Not all about Supply and Demand: the case of oil prices

It wasn't long ago when we thought oil was a scarce commodity in the US. Now we have more oil in our stock piles than ever before, but oddly enough, sometimes we see conflicting signals. Hypothetically, the excess oil should be leading to lowered prices, but the sometimes the opposite occurs.

For instance, Marketplace's Dan Weissmann (@danweissmann) made a short on fluctuating oil prices where he featured a story on oil prices going up because the inventory went up. According to his interviewee, Walter Zimmerman, prices went up out due to imperfect information. With oil supply in excess, some traders expected prices to crash, but they didn't, and that may have worried some traders, so they bid prices up. As a correction, the oil prices dipped for the next days, but Zimmerman claims that this kind of thing is common in oil trading.

Its one thing to know the factors that shape oil prices over time, but figuring out which of those factors are most important is really hard. Sometimes it is neither about supply or demand, but about debt. But perhaps this is just something common to the world of trading. Sometimes you expect certain outcomes, and the disappointing results remind you every now and then that you aren't a wizard.

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Un- and Under-researched topics in (Counter-) Terrorism Studies

An article by Alex P. Schmid lists 50 topics in the field of (counter-)terrorism that are either un-researched or under-researched. Im not going to list them all here, but there are a few that caught my eye.

ISIS vs. al Qaeda: comparing and contrasting organizational structures.

ISIS's rise to infamy was rather fascinating. In 2014, they took over portions of Iraq and were aiming to achieve their goal of a caliphate. The world definately took notice, and ISIS might have been considered more dangerous a group than al Qaeda around that time, but the very fact that there was an al Qaeda and an ISIS shows that there was a different in ideology and (perhaps) management. What separates ISIS from al Qaeda? Are they organized any differently?

Terrorists released from prison: subsequent careers.

This would be an interesting find. What happens to extremists after being released from prison? Where do they go? How do these people attempt to re-assimilate into society? Do they try? Is their view on what society is and their path to extremism rather one and the same?

The targeting logic of terrorist attacks

(I think this was already explored in Berman's book, to a degree) What mode of attack do extremists use and under what circumstances do they use them? Why do they choose that particular mode of attack?

The terrorism - organized crime nexus: new insights and developments

This is by far one of the topics that I'm most interested in. Terrorism and organized crime aim at different kinds of ends, but find more use for each other than the public knows. What might we learn about (and from) the crossover between terrorism and drug trafficking? What about terrorism and human trafficking? etc.

Other:

• Freedom of speech vs. incitement to terrorism: the response of the courts
• Muslims, Christians, Hindus, Jews, and Buddhists under attack for their faith: a quantitative comparison in the post-Cold War period – claims vs. facts.
• The Arab Awakening and its possible implications for terrorism and international counterterrorism cooperation.
• Is there a disconnect between academic research on terrorism and the counter-terrorist intelligence community's knowledge (and knowledge requirements) regarding terrorism?
• Non-violent popular revolt and Salafist Jihadism: competing paradigms for political change in the Islamic world.
• New strategies for identifying and countering extremist ideologies on the Internet.
• The rehabilitation of terrorists vs. the rehabilitation of common criminals in prison: recidivism records compared

Resources

Schmid, A. 2011. "50 Un- and Under-researched Topics in the Field of (Counter-) Terrorism Studies". Perspectives on Terrorism Vol 5, No 1.

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Gretl: Picking between stacked time-series and stacked cross-sectional formats

When you're doing panel data regression in GRETL or any statistical software, you need your data formatted in a way that differentiates the time series dimensions from the cross sectional dimensions, which is more sophisticated and more informative in that matter. In GRETL, you can do this by allowing the software to "flatten" the data being used in two different ways:

• Stacked cross-sections: the successive vertical blocks each comprise a cross-section for a given period.
• Stacked time-series: the successive vertical blocks each comprise a time series for a given cross-sectional unit.

 ...but these two get confusing because they both seem to be the same thing, having the same options to set the number of cross-sectional units and time periods, regardless of whether you choose to make it 'stacked cross sections' or 'stacked time series'.

So it made me wonder whats so important about one versus the other, and whether it should matter which one you pick, and based off on the searches I made, it turns out that these options GRETL ultimately end up turning the data into just, stacked time series. A word from Allin Cottrell, one of GRETL's founders, sheds some light on this case. 

Allin Cottrell:

...maybe it's a bit confusing but in fact it is intended. The main point is that a panel dataset _must_ be organized as stacked time series for use in gretl. "Stacked cross sections" is not an option for panel data in gretl, it's just a way of saying that your data are currently the wrong way round and need to be fixed. 

So, if you go to "/Data/Dataset structure" and say that your dataset is stacked cross sections, gretl will reorganize it for you as stacked time series (a "physical" reorganization of the data). Note that if you then go back to the "Dataset structure" dialog your data will initially appear as "Stacked time series", so, naturally, stating that the structure is stacked time series will produce no change. 

If you want to change the actual data layout back to what it was originally, you have to say that it's stacked cross sections (again), and gretl will reorganize the data in the opposite direction.

Perhaps that could be easier for users to understand in later updates.

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Migrations and Diasporas of New York

A fascinating NYT post describes our migration patterns to and fro each state.

The migration data is based on Census data, particularly ipums, which was used to compare the state of residence versus the state of birth of a representative sample of Census forms. According to information aesthetics, the visualization technique used in this post "resembles that of organically shaped, stacked area graphs, also coined as stream graphs or ThemeRiver.

For a glimpse, here is are two visuals on the migration patterns in NY.

MIGRATION INTO NEW YORK (NYT):

The image of New York as a beacon that attracts all is definitely true for immigrants, but for people born in the United States, the picture is more complicated. With the recent growth in immigration, the percentage of foreign-born residents in New York is approaching Ellis Island days. But domestically, one of the less-noticed trends is the decline in population of blacks born in other states. Since 1980, the population of Southern-born blacks has declined by more than 350,000. You can also see in the "U.S. Other" category the impact of migration from Puerto Rico, which was particularly large in the post-war years.

DIASPORA OUT OF NEW YORK (NYT):

Of the 20 million New Yorkers alive today, nearly one in six are now in the South, an idea that would have been almost unthinkable 50 years ago. Florida is still the main attraction, followed by New Jersey. But in terms of growth, since 1980 the number of New Yorkers living in South Carolina increased by about as much as the number living across the Hudson River. As our colleague Nate Cohn puts it, one of the state's leading exports is its people.

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