Economics Detective Radio

 2 people rated this podcast

Best Episodes of Economics Detective Radio

Mark All
Search Episodes...
My guest today is Kevin Leyton-Brown, he is a Professor of Computer Science at the University of British Columbia. Kevin's work involves not only computer science topics such as artificial intelligence, but also game theory, and the intersection between the two. Our topic for today is an app that Kevin co-founded called Kudu, which uses double auctions to help Ugandan farmers trade more effectively. Kevin was interested in using his skills to help people in the developing world, so during a sabbatical seven years ago, he resolved to go to a country in sub-Saharan Africa to do just that. He settled on Uganda and, after living there for a time, noticed something peculiar about the market for agricultural goods there. In the city, you would sometimes find vendors selling goods at very high prices, and even running out. Meanwhile, in the countryside, vendors would have so much stock they would be selling at extremely low prices, even rotting before they could be sold. Kevin, along with his partners John Quinn and Richard Ssekibuule, set out to help the locals seize these apparent arbitrage opportunities by constructing a platform to allow buyers and sellers in these markets to trade with one another at competitive prices. Most Ugandans have cell phones. Not fancy smartphones (as I wrongly guessed) but basic flip phones. So Kevin and his partners decided to set up a platform by which people could make bids and asks using a basic text-message system, and that system turned into Kudu. The platform has facilitated $1.5 million USD worth of confirmed trades, and it has made the prices of agricultural goods much more transparent for everyone trading in these markets. Related links: Myerson–Satterthwaite theorem Vickrey–Clarke–Groves mechanism  
Today's guest is Scott Beyer, a columnist who writes about urban issues. He is the creator of the Market Urbanism Report. Our discussion addresses some common concerns about housing markets. For instance, why do new luxury homes sometimes sit empty? What's the deal with Houston's land-use laws? And what can we do about the urban housing crisis?
Tooday's guest is Jennifer Murtazashvili of the University of Pittsburgh. We discuss her book, Informal Order and the State in Afghanistan. Despite vast efforts to build the state, profound political order in rural Afghanistan is maintained by self-governing, customary organizations. Informal Order and the State in Afghanistan explores the rules governing these organizations to explain why they can provide public goods. Instead of withering during decades of conflict, customary authority adapted to become more responsive and deliberative. Drawing on hundreds of interviews and observations from dozens of villages across Afghanistan, and statistical analysis of nationally representative surveys, Jennifer Brick Murtazashvili demonstrates that such authority enhances citizen support for democracy, enabling the rule of law by providing citizens with a bulwark of defence against predatory state officials. Contrary to conventional wisdom, it shows that 'traditional' order does not impede the development of the state because even the most independent-minded communities see a need for a central government - but question its effectiveness when it attempts to rule them directly and without substantive consultation. Our conversation dives deep into the modern history of Afghanistan, including its 1978 communist revolution and subsequent Soviet invasion.
Sam Hammond returns to the podcast today to discuss the free market welfare state. He and Will Wilkinson have both written articles in this area recently, and we discuss some of the concepts they bring up. People tend to think of government functions on a one-dimensional spectrum with "big government" on one end and "small government" at the other. Sam points out that the welfare state is separable from the other functions of government (regulation, command and control, protectionism, etc.). Not only is this true in theory, but it is played out in practice, with Nordic countries having very large welfare states as well as high economic freedom. We discuss some of the problems with current welfare states and some ways to improve them. Related links: Study: "Early Medicaid Expansion Associated With Reduced Payday Borrowing In California" "Food Stamp Entrepreneurs," a study that shows that access to food stamps makes people more likely to start businesses.  
My guest today is Frank Milne of Queen's University. Our topic for today will be unintended consequences. Frank has written a paper directed at policymakers to help them understand some of the pitfalls that economists have identified. The paper is directed at Australian policymakers, so some of the examples are Australia specific, though they generalize quite well to other countries. We start where the paper starts, with a discussion of Australia's heavy investment in commodity exports to China in the wake of the 2008 crisis. Many people mistook the temporary increase in demand for Australian mineral exports for a permanent change, leading them to over-invest in developing the Australian mining industry. We go on to discuss many topics, with a particular focus on housing. We also touch on Frank's work on Systemically Important Real Sectors (SIRS), which he is working on with co-author John F. Crean. SIRS are sectors with the potential to cause systemic problems in the banking sector. They feature high volatility of costs and revenues, which create the potential for large losses to lenders. Related links: The Diamond-Dybvig model (Wikipedia) and the original paper. The Arrow-Debreu model (Wikipedia). House of Debt: How They (and You) Caused the Great Recession, and How We Can Prevent It from Happening Again by Mian and Sufi.
Today's guest is Russ Roberts, host of the quintessential economics podcast EconTalk. (If you haven't heard EconTalk, go subscribe to it right now, because it is excellent!) We discuss EconTalk's role in the economics profession, the things Russ has learned in the course of making it, the importance of intellectual honesty, and the enduring insights of Adam Smith. Here's the EconTalk interview with Bryan Caplan that I mentioned in the episode. Stay tuned for my own interview with Bryan! "The first principle is that you must not fool yourself---and you are the easiest person to fool." - Richard Feynman  
My guest for this is Ekaterina Jardim of the University of Washington. Ekaterina is one of the authors of the new minimum wage study that has been making headlines recently, "Minimum Wage Increases, Wages, and Low-Wage Employment: Evidence from Seattle." One reason this study is so interesting is that it was funded by the City of Seattle, which is something that governments aren’t obligated or expected to do when they enact major policy changes like these minimum wage hikes. There was a broad theoretical and empirical consensus in the 1980s that higher minimum wages have disemployment effects on the low skilled, and then Card and Krueger (1994) started a new empirical literature that found no evidence of disemployment effects. A major problem with Card and Krueger (1994) and with many of the other studies conducted over the past quarter century was their use of proxy measures for low-skilled workers. Instead of looking at workers who actually earned less than the new minimum wage, these studies looked at groups that they knew to contain many minimum-wage workers: generally teenagers or restaurant workers. This new study does not face this limitation because Washington State requires firms to report both the hours worked and the wages of all workers. One criticism I’m seeing a lot in response to the media coverage of this study is the fact that they had to drop multi-location firms from the sample. The reason for this is that the data only shows what firms people work for, not their location. So if a firm has locations both inside and outside Seattle, you don't know whether a given worker in that firm belongs in the treatment or the control. Still, despite this limitation, the study's sample included over 60 percent of workers in Seattle. Furthermore, the study authors surveyed employers and found that the multi-site firms that were excluded from the sample actually reported more reductions in work hours than did the firms that remained in the sample. So if anything, this omission understates rather than overstates the effect of the minimum wage increase. One big concern people have is just how much this study's results deviate from the established literature. The authors address this by repeating their analysis using employment in the restaurant industry as a proxy for low-skilled labour. They find that using this proxy for low-skilled labour reduces the measured impact of the minimum wage to near zero, consistent with past studies that have looked only at the restaurant industry. It seems that this apparently robust finding, replicated in study after study over the past few decades, was actually a quirk of studying the restaurant industry, which tends to substitute high-skilled labour for low-skilled labour rather than cutting total labour hours as a short-run response to minimum wage hikes. Related Links Kevin Grier explains the synthetic control method, which the minimum wage study uses to construct a control group.  
The guest for this episode is Jonathan Morduch, he is a professor of public policy and economics at NYU and the author of The Financial Diaries: How American Families Cope in a World of Uncertainty, co-authored with Rachel Schneider. The book looks at the financial situations of ordinary American families. It is centered around a detailed survey of 235 households where they recorded what they earned and what they spent at an extremely granular level. From a truck mechanic whose income depends on bad weather wearing out the parts on trucks to a blackjack dealer whose tips literally depend on her customers' winnings at the blackjack table, the surveys reveal a huge amount of variance in the incomes and expenses of these households. This variance is not captured in annualized statistics, but it has profound implications for the way these households spend and save. We discuss financial literacy in the context of the real problems people face and relate the stories to some results from behavioural and experimental economics.  
What follows is an edited transcript of my conversation with Judy Stephenson. Petersen: You're listening to Economics Detective Radio. My guest today is Judy Stephenson of Oxford University's Wadham college. Judy, welcome to Economics Detective Radio. Stephenson: Thank you very much. It's nice to be here. Petersen: So, our topic for today is economic history. Specifically we’ll be looking at some interesting research Judy has done on wage rates in the early modern period in London. This period is particularly interesting because it's the start of the Industrial Revolution which leads to a dramatic increase in the growth living standards and of technology and that trend of course is what has shaped our modern world and made it different from the world of the past. So, it's very important of course to understand this period if we want to understand the world as it is now. So Judy, start by giving us historical background. What was the world like in the period you study? Stephenson: Well, I work mostly on researching London, so urban environments. And London is very developed in this period between about 1600 and 1800. And London becomes the biggest city in the world during this period and as the biggest city in the world it's hugely vibrant, some of the largest merchant houses in the world are there, banking is advanced and developing. Most of the occupations of London are tertiary or service sector, even at this early date. The river is a huge source of both transportation and work, the port is where much of the capital, both physical and financial, from around the world comes through the city, and the professions and bureaucracy are well established in London in this period. It's growing at all levels of society, from the very poorest to the very richest exponentially. So, if you look at the population growth overall in the U.K. in the late 17th century from 1500-1600 to 1700, that actually is pretty much stable or slightly declining. But the population of London grows by a third or something in that period. London is this hugely vibrant commercial social and cultural center and it's pretty much overtaken Amsterdam, which has come to the end of its golden age in the mid 17th century, right at this period. So, although the world more generally and in a wider sense can be typified by pre-industrial or agrarian values, London is very commercial in this period. Petersen: Okay, so, if I were to get in a time machine and go back in time, maybe London would be more familiar to me, would seem, feel more modern than almost any other place. Stephenson: I think it would be very familiar to you the way of getting around would be a sedan chair or a carriage. You can hire them on the street, in fact you send your boy out to get one. It looks very like Uber, it's a gig economy. And most people working in unskilled, or who didn't have a trade or didn't have a profession or skill probably didn't have steady jobs. They thought of themselves as having work that they could rely on, but it wasn't wholly reliable and they definitely didn't have a contract that would keep them going, they probably didn't have many rights either. And they probably worked at two or three things and everything---the traditional literature about London in this period is one of inequality. So the very very poor literally scavenging on the streets among the smut because the streets were the sewers in those days, and the very very rich living in these incredibly grand environments with retinues and servants. It's a golden age for the aristocracy after they had a pretty rubbish time in the 16th century. It's a golden age for the aristocracy, it's a golden age for art, for architecture, for all these things but it is also a period of desperate poverty and mortality. The plague doesn't die out in London until the end of the 17th century, but still very very high infant mortality and living standards are nothing like they become in the later 19th century, after they sorted out all those things. But from a commercial point of view, you might well recognise it. Petersen: It's very interesting---and of course the whole period is interesting---but it's particularly interesting for what it becomes, really. The rest of the world starts becoming more like London, starting in this period. Stephenson: Yes. Petersen: And so you study wage rate of some of the day labourers and the workers in that period. How have economic historians gone about measuring things and getting data that far back in the past? Stephenson: Well, data on wages and prices for this period was originally gathered by a guy---Thorold Rogers---who was a 19th century historian who started collecting wages and prices in the mid 19th century and finished 40 years later, literally a broken man. These are seven volumes from around England and he basically went into any long run institution where there was an archive or records, as they were called in those days, and just noted the quantities and prices found in the books. But it was a huge project way before the days of even print noting, before the days of an efficient typewriter, let alone a computer. It was pretty haphazard as to what he was actually recording but it's very accurate. But he tended to take down labour costs or wages as day rates, and what he mostly found were builders because he was in big Oxford colleges and places like Westminster Abbey which had buildings from the 13th century and had required a lot of building maintenance and surprisingly he didn't find many other wages. So this way of recording had a sort of half dependence. These day rates because they were the only ones that people could find it was assumed that wages---wage rates are very hard to find but there's always good ones for builders---and it was assumed that builders were the same everywhere in terms of skill levels so these could be comparative. And Arthur Bowley---who is known as the father of modern statistics, an economist and statistician again working in the end of the 19th century and in the early 20th century---used builders in his first attempts to think statistically about an average wage, an average worker, and to establish a real wage. And Bowley’s work is absolutely seminal in the history of statistics, econometrics, and economic history. And he used Rogers' and others' wage rates of builders. And this tradition carried on as other historians gathered more rates, like Elizabeth Gilboy in the 1930s, and then Phelps Brown and Hopkins used all these people's data when they came up with the seminal Seven Centuries of Building Wages in 1955. And what Phelps Brown and Hopkins had done was they took all those day rates from the builders, and then they took a series of wages and prices and they created a basket of goods and they offset the wages against the prices and they came up with an index of the real wage or living standards across the ages. And this has been the standard for measuring welfare since 1955. And because it's very difficult to find wage rates for the 18th century for some of the reasons I spoke about a minute ago---not many people have jobs, etc etc etc---the dependence on builders' wages continued until, with the most amazing econometric and advanced econometrics techniques that Greg Clarke and Robert Allen were using, they still use that data from the 1930s. I think the latest good index Jeremy Boulton made in the early ‘90's, where he collected about 2,700 observations of wage rates. The key thing to remember here is all of these wage rates came from bills in the archives of the institutions. So they’re not really wages. In fact they are not wages at all. So, I don't know if you've ever worked for somebody and been charged out by the day, have you? Petersen: I have not, but my wife is charged out, she works in data science and yes, she gets one wage and she's charged out to other firms at a different rate. Stephenson: And what she's charged out is higher, right? So, when I worked in advertising, I cost my clients about 1,800 pounds a day, I saw about 350 of that. What a bloody enormous margin, actually. You got to look at how IPG were not making a really stonking profit on that but you know there's overhead and those kinds of things. Well, in the 18th century everything, but particularly in the building trades, that's exactly how you dealt with masons or bricklayers or carpenters or labourers. And any economy that has to organize production---and the building they were organizing was pretty big, the Great Fire of London destroyed the old city and was completely rebuilt in about a decade---there's some serious organizational coordination mechanism problems of making all that stuff happen. And the 18th century way of doing it is contract it out. Firms are a series of sub-contracts and so the way wage rates have been collected were the sums that were paid to contractors and what those contractors pay their men were substantially lower than those wages that Phelps Brown and Hopkins had used, or Robert Allen had used and Rogers and people have recorded. Petersen: Okay. In your paper you mention Robert Allen and he had a hypothesis that based on these faulty rage weights that high wages in London were a contributing factor in kicking off mechanization in the Industrial Revolution. So, can you talk a little bit about that hypothesis and how your new look at the data has, I suppose, called it into question? Stephenson: Yeah. So, Allen has made the most seminal contribution to the study of the Industrial Revolution. So, the Industrial Revolution is the savored big debate in economic history really and it's a favorite big debate for lots of parts or disciplines within economic history. The history of technology people like it because of the gadgets, the history of macroeconomics and supply and demand people like it because of the factor prices, the history of the organizational people and sociological people like it because of the institutions in the factories. So it has this broad appeal for everybody who's interested in the economics of the long run. Essentially, the core issue around the Industrial Revolution is it's unexplained. Why did it occur in England before anywhere else? It's this naughty problem that had never really been adequately explained until the early 2000s. Then there were two competing---well not two competing but two complementary---explanations by sort of giants of economic history in the same period. So, Bob Allen explained it through England being a high-wage economy and Joel Mokyr explained it through a series of innovations and enlightenment and how that brings about sort of an intellectual enlightment in scientific innovation. Allen’s theory was the economists’ theory and still is. And essentially what he proposed is that the high wages of England incentivized the owners of production to substitute capital for labour. Essentially because of the way series are constructed when you take all those comparative wage series of Amsterdam, London, Milan, Florence, Madrid, Antwerp, Strasbourg, when you sort of put them all together as a real wage series in the long run, the English wages looked substantially higher by comparison, particularly after 1650. It looked like the cost of labour for capital in England was much higher than it was in the rest of North Western Europe or Italy, where you had the traditional textile industries and banking, where there was some quite advanced commerce in places. Allen argued that the high wage economy first of all created those incentives but that also it had created higher human capital and skills, attracted capital to it, to prepare England for industrialization in the long run. But that the trigger was induced innovation through relative factor prices. And part of his theory also was that coal was cheap and available in England, which is very hard to argue that it wasn't, the coal in China is in Mongolia, the Dutch don't have any they've got coal in the Ruhr, of course. But you know coal has been at the center of English energy requirements for a very long time as Tony Wrigley has written about in a very distinct way actually in a lovely book called Energy and the English Industrial Revolution, which is the kind of thing your children could read. So the relative factor prices between energy and capital and labour were unique in England is Allen’s argument. So, obviously if you find out that the wages are 20% to 30% to even 40% lower than Allen thought, that presents a problem for that theory. Petersen: I believe I heard once that Germany had coal but it had to be transported over land and so was as good as useless to them before the age of the steam engine and trucking. Coal is really important. And so Robert Allen felt that high wages in London and in England were important but it seems like this issue of measuring the contract rate instead of the wage rate casts doubt on that, or even---does it close the whole gap between London and the rest of Europe? Stephenson: Good question. And that really depends on what sort of organizational form or coordination mechanism was in place in other countries. So,I've looked into this with Amsterdam and Antwerp quite a bit already. I've done some work with Heidi Deneweth who works on the Low Countries on economy and building particularly. She's at Ghent. And we're finding in the way that building is organized in Amsterdam, in London, is that in London very much the state has completely outsourced everything. So, the city doesn't employ people directly, that's too much hassle. It seems like the cost of management to something is very high in England because they outsource everything: the navy, the supply, the whole thing. Bits of the navy are integrated into it, but a lot of it, particularly the supply to it, is outsourced and all building is outsourced. Whereas in Amsterdam the city still employs people who are digging dikes, and looking after canals, and doing maintenance work on public buildings. Whereas in London the comparable projects which would be stopping London Bridge from falling down, or wharfing the fleet ditch and making these canals and things. Those are given to large contractors and the contractors are solely responsible for labour. Whereas there is some relationship between labour and the city, people are directly employed in Amsterdam, this is indicative only and we need to do a lot more work on comparing contracts in the same types of organizations. And then there's a guy called Luca Maccarelli, who is an established Italian historian of the building industry and industry in Milan generally and he has looked at some of the data for the wages for Florence and Milan particularly and he has shown that the day rate was only part of the wage there. In fact the contractors were throwing food, bonuses, cash savings, access to places to stay, and all sorts of perks at workers to try and induce them to work. So the wage in Italy was probably a little bit higher. In fact, Mark Reilly has said that we've understated Italy’s by 15-20% and then the person who's done the most work on France so far is Vincent Geloso, who's shown that the Strasbourg wages are probably problematic. But all this comparative stuff is at a really early stage. And we need people to get out into the field, the way I've been in the field in London, and look at more the form of employment and the form of the wage in those places. And really understand, the figures that we've got are they real or have they got other sort of recording factors like I've shown in London? So it's too soon to say although we started work on that. Petersen: So, for the modern era we have people collecting data and they're making a big effort to collect the same data across time and across place. Surveys asking the same survey question to everyone, or government data and making sure it's collected in the same way every year but when we're going back to the past, of course there was no one in the year 1700 collecting data on Italy, and London, and Amsterdam, and all these different places. And so we have to stitch it together from what is available and often that's very different datasets. Stephenson: Exactly, and different types of records. So, it may be the case that all the records are a bit skewed and you know there'll be a new schema once we have all the new data together that does reproduce the Allen’s story. And remember that we need to take the prices of goods into account. It's a real wage calculation he's done not just a nominal wage calculation. But until we've done that, what we do know is the living standards in England were not what Allen thought at the moment but you've got to do the whole comparative thing to know. Petersen: So, how do you distinguish the skilled from the unskilled? How do you make sure you're comparing the same kind of labour? Stephenson: That's a good question. Traditionally pretty much everywhere in Europe we've gathered two types of wage: a skilled wage for what we call craftsmen and craftsman are people who have completed an apprenticeship, who are qualified, that's the idea. So, a mason who has studied seven years in England---doesn't seem to be as long anywhere else---or a carpenter who has studied in the long run. So, who has invested time in the development of the human capital and acquired skills and then we think about the unskilled person as a counterpoint as being the labourer. And this is another important distinction because you know building labourers are actually of two kinds: there's the completely unskilled guy. Actually there are three kinds: there's the completely unskilled guy who's basically just handing them nails or wheeling a barrel around. But then there's the more skilled or semi-skilled assistant who actually is doing a lot more than that, who is preparing the work for the craftsman, who knows which tools go with which materials and who is fully assisting a craftsman and they couldn't really do the work without them. And you call that semi-skilled. And then there's a labourer who is hired really for their brawn. They've got a premium for being extremely strong and what you tend to see in building accounts is people who are actually hired by the load. They get 2 shillings and 8 to move a ton over a day or something---and probably need more than one man to do that---but so there's a brawn premium in these labourers or unskilled. And actually from Phelps Brown and Hopkins onwards we've taken this semi-skilled or brawn wage to be the unskilled wage, but these people aren't unskilled. Whereas the unskilled, the guy wheeling the barrel, or just picking out nails was paid a lot less than those. So, if the rate for the semi-skilled guy was 18 pence a day in 1700, the rate for the unskilled guy was 12 to 14. So you can see there's a considerable premium in here. That's another thing that colours our understanding of welfare because usually it's the unskilled or subsistence wage that the macroeconomist is interested in. They relate unskilled and subsistence even though they maybe should not. It's that unskilled wage that is an indication of supply and demand in the labour market, and the draw of that. So taking building labour to a semi-skilled to be unskilled leads to some problems because it implies that unskilled people in London could afford four times the subsistence basket of welfare goods in 1700, when actually they could barely afford two. So, if you're going to use a welfare basket these rates have a real issue and the distinction between skilled is… Petersen: So, the reason maybe we care more about unskilled wages is because that's the wage that you'd expect to see in other places in the economy. For instance unskilled work in agriculture or working in a shop or things that we don't have data for we can sort of guess because presumably there's a labour market and people have mobility and if there was too big a gap between wages for different unskilled jobs then people would move, they’d arbitrage away that difference. So your paper, it has some sort of case studies. You have data from particular construction projects. I thought those might be interesting to go through. So, one of them is the reconstruction of St Paul's Cathedral after the Great Fire of London, which is a massive project, could you talk a little bit about that? Stephenson: Well, yes it's a famous project because the old St. Paul’s had stood since I think the 14th century. It was this you know cultural and emotional symbol for Londoners apparently, and it had been redesigned---the front had been redesigned---by Indigo Jones, the kind of father of classical architecture in England. And it was completely destroyed by the fire and this was a sort of symbolic task to rebuild and so Christopher Wren hailed the King, came up with the design and you know Wren is pretty much the father of modern architecture and he's this enormous intellectual as well as architectural figure, he's very much part of the enlightenment. So the project lasted about 35-40 years, so they declared it finished in 1711 and the Great Fire was 1666 and it's still there today, absolutely intact, it survived the Second World War. So it's this incredible and very emotive building. The interesting thing from a work point of view is it's very much a craftsman's building, it's not an artist's building. So there is sculpture there, there is painting but nothing like a European cathedral like St. Peter's, St. Paul’s is very much a display of English craftsmanship and baroque style and most of it is stone faced. So, I have these wonderful papers, which are the day books of one of the Master Masons, one of the contracting masons who built the south west tower on the west front. His name was William Camster, his father was also a contracting mason on a separate contract and in the network of masons who served, ran and worked. We’d ran over 30 or 40 years and he was on site for about 10 years of the project from 1700 to 1709 or so and some after and I have his day books right, years of this, where he records every single man that was working for him and what they paid him. So, it's got an appeal because you can go and see what they did---which is very rare---working on the 18th century that you get some wage records and you can actually see the product as well. So, it's quite nice from that point of view. So, from an economist's point of view the interesting thing is the way that they contracted the construction because they just started out one contract at a time and then if it worked, they’d go "Yes. We'll do that again." So, they had these repeated idiosyncratic contingent claims contracting going on and on and on and obviously disputes arise and they resolve them, or people drop out and they get new contractors. But the whole thing is basically on a rolling contingent claims contract what Oliver Hart and Holmström said could never happen. Oliver Williamson would have had his head in his hands. But the other notable thing is that the contractors financed this really because the Crown didn't pay them. It did pay them but the Crown and the city, they leveraged the coal tax but mostly people waited two or three years on contracts to be paid. So, the cost of financing that was just swallowed up by the contractors, it was in the price. And that's one of the reasons why you see a margin on labour and materials. But the interest costs for St. Paul's were as a total of the entire bill over 35 years about 20%, and very little of that had been lent by citizens and the city, a lot of that had come from the contractors themselves through just rolling over bills. Petersen: That's interesting. So, we know not only what they were paying their day labours, but also implicitly we know the interest rate for that time. Stephenson: We do. Yes, 6% for to and from the cathedral. Six percent on an annualized basis. Stephen Quinn and Temin and Voth have found higher rates, above 8% for some private lending around the same time. And it is likely that these contractors will have had to have done some private borrowing or lending within their networks to keep rolling this finance over. Because they will have bought the stone, they will have paid the carter, they will have paid the labours who are working for the carter, they will have paid the craftsman, so they may have well have to borrow to do all those things but 6% is what they got from the cathedral. But the real question is then, so these networks of supply chains are surviving on that kind of finance. So really big contracts essentially on a very high level of trust or a very high level of interest. We need to do more work to find out which, but it does seem like these networks---because they repeatedly contract---they have good information and it's more effective than you would imagine those types of contracts to be. Petersen: And of course they're contracting---it's the government paying for it ultimately right? Stephenson: Yes, and it's financed through the coal tax which is also interesting. Bearing in mind the price of coal is relevant to development at this time. The coal tax was levied at a shilling a cauldron after the Great Fire to rebuild the churches for the city and then it was maintained through and into the Georgian period by parliament who kept sort of either adding to it or continuing it and apparently it was detested and greatly avoided. But we definitely need some more research on how this work, and how people avoided it, and and what it did to coal consumption. Because you find in the accounts that the coal tax, they're expecting this much per year from it and consistently about 10 to 15% less comes in. So they have to turn to the city or to commissioners and people who might have money to borrow from them and tide it over. So financing the thing was unconventional. Petersen: So, we usually think of government debt as being highly safe at least in the modern period but back then it may not have been. Stephenson: Yes, and I don't know what the connection to other Treasury things are and Bank of England and everything. At the time it looks like it's just private between St. Paul's and the commissioners for St. Paul’s and either citizens or contractors and that it wasn't actually securitized as a state promise, but there may have been connections. It's something I haven't delved into enough. Petersen: So, another construction project, in this case it's a maintenance project, is the famous London Bridge which of course in the nursery rhyme "London Bridge is falling down" which apparently was true. Can you tell me a little bit about that? Stephenson: So, well London Bridge was it was built the end of 13th century and it's 19 stone piers across the Thames. It must have been the most fascinating and amazing structure, it stood for pretty much 500 years, but by the end of the 16th century in the early 17th century it is falling down. And the Thames because this sort of development further up river as well, the Thames is actually a very strongly flowing tidal river at this stage and the force of the water force through those 19 piers is wearing away. So they built wooden starlings, so they built a wooden constructions they look like boats around the piers, trying to guide the water through and these of course made the problem worse and they made the waters faster. So to pass under the bridge in a boat at high tide apparently you could drop 10 feet through the rushing rapids beneath. So you pay the shootsman who was contracted by the bridge to guide you through the piers. And it was really quite dangerous. So, the bridge has a number of maintenance problems: the first is the starlings the mason repairs. The second is until the mid 18th century the bridge was covered in housing just like Ponte Vecchio in Florence as a proper living bridge the housing was also in a state of disrepair and some of it owned by the bridge and some of it owned privately. So the bridge tried to take over the property that isn't theirs and then get rid of the housing that isn't working, it's falling into disrepair over this period. And there's a guy called Mark Leighton who's written a brilliant thesis at the University of Leicester all about how the bridge masters and the City of London get rid of the housing in the mid 18th century. But essentially the bridge is the only crossing from side to side, from north to south or vice versa until 1750. There isn't another way to cross the Thames. There was a little wooden bridge up in Putney in 1729. London Bridge it's got all of the infrastructure of London basically. And so it's hugely congested and falling apart. So, the maintenance bills are are huge. Oh yeah as well. So as well as the starlings you then have water wheels which are basically bringing the water from the New River Company and the Thames to give water to the city. So those are also in operation, these whole teams of little engineers looking after the water wheels. So it's a really busy bridge it's got people scrambling over it all the time looking after it, not before the shootsman or anybody else doing any work on it and those people were paid not very much. The master craftsmen were paid for their contract and got a really good rate for looking after the contract, and then they hired others piecemeal so they'd hire well-known carpenters or masons. But they'd never have regular days or regular work and then the labourers were paid by the tide. So at high tide you could work on the bridge or you could work on the upper bits of the bridge if you were in a boat; at low tide you could access all those damaged starlings and piers. So at low tide they worked in boats and that meant that in the winter you might only get four tides in the week depending on when the tide and the light coincided, in the summer you could maybe get 11 and then when they didn't need any work done you wouldn't get any tides at all. So, there were quite a number of people. It varied from teams of 12 to teams of 80 or so who were employed in this fashion in a piecemeal just waiting for a little sort of bit of peace work on London Bridge. So, it's an interesting bit of contact with the sort of materiality of the world as well, everything was literally ruled by when the water came in. Petersen: Right. And since it's such a long period of time, I suppose you can get a decent time series of that change in the wages over that period. Stephenson: Yes, from a labour economist point of view, one of the fascinating things about the 18th century is this persistence of rates, particularly for labourers, it's a very monopsonistic market it's a classic monopsonistic market. It's a wage posting. One where employers basically will see who will come at this set wage and what happens is they don't change the wage. The fluctuation happens around the number of days worked. So people don't turn up, or don't get work when there is less to do. The number of days fall away and when there is high demand, an upward-sloping curve, the number of days go up for everybody. But a transaction cost analysis would suggest that the 18th century employer understood the costs of such information very well indeed because they weren't going to have any asymmetry of information. They were going to post ‘this is what you get,’ particularly the unskilled hand and the time or the amount of work that you got was how the fluctuations and the dispersion occurred. So there's a lot more work to be done on that because nobody's really ever looked at this kind of market in those modern terms, understanding it as monopsonistic or having search or information costs. And it's only with these levels of micro data that we can begin to understand that it might have worked like the labour market we know. Until about 20 years ago people thought---until much more recently actually, the last paper I can see about this is in 2007 by Leonard Schwartz---that essentially before 1840 it's a market dominated by custom not by market forces. But on a micro analysis it looks very much like there are just the kind of market forces at play that we understand today. So, wage posting at the lower level, a little bit of wage bargaining at the skills level, and supply and demand do actually equilibrate but not through the rate, through the number of days worked, which of course brings about the income. Petersen: So, the third construction project you discuss is the Westminster Bridge, which I suppose is that that second bridge you mentioned earlier. Stephenson: Yes, the second bridge, the cross rail of the 18th century. Petersen: Is that interesting from an economic history point of view, we have a lot of data from that? Stephenson: You get less data because I don't have anybody's nice little book saying who came in and on which day, so I don't have the number of days' work for Westminster Bridge. The interesting thing about Westminster Bridge is the different kinds of contract. Everybody, they were making contracts for hundreds of thousands of pounds with the masons and engineers and they also had a contract with a guy who had a horse and three piles for 27 pounds for the year. So, you've got this variation in value or risk from a financial point of view which is quite dramatic. But the key thing is that at Westminster Bridge you find the tide and the day model as well. So a much smaller number of days than you would expect that are actually billed to the institution, but this means of paying by the tide, which protects productivity from an employer's point of view. So that also occurs at Westminster Bridge. And what you find is that people are doing quite advanced and quite dangerous work, but without the danger money. They were given gin instead. So they sank caissons, this is one of the earliest uses of caissons designed to create the piers. So these things are experimental to say the least, and they put people in diving gear into the caissons and it must have been terrifying, you know, what if the stuff gave way and they went under the Thames. In February, because that's the time you want to be in the Thames! You know, in 18th century diving gear. And got them to work on the masonry or on the carpentry on the bed of the river for the same rate as you could be having quite a nice comfy time carving out something simple, or doing some basic maintenance work on a couple of windows on some bridge houses. So, yes very dangerous work. There seemed to be a lot of skill available, ready to do that work at those kinds of rates. Petersen: So, where do you see this research program going in the future? Stephenson: There's obviously an issue about the rate of welfare, the real wage and welfare in the 18th century and to be honest if we're going to make a serious contribution to that, we need to start looking at people who aren't builders. I've started a project with the Cambridge Group for the History of Population and Social Structure, where I spent a year before I went to Oxford, on London occupations. Because that Cambridge group, they are the masters of working on occupational structure in the long run in England and we are sampling institutions that bought goods and services widely. And the kind of bills and the kind of businesses that they deal with to understand what sort of people were employed where. So, to try and get some welfare and some wage data beyond builders that we can normalize and use properly. I think the second direction for this research is to understand how labour markets worked. Was there such a thing as custom? Because one of the old things we believe about the Industrial Revolution, and this idea doesn't really stand up anymore, but it's something that's still emotionally alluring for a lot of people, we see the Industrial Revolution as that sort of capitalism thing and our version of capitalism got going. But if people already understood transaction cost economics, and Christopher Wren writes like Oliver Williamson sometimes, then maybe the market didn't start then, maybe they already had a view of the market. And there are some organizational things that we need to be looking at from that point of view. Essentially the 18th century will always be interesting because it is a free market. It is unregulated, there's no corporation tax and the finance is not state controlled at all. This is before the gold standard, this is before states get interested in managing money in a big way. There is monetary policy but it's not in the same way we conceive it now. And so labour and capital have a relationship that is unencumbered by the state, by government, by regulation. So what is the outcome of that? Was it a race to the bottom, was there any equilibrium, what happened? So, there's a contribution to be made to studying that as a sort of a history of ideas thing as well. It's hugely rich but those are broadly the three things that are on my agenda right now. Petersen: My guest today has been Judy Stephenson. Judy thanks for being a part of Economics Detective Radio. Stephenson: Thank you very much. I very much enjoyed talking to you.  
What follows is an edited transcript of my conversation with Vincent Geloso. Petersen: My guest today is Vincent Geloso of the Free Market Institute at Texas Tech University. Vincent, welcome to Economics Detective Radio. Geloso: It's a pleasure to be here. Petersen: So the paper we'll be discussing today is titled "A U-curve of Inequality? Measuring Inequality in the Interwar Period" which Vincent has co-authored with John Moore and Phillips Schlosser. The paper casts doubt on the claim from, most notably, Thomas Piketty and others that inequality fell from the 1920s to the 1960s and rose thereafter. So, Vincent let's start by discussing the inequality literature prior to this paper. What is this U-curve and where did it come from? Geloso: The U-curve is probably the most important stylized fact we have now in the debate over inequality and the idea is that, if you look at the twentieth century, there's a high point of inequality in the 1910s, 1920s and then from the 1930s onwards up to 1970s, it falls dramatically to very low levels and re-increases thereafter, returning to 1920s-like levels of inequality. So the U-curve is the story of inequality in the twentieth century. It's mostly a U.S. story because for other countries it looks less like the U-curve than an inverted J. So it's higher in the 1920s, it still falls like in the U.S. but really increases much more modestly than the United States in places like Sweden, or France, or Canada. But the general story is that there was a high level of inequality at the beginning of the century well up to the mid-second-half of the twentieth century and it re-increased in the latter years and then we have been on a surge since then. Petersen: So, a lot of this is coming from Thomas Piketty, who of course wrote the surprising bestseller "Capital in the Twenty-First Century." Could you talk a little bit about where his data came from? Geloso: Okay, by the way, this is where there's a failing on my part which I think I always find funny; an anecdote to tell about Piketty. I'm originally from Quebec, so I am a French-Canadian, I speak fluent French. His work started coming out in French first and I initially started to write elements of the paper we're discussing today back when it was only in French. And then I told myself, "There's no point, it's only a French book, nobody reads French. What's the point of writing a paper about a book that no one will read?" Biggest mistake of my career, I guess, not writing that paper before. But anyways, besides that, his entire argument is based largely on his most influential paper---which I think was published in 2003 in the Quarterly Journal of Economics---which was using tax data. So, the records, the fiscal statistics to create measurements of income inequality in the United States and the advantage of that is that since the income tax started in 1910s you've got a long, long period of measurement of income inequality with the same source. So it's a great advantage because a lot of the people before like Kuznets, like others had to use residual estimates, different sources, they were amalgamating different sources together and it was always a problem because you couldn't create one homogeneous time-series of inequality. You could get a rough idea and there's a few papers---for those who read economic history stuff---there was a paper by Lindert and Williamson in the 70s in research in economic history and you can see their first graph in that paper was a series of different measures of inequality. They were all pointing to the general similar shaped curve but they were all from massively different statistics, different sources. So one was the 50:10 ratio of earnings, another one was a measure of income, the other was wages and they are all different measures, they are not perfect. You can get a good idea, a rough idea but you cannot have a continuous time estimate which is what Piketty innovated by using the tax-wealth with Emmanuel Saez, recreating this long continuous trend in data from 1917 to the modern day. And they keep updating it regularly to include the new data on a yearly basis. Petersen: So tell me about tax avoidance. How does that affect things? Geloso: Okay, this is where the existing data that all the different sources had---Piketty made advancement. Rather than having variance across different sources, he was eliminating that variance. But there's still an issue of variance within a source. So it's not because you have used a homogenous source that the quality of the data contained within the source is consistent. There's actually quite a lot of variance in data quality because of the way the tax system was done. So a lot of the debate today for the data for today has been---has there been such a large increase in inequality as Piketty and Saez and Atkinson and others have been pointing out? And the reason for that was largely because, as Alan Reynolds, as Joel Slemrod, and a few others have pointed out, the tax changes of the 1980s were so large that people shifted the way they reported income. They changed the way they reported tax liability. What used to be classified as corporate income became classified as individual income, and so you get an artificial increase because of a way the tax system has changed. And this is why a lot of people say, as soon as you correct for the effect of changes in tax reporting behavior, you actually get a much more modest increase of inequality. But that's from 1980 to today with a massive tax change in the 1980s. If you go back further in time, to the interwar period the tax changes are much more dramatic. In 1913, the tax rate was 7%, went up to 15% in 1916 to 73% until 1921, went back down to 24% by 1929, went back up to 79% by 1939. Imagine, that's a lot of movements in the way taxes will affect behavior and it will affect reporting behavior. So, will you report, will you be as honest as you would be when you're filing taxes at 79%, as you are when you're filing taxes at 24%? So you're getting---because of these massive changes in tax regimes that are happening over very short periods of time---these massive changes affect the quality of the data set that Piketty is using for the left side of his U-curve. The left side of the U-curve is probably inaccurate to a very high level because of tax avoidance, and this is where the economists in general failed to talk to historians because there's a few papers out there that did measure---especially in the Journal of Economic History---that did measure changes in reporting. So changes in tax avoidance occur basically to a large level by the top incomes, as Gene Smiley argues in the Journal of Economic History, for example, which Piketty has never cited neither Saez, neither anyone in the debate. And he did corrections, so he checked: Okay, when a tax rate went down from 73% to 24%, did people change their reporting behavior? Did more rich people start to report incomes? And the answer is 'yes.' And as soon as he started doing corrections for that to control the "artificialness"---if that's a word---of the tax changes on affecting the level of inequality, he actually finds that the 1920s have a much lower level of inequality because of the reduction in tax rates and there was very little upward trend, especially when we're comparing with the Piketty, with the Mark Frank data, with the Kuznets data and it shows that as soon as you adjust for tax avoidance the left side of the U-curve flattens dramatically and it looks more like an L---an inverted L---or a J, but it doesn't look at all like a U-curve and that's just tax avoidance for the 1920s. The increases in the 1930s in tax rates would have had the opposite effect where people would have reported less income. So, the level of inequality in the 1920s is overestimated in Piketty and it's underestimated for the 1930s. So you're kind of flattening the entire interwar period as soon as you consider the one issue of tax avoidance. And there are estimates out there in the Essays in Economic and Business History by Gene Smiley and Richard Keehn. Smiley's article in the JEH, which has been ignored in the literature, but which did check that people at the top of the income distribution are generally very sensitive to changes in tax regime in the way they report their tax liability. Petersen: So, today they would do that by maybe registering---having their money in the Cayman Islands or Ireland or the Isle of Man, their tax shelters abroad. Was the avoidance different in the 1920s? I expect it would be harder to enforce taxes given that the income tax was so new and there were all these changes and they didn't have electronic records, or how did it work? Geloso: You're thinking of avoidance in a very negative term which is the illegal part, which is what has somewhat permeated the public debate and I have this reflex myself. I think of avoidance always in that way. But avoidance is sometimes just planning your taxes, your sources of income, differently. One example would be---and it's not really applicable to our case---parents can put their kids on company payroll because it's cheaper dollar for dollar relative to giving them an allowance from after-tax personal income. So, people can change their behavior in their way to get money, in the way they report their income. So you can pass corporate income as a personal income or personal income as corporate income. You can deduct expenses one way or another. And one way or another it comes to affecting the quality of the data set. And it does matter, because if you look at the 1980s when there was a rapid change in the income tax rate, which was much more important a change than the change in the corporate tax rate, it led people to change the type of incorporation they were in, so they became S corporations, so corporations that were not subjected necessarily to the corporate income tax. So, it affected the way people reported, classified their income and it appears artificially the income inequality statistics. The 1920s' equivalent was municipal bonds. Municipal bonds were assets that delivered incomes but they were not subjected to taxes so this was like a tax shelter that was completely legal and that rich people used in dramatic amount to reduce their tax liability. So, when people think of tax avoidance it's generally this idea that people just reorganized their classification of income to make sure they have the smallest liability possible and in a situation like that, what you get is a much different level and trend of inequality because of the changes in tax regimes that induce changes in tax reporting behavior. Petersen: So is Piketty not adjusting for this at all? He's just taking the tax data at face value? Geloso: He's trying some stuff but he gets a lot of the tax history quite wrong and what alerted us to this is that Gene Smiley's paper, which is not in an obscure journal, it's in the Journal of Economic History which is considered a top tier journal in the profession of economics---it's not AER, it's not QJE, but it is a very respectable journal. And Smiley's article is also very cited. There's a large number of citations of that paper and Piketty just ignores it. And you skim through his book and the discussion is always brushed aside and these effects of changes in tax regimes is always minimized as if it was not important. But tax avoidance is only like a fraction of the problem, because if you look, there's another issue that's much more dramatic than tax avoidance. Alone the issue of tax avoidance, if you take Smiley's stuff, changes the narrative dramatically but that's just our first shot in this debate with me, John, and Philip. It's our first shot, the second shot is that filing requirements were nowhere close to what they are like today. And actually this is something funny, the idea of Piketty is that you can create a series assuming tax compliance for a country that was founded on a tax revolt which is---for a historian---kind of a weird assumption built in the way he does his history part. And if you look at it, one of the example is that you look at the changes in wages of people---wages for unskilled workers, wages for mining workers, for agricultural workers---they do not evolve at all like his bottom 90% of income behaves, it behaves actually very differently. So, in our paper we show that the quality of what's at the bottom of the income distribution is dramatically different, so wages go up much faster than the income of the bottom 90%. And this is wages. So, you think what, maybe hours are going down? No they're not in the 1920s and 30s---well in the 30's they're going down---but in 1920s hours are actually staying stable and in some industries are actually slightly increasing. So you should not see what Piketty's data suggest, which is that there was stagnation in the income of the bottom 90%. There was declining unemployment, there was rising wages and hours remaining relatively stable. It's impossible to reconcile these facts with those of Piketty without considering that there might be problems in the way people filed their taxes. And this is where the entire thing breaks down and you look at, for example, the number of tax filers that were actually there. And you look at that as a percentage of the American population, up to the 1930s---so until the Second World War---there's never more than 6 or seven 7 percent of population that files in tax reports. Petersen: And you'd expect it to be the wealthier people too, who are filing right? Because you have people below a certain income, they don't file income tax, right? Geloso: Exactly. This wouldn't be a problem if your distribution of people behaved equal to the distribution of the general population and the movements were the same. It wouldn't be a problem. The thing is when you look at the number of adjusted tax returns which is what Piketty and other people like Estelle Sommeiller or Mark Frank do. They try to re-correct this issue of a very small number of tax reports that were actually filed in and they get an idea---and this is figured too, I think, in our paper. There's a steady upward trend in the number of adjusted tax units but when you look at the actual number of tax units it moves so much. It goes up and down and it doubles in the span of two years, then it reduces by half in the span of another two years and these are such large movements in the number of tax units that it's hard to see that this might be a representative sample of the American population. Differences in reports and such changes in our reporting---and the number of reports I should say---suggest that there is actually a problem in the quality of the data. And this is where we're saying that if you combine this with the observation that wages were increasing, unemployment was falling, and that hours were more or less stable, and that you add this fact of the massive changes in tax returns, you can easily question the quality of the data from the 1920s and the 1930s. This is where we're coming in and we're saying, no, the people who reported taxes were very volatile. They were rich people who reacted to changes in income taxes. Lower income individuals also were very much tax resisters. There's an entire story told by David Beito. I think it's with University North Carolina Press. He has a book on tax resistance in the United States during the 1920s and 30s and there's actually a large documentation of anti-tax leagues that have massive memberships of common individuals who are resisting filing taxes at that time. So it's quite plausible to say that, if there's such a difference in wages, in hours, in unemployment what they and these massive changes in the number of tax returns filed, it suggests that probably the poor people just didn't file in their taxes. So, any movement at the bottom of the distribution does not exist according to Piketty's data. But there were movements at the bottom. There were people who moved from poor Kansas to Illinois. They were still in the bottom 90% but by moving from farming Kansas to Chicago to work in a garment industry, they get a gain in income but that is not captured in Piketty's data because it's highly likely that poor individuals tended to file fewer tax returns and were probably more hostile to filing them, and the rich were just reacting to changes in tax regimes. So, the tax filing requirements would actually lower the level of inequality overall from the 1920s and 1930s. So, the tax avoidance issue would change the trend and the issue of tax filing requirements would drop the level because we're not capturing bottom incomes properly. So you're changing the U-curve progressively as each of our critiques is embedded in the argument you actually progressively bring down the left side of the U-curve and it looks more and more like a J, or an L, or a hockey stick. Petersen: I remember in 2012 Mitt Romney got in trouble for pointing out that 47% of the population doesn't pay income tax. So if Mitt Romney were running for president in the 1920s, I guess he would have said something like 94% of people are not filing and paying income taxes. Is that right? Geloso: Exactly. That would be a very accurate. Well it's 94% of people. The taxes were based on households, but still 6% and then later on after the Second World War it jumped above 40%. So there's a massive change not only in tax regimes in terms of rates, but filing requirement regimes, which will also change the tax behavior of individuals. And not only that, this is something that actually, it was buried in a footnote of Smiley's article which is---still I will point out not cited by Saez and Piketty---but it's so rigorous and it contains so many pieces of information that are crucial. Until 1938 public sector employees were not mandated to file in taxes. This is an unknown fact. Until 1938 they did not have to file in taxes. So this is actually a very very big factor. So in terms of wage earners, so not everyone, it excludes farmers, but all wage earners, 12% of them were government workers. This is a substantial share of the workforce and not only that, their earnings are slightly above the rest of the workforce and the increase in their earnings is above those of the other workers in the United States in that period. But they're just not considered in the tax distribution. So until the public salary Act of 1939---which was debated in the Senate in 1938-1939, the 1.2 million federal employees---this is a large number---were drawing large wages and they're just not included in the statistics based on tax data. This has a massive impact on the level of inequality. Public workers were not in the top 1%, they were not the richest, they were not poor and they were earning much more over time. I'm not trying to debate whether it was efficient government spending or if they were paid at actually providing public goods that people actually did want. But set that issue aside, they had higher wages than the average representative of a sizeable share of the workforce and their wages increased much more importantly than other ones. So you're affecting the trend. You're affecting the level and you add this other issue and then look again, imagine the U-curve in your head. Tax avoidance, it changed the trend. It made it less, it made it much lower in the 1920s than it was. It increased it relative to the Piketty data in the 1930s. The entire level then is reduced by adjusting for tax filing problems and then if you tried to adjust the issue of public sector employees who didn't have to file in their taxes you drop the level again, so it's looking less and less like a U-curve than what Piketty claims. So, we haven't made all these adjustments, we're just stating facts that should be known in the inequality debate. Our goal is later on to test each of our points. We're sending such a large number of criticisms that there's bound to be one that sticks in terms of the data quality. Because these are such huge data quality that it effects a major stylized fact about inequality: the U-curve. If today we believe that the U-curve---there's a debate over whether or not there's been such a large increase---everybody agrees that there's been an increase, but there's a massive debate over how big this increase is today. Imagine how crucial it would be to correctly debate the level of inequality and the trend of the left side of the U-curve. And if we're having all these debates with all the survey data, all the census data, all the private big data stuff that we have out there for the modern era and we still have high level of uncertainty, imagine anything with all the points I've mentioned for the interwar period, the left side of the U-curve. Everything seems to indicate that's probably much lower. I'm not saying there's not a U-curve, maybe it looks like a ball, a very modest ball, or there's a slight decrease, there's a slight increase, but it's not Piketty's U-curve, it's not the same stylized fact. And it changes the narrative we should have about inequality. Petersen: Yeah, I'll never forget one experience I had. It was the original Occupy movement and I went down to see the protests going on in Victoria B.C. where I was at the time and one guy just had a big sign where he had printed off a graph. You know, an inequality graph of the 1% versus the 99% from Piketty and Saez. I'm not sure if it went all the way back to the 1920s but really, that's sort of a very clear sign that these debates are expanding beyond academia and having a big effect on the public and their perception of the world we live in, the ideal policies that we should be pursuing. A big part of the U-curve narrative is to say look at how successful the policies in the 40s and 50s were at reducing inequality and of course if we do away with this U-curve then maybe those policies, all they did was bring more people into the data set. Geloso: Yes, and it changes who reports in the data set. I know Phil Magness, who is joining our team with me and John Moore and Bill Schlosser. Phil Magness has been working on showing that a lot of the changes in our tax regime actually just mimic the entire movement of the income share of the top 1%. It follows what share of taxes they're asked to pay and it leads to changes in reporting and basically it's a story of tax regimes and it changes the entire narrative. But what I find much more depressing---and this is a depressing fact---if just one of our criticisms lands and sticks, the U-curve doesn't look like a U. Let's say it looks like a J. So there's a mid-point in the 1920s and we've been increasing since then at a relatively high rate since the 1970s. So it fell from 1920 to 1970 and then it re-increased. If you look at what caused the leveling from 1920 to 1970, a lot of it has nothing to do with state intervention, with the efforts at redistribution. There's probably a sizable share of it that has to do with that. But there's also a sizable, and probably the larger share, that comes from poor regions catching up with rich regions. If you look at for example the history of inequality in the United States you would see that if you decompose the variance---so what caused the inequality---for most of American history a large share of inequality was caused by differences between states rather than differences between individuals. One way to see it, and I'm making a caricature here to get the point across, but you could have the same shape of distribution in income in Kansas and New York. But since the average in New York is much higher than in Kansas, you average the two in, you get a much higher level of inequality, so you can get like a Gini coefficient for the two of them of .4 but in each of them individually taken the level inequality is like .2. And this is what happens for most of US history. There are massive gaps between regions rather than gaps between skills, between levels, so Mississippi is poorer than New York for a long period of time. But in the 40s, 50s, 60s, 70s this gap basically volatilized, it began to disappear. One of the massive story of the twentieth century---some economists are aware---is this massiveness of convergence between regions. So the South gets richer. Poor black people move from poor states in the South where they're sharecroppers, they move to the North where they become wage earners in garment factories, in manufacturing and their earnings grow dramatically. So there's a massive convergence during that period. But, if you think about it for a second, it means that the gap between regions and the gap between races is actually a big driver in the leveling part of the U-curve, but that has nothing to do with tax redistribution. It has nothing to do with this. So, as soon as we integrate our criticism into the tax data, and we show that the U-curve looks less and less like a U, the left side of it makes it look less and less like a U. And you consider these two economic history facts that I've just mentioned, it's incredibly depressing to consider in the inequality narrative, to say well a lot of it is just stuff that would have happened anyways. There would have been a decline in inequality regardless of how much the state intervened to redistribute income because there was this convergence. And not only that, the leveling of inequality was not as great as we say it was. So it changes the entire story. We have inequality and how to address the issue and, not only that, I will point out that across the same period the one thing that goes up relatively steadily is government spending to GDP. If you were to account for all our criticism and then consider which part of inequality was reduced by government redistribution, it becomes more and more depressing because it seems like the effect is much smaller than people believe. This is where we're trying to disentangle all these elements to tell the correct story of inequality in the United States and it starts with getting the shape of inequality right. But look at the story I have just told you. As soon as we make this small change of properly assessing things, the entire narrative we have then changes. And this is why it's a dramatic fact to get right and which is why we're somewhat disappointed with Piketty's stuff because he's not making the right level of methodological discussion. Petersen: Right. Piketty uses his narrative to push for large-scale taxes and redistribution. Geloso: Yes. I'm not saying that what he does is bad. It was a massive improvement relative to what was there before. But his story has flaws, and these flaws tend to support his narrative. We point out the flaws that would support a different narrative, that point out that probably inequality is not as high as we say. It probably would have fallen up in the 1970s because of very natural forces and if you think about the fact that since the 1970s there's been a slight divergence---so, imagine the leveling of inequality between regions in the United States. The divergence fell until the 1970s, but it has increased modestly since then because of regulation on housing, things that limit mobility across states that the depress income growth in some areas. So you end up with a slight divergence since then and it is caused by states. It's not caused by anything that the government is doing. It's really an issue of very regionalized factors and each time you consider each of these nuances in, the narrative changes. And it changes dramatically against the story Piketty's telling and it shows that the flaws are biased in favor of the conclusion he supported. Petersen: Right. And I know Phil Magness has really criticized him on this, that he makes a lot of decisions where you could go one way or the other and they always seem to turn out his way. Which is maybe a coincidence, or maybe it's not really the best way to do social science. You point out that there were big price differentials between regions so how does that play into the regional inequality story? Geloso: So, we're basing our discussion on this part of a longer series of papers where each of the points we've discussed will basically be one paper in itself. Here we're just stating this entire case for skepticism, then we'll see how big the impact is. Regardless, even if they're all minor, they will all change the narrative. And prices, regional price differences are an issue in that. So, when you compare nominal income across a country you are getting an idea of inequality but---you will agree with me. So, you're in Vancouver. I'm originally from Montreal. If I give you a dollar income in Vancouver and I give myself a one-dollar income in Montreal you think that dollar will go as far in Vancouver as it does in Montreal? Petersen: I think it probably won't. Geloso: Exactly. So you would expect that regional price differences will affect the level of inequality. And there's actually a lot of people that do that. Each time you make controls for the level of price differences, you actually find that the level of inequality falls modestly. But it falls. But the thing is, the price differences that we have today between Vancouver to Montreal or between New York and the region of Mississippi are not at all what these gaps used to be in 1920 or in 1925. In 1925 the gaps would have been much, much, much larger and from 1925 to the 1940s there's been a convergence of prices across regions. So for the first 50 years, roughly, of the twentieth century you get a convergence of prices across regions. So if you just took nominal income without correcting for regional price differences, you would get a massive drop in inequality. However, if you were to correct for an increasingly smaller mistake because, if you think about it, if the wage gaps used to be on average 25% in 1890, let's say, and they used to be 5% in 1950, the error is decreasing over time. So you're getting the level off by a smaller and smaller quantity over time. So it means that the trend changes. The smaller your measurement error caused by regional price differences falls, the less pronounced the fall in inequality becomes. So you get a massive drop in inequality as measured by nominal income, which is not what it is when you correct the regional price differences, so you put this in real dollars adjusted for purchasing power parity. And not only that, the errors caused by regional prices actually also follow a U-curve. So the errors that would be caused by price level differences across regions declined up to 1950 but since then they've re-increased. So if before you're getting a lower and lower trend---a lower trend by a diminishing amount of error---that means the right side of the curve, that means the increasing disparity in prices across regions since 1950. It means that you're actually increasing nominal prices using nominal income across the country. You will underestimate the increase in inequality since then. So there are actually massive measurement errors caused by this issue of regional prices. When I say massive, I shouldn't say massive because it's dishonest but it affects both the level and the trends. So it affects the shape of the curve and remember we're making all these criticisms to the U-curve story piece by piece. Each one of them has a small prickly effect on the shape of the curve. As soon as one or more starts sticking---and they're all documented otherwise for other periods---not prior interwar period, not a sufficiently as we'd wish to, which is why we're doing this project of massive data collection. It changes the narrative, changes the story, changes the way the curve looks and it's not much of a U-curve anymore and the proper measurements get you a very different story of the evolution of inequality. And that different story forces you to change interpretations and solutions and the entire structure of the debate must change to reflect the higher level of precision that is required for that debate. Petersen: So. I'm trying to think of why these prices between regions might fall in the first half of the twentieth century and rise thereafter. I suppose a lot of it would be real estate, housing? Geloso: Exactly. So housing markets in the U.S. are more or less freer in the first half of the twentieth century than they are today. So most prices, if you can trade a good across borders it will arbitrage out price differences minus transport, right? So if goods are movable more or less as well, and you find it for food, for TVs, for durable goods, you tend to find that there's actually still convergence. But housing, you can't really move a house. There's actually movable houses but they're not a massive share of the market. So you'd expect less ability---and I'm saying this as a euphemism---but you'd expect less ability for arbitrage with housing. The only way you can do arbitrage for housing is by moving around. So I am in Mississippi and I see super high wages in New York. I move from Mississippi to New York. So in Mississippi there's one more housing unit available and in New York there's one less housing unit available. I've driven up housing prices in New York and I've got higher wages but housing is a little more expensive in New York and then it falls in the region where I left in terms of housing, so that real wages in that region converged. So there's a convergence in real wages by people moving around. The problem now is that, there is very, very, very little ability to move around in the United States because zoning restrictions actually make it harder for people to come and exploit the productivity of large cities like New York. So it prevents this convergence in real terms across regions. So a large part of the increase in inequality needs to be corrected for regional price differences, which is the argument about housing. And this is where it's probably that the soundest part of our argument is that the Rognlie papers that attack Piketty state that a large part of inequality was driven by rents towards housing, so the fact that income derives from housing is increasing importantly as a share of total income and has nothing to do with capital itself. It's really the artificial restrictions on housing. And this is largely the problem the inability of people to move to where wages are the most important. This changes the narrative. So that's why the story of regionally correcting price differences is crucial and it's rarely done over a long time series data set. But given the evolution of prices in the United States since 1900, it will affect the trend dramatically. It will affect the level, the shape, and this is not integrated in the argument. And this is why we're saying in this paper, each time you make a correction to get a higher level of precision, it's getting more and more plausible that the curve of inequality doesn't look like a U, it looks probably like an L, probably like a J, but not a U. So the early period of the twentieth century is not as high as people have claimed and there's probably been an increase since the 1970s. Not as much as some would claim, but the increase seems to have happened. The U-curve is probably just fictional. It is the result of poor controls or variations in equality of the taxes. Petersen: We've discussed the housing issue on other episodes of this podcast but it's sort of a one-two punch to inequality, where the people who, you know, maybe have bought a house in the San Francisco Bay area in the 1980s, have seen the value of that house skyrocket. And so of course that would contribute to the upper end of that wealth distribution. And the people who live in Mississippi and might like to move to the San Francisco Bay area and work for Google, can't afford to do it because of the extremely high price of rent there. So, that's reducing mobility and exacerbating these regional differences and also directly increasing the wealth of people who own homes who are, of course, already on the wealthier side. Geloso: Yes, in a static term, correcting for price differences across region. So if you were to take a picture of the economy right now and you make a picture of inequality based only on nominal incomes across the country---just using U.S. dollars---you'll get a higher level than if you correct for regional price differences. However, it's quite likely that if you were to make a movie of how inequality evolved, the housing restrictions---and this is a comment that's outside our paper and it's just something I think it's worth commenting on---if you make it so that it's impossible to move from low-income Mississippi to high-income California, you're going to make sure that inequality stays high and probably increases. If, let's say, there's a shock to international trade and Mississippi area tended to be manufacturing and people can't move from manufacturing to higher productivity jobs in San Francisco. So in dynamic terms, housing restrictions by preventing mobility prevent a strong equalizing source of income. So in static terms you get the level wrong, but in a dynamic term you're preventing the powerful force of mobility across the country---and this is something I like to point out---if you look for example, you bring someone from Italy to Canada in 1890, his income increased 300% as soon as he got to Canada. He was much richer the minute he set foot in Canada. You probably increased inequality in Canada---I don't know about if you decrease it or increase it in Italy---but when you move that guy away, you probably reduce global inequality. So by moving people to where the incomes are higher you level off inequality. In the United States it's the same narrative, you prevent this equalizing force from working through housing restrictions and making adjustments for---this is beyond the scope of our own research---but making adjustments for the increasing restrictiveness of housing that prevents mobility, you will probably get a large part of increasing inequality in the United States or even in England, which is also a situation like that, and in France, is not the result of terrible market forces responding to terrible government policies. Petersen: My guest today has been Vincent Geloso. Vincent thanks for being part of Economics Detective Radio. Geloso: It was a pleasure.  
What follows is an edited transcript of my conversation with Emily Hamilton about land use regulations' effects on affordable housing. Petersen: My guest today is Emily Hamilton. She is a researcher at the Mercatus Center at George Mason University. Emily, thanks for being on Economics Detective Radio. Hamilton: Thanks a lot for having me. Petersen: So, Emily recently wrote a paper titled "How Land Use Regulation Undermines Affordable Housing" along with her co-author Sanford Ikeda. The paper is a review of many studies looking at land use restrictions and it identifies four of the most common types of land use restrictions. Those are: minimum lots sizes, minimum parking requirements, inclusionary zoning, and urban growth boundaries. So Emily, could you tell us what each of those restrictions entail? Hamilton: Sure. So, starting off with the first, minimum lots sizes. This is probably what people most commonly associate with zoning. It's the type of Euclidian zoning that separates residential areas from businesses and then within residential areas limits the number of units that can be on any certain size of land. And this is the most common tool that makes up what is sometimes referred to as Snob Zoning, where residents lobby for larger minimum lots sizes and larger house sizes to ensure that their neighbors are people who can afford only that minimum size of housing. Petersen: So it keeps the poor away, effectively. Hamilton: Exactly. And then parking requirements are often used as a tool to ensure that street parking doesn't get too congested. So when cars first became common, parking was really crazy where people would just leave their car on the street, maybe double parked, or in an inconvenient situation near their destination. And obviously as driving became more and more common and that was just an untenable situation and there had to be some sort of order to where people were allowed to park. But street parking remained typically free or underpriced relative to demand. So, people began lobbying for a parking requirement that would require business owners and residential developers to provide parking that was off streets so that this underpriced street parking remained available. But that brought us to today where we often have just mass seas of parking in retail areas and residential areas, which are paper focuses on. Parking substantially contributes to the cost of housing, making it inaccessible in some neighborhoods for low income people and driving up the cost of housing for everyone who has been using the amount of parking that their developer was required to provide. Petersen: So that's one where you can really see the original justification. And it makes sense, if you have a business and a lot of people are parking and it spills over onto the street then maybe that's an externality. And it seems reasonable for you to have to provide parking for the people who come to your business, especially if a lot of them are driving there. But we push that too far, is what I'm hearing. Hamilton: Exactly. Yeah, it does seem reasonable but the argument in favor of parking requirements tends to ignore that business owners have every incentive to make it easy to get to their business. So, in many cases there's not necessarily an externality because the business owner providing the parking has the right incentive to provide enough to make it easy for their customers to get there. The externality really comes up when we think about street parking and Donald Shoup---probably the world's foremost expert on parking---has made the argument that pricing street parking according to demand is a real key in getting parking rules right. Petersen: So, on to the next one. What is inclusionary zoning? Hamilton: Inclusionary zoning is a rule that requires developers to make a certain number of units in a new development accessible to people at various income levels. Often inclusionary zoning is tied with density bonuses. So, a developer will have the choice to make a non-inclusionary project that is only allowed to have the regular amount of density that that lot is zoned for. Or, he can choose to take the inclusionary zoning density bonus which will allow him to build more units overall including the inclusionary unit and additional market-rate units. Typically, units are affordable to people who are making a certain percentage of the area median income, so people who might not have low income but who are making not enough to afford a market rate unit in their current neighborhood. Petersen: Okay, so that's sort of forcing developers to build affordable units that they then will probably lose money on, so that they can build the market rate units that they can make money on. Hamilton: Exactly. That's how cities make inclusionary zoning attractive to developers is by giving them that bonus that can allow them to build more market rate housing. In other cities, however, inclusionary zoning is required for all new developments so it really varies from jurisdiction to jurisdiction how it's implemented. Petersen: So the fourth land use restriction you mention is urban growth boundaries. What are those? Hamilton: So Oregon is the most famous example in the US of implementing an urban growth boundary. And what it is, is basically a state law that requires each city to set up a boundary around its edges, where for a certain amount of time no housing can be built outside of that boundary. And the idea is to gradually expand the city's footprint over time to allow the suburbs to expand a little further, but to restrict that suburban development using the boundary for some time period. Other examples like London's urban growth boundary I believe are permanent, so there are certain areas that can never be developed. Petersen: So I believe we have something like this in Vancouver. We have farmland in the metro Vancouver area which---for context this area is one of the most overheated high-priced housing markets in the world---and we have this land that's just zoned for farms. And a lot of the time people don't even bother to plant crops, they're just holding the land for the day when eventually it can be rezoned into housing. So I looked it up before we went on and some of these plots are $350,000 an acre, which of course is not reflective of just how productive they are as farmland but of how productive they would be when they are eventually rezoned. Hamilton: Exactly. Yes, very similar to Oregon's program. And a lot of empirical studies have been done on Portland's growth boundary because researchers can easily look at the block that are selling on either side of the boundary to see whether or not it's affecting land prices and several studies have found a very clear effect of the boundary in driving up the price of the land. Petersen: And in Vancouver, the city is very reluctant to rezone. So, people are constantly applying and being denied but you know it's like winning the lottery having your bit of useless farmland rezoned to super high value housing. And people are just holding on to those dead lands in the hopes of winning that lottery which is kind of---it's a bizarre outcome. Hamilton: It is. And urban growth boundary supporters often frame it as environmental regulation that's going to protect this open space. While encouraging people to live in more dense and transit and walkable friendly neighborhoods, but it's not as if Portland is free of other types of zoning rules. So at the same time it has this urban growth boundary it also has a lot of traditional zoning rules that limit the potential to build up while the growth boundary is limiting the potential to grow out. So it's coming from both directions. Petersen: So, just how costly do economists think these regulations are? What kind of estimates do they have? Hamilton: So, I think some of the most compelling estimates look at the macroeconomic effect of these rules. Because typically the most binding zoning rules are also in the most productive cities, where there's the highest level of demand for people to live. Because these are where the best jobs are as well as the best urban amenities, a lot of people want to live here. One study looking at this macroeconomic effect found that the three most productive cities which are New York, San Francisco, and San Jose---I should clarify; this is just looking at the effective growth within US---if those three cities lowered the burden of their land use regulation to that of the median American city it could result in a 9% increase in the level of US GDP. So, these rules are having just an enormous effect on economic growth. Not to mention the very substantial effect they have for individuals and making it difficult or impossible for people to afford to live in their desired location. Petersen: So, you know, San Francisco that's where Silicon Valley is. And so we think of it as a place with super high productivity---tech workers working at Google---and yet with their housing market being one of the most restricted. So not only is there the loss from the housing market itself, that you could sell a lot of housing there and that would increase GDP by itself, but also there are people living in less productive areas doing less productive jobs, who could come and work for Google. But they can't because they've been priced out of the market. Is that where most of the effect comes from? Hamilton: That's right. Yeah, I think the effect is also certainly at that top-end of the market where we're seeing all kinds of blog posts and articles about a person making six figures at Facebook who can't afford the Bay area. So those people might choose to go live in say Denver, or Austin, or a city that still has plenty of great jobs but isn't as productive as San Francisco or San Jose. But then we also see this down the income spectrum, where people who are in the service industry, say waiting tables, could make much more in San Francisco then they can in Houston, or wherever they happen to live. But their quality of life is much better in some of less productive cities because of the cost of housing and other areas of consumption that higher real estate costs drive up. Petersen: One thing I've heard about a lot of these Californian coastal cities---I think it was Palo Alto---where not a single member of the Palo Alto Police Department lives in Palo Alto because you just can't live there on a policeman's salary, so they all have to commute in every day and then commute out every night. Hamilton: Yeah, and for some of these hugely important needed services it just makes the quality of life of the people in those industries so much worse than it would be if they could afford to live closer to their job. Petersen: Right. So, to summarize the labor market mobility of the United States in general has been greatly restricted by these land use restrictions. Even though the land use restrictions are local, this has an effect on the national economy. Hamilton: Exactly right. And we can see this in the data where income convergence across areas of the country has greatly slowed down since the 1970's when these rules really started taking off. Petersen: You argue that the costs of these restrictions fall primarily on low-income households so can you talk through how that happens? Hamilton: Sure. It happens in two ways. First off, you have the low income people who are living in very expensive cities and these people might have to endure very long commutes---you talked about the police officer in Palo Alto who can't live anywhere near his job. Not that police officers are low income, but just as an example that illustrates the point. Or they have to live in very substandard housing, perhaps a group house that's just crammed with people maybe even illegally, in order to afford to live anywhere near where they're working. Petersen: Yeah, I was going to say I thought those group houses were illegal from these very same land use regulations, but I guess people get around it. Hamilton: Yeah, a lot of US cities have rules about the number of unrelated people who can live in a house. And certainly those rules are sometimes broken. That, I think, is clear to anyone who's spent time in an expensive city. You know, people have to live in these less than ideal conditions and waste too much of their time commuting in order to make that work. But the unseen version of it is the person who lives in a low-income part of the country and would like to improve their job opportunity and quality of life by moving to somewhere more productive, but they simply can't make it work so they stay in that low-income area without meeting their working potential. Petersen: There was a study by David Autor---I think I cited it in a previous episode and got the author name wrong but it's definitely David Autor---and it was looking at the shock, the trade shock that hit United States when it opened up trade with China in the early 2000's. And it basically showed that a lot of parts of the country just never recovered. So, if you worked in particular industries---I think the furniture industry was one that was basically wiped out---and if you worked in a town next to a furniture factory and that was your job, not only did you lose your job, you lost all the value in your home because the one industry in the town is gone. And you can't afford to move to one of the booming industries like Silicon Valley or in another part of the country because they've so greatly restricted the elasticity of their housing supply. And that's not all, Autor's paper basically just shows that it took a very long time to recover from the shock and a lot of places didn't recover at all. But I really think that housing is part of that picture if you're trying to figure out why the US economy can't respond to shocks like it used to in the 20th century. That has to be a big part of the picture. Hamilton: Definitely. And that trend, as far as people being able to leave these depressed or economically stagnant areas, this also comes out in the income's convergence as we talked about earlier. Petersen: So, the other part of that, I saw in your paper, was not only are poor people hurt but rich people who already own homes have seen those home prices rise. So it's affecting inequality at both ends of the spectrum, correct? Hamilton: Right, Bill Fischel at Dartmouth has done a lot of work on why it is that people lobby so hard in favor of rules that restrict development. And he terms it as the Homevoter Hypothesis, where people who own homes have a huge amount of their wealth tied up in their home and so they are in favor of rules that protect that asset and prevent any shocks such as a huge amount of new development that could result in a decline in their homes value. I think you talked about that in your episode with Nolan Gray on trailer parks. Petersen: Yeah, we talked about William Fischel's Homevoter Hypothesis. So the essence of that is that people vote in local elections, and they lobby to restrict the supply of housing in their neighborhood, and that increases their wealth by, you know, increasing the land values in that area. How do you deal with that when there's such an entrenched special interest everywhere to push up land prices? Hamilton: I think that's the hugely difficult problem. And at the same time as we have the challenges with the Homevoter system that Fischel plays out, we have a lot of federal policies that encourage homeownership as not just a good community-building tool but also as an investment. So people are programmed by the federal government to see their house as an investment in spite of economic challenges that it presents. David [Schleicher]---a law professor at Yale---has done some really interesting work on ways that institutional changes could limit the activity of homeowners and lobbying against new development. One of his proposals is called a Zoning Budget. And under a zoning budget, municipalities would have to allow a certain amount of population growth each year. So, they could designate areas of a city that are going to only be home to single family homes, but within some parts of the city, they would have to allow building growth to accommodate a growing population. Petersen: How would that be enforced, though? Hamilton: It would have to be a state law, or perhaps a federal law, but I think much more likely a state law that would mandate that localities do that. Massachusetts recently passed a law that requires all jurisdictions within the state to allow at least some multifamily housing. So it's kind of a similar idea. The state government can set a floor on how much local government can restrict development. Petersen: So, what I'm hearing is that different levels of government have different incentives with respect to restrictions. So, at the lowest level if I'm just in a small district or municipal area and I can restrict what my neighbors build on their property, that really affects my home price and that's the main thing that I'm going to lobby for at that level of government. But if I had to go all the way to the state government to try to push up house prices in my neighborhood, it wouldn't go so well. The state government has incentives to allow more people to live within their boundaries. Is that the gist of it? Hamilton: Yeah, that's right. It's easy to imagine a mayor of a fancy suburban community who simply represents his constituents' views that the community already has enough people, you know, life there is good and so nothing needs to change. But, I don't think that you'd find a Governor that would say "Our state doesn't need any more people or economic growth." So the incentives are less in favor of homeowners, local homeowners, the further up you go from the local to state jurisdiction. Petersen: Right. I guess a big issue is that the people who would like to move somewhere but live somewhere else don't get to vote in that place's elections or in their ballot measures. And so there's this group that has an interest in lower housing costs because they might move to your city or your town, if they could afford it, but they're not represented politically in that city or town and so they can't vote for more housing and lower prices. But then when you go to the whole state level and people are mobile within a state, those people do have a say or they are represented and pricing them out of the places they'd like to live really is bad for politics, bad for getting their votes. Hamilton: Right. So the Palo Alto police officer can't vote to change Palo Alto's policies but he can vote to change California policy. Petersen: Right, because he still lives within California. So one of the other policy recommendations I saw in your paper is tax increment local transfers or TILTs. What are they and how can they impact land use restrictions? Hamilton: That's another idea that comes from David Schleicher and I think it's another really interesting concept. The idea behind TILT is that a new development increases the property tax base within a jurisdiction. So, if you have a neighborhood, say a block full of single family homes that is allowed to be sold to a developer in order to build a couple of large apartment buildings, each apartment is going to be less expensive than the previous single family homes, but overall the apartment buildings will contribute more to property tax. And the idea behind a TILT is that part of this tax increment---which is the difference between the new tax base and the previous smaller tax base---could be shared with neighbors to the new development to kind of buy off their support for the development. So, those people who are in some sense harmed by the new buildings, whether in terms of more traffic or a change in their neighborhood's character, also benefit from the new building financially. So they're more likely to support it. Petersen: So economists talk about Potential Pareto Improvements, where you have a situation where some people are made better off while other people are worse off, but you could have a transfer to make everyone better off. And what I'm hearing with TILTs is you actually do that transfer, you actually pay off the losers with some of the surplus you get from the winners. So everyone can be better off when you make this overall beneficial change. Hamilton: Exactly. And sometimes communities do use community benefit as a tool to try to get developers to share their windfall and build a new project with the neighborhood. So they might say, "you can build an apartment building here, but you also have to build a swimming pool that the whole neighborhood can use at this other location," and in a way that achieves the end goal of buying off community support for new development. But it also drives up the cost of the new housing that the developer can provide. So TILTs have the advantage of keeping the cost of building the same for the developer, but still sharing that financial windfall of the new development with a broader group of people. Petersen: Yeah, I really like these policy recommendations. It would be so easy to just say "land use restrictions are bad, let's not have those anymore." But these really have an eye to the political structures that we currently have and towards making progress within the structure we have. So I like that approach to policy or to policy recommendations. I think economists should maybe do that more often. Hamilton: Yeah, looking for a win-win outcome. Petersen: The one other one that I don't think we've talked about is home equity insurance, which sounds like a business plan more than a policy proposal. But how can home equity insurance help to reduce the costs of land use restrictions? Hamilton: That proposal also came from Bill Fischel a couple of decades ago following on his work of the Homevoters theory. He proposed the idea that the reason home owners are so opposed to new development is often because they have so much of their financial wealth tied up in this house that they're not just opposed to a loss in their investment, but even more so, opposed to risk. So they want the policies that they see will limit the variance in their home equity and he proposed home equity insurance as a financial goal that could lower this threat and provide homeowners with a minimum amount of equity that they would have regardless to the new development. I think it's a really interesting concept but it's unclear, would this be a private financial product? Obviously the market isn't currently providing it, or would it be some kind of government policy? And while I do think it's very interesting, I think that we should be somewhat leery of new government policies that promote homeownership as a financial wealth building tool. Petersen: Well, the funny thing is that usually with insurance, if you have fire insurance you want to minimize the moral hazard of that, you don't want people to say: "Well I've got fire insurance so I don't have to worry about fires anymore." But with this, you sort of want that, you have insurance on the value of your home and then actually your goal is to make people less worried about the value of their home so that they will be okay with policies that reduce it. It's almost the opposite of what you want with insurance most of the time. In this case you want to maximize moral hazard. Hamilton: Yeah that's a great point and I think that's why it could only be a government product. Petersen: Right. Because if the private sector was providing home price insurance to homeowners then the company that provided the insurance would now have an incentive to lobby against upzoning the neighborhood. Hamilton: Exactly. Yeah it would create a new a new group of NIMBYs. Petersen: Yeah, at first I thought 'Oh great!', well this is something that we can just do, without the government. You can just get a bunch of people together, who have an interest in making cities more livable and they can provide this financial asset. But that seems like there are problems with it that are hard to overcome within the private sector. So overall do you think the tide might be turning on the NIMBYs? Are people becoming more aware of this issue and of land use restrictions and their effects on housing prices? Hamilton: I do think awareness is growing. There's a group popping up called YIMBY which stands for "Yes In My Backyard" as opposed to the suburban NIMBY to say "Not In My Backyard" to any sort of new development. And these YIMBY groups are gaining some traction in cities like San Francisco and lobbying in favor of new development to counter the voices that oppose new development. I am somewhat pessimistic, I have to say, just because from a public choice standpoint the forces in favor of land use regulations that limit housing are so powerful. But in spite of my pessimism, I'm seeing since the time that I started working on this issue several years ago, much more coverage of the issue from all kinds of media outlets, as well as much more interest in on-the-ground politics from people who aren't in the typical homeowner category. Petersen: Yeah, and I am hopeful too. But I often see people blame other factors for high home prices. They blame the speculators. The speculators are always the ones that are pushing up home prices. And rarely, I think, do people blame restrictions, although the YIMBY movement is a happy exception to that. Hamilton: Yeah, I think way too often real estate developers are framed as the enemy in these debates because they're the ones who make money off building new housing. But it's really the regulations that are to blame both for the inordinate profits that developers can make in expensive cities, and for the high costs of housing. Petersen: Do you have any closing thoughts about land use restrictions? Hamilton: I think that it's just really important to try to spread the message about the costs that these regulations have. Not just for low-income people but for the whole country and world economic growth. That's obviously a cause that I would think everyone would be behind: creating opportunity for people to live in the most productive cities where they can contribute the most to society and to the economy. Petersen: My guest today has been Emily Hamilton. Emily, thanks for being part of Economics Detective Radio. Hamilton: Thanks a lot for having me.  
In this episode, I have three guests on the show with me: Kewei Hou of Ohio State University, Chen Xue of the University of Cincinnati, and Lu Zhang of Ohio State University. Kewei, Chen, and Lu have coauthored a paper titled "Replicating Anomalies," a large-scale replication study that re-tests hundreds of so-called "anomalies" in financial markets. An anomaly is a predictable pattern in stock returns, or stated differently, it is a deviation from the efficient markets hypothesis. Their abstract reads as follows: The anomalies literature is infested with widespread p-hacking. We replicate the entire anomalies literature in finance and accounting by compiling a largest-to-date data library that contains 447 anomaly variables. With microcaps alleviated via New York Stock Exchange breakpoints and value-weighted returns, 286 anomalies (64%) including 95 out of 102 liquidity variables (93%) are insignificant at the conventional 5% level. Imposing the cutoff t-value of three raises the number of insignificance to 380 (85%). Even for the 161 significant anomalies, their magnitudes are often much lower than originally reported. Out of the 161, the q-factor model leaves 115 alphas insignificant (150 with t < 3). In all, capital markets are more efficient than previously recognized. We discuss the process of replicating these anomalies, issues involving the use of equal-weighted vs value-weighted returns, and the problems of p-hacking in finance research. Works Cited Hamermesh, Daniel S. 2007. “Replication in Economics.” Canadian Journal of Economics 40(3):715–733. Kewei Hou, Chen Xue, Lu Zhang; Digesting Anomalies: An Investment Approach. Rev Financ Stud 2015; 28 (3): 650-705. Hou, Kewei and Xue, Chen and Zhang, Lu, Replicating Anomalies (June 12, 2017). Charles A. Dice Center Working Paper No. 2017-10; Fisher College of Business Working Paper No. 2017-03-010. Other Links The Marginal Revolution post on this paper.  
My guest on this episode is Kevin B. Grier of the University of Oklahoma. Our topic for today is a paper Kevin wrote on the economic consequences of Hugo Chavez along with coauthor Norman Maynard. I had Francisco Toro on the show last year to discuss Venezuela's economic history, so you can listen to that episode if you want a refresher on Chavez. For this episode, our main topic is the empirical method Kevin used to quantify Chavez' effect on Venezuela: synthetic control. Synthetic control is a relatively new empirical technique. It grew out of an older technique called difference in differences (or diff-in-diff). Diff-in-diff is simple and intuitive: Given two statistics with parallel trends, we can compare their changes before and after some intervention affecting only one of them to see the effect of the intervention. So for instance, if you wanted to know the effect of Seattle's minimum wage increase, you could compare the employment trend among low-skilled workers in Seattle to the same trend in Portland. Then assuming Seattle and Portland would have had similar trends if not for the minimum wage hike, we say the difference between the employment growth in the two cities is attributable to the minimum wage hike. But what if Seattle and Portland don't have similar trends? What if there's no labour market similar enough to Seattle's to provide a valid comparison? That's where synthetic control comes in. Seattle might not be like Portland, but it might be like a weighted average of Portland, San Francisco, and several counties just outside Seattle. We could construct this weighted average and call it a synthetic Seattle; it is designed to mimic the dynamics of Seattle's labour market before the minimum wage hike. Then if the synthetic Seattle deviates from the real Seattle after the wage hike, we can attribute that difference to the hike. This is what Kevin has done to study the impact of Hugo Chavez on Venezuela. Listen to the episode to find out his results!
My guest for this episode is Mark Koyama of George Mason University. Our topic is a recent paper titled, "States and Economic Growth: Capacity and Constraints," which Mark coauthored with Noel Johnson. Just recorded at great podcast with @GarrettPetersen on my work on state capacity (with @ndjohnson). — Mark Koyama (@MarkKoyama) May 24, 2017 As stated in the paper, "state capacity describes the ability of a state to collect taxes, enforce law and order, and provide public goods." That said, state capacity does not mean big government. A state may have the power to impose rules across its territory, but it doesn't have to use that power in a tyrannical way. Another way of saying that is to say that having a high state capacity is compatible with Adam Smith's desire for "peace, easy taxes, and a tolerable administration of justice." One metric that researchers use to measure state capacity is tax revenue per capita. But as Mark is careful to point out, a state with less state capacity can still sometimes achieve a relatively high income through tax farming. This is the practice in many pre-modern states of auctioning off the right to extract tax revenues to local elites in different regions. We discuss the rise of modern nation-states in various regions, and why some states developed more state capacity than others going into the twentieth century. In particular, we discuss Europe's transition away from a feudal system ruled in a decentralized way by monarchs who held power based on their personal relationships with local lords. England's Glorious Revolution of 1688 allowed it to develop its state capacity earlier than other European nations, with a centralized tax system controlled by parliament. By contrast, continental powers like the French Ancien Régime and the Hapsburg Empire were legally and fiscally fragmented, leading them to develop their state capacity much later than England. We also discuss the development of state capacity in Asia, and why Meiji Japan was able to develop its state capacity much faster than Qing Dynasty China.  
Returning to the podcast is Vincent Geloso of Texas Tech University. Our topic for this episode is anthropometric history, the study of history by means of measuring humans. Doing serious historical research into the distant past is difficult work, because the further you look back in time, the less information you can access. For the 20th century we have wonderful thing like chain-weighted real GDP. Going back further, we have some statistics, lots of surviving physical evidence, and loads of documents and writings. Going further than that, we're left with the odd scrap of thrice-copied surviving manuscripts and second-hand accounts from people who lived centuries after the events they describe. And going even further than that, we have just bones and dilapidated temples with the occasional inscription. Anthropometric history allows us to look into the distant past at what economic historians like Vincent hope might be a good measure of different populations' health and standards of living: their heights. People who have healthy upbringings with lots of access to food tend to be taller than people who don't; that's why modern humans are much taller than they were a thousand or even a hundred years ago. Vincent has contributed to this literature with his latest co-authored paper, The Heights of French-Canadian Convicts, 1780s to 1820s. The abstract reads as follows: This paper uses a novel dataset of heights collected from the records of the Quebec City prison between 1813 and 1847 to survey the French-Canadian population of Quebec—which was then known either as Lower Canada or Canada East. Using a birth-cohort approach with 10 year birth cohorts from the 1780s to the 1820s, we find that French-Canadian prisoners grew shorter over the period. Through the whole sample period, they were short compared to Americans. However, French-Canadians were taller either than their cousins in France or the inhabitants of Latin America (except Argentinians). In addition to extending anthropometric data in Canada to the 1780s, we are able to extend comparisons between the Old and New Worlds as well as comparisons between North America and Latin America. We highlight the key structural economic changes and shocks and discuss their possible impact on the anthropometric data. Listen to the full episode for our fascinating discussion of this branch of historical research, including the so-called "Antebellum puzzle," the anomalous observation that American heights decreased in the years prior to the Civil War even though the economy was apparently growing rapidly. We also discuss the heights of slaves in the American South, who were taller than their white counterparts despite being oppressed as slaves.  
This episode features Anton Howes of Brown University. He is a historian of innovation, and in this conversation we discuss his work on the explosion of innovation that occurred in Britain between 1551 and 1851. You can check out his Medium blog for some of the articles we discuss. Anton has collected a data set of over 1,000 British innovators who worked during this period. He has documented their education, their experience, and their relationships with one another. Some of the interesting patterns that emerge in his data are the large fraction of innovators who developed technologies in industries outside of their areas of expertise, as well as the high degree of interconnectedness between innovators. Innovation, it seems, is a mindset; one that can be spread from person to person like a contagion. As far as Anton can tell, this mindset seems to have spread from Italy and the Low Countries during the Renaissance and taken hold in Britain to usher in its Industrial Revolution. With his view of innovation as a mindset, Anton's work complement's Deirdre McCloskey's work on the origins of modern economic growth. Our conversation concludes with stories about some particularly interesting innovators, some of whom were also pirates!  
Today's guest is Stephen Smith, he is an analyst for a New York real estate firm. Stephen did some research showing that at least 40 percent of the buildings in Manhattan could not be built under today's zoning regulations. In fact, the number is probably significantly higher. Classic landmarks like the Empire State Building, with its floor-area ratio of 30, wouldn't fly today. Watch this time-lapse of the New York City skyline, and pay close attention to the kind of changes that happen in the earlier part of the video compared to the later part: Before the twentieth century, the pace of change is very gradual. Two storey buildings are replaced with three storey buildings. Waves of development sweep through the city, replacing wood buildings with brick and stone and concrete. In the twentieth century, we see a different kind of development. Pay attention to any particular small building and you'll notice one of two things happening: Either the building stays exactly as it is, or it is replaced by a massive skyscraper. There's no more gradual change. This is caused by the city's adoption of land-use regulations. The first zoning code was adopted in 1916, but the really strict zoning came in 1961. Once this happened, tearing down and replacing a building meant pulling political strings to get it rezoned. Because of the significant fixed cost of getting a lot rezoned, developers opted to build a few extremely tall buildings rather than many moderately tall ones. Heavy restrictions in most of Manhattan led developers to concentrate development in the few places that would allow it. That's why Midtown built up while other neighbourhoods didn't. New York's mayors tend to be pro-development, but its city councillors block development at every turn. The city council's behaviour is consistent with William Fischel's home voter hypothesis. The city council tends to defer to individual councillors on their own local issues, giving each councillor de-facto control over development in his neighbourhood. When authority is devolved to the hyper-local level, there's a strong incentive to block development to raise real estate prices.  
Today's guest on Economics Detective Radio is Chuck Marohn, founder and president of Strong Towns. Strong Towns is a non-profit that seeks to reform America from the ground up, starting with its towns and cities. It aims to promote healthy local economies by improving local governance. The Growth Ponzi Scheme Chuck began recognizing the problems in America's towns and cities when he was working as a civil engineer. He recounts a story of working in a little city in central Minnesota in the late 1990s. The city had a 300-foot pipe that had cracked, allowing ground water to leak in and overflow their treatment facility. Chuck proposed a $300,000 solution to fix the pipe. However, this was a tiny town with an annual budget of $85,000. So Chuck went to higher levels of government (the federal government, the USDA, etc.) to find someone to fund the project. They all said, "This feels like maintenance. We don't have money for maintenance, so you need to pay for this yourself." Since the feds would only fund expansion projects, Chuck devised a plan: He would propose the largest expansion project he could, then repair the pipe as part of the expansion. This wasn't so much deviousness on his part as it was standard practice in his profession. He designed a couple miles of new pipe, doubled their treatment facility, and as part of that he included repairs for the old pipe. This new project cost $2.6 million. Everyone was happy about this project. The grant agencies were happy. The legislators issued glowing press releases and held a big ribbon cutting. Chuck got a big bonus from his company. The city was ecstatic. The only lingering problem was that this tiny city that couldn't afford to maintain 300 feet of pipe would now be left with a few miles more pipe and a larger treatment facility. This is an example of one part of what Chuck calls the Growth Ponzi Scheme. This is when cities and towns expand in ways they can't maintain without further expansion. There's a political reason why things like this happen. Building new infrastructure is very politically appealing. You can build a new highway and name it after a prominent politician, you can have a big ribbon-cutting ceremony, and you can get all sorts of good press for the project. Maintenance is less sexy; you close down a lane of some existing highway, delay everyone's commute, and then you don't have a ribbon-cutting or positive press for all the potholes you filled in. That's why higher levels of government have been paying for big projects and passing off the responsibility for maintaining them to local governments. These local governments become insolvent when the revenue from the initial big project runs out and the maintenance expenses come due. This process leads to a form of development where the local tax base is not sufficient to pay for the infrastructure that supports it. When the expansion can't go on any longer, the infrastructure crumbles, the affluent people leave, and the community ends up locked in poverty. What's Wrong with Big Box Stores? Embracing this form of unsustainable growth has made our cities less dense and walkable. Instead we have heavily subsidized driving as a means of getting everywhere. One consequence of this has been the rise of big box stores. The public debate on big box stores tends to miss the mark. The left says big box stores crowd out local businesses, which is true. The right says they pass the market test, offering lower prices and thus improving poor people's standard of living, which is also true. What both miss is that these big box stores only pass the market test because they don't bear the costs of the infrastructure needed to support them. By subsidizing infrastructure, and by building our cities to be spread out and unwalkable, we make bringing groceries to the people unviable. Instead, the people drive to where groceries are. In addition to the rise of big box stores, we've seen the demise of small town living. While small towns still exist, they used to have enough small businesses, shops, and grocers to allow a full and comfortable life without leaving the town. Today, small town life consists of driving to the regional hub, perhaps multiple times every week, to get many of your necessities. What's Wrong with Hastings Street? Chuck coined the term "STROAD" to push back against the interchangeable use of the terms "street" and "road." A street is where value lives. Homes and businesses locate themselves along streets so that they can be connected to rest of the transportation network, but the street itself features narrow lanes, low speed limits, and good sidewalks because it's designed more for pedestrians and less for vehicles. Roads, by contrast, are not meant to be valuable locations in themselves; they are optimized for transporting large volumes of traffic over long distances. They feature wider lanes and faster speed limits. STROADs are an unhappy blend of both elements. Wide lanes and low speeds make them bad for both pedestrians and drivers. One example of a STROAD is Hastings Street in Vancouver, which tries to be a major thoroughfare for thousands of commuters during rush hour, while still catering to the many businesses along its ten-kilometer span. Because of its high volume of traffic and many stop lights, motorists can expect to average just twenty kilometers an hour on their commutes to downtown Vancouver. Gentrification as Part of an Organic System Chuck wrote an article titled "The Gentrification Paradox," in which he argues that gentrification was actually a healthy part of urban development in the pre-automobile age: The pre-automobile development pattern was an organic process. It was both incremental and complex... Gentrification – investment followed by displacement – was part of the natural order of things and, as with any organic system, it had a positive role in making things work for everyone. Before the twentieth century, cities would gradually grow and change over time. But we've used zoning laws to turn our neighbourhoods into unchanging time capsules. Cities used to be antifragile, to borrow a term from Nassim Taleb. In the past, poorer people would buy property on the outskirts of town, on which they would live and run small businesses. Over time, as the city grew, these outskirts would gradually come to be incorporated into the urban ecosystem. These properties would become more valuable and they would grow with the community, perhaps adding a second storey and expanding the business. You couldn't do this today. Building codes and zoning laws make any new development into a million-dollar endeavor. People with very little capital can't start with a small property and gradually increase its value over time. This makes the modern form of urban development much less equitable than it was in the past.
Phil Magness returns to the show to discuss his work on slavery and capitalism, particularly as it relates to the New History of Capitalism (NHC) and the New York Times' 1619 project. Phil recently wrote an article entitled, "How the 1619 Project Rehabilitates the 'King Cotton' Thesis." In it, he argues that the NHC has unwittingly adopted the same untenable economic arguments made by slaveowners in the antebellum South: that slave-picked cotton was "king" in the sense of being absolutely indispensable for the global economy during the industrial revolution. [T]he economic reasoning behind King Cotton has undergone a surprising — perhaps unwitting — rehabilitation through a modern genre of scholarly works known as the new history of capitalism (NHC). While NHC historians reject the pro-slavery thrust of Wigfall and Hammond’s bluster, they recast slave-produced cotton as "not just as an integral part of American capitalism, but . . . its very essence," to quote Harvard’s Sven Beckert. Cornell historian Ed Baptist goes even further, describing slavery as the indispensable causal driver behind America’s wealth today. Cotton production, he contends, was "absolutely necessary" for the Western world to break the "10,000-year Malthusian cycle of agriculture." And this same NHC literature provides the scholarly foundation of the ballyhooed New York Times' 1619 Project — specifically, its foray into the economics of slavery. Guided by this rehabilitated version of King Cotton, Princeton sociologist Matthew Desmond enlists the horrors of the plantation system to launch a blistering attack on modern American capitalism. Desmond projects slavery's legacy onto a litany of tropes about rising inequality, the decline of labor-union power, environmental destruction, and the 2008 financial crisis. The intended message is clear: Modern capitalism carries with it the stain of slavery, and its putative excesses are proof of its continued brutality. It follows that only by abandoning the free market and embracing political redistribution will we ever atone for this tainted inheritance.
Today's guest is Thibault Schrepel of the University of Utrecht. We discuss his work on the relationship between blockchain technology, which allows for the decentralization of firms and organizations, and anti-trust law. Here's a quote from his article on the topic: But in the end, one question arises as follows: is blockchain the death of antitrust law? Should it be? Answering them today is not easy as blockchain is still prone to drastic evolution, but some initial answers are to be provided nonetheless. In order to do so, this paper proceeds in three parts. The first details how unilateral practices can be implemented on blockchain and further establish a risk map. The second part focuses on the challenges for enforcers and presents a new theory entitled “regulatory infiltration." The last part questions the legitimacy of competition law in the face of this technology - the "blockchain antitrust paradox" - and the need to decentralize competition authorities.  
Fabio Rojas returns to the podcast to discuss his work researching social media. He has three main papers on the subject. The first is "More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior," which shows how Twitter activity predicted the outcomes of the 2010 and 2012 US congressional elections. The second is "The social media response to Black Lives Matter: how Twitter users interact with Black Lives Matter through hashtag use" which tracks the spread of the #BlackLivesMatter movement through social media. The third is "Twitter’s Glass Ceiling: The Effect of Perceived Gender on Online Visibility" which shows how Twitter users treat each other differently based on how they perceive each other's gender. We discuss these three papers and more on this episode of Economics Detective Radio.  
Today's guest is Jeffrey Rogers Hummel of San Jose State University. He is the author of Emancipating Slaves, Enslaving Free Men: A History of the American Civil War. This book combines a sweeping narrative of the Civil War with a bold new look at the war’s significance for American society. Professor Hummel sees the Civil War as America’s turning point: simultaneously the culmination and repudiation of the American revolution. Links: The Curious Task from the Institute for Liberal Studies; mentioned in the outro.
Today's guest is Martin Gurri (Twitter, blog), author of The Revolt of the Public. We discuss his book, which deals with the impact of information technology on political trends and populism. In the words of economist and scholar Arnold Kling, “Martin Gurri saw it coming.” Technology has categorically reversed the information balance of power between the public and the elites who manage the great hierarchical institutions of the industrial age—government, political parties, the media. The Revolt of the Public tells the story of how insurgencies, enabled by digital devices and a vast information sphere, have mobilized millions of ordinary people around the world. Originally published in 2014, this updated edition of The Revolt of the Public includes an extensive analysis of Donald Trump’s improbable rise to the presidency and the electoral triumphs of “Brexit” and concludes with a speculative look forward, pondering whether the current elite class can bring about a reformation of the democratic process, and whether new organizing principles, adapted to a digital world, can arise out of the present political turbulence.  
Today's guest is Jonathan Meer of Texas A&M. We discuss his work on the minimum wage. The voluminous literature on minimum wages offers little consensus on the extent to which a wage floor impacts employment. For both theoretical and econometric reasons, we argue that the effect of the minimum wage should be more apparent in new employment growth than in employment levels. In addition, we conduct a simulation showing that the common practice of including state-specific time trends will attenuate the measured effects of the minimum wage on employment if the true effect is in fact on the rate of job growth. Using three separate state panels of administrative employment data, we find that the minimum wage reduces net job growth, primarily through its effect on job creation by expanding establishments. These effects are most pronounced for younger workers and in industries with a higher proportion of low-wage workers.  
Today I discuss one of my own papers: "Instructions" by Freeman, Kimbrough, Petersen, and Tong. This research project on experimental instructions has been ongoing for years, but it was recently conditionally accepted for publication. I tell the story of how the research came together and detail some of the results. A survey of instruction delivery and reinforcement methods in recent laboratory experiments reveals a wide and inconsistently-reported variety of practices and limited research evaluating their effectiveness. Thus we experimentally compare how methods of delivering and reinforcing experiment instructions impact subjects' understanding and retention. We report a one-shot individual decision task in which mistakes can be unambiguously identified in behavior and find that mistakes are prevalent in our base-line treatment which uses plain, but relatively standard experimental instructions. We find combinations of reinforcement methods that can eliminate half of subjects' mistakes, and we find that we can induce a similar reduction in mistakes via enhancements to the content of instructions. Residual mistakes suggests this may be an important source of noise in experimental studies.  
Rate Podcast
Get episode alerts
Subscribe to receive notifications by email whenever this podcast releases new episodes.

Subscribe to receive notifications by email whenever this podcast releases new episodes.

Recommend This Podcast

Recommendation sent

Followers

1

Join Podchaser to...

  • Rate podcasts and episodes
  • Follow podcasts and creators
  • Create podcast and episode lists
  • & much more

Podcast Details

Started
Aug 15th, 2014
Latest Episode
Mar 23rd, 2020
Release Period
Weekly
No. of Episodes
141
Avg. Episode Length
About 1 hour
Explicit
No

Podcast Tags

Do you host or manage this podcast?
Claim and edit this page to your liking.
Are we missing an episode or update?
Use this to check the RSS feed immediately.