Collateralization of Assets, Over-Extension of Credit, and Free Trade: An Empirical Analysis in Search of Justice and an Expanding Middle Class Part 3

Charalambakis

  • Dr. John E. Charalambakis is the Chief Economist at Blacksummit Financial Group, Inc. Lexington, Kentucky. He is also with the Adjunct Faculty at Patterson School of Diplomacy, University of Kentucky.

Coauthored by: Dr. David Coulliette of Asbury University and Dr. Kenneth Rietz of Centre College

 This article will be posted in three segments due its length. This is Part III.

The Empirical Results: Methodology, Selection of Variables, and of Countries

We need to emphasize in the beginning of this section that the results and analysis here is preliminary and research is already underway for better understanding of the ideas that have been developed in this paper. Since part of the research is to determine which factors in the four infrastructure areas would contribute to the emergence of a middle class (once capital formation has taken place via the means of international trade), the first (and admittedly most subjective) step was to develop an initial list of factors that describe the infrastructure for each country.

Data were collected from different sources, such as the World Bank, the IMF, different branches of the UN (UNDP, and UNCTAD), and the World Factbook for the 2005 year. Note that the first step of the algorithm scaled the data by dividing by the maximum absolute value that occurred for each data variable, to prevent the larger-scale factors (such as exports) from overwhelming the smaller-scale factors (such as student-teacher ratio) in the model. This allowed us to readily compare the effectiveness of the coefficients that we obtained.

Since part of the purpose was to establish a proof of concept for using the Support Vector Machine (SVM) and a broad scope of infrastructures, originally it was decided that limiting the number of countries would achieve the purpose. We selected small lists of countries under each of the three categories frontier, emerging, and developed. Frontier countries are ones that most economists would agree have very few people in the middle class, but have the potential, such as sufficient resources, to develop one. Emerging countries have a middle class that is growing. Developed countries have a mature and stable middle class. An initial run used a very small sample of countries in each category. It was exceedingly successful, prompting an expansion of the lists. This paper details the results of the newer results.

Discussion of Algorithm

The mathematical technique used to determine the significance of the factors was the Support Vector Machine (SVM).  This is a classification method from learning theory that uses a set of input training data {(x1, y1), (x2, y2), . . ., (xk, yk)} where the xi represents vectors of dimension n and the y values are assigned a value of +1 or -1, depending on whether the point is inside a set or not.  For the purposes of this study, the x vectors hold the list of factors that describe the state of a given country that may be characterized as having a middle class (y = +1) or not (y = -1).

In common with most learning algorithm, the SVM algorithm operates in two phases. In the training phase, the SVM model with a linear kernel takes the training data and produces a bias value b and a vector c (dimension n) of coefficients. The testing phase of SVM  is then run on all the data, using just the n-dimensional vectors even if the y-value is known. The algorithm will calculate the dot product of the coefficient vector with the data vector and then subtract off the bias value. If the resulting number is positive, the algorithm predicts a y-value of +1; if it is negative, the algorithm predicts a y-value of -1.  Running the algorithm on the training data verifies that the training phase worked well.

This particular implementation of the SVM algorithm uses what is termed a linear kernel. It was chosen because of the limited number of countries in the data set, and because the linear kernel tends to be the worst performer. If this kernel works, then increased data and a non-linear kernel should work much better. A non-linear kernel has an additional step when the data is transformed non-linearly before the coefficients are determined.

A non-linear kernel will be important as this study proceeds. An example will illustrate the reason. One factor that is critical to the development of the middle class is the extension of credit. People in the lower classes do not have the capital with which to start a business and thereby move to a higher class. The marvelous success of microloans illustrates this point. Therefore, in a linear model, the amount of credit extended would certainly have a positive coefficient. That would imply that as more credit is extended, even greater benefits accrue. But at some point, credit may become overextended, and become detrimental to the middle class (see concluding note.) This is arguably a significant factor in what caused the collapse of the middle classes of Argentina and Mexico in the recent past. That means that the extension of credit must, at that point, have a negative coefficient. Only a non-linear approach to modeling the middle class can accommodate both aspects of the extension of credit. Similar comments could be made about other data, such as inflation (CPI), which has a rather small range of values considered healthy, while values much outside that range are considered detrimental to a country’s economy.

Analysis of Data: Initial Run

First, we ran SVM on a collection of 44 countries using 45 factors for each country. The training set was the collection of 17 frontier countries and 10 developed countries. The testing phase consisted of finding the predictions for those as well as the 17 emerging countries. (The same process was used during the reduced factor run of SVM.) The results are summarized in Table 1 on the next page, giving the SVM output value, but not the prediction, which is easy to determine from the sign of the output.

The first 17 rows of the table list the frontier countries, the next 17 rows list the emerging countries, and the last 10 rows list the developed countries. There are also two columns. The first numeric column gives the SVM output using all 45 factors for training and testing. The other numeric column will be explained below.

The results show very clearly that the SVM algorithm (even with the linear kernel) works very well. The frontier countries, except for Thailand, all fall into the SVM output range of -1.0 to -1.6; the emerging countries mostly fall in the range from -0.8 to 0.0; the developed countries, except for South Korea, fall in the range 0.6 to 1.5. These results, especially for the frontier and developed countries, form a primary validation of the SVM algorithm; it does seem to be doing what we want it to do. The separation between the ranges for the different categories of countries also seems remarkably large, providing further evidence that the algorithm is working.

Country 45 Factors

 

10 factors
Albania

-0.9999

-1.0479

Angola

-1.5701

-1.3473

Bolivia

-1.0987

-1.2265

Ethiopia

-1.6106

-1.4777

Georgia

-1.2053

-1.1505

Ghana

-1.4369

-1.2124

Guatemala

-1.1876

-1.0855

Indonesia

-1.2804

-1.2320

Kazakhstan

-1.0000

-0.8798

Kenya

-1.4301

-1.3824

Lebanon

-1.0003

-1.0088

Morocco

-1.1062

-1.0533

Nigeria

-1.4359

-1.3758

Peru

-1.0963

-1.0486

Philippines

-1.1356

-1.1535

Thailand

-0.9608

-0.8136

Venezuela

-1.0001

-1.0002

Argentina

-0.6834

-0.7224

Botswana

-0.4742

-0.5624

Brazil

-0.7782

-0.9008

Chile

-0.4801

-0.3891

China

-0.1282

-0.6589

Czech Republic

0.4781

0.0827

Egypt

-1.1327

-1.1795

India

-1.1646

-1.1560

Iran

-1.1666

-1.0534

Malaysia

-0.2523

-0.4184

Mexico

-0.8208

-0.7842

Poland

-0.4681

-0.4366

Romania

-0.8441

-0.7429

Russia

0.0256

-0.6292

South Africa

-0.5709

-0.5240

Turkey

0.5125

0.8718

Ukraine

-0.5202

-0.7147

Australia

0.9445

1.0000

Canada

1.0754

1.0976

France

1.2936

1.0998

Germany

1.4943

1.5142

Japan

1.5026

1.0235

Republic of Korea

0.1209

-0.0290

Singapore

0.9340

0.9998

Sweden

1.0516

1.2535

United Kingdom

0.6674

1.0005

USA

1.4181

1.5219

Table 1

Reduction of Factors

It could easily be argued that with 45 factors and 44 countries, it is easy to expect results of this caliber. So, we attempted to reduce the number of factors used, still regarding the conceptual framework.

The factors used in the remainder of this discussion are as follows:

v For physical infrastructure:

  • Paved roads in kilometers per capita
  • Number of cell phones per capita

v  For social infrastructure:

  • Amount spent on healthcare per capita
  • Literacy Rate

v For financial infrastructure:

  • Private sector credit as a percent of GDP
  • GDP (PPP) per capita

v For legal infrastructure:

  • Corruption index (Transparency International)

v For international trade (in dollars):

  • Exports
  • Imports per capita
  • Foreign reserves per capita

Table 1 above lists the output of the SVM algorithm using only these ten factors, in the second numeric column. Table 2 below lists these ten factors, and the coefficients that the SVM algorithm generates for each. (It should also be noted that results equivalently good can be obtained with only six factors, showing that SVM is more than adequate for separating the categories of countries.)

Factor

Coefficient
Paved roads in km per capita

0.2416

Number of cell phones per capita

0.3675

Amount spent on healthcare per capita

0.7636

Literacy rate

0.05407

Private sector credit as a percent of GDP

0.1571

GDP (PPP) per capita

0.9074

Corruption index

0.8518

Exports (billions USD)

0.4490

Imports per capita

0.3133

Foreign reserves per capita

0.2819

Table 2

The following comments are in order: First, all developed countries, with the exception of South Korea, show up with SVM output values in the appropriate range. This exception appears puzzling at first glance, but an examination of the data shows that it is almost entirely due to a value of the corruption index that is considerably lower than for other developed countries.

Second, this time only the Czech Republic shows with a positive prediction, although Turkey is very nearly positive. This complies with the liberalization and openness that both countries have exhibited over the last two decades, both most likely the result of the incentive provided by the future possibility of membership in the European Union. We could then, make the claim that international openness and exchanges serve the purpose of forming capital and thus, advancing the formation of the needed infrastructures which in turn will lead to the creation of the middle class.

Third, the relatively weak positions of Egypt, India, and Iran need to be reviewed in a time series before any conclusion is reached.. However, it is also worth mentioning that just by trade alone China performs better in the SVM, a fact which by itself could help us understand a little better the value of international trade in forming the necessary cornerstones that a middle class needs.

Conclusion: A Word of Caution and Direction for Future Research

The empirical part of this paper should be viewed as a proof-of-concept attempt for using a multi-factor and linear approach to quantifying the extent to which international trade forms the basis of capital formation, which in turn advances the formation of infrastructures that create a middle class. These results seem to indicate that using international trade and the infrastructures as have been described above along with the SVM algorithm, is a feasible methodology, and is worth continuing in broadly the same direction.

However, at this point I would like very briefly to introduce the idea of what happens when things go to the extreme, especially when the financial sector’s interests diverge from the trade sector’s interests i.e. from the production or real economy’s interests.  When efforts are being made to sustain prosperity and the middle class with paper means rather than real assets and real production, then we will see a divergence of the production and real sectors interests from the financial sector’s interests.  The latter will tend to produce paper assets which will be over-collateralized, over-securitized, for the purpose of generating significant short-term profits. The table below shows the explosion of derivatives and other related instruments (CDOs, CLOs, etc.) in the last few years. It demonstrates the extent of irrational collateralization of “assets”, where the financial sector keeps pushing for more and more securitization of paper assets, which will be sliced into pieces and sold to individual and institutional investors.

Source: Bank of International Settlements, 2008

Of course, it seems that we are just start learning the lesson that these paper-assets are nothing more than paper, i.e. there is nothing behind them.  This is the phenomenon of extreme and irrational securitization and collateralization that is taking place in the U.S. and the EU, and which has been destroying the financial sector, because it can only create bubbles and bubbles usually burst. The bursting of the bubbles will create in turn instability not only in the economic sector but also in the political and social sectors, and therefore the whole economy’s cohesiveness may become unstable and questionable, which eventually may lead to significant destructions.  As direction for future research, it would be interesting to identify the possibility for economies to establish a rule by which they collateralize and securitize assets in a way that will not destabilize the economies.  The proposal for future research would be to form an index of internationalization of the economy – whether this is imports and exports as a fraction of GDP, foreign reserves, FDIs, currency swings, technology transfers, etc – and use this index as the compass/anchor of collateralization and securitization, so that the interest of the real economy (production) are not disassociated from the interests of financial capital, and thus do not jeopardize the sustainment of the middle class via misallocation of resources.

 References

Aristotle, 1985, Nicomachean Ethics. T. Irwin, trans., Hackett, IN

Bernstein William, 2008, A Splendid Exchange, Atlantic Monthly Press, NY

Chen, P.-H. & Lin, C.-J. & Scholkopf, B. A Tutorial on ?-Support Vector Machines, [available at  http://www.csie.ntu.edu.tw/~cjlin/papers/nusvmtutorial.pdf]

Crafts Nicholas, 2000, Globalization and Growth in the Twentieth Century, IMF Working Paper, march

Donaldson, James; Roberts, Alexander, ed., 1994, Ante-Nicene Fathers, The Teachings of the Twelve Apostles, Hendrickson Publishers, Vol. 7

Dunning, H. Ray, 1998, Reflecting the Divine Image: Christian Ethics in Wesleyan Perspective, Intervarsity Press

Edwrads Sebastian, 1998, Openess, Productivity and Growth: What Do we Really Know? The Economic Journal, Vol. 108, pp. 383-398

Goldberg P., and Pavcnik N., 2007, Distributional Effects of Globalization in Developing Countries, Journal of Economic Literature, Vol. XLV, No. 1

Hayek Friedrich, 1976, The Mirage of Social Justice, Vol. 2 of Law, legislation, and Liberty, Routledge and Kegan-Paul, London, UK

Harrison Ann and Hanson Gordon, 1999, Who Gains from Trade Reform? Some Remaining Puzzles, Journal of Development Economics, Vol. 59, No. 1

Hay Donald, 2001, The Post-1990 Brazilian Trade Liberalisation and the Performance of Large manufacturing Firms, Economic Journal, Vol. 111, pp. 620-641

Hobbes Thomas, 1926, Leviathan, Hafner, NY

Honan Park, 1983, Matthew Arnold: A Life, Harvard University Press, MA

Irwin, Douglas, 2002, Free Trade Under Fire, Princeton University press, NJ

Keller, Wolfgang, and Yeaple, 2003, Multinational Enterprises, International Trade, and Productivity Growth, NBER Working Papers, No. 9504

Lock John, 1983, The Second Treatise on Government, Hackett, IN

Mencius, The Mind of Mencius, D.C. Lau, trans., Penguin, NY

Mill, John Stuart, 1910, The Letters of John Stuart Mill, ed. Hugh Elliot, Longmans Green, NY

Montesquieu, 1989, The Spirit of the Laws, trans., Cohler, Miller and Stone, Cambridge University Press, NY

Nozick Robert, 1974, Anarchy State and Utopia, Basic Books, NY

Plato, 1982, The Republic, G.M.A.Grube, trans., Hackett, IN

Rawls John, 1971, A Theory of Justice, Harvard University Press, MA

Sachs Jeffrey and Warner Andrew, 1995, Economic Reform and the Process of Global Integration, Brookings Papers on Economic Activity, Vol. 25, No. 1

Sala-I-Martin, Xavier, 2006, The World Distribution of Income, The Quarterly Journal of Economics, Vol. CXXI, No. 2

Solomon Robert and Mark Murphy, 1990, What is Justice? Oxford University Press, NY

Vlastos Gregory, 1962, Justice and Equality, in R. Brandt, ed., Social Justice, Prentice Hall, NJ

Wood Adrian, 1999, Openness and wage Inequality in Developing Countries, in market Integration, Regionalism and the Global Economy, ed., R. Baldwin et al., Cambridge University press, NY

Zakaria Fareed, 2003, The Future of Freedom, Norton, NY

 

 

Collateralization of Assets, Over-Extension of Credit, and Free Trade: An Empirical Analysis in Search of Justice and an Expanding Middle Class Part 2

Charalambakis

  • Dr. John E. Charalambakis is the Chief Economist at Blacksummit Financial Group, Inc. Lexington, Kentucky. He is also with the Adjunct Faculty at Patterson School of Diplomacy, University of Kentucky.

Coauthored by: Dr. David Coulliette of Asbury University and Dr. Kenneth Rietz of Centre College

 This article will be posted in three segments due its length. This is Part II.

To that of course, we should add that it was the ability that the U.S. extended to Europeans to reconstruct themselves and buy American products, that helped not only the American producers but also the local communities in Europe for their reconstruction efforts, for employment, for income, for capital formation, and for growth.  So unless there is international trade, unless there is the liberty to move things, to buy imported goods, to move capital, to move technology, to move people across nations and communities, unless there is freedom to move financial capital across oceans, there could not be a case of capital formation. The latter is the seed that is necessary for any kind of infrastructure to be produced whether that infrastructure is in the social sector (hospitals or schools), in a physical form (highways, roads, bridges and water systems), or in the financial field (banks, exchanges, brokerages). The buildup of these kind of infrastructures will create jobs and by creating jobs there will be savings and that savings will become the seed for loans and for credit extension which is necessary for business formation.  Now, all the above could be represented in the following diagram.

Flow diagram

 

In a framework like the one above free trade is advanced for the sake of justice.  Therefore, free trade is not an end in itself, it is a means to a higher end and that higher end is to treat equals equally.

We believe the following table, taken from Bernstein’s book would demonstrate our argument, in the sense that open and free trade cultivates the means for the advancement of persons’ capabilities in a holistic way.

Per Capita GDP

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When we contemplate on the above arguments, we will wonder what has been happening to the distribution of income across nations, what has been happening to inequality and poverty or the concept of convergence among nations.

Just a couple of years ago, Xavier Sala-i-Martin (Sala-i-Martin, 2006) published a well- documented survey of the world distribution of income, and he concluded that we have been experiencing falling poverty. At the same time he shows that convergence is taking place around the globe,  primarily in continents and nations that were characterized prior to the 1970s by extreme poverty and divergence.  His chief examples are the nations of China and India along with the whole region of Southeast Asia.

It would have been great if the survey had discussed the role that free trade has played in uplifting those countries and those continents out of poverty.  However, before we explore in greater detail Sala-i-Martin’s arguments regarding the reduction of poverty and convergence of global income, as well as discuss this paper’s findings regarding the role that international trade plays in the formulation of capital, the forming of infrastructures, and the establishment of the middle class, we would like us to review briefly what the classic arguments of John Stuart Mill (Mill, 1910) were in the midst of the nineteenth century when he was writing on international trade.

We would like to emphasize that in his writings, while he articulates well the advantages of free trade in terms of lower prices, higher incomes, great efficiencies, reduction of costs, allocation of resources, inviting new investments and in terms of higher productivity, he makes a very good point when he says that international trade and foreign transactions become the cornerstone of surplus capital that can be used to produce other things. Therefore, it is the savings in capital which advances efficiency, prohibits misallocation of resources, and assists nations in the production of goods or in the consumption of imports, all of which lead to higher standards of living, higher levels of disposable income, and thus greater propensity for capital accumulation.  However, all these benefits from free trade are not as important according to John Stuart Mill as the intellectual and moral advantages that free trade carries with it.

Empirical studies throughout the world have documented that free trade of goods, capital, and technology not only reduce prices and enhance incomes, but also act as the conduit for transferring the technologies that enhance productivity, increase competition and therefore, stimulate industries to become more efficient.  Moreover, the push for efficiency forces unproductive businesses to reform or go out of business.  Competition stimulates efficiency, and over the years study-after-study has documented this phenomenon.  Therefore, when we look at studies by Keller (Keller, Wolfgang, and Yerple, 2003), Hay (Hay 2001), Edwards (Edwards, 1998), Crafts, (Crafts, 2000), Harrison and Hanson (Harrison and Hanson, 1999), and Sachs and Warner (Sachs and Warner, 1995), we can see that overall economic growth as well as productivity growth can double and sometimes triple when industries become less sheltered from foreign competition.

Mexico is a classic case because it can be demonstrated that after its trade liberalization in 1985 its productivity increased dramatically.  The same happened in India as well as in South Korea.  These productivity gains, which we clearly understand to be economic gains, take place due to the new and more efficient allocation of resources within industries as well as across industries.  Empirical studies have also shown that trade liberalization over the past few decades in Spain, Chile and New Zealand have contributed to rapid growth in productivity as well as greater growth in their economy. While there might be a dispute as to whether trade is directly responsible for greater growth – studies actually diverge in their conclusions, see Franklen and Romer, 1999 or Rodriguez and Rodrik, 2001 – we do have however, a consensus which says that trade may not be directly correlated with growth, however it stimulates growth indirectly through investments, i.e. we have sufficient evidence of indirect relationship where growth increases in countries via the mechanism of international investments, which in our paradigm is the cornerstone of capital formation.

Now, if we return for a moment to our previous intellectual benefits, the non-economic benefits from trade, we can still remember the perpetual peace advocated by Immanuel Kant who suggested that a durable peace could be built upon a tripod of representative democracy, international organizations and economic interdependence.  Of course, we cannot neglect the expanding political science literature which illustrates that indeed economic interdependence among nations reduces the risk of conflict, mitigates the risk of war and finds that there is a positive link between trade and peace.  Even if we are tempted to question the plausibility of the relationship, we should not neglect the fact that study-after-study points to the apparent link between political reforms as an outcome of liberalization.  So while trade may fail to generate movement towards democracy, there is ample evidence to point that domestic institutions perform better, and are less corrupt when there is open trade and competition and when nations are open to each other in an accountable manner (Irwin, 2002).

Is it Convergence or Divergence?

Of course, there is plenty of literature that reviews the distributional effects of globalization.  We could point out reviews by Harrison and Gordon (1999), Adrian Wood (1999), Goldberg and Pavcnik (2007.) The latter, points out to the fact that countries that have experienced great forms of globalization either through more imports and exports or through the magnitude of capital flows, (FDIs, foreign exchange fluctuations, etc.) have experienced higher levels of inequality. Particularly on pp.48-49 of that review, the authors point out that countries from different continents have experienced either significant or slight increases in inequality, with the latter being measured either as skill premium between skilled and unskilled workers, or by the Gini coefficient, and sometimes by consumption or income patterns.

We need to point out that, as we mentioned earlier, the Xavier Sala-i-Martin (2006) article is very emphatic in demonstrating that worldwide poverty has been reduced and convergence has been achieved through globalization.

Sala-i-Martin points out that China has a lot to do with this kind of convergence, and he shows that if we use the $2 per day income line, then we could clearly see that poverty estimates have experienced a significant decrease in China between 1980 and the beginning of the twenty-first century, from about 48% to less than 15%.  For China, Sala-i-Martin reports that more than 250 million people escaped poverty because of globalization. He further reports the same thing for countries such as Indonesia and Thailand with the only exception is Southeast Asia being Papua New Guinea.  Overall, and excluding China, more than 200 million people escaped poverty because of globalization in the last quarter of a century.

He does point out that the big Asian success is dramatically different from the African experience.  In Africa, the total number of those living in poverty has jumped by more than 200 million persons.  In all African countries poverty and inequality has increased, with the exception of Botswana and maybe some small countries like Mauritius. Sala-i-Martin composes what he calls the WDI (World Distribution of Income) and presents an impressive time-series table of the WDI from the 1970s to the beginning of this century.  In that table, we could clearly see that all measures of inequality have been declining, whether we measure inequality using the Gini coefficient or the variance in the logs of income.  Moreover, he shows that that ratio of income of the top twenty percentile to the bottom twenty percentile, as well as the ratio of income of the top ten percentile to the bottom ten percentile has been experiencing significant decreases by as much as 30%.  Therefore, the graph below summarizes the WDI from the 70s to the beginning of the twenty-first century.

world income

Source: Xavier Sala-I- Martin, 2006

The argument of the paper is that the significant reduction in inequality which has been empirically demonstrated by Sala-i-Martin is the effect and the outcome of capital formation using the means of international trade.  Now, this is a strong argument that needs further investigation and a lot more work, however from a theoretical standpoint as well as from a historical standpoint we can say that nations, empires and economic powers have built themselves up through savings and capital formation using the means of international trade.

As Bernstein clearly explains in his book, A Splendid Exchange, whether we talk about the Sumerians, Chinese, Portuguese, Spanish, British or the Americans, they all have built their capital by opening or financing (in the case of the U.S.) international exchanges.  So, in our theoretical framework there is always a need for a rule of law and the right to property, what we call the legal infrastructure.

However, this must always be accompanied by capital formation.

If historical experience is teaching us anything, it is that capital formation is best done through international trade, trade liberalization and international exchanges.  Eventually, trade liberalization becomes the venue or vessel of empowering people to experience upward economic mobility.  It is like having many people at a port on the coast and some of them board a vessel, the vessel empowers them to get better acquainted with technologies, to have better access to capital and other resources, exposes them to ideas, to better education, because it takes them away from the port, to new places.  The distance between those who are left behind at the port and those who are now sailing away from the port may be rising initially, but the ones who are on the vessel are the ones who are experiencing the phenomenon of being part of the middle class.  In another analogy, we can think of a moving escalator, the international trade becomes the escalator of moving people up, being part of better educational opportunities (social infrastructure), better health care provisions (again, social infrastructure), being able to move around and experience upward mobility, get better jobs, save and invest i.e. take advantage of physical and financial infrastructures. The country as a whole in that case, is able to export and import, to experience growth through investments and FDIs, capital importation, better technologies and production techniques.

The country through export-led growth experiences physical and social infrastructure investments, which eventually empowers the people and the middle class to enjoy savings. Those savings will become the seed for a financial infrastructure, both local and foreign-owned. The emergence of the this kind of infrastructure will finance the formation of new vessels, which in turn will bring the people from the port/coast to the ocean, thus sustaining the creation of the middle class.

So while we may be taking a leap forward without enough evidence at this point, I think it would be normal to expect that globalization, as it is evolving may be showing some measures of higher inequality. However, if properly realized that is simply a means to create and sustain a middle class via capital formation, then over time liberalization and higher international trade will lead to the creation of the middle class, leading eventually to lower rates of inequality and poverty.

If convergence is indeed achieved, then justice has been implemented, because justice relates to others and becomes reality when equals are treated equally.

LOCKHEED TRI-STAR REDUX: A PLAY TO WIN STRATEGY

GEORGE_SPARTAN0001George A. Haloulakos, CFA DBA Spartan Research and Consulting, Core Adjunct Finance Faculty – National University and Instructor-Finance, University of California at San Diego (UCSD) Extention

  

tri-star

ABSTRACT

The Lockheed L1011 Tri-Star, a tri-jet wide body aircraft introduced in the early 1970s, was regarded as a technical marvel whose commercial success was severely limited by financial and developmental problems with Rolls Royce, the sole developer of the Tri-Star’s engines.  Despite being a quiet, efficient, easy to handle wide-body aircraft with a stellar safety record (of the five fatal accidents involving L1011s, only one was due to a problem with the aircraft) the Tri-Star program was unable to overcome its late entry into the commercial market, and Lockheed announced in 1981production would end with the 250th and last L1011 on order in 1984.  Since then, the Lockheed Tri-Star has become a classic business school case study in finance.   The typical solution offered usually involves a variation of shutting down the commercial aircraft program and refocusing on Lockheed’s military aircraft and avionics businesses, or a “work-out” in which the firm struggles to drive commercial sales to the elusive break-even mark.  In this paper, it is shown that a positive Net Present Value for the Tri-Star was, in fact, achievable but requires one to depart from the oft-linear and sometimes limited vision from the standard MBA playbook.  The solution offered here requires a change in corporate strategy (utilizing a proven business model serving not one, but two end-user markets) and leveraging Lockheed’s significant competitive advantage in high-performance military aircraft.

FINANCIAL DECISION MAKING & THE CASE STUDY METHOD

Financial decision making requires one to make recommendations including, but not limited to capital budgeting, competitive strategy, marketing and other such areas with the goal of optimizing Net Present Value.  The case study method forces a person to define-and-solve the problem within the historic time frame in which the case takes place by utilizing given background information as well as supplemental data gathered from independent research.  Time pressure means that one does not have the luxury of dotting each “i” or crossing each “t” but to provide a defensible solution in accordance with the situation.  Playing it safe via risk-averse solutions (that are often self-evident from a strict, linear-based accounting prism) usually means staying within the realm of consensus views, while playing to win means having to take greater risk, but if done with a creative, non-linear approach can sometimes lead to more satisfactory outcomes.  As such, the goal with financial decision making using the case study method is offering a solution that provides the highest probability of success.  This paper presents a play-to-win strategy that incorporates a behaviorist view of finance aimed at achieving a financial outcome above consensus expectations

BACKGROUND INFORMATION

A synopsis of the facts of the case is as follows: The L1011 Tri-Star is a wide-body commercial aircraft with a capacity of up to 400 passengers.  Lockheed was late to enter the market due to jet engine production delays by Rolls Royce (sole supplier for the Tri-Star). In the early 1970s, Lockheed sought a $260 million federal loan guarantee to secure bank credit to complete its L1011 Tri-Star aircraft.  Preproduction costs were $960 million during 1967-71.  The production phase beginning in 1972 would be in the range of 210 – 300 aircraft, and extend as far as 1980.  The project was regarded as inventory intensive and front loaded; 35 planes per year was the planned annual output.   Unit production costs were given at $14 million for the low end of the output range and $12.5 million for the 270-300 unit output range.  Unit production costs above the 300 unit threshold were $11 million due to the learning curve effect.  To achieve unit sales of 270-300 aircraft assumed an optimistic 10% annual growth in commercial air travel.  Cash receipts from the sale of aircraft were based on: (1) advance deposit of 25% of total price received two years prior to delivery, and (2) the balance due of 75% received when aircraft was delivered.  This implies that for 35 aircraft built (and presumably sold at an average selling price of $16 million) in a year, $140 million of the $560 million in total annual revenue is received as cash flow two years earlier.

The required rate of return on Lockheed assets (prior to Tri-Star) was estimated to be 9%-10%, with 10% cited as the initial rate used by the company for valuing the project.  The main focus in evaluating the economic value of Tri-Star was primarily based on its commercial prospects.  Divergent views on commercial market potential ranging from 270-300 units as approaching break-even (versus an original plan of 210 aircraft) to theoretical sales potential of 500 aircraft, as well as differences in accounting versus economic results puts forth the question on whether or not to proceed with the program.  This situation is exacerbated by direct competition from the Airbus 300B and McDonnell Douglas DC-10 tri-jet, and indirect competition from the Boeing 747.

OBSERVATIONS

Betting the Company on a Single Project is an Industry Norm

Since the inauguration of the commercial jet age with the Boeing 707 in the mid-to-late 1950s, the behavioral norm among industry players is essentially to “bet the company” in launching a new generation of aircraft.  Part of this behavior arises from the enormous investment of financial capital and time (often a decade or more) inherently required for designing, developing and launching a new aircraft.  The propensity to undertake such risk is underscored by the prestige and brand equity associated with a successful jet aircraft program that can often create financial synergy for other related businesses that in turn, can generate very large, extended cash flows.  The notion of withdrawing from a new jet aircraft program carrying so much prestige and large financial stakes (even when caution is warranted) may be an acceptable alternative in the MBA playbook, but in the boardrooms where “betting it all” behavior is the norm, such a strategy is regarded as playing not to lose rather than playing to win.  As such, a strategy in this business environment aimed at resolving financial difficulty that will actually be implemented requires daring and a willingness to take risk.  Sir Isaac Newton, mathematician, once said that “No great discovery was ever made without a bold guess.”  This saying fits the jet aircraft industry where leading firms achieve technical and financial success with bold risk-taking behavior that seeks to go beyond linear-based consensus thinking.

Leveraging Cost Over Two Rather One End-User Markets = Better Return/Risk

Using the Boeing 707 program as the appropriate business model shows that financial success in commercial jet aircraft stems from having a military aircraft business that allows for risk sharing and diversification.  Specifically, Boeing’s success in commercial jet aircraft stemmed from its military aircraft business in terms of risk sharing (e.g., 707 and its military KC-135 version) and diversification.  The strong position in defense-related projects (e.g., Minuteman and Cruise missiles) provided stable, steady cash flow for the entire corporation thereby providing an additional financial cushion to undertake development of new generations of jet aircraft.  Boeing received orders for 400 KC-135 jet aircraft tankers in March 1955 from the US Air Force, and completed production-and-delivery of ½ of that order (or 200 aircraft) two years later that enabled the 707 to reach break-even in late 1956.  Commercial aircraft orders did not translate into large scale unit shipment until 1959-60 with 77 and 91 707s delivered to US and overseas airlines during that period.  Significant financial payback for the commercial 707 version did not really occur until 1967-68 when Boeing achieved triple digit unit deliveries, respectively, of 118 and 111, that enabled the company to post record corporate net income over the same period.  The triple-digit threshold for the 707 commercial deliveries, had proven elusive until that point, and was never achieved thereafter for the 707 model, thereby affirming the importance of its military version (which did achieve triple digit annual unit deliveries very early in the program life cycle).

Lockheed is the Premier High-Tech Military Aircraft Company

By the end of the 1960s, Lockheed established itself as the leading high-tech military aircraft manufacturer with a significant competitive advantage in speed, performance, efficiency, safety and ease of handling.  Lockheed’s product portfolio included interceptors (T33 Shooting Star and F104 Starfighter), transport aircraft (C141 Starlifter) and special reconnaissance (U2 Spy Plane and YF12 or SR71 Blackbird).  All of these aircraft featured a very sleek or streamlined look, plus utilized special materials that facilitated the aforementioned advantages.  This characteristic carried over into the Tri-Star: the L1011’s tri-jet configuration featured one jet under each wing, and the third, center mounted with an S-shaped duct air inlet embedded in the tail and upper fuselage.  With the Cold War still at its peak in the early 1970s, Lockheed’s expertise in this field was a most valuable national security asset.  The company’s competitive advantage in all the facets of this area resulted from a bold and visionary strategy implemented by its famed Skunk Works operation that handled top-secret classified projects.

Runner-up for the Super Sonic Transport (SST) Was a Game Changer

During the 1960s Lockheed’s L2000 was the company’s entry in the government funded competition to build the first supersonic transport for the United States of America.  On December 31, 1966 the contract was awarded to Boeing.  Federal funding was cancelled in 1971, forcing Boeing to take a loss on the project.  In the interim, Lockheed staked its commercial aircraft fortunes on the L1011 Tri-Star, eventually investing $960 in pre-production costs for this wide-body jet aircraft from 1967-1971.  Finishing as runner-up to Boeing was a “game changer” as it forced Lockheed to narrow its focus to a single program (rather than two) to gain foothold in the commercial market.  Ultimately, the cancellation of Federal funding for the SST further changed the game because now Boeing was forced to narrow its focus, thereby intensifying the competition in the wide-body jet market, with Airbus and McDonnell Douglas as direct competitors, and Boeing as an indirect competitor to Lockheed’s Tri-Star.

Commercial Wide-body Aircraft Warrant Additional Risk Premiums

Wide-body jet aircraft carry additional risk premiums that warrant a required rate of return that is greater than the rate given for Lockheed assets (prior to Tri-Star).  On the business side, not only is the Tri-Star risk elevated due to reliance on a single supplier for its jet engines, but unlike Boeing and McDonnell Douglas who are already well established in the commercial jet aircraft market, Lockheed has no installed commercial customer base upon which to leverage Tri-Star sales efforts.  The increased liquidity risk due to high up-front working capital is due to the large scale of manufacturing required for all wide-body jet aircraft versus the narrow-body predecessors.  On the financial side, there is a litigation concern due to the explosive rapid decompression risk that is inherent to all wide-body jet aircraft.  For these reasons, any calculation of economic value for Tri-Star necessitates use of a required rate of return that is greater than the 10% initially given.  We estimate that a 13% required rate of return is warranted and provide a breakdown on how we arrive at this calculation.

CALCULATING REQUIRED RATE OF RETURN FOR L1011 TRI-STAR

Initial Required Rate of Return (Prior to Tri-Star)

All Lockheed Assets

0.10

+ Business Risk

No installed commercial base, only one jet engine supplier (Rolls Royce)

0.01

+ Financial Risk

Explosive rapid decompression for wide-body jets = litigation risk

0.01

+ Liquidity Risk

Inventory intensive (front-end) of manufacturing cycle

0.01

= Tri-Star Required Rate of Return

Lockheed Assets + Tri-Star Risk Factors

0.13

 

RECOMMENDATION

In the context of this case study, it is recommended Lockheed revise its L1011 Tri-Star strategy to focus on both the commercial and military end-user markets in order to leverage its significant competitive advantage in high-tech military aircraft with the goal of positioning the Tri-Star to replace the original 200 Boeing KC-135 jet refueling aircraft deployed in 1957.

RATIONALE

This change in strategy would produce a positive Net Present Value of $149.85 million for the Tri-Star arising from: (a) spreading cost over two end-user markets rather than one, (b) reduce unit production costs (learning curve benefit) due to higher volume and (c) lower risk due to increased cash flow from a diversified sales base.  As noted in the OBSERVATIONS section, the higher risk associated with this project necessitates using a proven business model better suited for such considerations.

The theme for this strategy is driving cash flow via a “replacement cycle” as the aforementioned 200 Boeing KC-135 tanker aircraft would be due for replacement by the mid 1970s on account of metal fatigue and need for improved efficiency.  It is self-evident that with the Cold War necessitating round-the-clock deployment of strategic bombers worldwide that the KC-135 aircraft would be in constant use and therefore have take-off/landing cycles that are 2.5 to 3 times greater than its commercial 707 model.  This coupled with the fact that those first 200 KC-135 aircraft utilized lower strength 7178 aluminum alloy instead of the fail-safe standard with 2024 alloy underscores if not exacerbates the concern about metal fatigue arising from the aforementioned inherently greater number of take-off/landing cycles.

Lockheed’s L1011 Tri-Star with its high performance, efficiency, safety, special materials with greater durability and longevity plus ease-of-handling make it an ideal candidate to enable the US Air Force to significantly upgrade as well as diversify its tanker fleet.  Moreover, the technology transfer of Lockheed’s high-tech military aircraft into Tri-Star would transform the wide-body tri-jet into a complementary support vehicle for refueling the various military aircraft (bombers, interceptors, and reconnaissance plus transport vehicles) deployed worldwide.  The need to replace the first 200 KC-135 tankers is immediate for reasons already noted, and Lockheed could fulfill the task in a two-year time frame as Boeing did in the late 1950s.  This would ease financial pressure by enabling Tri-Star to achieve positive Net Present Value on the strength of its military unit shipments and give Lockheed the flexibility to further expand its commercial presence.  In sum, this shift in strategy would allow Lockheed to leverage its competitive advantage in high-tech military aircraft, reduce risk, lower unit costs and significantly increase sales volume.

This strategy expands Lockheed’s opportunity set and thereby increases the probability of greater overall financial success with a bold, “play-to-win” approach that reflects the company’s risk-taking style.  While politics may come into play with military contracts and is often the great unknown factor, Lockheed’s premier position in high-tech military aircraft versus its peers gives it considerably greater leverage than either Boeing or McDonnell Douglas, and this recommended change in strategy puts Lockheed in the best position to succeed with its Tri-Star L1011.

FINANCIAL MODEL

In this section, we present three scenarios that examine the accounting (earnings) and economic (cash flow) perspectives of the Tri-Star project.  Scenarios 1 and 2 demonstrate that while the Tri-Star achieves positive accounting profits, the economic value is negative because of negative Net Present Value arising from unsatisfactory sales volume by focusing only on the commercial market.  Scenario 3, the recommended strategy, yields much higher sales volume due to serving both commercial and military markets (with a 60/40 mix) and thereby achieves positive accounting and economic outcomes.

 

Scenario 1 (300 unit shipments @ 10% required rate of return)

Scenario 01

 

 

Scenario 2 (300 unit shipments @ 13% required rate of return)

Scenario 02

 

 

Scenario 3 (500 unit shipments @ 13% required rate of return)

Scenario 03

APPENDIX

Estimated Impact on Lockheed’s Stock Price

The equation for valuing an investment into perpetuity is: V = C / (r – g).

V: Value

C: Cash flow

r: Required rate of return

g: Long-term growth rate

The “r” is given initially as 10% (for valuing Lockheed assets prior to Tri-Star) and later estimated to be 13% for the Tri-Star project itself.  The “g” for valuing investments into perpetuity will have upper limit of 3% based on “e” – the mathematical constant which is the base of the natural logarithm – “e” is the base amount of growth shared by all continually growing processes [and this includes business or economic entities]. The natural logarithm is the logarithm to the base “e” where “e” is an irrational constant approximately equal to 2.718281828459.  This number falls between 2 and 3, and so the use of 3 as an upper boundary for the growth rate when estimating Value into perpetuity.

Part a: Explaining the Decline in Stock Price Based on Given Case Information

It is given that Lockheed’s stock price declined from $71 (1967) to $3.25 (1974) due to financial difficulties associated with the Tri-Star and unrelated military contracts, but no information is provided regarding cash flow, so it can be inferred that “C” is the unknown variable.  Using the aforementioned data we calculate the following:

V = C / (r – g)

71 = C / (0.10 – 0.03)

71 = C / 0.07

C = 4.97

Thus it can be mathematically inferred that at its peak share price of $71, Lockheed’s cash flow per share “C” was $4.97.

V = C / (r – g)

3.25 = C / (0.115 – 0.03)

3.25 = C / 0.085

C = 0.28

Thus it can be mathematically inferred that at its low share of $3.25, Lockheed’s cash flow per share “C” was $0.28.  Note that in calculating “C” we used an “r” of 11.5%, which is halfway between 10% and 13%.  Our reasoning is that Tri-Star became a more influential factor on Lockheed’s total required rate of return, but not sufficient to increase the total corporate “r” to the 13% Tri-Star level.

The conclusion from this exercise is a demonstration of stock price as the market’s estimated present value of cash flow.  In the case of Lockheed, the 95% decline in market value from 1967 – 74 tracks the equal percentage decline in cash flow and also reflects an upward revised required rate of return to incorporate higher risk premiums arising from the Tri-Star capital project.

Part b: Where Does the Stock Price Go From Its Low?

Here the problem can become a bit difficult as the case references both Tri-Star and military contracts as contributors to Lockheed’s financial difficulties, but there is no further information disclosing relative significance of each.  Since the case study itself concerns Tri-Star, our focus will be on estimating how improving the financial returns of the L1011 Tri-Star may translate into potential (and in this instance incremental) stock price appreciation with the caveat that the company stabilizes its other portfolio business groups.  Since stock price performance reflects the firm’s record in either adding or subtracting from intrinsic value based on execution of its capital projects, we may infer that a capital project yielding a positive Net Present Value (NPV) adds to stock price while a negative NPV reduces stock price.

The Scenario 3 Financial Model quantifies our recommendation that a dual commercial and military business model for Tri-Star yields a positive NPV of $149.85 million or $13.26 per share [based on 11.3 million shares outstanding given in the case study].  A simple, but reasonable inference is to impute the $13.26 per share NPV directly into the Lockheed stock price, and this yields a target stock price of $16.51 (or a 5-fold stock price improvement from its low).  The stock price equation quantifying the benefit for finding a way to retain and convert Tri-Star into a financial winner:

Target Price = Low + NPV per share

Target Price = 3.25 + 13.26

Target Price = 16.51

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