Modeling Barriers to International Capital Flows: A Multicountry Framework

338 Modeling Barriers to International Capital Flows: A Multicountry Framework A. Seddik Meziani Montclair State University, USA Abstract To explain the bias in favor of domestic securities known as the “international diversification puzzle,” the literature has considered many possible irritants of capital movements across national boundaries but the results remain inconclusive. This paper demonstrates that this complex multivariate problem can be addressed within an analytic hierarchy process (AHP)-driven expert system. The AHP can be modeled to select an optimal investment portfolio (OIP), herein a multinational portfolio composed of national markets where barriers to capital flows are least likely to adversely affect its return. Experts examined these barriers in relation to six national markets and the euro zone. The U.K. turns out to be their market of choice closely followed by Canada, and the Euro Zone. There is gain to be made from using the opinion of those with first- hand understanding of foreign markets and knowledge-based expert systems such as the AHP are best suited to capture that expertise. Introduction The underlying theoretical basis of diversification formalized in Markowitz Portfolio Theory and the Capital Asset Pricing Model has been well documented in the finance literature. International diversification enables investors to reduce the unsystematic risk of investing in one economy. Business cycles do not happen uniformly across countries; when one country is experiencing rapid growth, another may be in a recession. By investing across countries, investors should logically eliminate from their portfolios part of the cyclical fluctuations that would arise from the domestic business cycle. Such investors will only be exposed to systematic risk related to the global economy. Since Markowitz’s seminal work (1952), many of the studies that have explored the merit of holding international assets as a part of a strategically balanced portfolio confirm diversification as the most important motivating factor in international investment. For example, in Worzala’s survey (1994) diversification is ranked as very important by a substantial majority of respondents. In a survey of British investors, Baum (1995) also finds diversification as the main motivator of international investment. But in spite of the theoretical and matter-of-fact groundings of international diversification, many studies have demonstrated that investors nevertheless hold portfolios that consist nearly exclusively of domestic assets. This violation of standard theories of portfolio choice is known as the “international diversification puzzle.” For example, in 1991 French and Porteba report that U.S. investors hold about 94 percent of their financial assets in the form of U.S. securities. For Japan, U.K., and Germany, the share of domestic assets in each case exceeds 85 percent. They find an explanation to the apparent tendency of U.S. pension funds to overweight their own equity market in explicit limits on cross-border investment known as the ‘prudent man’ rule. In Japan where insurance companies cannot hold more than 30 percent of their assets in foreign securities this rule is also interpreted as limiting their degree of international exposure. In France a foreign investor may not hold more than 20 percent of any firm without prior approval from the Ministère de l’Economie et des Finances. In 1995, Tesar and Werner showed that domestic assets continue to overwhelmingly dominate portfolios despite the rapidly growing volume of international financial trade. They examined the foreign investment positions of major industrial countries and found that international investment as a fraction of the total domestic market of stocks and bonds equaled about 3 percent for the U.S., 4 percent for Canada, 10 percent for Germany, 11 percent for 339 Japan, and 32 percent for the United Kingdom. Excluding the U.K., calculations of a diversified portfolio would have much higher fractions devoted to international assets. So why do investors seem to have this bias in favor of securities of their home country? Standard models of optimal portfolio choice cannot rationalize this pattern of asset holdings, even in the presence of unhedged foreign exchange risk. Of the several possible reasons, Worzala (1994) finds that transaction costs in less liquid markets and particular taxation regimes such as a dividend withholding tax on payments to foreign shareholders could have significant repercussion for investment performance. He considers them among the most significant irritants of capital movements across national boundaries. Barriers to capital movements can take many other forms such as foreign exchange and capital controls. Exchange controls increase pure exchange rate risk while capital controls restricts capital flows across national boundaries. Where formal capital controls on foreign investment exist, securities command abnormal risk premium. Both effects are well documented in the literature (Errunza and Losq, 1985; Eun and Janakiramanan, 1986). Or perhaps, evidence given by Gatti and Tverski in 1990 that households behave as though unfamiliar gambles are riskier than familiar gambles even when they assign identical probability distributions to the two gambles should be given serious thought in future investment portfolio research. Obviously many factors can constraint the flow of capital movements across national boundaries. Various methodologies have been used to explain investors’ bias in favor of domestic securities but the results remain clearly inconclusive. This study advocates a different approach to this multivariate problem. It suggests that this problem can also be addressed within an analytic hierarchy process-knowledge-based expert system. First, the finance literature is used to identify the most significant barriers to international capital flows. These barriers are then submitted to the review of a sample of international investment experts operating in the New York metropolitan area. Using their market experience, they identify the most formidable of these barriers by comparing them to each other. They also compare them in relation to a sample of countries they were provided with. This identification and selection process ultimately generates the optimal investment portfolio (OIP). This diversified portfolio best represents a frictionless multinational portfolio. It is composed of national markets where barriers to international capital flows are least likely to adversely affect its return. This process takes full advantage of practitioners’ knowledge of these markets by providing them with a comprehensive model that integrates the effect of all the interactive parameters. The Analytic Hierarchy Process (AHP): A Knowledge-Based System Model This research illustrates how the OIP can be formed based on the analytic hierarchy process (AHP), first developed by Saaty (1980). The AHP is a simple decision analysis model appropriate when the decision maker wants to deal with complex, unstructured, and multi-attribute problems in arriving at the overall best decision. Applications of the AHP have been reported in numerous fields such as conflict resolution, project selection, budget allocation, transportation, health care, and manufacturing, but it has yet to be applied to portfolio selection. The strength of the AHP lies in its ability to mimic practitioners’ judgment about the importance that would be attached to different influential factors and to structure a complex and multi-attribute system matrix. The AHP assumes the three basic principles of logical analysis: constructing hierarchies, establishing priorities, and maintaining logical consistency. Structuring The Hierarchy The AHP initially breaks down a complex multi-criteria decision-making problem into a hierarchical structure. The hierarchy pyramid is structured by enumerating the relevant elements that should enter into the decision outcome. The elements are then grouped in levels. The top level of the hierarchy, referred to as focus, consists of a single element or goal, which is the overall objective. The elements that affect the decision are called attributes or criteria. They are included in the subsequent levels, each of which may have several elements. Attributes are mutually exclusive and their priorities are 340 independent of the elements positioned below them in the hierarchy. The lowest level of the hierarchy is referred to as alternatives, which are decision options (see Fig. 1) (Saaty, 1980). Setting Priorities Once the problem has been decomposed and the hierarchy constructed, the prioritisation procedure starts in order to determine the relative importance of the elements on the next higher level. The pair-wise judgment starts from the second level (first level of attributes) and finishes in the lowest level alternatives. The AHP uses pairwise comparisons to establish priority weights for all elements in the hierarchy. Pairwise comparisons are repeated until all combinations of elements have been exhausted. The level comparisons result in a “priority vector,” which indicates the relative importance of the elements with respect to each criterion. The decision maker must express preference between each pair of elements. Each pairwise comparison is scored as: equally important (1), moderately more important (3), strongly more important (5), very strongly more important (7), and extremely more important (9) (Saaty, 1980; 1982). An even preferential number scoring system can also be used to represent comparisons among a pair of attributes. This method of ranking enables the decision maker to incorporate his/her experience and knowledge in an intuitive and natural manner. Maintaining Logical Consistency After forming the preference matrices, the mathematical process commences in order to normalize and find the priority weights for each matrix. The AHP process then determines the consistent nature of the pairwise comparisons (i.e. consistency ratio (CR)) for all matrices. If the CR value is larger than 0.10 (which is the acceptable upper limit for CR (Saaty, 1982)), it implies that there is a 10 per cent chance that the elements are not compared well. In this case the decision maker must review the comparisons again. The mathematical process then starts to integrate the assigned weights in order to develop an overall evaluation process (i.e. the mathematical process to determine the CR values and the corresponding weights for each alternative). Although the mathematical process of the AHP is tedious, the use of expert system makes it simple and accurate to apply (Turban, 1993). Level I: Overall Focus Objective Level II: Attribute 1 Attribute 2 Sub-attribute Sub-attribute Sub-attribute Sub-attribute Sub-attribute Sub-attribute 1 2 3 1 2 3 Alternative Alternative Alternative 1 2 3 Fig. 1: A GRAPHICAL REPRESENTATION OF THE MECHANICS OF THE AHP Level III: Level IV: 341 Application Of The AHP Model The hierarchy in this application contains four levels (see Fig. 2). The first level of the hierarchy identifies the objective: selection of the OIP. The second and third levels are the intermediate levels, which include the criteria and subcriteria used to achieve the overall objective. These are the macro (criteria) and micro (subcriteria) barriers that determine the choice of the OIP. The fourth and final level of the hierarchy lists the particular national markets from which this portfolio will be constructed. The macro and micro barriers to international capital flows are defined in Table 1. Pairwise comparisons are used to establish priority weights for all the elements of the hierarchy. First, the decision maker provi des judgments about the relative importance of each macro and micro barriers of levels two and three in terms of its effect on the overall objective. Next, a preference is specified for each national market (level four) relative to each barrier. Given the information on the relative importance of the barriers and national market preferences with regard to each barrier, a mathematical process is used to synthesize the information and provide priority measures indicating the ranking of all the national markets. Table 1: DEFINITION OF MACRO AND MICRO BARRIERS TO INTERNATIONAL INVESTMENT ? Discriminatory Taxation: In some overseas markets, U.S. investors are more heavily taxed than domestic investors. ? Exchange Risk: U.S. investors in overseas markets are subject to the risk of dollar appreciation, which diminishes their total return when profits are repatriated. ? Legal Restrictions: U.S. investors face a complex web of regulations and rulings overseas, including: o Foreign Ownership: Limitation of the percentage of foreign ownership of financial assets or restriction of ownership to specific areas. o Market Regulations: Foreign ownership flowing into or out of overseas markets might be restricted through the imposition of capital controls. ? Liquidity Risk: In a shallow overseas market with insufficient demand, attempts to liquidate assets on a large scale reduce the market value of the assets. ? Political Risks: Funds invested internationally fall under the jurisdiction of the host country, subjecting international investments to rules established by local governments no matter how arbitrary or unfair such regulations may appear. The most common types of political risks are: o Expropriation of Assets: The government of the country where funds are invested confiscates the capital investment. o Repatriation of profits: U.S. investors are unable to convert earnings into dollars for the repatriation of profit because of the host government’s rigid currency rules. ? Psychological Barriers: Distance from overseas markets and perceived differences in work habits and standards may cause investors to hesitate in investing in foreign markets. This reluctance can be triggered by the following: o Language Barriers: U.S. investors can find it particularly difficult to conduct business in a national market that uses a language with which they are unfamiliar. o Source of information: Availability and dependability of information on individual companies and industries may vary greatly from one national market to another. This set of data, if available, may be hard to translate into familiar standards for comparison purposes. For example, differences in accounting measurement and auditing practices between the United States and other countries may make the financial statements from a firm located in a foreign market harder to interpret. ? Transaction costs: These are the costs incurred in placing the order and securing the certificates. Because of the international dimension of the investment, these costs can be higher than domestic costs. Major transaction costs are: 342 o Custodial fees: These fees cover international custodial services such as automated trade notification, cash management services involving different currencies, and a network of sub custodians in different countries. o Management Fees: These are fees charged by international money managers. They might be higher than those charged by domestic management because they reflect higher costs in terms of international database subscription, research, communication costs, and so on. Bold nodes represent macro barriers to international investment whereas clear nodes represent micro barriers. The basis of this procedure is the completion of an “n x n” matrix where the entries (a ij ) set forth the answers to the series of questions included in the survey. For example, “Which national market (a i or a j ) is more advantageous for the U.S. global investor with respect to foreign exchange risk?” Using the comparison scale, the answer to this pairwise comparison is entered into the “n x n matrix.” If the entry “9” is shown at the a 12 position (e.g., Euro Zone vs. Australia), this means that national market a 1 (Euro Zone) is “extremely favored” over national market a 2 (Australia) with respect to “foreign exchange risk.” One result of a pairwise comparison of elements within the matrix structure is that a diagonal that runs from the upper left corner of the “n x n” matrix to its lower right corner is composed entirely of cells with the value “1.” This depicts the comparison between a national market and itself. Once the upper triangular portion values above the “1 diagonal” are known, the lower triangular portion values can be determined because the transpose values are reciprocals (Saaty, 1982). Subsequently, in our example above, 1/9 is entered at the symmetric position a 21 . Once all the entries of the matrix are available, one can easily solve for the priority weights for all elements in the hierarchy. Sample Design The size of the sample is limited to seven markets to minimize inconsistencies in respondent judgments. A larger sample would generate an excessive number of pairwise judgments, which would heavily tax the capacity of the respondents to be consistent throughout the survey (Miller, 1956). Also, as the collaboration of U.S. global investment experts is critical to the completion of this study, a larger sample would mean a longer survey, which could limit the number of responses, thereby weakening the results of the analysis. Choice of the countries used in this analysis assumes that a low correlation coefficient between the U.S. market and other national markets is a key capital flow driver. It is generally accepted that if markets tend to experience somewhat identical cycles, diversification across national markets will be less effective. Note that, in the sample, the Euro Zone is the area in which the euro is the single currency for its twelve members. 1 Due to a lack of common statistics, the inclusion of the Euro Zone in the sample is justified by showing the correlations of Germany and France with the U.S in Table 2. This choice should be self-explanatory. In addition to being considered the two “economic engines” of Europe, their macroeconomic aggregates are widely viewed as having initially set the benchmarks for inclusion in the Euro Zone. Table 2 reports the correlations coefficients among the monthly returns of nine major stock markets in 1987-2000. Of the eight correlations reported between the United States and the eight other markets (bottom row), the highest is the coefficient between Canada and the United States (0.77). This comes as no surprise since Canada, being a neighboring country and the largest U.S. trading partner, has strong business linkages with the United States. The next highest correlation is found between the U.S. and the U.K. markets (0.67). Given the strong linguistic and economic ties between the two countries, the high correlation is also not surprising. On the other hand, the lowest correlation is found between the U.S. and the Japanese markets (0.26). This is to be expected considering that the 1990s saw the United States in a long and strong business cycle expansion. But the decade brought only severe recession in Japan. 343 The correlation coefficient matrix as a whole conveys that capital markets are becoming increasingly integrated. However, although their convergence has gradually decreased some of the benefits of international portfolio diversification, the correlation coefficient between markets are still far from 1.0, indicating that there are still factors acting against their total integration. Data Collection The AHP does not need a formal data set. It requires that experts use experience gained in the field to state judgments on criteria and alternatives. In this case, qualitative judgments on the barriers to international capital flows as defined in Table 1 are obtained from a 25-page questionnaire mailed during the fourth quarter of 1999 and first quarter of 2000 to 40 randomly selected firms operating international investment divisions in the New York metropolitan area. Bearing in mind that this study is based on the interview survey method conducted in an international context, the response rate could be considered fairly high with 15 respondents completing the survey. 2 The respondents are high enough in their institutions’ management hierarchy to have decision responsibility. Their experience making international investment decisions ranges from 3 to 10 years with an average of 4 years and 9 months. The names of the institutions that responded and accepted to be subsequently interviewed are listed in Table 3. Note that this list excludes five participants who did not answer all the questions in the survey because of their stated lack of expertise in some of the specific national markets included in the sample. All of the respondents insisted on having their names and remarks kept confidential. Two respondents also insisted on having the names of their employers undisclosed. In effect, the survey’s findings reflect the answers of 15 representatives although Table 3 lists only 13. TABLE 2: CORRELATION COEFFICIENTS AMONG MONTHLY RETURNS OF MAJOR STOCK MARKETS, 1987-1998 (All returns are converted to U.S. dollars) Correlation Coefficients Stock Market AU CA FR GE HK JA SI UK Australia (AU) Canada (CA) 0.65 France (FR) 0.43 0.46 Germany (GE) 0.33 0.35 0.68 Hong Kong (HK) 0.62 0.65 0.42 0.38 Japan (JA) 0.25 0.29 0.42 0.25 0.19 Singapore (SI) 0.68 0.63 0.47 0.45 0.78 0.37 United Kingdom (UK) 0.6 0.59 0.59 0.52 0.58 0.45 0.66 United States (US) 0.56 0.77 0.55 0.42 0.61 0.26 0.66 0.67 Source: Morgan Stanley's Capital International Perspectives (1999). 344 The survey outlines a scenario in which a U.S. investor is considering adding foreign securities or other types of foreign investment products to a portfolio of U.S. assets. 3 It asks respondents to evaluate the specific barriers to international capital flows as defined in Table 1. Other factors, such as inflation or interest rate differentials, were to be considered equal for the purpose of this study. The AHP model and the logic of its procedures were explained to the respondents and illustrated with simple examples by a group of graduate students who met with them. The same group of students met with them subsequently to go over the answers and collect some of their thoughts. The first part of the questionnaire asks the respondents to use their perspectives as expert global investors (without regard for a particular national market) to evaluate the relative importance of each barrier to international investment. They did this through a series of pairwise comparisons of each barrier to every other barrier. The AHP matrices of levels two and three of the hierarchy in Figure 2 are calculated from these pairwise judgments. In the second part of the questionnaire, the respondents are asked to make pairwise comparisons of the national markets with respect to each impediment in levels two and three of the hierarchy. Responses to the second part of the survey are used to construct level four of the hierarchy. All responses were combined using the geometric mean for each pairwise judgment to estimate the relative priorities. The resulting (geometric) mean judgments are evaluated using Saaty’s eigenvector method to estimate the priority of each barrier in terms of its contribution to constraining international capital flows and its subsequent weight in determining the OIP. Findings Table 4 shows respondents evaluation of the seven macro barriers of level two of the hierarchy in relation to each other (pairwise) and with respect to the selection of the OIP. The vector of priority weights in the bottom row can be interpreted to describe either the importance of one macro barrier over another or the relative attention that each should be paid in the selection of a national market for investment. AT&T Investment Management Corporation Mellon Financial Company Barclays Capital Merrill Lynch & Co. Cendant Corporation New Jersey Division of Investment Citigroup Prudential Financial Hoffmann-La Roche, Inc. Teachers Insurance Annuity Association Ingersoll-Rand Co. Name of institution withheld upon request International Paper Company Name of institution withheld upon request Lucent Technologies, Inc * Five organizations responded partially to the survey and thereby were not included in the analysis. Source: Respondents were selected from "The Money Market Directory of Pension Funds and their Investment Managers", Standard & Poor’s, 1999. TABLE 3: LIST OF RESPONDENTS* 345 The priority weights show that “foreign exchange risk” is the most important barrier, and “psychological barriers” the least important. “Foreign exchange risk” is given almost 20 percent more weight than the next highest barrier, “political risks,” and approximately 46 percent more weight than “discriminatory taxation.” These results imply that a national market with a stable currency is the most important criterion to U.S. global investors. If the currency of the market in which the funds are invested weakens against the dollar, earnings will convert into fewer dollars. Although this result outlines the important role played by foreign exchange markets’ in the world economy, it comes as a surprise especially in light of the many financial tools that could be used to neutralize “foreign exchange risk.” Experts, however, justified their answer emphasizing that these tools are not “exactly free” and are often “as good as the ability of analysts to forecast the path of a currency.” Some brought up past predictions of a strong euro that proved to be wrong. 4 But, in reality most respondents acknowledged that they have become especially wary of “foreign exchange risk” after the severe currency crisis in Mexico in late 1994 followed by that of Asia in 1997 and then Russia, Brazil, and Turkey. 5 As expected, these crises are hardly the ingredients for successful investing. In descending order of importance, the other highly ranked impediment is “political risk.” Defined as the inability to repatriate profits or/and likelihood of the capital investment being expropriated (micro impediments from level III of the hierarchy in Figure 2), the former seems to give more worry to the respondents than the latter. This result does not come as a surprise given that most countries have hardly any recent history of expropriations. As shown in Table 5 (Panel b), on the average, the respondents believe that the likelihood of a foreign government restricting repatriation of profits (0.106) is about twice as likely than a potential threat of expropriation of foreign assets (0.056). Seemingly, respondents have learned hard lessons from the rigid currency rules adopted by Asian countries in an effort to stop extreme short-term capital movements. Macro Discri- Exchange Legal Liquidity Political Psycho- Transaction Impediments minatory Risk Restrictions Risk Risks logical Costs Taxation Barriers Discriminatory 1 1 1 1 1 2 2 Taxation Exchange 1 1 1 1 1 3 3 Risk Legal 1 1 1 1 1 2 3 Restrictions Liquidity 1 1 1 1 1 3 2 Risk Political 1 1 1 1 1 3 3 Risks Psychological ½ 1/3 ½ 1/3 1/3 1 ½ Barriers Transaction ½ 1/3 1/3 ½ 1/3 2 1 Costs Priority 0.15 0.217 0.165 0.152 0.181 0.067 0.068 Weights ? max = 7.032 C.I. = 0.005 C.R. = 0.004 TABLE 4: SECOND LEVEL OF THE HIERARCHY: COMPARISON MATRIX OF THE MACRO BARRIERS TO CAPITAL FLOWS 346 Other macro impediments of importance to the respondents are “legal restrictions,” “liquidity risk,” and discriminatory taxation.” Components of “legal restrictions” are “foreign ownership” and “market regulations.” Their weights in Table 5 (Panel a) represent the priority of each one of these micro barriers in the selection of the OIP. For example, the first weight represents the portion of “legal restrictions” attributed to “foreign ownership” (0.086). The two weights are not very different, although the respondents express a slightly higher concern for “foreign ownership” problem in national markets where foreign capital can be limited by percentage than for “market regulations” such as imposition of capital controls. Constraints on ownership of financial assets to specific industries are still common in many countries. Although not included in the survey, some respondents gave the example of China still banning foreign investment in the telecommunications and banking industries whereas its financial markets still remain off limits to foreign firms. They also believe that the financial markets of most emerging economies lack both depth and liquidity for dollar-denominated debt, equity, interest-rate derivatives, and repurchase agreements. On the other hand, macro barriers such as “psychological barriers” and “transaction costs” (0.067 and 0.068, respectively) are judged by our sample of experts as insignificant impediments. These results are quite puzzling at first because one would expect a U.S. investor about to venture into unfamiliar markets to be affected by such factors. “Psychological barriers” such as the numerous differences in work habits and work standards that may exist between foreign markets and U.S. financial markets, and higher “transaction costs,” such as the extra costs involved in securing the ownership of a foreign certificate, would seem impossible to ignore when diversifying a portfolio across national boundaries. Table 5 (Panels c and d, respectively) breaks these two elements into the micro barriers of level III for the specific purpose of gathering more information from the respondents on their relative importance: “language barriers” and “sources of information” are micro aspects of “psychological barriers” while “custodial fees” and management fees” are micro aspects of “transaction costs.” (Panel a) (Panel b) Legal Foreign Market Political Expropriation Repatriation Restrictions Ownership Regulations Risks of Assets of Profits Foreign 1 1 Expropriation 1 ½ Ownership of Assets Market 1 1 Repatriation 2 1 Regulation of Profits Priority 0.086 0.078 Priority 0.056 0.106 Weights Weights ? max = 2.001; C.I. = 0.001; C.R. = 0.001 ? max = 2.000; C.I. = 0.0003; C.R. = 0.0003 (Panel c) (Panel d) Psychological Language Sources of Transaction Custodial Management Barriers Barrier Information Costs Fees Fees Language 1 1/3 Custodial 1 ½ Barrier Fees Sources of 3 1 Management 2 1 Information Fees Priority 0.018 0.049 Priority 0.02 0.059 Weights Weights ? max = 2.0002; C.I. = 0.0002; C.R. = 0.0002 ? max = 2.0006; C.I. = 0.0006; C.R. = 0.0006 Table 5 : THIRD LEVEL OF THE HIERARCHY: COMPARISON MATRIX OF THE MICRO BARRIERS TO CAPITAL FLOWS 347 The results show that survey participants believe these particular micro barriers should contribute only marginally to the selection of the OIP. When further interviewed, respondents justified their answer by the assertion that most U.S. investment firms trading internationally have established their own international links, thereby eliminating the need for costly intermediaries. Local staffing has reduced “psychological barriers.” A number of respondents mentioned that “language” is not much of a hindrance as most of the foreign experts they deal with speak adequate English. When asked about differences in accounting and reporting practices in the sampled national markets, participants responded that a knowledgeable local staff, versed in local accounting practices, provides them with an effective way to cope with this problem. 6 The pairwise comparison procedure is also used to determine the priority ranking of the seven “national” markets in terms of the barriers to international investment (level four of the hierarchy). The question asked now is: “Of the two national markets being compared in terms of a specific investment barrier, which one should be favored?” Tables 6 and 7 show the matrices and the national market priority weights for macro and micro impediments. These results show reasonable consistency indices, which indicate that experts responded with largely consistent judgments. The priority weights summarized in Table 8 (excerpted from Table 6) show that four out of the seven macro barriers are judged less important in the case of Canada and the U.K. than for the other national markets: “transaction costs,” “psychological barriers,” “political risks,” and “legal restrictions.” These results indicate the respondents’ preference for these two markets. The respondents’ evaluation of the micro impediments underlying “legal restrictions” and “market regulations” also show that they are less of an impediment to the U.S. investor in Canada and the U.K. Japan shares respondent preference with the U.K. with regard to “liquidity risk.” This is not a surprise, as Japan and the U.K have the two largest capital markets outside the U.S. That U.K. and Japanese markets are the most liquid after the U.S. is of particular interest as an important market selection criterion. On the other hand, the results in Table 8 indicate that in Australia foreign investments are taxed the least, followed next by the U.K., Canada, and the Euro Zone. “Discriminatory taxation” is judged the highest in Japan. The Japanese market does not seem to be an obvious choice for an investor who is reluctant to pay higher taxes. With “foreign exchange risk” the most heavily weighted macro impediment (0.217), the national market that is most favored by the respondents with respect to this factor will be prominent in the selection of the OIP. In this case it is the U.K.—not an unexpected result as the British Pound had tended to be more stable than the euro or the yen. For investors especially wary of currency fluctuations, the British market should be the market of choice, followed by the Euro Zone, Canada, and Japan. Although the Hong Kong dollar has been quite stable in the midst of Asia’s crisis, respondents remain quite skeptical. With new problems in the financial system cropping up almost daily, they believe that it is a matter of time before China’s central bank will introduce radical changes, such as allowing the currency to float freely. [...]... Saaty’s AHP to evaluate market barriers to capital flows across national boundaries The AHP makes it easy to model their influence on the OIP This process readily lends itself to multicriteria decision-making because of its ability to deal with subjective judgments Survey respondents use the AHP-derived priorities to rank several national markets in terms of particular barriers to international capital. .. Choi, and Levitch 1991 International accounting diversity: Does it affect market participants? Financial Analyst Journal, 47(4): 73-82 [3] Errunza, V and E Losq 1985 International asset pricing under mild segmentation: theory and test Journal of Finance, 40(1): 105-24 [4] Eun, S C and S Janakiramanan 1986 A model of international asset pricing with a constraint on the foreign equity ownership Journal... 0.068 1.000 Shaded numbers indicate experts' preference for a national market(s) vis-à-vis a specific macro impediment For example, Australia's market weight of 018 indicates that our panel of experts sees its tax system as the least discriminatory to foreign capital Finally, Australia, the U.K., and the Euro Zone are accorded about the same priority weights with respect to “political risks” (and its micro... other Although the U.K has yet to join the Euro Zone, global portfolio managers may already have started to view them as one market Overall priority weights next indicate inclusion of Australia (0.137) and to a lesser extent Japan (0.144) in the OIC Excluded by the U.S investor highly concerned with individual market imperfections are Singapore and especially Hong Kong Conclusion This study adapts Saaty’s... Finance, 41(4): 897-914 [5] French, K and J Poterba 1991 International diversification and international equity markets American Economic Review, 81(2): 222-226 [6] Ritov H., I Gatti, and A Tverski 1990 Differential weighting of common and distinctive components Journal of Experimental Psychology: General, 19(1): 30-41 [7] Jacquillat B and B Solnik 1978 Multinationals are poor tools for international. .. 1 1 1 1 5 Japan 1 1 1 1 1 1 1 6 Singapore 7 U.K 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Priority Weights 0.010 0.008 0.009 0.011 0.011 0.011 0.008 ?max = 7.008; C.I = 0.001; C.R = 0.001 349 TABLE 8: MARKET WEIGHTS WITH RESPECT TO THE MACRO BARRIERS TO INTERNATIONAL CAPITAL FLOWS Macro Impediments Discriminatory Taxation Exchange Legal Risk Restrictions Liquidity Risk Political Risks Australia Canada Euro Zone... McGraw-Hill [11] Saati, T L 1982 Decision making for leaders: The analytical hierarchical process for decisions in a complex world Belmont, CA: Lifetime Learning Publications [12] Standard & Poor’s 1998 The Money Market Directory of Pension Funds and their Investment Managers New York: McGraw-Hill [13] Tesar L and I.M Werner 1995 Home bias and high turnover Journal of International Money and Finance, 14(4):... important constraint is exchange risk The OIP is then constructed 350 by selecting those national markets judged least likely to be affected by the most important impediments Each stage of the AHP hierarchy contributes to the construction of the portfolio The national markets that constitute the OIP are judged least frictional, so they are suitable for investors who want to diversify across national boundaries... the main challenges faced by this study is to convince enough decision makers to contribute to this research Justifiably, some might view this challenge as the study’s weakness After all, how many time-pressed executives are going to take the time to fill out similar surveys whenever one wishes to generate an OIP using a knowledge-based expert system Those skeptics are reminded that a multinational corporation... research has demonstrated that the AHP is an appropriate approach to selection of such an investment portfolio There is gain to be made from using the opinion of those with first-hand understanding of foreign markets and knowledge-based expert systems such as the AHP are best suited to capture that expertise 351 References [1] Baum, A. 1995 Can foreign investment be successful? Real Estate Finance, 12(2): 81-9 . 338 Modeling Barriers to International Capital Flows: A Multicountry Framework A. Seddik Meziani Montclair State University, USA Abstract To explain the. Conclusion This study adapts Saaty’s AHP to evaluate market barriers to capital flows across national boundaries. The AHP makes it easy to model their influence