Greetings, and welcome back to ZacCast, your official podcast for local government nerdery. I'm Chad. Over there is the Guava Dude himself, Patrick, and, uh-

... gracious, we brought the Guava Dude out.

How you doing, Pat?

I'm good, nerd.

Rough times out there, huh?

It's, it's, uh, this is gonna be a nerdy podcast. We're gonna talk about things that are very data-intensive. Uh, so for people who sit on my side of the world, brace yourself. Uh, for people who sit on your side of the world, I mean, you know, get your soup out. Let's go. It's gonna be a, gonna be a fun topic-

I'm ready

... of conversation.

Yeah, so this is a little bit of an off-schedule podcast, mainly because if you're paying attention, it's getting kind of crazy out there. Um, I've, I think I've lost 8 or 9% of my portfolio in the past two days. I don't know about you. Uh, that's just based on, what is it right now? 9:48 in the morning on Friday. Where are we today? Yeah, three and a half percent down today, plus about five yesterday. So, Patrick, what do you... Like, what's going on? What are you hearing from people? Let's start there. What are you hearing from people, and what kind of questions are you starting to get that's sort of providing the impetus for this somewhat emergency episode?

Well, I think, you know, first off, let me start with this. Uh, I'm taking my kid to school this morning. It's April 4th, Friday, April 4th, uh, which, um, you know, so that people understand where we are. Hopefully, we get this posted by the weekend, but the reality is the market's been down, futures were down, the market's down this morning significantly. I think we're probably in, you know, significant correction territory at this point. We were with the S&P yesterday and with the Nasdaq yesterday. We are with the, the Dow. About 7:15 this morning, I'm taking my kid to school, and I'm, I'm getting my first phone call of the day from a, from a city official, city manager, asking questions about where we think things are gonna go, what it's gonna look like. I get off that phone call, and my kid looks at me, and he goes, "Dad, what's it mean when you're busy?" And I said...

It's usually bad.

It's usually bad. It... You know, you, y- you know, we, we talk about it all the time at Zach that we're, like, anti-cyclical. Uh, so, like, when things are really good and finances are really good, people don't need to talk to us much, but when things go, uh, bad or get... Uh, for a better term would be when things get uncertain, uh, people start looking for a level of certainty. Uh, and, you know, obviously, we don't provide 100% certainty, but we do, uh, provide some data analysis capabilities to be able to do that. So a, a lot of it is: "Hey, what are y'all doing? What are you seeing? What are you thinking? How deep is this gonna be?" Um, you know, obviously, during COVID, you and I made some very bold statements. I wouldn't say bold predictions because we kind of had some data to back up where we thought things were gonna go, even though we were in very unknown territory of a pandemic. But, you know, we told cities to kind of, "Hey, step back, calm it down, pump the brakes a little bit." Um, you know, we were using cell phone analytic data and some other things to look at, you know, how busy businesses were, and, you know, we were not seeing 30 to 40% drop-offs of, of consumer traffic. We were still seeing quite a bit of, you know, just a change in business model, but obviously, you know, we were closed for two weeks before we kind of opened back up a little bit, and but we just saw a change in consumer habits. That's kind of driven us to where our conversation is now and the conversations that are being had with folks that are giving us a call, which is: What are you seeing in consumer habits? And we're kind of in another unprecedented time. I mean, not since Hoover have we seen the use of tariffs like what we're seeing right now. Uh, I mean, you know, to use a little bit of our political science background here, before we went into city management and decided to be a little more apolitical in life, you know, Hoover made some really interesting decisions that, uh, you know, were, you know, very America first, and you know-

Yeah, but let's also state that Smoot-Hawley was passed by Congress, right? So it wasn't-

That is true

... just one person making these decisions.

Yes, that is, that is very true. It was not a, a single... And, and, and to give Rand Paul some credit here, Rand Paul made a pretty impassioned speech, I think, on Wednesday, uh, on, on the floor, where he specifically stated that we should not allow a president to take over taxation authority, which is basically where the use of tariffs is, in hi- his opinion, constitutionally reserved to the Congress, and so... Or the legislative branch. So there are some folks out there that are having conversations. You know, obviously, the Senate can pass a bill to try to take away the authority, but the way the House is set up right now, you know, you're, you're not gonna see that. And to be fair, I'm a fairly free market person. I think anybody who's listened to our podcast over the years would understand that I'm, I'm a pretty strong supporter of free markets, and I don't like market manipulation, except when it comes to zoning. Chad would call that out, but-

Facts.

Yeah, facts, right? I... You know, but our job right now is to provide a level of certainty or a level of floor. Uh, so to, just to kind of give an example of that, I've got a good friend of mine who's, you know, controls a large book of money, is, you know, a basically a financial advisor and trader, and started asking him questions about, you know, "Where's the floor?" There's always kind of a, a market floor, what's referred to as market support. What that means is, is there's usually a large amount of activity that will buy into the market at a sor- a certain point, and you have these floors, and sometimes those floors get broken through, right? So, like, if you look at the 2008 financial crisis, there was clearly some floors that were busted through, and we don't, we don't really know whether we're gonna- we're gonna hit that fully corrective floor and bust through it, or if that floor is gonna prop the market back into more of a stable territory. But right now, that looks like on the S&P, there's a lot of buying activity at about 5,100. The S&P is a little easier to look at than the Dow and the Nasdaq, but and the S&P is also significantly more heavy-centered on manufacturing. And so I, I think when you look at where that is and, and that information, and I appreciate my friend giving me that information from a-... from a trading standpoint, uh, I think that's kind of the next question that we have. Um, the S&P closed yesterday, I think at, at 53 and some change, almost 5,400, somewhere around there.

It's at 5,160 right now.

So it's at 5,160 right now. So we're-

I'm gonna suggest 5,100 is-

Yeah.

It's gonna get blown through.

I think we're gonna bust through a floor, which is, you know, that's gonna put us into a little bit more of a scary territory when we go through a support floor like that. So but, you know, when we start looking at this information, we start looking at consumer sentiment numbers, and, and we started to see this, um, you know, a month or so ago, really with just, like, the prices of gas, the prices of eggs, the prices of some goods going up, inflation really not hedging or coming down. Uh, we started to see consumer confidence numbers start to fall. So we started looking at, um, some of that information, and, and this is where I'm kinda gonna turn it over to you, Chad, and, and talk a little bit about this. But talk about how we come and how we start to guide ourselves because w- you know, we're in projection season, right? Selfishly, we're doing this because we have contracts with cities that are rolling in, where we have to go and project their sales tax for the next 18 months, uh, to the end of the year. Uh, we have to inform our data models. If you use our software, we have to inform, you know, some of that software model that we use there, and then obviously, going into the next fiscal year, we do some projections. And so we are trying to find some leading indicators, right, and some correlated leading indicators. So from there, I'm gonna kinda turn it over, and, and you can kinda talk about, you know, from, from the Department of Nerdery, which is your side of the business, like, what are, what are we doing right now? Where do you see that going, and, and what are we looking at to try to go and look at that? 'Cause, you know, I say this all the time about our business, and I think this is important to say: there's, there's just really smart people doing this work. It's not extra special. So, like, what we're telling you now, you could go do on your own if you wanted to. You don't need us to do it. If you're not a client, no big deal, go do it on your own. Um, you know, if, if you have the ability to do some of this data science work, you certainly can. But I kinda want you to talk this through and me to talk a little less here, so...

Well, that would be a first on this podcast. I don't know-

It would

... if you saw the, the waveforms from last episode. It was like my talking and then your talking.

Mm-hmm.

But that was okay because we were doing a, a thing that was geared around, you know, you kind of setting the stage for us. Okay, so a couple of things. First of all, I started my career in the budget office about eight months before the 2008 recession. I'm kind of sick of being in a countercyclical position. Like, it's great from a, a, a continuity standpoint and from, like, a security standpoint that I've pretty much always been in a job where when, when you know what hits the fan, like, that's when you need me more. But I gotta tell you, like, just in full honesty mode right now, I have never been more worried about forecast season than I am right now, not because we haven't been through these types of situations before, where, you know, like, there's uncertainty and we don't really... you know, the economy's kind of rough. The uncertainty that we have right now feels a lot different to me, and we haven't really been-

Because it's on a whim?

Yes.

Okay.

The last time that we had just sort of like put your finger in the air economic policies was FDR-

Yeah

... during the Depression, where if you've read Amity Shlaes' book, he would literally wake up and decide what the price of gold should be. Like, just experimenting, how can we try to get out of this, you know, this malaise here, um, on a daily basis, just making, making changes to... like, wholesale changes to economic policy. It feels like that's kind of where we are right now. And to, to, to get a baseline for what we should expect, you kinda have to understand where we are. So you hear people saying, "Well, this is all- this is all about negotiation," right? "This is an opening salvo, these tariffs, for negotiations." The truth is, these tariffs appear to have been written by ChatGPT. Like, did you see that thing I sent you last night?

I did, yeah. And can you explain that a little bit?

Okay, so-

There was, there was also some commentators on CNBC, some of the financial networks, there was somebody on Fox Business as well, that was kinda talking us through. But go ahead and talk about the ratio and how they arrived.

Yeah, so we were told that these were gonna be reciprocal tariffs, so that if a s- if a, a state has a 12% tariff on us, we would put a 12% tariff on them back, right? What apparently has happened is we have taken the trade deficit for every country, and in some cases, we actually appear to have used, like, the domain names, like the country domain names, and not the actual country, so that there are, like, territories that belong to other countries where you would think that they would have the same tariff rates as the main country, but instead it's different. Anyway, we've taken the trade deficit. So like, let's say we, we import $100 billion from a country, and we export $10 billion to them, so that deficit is $90 billion, right? Now, we s- it's, it's called a trade deficit, but it doesn't necessarily... it's not a bad thing inherently, right? We don't, we don't grow coffee in America. We don't really have the climate for it. We don't really have the soil for it. So we buy coffee from places around the world who are better at making coffee. It's okay to buy coffee from someone else who can make it better and more cheaply than us, right? So, like, we are getting something for the money that we're spending. But that having been said, the formula that was used for these tariffs was: figure out what that ratio is, and then divide it by two. So in that case, you'd have a 45% tariff that we're applying, 'cause we have a 90% trade deficit, divided by two is 45%. So now we're imposing a 45% tariff-... on this country. There is discussion about whether this is just an opening salvo, and we're just using this as leverage to, um, you know, to do other sort of negotiating tactics. There's also talk about how, "No, this is actually what we're intending to do, and it's gonna raise all this money, and then we're gonna be able to, like, reduce income taxes," which I don't know how you do that when we already have a $2 trillion deficit. Like, what's the point of just shifting the tax burden? But anyway, then we can- when we lower the income taxes, that'll offset the increases in prices. So, like, there's just so many justifications that are sort of floating around, that it's really difficult-

My favorite is-

to know.

Yeah, my... Sorry, my favorite is, which was yesterday, every Republican on talk shows yesterday talked about remodeling a house. "That's what we're doing. We're remodeling a house, and when you remodel your house, it just sucks for a little while." That's-

Well, I've heard, I mean-

... currently what's, what's being said.

You know, the vice president apparently said that, like, this could- it could take a year to see any fruit of this. Let me ask you an honest question here. Given the fact that these tariffs are imposed, are being imposed by the president, which is just one person, who has three and a half years left in his office, and he's term-limited, and if the economy does not flip, his party's probably gonna lose, and these tariffs are probably gonna be taken away, what is the likelihood that these major multinational businesses are actually going to invest significantly in reshoring or onshoring their manufacturing with, like, without having any kind of permanence behind these decisions?

I think the likelihood is extremely low that this method is, is gonna get you there, this, what I would consider more of like a draconian method, that, that they're using is gonna get you there. In my opinion, we are seeing a game of chicken being played with the American economy, right? In a game of chicken right now, there's, there's, like, three players in my mind, right? There's the American president, there's the world economy or world economies that he's fighting against over- overseas or, and Canada, Mexico, wherever, and then there's the markets, right? And right now, the markets have not found a bottom, and they're willing to go pretty low at this point to try to prove a point to the president that this is not what American markets are built on. And so you, you have a game of chicken that's going to happen. The reality is, is that consumer sentiment, voter sentiment, all of those things are extremely elastic on one issue, and it's the economy. I cannot say this loud enough. It's, like, the number one rule you learn in political science, "It is always about the economy, stupid." And if you look somebody in the eye, they're eventually gonna check their 401 statement, and if their 401 statement's down 10%, they're not gonna care who's in the office of the presidency-

It's been down-

or who's in power at that point

... 15% since February 19th.

Right. They're not gonna care. So this is a very interesting game of chicken that's being played that could have drastic and dire consequences, both on the economy and, and politically, right?

So I say all these things just to lay the groundwork, that there's a real possibility that on Monday, all of these things are gone, and we're just like, "Ah, never mind!" Like, because we've already been, over the past couple of months, through a couple of proposed tariffs on Canada and Mexico and et cetera, that either got delayed or we, like, said, "Never mind." If this continues, there's a good likelihood that that could also happen, so there's so, just so much uncertainty. So you have this scenario where this just all gets undone. How do the markets react to that? How does consumer sentiment react to that? Is there still, like, a looming threat that it could come back six months from now? Who knows? There's also a scenario where we actually just implement all of these tariffs, you know, on April 9th or whatever it is, and how does the market react to that? And I say, the market, how does the economy react to it? So given all that uncertainty, we, we now have to help cities project their sales tax for the next 18 months. So that, yeah, I, I, I'm s- I'm super nervous about going into this forecasting season, more so than I was during Covid, for sure. Okay, so let's talk then about sort of our approach because I think that's probably... Like, like you said, you don't have to use us for sales tax forecasting. Like, this is not a pitch for you to come use us. This is more of a, uh, hopefully a just, uh, a helping tool. Just we're just gonna have a discussion about what we would do, and then you can hopefully take some information from that and, and maybe make some better forecasts in this time of great uncertainty. So, the way that we approach forecasting, and really anything that involves uncertainty, is to look at things probabilistically. Prob- probabilistically? Probabilistically.

Based on probability.

Yes, based on probabilities.

Okay.

So instead of j- like, when you've set a budget, you have to just put a number out there, right?

Mm.

But the question that you have to answer as the finance director or the city manager or, you know, whatever, is, how likely is this number to occur? You know, if I set my sales tax budget at 50 million, do I have a 40% chance, an 80% chance, a 12% chance of this actually occurring? And what is my exposure? So risk is the measure of uncertainty. Exposure is taking that uncertainty and converting it to actual, like, a dollar amount. So w- when we do our sales tax forecasting, it's all based on the range of possible outcomes that we think are likely. So we use a 90% confidence interval, and that's based mostly on just a really deep dive analysis of the city that we're looking at, looking at h- how have they performed over the past several years. We look at various economic indicators and try to correlate those as b- best we can. We're, we're in a, an additional sort of weird thing because over the past 12, 13 months, there's been a lot of weird audit adjustments in our sales tax data, so you also have to account for that. We're also sort of buoyed by the fact that we still have a lot of population growth in Texas.... So there's a lot of noise in that data, and it's kind of hard to, to reason through sometimes.

So we look at housing permits, we look at growth. Those are things that we put into our model because of the- of what we see in Texas from a growth perspective.

Yeah.

Sorry.

So- you're fine. So we, we tend to look at the industry level, you know, retail, and sometimes we'll break it down further, department stores, you know, clothing stores, home, uh, like, home improvement retails. Whatever the individual city needs, if they have something very specific in their city that, that needs to be called out explicitly. But then we look at a month-to-month basis, and we set confidence intervals on where we think that that particular industry might grow or decline on a monthly basis. Typically, we are a lot less confident about what those numbers will look like the further away from today we are, right? So, like, we may be pretty confident, in a, in a normal situation, not in a situation like today, where who knows what's gonna happen. But say last year, you know, where there was a little bit, like, inflation was still kind of high, but, you know, we, we were kind of settled in to it. In the first couple of months, that, that 90% confidence interval may not be, like, too wide, uh, because we have a pretty good feel for, you know, how certain types of industries are going. But when we get 18 months out, those confidence intervals are gonna grow. So once we have these confidence intervals, we actually will run simulations on the sales tax data. So we're doing what's called an autoregressive forecast, where we're predicting on previous predictions, kind of like how ChatGPT works, right? Where it's predicting on the previous tokens and words that it's already made. So we use an autoregressive simulation engine, and all that really means is that we're just gonna run these forecasts thousands of times. Once we have these simulations and all these results for every month, for every industry, uh, in some cases, for every taxpayer, we roll that up, and that gives us a range of l- what we consider to be likely outcomes for your sales tax collections. This allows you to say, "In 30% of my simulations, we generated this amount of money," which is actually gonna be on the high side, right? 30% of simulations is, is gonna be on the, on the upper end. At the median, we generated this amount of money, and then on, you know, say, 80% of the time, we generated this lower amount of money. So when you actually set your budget, you have, you have a little bit more confidence about how likely each individual dollar amount is to occur.

So when times are-

One real benefit of this... Do what?

Yeah, I was just gonna say, so when times are good, to put that in, into, like, my world, right? When times are good, I may be a little bit more willing to project-

Towards the median.

Right, take a little bit more risk.

Or higher, right. Take a little bit more risk.

Yeah.

So-

Take a little bit more risk, and, and hope for a higher sales tax dollar. When times are uncertain, I'm gonna want my projections to have landed 80 to 85% of the time, which means the number that I'm projecting is lower, so.

What this- yeah, what this also helps you do is, let, let's just say that you, uh, you've set, uh, a median... Let's say you set your budget at the median, and say that's $50 million. When you get into, um, your budget discussions, and, you know, maybe there's a half a million dollar project that council really wants, and the only way to do that is to bump up your sales tax projections in the budget. Well, if going from 50 million to 50.5 million takes you from, you know, a 50% chance of hitting that target to a 43% chance of hitting that target, then you can measure the ex- the, the risk that you're taking by increasing that budget half a million dollars or whatever, you know, whatever the case may be. So there, there are, like, tangible managerial benefits to thinking about things in terms of probabilities. You can quantify the risk that you're taking by setting a budget. But also, it's just, especially in times like this, where, like, we really don't have any good idea about what to expect, I really can't think of any other way to do, uh, a forecast for, for sales tax in particular. Like, property tax, you know, whatever, January 1st, those values are set. Not super concerned about that right now. Maybe next year it could be a problem, but for the upcoming budgets-

Property tax, you can... Yeah, I mean, property tax, you can take a random sample of properties, grab some MLS data, figure out what the spread on those properties is from, you know, what they were last year versus what the MLS put 'em in in the new side, and, and you can... I, I don't- there's more certainty in property tax data. Uh, still important to have a model.

It's also much, much slower.

Yeah, much slower.

Like, it, it's, it's a lot less elastic. Sales tax can change overnight, which we saw during COVID.

And what-

As soon as we locked down-

We probably are seeing right now.

I don't know. We'll know on Wednesday.

Yeah.

Uh, although Wednesday is gonna be-

Six days

... when April's data comes out, that's for February sales, right?

Right.

So we may not know for two months, really.

So let's talk- let's talk about that right there, though. Right? Let's talk about the things that we're doing, 'cause we're, we're eventually gonna write a newsletter and try to get this out to all of our clients, but let's, let's talk about what we're trying to do to try to create a little bit more certainty within that two-month lag. Right? So kind of like Gavin's work, the stuff that he's been working on overnight, when I, when I say legitimately overnight, uh, thank you, Gavin.

Three o'clock in the morning.

Two o'clock in the morning last night to get us ready for at least to have a conversation today on this podcast.

To not have kids.

Yeah, exactly. And-

I remember those days

... we don't, we don't talk about, we don't talk about Gavin a lot.

But I, no, I, I built Zactax, uh, largely at two and three o'clock in the morning, you know, ten, 12 years ago.

And all I did at that point is respond to Chad when he sent me texts and say, "Yeah, that's awesome," or send emails to city managers. Uh, thank goodness for delay send when, when Gmail came out with that, 'cause I didn't look like a psycho working at two o'clock in the morning. Uh, but a little intro to Gavin. We don't talk a lot about Gavin, uh, but Gavin's our data scientist. He is finishing up his degree at Rice.... We are very blessed to have him, uh, and he does some incredible analysis work behind the scenes. So, so that is one area where it's different, Chad, than 2007, uh, and also COVID.

And 2020.

Right. Uh, in 2020, where, you know, we, we have invested significantly in data science and continue to invest in that because that's where things are going, obviously. Um, and, and we need that. But talk a little bit about trying to find correlation within leading indicators, uh, and what we're doing there to try to find those correlations so that we can show two, three, four months down the road where we think things are gonna go based on, uh, specifically what we're looking at now, which is like a consumer sentiment index, right? So kinda go there.

Yeah. Right now we've got Gavin poring over consumer sentiment data and trying to find any kind of correlations or, like you said, just leading indications about where sales tax is heading. I mean, I don't know, how much do you wanna get into this? He's got a lot of fancy charts and graphs in here. The thing I love about Gavin is that he's even nerdier than I am, and so when it comes to, like, building really statistically sound forecasting models, like, he's just so much more advanced than what I can do. But yeah, I mean, that's one area that we're trying to look at. We've got probably five or 10 other data points that we're trying to incorporate into this and see which, which ones give us the most predictive power. 'Cause right now, even a, even a two-month look ahead is better than nothing. Um, and so are there, are there historical times when we can go back and look? It doesn't do you a whole lot of good to be able to predict in the good times, right? So we need to find the data points that help us understand what's happening when there's a lot of uncertainty in the economy, and so that's kinda what he's, he's working on right now, is what can we find-

Yeah

... that will give us any kind of indication of where we're headed, even over the next three to four months?

Jerry-

We're also looking at things called, we call, uh, bellwethers, and so, you know, what communities are there that, that give us a hint of what's coming, right? There's a lot of cities in Texas, in particular, where you can get a really good indication of how certain industries, like oil and gas, are doing. When their sales tax starts to decline, that's a pretty good indication that, that we're pulling back quite a bit on oil and gas work. But that's a really small sector of... I mean, it's a big part of Texas' economy, but it may or may not be all that important for what we're dealing with right now. So given other situations that we've encountered over the past, 'cause we have data back 30 years for sales tax. So-

Because at some point, Chad thought to himself we were gonna start a sales tax analysis company and just started grabbing data from the controller.

Scraping data from the controller, like, 15 years ago. Yeah. It's worked out-

But-

... because, yeah.

Yeah. We have the data now. So, so to dig in that a little bit, I mean, I- to put this kind of in terms of something that, like, a, a city manager can understand without having to have a data science person, right? We used to always say this in a budget process, like, when we were simpletons back in the day: trash tonnage, right? And, uh, Jerry over at Republic, uh, Steve at Waste Management, they're gonna love me for this, but if I was a sitting city manager sitting at my desk right now, and I wasn't gonna be able to get data from us at some point or something like that, I would certainly go ahead and request your trash tonnage by month for the last five years, right? I'd try to get myself past 2020, maybe go to 2018, especially if you've had the same vendor, because that's an easy early indicator of consumer behaviors, right? If trash tonnage drops, then you most likely are seeing consumer behavior drop, and you're gonna see some impact in sales tax. So shout-out to Robert Hannah, he's the one who taught me about trash tonnage and using that as a leading indicator.

Do you think that we should explain why that's tends to be correlated, or is it pretty self-e-evident?

I think, yeah, I mean, we can. You know, obviously, if you-

The more you buy, the more trash you have

... if a consumer stops consuming, right, they, they produce less trash, and if you pollute- produce less trash, the correlation is, is that you've spent less money, right? You've spent less money, sales tax is gonna fall. That's, that's the thought process. There's also some, like, interesting things to look at, like commercial container tonnage versus residential tonnage, and look at those, those differences. You know, you obviously have to take your growth rates into account. Like, if your city grew by 30%, you've gotta factor that in during that period of time to make sure that you're, you know, you're not just looking at straight tonnage, but you're, you know, factoring that in for, like, a per capita measurement or something like that. So I, I think it, it's just overall, you're trying to connect it to a consumer behavior so that you can connect it to a dollar spend, so that that can be connected to what happens in sales tax. We've got better data now for us to use, where we can go use these, you know, consumer sentiment indexes and go look at how that impacted. Because you've been getting data for so long, and you've got 30 years of it, we can go look at all the downturns over the, the 30-year period because there were, you know... We, we technically have, like, the, the '90s downturn in our data too, don't we?

Uh, yeah.

We probably do.

The high-level data, we do.

Yeah, the high-level data. So, so we're looking at multiple different downturns, uh, you know, September 11th, um, you know, you're, you're gonna see that.

Dot-com boom.

Dot-com boom, yeah, you know, financial meltdown of '07 and '08, uh, and obviously COVID. Um, and there was kind of like a mini dip in, like, '14, '15, which was just kinda more like a, you know, stable. But, um, but we're gonna be able to pull that. I just think it's important, you know, as, as I get phone calls, and that's, that's why I wanted to do this podcast, I wanted to hear from people-... how we logically connect the dots. And y- to be fair, Chad, you have expressed more concern and worry here than I've probably seen from you in a very long time. I mean, 2007 was hard, right? I mean, y- yours and I's conversations in 2007 were pretty rough, too, to be fair. I felt like in COVID, we were more sure that things were not gonna be as bad as they really were.

Yeah, I mean, to me, COVID was like y- you, you kinda knew that at some point, the pandemic would be over, and it was just a question of, like, how can we get through the initial, like, craziness?

Right.

What's life gonna look like in the interim? And then how quickly can we get vaccines? And it turned out that was, like, eight months, right, before we started getting vaccines. And then case rates started to plummet, uh, particularly in states where vaccine adoption was higher. Um, 2007, so let's talk about that 'cause we were both so green-

So green

... in 2007, 2008. I mean, my first city job, I got hired in January 2008, like, my first actual city job, not as an intern or whatever. You already had a few years of experience kind of working in cities, but, I mean, neither of us had ever been through anything like that, obviously.

We were also sitting at a city, to be fair, I had technically rolled out of that city at that point, but we were also-

Yeah, but now, but then you were in a city that was totally dependent on sales tax.

Totally dependent on sales tax.

So.

Which is where I learned about trash tonnage correlations. But we were both in a city that not only... At that point, you were still there, but they had not done things well financially at that point. And so not only were they getting hit with a pretty extreme downturn, but they had made some really poor decisions. Previous management had made some really poor decisions. You know, we used to call it the wizard there, but-

Really?

You had a city manager who would say, "Uh, everybody needs to go through and cut the budget three to six percent," and then right at budget season, it was like: "Oh, we found money. No big deal. Don't need to cut it." And the reality is, that money was never found, right? We just kept spinning it down cash balances until we figured out that we didn't have the cash balances that we thought we did.

Until we did the audits-

Uh

... and we realized, yeah. But the good, I mean, the good thing is that that actually happened a year before. So that city had already kind of laid the groundwork for slowing down, making some changes, and when the economy totally collapsed, they were, they were much more well-positioned-

Yes

... to deal with it because we had already had to go through that process, you know, six to eight months beforehand. It didn't help that it, it was a mid-year adjustment because those are always chaotic, and, and you end up making bad decisions when you, when you have to do something quickly like that.

Like, you stop mowing parks.

Yes-

You know

... and you stop fixing roads.

That was a bad decision, yeah.

I don't know. I mean, I feel like I wasn't all that nervous about 2008. Like, it sucked-

Okay

... but maybe I was also, I was also, let's be honest, much more of, like, in a doge mode in 2008. I was like, "Yeah, let's just cut everything now!" I feel like I'm a little bit more measured in that regard now, having, you know, 15 years, 17 years, almost, of experience in and around this field. That being said, uh, yeah, you're right, I, I do feel a lot more nervous about where we are right now, and I, I, I think that that is mostly to do with just the fact that we don't really know... Like, th- this right now is a self-inflicted. In 2008, it was also self-inflicted, but it was the result of 50, 60 years of housing policy that finally caught up with us. This is just like, we just wanna have a trade war, so we're gonna have a trade war.

Housing policy's kind of back, but-

Yeah.

Yeah, I don't know if you look at-

It's not as bad, but yeah.

It's not as bad, but if you look at, uh, delinquent loan levels, it's pretty high.

Yeah.

So-

For different reasons, but yeah. So I think that, to me, is the bigger cause for concern, is that, like, this could all just be over tomorrow, or it could just make- it could be made worse tomorrow. And so, I mean, I just feel like that extra variable adds exponentially more uncertainty to where we are. And I really don't know how the average person is going to respond to this, uh, when it comes to just retail spending. Like, surely-

Yes, I think also-

... food's gonna be down. Like, people are gonna stop spending at restaurants, although maybe not, because now DoorDash is allowing you to buy your burrito on credit, so...

Should be a sign right there.

There, there are signs if you are willing to look for them, yes.

If you're making, if you're making three to five payments for your burrito from Chipotle on DoorDash, there should be a sign.

I did that when I was in college, but that's 'cause I didn't understand how credit cards worked very well, so.

Yeah, uh-

We would go out and, like, buy everyone's Taco Bell, and then I realized I was still paying for it a year later.

I will say this: city managers, when it comes to economic downturns, not in general, we're usually very optimistic individuals, right? You kinda have to be, uh, to work in this business. You gotta be optimistic about what the future is 'cause you're getting usually beaten to crap in, in the current reality that you're in, right? But in economic downturns, city management professionals, budget officials, finance directors are typically more pessimistic in their mindset than what our actual data will show. That we know, right?

Especially-

And so-

... we saw that in COVID.

We saw that in COVID. We saw some cities, and I had lot... I, I reached out to a lot of managers and said: "Hey, hey, don't..." You know, sending out memos to staff and things like that, and, and, and saying things that, you know, revenues were gonna be down 60% and, you know, just crazy things that I, you know, would pick up the phone and call people and say, "We, we just don't see that in the data." So I'm saying this ahead of time, as we're in the second day of a market freefall and, you know, obviously 45 days in at this point into, you know, negative market territory. I say this out loud so that everybody hears it.... don't do anything drastic right now. We're gonna, we're gonna provide some data. We're gonna provide some leading indicators. I do feel strongly that we're gonna be able to give you 60 days of heads-up before things turn, right? And so there's no reason for you to, on a Friday afternoon, write a memo, right? I'm gonna tell everybody here what I wrote in our staff announcement on Basecamp yesterday, which was, "Hey, this is a period of time of uncertainty that hits, and, you know, we've got some new staff members. We've grown quite a bit." And I made the statement that we're probably gonna work harder right now than we've worked in a long time. We're gonna get a lot of phone calls. We're gonna have a lot of people who reach out to us, and we need to provide information and data, be a listening post, and also, we need to connect those individuals that are decision-making- makers with Chad or me at any time, that we need to make sure that, that they have that availability. It is extremely important that folks just kinda step back, take a breath, let the data do the driving at this point, and we will make sure that that data is out there through newsletters. So if you're not a client, go to our website, sign up for the newsletter. We're gonna get information out there so that you can see it, and so that you have a better idea of what statewide data is gonna look like from a leading indicator standpoint. So we're working on it. Gavin was up at two o'clock in the morning working on it last night. We're gonna continue to work on it, and we're gonna get that stuff out there. I thought that was why it was important for us to come on and do this podcast now, because I think you're gonna have city managers go home after 8% losses on the market over the last two days. You're gonna have city managers go home, and they're gonna start thinking about the worst, right? They're gonna start thinking about: "What do we need to do to shore up finances? What programs do we need to cut?" And you have to remember, all of those decisions have consequences, right? So making those decisions too early can also have extreme consequences. If you kick that road project down the road three, four, five months, you may have price increases on imported steel. There's consequences to everything we choose and what we do. So I think we can kind of sit back for a minute, figure out what the data's gonna do, and then make a decision from there.

Yeah, I, I agree a 100%. I think we probably, at some point, will have a budget-focused episode as we get more into the summer. If I can maybe offer some perspective here, okay? Generally speaking, we are both of the opinion that most cities are functionally insolvent anyway. Is that a fair statement, like long-term?

I think most ci- lo-

Many cities are functionally long-term insolvent, given our development patterns and the amount of revenue that those generate versus the costs that they, they bring to it, the obligations they put on us.

And I do wanna say to the end of that, though, but there is time, especially a city in the state of Texas, there is time to make changes to how you develop to ensure that this-

Yeah, yeah, yeah

... does not continue into the future.

All I'm saying is, at the end of the day, this is gonna be... It might be a pretty big speed bump or, like, a, you know, a, a big blip, but we've been through recessions before. N- nothing that we do, I think, needs to have a super drastic reaction. You should have yourself set up to handle, in the short run, a situation like this. You've got cash balance, you know, you, you've got flexibility in your budget, most likely. I would recommend just generally not, like, still do your street maintenance this summer, but I don't know, h- however bad this could get, and it may get really bad, we don't have any idea right now, and so probably the worst thing you can do is to be rash and make, make a quick, big decision that's gonna be hard to undo. Like, you can always pull back. It's a lot harder to fix a decision that you made quickly that ended up being the wrong one, and we sa- like, we saw that a lot in 2020. We saw several cities make big cuts, and then two months later, sales tax was growing by double digits, and then it's like, "Well, crap, now what do we do?" You know, we just- we've furloughed all these people, or we laid off s- you know, people, and, and now we don't have the staff to provide the services that we are obligated to provide, that we have committed to providing. Just don't put yourself in that situation. You've got time to figure this out. We've got time to let these things kind of sort themselves out and get a better sense of where we're headed, you know, before you have to finalize your budget, and you can finalize your budget for next year with some extra flexibility in case it gets worse. So yeah, just use the data, take your time, and make a good decision versus kind of going into panic mode and trying to, trying to just react to, to the stuff that we're seeing. 'Cause stuff that we're seeing is kind of scary, to me at least. Like, I wouldn't want to be a city manager again right now, but it doesn't mean that we have to make quick, rash decisions. We still need to be professionals, take our time, use the data, and move forward in a, in a reasoned and logical way.

Let me wrap with this. Ladies and gentlemen of the city management movement, industry, find yourself a Recess magnesium drink or a strong whiskey, take a deep breath, and relax a little bit.

Apparently, Costco had, um, Basil Hayden Dark Rye for, like, $37 last weekend, but only-

No!

... in Houston. I know.

Okay.

That's, like, 40% off.

That's way, that's way cheap.

Yeah, but the-

I'm a big Basil fan

... arbitrage to drive to Houston for it wasn't, it didn't make sense.

You started calculating those numbers, though, didn't you?

You don't even have to spend a whole lot of time. You just do some quick back-of-the-envelope math.

For my friends that don't drink, if you have not had a Recess beverage, uh, which are sold, like, in the specialty beverage section of, of your local H-E-B store, if you don't ha- if you've never had one, it's like a magnesium drink, a high-magnesium drink that gives you that same, like, relaxed feeling that you get from, like, an alcoholic beverage but without the alcohol. So for those of us that have gotten very serious about our fitness chat-... and don't wanna ruin that fitness with our alcohol, um, you know, that's, that's a, that's another option for you. So

It's, it's a good life choice.

Yeah, I did love on the, the chat last night that you made fun of me. Uh, was it you that made fun of me about my pre-workout behaviors?

No, that was Allison.

I, I think it... That was Allison. Okay, thanks. I appreciate that. So anyways, that's all, folks. That's all we had today. We just wanted to get this message out there, and we wanted you to know what we were doing behind the scenes and what you could be doing behind the scenes to kinda give yourself a little level of certainty. As always, you can reach out to Chad or I. It's just our first name @zactax.com. Uh, so it's Patrick or Chad @zactax.com, and we are happy to respond out to you. Uh, most folks out there have our cell phone numbers as well, uh, so feel free to reach out there. I've had lots of those phone calls, including the one this morning at-

Just text me, though. I don't answer the phone.

You don't answer the phone unless I call, so... You answer your wife's phone calls.

I answer- Yeah, but she, if she calls me, something's going on. Like-

Something's up

... there's a problem.

Yeah. So but that's it, man. You got anything else you wanna chime in on? Uh, the latest, latest news is employment data came back a little more positive, but we adjusted the last prior two months, so the unemployment rate went from 4.1 to 4.2. So a little uptick in the unemployment rate happened this morning as well.

So here's just real quick about the un- the, uh, the, like... Every month, the prior months get revised down. Feel like after a certain amount of time, you should expect that and adjust your real-time calculations an- accordingly, but that's just me. Maybe the... I, like, I don't know all the inner workings of how those surveys are done, but it feels like if you're constantly having to revise down historical data, you could probably account for that when you're actually putting it out the first time.

It's- it has been the predominant revisions lately. I mean, it's, it seems like we're revising down every single month on the release of unemployment data. So yeah, GDP data has been revised down significantly as well.

You see the Atlanta Fed's e- estimates?

Yeah, Chase, Chase increased their, uh, likelihood of a recession from 40% to 60% due to the tariffs after the first couple of days of the market reaction as well. So the Atlanta Fed is projecting a negative GDP.

You saw that, Chase? I just looked at my portfolio again.

It's unfortunate.

I'm trying to pull the Economy Now app up.

What is the, what is the Atlanta Fed's GDP prediction?

Uh, they said, I believe, uh, more than 3% decline for Q1.

Okay.

Which obviously-

Yeah

... just ended, so. Now, uh, let's see, 2.8% is the latest-

Okay

... GDP now estimate.

A decline of 2.8%? Wow!

See that there? Is that focused?

Yeah, sorta.

Yeah, so that's, that's not good.

Yeah.

Not good, Bob.

So-

All right, we should wrap up.

We should wrap up. So thanks for joining us, guys. I hope you... If you got any questions, reach out to us. Uh, happy to be available at any given time. We are here for you, and, uh, we'll be back with another episode here in about a week and a half, I believe, would be our normal scheduled time. So we'll see you then.

Bye, Pat.

Bye, Chad.