Alpaca Lies? Speculative Bubbles in Agriculture: Why They Happen and How to Recognize Them

Agricultural & Applied Economics Association

Alpaca Lies? Speculative Bubbles in Agriculture: Why They Happen and How to RecognizeThemAuthor(s): Tina L. Saitone and Richard J. SextonSource: Review of Agricultural Economics, Vol. 29, No. 2 (Summer, 2007), pp. 286-305Published by: Oxford University Press on behalf of Agricultural & Applied Economics AssociationStable URL: http://www.jstor.org/stable/4624836 .

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Review of Agricultural Economics-Volume 29, Number 2-Pages 286-305 DOI:10.1111 /j.1467-9353.2007.00343.x

Alpaca Lies? Speculative Bubbles

in Agriculture: Why They Happen and How to Recognize Them

Tina L. Saitone and Richard J. Sexton

The speculative bubble phenomenon has been studied extensively by economists and psychologists in recent years. The recent literature is surveyed and extended to enhance the understanding of speculative bubbles in agricultural industries. The analysis is applied to the U.S. alpaca industry, where prices for breeding stock are many times higher than in Peru, home of the world's largest alpaca herd. We present a framework to assess whether current prices for U.S. alpaca stock are supported by market fundamentals or are likely to represent a speculative bubble. Finally, we identify "warning signs" common to agricultural bubbles.

S peculative bubbles have a long and colorful history in agriculture. While Dutch

tulip mania represents perhaps the most famous example, speculative manias with dire consequences for investors in pre-Civil War U.S. history include Merino sheep, Berkshire hogs, Broom corn, and Rohan potatoes (Cole). More

recently, such exotic animal and bird species as emus, Shetland ponies, thoroughbred yearlings, Boer goats, and ostriches have experienced speculative bubbles

(Gillespie and Schupp). Studying bubble episodes in agricultural history is interesting and entertain-

ing, and leads one to ask in each instance how so many people could be caught in the euphoria of the moment, making investment decisions destined to have dis- astrous consequences. The passage of time, improved access to information, and

presumably greater sophistication of investors have apparently not eliminated market's vulnerability to speculative bubbles.

Fortunately, the bubble phenomenon is better understood through the work of economists interested mostly in bubbles outside of agriculture, but the lessons learned from this research can also be helpful in understanding speculative

N Tina L. Saitone is a Ph.D. candidate in the Agricultural and Resource Economics Department at the University of California, Davis. 0 Richard J. Sexton is a professor in the Agricultural and Resource Economics Depart- ment at the University of California, Davis and member of the Giannini Foundation of Agricultural Economics.



Speculative Bubbles in Agriculture 287

bubbles in agricultural industries. Bubbles exact a real human toll in terms of lost nest eggs and disrupted or destroyed lives. Therefore, economists in a po- sition to advise agricultural investors need to understand the economics and psychology that can lead to speculative bubbles, recognize the symptoms that tend to surround them, and have an analytical framework available to determine whether prices for agricultural assets are supported by economic fundamentals or are likely the product of irrational speculation.

In this paper, we attempt to enhance understanding of speculative bubbles in agriculture by reviewing and distilling the lessons from recent advances in the economic analysis of bubbles and applying the knowledge to a contemporary U.S. agricultural industry that might currently be in the midst of a speculative bubble. Specifically, we investigate the evolution and current state of the U.S. alpaca industry and adapt an investment framework due originally to Jarvis to determine if current alpaca prices are supported by market fundamentals or if they represent a speculative bubble.

Most speculative bubbles throughout history have been studied ex post, using retrospection and econometric tests to assess whether market fundamentals or self-fulfilling speculation determined the historical price patterns. Such retro- spective analyses provide small comfort to disappointed investors, who might have avoided or at least limited losses if objective economic analysis had been available when the speculative bubble was underway. Our application to the alpaca industry is a rare attempt to investigate a potentially ongoing speculative bubble, and, as such, offers the practical benefit of advising potential investors. The more fundamental goals of the paper are to contribute to understanding the circumstances that lead to speculative bubbles in agriculture, distill the lessons that can be learned from the alpaca case and the preceding speculative bubbles, and provide a general conceptual framework to evaluate whether an agricultural asset's price is supported by economic fundamentals or likely is the product of irrational speculation.

The Economics and Psychology of Speculative Bubbles

I define a speculative bubble as a situation in which news of price increases spurs investor enthusiasm, which spreads by psychological contagion from person to person, in the process amplifying stories that might justify the price increases and bringing in a larger and larger class of investors, who, despite doubts about the real value of an investment, are drawn to it partly by envy of others' successes and partly through gambler's excitement (Shiller, 2005, p. 2).

The efficient market hypothesis (EMH) reigned supreme during the 1970s as the conceptual model to explain financial asset pricing. According to the EMH, the price of an asset is equal to the discounted present value of the expected future cash flows derived from that asset, conditional on the information available at the time. This theory assumes that economic agents are strictly rational, expected-utility maximizers who are able to understand, process, and incorporate all available information into their investment decisions. Thus, any movements in the price of the assets must emanate from additional information becoming available.

While the EMH provides an elegant and appealing way to view asset markets, by the late 1970s, empirical evidence rejecting the validity of the model began to



288 Review of Agricultural Economics

accumulate and the tenets of the model were subject to increasing criticism (Bow- man and Buchanan). Early empirical work testing the EMH using stock prices and dividends (e.g., LeRoy and Porter; Shiller, 1981) began to highlight theo- retical anomalies and inconsistencies. Beechey, Gruen, and Vickery suggest that observed price deviations from fundamental asset valuations that persisted over sustained periods of time and recurred consistently throughout history brought the validity of the EMH under increased scrutiny.

Critics of the EMH emerged long before the model lost favor and was cast with doubt by empirical anomalies. The critics argued that it is unrealistic to assume that all investors are rational. Kindleberger wrote: "dismissing financial crisis on the grounds that bubbles and busts cannot take place because that would imply irrationality is to ignore a condition for the sake of a theory" (p. 24). Kindleberger posited that bubbles resulted from irrational crowd behavior and suggested that each speculative bubble has three stages: (a) mania; (b) distress; and (c) panic. Further, he described the evolution of speculation in two phases. Initially, there is a sober phase of investment, where investors act in a rational manner, followed by a phase in which large gains are made by selling the asset. Kindleberger further suggested that these phases create two groups of speculators: "insiders" and "outsiders." The insiders, attempting to capture windfall profits, sell their assets to the outsiders at the top of the market, while outsiders lose by selling out at the bottom once the insiders have driven the market down by selling off their assets.

During the mania stage of a bubble, speculation is prompted by investors who promote their investment as having unusually high returns (Abolafia and Kilduff). In attempting to increase their own returns, these insiders act rationally in their own self-interest, despite the fact that the market as a whole is considered to be irrational. The distress phase of the bubble usually begins with the exit of industry insiders. At the outset of the distress stage, insider exit may be offset by outsider entry. However, when industry instability and the exit of market participants becomes public knowledge, prices begin to decline (Abolafia and Kilduff), initiating the panic stage. During this period, investors rush to sell their assets before prices drop further. Yet the sale of assets only serves to further perpetuate the decline in asset valuations.

The anomalies emanating from the efficient market model, its inability to explain asset price fluctuations, and economists' unwillingness to assume that economic agents are inherently irrational has caused researchers to develop behavioral models of finance that incorporate insights from psychology. Camerer places the research and theories surrounding pricing bubbles into three categories: (a) rational growing bubbles; (b) fads; and (c) information bubbles. Fads are defined as mean-reverting deviations from the fundamental value of the asset, and information bubbles are a result of economic agents having different information. Rational growing bubbles, which can occur when agents act rationally, are relevant to understanding bubbles for agricultural assets. Rational growing bubbles grow each period and must provide some return, or they would come to an abrupt conclusion because current prices reflect the discounted expected future bubble price. Camerer offers examples of rational growing bubbles, including thoroughbred yearlings, a speculative bubble that peaked in 1983-1984. Like the alpaca industry, the thoroughbred yearling bubble emanated from breeding potential such that "the possibility of reproduction creates an equilibrium condition between the




price paid for the yearling today and the expected sale of the yearling's offspring tomorrow which allows rational pricing bubbles to form" (Camerer, p. 6).

Feedback loops represent one of the oldest theories about financial markets and are commonly viewed as price-amplification mechanisms (Shiller, 2005). Also referred to and recognized as "herd behavior," a "self-fulfilling prophecy," or a speculative bubble, a price-to-price feedback loop occurs when the preliminary price increase alters the expectations of market participants, driving the price up further. Consequently, price-to-price feedback loops allow investor actions and perceptions to influence prices by altering future expectations and increasing demand, thereby again causing prices to increase.

Within feedback loop theory, prices are only high because investors believe that prices will continue to rise. Thus, these high prices are not sustainable based upon economic conditions, and eventually will decline rapidly, signifying the bubble bursting (Shiller, 2003). Shiller (2003) also suggests that the word-of-mouth communication inherent in feedback theory and responsible for exacerbating speculative bubbles has been augmented with the increasing dependence on the news media for financial and investment information. Word-of-mouth communication can also create and perpetuate envy of investors who have achieved financial success. Shiller (2003) suggests that envy of this sort could mitigate or eliminate doubts that agents have about the investment and could increase demand for the asset. Investor envy in agricultural settings may extend beyond financial returns to include the impression that extant investors have escaped the urban rat race in favor of a happier rural lifestyle.

Kyle introduced the term "noise traders" to describe investors who are assumed to be irrational and act in a herdlike manner. While the EMH implies that rational investors will arbitrage away the pricing discrepancies created by noise traders, pricing errors will persist if there is not a sufficient number of rational agents or if shorting assets is difficult (Leroy). Miller suggests that speculative bubbles can occur in markets where there is insufficient short selling or a complete inability to short sell. Noise traders and rational investors are analogous to the groups that Shiller (2003) refers to as the "ordinary investors" and the "smart money." The agricultural assets that have experienced speculative bubbles over history are difficult or impossible to sort, thereby preventing the smart-money investors from profiting from their knowledge and allowing deviations in prices from the assets' fundamental value caused by ordinary investors or noise traders to persist. The chronic inability to sort typical agricultural assets thus represents a key reason why agricultural industries have been vulnerable to painful speculative episodes.

When making investment decisions, it is impossible for economic agents to completely ignore the opinions and actions of other market participants. Con- sequently, common beliefs and misconceptions permeate individual investment decisions. For these reasons, Shiller (2002) suggests that many bubbles are not the result of naive or gullible investors, but rather are the result of a "new era theory." This is the tale that accompanies an asset and which seems credible on the surface, is assumed to emanate from a reliable source, and contains "facts" that are not verifiable or conclusively refutable. As a result, individuals are not acting irrationally, but rather are making errors based on incomplete information. There- fore, the story surrounding the asset is the very thing that perpetuates the price




increases, stimulates additional investors, and creates and fulfills that speculative bubble. Along the same theme, Bowman and Buchanan assert that investors tend to overvalue anecdotal information and make investment decisions based on the alleged experiences of others.

While the actions and opinions of fellow market participants commonly influence investors, economic agents are also influenced by their own past experiences. Bowman and Buchanan suggest that investors succumb to "the law of small numbers," which allows them to believe that success in a very limited number of transactions makes them experts on investments. Investors who have enjoyed past success with particular types of investments fancy themselves as skilled and savvy in those areas, and they can become "emotionally, reputationally, as well as financially" attached to these assets (Shiller, 2002). This type of "connection" can propagate a "wish thinking" bias. Shiller (2002) posits that individuals who suffer from this type of bias are overly confident about the investments or assets with which they feel connected, which can contribute to creation and perpetuation of speculative bubbles.

To summarize, the failure of empirical tests to affirm EMH predictions in many cases led researchers to meld economics and psychology into conceptual and empirical models under the rubric of behavioral finance. Because human behavior is not strictly rational and markets are believed to be anthropomorphic (Bowman and Buchanan), behavioral finance has helped expand our understanding of the fluctuations, perturbations, and anomalies observed in asset markets. Whether they are called "outsiders," "noise traders," or "ordinary investors," many investors do not satisfy the rationality postulate of the prototype investor in the EMH and in many instances, the "smart-money" investors are unable to arbitrage effectively against the actions of these investors. The outcome can be prices that deviate substantially and for rather long periods of time from an asset's fundamental economic value.

Alpaca Lies? The Auspicious Beginnings of the U.S. Alpaca Industry

Guided by the recent advances in economics and psychology in understanding the bubble phenomenon, we analyze the advent and astonishing growth of the U.S. alpaca industry and ask whether it is in the midst of its own speculative bubble.

The first alpacas were imported into the United States from South America in 1984. Touted in advertisements on national television as an alternative to the corporate lifestyle for average Americans, the U.S. alpaca herd has grown substantially over the past twenty years with the stock of registered animals exceeding 86,000 at the start of 2006.1

A typical auction price for alpaca breeding stock in the United States may exceed $25,000, while in Peru, where over 3 million alpacas reside and the world's only viable alpaca textile industry is maintained, alpacas sell for a small fraction of this price. The pricing dichotomy is especially striking considering that the U.S. alpaca herd was begun little more than twenty years ago from South American imports, and U.S. alpacas have few, if any, distinguishing characteristics from their ancestors.




Table 1. Alpaca auction price statistics

2001 2002 2003 2004

All Huacaya Average ($) 16,910.47 23,464.62 28,194.59 26,080.16 Observations 43 171 157 160 High ($) 57,750 165,000 102,000 83,000 Low ($) 3,900 6,500 6,000 6,000

All Suri Average ($) 16,866.67 26,443.24 27,496.51 30,796.20 Observations 27 111 86 79 High ($) 34,100 265,000 84,000 103,000 Low ($) 7,200 6,500 9,500 11,500

Note: The following auctions were surveyed to compile the data in this table: 2004--America's Choice Alpaca Sale (ACAS), Breeder's Showcase Alpaca Sale (BCAS), Mapaca Jubilee Alpaca Sale, AOBA Alpaca Sale (AOBA-AS); 2003-ACAS, Celebrity Alpaca Sale (CAS), AOBA-AS, Parade of Champions Alpaca Sale, Breeder's Choice Alpaca Sale (BCAS); 2002-ACAS, CAS, AOBA-AS, Accoyo Alpaca Sale (AAS); BCAS, 2001-Spring Celebration Alpaca Sale, AOBA-AS, BCAS, AAS.

There is no systematic public reporting of alpaca prices, so table 1 represents a survey of over 900 auction prices collected by the authors. Although the table evinces considerable variation in the sales prices of alpacas, even the lowest prices recorded at the auctions surveyed were several thousand dollars. Average prices in most cases exceeded $25,000 and prices exhibited a clear tendency to rise during the four-year period surveyed. Although we cannot attest that the prices reported in the table are a representative sample, they are broadly consis- tent with the information that Alpaca Owners and Breeders Association (AOBA) provides to potential investors. The acquisition cost of an average female is between $12,000 and $25,000, while the price for an average herd sire could fall in the range of $20,000-$50,000 (Alpaca Owners and Breeders Association). No systematic reporting of sales prices is available for Peruvian alpacas either, but in personal communications Peruvian colleagues have indicated prices for breeding males in the range of 1,200-1,500 New Soles, about 350-450 U.S. dollars at current (2006) exchange rates (Huarachi).

Evolution of the U.S. Alpaca Industry The AOBA was established in 1988, four years after the first alpacas were im-

ported into the United States. Upon inception, the AOBA created the Alpaca Registry, Inc. (ARI) to undertake blood typing, DNA testing, and registering of animals imported into the United States. Originally, any alpaca could be registered with the ARI regardless of its country of origin, but as the population of alpacas grew, the AOBA began expressing concerns regarding the genetic in- tegrity and overall quality of the U.S. herd (Safley). Consequently, increasingly stringent screening processes were implemented, culminating with the closure of the registry in 1998 when the ARI began restricting registration to only those




offspring (cria) of registered sires and dams. As a result, all animals are now blood typed prior to registration to confirm their parentage. Currently, nearly 99% of all alpacas in the United States are registered, and unregistered animals in the United States have minimal value as breeding stock or in auctions and are extremely difficult to sell via private transactions (Collins).

The registration requirements and the closure of the ARI represent a barrier to the importation of alpacas. Additional import restrictions are in place because Peru has endured outbreaks of foot and mouth disease (FMD) as recently as 2001, and is not classified by the U.S. Department of Agriculture (USDA) as a FMD-free country. Peru's FMD status precludes the importation of any ruminant from Peru into the United States.2 Chile is the only South American country with an alpaca population that is eligible, currently, to export ruminants to the United States, but Chilean alpaca exports to the United States have not been a factor due to the substantial costs, quarantine time, and risks associated with intercontinental trade in live animals, and, since 1998, their preclusion from the ARI.

A Capital Asset Pricing Model for Alpacas and Other Livestock In this section, we establish an analytical framework to determine whether

prevailing auction prices in the United States noted in table 1 are reflective of alpacas' true economic value. The model, which adapts the seminal work of Jarvis, can be applied readily to other livestock settings. An alpaca can be regarded as a capital good whose fundamental economic value is determined by the derived demand for the product(s) it produces. Thus, the competitive auction price paid for an animal should be based on the discounted present value of the purchaser's expected future cash flows, as computed at time of the auction. Apart from a small market for alpacas as pets or as rural "lawn mowers," fiber and progeny are the only marketable products produced by alpacas.3

Production practices can influence both the quantity of fiber, F, that an alpaca produces annually and the quality of the fiber, measured primarily by micron count, m.4 Thus, when alpaca owners choose variable inputs, such as feed, la- bor, and veterinary services, to utilize in alpaca production, they must take into account these joint effects in determining the optimal input mix.

For simplicity, we assume that input decisions in a given year t affect profits only in year t, so that there are no feedback effects across years. Let X = {X1,..., Xn} denote a vector of variable inputs and w = {wl, ..., w, } the vector of those inputs' prices. Let S denote a vector of fixed characteristics of an alpaca, such as its age and breed, and Z denote exogenous market factors that affect the price of alpaca fiber. (We omit time subscripts except when they are necessary for clarity.) Pf is the grower price per lb of fiber, which is determined by m and Z. We can then express both quantity and quality of fiber in terms of X, given S : F (X I S), m(X I S). Assuming an interior solution, the optimal application of inputs per animal is determined by the conditions:

P(m (X|S) Z) F (X I S) (1) F (m(XIS)IZ (X I S)+ F(XS)Pf(m(X IS)IZ) = wi, i 1, n, ax, a xi




i.e., the marginal value product of an input in fiber production is the sum of a "quality effect," given volume; and a "volume effect," given quality.

Solving the system in equation (1) enables us to formulate the value function indicating the maximum variable profits associated with an alpaca's fiber production in a given year t:'rri(w, S, Z). Purchasers of juvenile alpacas will also incur husbandry costs prior to the time the animal begins to bear fiber. We denote those expected costs discounted to the time of purchase by C(w,S).

The expected value at time t derived from ownership of a male alpaca, VM(t), not used for breeding can then be expressed as

SsV E t(w,SZ) (2) VM(t)

= Et ( - C(w, S) ,E + t=tl (1 + )t

where Et denotes expectations formed in period t, ti > t denotes the time when the alpaca can first be sheared and its fiber sold, t3 > ti represents the animal's life expectancy, and r denotes the relevant discount rate. The summation term in equation (2) represents the discounted variable profit from the fiber stream provided by the animal. Note also that there is no terminal value because, unlike cattle, alpacas have no value in meat consumption.

VM(t) will differ among potential bidders, both due to differences in expectations and to differences in profitability due to location of the bidder's ranch, his/her skill as a producer, etc. In any type of auction format, each potential buyer's bid for a fiber-male alpaca is based upon the bidder's VM(t). However, determining the optimal bid is nontrivial because the bid must, in general, be adjusted downward from VM(t) to account for factors such as the bidder's degree of risk aversion, the competitiveness of the auction, and the winner's curse (e.g., Krishna; Klemperer). It suffices for our purposes to merely note that the winning bid, BM(t), is positively correlated with the VM(t) and bounded from above by highest value of VM(t) emanating from the pool of bidders: BM < sup{VM(t)}.

The valuation equation for female alpacas, VF(t) includes the same terms as the valuation for fiber males plus an additional term to reflect the revenue derived from the female alpaca's ability to also produce cria.5 Let D denote the market value at auction of a cria. Clearly D is based upon the characteristics, S, of the mother and of the father, SM, the expectation of demand factors, Z, that determine the price of fiber during the cria's productive life, the expectations of costs, w, of maintaining an alpaca, and, of course, whether the cria is male or female. We assume that gender cannot be controlled by the owner, and males and females are born with equal probability, so Dt(S, SM, Z, w) represents the value at time t of a cria that has equal probability of being male or female. The value function, expressed at time t, for a female alpaca is thus:

(3) VF(t) = Et I Tt(W,SZ) +

tt2

D(S,SM,Z,w)- C(w, S, Z) , E(1 + r)t (1 +

2 )t

where t2 is the time when the female is first able to reproduce. A typical female alpaca bears her first cria at two to three years of age and has the ability to have six to seven offspring over her lifetime.




The Domestic and International Alpaca Fiber Industry The preceding conceptual analysis demonstrates that the current fundamental

value of the alpaca stock is based upon current and projected future conditions in the alpaca fiber market. Addressing whether current U.S. prices for alpaca stock represent economic fundamentals or a speculative bubble hinges upon an assessment of current and expected future market conditions for alpaca fiber. Peru, with the world's largest alpaca population, is also the leading alpaca fiber and textile product exporter. The 3+ million Peruvian alpacas produce over 4,000 tons of fiber annually, nearly 80% of the world's alpaca fiber production (Vega).

Although barriers to international trade in live alpacas are multiple and, for the short term, apparently immutable, trade barriers for alpaca fiber have been virtually eliminated. In December 2001, the Andean Trade Preference Act (ATPA) ex- pired and prompted passage the Andean Trade Promotion and Drug Eradication Act (ATPDEA). According to the Office of the United States Trade Representative (USTR), "the National Society of Industries estimates that the largely duty-free textile and apparel exports from Peru to the United States under the ATPDEA could increase from $400 million in 2002 to $2 billion in 2006" (p. 43). With respect to the alpaca industry specifically, the government of Peru estimated that the increased access to U.S. markets could cause alpaca fiber and textile exports to the United States to grow from 30% to 50% in one year (Office of the United States Trade Representative).

Sheared annually, the average alpaca produces between 6 and 8 lb of raw fiber per year. Alpaca fiber prices are determined primarily by two specific criteria: micron count and the type of alpaca (huacaya or suri) producing the fiber.6 The market for alpaca fiber in North America has been limited due to lack of large- scale processing facilities, and revenue has been generated primarily from two sources: small-scale (cottage), independent textile producers or the Alpaca Fiber Cooperative of North America (AFCNA), established in 1998.

Some anecdotal evidence suggests that reputable producers with established contacts in the niche textile markets may be able to obtain upwards of $44/lb for raw fiber of highest quality (Heinrichs). Yet it is widely accepted within the industry to be virtually impossible to sell raw fiber in any significant volume at these prices. The growing number of alpacas in the United States has essentially saturated this niche market demand, forcing most producers to seek alternative outlets, such as the AFCNA, to process and market their fiber. The lack of U.S. processing facilities has forced AFCNA to utilize processors in South America, despite the significant transportation costs associated with such outsourcing. As of 2005, AFCNA members received anywhere from $5.00/lb for highest-quality (royal baby) fiber to $0.50/lb for short or coarse/strong fiber. In addition, a premium of nearly $2.50/lb has been paid for high-quality fiber produced by suri alpacas (AFCNA, 2005). These AFCNA prices are above the prices paid for raw fiber in the world market, but they are significantly less than prices reportedly paid by cottage-industry textile producers. Additionally, AFCNA patrons have not received payment in cash but, rather, through credits at the cooperative store. The cooperative has yet to turn a profit or pay patronage dividends to members, suggesting that even these prices are not sustainable without cost reductions or improvements in the fiber market.




The costs of alpaca maintenance offset the revenues from fiber sales. The AFCNA (2005) estimates that the feed, vaccination, and general health requirements of the average alpaca raised in the United States are approximately $169 annually (about $26/lb of fiber harvested annually). We derived an independent cost estimate of $208 annual cost at 2005 input prices by surveying the veterinary literature (e.g., Van Saun; Purdy) and various industry publications regarding the nutritional requirements for camelids in North America. Alpacas should also be wormed and vaccinated at an annual cost of about $100. Thus, we estimate that it costs approximately $308 per year ($47/lb of fiber harvested) to provide proper nutrition and veterinary care for an alpaca. (Details on these cost estimates are available in a working paper by the authors.)

Are U.S. Alpaca Prices the Result of a Speculative Bubble? Table 2 summarizes the cost and revenue analysis. Based on AFCNA's (au-

thors') estimate of production costs, the price of unprocessed fiber would have to be nearly $26/lb ($47/lb) for alpaca breeders to cover variable production costs from fiber revenues. At current fiber prices, a U.S. alpaca whose sole economic purpose is to produce fiber (e.g., a gelded male) has no economic value under any of the scenarios depicted in table 2 that involve sale of fiber through AFCNA. None of the scenarios yield a positive variable profit-e.g., even those raising suri alpacas and producing the highest-quality fiber are receiving only about $7.50/lb from AFCNA. Positive variable profit and, hence, positive economic value can be ascribed in the optimistic but isolated scenario where a producer (a) is able to sell raw fiber at $44/1b7; (b) can maintain an alpaca herd at the costs reported by AFNCA; (c) anticipates that this profit margin will continue into the future; and (d) has no aversion to the risk inherent in this type of operation. In this setting, a producer would be willing to pay upwards of $339 for a juvenile alpaca (two years of age), based solely upon the animal's fiber producing

Table 2. Revenue and cost of fiber production

Independent AFCNA Member

Producer Suri Suri Huacaya Huacaya 6.5 lb 6.5 lb 5 lb Baby 6.5 lb 5 lb Baby Royal Royal 1.5 lb Royal 1.5 lb Baby Baby Adult Baby Adult

Revenue from fiber ($) 286 48.75 31.5 32.5 21.5 Shearing ($) 25 25 25 25 25 Sorting ($) 5.98 5.98 5.98 5.98 Net revenue from fiber ($) 261 17.77 0.52 1.52 -9.48 Variable cost ($) (authors) 307.85 307.85 307.85 307.85 307.85 Variable cost ($) (AFCNA) 169 169 169 169 169

Profit from fiber ($)(authors) -46.85 -290.08 -307.33 -306.33 -317.33 Profit from fiber (AFCNA) 92 -151.23 -168.48 -167.48 -178.48




potential.8 Notably under the more realistic revenue scenario, the value of a huacaya's fiber does not even cover the variable costs associated with harvesting it.9

Although the analysis in table 2 is pessimistic regarding the opportunities to cover the variable costs of raising alpacas through the sale of alpaca fiber, it is, nonetheless, too optimistic because the revenue estimates assumed that alpacas produce uniform, high-quality fiber. The analysis also did not incorporate some costs such as shipping and insurance.10 In reality, only about 60-70% of the clip, or 3.6-5.6 lb, can be sold as quality fiber. The remaining portions can be sold for a lesser price if they have a micron count less than 31.9 and are not matted or stained. AFCNA (2004) statistics confirm the significant quality heterogeneity in U.S. alpaca-fiber harvest. Only 1-2% of total past clip collections have been of the highest (royal baby) quality. As much as 66% of all fiber collected by AFCNA is either superfine (23-26.9 micron count) or adult (27-31.9 micron count) quality, which are valued by AFCNA at only $3/lb and $1/lb, respectively, for huacaya fiber and $4.5/lb and $1/lb, respectively, for suri fiber.

Proponents of the industry would respond to this analysis by arguing (correctly, in the current environment) that many alpacas (most females and some males) have considerable economic value as breeding stock. Second, they would argue that alpacas produce a desirable, luxury fiber that is likely to experience increasing demand as its properties become better understood by consumers and, third, as the U.S. alpaca herd grows, various costs of maintaining alpacas and processing fiber will fall. Thus, both rising fiber prices and falling maintenance and processing costs should be anticipated in an alpaca valuation equation (3).

These seemingly distinct arguments about breeding value and future profitability of fiber production and sale actually collapse to only one argument that hinges on the future profitability of producing and selling fiber, as we now show in the context of the alpaca pricing model and equation (3). Although Jarvis does not extend his valuation framework in this direction, it follows that the economic value of a cria, Dt(S, SM, Zw), in equation (3) produced by a female alpaca or sired by a male alpaca whose valuation is at issue, is determined by the value of the product(s) the cria is expected to produce in the future, namely fiber and still more cria. Those second-generation cria would, in turn, be evaluated the same way. Thus, the Jarvis framework leads ultimately to a valuation process that requires forecasts of the market conditions for fiber and alpaca stock over the long term, in the limit to infinity. Of course, discounting applies to this valuation process, so events forecasted to occur further into the future become less important to the evaluation and ultimately can be ignored.

It is axiomatic to the valuation process for an alpaca that, because fiber is the only broadly marketable product that an alpaca produces, its economic value, whether expressed directly through the animal's own fiber or indirectly through the fiber of its progeny, must be based exclusively upon forecasts of the value of producing and selling alpaca fiber. Because alpacas sold today as breeding stock have values wildly in excess of even the most optimistic scenarios based upon current fiber prices and production costs, these prices can be justified by economic fundamentals only if investors can rationally forecast substantially better conditions in the fiber market in terms of higher prices, lower production costs, or both




Figure 1. The registered alpaca population in the United States

50,000

45,000

40,000

35,000

30,000

• 25,000

20,000

15,000

10,000

5,000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Year

-- Registered Huacaya Alpacas -- Registered Suri Alpacas -ATotal Registered Alpaca Population

that will make fiber production and sale a much more profitable proposition in the future.

What can a rational economic assessment tell us about the prospects for fiber production in North America? The stock of registered alpacas more than doubled between 1998 and 2002, rising from 19,384 registered animals to 46,105 (figure 1). The population rose further, to over 86,000, by the start of 2006. Biological growth often follows an exponential path, and we can use a biological growth function to forecast future growth in the U.S. alpaca herd.

The Malthusian parameter or instantaneous rate of natural increase in the population, 12, is estimated using:

(4) Inpop = 13 + P2t ,

where Inpop represents the natural log of total U.S. population of alpacas and t represents time.1 Table 3 provides estimation results for equation (4) for two alternative estimation horizons. Based upon the history of U.S. alpacas from 1991 to 2002, the estimated growth parameter is P2 = 0.28.12 Because this growth rate is influenced somewhat by imports prior to 1998, a more conservative and perhaps realistic growth rate focuses on years after 1998. The estimated growth parameter for this period is 32 = 0.17.

Table 4 indicates the years required for the U.S. alpaca population to reach various levels, given either of these two growth rates. For example, even under the more conservative growth rate, the U.S. alpaca herd size is projected to reach 1 million, twelve times its size in 2006, in just over fourteen years.




Table 3. Regression results to determine the Malthusian parameter

1991-2002 1999-2002

Standard Standard Coefficient Error p-Value Coefficient Error p-Value

Constant -569.760 20.740 0.000 Constant -347.440 26.140 0.006 Time 0.290 0.010 0.000 Time 0.170 0.013 0.005

R2 = 0.9873; Adjusted R2 = 0.9894 Adjusted R2 = 0.9861; R2 = 0.9842;

Table 4. Size of the U.S. alpaca herd for alternative growth rates

Growth Rate

0.17 0.28

Years from 2006 Population Necessary to Reach Population

250,000 6.21 2.99 500,000 10.29 5.46 750,000 12.68 6.91

1,000,000 14.37 7.94 1,500,000 16.75 9.39 2,000,000 18.45 10.41 2,500,000 19.76 11.21 3,000,000 20.83 11.86 3,500,000 21.74 12.41 4,000,000 23.52 12.89

This rapid growth may enable a viable domestic fiber processing sector to

emerge and the upstream industries supplying inputs to alpaca production to benefit from economies of size, thereby reducing the costs for processing alpaca fiber and providing inputs into alpaca production. On the negative side, this rate of expansion of the U.S. alpaca herd will imply a roughly proportional expansion of domestic fiber supply, meaning that the lucrative niche cottage industries, already unable to absorb a significant portion of the U.S. clip, will become even less relevant as a market outlet and source of above-market revenue for U.S.

producers. Regardless of the growth of the domestic alpaca herd, the United States will, for

the foreseeable future, be a small player in alpaca and fiber production relative to Peru, with its growing herd of over 3 million animals.13 How does the dominant Peruvian alpaca sector affect the evolution of the industry in the United States? Because the United States is in an autarkic state with respect to trade in live

alpacas, producers are able to sell the animals for average prices in the $25,000 range in the United States, while they sell for the equivalent of a few hundred dollars in Peru.




Is it possible that an autarkic equilibrium in live animals can be sustained wherein U.S. alpacas sell for fifty to hundred times their cost in Peru, when there are no barriers to arbitrage in the single marketable product these animals produce, namely fiber? The answer clearly would seem to be no. Alpacas, wherever they reside, are valued, based upon the fundamental Jarvis capital asset model, according to the value of the fiber they and their progeny produce. If the fiber market is subject to free trade and arbitrage, then fiber prices across producing countries for a similar level of quality will converge with due allowances for transportation and other arbitrage costs, meaning that prices for the capital asset must converge also. The presence of free trade and relatively low arbitrage costs in alpaca fiber means, thus, that either the U.S. alpaca herd is dramatically overvalued relative to its fundamental worth or the Peruvian herd is dramatically undervalued.

How Fast Must Fiber Prices Rise to Justify Today's Alpaca Prices? To determine which of these explanations is correct, we designed a simulation

analysis to answer the question of how rapidly fiber prices must increase over time as a consequence of demand growth, given the current state of the industry and holding all costs constant at today's levels, to justify the types of prices we observe for alpaca stock. We then ask, given the economic fundamentals of the industry, whether it is realistic that such growth rates can be achieved. This methodology is in contrast to econometric tests for the presence of a bubble, which are necessarily ex post in their orientation and have also been subjected to a variety of technical criticisms.14

The framework begins with a single juvenile alpaca female (age 2) that might be purchased at auction today for $15,000-25,000. This female was assumed to bear fiber annually from the time of her purchase over her assumed fifteen-year life span. Based upon consultations with veterinarians, this female was assumed to bear a cria on average every eighteen months, seven in total over her lifetime with a reproduction rate of 100%. Additionally, we assume that 50% of all cria born are female. These cria also eventually bear fiber and, if female, also bear additional cria, and so on as the generations unfold. All of this activity is at- tributable ultimately to the purchase of the original female and determines her value, as expressed in equation (3). Although the process in principle continues indefinitely, we truncated the simulation at twenty years, assuming that this represents a maximum time horizon over which any rational investor would seek to recoup his investment. We ignored stud fees because they add zero net revenue to the industry on aggregate (endnote 5) and, thus, are appropriately ignored for our representative alpaca as well.15

The key parameters in the simulation are g, the exogenous rate of growth in fiber prices, the discount rate r (we alternatively used 8%, 10%, and 12%) the maintenance costs which we assume to be constant over time (we used both AFCNA's and our own estimates); and the initial value for fiber to which the growth rate is applied annually (from table 2, we utilized the realistic fiber revenue estimates of $31.50 [suri] and $21.50 [huacaya]). The market valuation of our original alpaca is the discounted value of the fiber produced over the twenty-year horizon by the original alpaca and her progeny, less the costs of maintaining the herd and harvesting the fiber.16




Table 5. Profitability simulation

Fiber Revenue Annual Growth Rate

1% 3% 5% 10% 21%

Discount rate 8% Suri ($) -32,270.81 -30,641.49 -28,437.38 -18,951.19 53,706.31 Huacaya ($) -33,759.44 -32,647.37 -31,142.98 -24,668.28 24,923.35



Table 5 reports results of the simulation for alternative values of g and r. The table utilizes the AFCNA's estimates for costs of alpaca maintenance. Moderate growth in prices (i.e., in the range of 1%, 3%, or 5%) sustained over the entire twenty-year horizon (while holding costs constant at current values) does not generate a positive economic value for the original female. For example, at a 10% discount rate, sustained 5% annual growth in fiber prices leads to a discounted loss ranging from $22,000 to $24,000, depending upon the alpaca type. Even 10% growth in fiber prices does not produce a positive valuation. The magnitude of the losses is even greater when the authors' costs of alpaca maintenance are utilized, as reported in our working paper. Indeed, a greater than 20% sustained annual growth rate is needed to justify alpaca prices in the range of $15,000 or higher.17

As noted, the U.S. fiber supply is poised to increase rapidly (table 4) and offset the price impacts of any demand growth. Although it is currently growing slowly, the large Peruvian herd could also expand rapidly, if fiber and textile prices were to rise at a significant rate. This would provide an additional supply response to mitigate fiber and textile price increases caused by demand-side growth. Thus, even wildly optimistic scenarios for the growth rate of demand for alpaca fiber cannot be expected to translate into the revenue growth needed to sustain the types of prices observed today due to the certainty of offsetting supply responses, both domestically and internationally and an open world market for alpaca fiber.

Speculative Bubbles in Agriculture: How to Recognize One When You See It

In this section, we assemble results from the behavioral finance literature and the record of speculative bubbles in agriculture, including U.S. alpacas, to identify several "warning signs" that are common to agricultural bubbles and which should cause wariness among potential investors and their advisors.




1. The asset itself and not its product is promoted. Advertising in the development stages of an industry is necessary to distribute information about product attributes. Yet, marketing aimed at attracting additional producers rather than promoting the product actually being brought to market for consumption creates a substantially different effect. As Cole noted regarding the Chinese mulberry tree bubble, limited information was available through agriculture and industry publications, which promoted industry development with articles surrounding "successful cultivation, the happy experience of experimenters, and testimoni- als of the tree's exceptional qualities," completely ignoring the marketable silk product produced from the trees. Similarly, the alpaca industry's advertisements, including the "I Love Alpacas" website, focus on the animals' attractiveness and pleasant demeanor and the benefits of a rural lifestyle, and are designed to attract additional alpaca producers instead of promoting alpaca fiber.

2. Investors have unrealistic expectations regarding the market, including (a) potential for growth in sales of the product; (b) the benefits that will be derived if such growth materializes; and (c) the prospects for and consequences of outside competition. U.S. facilities to process the silk derived from the Chinese mulberry trees were few and small in scale. Yet, investors ignored the difficulties associated with developing the downstream processing sector and the fact that established silk industries in Italy and France gave those countries a comparative advantage over the nascent U.S. industry.

U.S. breeders of Marino sheep enjoyed a sustained period where livestock trade embargos, as a result of Non-Intercourse acts, increased domestic demand for breeding stock (Cole). As the domestic supply of breeding stock became more plentiful, the embargo was lifted, causing the ultimate and precipitous decline of breeding stock prices. By the time the processing sector expanded, providing adequate capacity for wool processing, the Merino sheep industry was essentially destroyed. Similarly, the U.S. alpaca industry has benefited from barriers to trade in live alpacas and has expanded with little or no consideration given to the dominant Peruvian industry, its impact in a free-trade environment for the marketable commodity, fiber, and the fact that intercountry price differences in live alpacas should be readily arbitraged through free trade in fiber.

Using the ostrich case, Gillespie and Schupp address the belief that growth represents a panacea for the industry and ultimately will justify the current exuberant expectations. Investors believed that ostrich meat would eventually compete with beef, chicken, and pork as a staple in American diets. The parallel belief for alpacas is that manufacture of alpaca fiber can replace the declining U.S. sheep-wool industry. The supply-side impact on prices of such growth, if it were to materialize, seems never to be considered. These scenarios for the industry's evolution and prosperity all fit Shiller's (2002) description of "new era" theories proffered in support of speculative investments. Although the theories cannot withstand objective economic analysis, they also cannot be disproved in a way that is conclusive or convincing to those invested in the industry's success.

3. Information is controlled through industry sources. The industry provides virtually the only information available to potential alpaca investors through promotional publications, farm and ranch websites, industry seminars and col- loquiums, and television advertisements.18 The same has been true for similar "exotic" but inessential agricultural enterprises that have been the subjects of speculative euphoria, such as tulips, ostriches, Shetland ponies, and emus. Information




that does appear almost inevitably has the character of ex post retrospectives (e.g., Cole; Gillespie and Schupp), which add to our knowledge regarding speculative bubbles but do nothing to mitigate the losses of those who were swept up in the euphoria. To Tirole, these tightly knit industry groups have the character of social networks that not only control information about the investment but also provide support and reinforcement to members of the network

4. Small-scale investors predominate. Alpaca ranches are primarily small-scale op- erations, whose owner-investors may lack the expertise and resources to conduct independent investment analysis. Alpaca investors often come to agriculture from other careers-behavior that is encouraged in the advertisements. According to Gillespie and Schupp, the ostrich industry in its infant stages was promoted in much the same fashion, with claims that this animal represented the perfect investment for individuals with small quantities of land to enter an agricultural industry. Similarly, raising chinchillas for fur was touted as a way in which re- tirees could supplement income, housewives could have their own businesses, and hobbyists could become distributors and make a bundle (Animal People).

5. Biological or trade barriers to growth in the stock of the asset are present. Noteworthy is that most of the documented speculative bubbles in agriculture have involved livestock, although Dutch tulip mania and the Chinese mulberry tree bubble represent notable exceptions. If coupled with trade barriers, the reproductive cycle of the livestock determines the rate at which supply can grow and enables industry incumbents, as the sole suppliers of the stock, to profit from supply growth. Similar barriers to supply expansion almost never apply to field crops, where seed can be accumulated quickly and land shifted from the production of less profitable crops.

In addition to determining the types of agricultural commodities vulnerable to speculative bubbles, the reproductive potential of the asset appears to play a major role in determining the longevity of the bubble. U.S. alpaca prices have been high almost since the inception of the industry in 1984, and the persistence of the prices is a key factor noted by industry proponents in arguing that they will continue into the future. The animals' reproductive rate is slow and the U.S. industry literally "started from scratch," meaning it has been operating for most of this time along the "flat" portion of the exponential growth path summarized in (4), with limited supply response relative to the demand created for the asset. However, recent bubbles in the United States for thoroughbred yearlings and ostriches were much shorter in duration, likely due in part to the speed with which supply of the asset could expand. In the case of ostriches, a hen could produce 10-20 chicks a year (Gillespie and Schupp). Thoroughbreds' reproductive cycle is similar to alpacas', but a large stock of thoroughbreds existed at the advent of the bubble that were not being used for breeding purposes, but which subsequently entered the breeding pool in response to the price signals.

Conclusion Economists' thinking about asset markets has evolved considerably over the

past thirty years. Aided by insights from the psychology literature regarding investor behavior, advances have been made in understanding the emergence and life cycle of speculative bubbles. Agricultural industries have not been immune to speculative bubbles and in some respects, are particularly vulnerable to episodes




of speculation because a rural lifestyle carries considerable appeal for many investors and the assets at issue are often impossible to sort.

This paper has summarized and distilled knowledge from the recent advances in economics and psychology regarding asset speculation and applied it to the study of speculative bubbles in agriculture, focusing in particular on the evolution of the U.S. alpaca industry. We presented an investment framework to assess whether current prices for U.S. alpaca stock can be supported by market fundamentals or whether they likely represent a speculative bubble that is destined to burst to the dismay of investors who have been swayed by the persuasive television commercials and the animals' charming appearance. In this regard, the evidence seems to be rather overwhelming that the current prices are not supportable by economic fundamentals and, therefore, are not sustainable.

Thus, our conclusion is that the U.S. alpaca industry represents the latest in the rich history of speculative bubbles in agriculture. This analysis may provide a useful caution for those considering investing in the industry or their advisors. More importantly, because the historical record suggests that future speculative bubbles are destined to appear on agriculture's horizon, whether in the United States or elsewhere, the lessons distilled here from the U.S. alpaca experience and the other episodes of speculative bubbles in agriculture may be useful in gaining early recognition of these subsequent events, mitigating their severity, and thus reducing the harm inflicted upon unwary investors.

Acknowledgments This research was supported by a grant from the Giannini Foundation of Agricultural Economics.

The authors are grateful to Jeffery Williams for helpful comments on this research.

Endnotes 1Ohio, with 11,380 registered animals, is the leading U.S. state in terms of alpaca population fol-

lowed by Washington, Oregon, and California, respectively (Alpaca Registry Inc.). 2Although Peru and much of South America have never been characterized as FMD-free, the U.S.

alpaca herd is exclusively of South American origin due to the opportunity from 1979 to 1998 to import livestock from countries classified as high disease risk through the Harry S. Truman Animal Import Center (HSTAIC) in Key West, Florida. Of the 6,713 animals imported through the center over the nineteen years that the facility was in operation, 5,046 were alpacas (U.S. Environmental Protection Agency). The HSTAIC was closed in 1998, ostensibly due to lack of business, but also coinciding with the date of closure of the Alpaca Registry. Closure of the HSTAIC effectively prohibits the importation of alpacas into the United States from any country not classified as FMD-free. Even in the absence of FMD issues and the restrictions imposed by the ARI, it is unlikely that Peru would permit substantial exports of alpacas to the United States. Hoping to safeguard against the establishment of substantial alpaca herds elsewhere in the world, the Peruvian government has allowed the exportation of only 3,308 alpacas since 1997 (Gil, 2005).

3Alpacas can be used to graze pasture lands and provide aesthetic value to rural landscapes. According to Kershaw (2004), a few animals are bought and sold as pets for a few hundred dollars without being registered. Thus, the market for unregistered alpacas as pets or grazing animals is limited at best and quite distinct from the commercial market at issue here. The cost of registered alpacas is a powerful deterrent to using them to graze pasture lands when more cost-effective options, such as goats or sheep, are available.

4The higher the micron count of the fiber, the coarser the yarn and the lower the quality of the textile end product. Consequently, processors pay a premium for fiber with lower micron count.

5We do not analyze value for alpaca males used for sires for two reasons. First, relatively few males will be used as herd sires. Second, stud fees are a zero-sum game from the industry's perspective, in the sense that members of the industry both pay and receive the same revenues. Therefore, stud fees cannot contribute anything to the overall profitability of the industry.

6Huacaya alpacas comprise over 80% of the U.S. alpaca population and produce short, crimped fiber. Suri alpacas are rarer and earn a premium for their fine, lustrous fiber which resembles long mohair.




7The reported prices for sales to the cottage milling industry must be viewed with some circum- spection. Given that a large share of U.S. production is apparently selling for a small fraction of these prices, and fiber can also be imported from Peru at a considerably lower cost, it is not clear why rational millers would pay these premium prices.

8The discounted present value profit calculation assumes that an alpaca is purchased at auction at age 2 and sheared for the first time shortly thereafter. Additionally, we assume that the purchaser retains ownership of the animal and harvests fiber annually throughout its fifteen-year life span. A 10% discount rate is utilized to convert all figures to present value, while both fiber prices and variable costs are assumed to be constant over the fourteen-year time frame considered.

9Another possible fiber-marketing strategy for alpaca owners is to procure custom fiber processing and sell processed fiber to independent textile producers. We did not consider this strategy because we found little information on it, and, more importantly, because processing is unlikely to be an activity that generates economic profit for alpaca owners. Alpaca owners would have no advantage relative to textile producers in obtaining processing services, and, thus, willingness of buyers to pay for processed fiber relative to raw fiber should not exceed the full cost of procuring processing services.

10We have no estimates on shipping costs for the industry. Average annual insurance rates are 3.25% of the value of the animal (Alpaca Owners and Breeders Association).

"This approach yields a constant growth rate parameter and is an adequate representation of growth if the graph of the natural log of population relative to time is approximately linear, which seems to be true for the U.S. alpaca herd.

12The year 1991 was the first year for which reliable alpaca population numbers were available for the United States through the ARI. Additionally, because the Durbin-Watson statistic associated with the original regression was less than the Durbin-Watson lower critical value at the 5% level of significance, we adjusted the model for first order serial correlation and used this estimate of the Malthusian parameter throughout the analysis.

13Statistics from the Ministerio de Agricultura in Peru indicate that the Peruvian herd increased from 2,668,000 in 1990 to 3,087,000 in 2003. Since this growth rate is clearly less than what is biologically feasible, it suggests culling within the Peruvian herd, most likely due to profitability concerns.

14Empirical work on rational bubbles has been complicated by the fact that econometricians are always testing the joint hypothesis of a rational bubble occurring and whether the market fundamentals are specified correctly. Due to the complications associated with properly incorporating market fundamentals into an empirical model and then testing for the presence of bubbles, Flood and Hodrick (1990) stressed that empirical evidence is often not adequate to confirm or deny econometrically the presence of speculative bubbles in asset markets.

15We also did not consider income tax effects and, thus, the simulation results should be regarded as pre-tax. Alpacas are eligible for the same tax treatment afforded other agricultural investments, and, in fact, tax benefits are touted to potential investors. The primary benefit is the opportunity to fully expense (instead of depreciate) many costs and use these deductions to offset taxable income from other sources. The extent of the benefit thus depends upon the investor's tax bracket, and its continuation over time requires convincing the Internal Revenue Service that the venture is intended for profit.

fOf course, the typical alpaca rancher would intend to sell many of the cria born during this horizon, but the key point is that the fundamental value of these cria is based upon the expectation of the value of the fiber they and their progeny will produce. The effect of "retaining" all of the progeny in the herd to produce fiber is to ascribe 100% of the fiber revenue over the horizon to the original female. If sales occurred, buyers would be expected to capture some of the economic value. Thus, the no-sale assumption invoked in the simulation errs on the side of overvaluing the original female.

170ur analysis ignores the value of the stock of alpacas that exist at the end of the twenty-year horizon. The stock's value would depend upon fiber prices forecast into the even more distant future. Note that the present value of $1 received twenty years from now at a 10% discount rate is less than $0.15, making stock value relatively unimportant in the analysis, even if one were able to estimate it with any confidence.

18For example, in our research in preparing this article, we did not locate a single academic article or extension publication on the U.S. alpaca industry, despite its presence in all U.S. states.

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