State Ownership at the Oslo Stock Exchange. Bernt Arne Ødegaard

Transcription

1 State Ownership at the Oslo Stock Exchange Bernt Arne Ødegaard

2 Introduction We ask whether there is a state rebate on companies listed on the Oslo Stock Exchange, i.e. whether companies where the state is a major owner are priced lower than they would be had the state not been there as an owner. We first ask whether there are potential reasons for this to happen, before looking at two empirical investigations that speaks to this.

3 Theory Looking at: Regular companies, listed on a stock exchange. Implicit goal: Maximizing the value of the equity stake. Enter the state (or more generally, government) as an owner some fraction of a company s stocks are owned by a governmental owners. One view: This does not make any difference. The company is run by its management to maximize value, the state as an owner does not affect that.

4 Theory More complicated view: Agency view, (Jensen and Meckling, 1976). Firm is run as a result of interaction between various groups. In particular, the three groups Equity owners Creditors Management are all interested in the running of the firm, but have different objectives.

5 Theory They also have different saying in the running of the firm. Objectives: Shareholders: Maximize the value of outstanding equity. Creditors: Maximize probability of full repayment of debt. Managers: High salaries (Can be justified by increasing firm size) Easy life Minimize probability of bankruptcy (Their human capital to some (more or less) degree bound to their current employment.)

6 Theory These different preferences may impose nonvalue maximizing behaviour. Why? Informational asymmetries makes it impossible for providers of capital to write contracts that make managers always act in their best interest.

7 Theory Mechanisms that indirectly prevent the managers of the firm from deviating too far Equity ownership concentration If ownership concentrated with few investors. Each investor has incentives to monitor management. The investor also has power, both voting power representation on board of directors Cost of large stake in a firm: Limited diversification. Debt ownership concentration: Suppose debt is concentrated with a few investors/banks. Debtholders have incentives to monitor firms performance. Can threathen to withold funds, gives leverage over management s decisions. But debtholders only care about lower part of cashflow distribution. This is the main features of the corporate governance problem.

8 Theory Where does the state as an owner fit? As a large, external, owner. (Concentrated ownership). Issue: Who influences how the state uses its power to affect running of the firm (voting/investor representation on board). Bureaucrats (e.g. ministry of industry)? Do these have incentives to monitor the running of the firm? Politicians? May have different (political) objectives that conflict with efficient running of the firm.

9 Estimation How can one estimate whether the presence of the state as a large owner affects firm value? Look at two types of estimation.

10 Governance modelling Consider the regression Firm value = f(corporate Governance) Here it is impossible to observe directly the corporate governcance mechanism, so one specifies a bunch of proxy variables believed to be part of the governance of a firm. Typical Governance variables in such studies Ownership concentration (external owners) Type of the large owners Inside concentration Corporate Financing (Debt/Equity) Product market...

11 Governance modelling The estimate of firm value is usually Tobin s Q. In this type of study add fraction owned by state. See Table

12 Governance Performance regression with state Q Variable coeff constant (0.00) Herfindahl index (0.00) Insider ownership fraction (0.00) Kvadrert(Insider ownership fraction) (0.00) Fraction owned directly by state (0.22) Fraction owned by foreign owners (0.00) Fraction owned by financials (0.56) Fraction owned by nonfinancials (0.88) ln(company Size) (0.01) Product market: 10 Energy (0.00) Product market: 15 Material (0.00) Product market: 20 Industry (0.00) Product market: 25 Consumer Discretionary (0.00) Product market: 30 Consumer Staples (0.00) Product market: 45 IT (0.00) n 1327 R So for the whole period, the state ownership is not a significant determinant of Q.

13 The Norwegian state portfolio returns Example application: Norwegian Government Direct Ownership at the Oslo Stock Exchange. Government: hands off policy companies on the Oslo Stock Exchange Even those where the State holds a majority (> 50%) or blocking minority (> 33%). listed companies should act so that they maximize the stock value, ie. act in the shareholders interest. The state is not supposed to pursue political objectives that makes companies where they are majority owners deviate from value maximization.

14 How to empirically investigate whether this is the case? A prediction we can check at is whether the companies on the exhange with state majority ownership earns less returns than they should. This is a question we can ask as a portfolio performance question. We evaluate the state portfolio.

15 Dataset: the monthly returns from the government s portfolio (or part of it, Statoil is actually not here since that is owned by a different department). The returns are from 1992 to 2008.

16 The annualized return on this portfolio is 13.6% per year. Another nice way to vizualize such data is to plot the evolution of the implied wealth from investing in this portfolio. We show one way to generate this, by adding the monthly return month by month.

17 Evolution of state portfolio wealth

18 An obvious first try is to look at an alternative investment, such as a market portfolio. Evolution of EW market portfolio

19 Evolution of state portfolio compared to market portfolios state ew market vw market

20 But just comparing things to the market is not what we should be doing. Instead, this is of course when we need a model saying: What should the portfolio return have been? In particular, we need to formulate this as a finance question: What is the expected return on a portfolio with the same risk as the state portfolio?

21 The classical performance measure is the calculation of an alpha relative to the CAPM. Let r p be the return on the state portfolio, r f be the risk free rate, r m the return on a market portfolio. Consider the CAPM relationship r pt = r ft + b p (r mt r ft ) Rewriting in excess return terms er pt = r pt r ft er mt = r mt r ft We see that the CAPM relationship is r pt r ft = β p (r mt r ft ) or er pt = β p (er mt ) To get a testable model we consider the regression er pt = a p + b p er mt + e pt If the CAPM holds a p = 0.

22 To calculate excess returns: need an estimate of a risk free rate. We use montly observations of NIBOR. Simple OLS estimates: alpha estimates and their t-stats ew: (0.918) vw: ( 1.86) Using the ew portfolio as the market, we have a negative (albeit not significant) alpha.

23 Produces the output > lm(formula="ers ~ ermew") Coefficients: (Intercept) ermew > lm("ers ~ ermvw") Coefficients: (Intercept) ermvw

24 The complete results of the analysis > summary(runs.ew) Residuals: Min 1Q Median 3Q Max Coefficients: Estimate Std. Error t value Pr(> t ) (Intercept) ermew <2e-16 *** Residual standard error: on 214 degrees of freedom Multiple R-squared: ,Adjusted R-squared: F-statistic: on 1 and 214 DF, p-value: < 2.2e-16

25 VW > runs.vw=lm(formula="ers ~ ermvw") > summary(runs.vw) Residuals: Min 1Q Median 3Q Max Coefficients: Estimate Std. Error t value Pr(> t ) (Intercept) ** ermvw < 2e-16 *** Residual standard error: on 214 degrees of freedom Multiple R-squared: ,Adjusted R-squared: F-statistic: on 1 and 214 DF, p-value: < 2.2e-16

26 This result relies on the CAPM as the true model of returns. An alternative model of returns than CAPM is very popular among academics is the Fama French 3 factor model. Essentially, this model uses two additional factors SMB and HML to explain asset returns r pt = r ft + b p (r mt r ft ) + b HML HML + b SMB SMB Estimate the alpha in this setting.

27 > runs.ew=lm(formula="ers ~ ermew + SMB + HML ") > summary(runs.ew) Residuals: Min 1Q Median 3Q Max Coefficients: Estimate Std. Error t value Pr(> t ) (Intercept) ermew <2e-16 *** SMB <2e-16 *** HML Residual standard error: on 212 degrees of freedom Multiple R-squared: 0.66,Adjusted R-squared: F-statistic: on 3 and 212 DF, p-value: < 2.2e-16

28 > runs.vw=lm(formula="ers ~ ermvw + SMB + HML ") > summary(runs.vw) Residuals: Min 1Q Median 3Q Max Coefficients: Estimate Std. Error t value Pr(> t ) (Intercept) ermvw < 2e-16 *** SMB *** HML * Residual standard error: on 212 degrees of freedom Multiple R-squared: ,Adjusted R-squared: F-statistic: on 3 and 212 DF, p-value: < 2.2e-16

29 Changing risk levels? When we run the regression er pt = a p + b p er mt + e pt we are assuming that the risk is constant. But the portfolio composition is changing over time. (See the data on the shares owned.) One way deal with that is to let the beta change over time: er pt = α p + β pt er mt

30 If we have an estimate of beta we can simply plug in the estimated beta, calculate the ex post alpha, and take the average. Portfolio beta estimates. Time series of estimated beta β pt = i w i β it where β it is a rolling beta estimate for the beta of each stock

31 Doing the calculations we find the ex post average abnormal returns Histogram: Ex post excess returns relative to ew portfolio

32 Histogram: Ex post excess returns relative to vw portfolio

33 Calculating t-stats for testing whether the estimated excess returns are different from zero: >> t=mean(e_ew)/(std(e_ew)/sqrt(t)) t = >> t=mean(e_vw)/(std(e_vw)/sqrt(t)) t = We actually reject the null using the value weighted portfolio as a comparison. The state portfolio underperforms relative to the value weighted portfolio.

34 Michael C Jensen and William H Meckling. Theory of the Firm: Managerial behavior, Agency costs and Ownership structure. Journal of Financial Economics, 3: , October Bernt Arne Ødegaard. Statlig eierskap på Oslo børs. Praktisk Økonomi og Finans, 25(4), 2009.