Archive for the ‘economics’ Category
A few years ago, I bought a copy of Charles Tilly’s Why?, just for fun sociology reading. All the Important sociology reading got in the way, and I never read Why?
But while I was unpacking this week I came across it and thought I’d bring it along on a car ride to Providence over the weekend. Not only is it a fun read, as well as touchingly personal at times, it turned out to be surprisingly relevant to stuff I’ve been thinking about lately.
The book is organized around four types of reasons people give for things…any things: their incarceration in mental hospitals, why a plane just flew into the World Trade Center, whether the last-minute change of an elderly heiress’s will should be honored. In grand social science tradition, the reasons are organized into a 2 x 2 table:
|Cause-Effect Accounts||Stories||Technical Accounts|
Why? illustrates these types with a wide range of engaging examples, from eyewitness accounts of September 11th to the dialog between attending physicians and interns during hospital rounds.
Conventions are demonstrated by etiquette books: they are reasons that don’t mean much of anything and aren’t necessarily true, but that follow a convenient social formula: “I lost track of the time.” Stories are reasons that provide an explanation, but one focused on a protagonist—human or otherwise—who acts, and which often contain a moral edge: evangelist Jerry Falwell’s account of how he came to oppose segregation after God spoke to him through the African-American man who shined his shoes every week. Both conventions and stories are homely, everyday kinds of reasons.
Codes and technical accounts, on the other hand, are the reasons experts give. Reasons that conform to codes explain how an action was in accordance with some set of specialized rules. The Department of Public Works did not repair the air conditioning because they lacked a form 27B/6. While law is the quintessential code, Tilly shows that medicine follows codes to a surprising extent as well.
Finally, technical accounts attempt to provide cause-effect explanations of why some outcome occurs. Jared Diamond argues that Europe developed first because it had domesticable plants and animals and sufficient arable land, and lacked Africa’s north-south axis. Technical accounts draw on specialized bodies of knowledge, and attempt to produce truth, not just conformity with rules.
I’ve spent a lot of time in recent months thinking about what experts do in policy, and thinking about the different paths through which they can have effects. Lots of these effects are technical, of course. Expert opinion may not determine the outcome in debates over the macroeconomic effects of tax policy changes or what standards nutrition guidelines should be set at, but there’s no question that they’re informed by technical accounts.
But at least as important in influencing a wider audience are the stories experts can tell. Deborah Stone wrote about these “policy stories” decades ago, though she wasn’t especially focused on experts’ role in creating them. Political scientists like Ann Keller, however, have shown that scientists, too, translate their expertise into policy stories—for example, that human activity was creating the sulfur and nitrogen oxides that produce acid rain, destroying fisheries and making water undrinkable. These stories are grounded in technical accounts, but are simplified versions with moral undertones that point toward a particular range of policy solutions—in this case, doing something about the SOx and NOx emissions that the story identifies as creating the problem.
Some kinds of expertise, or rather some kinds of technical accounts, are more amenable than others to translation into policy stories. Economic models, in particular, are often friendly to such translation. For example, although this isn’t the language I use there, my book in part argues that U.S. science policy changed because of a model-turned-story. Robert Solow’s growth model, which includes technology as a factor that affects economic growth (by increasing the productivity of labor), became by the late 1970s the basis of a powerful policy story in which the U.S. needed to improve its capacity for technological innovation so that it could restore its economic position in the world.
Similarly, a basic human capital model in which investment in training results in higher wages easily becomes a story in which we need to improve or extend education so that people’s income increases.
Sociological models, even the formal ones, seem less amenable on average to these kinds of translations. Though Blau and Duncan’s well-known status attainment model could be read as suggesting education as a point of intervention to improve occupational status, it seems fairer to read it as saying that occupational status is largely determined by your father’s occupation and education. While this certainly has policy implications, they are not as natural an extension from the model itself. It hearkens back to that old saw—economics is about how people make choices; sociology is about how they don’t have any choices to make.
I guess part of the appeal of Why? for me was that it mapped surprisingly well onto these questions that were already on my mind. Mostly I’ve thought about this in the context of economic models becoming policy stories. I wonder, though, whether my quick generalization about the technical accounts of sociology lending themselves less readily to compelling policy stories actually holds up. What are the obvious examples I’m missing?
This week, some readings on who goes to college and why:
- College Choice in America by Charles Manski. The standard model of how students choose the college they attend. Just add $40k to the tuition bill to update it.
- Read a bunch of reports summarizing the results of the annual freshman survey fielded by UCLA’s Higher Education Research Institute. Start with the 70s and move forward.
- How elite schools choose students: Crafting a Class by Duffy and Goldberg; Creating a Class by Mitchell Stevens; and The Chosen by Jerome Karabel. Each a classic in its own way.
- Academically Adrift by Arum and Roksa. Shows the limited learning in higher ed.
- Read Becker on human capital, Arrow & Spence on signalling, and Collins on credentialism. Each is a classic statement of different theories of how college plays into employment and income.
- Read Carnevale, Strohl and Melton on the incomes associated with different college majors.
- On student protest: Freedom’s Web by Richard Rhoads and From Black Power by myself.
Use the comments for more suggestions.
Over at Scatterplot, Andy Perrin has a nice post pointing to a recent talk by Rodney Benson on actor-network theory and what Benson calls “the new descriptivism” in political communications. Benson argues that ANT is taking people away from institutional/field-theoretic causal explanation of what’s going on in the world and toward interesting but ultimately meaningless description. He also critiques ANT’s assumption that world is largely unsettled, with temporary stability as the development that must be explained.
At the end of the talk, Benson points to a couple of ways that institutional/field theory and ANT might “play nicely” together. ANT might be useful for analyzing the less-structured spaces between fields. And it helps draw attention toward the role of technologies and the material world in shaping social life. Benson seems less convinced that it makes sense to talk nonhumans as having agency; I like Edwin Sayes’ argument for at least a modest version of this claim.
I toyed with the possibility of reconciling institutionalism and ANT in an article on the creation of the Bayh-Dole Act a few years back. But really, the ontological assumptions of ANT just don’t line up with an institutionalist approach to causality. Institutionalism starts with fairly tidy individual and collective actors — people, organizations, professional groups. Even messy social movements are treated as well-enough-defined to have effects on laws or corporate behavior. The whole point of ANT is to destabilize such analyses.
That said, I think institutionalists can fruitfully borrow from ANT in ways that Latour would not approve of, just as they have used Bourdieu productively without adopting his whole apparatus. In particular, the insights of ANT can get us at least two things:
1) It not only increases our attention to the role of technologies in shaping organizational and field-level outcomes, but ANT makes us pay attention to variation in the stability of those technologies. It is simply not possible to fully accounting for the mortgage crisis, for example, without understanding what securitization is; how tranching restructured, redistributed and sometimes hid risk; how it was stabilized more or less durably in particular times and places; and so on.
You can’t just treat “securitization” as a unitary explanatory factor. You need to think about the specific configuration of rules, organizational practices, technologies, evaluation cultures and so on that hold “securitization” together more or less stably in a specific time and place. Sure, technologies are sometimes stable enough to treat as unified and causal—for example, a widely used indicator like GDP, or a standardized technology like a new drug. But thinking about this as a question of degree improves explanatory capacity.
An example from my own current work: VSL, the value of a statistical life. Calculations of VSL are critical to cost-benefit analyses that justify regulatory decisions. They inform questions of environmental justice, of choice of medical treatment, of worker safety guidelines. All sorts of political assumptions — for example, that the lives of people in poor countries are worth less than people in rich ones — are baked into them. There is no uniform federal standard for calculating VSL — it varies widely across agencies. ANT sensitizes us not only to the importance of such technologies, but to their semi-stable nature—reasonably persistent within a single agency, but evolving over time and different across agencies.
2) Second, ANT can help institutionalists deal better with evolving actors and partial institutionalization. For example, I’m interested in how economists became more important to U.S. policymaking over a few decades. The problem is that while you can define “economist” as “person with a PhD in economics,” what it means to be an economist changes over time, and differs across subfields, and is fuzzy around the borders.
I do think it’s meaningful to talk about “economists” becoming more influential, particularly because the production of PhDs happens in a fairly stable set of organizational locations. But you can’t just treat growth theorists of the 1960s and cost-benefit analysts from the 1980s and the people creating the FCC spectrum auctions in the 1990s as a unitary actor; you need ways to handle variety and evolution without losing sight of the larger category. And you need to understand not only how people called “economists” enter government, but also how people with other kinds of training start to reason a little more like economists.
Drawing from ANT helps me think about how economists and their intellectual tools gain a more-or-less durable position in policymaking: by establishing institutional positions for themselves, by circulating a style of reasoning (especially through law and public policy schools), and by establishing policy devices (like VSL). (See also my recent SER piece with Dan Hirschman.) Once these things have been accomplished, then economics is able to have effects on policy (that’s the second half of the book). While the language I use still sounds pretty institutionalist—although I find myself using the term “stabilized” more than I used to—it is definitely informed by ANT’s attention to the work it takes to make social arrangements last. Thus I end up with a very different story from, for example, Fligstein & McAdam’s about how skilled actors impose a new conception of a field — although new conceptions are indeed imposed.
I don’t have a lot of interest in fully adopting ANT as a methodology, and I don’t think the social always needs to be reassembled. The ANT insights also lend themselves better to qualitative, historical explanation than to quantitative hypothesis testing. But all in all, although I remain an institutionalist, I think my work is better for its engagement with ANT.
In one of my graduate courses, I taught the Rand health insurance experiment. It’s a famous study where some people were randomly given health insurance coverage to see how it affected access and health. The bottom line is that using insurance to decrease the costs of health via low co-payment helps with access, but not with health. In the discussion, I mentioned how this result surprises people. Then, one of my BGS* said the following, paraphrased by me:
The reason this might be surprising from an economic perspective is that social behavior is a question of relative prices. Obviously, purchasing health care would become more common if it were made easier. However, health is often beyond the ability of individuals to directly influence. Health might be due to genetic factors, social class, occupation, and other processes that are not easily countered by a visit to a doctor. Health is the result of a long chain of events. These policy interventions only happen at the end, so the modest effects shouldn’t be surprising.
Now, we did discuss the famous finding that the intervention helped with low-income individuals. But this supports the “end of the chain” view of health. For most people, they already have the resources and environment that will help with prevention of chronic health problems (e.g., malnutrition in youth) or managing short term issues that could become long term issues (e.g., avoiding jobs that might lead to injury). But low income individuals don’t have the resources for basic health self-management and even simple interventions might have a big impact. My take home? Think about the chain and the closer you are to the end, the more focused the policy effects will be, if it exists at all.
* Brilliant Graduate Student
Wired recently produced a nifty graphic that showed were the major tech firms recruit their employees. The messages are obvious:
- Physical proximity – this is West Coast/Canada intensive.
IBM is the exception, in that it recruits from India. But still, it recruits from the big Indian engineering programs.
The other message that I get is from the absences. 1. The Midwest engineering powerhouses (Ohio, Kansas, Michigan, Illinois) are under represented due to geography. Path dependence is cruel. 2. The Ivy League and elite liberal arts are sparsely represented, probably due to a lot recruitment by finance and smaller engineering departments. So in terms of the upper strata of the economy, West Coast is for innovation, East Coast is elite training, and the Midwest is for building cars and stuff.
cfp on “The Rise of Finance: Causes and Consequences of Financialization” at Socio-Economic Review journal
Now that the spring semester is ending, some of our readers are kicking the manuscript preparations into high gear, judging from the uptick in the number of review requests that I’m starting to receive. For those of you looking for a special issue to target as an author or a reader, I wanted to call attention to a call for papers in the Socio-Economic Review that might be of interest (click this PDF for more info: SER 2015 Special Issue CfP on Financialization):
Call for papers
“The Rise of Finance: Causes and Consequences of Financialization”
Sabino Kornrich, Emory University
Alex Hicks, Emory University
Submission deadline: July 21, 2014
Publication of Special Issue in Socio-Economic Review: 2015
The financialization of the economy, as seen in the growing importance of financial markets and the shift from industrial to financial capitalism, stands out as one of the largest changes in the structure of the economy over the last half of the twentieth century (Krippner 2005, 2012; van der Swaan 2014). Indeed, van der Swaan’s (2014) review points to shifts in the structure of accumulation, the role of financialization in firms’ attention to shareholder value, changing individual and household approaches toward everyday life, and related changes in institutional structures. One important line of research focuses on the increasing concentration of profits in financial firms and its consequences for inequality due to its influence on top incomes, the labor share of income, and the distribution of income and profits across sectors (Tomaskovic-Devey and Lin 2011; Volscho and Kelly 2012; Kristal 2013). Even in firms which focus primarily on non-financial activities, financial divisions have become more important (Krippner 2012). While existing research has convincingly demonstrated the rise of financialization in the USA, fewer studies have examined these processes in other countries (e,g, Akkemik and Özen 2014, Godechot 2012). An important agenda remains to understand the extent to which the patterns and dynamics of financialization can be generalized or differ significantly across different types of capitalism, as well as how these have potentially reshaped global economic interdependencies.
This special issue aims to build on and extend this research by enlarging the explanatory focus. We seek contributions that either add empirical insights and advance theory in relation to the underlying causes of financialization, the consequences of financialization for
individual-level and organizational outcomes, and extending the focus of financialization
research beyond the United States and into a broader frame of comparative political