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Do Business Groups Change with Market

Development?

Borja Larrain‡ and Francisco Urzúa I.§

Abstract

Khanna and Yafeh (2007) hypothesize that business groups should be more common in economies

with less developed markets and institutions. We test the time-series version of this hypothesis by

looking at changes in Chilean groups over 20 years (1990-2009). In this period, Chile experienced a

deep economic transformation as measured by common proxies of market development (e.g., per

capita income doubled). Despite this dramatic transformation, groups remained mostly unchanged in

terms of relative size, industrial diversification, vertical integration, control structures, internal capital

markets, and reliance on external funds (minority equity plus debt). Only leverage increased. Also,

group’s initial conditions were uncorrelated with market development at the time of formation. This

evidence casts doubts on the institutional-voids hypothesis, although more subtle institutional voids,

not captured by the type of macro proxies we use, might explain the existence and resilience of

business groups.

∗We would like to thank Steven Ongena and participants of the First Latin American Workshop in Law and Economics (2014) for comments and suggestions. Carla Castillo provided excellent research assistance. Larrain acknowledges partial financial support provided by Programa Fondecyt (Proyecto Fondecyt Regular #1141161).

‡ Pontificia Universidad Católica de Chile, Escuela de Administración and Finance UC, Avenida Vicuña Mackenna 4860, Macul, Santiago, Chile. Tel: (56 2) 2354-4025, e-mail: borja.larrain@uc.cl

§ Rotterdam School of Management, Erasmus University, the Netherlands. urzuainfante@rsm.nl

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Do Business Groups Change with Market

Development?

Abstract

Khanna and Yafeh (2007) hypothesize that business groups should be more common in economies

with less developed markets and institutions. We test the time-series version of this hypothesis by

looking at changes in Chilean groups over 20 years (1990-2009). In this period, Chile experienced a

deep economic transformation as measured by common proxies of market development (e.g., per

capita income doubled). Despite this dramatic transformation, groups remained mostly unchanged in

terms of relative size, industrial diversification, vertical integration, control structures, internal capital

markets, and reliance on external funds (minority equity plus debt). Only leverage increased. Also,

group’s initial conditions were uncorrelated with market development at the time of formation. This

evidence casts doubts on the institutional-voids hypothesis, although more subtle institutional voids,

not captured by the type of macro proxies we use, might explain the existence and resilience of

business groups.

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Business groups are prevalent in emerging markets (e.g., Brazil, India, China, South Korea)

and developed markets (e.g., Italy, Sweden). Yet, despite their extended presence, we know little

about why they form and how they evolve. Khanna and Yafeh (2007) put forward several hypotheses

in this respect. One hypothesis is that business groups should be more common in economies with less

developed markets and institutions. Basically, business groups act as substitutes for capital, goods, or

labor markets when frictions are severe. A first approach to test this idea is to make cross-country

comparisons on the prevalence of business groups as a function of variables that proxy for market

development. A second approach is to use within-country, time-series data to see whether business

groups correlate with market dynamics. The time series approach has the advantage of controlling for

country unobservables that blur cross-country comparisons.

In this paper we contribute to the literature on business groups precisely by performing a

country-study in the style of the second approach described above. We use a relatively long time

series (20 years) of Chilean groups and test to what extent the structure of these groups correlates with

proxies of the development of markets and institutions. A crucial ingredient to our experiment is that

Chile’s economy experienced a deep transformation during this period (1990-2009): per capita GDP

doubled, the stock market tripled in size, international trade kept expanding after liberalization, and so

on. This transformation was the result of macroeconomic reforms (e.g., trade and financial

liberalization, pension reform, independent central bank and subdued inflation, among others) pushed

by the government in the 1970s and 1980s rather than by the business groups themselves. These

reforms, together with a peaceful transition back to democracy in 1990, made Chile one of the success

stories in Latin America, and hence a useful laboratory to test whether business groups lose

prevalence once markets develop. 1 In this way we are following Khanna and Yafeh (2007)’s

recommendation: “Many more historical studies with explicit hypotheses […] whose testable

implications can be contrasted in time-series data, could shed further light on the evolution of groups,

                                                            1 Data availability makes Chilean business groups a frequent focus of study in relation to their performance (Khanna and

Palepu, 2000), their organization and structure (Khanna and Palepu, 1999; and Lefort and Walker, 2000), interlocking and stock returns (Khanna and Thomas, 2009), internal capital markets (Buchuk, Larrain, Muñoz, and Urzúa, 2014), and board compensation (Urzúa, 2009). 

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on path dependence (ways in which “history matters”), and on the raison d’être of group formation

and development.” (p. 364).

By focusing on a particular country, instead of using a cross-country sample, we lose some

potentially interesting dimensions. However, identification (absent good instruments) is harder with

purely cross-sectional data. In our case, identification is driven by the massive size of the shock –the

reforms and subsequent economic development– that affected business groups in this period and

which allows us to perform a quasi-natural experiment. Several papers look at the historical evolution

of business groups in a country or perform a case study of the evolution of a particular group (see, for

instance, the recent country studies of Cuervo-Cazurra, 2014 (Spain); Ferreira da Silva and Neves,

2014 (Portugal); Larsson and Petersson, 2014 (Sweden); or the co-evolution of Indonesia and the

Salim group in Dieleman and Sachs, 2008). In the case of Chilean groups, Khanna and Palepu (1999)

study the evolution of business groups in 1987-1997 with field data based on interviews. Khanna and

Palepu (2000) study the benefits of group affiliation in Chile with a 9-year sample, and conclude that

the evolution of the institutional environment affects the benefits of group affiliation, albeit slowly.

Our approach complements and improves upon these previous papers in several respects.

First, we assemble a long time-series (20 years) of quantitative measures of group characteristics for

30 different groups. This panel structure, which is quite unique in the business group literature, allows

us to perform statistical analysis that is hard to do with purely historical or qualitative data. Second,

we cover a wide range of group characteristics such as size, industrial structure (diversification and

vertical integration), control structures (pyramidal characteristics), and financial structure (leverage,

external funding, internal capital markets), which gives a general characterization of business groups

instead of focusing on one particular dimension (e.g., industrial diversification as in Ferreira da Silva

and Neves, 2014). Our characterization of internal capital markets is particularly novel since data on

intra-group lending is extremely hard to get in other countries. Finally, we explicitly test the

institutional-voids hypothesis by looking at the relationship between Chile’s impressive development

path and group characteristics. More precisely, we compute the sensitivity of groups’ characteristics

to different proxies for market development such as per capita GDP, trade openness, bank credit,

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stock market capitalization, and regulatory improvements. For instance, given that financial markets

became deeper and more sophisticated throughout this period, the internal capital markets of groups

should become less active since, in theory, their purpose is to provide risk-sharing agreements that are

absent from formal markets (Khanna and Yafeh, 2005; Belenzon, Berkovitz, and Rios, 2013).

Our results show that, despite the changes that Chile experienced in these two decades, the

structure of groups remains very similar to what it was in 1990 or when they start. Although there are

some changes, most changes in group characteristics do not appear to be systematic (i.e., correlated

with market dynamics). The sole exception to the stability of group structure is leverage, which

increases significantly from an average of 30% in 1990 to 44% in 2009. This overall increase in

leverage is explained by old groups increasing leverage, and not simply by new groups being formed

with higher leverage. Business groups take advantage of the expansion of domestic credit by funding

more of their operations with debt, in a way that is perhaps analogous to the private equity industry in

developed countries, (see Axelson, Jenkinson, Stromberg, and Weisbach, 2013).

Initial conditions (i.e., group characteristics at the beginning of the sample period or when

groups start) explain the lion’s share of variation in group structure throughout the sample. Simply

put, the structure of groups is more closely related to the starting point of each group rather than to

subsequent market dynamics. Initial conditions themselves could be a function of market development

and institutional voids when each group is formed. In fact, looking at initial conditions is a stronger

test of the institutional voids hypothesis, because they are free from the interference of adjustment

costs. In particular, the absence of major changes that we mention above could simply be the result of

adjustment costs once groups are set up. However, in the data we do not find a clear association

between initial conditions and proxies of market development either. In other words, groups’ initial

structure does not seem to be designed to tackle different levels of market development or institutional

voids. Again, the sole exception is group leverage: new groups start off with much higher leverage

than the leverage that old groups had when they started.

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Our paper contributes, first and foremost, to the literature on business groups’ formation and

evolution. One strand of the existing theoretical literature is based on the idea that groups compensate

for underdeveloped markets and institutional voids (see, for instance, Almeida and Wolfenzon, 2006;

Kali, 2003; Khanna and Yafeh 2007). Our results show that the substitutability between groups and

markets is non-existent in the medium run, and even perhaps in the long run. Another view of our

results is that they help to quantify what “long run” means for business groups. In simple words,

twenty years does not seem to be enough to trigger a significant change in business groups. This is

despite the transformation of an economy that doubles in per capita income or triples in stock market

capitalization during the same period. This resilience of business groups is not unheard of, as shown

by empirical evidence (e.g., the survival of British trading companies through the market development

of the nineteenth and twentieth century; see Jones and Colpan, 2010) and recent theoretical interest on

this matter (Colpan and Hikino, 2014). Perhaps the underlying relationship between business groups

and markets is non-linear. It could be the case that Chile in these 20 years did not cross the particular

development threshold that triggers a change in group structure. Although this is a plausible

alternative, our results suggest that these thresholds, if they exist, are far apart in the development

path. For example, a country like Chile that doubles per capita income does not seem to cross such a

threshold.

An important caveat regarding the interpretation of our results is that we empirically examine

the correlation between group structures and mere proxies for market development. These outcome

variables, such as per capita GDP, stock market capitalization, or trade liberalization, are only

symptoms of development, but market structure is a much more complex and multidimensional

object. Khanna, Palepu, and Bullock (2010) argue that, in fact, characterizing market development

according to these outcome criteria can be very misleading for understanding the true institutional

voids present in an economy. They argue that development relates to the ease with which buyers and

sellers can come together. In this respect, the presence of market research firms, credit card

companies, head hunters, and other intermediaries can be much more revealing of institutional voids.

Measuring the myriad of voids that characterize markets is something that we do not claim nor

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attempt to do in this paper. However, our results can still tell us that market development, as

commonly measured in many studies, is not trivially correlated with the structure of business groups,

and perhaps that one has to think harder about the precise institutional voids that business groups

compensate for in an economy.

An alternative to the institutional-void hypothesis is that business groups survive by being

parasites of the political system, e.g., receiving industrial protection, bailouts, subsidies, takeover

protection, etc. The Chilean experience speaks against this hypothesis as well. Several facts make us

believe that groups were neither able to hinder institutional development, nor they enjoyed

preferential regulation that could reinforce the status-quo. First and foremost, all governments that

span the sample period 1990-2009 were active political opponents of General Pinochet (1973-1989),

whose privatization process led to the creation of many of Chile’s business groups. The privatization

process itself, and hence implicitly business groups, were heavily criticized (although privatization

was not reversed). Second, corporate misbehavior was actually punished as can be seen in several

emblematic fines imposed to controlling shareholders during this period. Finally, Chile deepened its

commercial openness and significantly reduced most barriers for foreign entry and trade. In fact,

several foreign investors acquired important participation in Chilean firms throughout this period.

Several authors (e.g., Rajan and Zingales, 2003) argue that international openness undermines the

ability of incumbents, such as business groups, to keep their rents. Hence, groups do not appear to

have restricted institutional development in Chile, nor institutional development appears to be

endogenous to the main interests of business groups.

Overall, we are left with little explanation for the resilience of business groups in an emerging

market such as Chile. Our results suggests that more research regarding the reasons behind group

formation is crucial for understanding the future, since group structure moves slowly or does not

change at all over long periods of time and amid strong market growth. This does not imply that

groups are necessarily static or inefficient organizations; in fact, Chilean groups grew strongly during

this period, keeping up with the pace of the economy. We simply find that they adapt to market

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development without modifying their basic structure in a systematic way. How this proccess of

adaptation within a stable structure comes into place is also an interesting area of future research.

The rest of the paper is organized as follows. Section 1 summarizes the relationship between

markets and business groups as seen in the literature. Section 2 presents a brief history of Chile’s

economic development and business groups since 1970. Section 3 explains the data sources and the

group variables that we assemble. Section 4 presents our main empirical results. Section 5 provides a

final discussion of the hypotheses about business group formation and their connection to our

findings. Section 6 concludes.

1. How do Groups Relate to Market Development in Theory?

Khanna and Yafeh (2007) summarize the prevailing views about business groups as follows:

business groups are either paragons or parasites. Although these represent two extremes –reality is, of

course, more nuanced-, they provide a framework for organizing the discussion.

Business groups are sometimes viewed as paragons because they can substitute for capital,

goods, and labor markets when frictions are severe. Business groups alleviate informational

asymmetries, moral hazard, or problems with contractual enforcement that reduce the effectiveness of

markets in allocating resources. Although they are viewed as second best arrangements, business

groups can survive in countries that often lack basic markets. As frictions are tackled by public and

private institutions (e.g., introduction of regulating agencies, adoption of disclosure and accounting

standards, etc.), and consequently as formal markets develop, the prediction of the paragons-view is

that business groups should retreat. In principle, business groups lose part of their comparative

advantage as markets develop and institutional voids disappear.

The effects on group structure are straightforward. Groups should become less diversified

across industries since the need for internal risk-sharing through diversification is reduced as capital

markets develop. Similarly, the internal capital markets of business groups should become less active

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as financing from banks, bondholders, and minority shareholders becomes available. Vertical

integration should also decrease as institutions develop, given that improvements in the contracting

environment allow the group to establish commercial relations with firms outside the group without

the risk of expropriation or hold up (Langlois, 2010). Increases in the protection of minority investors

–typically associated with well developed capital markets (La Porta, Lopez-de-Silanes, Shleifer, and

Vishny, 1998)– lead business groups to become less pyramidal or to decrease the divergence between

control rights and cash-flow rights (Claesens, Djankov, and Lang, 2000). International trade provides

incentives for specialization (Dornbusch, Fischer, and Samuelson, 1977), hence one can expect that

business groups should react by reducing industrial diversification. Also, vertical integration should

go down as international outsourcing becomes prevalent. Ultimately, business groups and markets are

substitutes under the paragons-view. Hence, rich families and entrepreneurs should be willing, or

forced by economic reality, to dismantle the complex business groups they had created in order to

take advantage of the emergence of markets.

In order to implement these predictions empirically one has to decide how to measure market

development. Sometimes the source of the improvement in market conditions can be clearly identified

in time (e.g., a change in law or regulation); although more often development is a continuous

process. In this case we have to settle for measuring outcomes rather than primitive variables. One

possibility is to use a catch-all proxy for market development such as per capita GDP, which is the

standard in the macro or development literature. Some predictions are more specific to the

development of financial markets, which suggests looking at, for example, the size of the banking

sector or the stock market. Trade openness has also received attention in the literature. Khanna,

Palepu, and Bullock (2010) argue that these catch-all proxies can overlook important institutional

voids that are crucial for defining the role of business groups. However, one can also argue that, if

goods and labor markets allocate resources in a more efficient way, this has to be reflected, sooner or

later, in per capita GDP or other catch-all proxies. Empirical feasibility is another reason for settling

for proxies such as per capita GDP or stock market capitalization. Some institutional voids are hard to

measure, and even more so in a consistent way over a long sample period.

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An alternative to the paragons-view is that business groups are parasites. This is perhaps an

even more common view as suggested by Morck, Yeung, and Wolfenzon (2005). Under this

hypothesis groups are plagued with severe agency problems. Families at the top of business groups

control many firms through pyramids without ultimately making a significant investment in them.

Agency problems become relevant because business groups control the lion’s share of capital in many

countries. Economic power is also translated into political power. For example, groups can receive

government support through beneficial regulation or protection from foreign takeovers (Dinc and

Erel, 2013). By misallocating capital, groups ultimately retard economic growth. In such a case, the

negative consequences of business groups can outweigh the market failures they help alleviate.

Under the parasites-view, rich families and entrepreneurs are likely to be suspicious of rapid

economic growth, and markets more broadly speaking. Of course, business groups, which act as

“expropriation devises”, benefit from growth by capturing the largest share of the cake. However,

unless they are able to capture all of the rents from the expansion of the economy, development will

most likely breed competition, and ultimately constitute a threat to their privileged position. As Rajan

and Zingales (2003) show, trade liberalization can be particularly harmful for business groups that

base their power and rents on the lack of competition. Similarly, the development of capital markets

can spur competition as credit constraints are lifted. Overall, the parasites-view of business groups

suggests that business groups retard market development because of their own inefficiency in the

allocation of resources, or because by suppressing competition they strengthen their incumbent

position.

2. Brief History of Chilean Business Groups since 1970

a. Business Groups between 1970 and 1989

The formation of many Chilean business groups can be traced back to two large privatization

waves that the country experienced in 1974-1978 and 1984-1987. The first wave came after the

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military coup of September 1973 that brought General Augusto Pinochet into power. The socialist

reforms of the previous government had implied the nationalization of Chile’s largest private

companies, which represented 85% of financial sector’s output, 70% of communications, and 100%

of utilities (Lüders, 1993; Larrain and Meller, 1991). Only a few private agents were able to make

bids in the privatization process because of the ongoing economic crisis (GDP fell by 13% in 1975).

As a consequence, the privatization process led to the concentration of ownership and the subsequent

formation of business groups (Meller, 1993). Foreign investors were not involved.

A second privatization wave took place in 1984-1987 after the crisis of 1982-1983, in which,

ironically, many large companies were re-nationalized. The new privatization round included firms

previously considered to be “strategic” in sectors such as energy, communications, steel production,

and airlines (Meller, 1993; Lüders, 1993). Some of the business groups that acquired firms in this

second privatization wave survive until today. For instance, the Angelini group bought Copec (a pulp

producer and an oil distribution conglomerate), which is nowadays Chile’s largest listed company.

The groups that still dominate the Chilean economy today were already in control of a majority of

their flagship companies by 1990 (see Table 1). All of the groups in Table 1 still exist in 2009, except

for Endesa which was absorbed by Enersis, another energy group.

b. Chile’s Development between 1990 and 2009

The two decades from 1990 to 2009 represent an extraordinary period of economic progress

for Chile. Per capita GDP almost doubled from 16% of U.S. per capita income to 30%. This is a

conservative measure of per capita income since it is adjusted for purchasing power parity. In nominal

(dollar) terms, per capita income in Chile quadrupled from $2,300 to $10,100. The average rate of

annual GDP growth was 5.4%. This growth is stronger than the one seen, for instance, in successful

Asian countries such as Korea, Malaysia, or Singapore in the same period. At the same time, the

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capitalization of the Chilean stock market, credit provided by commercial banks, and trade (exports

plus imports) grew steadily as can be seen in Figure 1.2

The underlying reasons for this impressive economic boom were the structural reforms

implemented by the market-oriented government of General Pinochet in the 1970s and 1980s (tax

reform, reduction in public spending, pension reform, liberalization of financial sector, tariff

reduction, etc.). These reforms were complemented by the political stability brought by a peaceful

transition to democracy in 1990. While most business groups in Chile certainly emerged as a result of

General Pinochet’s privatization policies, the governments that followed in the 1990s heavily

criticized privatizations, but did not reverse them. All governments that span the sample period in this

paper were active political opponents of General Pinochet, but in economic terms they kept the

market-based reforms basically intact.

In terms of financial regulation and corporate governance, Chile also became a relatively

advanced market in this period. Despite a legal tradition rooted in civil law, the protection to minority

investors in Chile is now similar to that of the average common law country (Djankov, La Porta,

Lopez-de-Silanes, and Shleifer, 2008). The regulation of tender offers changed significantly in 2001

as a result of the takeover of Enersis by Endesa España, a Spanish multinational, in 1997 (see Table

1). The problem arose when the controlling shareholders, a group of executives who led the

privatization of Enersis in the 80’s, tried to sell control without sharing the premium with the rest of

shareholders (workers, pension funds, etc.). The case became a political scandal, which ended up with

the former controlling shareholders paying a large fine (over US$ 50 million, something previously

unseen in the country). This and other improvements in corporate governance can be understood as

putting obstacles for “tunneling” in business groups (see also Urzua (2009), and Buchuk, Larrain,

Muñoz, and Urzúa, (2014) on tunneling in Chile).

Despite an impressive macroeconomic record, the country is still affected by more subtle

institutional voids. For example, trust and social capital are undermined by the division between the

                                                            2 The macroeconomic indicators for Chile are obtained from the World Bank and the Penn World Tables.

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pro- and anti-Pinochet factions that lives up to this day. Also contributing to this distrust is inequality

in income distribution, which remained stable during these two decades. The country has made much

progress in education, although still falls short of the educational achievement of developed countries.

This is particularly relevant for the high-end of the talent pool, which remains very small. The scarcity

of talent can be connected with a lack of technology developments and new entrepreneurial ventures.

Some of these institutional voids are hard to measure in a systematic way over long periods, while the

macro variables that we focus on in our empirical analysis are readily available. Still, they are

important to bear in mind for the interpretation of our results.

3. Data for Business Groups in Chile 1990-2009

a. Data Sources

We use a hand assembled dataset that covers non-financial firms listed in the Chilean stock

market between 1990 and 2009. All financial statements are taken from Economatica. We define a

business group as a set of two or more listed firms that have a common controlling shareholder. Since

the debt crisis of the early 1980s the Superintendencia de Valores y Seguros (SVS, the Chilean

equivalent to the U.S. SEC) reports a list of the companies that have the same ultimate controlling

shareholder. Our definition is stricter than the one in Khanna and Rivkin (2006) and Lefort (2010),

who include groups with only one listed firm (and thus equivalent to conglomerates in developed

markets). Many of the conflicts between controlling shareholders and minority shareholders that arise

in business groups only exist when there are two or more listed companies (see Morck, 2010). Our

definition of group boundaries is based on equity ties between firms, while others define groups based

on family ties. Family ties are sometimes better predictors of common behavior. However, at least in

the Chilean market, Khanna and Rivkin (2006) conclude that overlap in ultimate owners and equity

ties are better delineators of group boundaries.

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Details on the ownership structure are obtained from annual reports, some of them available

in electronic form at the SVS, from Fecus Plus, and Economatica. Listed companies are required by

law to disclose their 12 largest shareholders in their annual reports. Yet these are almost always other

companies -some of them listed, some private- so this information is in itself of little help in

identifying the stake of the ultimate controlling shareholder of a company. We check annual reports

by hand in order to understand the web of companies connected through pyramidal control structures

and other control mechanisms such as dual-class shares. With this information we compute the

fraction of shares held by the controlling shareholder for each firm between 1990 and 2009. For more

details on the ownership structure of Chilean firms see Donelli, Larrain, and Urzúa (2013). In the rest

of the paper we are particularly interested in two types of controlling shareholders –families and

foreigners (non-Chilean investors)–, who might have different objective functions and management

styles.

In order to illustrate our data we present in Figure 2 the structure of two large Chilean groups

in 2008. This figure includes listed firms and several private firms that are fully-owned subsidiaries of

the listed firms or related to them through ownership links. The Luksic group includes 8 listed firms

in 4 different industries, while the Claro group includes 7 listed firms in 4 different industries. As seen

in Table 1, during the Pinochet years (1973-1989) both the Luksic and the Claro groups acquired

many of the firms they still hold in 2008.

In Table 2 we summarize the industrial affiliation of group firms, also splitting the sample

according to the type of controlling shareholder.3 Most group firms are holding companies (42%), in

manufacturing (31%), and to a lesser extent in mining, utilities and construction (18%). Firms like

Quinenco (Luksic), Quemchi (Claro), Indiver (Marin), Almendral (Hurtado Vicuna), and Sigdo

Koppers (Sigdo Koppers) are examples of holding companies at the apex of Chilean groups. Given

Chile’s role in the worldwide copper market, it is perhaps surprising that mining plays only a

secondary role in the Chilean stock market. Foreign-controlled groups are more common in the

                                                            3 Groups that are neither controlled by a family nor foreigners are controlled by partnerships of rich individuals and/or families not related by blood (e.g., Sigdo Koppers in Table 1) 

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utilities sector, consistent with the acquisitions made by Spanish multinationals like Endesa or

Telefonica during the 90’s. We do not see a significant difference in the industrial affiliation of group

and non-group firms in Chile.

Three caveats with respect to our data are worth noting, although we do not see a reason why

they could affect the time-series or cross-sectional (i.e., cross-group) comparisons in a systematic

way. First, due to data availability we focus on non-financial firms therefore excluding banks, private

pension funds, mutual fund companies, and other financial firms. As noted by Larrain (1989) and

Khanna and Yafeh (2007), Chile’s business groups were heavily involved in the financial sector

before the crisis of the early 1980s. After the crisis some groups retained the control of banks, but it

was far from a common practice. For example, the Matte family controls Banco Bice, a relatively

small bank, whereas the Luksic family has been on an off the banking sector. One of the

consequences of the 1980s crisis was to restrict and regulate bank lending to related companies, which

implies that groups cannot obtain unfairly cheap financing from their banks.

A second caveat is that our data only covers Chilean companies, thus ignoring firms listed in

other markets that do not consolidate with the local firms. For instance, the Luksic family controls a

mining company (Minera Los Pelambres) through a firm that is listed in the London Stock Exchange

(Antofagasta Minerals). Cases like this are unlikely to have a material impact on our results since they

are very few. As seen in Table 1, many groups started international expansions in this period,

although most of these ventures are consolidated into the financial statements of the Chilean firms,

and therefore are included in our data.

Finally, and most importantly, because of data limitations we do not consider private firms

that are not consolidated into the financial statements of the listed firms. We do not consider this as a

big concern for several reasons. First, private firms are small. Most large Chilean firms are listed in

the stock market because of the several privatization waves previously described. This makes the

Chilean corporate structure different from, say, continental Europe where many large firms remain

private (Franks et al., 2012). Second, private firms typically consolidate with the listed firms. For

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instance, most of the private firms shown in Figure 2 for groups Luksic and Claro consolidate with the

listed firms. The Chilean rule for consolidation during our sample period is to have an ownership

stake of 50% plus one vote. The financial statement of the parent firm still includes equity stakes

below 50% on the asset side of its balance sheet, although it does not fully consolidate with the related

firm. Basically, we are only missing private firms that are directly linked to the family or ultimate

controlling shareholder without the involvement of a listed firm. Third, all transactions with business

groups’ private firms (i.e., related party transactions) are strictly regulated since the aftermath of the

banking crisis in 1982-83. These transactions have to be fully disclosed in firms’ financial statements,

and reported to the SVS. For example, if a listed firm sends cash to a private firm with the same

controlling shareholder (e.g., through an intra-group loan) the financial statement of the listed firm

will disclose this transaction.

b. Group Level Characteristics

We now explain the group characteristics that we study throughout the 1990-2009 period. We

use the Luksic and Claro groups (Figure 2) to illustrate the different variables.

Our first variable of interest is group size. We compute group size as the ratio of the group’s

assets over Chilean GDP. We take the consolidated book assets of the firm(s) at the top of the

pyramid, or equivalently the first line of the control pyramid. Therefore, the size of group g in year t is

defined as:

SizeAssetsGDP

1

∈

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Focusing on the consolidated financial statements of the firms at the top of the pyramid

prevents us from counting assets more than once. For instance, if we were to add up the assets of all

affiliated firms in the Luksic group we would be counting San Pedro’s assets three times since San

Pedro is owned through Quiñenco and CCU. In the case of the Luksic group, the total assets of

Quiñenco (the sole firm at the top of the pyramid, i.e., K=1 in equation 1) amount to approximately

USD 4.1 billion or 2.3% of GDP in the year 2008. The fact that we use consolidated assets also means

that group size is measured with assets controlled rather than strictly owned by the group’s controlling

shareholders. Naturally, a substantial fraction of group assets is financed by debtholders and minority

shareholders.

After size we focus on the industrial structure of the group. Diversification is measured as the

number of 4-digit industries in which a group operates.4 For example, the Luksic group participates in

4 industries: manufacturing (Madeco and Indalum), beverages and food (CCU and San Pedro),

telecommunications (Telefonica del Sur and Telefonica de Coyhaique), and holding companies

(Quiñenco and Peñon). The Claro group also operates in 4 industries: manufacturing (Cristales),

winery (Santa Rita), shipping (Vapores), and holding companies (Quemchi, Marinsa, Navarino, and

Elecmetal).

Vertical integration refers to how much of their input (output) group firms acquire (sell) from

(to) other firms in the group. A clear example of vertical integration can be seen in the Claro group in

Figure 2. Cristales (or Cristalerias Chile) is a glass container manufacturer that owns 54% of Santa

Rita, one of Chile’s largest winemakers. Besides wine, glass bottles are one of the main inputs of

winemaking.

The exact computation of the integration variable is as follows. Like Khanna and Yafeh

(2005), we first classify firms into industries using the industry classification from the 2002 input-

output matrix provided by the U.S. Bureau of Economic Analysis. Second, for each pair of firms

within the group we see whether their industries are upstream integrated (towards its suppliers) or

                                                            4 Khanna and Palepu (2000) measure diversification counting the number of industries at the 2-digit level. We use the same industry definition that later allows us to measure vertical integration.

17  

downstream integrated (towards its clients). For instance, for the CCU-Madeco pair in the Luksic

group we see from the input-output table that CCU’s industry (beverages) acquires 7.4% of its input

from Madeco’s industry (manufacturing), but sells close to nothing to Madeco’s industry. Similarly,

Madeco’s industry sells 6.2% of its output to CCU’s industry, but acquires close to nothing from

CCU’s industry. Third, we take the average of these two previous numbers, i.e., 7.4% and 6.2%, as

the measure of integration for this pair of firms. Fourth, in order to obtain a group-level measure of

integration we aggregate all pairs in the group (i.e. Quiñenco-CCU, CCU-San Pedro, Madeco-

Telefónica del Sur, and so on). We do this by computing an asset-weighted average of the vertical

integration of each pair, where the weight is the ratio between the sum of assets of the pair over the

sum of assets of all pairs in the group. Using an asset-weighted average allows us to see whether

groups integrate through time even though their industrial composition remains constant. This could

happen if related pairs benefit from internal trade and outgrow non-related pairs. More formally, the

vertical integration variable for group g with a total number of listed firm-pairs P (where each pair of

firm i and firm j is counted only once) in year t is as follows:

,2

2

∀

:

∑∀

∀

3

Overall, the vertical integration of the Luksic group in the year 2008 is 5.15%, which means

that on average 5.15% of the group’s inputs (output) can be acquired (sold) within the group. The

Claro group is more integrated, with an average of 8.28% for the year 2008. It is important to note

18  

that our definition of integration considers the existence of intra-industry trade, because it takes into

account pairs of firms within the same industry. The restriction in equation (3) above implies

that we exclude the idea of a firm trading with itself, but it does not exclude trading between two

firms in the same industry. For example, Madeco and Indalum in the Luksic group belong to the same

industry. The firms in this industry acquire more than 40% of their inputs from other firms in the

industry; hence the Madeco-Indalum pair has a high level of integration. One thing that our measure

does not take into account is the integration with non-listed firms since we do not have data on these

firms. Many of the private firms are fully-owned subsidiaries of listed firms (e.g., PVTEC is fully

owned by Indalum), so our measure is most likely a conservative lower bound of group integration.

On the other hand, and given our focus, it is arguably more interesting to see the integration between

listed firms, where minority shareholders participate, instead of exploring the organizational structure

within firms.

For the remaining group variables we use the generic formula:

∑ 4

Where is the variable of interest for firm i in year t, which is weighted according to the

assets of the firm that year in order to compute the group-level measure .

We first apply this formula to the ownership structure of the group. Our first measure of the

degree of horizontality of the control pyramid is what we call the “position” of each firm or the row of

the pyramid in which the firm is located. Simply put, we count how many layers there are in the

pyramid between the firm and the ultimate controlling shareholder. This is a simplified version of the

position variable in Almeida et al. (2011) since cross-shareholdings are not allowed in Chile. For

example, going back to the Claro group in Figure 2, Quemchi and Elecmetal would be in the first row,

19  

Navarino and Cristales in the second row, Marinsa and Santa Rita in the third row, and Vapores in the

fourth row.

For each group we calculate an asset-weighted position as follows from equation (4). A fully

horizontal group has an average position of 1. For example, in the year 2008 the Luksic group has an

average position of 1.53, which means that there are approximately one-and-a-half listed firms in the

control chain between the family and the average assets of the group. If we use an equal-weighted

average to calculate the Luksic group’s position, this number grows to 2.2, indicating that the group is

more pyramidal. Our asset weighted measure is smaller in this case because the large firms in the

Luksic group (Quiñenco, CCU and Madeco), which account for more than 90% of groups’ assets, are

all in the first and second rows of the pyramid. Firms in the third row represent little more than 5% of

group’s assets.5 In such a case an equal-weighted average overestimates the pyramidal structure of the

group. The asset-weighted scheme gives more weight to where the groups’ dollars are ultimately

controlled, so smaller branches of the pyramid become less relevant.

A second ownership variable is the wedge between voting and cash flow rights (Claessens,

Djankov, and Lang, 2000). Cash flow rights are computed by multiplying all of the ownership links in

the control pyramid. For example, the cash flow rights of the Luksic family over CCU are

approximately 25% (=82.11%x50%x61.67%), resulting in a 36% wedge (=61.67%-25%). Although

correlated with the position variable, we may find extended pyramids with relatively low wedges

(Almeida and Wolfenzon, 2006; Donelli, Larrain, and Urzua, 2013). The asset-weighted average

wedge for the Luksic group in 2008 is 6.1%, while for the Claro group it is 21%. These numbers are

comparable to firms in Italy or France as reported by Faccio and Lang (2002). They are significantly

lower than the average wedge of 40% in Korean firms (Almeida et al., 2011).

Finally, we study the capital structure of the group through three different measures. First,

leverage (book debt over book assets) considers the relative weight of debt in the capital structure of

the group. Considering the asset-weighted group leverage allows us to capture the group’s financial

                                                            5 Even if we consider non-consolidated assets for the weighting scheme there are no significant changes. Quiñenco, Madeco and CCU still account for more than 80% of group’s assets. At the same time, the smallest firms in the group do not increase their relative size by much, as they increase their weight from 5.3% to 6.9% of group’s assets.

20  

position in a more realistic way. The financial position of larger firms within the group matters more

than the position of relatively small ones, given that small firms can be easily bailed out whereas large

firms are harder to save (Gopalan, Nanda, and Seru, 2007). Second, we construct a variable that

captures the relative weight of all external funds in the capital structure of the group. We compute

external funds as debt plus the equity stake of minority shareholders, everything relative to book

assets. The minority stake is equal to 100% minus the fraction of shares held by the controlling

shareholder. In the case of the Luksic group in the year 2008, group leverage is 27% while external

funds represent 43% of assets. The Claro group is more levered (50%) and relies more on external

funds (62%) in the same year. By construction, external funds are always larger than leverage since

any listed firm has minority shareholders.

Our third capital structure variable is related to the internal capital markets of groups. This is

a key dimension of business groups, but often neglected because of the lack of good quality data. We

benefit from the unique disclosure requirements that affect Chilean firms, which are forced by law to

disclose in their financial statements all lending and borrowing activity with related parties (see

Buchuk et al., 2014, for more details). As an example of the type of transactions that involve internal

lending and borrowing, in the Luksic group we find that Madeco received in 2001 a loan of

approximately USD 7.9 million from Quiñenco which was due in 2010. Its annual interest rate was

inflation, plus TAB (Chile’s LIBOR equivalent), plus a spread of 1.75%.

For each firm we compute the ratio of intra-group lending plus borrowing over non-

consolidated assets. This information is only available in non-consolidated statements because it

disappears when consolidating (the transaction is both an asset and a liability at the consolidated level,

and thus it is not recorded). Adding lending and borrowing in principle implies double accounting

since any intra-group loan is an asset for a group firm and a liability for another group firm. However,

just looking at the lending side or the borrowing side might paint an incomplete picture of internal

capital markets. For example, it may be the case that listed firms are doing all the internal lending to

private firms in the group; hence if we were to look only at the liability side of the balance sheet

(internal borrowing) our measure would underestimate the extent of internal capital markets. The

21  

worst case scenario is that we are inflating internal capital markets by a factor of 2, which would

happen in the unlikely case that all of the internal lending and borrowing is among listed firms.

Although the ratio of intra-group lending and borrowing is taken with respect to non-consolidated

assets, the weighting scheme across group firms in equation (4) still uses consolidated assets as in the

previous variables. Overall, in the year 2008, the internal capital markets of the Luksic group

represent 21% of non-consolidated assets of the average firm, which is quite sizeable even if we

consider the potential for double accounting. Although we could expect that vertical integration and

internal capital markets go hand by hand, the internal capital markets of the Claro group only

represent 6% of assets that year, even though its integration measure was much higher than that of the

Luksic group.

c. Summary Statistics

In Table 3 we provide basic statistics about group characteristics. Our sample consists of 30

business groups. As a comparison, Almeida et al. (2011) cover 47 business groups in South Korea,

while Khanna and Palepu (1999) perform an in-depth study of nine business groups in Chile. Chilean

groups control on average 3.7 listed firms. Most of them are family controlled (62%), although

foreign-controlled groups are also a significant fraction of the sample (17%). The average group

controls assets that represent 2.72% of GDP, although there are some very large groups. For example,

Endesa, now a Spanish-controlled group focused on the generation and transmission of electricity

throughout Latin America, had assets that represented at some point 34% of GDP. These numbers are

not unusual in international comparisons. For example, Claessens, Djankov, and Lang (2000) report

that the top 15 families in Hong Kong control assets that represent 84% of GDP. Chilean business

groups are relatively horizontal with an average position of 1.44, and an average wedge between

control and cash-flow rights of 8%.

The average group firm acquires (sells) 5.79% of its input (output) within the group. This

level of vertical integration is very similar to the 6% reported for Chilean groups in Khanna and Yafeh

22  

(2007, Table 2). It is also comparable to the integration seen in other emerging markets such as

Argentina (6%), larger than that of Taiwan (2%), Korea (4%), and Indonesia (4%), but smaller than

that of Philippines (7%) and Mexico (8%) (Khanna and Yafeh, 2005, Table 10, or Khana and Yafeh,

2007, Table 2). The average Chilean group participates in 2.7 industries, which again is comparable to

international evidence.

The internal capital markets of Chilean groups represent on average 12% of their assets. This

data on intra-group loans is quite unique; hence we do not have a good international benchmark to

compare this level of activity. In terms of capital structure, average leverage is 38% and average

external funds represent 61% of assets. This implies that minority shareholders, on average, provide

financing for 23% (=61%-38%) of assets, and that their equity stake is 37% (=23%/(1–38%)). This is

in line with the high levels of equity concentration in Chile as reported by Donelli, Larrain, and Urzua

(2013).

4. Business Groups and Chile’s Development 1990-2009

a. Groups’ Characteristics and Market Development in Chile

In the descriptive analysis in Table 1 we see some changes in groups during this period. Firms

are acquired and divested, some groups are absorbed by others (e.g., Endesa), and there is entry to

new markets, in particular other Latin American countries. For example, the Matte group (mainly a

pulp producer) recently acquired one of the largest production units of Aracruz Celulose e Papel S.A.

in Brazil for almost USD 1.5 billion, in what was perhaps one of the largest foreign direct investments

in Chile’s history.

The question that we address in this section is whether there are systematic changes in group

structure in this period. Perhaps groups are very dynamic organizations in some dimensions, while

maintaining a stable structure. We are interested in changes that relate to this deeper structure of

groups, as characterized by the variables reviewed in the previous section and in the broader literature

23  

on groups. Also, we are not interested in any change, but in changes that are systematic in the sense of

being correlated with the market trends that Chile experienced in this 20-year period.

In Table 3 we look at the evolution of group characteristics between 1990 and 2009. There are

19 groups in 1990 and 23 in 2009, out of which only 15 exist during the whole period. Despite the

fact that new groups are formed, average characteristics remain fairly constant throughout the two

decades. As can be seen by comparing columns (a) and (b) almost none of the differences in averages

is statistically significant. Average listed firms per group increase only by 0.20. Families remain in

control of a majority of groups; even increasing marginally from 58% to 65%. Foreign groups

increase from 11% to 22%. Group size drops by 2.05% of GDP, which looks like a sizeable effect, yet

it is not significant. The dispersion in group size is quite high, so finding a significant effect on

average is hard. Average position increases marginally between 1990 and 2009, consistent with the

anecdotal evidence in Lefort (2010) that groups become less horizontal. However, the average wedge

in the sample decreases by 0.03, which implies that along this dimension groups become more, and

not less, horizontal. Vertical integration increases and diversification falls slightly, although none of

the effects is statistically significant. These results are similar to the ones in Khanna and Palepu

(1999) who find that between 1987 and 1997 large business groups in both Chile and India show no

evidence of a significant reduction in their scope of activities. Internal capital markets do not

experience a relevant change either. External funds remain close to 60%. Only leverage experiences a

significant increase of 14%.6 From the definition of external funds these last two findings imply that

groups simply substitute debtholders for minority shareholders as a source of funds.

In Figure 3 we plot the evolution of average group characteristics between 1990 and 2009.

We plot groups’ characteristics against Chile’s per capita GDP. The figure illustrates the patterns

already seen when comparing the beginning and the end of the sample. Average group characteristics

remain relatively stable throughout the 20 years, while there is an impressive increase in per capita

GDP. Perhaps the only pronounced dynamics are seen in internal capital markets, which were

                                                            6 The average leverage of non-group firms also increases, although less strongly, from 37% in 1990 to 43% in 2009. We cannot reject the hypothesis that the average leverage of group and non-group firms is the same at the end of our sample. 

24  

relatively active during the late 1990s, but then came back down to the levels seen in the beginning of

the sample. One possible explanation for this hump-shape in the activity of internal capital markets is

the Asian crisis that hit Chile in 1998-9. This crisis led many groups to increase internal lending in

order to support firms under financial stress.

The absence of significant change in sample averages can be due to two factors. First, the

obvious one is that groups do not really change much. Alternatively, stable averages can be the

product of sample composition. For instance, existing groups can change throughout the sample

period, but perhaps the addition of new groups with specific characteristics dampens the overall

trends. In order to uncover a potential compositional effect we report separately averages in 2009 for

“old groups” (i.e., those that exist at the beginning of the sample in 1990) and “new groups” (see

columns (c) and (d) of Table 3). Changes within old groups are, in general, comparable to changes in

the overall sample revealing that the lack of change is not an artifact of the addition of new groups. As

can be expected, the average size of old groups falls by less than the overall average (-1.47% vs. -

2.05%), because new groups are smaller. The increase in average leverage is seen within old groups

as well as in the overall sample. New groups are borne with relatively high leverage, as the difference

in leverage between these two types of groups in 2009 is not significant. Naturally, new groups

consist of fewer firms and, probably for the same reason, are less industrially diversified and more

vertically integrated. Foreign control is much more common among new groups because of the arrival

of multinationals as previously mentioned.

In Figure 4 we focus solely on the old groups that survive throughout the 20 year period.

Within this subset we split groups according to their initial level of a given characteristic (e.g., small

and large groups, diversified and focused groups, etc.). Again, this is interesting in order to explore

compositional effects in the overall averages. For example, it may be the case that business groups

that start diversified divest their non-core business while non-diversified groups increase their

diversification resulting in a stable average. However, this would be more of a statistical fiction than

evidence of group stability. Figure 4 allows us to see the dynamics of particular groups rather than a

generic average. We find that, with some exceptions, there is no discernible upward or downward

25  

trend over time in old groups. Most group characteristics, namely size, diversification, integration,

internal capital markets, and external funding are remarkably stable over time. Groups that start large

(small) continue to be large (small) after 20 years. The fact that we do not see a downward trend for

large groups means that they grow in order to keep up with the country’s GDP, so, again, size stability

does not imply that these are stagnant organizations. Groups that start diversified (focused) continue

to be diversified (focused) after 20 years; and so on. The exceptions are basically two. First, there is

an upward trend in leverage. In particular, old groups with low leverage increase their leverage

strongly throughout this period. Second, more horizontal groups increase their average position and

wedge. For instance, the Sigdo Koppers group, which started before 1990, became less horizontal

during this period by listing a holding company in 2005 that controls all of the previously listed firms

of the group. In this respect, the stability of average position and wedge for old groups is the product

of a compositional effect: some groups became more horizontal, and others less horizontal.

Table 4 focuses on group characteristics in 1990 and 2009 for the sample of old groups

previously reported in Table 1. This table reinforces the impression given by Figure 4 in the sense that

most group characteristics are either stable or not changing in a clear direction (some increase, others

decrease) throughout this period. For instance, while the Angelini group shows a strong reduction in

size, the Enersis group increases equally strongly. The Angelini group is an example of how non-

consolidating investments can bias downwards our estimation of size, since they haveve embarked on

several joint ventures with other partners.7 The Enersis group, on the other hand, grew significantly by

the acquisition of Endesa in the late 1990s. The only clear changes in Table 4 are, again, the

widespread increases in leverage and pyramidal position.

Beyond averages, we now take a more systematic approach to estimating group dynamics by

running OLS regressions of the following type:

. 5                                                             7 When consolidating, all of the assets of the firm that is controlled are incorporated into the financial statements of the controlling firm. In the case of joint ventures, only the equity stake is counted as an asset for the controlling firm.

26  

The dependent variable is the characteristic of each individual group g in each year t. The

initial characteristic is the characteristic measured in the first year for which we have data for the

group. The absence of strong dynamics in Figure 4 suggests that the initial characteristic –or the

structure of a group when it was born– is key for understading the structure of the same group in the

future. The initial characteristic is a constant in time for each group, hence we exclude it when we run

regressions with group fixed effects. Group fixed effects encompass any time-invariant feature of the

group (e.g., management style). The market variables are those in Figure 1. We also include a dummy

(“Law Dummy”) for the years after 2001, which marks the period after the regulation of tender offers.

If tunneling is the reason for business groups, we should see their decline after more stringent laws are

passed. The vector of coefficients contains the sensitivities of group characteristics to market

development, which is the main focus of the institutional-voids hypothesis. Standard errors in

equation (5) are robust and clustered by business group.

The results in Table 5 show that every single characteristic is strongly related to its initial

value, i.e., groups remain extremely similar throughout the period we study. The coefficient for initial

size is 0.55 (column 1 Panel A) and 0.97 for initial diversification (column 1 Panel B). The smallest

coefficient on any initial characteristic is 0.35 as seen in the regression with internal capital markets

(Panel B, column 3), but it is still a sizeable degree of persistence.

Given the stability of sample averages as noted in previous tables, it is not surprising that

market variables have little or no impact on group characteristics, except for a few cases. 8 In

particular, higher stock market capitalization is associated with smaller groups, although once we

control for group fixed effects the effect is only significant at the 10% level. Still, the -0.45 coefficient

in column 2 of Table 5 (panel A) implies that a 100% increase in market capitalization over GDP

conveys a 0.45 reduction in groups’ size, which is only an 17% (=0.45/2.72) decrease from the sample

average in Table 3. While the 100% increase in market capitalization might seem large, market

                                                            8 Introducing market variables one by one into the regression instead of all simultaneously has no material impact on the results and the overall message of Table 5. 

27  

capitalization went from 43% in 1990 to 127% of GDP in 2009. There is also a statistically robust

impact of trade openness on diversification. This is in line with models that predict a less diversified

productive structure as trade opens up (Dornbusch, Fischer, and Samuelson, 1977), and also with

anecdotal evidence from Brazilian groups (Aldrighi and Postali, 2010). A one standard deviation

increase in trade openness decreases diversification by 0.23 (0.23=2.48x0.09). Again, this effect is

relatively small, as it represents only an 8.4% (=0.23/2.7) reduction from the overall group average.

Trade also has a negative effect on internal capital markets, although domestic credit has a

simultaneous positive effect. The positive and significant effect of domestic credit on internal capital

markets is the most surprising, because it goes in the opposite direction as the institutional-voids

hypothesis. Finally, leverage is the sole variable that is clearly increasing with GDP per capita, which

is consistent with the previous evidence in Tables 3 and 4. The increase in GDP per capita in this

period can explain 11 percentage points (=0.15x0.75) out of the 14 percentage points of increase in

average leverage, or close to 80% of the increase.

The overall message of Table 5 is that the sensitivity of most group characteristics to market

variables is almost non-existent. Groups evolve in a very slow fashion even within a rapidly growing

economy. On the contrary, initial characteristics or simply group fixed effects have the largest

explanatory power for group characteristics. We also find (in unreported results) that these findings do

not vary according to family and non-family groups, or foreign and local groups. Hence, if we really

want to understand group structure, we need to look at the conditions at the time of formation rather

than the evolution of groups in response to market dynamics.

b. Groups’ Initial Conditions

What lies behind the initial structure of groups? We attempt to explain the drivers of initial

conditions in two ways. First, we study the change in initial conditions through time as new groups

are formed. The evidence in the previous section shows that groups stay close to their initial structure,

but this initial structure in itself might be a response to market conditions at the time of formation.

28  

This is potentially a cleaner test of the institutional-voids hypothesis, since groups at formation are not

concerned about adjustment costs like ongoing groups. For example, the lack of response to market

development that we saw in the previous section can be interpreted as evidence of high adjustment

costs (e.g., costs of acquiring or divesting firms, entering or exiting industries, raising funds from

financial markets, and so on), but not necessarily as evidence that the desired group structure is static.

In principle, when groups start they are choosing the structure that best fits their needs while taking

into account the particular institutional voids present. Second, we explore whether initial conditions

correlate with the identity of the controlling shareholder. Controlling shareholders may have

management styles that drive differences between groups for long periods of time (see, for the

example, the discussion on the Rothschild family in Bertrand and Schoar, 2006).

A couple of examples can help illustrate how new groups are formed in the period between

1990 and 2009. Some new groups are formed after a controlling shareholder lists a holding company

that owns all the shares of an already listed firm, creating a pyramid. For instance, Aguas Andinas is a

listed water utility and it is controlled by Agbar, a Spanish water utility firm from Barcelona. In 2005

Agbar listed IAM (Inversiones Aguas Metropolitanas S.A.), which holds all of Agbar’s shares in

Aguas Andinas, and where Agbar also retains a controlling stake. In this way a new pyramid was

created and the Aguas group started. On the other hand, some groups form as listed firms list their

subsidiaries. For example, Gener lists Puerto Ventanas in 1991 while retaining a 68% controlling

stake. Gener is one of Latin America’s largest energy producing and distribution companies, while

Puerto Ventanas is an industrial port in the seashore next to Chile’s capital. The idea behind listing

Ventanas was to allow its full development, which was difficult to achieve as a privately owned

subsidiary.

Table 6 shows the initial characteristics of groups as they are formed. Old groups (19) date

before 1990 so we report their characteristics in 1990 when our sample begins. There is a downward

trend in initial size which is consistent with the institutional-voids hypothesis. However, it would be

unwise to put much weight on this evidence since, as we see later on, it is not statistically significant

because of the large dispersion in initial size (in particular, the Angelini group is extremely large in

29  

1990 and drives up the average initial size of old groups; see Table 4 and Figure 5). Although we have

only a few observations for each 5-year period, there seems to be an upward trend in initial leverage.

It is hard to see any trend with respect to the other initial characteristics. For instance, initial vertical

integration goes up, then down, and finally up again. Overall, most initial conditions do not seem to

have systematic changes in this 20-year sample.

Figure 5 shows the histograms of initial characteristics for old and new groups. For most

characteristics both distributions (old and new) are basically overlapping. The only clear difference is,

again, in leverage. The distribution of initial leverage for new groups is shifted to the right when

compared to the distribution for old groups. We do not see a similar shift for initial external funds,

which implies that new groups are formed with more debt than minority shareholders when compared

to old groups, but on average these two sources of external funds substitute for each other. In Table 7

we test formally the differences in means between old and new groups. The sole significant difference

in initial characteristics is that new groups start with much higher leverage (43%) than old groups

(30%). In other dimensions, although new groups are borne into a more developed economic

environment, their initial structure does not seem to vary in systematic ways when compared to

groups formed in the 1980s or earlier.

In Table 8 we perform a regression analysis of initial conditions. In these regressions each

group represents a single observation. We attempt to explain variation across groups with the level of

market development seen at the time each group enters the sample. As seen in the last two columns of

Table 8, we only see some significant predictive power of market variables in the regressions for

leverage and external funds. The positive effect of trade openness and stock market capitalization on

leverage is somewhat compensated by the negative effect of domestic credit, which may seem a bit

counterintuitive from the point of view of the institutional-voids hypothesis. However, the first two

variables have more pronounced upward trends like leverage, hence the stronger positive correlation.

In the external funds regression, both the positive and negative coefficients on market variables seem

to cancel each other, hence the stability of this initial condition through time (see Figure 5). Overall,

we do not find that proxies for market development explain much of the cross-group variation in

30  

initial conditions, except, again, for leverage. This leaves is with the conclusion that we do not really

understand what explains groups’ initial conditions, or what institutional voids do they compensate

for at the time of formation.

A second approach to understanding the drivers of initial conditions is to study whether

groups differ according to the type of controlling shareholder, such as a family or foreign investor.

We do not find significant differences in the initial conditions of family and non-family groups (see

Table 7). We do find some small differences when comparing foreign and local groups. Foreign

groups start with control structures that are slightly less horizontal (higher position, higher wedge).

However, the overall impression is that there are few differences in the initial structure of groups

along these dimensions. One obvious caveat to our study of initial conditions is that we only have one

observation of initial condition per group and therefore these comparisons are made with a relatively

small sample (30 observations).

5. What Explains the Resilience of Chilean Business Groups?

If the institutional-void hypothesis does not seem to explain much of the dynamics of Chilean

groups, what alternative theories do we have? The parasites-view is one alternative. One possibility is

that groups survive by holding on to monopoly power or to the exploitation of natural resources.

While in Chile some groups operate in industries with natural monopolies such as utilities (water,

electricity), it is interesting to note that most of those groups are nowadays foreign-owned after

control was transferred. Other Chilean groups operate in highly competitive international industries

such as pulp production, shipping, or winemaking. Similarly, very few of the Chilean groups are

focused on mining (SQM is the exception, see Table 1), although Chile has a natural advantage in

these natural resources (particularly copper).

Also within the parasites-view is Morck (2010)’s “eternal life” hypothesis, which argues that

business groups persist because of their political influence. Many of the groups in Chile formed

during Pinochet’s authoritarian government, so it might be the case that they enjoyed access to

31  

political rents (industrial protection, generous bailouts, subsidies, takeover protection, etc.). However,

after 1990 the Chilean political system has been dominated by opponents to Pinochet. In particular,

the privatization policies of the 80’s have been severely questioned on the grounds of transparency

and probity.9 Although the basic market reforms of Pinochet were kept in place, the tight regulation

and overall political climate in the period 1990-2009 can hardly be characterized as lenient towards

bad behavior in business groups, at least in comparison to other Latin American countries.

In particular, corporate misbehavior was punished as can be seen in several emblematic fines

imposed to controlling shareholders (e.g., the transfer of control of Enersis). Several foreign investors

acquired important participation in Chilean firms throughout this period; hence takeover

protectionism in the style of Dinc and Erel (2013) has not been seen. Moreover, after 1990 the country

continued with its commercial openness strategy and removed most remaining barriers for foreign

entry and tariffs.10 As argued by Rajan and Zingales (2003), trade openness is one of the key factors

that undermine the economic power, and political influence, of large incumbents like business groups.

If anything, the evidence suggests that groups during this period were not enjoying lighter regulation

or political perks as was the case with, say, South Korean groups during the government-led

industrialization push (Kim, 2010). Simply put, their “eternal life” in Chile does not seem to be rooted

in political capture.

Perhaps a final candidate to explain the resilience of Chilean business groups in Chile is a

more subtle version of the institutional voids hypothesis that we explore in this paper. In particular,

even if outcome variables, such as per capita GDP, stock market capitalization, or international trade

are booming, other institutional voids are likely to continue in the economy. In fact, Khanna, Palepu,

and Bullock (2010) argue that characterizing market development according to outcome criteria, such

as per capita GDP, can be very misleading for understanding the true institutional voids present in an

economy. They argue that the absence of intermediaries between buyers and sellers such as market

                                                            9 In 2004 there was a parlamentary commission that investigated into the privatization process and its consequences. Its conclusions were that there was a massive transfer of wealth from the state to the private sector by selling under-priced firms, which led to an excessive concentration of wealth among a few families. Nevertheless, no political or legal consequences emerged from the commission’s report. 10 Chile signed free trade agreements with Canada (1996), the EU (2002), US (2003), China (2005), and others. 

32  

research firms, credit card companies, head hunters, and other can be much more revealing of

institutional voids. Measuring the myriad of voids that characterize markets is a daunting task. Our

results perhaps suggest that one has to think harder about the precise institutional voids that business

groups compensate for in an economy. “Typical” indicators or market development do not seem to

explain the evolution, or lack of evolution, of group structures in Chile.

6. Conclusions

Why do business groups form and how do they evolve? In this paper we try to shed light on

these questions by analyzing Chile’s business groups in the last 20 years. In doing so we follow one

(out of several) view on business groups that argues that they form to fill development voids (Khanna

and Yafeh, 2007). For instance, groups can overcome underdeveloped capital markets through their

internal capital markets. In the same way, they can overcome poorly regulated environments by

enforcing contracts with related firms.

We build a database that allows us to study the structure of Chilean business groups between

1990 and 2009. We assemble group-level variables along four dimensions: size, industrial structure,

control structure, and capital structure. The idea is very simple. If groups arise to overcome

development voids, then they should adjust significantly as markets develop. Chile experienced a

unique period of development in the last 20 years: per capita income doubled in PPP terms, the stock

market tripled in size, bank credit expanded up to 90% of GDP, and so on. However, our results show

that Chilean business groups remain very similar to what they were in the beginning of the sample. At

the least, groups seem to respond very slowly to changes in the environment. Only leverage increased

systematically in this period. Also, we do not find evidence that groups’ initial conditions are shaped

by market development at the time of group formation. The evidence we show casts doubts on the

institutional-voids hypothesis, i.e., the idea that business groups exist to fill specific institutional

voids. A caveat to this interpretation is that we focus on macro proxies for market development, but

33  

other more subtle institutional voids might be shaping business groups and explaining their existence

and resilience. More research is needed to uncovered and measure those particular institutional voids.

34  

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Table 1: Main Developments of Chile’s Largest Groups (1990-2009)

The table reviews the origins, listed firms, industry affiliation, and main subsequent developments for ten of Chile’s largest groups in 1990. Data was obtained from firms’ annual reports, SVS, Fecus Plus, and Economatica.

Group Origins Listed Firms in 1990 (Controlled in 2009?)

Industry Main Developments (1990-2009)

Copec (Yes) Pulp producer

Antarchile (Yes) Holding company

Eperva (Yes) Fishing

Siemel (Yes) Insurance

Saesa (No) Energy

Cholguan (Yes) Forestry

Iquique (Yes) FishingCmpc (Yes) Pulp producer

Volcan (Yes)Non-metallic building products

Minera (Yes) HoldingColina (Yes) HoldingInforsa (Yes) ForestryPuerto (Yes) PortPasur (Yes) Holding

CCU (Yes) Beverages

Carrera (No) Hotel

Penon (Yes) Holding

Telcoy (Yes) Telecommunications

Telsur (Yes) Telecommunications

Madeco (Yes) Metal manufacture

Enersis (Yes) Holding

Rio Maipo (No) Energy distribution

Chilectra (Yes) Energy distribution

Anacleto Angelini arrives to Chile from Italy in the late 40's. Incorporates a paint producer and later a fishing company. Acquires Copec (group's flagship) in the late privatization waves (1986).

In 1996 enters Argentina by acquiring a forestry company. In 2001 divests Saesa to PSEG Global. In 2002 finishes a pulp plant that allows the group to become one of the largest pulp producers in the world. Anacleto Angelini dies in 2007 being succeded by his nephew. In 2009 enters Brazil with Stora-Enso for a forestry-pulp project.

Angelini (family

controlled)

Matte (family controlled)

Luis Matte Larrain founded a cardboard and paper factory (CMPC) in 1920. The company evolved into a forestry and pulp producer

The group acquires a stake in a state controlled energy producer in 1997, merging all its relatively small energy businesses with this new firm (Colbun). CMPC (the flagship) acquired related business all through Latin America: Argentina 1991, Uruguay 1994, Peru 1996, Mexico 2006 and Brazil in 2009.

Andronico Luksic began with copper mining in the early 50's. The group controls Madeco in 1983 and CCU in 1986.

Luksic (family controlled)

In 1997 the group lists its holding and flagship company, Quinenco. Also in 1997 began the construction of Los Pelambres, one of Chile's largest copper mines. In 2003 it divests its hotel business. In 2008 divests part of Madeco and enters Nexans, a leading cable producer from France. In 2009 divests Telsur and Telcoy (effectively transferred in 2010). The founder retires in 2002 and dies in 2005, leaving his three male children in charge.

In 1981 Compañía Chilena de Electricidad S.A. reorganized into three subsidiaries. One of them, Compañía Chilena Metropolitana de Distribucion Electrica S.A., was fully privatized in 1987, giving birth to the group. In 1988 it changed its name to Enersis.

Enersis (foreign

controlled)

Between 1992 and 1998 Enersis enters Argentina, Peru, Brazil and Colombia by acquiring energy distribution firms, a process that has further developed allowing Enersis to be one of the leading energy firms in Latin America. In 1997 Endesa Espana acquired 32% of Enersis, which increased to 64% in 1999. In 1999 Enersis acquires control of Endesa in the largest M&A in Chile's history. Divests Rio Maipo in 2003. Enters a water utility in 1996 and divests it in 2000. In 2007 Enel and Acciona take control of Endesa Espana (and thus Enersis)

Group OriginsListed Firms in 1990 (Controlled in 2009?)

Industry Main Developments (1990-2009)

Vapores (Yes)Shipping and maritime transport

Elecmetal (Yes) Holding

Marinsa (Yes) Holding

Cristales (Yes) Glass producer

Navarino (Yes) Holding

SQM (Yes) Non-metallic mining

Calichera (Yes) Holding

Somela (Yes)Household appliance manufacturing

CTI (Yes)Household appliance manufacturing

Concha y Toro (Yes) Winery

Emiliana (Yes) Winery

Viconto (Yes) Winery

Agunsa (Yes) Holding

Interoceanica (Yes) Maritime transport

Endesa (No)Holding/Energy production and distribution

Pehuenche (No)Energy production and distribution

Concha y Toro (family controlled)

Incorporated in 1883, the controlling family arrives in the 50's.

In 1994 lists its shares in the NYSE. During the 90's develops an export vocation that sets the trend for the Chilean wine industry. In 1997 signs a joint venture with Baron Philippe de Rothschild. By 2009 its wines can be found in more than 100 countries

Endesa (local and now foreign)

Incorporated in 1943, was privatized in 1989. During the 90's expands into Argentina (1992 on), Peru (1995), Colombia (1996) and Brazil (1997). In 1999 Enersis acquires control of Endesa. The group developed toll roads in late 90's (later divested by Enersis).

Urenda (family controlled)

Incorporated in the 1930, Interoceanica incorporates Agunsa in 1960.

During the 90s the group expands internationally through Latin America, which continued during the 2000s into Asia and Europe. The flagship (Empresas Navieras) is listed in 1992.

Sigdo Koppers

The group enters Peru in 1998 through an engineering subsidiary. Acquires Puerto Ventanas, an industrial port in Chile in 2001. In 2003 acquires Fepasa, a railroad trainsport company. In 2005 lists its holding and flagship company, Sigdo Koppers, and its subsidiaries expand in Argentina and Mexico.

SQMSQM was incorporated in 1968 to exploit saltpeter. The firm is nationalized and in 1983 begins a privatization process led by Julio Ponce Lerou, current controller.

The controlling shareholder incorporates and lists a pyramid allowing him to control SQM. First Calichera in 1990 (which controls SQM directly), then Oro Blanco in 1991 (which controls Calichera), Norte Grande in 1992 (controls Oro Blanco) and Soquimich Comercial in 1993 (SQM's subsidiary). In 1993 it issues ADRs in NYSE. In 2009 it has both commercial presence and subsidiaries in more than 20 countries around the world.

Incorporated in 1960, it acquired CTI and Somela in 1987. It acquires Enaex in 1990, and lists it in 1991.

ClaroRicardo Claro acquires Elecmetal in 1976, which had acquired Cristales in 1975. The group enters Santa Rita in 1980.

In 1989 the group enters the TV business and in 1995 the cable TV businnes. In 1991 the group lists Santa Rita and in 1997 Santa Rita enters Argentina. In 2000 began with the port business in San Antonio (Chile's main port) which then expanded to many other Chilean and Latin American ports. In 2008 the founder dies and Vapores enters a crisis which ends with a change in control by 2011.

Table 2: Industry Affiliation of Chilean Listed Firms (1990-2009)

The table shows industry affiliation for all group and non-group firms. Frequencies are at the firm-year level. The table also splits between old and new groups, family and non-family groups, and foreign and local groups. Old groups are those formed before 1990, new groups are those formed afterwards. Family groups are controlled by a family. Foreign groups are controlled by non-Chilean investors. The sample covers all non-financial Chilean listed firms between 1990 and 2009. A business group is defined as a set of two or more listed firms with the same ultimate controlling shareholder. Data was obtained from firms’ annual reports, SVS, Fecus Plus, and Economatica.

All Old New Family Non-Family Foreign Local

NAICS 1 (Agriculture and forestry) 1% 1% - 2% - - 1% 1% 1%NAICS 2 (Mining, utilities, and construction) 18% 20% 5% 7% 40% 46% 14% 14% 16%NAICS 3 (Manufacturing) 31% 32% 24% 36% 21% 11% 34% 46% 37%NAICS 4 (Retail and wholesale trade) 7% 7% 8% 8% 5% 0% 8% 9% 8%NAICS 5 (Holdings, real estate, and others) 42% 39% 63% 46% 34% 43% 42% 24% 35%NAICS 6 (Educational and health services) - - - - - - - 5% 2%NAICS 7 (Recreation and accommodation) 1% 1% - 1% - - 1% 1% 1%

Full Sample (%) 59% 49% 9% 39% 19% 7% 51% 41% 100%

GroupsNon-

GroupsAll Chilean

Listed FirmsForeign vs. LocalFamily vs. Non-familyOld vs. New

Table 3: Summary Statistics on the Characteristics of Chilean Groups (1990-2009)

The table shows summary statistics for the following group characteristics: number of listed firms per group (firms per group), the fraction of groups that is family controlled (family control), or controlled by non-Chilean investors (foreign control), the ratio of the sum of consolidated assets for firms at the top of the pyramid over GDP (size over GDP), pyramidal structure (position), difference between voting and cash flow rights (wedge), fraction of firm's input or output that is acquired or sold within the group (vertical integration), number of industries per group (diversification), lending and borrowing to intra-group firms over assets (internal capital markets), debt over total assets (leverage), and debt and minority equity over total assets (external funds). The table also shows means of group characteristics in 1990 and 2009 for all, old, and new groups, along with the differences in means. The sample covers non-financial Chilean listed firms which are affiliated to business groups between 1990 and 2009. Data was obtained from firms’ annual reports, SVS, Fecus Plus, and Economatica. Significance at the 1% ***, 5% **, or 10% * refers to the t-test for differences in means between the corresponding columns.

All (a) All (b) Old (c) New (d)Mean SD Min Max 1990 2009 2009 2009 (b-a) (c-a) (d-c)

Firms per group 3.73 2.06 2.00 10.00 3.37 3.57 4.27 2.25 0.20 0.90 -2.02***Family control 0.62 0.49 0.00 1.00 0.58 0.65 0.80 0.38 0.07 0.22 -0.43**Foreign control 0.17 0.38 0.00 1.00 0.11 0.22 0.07 0.50 0.11 -0.04 0.43**Size over GDP (%) 2.72 4.87 0.01 34.41 3.79 1.74 2.32 0.65 -2.05 -1.47 -1.68Position 1.44 0.53 1.00 3.75 1.37 1.45 1.55 1.26 0.08 0.18 -0.29Wedge 0.08 0.09 0.00 0.49 0.10 0.07 0.08 0.05 -0.03 -0.02 -0.03Vertical integration (%) 5.79 8.52 0.00 42.06 5.17 7.71 5.81 11.02 2.54 0.64 5.21Diversification 2.70 1.66 1.00 9.00 2.63 2.52 2.93 1.75 -0.11 0.30 -1.18*Internal Capital Markets 0.12 0.12 0.00 0.59 0.05 0.08 0.06 0.12 0.03 0.01 0.06Leverage 0.38 0.15 0.00 0.91 0.30 0.44 0.43 0.45 0.14*** 0.14*** 0.02External Funds 0.61 0.15 0.06 0.93 0.62 0.59 0.60 0.58 -0.03 -0.02 -0.03

Number of groups 30 19 23 15 8

Differences in MeansMeans for Subsamples

All Groups 1990-2009

Table 4: Characteristics for Selected Groups in 1990 and 2009

The table shows the main characteristics in 1990 and 2009 for some selected business groups that survive the entire sample period. Variables are described in Table 3. Data was obtained from firms’ annual reports, SVS, Fecus Plus and Economatica.

Variable 1990 2009 1990 2009 1990 2009 1990 2009 1990 2009 1990 2009 1990 2009 1990 2009 1990 2009Size over GDP (%) 22.05 7.21 6.31 5.70 4.91 1.37 4.12 11.63 2.00 1.51 0.88 0.98 0.56 0.88 0.57 0.50 0.87 0.28Position 1.13 1.53 1.80 1.63 1.01 2.16 1.00 1.39 2.07 2.27 1.00 2.68 1.16 1.37 1.00 1.00 1.00 1.50Wedge 0.02 0.09 0.16 0.06 0.00 0.13 0.00 0.10 0.20 0.22 0.16 0.15 0.07 0.04 0.00 0.00 0.00 0.12Vertical integration (%) 1.49 1.11 2.48 3.45 2.35 6.15 0.00 0.00 7.77 8.21 22.67 8.17 0.21 0.41 17.39 17.39 1.37 2.51Diversification 7 6 6 7 5 4 1 1 3 4 2 3 1 4 1 1 2 2Internal Capital Markets 0.01 0.00 0.05 0.00 0.18 0.14 0.18 0.00 0.04 0.11 0.02 0.27 0.04 0.05 0.08 0.17 0.00 0.00Leverage 0.33 0.40 0.10 0.31 0.60 0.41 0.28 0.50 0.34 0.61 0.23 0.46 0.46 0.43 0.39 0.38 0.37 0.69External Funds 0.57 0.55 0.50 0.51 0.69 0.62 0.73 0.61 0.55 0.71 0.50 0.63 0.73 0.57 0.78 0.73 0.61 0.78

GroupSQM Sigdo Koppers Concha y Toro UrendaAngelini Matte Luksic ClaroEnersis

Table 5: Do Business Groups Change with Market Development? Main Regressions

The table shows OLS and fixed-effect regressions where dependent variables are: group size over GDP, position, wedge, vertical integration, diversification, internal capital markets, leverage, and external funds as described in Table 3. Independent variables are: initial level of each characteristic for each group; per capita gross domestic product (GDP) of Chile relative to the U.S.; domestic credit by banking sector over GDP; trade openness (exports plus imports) over GDP; stock market capitalization over GDP (Market Cap over GDP); and a dummy that takes the value of one after the regulation of tender offers was improved in 2001 (Law dummy). The sample covers non-financial Chilean listed firms which are affiliated to a business group between 1990 and 2009. Data was obtained from firms’ annual reports, SVS, Fecus Plus, and Economatica. Macroeconomic variables are from the World Bank and Penn World Tables. Standard errors, in parenthesis, are robust and clustered at the group level. Significance at the 1% ***, 5% **, or 10% *.

1 2 3 4 5 6 7 8Initial Characteristic 0.55*** 0.56** 0.77*** 0.73***

(0.06) (0.26) (0.20) (0.14)GDP Per Capita -2.00 -4.11 -0.65 0.41 -0.09 -0.03 1.52 -3.48

(4.84) (7.38) (0.82) (0.57) (0.13) (0.12) (8.67) (6.08)Domestic Credit 5.91 6.39 -0.10 0.11 0.01 0.01 0.54 -0.48

(4.96) (5.71) (0.24) (0.23) (0.06) (0.06) (1.81) (1.75)Trade Openness -6.88 -7.27 0.34 -0.21 0.03 0.04 1.26 3.76

(6.14) (8.11) (0.38) (0.47) (0.08) (0.09) (3.47) (3.32)Market Capitalization -0.45** -0.45* 0.03 0.06 0.01 0.01 0.01 -0.18

(0.17) (0.23) (0.03) (0.05) (0.01) (0.01) (0.51) (0.48)Law Dummy -0.21 -0.12 0.04* 0.05* 0.00 -0.00 0.07 -0.04

(0.23) (0.26) (0.02) (0.03) (0.01) (0.01) (0.25) (0.27)

Group Fixed Effects No Yes No Yes No Yes No YesR squared 0.39 0.76 0.14 0.90 0.55 0.88 0.77 0.96Observations 441 471 441 471 441 471 440 470

Size over GDP Position Wedge Vertical IntegrationDependent variable

1 2 3 4 5 6 7 8Initial Characteristic 0.97*** 0.35** 0.46*** 0.66***

(0.10) (0.13) (0.15) (0.15)GDP Per Capita 1.36 2.20 -0.03 0.17 0.75** 0.80** -0.36 -0.45*

(1.49) (1.49) (0.31) (0.31) (0.30) (0.31) (0.27) (0.23)Domestic Credit 0.79 1.06** 0.37*** 0.41*** 0.15 0.22* -0.12 -0.03

(0.47) (0.52) (0.12) (0.13) (0.11) (0.11) (0.09) (0.08)Trade Openness -1.76** -2.48** -0.31* -0.46** -0.24 -0.36** 0.16 0.04

(0.82) (0.95) (0.17) (0.17) (0.15) (0.16) (0.15) (0.13)Market Capitalization -0.02 0.02 0.03 0.03 -0.02 -0.02 -0.00 -0.00

(0.06) (0.07) (0.02) (0.02) (0.02) (0.02) (0.02) (0.01)Law Dummy 0.07 0.08 0.01 0.02 0.03 0.03* 0.01 0.01

(0.08) (0.09) (0.02) (0.02) (0.02) (0.02) (0.01) (0.01)

Group Fixed Effects No Yes No Yes No Yes No YesR squared 0.84 0.94 0.13 0.53 0.28 0.66 0.33 0.76Observations 441 471 441 471 441 471 441 471

Dependent variableDiversification Internal Capital Markets Leverage External Funds

Table 6: Groups’ Initial Conditions 1990-2009

The table shows means of groups’ initial conditions, i.e., characteristics at the time of their first appearance in our sample, for the year 1990 and in 5-year periods afterwards. The number of groups corresponds to the groups that first appear in our sample in each period. Variables as described in Table 3. The sample covers non-financial Chilean listed firms which are affiliated to a business group between 1990 and 2009. Data was obtained from firms’ annual reports, SVS, Fecus Plus, and Economatica.

1990 1991-1995 1996-2000 2001-2005 2006-2009Size over GDP (%) 3.79 4.30 1.04 0.91 0.22Position 1.37 1.01 1.00 1.21 1.44Wedge 0.10 0.01 0.00 0.05 0.14Vertical integration (%) 5.17 12.39 2.45 0.25 27.70Diversification 2.63 1.60 2.00 2.00 1.50Internal Capital Markets 0.05 0.11 0.00 0.09 0.18Leverage 0.30 0.48 0.39 0.28 0.48External Funds 0.62 0.74 0.59 0.45 0.63

Number of Groups 19 5 2 2 2

Means of Groups' Initial Conditions

Table 7: Means of Initial Conditions by Group Type

The table shows averages on group characteristics at the time of groups’ first appearance in our sample. Variables as described in Table 3. The table distinguishes between old and new, family and non-family, and foreign and locally controlled groups. Old groups are those formed before 1990, new groups are those formed afterwards. Family groups are controlled by a family. Foreign groups are controlled by non-Chilean investors. The sample covers non-financial Chilean listed firms which are affiliated to a business group between 1990 and 2009. Data was obtained from firms’ annual reports, SVS, Fecus Plus, and Economatica. Significance at the 1% ***, 5% **, or 10% * refers to the t-test for differences in means between group types.

Old(a)

New (b)

Difference (b-a)

Family (c )

Non-Family (d)

Difference (d-c)

Foreign (e )

Local (f)

Difference (f-e)

Size over GDP (%) 3.80 2.35 -1.45 3.12 3.41 0.28 2.24 3.52 1.28Position 1.37 1.12 -0.24* 1.24 1.32 0.08 1.50 1.22 -0.28*Wedge 0.10 0.04 -0.06 0.06 0.10 0.04 0.15 0.06 -0.09**Vertical integration (%) 5.17 11.16 5.99 10.28 4.44 -5.84 8.63 7.05 -1.58Diversification 2.63 1.73 -0.90 2.67 1.93 -0.73 1.83 2.42 0.58Internal Capital Markets 0.05 0.10 0.05 0.07 0.07 0.00 0.09 0.06 -0.03Leverage 0.30 0.43 0.13** 0.34 0.35 0.01 0.44 0.32 -0.12External Funds 0.62 0.64 0.02 0.62 0.65 0.03 0.65 0.63 -0.03

Averages of Initial Conditions by Group Type

Table 8: Do Groups’ Initial Conditions Change with Market Development?

The table shows cross-sectional OLS regressions where the dependent variable is the initial value of a characteristic for each group. Group characteristics are: group size over GDP, position, wedge, vertical integration, diversification, internal capital markets, leverage, and external funds as described in Table 3. Independent variables are: per capita gross domestic product (GDP) of Chile relative to the U.S.; domestic credit by banking sector over GDP; trade openness (exports plus imports) over GDP; stock market capitalization over GDP (Market Cap over GDP); and a dummy that takes the value of one after the regulation of tender offers was improved in 2001 (Law dummy). The sample covers non-financial Chilean listed firms which are affiliated to a business group between 1990 and 2009. Data was obtained from firms’ annual reports, SVS, Fecus Plus, and Economatica. Macroeconomic variables are from the World Bank and Penn World Tables. Standard errors, in parenthesis, are robust. Significance at the 1% ***, 5% **, or 10% *.

Size over GDP Position Wedge Vertical Int. Diversification Internal Cap. Mkts. Leverage External FundsGDP Per Capita -23.14 3.86 1.19 150.70 -2.86 3.65 0.32 0.00

(46.91) (4.65) (1.50) (299.85) (11.45) (3.23) (1.81) (2.52)Domestic Credit -15.65 -0.51 -0.23 -76.03 3.79 -1.84 -1.88** -1.98**

(14.65) (1.60) (0.50) (109.13) (4.61) (1.20) (0.69) (0.74)Trade Openness -3.09 -1.26 -0.27 299.62 -4.77 -0.79 3.97** 4.21*

(26.48) (3.04) (0.93) (188.10) (6.05) (1.16) (1.84) (2.11)Market Capitalization -2.71 -1.46* -0.40 29.40 -1.90 -0.77 0.61* 0.39

(8.88) (0.78) (0.25) (55.02) (2.17) (0.47) (0.32) (0.45)Law Dummy 3.71 0.85 0.23 -64.85 1.18 0.54 -0.77* -0.75

(4.95) (0.85) (0.26) (41.57) (1.59) (0.35) (0.41) (0.51)

R squared 0.05 0.18 0.18 0.24 0.09 0.34 0.34 0.27Observations 30 30 30 30 30 30 30 30

Dependent variable

Figure 1: Evolution of Chile’s Key Economic Indicators 1990-2009

The figure shows the evolution of Chile’s per capita GDP relative to the U.S., domestic credit by the banking sector over GDP, trade openness (exports plus imports) over GDP, and stock market capitalization of listed companies over GDP. Data are from the World Bank and Penn World Tables.

.15

.3

1990 1995 2000 2005 2010

GDP Per Capita

0.5

1

1990 1995 2000 2005 2010

Domestic Credit.5

.75

1

1990 1995 2000 2005 2010

Trade Openness

.51

1.5

1990 1995 2000 2005 2010

Market Capitalization

Figure 2: Examples of Chilean Pyramids

The figure shows a simplified version of the Luksic and Claro groups in 2008. Shaded boxes represent listed firms and white boxes represent private firms. The arrows indicate ownership links and the percentage number over each arrow indicates the percentage of ownership. Data was obtained from firms’ annual reports.

Figure 3: Average Group Characteristics and Chile’s Per Capita GDP (1990-2009) The figure shows the evolution of business groups’ average characteristics such as size, position, wedge, vertical integration, diversification, internal capital markets, leverage and external funds, together with the level of per capita GDP of Chile relative to the U.S.

   

.15

.2.2

5.3

GD

P pe

r Cap

ita

01

23

45

1990 1995 2000 2005 2010

Size over GDPGDP per Cap

Size

.15

.2.2

5.3

GD

P pe

r Cap

ita

11.

52

1990 1995 2000 2005 2010

PositionGDP per Cap

Position

.15

.2.2

5.3

GD

P pe

r Cap

ita

.025

.05

.075

.1.1

25

1990 1995 2000 2005 2010

WedgeGDP per Cap

Wedge

.15

.2.2

5.3

GD

P pe

r Cap

ita

02.

55

7.5

10

1990 1995 2000 2005 2010

IntegrationGDP per Cap

Vertical Integration

.1

5.2

.25

.3G

DP

per C

apita

12

34

1990 1995 2000 2005 2010

DiversificationGDP per Cap

Diversification

.15

.2.2

5.3

GD

P pe

r Cap

ita

0.0

5.1

.15

1990 1995 2000 2005 2010

Internal Capital MktsGDP per Cap

Internal Capital Mkts

.15

.2.2

5.3

GD

P pe

r Cap

ita

0.2

5.5

.75

1

1990 1995 2000 2005 2010

LeverageGDP per Cap

Leverage

.15

.2.2

5.3

GD

P pe

r Cap

ita

0.2

5.5

.75

1

1990 1995 2000 2005 2010

External FundsGDP per Cap

External Funds

Figure 4: The Evolution of Group Characteristics for Old Groups (1990-2009)

The figure shows the evolution of average characteristics for old groups (i.e., groups formed before 1990) that are split into two sets according to their initial characteristics in 1990 (large and small, vertical and horizontal, and so on). Throughout the sample period we compute the average characteristic for each set of business groups separately.

02.

55

7.5

10

1990 1995 2000 2005 2010

LargeSmall

Size

11.

52

1990 1995 2000 2005 2010

VerticalHorizontal

Position

0.0

5.1

.15

1990 1995 2000 2005 2010

High WedgeLow Wedge

Wedge

03

69

12

1990 1995 2000 2005 2010

More IntegratedLess Integrated

Vertical Integration

12

34

1990 1995 2000 2005 2010

More DiversifiedLess Diversified

Diversification

0.0

5.1

.15

1990 1995 2000 2005 2010

High ICMLow ICM

Internal Capital Mkts

.1.3

5.6

1990 1995 2000 2005 2010

High LeverageLow Leverage

Leverage

.4.6

.8

1990 1995 2000 2005 2010

High External FundsLow External Funds

External Funds

Figure 5: Histogram of Groups’ Initial Conditions

The figure shows histograms for groups’ initial conditions, splitting the sample between old and new groups. Old groups are those formed before 1990.

   

020

4060

Per

cent

0 5 10 15 20 25

Old New

Size

020

4060

80P

erce

nt

1 1.2 1.4 1.6 1.8 2

Old New

Position

020

4060

80P

erce

nt

0 .1 .2 .3

Old New

Wedge

020

4060

80P

erce

nt0 10 20 30 40

Old New

Integration

020

4060

8010

0P

erce

nt

0 2 4 6

Old New

Diversification

020

4060

80P

erce

nt

0 .1 .2 .3 .4

Old New

Internal Capital Mkts

010

2030

Per

cent

0 .2 .4 .6

Old New

Leverage

05

1015

20P

erce

nt

0 .2 .4 .6 .8 1

Old New

External Funds