<story><title>Remote software developers earn more than non-remote developers</title><url>https://whoisnnamdi.com/remote-software-developers-earn-more/</url></story><parent_chain><item><author>whoisnnamdi</author><text>Author here&lt;p&gt;Agreed, which is why I didn&amp;#x27;t say,&amp;quot;working remote causes developers to earn 22% more&amp;quot;, only that developers who work remote earn 22% more, which is an interesting fact in itself.&lt;p&gt;Early in the article I adjust this for various controls to better get at causality. This includes observable factors like age, years of experience, hours worked, size of employer, programming languages used, etc.&lt;p&gt;As I note in the article:
&amp;gt;Much of the apparent premium earned by remote developers is in fact driven by seniority and tenure. These are older, more experienced developers who either prefer to work remote or whose organizations grant them that privilege.&lt;p&gt;However, controlling for manually selected factors doesn&amp;#x27;t imply causality, so I use principled covariate selection to select the best set of controls and get closer to something that could be called causal. You can read more about this method, called Double Lasso Selection, in Urminsky, Hansen, and Chernozhukov [0].&lt;p&gt;This results in an adjusted pay premium of 9.4% for remote developers relative to those that never work remote. Hard to know for sure if this is causal either, but it&amp;#x27;s likely much closer to whatever the true causal impact is. Unsurprisingly, it&amp;#x27;s a lower number.&lt;p&gt;Thanks for reading!&lt;p&gt;[0] &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;home.uchicago.edu&amp;#x2F;ourminsky&amp;#x2F;Variable_Selection.pdf&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;home.uchicago.edu&amp;#x2F;ourminsky&amp;#x2F;Variable_Selection.pdf&lt;/a&gt;</text></item><item><author>JackPoach</author><text>I think that it&amp;#x27;s cause and effect issue. Developers who&amp;#x27;ve proven themselves to be reliable and experienced can &amp;#x27;force&amp;#x27; their preferences onto employers. And they happen to cost more as well. I don&amp;#x27;t believe that going remote magically makes you able command higher salary.</text></item></parent_chain><comment><author>munificent</author><text>One easy dumb trick I use to filter out &amp;quot;interesting&amp;quot; results that are likely just getting causality backwards is to flip the title around and see if it immediately sounds like an obvious truism. In the case of this article, it goes from:&lt;p&gt;&lt;i&gt;&amp;gt; Remote Software Developers Earn 22% More Than Non-Remote Developers&lt;/i&gt;&lt;p&gt;To something like:&lt;p&gt;&lt;i&gt;&amp;gt; Higher-paid software developers more likely to be working remotely&lt;/i&gt;&lt;p&gt;And at that point, yes, it&amp;#x27;s fairly obviously going to be true. Working remotely is a perk for those who prefer it so we should expect it to be positively correlated with other forms of compensation.&lt;p&gt;I think all that your data really shows is a hidden variable: competence. Better software developers get paid more, work remotely more, and probably also get more paid time off, larger bonuses, and all sorts of other perks.</text></comment>
<story><title>Remote software developers earn more than non-remote developers</title><url>https://whoisnnamdi.com/remote-software-developers-earn-more/</url></story><parent_chain><item><author>whoisnnamdi</author><text>Author here&lt;p&gt;Agreed, which is why I didn&amp;#x27;t say,&amp;quot;working remote causes developers to earn 22% more&amp;quot;, only that developers who work remote earn 22% more, which is an interesting fact in itself.&lt;p&gt;Early in the article I adjust this for various controls to better get at causality. This includes observable factors like age, years of experience, hours worked, size of employer, programming languages used, etc.&lt;p&gt;As I note in the article:
&amp;gt;Much of the apparent premium earned by remote developers is in fact driven by seniority and tenure. These are older, more experienced developers who either prefer to work remote or whose organizations grant them that privilege.&lt;p&gt;However, controlling for manually selected factors doesn&amp;#x27;t imply causality, so I use principled covariate selection to select the best set of controls and get closer to something that could be called causal. You can read more about this method, called Double Lasso Selection, in Urminsky, Hansen, and Chernozhukov [0].&lt;p&gt;This results in an adjusted pay premium of 9.4% for remote developers relative to those that never work remote. Hard to know for sure if this is causal either, but it&amp;#x27;s likely much closer to whatever the true causal impact is. Unsurprisingly, it&amp;#x27;s a lower number.&lt;p&gt;Thanks for reading!&lt;p&gt;[0] &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;home.uchicago.edu&amp;#x2F;ourminsky&amp;#x2F;Variable_Selection.pdf&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;home.uchicago.edu&amp;#x2F;ourminsky&amp;#x2F;Variable_Selection.pdf&lt;/a&gt;</text></item><item><author>JackPoach</author><text>I think that it&amp;#x27;s cause and effect issue. Developers who&amp;#x27;ve proven themselves to be reliable and experienced can &amp;#x27;force&amp;#x27; their preferences onto employers. And they happen to cost more as well. I don&amp;#x27;t believe that going remote magically makes you able command higher salary.</text></item></parent_chain><comment><author>whack</author><text>&amp;gt; &lt;i&gt;Early in the article I adjust this for various controls to better get at causality. This includes observable factors like age, years of experience, hours worked, size of employer, programming languages used, etc.&lt;/i&gt;&lt;p&gt;There are likely many other factors which aren&amp;#x27;t &amp;quot;observable&amp;quot; by your methodology, which are causing the 9.4% pay-premium. Factors like competency, domain knowledge, and how essential they are to the organization. I find it much more believable that these unobservable factors are causing both the pay-premium, and working-remote flexibility.&lt;p&gt;This is a common problem that comes up in such studies. Adjusting for various observable factors is great, but it still leaves behind the other unobservable factors. At which point you have to use your judgement to figure out whether those unobservable factors are more compelling than the hypothesis being tested.&lt;p&gt;That said, this is still a very cool analysis that demonstrates an interesting correlation. Thanks for sharing!</text></comment>