<p>In econometrics and statistics, you sometimes will truncate outliers. Otherwise, maybe it's worth mentioning that in the business of predicting, analysts are punished for either being wrong, but their punished even more if they were boldly wrong. This is a form of herding behavior. Deviating from the consensus can be disproportionately risky.</p>

<p>Here's a paper that talks about it: "<a href="https://www.princeton.edu/~hhong/rje-analyst.pdf" rel="nofollow">Security analysts’ career concerns and
herding of earnings forecasts</a>" in the RAND Journal of Economics.</p>

CC BY-SA 3.0
2014-11-20T03:37:43.823Z
2014-11-20T03:37:43.823Z
jmbejara
<p>While <a href="http://en.wikipedia.org/wiki/Regional_Input-Output_Modeling_System" rel="nofollow">RIMS II</a>, <a href="http://en.wikipedia.org/wiki/MIG,_Inc." rel="nofollow">IMPLAN</a>, and <a href="http://en.wikipedia.org/wiki/Economic_impact_analysis#Methodology" rel="nofollow">other methods</a> regularly deviate substantially from each other in the answers they yield to analytical questions, is there a "band" within results should be considered "more accurate".</p>

<p>For example, if RIMS and IMPLAN give a quantitative result on the order of <code>x</code>, and a third method gives a result 2,3, or more orders of magnitude higher, should the third method be disregarded?</p>

<p>I ask this because I've submitted analysis based off industry-specific methods and had it roundly rejected not because there was a flaw in my analysis, but because it didn't agree with general case tools, or differed to markedly.</p>

<p>Is there a best practice within econometrics that says "throw out all results farther than <code>Y</code> from some accepted average"?</p>

CC BY-SA 3.0
2014-11-19T02:17:28.800Z
I am unfamiliar with what RIMS II and IMPLAN are. Could you please add a line of explanation or a link.
Jyotirmoy Bhattacharya
CC BY-SA 3.0
2014-11-19T02:17:52.470Z
Will do when not on mobile.
Jason Nichols
<econometrics><rims-ii>
Comparative Methods of Econometric Analysis
Jason Nichols
# Comparative Methods of Econometric Analysis

(Asked by: username_0 on 2014-11-18)

While [RIMS II](http://en.wikipedia.org/wiki/Regional_Input-Output_Modeling_System), [IMPLAN](http://en.wikipedia.org/wiki/MIG,_Inc.), and [other methods](http://en.wikipedia.org/wiki/Economic_impact_analysis#Methodology) regularly deviate substantially from each other in the answers they yield to analytical questions, is there a "band" within results should be considered "more accurate".

For example, if RIMS and IMPLAN give a quantitative result on the order of `x`, and a third method gives a result 2,3, or more orders of magnitude higher, should the third method be disregarded?

I ask this because I've submitted analysis based off industry-specific methods and had it roundly rejected not because there was a flaw in my analysis, but because it didn't agree with general case tools, or differed to markedly.

Is there a best practice within econometrics that says "throw out all results farther than `Y` from some accepted average"?

**Tags:** econometrics, rims-ii
> **Comments:**
> **username_1**: I am unfamiliar with what RIMS II and IMPLAN are. Could you please add a line of explanation or a link.  
> **username_0**: Will do when not on mobile.  

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## 1 answers

### Answer by username_2 on 2014-11-20. Score: 1

In econometrics and statistics, you sometimes will truncate outliers. Otherwise, maybe it's worth mentioning that in the business of predicting, analysts are punished for either being wrong, but their punished even more if they were boldly wrong. This is a form of herding behavior. Deviating from the consensus can be disproportionately risky.

Here's a paper that talks about it: "[Security analysts’ career concerns and
herding of earnings forecasts](https://www.princeton.edu/~hhong/rje-analyst.pdf)" in the RAND Journal of Economics.


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