ABSTRACT

COLLEGIO CARLO ALBERTO

DIPLOMA IN ECONOMICS DISSERTATION

POLITICAL INSTABILITY AND SOVEREIGN WEALTH FUNDS INVESTMENTSCandidate: Alberto RaccaSupervisor: Prof. Bernardo Bortolotti

July 2011ABSTRACT

Investments ofSovereign Wealth Funds(SWF)in somewesterncompanies and financial institutionshave spurredconcerns abouta newkind of capitalismthat might subvert theinternational economic system.The analysisand research into theSWFhas beenfocusedon the characteristicsof the fundin termsof transparency,disclosure of informationand accountability.However, another element of risk could arise in light of the close interconnection between SWF and political regimes. Evidence for this hypothesis can be found in the recent political turmoil that is changingthe geopoliticsof the MiddleEast. The instability of thecountry where theSWFis based could bear a negative effect on the performance of an invested company, thus limiting returns to its shareholders.The aim of this short essay is to describe the key features of SWFs, their most recent behaviour, and the economic implications of political riskrelated SWF investment for host countries and invested companies. After pointing out a new market failure, I set forth some tentative recommendations that by regulating SWF investment aim to preserve free capital flows while fostering social progress in resourcerich, non democratic countries.1. INTRODUCTION

The shift in the distribution of wealth around the world is impressive: financial power, so long concentrated in the developed economies, is dispersing. Oil-rich countries and Asian central banks are now among the worlds largest sources of capital. Moreover more, the influx of liquidity these players have brought is enabling hedge funds and private-equity firms to soar in the pecking order of financial intermediation. In 2006 oil-exporting countries became the worlds largest source of global capital flows, surpassing Asia for the first time since the 1970s (Exhibit 2). These investorsfrom Indonesia, the Middle East, Nigeria, Norway, Russia, and Venezuelainclude sovereign wealth funds, government-investment companies, state-owned enterprises, and wealthy individuals. This flood of petrodollars comes from the tripling of world oil prices since 2002 and the steady growth in exports of crude oil, particularly to emerging markets. A large part of the higher prices paid by consumers ends up in the investment funds and private portfolios of investors in oil-exporting countries. Second in size to petrodollars are the reserves of Asias central banksreserves that have grown rapidly as a result of rising trade surpluses, foreign-investment inflows, and exchange rate policies. In 2006, Asias central banks held $3.1 trillion in foreign-reserve assets, 64 percent of the global total and nearly three times the amount they held in 2000. Compared with petrodollars, these assets are concentrated in just a handful of institutions. China alone had amassed around $1.4 trillion in reserves by mid-2007. Unlike investors with petrodollars, Asias central banks have channeled their funds into conservative investments, such as US treasury bills. According to estimates by the end of 2006, these institutions had $1.9 trillion more in foreign reserves than they needed for exchange rate and monetary stability.

Asovereign wealth fund(SWF) isan institutioncontrolled bya governmentaiming to obtain a return higher than the risk-free rate for its capital.The sourceof the assetsmay bedifferent in nature, rangingfrom the proceedsof thesale ofnatural resources inoil-exporting countriesto the reservesaccumulatedthanks totrade surplusesand budget policies. Starting from this definition a recent study by Chris Balding from Irvine University sheds light on the portfolios of the main SWF, dispelling few myths about them. First,thegeographical allocationof theirportfoliosshowsa clear preference for domesticinvestment.Theaverage percentage ofassetsinvestedwithin its borders by the Abu DhabiInvestment Corporationand by Singapore'sTemasek andGICis above 70%,whichqualifies themmore asactorsof local developmentrather thanthe new barbarians at the gate.SWF seldomacquiredcontrolling stakes inacross-border investmentsand mostlykepta lowprofile in thecorporategovernanceof invested companies in orderto avoida politicalbacklash:one is truly sovereign onlyin his own country,abroadpowerbelongs to others. Nevertheless,weare faced with anew and interestingphenomenoncharacterized by an increasing roleof governments and regime-connected institutions thatposes new legal and diplomatic challenges.In an article in theFinancial Timeslast year, Larry Summers, a former American treasury secretary, wrote that a signal event of the past quarter-century has been the sharp decline in the extent of direct state ownership of business as the private sector has taken ownership of what were once government-owned companies. Yet governments are now accumulating various kinds of stakes in what were once purely private companies through their cross-border investment activities. Mr Summers called for a new policy: Governments are very different from other economic actors. Their investments should be governed by rules designed with that reality very clearly in mind.

2. POLITICS AND INVESTMENT CHOICES OF SWFsIn the Westwe can witness a widevariety ofreactionsto the adventof theSWFs: they werecelebrated asthe newRothschild,saviorsof the financial systemand at the sametimewere feared as "Trojan horses"behind whicha dark designof conquestwas to be hidden.MorganStanleyestimates thatin 2007 alone,SWFs haveinvested $69 billionin theU.S. financial system.Evenif allSWF together holdonly 2%of stocks tradedin the worldtheyhavemoreequity than all privatefunds, andmorecapital than allhedge funds,as shownin the table:these numbersare enough to frighten manyWesternpolicy makers.TheoreticallySWFhave many things in common withother funds andshould aim to the same objectives ofpension funds orcompanies who manage theirinvestmentsin along term perspective. However,the creation and funding of SWFs isthe resultof specificpolicies pursued by governmentsor central banks,mostlyfrom countries withauthoritariansystems of government and still obscuredecision making processes.The weight ofthe SWFin the financial marketscombined with thepotentialunreliability ofthose at their helmis the largestelement ofriskas evidencedby E.Truman(Sovereignwealth funds: theNeed forGreaterTransparency andaccountability) that invokesthe creation ofan authoritysetting internationalstandardsaimed at guaranteeingthe independence of thegovernance and thefull transparencyand disclosure of sensitive information relative to the operations carried out by the fund.The key issue is thereforethe extent to which politics influencesthe investment decisionsof SWFs:Avendano andSantiso (SWFInvestments arepolitically biased? ComparingMutualFunds and SWF)havecompared cross-borderinvestmentpolicies of SWF Mutualfundsin somekey areas.Here aresummarizedthe results.

Political regime in the sending and recipient countries. Although it is not surprising to find differences in the political regime of sending countries (sovereign wealth funds regimes tend to be less democratic), A&S find that sovereign wealth funds investments are not different from mutual funds when it comes to the political regime characteristics of the destination countries in cross-border investments. This evidence suggests that both sovereign wealth funds and mutual funds do not discriminate by this criterion in their asset allocation and invest indifferently in both democratic and autocratic regimes. Comparative portfolio

The portfolio characteristics of sovereign wealth funds and mutual funds (i.e. holder style, capitalization group style, turnover, P/E ratio, dividend yield, etc) immediately appear as very similar, although SWFs funds portfolios do however show a slightly lower beta, higher price-to-earnings ratio, higher sales growth and dividend yield, and lower price-to-book ratio.

Governance characteristics

Looking at internal governance characteristics (transparency, use of benchmarks, credit rating restrictions, etc.) we find that mutual funds have higher transparency levels, their investment strategy is communicated more clearly, the use of benchmarks is more frequent, investments are more constrained by credit rating minimums, and their policy towards specific investments is more defined. This suggests a gap in the investment policies between the two groups. When comparing these same characteristics between OECD and non-OECD sovereign wealth funds or between commodity and non-commodity funds, internal differences in their investment governance and strategies are accentuated.

Technology transferMuch hasbeen saidon this subjectand this ideahas been the justificationbehindmuchpolitical lobbying thatcalled forstricterstandardsand improved controlsofSWFinvestments:today, however,data do notreveal anythingsignificant.In factbe verydifficult for a ChineseSWF to take over a strategic U.S. oilcompany, asevidenced by thetakeover attemptof UnocalbyCNOOC: it was notasovereign fund,but the argumentsfor rejectinga possibledealwouldin fact be the same.Such actionshave never taken place because they arepolitically risky(Unocalcasedocet) and rarely successful. Countriesveryinterested in the technologycountriessuch as Chinacould get it quite easily barteringaccess to themost promising marketin the worldwith a gradualtechnologytransfers. This is indeed what happened with high-speed trains, andthe same phenomenon is likely to occurin the aviation sector.

After thisquick overview it seems prettyclear thatcertainarguments usedby politiciansappear flawed andmotivated byrather populism or somenostalgiaof protectionismthanto grounded concerns. This data provide a quite reassuring picture for Western politicians. SWF seem to pursue

commercial objectives whey they invest abroad. But what are the economic implications of

SWF investment for target firms?EFFECTS OF INVESTMENT ON TARGET COMPANY

An often overlooked but crucial problem is the effect of the investment on the performance of the target company. Several competing arguments can be made to explain why an SWF acquisition could influence the performance of the investee company. There are many reasons for this: first, SWFs tend to be large investors with significant ownership position that enables them to play an active monitoring role in management, reducing agency costs and managerial slack. Second, as liquidity providers of last resort, SWFs may alleviate financial constraints in distressed companies. Third, as ultimate owner of the SWF the government can provide business opportunities for the investee company in their country, such as contracts, licenses, market access, etc. Fourth, the SWF could also operate with noncommercial objectives against the investee company by channelling

corporate resources and technologies for the benefit of its home country. Bortolotti, Fotak, Megginson e Miracky (Quiet Leviathans: SWF investment, passivity and the value of the firm) examine whether SWFs impact value as investors in listed companies. The results are impressive. From a sample of 802 transactions they find that on average, the stocks of companies receiving SWF equity investments increase significantly (about 1,25%) over the three-day window surrounding the purchase announcement, suggesting that investors welcome SWFs as shareholders. This feature of SWF investment suggests that funds become the allies of target-firm managers and are thus constrained from playing a meaningful disciplinary or monitoring role. In addition, these government-owned funds face significant political pressure from recipient countries to remain passive investors in cross-border deals. This description perfectly matches the Constrained Foreign State Investor Hypotesis, according to which SWFs should be especially reluctant to interfere in target firm management by demanding high performance or by holding managers to account. Despite these positive announcement-period reactions, SWF stock purchases are associated with much larger and significantly negative abnormal returns over the three years following the initial investment, and this long term effect exceeds by far the positive initial boost. The longer-term post-acquisition target performance is related to fund characteristics and to the SWFs level of involvement. The performance of SWF investment targets is worse for more passive funds, for foreign targets, and for targets headquartered in an OECD country, but long-run returns are negatively related to the size of the stake acquired and to the size of the target firm. In light of their close connection to authoritarian and unaccountable governments (excluding Norway SWF) that differentiates SWF from other investors we could think their long term effect on the target companys performance not to be just related to a SWFs specific features but to the political setting they are part of. Political risk is one possible explanation for this poor performance that is seldom taken into account in the academic literature and in the wider debate. POLITICAL RISK AND PERFORMANCEAs we have seen, the overwhelming majority of SWFs originate from undemocratic countries

and authoritarian regimes. With the exception of Norway, the countries endowed with large

SWFs are characterized by the lack of political legitimacy of their regimes and the weakness of

institutions granting an orderly succession of powers. More importantly, the socioeconomic

indicators of most countries alert about mounting tensions and likelihood of conflict which

could ignite turmoil and rebellion against the incumbent rulers and regimes.

This trend is clearly visible in the data. I have constructed the index for the countries with an operating SWF for 2010. Countries with an SWF display a considerable likelihood of unrest, even if the variability is quite high. The index, which ranges from 0 to 10, takes the value 2.3 for Norway (one of the soundest democracies around the world) to 8.06 in the case of Libya, actually torn by civil war. According to our data, Oman, Bahrain, and, interestingly, China also display high likelihood of unrest.I believe that the political risk in most SWF countries could affect the risk and return properties of the investee company through two main channels: upheaval risk, transforming the countrys wealth management and geopolitical risk triggered by targeted sanctions.

As to upheaval risk, in the event of incipient political unrest, sovereign owners of SWFs may

choose to divert their surplus away from their funds saving for future generations, towards

meeting the welfare needs of the population and buy out peace and social cohesion.

If such a trend were to be replicated across the MENA region, we might observe an aggregate

reduction in the demand for global shares, and at the company level an increase in divestitures,

causing a reduction in share prices and stock overhang. As to geopolitical risk, if the tensions revealed by the index reached a critical level igniting revolts, rebellions and civil war as happened in Libya, Yemen and Syria, concerns that SWFs financial resources could be used by the challenged authoritarian regimes to suppress the political opposition may motivate the use of targeted sanctions involving for example the freeze of SWF assets. Again Libya is a case in point. On 17 March 2011 in resolution 1973 the Security Council of United Nations imposed inter alia an asset freeze on assets owned by the Libyan authorities. The Council of the European Union officially endorsed the resolution, and it was implemented by most member states. The asset freeze caused tensions on listed companies in the LIAs portfolio, including bellwether stocks such as Unicredit, Pearson, the owner of the Financial Times, and Finmeccanica. Companies in the portfolio of a SWF originating from an undemocratic country are thus exposed to this upheaval and geopolitical risk, and this could increase volatility, causing higher expected returns and generally a higher cost of capital in the investee company. Obviously, the degree of exposure will depend on the size of the stake. While portfolio diversification is often a stated objective in SWF strategies, it is widely documented that SWFs tend to acquire large direct ownership positions in listed companies. The average and median direct stake acquired in foreign SWF deals is 19.9%, and 4.9%, respectively. Consequently, when they make an investment, SWFs should consider the political position of the recipient country, its tolerance for what could be considered repressive action or human rights abuses, and the likelihood that it might impose unilateral sanctions on a regime for acting in that manner.As the potential for the Arab Spring spreading increases, this political risk for undemocratic SWFowning nations thus becomes greater.In broader terms, the mounting social and political instability in MENA (which could spread eastwards), is contributing to a change in the fundamental nature and behaviour of global SWF. This metamorphosis involves the partial loss of SWFs status as patient, longterm investors, providing capital and liquidity across business cycles, and turning them into financial players with shorterterm horizons, unpredictable liquidity needs, and carrying political risk.We have begun to see this trend in some cases like China where the China Investment Corporation has reportedly been advised to improve its shortterm returns.To test the hypothesis that the political risk associated with an SWF investment negatively

affects financial performance of investee companies, I have conducted a preliminary analysis

on the possible effect of political risk on the financial performance of SWF targets after the

acquisition. I measure performance using buyandhold abnormal return over different time horizons (6 months, 1, 2, and 3 years) and regress it against the index of unrest described above, controlling for a several other possible factors. As expected, political risk is negatively associated with financial performance, and this relation is particularly strong and statistically significant over the 1 and 2 year period postacquisition. This evidence is broadly consistent with the broader story: rational investors tend to discount country risk in the pricing of securities acquired by SWFs.DATA ANALYSISI perform a series of regressions to evaluate the impact of the uprising risk of the country where SWF is headquartered on the performance of the invested company over the short term (three days) and longer period (six-month, one-year, two-year and three year). The final number of observations employed in each regression specification ranges from 294 in the ST to 23 in the LT, as detailed in the tables. The set of explanatory variables includes: a measure of country risk (Country risk) from an index taking into account key parameters as GDP per capita, level of democracy, population under 25 y.o., percentage of internet users and censorship; a measure of government involvement in SWF operations (t_government), computed as one minus the score given by Truman (2008) to the level of managerial independence from the government; a measure of how passive the SWF is in its investments (t_passive), obtained by adding the scores given by Truman (2008) on the presence of stake limits and on the ban on controlling stakes a binary variable equal to one if the target is in the strategic industrial groups Aerospace and Defense, Energy, Utilities, Resources, or Telecoms and IT (target_str-2); a variable measuring the age, in years, of the investing SWF at the time of the investment (SWF_Age) to test for the presence of learning effects in stock-picking; a variable equal to the proportion of the stake acquired in a capital infusion or zero in the case of a secondary-market transaction (Capital Infusion); a variable measuring the size of the stake owned after the investment (Stake Owned), to test whether market reaction depends on the proportion of the firm that is under SWF control; a binary

variable equal to one if the SWF investment is in a foreign company (Foreign); the market

capitalization of the target firm (mv_c_yn1), the leverage (dtoa_c_yn1) of the target firm, proxied by debt-to-asset ratio, and its liquidity (qr_c_yn1), proxied by the firms Quick Ratio, all three measured as of the end of the calendar year prior to the SWF investment; and a binary variable set equal to one if the SWF acquires one or more seats on the board of directors (bod_d). Finally, we add a control variable measuring abnormal stock market returns (bhar_li_pr-r) over the one-year period preceding investment, to control for possible momentum or reversal effects. All regressions are estimated with robust standard errors clustered by target firm, to mitigate potential econometric problems caused by multiple investments in the same target firms.

SHORT TERM RESULTSI find a slight negative relation between country risk where SWF is headquartered and performance of the invested company. Both results are not statistically significant at any level. This can be interpreted as a consequence of evidence that acquisitions of stakes or capital infusions by SWF are often agreed upon by managers and therefore the potential risks perceived are offset by the welcomed injection of new capital in company. We can find additional evidence about this hypothesis in the positive relation between capital infusion by SWF and performance of the invested entity (significant at5% level): it is clear that a friendly capital infusion would definitely benefit shareholders and managers alike, especially if they are not bound to strict monitoring or disclosure agreements. The level of government involvement in the SWF is negatively related to the performance of the target company and the result is statistically significant at 1% level. The level of passivity of the investing fund is negatively related to abnormal returns but the coefficient is not statistically significant. The binary variable identifying strategic targets and the dummy for foreign investments have both negative but display no statistically significant coefficients. SWF age has a slightly negative effect, significant at 1% level whereas the size of the stake owned has a positive but not significant coefficient. The coefficients on the leverage and liquidity variables show different signs but none of these relations is statistically significant. The same applies to seats in the Board of Directors, whose effect on performance is not relevant, with the coefficient being not statistically significant. Finally there is a negative relation between buy and hold abnormal returns one year before SWF investment and current performance, not significant too. Therefore in the short term (3 days) we have no evidence about target companys underperformance following the investment of the SWF and this result complies with our previous hypothesis stated above.

LONG TERM RESULTS

The level of country risk is negatively related to the performance of the target company in the six-month one-year and two-year period and the first two coefficients are significant at 10% level. This finding confirms our hypothesis that instability of the country where SWF is headquartered could hinder the performance of the invested company in a longer period after the positive (or, taking all elements into account, neutral) impact immediately after the investment decision. The coefficients about the level of government involvement are not statistically significant in any time horizon while the level of passivity of the investing fund is negatively related to abnormal returns, but results are not significant too. The binary variable identifying strategic targets has positive but not statistically significant coefficients, the same applies to the coefficients of the variable taking into account SWF age . The variable measuring the size of the capital infusion has coefficients of different signs, none statistically significant. We interpret this as the fading away of the positive shock due to the capital infusion at the time of the investment decision. The size of the stake owned has different coefficients at various time horizons, none statistically significant. The dummy variable indicating foreign targets has negative coefficients for all periods, significant at the 1% level at the one-year, two-year and three year horizon ; overall, this suggests worse performance for foreign targets. The coefficients on the leverage and liquidity variables change signs at different horizons and none of the relationships are statistically significant. Finally, we see no clear relation between seats in the Board of Directors and firm performance, with none of the results being statistically significant. There is a negative relation between buy and hold abnormal returns one year before SWF investment and current performance, significant at 5% in one-year and two-year period.CONCLUSIONS AND POLICY IMPLICATIONSIn this dissertation I tried to assess the impact of the level of political risk of the country where a SWF is headquartered on the performance of the SWF's target company.This risk factor is not directly tied to the structure or governance of the fund but it could definitely alter the performance of both the SWF and the invested companies.I have found that while in the short term positive market reaction to the injection of new capital prevails, in a longer time horizon the performance of the invested company compared to its competitors is inversely proportional to the level of risk of the country where the SWF investor is headquartered.If this outcome is confirmed and strengthened in the future it would we should change our assumptions and expectations about SWF's investment: we are not dealing anymore with "Quiet Leviathans", or investors on a projected long-term vision that give stability to invested companies and their performance, but with rather obscure entities whose assets could be frozen or fall into the handsof unknown and potentially unreliable subjects. This result may suggest a few policy Implications. First of all is that, although it is certainly useful to issue guidelines designed to improve the governance of the SWF, those measures will be relatively meaningless in this new perspective: even if the governance of a SWF accepted and implemented best practices in terms of transparency and accountability, the risk factor of the country where it is headquartered would hardly change.Therefore, a policy proposal to advance in the international community could be to make the opening of SWF investments proportional to political and economic reform pursued by the countries where they are located. Those methods would that at the same limit the negative impact on long-term performance on western companies and help to enhance political standards and promote a transition to greater freedom in many states. 5. BIBLIOGRAPHY

Cash in hand, The Economist, June 17th 2010

Be careful what you risk for, The Economist, June 12th 2008

The rise of state capitalism, The Economist, Sept. 18th 2008

Asset backed insecurity, The Economist Jan. 17th 2008

SWF, a developing country perspective, Griffith Jones and Ocampo, Foundation for European Progressive Studies working paper series, May 2010

Four myths about SWF , E. Truman, VOX.eu, Aug. 14th 2008

SWF, the need for greater transparency and accountability, E. Truman, Peterson Institute Policy Brief, Aug. 2007

SWF, governance and reserve accumulation, Aizenman and Glick, VOX.eu, Jan. 16th 2009

Are SWF investments politically biased? Comparing mutual and SW funds, Avendano and Santiso, VOX.eu, Feb 3th 2010

SWF and Financial Stability Sun and Hesse, VOX.eu, March 2009

Quiet Leviathans: SWF investment, passivity and the value of the firm; Bortolotti, Fotak, Megginson and Miracky; Oct. 2010

SWF investment behavior; Barbary, Bortolotti, Fotak, Megginson; Semiannual report, FEEM and Monitor group, Jan-June 2010

A Scoreboard for Sovereign Wealth Funds, E. Truman, Presented at the Conference on China's Exchange Rate Policy, October 19, 2007, at the Peterson Institute, Washington, DC.

A change of strategy,Sophia Grene, FINANCIAL TIMES, June 23, 2010

TABLE 2 RESULTS FOR THE SHORT TERM

(three-day event window spanning days -1 to +1, where day 0 is the day the SWF investment is announced)

Linear regression Number of obs = 294

F( 15, 152) = 3.04

Prob > F = 0.0003

R-squared = 0.0827

Number of clusters (target_id) = 153 Root MSE = .04757

------------------------------------------------------------------------------

| Robust

bhar_li~3day | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

Country risk | .0021919 .0183112 0.12 0.905 -.0339854 .0383692

t_government | -.1723797 .074832 -2.30 0.023 -.3202247 -.0245347

t_passive | -.0412864 .1078006 -0.38 0.702 -.2542674 .1716946

norway | .0497562 .1779114 0.28 0.780 -.3017423 .4012546

oecd | .0253848 .032137 0.79 0.431 -.038108 .0888776

target_str~2 | -.003792 .0061159 -0.62 0.536 -.0158751 .0082911

swf_age | -.0055099 .0024888 -2.21 0.028 -.0104271 -.0005927

capitalin~ke | .7175019 .2977453 2.41 0.017 .1292483 1.305756

stake_owne~s | .0270347 .0729888 0.37 0.712 -.1171689 .1712383

foreign | -.0342156 .0367468 -0.93 0.353 -.1068161 .0383849

mv_c_yn1 | -5.64e-07 3.76e-07 -1.50 0.135 -1.31e-06 1.78e-07

dtoa_c_yn1 | -.0059351 .0141292 -0.42 0.675 -.0338502 .0219799

qr_c_yn1 | .0004985 .0008348 0.60 0.551 -.0011509 .0021478

bod_d | .0109459 .0248483 0.44 0.660 -.0381468 .0600386

bhar_li_pr~r | -.0022325 .0022973 -0.97 0.333 -.0067713 .0023063

_cons | .1411225 .1239995 1.14 0.257 -.1038626 .3861076

------------------------------------------------------------------------------

Linear regression Number of obs = 294

F( 13, 152) = 2.55

Prob > F = 0.0033

R-squared = 0.0784

Number of clusters (target_id) = 153 Root MSE = .04751

------------------------------------------------------------------------------

| Robust

bhar_li~3day | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

Country risk | -.0174264 .0257909 -0.68 0.500 -.0683813 .0335285

t_government | -.1470119 .0461576 -3.18 0.002 -.2382052 -.0558186

t_passive | -.0138429 .014125 -0.98 0.329 -.0417497 .0140638

target_str~2 | -.0034878 .0060962 -0.57 0.568 -.015532 .0085564

swf_age | -.0061438 .0017732 -3.46 0.001 -.0096471 -.0026405

capitalin~ke | .7368852 .2977077 2.48 0.014 .148706 1.325064

stake_owne~s | .0552168 .08703 0.63 0.527 -.1167279 .2271615

foreign | -.0447588 .0296377 -1.51 0.133 -.1033139 .0137963

mv_c_yn1 | -5.30e-07 3.78e-07 -1.40 0.163 -1.28e-06 2.16e-07

dtoa_c_yn1 | -.0059013 .014096 -0.42 0.676 -.0337507 .0219481

qr_c_yn1 | .0005374 .0008362 0.64 0.521 -.0011146 .0021895

bod_d | .0129747 .0214295 0.61 0.546 -.0293633 .0553127

bhar_li_pr~r | -.0028291 .0021244 -1.33 0.185 -.0070263 .0013681

_cons | .2356604 .1335217 1.76 0.080 -.0281377 .4994585

------------------------------------------------------------------------------

TABLE 3-RESULTS FOR THE LONG TERM ------------------------------------------------------------------

Variable | reg6months reg1year reg2years reg3years

-------------+----------------------------------------------------

Country risk | -.17337899 -.3341552 -.11802572 2.8173935

| 0.4059 0.0760 0.5311 0.4326

t_government | -.43493807 -.31767225 -2.8037939 -4.5892641

| 0.4188 0.6824 0.0545 0.2626

t_passive | -.94876096 -.62100354 -2.0138526 -2.8103485

| 0.0173 0.2445 0.0009 0.1089

norway | 1.6141807 .74414115 2.632711 6.9219514

| 0.0151 0.4059 0.0008 0.0234

oecd | -.4201306 -.2822485 -.40765459 -.21035602

| 0.0032 0.3073 0.1740 0.8728

target_str~2 | .05164164 .02103695 .04269399 .09363804

| 0.3730 0.7247 0.7369 0.8072

swf_age | -.0223115 -.02600275 -.1064126 -.04601124

| 0.1440 0.2965 0.0181 0.6950

capitalin~ke | -.23764907 -1.0481732 .66659183 7.0235771

| 0.8294 0.5202 0.6510 0.4126

stake_owne~s | .55507688 .23335357 -1.1885056 -11.804437

| 0.6804 0.8515 0.0955 0.3705

foreign | -.05072528 -.53622597 -.79438129 -1.2295013

| 0.7978 0.0125 0.0000 0.0836

mv_c_yn1 | -6.022e-06 -3.341e-06 -.00001074 -.00003313

| 0.1583 0.3698 0.0246 0.3407

dtoa_c_yn1 | -.17139157 .10508673 -.24501775 .5597118

| 0.2817 0.4716 0.2646 0.8317

qr_c_yn1 | .00976197 .01152953 -.00215658 .1686102

| 0.1834 0.2658 0.9517 0.5396

bod_d | -.16214447 .01114861 -.31026168 -1.4514607

| 0.3519 0.9403 0.0168 0.0569

bhar_li_pr~r | .0007518 -.05598752 -.05791255 -.16352535

| 0.9649 0.0085 0.0074 0.3344

_cons | 1.696789 2.6016505 4.9063554 -6.9482232

| 0.1002 0.0099 0.0004 0.6419

-------------+----------------------------------------------------

N | 294 293 144 23

r2 | .05010803 .04678684 .240028 .75393131

------------------------------------------------------------------

------------------------------------------------------------------

Variable | reg6months reg1year reg2years reg3years

-------------+----------------------------------------------------

Country risk | -.18511165 -.31309864 -.32604307 .28450013

| 0.2826 0.0284 0.0747 0.8190

t_government | .31827176 .05410613 -1.4061047 .25772883

| 0.4259 0.9327 0.3018 0.9187

t_passive | -.01508784 -.19614493 -.50469912 .19217559

| 0.8998 0.2138 0.1473 0.7826

target_str~2 | .05232834 .020129 .04296757 .28980349

| 0.3628 0.7333 0.7322 0.5061

swf_age | .00379292 -.01018229 -.07029254 .00626383

| 0.7765 0.6413 0.1436 0.9293

capitalin~ke | .66672563 -.62466721 1.9326637 4.5073733

| 0.7125 0.7566 0.4157 0.4679

stake_owne~s | .6855408 .21320963 -.8246279 -3.0536747

| 0.6204 0.8604 0.1488 0.5612

foreign | -.21943834 -.62759119 -1.1820403 -1.8631338

| 0.1814 0.0000 0.0000 0.0501

mv_c_yn1 | -6.354e-06 -3.622e-06 -.00001155 -.00003911

| 0.1401 0.3285 0.0173 0.3976

dtoa_c_yn1 | -.16469603 .10698612 -.23162654 .49911629

| 0.3000 0.4606 0.2909 0.8698

qr_c_yn1 | .00910202 .01115337 -.00152727 .12978344

| 0.2205 0.2823 0.9656 0.6737

bod_d | .06382463 .13625312 .04482498 -.75136739

| 0.5684 0.2150 0.7342 0.1639

bhar_li_pr~r | .0087364 -.05082958 -.05358762 -.11222583

| 0.6176 0.0090 0.0104 0.5394

_cons | .75896724 1.9691506 4.4301511 .282822

| 0.3712 0.0237 0.0119 0.9622

-------------+----------------------------------------------------

N | 294 293 144 23

r2 | .04099491 .04359465 .22252844 .63033569

------------------------------------------------------------------

_1372772806.xlsGrafico1

Sheet1

1 Trim.2 Trim.3 Trim.4 Trim.

Est27.49020.4

Ovest30.638.634.631.6

Nord45.946.94543.9

_1368883560.xlsGrafico1

Sheet1

1 Trim.2 Trim.3 Trim.4 Trim.

Est27.49020.4

Ovest30.638.634.631.6

Nord45.946.94543.9