Air Pollution Fact Roundup

Recently, the city I’ve called home for the past few months (Chiang Mai, Thailand) has been making it to the top of the most “world’s most polluted” lists on a pretty much daily basis. Today, the PM10 meter maxed out at 999 μg/m3 in one area, and the PM2.5 meter wasn’t far behind at around 850. For reference, the EPA defines an “acceptable” level as being below 12 micrograms per cubic meter (μg/m3). 12-35 is moderate, 35-55 is unhealthy for sensitive groups, 55-150 is unhealthy for everyone, 150-250 is very unhealthy, and 250-500 is hazardous. The EPA’s scale tops out at 500, since that basically doesn’t exist in the U.S.

I’ve been getting throat and nose symptoms, a dull headache, and general tiredness out of this whole experience, which hasn’t been great. I lived in South Korea for a few years, where the air quality hasn’t been amazing recently (it can go above 100, but I didn’t see above 200 happening much), but I never felt symptoms there. I’m not exercising, barely leaving the house, and generally in kind of a bad mood as a result of all this, which has left me some free time to obsesively research air quality topics. One of the things that’s caught my attention is the “Air Quality Index.” It’s essentially a market basket of various pollutants developed to help people better understand the impact of air pollution on health, which is great, but also confusing, especially when you’d just prefer to know exactly how much PM2.5 is being pumped into the air, since that’s what we’re really worried about.

Air Quality Indexes vs PM2.5

When you look up the air quality in a certain city, you’ll probably see an AQI, or an Air Quality Index–not an actual measurement of any one pollutant. There are a few reasons this is confusing:

  1. Different countries have different air quality standards. In China, a 10 is fine. In Canada, 10 is basically “we can’t count the moose in our backyard.” These different metrics are all calculated using different mixes of pollutants, each of which may be weighted differently, measured over a different period of time, and interpreted differently.
  2. Many AQIs (the EPA’s in particular) are non-linear, as they’ve been normalized to fit the basket of pollutants into a scale ranging from 0-N. That means that multiplying a number on the scale by 2 does not necessarily mean that it will be twice as bad for you–it actually may be much more than twice as bad.
  3. Many AQI measures can be pushed up by less harmful pollutants, which makes them fairly misleading when you really just care about PM2.5.

In general, an air quality index is one good way to get a quick grasp on air pollution, and the equations do make sense. However, in a situation like the one I’m currently in, what I really care about is the mass concentration per cubic meter of PM2.5, and I think it should be more of a general standard than it is. It lets you directly know what the content of the air you’re breathing is, isn’t skewed by different equations or national standards, and it allows for pretty much any air situation to be immediately understood.

When it comes to air pollution data, which we use to make large and small decisions on a regular basis, simpler is better for the public-facing stuff, and in this case that doesn’t mean giving people a mystery number and a color. Ideally, different AQIs would be available as part of the data presented by air pollution information sites, but more emphasis on the concentration would really help improve general understandability. Going with concentration data is more scientific, it’s linear, and it’s universal.

In the meantime, if you see an EPA AQI number anywhere, you can use this calculator to find the actual concentrations of each pollutant.

On Nomaducation: could the next digital nomads be students?

“Digital nomad” is a term that’s been making its way increasingly into the mainstream. As internet access and speeds around the world increase and the economy increasingly goes digital, working remotely or on a freelance basis is becoming increasingly possible. Coincidentally, so is studying online: there are literally thousands of MOOCs (Massive Open Online Courses), more free or easy-to-access educational content than you could ever possibly consume, and even fully-accredited, inexpensive degree programs you can pursue via laptop no matter where in the world you are.

This is all fairly new, so it’s understandable that no community has really emerged around student nomads yet, but maybe that time is close. Maybe the “nomaducation” buzzword is just a few years away from becoming the next “digital nomad.”

I’ve been doing it. Albeit, not on a full-time basis at all: I got my undergrad in the U.S, moved to South Korea to teach for a few years (the savings were a great jump-start), moved back to the U.S, moved to Thailand, and am currently planning on moving to Tbilisi, Georgia. The whole time I’ve been working and studying at the same time, and while it eats up most of my free time it’s been going pretty great. I’ve built a lot of skills and identified some things I really want to work on more deeply. In a nutshell:

  • I’ve improved my math and stats skills,
  • gotten into programming,
  • developed my passion for economics,
  • studied data analysis and visualization,
  • cultivated in interest in behavioral sciences,
  • learned the basics of a few languages,
  • taught English as a foreign language (I actually got pretty good at it–after a while)
  • written for tech, finance, and blockchain publications,
  • learned how small the world can be
  • met people from all over
  • listened to hundreds of hours of podcasts
  • taken so many MOOCs
  • and way more

In terms of knowledge and experience accrued, it’s been a clear win. In terms of time, it’s certainly taking longer than if I’d gone straight to a masters program, but in retrospect, I’m glad I didn’t. I’ve explored so many new worlds since I started my journey that it’s starting to get hard to keep them all straight. That’s why I’ve decided I really need to start specializing–but I digress. Here’s the pitch:

  • Travel is its own form of education
  • Online degrees are getting more common and acceptable
  • Online work is becoming easier to find
  • Living in low-cost countries can often be cheaper
  • Resources to serve the digital nomad community are becoming readily available

Essentially, while it’s certainly not the right call for everyone, I’d argue that “nomaducation,” or studying and travelling at the same time, is a small trend just waiting for a name and a community. That community part is important, and it’s most of the reason I’m writing about this now: I’ll get to that in my next post. Suffice it to say that I haven’t found much of one, I miss it, and (as you might have guessed), I’m taking a shot at creating it.

Where are all the homebrewed bomb drones?

The title alone seems like enough to get me on a list, but this is a topic that’s been turning over in my head for a while now, and ever since the Gatwick incident in December 2018 when as-of-yet unnown drone operators paralyzed an entire airport by just casually flying around. The cheapness and availability of drones combined with humanity’s tendency to blow each other up seems like it should have sparked some sort of an epidemic of drones with explosives strapped to to them committing acts of terrorism.

That’s only happened a few times, though. All I was able to turn up were the following incidents:

Out of those, only ISIS and the Houthi rebels actually did any damage. The Houthi attack is too recent to know if it will be adopted as a future MO, but if ISIS didn’t find it especially effective, it may just not be that great of a way to take out targets. Though they did post a propaganda poster of a drone headed towards the Eiffel Tower [Autoplaying video behind link].


This is hardly a neglected threat–Nicholas Grossman has written a whole book on it, and FBI Director Christopher Wray has expressed his opinion that this will be a big issue in the future. The fact remains, though, that we have yet to see a large-scale, high-profile drone bombing in the vein of other terror attacks. A few possible reasons for this:

  • It lacks the impact of a personal attack: terrorism isn’t about eliminating valuable targets, it’s about sending a message, and sending in a drone just doesn’t say as much as sending in a person.
  • It’s actually not that easy: maybe figuring out how to get sufficient amounts of explosives onto a drone, getting the trigger mechanisms right, flying it into the right spot, and detonating it isn’t as easy as it sounds.
  • Maybe drones just haven’t caught on yet: sure, they’re a hit on the commercial market, but maybe the first domino hasn’t fallen to set off the terrorism market yet. Maybe all the pieces are there, but no one has seen them used destructively enough to copycat them.

Either way, it seems likely that we’re due for that first incident. Drones are easy to get and wiring explosives onto them surely can’t be harder than wiring them other places. A large-scale drone attack is probably coming sometime in the next decade, and that will likely be the start of a trend, which will, unfortunately, probably lead to lots of restrictions on drones and the increased government use of drones and drone countermeasures.

Honestly, I’m more surprised that, given humans’ historical fixation with implementing new and exciting ways of murdering each other, we haven’t already filled the skies with small exploding death-copters. Maybe the world actually is getting more peaceful.


Moving from Humanities to Data (and around the world)

My geographical and intellectual journeys aren’t directly related, but over the past few years, my lack of a stable location has certainly played into my sense of what’s possible, what’s measurable, and how best to understand the forces that shape the world. Long story short, I’ve been making the jump from math-averse humanities major towards a me that is comfortable with numbers, models, uncertainty, and testing hypotheses.

I’ve made a lot of different mental jumps in a lot of different places, though, and since my history education instilled in me a strong sense of narrative (something humans love to impose on the world, whether it belongs there or not), I feel driven to connect the two. In this post: how I apparently am choosing to explain some of my life choices.

tl;dr: I move around a lot, mostly between relatively affordable urban areas in different countries. Humans and cities can only be fully explained with data, which is why I’m going to be making a series of posts recording some interesting pieces of my now multi-year journey towards getting better at doing that. 

Global variables

Since graduating, I’ve lived long-term (6+ months) in several parts of the US, two cities in South Korea, one city in Thailand, and I’ll be moving on to Tbilisi in the Republic (not state) of Georgia pretty soon. Since I’ve sort of fallen into online work, it makes sense for me to live in places that offer more amenities and a lower cost of living than the US.

This has also given me a lot of opportunities to encounter a lot of different ways that things work, as well as radically different perspectives on the way they should work. I’ve generally come around to the idea, though, that these differences exist more on the surface than the photographs and travelogues would have you believe: humans tend to be humans. All other things being equal, the reasons for our behavior tend to change more than the behavior itself does.

The common currency I’ve fixed upon in trying to understand these forces is data. Obviously, you can’t plug variables into a regression and predict every aspect of a country’s culture–but you can make a pretty darn good guess about how things work in that country. As complex as our constructs are, there are global variables underlying them.

The data density of cities

That may be why my primary target in a new country is always the cities: nowhere can you find a higher density and diversity of available data. Walking around a new city for a few days, with open eyes and random feet, is basically skydiving for a certain type of data nerd. You won’t discover everything, and a lot of your impressions will be wrong (they’ll be wronger the less time you spend), but if you pay attention you’ll end up with a collection of means and standard deviations for everything from the price of a beer to the general quality of life experienced by residents.

My infovorous (what is the adjective form of “infovore”?) tendencies probably explain why, despite my rural upbringing, I’m an urbanite at heart. That’s an increasingly expensive thing to be in the states, where urban density and mixed-use zoning tend to meet stiff resistance, which, for better or for worse, has pushed me to venture out into other countries. Most of the cities I find attractive aren’t the ones with idyllic suburban neighborhoods or adorably preserved downtown boulevards, but the ones where you can find a new apartment building going up every corner, gradually being surrounded by the shops and restaurants its residents demand. As far as I’m concerned, aesthetics take a clear back seat to affordability and convenience.

A personal geography

This personal preference for efficiency over beauty probably explains a lot about what frustrated me with humanities (a tendency to emphasize the subjective and unquantifiable aspects of human experience) and what I find attractive about the prospect of engaging with data (the drive to measure what can be measured, to quantify the unquantifiable where possible, and a certain level of comfort with error). Neither extreme is preferable, of course: purely data-based decisions are likely to ignore things that are difficult to measure, while purely qualitative decisions are likely to be subject to a wide array of human psychological errors and biases.

I’m very happy to fall somewhere in the middle of the qual-quant spectrum, as that’s where a lot of truth (with varying confidence intervals) tends to lie, and especially since that’s where I’m likely to remain in terms of my abilities. I’m decidedly weaker on quantitative skills than I’d like, though, which is why, since graduating university in 2014, I’ve been on a journey to improve them. It’s been slower than I’d like, hindered by things like having to “earn money” and “live life,” but I know I’m not the only one trying to reconcile their idealistic teenage degree choices with the facts of a rapidly expanding reality, which is why I’m hoping to make this a series detailing my steps and missteps, the resources I’ve used, the progress I’ve made, and the gravities that have pulled me into various orbits.

This post hopefully takes care of a lot of the “why,” and in future ones I’ll mostly be focusing on the “how.”

Analyzing Facebook Data: Part 1

To get some practice using Python for data analysis, and to get more familiar with a few data visualization tools, I’ve decided to do a series of projects on random datasets and see what I can get out of them. For my first project, I’m taking a look at the data dump that Facebook gives you.

The mission:

  • Download all my data from Facebook, figure out what’s interesting about it, analyze it, and visualize it.

There will be two main dimensions to the analysis: a look at the general type and structure of data that Facebook keeps, and a delve into my own personal data to see what’s really going on there.


I graduated with degrees in history and sociology, so I’m incapable of starting a project without developing some research questions. Though they’ll be refined once I get into the data, initially, I’m looking to find out:

  • What are the main types of data Facebook has (interests, location, advertising, interaction history, etc)?
  • How extensive is this data, exactly? How far back does it go? What gets kept around?
  • What can I found out about myself (or someone else, theoretically) with unfettered access to this data dump?
    • Interesting sub-question: if I was to reconstruct my life using only Facebook data, what would it look like, and how closely does it match my real life?

Getting started

Downloading your Facebook data is pretty easy, though the files aren’t tiny. That’s probably because you’re not just getting text data and code—you’re getting every picture and video on your profile.

I opted to download all my data in both the JSON and HTML formats, just for kicks. Opening up the unzipped JSON folder with Jupyter Notebook reveals a bunch of folders with names like “friends,” “ads,” “location_history,” and a bunch of other stuff. The JSON files within the folders are, as you would expect, full of information on you in raw text format.

The HTML folder is a bit more user-friendly, so it should be good for answering some of my initial questions and getting an idea of what I should be looking for. The file structure is identical—same folder names and everything—but opening the HTML files gives you clear human-speak language in a nice format.

What are the main types of data?

Okay, first question: what’s in the box? (WHAAAAT’S IN THE BOOOOX?!”) Some big categories jump out right away:

  • Profile data: about you, pages, profile information
  • Friend data: Friends, groups, following and followers
  • Timeline/interaction data: Comments, events, likes and reactions, messages, photos and videos, posts
  • Advertising data: ads
  • Location/security: location history, security and login information
  • Stuff you looked for: search history, saved items

Upon inspection, it turns out that this is pretty much your entire timeline. The lion’s share of data here is your posts, comments, likes, photos, videos, and messages, which is all stuff you’ve generated and which has stuck around as a mini-history of you. This stuff will be interesting to look at from a behavioral/statistical standpoint. What’s my posting frequency by year? Average post length? Of course, I could get one of those funky little Facebook analysis apps to do this for me, but the whole point here is to analyze it myself.

What I’m really looking forward to here is the stuff I didn’t generate, because I don’t know exactly what’s in there. Do they know everywhere I’ve been? Do they keep a record of every login? What’s my advertising profile like? And search history? Yeah, I generated that, but are they keeping a record of every single search I’ve ever done? This is where it gets interesting, mostly because it’s a little creepy.

Over the next few weeks, I’m going to go piece by piece, looking at the data with both human eyes and some Python code. With any luck, I’ll produce some interesting data and some kind of data visualization on everything I look at. Coming up:

  • A personal analysis
    • My posting history
    • My comment/reaction history
    • Differences between my messages and posts
  • Photos
    • I noticed that the JSON files included a fair bit of photo metadata, so I’ll see what I can do with that.
  • Creep factor
    • My location history (Facebook also logs IP addresses in a separate location, so it probably goes back a long way)
    • My search history
    • Advertising: what are they looking at? Who is advertising to me?

Towards a theory of coffee pricing in Southeast Asia

Country Average price of 1 hot Americano
Indonesia (Bali) 1.60 USD
Singapore 2.25 USD
Thailand 1.60 USD
Laos 1.75 USD


Country Average price of a budget restaurant meal
Indonesia (Bali) 2.50 USD
Singapore 4.50 USD
Thailand 2.00 USD
Laos 2.50 USD
A cup of coffee in Cambodia, part of Southeast Asia I ironically did not include in this article

DISCLAIMER: These tables are based on my own experiences travelling on a budget through SE Asia; they are not actually representative of a random sample of coffee shops and are very subjective. But if you are travelling on a budget in SE Asia around late 2017, feel free to use this as a rough guide of what you’ll pay for coffee and food.

I lived in America for most of my life, and Korea after that, so something about the tables above is strange to me. I’ll give you a chance to guess what I think is odd.






Did you guess price ratios? Because if you did, you’re right, and I’m not apparently alone in thinking it’s odd.

In Indonesia you can buy a cup of coffee for about 65% of what you would pay for a meal. Singapore offers a more reasonable 45% (these numbers are skewed by my very driven efforts towards budget eating, though). In Thailand, a coffee will run you about 65% of your meal. Laos is about 65%. (Disclaimer again, these are fairly subjective numbers, but I have about 95% confidence that a cup in Thailand will cost you between 1.00 and 2.15, given that you aren’t above buying coffee from a street vendor and are avoiding anyplace that looks “too fancy.”)

In most of my experience, coffee rarely costs anything close to what the meal does, even if you are eating on a budget in America. I should point out that none of those average coffee prices above include visits to Starbucks or similar chains, because then all bets are off and you may as well stop eating altogether the way some of South Korea’s doenjang-hyoja (bean-paste girls: girls who eat very cheap food in order to afford fancy clothes and Starbucks) do.

So this made me curious–why are coffee and food such similar prices in Southeast Asia, and why is most coffee priced not that much lower than what you’d pay in the US?


Coffee beans are an imported input

In a way, the second question answers the first. Coffee prices worldwide don’t vary as much as food prices because coffee is difficult to produce domestically. The price of a coffee bean bought from a plantation in Brazil or Indonesia is about the same for a U.S importer as for a Thai one.

This means that the cost of coffee-making inputs remains fairly standard between countries, with some variability based on distance and perhaps grade of coffee purchased.


Making coffee isn’t very labor-intensive

But then you have the variable cost–people have to work to get that coffee bean to the store, keep the lights to the cafe on, grind the coffee, brew it, and serve it, and wages in America should definitely affect the cost of the coffee. It does, but the price of coffee in America definitely doesn’t rise proportional to the cost of labor/utilities/infrastructure in America versus Thailand.

I’m sure better people than I could do more than speculate, but my general theory is that for your average budget price of coffee, variable cost stays fairly low worldwide–it’s not too labor-intensive to make, so as long as you can pay the price of the coffee bean, you don’t have to invest too much in skilled workers to painstakingly prepare the perfect coffee. In Thailand, you pay a little less because the labor and operating overhead are cheaper. But you’re paying a lot for the coffee bean itself in both countries.


Food is domestically produced and labor-intensive

Food is, relative to coffee, a high-labor product. A single barista could churn out quite a few coffees in an hour, whereas a single chef probably couldn’t approach the same number of meals. So when you get a dish of pad see ew in Thailand, you can be sure it took more time to make than a coffee, and you’d expect the price to reflect the higher labor cost.

But you’d also expect the greater quantity and complexity of materials to be part of that price. A noodle dish needs meats, vegetables, sauces, seasonings, and all sorts of other things that require individual preparation and combination.

The big difference is that almost all of these materials can be produced close by, especially since the local cuisine tends to use cheap and available ingredients. There’s no single country exporting rice noodles or kale–the restaurant has access to a much more competitive, local market to source its materials from, and as such the cost of materials doesn’t include higher labor costs in the exporting country or the exporting costs themselves, or import duties, or supplier monopolies, or any of that.

And once you have those cheaper materials, you can use the cheap domestic labor to prepare them. The price is always higher than a cup of coffee for the reasons stated above (food requires more materials and labor), but the profit margin may be fairly similar–it took more labor to make your fried rice, and more ingredients, but both of those were cheap, whereas in the coffee equation only one of those was cheap.

So my basic, and almost definitely flawed, theory of coffee:meal relative pricing in Southeast Asia is this: With coffee you’re buying a little labor and a little of something expensive; with meals you’re buying a lot of labor and a lot of something cheap.

Stay tuned for my New York Times bestseller on the topic.

Some additions given new information

I’ve written a few speculative posts about Thailand–some updates on those, given my new experiences in Laos:

  1. In Laos, currently the poorest country in SE Asia, I’ve been seeing a higher ratio of “Asian  pickups,” and also a larger Korean and Japanese presence in the market in general. This leads me to believe that there are probably factors beyond necessity playing into the high Thai usage of “American” pickups, but the ratio I’ve observed in Laos has still been roughly 3:1 American:Asian pickups, so my guess may still hold some weight. There’s also a lot of Korean and Japanese aid going to Laos, so it’s possible that their pickup preference may derive from convenience over preference. I’m not ready to make this my master’s thesis yet though, so I’ll stop myself short of any actual research.
  2. ATM fees in Laos are about $2 USD, though given relative Lao income, this is still a fairly steep fee. Again, I believe it is only levied on foreign cards. We did once pay $4 since we were unsure of where the next ATM was going to be and we needed cash, thus contributing another data point to the elasticity of demand equation.

Thailand: ATMS and price discrimination

Like Bali, Thailand’s economy is often associated with tourism. In actual fact, the sector makes up about 9.3% of Thailand’s GDP, with manufacturing eclipsing it by quite a bit, along with the financial services industry (Thailand is a stable Southeast Asian economy whose currency, and probably their banking system, is well-regarded regionally, possibly explaining why that sector is doing well). Still, Thailand knows that the travellers from Britain, Australia, Singapore, the US, and other East Asian countries are an important resource, and it’s developed a very decent infrastructure to welcome them. Getting around can either be very easy (for a price) or moderately easy (for very cheap).

One thing that does not come cheap, however, is money. I don’t mean in the traditional economic sense of opportunity cost (you have to give up time to get money), but in the literal sense, that if you want to get money from your bank or credit card, you will have to pay for the privilege. As of October 2017 the exchange rate is roughly 30 baht to the dollar. An ATM withdrawal at any ATM in Thailand, regardless of bank, will run you 220 baht, or about seven U.S dollars.

How do the Thais afford these ATM fees? 220 baht is the cost of four or five meals, seven rides in a songthaew (bus-taxi pickup truck that is actually a great idea), a motorbike rental for a day–it’s a fair bit, especially if you’re earning a median Thai income, which is about 237 USD, or about 8000 baht per month. Two withdrawals would be about 5.5% of your income.

The answer is simply that the Thais do not pay these ATM fees–extra fees are charged only for foreign cards–any nationality. My American and Korean cards were both met with the same charge, and the ATM openly tells you that the fee is for foreign cards. This is a perfect example of…


Price discrimination!

An economic phenomena where businesses charge customers different prices for the same good, dependent on their willingness to pay. Usually it’s hard to pull off, because supermarkets can’t ask for your tax return every time you enter the store and change all the price labels to the maximum they think someone of your income group would be willing to pay.

It’s getting easier of course–online retailers can profile you based on past purchases and other collected data, get an idea of what you’re willing to pay, and change the price on that copy of Capital in the Twenty-First Century all with an algorithm if they want to, and once we all get contact lenses with HUD screens projected in front of us that let us shop in augmented reality, supermarkets could do the same thing.

That’s all in the future though–for now, we’re stuck with price discrimination based on simpler types of profiling, which is where Thailand’s ATMs come in. Charging 7 USD for an ATM withdrawal from foreign accounts is a nearly foolproof means of price discrimination in the country. Here are a few reasons Thailand can pull it off.

First, barely anywhere in Thailand accepts credit cards, especially not at normal levels of buying things. 7-eleven stores have a minimum, I believe, of around 3-500 baht, or at least nine dollars. That sounds easy to meet, but in Thailand that’s four bags of chips, three beers, a coffee, and two or three candy bars–and that’s all for my lowball estimate of 300 baht. That’s not a normal amount to purchase at 7-eleven most of the time.

So because everything from street food to the post office is cash-only, you need it–and as a traveller, you typically run out faster than you think you will due to unexpected expenses or just saying “lets do this cool thing” one too many times. And the only way to get cash is ATMs.

Second, there is absolutely no competition–I’m not sure exactly why all the banks charge the same rate, but the two main possibilities are government regulation (basically a tourist tax) or price-fixing/collusion by cartelized banks. In any case, if you need cash, you’ve got a few banks to choose from and they’re all the same price. I always liked Siam Commerce Bank because it’s got a slick color scheme.

Third, tourists aren’t going to organize and get anything done about this–they’re here for a few weeks, and they want to see some cool temples. They’ll bite the bullet and pay, then forget it until the next time. Elasticity of demand for money among tourists in Thailand is pretty low.

Fourth, Thailand doesn’t need to see tax returns to know what price to charge you–if you come to Thailand, you’re already paying a significant amount for travel, signaling that you’re in a disposable income bracket that will absorb higher prices without a lot of hesitation. Thailand’s tourism sector has a less reputable part that basically makes their entire living off this assumption, and even the more reputable parts hike the official prices (for national parks, temples, museums, etc) way up for foreigners. And of course it’s true–even with the price hikes it’s very affordable for someone like me and my U.S dollars.


Thailand: Guessing why there are so many pickup trucks here

(Correction: written while in Thailand, published significantly after writing :D)

I’ve been in Thailand a few days now, mostly in one southern region called Krabi Province. Yes, we felt crabby, no we didn’t eat crabs. It’s a bit south of Phuket, and while it has a fair bit to offer and caters extensively to tourists, the town is much quieter than its more famous neighbor and has a much slower pace. Staying there during rainy season meant that the town was even more peaceful than usual. It also gave me a chance to see a little more what the pace of life is like without the tourist industry in full swing.

I have plenty of things to say about Thailand already, but a few in particular stood out to me.


Pickup Trucks

This is my first mainland Southeast Asian country, so I’m not sure what the situation is elsewhere, but Thailand has a lot of pickup trucks. Sure, all Asian countries have pickup trucks–they’re very useful. But most that I’ve seen are different. In Asia, pickups to be smaller, less rugged, and much more street-ready than mud-ready. In Korea especially the most popular brand looks more like an oversized vehicle driven by a golf-course maintenance team than it does a typical American pickup.

But in Thailand, at least the south, it’s impossible to watch the street for more than a few minutes without sighting one or five real, 4-wheel-drive, mud-spattered, pickups. Some of them are clearly work vehicles, some of them are taxis–for real, some songthaews (taxi-like vehicles that get you where you need to go on the cheap) are actually modified pickup trucks with a shelter slapped on.

So what’s up? Frankly, I don’t know, because I didn’t take a poll. I have my suspicions though, and they start with infrastructure. Thailand is a wonderful places with plenty of roads–but a fair number of those roads happen to be dirt, and I’d bet that the ones I saw were the good dirt roads. It’s still very much a developing country, and nature is large and in charge. The Thais don’t have the luxury of cute little pickup trucks to the same extent that countries with a bit more asphalt do–they have to go onto some pretty rough roads every day, and if your business involves hauling things around–including people–you need to be pretty sure you can get where you’re going. Thai pickups are probably, in one sense, a symptom of an incomplete road system and a climate that can get very soggy.

Adding on to that, a lot of Thais are still employed in the agricultural sector, and manual labor is still more widespread than service jobs, trades, and professional occupations. Where do you find the pickup trucks? The farms and the worksites. Add to this that road conditions are likely to be a lot worse out in rural and developing areas and you’ve got a need for more muscle than you can get with what I’ve, perhaps unfairly, come to call the Asian pickup truck.

Are road conditions and economic sectors the reason for rate of big pickup ownership in Thailand? That’s a question for a masters’ thesis, but at a minimum, I can guarantee that pickups are common, roads can get rough; and the average employment of the Thai worker tends towards the manual.

Coming up: Thai music is mostly now acoustic covers of western top 40 hits (why?); ATM fees are price discriminating wonderfully; a coffee and a meal here are almost the same price (very cheap); and more!

Singapore: Free economy, flawed politics, and some interesting numbers

Singapore is exactly what you’d expect, but less so. Expensive? Yes, but you can be cheap. Clean? Yes, but not significantly more so than Japanese cities. Strict–draconian even? The signs telling you about fines are plentiful, but so are the people jaywalking and smoking in theoretical non-smoking areas. Efficient? Absolutely, but the bus stop didn’t have an electronic display and the subway made an unscheduled mid-ride stop; Korea had displays everywhere and 100% of my subway rides for the last three years have been uninterrupted. Polished and classy? Yes, but the good parts of the city are the more run-down, semi-gritty ones–and those do exist.

All that said, I enjoyed Singapore much more than I anticipated. I wouldn’t want to live there–I prefer a bit more personal freedom–but as a place to visit it offered a lot of budget-friendly, interesting options and a fairly painless experience getting around

Tangent: Singapore public wi-fi is a real pain

I’m going to get a bit more academic in a moment, but on a personal note I have to complain about the wi-fi situation in Singapore. I didn’t buy a SIM card for my two-day stay, thinking wi-fi would be ubiquitous. It is, somewhat, but only the city-run wi-fi hotspots are really ever open, and every time you want to connect you have to go through the multi-minute process of opening the login page on your browser, entering your foreign phone number (luckily I still had my Indonesian SIM card, or I would have been out of luck), getting a code via SMS, going back to the browser, entering the code, and then finally getting access to a fairly decent connection. You have to repeat this process every single time you want to connect, even if you’ve just moved to one down the street, unless you download the app–which I did, but couldn’t sign up for since I don’t have a Singaporean phone number. For a city called “the most tech-ready in the world” it has pretty horrible connectivity. I’ve had much better luck in most other Asian cities.

That said, here are some stats:

Population 5,600,000
GDP (nominal, 2017) $304 billion USD (37th largest; 39th in PPP terms)
GNI per capita nominal/PPP 2017 $52,000 USD/85,080 (3rd-highest)
Major sectors Manufacturing, business services, trade, finance
Unemployment (2016) 2.1% (not a typo, not an outlier)

Data from the World Bank and–which is an amazing statistical resource that I wish more countries had something like.

I’ll break down those numbers really quick, because they do get interesting. Nominal GDP just means straight-up how much money the goods and services produced in Singapore are worth. Given that Singapore is only 2/3 the size of New York City, it is fairly impressive that it ranks 37th overall–though it is worth nothing that NYC’s GMP (Gross Metropolitan Product) is 1.55 trillion USD–about that of South Korea. Though if you read carefully into that report you’ll notice that this number includes some areas of New Jersey in the NYC metro area–fair enough, but a bit tricky.

The good stuff comes when you see the GNI (Gross National Income) per capita (per person). In nominal terms (how much money a Singaporean citizen earns in U.S dollars), the average Singaporean income is nice and middle-class. In terms of PPP (Purchasing Power Parity, or how much stuff they can buy compared to the rest of us), they’re sitting at a very respectable 85,000 USD, which means your average Singaporean citizen is U.S upper-middle class, right?

Well, we’ll get into inequality later; for now, suffice it to say that GNI per capita is calculated by taking the average of all citizens’ incomes, and Singapore has some rich, rich people. Median income, a more accurate picture of typical incomes calculated by looking at the middle of the distribution, is about 36,000 USD–though this is still hardly anything to sneeze at, and adjusted up for PPP is still excellent. Though you also have to shave off about 20% for CPF, Singapore’s social security program.

In plain words, the average person in Singapore is doing really well, and they can get more with their money than Americans can. Why do bars exist in Singapore when drink prices average 8-20 USD? Because, while it’s still expensive for them, Singaporeans can in general afford those prices.

Finally, unemployment is 2.1%, and that’s been pretty steady for at least a decade–that is insanely low (lowest in the world), and I’ll get to that around the end of the post. For now, here are a few ramblings to break up the numbers stuff.

Strangely Free

As I mentioned in the introduction, Singapore has a reputation for being a bit strict. You’re technically not allowed to bring chewing gum into the country because they don’t want it on the sidewalks. The subway specifically disallows durians (a particularly pungent fruit popular in Singapore). You can’t even buy a beer in a convenience store after 10:30pm,and the laws governing the sale of alcohol on and around public holidays are undoubtedly as irritating to locals as they seem confusing to visitors.

Of course, Singapore’s massive alcohol taxes (a trait it shares with neighboring Malaysia and its neighbor, Indonesia) make buying alcohol a bit unpleasant anyway.

But despite having sin taxes through the roof, Singapore is actually one of the most economically free countries in the world, as ranked by The Economist, Freedom House, and others. Income and corporate tax rates are quite low (someone earning $30,000 USD pays about 2%), and Singapore, being essentially a nation in a single city, doesn’t impose many import duties. Actually, about 99% of all imports enter tariff-free, with the exception of tobacco and alcohol (the fun stuff, of course).

My personal stereotype before learning about it was that Singapore must tax pretty heavily in order to maintain the infrastructure it’s famous for, but oddly enough, it turns out that government spending is about on par with taxes collected. That is to say, Singapore’s government is fairly frugal. So where does all the good stuff come from?

One answer is that a tiny but wealthy nation is a lot easier to manage well than a big wealthy one. They have to manage exactly one subway system, one set of building codes, one police force, et cetera. This enables them to really cut down on budget leakage and misuse and limits administrative gridlock. Centralization does its best work in homogeneous environments.

Singapore is also still fairly young demographically, so it has a low dependency ratio (ratio of people draining the social safety net versus contributing), and high immigration is sustaining that demographic advantage.

State-owned enterprises (the government profits off of shares and ownership in several industries) also bring in a decent profit that add to tax revenue.

And then there’s also the fact that low tax rates still bring in a lot of money when you have a very wealthy population. So overall, it looks like Singapore’s government is having its cake and eating it too, because they only had to make a small, excellent cake, and they had some excellent ingredients to work with.

So why do I say it feels “strangely free?” Well, the overbearing rules that haunt your daily life in Singapore are a symptom of a political system that Freedom House and most other indexes rate “partly free” or “flawed democracy.” You are generally free to do whatever you want in a financial sense, but not necessarily to participate in the political process. Singapore is currently on its third prime minister. Number three. That wouldn’t be so bad if Singapore had begun a decade or two ago, but the history buff will have already remembered that the city-state gained independence from Malaysia in 1965.

One man, Lee Kuan Yew, held the post of prime minister for over thirty years. The new one, Goh Chok Tong, was chosen to succeed Yew and became prime minister in 1990 without a vote, though the one-party system slipped a bit in the parliamentary election in 1991. The third PM, Lee Hsien Loong, is currently in office after being made deputy prime minister simultaneously with Tong ascending to PM. Loong also happens to be Lee Kuan Yew’s son.

Citizens have more say at the parliamentary level but even so, the centralization that makes Singapore such an economically free place still serves to limit how much can be accomplished politically, and how many things can really be changed. Electoral manipulation and political suppression are both still present, and free speech is not guaranteed.

Ethnicities and enclaves/Workers and wages

My absolute favorite parts about Singapore were not the most-photographed ones. Yes, the fancy buildings and harbor views were spectacular, but much more interesting at a human level were the districts of Little India and Chinatown–which are genuinely populated by people from these countries and with these backgrounds, and which exude their own unique vibes at stark odds with the neatly administrated neighborhoods surrounding them.

Singapore has a very large migrant population–Indians, Malays, Chinese, and many more. Some migrated several generations ago and are now full Singaporeans; some are here on migrant worker visas. Currently about 15% of Singapore’s residents are migrants.

70% of Singapore is ethnically Chinese, but unlike China, there really is no obstacle to becoming a citizen provided you meet the other requirements. This is perhaps one of the only Asian countries I know of that is so: it would be laughably difficult for a non-Korean to gain Korean citizenship; likewise in Japan, China, etc. And even if they did–and some have–there is a very strong sense that you are never Korean/Japanese/Chinese if you lack the ethnic aspect.

The official language being English also gives it quite an international feel and makes it far easier for migrants to settle here, as English is widely spoken and practiced by those anticipating a career abroad.

For all their charm and melting-pot sensibilities, however, the ethnic enclaves can put on display some of Singapore’s high economic inequality. They score 49.3 on the GINI coefficient (a 1-100 measure of economic equality, with 0 being exactly even distribution and 100 being “one person has it all”).Of course, the GINI coefficient is flawed as it is highly susceptible to outliers–the more rich people move to Singapore, the higher the coefficient gets because more income is technically now going to the top, and Singapore has an especially high level of super-wealthy people in its population.

This last explanation does tend to be the state’s defense of their GINI score, but it hardly explains away everything. Especially among the migrant worker populations there are high rates of poverty which tend to be ignored. Given that Singapore’s economy benefits quite a bit from these non-citizen workers, perhaps they should be acknowledged a bit more.

That said, inequality is by no means automatically a bad thing, and the fact that people migrate to Singapore for work means that they tend to view it as a step up. The fact is, Singapore’s median income is excellent, and the standard of living there tends to be very high; both ends of the spectrum exist, but on the whole the average Singaporean is doing well enough.

Unemployment? What’s that?

Perhaps one of the most interesting aspects of Singapore is its freakishly low unemployment rates–they’ve hovered around two percent for quite a long time, which is far below the roughly five percent that most health economies tend to be at. Frankly, if you get too far below five percent for too long you end up, among other things, not having enough qualified workers available to fill open positions, leading to economic slowdowns as firms struggle to grow or even maintain their labor force.

So how’s Singapore, this crazy economic outlier, actually doing it?

One reason is already listed above–immigraton. Singapore has a fairly flexible workforce, and in fact the unemployment rate for residents only tends to be higher than that of the entire population, since temporary/non-resident workers tend to leave altogether if they lose their job.

They have also experienced pretty much non-stop economic growth, and with economic growth comes jobs.

So no extremely well-organized central planning committee or cultural work ethic necessarily–just immigrants and growth.


My advice for those visiting Singapore: eat at the hawker centers (it’s so much cheaper), take a break from the alcohol, visit the photo spots, and make sure you check out the parts of Singapore that don’t match up with the myth. And while you’re there, go ahead and contemplate the successes and paradoxes that underlie Singapore’s safe, smooth exterior.