# On Exploitation and Thin Markets

Exploitation: a word so overused by the political Left, so ignored by the political Right, and so misunderstood by both sides. A straw-man attack against capitalism that is so often so poorly defended by Libertarians (myself included). That all said, this is an important issue that demands a reasonable response from Capitalists, rather than talking past the often valid concerns (with completely unrealistic solutions) of the Left and attempting to turn the problem around on Government as the exploiter (which can and often is the case, but not in the ways the Right likes to claim). This is an attempt to both consolidate my thoughts about exploitation from an ethical/morality perspective, and also attempt to reconcile my free-market ideology with the fact that unregulated firms can and will find ways to exploit consumers.

# What is Exploitation?

First, we have to start with the basics: What is exploitation? According to Rebecca Kukla at the Kennedy Institute of Ethics, the broadest definition of exploitation is simply one party “taking unfair advantage of someone else” (see her video clip on Exploitation for EdX). She goes on to clarify that exploitation is not coercive. Coercion is something else entirely for the purposes of ethical and economic discussions. Instead, the decision made by the exploited party is voluntary and can still make that party better off, but the available alternatives are themselves very unattractive as well. In the terminology of Dr. Mike Munger (Duke University), the choice is voluntary, but not euvoluntary (or voluntary the way we think of voluntary in common vernacular and economic assumptions). This could be because the exploiter has somehow limited the available choices or not, though there should be some exclusion for natural consequences of poor decisions–e.g. It’s not exploitation for a spouse to make an ultimatum after the other partner was caught in an affair. In any case, the exploiter benefits from the fact that the exploitee has extremely limited/poor available alternatives.

Taking the example of sweatshops, it’s true, as most libertarians like myself are quick to point out, that the workers are free to take other jobs if they can find them and are remaining employed voluntarily. It’s also true that manufacturing, even in the horrible conditions that many manufacturing workers face, can lead to substantial improvements in well-being, particularly in the next generation. And it’s true that the sweatshop owners do not adequately protect their workers, treat them more like capital than people, and continue to pay exceptionally low wages (to keep prices for Americans low) because they know their workers don’t have any better alternatives. In other words, these manufacturers are profiting off the fact that these workers were born in a place with few economic opportunities. Furthermore, they are benefiting disproportionately more than the workers (who are still receiving a perceived net benefit). Therefore, I think it’s fair to say that sweatshop owners are behaving in an exploitative manner.

Although sweatshops in developing countries make for great examples of exploitation, I want to focus on more first world problems, because those are better for highlighting different policy approaches to prevent, or at least mitigate, exploitation.

# First World Problems (That aren’t exclusive to the developed world)

## Low Wages and Benefits

Although Donald Gracchus Trump managed to turn the conversation of the election away from policy and towards his Twitter feed, Bernie Sanders seemed poised to try to make minimum wage a key point in his platform had he gotten more news coverage. By no stretch of the imagination are minimum wage workers in the US being exploited like sweatshop workers in third world countries, but it is true that companies like WalMart, McDonalds, Burger King, KMart, etc. play legal games with part-time vs. full-time employment and other tactics to avoid paying benefits, avoid paying overtime, prevent employees from gaining the needed human capital to get promoted, underhandedly push people out, etc. All of this takes advantage of the fact that most of their entry-level workers don’t have better options; if they did, they probably wouldn’t be working in entry-level retail or fast food. In this way, there is a level of exploitation going on. Proportionality is also something to consider: a high schooler working at minimum wage is gaining valuable experience and resume building beyond just the paycheck; the 30-something single mother is not benefiting from this job as much as that teenager, but needs it more. Therefore I don’t think paying entry-level workers minimum wage and working them part time is inherently exploitative, but it can vary based on the situation and future prospects of the worker. As an aside, while I don’t believe the ratio between CEO salary and entry-level workers is meaningful metric, I also don’t really buy the “maximize shareholder value” argument since economic fundamentals have a very limited role in stock price, and it is true that most of these companies would still be profitable if they didn’t play these employment games.

## Price Gouging

In the wake of storms and other natural (or manmade) disasters gasoline, generators, water, ice, etc. become in very high demand and the supply of these things is either fixed or falls, so Econ 101 supply and demand models suggest that the prevailing market price will spike up to equilibrium. And it typically would, except most states have anti-gouging laws, and Governors and Mayors love to tout their enforcement of these laws in the wake of such an event. Of course, jacking up the price of something right before everyone in town needs it (e.g. Bottled water) does feel like kind of a dick move, and liberals in general tend to have a visceral reaction that this is wrong and exploitative: “what about the people who can’t afford the higher price?”. Take this practice to its logical, even if hypothetical, conclusions, and you can have stores arbitrarily upping their prices the night before a storm (as Russ Roberts does in his book, The Price of Everything) or resellers buying up all the bottled water in an area before a storm and reselling it after the storm for a substantial profit–effectively arbitraging across time. Such price hikes or intertemporal arbitrage can make a very large profit as a result of others’ misfortune, and there’s always something a little ethically uncomfortable about that.

## Captive Markets

In what can be thought of as a very particular form of Price Gouging, we have Captive Markets. In cases where a provider of a service (usually) has a secondary product (usually food or drink), they can create a local monopoly for that product: if you (voluntarily) buy the service they provide and would like to (voluntarily) buy the ancillary product, then you must buy it from the service provider at monopoly prices. For example, after jumping around in a mosh pit at a rock concert, you must buy water from the venue; when seeing a movie, you can only buy popcorn and soda from the concession stand in the theater. Other classic examples of Captive Markets include food/drink on planes, trains, and boats, college textbooks, and food/drink at sports events, or really any place you go to for a reason other than food, can’t leave easily, and can buy food at (but bringing in outside food is banned or discouraged). Captive Markets are localized monopolies, so they tend to charge the monopoly profit maximizing price as opposed to the (much lower) market price. In this case, this is exploitation because your options are very explicitly limited by the supplier of the primary service (even though that primary service is still competitive).

# The Wrong Approach

Exploitation is unethical, and while it can range in severity from degrading human dignity at it’s worst to be merely being a dick thing to do at best, it’s in the interest of society to prevent exploitation as much as possible and provide a legal recourse for the exploited when we can’t prevent it. Unfortunately, most proposals I hear (from the Right and the Left, but mostly the Left), would not, in my estimation, actually work.

## Teach People to be Nicer

This is really more of a general comment about policy, but it’s a good starting place for this conversation. Any solution that relies on people doing the right thing, even the wrong thing (ethically speaking) is more profitable and difficult to prosecute is going to fail. You can wax all you want about how people should be more loving and less motivated by money, but that won’t change the hearts of humanity. To quote Milton Friedman, “I do not believe that the solution to our problem is simply to elect the right people. The important thing is to establish a political climate of opinion which will make it politically profitable for the wrong people to do the right thing.” Even though most people, most of the time, aren’t out to get you, a few bad apples will spoil the bunch and break down the system.

None of the games employers play to avoid paying employees benefits (e.g. Health insurance) are illegal, which is why employers play them. After the ACA mandated that employers offer health insurance for workers who worked at least 30 hours a week, many employees saw their hours cut to 29 hours a week. Many democrats responded by recommending that the threshold be changed to 25 or even 20 hours a week. Most Republicans just ignored the issue or pointed to this as evidence that the entire bill is flawed, but I did hear one congressman (I don’t remember who) actually give an intelligent response: We should increase the cap to 40 because no matter what threshold we set, large employers’ legal teams will find a way around it, but at least if the threshold is 40 instead of 30, hourly workers will get an extra 10 hours of paid work. The specifics of this policy aside, this congressman understood that you can’t legislate that people do the right thing.

## Ban It!

### Unequal distribution

“A rising tide lifts all ships.” At least that’s the rhetoric that’s used. And to a degree, it’s absolutely true: innovation is knowledge, and knowledge is a non-rival good. The rising economic tide increases innovation and the body of knowledge available to society. However, economically, some ships are lifted more than others. While the income distribution of households is becoming (relatively) flatter, the income distribution of individuals is more skewed. Inequality in-and-of itself is not, in my view, inherently a bad thing; I want to live in a world where Bill Gates and Sergey Brin are filthy rich after creating products that improve the lives of billions. However, if growth benefits primarily the haves and the have-nots only see the downsides, is growth such a good thing for the majority? What good is growth, then, if it benefits many, but leaves many more desiring and building up credit card debt in pursuit of more, because they can, even when they don’t need to?

## Why Growth is Still a Net Positive

Economic growth is often thought as a unidirectional thing. After all, we see GDP growing over time on an x-y scatter plot.

(Source: FRED
)

But what composes that GDP can change dramatically over time. Preferences shift, societal needs change, and the pie-charts that show the composition of the workforce and goods and services can change dramatically. Growth can be multi-directional and multi-faceted.

For example, what is a normal good? By economic definition, a normal good is one where the demand for that good increases with income. The classic example for normal goods is high-quality foods: as we make more money, we want more of the meat half of the meat and potatoes diet. This is not to be confused with a luxury good, where quantity demanded increases with price–as we see with wine, fashion, and yachts. As Cochrane points out, some non-conventional normal goods include things like civil rights, environmental conservation, and self-determination.

### Environmentalism as a Normal Good

Next time you see someone working hard at minimum wage, ask (or just think about, for the shyer among you) if s/he buys energy-efficient lightbulbs or just the cheapest ones available. If they’ve done the math (and most people on that tight a budget have), they’ll probably tell you that they buy whatever’s the cheapest, which is probably not the energy efficient bulbs. When you’re living at the poverty line, you’re not particularly interested in the environmental consequences of your actions; your interests focus on putting food on the table. Concern with the environment and expensive products that are more “environmentally friendly” are normal goods: demand increases with income.

By all accounts, the Industrial Revolution was horrendous for the environment. However that fact does not attenuate emerging nations’ desire to reproduce the same thing in the least. It’s worth noting that John Muir and the Sierra Club didn’t emerge until after the Industrial Revolution had done its work: both in terms of economic growth and damage to the environment. Caring for future generations will, by human nature, always be secondary to caring for the humans alive today, in whatever form that takes. Only when the humans alive today are well-taken care of, will the focus really begin shift to future generations, because caring for nature and future generations is a normal good.

### Anti-Consumerism as a Normal Good

What about Palahniuk’s indictment that growth is just fueling that which truly does not matter? As previously posted on this blog, I have a general sympathy of sentiments with the Minimalist philosophy/movement. Given that consumption spending makes up approximately 70% of GDP, minimalism would, on the surface, be diametrically opposed to growth for growth’s sake. But when you dig deeper, it’s not.

What is consumption? When you look at the formula for GDP, we have this monolithic ‘C’ for consumption in Y = C + I + G + NX, where Y is (nominal) GDP, C is consumption, I is investment (which includes corporate capital outlays and residential mortgages), G is government spending (not including transfer payments), and NX is net exports (exports minus imports).

Minimalism is about living a meaningful life. The focus of minimalist thinkers like Joshua Becker, Joshua Fields Millburn, Ryan Nicodemus, Leo Babauta, and others is that mindless consumption of stuff gets in the way of self-actualization. And this is (in my experience) true. However, part of this claim is that experiences are more important than stuff, which is also true–when is the last time you thought about Christmas traditions with your family and when’s the last time you thought about that high-school yearbook you’re inexplicably holding onto? So what about that ‘C’ part of GDP? Consumer purchases are built up of two things: Goods (stuff) and Services (experiences).

Suppose that tomorrow, everyone were to become a diehard minimalist. The Goods part of that identity would fall, but the services (read: experiences) would compensate. Minimalism isn’t just about cutting spending; it’s opposed to unnecessary spending on “shit we don’t need” and replacing that with life experiences–preferably free, but more importantly meaningful.

From the perspective of economic growth, this is great. Growth is about productivity increases, and Minimalism makes people happier, and therefore more productive (in the general sense, not necessarily in the corporate human resources sense). More to the point, when looking at growth in Y (GDP), Investment and NX can, and should, rise, holding C and G constant. So growth does not necessarily–even if it historically has–increase consumption. The more important pieces is I: Investment. Less frivolous spending means more saving. This means more  money available for investment, lower interest rates for firms looking to expand (particularly expand their non-frivolous divisions), and higher standards of living in retirement (including more consumption). According to the Solow Growth model, increased savings will, indeed, cause a short dip in GDP, but increases growth and growth potential in the long run.

### First Principles: Adam Smith

Investment includes, among other things, increasing employment. Going back to first principles in Book 1 of An Inquiry into the Nature and Causes of the Wealth of Nations, when a resource is scarce (i.e. Demand is higher than supply) employers are willing to pay more for that resource, including labor. When the economy is in the upswing of the business cycle, employees (excluding public employees) get raises. More importantly, when the economy is growing, employers compete for employees, meaning that workers can change jobs (relatively) easily, and find a job that helps them to thrive–reaching self-actualization by challenging and growing them as a person. Workers can find the “right fit” of a job much more easily as a result of growth.

As a corollary, Research and Development is a normal good, and when firms are growing they are more likely to boost investment in this division. Similarly, startups–i.e. the the drivers of innovation–are able to get funding and capital during times of growth, much more so than during the trough of the business cycle. Moreover, startups are more successful–and therefore more influential–during times of growth. When the economy is growing, we’re learning more. We’re developing new technologies, new products, new processes, and increasing the pool of societal knowledge–even if, for a time, some of that knowledge is proprietary; knowledge never stays proprietary forever.

### Dynamism

In short, growth means dynamism. The Oxford English Dictionary defines dynamism as the quality of being characterized by vigorous activity and progress. Economic activity really just means transactions or interactions. When the  economy is growing quickly, the number of potential interactions increases:

• number of job openings, and the number of applicants willing to apply
• Venture capital availability and appetite for risk
• New products and services, and new consumers

When the number of interactions increases, the potential for mutually beneficial or euvoluntary exchanges necessarily increases.

When these exchanges are in goods and services, we benefit a little–new services, experiences, and useful tools. When these exchanges are in the labor market, we benefit a lot. People who are happy in their jobs are more productive, meaning increasing future growth. People who are happy in their jobs are (generally) happier in their lives overall. The extra monetary income we see from growth is nice, but money isn’t everything. More important than real income is the availability of opportunities for personal growth, advancement, thriving, virtue, and self-actualization. You can’t buy any of these things, no matter how high your income is, but they are still normal goods, and a higher income allows you to shift focus from merely surviving to truly living.

Dynamism isn’t just about increased sales or incomes, it’s about increased opportunities for change. Workers stuck in a dead-end job have more opportunities to find a new job when the economy is growing. New products emerge. Some of these are superfluous and engender the kind of mindless spending minimalists hate, but some legitimately make people’s lives better off–for example, digital pills to monitor drug regimen compliance, side-effects, absorption, and effectiveness. Dynamism is about new ideas bouncing off each other, about new people coming into contact with those ideas, and about competition doing what competition does best: forcing everyone to implement new technologies to provide better goods/services at a lower price. Economic dynamism is how we go from the abstract economics to the concrete improvements to people’s lives. And growth is what makes dynamism possible.

## Concluding Remarks

Among the works of man, which human life is rightly employed in perfecting and beautifying, the first in importance surely is man himself.

Ultimately, the goal of Economic advancement is human thriving. Economic growth and the dynamism it creates is the most effective way of increasing human thriving sustainably. Yes, it can have downsides. But ironically enough, more growth can also be the cure for downsides from previous growth. Admittedly, this is a little like saying that more alcohol can cure a hangover; it sounds a little insane, but enter the Bloody Mary. Also, would we ever have widespread solar and biodiesel energy without innovation? Economic growth has afforded us the opulence to care about the environment, the well-being of the poor in other nations, and other things that were far from the minds of our forebearers. The benefits of growth are agnostic to where that growth comes from. If we continue to “grow” by buying “shit we don’t need,” then growth will remain lackluster, and even if it doesn’t, we will remain lackluster. If, on the other hand, we grow the economy by growing ourselves, making ourselves more productive–and more interesting–then that will have very different outcome. Economic Dynamism comes from growth, and is what allows us to reinvent–or just tweak–ourselves to become happier, healthier, wealthier; without adversely affecting our fellow human.

## Bibliography

I originally wrote this with footnotes, but they didn’t copy over from Google Docs to WordPress. I may add them back in later, but here’s the list:

# OmniFocus 2 vs. Todoist vs. Outlook

Tags

Like all entries on this blog, it will come as no surprise to my readers (who, according to wordpress analytics, virtually all know me) to hear that I have a fond curiosity for dabbling and experimenting with task management tools. Recently, I’ve been experimenting with Todoist as an alternative to Outlook as a task management system. To my surprise, I actually found it even more useful than I was expecting, and decided to do a head-to-head against OmniFocus, my current GTD weapon of choice. So how do these three systems work, and how do they stack up?

# Background and Requirements for my GTD Trusted System

I’m currently writing this post on a Mac, but my work laptop is a windows computer, as is my personal laptop (although I would love an Airbook, I just can’t justify the price, and the windows laptop made sense for my computing needs at the time). One of the core tenants of GTD is that everything is in one system. When I bought OmniFocus, I wasn’t that concerned with this, since I wanted to keep my work life and home life separate. However, as I did more work (projects done for personal edification) split between my (PC) laptop and (Mac) desktop, my “system” started to fracture. I was using OmniFocus on my phone and desktop, outlook on my work laptop (which was, as expected, almost exclusively for work), and trello to piece the rest together, including on my iPad (see pricing section below) and personal laptop. It worked, but it was fragmented.

When I decided to try out Todoist, the primary driver was that I needed a better way to track projects, particularly small projects. Trello works really well (in my opinion) as a master project list and it even does a passable job as a project management tool for large projects. However, it gets very cluttered very quickly when you try to use it as a task management tool (i.e. all the unique next actions), especially when you include small projects of only 3-5 actions. Outlook is even worse. Outlook’s task list is useful only in that you can quickly turn emails into tasks using quick actions. However, Outlook completely lacks the concept of a project, and the only way of grouping tasks is using categories. Since I often have a lot of different projects going at once, this is completely untenable for me. What I wanted was a nice way to have sub-actions within subprojects, like I can do in OmniFocus on my Mac. Ideally, this should be available no matter what: home, work, in transit, whatever. Enter Todoist.

How did Todoist stack up to the other two?

# User Interface and Look-and-Feel

## Outlook

Being part of the Microsoft Office Suite, Outlook is familiar. Hell, it’s where I spend at least 2-4 hours every work day, so the email portion (and subsequent task portion) is clean, familiar, and very customizable. You can change the columns and information shown for each next action. Besides the normal MS ribbon at the top, the overall space is very clean and you can very easily switch between different views. Of these three tools, Outlook is definitely the most customizable.

## OmniFocus

Somewhat to my dismay when I first bought it, OmniFocus for Desktop feels cluttered. In an effort to highlight/bold information that really matters right now, they put other information (like project, context, etc.) in a light gray. Far from actually honing the eye in, this looks like a block of text. Also, the fact that they consider “due soon” as “within 24 hours” means that things that won’t be actionable until tomorrow show up now as yellow, even though they aren’t actionable right now.

Where it’s most cluttered/cramped though is the side panel that shows the details for each action. First of all, I have to scroll to see the notes section. Second of all, the note is very cramped, inconvenient, and can’t really contain any useful attachments. The due dates and whatnot are very useful, but not very useable and are very click-heavy.

On the positive side, there are a good number of shortcuts for switching perspectives, quick entry, and other tools to make using OmniFocus on the Desktop and on the iPhone very easy to use.

## Todoist

Of these tools, Todoist has hands-down the cleanest display. Labels only show when needed/specified (unlike OmniFocus’s contexts, which are omnipresent). The comments section is large and easily accommodates some stream-of-consciousness work and updates.

Like OmniFocus, it’s got a fairly click-heavy UI, but Todoist does allow more keyboard use when assigning due dates to new actions, which can save having to move your hand back and forth between keyboard and mouse with each task.

Where OmniFocus’s UI excels at displaying the same information in different ways, Todoist’s UI excels in its simplicity and the ability to jump between different projects and display different information in the same way.

# Features, Kludges, and Bugs

## Outlook

As previously mentioned, you can create tasks out of emails using quick actions. That’s really the only feature worth mentioning, because Outlook Tasks is really just a to-do list; it’s not a fully-fledged task management, much less project management tool. Quick actions, while useful, are a bit buggy in that the order of operations is not always respected, meaning that my categories don’t always take automatically

## OmniFocus

Of these three tools, OmniFocus seems to have the most features, and some of the most powerful features. Most notably, OmniFocus has the ability to defer tasks and has a robust concept of sequential tasks. In this example, Scan Wedding Cards is the next action I need to take for this sub-project, and the later actions, which are dependent on the first action, are listed as “remaining” but not “available” and can easily be displayed or hidden depending on the perspective.

Not only is this useful for projects with long time horizons, but it’s extremely useful for recurring actions that only happen 2 or 3 times a year, like scheduling a dentist appointment or changing the furnace air filter. Ideally, I want to forget that I have to do these things at all until the time comes to do them. If I accidentally think about these things, I can rest assured that my task management system has it covered. This “defer” feature can somewhat be replicated in other systems, but it’s not native the same way it is in OmniFocus.

The other feature I really love with OmniFocus is the weekly review. On a weekly basis, OmniFocus (for desktop only) allows you to quickly look at every remaining project, regardless of status, to make sure that the status (active, waiting, or on hold) is appropriate and the due dates are well defined.

On the negative side, OmniFocus desktop has a really annoying bug where if you complete a recurring task, it will automatically generate the next task, but if you un-complete and then recomplete the original action, it will re-copy the recurring action for tomorrow, creating a duplicate recurring series. Also, OmniFocus recurrences aren’t smart enough to “jump ahead” if you miss a day. Also, as mentioned, the notes section feels like an afterthought and is very limited in tools.

## Todoist

In many ways, I think Todoist’s biggest features are the UI and its ubiquity. Todoist is available on iOS, Android, OS X, Windows, and online. It also has plugins for CloudMagic (my email tool of choice for my apple devices) and Outlook (my mandated tool at work). The UI makes entering dates exceptionally easy compared to OmniFocus; for example I can enter things like “every weekday” or “next Thursday” and it will set the date appropriately.

The other particularly cool/unique feature of Todoist is the Filters functionality (premium only), which, if you’re reasonably comfortable with Boolean logic and are willing to put in the time setting them up, can replicate many (though not all) of the features in OmniFocus that Todoist lacks (like the defer feature).

# Organization and Structure

## Outlook

It’s a barely glorified to-do list. Tasks can be grouped by priority, due date, created date, or category. However, you can’t layer subtrasks within other tasks and you can’t group by combinations of categories.

## OmniFocus

Folders can contain projects, which can contain tasks, including sub-tasks, which may have their own sub-tasks. I love this level of nesting, since my brain tends to think in outline form, but being a mediocre developer, I don’t like it when my subroutines start getting more than 4 levels deep. Fortunately, OmniFocus can be configured to mark a sub-project complete when all the tasks within that sub-project are completed. I know it only saves a single click, but this is very nice.

## Todoist

Todoist is similar to OmniFocus with the multiple layers of projects, but instead of folders they have parent projects. Again, the nesting for the projects and the actions within the projects can, in theory, go on for a while, but I think 4 or 5 layers is probably the maximum you should ever do. In this screenshot, we just show the “projects” and the parent projects. We can also have tasks and subtasks in the main task window.

# Pricing

Finally, there’s pricing. Outlook comes as part of a package with the ubiquitous Microsoft Office, so let’s call that more or less free. Todoist has a free version that may work quite well for many people, but people with multiple roles or who want to compartmentalize work, home life, and personal edification would do well to purchase a premium subscription and use filters.

On the whole, OmniFocus and Todoist are fairly similarly priced:

• OmniFocus is priced on a software-as-a-product model with a different price per platform
• iPhone: $20 • iPad:$30
• OS X: $40 for the basic,$30 for the student version, and $70 for the premium version • Todoist is priced on a subscription model, at about$30 per year and is available on all platforms (including online) after that.

So assuming OmniFocus releases a new version ever 2-3 years and you purchase the basic model on all platforms, both will run you just under $100 over 3 years. OmniFocus can be a bit more expensive, especially for the professional/premium version, but again, it does have the richest features. # Conclusion As mentioned at the beginning, I have computers on multiple platforms, and I really want to consolidate my entire list of next actions—personal and professional—in the same place. To do that, I’ve chosen Todoist. Todoist has a nice outlook plugin, which makes it integrate seamlessly with my work email (which was the only advantage of Outlook tasks in the first place), and it’s available on my apple and PC devices. I’ve got my four different goal areas (think somewhere between 20 and 30 thousand feet in the GTD Horizons of focus model) listed as parent projects, with projects (10 thousand feet in the GTD model) delineated as appropriate underneath the parent project. Todoist has a built in view for “Today” and “Next 7 Days,” which are useful starting places, but I’ve created separate filters based on parent project (so far broken up broadly to “work” vs. “non-work”) to display only the sphere of tasks I care about right now. We’ll see how this works out, but for now, I’m quite happy with my switch, particularly if I can come up with a viable way of “deferring” tasks like I could in OmniFocus (current strategy is to just dump them in a “long term recurring” project, though that is, admittedly, not ideal. Others have used a combination of filters and labels, but since labels don’t get automatically added or removed, this would require some complicated filters that I just haven’t gotten around to caring enough to write. Let me know what you think. And with this, I’m going to cross off my next action in Todoist. (The Blog Posts project lives under the “Personal Edification” Parent Project in my system.) # Where is the Middle Class Going? ## Background and Data Source We’ve heard for quite some time that the middle class is in crisis and shrinking. But what to do the data say? Is the middle class in crisis? Where is the middle class going? What does that crisis look like in the data? Data for this exploration comes from the Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC). The CPS ASEC is a longitudinal survey of 50,000 households conducted by the US Census Bureau1. Despite the relatively small sample size (<1.5% of the population), this dataset is regularly used for income analysis and other demographic trends. Data were downloaded and pulled into R using code from All Survey Data Free from Anthony Damico2. ## Data Scrubbing Data were processed using the same steps as Pew Research Center’s 2015 report, America’s Middle Class is Losing Ground6. First, CPS ASEC data for the years 2000, 2005, 2010, 2015 were downloaded into MonetDB. Second, Total Income3, was adjusted for inflation to 2015 USD using the getSymbols function from the quantmod package4 to get Consumer Price Index (CPI) data from the Federal Reserve of St. Louis. Finally, household income was adjusted for household size. Intuitively, we know that when two people live together, their household income is the sum of each individual’s earnings. However, many expenses (most notably housing and utilities) are shared, so a household of two does not have double the expenses of a household of one. To adjust for this fact, the standard procedure is to divide total household income by the square root of household size5. In other words, a two-person household is assumed to have 1.41 times, rather than 2 times, the expenses as a one-person household. After income was standardized across all households in the dataset, income class was calculated using the definition used by Pew Research Center6: middle income is 2/3 to 2 times the median, adjusted income. Anying above two times median income is considered “upper” income, and anything below two-thirds of median income is “lower” income. This is distinct from lower, middle, and upper class, which has a wealth component in addition to income as well as connotations of lifestyle6. This is still a relatively crude measure since it does not account for cost of living, but it is useful for a broad-strokes analysis. ## Exploratory Analysis First, like Pew6, I found that the middle class is shrinking, at least in terms of people living in each income class. These proportions are slightly different than those found by Pew6, but they show the same general trend and are therefore close enough for my purposes. My larger interest is to look more in detail at how the distribution in income is changing. We can see that income is, as it always is, heavily skewed to the right, but the distributions are not identical year-to-year. ## Difference in Density Analysis ### Theoretical Construction and Example The question I want to answer is where the middle class is going. To some degree, this is answered by the above graphs showing the proportions of adults living in each income category, but I’m asking a further question: which incomes levels are more–and less–prevelent than they used to be. Conceptually, I want to zoom in to see the gaps between the density curves curves. Since this is something of an unconventional way of visualizing data, let’s start with a proof-of-concept example. First, we will take random samples from a uniform and a Gaussian distribution and graph the density functions of these two samples on top of each other. set.seed(100) #Set the seed #Get two random samples sample1<-data.frame(x=runif(100,0,2)) sample2<-data.frame(x=rnorm(100,1,.33)) #Convert these random samples to density distributions dist1 <-density(sample1$x,from=0,to=2)
dist2  <-density(sample2$x,from=0,to=2) #Put these density functions into a dataframe df1 <-data.frame(x=dist1$x,y=dist1$y) df2 <-data.frame(x=dist2$x,y=dist2$y) #Plot these density curves ggplot() + scale_x_continuous(limits=c(0,2)) + geom_line(data=df1,aes(x,y),size=1.4,colour="blue") + geom_line(data=df2,aes(x,y),size=1.4,colour="green") + geom_hline(yintercept=0)  As expected, we can see the sampling from the uniform distribution (blue) is more densely populated at the ends of the range and less prevalent around the mean. We can quantify these differences by looking at the differences in the density curves. For example, at x = 1 the normal density curve (green) is 1.214 and the blue curve is 0.57 making green 2.128 times as dense as the blue population at x = 1. To visualize this and see these differences in clearer relief, we can create a difference-in-density curve (no longer a density curve, because the difference can be negative). When we graph this difference curve, we can highlight the sign of the difference in density to see which population is higher or lower, and easily visualize the magnitude of these differences. As this is a comparison, we must have a base population and a comparison population where the resultant density curve is density(base)-density(comparison). In this case, blue (uniform distrubtion) will be our base population and green (normal distribution) is the comparison population. #Build a Dataframe with the difference in densities df3 <-data.frame(x=dist1$x,y=dist1$y-dist2$y)
#Graph it
ggplot() +
scale_x_continuous(limits=c(0,2)) +
geom_line(data=df3,aes(x,y),size=1.4,colour="black")   +
geom_area(data=subset(df3,y>0),aes(x=x,y=y),alpha=0.5,fill="green")+
geom_area(data=subset(df3,y<0),aes(x=x,y=y),alpha=0.5,fill="red")+
geom_hline(yintercept=0)

Now, we can see not just where in our x range the blue population is more prominent than the green population, but also the magnitude of these differences, the latter of which is harder to see when the two density curves are merely juxtaposed. As we’ll see later, we can calculate the area under the curve for different sections to quantify the relative magnitude of each difference between the base and comparison densities.

### Difference in Density in Income

Let’s apply this same methodology of differences in density to income distributions over time. Since this methodology necessarily requires a base year and can only compare two distributions at a time, we will use 2015 as our comparison year, and look at where household income has increased/decreased in relative to the base years of 2000 and 2010.

As expected, the proportion of middle income households is smaller (read: negative relative density) in 2015 than in 2010 or 2000. But where are those households going? As seen by the green on the far left, we can see more households living with $0 or ultra-low income. But the$100,000 to $200,000 range is far more common in 2015 than either base year, indicating that we also have more households in the upper income echelons. Calculating the areas under these curves, we can compare the size of the shifts to upper and lower echelons. Comparison of relative increases to lower and upper echelons from base year to 2015 baseyear lowerGain upperGain timesGain 2000 1.3e-06 1.51e-05 11.737 2010 6.3e-06 7.90e-06 1.258 lowerGain and upperGain columns are the areas under the positive portion of the difference in density curves where income is less than$50K (lower) or between $50K and$200K (upper). timesGain is the ratio between upper echelon increases and lower echelon increases.

## Economic Interpretation and Explanation

In the final column of the above table, we see that since 2010, 25% more households moved to upper income than moved into lower income. Note that this is a cross-sectional analysis, so we cannot comment directly on which households moved or other characteristics about those moves. There is some evidence that part of the gains to the $100,000 to$200,000 income levels came not from the middle income group, but from declines in the highest income earners. That said, particularly when we look at the last 15 years (base year 2000), we can see the relative shifts are far more (11 times) in favor of large opulence than poverty.

What do these graphs tell us? First, I think the hyperbolic notion that those evil, billionaire CEOs are taking all the money away from the middle class is solidly debunked by the substantial growth in the proportion of upper middle income households. Are the ultra-rich becoming richer while the mega-rich retire and don’t get replaced by burgeoning young professionals? That conclusion could be supported by the data (note the blocks of red above $250,000 annual income indicating decreases in that level individual, household-adjusted incomes in this range are less prevalent in 2015 than in the base years), but it is certainly not the only explanation. But what else is going on to explain these findings? Looking at the demographics, We can see some notable differences: most notably, is the number of workers per household. Pairwise T-Tests show statistically significant differences between all the socioeconomic income levels. However, the substantive difference seems to be the number of workers. Lower income households tend to only have one worker, though the average number of adults across income classes suggests that these are not, on average, a single parent as a single earner (though it is significantly and substantively more common in lower-income households than middle or upper-income households). On the other hand, upper income households have, on average, 2 or more earners. In other words, both the average and median households are better off in 2014 (the income year reported on in the 2015 survey) than they were in 1999 or 2009. However, a large part of that is due to the wider trend of two-income households and other demographic shifts5. This larger trend explains some of the shift between 2000 and 2015, but we can see that this cannot be the full story, since the average workers per household (and all other measures of household size) actually falls between 2010 to 2015. Unfortunately, I need to end my investigation herea, so I will delve into that question at a later date. ## Conclusion Yes, the middle class is shrinking. Inequality is real, as is poverty. CEO pay has exploded since the mid 1990s7. This is all true. But whatever the populists say, this does not mean that everyone is suddenly going to be subjugated to the ultra-rich. The median and average households are still doing okay. There are demographic shifts–lower fertility rates, higher cohabitation, higher divorce rates, lower/later marriage, higher rates of children living with parents longer, etc.–and these demographic shifts go a long way to explaining a growing proportion of upper middle income households. Whether these are good shifts or bad shifts depends on your values and worldview, but economically, they are preventing household inequality from rising. This all implies that maybe, just maybe, free market capitalism is doing what free markets do best: expand opulence for more people than are harmed by free trade and free markets. This is not to say that everything is perfect and rosy. Obviously, there are serious social challenges facing America today, and inequality has complicated and real ethical and moral concerns. However, the populist nightmare that the middle class is becoming poorer to the benefit of the upper classes of society does not appear to be one of those challenges. # Appendix A: Future Directions For better or for worse, I’m a busy guy, and this is–for now–just a hobby. I hope to add to this investigation as I have time, but in the meantime, I encourage readers to fork my repo and add some of the following adjustments and considerations I wish I had time to include: • Adjustment for Cost of Living, or at least calculating median (and therefore class) by region or FIPS code. This will almost certainly require a new, larger dataset, but is worth exploring given the urbanization of millenials. • More robust ways of accounting for household size generally. • Identifying the same households over time to track changes to income class. # Appendix B: Code All code is available on Github at github.com/dannhek/income_distribution. Below is a scattering of key pieces of code. #### SQL Query used to get a subset of the data from MonetDB #Retrieve Data from MonetDB SQL Database using dbQuery query2015 <- "select h_idnum1 ,h_year ,max(hwsval) ,max(htotval) ,max(h_numper) ,max(h_numper-hunder18) ,sum(case when earner=1 then 1 else 0 end) from asec15 where htotval > 0 group by h_idnum1,h_year" df2015 <- dbGetQuery(db, query2015) #From BuildHHCSV.r #### Variables used in analysis R_Variable_Name ASEC_Variable_Source Variable_Description X N/A Observation counter year h_year Survey year (Data reflect previous calendar year earnings) h_id h_idnum1 Household Identifier h_wages hwsval Household income from Wages or Salary in the previous calendar year h_income htotval Total household income in the previous calendar year h_size h_numper Number of people (all ages) living in household h_num_adults h_numper-hunder18 Number of adults (18+) living in household h_num_earners earner Number of people earning some income in household h_num_fams hnumfam Number of families living in household cpi_adj [FRED Data] Annual CPI adjustment factor adj_h_income [Calculated Value] (h_income / cpi_adj) / sqrt(h_size) seclass [Calculated Value] Social Economic Class, as defined by Pew. #### Difference In Density Function #Building the Difference in Differences Graphs getYearComparison <- function(df,year1=2000,year2=2015) { dist1 <- density(subset(df,year == year1, adj_h_income)$adj_h_income,from=0,to=1000000)
dist2 <- density(subset(df,year == year2, adj_h_income)$adj_h_income,from=0,to=1000000) df1 <-data.frame(x=dist1$x,y=dist2$y-dist1$y) ; df1$pos <- df1$y>0

compareYears <- ggplot(data=df1) +
geom_line(aes(x=x,y=y),size=1,colour="black")   +
geom_area(aes(x=x,y=ifelse(y>0,y,0),ymin=0),alpha=0.5,fill="lightgreen")+
geom_area(aes(x=x,y=ifelse(y<0,y,0),ymax=0),alpha=0.5,fill="pink")+
geom_hline(yintercept=0)+
ggtitle(paste0("Changes in Income Distribution Between ",year1," and ",year2)) +
xlab("Adjusted Household Income (2015 USD)") +
ylab("Difference in Distribution Density") +
scale_x_continuous(labels=comma,limits=c(0,500000),
breaks=c(0,50000,100000,200000,300000,400000,500000)) +
scale_y_continuous(labels=comma) +
scale_fill_brewer(palette="Set3")

#Return both a graph and the new dataframe
list(graph=compareYears,dataframe=df1)
}

## References

1: US Census Bureau. (n.d.). Small Area Income and Poverty Estimates. Retrieved from https://www.census.gov/did/www/saipe/data/model/info/cpsasec.html

2: Damico, A. J. (2016) Curren Population Survey. ASDFree. Github Repository. https://github.com/ajdamico/asdfree/tree/master/Current%20Population%20Survey; commit c680eec92cbba64512d756e533696dedaa3d415e

3: Variable htotval from the CPS Data Dictionary

4: Ryan, J. A.; Ulrich, J. M.; Thielen, W. (2015). Quantmod. CRAN Package. https://cran.r-project.org/web/packages/quantmod/quantmod.pdf 5: Burkhauser, R. (2012). Podcast interview with Russ Roberts. Retrieved from http://www.econtalk.org/archives/2012/04/burkhauser_on_t.html

6: Kochhar, R.; Fry, R.; Rohal, M. (2015). The American Middle Class is Losing Ground. Pew Research Center. Retrieved from http://www.pewsocialtrends.org/files/2015/12/2015-12-09_middle-class_FINAL-report.pdf

7: Planet Money. (2016). Episode 682: When CEO Pay Exploded. Retrieved from http://www.npr.org/sections/money/2016/02/05/465747726/-682-when-ceo-pay-exploded

# A (Mid-) Westerner’s thoughts on Abu Dhabi Culture

This isn’t meant to be authoritative or scholarly. And this isn’t meant to cohesive or well flowing. Most importantly, this isn’t meant to be offensive or read in the light of American cultural superiority, though I imagine that implicit bias will probably show up. This is just a scattering of thoughts I don’t want to forget. Some of this comes from my coworker/guide who lives here; most of it is just my own observations.

• English. English and Arabic are the official languages, and various guidebooks I’ve read say that English is the Lingua Franca for everyone except the Emiratis. As a very white, very obvious tourist, this has been my experience. That said, they aren’t speaking “proper” English, or even the slightly broken Indian/Asian English I’m used to (I work at a software company, after all). Instead, they seem to be speaking a formalized dialect based on Indian/Pakistani broken English. I even had one cabbie ask me if I spoke English because in his mind, he wasn’t speaking broken English.
• Public Transportation. I have a love-hate relationship with Public Transportation. I love the idea of it, and I love what it’s done for cities, but I am embarrassingly inept at using it. I also really hate having to schedule my time around catching the bus, because time planning has never been my forte. That said, in Dubai at least, Public transit, while stressful for me, is more my style. The metro runs every 6 minutes and the stations are spotless (thanks to the cheap labor, noted below). Similar to the US, everything runs on a check-in-check-out system with RFID Cards. Buses, at least the buses I took, all operate on a “when the bus is full we leave” basis. They don’t have as many bus routes, but more point-to-point buses, much like the metro, but with less overhead, and no timetables.
• Alcohol. The UAE is a Muslim Nation in the same way the US is a Christian Nation. Sure, the mosques send out the call to pray via loudspeakers and Alcohol is illegal to sell, but it’s not really illegal. Hotels and Resorts are allowed to sell alcohol, so at night, the little complex of my hotel is full of both tourists and locals coming for a drink. Locals have to pay hotel/resort prices for their beer (\$10+ for a pint of Stella or Budweiser), but it’s readily available and all the nightclubs and bars affiliate themselves with a hotel, and the hotels have a side door for non-guests to get in.
• Cheap Labor. The office building where I’ve been working has waiters. And I don’t mean at the restaurants, I mean that someone comes around to clean the breakroom, clear off the used coffee mugs from my desk, and will come in at the beginning of meetings to take orders for water or coffee. These aren’t interns just happy to sit in on the meeting, this is their livelihood. On my walk to work, I also saw someone polishing the metal rail on a bridge. He was going up and down the bridge with a rag polishing the big metal pole on the end of bridge. In the morning and evening, you can see shitty little buses bringing day laborers to and from the public housing compounds on the outskirts of town, but their clothes are always perfectly clean and ironed. But there are always people there to literally pick up after me. Busing your own table is non-existent here.
• The Pseudo Caste System. They don’t have India/Hindu’s rigid caste system since upward mobility is possible here. They also don’t have racism quite like we do in the US. But it’s something in between. My Middle Eastern colleague described it as a racial hierarchy: Pakistanis/Indians, Blacks and Philippinos, Non-Emeriti Arabs, Whites, Emiratis. And it’s like in a Brave New World where everyone knows their place (based on their race), accepts it, and complies diligently. Again, upward mobility is possible, but institutional racism seems to be the norm, albeit not in the same way it exists in the US. Each group also has its own code of conduct to which they are held (though tourists seem to be able to get away with almost anything).
• Build now, use later. I have some pictures of two park benches on the sidewalk, but behind them isn’t a park; it’s an empty sand lot. It’s full of trash and nothingness. But there are these two park benches. While I was there, I worked in a 40 something story building that was built in the last 5 years. It was a beautiful building, right next to an identical building that was completely empty. In both cases, the infrastructure was built not only before the need was there, but before the builder knew what the need was going to be. I’m sure that the vacant lot will be filled in and the benches will be used by people visiting whatever building or park goes in, and I’m sure that the second office building will eventually attract businesses to fill the various suites, but the speculation is rampant throughout all of the newer parts of town. It’s amazing what oil can build.