Big Data and Hayek

A recent post by Matt Bogard drew my attention to a Forbes article entitled "Big Data Versus Hayek." Both Matt's post and the article are interesting, and I recommend reading both (they're short), but I want to pick a few nits with the Forbes article.

The authors mention a few examples of firms using big data methods to "set prices" and note that

What’s interesting about such centralized, algorithmic approach to price setting is how un-Hayekian it is.

This is an interesting point as far as it goes, but a couple of things should be noted. Hayek's point about centralized decision making was about markets, not firms. If complete decentralization were optimal, then no firm need exist. Of course, such an absurd conclusion can't be drawn from Hayek's work.

Firms are obviously necessary (and Matt makes some good points about this in relation to Coase), but Hayek's point is about the markets in which firms operate. Decentralized markets generate prices that reflect the availability of resources needed for production and the tastes and preferences of consumers; these prices allow firms to provide what consumers want. The USSR was (largely) without the coordinating effect of prices, a key cause of its demise.

The second problem is the idea that these firms are "setting prices." Surely a price tag or the rate offered on the Uber app will in some sense be "set" by the firm. However, the firm has very little control over the price they receive because ultimately the consumer determines the equilibrium price to which actual prices continually move. The influence of regulations, competitors, and (perhaps most powerfully) the preferences of consumers will decide what price the firm receives. The firm can "set" any price it likes, but decentralized free markets ensure that these prices come to closely approximate the value consumers place on the product.

Do Supermarkets Have Market Power?

Back in 2013, a former graduate school colleague of mine at K-State, Veronica Pozo (now at Utah State) presented a paper on price transmission along the beef supply chain (retail, wholesale, and farm prices). The authors used data from the BLS and retail scanner data to look for asymmetries in the price adjustment process.

On the issue of BLS and scanner data, the authors note some problems with BLS data:

Evidence suggests that the BLS retail price data may be biased. Hausman (2003) showed that the methodology BLS uses to calculate the food Consumer Price Index (CPI) may overestimate the price of food. The omission of random-weight food items (BLS collects only price data, but does not collect quantity data) and supercenter purchases (reflecting shifts in shopping patterns to lower-priced stores) may cause a significant upward bias on price estimates. In addition, BLS data do not account for large volumes sold at discounted prices during retail specials (Rojas et al., 2008; Lensing and Purcell, 2006). Therefore, this issue raises the question of whether findings from previous studies that have used BLS retail price data are reliable.

Potpourri

I haven't done one of these in awhile, so I thought I'd put some stuff I've read recently that caught my eye.

Jayson Lusk recently blogged about my article currently in review at the Journal of Regulatory Economics on the effects of USDA and EPA regulation on ag productivity.

Don Boudreaux, spurred by a back and forth between Russ Roberts and Paul Krugman, has a couple of great posts (here and here) on economics as a science and its ability to generate falsifiable predictions. Very thought provoking.

Marc Bellemare documents the top 5 journals in ag economics based on recently-calculated impact factors. The ordering is interesting, but it's important to remember that there are many measures of journal quality. This paper, sent to me today by a colleague, puts ag and applied economics journals into groups (A+, A, B, C, D). All of this is good information which, as an assistant professor, I find very useful.

Matt Bogard has some interesting thoughts on the abilities required for working as a data scientist outside the academic world.

Fed: Rate Hike Will Come Later

On Wednesday, the Federal Reserve convened its regular FOMC meeting to discuss monetary policy and the state of the economy. These meetings are highly anticipated by the finance world, and rightly so. At these meetings, the chair of the Federal Reserve gives her thoughts on the economy and, some hope, an indication as to what interest rate policy will be in the coming months.

This particular meeting was interesting in that expectations for a rate hike had generally been high this year. Earlier this year, many expected a hike in the Federal Funds Rate (FFR) by mid-year. After this meeting, likely very few hold this position. Chair Yellen essentially indicated that a rate hike may come by the end of the year but that upward movement in the FFR target will be slower than originally anticipated.

Yellen has indicated before that monetary policy is "data dependent," so the slower-than-anticipated rate hikes imply that Yellen is not happy with the employment and inflation data/forecasts. The employment aspect of this is especially complicated, since we know that labor force participation has fallen and continues to fall, and many still remain underemployed.

The Atlanta Fed's GDP Now forecast for 2nd quarter GDP has strengthened dramatically since early June. To get anywhere close to the Fed's original annual growth forecast, 2nd, 3rd, and 4th quarter GDP growth is going to have to offset the -0.7% decline in GDP in the 1st quarter. Slow GDP growth also provides justification for low rates.

Intervention Breeds Intervention: The Case of the Trans Fat Ban

The recent decision to eliminate trans fats by regulatory fiat is an interesting example of intervention breeding intervention. It's safe to say everyone in my generation (I was born in the mid 1980s) was brought up on the Food Guide Pyramid. Unlike the vaunted Swanson Pyramid of Greatness we now know that the advice given in the Food Guide Pyramid isn't great. (Even South Park jumped in on the conversation.) The Pyramid taught that grains were the foundation of sound nutrition and that fats, particularly saturated animal fats, were bad. These fats were thought to cause heart disease and a whole host of issues.

The reality is that the sugar found in grain products like bread and pasta are the heart disease culprit. The Pyramid, designed by well-intentioned folks at the USDA and backed up by the CDC incentivized the use of partially-hydrogenated oils as a substitute to saturated animal fats. These partially-hydrogenated oils are a major source of trans fats. It turns out that the Food Guide Pyramid was wrong and your grandma was right: excessive carbohydrate consumption is bad for you, butter is better than margarine (often containing partially-hydrogenated vegetable oil), and animal products build healthy bodies.

So, it seems to me, if it weren't for the demonization of saturated fats and animal products in general, we wouldn't have been eating so many trans fats from partially-hydrogenated oils over the past 30 years. We'd have been following the same rules our grandmas taught us. There wouldn't be any need to ban trans fats because the crusade against the healthier alternative wouldn't have happened. This is, it seems, a negative outcome of government domination of the health conversation. The fitness community has been on the low-carb-is-best bandwagon for a long time. The rest of us are finally catching up.

I hope in the future school lunches are more in line with the "carbs aren't so great and animal products are" view. I suspect this will not only make them healthier for the growing bodies and minds of our children, but kids will actually want to eat the food.

Matt Bogard on GMOs and Farm Subsidies

Back in April, Matt Bogard posted a series of questions on GMOs and farm subsidies. As Matt notes, the typical view of ag subsidies is almost completely at odds with the data and relevant research.

I definitely recommend reading the whole thing, so here are his questions:

1) Do farm subsidies encourage farmers to plant biotech or GMO seeds?

2) If subsidies drive the production of commodities and most of these are GMO,  aren’t we indirectly subsidizing GMOs?

3) Do farm subsidies make unhealthy foods cheaper and contribute to obesity?

4) Do farm subsidies largely prop up wealthy farmers vs. helping small farmers thrive in a volatile, competitive global and corporate dominated marketplace?

I'm fairly confident that a large percentage of the population would confidently answer "yes" to each of these questions. The reality is either "no" or at least a much less emphatic "maybe."

Perfect Markets and the Beauty of B School Economics

Don Boudreaux at Cafe Hayek has written several posts recently that are related to some of the themes I've been focusing on lately. (See his posts here, here, and here.) I'll quote from the first one and provide some of my thoughts.

The market process is chiefly one of entrepreneurs spotting market failures and sub-optimal situations – spotting problems that have yet to be ‘solved’ adequately by market (or non-market) forces – and then experimenting with actions to address such problems.  The discipline to ensure that such experiments work as well as possible over time is supplied by (1) the fact that those who do the experimenting in private markets put their own money and effort on the line (rather than money and effort forcibly commandeered from others), (2) consumers’ freedom to buy or not to buy the resulting products, and (3) the actual and potential competing experimenters who do, or might, arise along side of the initial entrepreneurial experimenter.  And this on-going process is indeed just that: a process that, as much as it improves market performances over time, never comes close to creating any situation that deserves the name “perfect market.”