MSc Laure Carcaillon
email: laure.carcaillon@inserm.fr

MD, PhD G Berrut

MD F Sellal

MD, PhD J F Dartigues

PhD S Gillette

J J Péré

I Bourdeix

Diagnosis of Alzheimer's disease patients with Rapid Cognitive Decline in clinical practice: interest of the Deco questionnaire

Keywords: Alzheimer's disease, rapid cognitive decline, diagnostic tool

Background: Patients with Alzheimer"s disease (AD) who deteriorate rapidly are likely to have a poorer prognosis. There is a clear need for a clinical assessment tool to detect such a decline in newly diagnosed patients.

Objective: To identify the predictive factors of rapid cognitive decline (RCD) in a cohort of patients with mild to moderate AD ; and to validate a self-questionnaire for caregivers as a diagnostic tool for rapid decline.

Design and analysis: an open-label, observational, 12-month, multicenter, French study.

Physicians were asked to record data of three eligible rivastigmine naïve (or on rivastigmine for < 1 year) AD patients. Risk factors of RCD and the detection power of the Détérioration Cognitive Observée scale (Deco), a 19 item self-questionnaire for caregivers, were assessed at endpoint using regression analyses.

Results: Out of the 361 patients enrolled in the study, 91 (25.2%) were excluded due to loss of follow-up. Among subjects using cholinesterase inhibitors or memantine, 161 (59.6%) experienced a stabilization (29.2%) or an improvement (30.4%) in global functioning as measured by the CGI-C. Sixty of the remaining 204 patients retained for analysis (29.6%, CI 95% [23.4; 35.8]) lost three or more points on the MMSE score between the inclusion and one of the follow-up visit. In the multivariate logistic regression analysis, institutionalization, higher level of education and the loss of 3 points or more on the MMSE were found to be significant predictors of a rapid cognitive loss in this population. The threshold which maximizes the predictive values of the Deco score as a diagnostic tool of rapid cognitive decline was significantly different according to the age of the patient (below or over 75 years old). A score below 16 for patients < 75 years old and below 14 for patients ≥ 75 years old consistently predicted a RCD within the next year.

Conclusion:

The Deco test appears to be a simple tool to alert the physician to the possibility of an aggressive course of the disease which warrants particular management.

INTRODUCTION

Neurodegenerative dementias such as Alzheimer Disease (AD) are characterized by a progressive cognitive decline. However, the rate of progression can be highly variable from one patient to another [START_REF] Doody R S, Massman | A method for estimating progression rates in Alzheimer disease[END_REF] and some patients could have a more rapid cognitive decline (RCD). These patients are likely to have a poorer prognosis, with a higher mortality rate or a lower survival rate without severe dementia, than those with slower progression rates [START_REF] Doody R S, Massman | A method for estimating progression rates in Alzheimer disease[END_REF][START_REF] Carcaillon | Fast cognitive decline at the time of dementia diagnosis: a major prognostic factor for survival in the community[END_REF][START_REF] Helmer | Predictive value of 6-month decline in ADAS-cog for survival without severe Alzheimer's disease[END_REF].

A prospective observational study performed in a population of 455 AD patients followed for at least one year, demonstrated that the risk of deterioration was significantly decreased in patients taking cholinesterase inhibitors (ChEIs) for at least one year compared to untreated patients [START_REF] Gillette-Guyonnet | Outcome of Alzheimer's disease: potential impact of cholinesterase inhibitors[END_REF]. To date, rivastigmine is the only drug which has been specifically studied in patients with RCD. A meta-analysis of four 6-month, double-blind, placebocontrolled phase studies [START_REF] Farlow | Efficacy of rivastigmine in Alzheimer's disease patients with rapid disease progression: results of a meta-analysis[END_REF] showed that patients who experienced rapid decline, i.e. a decline of at least 4 points of the ADAS-cog score, during 26 weeks of placebo treatment, improved significantly more after 12 weeks of rivastigmine therapy than those who had declined by less than 4 points in the first 26 weeks. Thus, identifying AD patients at risk of RCD is important as these patients might benefit from specific primary or secondary care including more frequent clinical and neuropsychological evaluations, more frequent adaptation of drug treatment and more effective support for the caregiver.

Several factors may predict RCD in AD patients: cognitive status, presence of Extra-Pyramidal Signs, psychotic symptoms and hallucinations, prominent sub-cortical pathology with attention and executive deficits and poor nutrition [6; 7]. However many of these factors are of limited interest in a clinical setting for individual patients as it is difficult to obtain valid information about most of them during the time of a consultation. There is thus a clear need for a simple clinical assessment tool, drawing on caregiver input, to detect RCD in recently diagnosed patients. The "Détérioration Cognitive Observée" (Deco) scale is a 19-item questionnaire administered to a person with at least a monthly contact with the patient. Its aim is to evaluate the change in cognitive functioning of the patient over the previous year. This instrument has been shown to be highly sensitive to early changes in cognitive functioning in previous studies [START_REF] Ritchie | Classification criteria for mild cognitive impairment: a population-based validation study[END_REF].

The objectives of the prospective study we report here were to identify the predictive factors of RCD in a cohort of patients with mild to moderate AD ; and to analyze the predictive value of a self-questionnaire for caregivers (the Deco score) as a simple diagnostic tool for RCD.

PATIENTS AND METHODS

Study Design

EXPLORE was an open label, observational cohort study, 12-month, multicenter, French study for which 350 neurologists, geriatricians and psychiatrists were contacted in order to finally include 250 of them. Each was asked to record data of three eligible patients.

Eligibility criteria included: outpatients with AD over fifty years old, satisfying the criteria of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) for dementia and those of NINCDS-ADRDA Work Group; with Mini-Mental State Examination (MMSE) [START_REF] Folstein | Mini-mental state". A practical method for grading the cognitive state of patients for the clinician[END_REF] scores between 10 and 26; initiating therapy for the first time with rivastigmine or having already received rivastigmine for less than one year; with a planned follow-up visit within 12 months of enrolment and a caregiver"s burden assessment; with an available informant. Patients not treated according to the product labeling, patients involved in a clinical trial or patients treated by an experimental drug within the previous 4 weeks were excluded. Investigators were advised to follow product labeling.

The Steering Committee, the French National Council of Medical Practitioners Order (CNO) and the National Council of Informatics and Freedom (CNIL) approved the study. All the patients were given a study information sheet.

For the present analysis, only subjects followed during twelve months were considered (n=204). Figure 1 is a detailed flow chart of patients "selection and exclusion.

Study assessments

At study entry, a detailed medical history of each patient was taken and baseline and follow-up assessments of cognitive performances was performed.

Rapid cognitive decline was defined as a decline of at least three points of MMSE during the one year of follow-up. The following potential predictive factors of RCD were collected at baseline: MMSE, presence of behavioral disorders reported by the patient or his family (delusions, hallucinations, agitation/aggression), presence of extrapyramidal signs, lack of autonomy for the key Instrumental Activities of Daily Living (IADL) items (budget, phone, drugs, transport) [START_REF] Lawton | Assessment of older people: self-maintaining and instrumental activities of daily living[END_REF], lack of stabilization with previous IChE or memantine treatment, Body Mass Index (BMI) and level of education. The clock drawing test [START_REF] Galluzzi | Mild cognitive impairment: clinical features and review of screening instruments[END_REF], the 5-word test [START_REF] Dubois | L'épreuve des cinq mots[END_REF] and a verbal fluency test were also taken into account.

The 19-item caregiver questionnaire, the Deco score was collected at the end of the 12month follow-up. Safety (vital signs, adverse events and a physical examination) regarding the use of IChE was assessed throughout the study as needed.

Data analysis

Characteristics of the patients who were seen at the12-month visit were compared to those of all subjects enrolled in the study by appropriate univariate statistical tests.

Using simple and multiple logistic regressions, we studied the risk of RCD according to baseline characteristics of the patients. The multivariate analysis included all variables significantly associated with the risk in the univariate analysis at a p-value < 0.10. Moreover, we compared mean values of the Deco score according to some baseline characteristics of the patients. We used student t-test for the comparison.

In addition, we ran a Receiver Operating Characteristic (ROC) analysis to detect the best threshold of diagnosis of RCD for the Deco score. Sensitivity, specificity, positive and negative predictive values were calculated for the best thresholds found from the observed ROC curve. We systematically sought for interactions between age and Deco score on the risk of RCD. Indeed, the risk of rapid decline is higher among younger subjects so we hypothesized that the predictive value of Deco might have a differential association with RCD according to age. SAS statistical software version 9.2 was used to perform analyses.

RESULTS

Patients

Three hundred and sixty one patients were enrolled in the study by 152 neurologists, geriatricians and psychiatrists. Among subjects using ChEI or memantine, 161 patients (59.6%) experienced a stabilization (29.2%) or an improvement (30.4%) in global functioning, as measured by the CGI-C. One hundred and fifty seven patients (25.2%) were excluded from analysis because of loss of follow-up between baseline and the 12-month follow-up (n=151) or missing value on MMSE (n=6) (figure 1). Baseline characteristics of the analyzed and enrolled populations were comparable (Table 1). In the analyzed population, 89 patients (43.6%) had received prior ChEI treatment and 115 (56.4%) were de novo patients.

Of the 89 patients who had received prior ChEI treatment, 63 patients were already treated by rivastigmine and 26 discontinued from a previous treatment by another ChEI. There were more women than men (58.3% versus 41.7%) and the mean age was approximately 78 years (range 51-102 years). At baseline, patients included in this analysis had a mean MMSE score of 19.7 ± 4.4.

For patients who had been previously treated by ChEIs, the mean duration of treatment before starting the study was 14.0 ± 14.3 months with a mean MMSE decrease of 2.1 ± 3.0 (-1.1 ± 2.6 for rivastigmine; -4.1 ± 2.8 for donepezil and -3.6 ± 3.0 for galantamine).

For the analyzed population, the MMSE decrease within the previous year was only known for 101 patients (i.e., data missing for 103).

The mean follow-up period was 377.6 (± 61.2) days.

Predictive factors of cognitive decline

Sixty of the 204 patients retained for analysis (29.4%, 95%CI [23.4; 35.8]) were qualified as rapid cognitive decliners as they lost three or more points on the MMSE score between the inclusion and the 12-month follow-up visit.

Table 2 shows that the demographic and neuropsychological characteristics significantly associated with RCD by univariate analysis are: living in an institution and a high level of education (p-value < 0.03). In addition, a weaker level of autonomy and the loss of 3 points or more on the MMSE during the year prior to inclusion tended to be associated with RCD (p-value < 0.07). As there was a high number of missing values for the variable "loss of 3 points or more on the MMSE during the year prior inclusion", two multivariate models were performed to analyze the risk of RCD (table 3). Model 1 included residential status, level of education and loss of autonomy. In this model, only the level of education remained significantly associated with RCD (OR = 2.21, 95%I.C. (1.12 -4.37)). The second model (model 2) was further adjusted for the loss of more than 3 points on MMSE prior inclusion. In this model, the level of education and the loss of more than 3 points on MMSE were significant predictors of rapid decline.

The Deco questionnaire

The mean Deco questionnaire score was 19.0 ± 8.8. It was significantly different between rapid decliners (15.5 [13.6; 17.5]) and slow decliners (20. 3 [18.8; 21.8]) (p for difference = 0.001) (table 4). Table 4 displays the mean of the Deco score according to baseline characteristics of the patients. No significant association was found for socio-demographic characteristics.

Significant lower values of Deco scores were observed for subjects with low level of (p-value = 0.07).

Figure 2 shows the ROC curve of the predictive value of RCD according to the Deco score. Visually, the threshold which maximizes the specificity and the sensitivity of the score seems to be between 16 and 18. Table 5 reports the risks of RCD as well as the results from a sensitivity/specificity analysis for three thresholds (a Deco score <= 16, <=17 or <=18). The best model in terms of risk was observed for the threshold of 16. The risk of RCD for a patient having a score <= 16 for the Deco questionnaire was three times higher than for a patient scoring over 16 (p=0.002). However, we found an interaction between age and the threshold of 16 on the risk of RCD. For this threshold, the risk of RCD was significantly increased among younger subjects (age < 75) but not among older ones (respectively OR = 6.7, 95%C.I. (1.8-25.1) and OR = 2.1, 95%C.I. (0.9-4.8)). As a consequence we ran new analyses to evaluate the best predictive thresholds of RCD according to age-group (below or over 75). Results are reported in table 6. We found that a threshold of 16 among subjects aged below 75 years old and a threshold of 14 for subjects older than 75 years old maximized the predictive values of the Deco score. Sensitivity, specificity and predictive values were consistently better than in the analysis pooling the two age-groups.

DISCUSSION

In this one year observational study we found that 29.4% of patients with AD lost 3 points or more at the MMSE score and were thus classified as rapid decliners over the study period. Living in an institution, having a high educational level and being impaired for at least two activities in daily living were significantly associated with RCD. Finally, the Deco score was differently related to the occurrence of RCD according to the age of the patient. A threshold of 16 was found to be the best diagnostic tool for RCD among subjects aged < 75 years old while a threshold of 14 was found for subjects aged ≥ 75 years old.

In our study we found a relatively low proportion of rapid decliners compared with other studies. Although other definitions of cognitive decline have been proposed [3; 13], a decline of 3 points or more of the Mini-Mental State Examination (MMSE) over one year is a commonly used definition of RCD. Indeed, several clinical or population-based studies have shown that this threshold of decline was strongly linked to mortality or entry in an institution [2; 14]. Moreover, the use of MMSE compared to other neuropsychological tests is the only one to fit with clinical practice. In addition, all our patients were using ChEI so the low proportion of rapid decliners found is consistent with the fact that rivastigmine, which is the only therapy studied in this population, has been shown to reduce the risk of rapid cognitive decline in patients using ChEI [4; 15]. As AD patients with RCD have a poorer prognosis, they warrant particular attention from the clinician. Previous efforts have been made to identify risk factors of rapid decline which could be targeted for timely introduction of preventive actions [6; 7; 16; 17] . In our study, demographic factors as living in institution and high level of education, and previous rapid decline appear as independent factors correlated with a rapid disease progression, while the usual clinical predictors as poor nutritional status, psychotic or extrapyramidal signs were not found to be correlated. While this lack of correlation could be attributed to the greater benefits of rivastigmine in this population [5; 7], the low proportion of patients in our study with such clinical symptoms at baseline should also be taken into account.

Even if certain factors may be good predictors of rapid decline, available data remain contradictory [START_REF] Teri | Cognitive decline in Alzheimer's disease: a longitudinal investigation of risk factors for accelerated decline[END_REF] and are not sufficient or relevant in routine practice for clinical-decision making, especially for newly diagnosed patients. In this respect, we aimed to assess the capacity of a new scale to evaluate the one-year change in cognitive functioning of patients according to their caregiver (or a person in contact with them). The Deco questionnaire used in this study appeared to be a valuable clinical tool for the detection of RCD. Indeed, when taking into account the age of the patients, thresholds of detection were strongly associated with RCD. A Deco score of less than 16 among patients under 75 years old, and of less than 14 among patients over 75 years old, was found to be strongly associated with RCD. The risk of being a rapid decliner was 3 to 6 times higher among patients whose caregiver scored less than the threshold found for the Deco score. Moreover, the positive predictive value was close to 50% in the younger age-group which is a relevant value for clinical decision making. Indeed, it indicates that if an informant reports a score lower than 16 for a patient, there is 50% chance that this subject has actually encountered a rapid decline within the previous year. Preventive care for these subjects appears necessary and will be useful for one patient out of 2. In addition, it is to be noted that the predictive values of the Deco score were better in the younger group of patients. This finding may be explained by the fact that older patients complain less than younger ones and they, as well as their caregivers, may attribute their changes in cognitive performances to age rather than to a pathological process. They may report less frequently little cognitive changes. Hence, the Deco questionnaire could represent a simple way of detecting patients with a high probability of rapidly progressing symptoms and thus to adapt disease management accordingly.

While our results are promising, this study does have some limitations. It remains merely a historical comparison and no definitive conclusion can be drawn. Moreover, only a low number of neurologists finally recruited patients. Together with the fact that a quarter of the patients were lost to follow-up, this could have introduced a bias. Our sample may not be fully representative of the AD population and thus our results should be interpreted with caution. Nonetheless, when enrolled patients" baseline characteristics were compared to those of the finally analyzed population, no difference was found, especially in the items of level of autonomy and cognitive impairment.

Overall this study suggests that AD patients at risk of RCD can be identified in the setting of a regular consultation by means of the Deco questionnaire. Once alerted to the possibility of an aggressive disease course, the physician could pay particular attention to these patients and adapt disease management accordingly.

Figure 1 :

 1 Figure 1: Flow chart of the patients" selection for the per-protocol analysis

Figure 2 :

 2 Figure 2: ROC curve for the prediction of rapid cognitive decline according to DECO scores

Table 1 -

 1 Comparison of baseline characteristics of enrolled and analyzed patients 1 2

	Enrolled Population	Analyzed population
	N = 361	N = 204

Table 2 .

 2 Association between baseline characteristics of patients and the risk of rapid 1 cognitive decline. Univariate logistic regression. 2

	Rapid cognitive
	decline
	Yes	No
	n=60	n=144	OR (95%I.C.)	p-value

Table 3 .

 3 Risk of rapid decline in two multivariate logistic regression analyses

	Model 1 (n = 204)	Model 2 (n = 101)
	OR (95%I.C.) p-value	OR (95%I.C.) p-value

Table 4 .

 4 Association between baseline characteristics of patients and the Deco score

	m	sd p-value

Table 5 .

 5 Predictive power of 3 thresholds of the Deco score. Univariate logistic regression.RCD states for rapid cognitive decline, Se for sensitivity, Sp for specificity, PPV for positive predictive value, NPV for negative predictive value

		RCD
		Yes	No	OR (95%I.C.) p-value	Se	Sp PPV NPV
	DECO > 16	17 (37.8) 85 (64.4)	1.00
	DECO <= 16	28 (62.2) 47 (35.6)	2.98 (1.46-6.00)	0.002	62.2 64.4 37.3 83.3
	DECO > 17	16 (35.6) 79 (64.4)	1.00
	DECO <= 17	29 (59.9) 53 (40.2)	2.70 (1.34-5.46)	0.006	64.4 59.9 35.4 83.2
	DECO > 18	15 (33.3) 72 (54.6)	1.00
	DECO <= 18	30 (66.7) 60 (45.5)	2.40 (1.18-4.87)	0.015	66.7 54.6 33.3 82.8

Table 6 .

 6 Best predictive thresholds of the Deco score according to age-groups. Univariate logistic regression. RCD states for rapid cognitive decline, Se for sensitivity, Sp for specificity, PPV for positive predictive value, NPV for negative predictive value

		RCD
		Yes	No	OR (95%I.C.) p-value	Se Sp VPP VPN
	Age < 75 yrs old
	DECO > 16	4 (26.7) 29 (70.7)	1.00
	DECO <= 16	11 (73.3) 12 (29.3) 6.65 (1.76-25.1)	0.005	73.3 70.7 47.8 87.9
	Age >= 75 yrs old
	DECO > 14	14 (17.5) 66 (82.5)	1.00
	DECO <= 14	16 (39.0) 25 (61.0) 3.02 (1.29-7.08)	0.011	57.8 74.2 43.3 83.8


Irena Grosfeld

Ownership concentration and firm performance: Evidence from an emerging market

Keywords: D24, G32, L1, P2 Ownership structure, corporate governance, human capital intensive firms

Introduction

What are the characteristics of 'good' ownership structure? Does ownership structure matter for firm performance? Why certain firms have large block holders and others do not? Should the power of large shareholders be limited to avoid expropriation or encouraged to curb managerial discretion? These questions have been largely explored in corporate finance literature and we understand better now the intricacies of the relationship between ownership structure and firm performance.

But empirical evidence on the impact of shareholders with significant equity holdings on corporate performance remains ambiguous. Various authors using different samples of firms and different empirical strategies obtain different, difficult to compare and sometimes contradictory results. It is increasingly recognized that the problem in disentangling this relationship is largely due to the pervasive endogeneity of ownership which has to be taken into account in order to obtain unbiased results. But the existing empirical evidence also suggests that the relationship between ownership and performance may depend on the type of the firm and on the period of observation in the life of the firm.

The purpose of this paper is to explore more in details the determinants of ownership concentration and the relationship between ownership structure and firm value in the context of an economy undergoing important changes in its legal and regulatory framework, in macroeconomic policy and most of all, in its property rights allocation. Using a panel of firms listed on the Warsaw Stock Exchange (WSE) offers an unusual opportunity for this kind of investigation.

The Polish economy was exposed to radical institutional changes in the nineties. Privatization strategy in Poland was strongly influenced by the willingness to create appropriate ownership structure in privatized firms, i.e. to ensure that powerful block holders control the firm. A large portion of state-owned enterprises was privatized and the conditions for entry of new firms were significantly eased. Some of the privatized and newly created firms have entered the stock exchange established in 1991. These firms are likely to show a lot of heterogeneity. Their ownership structure is likely to be determined by the firm origin and for privatized firms by the method of privatization. New firms, when they become listed on the stock exchange are likely to have, at least during the initial years of listing, more concentrated ownership structure than privatized firms. Moreover, new firms established by their founders in a market friendly environment may require less ownership, financial and industrial restructuring than previously state-owned enterprises.

The sensitivity of firm performance to firm ownership structure is likely to vary across firms. It may also undergo important changes over time. Once firms are listed on the stock exchange, reallocation of ownership stakes becomes greatly facilitated. 1 The first part of this paper is devoted to the exploration of the determinants of ownership concentration. Trying to understand why certain firms have large owners and others have dispersed ownership structure, I build on the extant literature and notably on [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF] and [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF]. The contribution of my paper to the literature consists in taking into account the importance of knowledge related activities. 2 The idea is that analyzing the relationship between managers and shareholders requires different perspectives in firms belonging to the sector of "new economy" than in firms belonging to more traditional industries 1 [START_REF] Audretsch | Does the new economy need new governance? Ownership, knowledge and performance[END_REF]. In more 'mature' industries, it can be assumed that it is well understood what should be done and how and it is important to make sure that managers implement efficiently the objectives agreed on. In such conditions, the dominant concern is indeed about managerial shirking, laziness and laxity (Marshall, 1923). Such concern motivates the importance and high value of monitoring. In firms with strong human capital component, it is less clear what is the right strategy or the right project. Forcing managers to do a particular thing may be costly since shareholders may not know what the best thing to do is. In such highly uncertain environment, ('uncertain' in the sense of Knight), the crucial issue is less to make sure that the agent-manager realizes a given objective with a maximum effort than to incite the manager to search for the best project. 3 Managers are more likely to show initiative if they have some latitude to make effort and undertake innovative actions. In [START_REF] Aghion | Formal and real authority in organizations[END_REF] concentrated ownership provides incentives to monitor, but it also reduces the manager's initiative or incentive to acquire information. Recognizing the importance of managerial initiative is at the heart of the theory of [START_REF] Burkart | Large shareholders, monitoring and the value of the firm[END_REF]. They argue that increased monitoring by shareholders may be costly because it may depress initiative displayed by managers: managers are less likely to be active if they know that shareholders are likely to interfere. So too much monitoring may negatively affect managerial initiative and profitable investment opportunities will be lost. [START_REF] Burkart | Large shareholders, monitoring and the value of the firm[END_REF] view firm ownership structure as an instrument to solve the trade-off between control and initiative. Through more dispersed ownership structure shareholders commit themselves to weaker intervention which makes managers confident enough that they will not be dispossessed of the benefits of their initiative.

The trade off between initiative and control may be particularly strong in firms belonging to highly technological sectors. In such firms, ownership concentration (reflecting the value of monitoring) is likely to be lower than in more traditional sectors. 4 I examine whether ownership concentration is related to the importance of knowledge related capital by including a dummy for firms belonging to high technology sector.

I also use the importance of firm's "soft" capital, measured as the share of intangibles in fixed assets, as an additional proxy for the firm's specific uncertainty. 5 Following [START_REF] Zeckhauser | Are large shareholders effective monitors? An investigation of share ownership and corporate performance[END_REF], I expect that the higher the firm R&D intensity, the more diffuse is the informational structure and the more difficult outside monitoring. Large shareholders are supposed to recognize the problem and, therefore ownership concentration is likely to be negatively related to soft capital intensity. 6 The results show that the regression is able to explain on average about 25% of the variation in ownership concentration. They also confirm that firms belonging to highly technological sectors have more dispersed ownership structure. This effect is particularly noticeable in the sub-sample of 'new' firms which may be explained by the fact that high tech firms are almost exclusively 'new'.

In the second part of the paper I explore the relationship between ownership concentration and firm value. In pooled OLS regression higher ownership concentration improves firms' corporate value. When we take into account endogeneity of ownership, its impact on firm value becomes much stronger than in OLS regressions.

The results reported in this paper suggest that firm heterogeneity may significantly affect ownership concentration and its impact on firm value. They also confirm the need to take into account endogeneity of ownership but also the difficulty of doing it. The validity of chosen instruments should be carefully assessed and using alternative sets of instruments should be envisaged. Overall, the results yield a rather cautionary tale about one of the issues considered in corporate governance literature: "should the power of large shareholders be limited to avoid expropriation or encouraged to curb managerial discretion". Regulatory authorities should be very careful and avoid imposing constraints on the adjustment of firm ownership structure to firm specific characteristics.

Before I discuss these empirical results, in section 2 I briefly describe the relevant literature. In section 3 I present the data. Section 4 discusses the determinants of ownership concentration and section 5 the relationship between ownership and firm value. Conclusions are presented in section 6.

Literature

Following the early work by [START_REF] Berle | The Modern Corporation and Private Property[END_REF] and until the eighties, the main concern of the literature on corporate governance was the conflict of interest between shareholders and managers [START_REF] Jensen | Theory of the firm: Managerial behavior, agency costs and ownership structure[END_REF]. 7 Ownership concentration (ensuring better monitoring), and managerial equity holdings (increasing managerial effort and decreasing perquisite consumption), were supposed to lead to better firm performance. An important empirical literature examining this prediction mainly focused on the relationship between managerial ownership and firm value. Following [START_REF] Stulz | Managerial control of voting rights: Financing policies and the market for corporate control[END_REF] who predicted a concave relationship, several papers, including [START_REF] Morck | Management Ownership and Market Valuation: An Empirical Analysis[END_REF], [START_REF] Mcconnell | Additional evidence on equity ownership and corporate value[END_REF], [START_REF] Hermalin | The effects of board composition and direct incentives on firm performance[END_REF], [START_REF] Holderness | Were the good old days that good?: Changes in managerial stock ownership since the Great Depression[END_REF] found that low levels of managerial ownership increase firm value but at higher levels of managerial ownership firm value decreases. The results of these single-equation studies were interpreted as the evidence of managerial entrenchment beyond some threshold of insider ownership.

Since the 90s, careful observation of ownership structures across the world showed that dispersed shareholdings are much less frequent than expected and we observe instead a high degree of ownership concentration [START_REF] Porta | Corporate Ownership Around the World[END_REF]Becht and Roell, 1999). Consequently, the potential expropriation of the minority investors by the controlling owners became the main concern (Johnson et al., 2000, Faccio andLang, 2002;Lehman andWeigand, 2000, Gugler and[START_REF] Gugler | Is ownership really endogenous?[END_REF]. It was recognized that large shareholders may be costly because they have other objectives than small shareholders and may expropriate the latter.

Other costs of excessive ownership concentration have been underlined in recent literature and several theories have been proposed to explain the ambiguity of the relationship between ownership concentration and firm performance. Holmstrom and Tirole (1993) explored the tradeoff between ownership concentration and liquidity which may affect the informational role of the stock market. It has been also stressed that high ownership concentration limits diversification and reduces owners' tolerance towards risk [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF][START_REF] Admati | Large shareholder activism, risk sharing and financial market equilibrium[END_REF][START_REF] Bolton | Blocks, liquidity and corporate control[END_REF]. Finally, [START_REF] Burkart | Large shareholders, monitoring and the value of the firm[END_REF] analyzed how in some circumstances the control imposed by strong owners on managers may be too severe, restraining their initiative and incentives.

An important strand of the literature focuses on the endogeneity of ownership structure in its relationship with firm performance. The initial argument about the endogeneity of ownership structure was formulated by [START_REF] Demsetz | The structure of ownership and the theory of the firm[END_REF]. He argued that ownership structure is an outcome of shareholders' decisions. Maximizing the firm value may require a concentrated or a diffuse ownership structure. The trading of shares may reflect the desire of existing or potential owners to change their stakes. Following this important contribution, several papers explored empirically the impact of ownership structure on firm performance taking into account endogeneity of ownership. [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF], [START_REF] Hermalin | The effects of board composition and direct incentives on firm performance[END_REF]Weisbach (1991), Loderer andMartin (1997), [START_REF] Cho | Ownership structure, investment and the corporate value: an empirical analysis[END_REF][START_REF] Demsetz | The structure of ownership and the theory of the firm[END_REF][START_REF] Demsetz | Ownership structure and corporate performance[END_REF] use a system of simultaneous equations and find no significant relationship between ownership and performance. Kole (1994) finds evidence of reverse causality, performance affecting ownership rather than the other way round. [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF] argue that endogeneity of ownership may be largely due to individual heterogeneity. Using firm fixed effects they find no significant relationship and conclude that shareholders choose ownership structure optimally. Interestingly, Khanna et al. (2005) find that [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF] results of no correlation between managerial ownership and firm value in a fixed effect estimation are specific to the period considered. If the sample is extended over the next 10 years, the correlation turns out to be significant. Controlling for unobservable firm level heterogeneity was criticized by [START_REF] Zhou | Understanding the determinants of a managerial ownership and the link between ownership and performance: a comment[END_REF] who argued that including fixed effects may not allow detecting an effect of ownership on performance even in it existed. [START_REF] Gugler | Is ownership really endogenous?[END_REF] consider simultaneously whether the largest shareholder's stake matters for the endogeneity/causality relation in addition to managerial ownership. Using IV techniques they find, for US and Germany, that insider ownership does not significantly affect performance as measured by the return on total assets. But the largest shareholder remains significant for firm performance even if they control for simultaneity. There is also some empirical evidence of a negative impact of large equity holders on firm performance. [START_REF] Lehmann | Does the governed corporation perform better? Governance structures and corporate performance in Germany[END_REF], focusing on German corporations, find indeed a negative effect of ownership concentration on firm performance.

Empirical strategy

Before exploring the complex relationship between ownership and performance, I first look at the determinants of ownership concentration. It is important to understand how firm ownership structure varies across firms and how it is affected by the listing on the stock exchange. One of the hypotheses I want to test is whether ownership concentration is lower in firms with an important share of knowledge related activities. Investigating the determinants of ownership concentration will hopefully also provide us with the potential instruments for this variable.

Turning to the firm value equation, we know that the OLS results can be biased for two reasons: first, because of unobserved heterogeneity of firms which may be correlated with ownership concentration and firm performance; second, because of simultaneity and potential reverse causality between ownership and performance.

A solution to the problem of unobserved heterogeneity is the use of panel data. [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF] used panel techniques to control for firm level fixed effects and found that the impact of managerial shareholding is not significantly different from zero. I obtained similar results in the sample of Polish firms studied in this paper: once unobservable firm level fixed effects are included in the regression, ownership concentration does not seem to affect firm performance anymore (results available on request).

Using a model with fixed effects to investigate the relationship between ownership and performance may be, however, misleading. [START_REF] Zhou | Understanding the determinants of a managerial ownership and the link between ownership and performance: a comment[END_REF] argued that such approach may fail because it may not allow detecting an effect of ownership on performance even if it existed. 8 Using fixed effects we focus on within rather than cross-sectional variations. But what appears crucial in investigating the relationship between ownership and performance is to understand whether in some firms higher ownership concentration may be more beneficial than in others. An additional argument against treating unobservable variables as fixed effects comes from the specificity of the sample considered in this study. In a transition economy like the Polish one in the period under examination, firms are exposed to profound industrial, managerial and financial restructurings. It makes questionable the assumption that firm specific characteristics do not change over time. 9 Finally, fixed effects estimations are also costly because it is not possible to estimate coefficient on time-invariant variables.

Taking these arguments into account 10 I focus on the endogeneity due to the correlation between ownership and idiosyncratic errors in firm value equation. In order to investigate the relationship between ownership concentration and firm value, we have to consider not only the possibility that ownership concentration is likely to affect firm performance but also the possibility that ownership structure may depend on the value of the firm. The impact of performance on owners' decision to concentrate their holdings is a priori ambiguous. If shareholders believe they are able to create value and obtain benefits of control sufficiently large to override the cost of the effort and to compensate for the loss of benefits of diversification, they may be willing to increase their holdings in firms which have not yet capitalized their growth opportunities in the stock price. 11 However, especially in emerging markets, with potentially high informational asymmetries, investors may also want to get a dominant position in a firm if they plan to extract value from the company: in that case they would prefer increasing their equity holdings in more profitable firms.

Consequently, the empirical strategy adopted in this paper will rely on estimating a model of simultaneous equations: in the first equation, the dependent variable is ownership concentration measured as the share of the voting rights of the largest shareholder (ownconc); in the second equation the dependent variable is firm performance measured as Tobin's Q (Q).

Ownconc =f (Q, firm characteristics, Zownconc c(t), u(it)) Q = f (ownconc, firm characteristics, ZQ, c(t), e(it))

where c are year fixed effects, Zownconc is the vector of instruments for ownership concentration, ZQ is the instrument for Tobin's Q and u(it) and e(it) are white noise errors.

The obvious problem in estimating such system of equations is the problem of identification. We need at least two exogenous variables plausibly affecting only ownership concentration or firm value, not both of them. However, it is notoriously difficult to find valid instrumental variables for ownership concentration: most of the potential candidates are also likely to directly affect Tobin's Q. I will follow here two main studies in the relevant literature [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF][START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF] and instrument ownership concentration in performance equation by using firm level volatility (its standard deviation and variance). This instrument has weaknesses but it was used previously in important contributions to the literature. [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF] argued that stock price volatility is an acceptable although not perfect instrument for ownership structure; and that other potential candidates are probably worse because more likely to also affect Tobin's Q. Also see [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF].

Concerning the second equation, for Tobin's Q, I will use initial profitability as a predetermined variable for Tobin's Q. Initial profitability is calculated as a ratio of net profit to total assets averaged over the three years preceding the publication of the prospectus. Initial profitability is likely to affect firm performance; however, there is little chance that it affects ownership concentration

Data

Our sample includes all non-financial companies traded on the Warsaw Stock Exchange (WSE). 12 The WSE was established in 1991 and for the last fifteen years has been developing rapidly. There were 8 listed firms in 1991 and 214 in 2003. Market capitalisation of the WSE grew steadily through the period reaching 21 percent in 2003.

The quality of the information on the listed firms is very good as the requirements of reporting and transparency on the Warsaw Stock Exchange are quite strict and comparable to those of Western European stock exchanges. 13 The initial data base was created relying on published, audited accounts of balance sheets and income statements. It has been extended manually by including detailed information on ownership structure and the method of privatization. The information on ownership structure includes the identity of all shareholders holding more than the mandatory disclosure threshold of 5 percent of the shares and the percentage of cash flow rights and voting rights they hold. We were able to collect this ownership information for all years between 1991 and 2003, with the exception of 13 firms which were introduced to the WSE in 1991 and 1992: for these firms the Security and Exchange Commission (Komisja Papierow Wartosciowych) did not collect the ownership data in 1992 and 1993.

Our sample of listed firms allows distinguishing firms that were previously state-owned and firms, which can be considered as 'new' in the sense that they never belonged to the state and were created as private firms by their founders. In 2003 there were 90 new firms and 124 privatized firms. 30 firms were privatized through IPOs, 55 through direct sale, 13 through leveraged employee and managerial buyout, and finally 26 listed companies were privatized in the framework of the National Investment Funds programme (a version of mass privatization scheme). 14 The average employment in our firms is 1233 employees (median 509), the average age is 32 (median 23) and the average number of years of listing is 4 (median 3).

Table 1 provides information on our sample for years 1991 -2003. The number of firms entering the stock exchange varies significantly over time and reflects the privatization process and the development of the WSE. Table 2 shows the characteristics of the firms in the sample in 2003. These firms have an average Tobin's Q of 1.30 and the largest owners control on average 43 percent of voting shares.

Table 3 compares privatized firms with new firms. The last column in the table provides statistics for testing the hypothesis of equal group means (t-statistics). The table reveals that on average new firms are, as could be expected, smaller than privatized firms; they have higher Tobin's Q (1.50 versus 1.19) and their controlling owners hold a significantly larger portion of voting rights (47% versus 41%); they have more intangibles and have been listed for more years than privatized firms. The idiosyncratic risk (firm volatility)does not differ in a significant way between these two categories of firms.

The important advantage of this data base is that it makes possible observing the change in ownership structure of the firms over time: we can see how the introduction of the firms on the stock exchange and the years of listing affect their ownership structure. Two dimensions of ownership structure are taken into account: ownership concentration and the identity of the largest shareholder. I use the commonly used concentration measure which is the fraction of voting rights of the largest shareholder. Four groups of owners are identified: families, industrial firms, institutional investors, and the state.

Table 4 shows that ownership of companies becomes more dispersed with the number of years of listing. 15 The average voting rights held by the largest shareholder decreases quite rapidly notably during the first three years of listing. When we look separately at privatized and 'new' firms, we can observe that the initial differences in ownership concentration disappear with time.

16 More detailed information on the evolution of the ownership structure can be found in table 5: it presents changes in ownership concentration by the type of largest owners during the first six years of listing. We can see that the most important changes took place in privatized firms in which the state was the largest shareholder: state's voting rights declined on average from 85% to 32% (the decrease of median values is even stronger). 17 In firms in which the largest shareholders were families, firms or financial institutions the changes in ownership concentration were less spectacular. [START_REF] Demsetz | The structure of ownership and the theory of the firm[END_REF] and [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF] were first to argue that in equilibrium ownership structure is determined endogenously, trading off costs and benefits of ownership concentration. They suggested that whether shareholders hold large or small portions of firm equity depends on specific firm's characteristics and on its contracting environment. Following Demsetz and Lehn, several author estimated ownership structure expanding the initial specification (see [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF][START_REF] Demsetz | Ownership structure and corporate performance[END_REF].

Determinants of ownership concentration

I follow here these studies using similar explanatory variables for ownership concentration, measured as the share of the voting rights of the largest shareholder; I also augment the previously used specification along the lines discussed in the introduction. In order to distinguish firms by the importance of knowledge related activities and check whether firms with stronger human capital component have more dispersed ownership structure, I use a dummy variable for firms belonging to highly technological industries. I rely on the Warsaw Stock Exchange classification of listed equities, which distinguishes the segment of innovative technologies. I also use the observable measure of intangible assets as it appears on the balance sheet as a proxy for firm's soft capital. Intangible assets include R&D expenditures, acquired software, licenses, good will, etc.

Several control variables will be included in the regression for ownership concentration:

Size

In the existing empirical studies ownership concentration tends to be negatively affected by firm size [START_REF] Demsetz | The structure of ownership and the theory of the firm[END_REF]Lehn, 1985, Himmelberg et al. 1999). This result reflects probably wealth limitations (it is simply more costly to acquire large portion of equity in larger firms) and the concern with risk diversification. But size is also sometimes considered as a proxy for managerial discretion [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF]; in that case we expect size will positively affect ownership concentration. Size may also be viewed by potential shareholders as a proxy for reputation. I measure size as the natural logarithm of the firm's sales. 18 Year dummies Year dummies are included to control for macroeconomic shocks common to all firms. The use of these dummies is particularly important in an economy undergoing profound institutional and systemic changes.

Identity of shareholders

Ownership concentration may depend on the identity of the equity holders. For instance, financial institutions are less likely to accumulate large portion of equity in a given company than an affiliated industrial firm. I distinguish four types of owners: family, the state (the Treasury, municipality or a government agency), financial institution (bank, insurance company or investment fund) and industrial firm. A firm is classified as being controlled by a family when there is an individual or a group of individual belonging to the same family who control the largest voting block of shares. I identify families relying on family surname. I also use a dummy if a foreign investor holds at least 20 % of voting rights in firm's equity.

Current profitability

This variable, defined as net profit to sales, is often used in ownership equation 19 as a proxy for agency problems.

Volatility (risk)

This is another proxy for agency problems. [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF], [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF] and [START_REF] Demsetz | Ownership structure and corporate performance[END_REF] motivate including risk as a determinant of ownership concentration by the principal agent theory: when the environment is more volatile, it is more difficult for shareholders to monitor managers but there are also more potential benefits from closer supervising the managers (they call it 'control potential'). When firm environment is relatively stable, the argument goes, shareholders have less difficulty to monitor managers. Consequently, it is expected that highly risky firms will have higher ownership concentration. However, [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF] and [START_REF] Aggarwal | Why do managers diversify their firms? Agency reconsiderations[END_REF] also argue that beyond some threshold of idiosyncratic risk, investors may prefer to reduce their exposure. Following this argument I also suppose that the relation between risk and ownership concentration is concave.

I calculate each firm idiosyncratic risk using daily data of stock prices. The data on individual firm daily stock prices were collected from the data base provided by the Warsaw Stock Exchange. For each firm and for each year, I run a regression of firm's daily return on the market return. I use the residual standard deviation in the firm's return, i.e. the standard deviation in the firm's return after the effect of its covariation with the market is taken out.

Number of years of listing

The longer the firm's shares are traded on the stock exchange, the more is known about them and the potential agency problems become less important. It is therefore likely that ownership structure, which can be considered as an instrument of control and an answer to information asymmetries, will become less concentrated.

Firm value

Firm value will be included in the equation for ownership concentration to deal with the potential problem of reverse causality: it has been argued that although ownership may affect performance, ownership structure may also be affected by the quality of the firm. 20 The issue of endogeneity of firm value in ownership concentration equation will be addressed later on, in a simultaneous equations framework. Here, I simply look at robust correlations but to alleviate the problem of endogeneity, use lagged values of firm value.

Industry affiliation

Besides distinguishing companies from the segment for innovative technologies, I follow [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF] and keep dummies for utilities and media. [START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF] suppose that regulated firms (utilities) are less concentrated because regulatory constraints may be a substitute for shareholder monitoring. They also distinguish firms by the potential of control they offer and expect this potential is particularly high in the case of media industry.

Privatization method

Particular privatization method may significantly affect ownership structure of privatized firms, especially during the initial years of listing. For instance, firms privatized in the framework of the Polish mass privatization scheme had initially a uniform ownership structure (the largest shareholder holding 33 percent of shares). 21 For instance, firms privatized in the framework of National Investment Funds programme (a form of mass privatization scheme) had at the time of privatization a uniform ownership structure (the leading NIF had 33% of shares, 27% of shares were uniformly distributed among 14 NIFs, the employees had 15% and the State 25% of shares). In firms privatized through IPO the state has initially an important stake. New firms, when they enter the stock exchange, are often owned by their founders and are likely to have, at least during the first years of listing, a rather more concentrated ownership structure than privatized firms. I classify privatized firms by four privatization methods: IPO, private sale, employee and managerial buy out, or mass privatization scheme (mpp).

Consequently, I use the following model to estimate ownership concentration, defined as the logistic transformation of the share of the voting rights of the largest shareholder (Lvote1) 22 :

(1) where i and t represent the firm and time respectively; size is the logarithm of total sales; profitability is defined as net profits on sales; volatility is defined as standard error of the residual of CAPM equation per year; listing represents the number of years since the first listing; family, finist, state equal to one if, respectively, the largest share of voting rights is held by a member of a family, a financial institution or the state and zero otherwise (firm is a reference group); foreign20 is a dummy equal to one if a foreign investor holds at least 20 % of shares of firm equity; intangibles is the share of intangible assets in fixed assets; Q is defined as the ratio of the market value of equity plus total debt divided by the book value of total assets; media and utilities equal one if the firm belongs respectively to utilities or media industry, and zero otherwise; high-tech equals to one if the firm belongs to the segment of high technology and zero otherwise; mpp, embo and IPO are dummy variables equal one if the firm was privatized, respectively, in the framework of the mass privatization programme, through managerial and employee leveraged buy-out or through public share offering (private sale is a reference group); finally, γ t represent year dummies (to control for common macroeconomic shocks); ε it is a white-noise error.

The results of the OLS regressions are presented in table 6. In columns ( 1) -( 5) the results refer to the whole sample. We can observe how including additional variables increases the explanatory power of the regression which eventually (column ( 5) is quite high: we can explain 26 % of the variation in ownership concentration.

Concerning the measures of knowledge related capital, the results give support to the idea that ownership concentration varies inversely with intangibles and is significantly lower in firms belonging to the sector of high technology. Interestingly, even after controlling for high technology sector, I get significant result on the coefficient of intangibles. This result is quite strong as it could be expected that much of the variation in 'soft capital' could be explained by the industry dummy.

The impact of firm's idiosyncratic risk on ownership concentration is, as expected, positive. In some regressions the results show that risk affects ownership concentration in a non-linear way.

In columns ( 6) and ( 7) I perform separate regressions of ownership concentration on identical sets of explanatory variables for two smaller samples of privatized and new firms. We can see that the significant result on the proxies for uncertainty, obtained in the entire sample, is driven by new firms: intangibles and the dummy for the segment of high technology are insignificant in privatized firms. This can be explained by the fact that only one privatized firm (14 observations) belongs to the sector of high technology and intangibles are on average three times higher in 'new' firms than in privatised firms. It turns out that the regression is able to explain much better ownership concentration in privatized than in new firms: in the former R² equals 0.33 and the latter 0.21. This suggests that 'new' firms are closer to an 'equilibrium' ownership structure. In privatized firms more adjustment is probably needed. In the last column ( 8), adding privatization methods as additional explanatory variables increases R². The way firms were privatized significantly affects their ownership concentration, especially during the initial years of listing. 23 Table 6 does not give support to reverse causality hypothesis: the coefficient of the firm value is insignificant. But to properly deal with the issue of reversed causality, we need a simultaneous equations framework (see section 5 below).

Ownership concentration and firm value.

In order to test the impact of ownership concentration on firm value, I estimate the system of simultaneous equations in which the first equation is the equation ( 1) for ownership concentration and the second equation is the following equation ( 2) for Tobin's Q:

(2) where i and t represent the firm and time respectively; Q is defined as the ratio of market value of equity plus book value of total debt to book value of total assets; Lvote1 is defined as the logistic transformation of the percentage voting rights held by the largest shareholders; initial profitability is the ratio of net profit to total assets averaged over the three years preceding the publication of the prospectus; current profitability is defined as net profit to sales; size is the logarithm of total sales; family, finist and state are dummy variables equal to one if, respectively, the largest share of voting rights is held by a member of a family, a financial institution or the state (firm is a reference group); foreign20 is a dummy variable equal to one if a foreigner holds at least 20% of firm equity, and zero otherwise; intangibles is the share of intangible assets in fixed assets; media, utilities and high tech represent dummy variables for the three industries; mpp, embo and IPO are dummy variables equal one if the firm was privatized, respectively, in the framework of the mass privatization programme, through managerial and employee leveraged buy-out or through public share offering (private sale is a reference group);λ t represent year dummies (to control for common macroeconomic shocks); and ε ' it is a white-noise error.

Q it = δ 0 + δ 1 Lvote1 it + δ 2 initial_profitability
The necessary conditions for identification of such a simultaneous equations system are met because we include exogenous variables plausibly affecting only ownership concentration or firm value, not both of them. In the first equation, standard deviation and variance of volatility are used as instruments. These instruments were used in the literature and I follow this strategy for the sake of comparability.

Concerning the second equation, initial profitability, i.e. average firm profitability before it is listed on the stock exchange, is likely to affect firm performance; but there is little chance that it directly affects ownership concentration. The presence of current profitability in ownership concentration equation makes this identifying restriction assumption even more convincing.

Let me note that capital structure does not appear in this model. Debt is clearly one of the mechanisms of control that should be taken into account in a complete system of equations. However, including it would require estimating a much bigger system of equations taking into account a two-way relation of debt and performance and the relation between debt and ownership structure (see Loderer and Martin, 1997). This will certainly be one of the extensions of this paper.

In another specification not reported here, I have also explored the impact of dual class shares on firm value. Firm with such explicit separation of ownership and control may have important agency problems and may be less valuable than firms in which voting rights are equal cash flow rights. 24 Claessens et al. (2002) found indeed in their study of Asian firms that firm value decreases when the control rights of the largest shareholder exceed its cash flow rights. [START_REF] Lins | Executive ownership and performance: tracking faint traces[END_REF] found that this effect is significant in countries with low shareholder protection. In the sample studied in this paper the coefficient of the dummy variable indicating for each firm if it issues dual-class shares turned out to be insignificant. 25 In table 7, I report the results of OLS and of the second stage of 2SLS regressions for Tobin's Q.

26 I am mainly interested in the coefficient of ownership concentration δ 1 , other variables being used to control for various observable firm characteristics. For instance, the identity of the largest owner is included because different owners may have different incentives and capacities to perform efficient monitoring. So the relationship between concentrated ownership and firm performance may be sensitive to the type of the controlling shareholder. In the case of transition economies, it was notably argued that foreign investors bringing about their competence and the knowledge of market economy might have important positive effect on firm performance. 27 Let us note that in the sample of Polish firms considered in this paper the impact of foreign investors on firm value remain ambiguous.

We can observe that the increase in the share of the largest owner positively affects firm value and that this result in OLS regression is driven by the sub-sample of privatized firms (in 'new' firms, the coefficient of ownership concentration is not significantly different from zero). Durbin-Wu-Hausman test of the endogeneity of ownership concentration does not allow rejecting the hypothesis of the correlation between ownership concentration and the error term. Therefore, in columns ( 5) -( 7) I present the results for the 2SLS. We can see that after controlling for endogeneity, the impact of ownership concentration on Tobin's Q is stronger as compared with OLS results. 28

Conclusions

The main findings of this paper are as follows. Concerning the determinants of ownership concentration, the empirical results give support to the hypothesis that firms belonging to the sector of high technology have lower ownership concentration. The results reveal great heterogeneity across firms and over time. In 'new' firms, more similar to 'normal' firms in developed market economies, the impact of firm's specific uncertainty proxied by the importance of knowledge related activities is important. In privatized, previously state-owned firms, ownership concentration is highly sensitive to the legacy of privatization methods: important explanatory variables during the early years of listing, they loose, however, their significance after a couple of years. This suggests that shareholders progressively adjust their ownership structure to firm specific constraints and the requirements of firm environment. When firm's ownership structure approaches an 'equilibrium' level, it becomes more sensitive to variables representing firm specific risk and uncertainty.

In the case of privatised firms, OLS regression does not give consistent results and we have to take into account the endogeneity of ownership concentration. Consequently I estimate a system of simultaneous equations, in which ownership is the dependent variable in the first equation and firm value is the dependent variable in the second equation. It turns out that the impact of ownership on performance is even stronger when we control for the endogeneity of ownership.

More generally, answering the question what the characteristics of 'good' ownership structure are may depend on the underlying theory of the firm. The initial view of the advantages of ownership concentration in joint stock companies characterized by the separation of ownership and control was determined by the concern about the opportunistic behavior of managers. Far from being considered as entrepreneurs, managers of large corporations became even treated as civil servants: Schumpeter (1943) argued that the entrepreneurial function became obsolete because of the routinization of innovation. The growing importance of knowledge and human capital in the operation of firm shifts the focus of concern: excessive ownership concentration may stifle managerial initiative. This may be particularly true, and the results obtained in this paper support this hypothesis, in firms with high share of knowledge related activities. [START_REF] Helwege | Why do firms become widely held? An Analysis of the dynamics of corporate ownership[END_REF]. Exploring what makes US firms becoming widely held over time they find that variables motivated by agency theory are weak in explaining the evolution of ownership and stock market variables are important. 2 Carlin and Mayer (2003) examine the possibility that firms in some industries may require specific types of ownership and control. [START_REF] Rajan | The governance of the new enterprise[END_REF] argue that the theory of the firm should be revisited because of a significant structural movement towards the importance of human capital, at the expense of other, more tangible assets. 3 Demsetz (1983) considers that one of the costs of concentrated ownership is the disincentive effect of monitoring. Positive trade-off between uncertainty and incentives in the context of pay-for-performance contracts is analyzed by [START_REF] Prendergast | The tenous trade-off between risk and incentives[END_REF]. He argues that contrary to the standard prediction of agency theory, firms delegate decision-making power more in uncertain environments. It happens because a principal may have little idea what the right kinds of effort in such cases are and the marginal returns to delegation are likely to be higher in more uncertain environments. 4 Bolton and von Tadden (1999) argue that the value of monitoring may influence the degree of ownership concentration. 5 Intangibles include R&D expenditures, patents, brands, goodwill and any other nonmonetary assets without physical substance. 6 Moral hazard theories predict that in firms with more soft assets there is more scope for discretionary spending, so this variable should positively affect ownership concentration. In order to take into account the possibility that more volatility in firm's environment increases the value of monitoring, in the regressions for ownership concentration I will also include a proxy for firm idiosyncratic risk. 7 For the review of the literature see [START_REF] Shleifer | A survey of corporate governance[END_REF]. 8 Also see [START_REF] Hermalin | The effects of board composition and direct incentives on firm performance[END_REF] 9 Hausman test does not allow using random instead of fixed effects. 10 Additional arguments comes from Pindado and de la Torre ( 2004) who tried to identify the main source of endogeneity of ownership and found that that, in a sample of Spanish firms, it is rather due to the simultaneity between ownership and firm value than to unobservable heterogeneity. 11 Kahn and Winton (2002) predict a negative correlation between firm performance and ownership concentration. 12 I do not include banks and other financial companies because they have specific problems of valuation and regulation, which would make the comparison difficult. 13 See [START_REF] Glaeser | Coase versus the Coasians[END_REF] for the description of the stringent regulation of the securities market in Poland. 14 For details of the National Investment Funds program see [START_REF] Grosfeld | The emergence of large shareholders in mass privatized firms: Evidence from Poland and from the Czech Republic[END_REF]. 15 [START_REF] Helwege | Why do firms become widely held? An Analysis of the dynamics of corporate ownership[END_REF] show that US companies' ownership also becomes less concentrated following their IPO. 16 The information provided in tables 4 and 5 should be taken with caution as the sample changes across years. We do not know to what extent changes in ownership concentration are driven by changes in the sample or by changes within firms. 17 Let us note that the equity holdings of the state in 'new firms' seem high but these numbers concern a very limited number of firms (1-3). 18 As size will also be included in the regression for Tobin's Q, I use sales rather than assets to avoid a spurious correlation with the denominator of Tobin's Q (see Loderer and Martin, 1997). 19 See, for instance, [START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF] 20 Kole (1994) provides evidence of a reverse causality: performance affects ownership rather than the other way round. 21 In a recent paper, [START_REF] Boubakri | Postprivatization corporate governance: The role of ownership structure and investor protection[END_REF] include privatization method in their estimation of cross-firm differences in ownership concentration. 22 Such logistic measure is currently used in the literature (see for instance [START_REF] Demsetz | The structure of ownership and the theory of the firm[END_REF][START_REF] Demsetz | The structure of ownership: Causes and consequences[END_REF][START_REF] Himmelberg | Understanding the determinants of managerial ownership and the link between ownership and performance[END_REF]. It converts a bounded number (the simple percentage measure which varies from 0 to 100%) to an unbounded figure. 23 The results of separate regressions for the early and late years of listing confirm this hypothesis (results available on request).

  Lvote1 it = β 0 + β 1 size it + β 2 current_profitability+β 3 volatility it + β 4 volatility² it + β 5 listing it + β 6 family it + β 7 fininst it + β 8 state it + β 9 foreign20 it + β 10 intangibles it + β 11 Q it-1 + β 12 media i + β 13 utilities i + β 14 hightech i + β 15 mpp i + β 16 embo i + β 17 IPO + γ t +ε it

  + δ 3 current_profitability it + δ 4 size it + δ 5 listing it + δ 6 family it + δ 7 fininst it + δ 8 state it + δ 9 foreign20 it + δ 10 intangibles it +δ 11 media+ δ 12 utilities + δ 13 hightech+δ 14 mpp+δ 15 embo+δ 16 IPO+ λ t +ε ' it

  * I am grateful to Thierry Tressel, Philippe Aghion and Laszlo Halpern for their comments and suggestions and to Malgorzata Kalbarczyk for excellent research assistance. Financial support of the Japan Europe Cooperation Fund through the EBRD research program on "Institutional Development and International Integration: Strategies for Catch-up Growth and EBRD Operations" is gratefully acknowledged.

Table 1 : Description of the sample: number of new and privatised firms

 1 Description of the sample of non-financial firms listed on the Warsaw Stock Exchange used in this study: distribution of listed firms included in the sample by year and the origin of the firm (new versus privatized). The number of observations says for how many firms we have data on the ownership structure; financial data may be missing for some of the observations.

	Year	Number	Number of	Number of
		of	privatized	new
		observations	firms	firms
	1991	8	8	0
	1992	5	5	0
	1993	5	4	1
	1994	34	31	3
	1995	49	42	7
	1996	66	52	14
	1997	197	140	57
	1998	214	148	66
	1999	224	151	73
	2000	234	146	88
	2001	234	144	90
	2002	229	139	90
	2003	214	124	90

Table 2 . Descriptive statistics

 2 Characteristics of the sample of non-financial firms listed on the Warsaw Stock Exchange; 2003

	Variables	Definition	Mean	Median	Standard
					Deviation
	Tobin's Q	(market value of equity + book	1.30	0.99	0.97
		value of total debt)/ book value
		of total assets
	Initial	Average net profit/total assets,	0.22	0.19	0.20
	profitability	for the years preceding the
		publication of the prospectus
	Ownership	Share of the voting rights of	0.43	0.40	0.23
	concentration	the largest shareholder
	Firm size	Logarithm of total sales	11.10	11.26	2.07
	Years of	Number of years since the first	5.57	5.0	2.66
	listing	listing
	Intangibles	The share of intangible assets	0.02	0.003	0.04
		in fixed assets
	Operating	Net profit/sales	-0.34	0.02	3.88
	income
	Volatility	Standard error of the residual	3.70	3.35	2.06
		of CAPM equation

Table 3 : Differences in means of the main characteristics between privatized and new firms

 3 Characteristics of the sample of privatized and 'new' non-financial firms listed on the Warsaw Stock Exchange; 2003. See table 2 for the definition of the variables. The last column provides the t-statistics for the differences in means between privatized and 'new' firms. Significance at the 1%, 5%, and 10% level is denoted ***, **, and *, respectively.

	Variable	Privatized	New	t-statistics
	Tobin's Q	1.19	1.50	-2.07**
	Initial profitability	0.21	0.26	-1.45
	Ownership	0.41	0.47	-1.87*
	concentration
	Firm's size	11.36	10.79	1.98**
	Years of listing	6.48	4.14	7.46***
	Intangibles	0.01	0.03	-2.76***
	Operating income	0.52	-0.11	-0.74
	Volatility	3.92	3.33	1.80*

Table 4 : The change in ownership concentration in listed firms by their origin (privatized/new)

 4 The table presents summary statistics on ownership concentration measured as the share of the voting rights of the largest shareholder in our sample of non-financial firms listed on the Warsaw Stock Exchange between 1991 and 2003. The first 8 years of listing are reported. Ownership data before the first listing comes from the offering prospectuses. N represents the number of observations

		Voting rights of the largest shareholder by the number of years of listing
	Sample	Prospectus	1	2	3	4	5	6	7	8
			year	years	years	years	years	years	years	years
	All
	Mean	0.5286	0.5005	0.4070	0.3982	0.4206	0.4323	0.4123	0.3949	0.3725
	Median	0.4668	0.43	0.34	0.33	0.3338	0.3509	0.3518	0.34	0.325
	N	257	257	234	220	221	206	183	157	103
	Privatized
	Mean	0.5177	0.4894	0.3631	0.3618	0.3878	0.4033	0.3908	0.3960	0.3750
	Median	0.4195	0.3651	0.329	0.3202	0.3299	0.3291	0.3333	0.345	0.3252
	N	146	148	137	138	143	140	128	118	80
	New
	Mean	0.5428	0.5156	0.4690	0.4595	0.4807	0.4938	0.4625	0.3914	0.3638
	Median	0.49	0.4738	0.4521	0.4168	0.47	0.5	0.4396	0.3338	0.3236
	N	111	109	97	82	78	66	55	39	23

Table 5 : The change in ownership concentration in listed firms by their origin and identity of the largest owner

 5 The table presents summary statistics on the change in ownership concentration (during the first six years of listing) measured as the share of the voting rights of the largest shareholder in a sample of non-financial firms listed on the Warsaw Stock Exchange between 1991 and 2003. I consider four types of owners: families, financial institutions, industrial firms and the government. N represents the number of observations.

	Identity of the	Voting rights of the largest shareholder during the first six years of listing
	largest equity holder	Prospectus	1 year	2 years	3 years	4 years	5 years	6 years
	Family
	Privatized
	Mean	0.297	0.309	0.270	0.289	0.325	0.341	0.328
	Median	0.284	0.284	0.226	0.225	0.250	0.302	0.305
	N	14	14	13	17	21	25	26
	New firms
	Mean	0.56	0.522	0.478	0.438	0.435	0.455	0.457
	Median	0.5	0.480	0.451	0.384	0.361	0.450	0.42
	N	69	70	53	47	42	35	29
	Financial
	institution
	Privatized
	Mean	0.310	0.293	0.267	0.271	0.292	0.276	0.277
	Median	0.33	0.33	0.299	0.294	0.269	0.254	0.250
	N	55	52	59	47	40	33	28
	New firms
	Mean	0.264	0.295	0.349	0.281	0.437	0.425	0.270
	Median	0.179	0.198	0.335	0.263	0.370	6.274	0.231
	N	8	9	8	6	5	4	3
	Firm
	Privatized
	Mean	0.525	0.460	0.459	0.455	0.468	0.506	0.484
	Median	0.511	0.450	0.479	0.461	0.466	0.498	0.48
	N	34	38	46	53	65	66	61
	New firms
	Mean	0.568	0.568	0.467	0.528	0.58	0.575	0.493
	Median	0.557	0.569	0.453	0.446	0.5526	0.558	0.53
	N	29	25	31	24	27	25	22
	State
	Privatized
	Mean	0.849	0.796	0.495	0.391	0.384	0.338	0.324
	Median	0.999	0.999	0.503	0.315	0.349	0.292	0.275
	N	43	44	19	21	17	16	13
	New firms
	Mean	0.667	0.669	0.645	0.602	0.751	0.513	0.513
	Median	0.775	0.780	0.780	0.667	0.751	0.513	0.513
	N	3	3	3	3	2	1	1

Table 7 : Ownership concentration and firm value: OLS and 2SLS The

 7 table shows the regression results for Tobin's Q in the sample of non-financial firms listed on the Warsaw Stock Exchange. Lvote1 is the logistic transformation of the percentage voting rights held by the largest shareholders. See table 2 for the definition of other variables. All regressions include time fixed effects, dummies for media, utilities and high tech industries, dummies for the type of the largest owner and constant term. Dummies for privatization methods are included in regressions for all and privatized firms. Standard errors are presented in parentheses. Significance at the 1%, 5%, and 10% level is denoted ***, **, and *, respectively.

	Variables	All	All	New	Privatized	All	New	Privatized
		OLS	OLS	OLS	OLS	2SLS	2SLS	2SLS
		(1)	(2)	(3)	(4)	(5)	(6)	(7)
	Lvote1	0.025	0.028	0.032	0.025	0.975	0.749	0.497
		(0.013)*	(0.013)**	(0.037)	( 0.011)**	(0.229)***	(0.338)**	(0.168)***
	Firm size	-0.014	-0.024	-0.071	0.012	-0.102	-0.099	-0.043
		(0.018)	(0.018)	(0.037)**	(0.019)	(0.039)***	(0.054)*	(0.034)
	Current profitability	-0.038	-0.037	-0.036	-0.039	-0.022	-0.050	-0.029
		(0.010)***	(0.009)***	(0.047)	(0.007)***	(0.017)	(0.065)	(0.010)***
	Years of listing	-0.006	-0.012	-0.071	0.006	00.129	0.091	0.068
		(0.014)	(0.014)	(0.035)*	(0.013)	(0.044)***	(0.087)	(0.027)***
	Intangibles	-0.305	0.057	0.635	-0.752	3.157	3.344	-0.560
		(0.737)	(0.731)	(1.311)	(0.921)	(1.562)**	(2.331)	(1.239)
	Foreign20	0.170	0.156	0.311	0.078	-0.596	-0.377	-0.257
		(0.063)***	(0.062)***	(0.172)*	(0.055)	(0.208)***	(0.385)	(0.135)*
	Initial profitability		0.683	0.798	0.576	0.817	0.547	0.567
			(0.127)***	(0.240)***	(0.155)*	(0.257)***	(0.365)	(0.168)***
	F-stat 1 st stage					7.75	3.10	5.00
						(0.000)	(0.03)	(0.002)
	R2	0.254	0.273	0.264	0.235	.	.	.
	N	1185	1185	365	820	1002	297	705
								22

Table 6: Determinants of ownership concentration: OLS estimates

The table shows the regression results of ownership concentration in the sample of non-financial firms listed on the Warsaw Stock Exchange, measured by the logistic transformation of the percentage voting rights held by the largest shareholders (Lvote1), on the set of explanatory variables. See table 2 for the definition of other variables. All regressions include a constant term and year fixed effects.. Robust standard errors are presented in parentheses. Significance at the 1%, 5%, and 10% level is denoted ***, **, and *, respectively.

Variables

All ( 1) 4) All ( 5) New ( 6) Privatized ( 7) Privatized ( 8)