- Email: [email protected]
Comment on “Do credit rating agencies add to the dynamics of emerging market crises?” by Roman Kräussl
Journal of Financial Stability 1 (2005) 438–446
Discussion
Comment on “Do credit rating agencies add to the dynamics of emerging market crises?” by Roman Kr¨aussl S. Nuri Erbas¸ ∗,1 International Monetary Fund, Middle East and Central Asian Department, Room 6-107C, 700 19th Street, N.W. Washington, DC 20431, USA
Abstract Possible explanations are provided for two basic results in Kr¨aussl’s paper. First, rating effect may be stronger in emerging markets because they are less transparent. Transparency is interpreted in the context of Knightian uncertainty and institutional quality. Emerging markets have lower institutional quality ratings and present greater uncertainty than mature markets, therefore, they are more susceptible to rating agencies’ evaluations. Some empirical evidence on the correlations between institutional quality rankings and portfolio investment is presented. Second, sovereign credit downgrades generate a stronger market reaction than upgrades because decision makers value losses more than gains, as posited by cumulative prospect theory. © 2005 Elsevier B.V. All rights reserved. Keywords: Transparency; Uncertainty; Financial vulnerability
1. General observations This is a very interesting paper that persuasively answers the question it poses as follows: Country evaluations by credit rating agencies have a significant impact on financial market ∗
Tel.: +1 202 623 8348. E-mail address: [email protected]. 1 The views expressed in this article are those of the author and should not be interpreted as those of the International Monetary Fund. 1572-3089/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jfs.2005.02.008
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movements in emerging markets. The paper adds to the literature by considering a more comprehensive database than the previous similar studies and by exhaustively answering almost all the relevant questions the reader might anticipate. Indexes developed by the paper are useful and focused, and econometric methods used are persuasive and robust. Consequently, on the technical side, I have little to add to this paper. Two general observations the paper makes, however, deserve further discussion, on which I concentrate. They are the following. First, as the paper demonstrates, credit rating agencies’ evaluations have a significant impact on market movements in emerging markets. The question is why. Furthermore, do credit rating agencies wield the same degree of power in mature markets? If not, why? We get a hint of the answer in Section 3: “The rating effect is likely to be stronger in emerging markets, where problems of asymmetric information and transparency are more severe”. The impact of less transparency in emerging markets needs to be put in analytical perspective through a qualitative examination of the impact of transparency on investor decisions and, hence, on financial vulnerability and strength. It appears that in emerging markets, investors somehow react to rating agencies’ judgments more than they do in mature markets. Such reactions might be often subjective (ignorant herds) and perhaps instinctive (hysterical herds), and not necessarily as ‘rational’ as the efficient markets theory might assume. Arguably, in the thicker fog of emerging markets, subjective and instinctive investment behavior might become rather rampant rather quickly. There is greater ambiguity, or Knightian uncertainty, in such markets, which has an important bearing on this paper’s results. Secondly, a prominent result of the paper is asymmetric market response to ‘good’ rating changes versus ‘bad’ rating changes: “The empirical results suggest that sovereign credit rating downgrades generate a strong financial market reaction, while sovereign credit rating upgrades have a much lesser impact on financial markets in emerging market economies (Section 4)”. Again, the question is why. This strong and interesting result also calls for a qualitative explanation. A possible explanation is that investors value losses more than gains, as argued by cumulative prospect theory. If this conjecture is built into financial models, can we explain more about market behavior than we can under the efficient markets theory, which makes no such distinction between the valuation of losses and gains? This review concentrates on those two general observations. Although the remarks that follow are not necessarily intended for inclusion in the paper, if they were mentioned briefly, they might prove useful in qualitatively enhancing the paper’s results and in adding a new perspective to future research on similar topics of interest.
2. Transparency, institutional strength, and financial vulnerability Why do credit rating agencies wield such power in emerging market economies? A basic reason, as the paper points out, is that it is too costly for unspecialized investors to do adequate research on emerging markets and, therefore, they have to rely on specialists to do the research and, within a plausible margin of confidence, respond to the specialists’
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announcements.1 As Frank Knight (1921/2002) puts it, decision makers ‘shift’ uncertainty to specialists—in this case, to foreign specialists, or, international rating agencies. I have argued elsewhere (Erbas¸, 2004) that another important reason why rating agencies wield such power in emerging markets might be institutional weakness, which results in less transparency relative to mature markets. Transparency in this sense needs to be understood advisedly and requires further clarification. Transparency has a bearing on uncertainty in the Knightian sense—it is not only the availability of relevant data but also their reliability. If investors think that the available national data (e.g. those disseminated by country authorities or independent national bodies—chambers of commerce—on budget deficit, external reserve position, inflation, so on) are not reliable, they might turn to foreign specialists for a more reliable evaluation of a country’s financial position and prospects. Even if the relevant national data are available and reliable, there remains nevertheless greater uncertainty in emerging markets relative to mature markets. This reflects institutional weaknesses and vulnerabilities, which serve to increase the range of possible events and outcomes in emerging markets relative to mature markets. For example, in a less stable political environment, the present government (say, in line with an IMF program) might follow a sustainable budgetary policy but there may be a credible threat that the more populist government-in-waiting might reverse the current policies in the future (say, after the IMF program ends). Such a lack of policy consensus amounts to institutional weakness and greater uncertainty. Moreover, I believe it is a textbook folly to assume that the probabilities and payoffs (gains and losses) associated with such events can be known with precision by market evaluators (by credit rating agencies or even by more powerful international evaluators). I think we need to understand transparency in this broader sense. Beyond its robust econometric results, this paper’s main finding becomes stronger and perhaps more meaningful when we put it in the context of Knightian uncertainty: emerging markets are less transparent, hence exhibit greater uncertainty in the Knightian sense because of their institutional weaknesses; therefore, they are more susceptible to credit rating agencies’ evaluations than mature markets. In mature markets, there is a stronger consensus, as well as stronger legal and institutional checks, on economic policies; therefore, they are less vulnerable to outside evaluations. Institutional quality encompasses every aspect of economic (and social and political) interaction. Regulation, the theme of this conference, is an institution. Financial market regulation sets the rules of the game. When those rules are enforced effectively and impartially (good regulation), uncertainty is reduced because, first, rules set recognizable benchmarks to distinguish good behavior from bad behavior; second, bad behavior is punished. In other words, the range of possible outcomes is restricted by good regulation; for example, outcomes that reflect insider trading, fraud, and creative accounting are not allowed, or, they
1 Although, strictly speaking, the IMF is not a credit rating agency, the IMF’s recent transparency initiatives (e.g. public information notices and publication of staff reports following consultations with member countries) are steps to provide broadly neutral country information to interested parties, including private lenders. Glennerster and Shin (2003) present evidence that adoption of some transparency reforms has resulted in a decline in sovereign spreads in some countries.
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are expected to occur less frequently.2 This makes a market more transparent and reduces uncertainty in the broader Knightian sense.3 2.1. Two institutional quality indexes An index that can shed light on the transparency-uncertainty-financial vulnerability nexus is the Heritage Foundation’s Index of Economic Freedom. The composite index of economic freedom is constructed on the basis of the following subindexes: (a) trade policy; (b) fiscal burden; (c) government intervention; (d) monetary policy; (e) foreign investment; (f) banking and finance; (g) wages and prices; (h) property rights; (i) regulation; (j) informal market. Another useful index is the World Bank Indexes on: (a) voice and accountability; (b) political stability; (c) government effectiveness; (d) regulatory quality; (f) rule of law; (g) control of corruption.4 It is interesting to see if those indexes reveal useful information about capital flows to emerging markets. In line with this paper’s focus, the capital flows I focus on in this review are portfolio investment flows; more specifically, I choose portfolio investment liabilities (as reported by the IMF’s International Financial Statistics (IFS)) as a measure of financial capital inflows to a country. 2.2. Institutional quality and financial capital flows Table 1 below shows some relevant data on financial capital flows to the 28 emerging markets, which this paper includes in its database, and their overall and regulatory ranking according to the Heritage Indexes and the World Bank Indexes.5 Table 2 shows the same data for a selected set of 20 mature markets.6 How is institutional quality, as proxied by those indexes, related to portfolio capital inflows to emerging and mature markets? A plausible way to answer this question is through regressing portfolio investment liabilities on institutional quality indexes shown in Tables 1 and 2. Table 3 summarizes the regression results. First, for the emerging markets in the sample, the portfolio flows are correlated statistically significantly (at the 5 percent level) with both the Heritage and the Kauffman composite 2 In this sense, good regulation has a good impact on financial markets; for example, a country with a good regulatory environment might receive greater foreign capital inflows. 3 Indeed, this is Knight’s main point: market institutions, including regulatory institutions, emerge primarily to deal with uncertainty. Sargent (1993) emphasizes that, under the rational expectations hypothesis, equilibrium solutions are reached by making the assumption that decision makers are rational, which serves to restrict the range of possible outcomes. When such strong rationality is not a realistic conjecture, institutions may do the job (e.g. at least for the reasons that information is costly and limited, and investors might make subjective and instinctive decisions). 4 Details of how those categories are interpreted and the basis on which country rankings are made are available from the Heritage Foundation, 2005 and World bank, 2005 websites. 5 The World Bank Indexes shown in Tables 1 and 2 are the simple averages of the country rankings in various categories of institutional quality. 6 The Euro zone is added to the data set as a separate entity, although there is an overlap with many of the countries classified as mature markets. The Euro zone comprises Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, and Spain.
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Table 1 Portfolio investment flows to emerging markets and institutional quality rankings Composite
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Regulation
Portfolio investmenta
Heritage indexb
World bank indexc
Heritage indexb
World bank indexc
Argentina Brazil Chile China Colombia Czech Republic Ecuador Egypt Hong Kong Hungary India Indonesia Malaysia Mexico Morocco Pakistan Peru Philippines Poland Russia Singapore Slovakia South Africa South Korea Taiwan Thailand Turkey Venezuela
1.5 2.4 1.8 0.3 1.8 1.8 −5.3 0.5 15.7 2.4 0.7 0.1 −0.9 0.5 0.2 0.3 0.3 3.1 0.9 0.1 0.4 2.0 3.9 2.5 3.5 1.1 0.2 0.3
3.5 3.1 1.9 3.6 3.1 2.4 3.6 3.3 1.3 2.6 3.5 3.8 3.2 2.9 2.9 3.4 2.8 3.1 2.8 3.5 1.6 2.4 2.8 2.7 2.4 2.9 3.4 4.2
56.4 55.0 84.2 45.2 37.6 77.3 30.4 47.6 76.0 79.7 60.7 27.4 61.9 61.9 53.7 35.9 48.3 49.9 68.9 33.3 84.2 70.8 71.2 70.6 73.1 63.9 54.3 37.6
3.0 3.0 3.0 4.0 3.0 3.0 4.0 4.0 1.0 3.0 4.0 4.0 3.0 3.0 3.0 3.0 4.0 4.0 3.0 4.0 1.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0
62.2 61.3 91.7 41.9 60.8 80.1 41.6 44.6 96.9 83.7 42.2 41.9 71.1 73.4 56.2 29.1 73.4 65.3 72.7 28.5 99.7 64.7 62.0 70.3 84.3 67.4 66.3 38.2
Simple averages
1.5
3.0
57.7
3.2
63.3
Sources: Heritage Foundation, World Bank, and IFS. a In percent of GDP; 1994–2001 averages (in US$). b Higher index value indicates lower economic freedom raking; most recent 2004 rankings. c Higher index value indicates higher ranking; simple averages of the 1996, 1998, 2000, and 2002 rankings.
indexes. For the Heritage Index, higher value means lower ranking, and portfolio flows are negatively correlated with that index. For the World Bank Index, higher value means higher ranking, and portfolio flows are positively correlated with that index. The same results are valid for the subindexes for regulation and regulatory quality. On average, the emerging markets get substantially lower portfolio inflows as a percentage of their GDPs and rank lower than mature markets in institutional quality. Secondly, for the mature markets in the sample, the regression results are insignificant. The rankings for mature markets are high under both institutional quality indexes. Evidently, the mature markets enjoy higher institutional quality, higher transparency, and, therefore, higher portfolio inflows as a percentage of their GDPs. This is the case of ‘the dog that did
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Table 2 Portfolio investment flows to selected mature markets and institutional quality rankings Composite
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Regulation
Portfolio investmenta
Heritage indexb
World bank indexc
Heritage indexb
World bank indexc
Autralia Austria Canada Denmark Finland France Germany Greece Ireland Italy Japan Netherlands New Zealand Norway Portugal Sweden Switzerland United Kingdom Unites States Euro area
4.3 7.6 2.3 2.6 5.2 3.9 4.5 7.2 37.9 5.7 1.6 9.6 0.6 2.1 5.2 1.7 2.7 7.0 3.4 4.5
1.9 2.1 2.0 1.8 2.0 2.6 2.0 2.8 1.7 2.3 2.5 2.0 1.7 2.4 2.4 3.9 1.9 1.8 1.9 2.2
93.8 92.8 92.7 96.4 98.0 86.4 86.6 80.2 83.6 72.1 78.5 88.2 96.4 80.9 85.6 81.1 97.3 93.3 90.8 85.8
2.0 3.0 2.0 1.0 2.0 3.0 3.0 3.0 2.0 3.0 3.0 3.0 2.0 3.0 3.0 4.0 3.0 2.0 2.0 2.8
93.4 93.9 90.7 95.7 96.7 83.8 92.5 80.9 96.4 80.6 78.0 98.3 96.8 90.8 89.7 92.1 92.6 97.9 94.7 90.2
Simple averages
6.0
2.2
88.0
2.6
91.3
Sources: Heritage Foundation, World Bank, and IFS. a In percent of GDP; 1994–2002 averages (in US$). b Higher index value indicates lower economic freedom raking; most recent 2004 rankings. c Higher index value indicates higher ranking; simple averages of the 1996, 1998, 2000, and 2002 rankings.
not bark’. The rankings of institutional quality evidently do not matter for mature markets to attract capital. One wonders if rating agency announcements matter for mature markets. Finally, when the emerging markets and mature markets are considered together, both institutional quality indexes are significantly correlated with portfolio investment inflows, reflecting the impact of the emerging markets.7 What is the lesson here? I think institutional quality is a good proxy for transparency in that it sheds light on the question why emerging markets are more susceptible to announcements of credit rating agencies. Furthermore, institutional quality is a broader index of uncertainty and risk, as subjectively evaluated by investors. Emerging markets are more susceptible to credit rating changes because they confront investors with greater Knightian uncertainty.8
7
Regressing log of portfolio liabilities on the logs of the institutional quality indexes yields results similar to those in Table 3. 8 These results are corroborated by the findings of Gelos and Wei (2002). They find that transparency (as measured by certain indexes) has a significant impact on international portfolio investment, with less transparent
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Table 3 Regressions summary: portfolio investment liabilities on institutional quality indexes Heritage index Composite indexes Emerging markets (sample size: 28) Coefficient −3.1 t-statistic −3.9 Mature markets (sample size: 20) Coefficient −3.7 t-statistic −1.0 Emerging and mature markets (sample size: 48) Coefficient −4.0 t-statistic −3.6 Regulation indexes Emerging markets (sample size: 28) Coefficient −2.4 t-statistic −3.7 Mature markets (sample size: 20) Coefficient −1.8 t-statistic −0.7 Emerging and mature markets (sample size: 48) Coefficient −3.0 t-statistic −2.9
World bank index
0.1 2.5 −0.2 −0.7 0.1 2.6
0.1 2.8 0.3 1.0 0.1 3.2
Source: author’s estimates.
It would be illuminating to see how institutional and regulatory quality indexes (and other proxies that may be used as transparency indexes) might correlate with the speculative market pressure index (SMP) used in this paper. Thus, the impact of transparency (or lack of it) on the rating effect in emerging markets might be placed in an analytically broader and richer context. It would also be interesting to see how those indexes might correlate with variability of portfolio inflows in emerging markets, as opposed to mature markets. For future research, I venture to posit that financial market stability is significantly correlated with institutional and regulatory quality. 3. Asymmetric response to positive and negative rating changes I now turn to the second issue: Why do markets respond more to negative rating changes than to positive rating changes? I think an answer can be given along the lines of cumulative countries attracting less investment. It is also noteworthy that country risk rankings provided by the International Country Risk Guide (2004) correlate very significantly with the Heritage and World Bank composite institutional quality indexes in the case of emerging market countries in the sample, whereas this correlation is insignificant in the case of mature markets in the sample. Similar results are obtained when portfolio liabilities are regressed on risk indexes; such capital inflows are correlated significantly with risk rankings in the case of the emerging markets but are insignificantly correlated in the case of the mature markets in the samples (regression results are available from the author of this review). These results corroborate those reported in Table 3. Importantly, they underline the argument that institutional quality and transparency are good indicators of uncertainty and risk in a country.
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prospect theory (CPT) (Kahneman and Tversky, 1979; Tversky and Kahneman, 1992). In contrast to the expected utility theory, CPT posits two axioms: (i) decision makers derive utility from the increment (gain) or decrement (loss) in their wealth, as opposed to increase and decrease in total wealth; (ii) decision makers value losses more than gains.9 The rating agency announces a positive or a negative rating change. This is new information for investors. Looking forward, investors adjust their portfolios accordingly. If the announcement on an emerging market is positive, then they move a part of their portfolio from the less uncertain mature market assets to more uncertain emerging market assets, and conversely, if the announcement on an emerging market is negative. However, under CPT, investors value losses more than gains. Therefore, given transactions costs, for a ‘unit’ rating upgrade from which they expect to gain by going long on emerging market assets, investors move a smaller portion of their mature market assets to emerging market assets. But for a ‘unit’ rating downgrade, they expect to avert losses by going short on emerging market assets, and because losses are valued more than gains, they move a greater share of emerging market assets to mature market assets. Therefore, comparable negative rating changes have a greater impact than positive rating changes.10
4. Concluding remarks This is a very interesting and a technically solid paper. It provokes important questions for future research, two of which I have attempted to address. Future research on financial markets and portfolio selection should attempt to incorporate decision making under Knightian uncertainty and the arguments and experimental findings of cumulative prospect theory. Effective financial regulation is an important economic institution. Its impact on financial markets can be better understood in that context.
9 That is, in absolute values, U(Loss) > U(Gain) for all Loss = Gain, or, U(Loss) is everywhere steeper than U(Gain); the comparison is relative to the status quo, which is indexed at zero, or, U(0) = 0. This effect is sometimes referred to as loss aversion. For example, suppose an investor is allocating his or her portfolio between a safe (mature market) and a risky (emerging market) asset and the optimal ratio of wealth allocated to the risky asset is x* = f({ai }), 0 < x* < 1, where {ai } is a vector of variables that determines x* . A change in ai can imply a downgrade (increase in probability of default) or an upgrade (decrease in the probability of default). Loss aversion implies that |∂x* /∂ai |loss > |∂x* /∂ai |gain . I do not propose a portfolio model based on CPT here and rely on the intuitive arguments below. A formalization that supports my arguments is by Barberis et al. (2001). 10 Of course, asymmetric information on negative and positive developments in emerging markets may result in behavior similar to behavior with loss aversion. For example, rating agencies may have a greater informational advantage for downgrades than upgrades, hence the downgrade signal could be stronger than the upgrade signal (I am grateful to Prof. Jerry Dwyer for pointing out this possibility). The impact of informational asymmetry between downgrades and upgrades would strengthen the impact of loss aversion on asymmetric response to positive and negative rating changes. Nevertheless, a good case can also be made that rating agencies also have a strong incentive for sending as strong a signal for the good picks as for the bad picks, because, for example, they enhance their good reputation by picking money-making opportunities ahead of the pack.
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References Barberis, N., Huang, M., Santos, T., 2001. Prospect theory and asset prices. Quart. J. Econ. CXVI (1), 1–53. Erbas¸, S.N., 2004. Ambiguity, Transparency, and Institutional Strength, IMF Working Paper 04/115, Washington: International Monetary Fund. Gelos, G., Wei, S-J., 2002. Transparency and International Investor Behavior, IMF Working Paper 02/174, Washington: International Monetary Fund. Glennerster, R., Shin, Y., 2003. Is Transparency Good for You, and Can IMF Help?, IMF Working Paper 03/132, Washington: International Monetary Fund. Heritage Foundation, 2005. References available on the web, http://www.heritage.org. International Country Risk Guide, references available on the web, http://www.icrgonline.com. Kahneman, D., Tversky, A., 1979. Prospect theory: an analysis of decision under risk. Econometrica 47 (2), 263–291. Knight, F., 2002. Risk, Uncertainty and Profit. Beard Books, Washington, DC, originally published in 1921. Sargent, T., 1993. Bounded Rationality and Macroeconomics. Oxford University Press, New York. The World Bank Institute, 2005. Governance, Regulation and Finance Division, references available on the web, http://www.worldbank.org/wbi/governance/govdata2002/index.html. Tversky, A., Kahneman, D., 1992. Advances in prospect theory: cumulative representation of uncertainty. J. Risk Uncertainty 5, 297–323.
Discussion
Comment on “Do credit rating agencies add to the dynamics of emerging market crises?” by Roman Kr¨aussl S. Nuri Erbas¸ ∗,1 International Monetary Fund, Middle East and Central Asian Department, Room 6-107C, 700 19th Street, N.W. Washington, DC 20431, USA
Abstract Possible explanations are provided for two basic results in Kr¨aussl’s paper. First, rating effect may be stronger in emerging markets because they are less transparent. Transparency is interpreted in the context of Knightian uncertainty and institutional quality. Emerging markets have lower institutional quality ratings and present greater uncertainty than mature markets, therefore, they are more susceptible to rating agencies’ evaluations. Some empirical evidence on the correlations between institutional quality rankings and portfolio investment is presented. Second, sovereign credit downgrades generate a stronger market reaction than upgrades because decision makers value losses more than gains, as posited by cumulative prospect theory. © 2005 Elsevier B.V. All rights reserved. Keywords: Transparency; Uncertainty; Financial vulnerability
1. General observations This is a very interesting paper that persuasively answers the question it poses as follows: Country evaluations by credit rating agencies have a significant impact on financial market ∗
Tel.: +1 202 623 8348. E-mail address: [email protected]. 1 The views expressed in this article are those of the author and should not be interpreted as those of the International Monetary Fund. 1572-3089/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jfs.2005.02.008
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movements in emerging markets. The paper adds to the literature by considering a more comprehensive database than the previous similar studies and by exhaustively answering almost all the relevant questions the reader might anticipate. Indexes developed by the paper are useful and focused, and econometric methods used are persuasive and robust. Consequently, on the technical side, I have little to add to this paper. Two general observations the paper makes, however, deserve further discussion, on which I concentrate. They are the following. First, as the paper demonstrates, credit rating agencies’ evaluations have a significant impact on market movements in emerging markets. The question is why. Furthermore, do credit rating agencies wield the same degree of power in mature markets? If not, why? We get a hint of the answer in Section 3: “The rating effect is likely to be stronger in emerging markets, where problems of asymmetric information and transparency are more severe”. The impact of less transparency in emerging markets needs to be put in analytical perspective through a qualitative examination of the impact of transparency on investor decisions and, hence, on financial vulnerability and strength. It appears that in emerging markets, investors somehow react to rating agencies’ judgments more than they do in mature markets. Such reactions might be often subjective (ignorant herds) and perhaps instinctive (hysterical herds), and not necessarily as ‘rational’ as the efficient markets theory might assume. Arguably, in the thicker fog of emerging markets, subjective and instinctive investment behavior might become rather rampant rather quickly. There is greater ambiguity, or Knightian uncertainty, in such markets, which has an important bearing on this paper’s results. Secondly, a prominent result of the paper is asymmetric market response to ‘good’ rating changes versus ‘bad’ rating changes: “The empirical results suggest that sovereign credit rating downgrades generate a strong financial market reaction, while sovereign credit rating upgrades have a much lesser impact on financial markets in emerging market economies (Section 4)”. Again, the question is why. This strong and interesting result also calls for a qualitative explanation. A possible explanation is that investors value losses more than gains, as argued by cumulative prospect theory. If this conjecture is built into financial models, can we explain more about market behavior than we can under the efficient markets theory, which makes no such distinction between the valuation of losses and gains? This review concentrates on those two general observations. Although the remarks that follow are not necessarily intended for inclusion in the paper, if they were mentioned briefly, they might prove useful in qualitatively enhancing the paper’s results and in adding a new perspective to future research on similar topics of interest.
2. Transparency, institutional strength, and financial vulnerability Why do credit rating agencies wield such power in emerging market economies? A basic reason, as the paper points out, is that it is too costly for unspecialized investors to do adequate research on emerging markets and, therefore, they have to rely on specialists to do the research and, within a plausible margin of confidence, respond to the specialists’
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announcements.1 As Frank Knight (1921/2002) puts it, decision makers ‘shift’ uncertainty to specialists—in this case, to foreign specialists, or, international rating agencies. I have argued elsewhere (Erbas¸, 2004) that another important reason why rating agencies wield such power in emerging markets might be institutional weakness, which results in less transparency relative to mature markets. Transparency in this sense needs to be understood advisedly and requires further clarification. Transparency has a bearing on uncertainty in the Knightian sense—it is not only the availability of relevant data but also their reliability. If investors think that the available national data (e.g. those disseminated by country authorities or independent national bodies—chambers of commerce—on budget deficit, external reserve position, inflation, so on) are not reliable, they might turn to foreign specialists for a more reliable evaluation of a country’s financial position and prospects. Even if the relevant national data are available and reliable, there remains nevertheless greater uncertainty in emerging markets relative to mature markets. This reflects institutional weaknesses and vulnerabilities, which serve to increase the range of possible events and outcomes in emerging markets relative to mature markets. For example, in a less stable political environment, the present government (say, in line with an IMF program) might follow a sustainable budgetary policy but there may be a credible threat that the more populist government-in-waiting might reverse the current policies in the future (say, after the IMF program ends). Such a lack of policy consensus amounts to institutional weakness and greater uncertainty. Moreover, I believe it is a textbook folly to assume that the probabilities and payoffs (gains and losses) associated with such events can be known with precision by market evaluators (by credit rating agencies or even by more powerful international evaluators). I think we need to understand transparency in this broader sense. Beyond its robust econometric results, this paper’s main finding becomes stronger and perhaps more meaningful when we put it in the context of Knightian uncertainty: emerging markets are less transparent, hence exhibit greater uncertainty in the Knightian sense because of their institutional weaknesses; therefore, they are more susceptible to credit rating agencies’ evaluations than mature markets. In mature markets, there is a stronger consensus, as well as stronger legal and institutional checks, on economic policies; therefore, they are less vulnerable to outside evaluations. Institutional quality encompasses every aspect of economic (and social and political) interaction. Regulation, the theme of this conference, is an institution. Financial market regulation sets the rules of the game. When those rules are enforced effectively and impartially (good regulation), uncertainty is reduced because, first, rules set recognizable benchmarks to distinguish good behavior from bad behavior; second, bad behavior is punished. In other words, the range of possible outcomes is restricted by good regulation; for example, outcomes that reflect insider trading, fraud, and creative accounting are not allowed, or, they
1 Although, strictly speaking, the IMF is not a credit rating agency, the IMF’s recent transparency initiatives (e.g. public information notices and publication of staff reports following consultations with member countries) are steps to provide broadly neutral country information to interested parties, including private lenders. Glennerster and Shin (2003) present evidence that adoption of some transparency reforms has resulted in a decline in sovereign spreads in some countries.
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are expected to occur less frequently.2 This makes a market more transparent and reduces uncertainty in the broader Knightian sense.3 2.1. Two institutional quality indexes An index that can shed light on the transparency-uncertainty-financial vulnerability nexus is the Heritage Foundation’s Index of Economic Freedom. The composite index of economic freedom is constructed on the basis of the following subindexes: (a) trade policy; (b) fiscal burden; (c) government intervention; (d) monetary policy; (e) foreign investment; (f) banking and finance; (g) wages and prices; (h) property rights; (i) regulation; (j) informal market. Another useful index is the World Bank Indexes on: (a) voice and accountability; (b) political stability; (c) government effectiveness; (d) regulatory quality; (f) rule of law; (g) control of corruption.4 It is interesting to see if those indexes reveal useful information about capital flows to emerging markets. In line with this paper’s focus, the capital flows I focus on in this review are portfolio investment flows; more specifically, I choose portfolio investment liabilities (as reported by the IMF’s International Financial Statistics (IFS)) as a measure of financial capital inflows to a country. 2.2. Institutional quality and financial capital flows Table 1 below shows some relevant data on financial capital flows to the 28 emerging markets, which this paper includes in its database, and their overall and regulatory ranking according to the Heritage Indexes and the World Bank Indexes.5 Table 2 shows the same data for a selected set of 20 mature markets.6 How is institutional quality, as proxied by those indexes, related to portfolio capital inflows to emerging and mature markets? A plausible way to answer this question is through regressing portfolio investment liabilities on institutional quality indexes shown in Tables 1 and 2. Table 3 summarizes the regression results. First, for the emerging markets in the sample, the portfolio flows are correlated statistically significantly (at the 5 percent level) with both the Heritage and the Kauffman composite 2 In this sense, good regulation has a good impact on financial markets; for example, a country with a good regulatory environment might receive greater foreign capital inflows. 3 Indeed, this is Knight’s main point: market institutions, including regulatory institutions, emerge primarily to deal with uncertainty. Sargent (1993) emphasizes that, under the rational expectations hypothesis, equilibrium solutions are reached by making the assumption that decision makers are rational, which serves to restrict the range of possible outcomes. When such strong rationality is not a realistic conjecture, institutions may do the job (e.g. at least for the reasons that information is costly and limited, and investors might make subjective and instinctive decisions). 4 Details of how those categories are interpreted and the basis on which country rankings are made are available from the Heritage Foundation, 2005 and World bank, 2005 websites. 5 The World Bank Indexes shown in Tables 1 and 2 are the simple averages of the country rankings in various categories of institutional quality. 6 The Euro zone is added to the data set as a separate entity, although there is an overlap with many of the countries classified as mature markets. The Euro zone comprises Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, and Spain.
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Table 1 Portfolio investment flows to emerging markets and institutional quality rankings Composite
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Regulation
Portfolio investmenta
Heritage indexb
World bank indexc
Heritage indexb
World bank indexc
Argentina Brazil Chile China Colombia Czech Republic Ecuador Egypt Hong Kong Hungary India Indonesia Malaysia Mexico Morocco Pakistan Peru Philippines Poland Russia Singapore Slovakia South Africa South Korea Taiwan Thailand Turkey Venezuela
1.5 2.4 1.8 0.3 1.8 1.8 −5.3 0.5 15.7 2.4 0.7 0.1 −0.9 0.5 0.2 0.3 0.3 3.1 0.9 0.1 0.4 2.0 3.9 2.5 3.5 1.1 0.2 0.3
3.5 3.1 1.9 3.6 3.1 2.4 3.6 3.3 1.3 2.6 3.5 3.8 3.2 2.9 2.9 3.4 2.8 3.1 2.8 3.5 1.6 2.4 2.8 2.7 2.4 2.9 3.4 4.2
56.4 55.0 84.2 45.2 37.6 77.3 30.4 47.6 76.0 79.7 60.7 27.4 61.9 61.9 53.7 35.9 48.3 49.9 68.9 33.3 84.2 70.8 71.2 70.6 73.1 63.9 54.3 37.6
3.0 3.0 3.0 4.0 3.0 3.0 4.0 4.0 1.0 3.0 4.0 4.0 3.0 3.0 3.0 3.0 4.0 4.0 3.0 4.0 1.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0
62.2 61.3 91.7 41.9 60.8 80.1 41.6 44.6 96.9 83.7 42.2 41.9 71.1 73.4 56.2 29.1 73.4 65.3 72.7 28.5 99.7 64.7 62.0 70.3 84.3 67.4 66.3 38.2
Simple averages
1.5
3.0
57.7
3.2
63.3
Sources: Heritage Foundation, World Bank, and IFS. a In percent of GDP; 1994–2001 averages (in US$). b Higher index value indicates lower economic freedom raking; most recent 2004 rankings. c Higher index value indicates higher ranking; simple averages of the 1996, 1998, 2000, and 2002 rankings.
indexes. For the Heritage Index, higher value means lower ranking, and portfolio flows are negatively correlated with that index. For the World Bank Index, higher value means higher ranking, and portfolio flows are positively correlated with that index. The same results are valid for the subindexes for regulation and regulatory quality. On average, the emerging markets get substantially lower portfolio inflows as a percentage of their GDPs and rank lower than mature markets in institutional quality. Secondly, for the mature markets in the sample, the regression results are insignificant. The rankings for mature markets are high under both institutional quality indexes. Evidently, the mature markets enjoy higher institutional quality, higher transparency, and, therefore, higher portfolio inflows as a percentage of their GDPs. This is the case of ‘the dog that did
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Table 2 Portfolio investment flows to selected mature markets and institutional quality rankings Composite
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Regulation
Portfolio investmenta
Heritage indexb
World bank indexc
Heritage indexb
World bank indexc
Autralia Austria Canada Denmark Finland France Germany Greece Ireland Italy Japan Netherlands New Zealand Norway Portugal Sweden Switzerland United Kingdom Unites States Euro area
4.3 7.6 2.3 2.6 5.2 3.9 4.5 7.2 37.9 5.7 1.6 9.6 0.6 2.1 5.2 1.7 2.7 7.0 3.4 4.5
1.9 2.1 2.0 1.8 2.0 2.6 2.0 2.8 1.7 2.3 2.5 2.0 1.7 2.4 2.4 3.9 1.9 1.8 1.9 2.2
93.8 92.8 92.7 96.4 98.0 86.4 86.6 80.2 83.6 72.1 78.5 88.2 96.4 80.9 85.6 81.1 97.3 93.3 90.8 85.8
2.0 3.0 2.0 1.0 2.0 3.0 3.0 3.0 2.0 3.0 3.0 3.0 2.0 3.0 3.0 4.0 3.0 2.0 2.0 2.8
93.4 93.9 90.7 95.7 96.7 83.8 92.5 80.9 96.4 80.6 78.0 98.3 96.8 90.8 89.7 92.1 92.6 97.9 94.7 90.2
Simple averages
6.0
2.2
88.0
2.6
91.3
Sources: Heritage Foundation, World Bank, and IFS. a In percent of GDP; 1994–2002 averages (in US$). b Higher index value indicates lower economic freedom raking; most recent 2004 rankings. c Higher index value indicates higher ranking; simple averages of the 1996, 1998, 2000, and 2002 rankings.
not bark’. The rankings of institutional quality evidently do not matter for mature markets to attract capital. One wonders if rating agency announcements matter for mature markets. Finally, when the emerging markets and mature markets are considered together, both institutional quality indexes are significantly correlated with portfolio investment inflows, reflecting the impact of the emerging markets.7 What is the lesson here? I think institutional quality is a good proxy for transparency in that it sheds light on the question why emerging markets are more susceptible to announcements of credit rating agencies. Furthermore, institutional quality is a broader index of uncertainty and risk, as subjectively evaluated by investors. Emerging markets are more susceptible to credit rating changes because they confront investors with greater Knightian uncertainty.8
7
Regressing log of portfolio liabilities on the logs of the institutional quality indexes yields results similar to those in Table 3. 8 These results are corroborated by the findings of Gelos and Wei (2002). They find that transparency (as measured by certain indexes) has a significant impact on international portfolio investment, with less transparent
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Table 3 Regressions summary: portfolio investment liabilities on institutional quality indexes Heritage index Composite indexes Emerging markets (sample size: 28) Coefficient −3.1 t-statistic −3.9 Mature markets (sample size: 20) Coefficient −3.7 t-statistic −1.0 Emerging and mature markets (sample size: 48) Coefficient −4.0 t-statistic −3.6 Regulation indexes Emerging markets (sample size: 28) Coefficient −2.4 t-statistic −3.7 Mature markets (sample size: 20) Coefficient −1.8 t-statistic −0.7 Emerging and mature markets (sample size: 48) Coefficient −3.0 t-statistic −2.9
World bank index
0.1 2.5 −0.2 −0.7 0.1 2.6
0.1 2.8 0.3 1.0 0.1 3.2
Source: author’s estimates.
It would be illuminating to see how institutional and regulatory quality indexes (and other proxies that may be used as transparency indexes) might correlate with the speculative market pressure index (SMP) used in this paper. Thus, the impact of transparency (or lack of it) on the rating effect in emerging markets might be placed in an analytically broader and richer context. It would also be interesting to see how those indexes might correlate with variability of portfolio inflows in emerging markets, as opposed to mature markets. For future research, I venture to posit that financial market stability is significantly correlated with institutional and regulatory quality. 3. Asymmetric response to positive and negative rating changes I now turn to the second issue: Why do markets respond more to negative rating changes than to positive rating changes? I think an answer can be given along the lines of cumulative countries attracting less investment. It is also noteworthy that country risk rankings provided by the International Country Risk Guide (2004) correlate very significantly with the Heritage and World Bank composite institutional quality indexes in the case of emerging market countries in the sample, whereas this correlation is insignificant in the case of mature markets in the sample. Similar results are obtained when portfolio liabilities are regressed on risk indexes; such capital inflows are correlated significantly with risk rankings in the case of the emerging markets but are insignificantly correlated in the case of the mature markets in the samples (regression results are available from the author of this review). These results corroborate those reported in Table 3. Importantly, they underline the argument that institutional quality and transparency are good indicators of uncertainty and risk in a country.
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prospect theory (CPT) (Kahneman and Tversky, 1979; Tversky and Kahneman, 1992). In contrast to the expected utility theory, CPT posits two axioms: (i) decision makers derive utility from the increment (gain) or decrement (loss) in their wealth, as opposed to increase and decrease in total wealth; (ii) decision makers value losses more than gains.9 The rating agency announces a positive or a negative rating change. This is new information for investors. Looking forward, investors adjust their portfolios accordingly. If the announcement on an emerging market is positive, then they move a part of their portfolio from the less uncertain mature market assets to more uncertain emerging market assets, and conversely, if the announcement on an emerging market is negative. However, under CPT, investors value losses more than gains. Therefore, given transactions costs, for a ‘unit’ rating upgrade from which they expect to gain by going long on emerging market assets, investors move a smaller portion of their mature market assets to emerging market assets. But for a ‘unit’ rating downgrade, they expect to avert losses by going short on emerging market assets, and because losses are valued more than gains, they move a greater share of emerging market assets to mature market assets. Therefore, comparable negative rating changes have a greater impact than positive rating changes.10
4. Concluding remarks This is a very interesting and a technically solid paper. It provokes important questions for future research, two of which I have attempted to address. Future research on financial markets and portfolio selection should attempt to incorporate decision making under Knightian uncertainty and the arguments and experimental findings of cumulative prospect theory. Effective financial regulation is an important economic institution. Its impact on financial markets can be better understood in that context.
9 That is, in absolute values, U(Loss) > U(Gain) for all Loss = Gain, or, U(Loss) is everywhere steeper than U(Gain); the comparison is relative to the status quo, which is indexed at zero, or, U(0) = 0. This effect is sometimes referred to as loss aversion. For example, suppose an investor is allocating his or her portfolio between a safe (mature market) and a risky (emerging market) asset and the optimal ratio of wealth allocated to the risky asset is x* = f({ai }), 0 < x* < 1, where {ai } is a vector of variables that determines x* . A change in ai can imply a downgrade (increase in probability of default) or an upgrade (decrease in the probability of default). Loss aversion implies that |∂x* /∂ai |loss > |∂x* /∂ai |gain . I do not propose a portfolio model based on CPT here and rely on the intuitive arguments below. A formalization that supports my arguments is by Barberis et al. (2001). 10 Of course, asymmetric information on negative and positive developments in emerging markets may result in behavior similar to behavior with loss aversion. For example, rating agencies may have a greater informational advantage for downgrades than upgrades, hence the downgrade signal could be stronger than the upgrade signal (I am grateful to Prof. Jerry Dwyer for pointing out this possibility). The impact of informational asymmetry between downgrades and upgrades would strengthen the impact of loss aversion on asymmetric response to positive and negative rating changes. Nevertheless, a good case can also be made that rating agencies also have a strong incentive for sending as strong a signal for the good picks as for the bad picks, because, for example, they enhance their good reputation by picking money-making opportunities ahead of the pack.
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References Barberis, N., Huang, M., Santos, T., 2001. Prospect theory and asset prices. Quart. J. Econ. CXVI (1), 1–53. Erbas¸, S.N., 2004. Ambiguity, Transparency, and Institutional Strength, IMF Working Paper 04/115, Washington: International Monetary Fund. Gelos, G., Wei, S-J., 2002. Transparency and International Investor Behavior, IMF Working Paper 02/174, Washington: International Monetary Fund. Glennerster, R., Shin, Y., 2003. Is Transparency Good for You, and Can IMF Help?, IMF Working Paper 03/132, Washington: International Monetary Fund. Heritage Foundation, 2005. References available on the web, http://www.heritage.org. International Country Risk Guide, references available on the web, http://www.icrgonline.com. Kahneman, D., Tversky, A., 1979. Prospect theory: an analysis of decision under risk. Econometrica 47 (2), 263–291. Knight, F., 2002. Risk, Uncertainty and Profit. Beard Books, Washington, DC, originally published in 1921. Sargent, T., 1993. Bounded Rationality and Macroeconomics. Oxford University Press, New York. The World Bank Institute, 2005. Governance, Regulation and Finance Division, references available on the web, http://www.worldbank.org/wbi/governance/govdata2002/index.html. Tversky, A., Kahneman, D., 1992. Advances in prospect theory: cumulative representation of uncertainty. J. Risk Uncertainty 5, 297–323.