Avocado Toast and Home Ownership

I am sure that many of you are familiar with the story from 2 years ago linking millenials brunch habits with their low home ownership rates that sent ripples of laughter around the internet. The story I am referring to is this one https://www.theguardian.com/lifeandstyle/2017/may/15/australian-millionaire-millennials-avocado-toast-house where a millionaire informs young people that they need to cut down on their breakfast indulgence and $4 coffees to unlock the secret path to home ownership. I decided to try and put this to the test (only on paper of course because who wants to give up brunching and morning coffees) as an upcoming graduate heading back to London after graduation.
As someone lucky enough to be going back to London with a graduate job, I will be earning from September. Let's assume that I will try to move out immediately and begin renting in London. I will also use the average graduate salary for London schemes. The average graduate salary for an economics student is somewhere around the £29 000 mark. After tax, this would leave me with around £23 258. Now lets consider how much student loan I would begin to pay back: this works out to around £24.63 per week or £1280.76 a year. Our money left over is now £21 977.24. I am also going to assume, every year I get a raise of £3000.
Having looked at some properties in London,the prices are not low and with income in the first year equivalent to £1831.44 per month it is not unreasonable to assume that 50% of this income will be spent on rent and bills (and that's probably a conservative estimate). This leaves around £915.72 per month for residual living costs. Let's assume that I am particularly thrifty and am able to get a bus to and from work. With 25 days leave per year, this adds up to £705 per year on work travel (it costs £1.50 for a bus journey) adding a £58.75 monthly cost. £856.97 now has to cover groceries and leisure costs for the month. According to the Money Advice Service the average spend on food per person per month is £235. This leaves us with £621.97. Unexpected costs are bound to be needed so let's set aside £75 per month for this. We now have £546.97 for leisure and savings. Now for the avocado toast and coffees!
From my limited experience of brunching, avocado toast tends to be on the cheaper side of the menu around the £5 mark whilst more elaborate concoctions sit closer to £9. Let's average that out and assume each brunch excursion costs you £7 for food and £3 for a fancy beetroot latte. I will also add in the cost of a daily (workday) coffee at £2.75 a pop (you bring your own mug) adding up to £13.75 per week. I personally feel that assuming brunch is a weekly occurrence may be overstating things slightly but lets go with it being a weekly Sunday treat. All of this luxury adds up to £95 per month, or £1140 per year. This leaves £451.97 for savings and any other treats in the week. Because we are just testing the impact of avocado toast and coffees I am going to leave out other leisure for now and assume I can put away £451.97 every month for a deposit on a house. This adds up to £5423.64 of savings in my first year. Without avocado toast this would be £6563.64

According to Statista, the average house price in London is around the £475 000 mark. The recommended minimum deposit is now at the 20% mark so let's make that £95 000 saved for a property in London. Assuming an increase of £3000 every year, here is what the next 5 years would look like
saving with avocado toast year 2: £6293.6
saving without avocado toast year 2: £7433.6

saving with avocado toast year 3: £7163.6
saving without avocado toast year 3: £8303.64

saving with avocado toast year 4: £8033.6
saving without avocado toast year 4: £9173.52

saving with avocado toast year 5: £8903.6
saving without avocado toast year 5: £10043.64

Total saved in the first 5 years with avocado toast: £35818.04
Total saved in the first 5 years without avocado toast: £41518.04
This means that even after 5 years of salary progression, nonexistent leisure, low rent in an area probably far from your place of work you are still not even halfway to meeting your deposit on a house. Of course the dynamic changes if you and a partner are combining salaries. The reality is of course eating out adds up but the figures above are very conservative estimates of spending on these moments- if you don't spend it on avocado toast or equivalent meals and drinks with friends, is the plan to live between work and home religiously saving? Even if you do this it is likely you will be saving for at least 10 years before making the deposit. This is why it is ridiculous to say that avocado toast is whats holding the next generation back from buying homes- if only it was that easy!! So don't feel too guilty the next time you decide to catch up with a friend over a poached egg or two, it really won't slash your saving dreams.

Questions about the homeless and data problems

In this blog post, I write about an interesting question I would want to answer, and the reason why it probably won't get answered: The lack of available data.

One main thing economists do is answer difficult questions by using data. You could ask any kind of question and then try and find the appropriate data to answer it. One big problem occurs when there is simply no data available or the data that is available is inadequate. This can bring about big problems, because if everyone just studies the issues for which data are available huge areas of research can go completely untouched. This might be because data is difficult to acquire. For example, it's easier to find data for official government statistics on education that it is on people's attitudes towards important issues. In the latter case, you'd have to run a survey and this also bears the problem that the answers are self-reported and people might not always respond truthfully (whether it's conscious or unconscious). In a previous post, I wrote about the Gender Data gap and the fact that there is not enough data available on the lives and specific circumstances of women (especially in lower-income countries and areas). Similar problems are found elsewhere, in the post from last week Jocelyn writes about the book "Invisible Women" in which Caroline Criado Perez writes about how this world is designed for men and that one reason for this is that people don't make the effort to gather data on women.

The reason I'm writing about this is that I had a question for which there probably is no data available. I was wondering whether giving to the homeless is changing in the U.K. as the country transitions from predominately using cash to using cards. Usually, if things change drastically you see people adapting. If you walk around major cities in the U.K. today, most street musicians and artists have a small contactless device through which people can donate. Similarly, in museums, you can donate a specified amount using your contactless card instead of leaving some change. Clearly, the homeless could not adapt in this manner. You might even argue that homeless people with a contactless device would receive even less because people perceive them as less deserving. This question fits in the larger area of research on the homeless. While there is some data on how many homeless people there are or potential policies, there is less research on attitudes towards the homeless and their lives. A paper by Morgan, Goddard, and Givens from 2016 examines what determines people's willingness to help the homeless in direct face-to-face interactions such as willingness to give or volunteering in a homeless shelter. They find a strong link between the general level of empathy that a person feels and their willingness to give, but they also consider factors such as religion, gender, and race. Apart from attitudes towards the homeless, it might be also interesting to see what impacts their lives the most. Whether its services run by volunteers such as shelters or soup kitchens or direct giving from people on the streets. If receiving money from people on the streets is a major source for their food and clothing, a reduction in how much cash people carry with them could have drastic effects on the homeless. On the other hand, it might be that there is no effect at all because the people who give to the homeless will find a way to give with or without a card-based system. Or maybe, contactless won't have an impact on how much cash people carry in the first place. I think these are interesting questions to answer but clearly, there is not a lot of data available on the homeless. One could ask homeless people directly and conduct surveys but it would take a while until we'd have a sufficiently large data set. Furthermore, maybe homeless people don't know how much exactly they were given directly before the country moved to contactless. In this case, you could compare a country like the U.K. with a different more cash-focussed country such as Germany. But it might be that people in one country are just naturally more/less likely to give and that it actually has nothing to do with how much cash people carry with them.

I do not want to suggest that it lies in the public's responsibility to support the homeless, this is a huge policy failure, and governments should find ways to protect all its citizens and improve the lives of the homeless. Finland for example "solved" its situation with homelessness and while this solution might not work everywhere this suggests that through smart thinking and commitment it's not impossible to help the homeless.

Book Review: Invisible Women

This year, after watching this video https://www.youtube.com/watch?v=lIW5jBrrsS0, I have been encouraged to try and return to the heights of my preteen reading capacity (probably not possible with the rate I devoured YA novels) to expand my exposure to novels and books beyond the confines of my academic course. Whilst over summer I focused more on fiction (particularly recommend 'We Need to Talk about Kevin'), this month I treated myself to a (hardback!) book called 'Invisible Women' by Caroline Criado Perez, and whilst a lot of the book felt infuriating, many of the insights felt ever relevant and the solutions proposed optimistically straightforward.
Split into 6 sections, this book proved to be eminently accessible and even though economic understanding is present throughout, this is not a barrier for those intimidated at the thought of an 'economics book' as such. Whilst as I got towards the end of the book and came across sections I was more familiar with such as GDP calculation I found myself skimming, there was plenty of content I had not encountered before which felt more engaging. Perhaps then this book is best suited to an introductory investigation of key topics.
Whilst many of us have seen articles lamenting design flaws such as smartphone size and VR headsets, topics which Perez does discuss, what held most impact for me within this book were instances of planning, policy and research that failed to include the perspective of women and consequently held gendered consequences. Below I will include a couple of examples
Medical Research
This section in the book was probably where 80% of my outraged scoffs were aimed. Perez takes the reader through an academic and practical minefield for women. Referring back to her introductory remarks about the male default, Perez criticises assumptions made within medicinal teaching and care that the male body is the neutral norm whilst the only sex specific differences between men and women occur within reproductive systems. A lot of the reticence to examine sex differences relates to the 'messiness' of hormones commonly present within female bodies that complicate studies and warp results- the solution? Just exclude women from the study to get a neat conclusion and move on. In fact, sex difference exists within 'every tissue and organ system in the body', there are differences down to our cells, inevitably producing differential reactions to 'standard' treatments and diagnosis. Perez looks at the example of heart attacks to illustrate the dangers of such an approach. A 2014 review if the FDA database of CRT-D devices used to treat heart attacks found that only 20% of the participants in trials were women with individual studies having such negligible numbers of women that dis-aggregating results by sex found no major difference. When the results were combined however, it is revealed that women needed such devices at a lower threshold of symptoms than men. A shame then that medical guidelines releasing doctors to recommend this treatment relate to male averages then. If such devices were given to women at their lower threshold, Perez states that this would see a "76% reduction in heart failure or death and a 76% reduction in death alone" from having this pacemaker implanted. This implies that the gendered data gap is causing preventable deaths.
Moreover, Perez discusses 'Yentl syndrom', describing the instances when women are misdiagnosed and not believed unless their symptoms conform to the presentation of symptoms according to the male standard. Again referencing heart attacks, it becomes apparent that despite the fact that women and men often exhibit different symptoms that indicate an individual is having a heart attack, the male standard is used to measure a patient against, leading to many women being turned away or misdiagnosed. This is fatal!
Transport Funding
Whilst the title of the first chapter 'can snow clearing be sexist?' got a look of amusement from the man sat next to me on the bus, I am sure he might be even more surprised to find out that in fact, yes it can. Perez discusses the way that city planners can unknowingly and without any malice disadvantage women in the allocation of funding to different projects and schemes. In most countries, women tend to rely most heavily on public transport and walking. This is due to the fact that women tend to be more likely to have to make 'trip chains' running smaller errands and making multiple short journeys throughout the day. Walking and public transport lends itself to this. Men on the other hand, are more likely to drive, with a journey in and out of their workplace often covering their daily travel. So in Sweden when city officials of Karlskoga dedicated their efforts to clearing the roads rather than pedestrian walkways this was largely catered to one type of travel. Interestingly, this was actually costing Sweden, a lot, in healthcare during the winter months. The equivalent of £3.2 million was the cost of pedestrian falls in a single winter season! This sum was about twice the cost of road maintenance in winter- it made sense to adjust policy to cover broader winter safety measures and since changes has been introduced, considerable savings have been made.
This is just one of many seemingly innocuous policy choices unwittingly perpetuating a male bias, often entirely unintentional, unpacked in ‘invisible women’. Certainly the extent of impact policy at the city planning level was quite astonishing to me.

Whilst by the end of the book I felt that a certain argument was being copy pasted a lot with new examples, the very fact that there are so many instances where the argument applied should in itself give pause for thought. Overall I found the book to be packed with studies and statistics alongside enraging points that felt increasingly urgent. 

Incentive Problems in University Education

This blog post is inspired by the very boring lecture I've had to attend all semester.

While I am interested in all the modules I take this year (I picked them, after all) I don't have nearly enough time to spend on each one. As I try to allocate my time between the modules this year I can tell that I spend more time on some modules than others. Part of the reason for this is that some modules are simply better than others. But why?

Disclaimer: The following framework is pushing it a little bit because in the first bit I implicitly assume that lecturers care about students' final grades. This might not be the case but bare with me, because as will be revealed later in this post, it may be beneficial to the university experience if lecturers were invested in grade outcomes, too.

In our model set up, we have students and lecturers/course convenors. For each module, students can decide whether to put in a lot of effort (study a lot) or very little effort (do the bare minimum). Students care about the final grades they get but all else equal students will prefer to put in only a little effort. This means if students can get the same grade regardless of how much effort they put in, they will prefer to only do the minimum amount required.

On the other side, we have the course convenors/lecturers. They care about the final outcomes (grades) in the modules they design. Lecturers want students to exert high effort because studying a lot will increase the probability of students doing well in the exam. Maybe lecturers care about students' grades because they care deeply about our learning experiences, or maybe they get some kind of reward if students perform well in their exams.* Students are scarce on time which means that they can't spend a lot of effort (or time) on each module. Lecturers only observe the final results (good grade/bad grade) which doesn't necessarily tell them about the students' effort. This is because putting in a lot of effort only increases the probability that students do well in the exam. You might study a lot but on the day of the exam, you have a terrible headache so that you can't remember any of the course material. On the other hand, you might not study at all but the exam is multiple choice and through some miracle, you get all the answers right. The point here is that studying a lot will only increase the probability that you do well, it doesn't guarantee it. Overall, this means that lecturers want students to study a lot for their module to increase the probability of good grades. For example, Emma who teaches Microeconomics wants students to study the most for Microeconomics to increase the probability that they get good grades.

How can she do this? As we know by now, economics is all about incentives. What the lecturers will try to do is design their module in a way that is incentive compatible. This means course convenors will want to incentivize students to spend a lot of effort on their module. How could they do this?

1. They could make the module and lectures really exciting!
This would require more effort from the lecturers' side, but a well-designed module will always be preferred by students. If you explain concepts clearly, design interesting lectures with real-world examples, students might naturally prefer to study more for your module simply because it's more fun.

2. Weekly test
This one's a bit on the mean side, but it gets the job done. Instead of trying to make your module more fun you could incentivize students to study by holding weekly (or bi-weekly) tests on the material. Because students care about their grades to some degree, they will study the material every week to do well in the test. It is also less effort to revise material each week than it is to revise a semesters' worth of lectures the week before the exam. Again, this comes at a higher cost to the lecturers because they have to write and mark the tests (or they get the teaching assistants to do this).

It would be great if lecturers actually did these things because entertaining lectures and well-designed modules are more fun, and while weekly tests might be a pain, it will make revision before the exam easier. So, why don't all lecturers do this?** These things require effort, and apparently, not all lecturers are willing to put in that extra effort. There definitely are some lecturers who actually do care about these things and design great modules. Yet, it might be interesting to see what would happen if the university incentivized lecturers to care about grades, too.

The interested reader might have noticed that this is actually what the professionals call a double-incentive problem***. The incentive problem exists between the lecturers and students but there is a second one! To get lecturers to care about students' grades, the university needs to incentivize them to do so.****

* This, of course, assumes that they can't just design really easy exams but instead the only way to achieve this is by getting students to study for the module
** In other words: Why do I have to sit through two hours of boring formulas and terrible lecture design every week?
*** This is a joke, only I call it that
**** I don't know how lecturers' contracts are designed, maybe they already include something like this

Shorter Working Weeks; why the Permanent Three Day Weekend isn't just a Fantasy

"Eight hours labour, Eight hours recreation, Eight hours rest." This was one slogan used in the fight for shorter working days, legally defined limits to work and improved working conditions for the masses during the industrial revolution. Sure, this was for 6 days a week, but it was better than the 12 hour + shifts many were forced to do at the time. Fast forward a century or so and the accepted working week was about to be challenged again, this time from the top down. Henry Ford decided to remove a day from the working week at his factories, decreasing the weekly hours from 48 to 40. Certainly, such a move wasn't super selfless, Ford kept production targets high but just expected this to be achieved with less time. Setting this aside for now, productivity soared and so did profits.

Now, debates surrounding a shorter working week are surfacing again- Labour has incorporated the 4 day week into its party policy. Losing hours whilst maintaining a rate of pay might just take us one step closer to 'utopia', lengthening leisure, reducing stress from overwork, facilitating care responsibilities and allowing citizens greater capacity for democratic engagement. But is this unrealistic, supremely optimistic tunnel vision? Despite more comprehensive systems of protection for working conditions and limitations on working hours, we appear to be more accessible than ever before (on average we work an extra 7 hours a week after leaving work) and overwork has not gone away- so can we really afford to slow down?

4th Industrial Revolution
A shorter working week may seem completely radical- the 9 to 5 is just a fact of life! But with the age of AI and machines displacing workers, we need a radical rethinking of the way we structure work. A 30% increase in productivity, as made possible by technology addressing inefficiencies, would allow the UK to drop to a four day week of 32 hours. But these benefits are anything but guaranteed;"automation will not produce more free time for ordinary workers unless adequate policy is in place to ensure it". Certainly without effective policy, businesses may instead choose to cut costs and pay workers at the same rate for their reduced hours, defeating the gains made for ordinary workers whilst also leaving many unemployed and impoverished.
Beyond the context of a labour market about to be completely reshaped by technology, reducing hours has an impact without technology, actually causing increased productivity and thus gains for business.
A report published by the CDC in 2004 came back with a number of important findings regarding working beyond the 40 hour week;

  • People who regularly work overtime are less healthy than those who stick to 40 hours.
  • After the 8th hour of work, employees are less focused and less likely to make mistakes
  • People who regularly work overtime tend to be less productive.

Okay, so this is testament to the fact that working longer hours is counterproductive but actually reducing them?
When Kellogg reduced the working week to a 6 hour day in the midst of the great depression accident rates declined by 41%; this reduction was so successful that Kellogg announced "The unit cost of production is so lowered that we can afford to pay as much for six hours as we formerly paid for eight".
So not only does productivity not increase after an eight hour day, it might actually be the case that eight hours is not  the point of peak productivity.
Further studies contribute to the picture that not only does working fewer hours give us more lesiure time, it makes us happier and more productive.
For two months in 1974, the British government shortened the working week to just three days for two months. Despite this 40% drop in hours, productivity only dropped by 6%, demonstrating a rapid rise. Moreover, fewer employees took sick leave, further contributing to savings on the margin- when 57% of sick days are due to overwork related issues, shorter weeks can be an important change.
Meanwhile in France, when the less radical 35 hour week was mandated almost 60% of workers reported that the decrease had a positive impact on their work life balance and general happiness. This was just with a 5 hour decrease.
So really, it could be beneficial economically to decrease our working hours; as referenced in the above video, Britain works longer hours than many European countries and yet is less productive individually. Maybe a decreased working week can begin to change this.
Other benefits
It is easy when we are looking at things from a purely economic perspective to disregard elements that we are less able to quantify but in reality, a lot of these extra points can lead to a happier, healthier workforce. Fundamentally, less time at work = more leisure time. These extra hours can be put towards:
  • Civic engagement. With less time at work, individuals will be able to engage in a more meaningful way with politics, increasing accountability of our representatives and allowing more people to make informed and well thought out decisions when it comes to participating within our democracy. 
  • Unpaid work. Globally, 75% of unpaid work is completed by women ranging between 3-6 hours per day on this extra labour. this is impacting women's health too. Even working 41 hours a week holds an added risk of mental illness for women. Reducing the working week will allow greater leisure time for those engaging in unpaid labour but also more time for this unpaid labour to be completed in. It may also go some way to correcting the imbalance, with greater availability of both men and women to complete these extra tasks.
  • Family units. Decreasing the working week could go some way to family bonding and parental involvement in child rearing (as well as saving families the costs of childcare.) Moreover, the reduced burden of a four day working week may seem less intimidating for women on maternity leave, providing a route back into employment that still allows time for being a mother.
  • General leisure. Reducing the working week would give us more free time to do what we want with! This is the utopia imagined by economists in the past because humans receive great utility from having more leisure. Even without the added scope for uses of this leisure time, having more leisure in itself would be something to celebrate.

What book to read next?

I just recently finished reading Michelle Obama's "Becoming" after being immersed in the hype of the book release and after seeing virtually every woman around me reading it. I am usually not a fan of autobiographies (except Bernie Sanders' one which was amazing, and Tara Westover's "Educated" which is one of the best books I've ever read) and the first chapter confirmed my apprehension. I have no idea how authors can authentically write about their childhoods and "remember" the tiniest details when I can't even remember what I had for breakfast. The book definitely picks up after she starts her career, changes her career, meets her now-husband (don't worry, I won't spoiler who it is) and authentically discusses various topics from politics to race and gender. It's a great book and everyone should read it, but this is not what the blog post is about. Instead, I am casually trying to illustrate a few economic concepts using my hunt for the next book as an example.

Let's begin with scarcity - one of our favorite concepts. Economics is all about scarcity. In this example, I am scarce on time. In between studying, adulting (doing laundry, cooking, buying groceries - it's exhausting) and studying (yes, again) you don't get a lot of time to read. If I had all the time in the world only for reading I wouldn't make such a fuss of finding the next book. After all, if the book I choose is not that good, it's no big deal because I'll be on the next book soon enough. I'm not only constrained on reading time but going out to buy the book will also chop some time out of my day. I won't order off amazon (at least I try not to), but lucky for me there is a book shop on campus so we can ignore that constraint. Lastly, I am also constrained by my budget, books are not cheap and if it's a hardcover you can expect to pay around £20 for a new companion. Again, we will ignore this constraint, because I have a gift card (isn't life wonderful?). So, my main constraint is reading-time. Because I am scarce on time, this makes the time that I do have to read very valuable. This is an important result in economics: scare resources are more expensive (or at least they should be, in theory)! This means I want to spend my time well, so I need to find a book that is worth my time.

Now, how do I make this decision? I have some general preferences over books. I prefer to read books that are not too thick (too much commitment) and I weakly prefer books written by women over those by men. Not saying I don't read any books written by men, but if there are two books that are equally likely to be good I'll choose the one written by a woman. I don't want to read anything too heavy, but I am generally indifferent between fiction and non-fiction. Lastly, I think you could say I'm slightly risk-averse in my book choices (risk-taking is for the summer break). This means I am more willing to read a book by an author I have already read or someone I have heard of. This still leaves me with an incredibly huge pool of potential candidates. So what to do? My main strategy is to look for recommendations. This brings me to my next economic concept - information.

Information is most we talked about in my Advanced Microeconomics course so this should be a great recap for the midterm. Information in economics is the reduction in uncertainty. Uncertainty in this context means that I don't know whether a book will be good or bad. Information might help me identify whether a book is likely to be good or bad and make a better decision. I already have some information, my information set will consist of the knowledge I already have of authors that I know are great writes and those who are not. Furthermore, I can make a judgment on how likely I think it is that a book will be either good or bad.  New information can come from various sources, but the value of the information might be different. An example: Getting recommendations from the internet could be one source of information. I could look for the best reads of the year and pick a book from there. But compare this to me asking a friend.* The information my friend has to give is likely to have higher value because she knows me and has read similar books. One more component to incorporate here could be the reliability of sources in the past. Someone who has recommended a good book in the past might have more valuable recommendations**.

This was just one example, but the same thing could easily be applied to music, TV shows, movies, restaurants and so on. Economics offer structures to understand how we make our decisions and why a decision about which book to read next might be important enough to write a blog post about it (scarce time!!!). Either way, I hope you enjoyed this, but even more so, I hope that you have a good book recommendation!!!

* The combination of these two approaches is to look at recommendations by people I admire, thank you Bill Gates, thank you Barack Obama
**I wonder how you'd incorporate this in a theoretical framework.

Microcredit: exploitation or opportunity?

As a student of both politics and economics, I am often keenly aware of the difference in values and frameworks of right and wrong that exist between the two. Last year I had the opportunity to examine this in a bit more depth in the area of development. I took ‘politics of development’ as well as ‘development economics A and B’ in the hopes this would a) enrich the depths of my understanding and b) give me a more balanced account than taking either one or the other. This is not to say there is not a diversity of opinion within both politics and economics, however education of the two in my experience tends towards certain medians, with politics classes being more left leaning and economics classes more conservatively aligned. Below is a case study that illustrates the value in considering a topic from a cross disciplinary perspective.

Micro credit is a term you may or may not be familiar with. Micro credit is a development strategy formulated by a man named Muhammed Yunus; it is a concept perceived to be so impactful and empowering that Yunus and the Grameen Bank  won the Nobel peace prize in 2006 for their efforts at implementing the approach in 2006. To explain this fully, I invite you to consider a developing country context, specifically a small rural community where each individual has minimal disposable incomes, let alone assets to their name. If one such individual wants to take out a loan, whether for starting a business or for consumption purposes, they have two options (so far).

  1. Approach a formal lender. (These will be institutions such as banks)
  2. Approach an informal lender. (This could be someone in the village, an individual with money etc)

Formal institutions will always be preferable for the borrower- whilst interest rates are high they are a lot lower than informal alternatives.
So what is the problem?
Some of you may have gone through the process of getting a bank loan such as a mortgage. Often some form of collateral is needed so that if you fail to make the loan repayments, the bank can collect this collateral in lieu of the payment. In the above context of a developing country and a poor rural community, it is very unlikely that the borrower will have any acceptable collateral to promise to the bank in case they miss the repayments. Because they don’t have this, the borrower has nothing to lose - if they can’t make the repayment nothing can be taken from them. There is an incentive to choose riskier projects or try and cheat. The lender will be aware of this and, without any collateral, will refuse the loan.
So option 1 is not an option for the poor borrower. That leaves option 2. This is an undesirable option as interest rates are so high on any loan given. This is to account for all the risk (because the borrower has no collateral) that the informal lender is accepting.
So both options are unattractive or unavailable to the poor borrower. This is where microcredit comes in. The premise of microcredit is to provide some middle ground option using social collateral and peer monitoring.
Microcredit grants small loans to groups of people rather than individuals. The loans are staggered at first, to demonstrate the reliability of the group. Once this is established more loans will become available. So how can the lender afford to give lower interest rates when these are still risky borrowers? Two concepts are important to understand here.
Social Collateral-when monetary punishments are not an option, as is the case with a poor borrower, it can be more effective to take advantage of close knit communities and social sanctions that they can impose on people who do not pay back their loans. Social sanctions would include the awareness that an individual and their family are not to be trusted, making it unlikely that other members of the community will lend to this person again or work with them. This reintroduces the incentive to pay back the loan- you don’t want to be seen as untrustworthy and blocked out of business in your community. This is used in the Grameen Banks use of microcredit by making borrowers repay their loans publicly in the centre of the community so that their payment or lack thereof is witnessed and appropriate action may be taken.
Peer monitoring- this can be seen in the allocation of microcredit loans to groups rather than individual. If one group member fails to make a payment, the whole group is no longer eligible for loans. This means that other group members success and reputation is based upon each members reliability. There will be pressure placed upon each other to make the payments and if the group cares about each other, they will not want to let the group down. Furthermore, this helps microcredit institutions cut down on screening costs. You don’t have to check each person is reliable because each member of the group wants to make sure the group they are with when asking for the loan is reliable and hard working- they will only select good people for the borrowing group.
This means that microcredit can afford to offer lower interest rates and provide loans to poor people otherwise blocked from getting credit because the risks are severely reduced. Indeed in 2000 only 2% of loans were defaulted at the Grameen Bank, the first big implementor of microcredit, compared to default rates of 60-70% in informal rural credit markets. (Default= not able to pay back the loan)
From an economics perspective, this is a tremendous success, allowing people in developing countries increased opportunity to start businesses and improve their economic status (especially for women who are the principal recipients of microcredit loans) and actually providing the incentives needed for these borrowers to make the repayments without high costs of enforcement (chasing borrowers for their payment etc)

So what is the political perspective on this strategy?
First let’s consider the structural critique
“Encouraging the poor to participate in their own survival strategies by accumulating personal debt and creating small businesses displaces any sense that poverty may be structural or that the state has any responsibility for collective welfare”
This understanding considers the broader problem of the inequalities and poverty that has put these rural workers in this position of poverty in the first place. If you accept that this is the result of political structures, with poor social safety nets and a system that rewards the pursuit of profit at the expense of other people it may seem laughable to put the responsibility back onto the very people who are the victims of such a system and celebrating the fact that they need to work hard just to survive also may seem uncomfortable. This is especially pertinent because whilst yes, the interest rates are lower than other options, they are still high (30%!) and people are still putting themselves into debt.
Next let’s consider the disconnect between theory and reality
Despite theoretically appearing sound and assertions abound of the opportunities for business start ups and entrepreneurship, this may grossly underestimate the poverty that exists in targeted communities, and ignore the results. 94% of microcredit loans in South Africa are used for consumption- that is just to get by; to get food, water and basic necessities. This means that actually, these people are not making a return on their loans, placing themselves into debt for pure survival and not on a business idea to make a return. Even more misleading, when groups do use the loans for business start ups, there is a real deficit in consumer demand. Remember, these communities are poor, many can barely afford food let alone extra bits their neighbour is now trying to sell.
Jason Hickel describes this as a "socially acceptable mechanism for extracting wealth and resources from poor people".
A final point I would add here is related to the values microcredit depends upon; needing social collateral that potentially will lead to a generation of exclusion seems like a punishment for being poor rather than a punishment for not making a payment. This is particularly emphasised when microloans are being taken out for consumption.

Maybe theory doesn't always work the way it should

Basic economic concepts

Why do we write this blog? As Jocelyn mentioned in her latest post one reason is to break down the barriers between academic economics and everyone who might be interested in economics but scared away because of the jargon and the maths. But at the same time, we are rational, self-interested economist students (little economics joke) so we couldn't possibly do something just for the public's benefit. This post (and probably some of my future posts, too) will demonstrate how we can do both at the same time.

Let me explain. Just like everyone else, I am thinking (panicking) about what to do after third year and one route I am looking at is a research economist role at the Institute for Fiscal studies. They are an applied microeconomics (yes, please no more macroeconomics) institute that does economic research with a policy focus. The place sounds like an absolute dream to me so I want to do well in the applications. In the process, they will test our understanding of basic economic principles. So, today I will revisit some of these "basic" principles (this is the self-interest part). At the same time, I think it could be useful to explain some of the jargon and work through some of the basic theory economists use to explain the world. So, let's start.

Courtesy of Freeeconhelp.com I will discuss some of what they identify as the fundamental principles of economics.

The economist's best friend is the rational agent. But who is she*? The idea of rationality is based on preferences. Preferences must be complete and transitive (hello jargon!) to be rational. Completeness means that if I look at all the fruit at Lidl I have a preference over which fruit I prefer to the other, e.g. apples are better than oranges, and oranges are better than bananas, and so on. Completeness just means that I have an opinion on all of this. This could also mean that I am indifferent between apples and pears, for example, it just means that given the choice between an apple and a pear I'm happy to have either. Transitivity means that my choices are logical. For example, if I like apples better than oranges, and oranges are better than bananas, then that implies that I also like apples better than bananas. If both of these things hold then my preferences are considered rational. This concept can then be applied to larger scales, from what type of food I buy, to how I behave in day to day life. One thing that is absolutely crucial to understand is that the rational agent is just a theory. There are many, many cases where people don't behave perfectly rational and yes economists do know this. However, there are different degrees to which economists are willing to digress from this theory. Assuming people are rational agents enables economists to scale up this behavior and then make predictions about how people will behave. But what are these predictions worth if people don't even behave this way? But if we can't make any predicitons it makes it harder to say which programs governments should spend their money on or how high taxes on certain goods should be. The rational agent is definitely a balancing act. The main takeaway should be that economists have an "ideal" model of how people behave (the rational agent) which simplifies their analysis but that this model is flawed and these flaws should be taken into account when making predictions.

Costs and Opportunity Costs
This is actually a fun one. We all know normal costs, the price tag on that Lidl banana or the concert tickets we've been waiting to buy forever. These costs are pretty straight forward and are called "monetary" (because of money) costs. But economists also look at different types of costs - opportunity costs. The opportunity cost is the cost of the options forgone. For example, if I skip work to go to a concert, not only do I have to pay for the concert tickets, there is also the indirect cost of my forgone wages (assuming I am paid by the hour). Or, if I go on a night out with my friends instead of studying, I incur the costs of the drinks but there is also the cost of the lost studying time (although this is harder to measure - this could be measured in lost marks?). That's the basic concept of opportunity cost. A quick side note on costs here: There are many costs that are neither direct monetary costs nor can they straight-up opportunity costs. The most prominent example of this are environmental costs. What is the cost of building a parking lot on a green space? This doesn't have a straight price tag. Environmental valuation tries to approximate these costs by looking at the benefits and happiness people derived from going to the park or the benefit of the air quality provided from the green space. This is a good example where economic theory falls short and it's important to think beyond economic models to have a wholesome assessment of the situation.

Marginal Analysis
This plays a very important role in economics. Economists usually analyze things at the margin. What does that mean? The straight forward answer is that it's the next possible unit. So marginal utility (read: happiness) would mean how much happier I'd be from eating one more brownie. Marginal cost would be how much more it costs a firm to produce one more unit. For costs, the marginal costs could be quite low. For example, if you start a pencil-making business, in the beginning, you have to spend quite a bit of money to buy machines and rent a place (assume you're the only worker there) for example. But once all the equipment is bought it doesn't cost you anything to produce the next pencil. So the marginal cost from producing the fifth pencil after the first four is basically zero. This simplification again can help economists make inferences over people's behavior.

*Footnote: Yes, my rational agent is a she. But whenever I have read about the rational agent it was pretty much always a he. Why? Because the majority (pretty much all) of economists who came up with these theories were men, so all their examples are men. Recently, people have called attention to the fact that most examples in economics textbooks are men and that maybe we should change that. The result? My math econ lecturer priding himself on being politically incorrect because he used a male name in his example. Congrats K. you absolutely do not get the point.

Economics and its love affair with jargon

The above clip is an excerpt from a Michael Moore documentary poking satirical fun out of the lack of clarity so prevalent within economics dialogue. Whilst I might have found this slightly humorous when I watched the documentary during college (ages 16-18), after my entry into the world of academic economics with no prior experience, it hit home a bit harder. Since embarking on this journey, I often feel as though I have spent longer trying to decode and grapple with the definitions of economics terms and phrasing than I have needed to spend on actually understanding the underlying concepts. All of this is from the perspective of a student who has had access to good quality education and academic support throughout her 20 years of living as well as being a student who pretty consistently performs well and indulges in the use of excessively technical phrasing (to my detriment) from time to time. I mean, maybe it's just a Monday evening but I, an economics student, feel tired just reading stuff like this:
Late on Wednesday night, the governing council of the ECB decided that it would no longer accept Greek sovereign debt as collateral for its loans. Greece’s junk-rated bonds had been the subject of a “waiver”, where the central bank accepted sovereign and bank debt as security in return for cheap ECB funding.
According to research from the Post Crash Economics society at Manchester University, 60% of the 1500 students asked were unable to choose the correct answer for defining GDP whilst almost half could not identify what the budget deficit was. These terms are commonly used in media reporting, so if these definitions are ill-defined in the public eye, passages like the excerpt above are unlikely to feel particularly enlightening. Michael Moore makes the critique that the confusion of such terminology is intentional, meant to make you switch off and lose interest so you do not really know what is going on, and certainly when financial and economic terms are explained and illustrated in the format used by films such as the Big Short, it is scary to see how little we know and how angry it should make us sometimes.
If critique is limited to the upper echelons of discussion, doesn't it all feel a bit shady and elitist? If we want more people to engage with subjects like economics, the first step should be to reduce the barriers to accessibility. Maybe this way more people could become interested in economics and not yawn involuntarily when they see the word inflation in an article or zone out and nod along when someone grumbles about fiscal policy. We need to democratise economics! This is part of what we are trying to do in this blog, making economics seem doable, exciting and applicable to so much more than financial trends or Brexit predictions (but also these things). Whilst maybe part of the motivation behind this blog post is me tired of struggling through another economic concept, I think the point remains valid, and there is a lot more to gain than my individual time spent on studying (although I wouldn't be mad about that either).

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.

Book of the summer: Factfulness

Summer is the time when you can finally relieve yourself of the pain from the mountain of unread books that are piling next to your bed. Always amazed and impressed with myself when I read the same book as Bill Gates, I will write about a book that both Bill (yes, we are on a first-name basis) and I loved: Factfulness by Hans Rosling, Ola Rosling, and Anna Rosling Ronnlund.

I had heard of Hans Rosling ages ago when I watched his famous TED talk. He is a medical doctor and global health professor who worked his life to increase health care around the world. At the same time, Hans, alongside his son and daughter in law, set up the Gapminder foundation as a tool to fight ignorance. Both the foundation and his TED talk aim to show that - despite the negative images we see in the media and the menacing feeling that the world keeps getting worse every day - the world is actually improving. In his TED talk he introduces the now-famous moving bubble chart which visualizes the progress humanity has made over the past 100 or so years. Since the talk, Hans has been touring the world trying to inform experts and leaders around the world about the amazing progress we've made and where action is still needed. The book factfulness is a culmination of his life's work, and sadly, Hans passed away before it was finished. His collaborates Ola and Anna finished writing it and today I finished reading it.

What is factfulness?
Most simply, factfulness is the practice of only holding beliefs for which you have evidence that they are true. For example, believing that the planet is warming is a belief backed by the data. The problem Hans identified throughout his life and the central premise of the book is that people tend to not be very factful when they think about the state of the world. In fact, we tend to think that the world is worse than it actually. We think fewer children are vaccinated, more species extinct, and more people in poverty than the data actually shows. The reasons for this are various but Hans identifies 10 instincts we have that make us pessimistic about the state of the world.

This matters because if we stress and worry about the wrong things then we don't spend our resources as efficiently as possible. After working in government all summer "value for money" is deeply ingrained into my brain. Most of us care about suffering around the world and want to improve our societies but if we guide our efforts according to where we feel help is most needed we might not achieve as much good as we could. Instead, Hans argues, we should let the data guide our way and see where we can have the biggest impact. At the same time, we ought to be careful not to rely only on data and take any insights with a pinch of salt. Overall, the book teaches its reader to adopt a more differentiated world-view, to not take everything we read and hear as a given, but instead inquire and ask questions to gain a better understanding of our world.

The book is an extremely honest account of a very experienced and wise person and we see how Hans has learned from his own mistakes and how he himself has struggled to practice factfulness throughout his life. This is because the instincts he describes are there for a reason and often they can help simplify things or help us make decisions. But when it comes to complicated systems and decisions - as they usually are in the social sciences - we need to step back and take a breath before acting.

The most important thing the book thought me was to be humble. Reading about how Hans has struggled to overcome his own stereotypes showed how it is a life long process. In many of his accounts of his time when he was a doctor in countries on lower income levels than the West and different cultures too, he has become aware to the assumption he makes about people in other living situations and how often they can be misguided.

Factfulness is an amazing book for everyone interested in the state of the world and potentially improving it. Most of all, however, it is a reminder - among all the worrying of the state of the world and the many things we could be doing better - to celebrate and appreciate the progress we have already made and be inspired to take action to continue these achievements. 

The Heavy Price Tag of Fast Fashion

You may have seen Missguided's recent summertime offer of the £1 bikini being advertised, or criticised online in the last few months. As the name suggests, this bikini (pictured above) is sold for £1 for a limited time. Missguided's "one pound bikini statement" explains that
It cost us more to produce than one pound and we're absorbing the cost so we can offer it at an incredible price as a gift to our customers.
In spite of this cost sacrifice, this product can still be seen as a symbol of the ever-popular fast fashion industry. Fast fashion translates the latest trends at affordable prices through increasingly cheap production methods, often heralding reduced cost at the expense of more intangible social costs as well as material and design quality. This post is focusing in particular on the disconnect between the social costs of fast fashion production and the prices they are sold to illustrate the economics term 'negative externalities'
What is an externality?
Externalities are the third party costs from production and consumption of goods and services for which no appropriate compensation is paid. In other words, externalities are the costs which don't have a market price and so are not included in the market costs and pricing models of products. Things like the environmental impact of production are not traded in a market and so do not have a price. This means that even those these costs are very real, they are often disregarded when charging a customer and competing for lower price points. Negative externalities are an example of market failure because the spillover effects of production or consumption are occurring outside market mechanisms.
Externalities can also be positive. For example, when you consume education this provides the private benefit to you of your knowledge and skills (human capital) however this also provides a social benefit if you use this education for the benefit of others. This social benefit is not included in the price of education as this social contribution is something that is once more difficult to quantify with a market price, particularly as the extent of social benefit varies dramatically between individuals.
The case of fast fashion provides an example of a production negative externality market failure. Let's try to illustrate this graphically

This graph might seem a bit intimidating at first but all the logic from the initial explanation is here. Private cost refers to the market costs a producer has had to face, in the case of fast fashion this will include the costs of materials, labour, transport, design etc. The social cost is the aggregate cost of private costs and the externalities that do not have a price. External costs within fast fashion may be the environmental impact of outsourcing to use cheap labour, as well as the environmental consequences of the disposable quality of the product that is likely to find its way to a landfill after a handful of uses. Therefore there is a difference between the marginal private cost (the additional private cost from the production of 1 more unit) and the marginal social cost (the additional aggregate costs from the production of 1 more unit) due to the presence of externalities (social cost = private cost + externalities).
The market allocation of quantity sold and the price charged is illustrated by Q1 and P1. Conversely, Q2 and P2 represent the socially efficient equilibrium. As you can see from the graph, the socially efficient price is higher than the market price. This reflects that the market prices we pay for our products are not charging us for externalities, but they aren't paying for them either. This is where market failure occurs. The triangle formed by each dot on this graph represents the deadweight welfare loss or the loss of economic efficiency. This is an inefficient market.

So there you have a brief introduction into externalities as exemplified by the case of fast fashion.

No one escapes economics

Despite the common misconception that economics is mostly finance and banking (I haven't done a single finance module in my entire university career), economics is actually everywhere and it is almost impossible to escape it.

Today's world is as interconnected as it could possibly be; whether its next-day deliveries on amazon, ordering some cute Shiba-Inu themed socks from Canada, or paypal-ling a pal in a different country. Internationally, our economies are as connected as never before, both through trade and finance. Unions such as the EU have increased mobility enormously, it is now a lot easier to move to a completely different country, study abroad or simply travel than 50 years ago.

This interconnectedness brings many many advantages with it but it has also significantly increased some risks. Along the material interconnectedness through trade, for example, has also come financial globalization; banks nowadays hold monetary assets in other countries and people might have accounts abroad. While I won't bore you now with the details of financial integration (given that I barely grasped it myself in my last macroeconomics course) it is important to recognize the price we pay for EU-wide free roaming and ordering random stuff from across the ocean. Because this highly integrated system means that problems in one area can easily spread across the whole network as happened with the EU-crisis just a few years ago. How to remain connected while reducing the risk of crisis is a problem policy-makers still haven't solved. That has also to do with the nature of the crisis, given the complexity of the system no person understands all of it. That means you can put safety nets in place and try to anticipate potential problems but you won't know if your solutions work until the crisis hits.

But even if you ignore this international network and decide to consume and live only within your country (looking at you Trump) you will not escape economics. Because while nowadays we associate economics with big words like GDP, or labor markets, or stock prices, initially economics meant barter. Before money hit society people used to exchange goods for goods, one pair of shoes might have been worth 20 apples. We haven't lived in a full barter economy for many years but you have smaller forms of this in smaller units - such as prisons, where cigarettes act as a sort of currency.

I think the most striking example of how you can't escape the economy is that of the Westovers. Last weekend, I read the memoir "Educated" of Tara Westover, a woman who grew up in rural Idaho without any contact to the outside world. Her family were Mormons and her father did not want to interact with the government/ the establishment in any way, so Tara and siblings were born at home with a midwife, didn't have birth certificates (initially), didn't go to the hospital in any case, and weren't educated at a public school. It's a great book and I definitely recommend reading it to everyone, but one thing I noticed was despite trying to be completely self-sufficient, in his preparations for the end of the world Gene (pseudonym) Westover still couldn't escape the economy. He had to work so he could earn money, to pay for electricity and food, and later their family built a business around their mothers' herbal medicine - a business which could be explained with economic theories. I just found it impressive that no matter how hard you try to escape society, economics will always stay with you and the economic theories that we discuss on this blog can help organise and explain structures in almost any society.

What is the Value of Life?!

This blog post is not going to be as existential as the title may suggest. Instead, I am going to try and explore the economics of placing a value on life as well as considering some of the ethical concerns this has a tendency of raising.
The first point to raise in this article is the difference between the economic use of the phrase 'value of life' and the more general understanding of the term. 'Value of Life', often prefixed with 'statistical' (life), seeks to assign economic value to reflect the quantitative benefit of avoiding loss of life. Simply, this value reflects the economic cost of a fatality and the benefit of avoiding said fatality. In statistical terms this represents the "cost of reducing the average number of deaths by one" and is a useful component in the calculation of risk and cost-benefit analyses so central to economic planning. This is aligned with the neoclassical economic perspective as an essential component within responsible governance.
Because society has limited resources that it can spend on health and safety improvements, it should obtain the greatest benefits for each dollar spent, and ascertaining an appropriate value is necessary to that effort. ... To resist placing a dollar value on a statistical life is to abdicate any sense of rational decision‐making in the regulatory realm Brannon 2004
In contrast, the way that 'value of life' is perceived in general use relates to the more intrinsic importance and worth of life rather than a technical statistics term. This can lead to sensational headlines that warp the implications of this valuation when actually the two notions are pretty unrelated and it is misguided to interpret the statistical term as an authority on the worth we associate with our own lives and the lives of those around us.
These economic ‘values of lives’ are employed wherever policymakers are confronted with a difficult trade-off between safety and other desirable features such as speed, deliverability or cost-effectiveness. Policymakers aim to achieve a balance by weighing up these concerns. If there is too little consideration for safety, lives may be needlessly put in danger. However, it is equally important to recognise that all human activity involves some degree of risk; if there is excessive concern for safety, worthwhile policy changes can become impractical or unaffordable. The VSL is not an attempt to directly evaluate the worth of a human life, but a tool that allows policymakers to strike a balance between too much and too little safety risk.                                                                              - oxera.com

So how does an economist determine the 'Value of Statistical Life'?
According to the OECD there are 3 main methods used to identify this value.

  1. Cost of Compensation- this method looks at how much insurance companies payout in the case of an accident to determine how life and damage to life is valued.
  2. Human Capital- a more future oriented approach places a value on the potential a life had to give considering the accumulation of 'human capital' that includes the given individuals skills, education, qualifications and knowledge. Thus the loss of future earnings in the instance of loss of life is used to produce a value in this method. This has been criticised more recently as lacking the holistic approach intrinsic to economic life, with less tangible goods such as leisure failing to be taken into account. Moreover there is an implication that if you do not have the capacity or skill to be employed your statistical life has no value, something that seems inherently flawed.
  3. Willingness to Pay- this method is a current favourite for life valuation. It entails asking individuals how much they are willing to pay for some given safety measure that reduces their exposure to life risk. We can see this being implicitly used when workers who have riskier jobs are offered higher wages. This effectively asks the labourer to make a trade-off between safety and money. Some individuals may require lower or higher wages depending on the value they place upon their safety, which is equivalent to their 'willingness to pay' to ensure safety.

Are all lives values equally?
In spite of our clarification that statistical life is a separate concept to actual life, it may still be shocking to note that in fact, different values are used in different contexts, countries, projects to quantify life.
Under the willingness to pay method, it would follow that people with lower incomes may have a lower willingness to pay than those with higher incomes and this could factor into WTP values provided even if participants are told to disregard their income. On a international scale, this is made further evident with the value of statistical life rising in line with GDP per capita.

According to Shepard and Zeckhauser (1984) our willingness to pay increases until we reach 40, at which point we begin to become more indifferent towards risk and our willingness to pay decreases.

Ethics of Life Valuation
Some final consideration I wanted to put into this article surrounds the ethical implications of using life valuation techniques.
Economics has traditionally been able to maintain its credibility by relegating uncertainties in knowledge and complexities in ethics firmly to the sidelines.                                                                                       Funtowicz and Ravetz, 1994: 197
Is it comparable?
As mentioned previously, the value of statistical life is important for its inclusion within cost-benefit analyses. However should we be stating that this value is a statistical term in the same way that consumption benefits from a project or increased speed can be? Arguably, this is too crude a simplification, and by attaching a value to human life, this becomes merely another cost or benefit to weigh up within an equation with no more importance than any other variable. Whilst this is countered somewhat by attaching high value to human life, the implication remains.

What discourse is created within society?
Despite this article's emphasis upon statistical and actual life being different, statistical calculation has an impact on reality. This is particularly evident in our discussion of how the value of life an differ in line with age, risk preferences income etc. Much like a correlation between young people not ing turnout to vote in general elections and the lack of attention from politicians on the issues of younger generations, if people within certain groups express lower willingness to pay than others their lives may not be protected so vigourously within project formulation and creation because in a statistical sense, the loss is not as great.
This is alarmingly demonstrated in the below email included in a presentation by Clive Splash
This email, sent from a chief economist of the world bank makes the suggestion that polluting industries should be moved to developing countries with lower wages (as we have discussed wages can encapsulate willingness to pay figures that have also been shown in this article to be lower in countries with lower average incomes). Thus implications of certain lives being valued differently or at least in accordance with the willingness to pay model is problematic from an ethical glance.

Is life valuation implicitly preference utilitarianism and is this desirable?
Preference utilitarianism values actions that fulfil the largest possible number of personal interests. Whilst at face value this may seem unobjectionable and fair, there are further implications for equality. Whose preferences are being prioritised? Are we willing to sacrifice certain preferences in order to rather strive for greater international equity? Such questions challenge the assumptions made within some economic life valuation and reinforce that these are not obvious approaches to take.