Uncategorized – Page 6 – Michael Sykuta

A GMO Rose By Any Other Name?

An interesting article in today’s New York Times on how some companies are circumventing regulatory barriers in developing new plant varieties by using “genetic editing” rather than “genetic engineering,” which is often referred to as GMO. The difference? Not the outcome (a plant that’s DNA is changed to express different traits); just the way in which the genetic change is produced. From the article (emphasis added):

Regulators around the world are now grappling with whether these techniques are even considered genetic engineering and how, if at all, they should be regulated.

“The technology is always one step ahead of the regulators,” said Michiel van Lookeren Campagne, head of biotechnology research at Syngenta, a seed and agricultural chemical company.

The problem stems largely from defining (and regulating) genetically modified plants not based on the fact that they are genetically modified, but based on the technological process by which they are modified. Humans have been manipulating plant genes for millennia; more recently using (a growing number of) technologies in the lab rather than long, drawn-out, and less-precise processes in the field. That poses a problem for regulators and critics who need to carefully circumscribe what kind of genetic modifications are, and aren’t, considered acceptable.

Meanwhile, the real question is whether a (genetically modified) rose by any other name (or technology) would still smell as sweet.

The Price and Quality of Wine, Part II

After my previous post on the relation between the price and quality of the top red wines and the top wines under $50 in Vivino’s 2014 “People’s Choice” rankings, I got curious about the price-quality relation for the top white and sparkling wines. And I must say, i was a bit surprised.

For the Top 100 white wines, there is actually a moderate correlation between the quality rankings and prices; with a correlation coefficient of 0.51. Price isn’t a perfect signal for quality. In fact, the seventh best white wine cost only $27, just more than half the average price of $52.48. But price and quality are at least somewhat related overall, with the top five wines ranging from $244 to $404 and 21 of the last 25 wines below $50. As expected, the variance in price relative to the average was less than for the reds (std dev of 63.84).

However, if you’re looking for sparkling wine, it’s much safer to let price be your guide in judging quality. Price and quality rating have a correlation coefficient of 0.715, suggesting a fairly strong correlation between the two. This is completely opposite the case of the reds (recall, the price-quality correlation for those was just 0.053). And while the range of the Top 100 sparkling wine prices was considerable, from a high of $476 to a low of $10, the variance was lower relative to the average than for either the reds or the white (std dev = 95.779, average = $126.78)

Now, there are some caveats one should make about inferring too much from such a simple comparison. But the basic lesson is pretty straight-forward: if you’re shopping for quality sparkling wines, let price be your guide–at least in an ordinal sense. You’ll have to judge for yourself how much the additional quality is truly worth (i.e., is the quality of a top 10 wine five times better than the quality of the lowest 25, as their price difference would suggest?). If shopping for whites, price is a bit less reliable a guide, but not wholly unrelated. If shopping for reds, however, be careful about reading too much into the quality of the wine from the price on the bottle.

The Price and Quality of Wine, 2014

The makers of the Vivino app, which allows wine lovers to rate and share reviews of wines, produced their Top 100 lists for 2014. According to their website, over 13 million users rated over 3 million wines. Based on those reviews, they produced lists of the Top 100 reds, whites, sparkling wines, and “Under $50” wines. The lists included the average price reported by their users (another feature included in the app). Naturally, I thought it would be interesting to see how well prices correlated with the quality rankings.

I started with the Under $50 category because, seriously, if I’m going to buy a bottle of wine it’s going to be under $50 unless I’m hosting a Nobel Laureate wine connoisseur, or I’m out for dinner at a nice restaurant on someone else’s dime. Besides, there are WAY too many good wines under $50 to spend more than that for most purposes. Using the ranking score (from 1 to 100), the reported prices have a positive correlation, as one would expect (higher ranked wines have higher prices; lower ranked wines have lower prices), but it’s a pretty weak relationship (0.2075).* This suggests that while a higher price wine may be higher quality, don’t count on it. That ought to make you feel better about grabbing that less expensive bottle for your neighbor’s New Year’s party. The average price of wines on the list was $35.03, which is still higher than you might buy for an evening at home, but the cheapest wine was just $11 (Wild Rock’s The Infamous Goose Sauvignon Blanc Marlborough 2013 at #97) and only one wine hit the $50 cap (Pago De Carraovejas‘ Ribera del Duero Crianza Tinto 2009 at #31).

I was going to stop there, but decided to look at the Top 100 red wines as well. Since there was no cap on the prices, one might expect some very expensive, highly rated wines to push the expected correlation. However, it’s quite the opposite. The correlation coefficient between rank and price is a mere 0.0528, which means virtually NO relationship between quality ranking and price. Of course, the standard deviation was much larger relative to the average price (std dev = 803.5; average = $549.30) than it was for the lower priced wines (std dev = 10.53, average = $35.03). The highest priced wine on the list was $5,455 (yes, that’s right, Pétrus’ Pomerol 1982 at #36) while the lowest was just $81 (Concha y Toro’s Don Melchor Cabernet Sauvignon 2009 at #82). So if you’re looking at wines in the $100+ range, there is a good chance that relative prices tell you next-to-nothing about the quality in the bottle.

One thing that may affect the weaker relationship is the context in which the most expensive wines are likely purchased. I would suspect a good percentage of these were purchased in restaurants, where mark-ups can be quite high and varied across establishments. And one wouldn’t expect a large number of the highest priced wines to be purchased, even among the 13 million Vivino users, so there may a good deal of variance in reported prices and quality that is masked in the reporting of averages. Perhaps the good people at Vivino would be willing to share more of the data for a more thorough analysis.

I opted not to take the time to do the exercise for the Top Whites or Top Sparkling Wines. For one, I generally prefer reds. I would hypothesize that the correlation is probably just as low for the whites and sparkling, but I suspect the variance in price would be lower for each of those than for the reds, since reds are generally better for aging and therefore may have some appreciated (or potential) time value built-in that the whites may not. If you decide to check it out for yourself, please post a follow-up in the comments!

So you want to make sure you’re getting a good bottle of wine at a good price? Crowd-sourcing quality using apps like Vivino (or Untappd for craft brews) is likely a much more reliable source than just relying on price. Of course, a knowledgeable friend or local wine seller wouldn’t hurt either.

* Note: I edited the post to make the correlations more intuitive (higher quality, higher price positive correlations) rather than the negative numbers that resulted from the actual ordinal rank score. I also added in the names of mentioned wines along with a link to the wine’s profile on Vivino.com).

Formula Pricing and Profit Sharing in Inter-Firm Contracts

Roger Blair and Francine Lafontaine have a new paper out on “Formula Pricing and Profit Sharing in Inter-Firm Contracts” (here). They explore the use of profit-sharing contracts for vertical relationships, particularly the case of successive monopoly or the double-marginalization problem. Naturally, their focus is on franchise relations. The abstract follows:

Ronald Coase viewed transaction cost minimization as a central goal of contracting and organizational decisions. We discuss how a solution to the traditional successive monopoly problem that has not been discussed in the literature can economize on such costs. Specifically, we show that when we allow for profit sharing between upstream and downstream firms, a simple formula pricing contract can be used to generate the vertically integrated level of profits. This simple contract, empirically, would take the form of the standard linear wholesale price contracts that are ubiquitous in vertical contexts, even those where we might expect successive monopoly to be an issue. We discuss the advantages of the proposed contract from a transaction cost perspective. We also discuss some of its limitations, in particular the likelihood of misrepresentation of costs, and ways in which such misrepresentation might be addressed in the contract.

Journal of Law, Finance and Accounting International Conference 2015

The Journal of Law, Finance and Accounting (JLFA) and Hong Kong Polytechnic University School of Accounting and Finance are hosting an international conference June 1-2, 2015, on research at the intersection of the three fields. The JLFA is a new outlet sponsored by the NYU Stern School of Business, NYU Law School and KPMG. Per the email I received:

Topics of interest include, but are not limited to:

The impact of the structure of the legal system — including legal origins, procedural rules, and the legal environment in general, on the evolution of financial contracts, financial markets, business enterprises and business groups.
The impact of particular legal and market institutions, including accounting, on financial markets and corporate actions, and innovation, economic growth and stability.
The co-evolution of the legal rules and market institutions that govern financial sector activity, that activity itself, and the nature of the broader economy and financial markets.
The regulation, organization, and performance of financial institutions.
The relationships between the structure and performance of financial institutions, and the performance of these institutions and the overall performance of financial markets and economies.
The interplay between legal rules, accounting regulations, corporate governance, firm performance, cost of equity and debt capital, financial market performance, and economic performance.
The political economy of the regulation of corporate governance, financial institutions, and financial markets.
Accounting, finance, and legal issues concerning ownership and property.

Sounds like an interesting opportunity. For more information, see the conference announcement at SSRN (linked here).

Food Access and Food Policy

Ploeg, Dutko and Breneman have a new paper coming out in Applied Economic Perspectives & Policy taking to task the way food access and “food desserts” are measured and the implications of those challenges for policy design.

They provide a good description of the ways in which food access is measured and some of the data sources used for developing those measures. Most of these have to do with measuring things like income, distance to stores, availability of transportation, etc.; measuring retail food availability versus healthy food availability; a tendency to focus only on low-income neighborhoods; and defining what is means to say access is “adequate” or “inadequate” from a policy perspective.

One of the things they do not mention, which I have been thinking about recently as a potential research project, is the extent to which food access measures correlate with health outcomes in a community. This is closely related to work Diogo Souza Monteiro at Newcastle University has begun looking at the kinds of grocery stores in UK neighborhoods and the incidence of various public health outcomes.

Focusing on health outcomes would go well beyond the critique of the tendency to focus on low-income neighborhoods, since even in communities where food access is (relatively) good or where incomes are on average higher, there could be differing health outcomes associated with the types and numbers of food retailers available. Just because a healthy food option is readily available does not mean local health will necessarily be better. And after all, a significant reason for caring about food access is not for the sake of access to food itself, but for the (public) health consequences of limited food access. So the existence of a correlation between health outcomes (or types of health outcomes) and measures of food access and food security would seem a necessary first step in designing any potential policies to address the food access problem.

That said, Ploeg, Dutko and Breneman’s paper seems a good starting point for thinking more clearly about food access and food policy. Unfortunately, I think the paper is gated. The abstract follows.

Policymakers have dedicated increasing attention to whether Americans have access to healthful food. As a result, various methods for measuring food store access at the national level have been developed to identify areas that lack access. However, these methods face definitional, data, and methodological limitations. The focus on neighborhoods instead of individuals underestimates the barriers that some individuals face in accessing healthy food, and overestimates the problem in other neighborhoods. This paper reviews and critiques currently available national-level measures of food access. While multiple measures of food access are needed to understand the problem, we recommend greater attention be paid to individual measures of food store access.

Research Productivity of New Economics PhDs

The Economist posted a blog last week about the research productivity of new PhDs in economics. They point to a recent paper by John Conley and Ali Sina Önder in the Journal of Economic Perspectives. Below is the abstract:

We study the research productivity of new graduates from North American PhD programs in economics from 1986 to 2000. We find that research productivity drops off very quickly with class rank at all departments, and that the rank of the graduate departments themselves provides a surprisingly poor prediction of future research success. For example, at the top ten departments as a group, the median graduate has fewer than 0.03 American Economic Review (AER)-equivalent publications at year six after graduation, an untenurable record almost anywhere. We also find that PhD graduates of equal percentile rank from certain lower-ranked departments have stronger publication records than their counterparts at higher-ranked departments. In our data, for example, Carnegie Mellon’s graduates at the 85th percentile of year-six research productivity outperform 85th percentile graduates of the University of Chicago, the University of Pennsylvania, Stanford, and Berkeley. These results suggest that even the top departments are not doing a very good job of training the great majority of their students to be successful research economists. Hiring committees may find these results helpful when trying to balance class rank and place of graduate in evaluating job candidates, and current graduate students may wish to re-evaluate their academic strategies in light of these findings.

I remember one of my graduate advisers, Lee Benham, claiming that the mode number of publications among PhD economists was zero. I think that was Lee’s way of encouraging grad students who are sweating out their dissertations and trying to get papers out for publication. Conley and Önder’s results would seem to substantiate his claim.