Shipping the Good Anecdotes In: Illustrations of the

Perspectives on Economic Education Research 9(2) 18-38

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Shipping the Good Anecdotes In: Illustrations of the Alchian-Allen Effect from American Culture and History1 Steven B. Caudill,a,2, Franklin G. Mixon, Jr.b, Kamal P. Upadhyaya c a Department of Economics, Florida Atlantic University, Boca Raton, FL 33431, USA b Center for Economic Education, Columbus State University, Columbus, GA 31907, USA c Department of Economics, University of New Haven, West Haven, CT 06516, USA

Abstract

This study offers a number of compelling anecdotes for classroom presentation and discussion of the Alchian-Allen effect in economics principles and other courses. The stories included cover aspects of the Civil War, issues related to sports fandom and participation, the economic costs of higher education and other episodes that students of economics will view as interesting illustrations of the importance of relative prices to economic decision makers. Key Words: Alchian-Allen effect; relative prices; third law of demand; economic education JEL Codes: A20; D11; D12

1 The authors thank an anonymous referee of this journal for many helpful comments and suggestions. The usual caveat applies. 2 Corresponding author.

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Caudill, Mixon, Upadhyaya/Perspectives on Economic Education Research 9(2) 18-38

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1. Introduction and Background The quest for improvements in the delivery and assessment of economics education is a

continual one for many in the academy. The former category – improvements in delivery – has spawned a number of studies over the past ten years advocating innovative classroom methods such as the use of television (e.g., Mixon, 2001; Sexton, 2006; King-Adzima, 2010; Luccasson and Kathleen, 2010; Mateer, Ghent and Stone, 2011; Crisp and Mixon, 2012), movies (e.g., Mateer, 2004; Sexton, 2006; Mateer and Li, 2008; Mixon, 2010; Mateer and Stephenson, 2011), music (e.g., Harter, 2003; Mateer and Rice, 2007; Hall and Lawson, 2008; Lawson, Hall and Mateer, 2008; Raehsler, 2013) and even literature (e.g., Harter, 2003; Watts, 2003; Bekar and Grant, 2010; Ruder, 2010) in economics instruction. Since 2001, this list has expanded to include the use of comic strips (e.g., Lawson, 2006), video games (e.g., Kjar, 2009; Lawson and Lawson, 2010), art (e.g., Bohanan, 2011; Watts and Christopher, 2012) and internet podcasts (e.g., Moryl, 2013) in imparting economics principles to college and university students. Another branch of this literature simply offers vignettes that improve upon textbook expositions of various topics encountered in either economics principles courses or undergraduate field courses in economics. Recent examples of this branch that cover the areas of cartel theory, the economics of liability law and the Coase Theorem are provided by Caudill and Hicks (2005), Caudill and Mixon (2013) and Beaulier, Mixon and Cebula (2014), respectively.

This study extends the recent trend of offering fresh alternatives to the usual textbook examples for illustrating economic principles. In particular, we offer several compelling anecdotes for classroom presentation and discussion of the Alchian-Allen effect (Alchian and Allen, 1964; Borcherding and Silberberg, 1978) which can be used in economics principles and other courses. As Staten and Umbeck (1989: 166) indicate, Alchian and Allen (1964) provide “a classic series of examples . . . [o]ffered as indirect evidence of the law of demand, . . . involv[ing] consumption changes induced by transportation charges levied upon two different quality grades of the same good.” As they point out (Staten and Umbeck, 1989: 166), “Alchian and Allen suggested that the percentage of premium-quality California oranges (or Washington apples) sold in a distant market such as New York would be higher than the percentage sold in California itself.” Unfortunately, the “classic . . . examples” provided in Alchian and Allen (1964), and oftentimes repeated thereafter, are not always appealing to economics principles students today. The anecdotes presented here touch upon aspects of American culture and/or history, and, therefore, are likely to be better received by students than some of the staid illustrations offered in contemporary textbooks. The stories included herein cover (1) aspects of the Civil War, from antebellum slavery markets to the Union blockade of the Confederate South, (2) issues related to sports fandom and participation, (3) the economic costs of higher education, a popular topic across principles texts, and even (4) long-distance romance. 2. Slave Markets in the Antebellum South

The pricing of slaves in the antebellum South is examined by Pritchett and Chamberlain (1993), who find that the average quality of slaves transported to New Orleans from other parts of the antebellum South, and sold on the market there, was higher than that of their local (i.e., Louisiana) slave population counterparts. In the case of slave prices, the high average quality of imported slaves who were sold in New Orleans is explained by the cost of transportation, which consisted of lodging, medical care, clothing and food, sales commissions, funds transfer expenses and travel fare to New Orleans (Pritchett and Chamberlain, 1993: 462). Estimates of the actual shipping costs during the 1800s are $165-$170 per slave (Pritchett and Chamberlain, 1993).


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Table 1: The Alchian-Allen Effect and the Southern Slave Trade

Slave Market Slave Prices Relative Price of H L H Local $300 $525 1.750

New Orleans $470 $695 1.479

Note: Example assumes slaves are either sold on the local market in Savannah or exported from Savannah to New Orleans. L denotes lower quality slave; H denotes higher quality slave.

Using the shipping cost figure of $170, and hypothetical lower-quality and higher-quality slave

prices of $300 and $525, respectively, Table 1 provides a picture of the Alchian-Allen effect at work. According to the example, a slave located in Savannah and sold on the local market will exhibit a price range, depending upon quality, from $300 (lower quality) to $525 (higher quality). Thus, on the local slave market in Savannah, the relative price of a higher quality slave is 1.750 lower quality slaves. If exported from Savannah to the slave market in New Orleans, the slaves sell for, with shipping costs included, $470 (lower quality slave) and $695 (higher quality slave). Thus, on the slave market in New Orleans, the relative price of a higher quality slave is 1.479 lower quality slaves, or about 15.5 percent lower than back in Savannah. As Pritchett and Chamberlain explain, the lower relative price of the higher quality slave creates incentives for buyers in the distant market – in this case the New Orleans slave market – to purchase relatively more of the higher quality slaves. Looked at differently, one would expect that a greater percentage of higher quality slaves in one area of the antebellum South would be sold in distant markets relative to that percentage from among the local slave population surrounding that distant market.

While the above example is illustrative, it does not provide empirical evidence of the explanatory power of the Alchian-Allen effect. To provide empirical evidence, Pritchett and Chamberlain (1993) follow Greenwald and Glasspiegel (1983) by using slave age as a proxy for slave quality, given that a slave’s age was the only quality-related characteristic provided on actual sales invoices from the period. As Pritchett and Chamberlain (1993: 469) explain, if Alchian and Allen’s theory applies to the market for slaves, then disproportionately more prime-aged slaves in distant markets would have been shipped into New Orleans. Upon examination of the historical data, they find an average of 69.8 percent of all imported slaves were aged 15 to 35 years. For the census years 1830, 1840, 1850 and 1860, only 40 percent of the entire slave population was accounted for by this age group. These data support the Alchian-Allen theorem. Pritchett and Chamberlain (1993) take the analysis further by comparing prime-aged slave percentages from various southern states that are shipped to the New Orleans market to those from Louisiana that are also sold in New Orleans. These data are shown in Table 2 (Pritchett and Chamberlain, 1993: 470). In terms of the geographic analysis, Pritchett and Chamberlain (1993: 469-470) conclude that the apparent direct relationship between the distance from New Orleans to the region of origin and the percentage of imported slaves who were of prime age is also consistent with the Alchian-Allen theorem. In fact, as they indicate, only the fact that the percentage of prime-aged slaves shipped from the Old South is below that for the Border States mars a perfect rank-order relationship.


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Table 2: Percent of Prime-Aged Slaves Shipped to New Orleans by Region, 1830-1859

Region of Origin Percent Prime-Aged Number of Slaves Old South

(MD, VA, NC, DE, DC, SC) 74.63 335

Border States (KY, TN, MO)

82.21 163

Southeast (FL, GA)

71.25 80

New South (MS, AR, AL, TX)

65.64 195

Local (LA)

52.94 17

Unrecorded 56.53 2,355 Note: Percent prime age is defined as the percentage of slaves from a given region who were aged 15 to 35 years (Pritchett and Chamberlain, 1993). Source: Pritchett and Chamberlain (1993), although they note that original source is Fogel and Engerman (1974).

In order to provide an additional look at the ideas presented in Pritchett and Chamberlain

(1993), we use their prime-aged percentage data in Table 2 in a meta-analysis of the Alchian-Allen theorem. We regress the region-based percentage variable, using the data in Table 1.2, on Local Dummy, which is a dummy variable equal to 1 for “Local” as defined above, and 0 otherwise. It is expected that the coefficient estimate for Local Dummy will be negative. Alternatively, Distance Index replaces Local Dummy in a regression wherein Distance Index is an index variable representing distance between the geographic origin of the prime-aged slaves sent to the New Orleans market. In this case, Distance Index is equal to 4 for “Old South,” 3 for “Border States,” 2 for “Southeast,” 1 for “New South” and 0 for “Local.” Unlike Local Dummy, Distance Index is expected to be positively related to the region-based percentage variable.

Table 3: Meta-Analysis of Pritchett and Chamberlain’s Results

(1) (2)

Local Dummy −20.493 (−2.65)

―

Distance Index ― 5.995 (2.99)

F-statistic 7.001 8.946 R2 0.700 0.749

Notes: The dependent variable for the regressions above is the percent of prime-aged slaves by region (excluding “Unrecorded”) from Table 1.2. The numbers in parentheses above are t-values.

The meta-analysis results are provided in Table 3. In version (1), the Local Dummy coefficient

retains the expected negative sign; more specifically, the estimate of −20.5 suggests that the percentage of prime-aged slaves shipped to New Orleans from various locales in Louisiana is 20.5 percentage points


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lower than that shipped from other parts of the antebellum South. This result is both relatively large and significant at the 0.077 level. The version (2) results also support the Alchian-Allen hypothesis in Pritchett and Chamberlain (1993), given the positive and significant (at the 0.058 level) finding for the coefficient of Distance Index. The result indicates that as the distance index climbs by one level, the percentage of prime-aged slaves shipped to the New Orleans market grows by six percentage points. As such, this model predicts that the percentage of prime-aged slaves shipped from Georgia to the New Orleans slave market is about 12 percentage points greater than that shipped to the New Orleans slave market from various locales in Louisiana. Altogether, the statistical evidence presented in Pritchett and Chamberlain (1993) and in this section supports the idea that a significant relative price effect – the Alchian-Allen effect – existed in the antebellum slave trade. 3. The Importation of Lace and Linen in the Confederate South

The Alchian-Allen effect also played a prominent role during the American Civil War (1861-1865). In describing how the relative price effect worked through the Union blockade of the Confederate South to encourage blockade runners to supply luxury items, not essential war matériel, to the Confederate South during the war, Ekelund and Thornton (1992) refer to the Alchian-Allen effect as the “Rhett Butler effect.” Ekelund and Thornton (1992: 891) base their analysis on the proportion of value (V) to bulk (B) of the items that the Confederate South tended to import during the war, which is what they refer to as the “VB ratio.” Items rating high on the VB scale were, among other things, coffee, lace, ladies bonnets, spices and wines, while those that tended to have a low VB ratio were, among other things, finished nails, molasses, salt and sugar (Ekelund and Thornton, 1992). In a more recent study, Thornton and Ekelund (2004) add cognac, cordials, dresses, gloves, hoop skirts and ribbon to the high-VB ratio list, while boiler iron, copper, machinery, steel and zinc are added to the low-VB ratio list.3

Blockade running during the Civil War was a risky enterprise. Runners faced capture on each and every excursion, and as the Union devoted more and more resources to capturing blockade runners, the probability of capture increased. Thus, although prior to the blockade by the Union of the Confederate South the cost of supplying goods made elsewhere to customers in the South consisted of the resource costs (in production) plus transportation costs (to the South), after the blockade an additional transportation cost – a risk cost – was part of the calculation of the price of imports. This risk cost was, importantly, invariant to the type of cargo being transported, yet directly related to the probability of capture facing blockade runners. The example provided by Ekelund and Thorton (1992), and presented in Table 4, illustrates the issue. It provides hypothetical pre-blockade prices faced by citizens of Charleston for one pound of sugar (necessity) and one pound of coffee (luxury), each imported from Bermuda. These prices reflect both production costs and transportation costs. Before implementation of the blockade, the relative price of one pound of coffee is 2.000 pounds of sugar. After a “loose” blockade of the Confederate South goes into effect, however, blockade runners face enough risk to increase transportation costs by an additional dollar, thus raising the prices of imported sugar and coffee in Charleston to $1.50 and $2.00, respectively (see Table 4). Now, the relative price of one pound of coffee is 1.333 pounds of sugar. Later, when the Union blockade is “tightened,” transportation costs rise by an additional dollar, leading to import prices of $2.50 and $3.00 for sugar and coffee, respectively (see Table 4). At this point, the relative price of one pound of coffee, the luxury in this case, has fallen to 1.200 pounds of sugar. The Alchian-Allen effect is again evident, and in this case, “Southern demanders . . . faced lower relative prices for [luxury goods] . . . (Ekelund and Thornton, 1992: 892).”

3 Ekelund and Thornton (1992: 891-892) describe the linguistic convenience of the dichotomy of goods along the VB continuum by identifying goods with high VB ratios as luxuries and those with low VB ratios as necessities. They also add that blockade-runners generally had wide latitude in the selection of goods they imported.


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Table 4: The Union Blockade and the Alchian-Allen Effect

Blockade Charleston Prices Relative Price of Coffee Sugar Coffee None Loose Tight

$0.50 $1.50 $2.50

$1.00 $2.00 $3.00

2.000 1.333 1.200

Note: Example assumes 1-pound bag of each, sugar and coffee, imported from Bermuda. Source: Adapted from Ekelund and Thornton (1992).

In terms of anecdotal evidence in support of the Alchian-Allen effect, Ekelund and Thornton

(1992: 895) indicate that blockade runners did not find it profitable to ship heavy goods, and instead chose to bring to the South lighter, profitable goods such as silk, quinine, laces and linens. They also point out that the French Consul in Charleston indicated that a blockade runner’s first voyage paid for his ship and cargo, and also provided a profit, an assessment that was supported by the Confederate States of America’s commercial agent in the Bahamas. Lastly, Ekelund and Thornton (1992: 895) provide anecdotal evidence of the particularly profitable Bahamian entrepôt trade, which was reported to yield a $300,000 profit from a single voyage, and by the end of 1862, English-made ships were being ordered on the assumption that they would be paid for after only three round trips.

In terms of statistical evidence, Thornton and Ekelund (2004) use inbound and outbound capture data to calculate the capture rate (i.e., the percentage of unsuccessful attempts to total attempts to run the Union blockade). Their calculations are presented in Figure 1, which indicate that the blockade become effective in 1862, stabilized in 1863, rose in effectiveness in 1864, and fell off nearer the end of the war in 1865.4

Figure 1: Inbound + Outbound Capture Rate (%), 1861-1865

Source: Thornton and Ekelund (2004).

4 Thornton and Ekelund (2004) provide all of their data in figure form, but only some of it in the text. Thus, the numbers used to produce Figure 1 herein are very close approximations of their data.

05

1015202530354045

1861 1862 1863 1864 1865

Capture Rate (%)

Year


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Thornton and Ekelund (2004: 42) also construct relative price (luxuries to necessities) indices over the war years (i.e., 1861-1865), which are presented in Figure 1. These indicate that the relative price of luxury goods rose between 1861 and 1862, fell from 1862 to 1863, and fell again from 1863 to 1864, rising again between 1864 and 1865.5 The Rhett Butler effect (Alchian-Allen effect) predicts, as described above, a negative relationship between the effectiveness of the Union blockade and the relative price of luxuries. In other words, as the blockade becomes more effective, the risk associated with running the blockade rises, leading to a fixed, across-the-board increase in the prices of blockade cargo, regardless of type (luxury or necessity). When this occurs, the relative price of the higher-valued good falls.

Figure 2: Ratio of Luxury Prices to Necessity Prices, 1861-1865

Note: Luxuries are tea and coffee, while necessities are molasses and sugar. Source: Thornton and Ekelund (2004).

A simple visual examination of the time series in Figures 1 and 2 suggests that their relationship is negative; visual examination does not, however, constitute a proper examination in this case. Instead, the Alchian-Allen effect described in Ekelund and Thornton (1992) and Thornton and Ekelund (2004) is examined statistically here – for the period starting in 1862, “the beginning of effective blockade” (Thornton and Ekelund, 2004: 45), and running through 1865 – by calculating the Pearson correlation coefficient for the 1862-1865 time series, the period used in statistical tests by these authors, shown in Figures 1 and 2. That coefficient is −0.896, suggesting that the relationship between the last four years of the series in Figure 1 and the corresponding portion of the series in Figure 2 is strongly negative, just as the Alchian-Allen effect predicts. Moreover, the negative relationship between the blockade’s effectiveness and the relative price of luxury items is statistically significant at the 0.052 level. This example illustrates the Alchian-Allen effect with a change in relative prices of luxury goods caused by the blockade.

5 Thornton and Ekelund (2004) provide all of their data in figure form. Thus, the numbers used to produce Figure 2 herein are, again, very close approximations of their data.

0

0.5

1

1.5

2

2.5

3

1861 1862 1863 1864 1865Year

Relative Price of Luxuries


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4. Season Ticket Sales at Clemson University’s Death Valley In the studies highlighted above, the Alchian-Allen effect is exhibited in the traditional sense,

where two different qualities of the same good have shipping costs added to their distinct nominal prices, resulting in a lower relative price at the destination point for the good of higher quality. As the study by Bertonazzi, Maloney and McCormick (1993) shows, however, that the Alchian-Allen effect holds whether the goods or the buyers travel. In fact, as they state, the effect is so pervasive that they coin the term “third law of demand” to characterize it. The case examined by Bertonazzi, Maloney and McCormick (1993) is that of various Clemson University football fans choosing from among several season ticket packages of differing quality. The quality of a season ticket package may depend not only on the location of the seat, but also on factors like complimentary food and beverages, complimentary game-day program, access to semi-private restroom facilities, and guaranteed parking. Of course, if more game-day amenities are associated with a season ticket package, the price will be higher.

Table 5: Relative Prices of Clemson Football Tickets

Alumnus Season Ticket Prices Relative Price of Tiger Den Tickets Basic Tiger Den

Local Atlanta, GA Dallas, TX

$330 $469

$2,885

$1,020 $1,159 $3,575

3.091 2.471 1.239

Notes: The drive from Atlanta to Clemson is 124 miles, or 248 round trip. Using The Internal Revenue Service’s per-mile driving rate of $0.56, travel costs are approximately $139. Round trip air fare from Dallas to Columbia is assumed to be $365 (google.com). Source: www.clemsontigers.com.

Take, for example, the situation presented in Table 5 regarding two options for season tickets at

Clemson University (CU), whose stadium is known to fans as Death Valley. According to the CU Athletics Department, a basic season ticket package (assuming seven home games) for the 2014 season is priced at $330, while a higher-quality package, referred to as the “Tiger Den” package, is priced at $1,020 (clemsontigers.com). At these prices, a local alumnus and fan of the team, who does not incur a travel cost to attend the game, is presented with the relative price of a Tiger Den season ticket package of 3.091 basic season ticket packages. However, alumni-fans who live outside the local area face possibly significant transportation costs to the game.

A hypothetical Atlanta-based alumnus faces seven round-trip drives (248 miles per trip) to Clemson. Using the Internal Revenue Service’s per-mile driving rate of $0.56 as a measure of ground transportation costs, the money prices for the basic and Tiger Den season ticket packages are essentially $469 and $1,159. Thus, to the Atlanta-based alumnus, the relative price of a Tiger Den season ticket package is 2.471 basic season ticket packages, which is 20.1 percent lower than that facing the local alumnus. A hypothetical Dallas-based alumnus faces seven round-trip flights between Dallas and Columbia. Assuming a per-flight air fare of $365 (google.com), the money prices for the basic and Tiger Den season ticket packages are essentially $2,885 and $3,575. Similarly, to the Dallas-based alumnus, the relative price of a Tiger Den season ticket package is 1.239 basic season ticket packages, which is 49.9 percent lower than that facing the Atlanta-based alumnus. Of course, the largest relative price difference is that between the Dallas-based alumnus and the local alumnus. In the case of the Dallas-based alumnus, the relative price of a Tiger Den season ticket package is 59.9 percent lower than that facing the local alumnus. The hypothesis coming out of this example, and that tested by Bertonazzi, Maloney and McCormick (1993), is that more distant CU alumni-fans will be more likely to purchase the


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higher quality season ticket package (i.e., Tiger Den), given their travel costs, than local or even Atlanta-based CU alumni-fans. At the same time, the likelihood of a Tiger Den purchase will be, given travel costs, higher for Atlanta-based CU alumni-fans than that of local CU alumni-fans.

Table 6: Season Ticket Quality Choices at Death Valley

(1) (2)

Intercept 1,721† (6.846)

1,674† (6.640)

Income 0.086† (3.057)

0.091† (3.186)

# Tickets Purchased 1,410† (121.045)

1,411† (121.049)

# Years Purchasing 133† (16.197)

134† (16.197)

Population Density −0.008 (−1.440)

−0.008 (−1.444)

Intensity −0.038† (−7.514)

−0.039† (−7.539)

# Home Games 268† (10.816)

269† (10.816)

$-Cost of Travel Time (1-way) 0.009† (2.669)

Distance (Miles) Travelled (1-way) 0.009† (2.644)

n 23,440 23,440 R2 0.4084 0.4084

Notes: The dependent variable for the regressions above is ticket package quality, as by fixed fee paid. All variables in logs. The numbers in parentheses above t-values. † denotes significance at the 0.10 level or better. Source: Bertonazzi, Maloney and McCormick (1993).

To test the Alchian-Allen effect in CU season tickets consumption, Bertonazzi, Maloney and

McCormick (1993) construct a sample of more than 23,000 season-ticket purchases wherein the dependent variable is season ticket package quality, as measured by the fixed fee (donation) paid by the buyer.6 The dependent variable is a function of a number of controls, along with two measures of “buyer travel” – the dollar cost of travel time (one way) and the distance (in miles) travelled (one way).7 These are, of course, expected to be positively related to season ticket package quality choices. The results of the empirical work by Bertonazzi, Maloney and McCormick (1993) are shown in Table 6. As Alchian-Allen theorem predicts, higher quality packages are purchased by alumni-fans who face higher 6 Alumni-fans of college football teams typically face fixed fees or donations in order to secure the privilege of purchasing higher-quality season ticket packages. Generally, the fees are directly related to the amenities (game day or otherwise) received, which are themselves directly related to season ticket package quality. In CU’s case, these fees/donation are IPTAY donations, where “IPTAY” is the historic CU designation – standing for “I pay ten a year” – for alumni-fan contributors. 7 The controls listed in Table 6 are not central to this study. For more on them, see Bertonazzi, Maloney and McCormick (1993).


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travel costs or who travel greater distances, ceteris paribus. As such, this example makes for a compelling anecdote of the Alchian-Allen effect for classroom use. 5. Seaside Golfing on the Monterrey Peninsula An additional example involving “buyer travel” rather than “goods travel” is that of golfing, which is the subject of a study of the Achian-Allen theorem by Brown, Rascher, McEvoy and Nagel (2006). Consider, for example, the case of golfing on the Monterrey Peninsula. This area of California is home to two of the country’s finest public golf courses – Pebble Beach Golf Links and Spyglass Hill Golf Course – both of which are rated as five-star courses by Golf Digest (golfdigest.com).8 The peak, or weekend, price of a round of golf at Pebble Beach Golf Links is $530 (including cart), while the same for Spyglass Hill Golf Course is $360. These are, of course, the fees faced by a local golfer who resides in the town of Pebble Beach. As indicated in Table 7, the relative price facing this local golfer of one round at Pebble Beach Golf Links is 1.472 rounds of golf at Spyglass Hill Golf Course.

Table 7: The Alchian-Allen Effect on Links Golf in California

Course Patron Course Fees Relative Price of PBGL SHGC PBGL Local $360 $530 1.472 Atlanta, GA $864 $1,034 1.197

Note: Example assumes airfare between Atlanta and San Francisco of $504 (google.com). SHGC denotes Spyglass Hill Golf Course; PBGL denotes Pebble Beach Golf Links.

Table 7 also provides the relative price faced by a tourist-golfer from Atlanta, who requires

round trip air fare of $504 to reach the seaside courses of the Monterrey Peninsula. For this individual, the money prices are $864 and $1,034, both including air fare, for Spyglass Hill Golf Course and Pebble Beach Golf Links, respectively. For the tourist-golfer from Atlanta, the relative price of one round at Pebble Beach Golf Links is 1.197 rounds of golf at Spyglass Hill Golf Course, a figure that is 18.7 percent lower than that faced by the Pebble Beach native (i.e., the local golfer).

Brown et al. (2006) test an example of the Alchian-Allen effect like the one described above for golfing at Pebble Beach. These authors examine golfing in Ohio, which is home to 750 golf courses. Using a random selection of 45 golf courses, Brown et al. (2006) gathered survey data on buyer characteristics from 376 golfers who patronized the selected courses. These characteristics included golfers’ expenditures on greens (course) and cart fees, as well as distance travelled. Assuming a direct relationship between price and golf course quality, Brown et al. (2006) obtained Pearson correlation statistics for the relationship between various forms of spending on golf and distance travelled to the course by the respective course patron. Statistical results for their overall sample, and for the sub-sample of golf tourists, are presented in Table 8.

As the Brown et al. (2006) results indicate, there is a significant (0.01 level) positive correlation between total course spending (i.e., greens fee, cart fee and other expenses) and distance travelled by the golf course patrons. This correlation, 0.590, resides between correlations for greens fee spending and greens and cart fee spending, respectively, and distance travelled. These additional correlation statistics are 0.549 and 0.669, respectively, and each is significant at the 0.01 level. Interestingly, for the golf tourists’ sub-sample, the correlations are even stronger. For example, the correlation between total

8 Spyglass Hill Golf Course was designed by Robert Trent Jones, while Jack Nicklaus is one of the co-designers of Pebble Beach Golf Links’ modern layout.


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course spending (i.e., greens fee, cart fee and other expenses) and distance travelled by the golf tourists is a robust 0.986, while that for both the greens fee-distance and greens and cart fee-distance is 0.983. Lastly, in the case of golf tourists, even the relationship between cart fee spending and distance travelled is positive, based on a Pearson correlation coefficient of 0.360, and statistically significant (at the 0.05 level). Golf provides yet another example of the Alchian-Allen effect and “buyer travel.”

Table 8: Correlations between Travel Distance and Golf Spending

Spending Category All Golfers (n = 376)

Golf Tourists (n = 35)

Greens Fee 0.549* 0.983* Cart Fee 0.026 0.360† Greens & Cart Fee 0.669* 0.983* Total Course Spending 0.590* 0.986†

Note: *(†) denotes significance at the 0.01(0.05) level. Source: Brown, Rascher, McEvoy and Nagel (2006).

6. Macroeconomics and the Costs of College The opportunity cost of higher education attainment is a popular textbook example for explaining the concept of opportunity costs. As the story traditionally appears, a hypothetical student (freshman) faces explicit opportunity costs for a year of higher education consisting of tuition, fees and textbooks. Added to these are the implicit opportunity costs associated with foregone earnings that are incurred when the student pursues education on a full-time basis.9 For example, with annual tuition at $12,192 (ucsb.edu) for one year of study at the University of California – Santa Barbara (UCSB), and a full-time work week foregone due to education pursuits, the typical UCSB freshman faces an explicit opportunity cost of $12,192 and an implicit opportunity cost of about $14,040 for the traditional freshman year.10 In this case, the total opportunity cost is $26,232 for the first academic year.

Consider the case of two in-state universities, UCSB, a public institution, and the University of Southern California (USC), a private institution. As a private institution, prospective students face much higher explicit costs when considering USC over UCSB. With annual tuition at $23,781 (usc.edu) for one year of study at USC, and a full-time work week foregone due to education pursuits, the typical USC freshman faces an explicit opportunity cost of $23,781 and the same implicit opportunity cost as the UCSB freshman of about $14,040 for the traditional freshman year. Thus, the total opportunity cost is $37,821 for the first academic year. The comparison of the opportunity costs of attending these two institutions, as in Table 9, allows for a discussion of relative prices. For example, using the data above, which are also presented in Table 9, the relative price of one year of higher education at USC is calculated as 1.442 years of higher education at UCSB (i.e., $37,821/$26,232).

9 Following the “rule of two,” the typical college freshman must study three hours outside of the classroom for every assigned hour of classroom lecture. Thus, for a student registered for 15-18 semester hours, 30-36 hours of outside study are required. Combined with the 15-18 hours of in-class instruction, the pursuit of higher education consumes 45-54 hours per week. 10 In calculating explicit cost, this example assumes, for simplicity, that fees and book expenses are included in tuition. To calculate implicit costs, the California minimum wage ($9.00/hour) is applied to three-fourths (0.75) of a full-time work year (2,080 hours) to encompass a nine-month academic year, such that implicit costs equal 0.75×2,080×$9, or $14,040.


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Table 9: The Opportunity Costs of College

One Academic Year Explicit Costs

Implicit Costs

Total Costs

UCSB $12,192 $14,040 $26,232 USC $23,781 $14,040 $37,821

Sources: www.admissions.ucla.edu/prospect/budget.htm https://catalogue.usc.edu/tuition/

The analysis above falls short of a real-world scenario by not accounting for the state of the

macroeconomy and how it impacts the probability, p, of securing a job paying $14,040 over the nine-month academic year (i.e., full-time employment at the California minimum wage). In a relatively bad macroeconomy, like that of the 2008-present period, the unemployment rate (U*) is high and the probability of securing employment after high school is low. If we assume that in a bad macroeconomic situation p is a low 0.45, then the expected implicit costs of an academic year at either a public or private institution is only $6,318 (0.45×$14,040). This situation is depicted in Table 10 for a prospective student who is considering both UCSB and USC. As shown there, the total costs (per year) of attending these institutions are now $18,510 and $30,099, respectively. Both of these totals are well below those shown in Table 9, thus revealing the rationale for the countercyclical nature of college enrollments, which increase as the macroeconomy worsens (U* rises), ceteris paribus.

Table 10: College Costs in a Bad Macroeconomy

One Academic Year

Explicit Costs

Expected Implicit

Costs

Total Costs

UCSB $12,192 $6,318 $18,510 USC $23,781 $6,318 $30,099

On the other hand, in a relatively good macroeconomy, like that of the 1990s, the

unemployment rate (U*) is low and the probability of securing employment after high school is high. If we assume that in a good macroeconomic situation p is as high as 0.90, then the expected implicit costs of an academic year at either a public or private institution is $12,636 (i.e., 0.90×$14,040). This situation is depicted in Table 11 for a prospective student who is considering both UCSB and USC. As shown there, the total costs (per year) of attending these institutions are now $24,828 and $36,417, respectively. Both of these totals are well above those shown in Table 10.

Table 11: College Costs in a Good Macroeconomy

One Academic Year

Explicit Costs

Expected Implicit

Costs

Total Costs

UCSB $12,192 $12,636 $24,828 USC $23,781 $12,636 $36,417

The more complex presentation of the traditional opportunity costs of college story allows for

an integration of the Alchian-Allen theorem. The example in Table 12 is based on the numbers from the hypothetical scenarios shown in Tables 10 and 11. Starting with the bad macroeconomy, as the


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macroeconomy improves (i.e., U* falls), and the probability of securing employment rises (from 0.45 to 0.90), the relative price of an academic year at USC falls from 1.626 academic years at UCSB to 1.467 academic years at UCSB, a change that represents a 9.8 percent decrease. Given this development, the ratio of USC enrollment to UCSB enrollment should rise, as prospective students opt for the private university due to the decrease in its relative price. Of course, as the macroeconomy worsens (i.e., U* rises), and the probability of securing employment falls (from 0.90 to 0.45), the relative price of an academic year at USC rises from 1.467 academic years at UCSB to 1.626 academic years at UCSB, a change that represents a 10.8 percent increase. In this case, the ratio of USC enrollment to UCSB enrollment should fall, as prospective students opt for the public university due to an increase in the relative price of the private university.

Table 12: The Alchian-Allen Effect and the Costs of College

Macroeconomy Total Costs Relative Price of USC UCSB USC Bad $18,510 $30,099 1.626

Good $24,828 $36,417 1.467

The integration of the Alchian-Allen effect into the cost of college story is the focus of a study by

Kroncke and Ressler (1993). They hypothesize that as the economy worsens, and U* rises, the ratio of public college/university enrollment to private college/university enrollment will rise, reflecting the higher relative price of private college/university education that results from a decrease in the expected implicit costs of higher education. In the statistical sense, the expectation is of a positive relationship between U* and the enrollment ratio in this case.11 Results from two econometric tests of this hypothesis appearing in Kroncke and Ressler (1993) are shown in Table 13. The first is based on a time-series of national enrollment data, wherein the enrollment ratio is a function of U* and other control variables. The second is based on a cross-section of state-level enrollment data, wherein again the enrollment ratio (by state) is a function of U* and additional control variables.12

As shown in Table 13, U* is both positive and statistically significant in each of the two econometric models, although Kroncke and Ressler (1993: 347) note that the time-series approach suffers from first-order autocorrelation. As they point out, the cross-section approach was undertaken to account for the statistical shortcomings of the time-series results. As Kroncke and Ressler (1993: 348) conclude:

“This paper has stated and formally put forth the so-called Alchian-Allen effect and applied this phenomenon to higher education. Specifically, we have shown that when the magnitude of foregone employment opportunities changes (as shown by the unemployment rate), the relative full prices of public to private higher education changes. This, in turn, changes the relative quantities demanded of public and private educations.”

The more complex presentation of the traditional opportunity costs of college story that allows

for an integration of the Alchian-Allen theorem may make this particular Alchian-Allen anecdote too 11 It bears repeating here that Kroncke and Ressler (1993) model the Alchian-Allen effect from the opposite angle to the example presented here. That is, the model the public-to-private enrollment ratio rather than the private-to-public enrollment ratio depicted in our example. 12 The controls listed in the time-series and cross-section models shown in Table 13 are not central to this study. For more on them, see Kroncke and Ressler (1993).


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difficult for use in a traditional economics principles course. It may, however, be appropriate for a principles course taught via an honors section, or for an intermediate level economics course. In that sense, this particular essay extends beyond instructional attributes of the traditional principles course.

Table 13: Kroncke and Ressler’s Econometric Results

Time-Series

Model Cross-Section

Model Intercept −8.1563†

(−2.038) −0.5905

(−0.135) U* 0.2785†

(2.357) 7.0689†

(3.264) U*-squared −0.0158

(−1.700) −1.4551†

(−2.584) Income 1.6134†

(2.309) 0.1146

(0.232) Financial Aid −0.3480†

(−2.137) Tuition Ratio 0.0489

(0.255) Population −0.0751

(−0.438) n 25 94 R2 0.337 0.494

Notes: The dependent variable for the regressions above is the ratio of public enrollment to private enrollment. The numbers in parentheses above are t-values. † denotes significance at the 0.10 level or better. Source: Kroncke and Ressler (1993).

7. College Tuition Policies and Student Credit Hours Purchased

In an analysis of “substitution across characteristics within a good,” rather than the traditional approach of concentrating on substitution between two or more goods, Staten and Umbeck (1989) expand upon the uses, and importance of the Alchian-Allen effect. Their empirical analysis of what they term as “intragood substitution” is based upon the notion that most goods have multiple attributes, with only some of these being explicitly priced. As they indicate, given that most goods are heterogeneous across units, buyers adjust their consumption toward units of the good with relatively more of the un-priced attributes and away from the priced margins (Staten and Umbeck, 1989: 165). Among several examples, they point out that buyers of prepackaged strawberries (by the quart) will sort through the bundles for those with the ripest or juiciest berries. Integrating the shipping cost concept from Alchian and Allen (1964) into the intragood substitution concept, they add that one would expect (1) that “‘seconds’ (slightly defective merchandise, particularly clothing) to be more heavily consumed near the place of manufacture,” and (2) that “a larger percentage of meat shipped to Alaska is deboned, relative to meat consumed near the point of processing” (see also Alchian and Allen, 1983: 71).

Staten and Umbeck (1989) extend the analysis of intragood substitution to the Alchian-Allen effect by examining the different credit-hours consumption choices made by resident and nonresident students at public universities. More specifically, they examine the tuition policies at the University of Delaware (UD) during the mid-1980s, when the institution charged resident students the fixed fee of


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$795 for up to 15 semester credit hours, while at the same time nonresidents were charged a fixed fee of $1,950 for the same consumption option. As Staten and Umbeck (1989: 167-168) hypothesize:

“Under these conditions, a wealth-maximizing student would select the optimal number of credit hours to take during a given semester by weighing the extra costs (primarily nonmonetary) of more-intensive semesters against the savings associated with reducing the number of times the fixed fee must be paid, given the required credit hours in the degree plan. As the semester fee rises, so do the relative gains from injecting more credit hours into each semester, leading to an adjustment of education consumption toward units of the good (semesters) with more of the unpriced attribute, credit hours. Consequently, we should observe wealth-maximizing nonresidents taking course loads that are heavier, on average, each semester, than the loads taken by resident students with identical demands.”

To test their hypothesis, Staten and Umbeck (1989) examine the credit hours consumption

choices, during fall of 1983 and spring of 1984, of resident and nonresident students at UD, all across 15 separate academic majors. In order to control for demand differences between the two groups that may be due to ability differences, given that UD admissions standards for residents are less stringent than those facing nonresidents, they restricted their analysis to only those students scoring 1,200 or higher on the SAT. The results from their means-differences tests are shown in Table 14.

As Staten and Umbeck (1989) indicate, two semesters of data across 15 majors during an academic year (i.e., 1983-84) provide for 30 separate statistical tests of their hypothesis that the Alchian-Allen effect would lead to larger semester course-load choices by nonresident students at UD. As pointed out in Table 14, their hypothesis is supported in 22 of the 30 cases (73.3 percent), and significantly so at the 0.05 level in seven of the 22 supporting cases (31.8 percent).13 Although not reported in Table 14, additional results by Staten and Umbeck extend the analysis to all 10 semesters (at UD) from 1979 to 1984, resulting in 150 separate trials (i.e., 10 semesters and 15 academic majors). Their analysis indicates that in 126 trials (84 percent) the nonresident student credit hour average exceeded that of residents, and significantly so (at the 0.05 level) in 54 of these 126 trials (42.9 percent). On the other hand, in only 24 trials did the resident student credit hour average exceed that of nonresident students, with only four of these 24 meeting the 0.05 level of significance. These results are stronger than those wherein the data are restricted to only the 1983-1984 academic year.

As in the previous example from Kroncke and Ressler (1993), the more complex presentation of the importance of the Alchian-Allen effect by Staten and Umbeck (1989), given their integration of the “intragood substitution” concept, may render this anecdote too difficult for use in a traditional economics principles course. As in the Kroncke and Ressler (1993) anecdote, it may, however, be appropriate for a principles course taught via an honors section, or for an intermediate level economics course. Either way, it is a neat example that “freshens up” the traditional textbook presentation of the application of Alchian and Allen’s (1964) original work.

13 As Staten and Umbeck (1989: 169) point out, if one considers each of the 30 differences a separate and independent trial of the substitution implication, and one assumes that tuition differences have no effect, there would be no difference between the two groups in course credits taken (i.e., in repeated trials, one would expect to observe nonresidents taking more courses than residents only 50 percent of the time). This null hypothesis (i.e., actual ratio of trials wherein nonresident credit hour average exceeds resident credit hour average is 0.50), however, rejected in a chi-square test comparing 0.73, the actual nonresident credit hour average, to 0.50 at the 0.05 level of significance.


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Table 14: Comparison of Average Credits by Residency

Fall 1983 Spring 1984 Major Residency Avg. Hours Diff Avg. Hours Diff

Accounting NR R

14.88 14.77 0.11 14.53

13.77 0.76*

Biology NR R

15.00 14.78 0.22 14.87

14.32 0.55*

Chemical Engineering NR R

15.19 14.84 0.35 14.77

14.53 0.24

Chemistry NR R

15.37 15.05 0.32 14.97

15.31 −0.34

Communications NR R

15.68 16.20 −0.52 15.29

13.20 2.09*

Computer Science NR R

15.44 15.29 0.15 15.13

14.14 0.99*

Economics NR R

14.61 15.00 −0.39 14.50

14.77 −0.27

Electrical Engineering NR R

15.38 15.36 0.02 14.90

15.06 −0.16

English NR R

14.56 15.70 −1.14* 14.43

13.70 0.73

Management NR R

15.46 14.27 1.19* 15.00

14.70 0.30

Marketing NR R

13.75 16.50 −2.25* 13.91

15.50 −1.59

Mechanical Engineering NR R

15.55 15.02 0.53* 14.98

14.78 0.20

Nursing NR R

14.95 14.27 0.68 14.76

14.42 0.34

Political Science NR R

14.63 14.27 0.36 15.10

14.07 1.03

Psychology NR R

15.15 15.00 0.15 15.00

13.75 1.25*

Notes: NR denotes nonresident students; R denotes resident students. * denotes significance at the 0.05 level. Source: Staten and Umbeck (1989).

8. Is the Alchian-Allen Effect Bad for Long-Distance Romance?

It turns out that economics, in this case the Alchian-Allen effect, has much to say even about long-distance relationships, and why they are so difficult. Through his economics weblog, Marginal Revolution, economist Tyler Cowen addressed this issue in 2006, hinting at the reduced relative price of an expensive date facing two partners in a long-distance romance:14

14 See http://marginalrevolution.com/marginalrevolution/2006/09/trudie_on_longd.html.


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“. . . you must confront the Alchian and Allen Theorem. The higher the fixed cost, the ‘higher quality’ a trip you will both tend to seek . . . More concretely, who would fly across the country for a mere kiss on the cheek?”

On two separate occasions, economist Tim Harford echoes Cowen’s point about long-distance

romance. In a 2006 column in The Financial Times, Harford writes:15

“Economist Tyler Cowen, a professor at George Mason University, has pointed out that the Alchian-Allen theorem applies to any long-distance relationship. The theorem, briefly, implies that Australians drink higher-quality Californian wine than Californians, and vice-versa, because it is only worth the transportation costs for the most expensive wine. Similarly, there is no point in travelling to see your boyfriend for a take-away Indian meal and an evening in front of the tel[evision].”

Later, in a 2008 column in The National Post, Harford adds:16

“The answer [to the difficulty with long-distance love], says Mr. Cowen, lies in the Alchian-Allen Theorem. Developed in 1964 by economists Armen Alchian and William R. Allen, the theorem states that adding a per unit charge to the price of two substitute goods increases the relative consumption of the higher price good. In layman’s terms, ‘you don’t take a long trip unless you are going to make it worth your while,’ he says. Very few people in a long-distance relationship are going to fly across the country just to hang out in sweatpants with their sweetheart.”

Here, we provide a backdrop to Cowen’s (and Harford’s) point. At New York City’s Johnny

Rockets, a hamburger with fries for two is $18, while Muscovy Duck (with seared foie gras, roasted apricots, quinoa, almonds, mustard greens and ruby port sauce) for two at the Gotham Bar and Grill in New York City is $86. Suppose one of the partners lives in Chicago, and, thus flies to New York City to see the other. Suppose also that the flight to New York City from Chicago is $264. This fixed fee changes the relative price of the two potential dinner date destinations – Johnny Rockets and Gotham Bar and Grill. These changes are reflected in Table 15.

Table 15: The Alchian-Allen Effect and Long-Distance Relationships

Relationship Total Costs Relative Price of GBG JR GBG Local $18 $86 4.778 Long-Distance $282 $350 1.241

Note: Example assumes airfare between Chicago and NYC of $264 (google.com). JR denotes Johnny Rockets; GBG denotes Gotham Bar and Grill.

As indicated in Table 15, the plane fare increases the money prices of both meals (for two) by

$264, resulting in totals of $282 and $350 for Johnny Rockets and Gotham Bar and Grill, respectively. As such, the relative price of the Gotham Bar and Grill date falls by a whopping 74 percent, from 4.778 to

15 See http://marginalrevolution.com/marginalrevolution/2006/11/tim_harford_on_.html. See also Harford (2009). 16 See http://marginalrevolution.com/marginalrevolution/2008/02/the-costs-and-b.html.


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only 1.241. This decrease will exert pressure on the two “love birds” to choose Gotham Bar and Grill every time, thus raising the expectations of the romance. Cowen addresses this vexing point as well:17

“. . . moving too fast is dangerous and ill-advised. And in the longer run you will each ‘expect too much’ from each visit. Remember the old question: ‘Are We Having Fun Now?’ . . . The Alchian and Allen Theorem is a potent enemy of the all-important ‘low expectations’ and that alone is one good reason to keep transportation costs low in your life . . . The quest for continual high-quality excitement is not conducive to casual down time together, which is the glue which binds relationships together in the longer run.”18

In this instance, however, Cowen offers a solution, albeit a “difficult one,” to the problem facing

the two romance seekers:19

The solution is simple conceptually but difficult to implement. Do something else with part of your trip to the west (east) coast. Lower expectations for the visit. Meet another friend too, or set up some business, or give a paper at a scintillating academic conference. Yes you will have less time with your potential beloved, but the remaining time will get you further toward where you want to be. How much time does one need to fall in love anyway?”

Many current students of economics principles are, themselves, navigating the waters of long-

distance relationships. Thus, although the distances and other tribulations involved in their current circumstances may not reach those experienced by older adults in their particular situations, this anecdote should resonate well with principles of economics students today. 9. Concluding Remarks This study offers fresh alternative illustrations of the Alchian-Allen effect (Alchian and Allen, 1964; Borcherding and Silberberg, 1978). Drawing on examples as dissimilar as the slave trade in the South and long-distance romance, this paper provides several examples certain to engage, entertain, and educate students of economics about this important effect.

17 See http://marginalrevolution.com/marginalrevolution/2006/09/trudie_on_longd.html. 18 Harford adds (see footnotes 13 and 14) that the partners will, to justify the trip’s fixed costs, usually require “champagne [and] sparkling conversation,” thus putting “excess pressure on the relationship.” 19 See http://marginalrevolution.com/marginalrevolution/2006/09/trudie_on_longd.html.


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Documents

Shipping the Good Anecdotes In: Illustrations of the