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Ownership Concentration and Corporate Performance: New Evidence from the Budapest Stock Exchange* John S. Earle Central European University and Upjohn Institute for Employment Research Csaba Kucsera Loránd Eötvös University Budapest and Central European University Álmos Telegdy Budapest University of Economic Sciences and Central European University May 2002 Abstract Panel data on Hungarian firms listed on the Budapest Stock Exchange (BSE) provide an opportunity to estimate the effects of alternative measures of ownership concentration on firm performance. As in other continental European economies, ownership on the BSE is highly concentrated: the median shareholding is 40% for the largest owner and 61% for all 5% or greater blockholders. The proportion of shares held by the largest blockholder is estimated to increase performance strongly, with coefficients of 0.294 for return on assets and 0.942 for operating efficiency. When concentration is measured as the shareholding of multiple blockholders, the estimated effects are much smaller and statistically insignificant. The evidence suggests that the marginal costs of concentration may outweigh the benefits when the additional concentration is achieved through multiple blockholders rather than a single large block. This paper was written with support from the European Community’s Phare ACE Program 1998. Part of the ownership data collection was supported by the Phare ACE Program through the European Corporate Governance Network. The content of the paper is the sole responsibility of the authors and it in no way represents the views of the Commission or its services. * 1. Introduction The effects of ownership concentration on firm performance are theoretically complex and empirically ambiguous. Conceptually, concentrated ownership may improve performance through increased monitoring and alignment of incentives (e.g., Shleifer and Vishny, 1986), but other mechanisms may work in the opposite direction. As discussed by Wruck (1989), Barclay and Holderness (1989) and Shleifer and Vishny (1997), large shareholders may exercise their control rights to create private benefits, sometimes expropriating smaller investors. Moreover, fear of expropriation may limit the ability of firms with high ownership concentration to raise fresh finance through borrowing or new share offerings. Takeovers may become more costly for raiders to carry out when ownership is highly concentrated, due to the smaller fraction of liquid shares available to establish a "toehold," thus reducing the strength of this disciplinary device. The reduced liquidity lowers the utility of the firm's share price as a measure of managerial performance. Finally, none of these effects may matter if ownership structure tends to be optimally adjusted to firm characteristics, in which case, as argued by Demsetz (1983), there may be no relationship with performance whatsoever. Empirical studies of the firm performance-ownership concentration relationship have also produced mixed results. Among studies of the U.S., Demsetz and Lehn (1985) find no effect of concentration on accounting profits, and McConnell and Servaes (1990) find no effect on Tobin's Q (although they do find a positive effect of ownership by corporate insiders and by institutional investors). On the other hand, Wruck (1989) reports that private sales of blocks of shares, associated with increasing concentration, have an effect, although one that is nonmonotonic, on abnormal market returns. Similarly to Morck, Shleifer, and Vishny's (1988) analysis of managerial ownership, she finds that returns are increasing in concentration when concentration is low, they are decreasing when concentration is moderate, and they are again increasing at higher levels; as the coefficient for low concentration is statistically insignificant, this suggests a roughly U-shaped relationship. An interpretation of these results is that the negative effects of concentration outweigh the positive effects over some ranges of the level of concentration.1 1 Studies of non-U.S. economies also produce mixed results. For the U.K., Leech and Leahy (1991) report inconsistent findings, including a negative relationship when performance is measured as profitability, while Gorton and Schmid (2000) find that concentration increases the market-to-book ratio and returns to assets in Germany, although only the former result is statistically significant. For Japanese firms, Prowse (1992) finds no relationship, linear or nonlinear, between profitability and ownership concentration, while Claessens and Djankov (1999) find an inverse U-shaped relationship in the Czech Republic. 1 In this paper, we argue that an important issue in these studies, albeit one that has received relatively little attention, concerns the implications of alternative measures of ownership concentration. Most empirical research has followed Demsetz and Lehn (1985) in measuring concentration with respect to a group of owners, usually as the total equity share held by the largest five or largest 20 investors. Zwiebel (1995) has provided some indirect theoretical justification for this measure by suggesting that a large owner will tend to "create its own space," discouraging other blockholdings from forming, while in the absence of a large owner smaller shareholders may form coalitions to exercise joint control; this implies that a measure of the shareholdings of the group of largest blockholders captures either possibility. But it also stands to reason that small blockholders may face collective action problems and they may even quarrel, due to differing interests or conflicting views of corporate strategy. In the presence of a large owner, the marginal contributions to managerial monitoring of additional blockholders may be low, and they may serve only to increase costs of concentration by reducing liquidity. If the additional blockholders do not produce net benefits, then the inclusion of their shareholdings serves only to add measurement error to the concentration variable, thus reducing the magnitude of the estimated performance effect and increasing the estimated standard error. Thus, the estimated effect of concentration on performance may depend crucially on how blockholders interact with another one and on the measure of concentration employed in the analysis, the lack of attention to which could explain, at least partially, the conflicting findings of previous studies. We address these issues drawing on data from Hungary, an economy which has, as we show, a high average ownership concentration that is typical of Continental Europe and much of the non-Anglo-American economies , as shown by LaPorta, Lopez-de-Silanes, and Shleifer (1999). Around this high average, we observe cases of quite dispersed as well as extremely concentrated ownership. Contrary to Zwiebel's (1995) predictions, large blockholdings often co-exist within a single firm. Our empirical strategy involves the estimation of fixed-effect panel regressions of return on assets and operating efficiency on various measures of ownership concentration using all firms traded on the Budapest Stock Exchange (BSE) between 1996 and 2000. These within-estimators compare the effect of an increase in the largest shareholding with an increase in the shareholding of all blockholders, as well as some intermediate cases. We find that only the largest shareholding has a positive, statistically significant effect on corporate performance, while other blockholdings have coefficients that are statistically insignificant and usually negative; the sum of all blockholdings (the traditional measure in such studies) has effects that are estimated to be positive, but they are 2 always statistically insignificant and smaller in magnitude than that of the largest blockholder. The data show no evidence of nonmonotonicities in the performance-concentration relationship, and indeed there is some evidence that the marginal impact of the largest blockholding increases slightly as the blockholding rises. We conclude that the data strongly support the view that agency problems are reduced by ownership concentration – when concentration refers to the largest blockholder – but they provide no evidence that small blockholder cooperation can substitute for a single dominant shareholder, and they provide some suggestion that additional blockholdings actually tend to reduce value, possibly due to quarreling among blockholders and possibly by making the firm's shares less liquid. 2. Data Description and Estimation Framework This study analyzes official data published by the BSE (Budapest Stock Exchange and Bank & Tőzsde, 1996 – 2000). These data supply basic financial information for all listed firms as well as information on the direct blockholders of the firms (any owner possessing more than five percent of the company's shares). One shortcoming of our database, however, is that it has information only on direct holdings.2 The lack of indirect holdings may create a systematic downward bias of our measures of ownership concentration. The ownership information pertains to May in 1996 and 2000, and June for the other years. As we want to estimate the effect of the concentration on firm performance, which we measure as the year-on-year growth in two indicators, as described below, for consistency we define the ownership variables as the average across years t and t-1. Our first measure of concentration is the percent held by the largest blockholder (C1). Second, we add up the holdings of the largest and the second largest blockholder (C2), then we sum up the holdings of the three largest blockholders (C3). Our last measure of ownership concentration is very similar to that used in many of the earlier literature: the sum of all blockholders (Call). Since the ownership structure of the firms on the BSE is very concentrated, this is almost identical with the joint holdings of the largest five owners. 3 Table 1 presents the basic statistics for these variables.4 On average, the largest blockholder owns at the median 42 percent of the shares in the period of 1996 – 2000. The data reveal that there is 2 The legislation obliging owners to disclose indirect holdings was adapted only in 2001, and thus this information is not available for earlier years. 3 The structure of ownership is highly concentrated, as we show below, and even the fourth largest owner has very small or zero holdings: 30 – 34 companies do not have a fourth blockholder and the average holding of the fourth blockholder is 1.5 – 2.6 percent (zero holdings included). 3 substantial variation across firms in ownership concentration: despite the large mean and median, the minimum value for the largest owner's holding is 0 (that is, there are firms in which no owner holds at least five percent of the shares), and the maximum value is 74 – 84 percent, depending on the year studied. By contrast with Zwiebel's (1995) predictions concerning ownership structure, we find that the second largest blockholder also tends to have a large stake: 13.5 percent at the mean and 13.7 at the median. And the third is also not tiny, with 4.8 at the mean, and 7.0 at the median. Smaller blockholders tend to be much smaller, however, so there is little difference between C3 and Call. For all these variables, there is a substantial range across firms. This variation is useful for testing the relation between the concentration and firm performance. Insert Table 1 about here. The figures suggest strong similarity between the Hungarian listed firms and their counterparts from other continental European stock exchanges. Indeed, at the median, the largest voting block is around 50 percent in a number of European countries (Austria, Belgium, Germany, Italy), while it is only 9.9 percent for the United Kingdom and under 5 percent for the New York Stock Exchange (Becht and Röell, 1999).5 Claessens and Djankov (1999) show that the top five owners possess 68.4 percent in the Czech Republic. Telegdy et al (2002) report the joint holding of all blockholders for the firms on the Bucharest Stock Exchange at around 70 percent. In general, the volume of trading is low on the BSE, as in most continental European stock exchanges, and we do not believe that the share prices bear much correspondence to the true firm value, at least not for all listed firms, because many of them are only thinly traded. Table 2 contains the descriptive statistics for the measures of corporate performance we do study, the dependent variables in our equations. Return on assets (ROA) is defined as the ratio between profit and equity, while operating efficiency (OE) is the ratio of real sales to the number of employees. In both cases, we analyze the growth rather than levels; for ROA this is the simple difference ROAt - ROAt-1, while for OE it is log(OEt/OEt-1).6 Insert Table 2 about here. The table also presents summary statistics for the lagged level of performance and 4 The statistics of ownership concentration (and of the variables presented in the next table) do not differ much across years. To save space, we present them for the whole panel, thus, the unit of observation in these tables is firm-year. 5 Other studies gathering evidence on the presence of blockholders are La Porta, Lopes-De-Silanes and Shleifer (1999) for 27 industrialized countries and Claessens, Djankov and Lang (2000) on nine East Asian countries. 6 ROA is sometimes negative, and it is already measured in proportional units. We do not compute OE for the banking and finance sector because of difficulty of measuring sales for these firms. 4 employment size. ROA changed little on average during this period, although the standard deviation is substantial. OE grew rapidly, an average of 16 percentage points, again with a substantial standard deviation. The employment figures document that Hungarian listed firms tend to be large, with a mean employment level over 2400. We employ fixed-effects regression methods to eliminate any bias resulting from a permanent quality difference across firms that could be correlated with ownership structure.7 The regression equation is the following: Perfit = β0 + β1Cit + β2Perfit-1 + β3Empit-1 + tYeart + i + it, where Perfit is either ROA or OE, Ci,t measures the concentration of the firm's i ownership concentration in year t in several alternative specifications, as discussed earlier in this section. In each of our regressions, we control for the lagged level of performance, lagged employment, and year effects. 3. Regression Results We start with the results for the summary measures of concentration C1, C2, C3, and Call, shown in Table 3. The largest blockholding, C1, is estimated to have a large, positive impact on growth in both ROE and OE, both effects statistically significant at the one percent level. Insert Table 3 about here. On the other hand, the point estimate for the coefficient on C2 is much smaller in both equations, and it is statistically insignificant for ROA and only significant at the five percent level for OE. The coefficients on C3 and Call shrink still further, and neither of them are statistically significant for either dependent variable. At the same time, the standard error is roughly constant for all concentration measures. These results are inconsistent with the view that blockholders are easily able to form coalitions to monitor management. They are consistent with the hypothesis that only the top blockholder matters and that including additional blockholders into a broader measure of concentration not only introduces noise into the concentration measure, which would diminish the coefficient and increase its standard error. The fact that the standard error does not increase suggests that the additional blockholders actually have a negative effect on performance. To explore the last point more fully, Table 4 reports the results from disaggregating the shareholdings of the three largest blockholders and including them separately in the equations. Consistent with our findings for C2 and C3, the second and third largest 5 blockholders have negative point estimates for their effects on corporate performance, although the coefficients are not statistically significant. Furthermore, the additional blockholdings are even estimated to diminish the positive effects of the largest shareholding. These results are consistent with the view that additional blockholdings, beyond the largest, reduce firm performance. As we have discussed, this may occur if these additional blockholders are active, and they quarrel with the largest blockholder. It may also occur if they are passive but their presence reduces the liquidity of the firm's shares on the market, which decreases the informational value of the share price and increases the cost of a takeover, in both cases reducing the effectiveness of these disciplinary devices. Insert Table 4 about here. Finally, we consider the possibility that concentration works differently in situations when the largest blockholder is very large from when it is less dominant. For instance, if the largest blockholder has a majority stake, then additional blockholders may function only to create annoyances and reduce liquidity, but they seem unlikely to contribute to further monitoring of management. On the other hand, if the largest blockholder holds only a minority stake, then perhaps the additional blockholders would contribute to monitoring and for a given size of the largest blockholder, they would soak up less of the firm's share liquidity. The first situation corresponds to Zwiebel's (1995) picture of a dominant shareholder "creating its own space," while the second corresponds to his view of coalitions of smaller blockholders cooperating in the absence of a single dominant investor. To examine this possibility, we re-estimate the equations including both C1 and Call C1, interacting both with a dummy variable D1 = 1 if C1 > 50 and 0 otherwise. Thus, the equation is as follows: Perfit = β0 + γ1C1itD1it+ γ2(Call,it-C1it)D1it+ γ3 C1it(1-D1it) + γ4(Call,it-C1it)(1-D1it) + β2Perfit-1 + β3Empit-1 + tYeart + i + it, where γ1 > 0, γ2 = 0, γ3 = 0, and γ4 > 0 would suggest a regime switch associated with the largest blockholder's share passing some threshold. Table 5 contains the estimation results. We find no evidence of a regime switch, as γ1 > 0 and γ3 > 0, and γ2 < 0 and γ4 < 0, in both equations. γ1 > γ3, so that the effect of share concentration in the largest blockholder's hands is estimated to increase for C1 > 50, although the difference is not statistically significant. |γ4| > |γ2 |, which might suggest that additional blockholders have a larger negative effect when C1 ≤ 50, although again the difference is not statistically significant. Taken at 7 The Hausman test always supports the fixed effects versus random effects specification. 6 face value, the results seem to provide more support for the view that additional blockholders quarrel with one another than that they reduce liquidity. In any case, the data do not support the view that smaller blockholders are able to form coalitions to control management and increase performance – neither in the presence nor in the absence of a dominant shareholder. To assess the robustness of our results, we estimated a variety of alternative specifications. For instance, we re-estimated the regressions dropping some of the controls, such as the lagged value of performance, the lagged value of employment, and both variables. We also re-estimated the equations with lagged concentration measures. In all cases, the results qualitatively remains the same: only the size of the largest shareholding has a positively significant effect on both performance measures, and the estimated magnitude of the effect declines as the shareholdings of additional blockholders are included. Similarly to the results in Table 5, we also estimated a variety of non-linear specifications, permitting the concentration effect to enter piecewise linear, quadratic or cubic form. The data showed no evidence of nonlinearity. We also respecified the dominant ownership threshold dummy at alternative levels of 0.25, 0.33, and 0.40. Again, the results were qualitatively similar to those in Table 5. Finally, it would be possible to distinguish different types of blockholders in these data, including domestic and foreign owners, banks and nonbanks, individuals and institutional investors, and private and state actors (Kucsera, Earle and Telegdy, 2001). There are sufficient observations on these types only to permit estimation of the domestic – foreign distinction. The results from such estimates show no clear ranking of these two owners concerning their effect on enterprise performance. Only the shareholding of the largest owner appears to matter, while the identity appears to be secondary. 4. Conclusions The impact of ownership concentration on corporate performance has been a central idea in research on corporate governance, but evidence on the nature of the relationship has been decidedly mixed. Partly this may be due to the fact that concentration has costs as well as benefits, and if these vary in strength with the level of concentration, the implication is that the relationship may be nonmonotonic, as argued by Morck, Shleifer, and Vishny (1988) and by Wruck (1989). Estimates may also vary with data quality, with the estimation method applied, and due to heterogeneity in the population of firms. In this paper, we have suggested that estimates may also vary with the measurement of concentration, an idea that has received little attention in empirical studies. We find that 7 increased concentration in the hands of a single large blockholder is associated with improved corporate performance, that increased ownership by other blockholders does not improve performance and may even decrease it, and that there is no evidence of nonmonotonicity in the impact of any measure of concentration on performance. The idea that the measure of concentration makes a difference is not a simple argument either that results are sensitive to measurement considerations, or that one variable is superior to another, on measurement grounds alone. Rather, it carries implications for our view of how blockholders function and interact. It suggests that different forms of concentration – based on a single large blockholder or on a group of smaller blockholders – have different costs and benefits. Our findings that the marginal value of additional concentration is zero or negative when it comes in the form of additional holdings by blockholders other than the largest suggests that the additional blockholders have costs that exceed their benefits. The usual analysis of the costs of concentration has focused on the possibility that a dominant shareholder expropriates smaller investors (e.g., Shleifer and Vishny, 1997). We have argued that other costs, perhaps more significant ones, may be associated with blockholders quarreling with one another and with the decline in the liquidity of the firm's shares, which lowers the usefulness of the firm's share price as a measure of managerial performance and raises the costs of a takeover. Our findings suggest that these costs are indeed more significant. How generalizable are our findings? The BSE is a young market, but it appears to be fairly typical of stock exchanges in continental Europe and throughout most of the world, both in the degree of ownership concentration and the liquidity of trading. Our analysis permitted behavior to vary between companies that have a dominant shareholder and those that do not (the latter as an approximation for less concentrated Anglo-American type ownership structures), and we have found no evidence of significant differences between them: in both cases it is only the largest shareholding that matters. Of course, it would be interesting to investigate these questions with other data sets from other countries, but that is an effort we leave for future research. 8 References Barclay, Michael J., and Holderness, Clifford G. (1989), "Private Benefits from Control of Public Corporations." Journal of Financial Economics, Vol. 25, 2:371-395. Becht, Marco, and Ailsa Röell (1999), "Blockholding in Europe: An International Comparison." European Economic Review, Vol. 43: 1049 – 1056. Bolton, Patrick, and Ernst-Ludwig von Thadden (1998), "Blocks, Liquidity and Corporate Control." The Journal of Finance, Vol. 53, 1:1-25, February. Claessens, Stijn, Simeon Djankov and Larry H.P. Lang (2000), "The Separation of Ownership and Control in East Asian Corporations," Journal of Financial Economics, Vol. 58:81-112. Claessens, Stijn, and Simeon Djankov (1999), "Ownership Concentration and Corporate Performance in the Czech Republic." Journal of Comparative Economics, 27, 3:498-513, September. Budapest Stock Exchange and Bank & Tőzsde (1996), Company Fact Book. Budapest: Budapest Stock Exchange and Bank & Tőzsde. ____ (1997), Company Fact Book. Budapest: Budapest Stock Exchange and Bank & Tőzsde. ____ (1998), Company Fact Book. Budapest: Budapest Stock Exchange and Bank & Tőzsde. ____ (1999), Company Fact Book. Budapest: Budapest Stock Exchange and Bank & Tőzsde. ____ (2000), Company Fact Book. Budapest: Budapest Stock Exchange and Bank & Tőzsde. Demsetz, Harold (1983), "The Structure of Ownership and the Theory of the Firm." Journal of Law and Economics XXVI. Demsetz, Harold, and Kenneth Lehn (1985), "The Structure of Corporate Ownership: Causes and Consequences." Journal of Political Economy, Vol. 93, 6:1155-77. Gorton, Gary, and Schmid, Frank A. (2000) "Universal banking and the performance of German firms" Journal of Financial Economics, Vol. 58, 29-80. Kucsera, Csaba, John S. Earle and Almos Telegdy (2001), "Ownership Concentration of Listed Firms on the Budapest Stock Exchange." CEU Labor Project working paper. La Porta, Rafael, Florencio Lopes-de-Silanes and Andrei Shleifer (1999), "Corporate Ownership Around the World." The Journal of Finance, Vol. 54, 2:471-517, April. Leech, Denis and John Leahy (1991), "Ownership Structure, Control Type Classifications and the Performance of Large British Companies." The Economic Journal, Vol. 101:1418-37, November. McConnell, John J., and Servaes, Henri (1990) "Additional evidence on equity ownership and corporate value" Journal of Financial Economics, Vol. 27:595-612. 9 Prowse, Stephen D. (1992), "The Structure of Corporate Ownership in Japan." The Journal of Finance, Vol. 47, 3:1121-40, July. Shleifer, Andrei, and Robert W. Vishny (1986), "Large Shareholders and Corporate Control." Journal of Political Economy, Vol. 94, 3:461-488. Shleifer, Andrei, and Robert W. Vishny (1997), "A Survey of Corporate Governance." The Journal of Finance, Vol. 52:737-83. Telegdy, Álmos, John S. Earle, Victor Kaznovsky and Csaba Kucsera (2002), "Corporate Control: A Study of Firms on the Bucharest Stock Exchange." Eastern European Economics, Vol. 40, 3:6-26, May-June. Wruck, Karen H. (1989), "Equity Ownership Concentration and Firm Value. Evidence from Private Equity Financings." Journal of Financial Economics, Vol. 23:3-28. Zwiebel, Jeffrey (1995), "Block Investment and Partial Benefits of Corporate Control." Reveiw of Economic Studies, Vol. 62:161-85. 10 Tables Table 1: Descriptive Statistics for Concentration of Ownership Mean Median Std.Dev. C1 39.4 42.2 19.4 C2 52.9 55.9 23.1 C3 57.7 62.9 23.7 Call 60.9 67.2 24.6 Source: Budapest Stock Exchange and Bank & Tőzsde (1996 – 2000). Note: Number of firm-years: 168. Ownership measured as the average holding for year t and t-1. Table 2: Descriptive Statistics for Employment, Return on Assets and Operating Efficiency ROAt – ROAt-1 Mean 0.00 Median -0.01 SD 0.17 0.12 0.12 0.18 ROAt-1 Emp t-1 2407 907 4010 Log(OEt/OEt-1) 0.16 0.16 0.22 OE t-1 2.43 2.41 0.84 Emp t-1 2302 1066 3693 Source: Budapest Stock Exchange and Bank & Tőzsde (1996 – 2000). Note: Notes: 168 firm-year observations for ROA, 153 for OE. Return on Assets (ROA) defined as the ratio of profit to equity. Operating efficiency (OE) defined as the ratio of real sales to the average number of employees. Profits and sales deflated by 2-digit PPIs. OA not computed for financial institutions. Table 3: Estimated Effects of Ownership Concentration on Firm Performance C1 C2 C3 Call ROAt – ROAt-1 Std. Coeff. Error 0.294** 0.099 0.171 0.100 0.115 0.097 0.075 0.088 R2 0.760 0.746 0.743 0.741 Log(OEt/OEt-1) Std. Coeff. R2 Error 0.942** 0.233 0.465 0.560* 0.247 0.404 0.313 0.240 0.383 0.249 0.215 0.381 Notes: 168 observations for the ROA, 153 for OE regressions. All regressions include controls for previous performance, employment size, year effects, and firm fixed-effects. Financial firms excluded from the regressions using operating efficiency as dependent variable. ** = significant at 1 percent level, * = significant at 5 percent level. 11 Table 4: Estimated Impact of Individual Blockholders on Firm Performance Largest block Second largest Third largest R2 (within) N ROAt – ROAt-1 Coeff. Coeff. Coeff. (Std. Err.) (Std. Err.) (Std. Err.) 0.294** 0.261** 0.258* (0.099) (0.103) (0.107) -0.189 -0.179 (0.167) (0.183) -0.046 (0.352) 0.760 0.763 0.763 168 168 168 Log(OEt/OEt-1) Coeff. Coeff. Coeff. (Std. Err.) (Std. Err.) (Std. Err.) 0.942** 0.830** 0.778* (0.233) (0.245) (0.251) -0.538 -0.361 (0.386) (0.429) -0.776 (0.815) 0.465 0.476 0.481 153 153 153 Source: Company Fact Books 1996 – 2000. Notes: All regressions include controls for previous performance, employment size, year effects, and firm fixedeffects. Financial firms excluded from the regressions using operating efficiency as dependent variable. ** = significant at 1 percent level * = significant at 5 percent level Table 5: Performance Effects of Largest Blockholder and Other Blockholders, By Majority or Non-Majority Stake of the Largest C1*D1 (Call – C1) *D1 C1*(1-D1) (Call – C1)*(1-D1) R2 within ROAt – ROAt-1 Coeff. SE 0.284*** 0.113 -0.074 0.129 0.228* 0.134 -0.203 0.193 0.763 Log(OEt/OEt-1) Coeff. SE 0.963*** 0.268 -0.133 0.296 0.745** 0.311 -0.702 0.435 0.419 Notes: 168 observations for the ROA, 153 for OE regressions. D1 = 1 if the firm's largest owner owns more than 50 percent of the shares, 0 otherwise. All regressions include controls for previous performance, employment size, year effects, and firm fixed-effects. Financial firms excluded from the regressions using operating efficiency as dependent variable. *** = significant at 1 percent level, ** = significant at 5 percent level, * = significant at 10 percent level. 12