in turn are based on (imperfect) empirical observation, and are then led to their logical conclusions. In other words, Econometrics uses rigorous mathematics, induction, deduction and all the words dear to an epistemologist. Its epistemological foundations are solid as a rock.

What hangs on the balance is the ***observed** validity of its abstractions*. So the question is not whether Econometrics is a science, in the sense of whether it follows the scientific method or not. It does, fully. The question is whether its results are useful.

But *what are the criteria in order to determine "useful"*? Is it just adequate predictions? That would be a matter of disagreement between humans.

And *is it a matter of a "yes/no" answer*? Or is it a matter of *degree* to which it is useful? In which case, we have to somehow *measure* this degree (after we have agreed on the criteria), which brings us back to where we have to collect, analyze, assess, and debate the *evidence*.

> **Comments:**
> **username_0**: Good answer and interesting analogy. I should point out that medicine has a scientific testability that econometrics can only admire from afar: clinical trials, the daily operation of hospitals, the effects of drugs. Treatments that don't work are usually abandoned quickly. Econometrics has access to nothing even remotely comparable.  
> **username_1**: @username_0 Certainly. My main intent was to point out that "unquestionable predictive success", although perhaps the ideal final destination, cannot be a _rejection_ criterion in Social Sciences (since it is not even in medicine), but only, exactly, the "ideal final destination". Meanwhile, we have to manage with what tools we have, while trying hard to improve them.  
> **username_0**: Fair enough. My project isn't to discredit econometrics, nor to ask for "unquestionable predictive success", though it should be obvious by now I think it has far (far, far) less utility than you do, but it's not zero. We must "manage with what tools we have," though it's as if we're trying to mine for diamonds with a feather duster. At some point we may want to ask whether we are "managing" at all, or whether it's even a tool.  
> **username_5**: +1 Although a lot of economics is more like physical cosmology, astrophysics or climate science, where the models are similarly complex and experimentation is impossible. The predictions of these fields are frequently inaccurate, but that in and of itself doesn't invalidate the "scienciness" of their methods. Those fields also aren't always immediately "useful", but make modest improvements to generally inaccurate models over time.  

---

### Answer by username_6 on 2014-11-27. Score: 5

The first thing to say about this question is that it is important to look in the right places for good econometric predictions.

Physicists cannot reliably predict a wide-variety of quantum phenomena. Does this represent a failure of physics? No. Quite the contrary, we know (thanks to the work of a series of high profile physicists) that such phenomena are fundamentally *impossible* to predict.

In economics, too, there is good reason to think that certain kinds of shock or major economic event are virtually impossible to predict. Suppose that it was possible to predict the timing of the next financial crisis/recession, and that the next such event is predicted to happen tomorrow. Armed with such a prediction, firms would begin to reduce their capacity in readiness for the coming contraction in demand, traders would start to sell shares in anticipation of the coming stock market crash, households would reduce their spending in readiness for the expected contraction in their income, etc. In other words, anticipating the predicted recession tomorrow causes rational actors to take all of the actions necessary to induce a recession today: earlier than forecast! Any ability to accurately forecast the timing of such events is, therefore, to a large extent self-defeating.

Once one looks at variables that can realistically be predicted, virtually every field of economics is littered with examples of well-performing econometric models making predictions that are, by social science standards, excellent .

> **Comments:**
> **username_0**: I'm interested in what you mean by "predictions that are, **by social science standards**, excellent".  
> **username_1**: The question, which the OP chose to leave unaltered despite the suggestions that it was too broad (and enough members of this site agreed with him to re-open the question), requests _evidence_. This answer says only that "virtually every field of economics is littered with examples of well-performing econometric models..." etc (the last sentence). Is this considered _evidence_?  
> **username_6**: @username_1 No, it is not evidence. My answer should really be a comment, but it is too long. I feel like it is impossible to provide evidence unless the question is better specified. For example, take virtually any cross-sectional econometrics paper with a few thousand representative observations and you are going to get good predictions about new observations that arrive in the system so long as the structural parameters remain unchanged. That's basically tautological because all the econometric model does is produce conditional means that are very accurate in large samples.  
> **username_1**: @username_6 The comment was really addressed to the OP, in the hope that he will understand the impossibility of its question. Essentially such a question is an ideal invitation for the Chat, not for the Q&A space.  
> **username_3**: @username_0 Compare the confidence intervals we get away with, compared to hard sciences which can use real lab experiments. Its many orders of magnitudes... just look at the number of $0$s before the likelihood of the Higgs-Boson not existing.  
> **username_7**: One way of looking at it is that maybe econometrics has overstepped its role. The models and regressions that we have are too simplistic and yet too bold (they attempt to encompass a variety of phenomenon) to the point where our extrapolations are meaningless.  
> **username_0**: @username_1 I'm sorry, username_1, but I do not necessarily request evidence. You simply haven't grasped that I regard this as an epistemological question. It might be better phrased as, "Can econometrics conform to the scientific method?" A proper approach is not to perform a meta-analysis of its alleged successes or failures on a case-by-case basis, but rather to analyze the methodological assumptions that underlie econometrics to determine whether they conform to what one would expect of science.  
> **username_1**: ok, I just posted then an epistemological answer.  
> **username_6**: @username_0 Ah, now it becomes clearer. I will knock-up an epistemological answer later.  

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### Answer by username_3 on 2014-11-28. Score: 3

@username_1 has already mentioned one of the two points I wanted to make, here is my extension.

Econometrics has no value per se, it always comes from the data we use it on. In microeconomics, with many studies that are natural experiments, quasi-experiments or where we are somewhat sure that we are not capturing endogeneity, we could estimate many interesting parameters. One of the standard references would be the many wage regressions that have delivered fairly consistent and reproducible estimates.

On the other hand, in Macroeconomics, we have *no* hope of getting clean identification. *If* you assume every country to be identical, all we have is a panel of around 60 panels and 30-50 periods of observations (mostly of aggregates), depending on what you want to observe. Moreover, these are often not perfectly measured, **and** most importantly we cannot create random variation here.
Of course, when data fails, one can try to tweak the estimators, but even with partial identification as some VARs do it, we can only hope to get short-run identification, and still have to worry about endogeneity.

Yes, I agree. Economists have not consistently and univocally warned us about the financial crises and other macroeconomic shocks. But this does not necessarily mean that the structure that macroeconomic models assume are bad, nor does falsify any other section in Economics.

This is good news for Microeconomics: We can somewhat rely on Econometrics to reject and accept theory. It is bad news for Macro: We can almost never reject plausible models just looking at the data.

> **Comments:**
> **username_0**: Of all the responses, this one is the closest to my view, except I think I am still more pessimistic than you. "This does not necessarily mean that the structure that macroeconomic models assume are bad." Doesn't mean they are good either. How would we know?  
> **username_8**: It seems to me that we reject macro models all the time. Consider various consumption based asset pricing models (these are definitely "macro" in scope). They produce falsifiable predictions and the data has shown that the models are definitely wrong. Just because identification is near impossible in macro doesn't mean macro doesn't produce falsifiable hypotheses.  
> **username_3**: Sure, I should probably be a bit more careful with how I phrase that. I might look into it later again. But again, also with these models, we can argue that they are right *at the core*, but they lack an extension to become *more correct*, whatever that means. For example, the preferences that include past consumption . Im not saying that that is necessarily what I think is correct, but for many falsifiable prediction your model has, you can make up a story/extension that explains it.  
> **username_3**: There are some predictions that are so much off-the-hook that you just outright reject the model, but its not *as easy* as it is in lab-based science, even with falsifiable micro predictions.  
> **username_9**: > But this does not necessarily mean that the structure that macroeconomic models assume are bad,  That's true, but it doesn't take a lot of work to show that most macroeconomic models don't hold up to real world data, and it's equally easy to point to their asinine assumptions as the culprit. Macroeconomists love to handwave away 100+ years of solid psychological and sociological research.  

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### Answer by username_9 on 2014-12-01. Score: 3

Econometrics is nothing more than a fancy name for statistics. Namely, how do we apply statistics and economic theory together to get a clearer picture of reality?

Is statistics scientific? It can be when used properly. Statistics is merely a tool of science, in exactly the same way that econometrics is a tool of general economics. It is a tool that can be used for good science and for shit science.

> **Comments:**
> **username_0**: No one doubts the mathematical utility of statistics. It is the inputs that are the problem: Whenever the inputs are large aggregates of conscious beings with (potentially) very different subjective preferences, possibly across times, places, cultures, etc., when the number of free variables is very large, it is an open question whether there is much to be learned, or whether the discipline of statistics is even applicable.  
> **username_9**: Indeed, but the answer to ""Can econometrics conform to the scientific method?" is "Yes, it can."  
> **username_0**: If econometrics = statistics, the answer is clearly yes. But that is pretty uninteresting, almost tautological. If econometrics = statistics + "economic data as inputs", the answer is "no" at the macroeconomic level, and more muddled at the microeconomic level.  
> **username_10**: @username_0 have you ever done any econometrics? Research level, not off-the-shelf modelling? I am asking because I am curious whether your hypothesis about uselessness of econometrics (micro and especially macro) is based on personal experience, or just the impressions?  

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