How To: Deal with Journal Rejections Thinking About the Easter Island

The Easter Island is a very enigmatic place. If you do a brief research on the Island, you would realize that there are many different views about the history of the island. It has been well established, however, that the construction of the Moais stopped in the late 18th century. Why? I think we do not know.

I visited the Island after my first year in the Ph.D. At that time, I already had a journal rejection (or maybe even more than one). Although short, this academic experience led me to observe some of the things you can see in the Island with a surprisingly creative view (maybe too creatively).

After riding a bike for a couple of hours (see my post about biking around the Island), I made it to the quarry were the Moais were built. Although you can see many pictures before landing on the Island, it is still really interesting to walk around dozens of Moais lying on the ground in different positions. I walked around the external side of the volcano Rano Raraku and then I walked into the crater. When I was coming back from the crater, I ran into some rats and horses. I had to wait until the horses decided to move from the trail so I could keep going back to the entrance of the Park.

Rano Raraku, Easter Island

Rano Raraku Volcano.

Before getting to the entrance, I ran into a special Moai. The Moai was (and it is probably still like that) lying horizontally. However, the interesting part was that the Moai was not a single piece of rock anymore. The statue was broken into several pieces.


Broken Moais.

Looking at the Moai I got what I would describe as an interesting piece of wisdom from the Easter Island. In a less elaborated way, I thought:

“The craftsmen that carved this statue spent a long time working on it. Unfortunately, this Moai got completely destroyed and useless after being broken off the wall of the volcano. Could they repair it? It does not seem they could. You, as a researcher, can also spend a long time ‘carving’ a research paper. However, and fortunately, when it is rejected from a journal, the paper is not broken for good. You actually can repair it and try again.”

So, yes, fortunately, as a researcher you do not end up with a broken Moai when a paper is rejected from a journal. And if the Rapa Nui (native Polynesian inhabitants of Easter Island) kept carving Moais, you definitely have to keep trying to get your paper published.

I think it works.

If you ever meet me and hear me saying “well, it is not a Moai”, then you will know what just happened.

How To / STATA: Draw a Random Sample from Panel Data

Assume we have a data set containing firm data across years. The variable id uniquely identifies a firm. The variable performance is some kind of financial performance of the firm and the variable year indicates when that performance happened. Thus,  we have a small panel where firm-year is the unit of analysis.

If you want to draw a random sample from a data set like that, you shouldn’t directly use the command –sample-. If you use it, then you will lose the panel structure of the data (or at very least you are very likely to lose it!). What you should do instead is to randomly select firm ids and then keep all the observations (all years) for each of the randomly selected firm ids. Below you can see an example of a STATA code to perform this operation. Remember we have three variables: id, year, performance.

use "yourdataset.dta", replace

tempfile paneldata
save `paneldata'

collapse (mean) performance, by(id)
keep id
sample 50

tempfile randomsampleid
save `randomsampleid'

use `paneldata'

merge m:1 id using `randomsampleid'

drop if _merge == 1
drop _merge

After opening the data set, we save a temporary file called paneldata (lines 3-4). Then we get rid of the repeated ids using –collapse– and then we drop all the variables and we keep only id (lines 6-7). In line 8 we use the command –sample– so STATA randomly select, ins this case, a 50% of the total number of unique ids (-help sample– to see other options, such as defining the number of observations you want to draw from the original set). In lines 10-11 we save this subset of ids in a temporary file called randomsampleid.

Finally, we return to the panel data (line 13) and then we merge it using the randomsampleid. It is a m:1 merge because in the panel data the id variable does not uniquely identify each observation but it does that in the using data. Those observations that are successfully merged are the ones that STATA randomly chose for you, so we get rid of the rest in line 17.

Biking around Easter Island

Biking around the Easter Island (Rapa Nui) is a great idea. If you like to ride a bike, it is maybe the second best idea after the one you had when you decided to actually visit Easter Island.

I biked around the Island during winter, which seems to be a great season for biking if you are lucky enough not to see rain (I was lucky enough not to see rain at all during 5 days). I have not been to the Island in summer but I think it is probably not such a good idea to bike around the Island during summer (around 30°C and a lot of humidity).

In total, I biked around 120 km (75 mi) in 4 days. I was on the road (biking/walking/taking pictures) around 3-5 hours per day depending on the route I chose and the places I visited.

LAN Airlines' 767 at Easter Island's Airport

LAN Airlines’ Boeing 767 at Easter Island’s Airport

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How To / STATA: Calculate Variables for Groups of Observations

In management research, we usually need to create a variable that measures the experience of firms. Firms accumulate experience as they make acquisitions or invest in companies in certain countries. Sometimes this experience has an effect in future decisions, so we calculate variables that measure the number of times a firm has made an acquisition or has invested in a certain industry or country. In STATA, this can be done using the command –bysort– and –gen– (i.e. –generate-) or –egen-. In this post I will calculate an experience variable using a fictitious dataset.

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How To / STATA: Check if a File Exists Before Opening It

The STATA’s command –capture- allows you to check if the file that you are trying to open exists. This command evaluates whether or not the file is in the folder you are using. Then, –capture- assigns a value to the macro _rc depending on whether the file is in the folder or not. Therefore, we can use the value of _rc to continue with our STATA’s script.

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How To: Extract Highlighted Text from a PDF File

Some people enjoy reading on paper not only because they can make annotations and highlight text easily, but also because they actually like their handwriting. If you are not one of those, then the following guide may help you. I will show how to extract all the highlighted text and the annotations from a PDF using Acrobat Professional. I did an extensive research (i.e. I tried many different keywords in Google!) before understanding how to extract the annotations from a PDF file. I did not find too many useful articles on the internet. It turned to be an easier process than what most of the site I visited described, so I hope that Google ranks this page well!

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Send Starred Articles from Google Reader to Evernote

From time to time I discover interesting articles in Google Reader. I mark with a start those articles that I want to read later or store for future re-reading. Since I use Evernote to organize my notes, I was happy when I found that you can setup a simply process to send the starred items in Google Reader to your Evernote account. That is what IFTTT can do for you.

IFTTT lets you create “if X then Y” statements, in which X and Y are actions or events related to some internet services. In the case of my starred articles in Google Reader, I have the following recipe:

If “an item is starred in Google Reader” then “send it as a new note in Evernote”.

You can find a lot of recipes already created in IFTTT, so you may want to take a look at its website.