Krugman: Deficit Man and the 2020 Election [feedly]

Deficit Man and the 2020 Election
https://www.nytimes.com/2019/07/18/opinion/2020-trump-economy.html

I've seen a number of people suggest that the 2020 election will be a sort of test: Can a sufficiently terrible president lose an election despite a good economy? And that is, in fact, the test we'd be running if the election were tomorrow.

On one side, Donald Trump wastes no opportunity to remind us how awful he is. His latest foray into overt racism delights his base but repels everyone else. On the other side, he presides over an economy in which unemployment is very low and real G.D.P. grew 3.2 percent over the past year.

But the election won't be tomorrow, it will be an exhausting 15 months from now. Trump's character won't change, except possibly for the worse. But the economy might look significantly different.

So let's talk about the Trump economy.

The first thing you need to know is that the Trump tax cut caused a huge rise in the budget deficit, which the administration expects to hit $1 trillion this year, up from less than $600 billion in 2016. This tidal wave of red ink is even more extraordinary than it looks, because it has taken place despite falling unemployment, which usually leads to a falling deficit.

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Strange to say, none of the Republicans who warned of a debt apocalypse under President Barack Obama have protested the Trump deficits. (Should we put Paul Ryan's face on milk cartons?) For that matter, even the centrists who obsessed over federal debt during the Obama years have been pretty quiet. Clearly, deficits only matter when there's a Democrat in the White House.

Oh, and the imminent fiscal crisis people like Erskine Bowles used to warn about keeps not happening: Long-term interest rates remain very low.

Now, the evidence on the effects of deficit spending is clear: It gives the economy a short-run boost, even when we're already close to full employment. If anything, the growth bump under Trump has been smaller than you might have expected given the deficit surge, perhaps because the tax cut was so badly designed, perhaps because Trump's trade wars have deterred business spending.

For now, however, Deficit Man is beating Tariff Man. As I said, we've seen good growth over the past year.

But the tax cut was supposed to be more than a short-run Keynesian stimulus. It was sold as something that would greatly improve the economy's long-run performance; in particular, lower corporate tax rates were supposed to lead to a huge boom in business investment that would, among other things, lead to sharply higher wages. And this big rise in long-run growth would supposedly create a boom in tax revenues, offsetting the upfront cost of tax cuts.


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None of this is happening. Corporations are getting to keep a lot more of their profits, but they've been using the money to buy back their own stock, not raise investment. Wages are rising, but not at an extraordinary pace, and many Americans don't feel that they're sharing in the benefits of a growing economy.

And this is probably as good as it gets.

I'm not forecasting a recession. It could happen, and we're very badly positioned to respond if it does, but the more likely story is just a slowdown as the effects of the deficit splurge wear off. In fact, if you believe the "nowcasters" (economists who try to get an early read on the economy from partial data), that slowdown is already happening. For example, the Federal Reserve Bank of New York believes that the economy's growth was down to 1.5 percent in the second quarter.

And it's hard to see where another economic bump can come from. With Democrats controlling the House, there won't be another big tax cut. The Fed may cut interest rates, but those cuts are already priced into long-term interest rates, which are what matter for spending, and the economy seems to be slowing anyway.

Which brings us back to the 2020 election.

Political scientists have carried out many studies of the electoral impact of the economy, and as far as I know they all agree that what matters is the trend, not the level. The unemployment rate was still over 7 percent when Ronald Reagan won his 1984 landslide; it was 7.7 percent when Obama won in 2012. In both cases, however, things were clearly getting better.

That's probably not going to be the story next year. If we don't have a recession, unemployment will still be low. But economic growth will probably be meh at best — which means, if past experience is any guide, that the economy won't give Trump much of a boost, that it will be more or less a neutral factor.

And on the other hand, Trump's awfulness will remain.

Republicans will, of course, portray the Democratic nominee — whoever she or he may be — as a radical socialist poised to throw the border open to hordes of brown-skinned rapists. And one has to admit that this strategy might work, although it failed last year in the midterms. To be honest, I'm more worried about the effects of sexism if the nominee is a woman — not just the sexism of voters, but that of the news media, which still holds women to different standards.

But as far as the economy goes, the odds are that Trump's deficit-fueled bump came too soon to do him much political good.

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Paul Krugman has been an Opinion columnist since 2000 and is also a Distinguished Professor at the City University of New York Graduate Center. He won the 2008 Nobel Memorial Prize in Economic Sciences for his work on international trade and economic geography. @PaulKrugman

 -- via my feedly newsfeed

Tim Taylor: Antitrust in the Digital Economy [feedly]

What is property in intangible exchange?

Antitrust in the Digital Economy
http://conversableeconomist.blogspot.com/2019/07/antitrust-in-digital-economy.html

Discussions of antitrust and the FAGA companies--that is, Facebook, Amazon, Google, and Apple--often sound like a person with a hammer who just wants to hit something. Here's Peggy Noonan writing in the Wall Street Journal (June 6, 2019):

But the mood in America is anti-big-tech. Everyone knows they're too powerful, too arrogant, loom too large in public life. ... Here's what they [Congress] should be thinking: Break them up. Break them in two, in three; regulate them. Declare them to be what they've so successfully become: once a pleasure, now a utility. It all depends on Congress, which has been too stupid to move in the past and is too stupid to move competently now. That's what's slowed those of us who want reform, knowing how badly they'd do it. Yet now I find myself thinking: I don't care. Do it incompetently, but do something.

When it comes to regulation of the big digital firms, we may end up with incompetence at the end of the day. But first, could we at least take a stab at thinking about what competent antitrust and regulation might look like? For guidance, I've seen three reports so far this year on antitrust and competition in the digital economy:

• One is a report done by an expert panel for the UK government. Jason Furman, Diane Coyle, Amelia Fletcher, Philip Marsden, and Derek McAuley, Unlocking Digital Competition: Report of the Digital Competition Expert Panel (March 2019). 
• One is a report done by outside advisers for the European Commission: Jacques Crémer,  Yves-Alexandre de Montjoye, and Heike Schweitzer, Competition Policy for the Digital Era (April 2019). 
• The remaining report was written by a committee composed of Fiona Scott Morton, Pascal Bouvier, Ariel Ezrachi, Bruno Jullien, Roberta Katz, Gene Kimmelman, A. Douglas Melamed, and Jamie Morgenstern, called Committee for the Study of Digital Platforms: Market Structure and AntitrustSubcommittee Report, published by the Stigler Center at the University of Chicago (May 2019)

The three report are all at least 100 pages in length. They are all written by prominent economists, and they have a lot of overlap with each other. Here, I'll just focus on some of the main points that caught my eye when reading them. But be aware that the topics and terms mentioned here typically come up in at least two of the three reports, and often in all three.

Antitrust Policy is Not a One-Size-All Solution for Everything  

Antitrust policy is about attempting to ensure that competition arises. Pace Noonan, it's not about whether the firms or the people running them are powerful, arrogant, or large.

Digital technologies raise all sorts of broad social issues that are not directly related to competition.  For example, the appropriate treatment of personal information would still be an issue if there were four Facebook-like firms and five Google-like firms all in furious competition with each other. Indeed, it's possible that a bunch of new firms competing in these markets might be more aggressive in hoovering up personal education and passing it along to advertisers and others. The question of if or when certain content should be blocked from the digital sites will still be an issue no matter how many firms are competing in these markets. 

Digital firms use algorithms in many of their decisions about marketing and price, and such algorithms can end up building in various forms of bias. This is a problem that will exist with or without competition. The forces of corporate lobbying on the political process are a legitimate public issue, regardless of whether the lobbying comes from many smaller firms, or a larger firm, or an industry association.

In other words, the digital economy raises lots of issues of public interest. Responding to those issues doesn't just mean flailing around with an antitrust hammer, hoping to connect with a few targets, but instead thinks about what problems need to be addressed and what policy tools are likely to be useful in addressing them.

What is the Antitrust Issue with Digital Firms?

In the US economy, at least, being big and being profitable are not violations of existing antitrust law. If a firm earns profits and becomes large by providing consumers with goods and services that they desire, at a price the consumes are willing to pay, that's fine. But if a firm earns profits and becomes large by taking actions that hinder and block the competition, those anticompetitive actions can be violation of antitrust law. The challenge with big digital firms is where to draw the line.

When the internet was young, two decades ago, there was a widespread belief that it would not be a hospitable place for big companies. [T]he economic literature of the beginning of the 21st century assumed that competition between online firms would arise as consumers hopped from site to site, easily comparing their offers. The reality however quickly turned out to be very different. Very early in the history of the Internet, a limited number of "gateways" emerged. With the benefit of hindsight, this might not be too surprising. Users have limited time and need curators to help them navigate the long tail of websites to find what they are looking for. These curators then developed a tendency to keep users on their platform, and by the end of the 1990s, it was common place to speak about AOL's "walled garden". AOL's market power however rested in great part on its role as an Internet service provider and both competition in that domain and, according to some observers, strategic mistakes after its merger with Time Warner eroded its power.

Fast forwarding to today, a few ecosystems and large platforms have become the new gateways through which people use the Internet. Google is the primary means by which people in the Western world find information and contents on the Internet. Facebook/WhatsApp, with 2.6 billion users, is the primary means by which people connect and communicate with one another, while Amazon is the primary means for people to purchase goods on the Internet. Moreover, some of those platforms are embedded into ecosystems of services and, increasingly, devices that complement and integrate with one another. Finally, the influence of these gateways is not only economic but extends to social and political issues. For instance, the algorithms used by social media and video hosting services influence the types of political news that their users see while the algorithm of search engines determines the answers people receive to their questions.

As all of these reports note, it is now apparent that when a large digital company becomes established, entry can be hard. There is a "network effect," where a system that has more users is also attractive to more users. There's a "platform" effect, where most buyers and sellers head for Amazon because the most buyers and sellers are already on Amazon. There are economies of scale, where the startup costs of a new platform or network can be fairly high, but adding additional users has a marginal cost of near-zero. There are issues involving the collection and analysis of data, where more users mean more attraction to advertisers and more data, to which can then be monetized.

None of these issues are new for antitrust. But the big digital firms bring these issues together in some new ways. The markets become prone to "tipping," which means that when an established firm gets a certain critical mass, other firms can't attract enough users to survive. As economists sometimes say, it becomes a case where there is competition for the market, in the sense of which firm will become dominant in that market, but then there is little competition within the market.

One consequence is that when a big firm becomes established, entry is hard and future competition can be thwarted. Thus, there is reason to be concerned that consumers may suffer along various dimensions: price, quality innovation. In the areas of innovationstartup in that area slows down dramatically. From the Scott Morton et al. report:

By looking at the sub-industries associated with each firm—social platforms (Facebook), internet software (Google), and internet retail (Amazon)—a different trend emerges. Since 2009, change in startup investing in these sub-industries has fared poorly compared to the rest of software for Google and Facebook, the rest of retail for Amazon, and the rest of all VC for each of Google, Facebook, and Amazon. This suggests the existence of so-called "kill-zones," that is, areas where venture capitalists are reluctant to enter due to small prospects of future profits. In a study of the mobile app market, Wen Wen and Feng Zhu come to a similar conclusion: Big tech platforms do dampen innovation at the margin. Their study analyzed how Android app developers adjust their innovation strategies in response to entry (or threat of entry) by Google ...

Some Oddities of a Market with a Price of Zero

Big digital firms provide a remarkable array of services with a market price of zero to consumers. They make their money by attracting users and selling ads, or by charges to producers. Is this a case where the market price should actually be negative--that is, the big tech firms should be paying consumers. The Scott-Morton et al. report offers some interesting thoughts on these lines:

Barter is a common way in which consumers pay for digital services. They barter their privacy and information about what restaurants they would like to eat in and what goods they would like to buy in exchange for digital services. The platform then sells targeted advertising, which is made valuable by the bartered information. But, in principle, that information has a market price. It is not easy to see if the value of any one consumer's information is exactly equal to the value of the services she receives from the platform. However, many digital platforms are enormously profitable, and have been for many years, which suggests that in aggregate we do know the answer: the information is more valuable than the cost of the services. ...

Online platforms offer many services for zero monetary price while they try to raise participation in order to generate advertising revenue. Free services are prevalent on the internet in part because internet firms can harness multi-sided network externalities. While the low price can be a blessing for consumers, it has drawbacks for competition and market structure in a world where institutions have not arisen to manage negative prices. Because there is currently no convenient way to pay consumers with money, platforms are able to mark up the competitive price all the way to zero. This constraint can effectively eliminate price competition, shifting the competitive process to quality and the ability of each competitor to generate network externalities. Depending on the context this may favor or impede entry of new products. For example, entry will be encouraged when a price of zero leads to supra-competitive profits, and impeded when a zero price prevents entrants from building a customer base through low price. Moreover, unlike traditional markets where several quality layers may coexist at different price levels (provided that some consumers favor lower quality at low price), markets where goods are free will be dominated by the best quality firm and others may compete only in so far as they can differentiate their offers and target different customers. This strengthens the firm's incentive to increase quality through increasing fixed costs in order to attract customers (known as the Sutton sunk cost effect) and further pushes the market toward a concentrated market structure. ...

It is a puzzle that, to date, no entrepreneur or business has found a way to pay consumers for their data in money. For example, a consumer's wireless carrier could aggregate micropayments across all manner of digital destinations and apply the credit to her bill each month. ... Furthermore, a carrier that could bargain effectively with platforms on behalf of its subscribers for high payments would likely gain subscribers. Notice that an easy method to pay consumers, combined with price competition for those consumers, might significantly erode the high profits of many incumbent platforms. Platforms likely have no economic incentive to work diligently to operationalize negative prices.

Of course, this idea of a market in which consumers barter attention for zero-marginal-price services isn't new. Television and before that radio operate on the same basic business model.

Categories of Data

The ability to collect data from users, and then to collate it with other information and pass it along to advertisers, is clearly a central part of the business model for digital firms. There's a lot of quick-and-easy talk about "my" data and what "they" should or shouldn't be able to do with it. The Cremer et al. report offers some useful drilling down into different ways of acquiring data and different ways in which data might be used. Sensible rules will take these kinds of distinctions into account. They note:

Data is acquired through three main channels. First, some data is volunteered, i.e. intentionally contributed by the user of a product. A name, email, image/video, calendar information, review, or a post on social media would qualify as volunteered data. Similarly, more structured data—directly generated by an individual—like a movie rating, or liking a song or post would also fall in the volunteered data category. 

Second, some data is observed. In the modern era, many activities leave a digital trace, and "observed data" refers to more behavioural data obtained automatically from a user's or a machine's activity. The movement of individuals is traced by their mobile phone; telematic data records the roads taken by a vehicle and the behaviour of its driver; every click on a page web can be logged by the website and third party software monitors the way in which its visitors are behaving. In manufacturing, the development of the Internet of Things means that every machine produces reams of data on how it functions, what its sensors are recording, and what it is currently doing or producing.

Finally, some data is inferred, that is obtained by transforming in a non-trivial manner volunteered and/or observed data while still related to a specific individual or machine. This will include a shopper's or music fan's profiles, e.g. categories resulting from clustering algorithms or predictions about a person's propensity to buy a product, or credit ratings.  The distinction between volunteered, observed and inferred data is not always clear. ...

[W]e will also consider how data is used. We will define four categories of uses: non-anonymous use of individual-level data, anonymous use of individual level data, aggregated data, and contextual data.

The first category, non-anonymous use of individual-level data, would be any individual-level data (volunteered, observed, or inferred) that was used to provide a service to the individual. For instance, a music app uses data about the songs a user has listened to in order to provide recommendations for new artists he or she might enjoy. Similarly, a sowing app uses data from farm equipment to monitor the evolution of the soil. Access to individual-level data can often be essential to switch service or to offer a complementary service.

The second category, anonymous use of individual-level data, would include all cases when individual-level data was used anonymously. Access to the individual-level data is necessary but the goal is not to directly provide a service to the individual who generated the data in the first place. These would typically include cases of data being used to train machine-learning algorithms and/or data used for purposes unrelated to the original purposes for which the data has been collected. An example of this would be the use of skin image data to train a deep learning (Convolutional Neural Network) algorithm to recognise skin lesions or the use of location data for trading purposes. In specific cases, the information extracted, e.g. the trained algorithm, can then be used to provide a better service to some of the individuals who contributed data. For instance, film reviews are used collectively to provide every individual with better recommendations (collaborative filtering). For the anonymous use of individual-level data, access to a large dataset may be essential to compete.

The third category, aggregated data, refers to more standardised data that has been irreversibly aggregated. This is the case for e.g. sales data, national statistics information, and companies' profit and loss statements. Compared to anonymous use of individual-level data, the aggregation is standard enough that access to the individual-level data is not necessary.

Finally, contextual data refers to data that does not derive from individual-level data. This category typically includes data such as road network information, satellite data and mapping data.

It's interesting to consider whether people's objections about use of their data are rooted purely in principle, or are not about being paid. If firms used your observed data on location, shopping, and so on, but only sold aggregated versions of that data and paid you for the amount of data you contributed to the aggregate, would you still complain?

Some Policy Steps

After this probably over-long mention of what seemed to me like interesting points, what are the most useful potential margins for action in this area--at least if we want to take competent action? Here are two main categories of policies to consider: those related to mergers and anticompetitive behavior, and those related to data.

1) Big dominant firms deserve heightened scrutiny for actions that might affect entry and competition. This is especially true when a firm has a "bottleneck" position when everyone (or almost everyone) needs to go through that firm to access certain service. One particular concern here is that big dominant firms buy up smaller companies that might, if they had remained independent, offered a form of competition or a new platform.

Furman et al. write:

There is nothing inherently wrong about being a large company or a monopoly and, in fact, in many cases this may reflect efficiencies and benefits for consumers or businesses. But dominant companies have a particular responsibility not to abuse their position by unfairly protecting, extending or exploiting it. Existing antitrust enforcement, however, can often be slow, cumbersome, and unpredictable.  ...

Acquisitions have included buying businesses that could have become competitors to the acquiring company (for example Facebook's acquisition of Instagram), businesses that have given a platform a strong position in a related market (for example Google's acquisition of DoubleClick, the advertising technology business), and data-driven businesses in related markets which may cement the acquirer's strong position in both markets (Google/YouTube, Facebook/WhatsApp). Over the last 10 years the 5 largest firms have made over 400 acquisitions globally. None has been blocked and very few have had conditions attached to approval, in the UK or elsewhere, or even been scrutinised by competition authorities.

But along with mergers, there are a variety of other potentially actions which, when used by a dominant firm, may be potentially anticompetitive. Another concern is when big dominant firms start offering a range of other services on their own, and then use their dominance in  one market to favor their own services in other markets. Yet another issue is when big dominant firms choose a certain technological standard that seems more about blocking competition than advancing its own business. Some dominant platform firms use "best-price clauses," which guarantee that they will receive the lowest possible price from any provider. Such clauses also mean that if a new platform firm starts up, it cannot offer to undercut the original provider on price.

In other words, if a large dominant firm keeps your business (and your attention) by providing you with the quality and price of services you want, and earns high profits as a result, so be it. But if that firm is earning high profits by seeking out innovative ways to hamstring the potential competitors, it's a legitimate antitrust problem.

2) Data openness, portability, and interoperability.

Data openness just means that companies need to be open with you about what data of yours they have on-hand--perhaps especially if that data was collected in some way that didn't involve you openly handing it over to them. Portability refers to the ability to move your data easily from one digital firm to another. For example, you might be more willing to try a different search engine, or email program, or a different bank or health care provider if all your past records could be ported easily to the new company. Interoperability refer to when technical standards allow your (email, shopping, health, financial or other) data to be used directly by two different providers, if you desire.

Again, the underlying theme here is that if a big digital firm gets your attention with an attractive package of goods and services, that's fine; but if it hold you in place because it would be a mortal pain to transfer the data they have accumulated on you, that's a legitimate concern.

Finally, I would add that it's easy to focus on the actions of big digital firms that one sees in the headlines, and as a result to pay less attention to other digital economy issues of equal or greater importance. For example, most of us face a situation of very limited competition when it comes to getting high-speed internet access. In many ways, the growth of big digital firms doesn't raise new topics, but it should push some new thinking about those topics. 

 -- via my feedly newsfeed

Thai politics and Thai perspectives [feedly]

He had me at "non-doctrinaire" historical materialist, a.k.a, Marxism.

Thai politics and Thai perspectives
http://understandingsociety.blogspot.com/2019/07/thai-politics-and-thai-perspectives.html

One of the benefits of attending international conferences is meeting interesting scholars from different countries and traditions. I had that pleasure while participating in the Asian Conference on Philosophy of the Social Sciences at Nankai University in June, where I met Chaiyan Rajchagool. Chaiyan is a Thai academic in the social sciences. He earned his undergraduate degree in Thailand and received a PhD in sociology from the University of Manchester (UK). He has served as a senior academic administrator in Thailand and is now an associate professor of political science at the University of Phayao in northern Thailand. He is an experienced observer and analyst of Thai society, and he is one of dozens of Thai academics summoned by the military following the military coup in 2014 (link). I had numerous conversations with Chaiyan in Tianjin, which I enjoyed very much. He was generous to share with me his 1994 book, The rise and fall of the Thai absolute monarchy: Foundations of the modern Thai state from feudalism to peripheral capitalism, and the book is interesting in many different ways. Fundamentally it provides a detailed account of the political and economic transition that Siam / Thailand underwent in the nineteenth century, and it makes innovative use of the best parts of the political sociology of the 1970s and 1980s to account for these processes.

The book places the expansion of European colonialism in Southeast Asia at the center of the story of the emergence of the modern Thai state from mid nineteenth-century to the end of the absolute monarchy in the 1930s. Chaiyan seeks to understand the emergence of the modern Siamese and Thai state as a transition from "feudal" state formation to "peripheral capitalist" state formation. He puts this development from the 1850s to the end of the nineteenth century succinctly in the preface:

In the mid-nineteenth century Siam was a conglomerate of petty states and principalities and did not exist as a single political entity.... Economically Siam was transformed into what may be termed, in accordance with our theoretical framework, peripheral capitalism. Accompanying this development was the transformation of old classes and the rise of new classes.... At the political level a struggle took place within the ruling class in Bangkok, and new institutional structures of power began to emerge. As a result the previously fragmented systems of power and administration were brought under unified centralized command in the form of the absolute monarchy. (xiii-xiv)

This is a subtle, substantive, and rigorous account of the politics and economy of modern Siam / Thailand from the high point of western imperialism and colonialism in Asia to the twentieth century. The narrative is never dogmatic, and it offers an original and compelling account of the processes and causes leading to the formation of the Thai state and the absolutist monarchy. Chaiyan demonstrates a deep knowledge of the economic and political realities that existed on the ground in this region in the nineteenth century, and equally he shows expert knowledge about the institutions and strategies of the colonial powers in the region (Britain, France, Germany). I would compare the book to the theoretical insights about state formation of Michael Mann, Charles Tilly, and Fernand Braudel.

Chaiyan's account of the development of the Thai state emphasizes the role of economic and political interests, both domestic and international. Fundamentally he argues that British interests in teak (and later tin) prompted a British strategy that would today be called "neo-colonial": using its influence in the mid-nineteenth-century to create a regime and state that was favorable to its interests, without directly annexing these territories into its colonial empire. But there were internal determinants of political change as well, deriving from the conflicts between powerful families and townships over the control of taxes.

The year 1873-4 marks the beginning of a period in which the royalty attempted to take political control at the expense of the Bunnag nobility and its royal/noble allies. I have already noted that the Finance Office, founded in 1873, was to unify the collection f tax money from the various tax farmers under different ministries into a single office. To attain this goal, political enforcement and systematic administration were required. The Privy Council and the Council of State, established in June and August 1874, were the first high level state organizations. ... With the creation of a professional military force of 15,000 troops and 3,000 marines ... the decline of the nobility's power was irreversible, whereas the rise of the monarchy had never before had so promising a prospect. (85, 86)

Part of the development of the monarchy involved a transition from the personal politics of the feudal politics of the earlier period to a more bureaucratic-administrative system of governance:

Of interest in this regard was the fact that the state was moving away from the direct exercise of personal authority by members of the ruling class. this raises questions about the manner of articulation between the crown and the state. If direct personal control of the state characterizes a feudal state, the ruling class control of the state in a peripheral capitalist society takes the form of a more impersonal rule of law and administrative practice through which are mediated the influences of the politico-economic system and class interests. (88)

Chaiyan makes superb use of some of the conceptual tools of materialist social science and non-doctrinaire Marxism, framing his account in terms of the changes that were underway in Southeast Asian with respect to the economic structure of everyday life (property, labor, class) as well as the imperatives of British imperialism. The references include some of the very best sources in social and historical theory and non-doctrinaire Marxism that were available in the 1980s: for example, Ben Anderson, Perry Anderson, Norberto Bobbio, Fernand Braudel, Gene Genovese, Michael Mann, Ralph Miliband, Nicos Poulantzas, James Scott, Theda Skocpol, Charles Tilly, and Immanuel Wallerstein, to name a few out of the hundreds of authors cited in the bibliography. Chaiyan offers a relevant quotation from Fernand Braudel that I hadn't seen before but that is more profound than any of Marx's own pronouncements about "base and superstructure":

Any highly developed society can be broken down into several "ensembles": the economy, politics, culture, and the social hierarchy. The economy can only be understood in terms of the other "ensembles", for it both spreads itself about and opens its own doors to its neighbours. There is action and interaction. That rather special and partial form of the economy that is capitalism can only e fully explained in light of these contiguous "ensembles" and their encroachments; only then will it reveal its true face. 

This, the modern state, which did not create capitalism but only inherited it, sometimes acts in its favor and at other times acts against it; it sometimes allows capitalism to expand and at other times destroys its mainspring. Capitalism only triumphs when it becomes identified with the state, when it is the state.... 

So the state was either favorable or hostile to the financial world according to its own equilibrium and its own ability to stand firm. (Braudel Afterthoughts on Material Civilization and Capitalism, 64-65)

It is interesting to me that Chaiyan's treatment of the formation of a unified Thai state is attentive to the spatial and geophysical realities that were crucial to the expansion of central state power in the late nineteenth century.

A geophysical map, not a political one, would serve us better, for such a map reveals the mainly geophysical barriers that imposed constraints on the extension of Bangkok power. The natural waterways, mountains, forests and so on all helped determine how effectively Bangkok could claim and exert its power over townships. (2)

In actual fact, owing to geographical barriers and the consequent difficulty of communication, Bangkok exercised direct rule only over an area within a radius of two days travelling (by boat, cart, horse, or on foot). (3) 

Here is a map that shows the geophysical features of the region that eventually became unified Thailand, demonstrating stark delineation between lowlands and highlands:

This is a topic that received much prominence in the more recent writings of James Scott on the politics of southeast Asia, and his concept of "Zomia" as a way of singling out the particular challenges of exercising central state power in the highlands of southeast Asia (link, link). Here is a map created by Martin Lewis (link) intended to indicate the scope of the highland population (Zomia). The map is discussed in an earlier post.

And here is a map of the distribution of ethnic and language groups in Thailand (link), another important element in Chaiyan's account of the consolidation of the Thai monarchy:

It is an interesting commentary on the privilege, priorities, and limitations of the global academic world that Chaiyan's very interesting book has almost no visibility in western scholarship. In its own way it is the equal of some of Charles Tilly's writings about the origins of the French state; and yet Tilly is on all reading lists on comparative politics and Chaiyan is not. The book is not cited in one of the main English language sources on the history of Thailand, A History of Thailand by Chris Baker and Pasuk Phongpaichit, published by Cambridge University Press, even though that book covers exactly the same period in chapter 3. Online academic citation databases permitted me to find only one academic article that provided substantive discussion or use of the book ("Autonomy and subordination in Thai history: the case for semicolonial analysis", Inter‐Asia Cultural Studies, 2007 8:3, 329-348; link). The author of this article, Peter Jackson, is an emeritus professor of Thai history and culture at the Australian National University. The book itself is on the shelves at the University of Michigan library, and I would expect it is available in many research libraries in the United States as well.

So the very interesting theoretical and historical treatment that Chaiyan provides of state formation in Thailand seems not to have received much notice in western academic circles. Why is this? It is hard to avoid the inference that academic prestige and impact follow nations, languages, universities, and publishing houses. A history of a small developing nation, authored by a Thai intellectual at a small university, published by a somewhat obscure Thai publishing company, is not destined to make a large splash in elite European and North American academic worlds. But this is to the great disadvantage to precisely those worlds of thought and knowledge: if we are unlikely to be exposed to the writings of insightful scholars like Chaiyan Rajchagool, we are unlikely as well to understand the large historical changes our world has undergone over the past two centuries.

Amazon comes in for a lot of criticism these days; but one thing it has contributed in a very positive way is the easy availability of books like this one for readers who would otherwise never be exposed to it. How many other intellectuals with the insights of a Tilly or a Braudel are there in India, Côte d'Ivoire, Thailand, Bolivia, or Barbados whom we will never interact with in a serious way because of the status barriers that exist in the academic world?

*   *   *

(It is fascinating to me that one of the influences on Chaiyan at the University of Manchester was Teodor Shanin. Shanin is a scholar whom I came to admire greatly at roughly the same time when I was engaged in research in peasant studies in connection with Understanding Peasant China: Case Studies in the Philosophy of Social Science.)  

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Sean Gallagher : The Fourth Industrial Revolution Emerges from AI and the Internet of Things : "IoT has arrived on the ... [feedly]

 Sean Gallagher : The Fourth Industrial Revolution Emerges from AI and the Internet of Things : "IoT has arrived on the ...

Grasping Reality with Both Hands: The Se...by J. Bradford DeLong / 2h

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Sean Gallagher: The Fourth Industrial Revolution Emerges from AI and the Internet of Things: "IoT has arrived on the factory floor with the force of Kool-Aid Man exploding through walls.... Smart, cheap, sensor-laden devices paired with powerful analytics and algorithms have been changing the industrial world.... Companies are seeing more precise, higher quality manufacturing with lowered operational costs; less downtime because of predictive maintenance and intelligence in the supply chain; and fewer injuries on factory floors because of more adaptable equipment. And outside of the factory, other industries could benefit from having a nervous system of sensors, analytics to process 'lakes' of data, and just-in-time responses to emergent issues—aviation, energy, logistics, and many other businesses that rely on reliable, predictable things could also get a boost. But the new way comes with significant challenges, not the least of which are the security and resilience of the networked nervous systems stitching all this new magic together.... And then there's always that whole 'robots are stealing our jobs' thing. (The truth is much more complicated—and we'll touch on it later this week)...

...It's a robot! It's stealing my job! (Actually, it's doing carbon fiber layup, which is exactly the kind of time consuming task that we want robots to be doing.)...

MITRE has partnered with several robotics startups—including American Robotics, which has developed a fully automated drone system for precision agriculture. Called Scout, the system is an autonomous, weather-proofed unit that sits adjacent to fields. All a farmer has to do is program in drone flight times, and the AI handles drone flight planning and managing the flight itself, as well as the collection and processing of imagery and data, uploading everything to the cloud as it goes. That level of autonomy allows farmers to simply look at data about crop health and other metrics on their personal devices, and then act upon that data—selectively applying pesticides, herbicides, or additional fertilizers if necessary. With some more machine learning juice, those are tasks that could eventually be handed off to other drones or robotic farming equipment once patterns and rules of their use are established. Scout mirrors how human-machine teaming could work in the factory...

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Trump’s Fixation on Intellectual Property Rights Serves the Rich [feedly]

Trump's Fixation on Intellectual Property Rights Serves the Rich
http://cepr.net/publications/op-eds-columns/trump-s-fixation-on-intellectual-property-rights-serves-the-rich

Dean Baker
Truthout, July 15, 2019

See article on original site

Between making threats of actual war with North Korea and Iran, Donald Trump has also gotten us into a trade war with China. Trump's ostensible reason for this trade war — the large US trade deficit with China — actually did have some basis in reality, but in practice the trade war is straying into turf that is likely to offer few gains for US workers and could actually lead to sizable losses.

A major theme in Trump's campaign was that China is a world-class currency manipulator that deliberately keeps down the value of its currency to give its products an advantage in international trade. The basic story is true; China did intervene heavily in currency markets to keep the value of its currency from rising against the dollar.

However, it would probably be more appropriate to say that China managed its currency rather than manipulated it. There was nothing hidden or sneaky about China's intervention; it has an official exchange rate that it acts to maintain.

Most economists acknowledge, in retrospect, that China managed its currency in the last decade (they didn't at the time), but now say that China has stopped buying large amounts of reserves of foreign currencies, the tool used to suppress the value of the yuan. What these economists ignore is that China continues to hold massive amounts of reserves, which lowers the value of the yuan relative to its value if China held more normal amounts in reserve.

China's reserve holdings have the same effect on the value of its currency as the Fed's asset holdings do in keeping down long-term interest rates. While most economists acknowledge the impact of the Fed's asset holdings, for some reason they ignore the impact of China's reserve holdings. No one ever said economists were consistent.

By keeping its currency below market levels, China makes its products more competitive internationally. This allows it to continue to run large trade surpluses, even though a fast-growing country like China would typically be expected to run large trade deficits.

If Trump focused on currency, he would likely be able to reach an agreement with China, which would reduce its trade surplus with the United States. This would create more jobs for US manufacturing workers, which would likely be a boost to the large segment of the work force without college degrees (roughly two-thirds).

But currency seems to have largely slipped off Trump's trade war agenda. Instead, he is pushing for policies like requiring China to show more respect for the intellectual property claims of US corporations. That may be good for Boeing, Pfizer, Merck and other companies that are heavily dependent on intellectual property for their profits, but it is bad news for most American workers.

There are three reasons that most workers should not want to see Trump win his battles on intellectual property. The first is obvious. If major US companies know that they can offshore operations to China without having to worry about transferring technology to China (a frequent complaint), they will be more likely to offshore operations to China.

The second reason is a tiny bit more complicated. If China has to pay Merck and Microsoft more money for their patents and copyrights, it will have less money to spend on other US goods and services.

The way this works out practically is that, other things being equal, the money China needs to pay Merck and Microsoft, will increase their demand for dollars. That will raise the value of the dollar against the yuan, making other US goods and services less competitive than if China was not paying Merck and Microsoft for their intellectual property.

The third point is that by increasing the enforcement of intellectual property claims, both in the US and overseas, our government is redistributing even more income to those at the top. If you need a visual aid to understand this point, think of Bill Gates, one of the world's richest people. If the government did not threaten to imprison anyone who made copies of Microsoft software without Gates's permission, it is likely that he would still be working for a living.

Economists often talk about how technology is rewarding people with technical skills in areas like computer science and biotech. That's a lie. It is our intellectual property policy on technology that has explicitly structured the market to give more money to the Bill Gates crowd. Trump's China policy seems to be a further step in this direction.

An agreement crafted to help workers would instead focus on sharing knowledge and technology. China, along with India, Brazil and many other developing countries, has actually been pushing in this direction in the case of pharmaceuticals. If we had some mechanism for sharing research costs across countries, then new drugs could sell for a few dollars per prescription, instead of a few thousand.

There is a similar story with clean technology. China has more installed wind and solar power than the rest of the world combined. It also sells more electric cars. A forward-looking administration would be negotiating ways that we could share these technologies as quickly as possible.

But that will not happen with Trump. Instead, he is likely to construct a deal that will be great for a small number of rich people and pretty awful for everyone else. And, he will tell us that it is "terrific."

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ABM fundamentalism [feedly]

Agent based modeling (ABM) in the social sciences uses rules based simulations (i.e. GENERATING models in numerous social science domains where agents operate computationally like "humans", but with simpler "rulesets" than in real life).

Simplification, if done right (Read Paul Krugman's columns explaning complex economic phenomena for examples of a world class simplifier), much can be and has been learned, that equation approaches cannot easily reveal. Some good "socialist" agent-based modeling would be very interesting.....try to find some of those if I can, although Dan Little -- the author of the blog below -- is a plenty progressive scientist and intellectual.

  

ABM fundamentalism
http://understandingsociety.blogspot.com/2019/07/abm-fundamentalism.html

I've just had the singular opportunity of participating in the habilitationexamination of Gianluca Manzo at the Sorbonne, based on his excellent manuscript on the relevance of agent-based models for justifying causal claims in the social sciences. Manzo is currently a research fellow in sociology at CNRS in Paris (Centre National de la Recherche Scientifique), and is a prolific contributor to analytical sociology and computational social science. The habilitation essay is an excellent piece of work and I trust it will be published as an influential monograph. Manzo has the distinction of being expert both on the philosophical and theoretical debates that are underway about social causation and an active researcher in the field of ABM simulations. Pierre Demeulenaere served as a generous and sympathetic mentor. The committee consisted of Anouk Barberousse, Ivan Ermakoff, Andreas Flache, Olivier Godechot, and myself, and reviewer comments and observations were of the highest quality and rigor. It was a highly stimulating session.

One element of our conversation was especially enlightening to me. I have written a number of times in Understanding Society and elsewhere about the utility of ABM models, and one line of thought I have developed is a critique of what I have labeled "ABM fundamentalism" -- the view that ABM models are the best possible technique for constructing social explanations for every possible subject in the social sciences (link). This view is expressed in Joshua Epstein's slogan, "If you didn't grow it, you didn't explain it." I maintain that ABM is a useful technique, but only one of many methods appropriate to the problem of constructing explanations of interesting sociological outcomes (link). So I advocate for theoretical and methodological pluralism when it comes to the ABM program. 

I asked Gianluca whether he would agree that ABM fundamentalism is incorrect, and was surprised to find that he defends the universal applicability of ABM as a tool to implement any sociological theory. According to him, it is a perfectly general and universal modeling platform that can in principle be applied to any sociological problem. He also made it clear that he does not maintain that the use of ABM methods is optimal for every sociological problem of explanation. His defense of the universal applicability of ABM simulation techniques therefore does not imply that Manzo privileges these techniques as best for every sociological problem. But as a formal matter, he holds that ABM technology possesses the resources necessary to represent any fully specified social theory within a simulation.

The subsequent conversation succeeded in clarifying the underlying source of disagreement for me. What I realized in the discussion that ensued is that I was conflating two things in my label of ABM fundamentalism: the simulation technology and the substantive doctrine of generative social science. Epstein is a generativist, in the sense that he believes that social outcomes need in principle to be generated from a representation of facts about the individuals who make it up (Generative Social Science: Studies in Agent-Based Computational Modeling). Epstein is also an advocate of ABM techniques because they represent a particularly direct way of implementing a generativist explanation. But what Gianluca showed me is that ABM is not formally committed to the generativist dogma, and that an ABM simulation can perhaps incorporate factors at any social level. The insight that I gained, then, is that I should separate the substantive view of generativism from the formal mathematical tools of ABM simulations techniques. 

I am still unclear how this would work -- that is, how an ABM simulation might be created that did an adequate job of representing features at a wide range of levels -- actors, organizations, states, structures, and ideologies. For example, how could an ABM simulation be designed that could capture a complex sociological analysis such as Tilly's treatment of the Vendée, with peasants, protests, and merchants, the church, winegrowers' associations, and the strategies of the state? Tilly's historical narrative seems inherently multi-stranded and irreducible to a simulation. Similar points could be made about Michael Mann's comparative historical account of fascisms or Theda Skocpol's analysis of social revolutions.

So there is still an open question for me in this topic. But I think I am persuaded that the fundamentalism to which I object is the substantive premise of generativism, not the formal computational methods of ABM simulations themselves. And if Gianluca is correct in saying that ABM is a universal simulation platform (as a Turing machine is a universal computational device) then the objection is misplaced.

So this habilitation examination in Paris had exactly the effect for me that we would hope for in an academic interaction -- it led me to look at an important issue in a somewhat different way. Thank you, Gianluca!  

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China vs. United States: A Tale of Two Economies [feedly]

A great graphic comparing US and China economies.

China vs. United States: A Tale of Two Economies
https://ritholtz.com/2019/07/china-vs-united-states-a-tale-of-two-economies/

Source: Visual Capitalist     While comparable in total size, the makeup of each economy is totally different. United States is a sophisticated and highly diversified economy that is based on services, finance, and consumption from the middle class. China has similar aspirations in the future, but right now it is resource-intensive growth engine making the transition…

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The post China vs. United States: A Tale of Two Economies appeared first on The Big Picture.

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