Sexism in the National Accounts, QOTD

Since 1953, the United Nations has published an influential set of standards for national income statistics called the System of National Accounts (SNA). In the 1970s and 1980s, these statistics came under assault for ignoring women’s work, culminating in the influential critique of Marilyn Waring, If Women Counted published in 1988. (Edit: Specifically, the statistics were criticized for treating differently unpaid/non-market work performed by men from that of women. Much of men’s work was argued to be worth trying to estimate a value for even though no price was directly paid for it, while women’s work was simply left out.) What I would not have guessed is how much those critiques had already been internalized by the experts working in the UN. Among the papers of Richard Stone (lead author of the original 1953 SNA), I found this gem from a 1982 United Nations expert paper laying out an agenda for revising the SNA:

To a considerable degree, the [UN] Blue Book’s borderline between subsistence output, to be included in production and consumption, and household activity, to be excluded, reflects a sexist view that is gradually changing. Subsistence activities, for the most part, are male activities; household activities are female ones. Thus winemaking is included, cooking is not; caring for animals is, caring for children is not; and communal volunteer projects like road building and similar activities are, but those of women’s groups running volunteer community service programs like libraries health services, and school services are not. This disparity in treatment should be remedied.

And yet to present, 30 years later, not that much has changed. What went wrong? The report’s next paragraph offers some insight:

The problems of valuation are more difficult, however, for the kinds of non-market activity not now included in the SNA. In order to value household activity, for instance, it is necessary to decide whether to use the opportunity cost of the housewife in the labour market or the cost of hiring comparable household services o the market. For analyzing resource allocation an opportunity cost valuation might be appropriate, but for measuring consumption of household services, a market valuation might be better.

As I’ve argued elsewhere, from the 1920s to present, the objections to including housework have very rarely been on the principled ground that housework shouldn’t count but rather on the (seemingly) practical objection that valuing it is very hard. And yet, the end result is the same – housework remains (largely) uncounted (in official national accounts).

On the Origins of the Kuznets Curve

Today, I’m blogging from the Harvard University Archives. I’m five boxes deep into the Simon Kuznets collection, for my second visit related to my dissertation research. I just came across a letter that, while not especially important to my dissertation, seemed like it might be of wider use to anyone interested in the history of the “Kuznets Curve.” Simon Kuznets, in addition to spearheading the first official US national income statistics in 1932-1934, is probably most famous for this curve/hypothesis.* In his presidential address to the American Economics Association in December of 1954, later published as Economic Growth and Income Inequality, Kuznets argued that income inequality and economic growth might have an inverted-U shaped relationship. That is, as economic growth/development increases, inequality first goes up and then comes back down.

Kuznets based this empirical story on a few decades worth of data from the US and UK, and asserted in the conclusion that: “The paper is perhaps 5 per cent empirical information and 95 per cent speculation, some of it possibly tainted by wishful thinking.” (1955: 26) Since 1955, the paper has generated an entire literature asking whether or not the curve is real, whether it’s reversed in the past 30 years to create a new pattern, and so on. Much of the early research supporting the Kuznets curve came from cross-national studies which mapped inequality against current GDP/capita and showed the expected inverted-U shaped relationship. These studies, like Kuznets’, lacked longitudinal data. The recent consensus seems to be that the Kuznets curve does not hold within countries (e.g. Gallup 2012). That is, within a particular country, the relationship between economic growth and income inequality does not follow the expected path. Here are two graphs from Gallup 2012 that help sell the argument. The first is the relationship between log income and inequality, which looks like a Kuznets curve (though as Gallup notes, the fit is not quadratic for unlogged data):
Gallup 2012 Figure 3

The second is the author’s estimates of within-country income inequality trajectories (each line is one country). Note the chaos, and the absence of any coherent story, with some tendency towards a U-shape (not a upside-down U!):
Gallup 2012 Figure 8

Gallup further notes that Kuznets’ original data only had half of the original story. Yes, Kuznets shows a decrease in inequality in the US and UK in the late 19th century to post-WWII period. But Kuznets has no data on the initial upsurge in inequality! That is, Kuznets only has the falling half of the curve. Gallup graphs Kuznets’ income inequality data against historical gdp data now available from the work of Angus Madison to give some sense of what Kuznets was seeing:
Gallup 2012 Figure 1
Gallup (2012: 6) summarizes:

Kuznets showed that inequality fell in two high-income countries as they grew richer after World War I, but he had no evidence of rising inequality at low income levels. Ironically, Kuznets’ prediction that inequality will rise during the early stages of development, for which he had no evidence, is better remembered than his prediction that inequality will fall at higher incomes.

What did Kuznets have, if not data? He had a model. Specifically, Kuznets motivated his proposed empirical story (rising then falling inequality) with a two sector model of income inequality. Kuznets argued that agricultural incomes were likely as or more equal than industrial/urban incomes, but industrial incomes were much higher on average. Thus, as workers moved from agricultural to industrial labor, inequality would increase (low agricultural wages to higher industrial wages), until so few workers were in agriculture that a tipping point was reached and inequality came back down. This story falls apart, however, if agricultural incomes in the pre-development period are actually more unequal than industrial ones, because “if agricultural incomes are more unequal than industrial wages, perhaps due to unequal land ownership, movement out of agriculture into industry could reduce inequality right away.” (Gallup 2012: 7)

Ok, so why did Kuznets think that agricultural incomes were more equal than industrial ones? An archival document I just perused before starting this post sheds some light on the answer: Kuznets had some intuitions backed by absolutely no data. Data on income distribution are still poor now, and were even worse back in the 1950s, with historical data being extremely limited to a handful of studies (some conducted by Kuznets himself). These studies did not readily break incomes down by urban/rural or industrial/agricultural divides. Kuznets wrote to one of his collaborators, Selma Goldsmith (then at the Office of Business Economics, what is now the Bureau of Economic Analysis) to ask about the data she had been working on to produce official income distribution data for the United States (see, e.g., Goldsmith et al. 1954). In a letter dated August 15, 1954, Kuznets writes about his current work on economic growth and income inequality:

In my model, I somehow began with the assumption that inequality within the ag. sector is lesser than within the non-ag—although I had no evidence whatsoever. … the distributions that are available (in your D. of C. publication and elsewhere) show inequality among the ag. group (i.e. farm operator families) to be greater than among the non-ag—certainly in recent years. … Yet one would expect that with the much wider range of income opportunities in the non-ag sector, the inequality in size distribution would be appreciably wider in the latter. … Do you have any explanation for it?**

Let’s just stress that again: Kuznets had absolutely no evidence that inequality within the agricultural sector was less than the industrial one. Kuznets guesses that this discrepancy between his theoretical intuition and the data has something to do with the data not quite matching what they want – there’s higher year-to-year variability in farm incomes, but in the long-run the inequality within families might be less than appears in the data, or something like that. He’s not sure. And that uncertainty, among many others, is reflected in his strong caveats at the end of presidential address.

Years later, Kuznets himself would abandon the curve and caution against looking for historical laws of development, especially in cross-sectional data (Moran 2005). And yet the debate over it lives on, as does the search for laws of economic growth and development.

*In 1971, Kuznets won the Nobel Prize in economics, “for his empirically founded interpretation of economic growth which has led to new and deepened insight into the economic and social structure and process of development.”
**Papers of Simon Kuznets, Harvard University Archives, HUGFP88.10 Misc. Correspondence, Box 4.

Making Up Numbers About Money: An Up-Goer Five Study

Some of you have likely seen the amazing comic where former NASA employee Randall Munroe explains the Saturn V rocket using only the one thousand most common English words: Up-Goer Five.* This turned out to be so much fun, Since then, the game of explaining research using basic words has taken off, aided by the Up-Goer Five Text Editor. In that spirit, here’s an attempt at a dissertation title and abstract based on my own work.

Making Up Numbers About Money

I study how people think about money. I am really interested in why we think about money the way we do now, and how the way we think now is so different from how we used to think about money. Before, we didn’t have so many numbers to use for thinking about money, but now we have all sorts of numbers. We pay a lot of attention to some of these numbers, but only a little attention to others. I want to know why we focus on these numbers and not others, and what changed because we focus on these numbers.

*Notably, Dr. Seuss did something similar to write “The Cat in the Hat,” but with just 225 common words.

On the Limits of Presidential Power: FDR and Glass-Steagall

Matt Taibbi, rockstar financial journalist, has a new lengthy piece in Rolling Stone on How Wall Street Killed Financial Reform. I highly recommend the article, which covers strategies used by big banks to fight the implementation of the Dodd-Frank act. But, I also want to quibble with one of the arguments Taibbi – and many others – make about the act’s historical analog, the Glass-Steagall Act of 1933.

Both acts were passed in the wake of major financial crises, by majority parties swept into office by the fallout from those crises. Glass-Steagall famously separated commercial and investment banks, created deposit insurance (the FDIC), and capped interest rates on deposits (Regulation Q), among other things. Dodd-Frank’s goals were more modest, in some ways, but included the Volcker rule which prohibits banks from engaging in proprietary trading (somewhat analogous to the separation of commercial and investment banks) and requirements that derivatives be traded on market exchanges when possible (most derivatives were “over the counter” (OTC) before the act, and thus very difficult to make sense of and regulate). And, indeed, Glass-Steagall was frequently mobilized in the past few years as an explicit marker of what used to be great about American financial regulation and thus what needs to be recovered.

Taibbi mentions Glass-Steagall (GS) as well, in order to argue that Dodd-Frank (DF) started out weaker than GS, and thus was easier for banks to delay and evade. I agree in general, but I want to contest one part of Taibbi’s characterization of the history of GS:

In fact, Obama’s initial response to the devastating financial events of 2008 represented a major departure from the historical precedent his own party had set during the 1930s, when President Franklin D. Roosevelt launched an audacious rewrite of the rules governing the American economy following the Great Crash of 1929.

Upon entering office, FDR was in exactly the same position Obama found himself in after his inauguration in 2009. Then, as now, the American economy was in tatters after the bursting of a massive financial bubble, brought on when speculators borrowed huge sums and gambled on unregistered securities in largely unregulated exchanges. This mania for instant riches led to an explosion of Wall Street fraud and manipulation, creating a mountain of illusory growth divorced from the real-world economy: Of the $50 billion in securities sold in America in the 1920s, half turned out to be worthless.

Roosevelt’s response to all of this was to pass a number of sweeping new laws that focused on a single theme: protecting consumers by forcing the business of Wall Street into the light. The Securities Act of 1933 required all publicly traded companies to register themselves and offer prospectuses to investors; the Securities Exchange Act of 1934 forced publicly traded companies to make regular financial disclosures; and the Commodity Exchange Act of 1936 required all commodities and futures to be traded on organized exchanges. FDR also created the FDIC to protect bank depositors (through an insurance fund paid for by the banks themselves) and passed the Glass-Steagall Act to separate insurance companies, investment banks and commercial banks. Post-New Deal, if you put money in a bank, you knew it was safe, and if you bought stock, you knew what you were buying.

Ok, here’s my problem with this narrative: Roosevelt didn’t do it! Well, FDR did in fact sign each of these laws into existence. But FDR was not the driving force behind them. As co-author Russ Funk and I discuss in our history of the rise and fall of Glass-Steagall (working paper available here), pressure to pass financial regulation preceded FDR taking office. Senator Glass and Representative Steagall were both working on financial reform bills in the early 1930s, without much success. The Pecora commission investigations into Wall St. shenanigans created public outcry and helped push for specific provisions which ended up in the act. FDR, in fact, was on the record against the creation of deposit insurance, as he thought it was an overreach of federal regulation. Here’s how we put it in the paper:

In light of the Pecora Commission’s findings, Congress passed the Banking Act of 1933 in June. The law merged Congressman Steagall’s deposit insurance bill with Senator Glass’s bill separating commercial and investment banking, and thus is commonly known as the GlassSteagall Act of 1933. Roosevelt somewhat reluctantly signed the bill into law; he was concerned that deposit insurance was an overreach, and he had only lukewarm support for the separation of commercial and investment banking (Perkins 1971: 524). Thus, although the Glass-Steagall Act is commonly included in lists of Roosevelt’s New Deal accomplishments, his own role was quite minimal: both major components of the law were proposed before he took office, and Roosevelt simply allowed them to enter into law. (Funk and Hirschman 2012: 20)

Why does it matter that Congress, not FDR, provided the momentum for Glass-Steagall? For one, I think it reminds us of the importance of Congress in making and enforcing the rules. Democrats controlled Congress in 1933 when Glass-Steagall was passed, but they continued to control it well past the law’s implementations – for more than the next decade, in fact. In contrast, Democrats lost control of the House before Dodd-Frank was implemented. As Russ and I describe in our paper, and as political scientists have long known, the process of regulation is a slow and gritty one. New regulations take time to implement, and always have holes. Over time, these holes accumulate as businesses invent new practices and products (one field’s “innovation” is another field’s “policy drift”). Thus, continued control of Congress, and interest by legislators, is required to patch up the gaps, fund regulatory agencies, and so on. The President can’t do that alone.

For another, I think it also reminds us that the presidency has changed in the past 80 years. We tend to read back into history the modern executive, with their immense power. And that’s just bad history. FDR played a not insignificant role in the expansion of federal authority, and of executive power. But that’s a story that continues to present. The more we talk about “FDR did this” and “Obama should do this,” the more we naturalize the current power of the president as an inherent feature of the system. That makes for bad history, and also tends to foreclose discussions of the future. What can wax can also wane.

To reiterate, Taibbi’s article is a fantastic window into the strategies of big banks to stall the implementation of Dodd-Frank and repeal major provisions. And elsewhere, Taibbi does a fantastic job of showing the importance of Congress – for example, reminding us that they control the budget for key regulators like the CFTC. But I think the article would have been slightly stronger with just a bit more attention to the history of Glass-Steagall and the importance of Congress in its passage.

On the Difference Between GNP and GDP

One of the most common questions I am asked about my research is “Why did we switch from GNP to GDP? What difference did that switch make?” In this post, I sketch a quick and partial answer. First, I define GNP and GDP. Second, I note the historical emergence of GNP. Third, drawing on McNeely’s (1995) UN data, I show that the switch from GNP to GDP occurred in the international context in the late 1960s. Fourth, I report on the moment in which the United States switched (the 1990s) and the stated justifications for so doing. Fifth, I note that there has been a recent move to reconsider the choice of principal aggregate for analysis, as evidenced by the switch to GNI (Gross National Income) in the newest iteration of the UN Human Development Indicator (HDI). Sixth, I present my own analysis of Penn World Tables data to show the geographic distribution of divergent trajectories of GNP and GDP – that is, those countries in which the difference between the two aggregates varies most. Last, I reflect on the significance of the geographical distribution of GNP-GDP discrepancies and, in particular, how it showcases the limitations of relying on any single measure of national income, welfare, or “size of the economy.”

Google Scholar Scraper?

Dear Readers,

Does anyone have a good scraper for Google Scholar that they would be willing to share (or point me to)? I’m looking for something simple – input a search string (including a “cited by” search) and capture basic metadata (author, title, publication, year) of the results.


Partisan Perceptions in Economic Polling Data

SocImages has an excellent post today about perceptions of the economy based on an April, 2011 Gallup poll. Some of the interesting findings:

  • [M]ore than half of respondents said the U.S. is in either a recession or a depression, that’s down significantly from the 69% who said so in late 2008, while the 27% who said the economy is growing is an enormous jump compared to the mere 3% who thought it was in September 2008 …

  • [T]hose making less than $30,000 a year had a notably more negative outlook on the economy than those with higher incomes. Not only were they more likely to think the economy is doing poorly, but nearly half thought we’re experiencing a depression — twice as high as the proportion of those making $75,000/year who thought so.
  • The most interesting finding, to me, concerns the partisan split in perceptions of the economy. Here’s the results table, borrowed from SocImages:

    So, the main finding is that three times as many Dems as Reps think the economy is growing (42% vs. 14%) while 68% of Reps think we’re in a recession/depression vs. 43% of Dems. With access to cross-tabs, we could figure out quickly if the gap in perceptions by income and by party ID gap are connected – Republicans not actually being the party of the rich (in terms of voters, at least), it’s possible that the two are the same thing. But the gap by party is actually larger than the one by income, so that seems unlikely to explain everything. Suppose there remains a consistent partisan gap. Why?

    I wonder if part of the answer has to do with the context of the modern public opinion poll, especially as conducted by Gallup. For more than 70 years, Gallup has been associated with presidential polls (see Sarah Igo’s The Averaged American on the history of the Gallup poll). Polling and politics have become almost synonymous – academics refer to their tools as surveys, politicos deal in polls, and there is even linguistic conflation between elections and surveys (the Iowa Straw Poll vs. the Gallup Poll). All this to say, I wonder if the polling context is one that is already politically primed, and specifically primed to presidential politics. If that were the case, we would predict that Democrats and Republicans would give much more similar answers if asked in face to face contexts, or in say a psychology experiment, when not primed with any overtly partisan information, than they would in a poll, even if the poll never asked about politics (which of course these polls did, though I don’t have the question ordering in front of me).

    That would of course still be a fascinating finding, but it would mostly be a finding about the politicization of public opinion, and not as much as one about the way Americans “really” see the economy. An equally plausible, and interesting, finding would be that the economy itself has such a political valence that all our feelings towards it are tinted by the current political climate – because I’m a Dem and a Dem is president, the economy must be doing better than I would otherwise think (or vice versa). A way to test that explanation would be to compare questions about the assessment of the economy as a whole to more targeted questions – how is your family doing? How hard would it be for you to get a new job? Etc.

    By the way, if anyone wants to hunt for the data and run these analyses, I’ll gladly post them here. Or if anyone can think of other consequences of the thesis that polls are always already politicized that could be easily tested in the data, or knows of good existing research on the subject, please write a comment!

    Fair and Balanced? The GOP, the GDP and the Budget

    If you’ve been following the debates over the current federal budget*, you might have caught a little maneuver of the Republican members of the Senate: introducing another Balanced Budget constitutional amendment. The full text is available here. Bruce Bartlett calls it the “Dopiest Constitutional Amendment of All Time” and for good reason. The proposed amendment has two main forms of limitation on federal expenditures:

    SECTION 1. Total outlays for any fiscal year shall not exceed total receipts for that fiscal year, unless two-thirds of the duly chosen and sworn Members of each House of Congress shall provide by law for a specific excess of outlays over receipts by a roll call vote.

    SECTION 2. Total outlays for any fiscal year shall not exceed 18 percent of the gross domestic product of the United States for the calendar year ending before the beginning of such fiscal year, unless two-thirds of the duly chosen and sworn Members of each House of Congress shall provide by law for a specific amount in excess of such 18 percent by a roll call vote.

    The first part is classic balanced budget – limit expenditures to revenues. It’s silly for a lot of reasons, mainly the fact that government ought to be really good at spending countercyclically, since a lot of things that make revenue go down also make expenditures go up, e.g. when unemployment rises, tax revenues fall and benefits paid out go up. These sorts of increases in expenditures and decreases in revenue when the economy suffers are known as “automatic stabilizers” and are generally believed to be a good thing – when most people are not spending money, the government spends more, without anyone having to see it coming and pass a special bill. Automatic stabilizers were much smaller or non-existent 100 years ago, and there are arguments that our economy is much more stable because of them. Beyond that, a lot of these programs have the flavor of insurance, and in general I’m a big fan of the government providing insurance for the poor (a role that is under direct assault, and has been for years, in what Hacker calls “the great risk shift“.) So, a balanced budget, if actually balanced by year-to-year revenue, would have to somehow stop this automatic stabilizer business.

    That’s all old news. What’s fascinating about this proposal, to me and to Bartlett, is the attempt to limit government’s size by capping expenditures at 18% of GDP of the previous year. Bartlett’s take is interesting and coincides with mine, though he is much more shrill:

    Right at the moment, we think GDP was $14,657.8 billion in 2010, so that means that outays in FY2012 could not be more than $2,638.4 billion. But GDP generally rises over time. The CBO expects that calendar year 2012 GDP will be $15,858 billion. Assuming that Congress was somehow or other able to meet its spending target of $2,638.4 billion, that would equal just 16.6 percent of calendar 2012 GDP. The same thing would happen year after year, forcing down spending as a share of GDP under the guise of balancing the budget.

    I won’t repeat all of my previous criticisms of the balanced budget amendment that can be found in the links. But let me discuss one other thing. The gross domestic product is not a concept defined in law and is revised constantly; from time to time, the Bureau of Economic Analysis revises the GDP data all the way back to 1929. And of course, the 18 percent figure is totally arbitrary; the proposal effectively assumes that all federal outlays consist of funds that are appropriated annually, rather than consisting primarily of mandatory programs such as Social Security, Medicare and interest on the debt. Even if Congress was willing to cut mandatory spending, it is practically impossible to do so quickly unless it is willing to reduce the monthly checks going to current retirees and other actions difficult to contemplate.

    In short, this is quite possibly the stupidest constitutional amendment I think I have ever seen. It looks like it was drafted by a couple of interns on the back of a napkin. Every senator cosponsoring this POS should be ashamed of themselves.

    The key part for me is, of course, that the GDP is not a legal concept, but rather a constantly shimmering** data series generated by the Bureau of Economic Analysis. Near the end, the amendment suggests that: “The Congress shall have power to enforce and implement this article by appropriate legislation, which may rely on estimates of outlays, receipts, and gross domestic product.” That’s a nice addition, because all measures of gross domestic product are estimates. We have reason to think they are really good estimates, given the definitions we currently choose to employ and the data we have available, but they are still estimates. And there are thorny conceptual debates still only partially resolved at the heart of GDP calculations, about the nature of income and wealth (e.g. what counts as final production vs. an intermediate product), about the timing of production, about the relevant boundaries (which should be counted, e.g. unpaid housework), and about how to deal with environmental damages. Almost undoubtedly, economists and statisticians will push for changes to the current system, and that will probably be for the best. 90 years ago, we didn’t think much about the environment impacts of economic growth, now (especially with the looming climate crisis) we do, and hopefully someday our measures of development will factor those costs in. By keying something as huge as the Federal budget to these statistical estimates, the Republicans would ensure the overt politicization of these data as politicians suddenly became legally bound to a concept whose borders they could attempt to influence.

    Of course, this amendment will never be ratified, so perhaps the details are not entirely important. What this proposal signifies to me, though, is that we take very much for granted that we have something called an economy which is measured by something called gross domestic product, and that both of those things are uncontroversial enough that you could imagine fixing important decisions to them. How that came to be is what I’m studying right now. I’ll let you know what I find.

    * Hard to avoid here on my trip to DC, since tons of people will be out of work if there’s a shutdown, and since everyone is just a bit more into talking politics.
    ** Shimmering data is a concept borrowed from Paul Edwards, who uses it to refer to global climate data, which are constantly being updated as we incorporate new bits of information about past periods or make adjustments to our data models. See Edwards’ A Vast Machine for more. In this case, not only are the data shimmering, the definitions are quite open for debate – I believe this is considerably less true in the case of global temperature data, for example. So, some of the shimmering involves redefining the concept being measured, not just mapping from the historical record to the (stable) concept differently.

    Polanyi Was Right About Adam Smith and the Invisible Hand

    I’m currently reading through some of Karl Polanyi’s less famous works. I had always thought Polanyi was not a fan of Adam Smith based on his amazing, “Oh, Snap!” worthy comment in The Great Transformation. Polanyi argues that Smith was wrong about the nautralness of the motivation to “truck, barter, and exchange” and that for most of human history, trucking, bartering and exchanging are nowhere to be found. Polanyi then memorably says of Smith, “In retrospect it can be said that no misreading of the past ever proved more prophetic of the future.” (GT 45) So, Smith was utterly wrong about the 18th century and before, but prescient about the 19th century. Overall, not so positive, especially from someone like Polanyi who is so concerned with creating useful theories of economic life that make sense in different times and places.

    In “The Place of Economies in Societies”, Polanyi shows a bit more love to Smith. More specifically, in the previously unpublished lecture notes collected by Dalton, who edited the collection Primitive, Archaic and Modern Economies, Polanyi argues that economic thought has gone through five periods in the early 18th century. The first, which included Quesnay and Smith, still saw the economic system as part of society. Only with Townsend, Ricardo and Malthus do economists begin to think of the economic sphere as autonomous. As a side note, Polanyi’s reading of Quesnay is impressive, and very useful for me. Polanyi notes that Quesnay had been a vet before studying economic affairs, and that “In his physiology Quesnay had used the word economy in the sense of husbandry or householding of the animal body.” (PAME: 125) The idea of circulation inside the body was relatively new, and Quesnay adapted the idea to the social body. I need to dig into that claim for my dissertation, as it’s a fascinating hypothesis about how we came to talk about economies the way we do now.

    Polanyi’s reading of Smith is equally helpful. Writing here in 1947 according to the footnotes, Polanyi is in some sense anticipating the dramatic rise of Paul Samuelson and his famous economics textbooks which claimed that Adam Smith emphasized the power of the invisible hand of the market to produce socially optimal outcomes. Polanyi disagreed, noting:

    Reference to the ‘hidden hand,’ which made the self-interest of the butcher and the baker ‘serve me with a meal,’ have been exaggerated out of all proportion. Adam Smith wished to discourage the idea that the self-interest of the merchant naturally benefited the community. He demanded, e.g., that the British government should rule India, not the merchants of the East India Company, whose interests, he asserted, were contrary to those of the population, while the government’s interests ran parallel to that interest (for instance, in terms of taxation). Self-interest is not yet differentiated into economic motives of employers and employed. All through, the approach is still institutional, historical, and societal. (PAME: 128-129)

    Given Gavin Kennedy’s recent work on the history of the invisible hand metaphor, and my own reading of the passage, I couldn’t agree more with Polanyi. In some ways, I’m coming to appreciate more Emma Rothschild’s reading of the invisible hand as a “mildly ironic joke”. In particular, Smith devoted several extensive passages to showing how merchants (and others) often colluded to act in their own interests and against that of the public (think of: “People of the same trade seldom meet together, even for merriment and diversion, but the conversation ends in a conspiracy against the public, or in some contrivance to raise prices.” from Book I, Ch. X). And Smith’s hatred of corporations was evident, as noted by Polanyi. In the famous invisible hand passage, Smith notes that some merchants prefer to safeguard their capital and thus invest locally rather than abroad, in spite of the higher possible returns in foreign trade:

    By preferring the support of domestic to that of foreign industry, he intends only his own security; and by directing that industry in such a manner as its produce may be of the greatest value, he intends only his own gain, and he is in this, as in many other cases, led by an invisible hand to promote an end which was no part of his intention. Nor is it always the worse for the society that it was no part of it. By pursuing his own interest he frequently promotes that of the society more effectually than when he really intends to promote it. (Book IV, Ch. II)

    So, his point is that most merchants are most of the time out for themselves and do all sorts of terrible things that are not at all in the public interest to get their way. But, some merchants, those that out of fear (and not civic-mindedness) support domestic over foreign industry, end up promoting the interests of society by accident. Hence the irony of the joke.

    But to reiterate the overall point of this post: Polanyi was right about Smith, and far less negative than I had originally thought.

    Update: For continuing discussion of this post, see also Gavin Kennedy’s comments and my response over at Adam Smith’s Lost Legacy.

    Economist Caballero on Macroeconomics: “Fantasyland”

    The surprisingly reader-friendly Journal of Economic Perspectives has a symposium on Macroeconomics after the Financial Crisis. I’m working my way through the papers now, starting with a fascinating piece by Caballero on the “core” and “periphery” of contemporary macroeconomics. For Caballero, the periphery of modern macro includes useful analysis of bubbles, liquidity traps, financial disintermediation and the like, and restricts itself to specific problems under semi-realistic assumptions, and thus has provided much of the key explanatory power of economics in the current crisis. On the other hand, Caballero argues that the core includes both New Keynesian and Real Business Cycle theories that emphasize hyperrational agents solving incredibly complicated Dynamic Stochastic General Equilibrium calculations with increasingly complex “frictions” built in to add realism. These models attempt to solve for all variables at once, so to speak. Caballero (2010: 90) argues that the core may suffer from a “pretense of knowledge” problem brought about by its approach of adding more and more complicated deviations into what begins as a simple, straightforward model:

    However, I think this incremental strategy may well have overshot its peak and may lead us to a minimum rather than a maximum in terms of capturing realistic macroeconomic phenomena. We are digging ourselves, one step at a time, deeper and deeper into a Fantasyland, with economic agents who can solve richer and richer stochastic general equilibrium problems containing all sorts of frictions. Because the “progress” is gradual, we do not seem to notice as we accept what are increasingly absurd behavioral conventions and stretch the intelligence and information of underlying economic agents to levels that render them unrecognizable.

    The beauty of the simplest barebones real business cycle model is, in fact, in its simplicity. It is a coherent description of equilibrium in a frictionless world, where it is reasonable to expect that humans can deal with its simplicity. I would rather stop there (perhaps with space for adding one nominal rigidity) and simply acknowledge that it is a benchmark, not a shell or a steppingstone for everything we study in macroeconomics, which is unfortunately the way the core treats it today.

    When a high-profile MIT economist in an AEA-sponsored journal can accuse the core of his subfield of descending “deeper and deeper into a Fantasyland”, I wonder what economic sociology is to do. I mean, we’re not going to come up with better, more authoritative critiques of the unreality of the field than that! So perhaps we should be looking for other tasks – for example, the work of scholars like MacKenzie and Callon who focus on the effects of economic theorizing (independent of its “truth”), or the work of historians of economics like Marion Fourcade who ask, how did economics get to be the way it is in various times and places? Just bashing economics for its unrealistic assumptions seems so… unnecessary? at this point from our discipline. Or at least, if we do so, we must be careful to address the internal critiques along the same lines – from authors like Caballero, as well as the whole behavioral economics movement. What is economic sociology offering that goes beyond these critiques? Etc.

    As a fun aside, and research note for myself, Caballero also notes that modern macro models assume that agents possess complicated understandings of the current workings of the economy, and that this knowledge justifies the generalization from everyday microeconomic rationality, yet:

    Agents could be fully rational with respect to their local environments and everyday activities, but they are most probably nearly clueless with respect to the statistics about which current macroeconomic models expect them to have full information and rational information. (91)

    From this argument we might then conclude that the compilation and distribution of macroeconomic statistical knowledge itself affects the possibilities for rational action. Not that I have any interest in such topics or anything…