 My name is Brian Edwards. I'm with Los Alamos National Laboratory. And I guess one of you asked a few minutes ago what happened to the markets for malware presentation that I think is on your schedule. It just evolved into measuring and integrating the shadow economy, a sector-specific approach. As an economist, we are often involved in doing impact analyses. We certainly do a lot of it at Los Alamos we analyze the impacts of hurricanes and other kinds of catastrophic events on regional economies as well as, and we also look at impacts on critical infrastructure. We got interested in the unofficial economy or the shadow economy. There's lots of different names for it because there are our own economy but also the economies of other countries that have small, or ranging from small to significant parts of their economies that are unofficial. So I wanted to, we started thinking about ways of looking at this from an economic perspective. So I'm gonna talk today a little bit about the scope of shadow economic activity and look at some comparisons of the shadow economies in the US and other countries, why they exist and then what we're really beginning and what you're seeing here is some very preliminary work on taking a slightly different or actually a pretty different view of the shadow economy with respect to the rest of the economy as a whole. Traditional views of the shadow economy have been what economists would call macroeconomic. They basically said, well, the shadow economy in Belarusia is about 30 or 40% of the GDP of the gross domestic product of Belarusia. In the United States, it might be eight to 10% of the economy of the United States and one of the tables that I'll be showing you in a few minutes will show some of the international comparisons. This is a table that is adapted from a Journal of Economic Literature review article that you can get on the web. I hope you can hear me okay, I'm sort of bouncing back and forth between this microphone and so if I'm not doing that right, let me know. And this was kind of a taxonomy of shadow economic activity. And a lot of the shadow economic activity that people talk about is the usual suspects, gambling, prostitution, illegal drugs, trade and stolen goods and so forth and so on. And there's kind of an interesting anecdote, at least to me, this article was published in the year 2000 and I actually had to add, and if you go to the top left cell of this where we have monetary transactions and illegal activities, that italicized piece is something I added because in the year 2000, people really didn't, you know, hacking and, you know, the shadow information sector activities that people talk about now was not something that was really, I guess, significant enough at that time to be included. But again, I'm quite new to this area so I really don't know when it started becoming more significant. But anyway, in any case, this is sort of a taxonomy that's in that Journal of Economic Literature article. If any of you have access to JSTOR or if you could get your hands on this article, it's quite interesting and it gives you a pretty good overview of how economists look at illegal activities. As far as measuring the shadow economy or the unofficial economy or underground economy, however you wanna put it, most of the studies, as I said a little while ago, have been in the macroeconomic, have taken a macroeconomic point of view. They have just looked at, well, we think it's about 20% of GDP or 10% of GDP and so forth. And we've really had little attempts, very few attempts to try and measure it in more of a microeconomic sense. Microeconomic, I mean, in terms of looking at individual sectors of the economy, industries of the economy, that will have unofficial subparts. And so what we're looking at here is the beginnings of some work that might look at a shadow agricultural sector or a shadow manufacturing sector or a shadow information sector, which is what I'm focusing on today, that would accompany the economic, the activities of the official versions of these sectors. And here are just some shadow economy in the US. I think I've already mentioned that about 8% to 10% of US GDP is considered unofficial. But the evidence that we have on this is largely anecdotal. The official measuring that they do in the federal government captures some of the unofficial activity, but it doesn't really capture all of it. And as far as international comparisons are concerned, we have some pretty wide variances across countries. Thailand, Nigeria, Egypt are estimated to be about 70% of their respective gross domestic products. Guatemala, Mexico, and Peru were 40 to 60. And Philippines, Sri Lanka, and so forth, some of these other countries are a little smaller. And I don't know if you can read this, I hope you can, but this is, again, adapted from that Journal of Economic Literature article, they're basically giving you a sense of the ranges of the sizes of the shadow economies in these different countries. Japan, United States, Austria, Switzerland, relatively small, Nigeria, Egypt, at the other hand, relatively large. There's been a lot of economic interest by economists in illegal activities. Going back to the work by Gary Becker, who won the Nobel Prize in Economics in the mid to late 1980s, I believe, the idea is that people engage in shadow economic or illegal activities because of incentives. And the incentives can be anything from just monetary incentives. And it can also be affected by the institutional regulatory environment that people live. In the former Soviet Union, there was a large black market, there were large black markets there because there were price controls. And in the former Soviet Union days, most goods and services that were available had two prices. There was an official price, and then there was an, that was in rubles, and then there was the unofficial price that was also in rubles, but it was a lot more rubles. But there's lots of incentive areas of, where the incentives to engage in shadow economic activity can exist. And some of the incentive areas that we've been interested in have been the burden of taxes and social insurance contributions, the intensity of regulation, social transfers, labor market regulation as well, and public sector services. And some of these incentives issues, for example, the burden of taxes and social insurance contributions, if workers and employers are required to pay taxes and make contributions to social insurance, there may be cases where they may consider this too costly and so people are gonna be paid under the table. And so this, so you know, so that activity is automatically gonna go from being official to unofficial. There's a fellow by the name of Louisa who estimated the size of shadow economies in 14 Latin American countries and found that the greater tax burdens and labor market restrictions increase the size of the shadow economies of those countries. So there's just a fairly natural response to the incentives that are created by the country's regulatory makeup. And it also applies to the intensity of regulation where the increased regulation reduces individuals' choices in the official economy. And so they're gonna want goods and services. If they're not available officially, they will try and go outside and get them. And suppliers will do the same thing. They will find ways to supply these, albeit illegally. And shifting regulatory costs to employees provides incentives for workers to supply labor to the shadow economy, another finding. As far as social transfers are concerned, a social transfer is basically any kind of transfer payment from the government to someone else. Social welfare systems can increase tax rates, reducing incentives to work in the official economy. And the system can also provide disincentives for individuals receiving welfare payments to work in the official economy. If it's more costly to do something, less people are gonna do it. If it's less costly to do something, more people are probably gonna do it. So that's what you learn when you get a PhD in economics. My father used to tell me, all you ever need to know about economics is buy low and sell high. And I think he was probably right, but who knows? Labor market regulation, overregulation on labor costs in the official labor market are driving forces for the shadow economy, according to Schneider and Ensti. Again, I'm giving you kind of a quick rundown of some of the literature on this. Force reduction working hours can often encourage shadow economic activity. I know that in France, for example, they've been going back and forth on number of hours restrictions. And the idea is if people can only work 35 hours a week, for example, then there's gonna be more people that are gonna be employed. Well, there may or may not be, but there's probably also going to be more people employed in the shadow economy as well. And public sector services, again, if there's also a feedback effect that we talk about here, if an increase in shadow economy decreases government revenues because now you're doing stuff that's under the table, this can reduce the quantity and quality of public services which can then lead to higher taxes. And so there can be a negative feedback that occur under those circumstances. As I've said before, people accuse me of being very repetitive in my presentations and I'm probably just as guilty today as I've always been in the past. The previous work that attempts to link shadow and official economy economic activity have been macroeconomic. There's a Houston who developed business cycle model. Business cycles is an analysis of the ebb and flow of macroeconomic activity. Okay, 10 minutes, thank you. Adam and Ginsburg focus on the implications of the shadow economy on official growth. So there's been analyses that have been done that have tried to say, well, okay, we have this official economic activity that it takes place. What effect does that have on official economic activity? Now, as I said at the beginning, what we're attempting to do here is look at shadow economic activity in terms of specific sectors and how those specific sectors integrate with the rest of the economy. And again, we could have looked at agricultural underground activity, marijuana growing I suppose would be an example of that. And we could talk about illegal services, prostitution, gambling, at least outside of the state of Nevada and other kinds of activities that take place in different sectors, chemical manufacturing and illegal drugs, for example. But what I'm focusing on today is the information sector, what the National Income Accounting System refers to as the telecommunications, data processing, data services sector of the economy. And the kinds of economic activities that we're talking about are basically computer system hacking, trading stolen information, identity theft, spamming, and other activities. And I'm sure there's lots more of them and I'm sure any one of you could give me a much more thorough rundown of what those activities are. And what I wanted to look at was what are called input-output models. And what an input-output model is, and I don't know how familiar you are with these kinds of models and economics, it's basically looking at the economy from the point of view of different industries that purchase outputs from other industries in order to produce whatever goods and services they produce. So when an automobile manufacturer manufactures a car, they are purchasing commodities and raw materials from other industries. They may purchase the tires that go onto the car from another part of the manufacturing sector. And it's very common for years the US economy has been looked at from this perspective. And what I'm giving you, what I want to start with is a very simplified three sector official US economy where I've taken the all 20 some odd sectors of the economy and I've aggregated them up into three sectors. And I'm gonna be looking at manufacturing services and others, so we're just gonna have an economy that where we've left manufacturing alone, we've left services alone, and then we've taken everything else, ag construction, utilities, and so forth and so on, and we've just aggregated that into one big other category just for purposes of keeping things simple and manageable. And based on 2002 data, where we have a GDP of approximately $10.7 trillion, we have an economy that looks something like that. And these are a little strange to read, but basically if you were gonna read across the manufacturing row, the manufacturing to manufacturing cell is basically telling you that about $1.3 trillion of manufacturing output was purchased by the manufacturing sector. And about $1.018 trillion of manufacturing output was purchased by the services in other sectors, the services in other sectors then turns around and makes goods and services with those inputs. And then if you were gonna stay in the services in other column, for example, that would be just telling you what outputs from services in other and information that they were purchasing from those sectors in order to produce those outputs. If you take the first three columns and sum them up, you get the total intermediate use, that's the total intermediate input purchases that they buy from these industries. And that along with what we call final uses, which is GDP, if you ever took a macroeconomics principles class in college and they said, well, GDP is consumption investment plus government spending, got you, plus net exports, that $1.392.6 trillion is what that number is, but that's not really the total output of the economy. The total output actually includes all of those, all that intermediate production that took place as well. So when you add those, what, fourth and fifth columns and you get the total commodity output of 3.8 trillion, that's really the number that we look at. Anyway, so, and that is basically just an input output representation of a hypothetical, or it's not really a hypothetical economy, it's the actual economy, it's just a very highly aggregated version of the economy, at least as far as the services in other sectors are concerned. Now we're gonna consider an economy with an added shadow information sector and we decided to look at one or 3% of the official information sector output as sort of an estimate of how big the shadow information sector is. And we did that because there's an OECD organization of economic cooperation and development report measuring the non-observed economy that got about, that estimated the size of the information sector in the United States to be about 1% to 3% of the official information sector. So it's pretty small, okay. And we basically created a shadow information sector which is now that fourth column. There's an official information sector which is the same as before. But now if you add that fourth column, we basically added a little bit more and we've added those inner industry purchases. In other words, the shadow information activity is gonna take place, but shadow economic activity, even though it may be illegal, okay. They're also engaging and interacting with other official sectors of the economy, okay. And that's one of the things that we're really trying to pick up is if we wanna model this, we don't wanna just look at the aggregate, we wanna see how it's interacting with other industries. And then we basically go through the same, and again, these are very, very preliminary estimates of how big it is, but the GDP is gonna be slightly larger now because we're now measuring economic activity that we weren't measuring before, okay. Let me go back to that. And so that's what our, this is, again, a very, very rough preliminary estimate of what this total economy would be with the shadow economic activity added. And then we discussed the 1% case. GDP is slightly higher. And we show only the addition of a shadow information sector. Other shadow sectors could easily be added, ag, and so forth. We don't really get into the issue of burdens that are imposed, but we know that there's additional economic activity that's taking place as a result of shadow economic activity. Peter Norton, I think, probably owes his existence to the shadow economy. And we're not really talking about additional burdens that this activity imposes. And I'm not being judgmental at all about this. I'm just looking at it very coldly and crudely as an economist. And the other thing, though, is that if spending my additional firms take place, and this is another area where we'd have to fine-tune our estimates a little bit more, if firms in the official economy are engaging in other kinds of activities, spending additional money to protect their networks, or if I, as a consumer, have to go out and buy anti-spamming software or something like that to protect me from spammers, then that has a negative impact on me and it also has an impact on the expenditures that are undertaken by these other firms. So if you went back to this table, there would be an additional activity throughout all the cells of this table that would reflect that. And I'm getting down to about a minute, I think. The discussion with the 3% case is roughly the same. We've also got some very, very rough estimates of employment in the hacker economy, something on the order of about 3 million people. I'm sorry, the information sector having about 3 million people. And if we apply this 1% estimate, we get about 34,000 people involved in this underground economy nationwide. And the higher end estimate would multiply that number by three. And some summary conclusions, as far as summaries and conclusions are concerned, it's very hard to get information about this sector, so really getting reliable estimates of how this would work, of what these numbers are, is likewise difficult. This sector of the economy is always in a state of flux. And so I think we may just, just by the nature of the beast, be stuck with just, okay, I've been given the skull and crossbones, which means that I have to be quiet. But anyway, I'll be over in 106. If you have any questions, I'd be more than happy to answer them. And thank you very much for your time. And I know that this is probably a very strange topic for this convention, but I thank you very much for having me. And thank you.