You Needn t be the First Investor There: First-Mover Disadvantages in Emerging Private Equity Markets

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1 You Needn t be the First Investor There: First-Mover Disadvantages in Emerging Private Equity Markets Alexander Peter Groh* This version: 6 January 2017 Abstract: Early movers into emerging private equity markets may capitalize on growth opportunities and build up networks. However, the deal-making conditions might not (yet) be favorable for the pioneers and they may lack local experience. I support this alternative conjecture by analyzing a unique, hand-collected dataset on emerging private equity market transactions. I analyze 1,157 deals in 86 host countries between 1973 and 2009, and find that waiting and learning pays. I control for the opportunity cost of capital, cross currency rate fluctuations, GDP growth over the holding periods, exit market liquidity, and socio-economic factors such as a country s innovation capacity, its legal quality, its human capital, and labor market frictions, to show that early transactions underperform later ones. I interpret this to be the result of learning benefits and of improvements in the deal-making environment over time. The learning benefits are stronger if investors are located in the country of the investee firm. JEL codes: G23, G24, O16, P52 Keywords: Emerging Markets, Venture Capital, Private Equity, Alternative Assets *) EMLYON Business School, 23 Avenue Guy de Collongue, Ecully, France, Phone: , groh@em-lyon.com

2 You Needn t be the First Investor There: First-Mover Disadvantages in Emerging Private Equity Markets This version: 6 January 2017 Abstract: Early movers into emerging private equity markets may capitalize on growth opportunities and build up networks. However, the deal-making conditions might not (yet) be favorable for the pioneers and they may lack local experience. I support this alternative conjecture by analyzing a unique, hand-collected dataset on emerging private equity market transactions. I analyze 1,157 deals in 86 host countries between 1973 and 2009, and find that waiting and learning pays. I control for the opportunity cost of capital, cross currency rate fluctuations, GDP growth over the holding periods, exit market liquidity, and socio-economic factors such as a country s innovation capacity, its legal quality, its human capital, and labor market frictions, to show that early transactions underperform later ones. I interpret this to be the result of learning benefits and of improvements in the deal-making environment over time. The learning benefits are stronger if investors are located in the country of the investee firm. JEL codes: G23, G24, O16, P52 Keywords: Emerging Markets, Venture Capital, Private Equity, Alternative Assets

3 By entering a new market, firms can exploit significant growth opportunities without generating excess capacity (Spence, 1979). Empirical research supports the notion that there are important advantages to being the first entrant in some sorts of markets (Schmalensee, 1982). First-mover advantages for pioneering firms are expected to include gaining a head start over rivals. This opportunity may occur because the firm possesses unique resources or foresight (Lieberman and Montgomery, 1988). Learning may also generate a first-mover advantage. Spence (1981) demonstrates that if learning can be kept proprietary, the learning curve can generate substantial barriers to entry. However, the mechanisms that benefit the first mover may be counterbalanced by disadvantages, such as the ability of followers to free ride on the first movers activities. Emerging private equity (PE) markets are new markets in the investors universe. First movers might be able to benefit from untapped deal flow and gain a head start over rivals. Emerging countries economic growth requires substantial funding. Early movers may be able to capitalize on the growth opportunities, thereby gaining local experience and building up networks. For investors in emerging market PE funds there is a widely accepted argument for committing capital early: access to the top general partners might be restricted once they have a proven track record. Their follow-on funds will be oversubscribed and therefore not accessible by limited partners who had no relationship with them in the pioneering phase. This motivates institutional investors to move quickly into emerging regions and to develop strategic partnerships with local fund managers. Nevertheless, a supportive environment for PE deal making requires more than economic growth. Traditional PE markets (e.g. the U.S., the U.K., Canada, France, Japan, Germany, etc.) 1

4 exhibit lower GDP growth rates than the average emerging country but they have many other favorable characteristics. These characteristics have been analyzed in numerous empirical studies and include the depth of the country s capital market (Jeng and Wells, 2000; Black and Gilson, 1998; and Gompers and Lerner 2000), labor market frictions, investor protection, general ease of doing business, the country s human capital (Lazear, 1990; Blanchard, 1997; La Porta et al., 1997 and 1998; Roe, 2006; Glaeser et al., 2001; Djankov et al., 2003 and 2008; Lerner and Schoar, 2005; Cumming et al., 2006 and 2010), and its innovation capacity (Gompers and Lerner, 1998; and Kortum and Lerner, 2000) among others. If these favorable characteristics are required for successful PE deal making, it might not be easy for emerging market pioneers to gain first-mover advantages because the characteristics have not yet developed to the necessary extent. Instead, it seems somewhat beneficial to wait until the countries are sufficiently developed to facilitate PE deal making. Despite the level of socio-economic development required for PE activity, research has provided evidence on value drivers in PE transactions and on appropriate target company characteristics. It is commonly understood that PE sponsors can add value to their portfolio companies by reducing agency costs and by exploiting debt tax shields. Active monitoring, incentive structuring, and bonding may lower the agency costs of free cash flow. Improvements in operating efficiency, focusing on core activities, and selling off non-core assets all create more competitive entities (Jensen, 1988; Kaplan, 1989a and 1989b; Lichtenberg and Siegel, 1990; Muscarella and Vetsuypens, 1990; Smith, 1990; Wruck, 1990; and Kaplan, 1991). The benefit of PE is assumed to be greatest for corporations with high agency costs of free cash flow, in other words high operating cash flows but missed investment opportunities. Jensen (1986) notes that 2

5 desirable leveraged buyout candidates are frequently firms or divisions of larger firms that have stable business histories and substantial free cash flow (i.e., low growth prospects and high potential for generating cash flows) situations where agency costs of free cash flow are likely to be high. I argue that the required socio-economic environment for successful PE deal making has not yet developed in many emerging PE markets, in particular when the pioneers enter the market. I also expect that creating deal flow will be cumbersome because potential target firms do not fulfill the appropriate characteristics of ideal buyout candidates (i.e. high agency costs of free cash flow). It is doubtful that companies in rapidly growing markets provide these opportunities because they have high capital expenditure. The need to exploit growth potential within a short timescale also leaves little room for operational improvement. Furthermore, as the opportunity cost of capital is usually high in emerging countries, other investment channels, such as portfolio and corporate foreign direct investment, may be better suited for capitalizing on growth expectations. The assumption of a lack of appropriate buyout target candidates is supported by the observation that many of the emerging market PE deals are not in fact true buyouts but are actually disguised project, infrastructure, or growth-financing transactions. As a result, we do not expect first-mover advantages from early entry in emerging PE markets. There is no need to be among the first investors because PE deal-making conditions are not sufficiently developed at the time the pioneers enter. Furthermore, deal making is different in emerging countries. Investors need to gain local experience and should not expect the traditional PE deal model they are confident with to be easily transferrable to emerging environments. 3

6 I support this claim by analyzing the dataset from Lopez-de-Silanes et al. (2015), which is the largest dataset on emerging PE markets used to date. 1 I analyze 1,157 emerging market PE transactions in 86 host countries between 1973 and 2009 and find that waiting and learning pays. I control for different definitions of the opportunity cost of capital, for cross currency rate fluctuations, for real GDP growth during the transaction holding period, for exit market liquidity, and for socio-economic determinants such as the country s innovation capacity, its legal quality, its human capital, and its labor market protection, and find that early transactions underperform later ones. The performance of PE transactions (measured by their internal rates of return), increases over time from the date of the pioneering investment. This effect is consistent with learning benefits and improvements in PE deal-making conditions. However, learning effects are not proprietary; instead they benefit the whole investment community because later entrants also earn higher returns. I therefore conclude that there are no directly measurable first-mover advantages and that it is preferable for investors to delay their emerging market PE allocations until the individual countries are mature enough to establish liquid PE activity. The data also reveals that if investors aim to enter emerging PE markets, they should allocate their investments to general partners located in the investment host country. Cross-border deals yield significantly lower returns than national transactions, and distantly managed funds (e.g. those headquartered in the U.S.) underperform funds that are closer to the investment host country. The findings are robust with respect to a variety of potentially confounding factors. I show that cross currency rate changes, alternative measures for the opportunity cost of capital, over-represented sample countries, and misspecifications in the dates of pioneering transactions do not affect the findings. I also reveal 1 I am very grateful to Ludovic Phalippou for making the data available for this paper. 4

7 that the learning benefit declines over time so that emerging PE market performance returns to an average level. The paper is structured as follows: I first discuss the related literature before developing my hypotheses in the following section. I then describe the data, perform the analyses and robustness checks, and interpret the results before concluding. 1. Related Literature While several contributions focus on the performance of PE funds and leveraged buyout transactions in general, research on emerging market PE returns is limited. Only a few publications include transactions in developing countries in their sample, and these studies usually focus on general investment activity rather than on returns to investors. Strömberg (2008) provides a comprehensive overview of global LBO activity. He collects data from a commercial provider relating to 21,397 LBO transactions between 1970 and 2007 with a total transaction value of approximately $3.6 trillion and documents the tremendous growth of the industry, particularly in terms of its geographic dispersion. Nevertheless, LBO transactions outside North America and Western Europe are still relatively few and account for only 13% of the global volume in numbers and 7% in value. Kaplan and Stömberg (2009) note that PE activity strongly spread to new parts of the world between 2001 and 2006, to Asia in particular, where deal size almost tripled during the period. Lerner and Schoar (2004) argue that systematic data on emerging market PE returns is hard to come by, but submit that returns in these nations appear to have been far lower than in the U.S. 5

8 and Europe. They conclude that the experience of PE funds in the developing world poses interesting issues that have been little explored in academic research to date. Lerner and Schoar (2005) address the contractual structures of emerging market PE transactions. In low enforcement and civil law countries, PE sponsors tend to use common stock and straight debt and therefore rely on equity and board control. This might alleviate potential enforcement problems arising from the contractual provisions of convertible preferred securities, which are commonly used in the U.S. On the other hand, transactions in inferior enforcement countries have lower valuations and returns. Kaplan et al. (2007) provide detailed analyses of contracts used for venture capital transactions in 23 countries and compare them with the typical U.S. style contract used at the time. They find that contracts differ strongly across legal regimes and conclude that transactions using non-u.s. style contracts fail more often. Leeds and Sunderland (2003) emphasize the notion of inferior returns to investors from emerging market PE activities and discuss potential determinants of under-performance. They argue that the U.S. PE industry evolved gradually over a forty-year period that was increasingly conducive to this type of financing and point to a sympathetic public policy environment, a reliable legal system, stability, a well-developed financial market, and finally, demand from cooperative entrepreneurs. In particular, they identify low standards of corporate governance, limited legal recourse, and dysfunctional capital markets as factors impeding PE activity in emerging markets. Nahata et al. (2014) elaborate on these assumed deficiencies and reveal that the quality of legal rights and investor protection, and the general development of stock markets are indeed inhibitors. Cumming and Walz (2009) and Cao et al. (2014) confirm the role of legal protection for PE sponsors in emerging countries. Lopez-de-Silanes et al. (2015) find that 6

9 emerging market PE transactions have slightly longer durations and exhibit statistically significantly poorer performance across several measures with the exception of bankruptcy rates. However, the authors had expected the opposite due to higher assumed cost of capital in these countries. The lower returns could be the result of costly learning, poor legal environments, and illiquid exit markets. They also find lower degrees of leverage for developing country PE transactions and suggest this as another reason for smaller returns on equity. Demiroglu and James (2010) find that LBO activity and the likelihood of success are largely driven by debt market conditions, loan spreads in particular. Ivashina and Kovner (2011) quantify the expected increase in the return on equity of a buyout sponsor generated by a decrease in the cost of debt and suggest that PE firms should repeatedly interact with banks to maintain relationships and offer cross-selling opportunities to reduce the credit spread for their investee firms. Their finding that lower costs of debt increase the return on equity (all else being equal) is consistent with standard theory on capital structuring decisions. Axelson et al. (2013), however, cannot replicate the results of Demiroglu and James (2010) or of Ivashina and Kovner (2011) with their sample of 1,157 buyouts in developed economies. Instead, they conclude that the pricing of buyout transactions is cyclical and driven by the cost of debt. High deal leverage is associated with higher transaction prices and lower equity returns suggesting that acquirers overpay when access to debt is easy. Nevertheless, access to debt financing is more restricted in emerging countries and the cost of debt is generally higher. The conclusions drawn in Lopez-de-Silanes (2015) therefore seem to better explain emerging countries lower PE returns. Taussig (2011) addresses the liability of foreignness of investors who participate in emerging market PE transactions. He argues that foreignness could cause investors to be discriminated against by local market participants and regulators or to be at an information disadvantage when 7

10 investing in emerging country target firms. Nevertheless, the setting changes on exit when foreign PE investors are able to benefit from their international networks and reputations to sell stakes in companies from countries with weaker formal contracting institutions. In this context, positive institutional change during an investment s holding period should reduce acquirers concerns about buying from local PE firms, thus reducing the competitive advantage of foreign PE funds. Returns on investment of internationally acting PE funds should thus be negatively affected by improvements in formal contracting institutions in low enforcement countries. Taussig (2011) receives support for this claim by running multivariate analyses on 267 PE transactions in emerging countries originating from OECD countries. Chemmanur et al. (2014) add to the research on the liability of PE investors foreignness. They find that syndicates composed of international and local investors are more successful than syndicates of either exclusively international or exclusively local funds. Both groups of investors have comparative disadvantages: international PE firms lack proximity but local funds might have less investment experience. The benefits of mixed syndicates are stronger in emerging regions, which is consistent with the notion that difficulties in monitoring and deficiencies in local knowledge faced by international investors are more severe in these regions. Reddy and Blenman (2015) analyze LBO transactions in different investee growth phases and compare developed and developing economies. They find that financial sponsors achieve higher average returns on transactions in developed countries. However, in periods of strong economic growth, the returns are higher in emerging economies. This paper contributes to the existing literature by focusing on the socio-economic determinants of the internal rates of return of emerging market PE transactions. To do this, I use 8

11 the most comprehensive and accurate data set on emerging market PE transactions used in academic research to date. This replicates some of the above findings but also provides additional evidence on the existence of a timing effect in emerging PE markets. I use a detailed mapping of the entry order in every country covered by the data set to reveal that pioneers do not earn superior returns. Instead, the performance of emerging market PE transactions increases over time. I argue that this increase in investor return can be attributed to learning and to improvements in the deal-making environment. The learning speed is higher for GPs who are located inside the target country rather than abroad. However, learning cannot be kept proprietary because later entrants also earn higher returns as time elapses following the pioneer s entry. Followers therefore benefit from waiting for the deal-making environment to improve. I conclude that it is not necessary to enter early into untapped PE markets. 2. Development of Hypotheses The pioneering emerging market PE investor is exposed to particular risks and deal-making constraints. The market may lack deal-supporting infrastructure such as investment banks, law firms, consultants, and accountants specialized in PE-related issues. Furthermore, while the pioneering funds investment managers may have substantial experience in advanced PE markets, such as North America or Western Europe, this knowledge may be of little value in geographically and culturally distant locations because of differences in the way business is conducted. Additionally, managers and employees of local investee firms may have no experience of these new investors and their governance structures. All market participants therefore need to gain experience. I hypothesize that the success of emerging market PE transactions rises over time due to learning effects. This contradicts the hypothesis of first-mover 9

12 advantages: if there were first-mover advantages, e.g. because the pioneers gain access to untapped, superior-quality deal flow, then earlier transactions should be more successful than later ones. I further hypothesize that building up emerging market PE experience requires local presence. Differences in deal-making conditions between developed and emerging markets might be too large for investors to gain experience without geographical proximity to the investee firms. Making deals from distant locations or across borders therefore diminishes learning effects. In parallel to the first hypothesis, I assume that PE is a financial intermediary relationship requiring a level of development not necessarily reached in many of the emerging countries. Certain socio-economic characteristics need to be present for a PE market to be successfully established. As these characteristics advance, PE deal making becomes more successful. Emerging countries typically improve these characteristics during their socio-economic development. However, once again, this takes time and I therefore hypothesize that PE deal making depends not only on learning, and on investor or investee-specific determinants, but also on the socio-economic environment in the emerging host country: the more developed the environment, the more successful PE transactions will be. Despite the potentially less favorable deal-making conditions in emerging countries compared to developed countries, the developing markets have one major advantage: their expected economic catch-up potential. The most important rationale for emerging market PE investments is the anticipation of strong GDP growth considerably in excess of that of developed countries. The high economic growth rates may even compensate for deal-making obstacles, such as the lack of deal-supporting infrastructure or mature socio-economic conditions. In any case, I 10

13 hypothesize that economic growth rates strongly affect the success of emerging market PE transactions. I finally assume that even if economic growth is one of the expected drivers of success, the deals still underlie the typical market conditions. These conditions are valuation multiples, financing costs, and exit market liquidity. I therefore hypothesize that emerging market experience, GDP growth, and socio-economic factors are not the only elements that shape investor returns: additional determinants such as stock market valuations, the cost of debt, and exit market liquidity also affect successful PE deal making. I address each of these hypotheses below. 3. Data Set and Descriptive Statistics A. General Sample Characteristics and Dependent Variable The sample is based on 1,655 emerging market PE transactions collected from Private Placement Memoranda (PPMs) and extracted from the data used in Lopez-de-Silanes et al. (2015). The dataset offers a broad pool of variables describing each individual investment. Unfortunately, some data records are incomplete meaning that several transactions need to be removed. The most important information for our purpose is the timing of the transaction, the host country of the target, and the transaction s success expressed by the internal rate of return (IRR) of the underlying cash flow stream. The IRRs are gathered gross of management fees and are therefore comparable across time, countries, and general partners. Unfortunately, not all of the transactions had exited at the time the dataset was created. I therefore have to rely on reported net 11

14 asset values to assess these IRRs, which creates uncertainty with respect to the real returns ultimately earned in these transactions. The proportion of reported net asset values in our sample naturally falls with older funds vintage years. As a consequence, I observe more reported net asset values for the deals at the end of the sampling period. Brown et al. (2014) and Jenkinson et al. (2013) find that reported net asset values are generally conservative. Hence, any bias induced by reported net asset values works towards my finding that later emerging market PE transactions outperform earlier ones. Since this paper focuses on emerging PE markets I pay particular attention to the fact that several of the sample countries developed to an advanced state during the observation period. I refer to the IMF definition of emerging and advanced economies and further discard transactions that closed after the host country s status changed from emerging to advanced. This reduces the number of real emerging market PE transactions to 1, The sample comprises investments in 86 host countries by 73 different general partners between 1973 and 2009 with exit/reporting dates ranging from 1975 to 2009 and durations from one month up to 18.5 years. Table 1 presents these primary sample characteristics. ============ Insert Table 1 here ============ The table shows the representativeness of our sample in terms of geography, closing and exit timing, and transaction duration. Nevertheless, it seems that some countries, e.g. Poland or South 2 Specifically, I discard transactions in the Czech Republic with a closing date after 2008, in Hong Kong after 1997, in Singapore after 1997, in Slovakia after 2008, in Slovenia after 2006, in South Korea after 1997, and in Taiwan after

15 Africa, are over-represented. This potential over-representation will be addressed in robustness checks. The timing information for individual deals is given to monthly accuracy suggesting that the month end can be used as the settlement date for all benchmark comparisons. However, for some transactions, no information on the closing or exit month is given. For these cases, I use June, 30 of the closing/exit year as the reference date for all benchmark calculations. Figure 1 presents the distribution of the transaction closing dates in the sample. It reveals that the bulk of the transactions were made after Several deals were closed earlier, but exclusively in Hong Kong. ============ Insert Figure 1 here ============ The origins of the investors are not as broadly diversified as the host countries of the investees. This corresponds to the typical pattern of emerging market PE transactions being originated in financial centers. Almost 50% of our sample transactions are sponsored by general partners based in the US. 11% are undertaken by UK GPs. Other hubs in Poland, Finland, the Netherlands, the Czech Republic, the Russian Federation, and Greece serve the PE markets in Central and Southeastern Europe and in the Commonwealth of Independent States (for approximately 16% of our sample transactions). GPs from financial centers in China, India, Hong Kong, and Malaysia provide financing for 10% of the transactions, mainly in Southeast Asian markets. South Africa serves as a hub for 108 African transactions and Argentina and Brazil for 49 Latin American deals, representing approximately 9% and 4% of the sample, respectively. From this geographic distribution of investor locations, I observe that 73% of the transactions are 13

16 cross-border while 27% are local deals, i.e. emerging country investors investing in their own country s investees. The paper focuses on the development of PE returns across countries and over time. The most important information is therefore the annualized gross internal rate or return (Gross IRR) of each individual transaction as disclosed in the PPM. It is the dependent variable in most of our analyses. The IRR is calculated from a USD investor s point of view in most of the PPMs. However, in several of the transactions the IRR has been calculated in EUR, GPB, YPN, or ZAR. I convert these returns into USD IRRs by correcting for cross currency rate changes between closing and exit. A few transactions yielded extraordinary high returns, beyond conventional levels. To correct for these outliers, I winsorize the IRR distribution at the 95-percentile and present it in Figure 2. Table 2 provides a breakdown of these IRRs (in USD) by investment host country. ============ Insert Figure 2 and Table 2 here ============ The mean (winsorized) IRR of the 1,157 transactions is 18.8% and their median is 15.1%. The upper limit of the (winsorized) IRRs is 148%, while some transactions wiped out the invested capital. The right-skewed distribution is typical for returns in the PE asset class. Mean comparisons tests reveal at high levels of significance (all levels below 0.01) that cross-border deals yield IRRs 13% lower than national deals, that US-sourced transactions return 23% less vs. sourcing in other countries, and that earlier transactions (split at the median level of entry in the sample) yield a 10% lower IRR than subsequent deals. 14

17 The industry classifications of the sample transactions follow Fama and French (1997). I identify 47 different industries. Approximately 14% of the investments were made in companies in Trading industries and 11% in Communications. The remainder of the sample is broadly diversified along the industry spectrum. For 11 transactions, I do not have information about the investee firms industry and treat the transactions as others/unknown. The industry segmentation of the sample is presented in Table 3. ============ Insert Table 3 here ============ B. Independent and Control Variables I collect several independent and control variables. Most importantly, the key variable of interest is a proxy for the experience that investors have in the various countries. Since I have no detailed information about the sponsors at the time of the transactions, e.g. their team s emerging market experience or their tenure/experience in general, I refer to simple proxies that can be determined from my own data collection. The first stylized measure for experience in a particular country uses our sample s first transaction entry date: the pioneering observation in every investment host country sets the cut-off entry date and all subsequent transactions are related to this date. The key variable (1) Time Since the 1 st Investment in the Host Country is the difference between the closing dates of a particular transaction and the pioneering transaction in the same country. Obviously, for the initial transactions in every country this variable has a value of zero. This proxy therefore captures the experience that the overall investment community has in an individual country. It can also be interpreted from another perspective: it serves as a proxy 15

18 for the development and state of the PE market and characterizes the awareness of the asset class in a country s society and professional investment community. However, the variable needs to be interpreted with some caution because I am unable to verify whether the first observation is indeed the pioneering deal in a particular country. The proxy might therefore be biased towards values that are too small. I address this concern in robustness checks. The second alternative experience measure focuses directly on the investors. Variable (2), GP's Experience in the Host Country, assesses the knowledge a particular general partner (GP) has gained in the respective country, independent of all other market participants. Its definition is similar to the primary key variable: the first transaction of a general partner in a particular country sets the offset date for the general partner in that country. All of the general partner s subsequent transactions in the same country are related to this date. The measure is the difference between the closing date of any of a general partner s transactions and the closing date of its first deal in the country. Since every general partner can invest in several countries, the variable takes a value of zero more often than the primary key variable. However, this variable does not have a potential bias caused by failing to observe the pioneering investment. GPs report their complete track records in PPMs. Thus, I should have collected the correct entry dates in a particular country for every GP. ============ Insert Table 4 here ============ Table 4 presents the key measures of experience and all other independent and control variables that I use in my multivariate analyses. Public stock markets have an important signaling 16

19 effect for unquoted equity markets. PE investors usually use public peer group multiples when valuing unquoted investees. Stock market valuations therefore strongly drive target values and, hence, the returns of PE transactions (Lopez de Silanes et al., 2015). However, it is not clear which stock markets serve to determine peer group valuations for emerging market PE transactions. Market participants could either refer to peers traded in the U.S. or locally. Variable (3), the time-matching S&P 500 return, is therefore used to determine the benchmark return if valuations follow U.S. peers and variable (4), the time-matching local or regional stock market return, determines the public market equivalent return if peers are selected from local (emerging) stock markets. However, several of the investee host-countries do/did not (at transaction date) have a public stock market or a representative benchmark index. For these countries, I refer to close neighbors or regionally representative indices to determine the alternative benchmark returns. Table 5 lists all the emerging market benchmark indices that I consider and provides information on how often they serve as the benchmark and which alternative indices are used. ============ Insert Table 5 here ============ Variable (5), (of Table 4) the time-matching S&P 500 return in local currency, and variable (6), the time-matching local or regional stock market return in local currency, are based on variables (3) and (4), but converted to benchmark returns in local (emerging market) currencies. They are used in a robustness check that examines whether the detected effects result from currency exchange rate fluctuations between USD and emerging country currencies over the transaction holding periods. 17

20 Variable (7), time-matching GDP growth, measures the real growth of the gross domestic product in the investment host country over the holding period of the transaction. The GDP growth is annualized and extrapolated according to the exact (month-end) closing and exit days. Variable (8), the aggregated IPO proceeds in the investment host country in the year of exit, captures the liquidity of the exit market at the time of divestment. Several countries do not have public stock markets/ipo activity and hence have zero proceeds. Variable (9), the host country s global innovation index, is an indicator assessing countries innovative capacity. Variable (10), the quality of the host country s educational system, controls for the available human capital in the country. Variable (11), the host country s interest rate spread in the year of closing, is a proxy for access to debt and debt financing cost at origination. Variable (12), the difficulty of firing index, is a doing business indicator that assesses labor market frictions and the ability of investors to implement new strategies during their holding period. Variable (13), the host country s Property Rights Index, controls for legal quality in the investee country. Variable (14) is a dummy signaling whether a PE fund s headquarters are in the U.S. and variable (15) is another dummy indicating a cross-border transaction, i.e. the GP and investee firm are not located in the same country. The number of GPs in other fund locations in our sample is too small to distinguish further. Variables (9), (10), (12), and (13) are often not available for years prior to 2000 and do not change meaningfully over time. I therefore consider them time-invariant and use their 2009 values. All other variables either match the duration of the sample transactions or correspond to the entry or exit/reporting year observation. Table 6 presents the descriptive statistics of our independent and control variables. 18

21 ============ Insert Table 6 here ============ From Table 6, I observe that the mean and median IRRs in local currencies are slightly higher than those calculated in USD. This is the same for the variables measuring public market equivalent returns in USD and in local currencies, i.e. variables (3) and (5) and variables (4) and (6). This signals, on average, that the emerging market currencies depreciated against the USD. The relatively small public market equivalent returns of the S&P 500 index can be explained by the observation period. As presented in Figure 1, most of our sample transactions were closed after the index peaked in 2000 and accordingly have negative benchmark returns. The other variables exhibit rather intuitive distributions. ============ Insert Table 7 here ============ Table 7 shows the correlation matrix of all independent and control variables. It reveals a high correlation (0.61) between the two experience measures, and relatively high negative correlations (-0.3 and -0.42) between the S&P 500 benchmark returns (in USD) and the two experience measures. The correlations are equally high (-0.41 and -0.31) if the S&P 500 benchmark returns are calculated in local currencies. I therefore use each experience measure exclusively (as one possible alternative) throughout the regression specifications and analyze the impact of the stock 19

22 market indices in a separate robustness check. All other independent and control variables are introduced stepwise to rule out any multicolinearity concerns. Unexpectedly, the time-matching emerging stock market benchmark returns only correlate weakly with the S&P 500 public market equivalents (variable pairs [3] with [4] and [5] with [6]). I would have expected a stronger globalization effect for the public equity markets. The high correlations between (3) and (5) and between variables (4) and (6) reveal that, on average, cross currency rate changes do not meaningfully affect the benchmark returns. 4. Multivariate Analyses I address my hypotheses with several stepwise OLS regressions. The independent variable is always the winsorized IRR of the sample transactions either calculated in USD or in local currencies. All standard errors are robust. a. PE Returns from the USD Investor Perspective In the first specification in Table 8, Panel A I regress the winsorized IRR in USD on the experience measure Time Since the 1 st Investment in the Host Country, a constant, and controls including country, GP, industry fixed effects, and the legal quality indicator. Time fixed effects cannot be added because they correlate with the experience measure and drive the variance inflation factors of the models to unacceptable levels. The number of observations is 1,157 and the adjusted R 2 is 22.74%. The coefficient of the independent variable in the first line of Table 8 is and is statistically significant at the 1% level. The second line (0.119) represents the standardized 20

23 parameter coefficient, i.e. the estimate if all variables are transferred into their z-scores. The third line [0.005] is the estimate s standard error. ============ Insert Table 8 here ============ The economic magnitude of the parameter estimate can be interpreted as follows. Every year of waiting until a transaction has been closed pushes up the IRR by an average of 1.3 percentage points. This effect is strong and meaningful for investors and I attribute it to two factors. The first is the experience that market participants gained in the particular emerging country. The second is the simple result of further developments in the deal-making conditions that facilitate PE transactions in the country. Specifications B to E add independent variables and alter the set of control variables. In specification B, I include the transaction period-matching S&P 500 benchmark return as independent variable. As expected, the global stock market benchmark has a strong impact on valuations in the non-quoted emerging markets and hence, on the PE returns. A 1% increase in the benchmark return over the holding period increases the transactions returns by an average of 1.15%-points. The standardized parameter coefficient (0.273) is slightly larger than that of our experience measure, signaling that the public stock market has a stronger effect on PE performance than the experience measure. The adjusted R 2 of this regression increases from 22.74% to 26.55% compared to specification A. 21

24 Specification C adds the transaction time-matching local benchmark return as independent variable. Its parameter is significant at the 1% level, indicating that investors refer not only to the U.S. to determine valuation multiples, but also to local stock markets. Alternatively, one could argue that the local stock market indices provide more appropriate information about the local economic conditions than the S&P 500 index. However, the local benchmarks standardized coefficient is smaller than that of the other variables, suggesting that the local benchmark returns have less impact on emerging market PE returns than experience or the S&P 500 levels. It is furthermore surprising that both variables respectively gain or maintain significance in this and the subsequent regressions rather than cancelling each other out. I assume that controlling for the standard benchmark index performance (i.e. the S&P 500 index) is sufficient to explain emerging market PE returns, and therefore address the impact of the benchmark indices and potential multicolinearity in a separate robustness check. From specification D onwards, country specific properties are included and country fixed effects are dropped to avoid multicolinearity. The first country-specific characteristic is the holding period matching real GDP growth. This decreases the adjusted R 2 from 26.94% to 22.66%, compared to specification C. The regression reveals that the GDP growth s parameter coefficient is significant at the 1% level. Economic growth is the underlying source of value creation in the investee corporations and therefore strongly drives transaction return. The impact of GDP growth is substantial. A 1%-point increase in real GDP growth improves the average transaction performance by 2.5%-points. 22

25 Specification E adds the IPO proceeds in the country in the transaction s exit year to the set of independent variables. The coefficient for the proxy of exit market liquidity is significant at the 1% level and highlights its importance for the asset class. Regression specification F of Table 8, Panel B also includes the proxy for innovation capacity and the dummy variable for the general partners location in the U.S. At the same time, the funds fixed effects are dropped because of their colinearity with the U.S. fund location dummy. The coefficient of the Global Innovation Index is significant at the 1% level and highlights the importance of technological innovations for emerging market PE returns. At the same time, the fund location dummy has a strong and significant negative coefficient. Since this dummy variable also resembles a geographic distance parameter (all other transactions are managed at closer distances), this signals that locally (or closer to the investee countries) managed emerging market PE portfolios yielded higher returns. From regression F, I conclude that, on average, portfolios managed from the U.S. generated 9.9% lower returns for their investors, all else being equal. The reference group is all other general partners, either directly located in emerging markets or closer to them. I use the alternative experience measure GP s Experience in the Host Country in regressions G and H, which produce statistically and economically less powerful results, revealed by smaller standardized coefficients and larger standard errors. However, I interpret the consistently positive significant parameter coefficients as evidence of the learning effects that general partners have after the entry into a particular emerging country. They gain experience and benefit from delaying their investments because of improving deal-making conditions. Nevertheless, the experience gained cannot be kept proprietary as demonstrated by the above analyses using the 23

26 alternative key variable Time Since the 1 st Investment in the Host Country, which measures the experience and waiting benefits to all participants. All players in emerging PE markets benefit from additional experience and improving deal-making conditions. Furthermore, I add the quality of education in the host country in specification G. The parameter s coefficient is significant at the 10% level. This highlights the importance of human capital for this asset class. Countries with higher education quality are ultimately better suited to generating appropriate PE investee firms. Regression H also includes the host country s interest rate spread at transaction closing and its difficulty of firing index. Unfortunately, this reduces the number of observations by 49 because the two indicators are not available for a number of countries. Both parameters have significant negative coefficients. First, this provides evidence that the cost of debt affects PE returns in the expected direction for emerging markets. Second, the implementation of strategic changes is less likely to be successful in host countries with higher labor market frictions. However, including the two additional variables (or only one of them) cancels out the quality of the educational system indicator. b. PE Returns from the Local Investor Perspective As fundraising documents, PPMs usually address the international investment community and are edited using USD as the reference currency. This is also valid for my sample, with a few exceptions where the reference currency is EUR, GBP, YPN, or ZAR. Regardless of the reference currency chosen, the reported IRRs might be affected by exchange rate changes between the reference currency and the local (emerging country) currency. I recall that value 24

27 creation (or destruction) happens at the level of the investee firm. Using foreign multiples to benchmark transactions and foreign currencies to settle them imposes additional variability and a potential bias in reported IRRs. I therefore also calculate all IRRs and all detected parameters from a local investor perspective and rerun the regressions described above. Table 9 presents the four most important regressions using IRRs and the benchmark returns in local (emerging market) currencies. ============ Insert Table 9 here ============ Specification I from Table 9 regresses the transactions winsorized IRRs in local (emerging market) currencies on the experience measure, on the time-matching S&P 500 and the timematching local stock market return, both also converted into local currencies, on the controls for country, fund, industry and legal quality, and on a constant. Specification J adds time-matching GDP growth, the countries aggregated IPO proceeds in the exit year, the global innovation index score, and the GP headquarter dummy for the U.S. At the same time, country and GP fixed effects are dropped. Regressions K and L use the alternative experience measure and add the quality of the emerging country s educational system (in K) and its difficulty of firing index (in L). Again, including the difficulty of firing index reduces the number of observations to 1,108. The four regressions provide evidence that the implications detected are not affected by cross currency rate changes. All parameter coefficients retain their significance, their sign, and their economic magnitude if the determinants are converted to local currencies. The most important 25

28 result is that the IRRs of the emerging market PE transactions did not improve over time as a result of their currencies appreciating against the USD; instead, the IRRs rose because of the experience that investors gained respectively due to improving deal-making conditions. c. GP Location and Learning Effects Next, I analyze the impact of geographical and cultural distance in emerging market PE transactions on the learning curve. As hypothesized above, the positive effects of gaining experience in emerging market PE deal making may be smaller without local GP presence. There may be large differences in the way PE business is conducted in developed countries, where most of the GPs of the sample are located, compared to the investment host countries, which may cause difficulties for investors who struggle to gain experience without local presence. I therefore introduce a proxy for geographic and cultural distance between the investor and the investee, a dummy variable that is equal to one if the GP and the target firm are not in the same country, i.e. if a particular deal is a cross-border transaction. When including this dummy in the regressions, I need to discard variables causing multicolinearity, i.e. GP fixed effects and host country fixed effects. The rationale is simple: several GPs only do cross-border deals and, similarly, many countries only receive PE funding from external locations. ============ Insert Table 10 here ============ 26

29 Panel A of Table 10 presents regressions equivalent to those presented in Table 8, Panel A, but adds a dummy variable that indicates cross-border transactions and its interaction term with Time Since the 1 st Investment in the Host Country. The dependent variable is always the winsorized IRR of the PE transactions from a USD investor's point of view. Standard errors are robust. Specification M regresses the dependent variable on investee industry fixed effects, the legal quality indicator, and the cross-border deal dummy variable. It reveals that the IRRs of cross-border deals are 11.6% below nationally originated transactions. Specification N shows that the learning effect remains if we control for cross-border transactions. In specification O, I add the interaction term between the first two variables. The cross-border dummy itself is no longer significant but the negative parameter of the interaction term provides evidence that the learning benefit diminishes in cross-border transactions. The remaining specifications support the robustness of the previous results. In Panel B of Table 10, I use the alternative experience measure GP s Experience in the Host County and its interaction term with cross-border transactions as the main independent variables. The regressions R to U reveal that GPs should stay local to benefit most from learning how to perform emerging market PE transactions. The economic and statistical significance of the interaction term is stronger than that obtained using the key variable Time since the 1 st Investment in the Host Country. d. Robustness of the Results The results could be affected by a non-representative sample of emerging market transactions or be exposed to correlating covariates. I run therefore a series of robustness checks to reveal that this is not the case. 27