I’ve finally finished doing some basic analysis of the results of my survey of econ bloggers that I conducted at the end of last year. Out of 218 bloggers I invited to participate (basically all the authors of blogs in my econ blogs ranking), I received 107 responses. Of these, three were discarded for not meeting some quality criteria, leaving 104 responses for the analysis. There were quite a few questions and many different ways to cut the data up, so I haven’t attempted to do all of the possible analysis. I’ve created a summary of the results, and done some basic analysis of some questions that seemed interesting to me. You can read all the gory details in this report that I wrote. I’m also releasing the data publicly for further analysis. Of the 107 responses, only one respondent was not willing to let their data be released. Accordingly, this Excel file contains the other 106 responses. Be ware that this includes the three respondents that I discarded because I deemed their responses to be unreliable. It also includes a few other quality issues that I corrected. These are highlighted in the file, and my report explains how I dealt with them.

With that stuff out of the way, let me present a few of the results. First up it’s important to bear in mind that I did not use a random sample, nor did I conduct a census. (Also bear in mind that I am not a very sophisticated statistician …).

In terms of age, the respondents are relatively old, with almost 50% over the age of 40. The respondents were also quite experienced bloggers, with about 58% having blogged for two years or more, and only 7% for less than 6 months. Academic were highly represented too, with 66% identifying themselves as either a tenured or non-tenured professor, or a student. Most respondents blog under their real name (88%) and most write for one (57%) or two (25%) blogs. There was a wide range of popularity of the respondents’ blogs. About 59% receive less than 1,000 readers or visitors per day, while just under 5% were super-stars receiving more than 10,000 per day. More than 14% of respondents did not know how many daily visitors or readers they have.

Respondents do not leave comments on other blogs that they don’t write very frequently, with 73% responding that they do so “a few times a month” or less. Only 9% comment almost every day or more often. There was a wide variation in the number of blog posts that respondents reported writing in the past month, from 1 post to 200, with a median of 25. About two-thirds of bloggers write 30 or fewer posts per month, while 14% write more than 60. The distribution of time spent on blogging over the past month was similar, ranging from 0.5 hours to 300 hours, with a median of 20 hours. Overall, this works out to 48 minutes per post.

Respondents were asked how much time they are spending on blogging now compared to when they first started, and how much they expect to be spending one year from now compared to now, with discrete choices ranging from “a lot less” to “a lot more”. Responses to both questions were roughly centered around “about the same”, however there was much greater variation in responses to the question comparing blogging activity now to one year ago. Overall, 32% of respondents reported spending less time on blogging now compared to a year ago, compared to 33% who reported spending more time. In contrast only 16% expected to be spending less time a year from now, and 13% expected to be spending more time. In terms of time, respondents were also asked to estimate how their time spent blogging was divided between writing and editing posts, reading or researching material for posts, dealing with comments and email, and other tasks. Roughly, the distribution among these tasks for the average blogger is 50%, 35%, 10% and 5% respectively.

Most respondents do not use third-party advertising, with only 30% reporting to have advertising such as Google Adsense on their blog, while 26% said that they advertise other services such as books they sell or consulting on their site. In total, 43% of respondents reported using their blog for either of these two purposes. The two categories of revenue seem to be somewhat exclusive, with only 29% of respondents who use at least one source of revenue reporting that they use both. In other words, among bloggers who try to raise revenues from their blog, most choose either third-party ads, or selling their own stuff, but not both.

Respondents were also asked to rate the adequacy of the direct income that they received from blogging as compensation for the time they spent. Perhaps not surprisingly, 52% rated it as “very inadequate”. Nevertheless, some people do appear to be making money from blogging, with almost 10% rating their direct income as “more or less adequate” or higher, and 3% rating it “very much more than adequate”. In addition, 26% did not answer this question.

There were a series of questions asking respondents to rate factors according to their importance as motivations for blogging on a scale of 1 to 5. “Fun or entertainment”, “To raise my profile”, “Contribute to policy/political debates”, “To educate the public or disseminate research”, and “As a way of recording thoughts or ideas” were rated highest, all with a median score of 4. “Contribute to academic debates” had a median of 3, “To get reader feedback from comments” and “To improve writing skills” both scored 2, while “Actual or potential direct income” and “Actual or potential indirect income” both had a median of 1.

The next set of questions asked respondents to rate the importance of various metrics for judging the success of their blog, again on a 1 to 5 scale. “Number of readers or website visitors”, “Links or reactions from other blogs”, and “Links or reactions from non-blog websites” all scored a median of 4, while “Volume of comments from readers” scored a median of 3. One thing in common with the responses to the previous question appears to be the lack of interest by bloggers in comments from readers.

The final set of questions asked respondents to rate the importance of some factors in terms of making blogging unattractive to them, on a 1 to 5 scale. “The time required” had a median of 4, and “Lack of interest from readers” had a median with 3, somewhat contradicting the apparent apathy towards reader comments in the previous two questions. “Low actual or potential direct income”, “Difficulties coming up with material for new posts”, “Concerns about adverse effects on my reputation” and “Inappropriate comments from readers” all scored a median importance of 2.

Beyond these basic results, I did some further detailed analysis by splitting the respondents into groups according to various characteristics. The first split I examined was “academic” versus “non-academic” bloggers. I classified academics as those who identified themselves as a tenured or non-tenured professor, or a student. I found that academics were more likely to use their real name (90% vs 82%), marginally less likely to have third-party advertisements (28% vs 30%) and marginally more likely to advertise other products or services (26% vs 24%). For all the questions with ordinal responses, I tested whether there was a significant difference in the distribution of responses by academics versus non-academics using a statistical test (a nonparametric Wilcoxon rank-sum test aka the Mann-Whitney U test, if you really want to know). In most cases there were no statistically significant differences. However, academic respondents appear to be less likely to leave comments on other blogs than non-academics. Academics also expected to be spending less time on blogging a year from now compared to non-academics. In terms of motivations, not surprisingly, academics were less motivated by income, and more motivated by contributing to academic debates compared to non-academics. In terms of negative factors, academics put less importance on the time required and the lack of potential income.

I also separated respondents into “commercial” and “non-commercial” categories, based on their responses to the questions about whether they have third-party advertising on their blog, or whether they advertise other products or services such as textbooks or consulting. I called a blogger “commercial” if they answered yes to either of these two questions. Not surprisingly, commercial bloggers put significantly more importance on direct and indirect income as motivations for blogging, and in terms of success metrics commercial bloggers were significantly more concerned about the number of website readers or visitors. Commercial bloggers also seem to be relatively more concerned about low actual or potential income and inappropriate comments from readers as factors that make blogging unattractive.

Finally, I tried to look at blogger “productivity” by using the results from the questions about the number of posts written and hours spent blogging in the past month. First it’s important to note that not all this time would become free if the respondent stopped blogging, as some of the time that they counted as reading or researching posts may still continue even if they were not blogging. With this in mind, there was no significant difference in the productivity of academic versus non-academic bloggers, or between “experienced” bloggers (those blogging for one year or more) and non-experienced bloggers. However, academic bloggers do spend significantly less time and write significantly fewer posts than non-academic bloggers. The median academic blogger writes 20 posts and spends 15 hours per month, while the median non-academic writes 30 posts and spends 30 hours. Nevertheless, there is no significant difference in posts per hour between academics and non-academics.

I also estimated a “production function” over all respondents and found a reasonable relationship between hours input and posts written. There appears to be diminishing returns, with a 1% increase in time spent per month associated with a 0.78% increase in the number of posts written per month.

So those are some of the highlights from my analysis. Please read the report for the full details, and download the data if you want to play with it. I’d appreciate if you’d let me know anything interesting that you find (or any mistakes in my work!).