Ladies and gentlemen Let's start with the next panel because it's an exciting one and we have inherited five minutes delay So we need to get going The next topic is life Below zero bank lending under negative policy rate is quite an exciting topic. This is a new monetary policy tool Which does not have proven track record yet. There is not much academic research on it and it's also controversial tool Not so much perhaps as to its effectiveness Effectiveness which is still being studied, but in particular when it comes to the next step Of the transmission mechanism and whether it is legally possible and economically appropriate to pass it on To negative to to to the customers the negative rates The fact that Negative yields can also arise in a negative rates environment for certain bonds Has also been raised by the German constitutional court recently to the European Court of Justice Wondering whether buying bonds that have an negative yield does not in fact amount to Financing government now all these issues are not for us today today We are focusing on an important aspect of this uncharted territory Which is how the policy rate transmits in the economy in a situation of negative rates on this topic We will hear Glenn Shepherd He will present the paper he has authored together with Florian Hyder and Farthad Saidi Glenn is an economist in the financial reserve division of the ECB and His primary research interest is financial intermediation banking and financial regulation So obviously he was attracted by this particular topic and Before joining the ECB he worked in the National Bank of Belgium obtained a PhD in the in economics in hand and His work has been published in many places, but among others in the Journal of Financial Economics And then as discussed and we are very lucky to have and to welcome here about at the Han who is since 2011 professor of economics at the London School of Economics and his co-director of the Center for macroeconomics and program director of the Center for Economic Policy Research of the CEPR Professor Han obtained a PhD at Carnegie Mellon University in Pittsburgh in 91 and then moved to California as many people do To San Diego where he started as a system professor and became professor in 2001 And then he had positions in many places must be a frequent traveler So London Business School University of Amsterdam and served also as editor of the economic journal of economic and the Journal of Economic Dynamics and control, so He is a research focusing on macroeconomic models and heterogeneous agents I'm sure he would be very qualified to discuss this unchartered territory Presentation and without further ado I give the floor to Glenn Thanks, Kara for this nice introduction. So good morning everyone. So in the next 30 minutes I'll be talking about our paper on Bank lending under negative policy rates as Kara already mentioned this papers joint work with Florian Haider who's also at the research department here in the ECB and With Fazid Saidi who's at Stockholm School of Economics and given that Florian and I are at the ECB The usual disclaimer applies. These are our views and not necessarily those one of the European Central Bank now as the title already Indicates in this paper. We're really very much interested in whether negative rates are anything special. So in whether Bank lending behavior under in times of negative policy rates is anything different from times of Positive rates second. We also very much interested in if this stick in if in if this the case Why is this the case? So what are the mechanisms behind this change in behavior and then third? We're we also want to learn something what about what the potential consequences might be for firms for borrowers and for for their investment behavior and for ultimately for the real economy But before going deeper into all this let me first talk a little bit about the motivation for this paper about why we think these are very interesting questions to ask so I I'm sure that a lot of you or everyone here is aware of the fact that monetary policy has been Unchartered territory for quite a while now. So ever since the 0709 Financial crisis a lot of central banks have resorted on non-standard monetary policy tools such as large-scale Asset purchases for and for guidance in order to revamp the the post crisis economy in order to get back to Inflation targets some central banks such as the ECB, but also the Riggs Bank in Sweden the Swiss National Bank and a number of others Have even moved policy rates into a negative territory while others have either implicitly or explicitly Spoken out against it. So this seems to be a somewhat controversial issue and on top of that while by now we have quite some Interesting papers and a fast-growing literature on the impact of large-scale asset purchases on On bank lending behavior. We still know very little about the actual impact of negative rates And that's exactly where this paper comes in So in this paper as I already mentioned we're very much interested in whether this transmission of bank lending is anything different during times of negative rates Why this might be the case and what the potential benefits and costs costs might be both for banks But also for borrowers and their investment behavior So let me immediately give you the main takeaways of our of our paper and then for the remainder of the presentation I'll focus on Explaining how we got to this conclusions So first and then and definitely the most important finding in this paper Is that the transmission of negative rates indeed seems to be somewhat special? So it seems to depend a lot on a bank's funding structure So what we show in in this paper is that banks that rely more on deposits to to fund their activities Have a high incentive to increase their risk taken and reduce their lending compared To banks that rely on other sources of funding and importantly we do not find such an effect for low But negative rates so this impact or this effect that kicks in due to the deposit funding is really something that is Specific to times of negative rates and I'm going to talk a lot more in a couple of minutes about the exact mechanisms Behind this but allow me to already mention that a lot of this will have to do with the fact that there seems to be a Very hard a zero lower bound for customer deposit rates So banks seem to be a very reluctant to charge negative rates on Customer deposits and this will lead that during periods of to the fact that and this will lead to a Funding cost disadvantage for banks relying a lot on Deposits during times of negative rates, which will Which will in the end Eden in into their net worth and lead to an increase in risk taking and Reduction and lending for these for these type of banks No, so once we've established these these findings we try to dig a bit deeper and Talk a bit more about How these risks are effectively materializing and what the impact is for the real economy now We have a lot of results on this in the paper And I'm not going to go through through all of them here But allow me to to pick a couple of them out of out here So first of all, one of the things we observe is that while high deposit banks indeed seem to lend less and take on more Risks they also seem to focus on new risky borrowers So borrowers that were not active in the market that we're studying before rates became became negative And this already seems to indicate that there might be some a bright side to this increase in risk-taking once rates become negative namely that banks that are were That were more constrained in the past and now seem to be able to get access to bank loans Second another another finding here is that we observe that safe borrowers seems to be switching to low deposit banks while More risky borrowers seems to switch to to high deposit banks So there seems to be a change in the matching between firms and banks which might have important implications for for financial stability and third what we also observe is that the borrowers that are or the new borrowers in our data set that are effectively getting the loans are also using these loans to increase investments and not for example to build up cash buffers Now where does this Place us in the in the existing literature. I'm not going to go through all these papers here Just allow me to say that apart from the the new and quickly Emerging literature on negative rates and their impact on bank lending We're also very very closely related to a longer strand of literature on the transmission of policy Positive policy rates on both bank lending and bank risk-taking and to a more recent strand of papers that looks at the impact of non-standard monetary policy on on bank lending Now for the remainder of this presentation what I'm going to do is first talk a bit more about the hypothesis development For this paper and the framework that we have in the back of our minds when trying to answer these questions Then I'm shortly. I'll shortly go over the data and some identification issues and then I'll walk you through the main results of the paper So first hypothesis development and just to make absolutely sure that we're all On the same page here in terms of in terms of context for this paper Let me put up this chart where which I'm sure that a lot of you are very familiar with and shows the evolution of the three main policy rates in the eurozone and the eonia so the Overnight interbank rate so from top to bottom We have the marginal lending facility rate the MRO rate then the eonia the interbank rate and then the deposit facility rate and what we'll be especially interested in in this paper is the moment that the deposit facility rate Becomes a negative so around so that's in June 2014 and during this period These deposit facility rate is effectively the main policy rate due to the fact that there's lots of excess liquidity in the system And this is for example illustrated here by the fact that the only has very closely following this deposit facility rate during this period So what we're going to do in this paper is basically compare Bank lending behavior before and after this this dip into a negative Territory or during the period of negative rates Now what's the The analytical framework that we have in the back of our mind when trying to answer these questions Well, first of all, we think it's a very important to remember that bank risk-taking highly is highly dependent on on a banks and net worth so a lot of theoretical moles out there see banks as institutions that have opaque assets which require costly screening and monitoring and Importantly when a bank has Doesn't have much skin in the game So when it's net worth is is low There will be a lot of moral hazard and an agency problems around which will lead to lower screening incentives for these For these banks and which will lead to a more risky Investments on the asset side at the same time and interestingly enough We can also think about bank lending as being in a function of net worth So basically the literature on the external finance premium applied to apply to banks So typically a lower net worth will read to a reduction in a bank lending due to the fact that the slower net worth will Will typically lead to higher external financing premium making it harder for the bank to get access to external funding to To finance these new loans so the main takeaway for this For this slide is that we can easily think about bank lending and both bank risk-taking as being a function of net worth which makes it easier to think about the impact of monetary policy on on these on both on both lending and risk-taking so putting it very generally Monetary policy will typically affect banks net worth via true ways via an asset side channel and liability side channels on the asset side Reduction in policy rate reduces loan rates and in that way reduces net worth on the liability side The reduction in policy rates will also reduce the cost of funding and in this way increase in net worth So in normal times we typically think about this as a liable the liability side Dominating because banks typically engage in maturity transformation So they have short-term liabilities and long-term assets making this liability side dominate during times of positive policy rates However, and very importantly, there's something Particularly going on when rates become negative and this is that this liability channel Will be shut down or will be partly shut down for banks that mainly rely on deposit funding and the simple reason for that is Is that there seems to be a very hard zero lower bound for for deposit rates? So this graph shows the evolution of the overnight deposit rates for non-financial companies the overnight deposit rates for households and for the Ionia between 2009 and 2016 so the Solid line is the rate for for non-financial companies the the dashed line is the rate for for households And and the dotted line is the Ionia. So what we're interested in is in is in what's happening around June June 2014 because there we see that while the Ionia keeps following the deposit facility rate that is going below zero around that point the deposit rates flatten out above Zero above zero just above zero. So there seems to be a very hard zero lower bound for customer deposit rates Now this has very important Implications for the for the channels that I was just describing because it means that the liability side channel will be shut down For banks that mainly rely on on deposits to fund their activities So these banks will not benefit from a reduction in their cost of funding and hence will experience a relative reduction in In their net worth which will lead to high risk-taking incentives and less lending by these high deposit banks So what we're going to do in this paper To wrap this to wrap this part up is simply compare the lending by banks with different extents of deposits funding before and after Policy rates became a negative And what we expect to see is that for high deposit banks relative to low deposit banks a decrease in the end their net worth Which leads to a relative decrease in their lending and an increase in their in their risk-taking? And let me stress here that the the word relative is very important here So all the results that I'll be showing throughout the remainder of the of the stock should be interpreted as An impact on high deposit banks compared to or relative to a group of low deposit banks banks that rely on different sources of funding now In terms of the the data that we're using So we're mainly we're going to be looking at syndicated loans So we're using a deal scan to get the syndicated loan data So the firms in this in this data set will match with Amadeus to get information on the balance sheets and the profit and loss Accounts of this firms we do the same thing for for the banks that are granting the loans But here for we use SNL data and we'll do this for the period January 2013 till December 2015 For the main part of our analysis and robustness checks. We even go back to 2011 So all the data on the loan site will be on the on the monthly level the other data is on the on the yearly level The baseline measure of risk-taking that we'll be using Throughout our main analysis is the ex ante a profit volatility of the firms that are getting the loan So for each loan that we observe in this deal scan database, we will calculate a proxy for it for its riskiness by Looking at the volatility of the profits of the firm that is getting the loan during the five years Before the loan is is being is granted And the exposure to treatment in our in our setup will be the deposits or the average deposit to asset ratio of The banks in this indicate that are granting the loan and that's in 2000 at the end of 2013 So the moment just before rates became became negative Now the empirical setup then then looks as as follows So we will be having it will be using a fairly standard difference and different specification With on the left-hand side, we'll have our risk or lending variable of interest and on the right-hand side Our main coefficient of interest will be the beta one which is the coefficient for the interaction term between The deposit ratio and and a dummy equal to one during the period of negative rates now when estimating this this type of Regressions one runs into a number of identification challenges and here there's basically two main identification challenges. So first of all Monetary policy also typically affects a firm's demand for loans So for example simply think about an at work channel or an external finance premium channel That is there at the at the firm site So lower rates leading to an increase in the net worth of firms leading to a potential increase in loan demand So this might buys our estimates of what how the the change in policy rates really impacts the the supply of loans by by banks and Secondly a monetary policy also obviously reacts to two economic conditions. So it's it's very very likely that the reduction in rates Was is being done due to the fact that the economy is in is in a bad state and at the same time this bad state of the economy might might also lead to Pull of borrowers that is more risky than during normal times or In general a lower a lower demand for loans now the way that we're go We're going to try to tackle these problems in in our papers by trying to ensure That are treated in our control groups or high and low deposit banks are Facing a very similar economic conditions and are are are facing very similar Barbers are facing a very similar demand for loans So in order to do that we take a number of steps So first of all we saturate our specifications with country year and industry year fixed effects in order to make sure that Borrower demand in these groups that these different banks are facing is fairly fairly similar in some specifications We're even able to look at within firm year Variations so which allow allows us to even more properly control for for demand effects in robustness checks We'll then also look at lending to borrowers outside of the euro area because it's less likely that the monetary policy In the euro area reacts to economic conditions outside of the euro area And also it's it's less likely that the demand of these firms outside of the euro area is heavily impacted by monetary policy decisions of the ECB and finally we'll have a placebo test around July 2012 which is When rates were reduced but all but we're still in positive territory and there we will Basically show that we have no Difference in the lending behavior between or risk-taking behavior between high and low deposit banks during during this period Again showing that this this impact of the deposit ratio is something that's very specific to to negative times Okay, let me then walk you through the the main results in the paper So first of all the results on on bank Risk-taking so the first four columns in this table show Regression results were on the left hand side. We have the the profit volatility so our main risk variable So the period here is 2013 to 2015 We have monthly data on on these loans and what these tables basically show is that we get or what the first Fallen the first four columns basically indicate is that there is a positive and significant Coefficient on the interaction term between the deposit ratio and The and the dummy equal to one during times of negative rates So implying that indeed these high deposit banks seem to take on more risk once rates become negative relative to this group of low deposit banks and this seems to be also Quite significant in economic terms because there we see that a one standard deviation increase in the deposit ratio leads to a 16 to 90 19% increase in loan risk depending of the exact Specification so the the only difference between the first four specifications in this table is that we gradually Saturate the the regressions with with a set of fixed effects Now in the the fifth column of the table we expand the sample period to 2011 2015 And this allows us to look at what's happening around the reduction in rates in July 2012 so when rates were still positive and there we see no effect at all or no difference at all in the reaction between high versus low deposit banks Showing that this channel that we're describing is really something that's particular to times of negative policy rates then in the last two columns We then look at the sample of non eurozone borrowers and there we again see that for the eurozone Landers in that sample there is an increase in risk taking for the for the high deposit banks while we do Well, we don't see any effect if we if we study loans to that same set of borrowers But loans coming from Banks outside of the eurozone so banks that are not facing an environment with Negative policy rates in there in their main in their main market now in the paper we then Have a number of a number of robustness checks So I'm not going to go through all of these here Just I mean we we for example look at alternative risk measures We look at the shorter sample if you might be worried that The 2015 PSPP might be impacting our results We look at non eurozone landers that are also facing negative rates all these results basically further confirm This are finding on the on on bank risk taking Now for on the on the lending side then so due to the fact that these high deposit banks Encounter a relative reduction in their net worth We also expect them to to lend less and we we look at this From two different perspectives. So first of all we look at total loan volumes at the bank month at the bank month level and there we already see that Indeed the loan volumes for the the change in loan volumes for banks with a higher deposit ratio Is is lower than for banks with the with a low with a low deposit ratio now the potential problem with this With this type of setup of course is that it's very hard to properly control for for demand effects given that we're running These regressions at the at the bank bank month level. So an Alternative setup we can look at is a setup where we further exploit The granularity of the of the syndicated loan data we have available So in this syndicated loan data set we have information of the different loan shares of the different banks that are involved in In the syndicated in the syndicated loan So we have multiple banks per loan and we have also for some firms in our in our data in our database We have several new loans new loans over the sample period to the same firm So this allows us to examine banks loan share in this indicate while at the same time controlling for for for firm fixed effects and when when doing that we first of all observe that high deposit banks indeed seem to keep Hold hold on to smaller loan shares. So this is illustrated in the first two Columns of this table. So there we see that indeed by banks with a higher deposit ratio seem to reduce their loan share their loan shares Most interestingly in the last two columns We show that when we split up our sample into Risky and and more safe firms that this reduction in Landing by these high deposit banks is particularly coming from a reduction in lending to To safe to safe firms. So when you look at the sample of of risky firms You do not observe these reduction and lending there they're effectively even increasing their their loan shares so in in the way this table come combines our results on the on the loan volumes and on on the risk-taking as we see a Reduction in lending or reduction in the loan shares for these high deposit banks for For safe firms while they shift towards the more risky firms or the more risky borrowers in our in our sample Now a lot of So these are basically the main results for for the paper and Importantly if the channels that we've been that I've been discussing earlier on are really at work And are really driving this increase in risk-taking and this relative reduction in lending then you also Expect to see that there's a change in Net worth effectively change in net worth for these high versus these low deposit banks in one way We can try to measure this is by by looking at these stock returns of these two groups of banks so this graph Shows the evolution of a stock return index for banks in the so the listed banks in our sample in the top Terrasile of the deposit ratio distribution So the solid line and for the banks in the bottom Terrasile of the deposit ratio and there again we effectively see a sharp reduction in the or a relative gap opening opening up in The evolution of the of the stock returns for these two groups of banks So high deposit banks seeing a relatively large reduction in their net worth around this around this period Confirming that indeed it might be these channels that that are effectively at work Now as I mentioned in the paper we then try to dig a bit deeper in here I'm going to be very short on the the additional results There's a lot more information on this on this in the paper Just allow me to highlight two of these additional results first of all and we see that Loan terms do not seem to be adjusted to reflect this higher risk of the borrower So it seems to be really an increase in the in the risk taking from the bank side Additionally, we also see an interesting interaction of the treatment with bank capitalization So it seems to be that this effect on a bank risk taking seems to be a lot stronger for banks with a Low capital ratio which makes which makes a lot of sense. We think given that these banks are more I mean agency problems will be A lot more severe for these for these banks and finally we Try to say something on the impact on the real economy and there are a number of interesting results There are that risk taking seems to be concentrated in private and not in publicly listed firms We also observe that new lending is not going to not going to do zombie firms So not particularly going to firms which have very low profitability and we're already borrowing from The bank from which it's getting the new loan and most interestingly We see that the riskier borrowers that receive a loan effectively use this loan to increase To increase their their investments and not to for example start hoarding start hoarding cash So overall what we What we conclude in this paper is that below zero the transmission of monetary policy indeed seems to be somewhat different and There seem to be some heterogeneous effects across different types of banks We also find that so we find that there's a reduction in lending by By high deposit banks and increase in their and increase in their risk taking we also see that there seems to be a short slight increase in lending to more constrained borrowers and importantly these constrained borrowers effectively use This these new funds to to invest and finally we also notice that there's some change in the matching between banks and firms and That goes like and the it implies that the lending by high deposit banks seems to Be going more to more risky borrowers and by low deposit banks to more safe borrowers And one can then of course think about whether this matching is efficient and what what the potential implications are for for financial stability So that's it from my side, and I'm very much looking forward to water's discussion You're being wonderful even a few minutes less. So we will have more time for discussion Somebody gonna put up the slides So I'm not sure I should thank the organizers for asking me to discuss the paper because somehow I ended up doing three discussions in an Eight day period but the good news is at least is that it's a very nice paper It it reads very well. It's carefully crafted And it's an incredibly important topic and so I'm actually not gonna be that critical I'm just gonna raise some some some big issue questions, but let's start at the beginning So the objective is the paper is is to see is is that how banks are gonna respond? If the policy rate against it gets into negative territory, right? So over here I draw something down with sloping, but it also could be upward sloping So the question is that is sort of the response fundamentally going to change if the policy rate gets negative So that's the question and as Glenn made clear in his Presentation is is that that's a nasty identification problem, and they have an incredibly interesting way to do it And this is a graphical representation of this identification assumption So the data sets covers two years from January 2013 to December 2015 and then July 2014 we got into negative territory and so the regression that they run is is that it's the bank outcome and so there's three Subscripts so I is the firm J is the bank and then T is time And then the idea is is that they have these different banks and they differ in terms of how much they finance with deposits and Then they have a dummy for when it happens after the Change into negative territory. So one thing I want to emphasize is that right? So in their sample is only a six-month period when we had those those negative interest rates, so I'll get back to them Okay, so what are the results so these are quotes from the abstract and So it says if the interest rate gets negative and it induces banks with more deposits to lend less to risk your borders And banks do not adjust loan terms So this seems incredibly scary All right, because it's just now they start lending more to rescue your guys and It's not searched for yield because they don't charge a hiring, you know rate for that is that they do it at the same Races before so that seems to be scary I'll get back to that too. Okay, so Glenn was actually careful during the presentation and quite often in the paper They're quite careful too, but the way it reads is often the following and that could very well, you know one interpretation of the paper So over here, I have these bank responses So in the top graph it's risk and in the bottom graph it's lending and so after the positive ratio over here I draw a horizontal line in the benchmark so before things get negative That's just a normalization that could be upward sloping or downward sloping right because yet we're gonna look at the change And so the way the read the paper reads like like I just shown with the quote from the abstract is that this is the interpretation They they most seem to like That suggests this is that when we got into this negative territory It says that these high deposit banks or in the right Inside of the graph they started taking on more risk and overall banks started to lend less, right? and that's that's And then the the mechanism would be the following is is that when the interest rates gets negative And the problem is the positive rates they cannot be lowered And so that means that profits are gonna go down and profits are gonna go down Then lending is gonna go down and this is especially the case for these high deposit banks And then we're gonna get more risk-taking I guess because of the usual Convex payoffs say because of limited liability now there's an incredibly interesting result because it's the opposite of what we usually think Right, so we usually think is that if the interest rate is going to go down The rate on deposits is kind of sluggish. It doesn't move very much, but they get more on their On their assets on their loans and so then you know lending actually would go up It would be good for network. So it means absolutely fascinating kind of finding Okay, so let's start with a couple sort of simple clarifying questions So a Bank that has a low deposit ratio that could mean that they have more interbank funding and so when the interest rate gets negative It's nice if you fund a lot of your assets your loans with interbank funding because like we saw in the graphs The only it actually does get negative right so deposits. They sort of stuck at the true zero lower bound But the only gets it negative. So that's nice However, I mean, maybe this is a dumb question is because I don't know much about bank balance sheets But there's other possible funding why so there could be long-term funding and that also will not change right if short-term policy rates are turning negative So instead of looking at the deposit ratio, why not directly look at you know the level of interbank funding? That seems to be a positive when interest rates get negative So that's a relatively minor comment The other relatively minor comment is the placebo So again a sort of strength of the paper is that they show is is that if you look at another event when the interest rate turn Basically zero is is that we don't see any difference between the high deposit banks and the low deposit banks I think it would be more interesting to look at the placebo during normal times Where we actually expect the opposite, right? Is it that it's the large? The banks with a large deposit ratio that benefit and actually would start lending more But you know, these are relatively minor comments. Okay, so now I have sort of two to big picture kind of questions and Long long time ago way before the crisis with my colleagues in San Diego I had a paper on sort of behavior of lenders of banks And so there the story was is that how bank equity affects lending and then Tim Keeho You know discussed our paper at an NS NSF conference and I'm basically gonna sort of copy his his way of questioning the story And so what is the actual nuts and bolts kind of story? How does it happen that if the ECB has these negative policy rates that there's gonna be less loans Right by these high deposits Banks and how does it happen that they actually take more risk and how does that all happen within a six month period? Okay, so You start with the ECB and they have a negative interest rate and so what's gonna happen? So we're gonna look at a typical bank. So a typical bank has an accountant And so he's in charge of the money flows, right? And so he has to keep track of you know What he gets from the ECB or gives to the ECB and so there's a negative interest rate on that Okay, so then we have the depositor And so you have this nice lady and this nice man and we don't want to screw this nice lady So this nice lady gives money to the bank is that we don't want to have negative interest rates on that I'm perfectly fine with that. But what we really interested in is is that how this loan officer is going to change his behavior? All right, so what's happening in this six month period when the ECB is this negative policy rate? That that guy if he's at a high deposit bank So it's taking on more risk and lending less at least start lending less overall possibly more to you know to the risky guys. So There must be sort of anecdotal evidence, right? How that happens? And so what Tim Kio said he said well, you know, I went to a bank yesterday And I told him I needed a loan because I wanted to start an Italian restaurant And so we sort of talked about what was important and his loan officer couldn't care less about the bank equity position of the bank We know that that somehow that cannot be true Right is that somehow that's got a matter and the same over here is the cost of funds, right? Or the alternative interest rates that got a matter for what this loan officer is going to do But how does that happen and how does that happen in a six month period that right? When the ECB has a negative policy rate that someone is loan officer is going to have a different Schedule and so it's going to change his behavior now There may be a boss who's sort of shouting around over there what a guy should do And so I struggled with that question a lot and I sort of tried to look in you know The banking literature is is that and there is actually quite a bit right on sort of you know the behavior of loan officers But you don't see these sort of these big picture things about sort of the financial health of the bank things like net worth And cost of funds for the bank sort of showing up and over here I think that's key so we write in our models We think of this bank as like one person who maximizes something but a bank of these these you know these big Complex institutions and so how does that happen this transmission within this institution that is loan officer? In a relatively short amount of time really starts changing his behavior as he gets instructions from the top and saying well You know by now you should take more risk Okay So that was my my first big question. So Like I showed you before is that the paper reads a little bit as is that by you know the banking sector overall is going to take on more risk And they're going to land less but I Mean plan was very careful in this presentation and to be fair is that they do point that out in the paper too But nevertheless is this they seem to like the other present Interpretation more at least that's the way I read the paper But equally consistent with the literature is is that on average there is not much change in the banking sector Is is that the high deposit? Ratio banks is that they're going to take more risk, but the low deposit ratio guys are actually going to take less and This is also possible Right so the other possibility is is that we actually get results which are more or less consistent with the standard story Is that there's going to be more lending right again? And this interpretation you see is is that the high deposit banks? They land less relative to the low deposit ratio banks. So this is a possibility to now. What would be a possible story for this? Interpretation of their results Well, maybe these high deposit banks they're small banks, and I think that's true and they don't want to change the characteristics of their Loans that often and so it's like a sort of habit And so that kind of sticky and so they sort of stay where they were and it's the low deposit ratio Banks that sort of do the adjusting and they sort of adjust in a relative way. You may say well, why are they sort of you know? Lowering risk because it's probably true even in this interpretation that met network goes down well, maybe Banks have some kind of precautionary behavior too is that managers do not want to go bankrupt and so When sort of you know the the margin between the return on Liabilities and assets is going down is is that they do start to take on less risk Okay, almost there. So that was sort of the the explanation but but It may very well be is that you know the that the first sort of interpretation is is the one that happens, right? So let's take that for granted and I have to admit I find that you know somewhat more plausible than my own interpretation on the last slide So suppose it truly is the case that when we got into negative territory the banking sector as a whole overall Was going to take on more risk and land less Then of course the question is you know, why did the ECB lower interest rates into negative Terry? Was it a good idea? so it doesn't Sort of carry over into negative deposit rates for consumers and so consumers are not directly affected The other thing that I think we beginning to realize is that whenever we have a reduction in the interest rate It's usually temporary and then we think the substitution effect is going to dominate and the substitution effect is the same for a lender and a Saber right, so that's why we think is the reduction in the interest rate That's going to be expansionary But the interest rate has been low for a long time now and so Then the income effect becomes more important Then the question is is the income effect for the savers or for the borrower is going to be more important because it would have the Opposite sign and so I'm a saver and I'm actually worried that the interest rate has been low for so long And I expected to be low for quite a while and so for me This reduction in interest rates actually had a contractionary effect because I worry about my pension And since I had been at so many different institutions my pension plan is a mess So saving this kind of important and so if the return is so low, I mean, I feel I got to save more right so Suppose the authors right results have to be interpreted in the ways is that Banks did not lend more overall. It's just that you know the high deposit ratio banks And the high deposit ratio banks even lend to risky firms. It's not clear. That was a smart investment Then why did the sent ECB do what they did? Is it through asset prices or exchange rates or other types of rates that were affected by I? Think that's it. Thanks Wonderful. Thank you to both for your discipline and also anyway clarity and conciseness in presenting this topic


Do you ever long for the ability to create without worrying about the money? Well, join the club. I think a lot of us who are here in my community have that desire. And you know what? It is completely worthy. And it's possible. If you just do it step by step. Now, let's first talk about how a lot of us we are especially heart based service providers. We start creating a new business, you know, or or a new offering. And it comes out of the abundance of our desire to serve to connect to create. And yet we also require that it needs to make a certain amount of money or to get a certain number of clients. And that attachment of requirement to make money, or to enroll a certain number of clients. And you can tell that it pollutes the purity of the service, the creation, or the connection project. Right. So, it's important to understand that there we're really talking about two different sides of this one is hobby and one is business. Okay, you need to understand this because if you don't, you require your hobby to make money, and you perhaps don't realize you can put more of your hobby in your business so let's let me explain. The yearning to just create without thoughts of money is essentially what a hobby is about. Right. You can, you know, practice, you know, enjoying playing music or creating art or, or writing or any kind of creative project where you're like this is just for me. This is something that inspires my, you know, a different side of me than I usually do at work. And that's a wonderful and necessary, I think it's a necessary aspect of life to carve out at least some time to do our hobbies without thinking about whether this is going to make money. The thing about a hobby is that we don't even care if it's purely a hobby we don't care if anybody likes it or not. It's done because we enjoy it. We love it. We love the activity itself we're not doing it as a performance in front of others now some hobbies. You know, such as music or, or even some art. We do enjoy performing in front of sharing it with others and having them be delighted, but from that at that point, it starts to go into the territory of business. Now, when I say business, I don't really mean that has to make money, but what what a business is. Where does money income come from in a business.  Right. And so a business requires that other people are on the same page and would be excited and interested willing to pay money for a product. So, you know, on the one hand you're doing it for yourself. And on the other hand for business you are doing it for others. If you want to business to survive. If you're not doing it for others it's a hobby, you're doing it for yourself we don't care if anybody likes you don't care of anybody ever spends a single dollar on your hobby. Right. So these are the two ends of the spectrum that we need to respect and understand. And so many of us heart based people. We started business or we create an offer, a new program, a new service, a new package, a new offering, a new course. And we just think my God this things I love this thing so much. And I'm going to I love this thing so much that there's a hobby part of it, and it must make this much money it must enroll this many clients. So, we often find that it doesn't, because it came out of the hobby stage it came out of our abundant love for that skill or that area of life with for that particular subject of study or whatever it is, it came out of that. And then yet, we expect that people will pay us for it. And we get disappointed. And we might even have expected that it would make us enough money so we spend all this time and effort, maybe even money on the hobby. And we realize, oh wait, I've been in hobby mode, rather than in business mode. And now I can't make a living, because it's so how can we eventually create a life where we can be in hobby mode and still people want to pay us for it. And this is why I always talk about the importance of growing a true fan base, right, a community and audience of true fans means the people that you've shown up in front of again and again and again and again, year after year it takes several years. I'm not sad enough. It's, it's often.  And usually you don't make a, you don't make a living wage until at least a second or third, or 10th year. I know some people take them 10 years. And yet, a lot of you are expecting that's going to happen in three or six months I don't know where that came from. Well I know I do know where that came from it's a lot of the people in my industry are selling you that you can make six figures or even five figures in what three, six or 12 months. I'm going to tell you that having seen a lot of these have seen a lot of solopreneurs of all of all types. It usually takes at least a year or two to start making $5,000 a month. And I'm sorry that no one else told you this but I'm not trying to plant a limiting belief either. Who knows it might take you three months, but to expect that it will take you three or six months without having built a successful business before is expecting a lot of your hobby especially if it's especially if it's something that came comes out of your love of creating and service and exploration and your dreams, you know, your pure enjoyment, and then to expect it to make $5,000 $7,000 a month in six months, a year or 18 months. I recently heard another very experienced content creator, Joe Pulizzi he had created the content marketing Institute, and he says that content creators should expect to take 12 to 18 months of building an audience before they can monetize it. And content marketing expert who has built a whole Institute around and has consulted and taught many, many people he's one of the, you know, true experts in the industry says 12 to 18 months of consistent content before you can expect to monetize it. And this is why he actually sometimes recommends that people buy content properties like buy buy someone's blog which can take 10s of thousands of dollars to be able to start monetizing it right but it's like if you don't have the 10s of thousands to buy someone's blog and plug probably you'll find someone who's blog you respect enough to be able to buy it, or that you align with enough. Then we we build our own audience. That's how I do it that's how most of my clients do it most of my students do it. And instead of spending 10s of thousands in you know anyone fell swoop, you spend, you know, probably several thousand but gradually over time with ads, Facebook, Instagram, LinkedIn ads to build an audience of true fans. Once you have an audience of fans. Again, it probably takes 12 to 18 months. Once you have an audience of true fans. You are then able to sell almost anything that they want, and that they will buy it. So, alright, let me, let me, again, big picture and then we'll talk a bit more detail. The next picture, again, is to understand that when you are just creating from a love of creation and exploration, you are in the hobby mode. And to require that other people must enjoy your hobby require the other people must enjoy your art enough to pay you for it is asking a whole lot. How do you grow in an audience of true fans. And how do you grow an audience of true fans 12 to 18 months of consistent content now how consistent Joe Pulizzi when you know he's, he has at least one or two quality blog posts every single week. Right, and probably several short videos I mean you know someone like that is a professional and that and he expects 12 to 18 months. So for those of you who are creating a quality blog post once a month or once every two weeks, probably going to take two or three years before you can start to expect. And I'm sorry, I don't mean to discourage you. I don't mean to praise place learning beliefs. I'm just telling you what we are seeing in the industry. Now, again, you might be a miraculous person and do it in three or six months. You know, but but the more you focus on building a true fan audience. The more you are willing and able to show up authentically in an interesting way. And consistently, and using ads enough add dollars a couple hundred dollars a month ideally to run ads to bring enough people couple hundred a month. Yeah, three to 500 a month ideally. But even if you started 30 to 100 a month, it's okay. It's just again how fast you want to do it. You want to do a faster several hundred bucks a month slower through you know again 12 to 18 months. That's 30 to $100 a month. So you build an audience of true fans how why are they true fans how how how did they come to you well, you need to learn how to run ads again. So you have to just post stuff on Instagram and YouTube and suddenly your audience keeps growing hashtags don't work hashtags don't work. Not in the way that you're expecting Oh my God hashtag now I can make money doing it hashtags obviously work in subtle ways and over a long, long period of time, but ads work much faster if you said hashtags come on are you serious. I discovered with hashtags. Really. How's it going. Have you tried it. Of course I've tried of course I have tried it. Instagram linked in YouTube, Facebook, Twitter, I've tried hashtags everywhere. I've tested them with my marketing mind and my marketing instinct I've tested them, you know, they're not a reliable strategy that I would recommend to anybody. They're reliable ads. You've got to spend at least $30 to $100 a month if you want to build a true fan audience with ads you either you know ideally use ads and use collaborations. Those two are reliable.  No, it's not reliable you can't expect that you have word of mouth comes from ads or collaborations where the mouth comes from your work.   You see what I mean.   And by by doing it consistently and noticing what works, what is making an impact, then I can adjust myself in that direction again, I put out a lot of stuff kind of like like in hobby mode I just put out a bunch of stuff. I noticed what mixing it makes an impact, and I do more in that direction which is more in the business mode I do more content in those directions because I know that that's what people want. And if people want that they will tend to share it more often or like or engage in the algorithms help with that. And then I pushed along much much faster with ads, and with collaborations, meaning other people interviewing me and meet any of you other people in return. Similar sized audience similar sized audiences me. And so you build a true fan audience by doing just a whole lot of content you've got to do more than you probably are doing and I know you don't want to hear that. I know you're exhausted, which means if you're exhausted means you have to keep better boundaries about your work. I keep very good I take four naps a day. I've said, people who are my program notice and then we often joke about it. You have to keep really good boundaries of your work, how many hours you work at each stretch, how you work, you work, I work lightly, right so I don't make anything so serious. I don't have a lot of light for me everything so casual. But that's how I can I can be so consistent showing up a year day after day month after month year after year and I'm still very happy and healthy. You got to work lightly, you guys said a lot of boundaries with yourself with yourself, besides with the people in your in your notice the doors closed and I'll let my family members just barge in and say whatever they want. Boundaries with others boundaries with yourself, and a whole lot of content like just every day if you can get put out content. If you can't do it every day. Do it three times a week if you can't do it three times a week do it twice a week, you can't do it twice a week you got to do it at least once a week. Once a week you're slowing down it's going to be three to five years now, rather than two to three years every day. 12 to 18 months, you're now monetizing your your your business right. So, creativity and money making must understand that people won't pay you for your creativity because you think your creativity so great. Nobody else does until you show up day after day after day after 12 or 18 months, and then you have with ads hopefully to get it out in front of 10s of thousands of people. And then you have enough people couple dozen people maybe a couple hundred people who think your creativity is pretty great too. And then, once you have those couple hundred people ideally, then move into. So first of all, build an audience of true fans. Step two, move into the space of curiosity and alignment. Well you're you're in that curiosity and alignment the whole time hopefully when you're when you're testing content for for two three years. Your curiosity and alignment meaning, I wonder what's going to work. Let me go and test this out I don't know if it's going to work I'm going to test it out. Am I going to be interesting to watch on video I don't know. Let me play let me test it out let me show up consistently for six months as a test, consistently every day for six months to see if I really like it to see if yes you don't just go three times a week and you're like no I don't like it. Six months daily. Right, that's what I did. Right, I did six. When I was first starting to make videos six months daily money through Friday I can, you can take the weekends off if you want to. But six months daily to like figure out if this video thing is really for me or not. If you can't do daily, like I said, can't do daily, three times a week if you can't do three times, twice a week if you can't do twice a week, once a week is a bare minimum. So six months to test something out because only after six months when you have built in just enough skill just enough skill where you're comfortable, you're confident. And now you can really express yourself and I mean notice I'm able to really express myself on video right took a lot of practice to be comfortable at this it doesn't come naturally I wasn't natural on. So you build a true fan audience in curiosity and alignment alignment meaning you're curious to test a lot of different things and your alignment means you're wondering which ones make the most impact. And then you align yourself more and more in that direction. Oh, I've talked about 10 different topics, and two of these make the most impact so let me align myself more with those two topics and create more in those two topics. Let me see. Once you built a true fan audience, then a couple hundred people who follow you on a consistent basis and many of them comment or at least like your stuff. Then you can talk to them again in curiosity and alignment to say, What would you buy from me. Now, if you're too shy of asking that at least at least try to ask, What have you purchased in my field in the field of whatever it is you do personal growth, spiritual growth, relationship, career, you know health, whatever it is you do what what have you bought in this area have you bought any coaching have you bought any workshops courses, programs, what have you bought, you know, or what could I sell that maybe you think my audience would would would would sign up for. So, you ask your true fans, what they would buy and what they happen buying. So that with curiosity and with alignment, you put those offers out. Now you're in business mode, because you've been in hobby hobby mode testing different things you're kind of moving gradually towards a business mode because now you're building true fan audience. Now you're in business mode where you can say, Let me give you what you want, rather than me coming out of my own creativity and love of creating and exploring and, but then I'm still in myself. I'm still in my own head. Too many of us are in our own heads and we wonder why people aren't buying it. Because number one we don't even have a true fan base yeah. Right, not enough people anyway. And number two, we haven't asked them in the business mode what would you buy from me, because then I will make it. And if I buy that, I will make it. And then you make it. Now, of course, you might give them several options like out of these three things which one would you most likely buy will tell you one out of these three I'd buy number two. Okay, great. Now, you, you make number two. And then you, again, you pull them hey I made number two which title do you think sounds best or what should I name the program what should I name the service you know, but you always keep aligning yourself with the audience your true fans along the way of creating something you create, you create with their feedback all the time. So that that's how you make money through your creativity. You see that's the whole journey. You first test out a lot of things from your love from your create, knowing that it takes 12. It takes a year to five years to build enough fans who actually want to spend money with you. You can ask them what would they spend, and then you can make for them, and then now you're making money now. I'm not saying you don't make a single dollar in those five years or three years or one year. You know, because you already have a skill set and a service, probably a lot of you watching this already have, and you already can go to your network and ask them to, to, to share the spread the word or to buy something. So starting from scratch if you had nothing, it would take that time so I hope you would please give your, your creativity, some more patience, some more generosity of space, spaciousness, so that, and, and to be really with gusto test a lot of different things from from the hobby place, trying a lot of different things out not not caring if anyone likes it, because you don't know if they'll like it or not. Stay in curiosity and alignment. Give yourself the spaciousness of time of years, and you will be able to make money from your authentic creativity. I hope this is helpful. I hope this is inspiring, and a little bit of a pep talk and a reality check perhaps. I look forward to your comments below. Thanks for joining me.


Let's get started. I can't see very well out there, so shout if you feel the need to ask questions or interrupt. How's the conference for everybody so far, good? All right, excellent. All right, this thing's not gonna work apparently. So, I'm Alex Boster, I work for AppFolio, which is a company in Santa Barbara. I work in their San Diego Engineering Office. We're hiring, come talk to me. So, the last, I would have said one particular project inspired this talk, but really it's also the culmination of the kind of experience you get after a few years of doing web development. So, this is a survey of surprisingly difficult things. Now, what things do I mean? I mean commonplace things that you know all about in your day-to-day life, so they're easy to model and you model them and they're great, and then it turns out it's actually a lot harder than that. So, things where the obvious implementation may very well cause problems. And in fact, these are things like time stamps, time zones, physical addresses, human names. Now, when you hear these terms, what do you think? Does this sound easy? These are solved problems, right? Easy, no problem, no complications. What am I not gonna talk about? I'm not gonna talk about cash invalidation or distributed systems or other also surprisingly difficult things, but this is about real world stuff. So, one of the things, you know, one of the reasons I wanted to give this talk was that developers fall into these traps all the time. We spent months cleaning up old buggy code and then new bugs of the same type are introduced six months later by other developers. So, maybe, you know, with a laundry list of things to be aware to watch out for, maybe you won't fall into that trap. And even very senior developers, you know, it might help to just have the occasional reminder here. If you're not a senior developer and you haven't dealt with this stuff much before, then hopefully this talk will save you some time in the future. Another good thing is that if you follow these best practices or similar things, then your app could be more inclusive. So, I know that when I start dealing with these real world things, I, you know, causes me to wanna drink. Might just drive you to drink too. So, let's start with time.  The only one I really wanna draw attention, this is mostly for reference later, but the one I wanna draw attention to is the last line, where there's just no good cross-system standard for duration. It's different in every database. It's different in Ruby than it is in the databases. So, pay a little attention to that and check out active support duration. But what makes time actually hard to deal with is not this, it's time zones. So, again, isn't this a solved problem? You can just have a sufficiently large integer to represent seconds or fractions of a second and now you have a time value and you're good, right? No problems, let's all go home. Well, again, the problem is in time zones. So, how many time zones do you think there are? Anyone? 30 something? Say it again? 40? Well, you may be right at a certain level. Certainly, the time zone database, which I'll talk about in a minute, defines 385 time zones and then has a further 176 internal links, which are aliases, basically, to give them different names. So, something to remember, there are half hour time zones. There are quarter hour time zones. You've got daylight savings time to take into account. Daylight savings time may start, a place may start observing daylight savings time that previously didn't, like Arizona currently doesn't. A place may change their schedule, like the entire United States did 10 years ago or so and shifted when daylight savings time started. I don't know if this is true currently, but certainly in the past, we've seen examples of two hour daylight savings time changes. This was called double summertime in the UK. And a place may change time zones entirely. They may just switch. So, this time zone database I spoke of is used in many UNIX-like systems. It's used all over the place with a small band of dedicated developers. It tracks all geographic time zones since 1970. They define an area as, you know, where any two places share the same time zone at the same, share the same time at the same time. So, not before, seriously. Before 1970, they don't care as much, but they do have historical data. And it does track daylight savings time changes. So, an example of this is updated several times a year. If you think this stuff is static, no. It's updated several times a year and here's an example of some release notes. You can read through that quickly. Mongolia no longer observes daylight savings time. This region moved from one to another year round and the clocks starting at this particular time hived off a new area, which also affects part of Antarctica. If this change fixed many entries for historical time for Madrid before 1979. And it noted that Ecuador switched, actually observed daylight savings time at a particular time. So, the exact details aren't important, but just know this stuff is really complicated and they're good as somebody's keeping track of it. And that's an example of all the actual regions defined. And that's, again, just unique regions since 1970. Another little trivia, you know, how many time zones are in the United States according to this map? Just the continental United States. I count at least six. So, we use UTC as a way to standardize things. You know, when things happen at the same instant in time regardless of what you actually call that time in a particular place. Hopefully, we know that that stands for neither coordinated universal time nor Thomson and Ursell coordinate, named by diplomats no doubt. UTC is not a time zone, but every time zone has an offset from UTC. And as a rule, you should store your time values in UTC. So also, before I proceed, how many, what are the possible offsets from UTC? UTC is kind of in the middle and you can go forward from it and you can go back. How far do you, how did they go? Anyone want to take a guess? That is exactly what I thought. So, in 1995, Kiribati got tired of having their country in two different days. So, they moved the time zone of some of their outlying islands from minus 10 to plus 14. So, there are plus 14 time zones on that side. So, keep in mind, without a time zone, any time value you have without context could take place within a 26 hour range, possible half hour or quarter hour. So, how do you handle this? Well, if you don't explicitly provide a time zone, a time you provide could be interpreted using the operating systems default, using your databases default, or using your applications default time zone. That should be configured in your Rails app. Okay, now I need a slightly bigger drink. So, as we said, keep your system and database time in UTC. Rails will store its date times in UTC and time zone aware methods in Rails will use the applications default if you don't overwrite it by expressly providing one. So, for example, if you have users, be sure to store a time zone on the user's model and always use that in your views if you care at all about when things occur for said users. And just as an example here, you can see that you wanna use time.zone.now, I'll talk about this a little more in a minute, and ActiveSupport provides some really sophisticated stuff around it. So don't just use bare Ruby time, use the Rails classes for all this stuff. So these time zone aware methods, you can see we're parsing two different times in different time zones, but they're actually the same time. So it all works, that's cool. And here are some examples of methods you should use. Hours from now, days ago, those are all good. Always do time.zone.parse, don't do time.parse. If you use string parse time in the middle here, always use in time zone at the end or you will be screwed. Prefer definitely time.current to other methods for getting the current time and the UTC ISO 8601 is for if you're providing an API. Excuse me, if you're providing something to an API. These examples are all from a stolen shamelessly from a blog post. So dates are simpler, right? Dates don't have a time zone. How do you know if you should be storing something in a date or a time? Ask yourself, does it matter what time of day? This seems really basic, but people make this mistake all the time and just convert a date to a time willy-nilly. So don't do this. So what are some examples of dates? Well, birthdays, a birthday occurs on a day. We don't generally observe when the actual minute of the day a person was born. All day calendar events, maybe holidays you might think of. So, for example, I don't know. To take a Western example, Christmas is on the 25th regardless of whether or not you're in Beijing or Toronto. So as I said, don't store dates and date times. You will have problems. Be very leery of converting back and forth. You almost never wanna do that. For example, the one case I can think of offhand is if you have a calendar that you've written and you want to convert, somebody's editing an event and it goes from being, say, an all day event to a timed event, then maybe. So let's see, where are we? So, this is fine. Where did that come from? I don't know. So, you wanna use date.current because I ran these two lines in the middle of the day, seconds from each other, and that's what I got. Why did it behave that way, anyone? Yeah, basically current takes into account your time zone. The other one is basically telling me that in London it's the 24th. But I see date.today all over the place in code. So, these are really the only two date methods you should be using, and you absolutely have to avoid time.now, time.parse, time.string.parse.time without the in time zone things at the end or date.today. Something that can help you with this is, be sure to use, who uses Rubicup? Okay, how many of yous put that into your actual process formally? A few, good, cool. I gave a lightning tell a couple of years ago on this and depressingly few people did that. So, there are services like Hound, Farsi, there's probably others that I'm courtesy that I'm not thinking of or I'm not familiar with, but you can make it a blocker so that you can't merge a PR unless it passes your style check. And amongst the many benefits of that is Rubicup allows you to catch some of these errors for you. Any more comments, questions about dates and times? Let's move on to human names. So, many of you may have read, there were a couple of blog posts that were related. One was called falsehoods programmers believe about names, which I believe was actually inspired by falsehoods programs believe about time. And to take a few examples from this, we have things like, none of these statements are true. People have exactly one canonical full name. Nope, people have exactly one full name which they go by. No, people have at this point in time exactly one canonical full name. People have at this point in time one full name which they go by. No, people's names do not change. That's not true. People's names change, but only at a certain enumerated set of events. No, people's names are assigned at birth. Not true. People's names are written in ASCII, absolutely not true.  Although I'm guessing very few in just emojis yet, but that'll come. People's names are written in a single character set. That's not true. People's names are all mapped in Unicode code points. That's not true. Two different systems containing data about the same person will use the same name for that person. That's hopefully pretty obviously not true either. This is terrible. So now I'm feeling a bit crabby. So really the only thing you can do here with names is validate as little as possible. Just don't bother. Why are you trying? Yes, their cardholder name probably has to match when you submit a credit card, but that's their problem. If you can avoid first name, last name, consider doing so. Just use full name. No idea what's going on. And maybe use given name, family name to be a little bit less English specific. Also store things in Unicode. Remember, you can't guarantee real names are used. And don't assume just because you might have a US based and a US centric business that your users will be primarily English speaking or even have as key names. That's, you know, these things are true in the US as well as overseas. Okay, physical addresses. So how do you model physical addresses? Right? Yeah. Mm. That's good. Well, there are a lot more variations on this than you might expect, even in just the United States Postal Service. So even in the US, remember there are rural routes that look like this. There are military addresses that look like that. That doesn't quite fit the city-state paradigm. Remember, US Postal Service is Puerto Rico, which has a very different address structure. You can actually have a surprising number of lines in a valid address. I saw one example that was supposedly valid that had 12 lines long. It was an international one, but still. And basically don't do this. So until I moved recently, my address had a slash in it. These are actually pretty common in California in numbers. It doesn't validate with Southwest and it doesn't validate with quite a few legacy systems that you'll see out there. I had to have a bunch of banks and things send things to apartment one half. So you can standardize these addresses via the US Postal Service. They'll convert them for you and give you some of the right abbreviations. But remember that special characters are still allowed even after that. Note, for example, cities can have apostrophes in them. Addresses can have slashes or dashes and so forth. Some things to know about US postal codes. Don't use just zip codes. In general, try to use postal code, which is the international version of the word. And don't just make it five characters long or 10 characters long if you wanted to do plus nine because again, you're excluding the ability to store addresses from other countries. Including Canada, which is close enough you might actually wanna be able to ship to it. And also as a bit of trivia, remember that you can't even use zip codes to map to states. There is a database you can buy or possibly download for free that will attempt to give you city information but zip codes not only can cross city boundaries, they can cross state boundaries and here are the ones that currently cross state boundaries. And that's all because zip codes map to postal routes not to geography. It just so happens that most postal routes are geographically constrained. So let's say you wanna validate addresses. Again, my first instinct is to say, why are you doing this? But okay, great. The US Postal Service has a database of them. However, these are not always the same as physical addresses. There are entire towns and communities that have no physical addresses in the US Postal Service database. For example, I'm in San Diego, one of the very wealthy suburbs, not suburbs, it's actually a separate city, one of the very wealthy cities in the center of San Diego County is Rancho Santa Fe. Postal Service delivers everything to their post office and that's it because they didn't want ugly postal trucks driving around going to people's houses. Yet, UPS and FedEx will deliver to people's houses there. So if you're shipping something, maybe you should let them enter their home address even though it's not gonna validate. Oh geez, any comments, questions about fun stuff with addresses here? Anyone, Bueller? All right, money. Yay, y'all need to get paid, right? How do you model money in your Rails apps database schemas? That's a given, no, correct, not as a float. I've seen that though. Any other possibilities? That's a good one. And decimal, so I heard those two. Those are sort of the other two approaches that I'm familiar with. So you may use decimal values. That's what a migration doing that would look like. There are some issues with that. Not that it's invalid. Here we have a line of Ruby code that will render your product for your API. We'll send this out, because it's a decimal, it'll look like that when rendered. And now in JavaScript, we do this. What's wrong with that? I'm sorry, well, maybe. Anything else? Correct, ding, ding, ding, he said floating point. Current product price in JavaScript is now naively a float. That's how the JSON, so you can, sorry, after that bug came up three different times. So you can get around that. If you want to always remember to use a decimal library on the JavaScript side, there's no problem with that, but inevitably someone will forget to cast to make a new decimal object and the bug will be introduced. Also, you'll get very strange rounding when, for example, you're multiplying by, say, a tax rate or something like that that's maybe, has three significant digits, and then suddenly you'll have IEEE rounding issues in your money. Not good. So I prefer the just store sense. Use integers everywhere, you won't have rounding errors. I recommend you keep the name in sense as part of it everywhere and then only convert at the last minute for display purposes to dollars or whatever your currency is. Do be aware, some currencies have mills instead of cents. So if that's important, just remember you're multiplying by 1,000 instead. And in this case, usually it's obvious when you've forgotten to convert because it's there on the display. Your totals will be wrong, easier to test. Email addresses, those are easy, right? So this is now a valid email address. Just keep that in mind. This is now a top level domain. There are still places out there that try to validate.com.net.edu. You can validate that there's an at, there has to be an at sign in an email address and there has to be a dot somewhere in the domain name. That's it. Otherwise, you can do the whole verification email dance, right? Which everybody, people know this, but again, people still try to over validate. And it's kind of like, again, why are you doing this? I'll also just mention as a sidebar that for people who aren't aware of this most email systems, particularly Gmail, will allow you to add a plus after your username and it'll still get delivered to you, but now you can have an infinite number of email addresses without creating new users. This is great for testing or for creating a thousand free trials or whatever you need to do. So, all right, internationalization. I'm not gonna talk much about internationalization because it's a huge topic. There are literally entire conferences on it. I do have a suggestion, which is that particularly if you have a green field application, you've just done Rails Nu, start putting your hard-coded strings in your config locales just from the beginning, even if you have no particular plans to go international or support other languages. A cool thing, a cool result of doing that is that one, changing copy is easier. You don't have to search all over the place. It's all in one place. And furthermore, you can even turn over the keys to a product person or a non-dev and they can make copy changes themselves directly in the code instead of handing it off to you and then you just review their change. Also, if you add a locale to your user model and always use it, then again, you won't have to backport or fill this stuff in later and you can just start if you're in the US with USEN or whatever makes sense for you and then it's there. Payments and credit cards, another huge topic that there's a lot to talk about. Read up on PCI compliance. Again, there's an entire industry around PCI compliance. I think what most people know about it and what you need to take home is never store it, credit card information, but don't even send it from your client browser to yourself. Use a service that will let you send it directly from the client browser and then give you a web hook back. That way you're not even relying on the browser that somebody's using on an airplane with a credit. They're on a Chromebook on an airplane. Just imagine that scenario and now you're relying on them getting the token and sending it forwarding that to you. No, just use web hooks here. And be sure to consider what happens if the call to your provider, Stripe or whatever, times out. That can happen and depending on your architecture, if you don't use web hooks, you have to actually escalate timeouts to a human being to go and look and see what really happened, like did the call go through or did it fail? Recurring calendar events, that's easy, right? You just have like a day of the week and say when it recurs or something like that and you're fine, right? Now, read this RFC and consider that most recurring events have no end date. So how are you gonna model that? There's an infinite number of them. The rules can get pretty complex. This is a fairly simple one, like every month on the second to the last Thursday. And individual instances of a recurring event can be edited or moved or canceled separately from the actual recurring event. Yeah, now I need this particular Bloody Mary. That's right. Check out the garage in Seattle. I'd like to just point out that this particular one has as a garnish a second Bloody Mary for you to get through. While you're working your way down to the Bloody Mary. And in case you think onion rings, chicken wings, a submarine sandwich, a 12 inch pizza, French fries, and a lime are not enough. Here's the back view. There's a cheeseburger, an onion, a lime, a lemon, and two grilled cheese sandwiches. But you might need this if you start working on recurring events. I highly recommend it. So I talked a little fast, ran a little early. In conclusion, the main takeaway is don't overvalidate. People just have this need to check the values of these things when you can't. And I don't understand it. Even US only products will have global like problems. Be culturally aware. Remember that your experience isn't universal and probably isn't typical. And just don't make assumptions. And there are some references if you get my slides later for the blog posts I was talking about. Thank you. I have a request for that slide.