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Innovation trends in agriculture and their implications for M & A analysis

Innovation trends in agriculture and their implications for M & A analysis published on

This is a repost from the Mergers in Ag-Biotech blog symposium over at Truth on the Market. If you’re interested in more perspectives on the topic, I encourage you to read the other posts there.  If you’d like to comment, please do so on the TOTM version so it’s part of the general discussion.

The US agriculture sector has been experiencing consolidation at all levels for decades, even as the global ag economy has been growing and becoming more diverse. Much of this consolidation has been driven by technological changes that created economies of scale, both at the farm level and beyond.

Likewise, the role of technology has changed the face of agriculture, particularly in the past 20 years since the commercial introduction of the first genetically modified (GMO) crops. However, biotechnology itself comprises only a portion of the technology change. The development of global positioning systems (GPS) and GPS-enabled equipment have created new opportunities for precision agriculture, whether for the application of crop inputs, crop management, or yield monitoring. The development of unmanned and autonomous vehicles and remote sensing technologies, particularly unmanned aerial vehicles (i.e. UAVs, or “drones”), have created new opportunities for field scouting, crop monitoring, and real-time field management. And currently, the development of Big Data analytics is promising to combine all of the different types of data associated with agricultural production in ways intended to improve the application of all the various technologies and to guide production decisions.

Now, with the pending mergers of several major agricultural input and life sciences companies, regulators are faced with a challenge: How to evaluate the competitive effects of such mergers in the face of such a complex and dynamic technology environment—particularly when these technologies are not independent of one another? What is the relevant market for considering competitive effects and what are the implications for technology development? And how does the nature of the technology itself implicate the economic efficiencies underlying these mergers?

Before going too far, it is important to note that while the three cases currently under review (i.e., ChemChina/Syngenta, Dow/DuPont, and Bayer/Monsanto) are frequently lumped together in discussions, the three present rather different competitive cases—particularly within the US. For instance, ChemChina’s acquisition of Syngenta will not, in itself, meaningfully change market concentration. However, financial backing from ChemChina may allow Syngenta to buy up the discards from other deals, such as the parts of DuPont that the EU Commission is requiring to be divested or the seed assets Bayer is reportedly looking to sell to preempt regulatory concerns, as well as other smaller competitors.

Dow-DuPont is perhaps the most head-to-head of the three mergers in terms of R&D and product lines. Both firms are in the top five in the US for pesticide manufacturing and for seeds. However, the Dow-DuPont merger is about much more than combining agricultural businesses. The Dow-DuPont deal specifically aims to create and spin-off three different companies specializing in agriculture, material science, and specialty products. Although agriculture may be the business line in which the companies most overlap, it represents just over 21% of the combined businesses’ annual revenues.

Bayer-Monsanto is yet a different sort of pairing. While both companies are among the top five in US pesticide manufacturing (with combined sales less than Syngenta and about equal to Dow without DuPont), Bayer is a relatively minor player in the seed industry. Likewise, Monsanto is focused almost exclusively on crop production and digital farming technologies, offering little overlap to Bayer’s human health or animal nutrition businesses.

Despite the differences in these deals, they tend to be lumped together and discussed almost exclusively in the context of pesticide manufacturing or crop protection more generally. In so doing, the discussion misses some important aspects of these deals that may mitigate traditional competitive concerns within the pesticide industry.

Mergers as the Key to Unlocking Innovation and Value

First, as the Dow-DuPont merger suggests, mergers may be the least-cost way of (re)organizing assets in ways that maximize value. This is especially true for R&D-intensive industries where intellectual property and innovation are at the core of competitive advantage. Absent the protection of common ownership, neither party would have an incentive to fully disclose the nature of its IP and innovation pipeline. In this case, merging interests increases the efficiency of information sharing so that managers can effectively evaluate and reorganize assets in ways that maximize innovation and return on investment.

Dow and DuPont each have a wide range of areas of application. Both groups of managers recognize that each of their business lines would be stronger as focused, independent entities; but also recognize that the individual elements of their portfolios would be stronger if combined with those of the other company. While the EU Commission argues that Dow-DuPont would reduce the incentive to innovate in the pesticide industry—a dubious claim in itself—the commission seems to ignore the potential increases in efficiency, innovation and ability to serve customer interests across all three of the proposed new businesses. At a minimum, gains in those industries should be weighed against any alleged losses in the agriculture industry.

This is not the first such agricultural and life sciences “reorganization through merger”. The current manifestation of Monsanto is the spin-off of a previous merger between Monsanto and Pharmacia & Upjohn in 2000 that created today’s Pharmacia. At the time of the Pharmacia transaction, Monsanto had portfolios in agricultural products, chemicals, and pharmaceuticals. After reorganizing assets within Pharmacia, three business lines were created: agricultural products (the current Monsanto), pharmaceuticals (now Pharmacia, a subsidiary of Pfizer), and chemicals (now Solutia, a subsidiary of Eastman Chemical Co.). Merging interests allowed Monsanto and Pharmacia & Upjohn to create more focused business lines that were better positioned to pursue innovations and serve customers in their respective industries.

In essence, Dow-DuPont is following the same playbook. Although such intentions have not been announced, Bayer’s broad product portfolio suggests a similar long-term play with Monsanto is likely.

Interconnected Technologies, Innovation, and the Margins of Competition

As noted above, regulatory scrutiny of these three mergers focuses on them in the context of pesticide or agricultural chemical manufacturing. However, innovation in the ag chemicals industry is intricately interwoven with developments in other areas of agricultural technology that have rather different competition and innovation dynamics. The current technological wave in agriculture involves the use of Big Data to create value using the myriad data now available through GPS-enabled precision farming equipment. Monsanto and DuPont, through its Pioneer subsidiary, are both players in this developing space, sometimes referred to as “digital farming”.

Digital farming services are intended to assist farmers’ production decision making and increase farm productivity. Using GPS-coded field maps that include assessments of soil conditions, combined with climate data for the particular field, farm input companies can recommend the types of rates of applications for soil conditioning pre-harvest, seed types for planting, and crop protection products during the growing season. Yield monitors at harvest provide outcomes data for feedback to refine and improve the algorithms that are used in subsequent growing seasons.

The integration of digital farming services with seed and chemical manufacturing offers obvious economic benefits for farmers and competitive benefits for service providers. Input manufacturers have incentive to conduct data analytics that individual farmers do not. Farmers have limited analytic resources and relatively small returns to investing in such resources, while input manufacturers have broad market potential for their analytic services. Moreover, by combining data from a broad cross-section of farms, digital farming service companies have access to the data necessary to identify generalizable correlations between farm plot characteristics, input use, and yield rates.

But the value of the information developed through these analytics is not unidirectional in its application and value creation. While input manufacturers may be able to help improve farmers’ operations given the current stock of products, feedback about crop traits and performance also enhances R&D for new product development by identifying potential product attributes with greater market potential. By combining product portfolios, agricultural companies can not only increase the value of their data-driven services for farmers, but more efficiently target R&D resources to their highest potential use.

The synergy between input manufacturing and digital farming notwithstanding, seed and chemical input companies are not the only players in the digital farming space. Equipment manufacturer John Deere was an early entrant in exploiting the information value of data collected by sensors on its equipment. Other remote sensing technology companies have incentive to develop data analytic tools to create value for their data-generating products. Even downstream companies, like ADM, have expressed interest in investing in digital farming assets that might provide new revenue streams with their farmer-suppliers as well as facilitate more efficient specialty crop and identity-preserved commodity-based value chains.

The development of digital farming is still in its early stages and is far from a sure bet for any particular player. Even Monsanto has pulled back from its initial foray into prescriptive digital farming (call FieldScripts). These competitive forces will affect the dynamics of competition at all stages of farm production, including seed and chemicals. Failure to account for those dynamics, and the potential competitive benefits input manufacturers may provide, could lead regulators to overestimate any concerns of competitive harm from the proposed mergers.

Conclusion

Farmers are concerned about the effects of these big-name tie-ups. Farmers may be rightly concerned, but for the wrong reasons. Ultimately, the role of the farmer continues to be diminished in the agricultural value chain. As precision agriculture tools and Big Data analytics reduce the value of idiosyncratic or tacit knowledge at the farm level, the managerial human capital of farmers becomes relatively less important in terms of value-added. It would be unwise to confuse farmers’ concerns regarding the competitive effects of the kinds of mergers we’re seeing now with the actual drivers of change in the agricultural value chain.

A win for the auto cartel, a loss for Missourians

A win for the auto cartel, a loss for Missourians published on

The Missouri Auto Dealer Association (MADA) has been exercising its political muscle for at least a couple years to protect its antiquated state-supported cartel over new car sales. It seems they have finally succeeded in court where their lobbying efforts have failed. In an opinion  last week by Cole County Circuit Judge Daniel Green, the court ruled that Missouri state statutes governing automobile distribution prohibit Tesla from operating its own retail stores in the state.

The case, which the MADA filed against the Missouri Department of Revenue, contested the State’s issuance of two franchise dealer licenses to Tesla for Tesla to open its own “franchise” retail stores. Basically, Missouri statutes have implemented a circular argument that prohibits auto manufacturers from owning new vehicle dealerships. § 301.550.3 RSMo specifically limits new car dealers to being franchises, statutorily side-stepping the possibility of a non-franchise new car dealer. The court essentially argued (perhaps rightly) that Tesla’s self-dealing of the franchise to itself was merely a rhetorical ploy to circumvent this failure of the statutes to allow for non-franchise dealers. However, even if that side-step were permissible, § 407.826.1 RSMo specifically prohibits auto industry franchisors from “owning or operating a new motor vehicle dealership in this state.”

Judge Green’s opinion basically means the laws of the state of Missouri preclude the possibility of any auto manufacturer selling its cars in Missouri directly to consumers. While Tesla can continue to operate its two service centers in the state, it cannot make car sales there. Instead, the company must continue to sell to Missourians over the internet with a point-of-sale in another state. (So much for more sales jobs.)

I and others have written previously (here, here, and here) why bans on Tesla’s direct-to-consumer sales model are bad for consumers and for society in general. This most recent ruling in Missouri just highlights how fundamentally flawed the regulation of commerce can be. Missouri’s laws, to the extent they ever made sense, are rooted in an antiquated industry and technological setting. Advancements in information technology alone have undercut many, if not all, of the economic justifications for an auto manufacturer to use a franchised distribution system. Laws that were written to protect franchisees in a 1950s-era distribution system do nothing now but raise consumers’ costs and thwart technological and organizational innovation that make everyone better off. Everyone, that is, except the franchised auto dealer cartel that sees all too clearly how little value it now adds in the sale and distribution of new cars.

Hopefully Missouri’s legislature will have the gumption to fix the flaws in its statutes that limit all new car retailers to “franchises” and instead let auto manufacturers (or any other manufacturer) choose the model they find best for themselves and their customers.

 

Markets, Incentives and a Krugman (et al.) Fail

Markets, Incentives and a Krugman (et al.) Fail published on

Pity the poor teenager taking an AP Economics course whose father is an economist. Especially when the local school district has adopted a text that is based on Paul Krugman’s Economics (3rd ed., coauthored with Robin Wells). Even more especially when the father-economist has a fundamental disagreement with much of what Mr. Krugman has become since surrendering his academic credentials for political punditry. Yeah, that’s my lucky kid.

So of course, I had to thumb through the text. I suppose I shouldn’t have been too surprised to find on only the third page of Module 1 a gross error in explaining the trouble with command economies. After explaining the failed history of command economies, the text asserts (p. 3):

At the root cause of the problem with command economies is a lack of incentives, which are rewards or punishments that motivate particular choices.

Where to start? How about with the simple fact that incentives always exist, no matter the type of economy. And there were plenty of incentives in the former Soviet Union (the textbook example of a command economy–literally in this case). I remember the late Nobel Prize-winning economist James Buchanan sharing the story of his visit to Moscow shortly after the fall of the Soviet empire during which he was surprised to learn of a market for burned out light bulbs — because people could use them to steal working light bulbs from their workplaces when they couldn’t get light bulbs in the stores. People responding to incentives. It’s The Basics 101. The problem with command economies is not a lack of incentives–but a lack of incentives that are based on the wants of consumers themselves and a lack of incentives for innovation or efficiency. In short–the absence of the incentives created by a free market economy.

More importantly, the focus on incentives misses the point in a way that has significant implications for what the text goes on to say about economic policy. At the root of the problem with command economies was the lack of information available to decision-makers about the wants and desires of an entire population of individual consumers with different tastes and preferences and about the conditions of scarcity and desires in dispersed local markets across the society’s economy. As F.A. Hayek (another Nobel Prize winner) explained, the fundamental role of markets is to discover and reveal information based on the complex interactions of individuals across product types and geographic space.These interactions result in prices that reflect the relative scarcity and value of goods across society. Those prices create incentives, and those incentives are fundamentally important in guiding individuals to use their resources in ways that innovate, create value, and serve consumers. But the incentives are secondary–derived from the information discovery role of the market that cannot be replicated in a command economy.

Why is this such an important distinction? Because of the way the text goes on to describe the objective of policy making. After (fairly accurately) explaining how prices create incentives, the authors state (p. 3):

In fact, economists tend to be skeptical of any attempt to change people’s behavior that doesn’t change their incentives. For example, a plan that calls on manufacturers to reduce pollution voluntarily probably won’t be effective; a plan that gives them a financial incentive to do so is more likely to succeed.

The implication? All we need to do is create incentives (implicitly, in the form of taxes, fines or subsidies) to create financial incentives for manufacturers (or people) to do what we want them to do. But this line of argument ignores the more fundamental question of determining whether the plan makes social or economic sense in the first place. What is the economic basis for whether we uses fines or subsidies and how large they should be? At what point, if any, would doing nothing be economically more efficient than doing something? By taking away the fundamental information function of the market and jumping immediately to incentives, we skip the whole messy discussion of the information requirements by legislators, bureaucrats and policy makers in coming up with “the plan” to begin with. All we need to do is trust the omniscience and beneficence of policy makers to know what the “right price” is–and to set arbitrarily the incentives to get the outcomes we want. But that’s exactly why command economies fail.

The root problem of a command economy is not that there are no incentives, but that there are socially inefficient incentives. The incentives are socially inefficient because it is impossible for a central authority to know the value individual citizens place not only on existing goods and services, but on the latent value of potential goods and services that can only be discovered by innovation and experimentation–and a central planner cannot think beyond her own imagination in the realm of possibilities. And it’s not only true of Soviet-style planned economies, but of any central decision-making authority–including the US federal government–even in the context of a heavily market-dominated economy.

Note: AP Economics students (and teachers), remember….the correct answer on the test may not be the right answer in reality. Answer the questions from the textbook based on the information in the textbook. But in your real life as a consumer of information and participant in the market place of ideas and politics, be sure to get to the fundamentals rather than the superficial.

Tesla, Dealer Franchise Laws, and the Politics of Crony Capitalism

Tesla, Dealer Franchise Laws, and the Politics of Crony Capitalism published on

About a year ago I posted a couple of pieces (here and here) related to auto dealers’ attempts in various states to shut down Tesla’s direct-to-consumer distribution system. Dan Crane (Michigan Law) has a recent paper on the issue available at SSRN. Below is the abstract:

Tesla Motors is fighting the car dealers’ lobby, aided and abetted by the legacy Detroit manufacturers, on a state by state basis for the right to distribute its innovative electrical automobiles directly to consumers. The Tesla wars showcase the important relationship between product innovation and innovation in distribution methods. Incumbent technologies may block competition by new technologies by creating legal barriers to innovative distribution methods necessary to secure market acceptance of the new technologies. While judicial review of such special interest capture is generally weak in the post-Lochner era, the Tesla wars are creating new alliances in the political struggle against crony capitalism that could contribute to a significant re-telling of the conventional public choice story.

A Review of Occupational Licensing

A Review of Occupational Licensing published on

This week the US Supreme Court is hearing arguments in the case of North Carolina Board of Dental Examiners v. Federal Trade Commission, addressing the questions of whether (or under what terms) state occupational licensing boards are immune from antitrust scrutiny. This is the case I referred to last week and linked to the preview of the arguments on SCOTUSblog.

Today I ran across a review of Morris Kleiner’s recent book, Stages of Occupational Regulation: Analysis of Case Studies, on Econ Journal Watch. Uwe Reinhardt (Princeton) provides a great overview of the general issue and Kleiner’s treatment of it. Below is the abstract of Reinhardt’s review:

The licensing of occupations—a very forceful intervention in markets—is pervasive and growing in modern economies. Yet the attention paid to it by economists and economics textbooks has been small. Highly welcome, therefore, has been the extensive and intensive work on this subject by Morris Kleiner. Kleiner’s latest book, titled Stages of Occupational Regulation: Analysis of Case Studies (2013), explores the progression of occupational regulation, from mere registration to certification to outright licensing—three distinct stages. Kleiner carefully selects for his analysis a series of occupations representing the stages of regulation, devoting a chapter to each occupation. He uses a variety of statistical approaches to tease out, from numerous databases, what the impact of mild to heavy regulation on labor markets appears to be.

Kleiner’s work leads him to call for a pervasive review of occupational regulation in the United States, with a view towards replacing occupational licensure, which introduces the most inefficiency and welfare loss, with mere certification of occupations. That recommendation gains plausibility in an age where cheap computation and data mining makes it possible to protect consumers from low-quality and possibly dangerous services by providing robust, user-friendly information on the quality of services delivered by competing occupations, such as doctors and nurse practitioners.

You can access the full article here. I may need to add Kleiner’s book to my list of fun-things-to-read-when-I-get-a-chance.

Legal and Illegal Cartels in Europe

Legal and Illegal Cartels in Europe published on

There’s what looks to be an interesting workshop next month (10 September) in Belgium  on the organization and behavior of cartels in different legal environments. From the workshop webpage:

Economists and policy analysts know very little about the conditions under which cartels are formed in different legal environments, how they behave against outsiders, how they behave against deviating insiders, and how they react to changes in the economic environment. This event will provide a space to discuss these aspects, based on two projects funded by SEEK.
One of the projects studies cartel organization – a topic on which there is little information to date – through the lens of legal cartels. While such cartels did not have to fear detection and prosecution, they faced the same internal organizational challenges as illegal cartels. The focus is on comparing empirically, in specific sectors, the organizational forms of legal cartels in countries with different legal regimes. The project has collected data on Austrian, Finnish, Norwegian, Swedish and American legal cartels.
The other project has developed new theoretical insight into the anatomy of hard-core cartels and combined it with a rich data set on the recent German cement cartel. The results of this project will be presented to the audience attending the event. The private data set comprises about 340.000 market transactions from 36 customers of German cement producers and encompasses most of the period during which the cartel was functioning, as well as a period after the collapse of the cartel.

The conference is jointly sponsored by Bruegel and SEEK. For more details on speakers or if you’re close enough to be able to attend, check out the website for details.

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