Coin Problem

Problem:

Suppose you can bid on a coin of an unknown value between 0 and 100. If your bid placed is greater than the value of the coin, then you win the coin. Furthermore, if you win the coin, then you are guaranteed to be able to sell it to your friend, a coin collector, for 1.5 times the coin's value. How much should you bid for the coin?

Solution:

Let X be the value of the coin, where X ~ unif(0,100).

Let Y be your bid.

Your return, R, is 1.5X - Y if Y > X, or -Y if Y ≤ X

Your expected return, E(R), is given by the following formula:

E(R) = E(1.5X - Y | Y > X)*P(Y > X) + E(-Y)*P(Y ≤ X)

E(R) = -Y + 1.5*E(X | Y > X)*P(Y > X)

To gain some intuition into how these terms work, here are some numerical examples:

Bid Y = 0

In this case, P(Y > X) is 0, because 0 is the lower bound of the coin's value.

So E(R) = 0.

 

Bid Y = 1

E(R) = -1 + 1.5*E(X | X < 1)*P(X < 1)

The probability of X < 1 is 1/100. If we know that X < 1, then the random variable X | X < 1 is distributed uniformly between 0 and 1. Thus, E(X | X < 1) = 1/2.

So E(R) = -1 + 1.5*0.5*0.01 = -0.9925

 

Bid Y = 2

E(R) = -2 + 1.5*E(X | X < 2)*P(X < 2)

The probability of X < 2 is 2/100. If we know that X < 2, then the random variable X | X < 2 is distributed uniformly between 0 and 2. Thus, E(X | X < 1) = 1.

So E(R) = -2 + 1.5*1*0.02 = -1.97

 

Bid Y = 10

E(R) = -10 + 1.5*E(X | X < 10)*P(X < 10)

Following a similar pattern, E(R) = -10 + 1.5*5*0.1 = -9.25

 

Bid Y = 50

E(R) = -50 + 1.5*E(X | X < 50)*P(X < 50)

Following a similar pattern, E(R) = -50 + 1.5*25*0.5 = -31.25

 

Bid Y = 80

E(R) = -80 + 1.5*E(X | X < 80)*P(X < 80)

Following a similar pattern, E(R) = -80 + 1.5*40*0.8 = -32

 

Bid Y = 100

E(R) = -100 + 1.5*E(X | X < 100)*P(X < 100)

Following a similar pattern, E(R) = -100 + 1.5*50*1 = -25

This leads us to the finding that E(X | Y > X) = Y / 2; additionally, P(Y > X) = Y / 100.

Therefore, our general formula for our expected return is:

E(R) = -Y + 1.5*(Y/2)*(Y/100), or:

E(R) = 0.0075Y² - Y

It turns out that under the rules of this game, there is no bid that returns a positive expected return. To see this, we can find the optimum of the return function:

E(R)' = 0.015Y - 1 = 0

Y* = 1 / 0.015 = 66.66667

However, this optimum Y* is a local minimum rather than a local maximum, because the expected return function is convex; E(R)'' = 0.015 > 0. Indeed, E(R) when Y = Y* is -33.33333.

In our numerical examples above, we checked the boundary conditions of Y = 0 and Y = 100, and thus have confirmed that for this game, Y = 0, or not placing a bet at all, yields the highest return.

*    *    *

Problem:

Suppose the return multiplier on the resale value of the coin differs from 1.5. What multipliers would cause you to change your bidding strategy?

Solution:

Let a represent the multiplier, and assume a > 0. Our expected return formula is modified to the following:

E(R) = -Y + a*(Y/2)*(Y/100)

E(R) = (a/200)*Y² - Y

We can first identify the values of a under which we would expect any positive returns; or, solve for a such that:

(a/200)*Y² - Y > 0

Y((a/200)*Y - 1) > 0

a > 200/Y

In our most extreme bid of Y=100, this inequality indicates that a > 2 is the requirement for this game to yield any positive return. This explains why a = 1.5 indicated that the best strategy was not to place a bid.

Now, assuming a > 2, what is the optimal Y to bid? Once again, we consider the optimum Y* of the return function:

E(R)' = (a/100)*Y - 1 = 0

Y* = 100/a

However, once again, this is a local minimum, since E(R)'' = a/100 > 0. So we must check the boundary conditions.

When Y = 0, E(R) = 0. When Y = 100, E(R) = 50a - 100. With a > 2, this indicates that bidding 100 is always the strategy that yields the highest expected return.

Intuitively, this makes sense, as a bid of 100 guarantees that you will win the coin and that you will receive the payout. As the payout multiplier increases above 2, the expected payout dwarfs the fixed cost of placing the bid.

November 6, 2024

2016 felt unfair because he lost the popular vote. This time, the popular vote aligned with the electoral results. That feels fair to me.

I can't say it was a surprise.

With this outcome, we know there won't be another insurrection. Because only one side would have done that, and they won. No one is claiming voter fraud.

I'm tired.

Over 72 million people voted for him. I and most other people in the circles around me are in the minority. I can't delude myself into thinking that all 72 million people are all idiots and that I know better than all of them.

You can't run a campaign on vibes. Brat ain't enough.

We survive. We take it day by day. We did it before, and we'll do it again.

The grocery stores are still open. The electricity is still running. The checks are still clearing. The hot water is still flowing. It is not the apocalyptic hellscape the left said it would be.

When Obama won in 2008, the community by which I was surrounded--conservative evangelical Christianity--decried the advent of socialism, the collapse of democracy, and even the ascendance of the anti-Christ. In retrospect, 2009-2016 were exceedingly politically tame.

Even if we lose democracy, we won't be killed or slaughtered. We are not in physical danger. Millions and even billions exist and survive under much more oppressive governments.

It may turn out worse for others. But I don't have the energy to think or care beyond the (minimal) impacts to me personally, because that's the only way I can maintain any sense of hope.

And I hope more than anything else that SNL does not do "Hallelujah" again.

Heaven is a Sham

Near the end of a recent session, my therapist dropped a statement which was uncharacteristically editorial of him: "You are a good person." It stuck with me, perhaps because he typically doesn't interject his judgments and leaves space for me to do the analysis, but also because it's not a statement I've heard much in my life.

"Why do you call me 'good'? No one is good except God alone."

Not even Jesus claimed he was good. If even he didn't claim he was good, then how could I possibly lay claim to that identity? called the echoes of evangelical Christianity in my brain. Though the way that retort comes off in the text, perhaps he was just being coy with the rich dude.

My therapist uttered another statement in the same session that I was also left pondering: "Just because you hurt someone doesn't mean you did something wrong."

Hold on. Is that true? Certainly I can think of a few select instances in which it was, but is it true as a general rule? Hmm. I'll have to think on that one.

For much of my adult life, I've relied on whether someone got hurt as the indicator for the morality of my actions. With that indicator's reliability called into question, I struggled to identify what could be used to measure an action's morality. Is it an action's intention (rather than its outcome)? Is it the proverbial sin of omission ("Anyone who knows the good he ought to do and does not do it sins")? Is it the failure to abide by a promise or commitment made, whether explicitly stated or not?

I tested these candidate rules against a wide selection of prior incidents in which I hurt someone. But in this exercise, I realized that none of these rules was broadly applicable enough to apply in all situations. So I was once again left without a barometer, a compass to indicate moral failure.

But why am I so laser-focused on the ability to discern right and wrong? Why do I have such hyper-sensitivity to moral responsibility?

Certainly my evangelical upbringing instilled in me the paramount importance of the skill of discernment, with the objective being to "come back to your senses as you ought and stop sinning". Of course, that was always hard to square with the premise of Christianity, which is that all your sins had already been forgiven (so why did it matter?).

But I think there's a more practical reason for my excessive focus on morality. I simply want to be able to tell when I have committed a moral error so that I can avoid it in the future. To me, consistently repeating my wrongdoings without any sense of remorse would make me a bad person. Being labeled a bad person is what I am afraid of.

Being a bad person makes one less desirable to be around; it drives other people away. Driving other people away results in a state of loneliness--a self-inflicted loss of community. So my fear associated with being labeled a bad person represents my fear of being alone, of losing the relationships I have. Therefore, perhaps my excessive focus on right and wrong and moral responsibility is a preemptive strategy to stave off being alone.

At this point, I also realized that I could swap out many of the key terms--moral error/wrongdoing/moral failing, remorse, bad person, right, wrong--with loaded religious terminology--sin, guilt, unrepentant sinner, good, evil--and the meanings of the statements would be equivalent to me. I'm not sure what exactly that means, but it suggests that my relationship to these concepts is unchanged irrespective of my faith status. If that is true, then what's not clear is whether my prior faith set that relationship, and my current weltanschauung has simply commandeered it, or if the relationship is more fundamental to my being.

So, it bears asking whether there exists a religious analog to my fear of loneliness resulting from being a bad person. Here are the ideas in prior paragraphs, translated:

I want to be able to tell when I have committed a sin so that I can avoid it in the future. Consistently repeating my sins without any sense of guilt would make me an unrepentant sinner. This label is what I am afraid of, because being an unrepentant sinner drives God away. I am afraid of being excluded from heaven as a result of my of my recurrent sin driving God away.

This squares with the theology I grew up believing. I was taught that God cannot be in the presence of sin, so being an unrepentant sinner--a bad person--would keep me separated from God.

What I now have the courage to admit to myself, though, is that exclusion from heaven was so frightening not because of the prospect of being away from God. As far as I was concerned, he was kind of unknowable, and it's hard to feel a strong desire to be with someone for eternity if you don't feel like you know them. The frightening part of exclusion from heaven was that I would be separated from my community, from the people with whom I had grown close on earth. I deeply loved my Christian friends in church, at school, and in my family, but what if I did something or continued to do something that classified me as an unrepentant sinner and barred me from an eternity with these cherished people?

This is what I was afraid of: being alone outside of heaven without the people I knew. Because most everyone in my life at one point or another was a Christian and would be going to heaven. I would be left with no one if I was a bad person by God's standards.

This is one reason why the fact that I couldn't shake looking at gay pornography in high school so demoralizing to me.

I very clearly hear the echoes of my anxieties from my Christian days reverberating in my present-day thoughts about morality and ethics. I am deeply fearful of doing something that will cause me to lose the people around me whom I love.

But what about the people who made it into heaven? I wondered. How would they feel about losing me if I didn't make it in because of something I did?

"He will wipe every tear from their eyes. There will be no more death or mourning or crying or pain, for the old order of things has passed away."

If I didn't make it into heaven, but my friends did, I would be grieving and in pain for the forever loss of those relationships. But they would not reciprocate that feeling on the other side of the pearly gates. There will be no sadness, no crying, no pain in heaven--no grieving. There will be no grieving for the people who did not make it in, for the relationships forever lost. That's fucked. Grieving is part of the human experience. And that experience is not allowed in heaven. Heaven strips people of their humanity, and they feel nothing for the people who did not make it in.

If that's what heaven is, I want nothing to do with it.

Or perhaps those who made it in would feel morally superior to those who did not. "I got mine; you get yours." I think whenever I imagined a scenario in which I was excluded from heaven, I pictured those inside whom I had loved suddenly turning on me, asserting that it was my own fault for losing my eligibility to enter.

Perhaps this scenario is how evangelicals today make heaven on earth.

Heaven is a sham.

Thoughts at TRB 2024

I attended the Transportation Research Board Annual Meeting in Washington, DC in 2024. I'm about two months late, but following is a summary of my "aha" moment during the conference. Because after all, if I didn't have some kind of vaguely profound-to-me series of thoughts at a conference, then was I really there?

This year, my musings were on aviation forecasts. There were two major triggers for my musings this year which happened in quick succession on Tuesday. First was the Aviation Economics and Forecasting Committee (AV040) meeting; immediately afterward was a session sponsored by the Airport Terminals and Ground Access Committee (AV050) entitled, "Persistent Impacts of the COVID-19 Pandemic on Passenger Processing".

The AV050 session was introduced with some background on passenger statistics before and after the COVID-19 pandemic. The moderator consistently framed the discussion of the statistics as still not quite having "returned" to pre-pandemic levels. This discussion was not unique to this session; it is frequently cited as a benchmark when setting the stage for a range of recent changes in aviation. But why, I wondered, is a return to 2019 demand levels seen as a goal that we want to reach again? Why is that the light at the end of the tunnel before things are back to "normal" and we can continue on our forecast growth trajectories?

Aviation forecasts always show perpetual growth for any forward-looking interval examined, even out to twenty years into the future. It is a reflection of the capitalistic mindset: growth forever. But this is not sustainable. Aviation demand cannot grow forever. When, I wondered, will growth simply stop--not caused by exogenous factors, but simply because the market is saturated and the demand for air travel is satiated, or an "equilibrium" of sorts is reached?

I thought back to the AV040 committee meeting immediately prior. The last third of the session consisted of a "roundtable" discussion on forecasting methodologies, especially into the future. Four speakers scattered around the room were asked questions, and despite their detailed answers to questions and the differing systematic approaches that they apply to their forecasting practices, I was reminded that forecasts are always wrong, regardless of the systematic approach used.

Forecasts are always wrong. They are always wrong because they are econometric regression models that only account for a handful of explanatory variables--perhaps six or seven at most. Explanatory variables are chosen that are assumed to have a relationship with aviation demand and result in regression models with reasonably high R² values. Common variables like economic output and population tend to show up in many forecasts, but these variables have a correlative relationship, not a causal relationship.

Irrespective of the variables chosen, an R² of 1 is never achieved. That is because the model would need to include an infinite data set and an infinite number of explanatory variables. However, the models used are never robust enough to predict events like the Great Recession or the COVID-19 pandemic. Or, conversely, many forecast models prepared around 2014 to 2016 underperformed in their near-term projections through 2019. Even though the model's R² value may have been over 0.9, that remaining 10% of explanatory variability can hold a massive sway on how demand actually materializes.

Therefore, there must exist some other variable or set of variables that, if they could be included in the forecast models, should be able to predict massive downturns like the Great Recession or the COVID-19 pandemic. I call these "dark variables", analogous to the dark matter in the universe that we cannot observe but nevertheless accounts for 75% of the total mass in the universe.

Using AI in preparing forecasts briefly came up during the committee meeting. Frankly, the panelists were extremely short-sighted in their views on how AI will influence aviation forecasting. They asserted that AI can be used as a tool in forecasting, but it will never replace the "human element" of aviation forecasting. I don't believe that for a second. This is exactly what AI is good at: identifying patterns in data, often ones that most humans would otherwise overlook. And given that much of the work of preparing a forecast is setting up a regression model, this is a task that almost certainly will be trivially taken over by AI. AI may even have the ability to generate more accurate forecasts, as it may pick up explanatory variables that most forecasters would not consider including. To me, forecasting seems like a practice which is perhaps among the most vulnerable to being displaced by AI. Aviation forecasters would be wise to start getting savvy on other areas.

There were a number of times early in my career when I was asked to pull historical schedule data for an airport. I was also instructed to exclude certain periods of "non-representative" demand patterns--usually the Great Recession. I wondered how much insight was left on the table by excluding these periods, which surely contain valuable information about factors causing declines in aviation activity and how markets behave under such circumstances. I wondered how much data was thrown out unnecessarily. AI, by contrast, benefits with more input data, so this practice of excluding non-representative data must be discarded.

I have reviewed several papers for TRB over the last few years. Many of these papers develop regression models for measuring whatever phenomenon the authors are measuring. The analyses of the resultant regression coefficients discuss the impacts of one variable on the measured quantity. But a fundamental assumption for a regression model is that the explanatory variables are independent of each other. In almost all cases that I have seen, the explanatory variables are not independent, which poses a challenge to the model's validity and its predictive ability. Furthermore, the models often rely on linear multivariate regressions, when other forms of regression (exponential, power) exist. Of course, the problem with any such model is that it presumes that all the terms are subject to the same mathematical operators: addition, exponentiation, or multiplication. What if forecasters or AI were able to develop mathematical relationships for aviation forecasting that combined mathematical operations and was able to correct for dependent variables?

So, after all that, my takeaway was that no one actually knows what they are doing with respect to aviation forecasting. It's all perfunctory and dressed up in a gold sheen of mathematical rigor.

Then what does it mean for the FAA to review and approve a forecast? For airport master plans, the forecast is one of two items that the FAA has approval authority over (the other being the Airport Layout Plan set. Contrary to popular belief, the FAA does not have approval authority of the master plan as a whole.) If even the forecasting experts who prepare the airports' forecasts cannot prepare anything truly defensible, what endows the FAA with the ability and secret knowledge such that they can judge whether a forecast is appropriate?

When the FAA reviews a forecast, they often come back with comments as to why the approach or method was taken over a different one. If the sponsor and consultant agree, or if they just want to get the forecasts done so they can continue the rest of the master planning process, then they may change the approach or method at the FAA's suggestion. But who is to say that the second approach or method is more accurate or valid than the first?

Hint: they're both wrong. Once again, it is cloaked behind a gold sheen of mathematical rigor.

So, we are back to the question: what does it mean for the FAA to approve a forecast, especially if no one can actually get a forecast right?

An FAA-approved aviation forecast represents a level of demand that the FAA is comfortable having inform an airport's facility requirements and, ultimately, its capital improvement plan. All projects in the capital improvement plan need to be supported by an FAA-approved demand basis, i.e., the forecast. So, perhaps the FAA's approval of a forecast should be thought of as a pre-approval of a capital improvement plan. It is a statement of what the federal government is willing to pay for.

And, fundamentally, this is a policy stance. It is similar to the government's historical push for other transportation projects such as, "a freeway must go here". It is a policy stance in that it is an indirect for the federal government to commit federal money to airport capital projects. Of course, these can create jobs, so there is a positive there. However, that may skew the incentive for the FAA to want to always see positive growth in airport forecasts.

Now, who is holding the federal government accountable for this policy decision? What occurred to me was this insane idea: should the FAA's approval of a forecast be classified as a federal action under NEPA requiring review?

I talked about this with a colleague who has worked in aviation environmental for over fifteen years. Her immediate answer was no, because the forecast approval itself does not have effects in the impact categories as outlined in NEPA. The NEPA review occurs at the project stage, when the impact categories can be measured for a specific project or set of projects in question.

However, by that point, the forecasts are considered set in stone. Many projects' justifications rely on the forecast growth in demand, and the need to deliver these projects to meet this forecast growth in demand. So the NEPA process creates accountability for the project itself, but not for the demand assumptions underlying the project.

In short, forecast review and approval by the FAA is a sham. It  is subject to the whims of the local ADO or the FAA headquarters and is likely reflective of what capital projects they are willing to help pay for. It thus constitutes a policy decision, and there is no real accountability for this decision.

So, those were my profound-to-me musings at TRB 2024. I'm not really sure where this goes, if anywhere, but it was certainly a fun thought trajectory.

2023 in Flight

GOALS FOR 2023

In last year's year-end post, I set five goals for myself in 2022 with respect to my flights taken. Let's see how I did.

1. Achieve airline status. It need not be on Alaska again.

Did it again. On Alaska again. 2024 will be my sixth consecutive year with MVP status on Alaska. I didn't even come close on any other airline.

2. Avoid flying United.

By the letter of the law, I failed to achieve this goal. When flying to and from Vancouver in November, Air Canada was by far the cheapest option, and they outsource more than half of their daily non-stops to Vancouver to United, their Star Alliance partner. Of course, United operated the favorable schedule times. However, by the spirit of the law, I arguably managed to achieve this goal. Although I flew on United metal, I deliberately booked it through Air Canada.

The weird thing was, though, that when I attempted to add my United MileagePlus number to the reservation, I was unable to do so through Air Canada's online reservation management system. I even called Air Canada, and they were also unable to help me. I was able to add my United number, however, through United's app by entering the Air Canada confirmation number. Explain to me how that works?

Now, in spite of my (overblown) grudge against United, I will say that I was quite impressed with their IT. Their in-flight tracking, status updates, and phone sync was top-notch. Of course, that could be because I am used to Alaska's IT, which is absolute trash (not even by comparison).

3. Fly at least once a moth.

This is the one goal I achieved that I'm most proud of. I hadn't done this since 2018.

4. Get out of the country again.

I achieved this goal. I visited Mexico in July and Canada in November.

5. Hit four new airports.

Success. GEG, BOI, PVR, and LEB.

YEAR-OVER-YEAR TRENDS

 

 

40,580 miles flown in 2023, measured as great-circle distances in statute miles. 21% increase over 2022; 47% increase over 2021.

 

Coincidentally, 2022 was also a 21% increase over 2021.

 

 

40 segments flown in 2023. 25% increase over 2022; 82% increase over 2021.

 

 

Both the longest and shortest segments of 2023 occurred within the same trip. In December, I traveled to Boston for work, and while there, took a jaunt to Lebanon, NH on Cape Air. The day I returned home was the same day I did the Cape Air excursion, and since BOS-SFO is the same length as the converse route, I technically flew my longest and shortest segments of 2023 on the same day.

 

 

$7,167.62 in airfare paid in 2023, which considers the actual amounts charged to my card, inclusive of airline credits, miles used, taxes, and fees. 41% increase over 2022; 219% increase over 2021.

EDITOR'S NOTE: Last year, I changed how I accounted for the companion fare; I changed it to count the full single-ticket price, rather than the single-ticket price plus the companion fare divided by two, which it had been prior to last year. As I wrote last year's post, I was torn about how to count this, because, "recording the full single-ticket price is perhaps unrepresentative in that it suggests that I booked itineraries that I may not have otherwise booked." I concluded last year's discussion by saying, "Maybe I'll change it back next year."

I changed it back. This reversion adjusted the 2022 total when compared with last year's summary statistics.

 

 

This was the year that I started tracking operating carriers as well. Previously, I had only tracked marketing carriers. I began differentiating marketing from operating carriers solely so that I could argue that I flew Air Canada this year and maintained my non-United streak. Petty, I know.

 

 

 

 

MORE ON MILES

 

 

There you have it. Every month.

 

 

I've started adding notes to the graph themselves so that I don't have to spell things out in the captions.

 

 

Again with the marketing versus operating carrier.

 

 

Two years without a wide-body. Boring.

 

 

Still boring. Though at least I got a prop in there.

 

 

Also pretty boring, except for the C402. It was supposed to be a Tecnam P2012, but Cape Air made an equipment swap at the last minute. Which was just as well, because the particular airframe I flew was the Pride-branded airframe.

 

 

Flying back on Saturday from leisure trips is usually way cheaper than Sunday. And you get a full day to settle back at home before going back to work. I highly encourage traveling on Saturdays.

MORE ON MONEY

 

 

Yeesh. I still do not understand why ONT is such an expensive airport to fly into and out of.

 

 

"Lead time" is defined as how many days in advance of departure the ticket was purchased. The 215-day lead time purchase is not shown because it would distort the scale otherwise and make the other data points unintelligible. That was when I was on a travel-booking spree in May and booked my Christmastime air travel. It was so far in advance that the schedule was a phantom. The originally booked flight got cancelled, we got rebooked on a 6 AM departure, and then re-rebooked onto a 10 AM departure the next day. Finally, I called and re-re-rebooked onto a flight which had reappeared at about the same departure time as the original booking.

 

 

I guess I didn't have this graph last year. This is a fun one. The shapes are loosely concave.

 

 

Second year in a row with no ticket purchases on Saturday.

 

 

 

MORE ON WHERE

 

 

A "visit" is defined as a segment either originating or terminating at a given airport. So connections grant two visits to the connecting airport.

The size of the font is directly proportional to the number of visits.

We love a radial network. Along with a kite-shaped routing to and from BOI. Just because I wanted to pick up another new airport--GEG--along the way as an unusual connection.

 

 

Literally nothing on this list is a surprise. PDX-SFO received an arbitrary "honorable mention" distinction simply because it was featured quite a bit in 2023.

 

 

These represent both originating and terminating mode shares combined. Each color of bars sums to 100%.

"POV" also includes cases when I was picked up from or dropped off at the airport in another person's rental car. "Rental car" implies that I transited through the airport's rental car facilities, even if I walked or took a bus from the rental car center to the terminal. "Walk" typically covers cases where I am at a client site.

WHILE IN FLIGHT

 

 

I'd consider this a win.

 

 

A "pushback pause" is defined as the time when the aircraft is stationary after being pushed back from the gate. Specifically, it begins when the aircraft stops moving backward and the tug begins detaching, and it ends when the aircraft begins moving forward on its own power. Collecting these data were the reason I began a flight log at all. I sought to collect data around this specific statistic for use in simulation modeling.

 

 

I did much better with upgrades this year, though a lot of them were just on intra-California regional jet flights. Nevertheless, I'll take the free booze. 2023 was my wettest travel yet, surpassing 2019's 20 drinks consumed.

 

 

Thanks to my ASPM login, which grants me access to Individual Flights records, I was able to look up almost all prior flights in my log and obtain the tail number for each airframe. N296AK is the only airframe that I am aware of having flown three times.

 

 

 

RECORDS

A project I undertook this year was adding as many historical flights (i.e., before 2016) I could to my log. My access to ASPM Individual Flights, as well as my mom's digging into historical family travel reservations, helped me reconstruct several historical itineraries. This project was motivated by my introduction of Records last year, after which I realized that 2008 would become a contender for one of my busiest air travel years. Behold; here is how it stacks up as best I can tell.

Flying round-trip to Israel via connections through major international U.S. gateway airports gives you a pretty major leg up on setting a busiest month record.

This statistic speaks to how well distributed air travel is throughout the year.

Last year's version had SJU-SFO and LAX-SJU as the fourth and fifth longest segments, respectively. However, what I learned through my historical itinerary digging was that neither of these segments existed. We connected through DFW on these itineraries. (Originating at SFO and terminating at SJU on 1/1/2008 actually included two connections: LAX and DFW!)

Southwest continuing to come in hot. Also Cape Air, but I'm not fully convinced that the "pushback pause" is a thing on a little eight-seat C402.

This record was also updated to attribute credit to the operating carrier rather than the marketing carrier, which seems most appropriate.

ONT! Yikes!

As described earlier, I switched the accounting of costs back to be inclusive of the Alaska companion fare discount. This explains why the #1 lowest itinerary was shown as #5 last year.

When I was deciding to book a flight on Cape Air, I considered booking BOS-PVC roundtrip. This would have been an approximately $240 ticket. At 90 miles roundtrip, this itinerary would have far and away become the most expensive itinerary per mile flown, at over $2 per mile. Instead, I booked BOS-LEB roundtrip, which became the third cheapest full-fare single ticket (not per mile flown).

With this iteration, Virgin America, 2017, was booted from the top five in miles. Actually, it was technically booted in 2008, but this iteration of statistics is the first instance in which it fell off the list.

I am very glad that OAK-LGB made this list as a result of entering prior itineraries into the log. It is truly a tragedy that the days of $39 and $49 one-way fares on JetBlue between OAK and LGB are gone.

I am surprised that I have not flown a single route any more than 11 times in my life. That seems low.

I am surprised at the degree to which SFO leads OAK, despite the fact that OAK was my primary airport for 22 years of my life. But, I suppose I traveled far less in those first 22 years than in the following 8 years. I am also surprised that ONT is already my #3 airport.

HIGHLIGHTS FROM 2023

First time flying...

• ...on these aircraft types: C402C
• ...with these carriers: Cape Air
  
• ...to/from these U.S. states: Idaho, New Hampshire
• ...an EAS (Essential Air Service, a federal subsidy program) route: BOS-LEB and LEB-BOS

First time experiencing a flight cancellation! My return flight PDX-SFO on 3/21 was cancelled due to nasty weather at SFO all day. Originally, the gate agent had announced that the approximately 6:00pm scheduled departure was to be delayed by six hours. Instead, I left the gate area and spoke to an agent at the check-in desks to get rebooked onto a flight the next day rather than getting rebooked onto a flight to SJC that would land around 11:00pm.

First time submitting a credit card insurance claim for a delayed or cancelled flight. The incident described in the previous "first" was fully reimbursed by my American Express Gold Card.

Still no diversions or go-arounds.

GOALS FOR 2024

So. As I prepared the graphs of my annual statistics for 2023, I began feeling a little bit weird about all these data. It felt like a flex of privilege to compile all these statistics showcasing all the air travel I have taken. Perhaps it didn't bother me when I first started preparing these summary statistics after 2018 because that was the first time in my life I had gotten the chance to fly as much as I had. Now, it doesn't sit quite as well with me from an optics standpoint.

I will continue to collect and summarize my flight statistics. But perhaps I will be less forthcoming about showing the final results. And I think I would like to skip the goal-setting. This hesitance may be coming from sensitivity of the privilege required to achieve goals such as those I set for myself. Perhaps there is also some climate anxiety baked in there. Besides, my goals in recent years have become somewhat stale and repetitive anyway.

So, no goals for my air travel in 2024.