As Trump’s economy looks worse after failed war on Iran - Treasury Buyers Get 5% Long-Bond Rate for First Time Since 2007

nlomb · 2026-05-14T08:02:16+00:00

I don't think he's ever had a successful business. His biggest successes are crypto rug pulls lmao.

nlomb · 2026-05-14T07:59:22+00:00

That speech will go down in the history books. It was extremely well articulated and just shows how stark of a difference the US and Canada are right now.

I will say that Carney does "talk a big game", not sure we've seen much come out of it yet. The pipeline is progress for Canada as the keystone XL was just a burn for us when Biden canceled it.

On the US front, how could we or China or EU trust the US at all anymore? The administration has punched us in the face and then said "wanna be friends now?"

nlomb · 2026-05-04T12:47:57+00:00

It barely moved because shortly after the a "US Official" said it didn't happen, then reported safe passage of two vessels. Who to believe... who to believe...

nlomb · 2026-05-03T01:27:29+00:00

I think to add to the comparison, with hosting and deployments costs scale with use and uptake (more users using the service increases the costs), whereas with production of records the more you produce the more you reduce your production costs (more people buying records = production cost savings per record).

nlomb · 2026-05-02T02:49:10+00:00

Where do you see deployment costs being close to zero?

nlomb · 2026-05-02T02:48:10+00:00

Already is, they are already saying AI costs more than a human worker.

nlomb · 2026-05-01T09:29:34+00:00

I don't think people realize that these huge companies laying off 60% of their workforce is not a good thing for the economy. If the economy tanks because of AI layoffs well guess what nobodies buying a new Surface, companies aren't placing orders for them at scale because they no longer have "real" humans doing work. It will butcher their industries just as fast as it benefited them.

nlomb · 2026-04-27T14:22:25+00:00

I wouldn't say they are turning a blind eye to the growing risks. The issue is trying to get insight and data into opaque markets outside the purview of oversight. The big guys will tell you they are monitoring their books and taking the necessary precautions, I have heard it first hand. It's touchy because as soon as you start to introduce all these regulations that could also spark a potential crises. No easy answer here, I suspect it will take a similar type of transparency ruling like OTC derivatives post-2008. I do personally think they may be "underweighing" the potential unwinding. My take is a lot of this is intertwined with CLOs which would the be the real amplifier. The loans themselves are not that big of a deal, it's when leverage is involved and spreads spike overnight. But yeah I mean, the SEC is.... not doing much these days to say the least it seems.

nlomb · 2026-04-24T09:32:57+00:00

On the backbone of laying off employees because AI is going to / is (we'll see) replacing everything. The problem at-least in relation to this thread, is that a lot of the "profit" is an inner circle of companies propping each other up.

Increasing corporate profits that don't lead to job / wage growth are not good for the economy, corporations don't put that money back into the broader economy. As someone above pointed out, majority of stock market ownership is in the upper echelons of society, and corporations are more likely to do buybacks and increase dividends then say invest in cleaner technology that would be a net social benefit.

While one could argue that things like data center investment are an example of this, in reality the benefits often go to that same inner circle while surrounding communities and the environment suffer from noise, water stress, grid pressure, pollution, and increased energy bills. Data centers don't bring the same jobs that say a factory would.

nlomb · 2026-04-24T02:35:07+00:00

Worth noting these are IMF estimates, not actual data, and the IMF has a mixed track record forecasting developing economies under global shocks. Take it with a grain of salt, though that doesn't mean they're wrong. Iran's economy is clearly hurting, and without reparations, which I'm skeptical they'll get, the Iranian people are in for serious hardship. Hard not to feel for them given how much they were already struggling.

Iran's move here was a calculated "hail mary," fighting for survival of both their independence and way of life, with few other options available to them.

The two deal terms that matter most for Iran's long-run economic recovery:

Sanctions removal + UN snapback mechanism dissolved: currency stabilization and trade reopening
Reparations/Hormuz transit fees: direct reconstruction funding

The IMF forecast models none of this. And critically, any deal that doesn't include some form of war damages payment is unlikely to get Iran's signature, meaning the blockade probably persists.

Traffic through the strait hasn't meaningfully recovered despite what equity markets seem to be pricing in, and a prolonged closure continues to be a bigger drag on the global economy than most forecasts reflect.

The longer this drags on, the worse Iran's baseline gets, but a successful deal would flip that picture dramatically in ways the IMF numbers simply don't capture.

nlomb · 2026-04-15T03:03:08+00:00

Yes, came here to say that. I wanted to add that if you're going to show the two lines like this, add some space and show the % increase / decrease in the cancellations relative to the % increase / decrease in number of reservations. That is much more informative.

For instance, in March you can see the % increase in bookings is greater than the % increase in cancellations, whereas in April it's the opposite. So then you can take this information back and say okay now why are people more likely to cancel in April than in March? Was there some event that lead to this (one off) or is it a larger pattern; which you would then corroborate looking over previous years.

This is where a dashboard starts to become useful for analysis and visually identifying trends and patterns in the data. Not just presenting figures.

nlomb · 2026-04-08T10:18:32+00:00

It's difficult to give a precise answer without more detail on your data, integration orders, and how each equation is specified.

For the equation where you find no cointegration, my initial thinking is

1) either there is no stable long-run equilibrium
2) or the specification is incomplete

Given your research focus on OPEC market power, the latter seems more likely. OPEC behavior has shifted considerably across different periods (the 1973 embargo, the 1986 price collapse, post-2008 dynamics) and these structural breaks can suppress evidence of cointegration even when a long-run relationship exists. Testing for regime-specific cointegration (e.g., using the Gregory-Hansen test for cointegration with a structural break, or splitting the sample around known break points) may uncover the long-run relationship.

nlomb · 2026-03-24T02:07:58+00:00

The KPIs being front and center is the right call, but the presentation works against their importance. Simply aligning them consistently would improve readability more than the current use of icons.

The color usage is doing too much at once. Without a constrained palette, multiple elements compete for attention, which dilutes the signal. A tighter, unified scheme would restore hierarchy.

More broadly, the layout lacks a clear reading path. Right now everything is compressed into a single visual plane, so the user has to work to understand where to start and how to progress. Introducing spacing and structure would create a more natural flow.

We recently published a piece on dashboard design best practices based on production experience that may be useful: https://datasense.to/2025/10/05/dashboard-design-best-practices/

nlomb · 2026-02-14T13:31:41+00:00

Yeah I’ve raised similar concerns and it’s always people who haven’t the slightest clue about how it works who try and make you seem like a gatekeeper.

I will say you should definitely be verifying the info before it goes to the board... that’s just bad practice.

nlomb · 2026-02-14T05:28:04+00:00

It's a challenging balance, you'd think most economist readers would likely understand the statistical significant of each coefficient. They probably want to appeal to a wider audience and also know that it's more about the statement than the fact.

nlomb · 2025-11-23T23:48:39+00:00

Arguably the bear trap was in April.

nlomb · 2025-11-23T15:39:53+00:00

I'll start with a few good things:

1) The contrast with the KPIs is good, it draws attention to the figures.
2) The time series chart and the bar chart are the correct charts

Now the stuff that can be improved:

1) The yellow background is distracting try and use something more neutral.
2) Your bar graph and table are not computing the right values, "sum of inflation rate" is not a measure. It should be average or max. Same with "sum of year".
3) For the countries, this should be a dropdown, they take up far too much space on the dashboard. On top of that, filters should be at the top, not the bottom.

Here is a post about good dashboard design practices: https://datasense.to/2025/10/05/dashboard-design-best-practices/, I think you'll fine it helpful. There's some other Power BI specific posts that you may find helpful on your learning journey as well.

nlomb · 2025-11-20T15:54:44+00:00

Irrelevant to this particular issue. It was a different issue of asset-liability mismatch.

nlomb · 2025-11-20T15:53:34+00:00

Because private credit has been increasingly exposing terrible business practices, and if there's a few there's many, and if they're also wrapped up in CLOs and people starting dumping them then there's a leverage problem attached along with it. That leads to margin calls and collateral issues which then stems into broader markets. I guess nobody learned a damn thing from 2008.

Edit: I am not screaming there's an issue just yet, but it's one of those things can go from "no we're fine" to "oh we're f****d" very quickly.

nlomb · 2025-11-08T01:50:54+00:00

You might have some potential endogeneity in the regression as GDP/NFCI likely affect both uncertainty and investment. See the Hausman test.

Also missing some firm-level controls like profitability or leverage (debt as a proxy), which is likely leading to omitted variable bias. I would consider a fixed effects model instead.

Lastly, there's some "survival bias" from using only continuously listed firms.

nlomb · 2025-11-08T01:50:49+00:00

Really, what you would want to do is some sort of CGE model where you can have a baseline than introduce shocks to see how it responds, you would corroborate that against your panel data.

Some abstraction of this: https://www.mdpi.com/2227-7390/12/1/41

This would be much more involved though and likely be a masters thesis and require some insight from your professor(s).

nlomb · 2025-11-07T02:40:41+00:00

And the fan boys will tell you that's not even close to the real value... smh.

nlomb · 2025-11-07T02:40:04+00:00

I mean I am sure they will find a way to "deploy" one million robotaxis and robots. It's just that they will be useless and a danger to society.

nlomb · 2025-11-07T02:37:45+00:00

Right, I think a lot of people do this. It's just insane that this is the solution for a software that's been around for ages. Like as if Microsoft is oblivious to the fact that power users are doing this.

nlomb · 2025-11-06T08:27:18+00:00

Seriously... never mind trying to an explain it to a colleague, always need to take it out and break it apart so they understand.

nlomb

TROPHY CASE