Economic research: causation

One great thing about studying economics is that career prospects are quite broad. Whether you are interested in business, insurance, data science or politics even, a degree in economics likely makes you a suitable candidate. If you'd rather not face the challenges of real-life and having a job straight after your Bachelors you can always extend your stay in the academic bubble and continue on a Masters course (obviously this isn't only an option for economists). In this case, you are likely to come across doing economic research, and if you are doing your Bachelors dissertation (like me) it is sooner rather than later.

Research is a pretty broad term and there are various types of research out there. You could be a scientist and trying to figure out how a specific drug works or how this star has come to be (as you can tell I know A LOT about astrophysics). In the social sciences - so anything from social anthropology to political science - you are likely interested in understandings society and human interaction. Now economics sits somewhere between the two. To some degree, economics would love to be considered a science such as physics or mathematics but this is complicated by its subjects. The economy is not some natural thing that is guided by the laws of nature (although we do try to sound sciences by calling them the laws of supply and demand, although I would consider them more guidelines than actual laws) which makes it so much more difficult to find a definite answer to an economics question. If I drop my pen gravity will ensure that it always falls according to some rule. But humans don't always behave according to specific rules. The rational agent in economics is an unrealistic chimera that serves as a simplification more than anything else. Nobody (I hope) in economics believes anymore that humans actually behave like rational agents. Yet, the rational agent can be useful in helping us model how we would behave if we were rational and then understand why that might not be the case. But I digress. What all this is trying to say that economics is a social science in terms of the things it studies. But in doing so, economists use methods that aim to make the conclusions as scientifically robust as we can.

One thing economists are particularly interested in is causation. This happened because of this: "the price increased because more people wanted to buy this good". In this sense economics is similar to the natural sciences: "the pen fell down because of gravity". Causation is very, very difficult to identify because in the social sciences there are so many things that might be the reason for something to happen. Here's a real-life example. A group of economists wanted to study the effectiveness of political protests. Demonstrations and protests are recognized as being an important aspect of democracy, but are protest actually the reason (the cause) for political change? Or are protest not the actual cause of political change, but instead people have changed their beliefs and preferences and protests are just a symptom of this change in opinions? The paper "Do Political Protests matter? - Evidence from the Tea Party movement" tries to answer this question. More simple: are political protests the reason for political change. So they try to measure whether bigger protests resulted in more political change. The problem is that they can't just estimate an equation for this, because maybe it's actually a change in opinions that causes BOTH bigger protests AND more political change. If this is true, it's just that bigger protests and more political change are related* but one isn't really the cause of the other and remembers we want to identify causation. So what to do about all this?
Luckily, these researchers came up with a cool way to identify causation. Instead of estimating the effect bigger protests had on political change, they estimated the effect of rainfall on political change. Huh? Why would they do that? The reasoning goes like this: We know (or more we make the reasonable assumption) that more rainfall doesn't have a direct effect on political change, because why would it. But we also assume that more rainfall means smaller protests, because we might be passionate about a cause but less motivated to actually join a protest if it rains like crazy. So we assume that more rainfall means smaller protests, assuming that everything else (in terms of peoples beliefs or other things that might have an impact on their voting behavior such as income) stays the same. Now we estimate the effect of rainfall on political change, also assuming everything else stays the same. Remember, if you think about it rainfall should not really have an effect on political change because there's not any reason why more rain would cause - or be the main reason for - political change. That is unless there is something going on in the background. The something that is going on in the background is the relationship between rainfall and the size of protests - more rain means smaller protests and vice versa no rainfall means bigger protests. Bringing it altogether if we find that an absence of rain (compared to when there is high rainfall) leads to more political change we can make the conclusion that the size of protests does cause policial change. And this is exactly what the researchers found. On rainy days there were smaller protests and in those areas, there was less political change (in the context of the tea party movement which their article was about). But when protests were on sunny days there were bigger protests, and suddenly they saw quite a bit of political change. Everything else is the same, people have the same political opinions, same income, etc, the only thing that was different was the weather. This allowed the researchers to conclude that political protests do matter.

This example illustrates how tricky it can be to identify causation but how smart economic techniques (and researchers!) can help overcome this burden and make robust conclusions about social issues. Of course, this isn't always the case and not all researchers truly identify causation. At the same time not all research is on causation, economists might also be interested in evaluating the effects of policies and programs or many other issues. But the issue of causation is a good example to show how economists research social issues using scientific methods.

*Footnote: There are many things that are correlated but where one thing doesn't cause the other. Correlated means for example that as one thing increases, the other does as well. Tyler Vigen has collected a number of these "spurious regressions" where things are correlated but obviously have nothing to do with each other like cheese consumption and the number of people dying from bedsheet entanglement.

Careers in Focus: Futurist

One of my big fears when thinking about jobs and career paths was my incapacity to know the breadth of options available for me to choose from. What if my dream job exists but I just don't know it?! Ultimately I have come to realise this way of approaching my options is more of a hindrance than an aid and certainly, with the dawn of the tech revolution, it's probably more important to be savvy with job choices and consider their longer term viability and compatibility with technological innovation. However I thought I would use this blog post to discuss one such job that I had not heard of before some summer podcast listening (see the linked podcast to explore the possibilities surrounding smart home technology) which has the capacity to be a hidden gem for some readers whilst retaining great relevance in today's job climate.

Futurist- Job Description
Whilst not claiming to be able to see the future, individuals in this role try to forecast what the future might look like. This includes, perhaps most prominently today, what the consequences could be of technology development and innovation. Certainly recent concern surrounding data handling on social media platforms was not accounted for early on in the formation of social media, leading to a flurry of panic and reactive legislation as data concerns surface. However, the field is not just limited to one specialism. Futurists could apply themselves to forecasting future political tensions, threat actors, business vulnerabilities etc. They could even advise with legislative attempts to promote safe and ethical innovation or in the consideration of unintended consequences that could stem from new law. Futurists provide this analysis to advise companies and individuals on the map of possibilities they could face and how to react in an effective and ultimately successful manner.
It helps us to protect against unknown risks and eventualities, two things that most of us like to avoid.
Another great thing about this job is that futurist insights can originate from across subject areas, each contributing different methods and analytical frameworks to begin predicting trends. So there isn't a specific degree that is more likely to succeed or give you a head-start if this is something you are interested in.

Average Salary
between $33 000 and $110 000. Average salary is around $83 000

Potential Employers
Part of the appeal of a futurist career is the breadth of options within the career itself. For those who are nervous about the prospect of committing to one job, futurism provides options with work available within government, business, think tanks, international bodies, media. Of course, there is still the capacity to specialise once you have found an area you love.

So there you have it, a career that is by definition future focused and ever relevant:

The Value of a Gap Year

With the new academic year just around the corner, there's a wave of Freshers (first-year students) flooding the streets of Manchester. If someone is younger than you, they always look waaaay younger, but this year, in particular, is weird to me because these Freshers are about the same age as my baby brother who in my mind is still 12.

When I started uni many moons ago I was already a year older than the rest of my cohort, because I had taken a gap year - before starting university I spent a year doing something non-school related. I spent half a year working to save money and then spent it all traveling around the U.S. Personally, taking a gap year changed my life. Before, I was on a track to study medicine simply because it's what I wanted to do since I was 14 (and started watching Grey's Anatomy) and had I not taken a gap year I'm sure that's what I would have done. But taking some time out to reflect and truly think about what I want from my life showed me that studying medicine wasn't what I wanted to do. All the reasons I wanted to study medicine - having an impact, working in a fast-paced environment, helping people - could be combined with my passion and interest for the social sciences. So here I am - three years later (as my Snapchat memories keep reminding me) - studying economics and I am sure I have made the right choice.

So why take a gap year?
There are many reasons you would want to take a gap year, you might not be sure about what you want to study, you simply don't want to go to university straight away, or you maybe want to travel. But for your personal development, it can be very important to do a gap year. You learn to be independent, figure out problems on your own, and learn life skills they simply don't teach at high school or university. What you do on your gap year is completely up to you. Many would like to travel but not everyone has the means or privilege to go on a trip around the world. But this isn't what a gap year should be about. It's primarily about experiencing something other than the educational system before embarking on a costly three-year journey to higher education. Whether you work a job, volunteer, or travel you will have some time to think about yourself and your future. And - as it did in my case - it might help you figure out what you want to do. During your time at high-school, you're concerned with getting good grades to get into uni, but you simply don't have enough time to figure out what you want to study. And this can be a huge factor of anxiety to many young people.
Apart from helping with your personal development, and thinking about your future, a gap year could also help in your academic and professional life. The same skills that help you in your personal life are also the "soft-skills" valued by employers. These skills allow students to differentiate themselves when applying for jobs or even higher education. Many of these benefits of taking a gap year are assumed because of the experiences from other "gappers" and haven't been systematically investigated. The paper "Widening the gap: pre‐university gap years and the ‘economy of experience’" by Sue Heath (2007) pulls together the presumed benefits and the level of evidence available to date.

It would be interesting to have some (more) research done on these issues. Do gap year students perform better than their peers? (this paper suggests yes!). Is there a benefit to the economy from students taking gap years? Are gap year students happier in their studies than their peers?

If you could quantify these benefits and show that individuals and society benefit from students taking gap years, you could make a case for government spending to increase these opportunities. Because when talking about gap years it is important to note that not everyone can afford to take a year before starting uni or a job, let alone travel. But the benefits of taking a gap year should be available to everyone so the government should increase these opportunities, whether it is through volunteering opportunities or internship experiences for example.

At the same time, the stigma around gap years as being an option for lazy teenagers to not go to uni needs to be reversed. Deciding about which uni to get into, what to study, and where your future is heading can exert considerable stress on teenagers, it certainly did on me.

For the future, it would be good to open up more options for teenagers as to what they can do after graduating high school, especially enabling and encouraging them to take a gap year.

Cyber Security; it’s the social engineering, stupid

In preparation for an interview this week I have been researching all things cyber security. As someone from a non-technical degree and devoid of the capacity to code, I have been searching for ways to relate my own understanding and experience to this position. It turns out, this has been easier than I envisaged.
According to the Global State of Information Security Survey 2018 by PWC, 27% of cyber breach incidents are the result of an employee action. Upon doing some more digging into large cases of cyber attack, the term social engineering kept cropping up. Within an information security context, social engineering can be understood as ‘ the use of deception to manipulate individuals into divulging confidential or personal information that may be used for fraudulent purposes.’ In many ways, this concept appeared more important than the tech itself; a phishing email is no good if nobody clicks on the link. Appealing to human fear, interest and expectation for normal online interaction can provoke a panicked irrational response which in the light of day sounds implausible. Let’s consider some examples to illustrate this point.

This cyber attack used a pop up claiming the device had been used for illicit behaviour and an immediate fine was required. To further drive home the veracity of the request, a webcam recording was included. We have all seen that black mirror episode, and this tactic worked well, with many individuals opting to pay the fine to make the elusive ‘criminal activity’ disappear.

A ransomware attack dependent upon phishing emails avoided malware detection software by first directing victims to a legitimate website. Following their arrival on the site the individual was asked to enter a CAPTCHA code regarding a missed delivery, a request that would hardly raise eyebrows. Upon completing this entry, a pop up appeared and data was stolen, requiring payment for the retrieval of the stolen files.

What these two examples serve to demonstrate is that we are more fallible than we like to believe. It’s not always as easy to detect an attempt at gaining access to your computer as the scam email I received from Bill Gates earlier this year wanting to give me however many billion dollars for no particular reason. (See below for reference) and a lot of work goes into understanding what will make you click, pay up and react before thinking.

To bring this brief post full circle, I am proposing a broader consideration of social factors to counter the successes of social engineering. Behavioural economics highlights the significance of nudge theory to encourage and steer people towards ‘correct’ or ‘rational’ decisions. Why should this not be applicable to cyber security? Companies are already grabbing hold of this and trying to innovate when pursuing the cultural shift necessary to recognise and combat cyber crime. Even something as simple as a thank you email to employees practicing good cyber hygiene has been shown to have a positive impact. So maybe it’s possible to play the cyber criminals at their own game and socially engineer businesses to exude good cyber practice, awareness and consideration.