[This is for /u/Cutlasss. Sorry for the delay.]

Question: Is prostitution illegalization bad economics?

A year or so ago I wrote my BA thesis on a niche topic within the already niche topic of the economics of prostitution. It was mostly an exercise in applying a sophisticated new method of regression analysis to a novel data set that I had stumbled upon, which just so happened to be data on prostitutes. However, my studies made me a bit familiar with the general literature surrounding the econ of prostitution: Theories of price setting, general equilibrium in sex, dating, and marriage markets, the externalities associated with illicit sexual activity, and much more. Here, I will briefly cover the salient features of this body of literature in order to comment on the question of whether or not prostitution should be made legal in the United States. I won't come up with a definitive answer, but I will cover the points one must keep in mind when discussing this question.

First I will highlight the costs and benefits of prostitution: Costs to the individual, costs to society, and benefits to the individual and society. Then I will cover the demand side of sex markets, the “johns”, and what little study has been done on them, even though some would argue that we should be cracking down on johns, not prostitutes, if we want to police sex markets.

Individual Costs

On the supply side, women choose to enter prostitution for a variety of reasons. On one hand, it is generally a low-skill profession with few restrictions to entry and the potential for high earnings. On the other hand, there are significant explicit and implicit costs associated with prostituting, including the risk and consequences of arrest (where prostitution is illegal), violence and exploitation from customers and managers, risk of contracting STDs (Potterat et al, 2003), low to almost non-existent options for advancement within the profession (Lim, 1998), and foregone marriage opportunities due to the stigma attached to the sex market (Edlund and Korn, 2002; Edlund et al, 2009).

Individual Benefits

The widespread persistence of prostitution around the world, however, implies that earnings or earnings potential compensate for or exceed the costs for those who prostitute. Evidence suggests that women with fewer prospects in the formal economy are selected into prostitution, likely due to the low opportunity costs (Lim, 1998; Edlund and Korn, 2002; Levitt and Venkatesh, 2007). Males, particularly those solicited by homosexual clients, enter the profession for similar reasons, at least those who are young or immigrants, although many are employed in the formal economy as well (Cameron et al, 1999). High-end escorts also experience flexible hours (Benson and Matthews, 1995; Cameron et al, 1999) and significantly higher wages than other prostitutes (Edlund et al, 2009). For both genders there is a significant premium associated with working in the sex sector (the proposed reasons for this premium are explored later) (Edlund and Korn, 2002; Cameron et al, 1999).

There is also an urban premium. Moffat and Peters (2004) utilize a unique dataset gathered from punternet.com to regress individual prices onto several variables such as appearance, duration, and location using an hedonic pricing model and find that prostitutes in London earn significantly more than those in other parts of the UK. (Check out that paper if you want to see which physical/etc. features correlate with higher or lower prices of male prostitutes in the UK.)

Societal Costs and Surprising Benefits

First, there’s the obvious and often-argued link between prostitution and drug markets. See the end of this section for that.

There is still much to be said about the relationship between prostitution and the environment. For instance, common intuition tells us that adult businesses, especially illicit ones, will lower property values, but survey data and spatial regression analysis shows that this may not always be the case. Hubbard et al. (2013) find that those living in close proximity to a commercial sex establishment in New South Wales, Australia report “few negative impacts on local amenity or quality of life, with distance from a premise being a poor predictor of residents’ experiences of nuisance” (p. 1). Bastiaens (2007) applies a classic monocentric city model to land values in New York City from 1867-1876 and finds that the working-class, immigrant enclaves of Bleecker and Washington Square were disamenities while the Tenderloin, also a middle-class shopping center by day, was an amenity. From these studies, the purported negative externalities associated with the development of historical and modern urban sex markets are, at best, ambiguous, although there is much work to be done on this topic.

As many might be aware, prostitution is actually legal in all counties of Nevada other than Las Vegas. Prostitutes in Nevada may work in heavily-regulated brothels and are required to have frequent medical exams. I believe they are also given security and legal protections just like any other laborer in the state. My memory is fuzzy on this topic, but the book to consult on this issue is a very comprehensive and theoretical study, The Economics of Prostitution by Helen Reynolds (1986). Link. More recent work on prostitution in Nevada can be found via Google. Surprisingly, I’ve found few economic studies on the topic in EconLit.

Prostitution is also legal in the Netherlands, but again, I don’t have many studies on that area, ironically enough. Several developing countries also tolerate prostitution (see below).

Finally, the issues of human trafficking and child prostitution deserve brief mention, as the operation of these markets are often directly related to the operation of the market for adult commercial sex and sex tourism. Trafficking refers to the coercion of people into joining the sex sector. Some scholars have shown legalized prostitution to be related to higher rates of trafficking (Cho et al., 2013; Jakobsson and Kotsadam, 2013), although others contend this finding (Lee and Persson, 2012). Economists are less likely to study child prostitution (see Lim 1998 for a policy-centric overview), and there is room for study of this practice which may be promoted by the existence of adult prostitution.

Both of these practices may be seen as externalities of the commercial sex market in addition to linkages to crime and drug use (Logan and Leukefeld, 1999; May et al., 1999) and the spread of disease (Rao et al., 2009).

Demand

There has been relatively little research on the demand side of illicit sex markets. Evidence both quantitative and qualitative is lacking, likely due to the fact that johns are paying for secrecy, among other things, when they employ the services of sex workers. As such, willing participants for case studies and surveys must be harder to come by than sex workers who may see a potential benefit in publicizing the details of their trade.

There are two particularly noteworthy studies that have contributed significantly to the field by studying the demand side of commercial sex. Cameron and Collins (2003) use a unique national survey of sexual behavior in the UK to estimate a model for the choice by heterosexual males to consume commercial sex at the margin. They find that risk of disease has a significant deterrent effect, while engaging in other risky behaviors (such as smoking) and belonging to a sexually restrictive religion have a significantly positive effect on the likelihood one has paid for sex in this sample. Roberts, Jr. and Brewer (2006) use a capture-recapture method based on records of arrest of male clients in Vancouver to estimate the size of the male clientele in the commercial sex market and also find evidence of severe underreporting of encounters with prostitutes by men.

Conclusion

Okay, so I’ve given you a big stream-of-consciousness wall of text on prostitution without commenting on laws or legality issues. I also haven’t covered the feminist debates surrounding prostitution, both for the sake of brevity and the fact that that is beyond the scope of my work and this post. A good article on the feminist debates surrounding prostitution is Kissil and Davey (2010), here. Key issue: “While feminist scholars agree that inequality within patriarchal hierarchy is the core problem in prostitution, they have been polarized about whether classist or sexist inequality is the primary issue and consequently, on viewing the prostitute as either a coerced victim or an entrepreneur.”

Anyway, I suppose some of the standard arguments for drug legalization could and would be made for prostitution legalization: Legality would bring labor protections and bankrupt the abusive pimps and johns, the public health issues could be addressed, personal freedom would be facilitated (assuming prostitutes are merely entrepreneurs and not coerced), etc. The economic literature applies the same basic rational choice and pricing models to sex markets, and they find that the risk and individual costs of prostitution are compensated by the price premium. Often, this is a welcome alternative to the formal labor market given an individual’s skill set.

As we’ve seen, there are a few negative and a few possible positive externalities associated with prostitution, most of which can probably be internalized except for the possible link between legal or tolerated prostitution and human trafficking. If the link exists (which some studies contest), then I can only see the solution being a devotion of our excess policing resources to preventing human trafficking after we legalize.

General Interest Book

I recommend Economics Uncut for its chapters on prostitution.

References

Bastiaens, I. (2007). Is Selling Sex Good Business? : Prostitution in Nineteenth Century New York City. Undergraduate Economic Review, 3(1). http://digitalcommons.iwu.edu/uer/vol3/iss1/8.

Benson, C. and R. Matthews (1995) ‘Street Prostitution: Ten Facts in Search of a Policy,’ International Journal of the Sociology of Law 23: 395–415.

Bowmaker, Simon. Economics Uncut

Cameron, S., & Collins, A. (2003). Estimates of a model of male participation in the market for female heterosexual prostitution services. European Journal of Law and Economics, 16(3), 271-288.

Cameron, S., Collins, A., & Neill, T. (1999). Prostitution services: An exploratory empirical analysis. Applied Economics, 31(12), 1523-1529.

Cho, S., Dreher, A., & Neumayer, E. (2013). Does legalized prostitution increase human trafficking? World Development, 41(1), 67-82.

Edlund, L., & Korn, E. (2002). A theory of prostitution. Journal of Political Economy, 110(1), 181-214.

Edlund, L., Engelberg, J., & Parsons, C. A. (2009). The wages of sin. Unpublished manuscript. http://www.econ.columbia.edu/RePEc/pdf/DP0809-16.pdf.

Hubbard, P., Boydell, S., Crofts, P., Prior, J., & Searle, G. (2013). Noxious neighbours? interrogating the impacts of sex premises in residential areas. Environment and Planning A, 45(1), 126-141.

Jakobsson, N.., & Kotsadam, A. (2013). The law and economics of international sex slavery: Prostitution laws and trafficking for sexual exploitation. European Journal of Law and Economics, 35(1), 87-107.

Kissil and Davey (2010), here.

Lee, S., & Persson, P. (2012). Human trafficking and regulating prostitution. Unpublished manuscript. Levitt, Steven & Sudhir Venkatesh. (2007). An Empirical Analysis of Street-Level Prostitution. Unpublished. http://economics.uchicago.edu/pdf/Prostitution%205.pdf

Lim, L. L., ed. (1998). The sex sector: The economic and social bases of prostitution in southeast asia. Geneva:; International Labour Office; distributed by ILO Publications Center, Waldorf, Md.

Logan, T., & Leukefeld, C. (1999). HIV risk behavior and drug use among heterosexual male crack users by prostitution involvement. Population Research and Policy Review, 18(1-2), 23-38.

May-Tiggey, Edmunds-Mark, & Hough-Michael. (1999). Street business: The links between sex & drug markets. London: Research, Development and Statistics Directorate

Moffatt, P. G., & Peters, S. A. (2004). Pricing personal services: An empirical study of earnings in the UK prostitution industry. Scottish Journal of Political Economy, 51(5), 675-690.

Potterat, J. J., Muth, S. O., Woodhouse, D. E., Muth, J. B., Stites, H. K., Brewer, D.D., Brody, S. (2004). Mortality in a long-term open cohort of prostitute women. American Journal of Epidemiology, 159(8), 778-785.

Rao, V., Gupta, I., Lokshin, M., & Jana, S. (2003). Sex workers and the cost of safe sex: The compensating differential for condom use among calcutta prostitutes. Journal of Development Economics, 71(2), 585.

Reynolds, Helen. (1986). The Economics of Prostitution.

Roberts, J., John M., & Brewer, D. D. (2006). Estimating the prevalence of male clients of prostitute women in vancouver with a simple capture-recapture method. Journal of the Royal Statistical Society: Series A (Statistics in Society), 169(4), 745-756.

I'm much more of a macroeconomist so here's mine:

Unravelling the New Classical Counter Revolution by Simon Wren-Lewis and How the Case for Austerity Has Crumbled by Paul Krugman.

Edit: I've nearly finished my master in development economics, and now spend most of my time reading philosophy and history to get a firmer grip on how the world and life works (I took a few more months off just to focus on this). My approach is to get a firm grisp on principles that work most of the time, like 'good starting points for clear thinking'. For economics I already started Hyman Minsky's 'John Maynard Keynes', and there is a paper on the fundamentals of Ricardo by (I believe) Bernhoven and Brown that I liked and intend to read again.

Is there a paper you'd think would add to this?

Update: Discuss chapters 1 & 2 here.

Read chapters 1 and 2 by Friday, 08/19, and be ready to discuss them on /r/EconPapers. I'll post a discussion thread on Friday. The book is freely available online here. There are a few corrections on the book's site blog, so bookmark it.

If you feel like it, replicate the t-stats in the table on pg. 13 with this data and code in Stata.

See also:

A statistician’s perspective on “Mostly Harmless Econometrics"

Andrew Gelman's review of MHE

If correlation doesn’t imply causation, then what does?

Causal Inference with Observational Data gives an overview of quasi-experimental methods with examples

Rubin (2005) covers the "potential outcome" framework used in MHE

Buzzfeed's Math and Algorithm Reading Group is currently reading through a book on causality. Check it out if you're in NYC.

Later for chapter 3:

What Regression Really Is

Many of us over at /r/badeconomics wanted to make "starter kits" for anyone with a bit of a background in econ who wants an introduction to a certain field. The ideal audience is probably someone working in one field who wants to learn about or break into another, or someone with an undergrad degree in econ who wants an intro to the various fields of econ. See this thread for details.

Anyone who wants to do a starter kit can tell us and post it here. Discuss anything else related to the starter kits here, as well. If someone wants to request a certain field, do it here.

Integralds' vision for each starter kit is as follows:

Basically, it's ELIHAUD¹ your subfield for people who aren't in your subfield, via 3-5 papers. Include an intro with your papers containing orienting remarks.

For example, I could list 3-5 papers on the basics of macroeconomics, the core topics, and what we know, what we don't know, and where research is going. Something for an economist who knows economics, but doesn't know about the subfield, and is interested in learning about the subfield.

E.g., Integralds finished two starter guides here. I'll compile them all and post them on the /r/EconPapers wiki when we're done.

Footnote 1: Explain It Like I Have An Undergraduate Degree

Feel free to ask questions or share opinions about any material in chapters 1 and 2. I'll post my thoughts below.

Reminder: The book is freely available online here. There are a few corrections on the book's site blog, so bookmark it.

If you haven't done so yet, replicate the t-stats in the table on pg. 13 with this data and code in Stata.

Supplementary Readings for Chapts 1-2:

Notes on MHE chapts 1-2 from Scribd (limited access)

Chris Blattman's Why I worry experimental social science is headed in the wrong direction

A statistician’s perspective on “Mostly Harmless Econometrics"

Andrew Gelman's review of MHE

If correlation doesn’t imply causation, then what does?

Causal Inference with Observational Data gives an overview of quasi-experimental methods with examples

Rubin (2005) covers the "potential outcome" framework used in MHE

Buzzfeed's Math and Algorithm Reading Group is currently reading through a book on causality. Check it out if you're in NYC.

Chapter 3: Making Regression Make Sense

For next week, read chapter 3. It's a long one with theorems and proofs about regression analysis in general, but it doesn't get too rigorous so don't be intimidated.

Supplementary Readings for Chapt 3:

The authors on why they emphasize OLS as BLP (best linear predictor) instead of BLUE

An error in chapter 3 is corrected

A question on interpreting standard errors when the entire population is observed

Regression Recap notes from MIT OpenCourseWare

What Regression Really Is

Zero correlation vs. Independence

Your favorite undergrad intro econometrics textbook.

I'm much more of a macroeconomist so here's mine:

Unravelling the New Classical Counter Revolution by Simon Wren-Lewis and How the Case for Austerity Has Crumbled by Paul Krugman.

What Econ paper left a lasting impression on you and why? Or what Econ paper has had the biggest real world impact? Link it below and say why the paper is so memorable.

The 2016 prize winner will be announced on Monday, October 10. Meaning we have less than a month to go.

Here's what I might want to do around that time:

1. A week before the Nobel announcement, create a nomination/voting thread for the recipient of the first ever annual "Reddit Prize in Economics." Let users nominate and vote. Perhaps weigh votes based on total karma received here or in /r/badeconomics, etc. Choose winner (just one) the night before the Nobel is announced.

2. After Nobel announced, create megathread to discuss laureates' work, papers, etc.

3. I'm working on having the CSS improved. Maybe a sliding collage of past laureates.

Is this something you'd like to see and participate in?

Introduction

I wrote my senior thesis on the Fisher effect – the one-to-one relationship between inflation and the nominal interest rate. Most of us know of the Fisher effect from the Fisher equation:

i_t = r_t + E(pi_t)

where i_t is the nominal interest rate, r_t is the real interest rate and E(pi_t) is the expected inflation rate over the current period. The Fisher effect is named after Irving Fisher, who first proposed the idea in his 1930 book The Theory of Interest. Fisher hypothesized that there is a “real” interest rate that is unaffected by money and a “nominal” interest rate that covaries positively with inflation. The Fisher effect has strong intuitive appeal. Consider a creditor giving a $100 loan to a borrower. This creditor just wants all of his money paid in full after one year, nothing more. But, say that there will be a 6% increase in the price level between the time he loans that $100 and the time he gets that $100 back. He wants $100 back in today’s dollars so he would ask for $106 at the end of one year with an interest rate of 6%. In other words, all interest rates reflect the expected change in purchasing power over the maturity of the loan.

The intuition behind the Fisher effect is so powerful that most people accept the Fisher effect at face value. It is taught in every introductory macroeconomics course as fact. However, finding the Fisher effect in the data is extremely difficult. This literature review covers empirical tests of the Fisher effect.

Empirical roadblocks

I made the claim that it is hard to find the Fisher effect in data. This is because of the fact that the real interest rate and market participants' inflation expectations are unobservable variables. Hence, economists have had to make a few assumptions when testing the Fisher effect. Most economists have used actual inflation and an assumption of rational expectations to test the Fisher effect. Economists have assumed a constant real interest rate. This is a tough pill to swallow, but there is no good substitute for the real interest rate. The last big roadblock is the fact that interest rates aren’t just a function of the real interest rate and inflation expectations. They also include different premia like risk premia or liquidity premia. These premia are also unobservable. Economists generally assume these premia are all zero when testing the Fisher effect because economists use government bond yields to do their tests. This is not a bad assumption, as most people think of government bonds as nominally risk free and government bonds are quite liquid.

Testing the Fisher effect

Irving Fisher himself was the first person to test the Fisher hypothesis. He found that interest rates and inflation have a positive relationship and in the long run the relationship is close to but below unity. He finds, in general, that interest rates tend to be high while inflation is rising and low when inflation is falling. In summary, he writes:

>When the effects of price changes upon interest rates are distributed over several years, we have found remarkably high co-efficients of correlation, thus indicating that interest rates follow price changes closely in degree, though rather distantly in time. (Fisher, 451)

In other words, the Fisher effect happens in the long-run, but not in the short-run.

In the post-War era, landmark research into the Fisher effect came from Fama and Gibbons (1982). Under the assumption of a constant real interest rate and a rational bond market, they tested the ex ante interest rate with ex post inflation. The equation they tested took the form:

pi_t = -(r_t-1) + i_t-1

Fama and Gibbons tested this equation using 1-month and 3-month US Treasuries yields from 1954 to 1979. They found that the Fisher effect does exist in this data. This research shows that the short-run Fisher effect exists. Fama and Gibbons also set the stage for further research: if market actors are rational, inflation can be used for expected inflation and errors from regressions will be white noise. So, most other researchers have used actual inflation with the assumption of rational expectations in their estimation of the Fisher effect

In 1992 Frederic Mishkin updated the Fama-Gibbons arrangement of the Fisher equation with new US Treasury data through 1990. Mishkin (1992) wasn’t able to confirm the results of Fama and Gibbons. However, Mishkin’s research did test for a long-run Fisher effect using cointegration tests. Mishkin found that when interest rates are high, inflation is also high. As Mishkin himself wrote in his paper, his findings (both in the short-run and long-run) are consistent with Irving Fisher’s original findings in 1930.

Evans and Lewis (1995) tested the Fisher equation using conventional time-series methods as well as a Markov switching model – a model where market actors anticipate inflation process changes. Evans and Lewis rejected the Fisher effect with their time-series estimation, showing that the inflation coefficient was less than unity. However, if there was a structural break in inflation processes, that would confound the results. Evans and Lewis found that inflation did have structural breaks and thus modeled these breaks using a Markov switching model. Using this model, they were unable to reject the hypothesis that inflation moves one-to-one with the nominal interest rate in the long-run. Evans and Lewis not only use actual inflation, but also the Livingston Survey as a measure of inflation expectations.

In 1996, William Crowder and Dennis Hoffman tested the Fisher equation before and after adjusting for tax effects associated with making money on bonds. Without adjusting for taxes, Crowder and Hoffman found an inflation coefficient larger than one. However, after adjusting for taxes, they found that the coefficient for inflation is insignificantly different from one. This runs contrary to the other authors thus far. Most were unable to find even a one-to-one relationship between inflation and the nominal interest rate, but Crowder and Hoffman did. Other researchers did not adjust for taxes and yet their coefficient on inflation was consistently below unity.

Alternative measures of inflation expectations

The authors I’ve covered so far have all been using government bonds and actual inflation for the variables in their regressions. However, Evans and Lewis (1995) include the Livingston Survey as well. There exist alternative measures of inflation expectations mostly in the form of surveys. The two surveys people are most familiar with are the Survey of Professional Forecasters and the Livingston Survey. These surveys ask economists and other forecasters what they expect inflation to be over certain time periods. The surveyors then release this data publicly. Unfortunately, surveys of forecasters are about as useful as proxies for inflation expectations as sun spots are. So what other recourse is there?

In the 1980s the United Kingdom and Australia both introduced inflation-indexed government bonds. The US and Canada followed suit in the late 1990s. These bonds promised a real return as opposed to a nominal return like regular government bonds do. In 1990, Woodward was the first author to develop a data set of market derived inflation expectations. Woodward utilized inflation indexed UK gilts and regular UK gilts to create a series of inflation expectations using quarterly data. The amazing thing about this is that Woodward made an unobserved variable, inflation expectations, completely observable. In 1992, he updated his 1990 methodology using monthly data and explicitly tested the Fisher effect for different maturities. Like Crowder and Hoffman, Woodward found that, when yields are not adjusted for taxes, the coefficient for inflation is higher than one. However, when adjusted for taxes, the coefficient for inflation is either slightly below or insignificantly different than one on long-term maturities. The coefficients for inflation on short-termed securities were less than one. Thus, Woodward corroborated Fisher’s original findings that inflation manifests itself in interest rates over the long-run but not in the short run.

Summary of findings

Nearly all researchers find some support for the Fisher effect but it is one-to-one in nearly all studies. No author finds short-run support for the Fisher effect besides Fama and Gibbons, but Mishkin showed that Fama and Gibbons’ results were unique to the data set Fama and Gibbons used. Adjusting for taxes pushes down the coefficient for inflation in two papers but papers that don’t adjust for taxes do not find a coefficient for inflation above unity. Only one author uses a realistic measure of inflation expectations. However, all the data seems to point in the direction of “Irving Fisher was right.” The research is certainly not an emphatic “yes”, but it gives the Fisher effect two thumbs up and the research doesn’t warrant any asterisks in macroeconomics textbooks.

Okay, but who cares?

More politely “what useful conclusions can you draw from this research?” While a few things come to mind, I think the most important thing for me is that all of this research points to Milton Friedman being right in Friedman (1968). Friedman states that the conventional wisdom of judging the stance monetary policy by what the federal funds rate is, is entirely wrong. Since the Fed lowers the federal funds rate to expand the money supply we think that low interest rates signals easy monetary policy. However, when the Fed lowers interest rates, inflation goes up after some time. Market actors include this increase in inflation in the interest rate due to the one-to-one relationship between inflation and the nominal interest rate, so interest rates rise - especially on long-termed maturities. If the Fed thinks that high interest rates means tight money, then the Fed will lower the federal funds rate further, thus increasing inflation. This increase in inflation then makes interest rates go even higher. Since high interest rates coincide with high inflation, this means that high interest rates - especially on long-term maturities - are a sign of easy monetary policy.

Final remarks

I hope some of you found this interesting. If anyone has any other questions, feel free to ask me. If you want to know what I did in my senior thesis, I can give you a run down. I've run out of space here to discuss it.

References

Crowder, William J and Dennis L. Hoffman, “The Long-Run Relationship between Nominal Interest Rates and Inflation: The Fisher Equation Revisited” Journal of Money, Credit and Banking, (February, 1996), 102-119

Evans, Martin D. D. and Karen K. Lewis, “Do Expected Shifts in Inflation Affect Estimates of the Long-Run Fisher Relation?” The Journal of Finance (March 1995), 225-253

Fama, Eugene F. and Michael R. Gibbons “Inflation, Real Returns and Capital Investment” Journal of Monetary Economics (1982), 297-323

Fisher, Irving, The Theory of Interest (New York: Macmillan, 1930)

Friedman, Milton “The Role of Monetary Policy” The American Economic Review (March 1968), 1-17

Mishkin, Frederic S. “Is the Fisher effect for real? A reexamination of the relationship between inflation and interest rates”, Journal of Monetary Economics (1992) 195-215

Woodward, G. Thomas, “The Real Thing; A Dynamic Term Structure of Real Interest Rates and Inflation Expectations in the United Kingdom: 1982-1988,” *Journal of Business *(July 1990), 373-398

_________, “Evidence of the Fisher Effect From U.K. Indexed Bonds” The Review of Economics and Statistics (May 1992) 315-320

All of these were posted during /r/Economics Journal Day.

The Causal Effect of Place: Evidence from Japanese-American Internment

Abstract:

Recent research has stressed the importance of long-run place effects on income and economic mobility, but the literature has struggled to isolate the causal impact of location. This paper provides new evidence on these effects using administrative data on over 100,000 JapaneseAmericans who were interned during World War II. Internees were conditionally randomly assigned to camps in seven different states and held for several years. Restitution payments paid in the early 1990s to the universe of surviving internees allow us to measure their locations and outcomes nearly half a century after the camp assignments. Using this unique natural experiment we find, first, that camp assignment had a lasting effect on individuals’ long-term locations. Next, using this variation, we find large place effects on individual economic outcomes like income, education, socioeconomic status, house prices, and housing quality. People assigned to richer locations do better on all measures. Random location assignment affected intergenerational economic outcomes as well, with families assigned to more socially mobile areas (as designated by Chetty et al., 2014) displaying lower cross-generational correlation in outcomes. Finally, we provide evidence that assignment to richer places impacted people’s values and political views, a new and intriguing mechanism through which place effects operate. Together, this new causal evidence on location effects has broad implications for urban economics, as well as potential policy implications for policymakers struggling to resettle and integrate large refugee or immigrant populations.

Industrialization: Why Britain Got There First

Abstract:

This paper provides an introductory overview of the British Industrial Revolution. The dimensions of growth are discussed as well as notable recent explanations for Britain’s primacy. Obstacles to faster growth are considered as well as advantages that were conducive to stronger TFP growth. In this context, reasons for the long delay before steam power had any significant impact on productivity are highlighted. Some implications of Britain’s early start to modern economic growth for subsequent economic performance are noted. The paper concludes that precocious British industrialization is much easier to explain than the timing of the acceleration of technological progress.

Start-up Nation? Slave Wealth and Entrepreneurship in Civil War Maryland

Abstract:

Slave property rights yielded a source of collateral as well as a coerced labor force. Using data from Dun and Bradstreet linked to the 1860 census and slave schedules in Maryland, we find that slaveowners were more likely to start businesses prior to the uncompensated 1864 emancipation, even conditional on total wealth and human capital, and this advantage disappears after emancipation. We assess a number of potential explanations, and find suggestive evidence that this is due to the superiority of slave wealth as a source of collateral for credit rather than any advantage in production. The collateral dimension of slave property magnifies its importance to historical American economic development.

Causes and Consequences of the Protestant Reformation

Published version.

Abstract:

The Protestant Reformation is one of the defining events of the last millennium. Nearly 500 years after the Reformation, its causes and consequences have seen a renewed interest in the social sciences. Research in economics, sociology, and political science increasingly uses detailed individual-level, city-level, and regional-level data to identify drivers of the adoption of the Reformation, its diffusion pattern, and its socioeconomic consequences. This survey takes stock of the research so far, tries to point out what we know and what we do not know, and which are the most promising areas for future research.

Tuskegee and the Health of Black Men

Abstract:

For forty years, the Tuskegee Study of Untreated Syphilis in the Negro Male passively monitored hundreds of adult black males with syphilis despite the availability of effective treatment. The study's methods have become synonymous with exploitation and mistreatment by the medical community. We find that the historical disclosure of the study in 1972 is correlated with increases in medical mistrust and mortality and decreases in both outpatient and inpatient physician interactions for older black men. Our estimates imply life expectancy at age 45 for black men fell by up to 1.4 years in response to the disclosure, accounting for approximately 35% of the 1980 life expectancy gap between black and white men.

Obituary.

This man was Economic History. He and co-laureate Robert Fogel were pretty much the reason why the New Economic History became a thing. North is also one of the principal founders of the New Institutional Economics. We have him to thank for EH and IE being vibrant and growing fields today.

• Here is North's Nobel prize lecture, "Economic Performance through Time."

• Here is his Nobel banquet speech.

• Here is his most highly cited book, "Institutions, institutional change and economic performance," which is also his most highly cited work, cited by 41,179!!

• Here is his most highly cited paper, "Constitutions and Commitment: The Evolution of Institutions Governing Public Choice in Seventeenth-Century England," with 3963 citations listed on Google Scholar.

• I'm also a fan of his history of the economic development of the United States.

• Here is a paper summarizing North's contributions to New Institutional Economics.

• Here is a summary of his work at the Library of Economics and Liberty

• Here is his JEP article, "Institutions," geared toward a more general audience.

• For the rest of his work, here is his IDEAS page.

Rest in peace.

Some freely available papers of his I thought sounded very interesting from the Google Scholar page:

1. The New Institutional Economics and Third World Development.

2. A Conceptual Framework for Interpreting Recorded Human History.

3. The Paradox of the West.