Economics

The best economic history papers of 2017

Vincent Geloso Economics, History , , , , , , , , , , , , ,

As we are now solidly into 2018, I thought that it would be a good idea to underline the best articles in economic history that I read in 2017. Obviously, the “best” is subjective to my preferences. Nevertheless, it is a worthy exercise in order to expose some important pieces of research to a wider audience.  I limited myself to five articles (I will do my top three books in a few weeks). However, if there is an interest in the present post I will publish a follow-up with another five articles.

O’Grady, Trevor, and Claudio Tagliapietra. “Biological welfare and the commons: A natural experiment in the Alps, 1765–1845.” Economics & Human Biology 27 (2017): 137-153.

This one is by far my favorite article of 2017. I stumbled upon it quite by accident. Had this article been published six or eight months earlier, I would never have been able to fully appreciate its contribution. Basically, the authors use the shocks induced by the wars of the late 18th century and early 19th century to study a shift from “self-governance” to “centralized governance” of common pool resources. When they speak of “commons” problems, they really mean “commons” as the communities they study were largely pastoral communities with area in commons.  Using a difference-in-difference where the treatment is when a region became “centrally governed” (i.e. when organic local institutions were swept aside), they test the impact of these top-down changes to institutions on biological welfare (as proxied by infant mortality rates). They find that these replacements worsened outcomes.

Now, this paper is fascinating for two reasons. First, the authors offer a clear exposition of its methodology and approach. They give just the perfect amount of institutional details to assuage doubts.  Second, this is a strong illustration of the points made by Elinor Ostrom and Vernon Smith. These two economists emphasize different aspects of the same thing. Smith highlights that “rationality” is “ecological” in the sense that it is an iterative process of information discovery to improve outcomes.  This includes the generation of “rules of the game” which are meant to sustain exchanges. These rules need not be formal edifices. They can be norms, customs, mores and habits (generally supported by the discipline of continuous dealings and/or investments in social-distance mechanisms). On her part, Ostrom emphasized that the tragedy of the commons can be resolved through multiple mechanisms (what she calls polycentric governance) in ways that do not necessarily require a centralized approach (or even market-based approaches).

In the logic of these two authors, attempts at “imposing” a more “rational” order (from the perspective of the planner of this order) may backfire. This is why Smith often emphasizes the organic nature of things like property rights. It also shows that behind seemingly “dumb” peasants, there is often the weight of long periods of experimentation in order to adapt rules and norms in order to fit the constraints faced by the community.  In this article, we can see those two things – the backfiring and, by logical implication, the strengths of the organic institutions that were swept away.

Fielding, David, and Shef Rogers. “Monopoly power in the eighteenth-century British book trade.” European Review of Economic History 21, no. 4 (2017): 393-413.

In this article, the authors use a legal change caused by the end of the legal privileges of the Stationers’ Company (which amounted to an easing of copyright laws).  The market for books may appear to be “non-interesting” for mainstream economics. However, this would be a dramatic error. The “abundance” of books is really a recent development. Bear in mind that the most erudite monk of the late middle ages had less than fifty books from which to draw knowledge (this fact is a vague recollection of mine from Kenneth Clark’s art history documentary from the late 1960s which was aired by the BBC). Thus, the emergence of a wide market for books – which is dated within the period studied by the authors of this article – should not be ignored. It should be considered as one of the most important development in western history. This is best put by the authors when they say that “the reform of copyright law has been regarded as one of the driving forces behind the rise in book production during the Enlightenment, and therefore a key factor in the dissemination of the innovations that underpinned Britain’s Industrial Revolution”.

However, while they agree that the rising popularity of books in the 18th century is an important historical event, they contest the idea that liberalization had any effect. They find that the opening up of the market to competition had little effects on prices and book production. They also find that mark-ups fell but that this could not be attributed to liberalization. At first,  I found these results surprising.

However, when I took the time to think about it I realized that there was no reason to be surprised. First, many changes have been heralded as crucial moments in history. More often than not, the importance of these changes has been overstated. A good example of an overstated change has been the abolition of the Corn Laws in England in the 1840s. The reduction in tariffs, it is argued, ushered Britain into an age of free trade and falling food prices.

In reality, as John Nye discusses, protectionist barriers did not fall as fast as many argued and there were reductions prior to the 1846 reform as Deirdre McCloskey pointed out. It also seems that the Corn Laws did not have substantial effects on consumption or the economy as a whole (see here and here).  While their abolition probably helped increase living standards, it seems that the significance of the moment is overstated. The same thing is probably at play with the book market.

The changes discussed by Fielding and Rogers did not address the underlying roots of the level of market power enjoyed by industry players. In other words, it could be that the reform was too modest to have an effect. This is suggested by the work of Petra Moser. The reform studied by Fielding and and Rogers appears to have been short-lived as evidenced by changes to copyright laws in the early 19th century (see here and here). Moser’s results point to effects much larger (and positive for consumers) than those of Fielding and Rogers.  Given the importance of the book market to stories of innovation in the industrial revolution, I really hope that this sparks a debate between Moser and Fielding and Rogers.

Johnson, Noel D., and Mark Koyama. “States and economic growth: Capacity and constraints.” Explorations in Economic History 64 (2017): 1-20.

I am biased as I am fond of most of the work of these two authors. Nevertheless, I think that their contribution to the state capacity debate is a much needed one. I am very skeptical of the theoretical value of the concept of state capacity.  The question always lurking in my mind is the “capacity to do what?”.

A ruler who can develop and use a bureaucracy to provide the services of a “productive state” (as James Buchanan would put it) is also capable of acting like a predator.  I actually emphasize this point in my work (revise and resubmit at Health Policy & Planning) on Cuban healthcare: the Cuban government has the capacity to allocate large quantities of resources to healthcare in amounts well above what is observed for other countries in the same income range. Why? Largely because they use health care for a) international reputation and b) actually supervising the local population. As such, members of the regime are able to sustain their role even if the high level of “capacity” comes at the expense of living standards in dimensions other than health (e.g. low incomes). Capacity is not the issue, its capacity interacting with constraints that is interesting.

And that is exactly what Koyama and Johnson say (not in the same words). They summarize a wide body of literature in a cogent manner that clarifies the concept of state capacity and its limitations. In doing so, they ended up proposing that the “deep roots” question that should interest economic historians is how “constraints” came to be efficient at generating “strong but limited” states.

In that regard, the one thing that surprised me from their article was the absence of Elinor Ostrom’s work. When I read about “polycentric governance” (Ostrom’s core concept), I imagine the overlap of different institutional structures that reinforce each other (note: these structures need not be formal ones). They are governance providers. If these “governance providers” have residual claimants (i.e. people with skin in the game), they have incentives to provide governance in ways that increased the returns to the realms they governed. Attempts to supersede these institutions (e.g. like the erection of a modern nation state) requires dealing with these providers. They are the main demanders of constraints which are necessary to protect their assets (what my friend Alex Salter calls “rights to the realm“). As Europe pre-1500 was a mosaic of such governance providers, there would have been great forces pushing for constraints (i.e. bargaining over constraints).

I think that this is where the literature on state capacity should orient itself. It is in that direction that it is the most likely to bear fruits. In fact, there have been some steps taken in that direction For example, my colleagues Andrew Young and Alex Salter have applied this “polycentric” narrative to explain the emergence of “strong but limited states” by focusing on late medieval institutions (see here and here).  Their approach seems promising. Yet, the work of Koyama and Johnson have actually created the room for such contributions by efficiently summarizing a complex (and sometimes contradictory) literature.

Bodenhorn, Howard, Timothy W. Guinnane, and Thomas A. Mroz. “Sample-selection biases and the industrialization puzzle.” The Journal of Economic History 77, no. 1 (2017): 171-207.

Elsewhere, I have peripherally engaged discussants in the “antebellum puzzle” (see my article here in Economics & Human Biology on the heights of French-Canadians born between 1780 and 1830). The antebellum puzzle refers to the possibility that the biological standard of living (e.g. falling heights, worsening nutrition, increased mortality risks) fell while the material standard of living increased (e.g. higher wages, higher incomes, access to more services, access to a wider array of goods) during the decades leading to the American Civil War.

I am inclined to accept the idea of short-term paradoxes in living standards. The early 19th century witnessed a reversal in rural-urban concentration in the United States. The country had been “deurbanizing” since the colonial era (i.e. cities represented an increasingly smaller share of the population). As such, the reversal implied a shock in cities whose institutions were geared to deal with slowly increasing populations.

The influx of people in cities created problems of public health while the higher level of population density favored the propagation of infectious diseases at a time where our understanding of germ theory was nill. One good example of the problems posed by this rapid change has been provided by Gergely Baics in his work on the public markets of New York and their regulation (see his book here – a must read).  In that situation, I am not surprised that there was a deterioration in the biological standard of living. What I see is that people chose to trade-off shorter wealthier lives against longer poorer lives. A pretty legitimate (albeit depressing) choice if you ask me.

However, Bodenhorn et al. (2017) will have none of it. In a convincing article that has shaken my priors, they argue that there is a selection bias in the heights data – the main measurement used in the antebellum puzzle debate.  Most of the data on heights comes either from prisoners or enrolled volunteer soldiers (note: conscripts would not generate the problem they describe). The argument they make is that as incomes grow, the opportunity cost of committing a crime or of joining the army grows.  This creates the selection bias whereby the sample is going to be increasingly composed of those with the lowest opportunity costs. In other words, we are speaking of the poorest in society who also tended to be shorter. Simultaneously, fewer tall individuals (i.e. rich individuals) committed crimes or joined the army because incomes grew. This logic is simple and elegant. In fact, this is the kind of data problem that every economist should care about when they design their tests.

Once they control for this problem (through a meta-analysis), the puzzle disappears. I am not convinced by the latter part of the claim. Nevertheless, it is very likely that the puzzle is much smaller than initially gleaned. In yet to be published work, Ariell Zimran (see here and here) argues that the antebellum puzzle is robust to the problem of selection bias but that it is indeed diminished. This concedes a large share of the argument to Bodenhorn et al. While there is much to resolve, this article should be read as it constitutes one of the most serious contributions to the field of economic history published in 2017.

Ridolfi, Leonardo. “The French economy in the longue durée: a study on real wages, working days and economic performance from Louis IX to the Revolution (1250–1789).” European Review of Economic History 21, no. 4 (2017): 437-438.

I discussed Leonardo’s work elsewhere on this blog before. However, I must do it again. The article mentioned here is the dissertation summary that resulted from Leonardo being a finalist to the best dissertation award granted by the EHES (full dissertation here). As such, it is not exactly the “best article” published in 2017. Nevertheless,  it makes the list because of the possibilities that Leonardo’s work have unlocked.

When we discuss the origins of the British Industrial Revolution, the implicit question lurking not far away is “Why Did It Not Happen in France?”. The problem with that question is that the data available for France (see notably my forthcoming work in the Journal of Interdisciplinary History) is in no way comparable with what exists for Britain (which does not mean that the British data is of great quality as Judy Stephenson and Jane Humphries would point out).  Most estimates of the French economy pre-1790 were either conjectural or required a wide array of theoretical considerations to arrive at a deductive portrait of the situation (see notably the excellent work of Phil Hoffman).  As such, comparisons in order to tease out improvements to our understanding of the industrial revolution are hard to accomplish.

For me, the absence of rich data for France was particularly infuriating. One of my main argument is that the key to explaining divergence within the Americas (from the colonial period onwards) resides not in the British or Spanish Empires but in the variation that the French Empire and its colonies provide. After all, the French colony of Quebec had a lot in common geographically with New England but the institutional differences were nearly as wide as those between New England and the Spanish colonies in Latin America. As such, as I spent years assembling data for Canada to document living standards in order to eventually lay down the grounds to test the role of institutions, I was infuriated that I could do so little to compare with France. Little did I know that while I was doing my own work, Leonardo was plugging this massive hole in our knowledge.

Leonardo shows that while living standards in France increased from 1550 onward, the level was far below the ones found in other European countries. He also showed that real wages stagnated in France which means that the only reason behind increased incomes was a longer work year. This work has also unlocked numerous other possibilities. For example, it will be possible to extend to France the work of Nicolini and Crafts and Mills regarding the existence of Malthusian pressures. This is probably one of the greatest contribution of the decade to the field of economic history because it simply went through the dirty work of assembling data to plug what I think is the biggest hole in the field of economic history.

On the “tea saucer” of income inequality since 1917

Vincent Geloso Economics, History , , , , , , ,

I disagree often with the many details that underlie the arguments of Thomas Piketty and Emmanuel Saez. That being said, I am also a great fan of their work and of them in general. In fact, I think that both have made contributions to economics that I am envious to equal. To be fair, their U-curve of inequality is pretty much a well-confirmed fact by now: everyone agrees that the period from 1890-1929 was a high-point of inequality which leveled off until the 1970s and then picked up again.

Nevertheless, while I am convinced of the curvilinear aspect of the evolution of income inequality in the United State as depicted by Piketty and Saez, I am not convinced by the amplitudes. In their 2003 article, the U-curve of inequality really looks like a “U” (see image below).  Since that article, many scholars have investigated the extent of the increase in inequality post-1980 (circa). Many have attenuated the increase, but they still find an increase (see here here here here here here here here here). The problem is that everyone has been considering the increase – i.e. the right side of the U-curve. Little attention has been devoted to the left side of the U-curve even though that is where data problems should be considered more carefully for the generation of a stylized fact. This is the contribution I have been coordinating and working on for the last few months alongside John Moore, Phil Magness and Phil Schlosser. 

Blog Figure

To arrive at their proposed series of inequality, Piketty and Saez used the IRS Statistics of Income (SOI) to derive top income fractiles. However, the IRS SOI have many problems. The first is that between 1917 and 1943, there are many years where there are less than 10% of the potential tax population that files a tax return. This prohibits the use of a top 10% income share in many years unless an adjustment is made. The second is that prior to 1943, the IRS reports net income and reports adjusted gross income after 1943. As such, to link post-1943 with pre-1943, there needs to be an additional adjustment. Piketty and Saez made some seemingly reasonable assumptions, but they have never been put to the test regarding sensitivity and robustness. This is leaving aside issues of data quality (I am not convinced IRS data is very good as most of it was self-reported pre-1943 which is a period with wildly varying tax rates). The question here is “how good” are the assumptions?

What we did is verify each assumption to see their validity. The first one we tackle is the adjustment for the low number of returns. To make their adjustments, Piketty and Saez used the fact that single households and married households filed in different quantities relative to their total population. Their idea is that a year in which there was a large number of return was used, the ratio of single to married could be used to adjust the series. The year they used is 1942. This is problematic as 1942 is a war year with self-reporting when large quantities of young American males are abroad fighting. Using 1941, the last US peace year, instead shows dramatically different ratios. Using these ratios knocks off a few points from the top 10% income share. Why did they use 1942? Their argument was there was simply not enough data to make the correction in 1941.  They point to a special tabulation in the 1941 IRS-SOI of 112,472 1040A forms from six states which was not deemed sufficient to make to make the corrections. However, later in the same document, there is a larger and sufficient sample of 516,000 returns from all 64 IRS collection districts (roughly 5% of all forms). By comparison, the 1942 sample Piketty and Saez used to correct only had 455,000 returns.  Given the war year and the sample size, we believe that 1941 is a better year to make the adjustment.

Second, we also questioned the smoothing method to link net income-based series with adjusted-gross income based series (i.e. pre-1943 and post-1943 series). The reason for this is that the implied adjustment for deductions made by Piketty and Saez is actually larger than all the deductions claimed that were eligible under the definition of Adjusted Gross Income – which is a sign of overshot on their parts. Using the limited data available for deductions by income groups and making some assumptions (very conservative ones) to move further back in time, we found that adjusting for “actual deductions” yields a lower level of inequality. This is contrasted with the fixed multipliers which Piketty and Saez used pre-1943.

Third, we question their justification for not using the Kuznets income denominator. They argued that Kuznets’ series yielded an implausible figure because, in 1948, its use yielded a greater income for non-fillers than for fillers.  However, this is not true of all years. In fact, it is only true after 1943. Before 1943, the income of non-fillers is equal in proportion to the one they use post-1944 to impute the income of non-fillers. This is largely the result of an accounting error definition. Incomes before 1943 were reported as net income and as gross incomes after that point. This is important because the stylized fact of a pronounced U-curve is heavily sensitive to the assumption made regarding the denominator.

These three adjustments are pretty important in terms of overall results (see image below).  The pale blue line is that of Piketty of Saez as depicted in their 2003 paper in the Quarterly Journal of Economics. The other blue line just below it is the effect of deductions only (the adjustment for missing returns affects only the top 10% income share). All the other lines that mirror these two just below (with the exception of the darkest blue line which is the original Kuznets inequality estimates) compound our corrections with three potential corrections for the denominators. The U-curve still exists, but it is not as pronounced. When you look with the adjustments made by Mechling et al. (2017) and Auten and Splinter (2017) for the post-1960 period (green and red lines) and link them with ours, you can still see the curvilinear shape but it looks more like a “tea saucer” than a pronounced U-curve.

In a way, I see this as a simultaneous complement to the work of Richard Sutch and to the work of Piketty and Saez: the U-curve still exists, but the timing and pattern is slightly more representative of history. This was a long paper to write (and it is a dry read given the amount of methodological discussions), but it was worth it in order to improve upon the state of our knowledge.

FigureInequality

On Ronald Coase as an Economic Historian?

Vincent Geloso Economics, History ,

Can we consider Ronald Coase as an economic historian? Most economists or social scientists that read this blog must appreciate Coase largely for his Nature of the Firm and the Problem of Social Cost. Personally, while I appreciate these works for their theoretical insights (well, isn’t that an understatement!), I appreciate Coase much more for articles that very few know about.

Generally, after these two articles, most economists do not know what Coase wrote about.  Some might know about Coase’s proviso regarding durability and monopoly (a single firm producing a durable good cannot be a monopoly because it competes with its future self) or about his work on the Federal Communications Commission (which is an application of his two main papers).

Fewer people know about his piece about the lighthouse in economics. While it is not an unknown piece, it is mostly known within the subfield of public economics as it concerns the scope for the private provision of public goods. Generally, I found that those who know about the piece know the “takeaway” which was that lighthouses (which because of their low marginal costs and non-excludability have been deemed public goods ever since J.S. Mill) could be produced privately. While this was indeed Coase’s point, this summary (like that Stigler made of the Coase Theorem) misses the peripheral insights that matter. Coase did the economic history job of documenting the institutional details behind the provision of lighthouses which sparked debates in journals such as Journal of Legal Studies, Cambridge Journal of Economics, European Review of Economic History, Public Choice and Public Finance Review (they still go to this day and I am trying to contribute to that with this piece that me and Rosolino Candela have recently submitted). It seems unclear whether or not the lighthouse can even be considered a public good or if it was merely an instance of government failure rather than market failure (or the reverse). Regardless of the outcome, if you read the lighthouse paper by Coase, you will read an application of theory to history bringing a “boring” topic (i.e. that of maritime safety pre-1900) to life through theory.  The lighthouse paper is an application of industrial organization through the Coasean lenses of transaction costs and joint provision. And it is a fine application if I might say!

But that is not his only piece! Has anyone ever read his article in the Journal of Law & Economics on Fisher Body and vertical integration? Or his piece on the British Post Office and private messengers in the same journal?  In those articles, Coase brings theory to life by asking simple questions to history in ways that force us to question some common day conceptions like “vertical integration was the results of holdup problems” or “postal services need to be publicly provided”.  In both of these articles and the lighthouse article, Coase basically applies simple theoretical tools to cut through a maze of details in order to answer questions of great relevance to economic theory and even policy (i.e. the post office example). And this is why, earlier in 2017, I mentioned that Coase should be considered in the league of the top economic historians.

On the popularity of economic history

Vincent Geloso Books, Culture, Economics , , , , , , , , , , ,

I recently engaged in a discussion (a twittercussion) with Leah Boustan of Princeton over the “popularity” of economic history within economics (depicted below).  As one can see from the purple section, it is as popular as those hard candies that grandparents give out on Halloween (to be fair, I like those candies just like I do economic history). More importantly, the share seems to be smaller than at the peak of 1980s. It also seems like the Nobel prize going to Fogel and North had literally no effects on the subfield’s popularity. Yet, I keep hearing that “economic history is back”. After all, the Bates Clark medal went to Donaldson of Stanford this year which should confirm that economic history is a big deal.  How can this be reconciled with the figure depicted below?

EconomicHIstoryData

As I explained in my twittercussion with Leah, I think that there is a popularity for using historical data. Economists have realized that if some time is spent in archives to collect historical data, great datasets can be assembled. However, they do not necessarily consider themselves “economic historians” and as such they do not use the JEL code associated with history.  This is an improvement over a field where Arthur Burns (former Fed Chair) supposedly said during the 1970s that we needed to look at history to better shape monetary policy. And by history, he meant the 1950s. However, while there are advantages, there is an important danger which is left aside.

The creation of a good dataset has several advantages. The main one is that it increases time coverage. By increasing the time coverage, you can “tackle” the big questions and go for the “big answers” through the generation of stylized facts. Another advantage (and this is the one that summarizes my whole approach) is that historical episodes can provide neat testing grounds that give us a window to important economic issues. My favorite example of that is the work of Petra Moser at NYU-Stern. Without going into too much details (because her work was my big discovery of 2017), she used a few historical examples which she painstakingly detailed in order to analyze the effect of copyright laws. Her results have important ramifications to debates regarding “science as a public good” and “science as a contribution good” (see the debates between Paul David and Terence Kealey on this in Research Policy for this point).

But these two advantages must be weighted against an important disadvantage which Robert Margo has warned against in a recent piece in Cliometrica.  When one studies economic history, one must keep in mind that two things must be accomplished simultaneously: to explain history through theory and bring theory to life through history (this is not my phrase, but rather that of Douglass North). To do so, one must study a painstaking amount of details to ascertain the quality of the sources used and their reliability.  In considering so many details, one can easily get lost or even fall prey to his own prior (i.e. I expect to see one thing and upon seeing it I ask no question). To avoid this trap, there must be a “northern star” to act as a guide. That star, as I explained in an earlier piece, is a strong and general understanding of theory (or a strong intuition for economics). To create that star and give attention to details is an incredibly hard task and which is why I argued in the past that “great” economic historians (Douglass North, Deirdre McCloskey, Robert Fogel, Nathan Rosenberg, Joel Mokyr, Ronald Coase (because of the lighthouse piece), Stephen Broadberry, Gregory Clark etc.) take a longer time to mature. In other words, good economic historians are projects that have have a long “time to build problem” (sorry, bad economics joke).  However, the downside is that when this is not the case, there are risks of ending up with invalid results that are costly and hard to contest.

Just think about the debate between Daron Acemoglu and David Albouy on the colonial origins of development. It took more than five years to Albouy to get his results that threw doubts on Acemoglu’s 1999 paper. Albouy clearly expended valuable resources to get the “details” behind the variables. There was miscoding of Niger and Nigeria, and misunderstandings of what type of mortalities were used.  This was hard work and it was probably only deemed a valuable undertaking because Acemoglu’s paper was such a big deal (i.e. the net gains were pretty big if they paid off). Yet, to this day, many people are entirely unaware of the Albouy rebuttal.  This can be very well seen in the image below regarding the number of cites of the Acemoglu-Johnson-Robinson paper on an annual basis. There seems to be no effect from the massive rebuttal (disclaimer: Albouy convinced me that he was right) from the Albouy piece.

AcemogluPaperCites

And it really does come down to small details like those underlined by Albouy. Let me give you another example taken from my work. Within Canada, the French minority is significantly poorer than the rest of Canada. From my cliometric work, we now know that there were poorer than the rest of Canada and North America as far as the colonial era. This is a stylized fact underlying a crucial question today (i.e. Why are French-Canadians relatively poor).  That stylized fact requires an explanation. Obviously, institutions are a great place to look. One of the institution that is most interesting is seigneurial tenure which was basically a “lite” version of feudalism in North America that was present only in the French settled colonies. Some historians and economic historians argued that there were no effects of the institutions on variables like farm efficiency.  However, some historians noticed that in censuses the French reported different units that the English settlers within the colony of Quebec. To correct for this metrological problem, historians made county-level corrections. With those corrections, the aforementioned has no statistically significant effect on yields or output per farm. However, as I note in this piece that got a revise and resubmit from Social Science Quarterly (revised version not yet online), county-level corrections mask the fact that the French were more willing to move to predominantly English areas than the English were willing to predominantly French areas. In short, there was a skewed distribution. However, once you correct the data on an ethnic composition basis rather than on the county-level (i.e. the same correction for the whole county), you end with a statistically significant negative effect on both output per farm and yields per acre. In short, we were “measuring away” the effect of institutions. All from a very small detail about distributions. Yet, that small detail has supported a stylized fact that the institution did not matter.

This is the risk that Margo speaks about illustrated in two examples. Economists who use history merely as a tool may end up making dramatic mistakes that will lead to incorrect conclusions. I take this “juicy” quote from Margo (which Pseudoerasmus) highlighted for me:

[EH] could become subsumed entirely into other fields… the demand for specialists in economic history might dry up, to the point where obscure but critical knowledge becomes difficult to access or is even lost. In this case, it becomes harder to ‘get the history right’

Indeed, unfortunately.

On the point of quantifying in general and quantifying for policy purposes

Vincent Geloso Economics , , , , , , , , , , , , ,

Recently, I stumbled on this piece in Chronicle by Jerry Muller. It made my blood boil. In the piece, the author basically argues that, in the world of education, we are fixated with quantitative indicators of performance. This fixation has led to miss (or forget) some important truths about education and the transmission of knowledge. I wholeheartedly disagree because the author of the piece is confounding two things.

We need to measure things! Measurements are crucial to our understandings of causal relations and outcomes.  Like Diane Coyle, I am a big fan of the “dashboard” of indicators to get an idea of what is broadly happening.  However, I agree with the authors that very often the statistics lose their entire meaning. And that’s when we start targeting them!

Once we know that this variable becomes the object of target, we act in ways that increase this variable. As soon as it is selected, we modify our behavior to achieve fixed targets and the variable loses some of its meaning. This is also known as Goodhart’s law whereby “when a measure becomes a target, it ceases to be a good measure” (note: it also looks a lot like the Lucas critique).

Although Goodhart made this point in the context of monetary policy, it applies to any sphere of policy – including education. When an education department decides that this is the metric they care about (e.g. completion rates, minority admission, average grade point, completion times, balanced curriculum, ratio of professors to pupils, etc.), they are inducing a change in behavior which alters the significance carried by this variable.  This is not an original point. Just go to google scholar and type “Goodhart’s law and education” and you end up with papers such as these two (here and here) that make exactly the point I am making here.

In his Chronicle piece, Muller actually makes note of this without realizing how important it is. He notes that “what the advocates of greater accountability metrics overlook is how the increasing cost of college is due in part to the expanding cadres of administrators, many of whom are required to comply with government mandates“(emphasis mine).

The problem he is complaining about is not metrics per se, but rather the effects of having policy-makers decide a metric of relevance. This is a problem about selection bias, not measurement. If statistics are collected without an intent to be a benchmark for the attribution of funds or special privileges (i.e. that there are no incentives to change behavior that affects the reporting of a particular statistics), then there is no problem.

I understand that complaining about a “tyranny of metrics” is fashionable, but in that case the fashion looks like crocs (and I really hate crocs) with white socks.

In health care, expenditures to GDP may be misleading!

Vincent Geloso Economics , , , ,

In debates over health care reform in the US, it is frequent for Canada’s name to pop up in order to signal that Canada is spending much less of its GDP to health care and seems to generate relatively comparable outcomes. I disagree.

Its not that the system presently in place in the US is so great, its that the measure of resources expended on each system is really bad. In fact, its a matter of simple economics.  Imagine two areas (1 and 2), the first has single-payer health care, the other has fully-private health care.

In area 2, prices ration access to health care so that people eschew visits to the emergency room as a result of a scraped elbow. In area 1, free access means no rationing through price and more services are consumed. However, to avoid overspending, the government of area 1 has waiting lists or other rationing schemes. In area 2, which I have presented as an ideal free market for the sake of conversation,  whatever people expend can be divided over GDP and we get an accurate portrait of “costs”. However, in area 1, costs are borne differently – through taxes and through waiting times. As such, comparing what is spent in area 1 to what is spent in area 2 is a flawed comparison.

So when we say that Canada spends 10.7% of GDP on health care (2013 numbers) versus 17.1% of GDP in the US, is it a viable comparison? Not really.  In 2008, the Canadian Medical Association produced a study evaluating the cost of waiting times for four key procedures : total joint replacement surgery, cataract surgery, coronary artery bypass
graft (CABG) and MRI scans. These procedures are by no means exhaustive and they concern only “excessive” waiting times (rather than the whole waiting times or at least the difference with the United States). However, the CMA found that, for the 2007 (the year they studied), the cost of waiting was equal to 14.8$ billion (CAD).  Given the size of the economy back in 2007, this represented 1.3% of GDP. Again, I must emphasize that this is not an exhaustive measure of the cost of waiting times. However, it does bring Canada closer to the United States in terms of the “true cost” of health care.  Any estimate that would include other wait times would increase that proportion.

I know that policy experts are aware of that, but it is so frequent to see comparisons based on spending to GDP in order to argue for X and Y policy as being relatively cheap.  I just thought it was necessary to remind some people (those who decide to read me) that prudence is mandatory here.

What should universities do?

Rick Weber Culture, Economics, Liberty , , ,

The new semester is here so it’s time for me to figure out what the hell I’m supposed to be doing in the weird world of modern American university life. Roughly speaking, the answer is going to be “do the stuff that professors do to help universities do what universities do.” So what do universities do? What are they supposed to do?

Universities occupy a few different niches in society. I’m usually tempted to think of universities like a business. And in that framework, I justify my salary by providing something of value to those students. At my school, something like 90% of the operating budget comes out of students’ pockets.

But that’s an overly narrow view. Students pay to go to school because they expect they’ll get value from it, but they also go to school because them’s the rules–if you want to enter adult society, university is the front gate. In this framework, I justify my salary by serving as a gatekeeper. Even though it’s students paying, the (nebulous) principal I’m obliged to is the collection of people already inside the walls.

But wait! There’s more! Universities are (in no particular order):

  • A repository of knowledge,
  • A generator of new knowledge,
  • A place people go to learn,
  • A place people go to prove themselves,
  • A place people make friends and have fun (in a way that may be hard to replicate),
  • A business (engaging in mutually beneficial exchange),
  • A special interest group,
  • An institution that holds a particular (privileged) position in a wider cultural landscape.

Any one of these functions is a can of worms in its own right. When we start to consider tradeoffs between each function (and the many less visible functions I’ve surely missed), it gets downright intractable. I’m going to focus on the student-focused aspects of university life.

The mainstream view:

University is a place students get educated. This education helps them get jobs because employers value it. Students might also learn things that help them be better citizens.

The mainstream view doesn’t seem far off from what I’ve got in mind until you get your hands dirty and start disentangling what that view says. Here are three big problems inherent in that mainstream view:

  1. The education-for-job myth.
  2. The definition problem.
  3. The one-size-fits-all problem.

The Job-training myth

We’re told that students go to school to learn valuable skills. I think that’s true, but not in the usual way. Any specific skills students learn in school are a) incredibly general, or b) out of date. My students might learn some interesting ways of looking at the world (general knowledge), but a lot of what I teach is completely useless in the workforce (“Johnson, draw me a demand curve, stat!”). But students do learn valuable skills incidentally. They learn to manage their time (ideally), how to be conscientious, and in general they’re socialized so that they can fit in with adult society.

Lately I’ve been thinking of college as a form of upfront consulting. Instead of going to school when you’ve got a specific problem to solve, go when you’re young and have nothing better to do. Since you’re getting the consulting before you know what sort of problems you’ll face in the future, we couldn’t possibly give you exactly the right bundle of knowledge.

College exposes students to lots of different ideas that might combine in unexpected ways. Your class in underwater basket weaving might seem like a waste of time until some day 30 years later you are trying to solve some problem that turns out to make a lot more sense if you think of it like wet wicker (I’m looking at you civil engineers!).

Some of what I (and my colleagues) do helps prepare students for their careers, but mostly I’m trying to help them be better–better thinkers, better able to understand and appreciate, better able to enjoy life.

The definition problem

The word “Education” means a lot of things to a lot of people. More often than not, people use the word without being clear about what they mean. Often it means “job training.” Sometimes it means “enlightening.” Other times it means “making you agree with me.” In practice, it means surviving enough classes that you get a piece of paper indicating as much.

It should be recognized as a vague and nebulous word instead of being pigeonholed. It isn’t a binary state (I was ignorant, now I’m educated). It’s helpful to think of people as being more or less educated, but the state of your education isn’t something we can really objectively compare to my state of education.

There are lots of important but nebulous things in our lives: health, happiness, moral worth. Their vagueness makes them difficult, but it isn’t going away.

It isn’t hard to convince people that education is nebulous, but it is hard to get people to behave as though they really understand that.

Homogenization and commodification

Once people start thinking of education as some objective thing we can pull off a shelf and give to someone, we run into the real problems. This unexamined view leads to bureaucracies that attempt to standardize and commodify education.

Don’t get me wrong, I get why people would try to do this. We want everyone to get education (and moral training, and good health, and…). And as long as we’re worried about that, we’re going to worry about making sure everyone gets the best education possible. But “the best” gives the false impression that there’s one right answer.

A top-down approach isn’t the right way to achieve the goal of widespread education. Attempting to systematically scale up education provision kills the goose that lays the golden eggs. We should fight against attempts to commodify university (which currently happens via accreditation-as-gateway-to-subsidy and the general expansion of bureaucracy through administration).

So what should universities do?

There are different margins on which we can justify our existence, but it’s not obvious how to balance our tasks: teaching, researching, advocating, etc.. Given the high degree of uncertainty, I’d argue for pluralism… different schools (and professors) should be trying different things. As universities adapt to the future, it’s important that they don’t all try to adapt in the same way at the same time.

I think a big part of the problem is that we’ve been too successful at rent seeking. All money/privilege/goodies comes with strings attached, and more money comes with more strings. We’re always going to get a little tangled up in those strings, but in the last couple generations we’ve hamstrung ourselves. Accreditation and assessment have become the most important things a modern university does, which distracts from our more fundamental goals.

A bottom up approach doesn’t mean less education, just different education. A more modest education system would change the mix of costs and benefits faced by stakeholders. Employers might rely less on degree signalling, which means hiring managers and potential employees exercising more judgement in sending and evaluating quality signals. I don’t know exactly what would happen, but flexibility is valuable for the nebulous goals universities are supposed to be pursuing.

But at the moment we seem to be in an equilibrium. Students are expected to go to school, schools are expected to deliver on promises they can’t really fulfill, and we go through the motions of keeping schools accountable in a way that basically misses the point.

So what will I do this semester? I’m going to keep talking about interesting stuff to students. I’m going to keep working towards getting tenure. But I’m also going to quietly subvert attempts to commodify university.

 

On Monopsony and Legal Surroundings

Vincent Geloso Economics, History , , , , ,

A few days ago, in reply to this December NBER study, David Henderson at EconLog questioned the idea that labor market monopsonies matter to explain sluggish wage growth and rising wage inequality. Like David, I am skeptical of this argument. However, I am skeptical for different reasons.

First, let’s point out that the reasoning behind this story is well established (see notably the work of Alan Manning). Firms with market power over a more or less homogeneous labor force which must assume a disproportionate amount of search costs have every incentive to depress wages. This can lead to reductions in growth as, notably, it discourages human capital formation (see these two papers here and here as examples). As such, I am not as skeptical of “monopsony” as an argument.

However, I am skeptical of “monopsony” as an argument. Well, what I mean is that I am skeptical of considering monopsony without any qualifications regarding institutions. The key condition to an effective monopsony is the existence of barriers (natural and/or legal to mobility). As soon as it is relatively easy to leave a small city for another city, then even a city with a single-employer will have little ability to exert his “market power” (Note: I really hate that word). If you think about it simply through these lenses, then all that matters is the ability to move. All you need to care about are the barriers (legal and/or natural) to mobility (i.e. the chance to defect).

And here’s the thing. I don’t think that natural barriers are a big deal. For example, Price Fishback found that the “company towns” im the 19th century were hardly monopsonies (see here, here, here and here). If natural barriers were not a big deal, they are certainly not a big deal today. As such, I think the action is largely legal. My favorite example is the set of laws adopted following the Emancipation of slaves in the United States which limited the mobility (by limiting the chances of Northerners hiring agents to come who would act as headhunters in the South). That is a legal barrier (see here and here). I am also making that argument regarding the institution of seigneurial tenure in Canada in a working paper that I am reorganizing (see here).

What about today? The best example are housing restrictions? Well, housing construction and zoning regulations basically make the supply of housing quite inelastic. The areas where these regulations are the most severe are also, incidentally, high productivity areas. This has two effects on mobility. The first is that low-productivity workers in low-productivity areas cannot easily afford to move to the high-productivity area. As such, you are reducing their options of defection and increasing the likelihood that they will not look. You are also reducing the pool of places to apply which means that, in order to find a more remunerative job, they must search longer and harder (i.e. you are increasing their search costs). The second effect is that you are also tying workers to the areas they are in. True, they gain because the productivity becomes capitalized in the potential rent from selling any property they own. However, they are in essence tied to the place. As such, they can be more easily mistreated by employers.

These are only examples. I am sure I could extend the list to reach the size of the fiscal code (well, maybe not that much). The point is that “monopsony” (to the extent that it exists) is merely a symptom of other policies that either increase search costs for workers or reduce the number of options for defections. And I do not care much for analyzing symptoms.

Paul Romer, the World Bank and Angus Deaton’s critique of effective altruism

Nick Cowen Current Events, Economics , , , , , ,

220px-Paul_Romer_in_2005

Last week Paul Romer crashed out of his position as Chief Economist at the World Bank. He had already been isolated from the rest of the World Bank’s researchers for criticizing the reliability of their data. It seems there were several bones of contention, including the accusation that Chile’s current social democratic government falsified data contributing to some of its development indicators. Romer’s allergic reaction to the World Bank’s internal research processes has wider implications for how we think about policy research in international NGOs.

Continue reading →

In the Search for an Optimal Level of Inequality

Federico Sosa Valle Economics, Philosophy , , , , , , , ,

Recently, the blog ThinkMarkets published a post by Gunther Schnabl about how Friedrich Hayek’s works helped to understand the link between Quantitative Easing and political unrest. The piece of writing summarized with praiseworthy precision three different stages of Friedrich Hayek’s economic and political ideas and, among the many topics it addressed, it was mentioned the increasing level of income and wealth inequality that a policy of low rates of interest might bring about.

It is well-known that Friedrich Hayek owes the Swedish School as much as he does the Austrian School on his ideas about money and capital. In fact, he borrows the distinction between natural and market interest rates from Knut Wicksell. The early writings of F.A. Hayek state that disequilibrium and crisis are caused by a market interest rate that is below the natural interest rate. There is no necessity of a Central Bank to arrive at such a situation: the credit creation of the banking system or a sudden change of the expectancies of the public could set the market interest rate well below the natural interest rate and, thus, lead to what Hayek and Nicholas Kaldor called “the Concertina Effect.”

At this point we must formulate a disclaimer: Friedrich Hayek’s theory of money and capital was so controversial and subject to so many regrets by his early supporters – like said Kaldor, Ronald Coase, or Lionel Robbins – that we can hardly carry on without reaching a previous theoretical settlement over the apportations of his works. Until then, the readings on Hayek’s economics will have mostly a heuristic and inspirational value. They will be an starting point from where to spring new insights, but hardly a single conclusive statement. Hayekian economics is a whole realm to be conquered, but precisely, the most of this quest still remains undone.

For example, if we assume – as it does the said post – that ultra-loose monetary policy enlarges inequality and engenders political instability, then we are bound to find a monetary policy that delivers, or at least does not avoid, an optimal level of inequality. As it is explained in the linked lecture, the definition of such a concept might differ whether it depends on an economic or a political or a moral perspective.

Here is where I think the works of F.A. Hayek have still so much to give to our inquiries: the matter is not where to place an optimal level of inequality, but to discover the conditions under which a certain level of inequality appears to us as legitimate, or at least tolerable. This is not a subject about quantities, but about qualities. Our mission is to discover the mechanism by which the notions of fairness, justice, or even order are formed in our beliefs.

Perhaps that is the deep meaning of the order or equilibrium that it is reach when, to use the terminology of Wicksell and Hayek’s early writings, both natural and market interest rates are the same: a state of affairs in which the most of the expectancies of the agents could prove correct. The solution does not depend upon a particular public policy, but on providing an abstract institutional structure in which each individual decision could profit the most from the spontaneous order of human interaction.

SMP: The Macro Bifurcation

Nicolas Cachanosky Economics, Links , , , ,

One of the major issues in contemporary macroeconomics concerns monetary policy since the 2008 crisis. For many, if not most, of the major central banks, the conventional channels through which the money supply changes do not work anymore. For instance, by paying interest on reserves, the Federal Reserve has moved from adjusting the money supply to influencing the banks’ money demand. Some central banks have even maintained that money supply does not affect inflation anymore.

Continue reading at the Sound Money Project.

Can you manage what you can’t measure?

Rick Weber Economics, Liberty , ,

Disclaimer: I’m not a macroeconomist, but I play one in Principles classes. Feel free to point out my errors in the comments.

Economics is filled with imperfect measures of important concepts. GDP, unemployment rates, and price indices all have significant flaws. Measures of entrepreneurship are even worse.

The Chicago Booth IGM Experts’ Panel recently posted an interesting result about the problems with unemployment:

IGMChicago_EmploymentandtheUSEconomy

The question is: “The concept of “maximum sustainable employment” is well defined enough to be used beneficially in economic policymaking.”

That’s 42 economists asked, 34 with an opinion (including “uncertain”), and about half of the sentiment is positive. And that sounds about right to me. I read this question as “can we engage in macroeconomic policy that doesn’t do long-run harm?” And if I were to describe my opinion probabilistic, it would look like these results. We could probably do “good policy” with a low degree of precision (i.e. useful enough for severe situations) if 1) we magically didn’t have to deal with political squabbling and 2) explicitly limited our goals to the short run.

Respondents agreeing emphasize that it’s “good enough.” But what does that mean? What level of precision and control are we looking at here?

Here’s the basic situation: given the underlying economic reality (everyone’s individual preferences, capabilities, knowledge, etc.) it makes sense to have some limited number of unemployed people at any given time. Unemployment rate is a measure of “how far are we from 0,” not, “how far are we from the ideal level?” That raises the following questions:

  • How accurately can we know what’s going on in the world?
  • How accurately can we know what’s supposed to be going on in the world?
  • How precisely can we affect the world?

The aggregate macroeconomic theory and empirics of the 1960’s were seriously imprecise. Trying to target macroeconomic policy would be like doing eye surgery with a hand grenade. In that sort of world, your best medicine is probably chicken soup and bed rest.

Here in the present we have much better data and computation. And it’s going to get better. Facebook already has data precise enough to track the exact effects of policy down to the individual level.

But think about a precise outcome and imagine what sort of policy would be required to get there. Let’s say our outcome is “get Rick to buy a new car.” Some mix of low interest rates, the right set of subsidies, and ideal circumstances might move things in that direction. But that sort of surgical outcome is just never going to be possible through legitimate macroeconomic policy (and definitely not monetary policy*). The size of the problem just means that Butterfly Effect problems will prevent macroeconomic policy from having household-level precision, even if the data could (in principle) measure the effect.

Less precise outcomes seem plausible (e.g. “get middle class households in the north east to buy 30-60,000 new cars”), but not without making a lot of second order problems. It’s not so much a “middle of the road leads to socialism” situation as a multiplier effect from a convergent series. Push a billion over there, create big distortions, follow those up with medium distortions, and finally let small remaining problems fizzle out on their own. Throw in public choice issues and it seems obvious that the efficiency cost of precise interventions won’t scale up nicely.

We’re now in a world where our theoretical and empirical tools are more precise than our implementation tools. We’re no longer trying to do surgery with a hand grenade. But that doesn’t mean we’ve got a laser scalpel either. It’s more like we’ve got we’ve got laser-like measuring tools but our implementation tools are blunt objects. If we aren’t careful, we’ll spend our time swatting flies with sledge hammers.

All told, it seems possible that we could engage in fairly targeted macroeconomic policy. But as the scale increases, the marginal cost will rise rapidly (maybe less so with the right institutions). Better timing might increase the effectiveness of each dollar spent*, but overall, it seems like things have to be really bad before the government should consider anything too ambitious.

Manage an economy’s economic health using imperfect measures like unemployment rate is about like trying to manage your physical health using heart rate and body mass index figures. Can we do “good enough”? Only to a limited extent. We could stop eating garbage and get some exercise. But there isn’t some magic combination of vitamins and crystals that will stop cancer. Anyone who tells you otherwise is a) trying to sell you something and b) trying to convince themselves they’re in control of the uncontrollable.

In terms of macroeconomic policy, we should start by caring about fundamentals (i.e. long run economic development) and be skeptical of people promising to control the business cycle.

*And let’s face it, we aren’t likely to get decent macroeconomic policy (in terms of efficiency, timing, and appropriateness of policy to circumstances) out of Congress until there’s a serious cultural shift.

The Dictator’s Handbook

Rick Weber Books, Economics, Liberty , , , , , , ,

I recently pointed you towards a book that has turned out to be a compelling and interesting read.

At the end of the day, it’s a straightforward application of public choice theory and evolutionary thinking to questions of power. Easy to understand theory is bundled with data and anecdotes* to elucidate the incentives facing dictators, democrats, executives, and public administrators. The differences between them are not discrete: they all face the same basic problem of compelling others’ behavior while facing some threat of replacement.

Nobody rules alone, so staying in power means keeping the right people happy and/or afraid. All leaders are constrained by their underlings. These underlings are necessary to get anything done, but they’re also potential rivals. For Bueno de Mesquita and Smith the crucial facts of a political order are a) how big a coalition (how many underlings) the ruler is beholden too and b) how replaceable the members of that coalition are.

The difference between liberal and illiberal orders boil down to differences in those two parameters. In democracies with a larger coalition and less replaceable coalition members, rulers behave better.

 

I got a Calculus of Consent flavor from Dictator’s Handbook. At the end of the day, collective decision making will reflect some version of “the will of the people… who matter.” But when we ask about the number of people who matter, we run into C of C thinking. Calling for bigger coalitions is another way of calling for an approach to an effective unanimity rule (at least at the constitutional stage).

In C of C the question of the optimal voting rule (majority vs. super majority vs. unanimity) boils down to a tradeoff between the costs of organizing and the costs of externalities imposed by the ruling coalition. On the graph below (from C of C) we’re comparing organization costs (J) against externality costs (I) (the net costs of the winning coalition’s inefficient policies). The idea is that a unanimity rule would prevent tyranny of the majority (i.e. I is downward sloping), but that doesn’t mean unanimity is the optimal voting rule.

Figure 18. Click to open in new window.

But instead of asking “what’s efficient” let’s think think about what we can afford out of society’s production, then ask who makes what decisions. In a loose sense, we can think of a horizontal line on the graph above representing our level of wealth. If we** aren’t wealthy enough to organize, then the elites rule and maximize rent extraction. We can’t get far up J, so whichever coalition is able to rule imposes external costs at a high level on I.

But I‘s height is a function of rent extraction. Rulers face the classic conundrum of whether to take a smaller piece of a larger pie.

The book confirms what we already know: when one group can make decisions about what other groups can or must do, expect a negative sum game. But by throwing in evolutionary thinking it shed light on why we see neither an inexorable march of progress nor universal tyranny and misery.

As you travel back in time, people (on average) tend to look more ignorant, cruel, and superstitious. The “default state” of humanity is poverty and ignorance. The key to understanding economics is realizing that we’ve bootstrapped ourselves out of that position and we aren’t done yet.

The Dictator’s Handbook helped me realize that I’d been forgetting that the “default state” of political power is rule by force. The liberalization we’ve seen over the last 500 years has been just the first part of a bootstrapping process.

Understanding the starting point makes it clear that more inclusive systems use ideas, institutions, capital, and technology to abstract upward to more complex levels. Something like martial honor scales up the exercise of power from the tribe (who can The Chief beat up) to the fiefdom (now the Chief has sub-chiefs). Ideology and identity can tie fiefdoms into nation-states (now we’ve got a king and nobility). Wealth plus new ideologies create more inclusive and democratic political orders (now we’ve got a president and political parties). But each stage is built on the foundation set before. We stand on the shoulders of giants, but those giants were propped up by the non-giants around them.

Our world was built by backwards savages. The good news is that we can use the flimsier parts of the social structure we inherited as scaffolding for something better (while maintaining the really good stuff). What exactly this means is the tricky question. Which rules, traditions, organizations, and processes are worth keeping? How do we maintain those? How/when do we replace the rest? And what does “we” even mean?

Changing the world involves uncertainty. There are complex interrelations between every part of reality. And the knowledge society needs is scattered through many different minds. To make society better, we need buy-in from our neighbors (nobody rules alone). And we need to realize that the force we exert will be countered by an equal and opposite force some plural, imperfectly identifiable, maybe-but-probably-not equal, and only-mostly-opposite forces. There are complex and constantly shifting balances between different coalitions vying for power and the non-coalitions that might suddenly spring into action if conditions are right. Understanding the forces at play helps us see the constraints to political change.

And there’s good news: it is possible to create a ruling coalition that is more inclusive. The conditions have to be right. But at least some of those conditions are malleable. If we can sell people on the right ideas, we can push the world in the right direction. But we have to work at it, because there are plenty of people pitching ideas that will concentrate power and create illiberal outcomes.

*I read the audiobook, so I’m basically unable to vouch for the data analysis. Everything they said matched the arguments they were making, but without seeing it laid out on the page I couldn’t tell you whether what they left out was reasonable.

**Whatever that means…

SMP: The War on Cash: What Do You Have to Hide?

Nicolas Cachanosky Economics, Links , , ,

The war on cash we see starting to take place in recent times has a dangerous component. Besides the technical arguments in favor (and against) the efficiency gains of a cash-less economy, politicians are putting forward the argument that only those who have something to hide would oppose to a cash-less economy.

The problem is that this rhetoric implies that any individual is guilty of something until proven innocent. The presumption of innocence, one of the most basic principles of a free society, is being dangerously inverted.

Some economists, including Harvard’s Ken Rogoff, want to minimize the circulation of cash. Such proposals are usually justified on the grounds that they would (1) reduce criminal activity and tax evasion while also (2) helping central banks execute monetary policy when interest rates are at the zero lower bound. Both arguments have been challenged on this blog (here, here, and here).

Continue reading at SMP.

SMP: Separating the Technology of Bitcoin from the Medium of Exchange

Nicolas Cachanosky Economics , , , ,

At the Sound Money Project I have a comment on the importance of distinguishing between the bitcoin technological innovation and its use as a means of exchange. A solid technological innovation does meant that bitcoin is necessarily properly coded to be a successful monetary experiment.

Bitcoin is back in the spotlight as its price has soared in recent weeks. The most enthusiastic advocates see its potential to become a major private currency. But it is important to remember bitcoin is a dual phenomenon: a technological innovation and a potentially useful medium of exchange. One might recognize the technology as a genuine innovation without accepting its usefulness as a medium of exchange.

Continue reading at SMP.