Joan-Ramon Borrell
email: jrborrell@ub.edu

Pricing and Patents of HIV/AIDS Drugs in Developing Countries

Keywords: L11 -Production, Pricing, and Market Structure|Size Distribution Patents, Pricing, Pharmaceuticals, HIV, AIDS Patents, Pricing, Pharmaceuticals, AIDS. JEL Codes: L11, L51, L65, O34

This paper provides empirical evidence on the impact of patents on drug prices across developing countries. It uses sales data on HIV/AIDS drugs in a sample of 34 low and middle-income countries between 1995 and mid-2000. The main findings are that patents do shift drug prices up, that drug prices are correlated to per capita income levels, and that drug firms follow a skimming strategy when pricing new HIV/AIDS drugs. That is, there is across country and intertemporal price discrimination in the global drug markets.

Introduction

The impact of patents on drug prices has emerged as a controversial issue in the face of the Human Immunodeficiency Virus (HIV) public health crisis. Activists blame patents for keeping prices out of the reach of those who badly need new drugs called antiretroviral drugs (ARV), and lobby strongly for letting generics compete with original brand products protected by patents in developing countries. ARV drugs are effective and safe drugs that have changed the late stage of the HIV infection, the Acquired Immune Deficiency Syndrome (AIDS), from a death sentence to a chronic disease. Drug firms argue that patents are not a barrier to access to the new drug therapy, because of tiered or compassionate pricing, and that patents are key mechanisms to encourage research and development of new medicines and vaccines.

Most of the studies on patents and pricing focus on the effect of patent expiration on drug pricing and shares in the US: [START_REF] Hurwitz | Persuasion or Information? Promotion and shares of brand name and generic pharmaceuticals[END_REF]; [START_REF] Caves | Patent expiration, entry and competition in the US pharmaceutical industry[END_REF]; [START_REF] Grabowski | Brand loyalty, entry, and price competition in pharmaceuticals after the 1984 drug act[END_REF]; Frank andSalkever (1992, 1997); [START_REF] Griliches | Generics and new goods in pharmaceutical price indexes[END_REF]; [START_REF] Hellerstein | The demand for post-patent prescription pharmaceuticals[END_REF] and, [START_REF] Fisher | Aggregate price indices, new goods, and generics[END_REF]. [START_REF] Hudson | Pricing dynamics in the pharmaceutical industry[END_REF]2000) analyzes drug pricing dynamics and patent expiration not only in the US, but also in the UK, Germany, France, and Japan. A common finding 3 of these papers is that the larger the numbers of competitors, the lower drug prices are, and that brand name products might even increase in price after the introduction of generics. This is what [START_REF] Scherer | Pricing, profits and technological progress in the pharmaceutical industry[END_REF] named the "generic paradox."

Very little attention has been devoted to studying the impact of patent rights on drug pricing in developing countries. Some papers attempt to simulate the likely effects of product patents on average drug prices in developing countries. In the cases of Argentina and India, [START_REF] Challu | The Consequences of Pharmaceutical Product Patenting[END_REF], [START_REF] Fink | How Stronger Patent Protection in India Might Affect the Behavior of Transnational Pharmaceutical Industries[END_REF], and [START_REF] Watal | Pharmaceutical Patents, Prices and Welfare Losses: A Simulation Study of Policy Options for India under the WTO TRIPS Agreement[END_REF] obtain impacts of patents on average prices of a different order. Impacts of about 200% are obtained by using the assumptions that yield the highest impact and of 26% [START_REF] Watal | Pharmaceutical Patents, Prices and Welfare Losses: A Simulation Study of Policy Options for India under the WTO TRIPS Agreement[END_REF], or as low as 12% [START_REF] Fink | How Stronger Patent Protection in India Might Affect the Behavior of Transnational Pharmaceutical Industries[END_REF], with the assumptions that yield the lowest impact. Using less detailed data, [START_REF] Maskus | Trade-Related Issues of Intellectual Property Rights: Issues and Exploratory Results[END_REF] and [START_REF] Subramanian | Putting Some Numbers on the TRIPS Pharmaceutical' Debate[END_REF] obtain maximum price increases of up to 67% due to the introduction of pharmaceutical product patent rights.

Another stream of works has focused on studying the dynamics of drug pricing.

Lu and Comanor (1998) described that there are two different pricing strategies in the drug markets. The pricing strategy named "skimming strategy" corresponds to what Lu and Comanor (1998) found to be the pricing strategy for the subset of drugs which represent important therapeutic gains, as opposed to the "penetration strategy" that Lu and Comanor (1998) found to be the pricing strategy for the subset of drugs which largely duplicate the actions currently available products.

In the skimming strategy cases, drug firms introduce their products at high price which later on declines. In the penetration strategy cases, drug firms introduce their products at low price which later on increases. The literature on experience goods (those whose users determine product attributes only by using the product) explains when pioneering brands try to build up their consumer base and their reputation by a low/high (Schmalensee, 1982), and also when monopolists prefer instead to "milk its reputation" using a high/low pricing sequence [START_REF] Shapiro | Optimal Pricing of Experience Goods[END_REF]. The key issue in this literature is the buyer's perceptions of the new product quality. When consumers are pessimistic regarding the product quality, the firms needs to build the reputation of the product largely by setting a low introductory price followed by a higher regular price.

When consumers overestimate product quality, the firm will optimally set a high launch price but then lower its price over time. 1 This paper tries to fill part of the gap in the empirical literature on drug pricing. It investigates the impact of patents on pricing of HIV/AIDS drugs in a sample of low and middle-income countries in the late 1990's. This is a companion paper to that by [START_REF] Borrell | Impact of Patents on Access to HIV/AIDS Drugs in Developing Countries[END_REF] on studying patents and access to HIV/AIDS drugs. The hypothesis is that drug prices are higher under patent regimes. Patents legally prevent unauthorized manufacture, sale, importation, and using or stocking for sale of the patented product during a limited term. Patents prevent competition between the innovator of the drug (and any of its licensees) and the imitators (unauthorized providers). Patents prevent competition between providers of products that contain the same therapeutically active substance, and that only differ slightly in other characteristics. The lack of such close competitors is expected to shift prices upward.

Additionally, this paper studies how the pricing dynamics differ across patent regimes. We expect pricing strategies to differ strongly across patent regimes. Patents allow drug firms to get the most from skimming and penetration strategies. By contrast, pricing in no-patent regimes will be more closely linked to the dynamics of production costs and competition.

1 [START_REF] Bagwell | High and Declining Prices Signal Product Quality[END_REF] analyze the case in which the firms signal high quality new products with prices that are above full information profit maximizing prices. As information about the prices diffuses, the price distortion disappears. This paper uses sales data on HIV/AIDS drugs in a sample of 34 low and middle-income countries, between 1995 and mid-2000, and reduced form regressions to empirically assess the impact of market exclusivity on pricing of clinically tested ARV drug bundle (so called "cocktail therapy").

Our main finding is that the daily dose price of any "cocktail therapy" differs significantly in two dimensions: (1) drug bundles are on average more expensive when they include products under patent regime, and (2) drug bundles are on average more expensive when they include products under licenses from the firm that originally developed the drug. We also find a positive relationship between drug prices and per capita income in both patent and non-patent regimes. This finding suggests, that not only competition under non-patent regimes drives drug prices to be related to per capita income across countries, but also that multinational drug firms have effectively tiered their prices to per capita income across countries when drugs are under patent regime.

Finally, we find that drug firms set a very high initial price and then lower it over time during the 9-year period after the date the drug bundle was available on the US market only in patent regimes. This pricing strategy, named skimming pricing (as opposed to penetration pricing), corresponds to what Lu and Comanor (1998) found to be the pricing strategy for drugs, which represent important therapeutic gains.

Competition prevents price discrimination in no-patent regimes.

This paper is organized in the following way: section 2 describes the method we follow to test whether patents have a positive or negative effect on pricing, and the characteristics of the data set. Section 3 offers some descriptive statistics on patents and prices. Section 4 shows the results of estimating the impact of patents on pricing. Section 5 concludes.

Methodology

There are large number of studies in economics that use natural experiments or quasiexperiment designs to examine outcome measurements for observations in treatment groups and comparison groups. Meyer (1995) describes the strengths and weaknesses of using quasi-experiments in economics. Among good natural experiments, Meyer (1995) cites those induced by policy changes that may allow a researcher to obtain exogenous variation in the main explanatory variables. This paper uses the difference approach in a quasi-experiment to study how the outcome of interest -i.e. drug pricing, -differs for treatment groups and comparison groups that are not randomly assigned. The treatment group contains all the countrydrug pairs for which any ARV drug, in the country of a sample of developing countries, is under a patent regime, while the comparison group contains all the country-drug pairs for which the drug is not under a patent regime. Quasi-experiments allow us to distinguish the effects of exogenous variation in an explanatory variable that is, in other situations, endogenously related to the outcome of interest. The estimates of the effect of patents on drug prices are usually biased because drug firms apply for patent status across countries and drugs in a non-random way. Drug firms apply and renew the patent status of a particular drug in a given country only when both of the two following conditions hold: (1) when the firm may legally obtain a patent right from the government of that particular country (what we will refer to as the "patent regime") for the drug and

(2) when the present discounted value of the expected cash flow of patenting that drug in that country is positive (what we will refer to as the firm "patenting decision"). This paper overcomes the bias by studying the effect of a policy change on the patent regime of a set of HIV/AIDS drugs and country pairs on the outcome of interest -i.e. drug pricing. The key identifying assumption in the study is that differences in patent regimes across drug-country pairs are exogenous with respect to the outcomes in the market for ARV drugs. The paper sustains that patent law changes in the countries sampled were driven mainly by bilateral or international agreements and national developments, rather than by concerns related to the treatment of HIV patients.

As Meyer (1995) highlights, three of the main goals of the research design should be: (1) having a large enough variation in the key explanatory variables so that it is exogenous, (2) finding comparison groups that are comparable, (3) probing the implications of the hypotheses under test.

With respect to the first issue, this paper identifies the factors that drove changes in the patent regime to rule out obvious sources of endogeneity. Each drug-country patent regime indicator depends on two data: (1) whether patent protection is locally available and, (2) when the innovator can apply for patent protection in any of the World Trade Organization (WTO) member countries. The differences in patent regimes across countries, and the timing of the invention of the 14 different ARV molecules (from 1985 to 1995) lead to an appropriate mix of patent regimes across drug-country-pairs. With respect to the second issue, this paper uses different regression specifications including different sets of controls to avoid the possibility of omitted variables, trends in outcomes and omitted interactions to examine the comparability of treatment groups and comparison groups. In the regression analysis, we treat omitted variables, trends in outcomes and omitted interactions by controlling for relevant country characteristics, and also country, brand licensing status (licensed brands versus nonlicensed brands), pharmaceutical form, and annual fixed effects, and country and year Additionally, the empirical literature on drug markets draws our attention to the additional need for controlling differences in observed drug qualities such as dosage, efficacy, and side effects. 2 The following regression equation provides a simple and parsimonious way to control observable differences in the observations of different groups,

2 1 δ δ β α α j i t i j i t i jt z z r p + + + + =
where i jt p is the price of the daily dose of a single, double or triple drug bundle j in country i in year t, i t α are fixed effects for country i and year t, i j r is the patent regime of the drugs of the bundle j in country i , and β is the true causal effect of the treatment on the outcome. The regression controls for country and year characteristics ( i t z ), and also for drug bundle characteristics ( j z ). The regression equation adjusts for observable differences between the observations in the different groups.

With respect to the third issue, the paper further probes for hypotheses by testing whether the causal effect of the patent regime holds in different settings: for single, double and triple drug bundles separately, and for countries with variation in drug patent 2 The empirical literature that studies specific drug markets shows that we should control dosage, efficacy, toxicity, and side effects among other observed qualities: Berndt, Griliches and Rosset (1993) study antihypertensive drugs; [START_REF] Berndt | Information, Marketing, and Pricing in the U.S. Anti-ulcer Drug Market[END_REF][START_REF] Berndt | Network Effects and Diffusion in Pharmaceutical Markets: Anti-ulcer Drugs[END_REF]and 2000) focus on anti-ulcer drugs; [START_REF] Berndt | Pharmaceutical Innovations and Market Dynamics: Tracing Effects on Price Indexes for Antidepressant Drugs[END_REF] analyze antidepressant drugs; and Cockburn and Anis (1998) arthritis drugs. We do not have enough data on differences in drug toxicity among ARV's although higher life-threatening toxicity has been related to the use of a type of ARV, the so-called Nucleoside Reverse Transcriptase Inhibitors (NRTI). Therefore, at least drug fixed effects take care of fixed differences in toxicity across drug types. δ and 2 δ are equal across groups is important because otherwise the regression equation will not adjust for differences in control variables across groups. [START_REF] Scherer | Post-TRIPS options for access to patented medicines in developing countries[END_REF] estimated reduced form pricing equations across countries and time by using this same data set. They found a significant negative impact of patent rights on average leading multinational prices. They qualified this result as 'anomalous' and driven by: (1) measurement error, or (2) complex interrelationships between patent and other variables.

This study of the impact of patent on prices differs from that conducted by [START_REF] Scherer | Post-TRIPS options for access to patented medicines in developing countries[END_REF] in three aspects. First, we study the effect of the patent regime indicator on all firms pricing, not only on multinationals. Second, the patent regime indicator has been improved with respect to that used by them. It includes data on patent rights, exclusive marketing rights (EMR), and 'pipeline protection' available to innovators across countries and drugs as explained below. Finally, instead of regressing the price of each product on a set of country and drug effects, we regress the price of each clinically tested bundle of drugs available in any given country and year, on a set of characteristics including the patent regime indicator. This is important because ARV drugs have strong complementarities in consumption. Effective therapies are usually cocktail therapies combining two or three different drugs. Equilibrium prices are likely to be related to the dosage, efficacy and adverse reactions of each bundle of drugs that is actually available to the AIDS patients in a given country and year.

Data

Treatment of AIDS in rich countries changed dramatically after 1995, when new, more effective, and safer drugs were approved. According to [START_REF] Henkel | Attacking AIDS with a "Cocktail" Therapy[END_REF] 11 IMS data, we compute sales in milligrams for each presentation. We collected data on the minimum recommended milligrams for completing a daily dose of our 15 drugs from [START_REF] Who | ATC classification index with Daily Defined Doses 2000[END_REF] and [START_REF] Pdr-Cg | Physicians Desk Reference Companion Guide[END_REF]. Combining this information, we computed sales in terms of the number of daily single-drug treatment dose. We then obtained the price per daily single-drug treatment dose by dividing revenues in $US by sales in the number of daily treatment doses.

Patent protection on pharmaceuticals changed substantially in the countries of our sample due to the World Trade Organization (WTO) Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS). Before January 1 st 1995, 14 countries in our sample did not grant product patents. 5 Between 1996 and 2000, eight of those countries introduced patent protection for pharmaceuticals. 6Under TRIPS, WTO member countries were obliged to allow for the filing of product patents for pharmaceuticals by 1 st January 1995 and the subsequent grant of either product patents or exclusive marketing rights for eligible pharmaceutical products.7 5

These were Argentina, Bangladesh, Brazil, Colombia, Egypt, Guatemala, Guinea, India, Morocco, Pakistan, Peru, Tunisia, Uruguay and Venezuela. Pakistan had a patent law in force, but an executive order disallowed pharmaceutical patents. In the countries not providing patents to eligible drugs before 1 st January 1995, TRIPS obligations do not affect drugs that were no longer "new" for patenting purposes as of the date of filing in that country, or as of the date of priority accorded to them upon request. Therefore, we can conclude that all WTO Members would be obliged to make patents (or exclusive marketing rights) available to inventions for which the first patent application was made in any WTO member on or after 1 st January 1994. 8

"Mailbox" applications do not have to be examined until the local patent law is passed. However, when a drug subject to a "mailbox application" obtains marketing approval before the local patent office makes a decision on whether granting a patent right or not, the following special rule applies: An Exclusive Marketing Right (EMR) of up to five years (or until the patent is granted or rejected, whichever is shorter) must be granted from the date of local marketing approval, provided that a patent has been filed for that drug and a patent and marketing approval obtained in another WTO member country after 1 st January 1995. We lacked direct data on patents granted for each of the 14 different ARV molecules in each country. Therefore, we assessed instead the patent regime for each drug-country pair. We gathered information on whether product patents for pharmaceuticals were available in each country for a year after each ARV product patent application was filed in according to the key priority date given in the US. [START_REF] Balasubramaniam | Background Information on Fourteen FDA Approved HIV/AIDS Drugs[END_REF] provides the date of filing of the patent application, which the US Patent and Trademark Office reports as the key patent for each ARV. 9

Using a variety of sources, including local legislation and the complete cross-country data-set compiled by [START_REF] Qian | Do Additional National Patents Law Stimulate Domestic Innovation in a Global Patenting Environment. A Cross-country Analysis of Pharmaceutical Patent Protection: 1978-1999[END_REF], we obtained the hypothetical date from which patent protection for pharmaceuticals could have been granted for each drug in each one of the 34 countries of our sample.

We built up the patent regime indicator using the key patent priority date and the date from which each country could have granted patent protection. For each drugcountry-pair, we assessed whether product patents would have been available locally within a year from the key priority date of each molecule. TRIPS provisions on exclusive novel (since later than this date the application would then be published by another patent office after 18 months and so would no longer be novel as of or after January 1995), but we believe that this is unlikely to happen in practice. 9 The US Federal Food, Drug, and Cosmetics Act required that drug firms provide patent information with all new drug applications. Taking into account this information, the FDA sets the exclusivity term during which an abbreviated new drug application is not granted (a generic is not approved). The Electronic Orange Book (FDA, 2000) publishes the number of the appropriate patents claimed by the firms when the drugs are subject to approval. Using the patent numbers, [START_REF] Balasubramaniam | Background Information on Fourteen FDA Approved HIV/AIDS Drugs[END_REF] 1994); Ritonavir (key patent priority date -April 25 th 1995); Efavirenz (key patent priority date -June 2 nd 1995). We set the patent regime dummy variable to be 1 for these four drugs in all countries in our sample because local governments would be obliged to provide EMR or product patents to the innovators of these molecules under TRIPS rules.

Remember that the patent regime indicator does not report whether the innovator was granted or had even applied for patent protection for each drug-countrypair of our sample. In other words, it does not reflect the actual patent status of the drug.

It only shows that patent or other market exclusivity status was attainable for some years, to the best of our knowledge. So, the patent regime is arguably exogenous to any firm decision. Taking into account the value of patent protection, innovators may decide whether or not it pays to apply in each one of the countries that make available such rights.

Table 2 shows that Central America, French West Africa, Malaysia and South Africa led the sample in the number of drugs for which patents could have been granted by 2000. In these four countries or country groupings, the patent holders of all 15 ARV's could apply for patents. 10 In a second set of countries, patent laws have changed recently to make product patents available for pharmaceuticals: Mexico (1991), Thailand (1992), 10 Product patents for drugs have been granted in all Central American countries since the 1950s, except in Guatemala where product patents were introduced in 2000. We set the patent regime indicator to be equal to 1, in all the country-drug-pairs corresponding to Central America. Chile (1991) and Indonesia (1993). Mexico and Thailand led this second group of countries because they granted the so-called 'pipeline' protection when introducing legislation on product patents. In these countries, innovators could apply for patent protection for drugs in the 'pipeline', i.e. drugs not already marketed although not 'new'

for patenting, when the new law came into force. Finally, in 14 countries in our sample, innovators could only apply for patents or EMR's for the 4 drugs affected by the TRIPS rules on 'mailbox applications'.

Local prices of ARV drugs differ substantially from US prices across countries and time. Table 4 shows the wholesale minimum price per year of a set of clinically tested ARV therapies in any oral solid form (tablets, capsules, and the like): single-drug therapy;

double-drug therapy and the so-called Highly Active Antiretroviral Therapy (HAART) three-drug therapy. At the top end, the lowest priced annual triple drug bundle per patient in 1999 was higher in Mexico (US$ 8,149), Colombia ($US 7,728), Chile ($US 6,853) than in the US ($US 6,770). At the bottom end, the minimum price per annual triple drug bundle is $US 4,366 in South Africa and $US 3,025 in Brazil. The last column in Table 4 shows that the minimum price per annual triple drug bundle in 1999 was higher than the per capita income in $PPP in all the countries of the sample except in Brazil (47% of per capita income), Argentina (58%) and Chile (81%), while the minimum price was 21% of the per capita income in the US. All minimum prices of single and double drug bundles are smaller than the minimum price in the US, particularly in India, Thailand, Brazil, and South Africa.

We also matched each local product to an equivalent product in the US using data on the minimum list price in the US. 11 In 1995, sales weighted mean prices were 11 As reported in the Red [START_REF] Book | Drug Topics Red Book[END_REF][START_REF] Book | Drug Topics Red Book[END_REF]Book ( , 1997[START_REF] Book | Drug Topics Red Book[END_REF]Book ( and 2000)), the PDR-Generics (1997),

and PDR-CG (1998, 1999 and 2000). We matched each local price with the US minimum What are the drivers of the pricing dynamics? Table 6 shows that the cumulative annual decrease in the sales weighted mean price in current $US between 1995 and 1999 (column 1) is driven by three factors: (1) the introduction of cheaper new products particularly in India, Uruguay, French West Africa, and Malaysia (column 2); (2) the drop in nominal prices in current $US for the drugs already on the market, particularly in Central America, the Philippines, South Africa, and Peru (column 3); which in turn is mainly driven by (3) the depreciation of the exchange rate between the local, and the US currency, particularly in the Philippines, South Africa, and Peru (column 4). prices in local currencies because many firms were not able to increase nominal prices (column 2) to offset the negative impact of local inflation (column 3).

Results

Table 8 shows summary statistics of the variables used in the regression analysis. The dependent variable in the pricing regressions is the log of the price per daily dose of any clinically tested drug bundle available to patients in any country, in any year. There are 2,459 clinically proven one-drug, two-drug, or three-drug bundles available to AIDS patients in our data set. The right hand side variables of interest in the pricing regressions are the dummies that are equal to 1 when (1) the bundles include at least one original drug in a patent regime, (2) when the bundles includes at least one original drug in a nopatent regime, and (3) when the bundles includes at least a generic in a patent regime.

The omitted category is the case when all the drugs in the bundle are local copies introduced in no patent regimes.

We control for different vectors of price shifters. Table 9 shows the results from estimating different specifications of the pricing equation. In column (1) we include the country mean income, the country income inequality, the dosage, the efficacy, the adverse reactions of each bundle, and the fixed effects related to the number of years since the drug bundle was available in the US (1…12), the number of drugs contained in each bundle (1, 2 or 3), pharmaceutical form (oral solid, oral liquid, vials), years (1995…1999), and a fixed effect for controlling when the data also includes hospital sales. In column (2) we add a set of country fixed effects. In column (3), we add to this latter specification a set of country-year pair effects. of drug therapy because when including double and triple therapies in the regression, we might be introducing heterocedasticity of unknown form.

Results in table 9 and 10 do not differ much. As a larger number of drugs of the bundle are under a patent regime, expected prices increase. This result becomes more significant as we include country, year, and country-year pair fixed effects. The effect of the patent regime variable grows as we go from single therapy to triple therapy.

Results in column 3 of table 9 allow us to compare expected prices. Panel A in

Table 11 shows that drug bundles containing at least one original drug in a patent regime are on average priced 70% higher than drug bundles containing only local copies marketed in no patent regimes.

Table 11 also shows that drug bundles containing at least one generics marketed in a patent regime (probably when the drug goes off patent in country-drugs previously under patent regime) are on average priced 22% higher then drug bundles containing only local copies. Moreover, drug bundles containing at least one original drug are priced 16% higher than local copies even when it is introduced in no-patent regimes. Panels B, C and D show the estimates of these price differences using the results in Table 10.

These results show that patients have access to cheaper drug bundles, and to a wider range of prices in no-patent regimes i.e., drug bundles containing only cheaper local or generic non-licensed brands rather than bundles containing more expensive big pharma brands. That is the expected result from the competition among different firms offering drugs that contain the same chemical entities on the market. For instance, we observe that in a no-patent regime such as the corresponding to the country-drug pair Argentina-Zidovudine eight firms compete offering close substitute brands.

Results also show that competition of just one generic firm at the end of the patent term also induces a reduction of prices. For instance, a generic Canadian firm term of the original developer ended. These results suggest that drug prices flatten out only gradually as new competitors come in. Furthermore, these price differentials also show that big pharma licensed brands are priced differently across patent regimes.

Tables 9 also show that the prices across countries are closely related to each country per capita income and income inequality. More importantly, the positive link between prices and mean income is persistent across patent regimes, and gets stronger for drug bundles containing more drugs. The relationship between prices and income inequality is ambiguous, probably because the functional form is too restrictive to handle the non-linearity relationship between prices and income distribution. However, these results are consistent with the assumption that price relatives depend not only on the degree of differentiation among products on the market, but also on the income distribution of each country, the characteristics of the outside good, and the marginal and fixed costs of production.

Finally, tables 9 and 10 show that launch prices are very high, and that drug bundle prices adjust down strongly. Figure one uses the results of a regression using country-year fixed effects and allowing for different time trends for single, double and triple therapies to predict the evolution of mean prices across the life cycle of the products. The figure shows that drug firms use the so called "skimming strategy" when pricing new drug in the case of original drugs in patent-regimes. This is the pricing strategy named "skimming strategy." More should be studied to understand the fundamentals of this strategy, particularly, whether and why drug firms are discriminating prices intertemporally and across countries. Our main finding is that the average daily dose price of any ARV "cocktail therapy" differs significantly between the treatment group of country-drug pairs in which pharmaceutical firms may apply for product patent rights, and the comparison group of country-drug pairs in which pharmaceutical firms may not apply for product patent rights. We find that on average cocktail therapies are more expensive when they include big pharma licensed brand products.

Additionally, we find evidence of a persistent relationship between drug prices and per capita income under patent and no-patent regimes, and a strong decreasing trend in prices. Sales-weighted average ARV prices were quite close to US average prices in all countries by 1995. By mid-2000, these prices had dropped significantly in current $US.

However, ARV prices were still well above US prices in PPP terms in all poor countries throughout the period under study. Prices in $US decreased due to two factors: (1) the introduction of cheaper local and generic brands in local markets; and (2) firms' difficulties in increasing nominal prices when local currencies depreciated. Patients do not, however, benefit from decreasing prices in nominal local currency terms, but benefit from decreasing prices in real terms because of firms' inability to increase nominal prices to offset the negative impact of local inflation. Drug firms appear to use the "skimming strategy" when pricing new drugs in patent regimes. [START_REF] Balasubramaniam | Background Information on Fourteen FDA Approved HIV/AIDS Drugs[END_REF]FDA (2000). 1995 1996 1997 1998 1999 2000 1995 1996 1997 1998 [START_REF] Who | ATC classification index with Daily Defined Doses 2000[END_REF], Red [START_REF] Book | Drug Topics Red Book[END_REF][START_REF] Book | Drug Topics Red Book[END_REF]Book ( , 1997[START_REF] Book | Drug Topics Red Book[END_REF][START_REF] Book | Drug Topics Red Book[END_REF]Book ( , 2000)), PDR-Generics (1997) and [START_REF] Pdr-Cg | Physicians Desk Reference Companion Guide[END_REF], 1999, 2000). From the estimates including country-year fixed effects. Price differences with respect to the nopatent and unlicensed brand (local firm) are statistically significant at 1% (**), 5% (*), or 10% (+).

F

  In any regression equation, the restriction that 1

  allowed up to 1 st January 2005, and the least-developed countries up to 1 st January 2006 (and now up to 2016 under the Doha Ministerial Declaration on the TRIPS Agreement and Public Health) so as to formally change patent laws to introduce pharmaceutical product patent protection. Furthermore, those lesserdeveloped countries may obtain further extensions from WTO on a case-by-case basis.

  Central America as a non-licensed brand after the exclusivity

  Fig 1. Daily Price Across Time Since US Launch Date Bands: 95% prediction conf. interval Some in Patent & Some Original Brand

  10of the new ARV drugs with the older ones ("cocktail therapy") "has helped change AIDS in the last three years from being an automatic death sentence to what is now often a chronic, but manageable, disease." As Table1shows, 14 different products containing one molecule, and one product combining two molecules (i.e. a total of 15 products), were available in the US by June 2000.IMS, the leading collector of data on drug sales world-wide, provided us with annual sales data for the 15 ARV's in 21 different countries and two country groupings, viz.French West Africa and Central America, between January 1995 and June 2000.

	F o F o
	r r
	P e P e
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	r r
	R e R e
	v i v i
	e w e w
	, the combination

3 IMS data consist of unsubsidized annual wholesale sales and revenue estimates corresponding to each particular drug presentation sold at retail outlets between 1995 and mid-2000, except in 4 cases. IMS reports total aggregated retail and hospital sales (R&H) in South Africa, Thailand, the Philippines, and Indonesia. IMS data refer only to unsubsidized sales. They do not include subsidized distribution of drugs to patients (particularly important in Brazil and Thailand), nor do they include any donations of drugs. 4 Using 3 IMS provided us with aggregated sales data for two supranational entities: French West Africa, comprising aggregate sales in Benin, Cameroon, Democratic Republic of Congo, Ivory Coast, Gabon, Guinea and Senegal; and, Central America, including Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, and Panama. All economic indicators for those two supranational entities are population weighted averages of the national indicators. The data set includes annual data referring to the calendar years from 1995 to 1999, and also to the year from July 1999 to June 2000.

4 For each drug presentation, IMS reports data by year, country, molecule, firm, brand name, pharmaceutical form, strength, and pack size. Sales revenues obtained from each package or presentation at the wholesale level are reported in current $US. Physical sales are reported in standard units (number of tablets, vials or teaspoons). IMS did not provide us with sales of the active ingredient in milligrams, or in daily doses.

8

  An invention is considered to be new if it does not form part of the state of the art. The "state of the art" is generally defined, as everything made available to the public by means of a written or oral description, by use, or in any other way, before the date of filing of the patent application.

	F o
	r
	P e
	e
	r
	R e
	v i
	e w
	Under WTO rules, incorporating existing WIPO (World Intellectual Property Organization)
	conventions, for purposes of determining novelty, patent applicants may claim the priority of an
	earlier application made during the period of 12 months from the date of filing. It is theoretically
	13

possible to have a patent applicant not to claim priority from the date of an earlier filing and to claim that products for which patent applications were filed elsewhere from say, mid-1993 are

  EMR's) affect four of the 14 ARV molecules. For the following four molecules, patent applications could have been filed after January 1 st 1995 in all WTO countries apart from the country where the priority date was set: Nelfinavir (key patent priority date -February 2 nd 1994); Delavirdine (key patent priority date -February 22 nd

	marketing rights (
	F o
	r
	P e
	e
	r
	R e
	v i
	e w
	14

obtained each ARV key priority date from the US Patent and Trademark Office online database (http://www.uspto.gov). We thank Mike Palmedo from the Consumer Project on Technology for explaining to us how this data was gathered.

Table 7

 7

	shows that relative price indices in local currency (column 1) decreased in
	all countries except Thailand, Malaysia, and Argentina. Patients benefited from lower
	wholesale list price for each particular drug and pharmaceutical form pair between 1995 and
	2000.

Table 1 .

 1 ARV's approved in the US by June 2000 (from older to newer in the US)

	o
	r
	P e
	e
	r
	R e
	v i
	e w

Table 2

 2

	. -Number of drugs for which the innovator
	could obtain patent or EMR rights
		1995 1996 1997 1998 1999 2000
	US	6	9	12	13	15	15
	CENTRAL AMERICA	6	9	12	13	15 15
	FRENCH WEST AFRICA	6	9	12	13	15 15
	MALAYSIA	6	9	12	13	15 15
	SOUTH AFRICA R&H	6	9	12	13	15 15
	PHILIPPINES R&H	6	9	12	14	15 15
	MEXICO	5	8	11	12	13 13
	THAILAND R&H	4	7	10	11	13 13
	INDONESIA R&H	2	5	8	10	11 11
	CHILE	1	4	6	7	8	8
	BRAZIL	0	1

Table 4 .

 4 -Wholesale minimum price for an annual ARV therapy in 1999 (tablets only)

		Single	Double	Triple Therapy	Per Capita Income
		Therapy	Therapy	(HAART)	(PPP$)
	US	2533	5114	6770	31910
	ARGENTINA	1567	3845	6632	11324
	CHILE	1513	4825	6853	8370
	SOUTH AFRICA R&H	835	2023	4366	8318
	URUGUAY	1533	7941	..	8280
	MALAYSIA	1247	3153	..	7963
	MEXICO	1195	2589	8149	7719
	BRAZIL	757	1982	3025	6317
	COLOMBIA	1431	2862	7824	5709
	THAILAND R&H	593	2029	4345	5599
	VENEZUELA	1869	4432	6301	5268
	DOMINICAN REPUBLIC	1290	4161	..	4653
	PERU	1476	4061	..	4387
	PHILIPPINES R&H	1915	4770	6685	3815
	CENTRAL AMERICA	1181	3019	..	3545
	EQUADOR	954	2692	..	2605
	INDONESIA R&H	1299	3408	..	2439
	INDIA	634	1319	7728	2149
	FRENCH WEST AFRICA	1411	3363	6624	1092
	HAART: Highly Active ARV Therapy
	Source: Author's computations on the price of single double and triple clinically tested drug
	bundles that can be combined using the drugs available in each country in 1999 based on IM.
	Per capita incomes from World Bank (2000).

Table 5 .

 5 -Sales weighted local to US price ratios At current $US At purchasing power parity

Table 6 .

 6 -Drivers of Pricing Dynamics in $US (annual cumulative change between 1995 and 1999) 1 Or between the first year when any of the ARV's is locally available and 1999. ..: not available. Source: Author's calculations based on IMS,[START_REF] Who | ATC classification index with Daily Defined Doses 2000[END_REF],[START_REF] Pdr-Cg | Physicians Desk Reference Companion Guide[END_REF],[START_REF] Imf | International Finance Statistics, CD-Rom edition, Produced by Joint IMF and World Bank CD[END_REF].

		Mean price in	Entry &	ARV price	Local
		$US	Mix	index in $US	Currency
	INDIA	-30.50% -22.36%	-8.14%	-8.16%
	SOUTH AFRICA R&H	-16.45%	-4.81%	-11.65% -12.22%
	URUGUAY	-15.29% -13.76%	-1.53%	-7.65%
	PERU	-15.23%	-3.60%	-11.63% -11.26%
	FRENCH WEST AFRICA	-14.81% -11.10%	-3.72% -26.22%
	MALAYSIA	-14.72% -11.96%	-2.75%	-9.90%
	BRAZIL	-10.87%	-0.01%	-10.86% -15.67%
	PHILIPPINES R&H	-8.36%	2.67%	-11.03%	-9.94%
	COLOMBIA	-7.91%	-8.29%	0.38% -15.09%
	CHILE	-7.13%	0.79%	-7.92%	-9.22%
	THAILAND R&H	-6.96%	-2.26%	-4.70%	-9.90%
	CENTRAL AMERICA	-6.86%	10.67%	-17.53%	-6.14%
	ECUADOR	-5.78%	-5.78%	..	..
	INDONESIA R&H	-2.08%	4.46%	-6.54% -33.19%
	ARGENTINA	2.08%	0.93%	1.14%	0.01%
	MEXICO	3.45%	-0.51%	3.96%	-9.48%
	VENEZUELA	27.33%	28.57%	-1.24% -10.18%
	1

Table 8 .

 8 -Summary Statistics Observations: 2,459 single, double and triple drug bundles in 23 countries or regions that combine 14 different drugs between 1995 and 1999

	Variable	Mean	Std. Dev.	Min	Max
	Price per minimum daily dose	20.66	20.59	0.13	141.97
	Drugs in Patent Regimes (%)	0.37	0.39	0.00	1.00
	Original Brands (%)	0.71	0.34	0.00	1.00
	Original drugs in patent regimes (%)	0.32	0.38	0.00	1.00
	Country Mean Income	8684.47	3023.32 1092.00 11844.00
	Country Income Inequality (Gini, %)	49.28	5.61	36.45	64.33
	Including an oral liquid	0.37	0.48	0.00	1.00
	Including a vial	0.04	0.19	0.00	1.00
	2 drugs	0.58	0.49	0.00	1.00
	3 drugs	0.18	0.39	0.00	1.00
	Number of Doses a Day	4.47	1.87	1.00	12.00
	Efficacy	0.21	0.24	-0.14	0.90
	Adverse Reactions	0.09	0.05	0.00	0.29
	Retail and Hospital sales	0.21	0.41	0.00	1.00
	First year on the US market	0.04	0.19	0.00	1.00
	Second year on the US market	0.24	0.43	0.00	1.00
	Third year on the US market	0.17	0.38	0.00	1.00
	Fourth year on the US market	0.14	0.34	0.00	1.00
	Fifth year on the US market	0.14	0.35	0.00	1.00
	Sixth year on the US market	0.03	0.17	0.00	1.00
	Seventh year on the US market	0.04	0.19	0.00	1.00
	Eighth year on the US market	0.06	0.23	0.00	1.00
	Ninth year on the US market	0.08	0.27	0.00	1.00
	Tenth year on the US market	0.01	0.12	0.00	1.00
	Eleventh year on the US market	0.02	0.13	0.00	1.00
	Twelfth year on the US market	0.02	0.14	0.00	1.00

Table 9

 9

	. -Drug Bundle Pricing Regressions -OLS
	Coefficient (Standard Errors)
	Single, Double and Triple Therapy (n=2,459)
		Log of Price per Daily Dose of a Drug Bundle
		(1)	(2)		(3)
	Local copies in no-patent regime	----	----		----
	Original drug in patent regime	.34 (.17) +	.56 (.07)	**	.53 (.08) **
	Original drug in no-patent regime	.12 (.12)	.16 (.12)		.15 (.12) +
	Generics after patent expiration	.09 (.16)	.06 (.07)		.19 (.07) **
	Log of Country Mean Income	.23 (.08) **	.23 (.51)		.32 (.06) **
	Country Income Inequality (Gini, %)	-.15 (.48)	5.96 (1.56)	**
	Number of Doses per Day	.17 (.04) **	.13 (.04)	**	.13 (.04) **
	Efficacy	.42 (.10) **	.20 (.15)		.17 (.14)
	Adverse Reactions	-1.63 (.63) *	-.84 (.23)	**	-.73 (.23) **
	Years in the US market:
	First	----	----		----
	Second	-.12 (.04) **	-.19 (.07)	*	-.15 (.26)
	Third	-.14 (.07) *	-.18 (.08)	*	-.13 (.08)
	Fourth	-.31 (.09) **	-.27 (.07)	**	-.10 (.11)
	Fifth	-.33 (.09) **	-.27 (.09)	**	-.21 (.07) **
	Sixth	-.18 (.10) +	-.19 (.12)		-.22 (.05) **
	Seventh	-.25 (.10) **	-.22 (.11)	+	-.13 (.08) +
	Eighth	-.30 (.14) +	-.28 (.11)	**	-.16 (.08) *
	Ninth	-.36 (.12) **	-.36 (.10)	**	-.25 (.09) **
	Tenth	.17 (.10)	.06 (.11)		-.32 (.08) **
	Eleventh	.11 (.08)	.03 (.09)		.16 (.08) +
	Twelfth	.05 (.07)	.05 (.08)		.13 (.06) *
	Fixed Effects:
	Pharmaceutical Form	Yes	Yes		Yes
	Number of Drugs	Yes	Yes		Yes
	Year	Yes	Yes
	Country		Yes
	Country-Year				Yes
	R 2	.64	.71		.73
	Hospital sales fixed effects included.
	Robust Standard Errors Clustered on Country.
	Significant at 1% (**), 5% (*), or 10% (+).

Table 11 .

 11 -Mean Price Differences by Patent Regime and Licensing Status A. -All sample: Single, Double and Triple Therapy (n=2,459)

	Local copies in no-patent regime

Colombia, Ecuador and Venezuela introduced product patents in 1996; Brazil in 1997; Argentina in 1999; Guinea, Guatemala, and Morocco in 2000. We focus on product patents (exclusivity related to therapeutically active ingredient) rather than process patents (exclusivity related to the method of obtaining such an active ingredient). Process patents, like other type of patents on therapeutic uses, pharmaceutical forms, and so on, are important but accessory ways of protecting the main and broader exclusivity right of the innovator, that protecting the therapeutic active ingredient from being copied and sold.

When product patents are not available as of 1 st January1995, WTO members have to provide a system whereby drug patent applications can be filed (often referred to as a "mailbox" system).

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UKSubmitted Manuscript

I gratefully acknowledge the comments from Albert Saiz and many participants at Harvard, NBER, Carlos III, and Vigo Seminars. I was a post-doctoral fellow at Harvard Economics Department while working on this paper. I thank my host and Ariel Pakes kindly supervision. I gratefully acknowledge funding from the CID, and unrestricted educational grants from Fundacion Ramon Areces (Madrid, Spain) and The Merck Foundation, the philanthropic arm of Merck & Co. Inc., Whitehouse Station (New Jersey, USA).

 [START_REF] Balasubramaniam | Background Information on Fourteen FDA Approved HIV/AIDS Drugs[END_REF]and [START_REF] Qian | Do Additional National Patents Law Stimulate Domestic Innovation in a Global Patenting Environment. A Cross-country Analysis of Pharmaceutical Patent Protection: 1978-1999[END_REF]. 4 (4)


Saziye Gazioglu

J E Lit

: Nos

F32 E60

Financial Markets < , F36 -Financial Aspects of Economic Integration < , F40 -General < , F41 -Open

Keywords: F32 -Current Account Adjustment|Short-Term Capital Movements <, G15 -International financial crisis, stock market, international debt, real exchange rate, Istanbul stock stock market, international debt, real exchange rate, financial crisis, Istanbul stock Market (ISM) F34, F36, F40, G15

. In this paper we explore the effects of capital inflows and outflows to real exchange rates and the real stock market returns, before, and after the financial crisis.

We investigate the relationship between real exchange rate, real stock returns and capital flows. We decompose the foreign flows into real assets and liabilities, in order to investigate the possible long-term effect of inflows and outflows.

Empirical investigation shows that the long-term relationship only appears between the real exchange rates and the real bank liabilities owned by the foreigners. The first half of the subperiod, which is the pre-crisis period, is dominated by capital inflows and outflows. These affect the real exchange rate whereas the second sub-period, which is the post crisis period, is dominated by unstable the capital inflow and outflows causing the decline of real stock market returns and the depreciation of the currency.

The post financial crisis period demonstrates a long-lasting effect on lowering the stock market returns. This confirms the theoretical findings of this paper.

Introduction

A financial crisis in one part of the world is very likely to be felt by other financial markets via the domino effect. This transmission of foreign exogenous shocks to other economies, through financial markets, became a serious concern to emerging financial markets (EFMs).

The electronic revolution assisted the high speed of capital flows, an important cause of economic volatility. Kaminsky and Schumukler (1999), Collines and Gavron (2004) referred to common factors affecting all countries as 'contagion'. Turkey, as a newly emerging financial market, was influenced by international financial turbulence e.g. the negative influence created by the Russian crisis. However, the Asian crisis of 1997 had negligible 'contagion' effect on Turkey. None of these models relate short-term capital flows to stock market structure and price index during the crisis period.

These theories apply to some countries but not others. Turkey was advised by the IMF to introduce a 'Managed Float' from January 2000 until June 2001, despite having introduced currency convertibility in 1989. This was similar to other emerging markets, e.g. Mexico, Thailand and Korea. However, foreign exchange attacks in November 2000 and February 2001 prevented this plan. There has been empirical investigation into whether the crisis was caused by financial panic or by the weakness of economic fundamentals. Johnson et. al. (2000) created a vulnerability matrix using sets of criteria including macro indicators. [START_REF] Berg | Anticipating Balance of Payments Crisis-The role of early warning Systems[END_REF] specifically looked at macroeconomic vulnerability. Their analyses were based on flow variables, with no consideration of stock variables such as wealth effects and foreign indebtedness. [START_REF] Calvo | Capital Flows: Emerging Issues' Panel: 3 Are we in a Global Economic Crisis[END_REF] points out that the financial markets of the emerging market countries are administered by central banks, which are very sensitive to bankruptcies in the domestic financial institutions. This creates a moral hazard problem due to the expectation of bail out. The markets become vulnerable to speculative attacks due to rumour of devaluation.

The moral hazard model partly explains the Asian and Turkish crises in February 2001. [START_REF] Calvo | Capital flows and Capital market Crisis: The Simple Economic of Sudden Stop[END_REF] pointed out that the Chilean, Mexican and Venezuelan crises brought about Both [START_REF] Kaminsky | On Crisis, contagion, and confusion[END_REF], and Forbes and Rigoban (2000) examined the effects of crisis on the stock market. Changes in stock prices have been given special attention since the stock market of a country absorbs all available information related to national and global markets. Furthermore, changes in stock prices provide a frequent form of data to investigate the market.

None of these models relate short-term capital flows to stock market structure and stock price index during the crisis period. [START_REF] Calvo | Capital flows and Capital market Crisis: The Simple Economic of Sudden Stop[END_REF] argued that the large negative swings in capital inflows -Sudden Stops-are harmful. This implies that large current account deficits are to be feared, irrespective of how they are financed, and particularly if they are financed by shortterm debt. The capital inflow slowdown or reversal of capital flows could push the country into insolvency or drastically lower the productivity of its existing capital stock. This might lead to large unexpected swings in relative prices and costly bankruptcy battles.

Our paper focuses on both short-term capital flows and the stock market as sources of international financial crisis. Both personal and corporate foreign investors are free to invest in the Istanbul Stock Market (ISM), as all kinds of financial controls have been abolished. In this analysis we also need to include the domestic banking and financial sectors in order to investigate the investment opportunities for short-term foreign capital. In addition to these considerations, we argue that the degree of volatility or magnitude of the financial crisis is closely related to the proportion of foreign investors in the domestic stock market. Furthermore, capital inflows and reversal outflows have asymmetric effects on real exchange rate and stock market prices.

Section 2 describes the financial structure of Turkey, including the Turkish Banking sector.

In Section 3 we outline the model and its policy. Section 4 presents our empirical results. We conclude in Section 5 and offer suggestions for further research. Kaminsky and Reinhart (1999) investigated the link between banking and balance of payment problems. They found that there are causality between the currency crisis and Banking crisis 1 in both directions. Hahm (2004) suggested that interest and exchange rate exposure of the banking sector was measured with their sensitivity of stock market return. It has been found that the banking sector had high foreign exposure before the financial crisis.

Development of the

Since 1980 there has been significant expansion and development in the Turkish banking sector.

Together with technological improvements and diversification of services;

employment in the sector and the number of banks has been growing substantially.

Theoretical Model

The model is based on [START_REF] Gazioglu | An Emerging Market, Volatility of Real Exchange Rate : The Turkish Case[END_REF][START_REF] Gazioglu | A Non-Linear Currency Substitution Model of Hysterisis in Debt and Consumption[END_REF][START_REF] Gazioglu | Capital Flows to an Emerging Market: Turkish Case study[END_REF], with incorporates a 'profit maximising firm' and a representative domestic consumer that maximises time separable utility functions [START_REF] Obstfeld | Exchange Rate Dynamics Redux[END_REF] and [START_REF] Ramsey | A Mathematical Theory of Saving[END_REF]). Following [START_REF] Obstfeld | Exchange Rate Dynamics Redux[END_REF], the stock market constraint is as follows:

V X X V X D d d d d d d & & + (1)
Equation ( 1) states3 that a change in the proportion ( X d ) of the value of domestic firms4 owned by domestic individuals (in other words, shares: the value of domestic claims to the 2 Sumerbank was also taken over by foreign Secondly, the balance of payments constraint:

[ ] & ( & ) H T H E E R f = + + + 1 1 (2)
The aggregate constraint of the stock market, net accumulation of foreign assets, and & H , can only be accumulated by running a trade surplus, where is the foreign owned share of domestic dividends minus the domestic owned share of foreign dividends, and

[ ] H E E R f ( & ) 1 1 + +
is any capital gain from holding foreign money in terms of foreign goods (a simple representation can be found in Gazioglu (1996), where external balance is also equal

to internal balance.) ( ) ( ) ( ) f f f f f f d d d d d R E E H V D V V X V D V V X I A Y H E X + + + + + + + = 1 1 &
Therefore the right hand side of the constraint represents net domestic 'income' (factor earnings, net interest from asset holdings, return on shares) minus 'consumption' (private and investment), reflected by the 'saving' (net wealth accumulation) on the left hand side. This combines the stock market constraint, following [START_REF] Obstfeld | Exchange Rate Dynamics Redux[END_REF] and Net

International Debt following [START_REF] Gazioglu | An Emerging Market, Volatility of Real Exchange Rate : The Turkish Case[END_REF][START_REF] Gazioglu | A Non-Linear Currency Substitution Model of Hysterisis in Debt and Consumption[END_REF][START_REF] Gazioglu | Capital Flows to an Emerging Market: Turkish Case study[END_REF]. If the percentage of shares under foreign ownership in the domestic stock market increases, debt in the domestic economy increases, which is analogous to 'selling the family silver'. It would appear that the domestic economy is very sensitive to the level of foreign investment in the stock market. How severely a foreign shock affects the domestic market will be directly related to the percentage of shares under foreign ownership. The greater the share of foreign investors in the domestic stock market, the greater the vulnerability of the domestic economy is. The Asian crisis can be considered to fall into this category. Whether other emerging financial markets become The dynamics of the whole system may be summarised 5 in matrix form by

[ ] k V H E V H E V V V H H H E E E V H E k k k V H E V H E V H E + = & & (5))
where the signs of the elements of the matrix are, from the discussion above: 0

> E E & , 0 < H E & , 0 > V E & and 0 < E E & ; 0 < E H & , & H H < 0 , & H V < 0 and 0 > k H & ; 0 < E V & , & V H > 0 , & V V < 0 and 0 > k V &
. Now the dynamic model is complete, empirical analysis may follow in the next section. The model has two stable equilibria and one unstable equilibrium. [START_REF] Gazioglu | An Emerging Market, Volatility of Real Exchange Rate : The Turkish Case[END_REF][START_REF] Gazioglu | A Non-Linear Currency Substitution Model of Hysterisis in Debt and Consumption[END_REF][START_REF] Gazioglu | Capital Flows to an Emerging Market: Turkish Case study[END_REF] show that having a high percentage of shares under foreign ownership has an asymmetrical effect on exchange rate and on international indebtedness during inflows and outflows. The unstable equilibrium represents the "Ponzi game" position when a country has to borrow in order to make its debt repayments.

This model also highlights the asymmetric effect of capital inflow and outflow on exchange rate and international indebtedness. The phenomenon of hysteresis is due to the non-linearity of international debt dynamics. Initially international assets accumulate with capital inflow; later occurrences of capital outflow will push the equilibrium to unstable equilibrium in international debt and create a "Debt Trap"6 .

We use the dynamic variables of real exchange rate, real stock market return index and foreign capital flows in our empirical work. [START_REF] Ghosh | from Turbulence To Tranquillity: Is Restructuring The Means For Malaysia[END_REF]. [START_REF] Hui | Financial Volatility and Stock Prices: The Malaysian Experience Before and During the Asian Currency Crisis[END_REF] used only the real exchange rate and real stock market index to find out the direction of causality. Theoretically, ordering of the variables does not mater in the co-integration method we use. So, causality test is not necessary. in this work. Disaggregating the net foreign capital into inflows and outflows gives us the opportunity to assess the asymmetric effect of the flow 5 Although portfolio shares dynamically adjust to flow disequilibrium, they are, of course, constant in long term equilibrium, hence 0 = X & . Furthermore, following [START_REF] Obstfeld | Foundations of International Macroeconomics[END_REF], to concentrate on the dynamics of domestic net international debt, real exchange rate and the stock market, we assume & V f = 0 .

F

Estimation of the Structural Model:

We Using unrestricted VAR estimation methods implies that ordering the variables do not matter in testing the co-integration. We imposed the following restrictions to the simultaneous estimations of the three variables:

0 = E H & , 0 = H H & , 0 = V H & and 0 = k H & ; 0 = E V & , 0 = H V & , 0 = V V & and 0 = k V & . The Hence we estimate only 0 < H E & , 0 > V E & .
We compare the stability conditions of the theoretical model, which are signs of the coefficients, and the signs of the estimated coefficients of the empirical model. This helps to assess the stability of the system.

Empirical Results:

The the real exchange rate was near constant and the nominal exchange rate was managed pegged.

After the crisis there is real currency depreciation during 2001, but after 2002 the real exchange rate reaches its pre-crisis level. This implies that the crisis was followed by the declining real stock market return and exchange rate depreciation and appreciation after 2002.

Our hypothesis is that foreign short-term capital inflows (real foreign assets) are invested in the stock market, increasing the foreign stock market returns and appreciates or reduces the depreciation of the foreign currency (Model 1). A shock to capital outflow (real foreign asset liabilities) has an asymmetric effect of reducing the real stock market return (Model 2).

Structured VAR Approach

The estimated co-integrating equations may or may not confirm the signs of the expected stability conditions. Our aim is to do the co-integration test and compare the signs of the estimated coefficients and the signs of the stability conditions of the theoretical model.

The existence of unstable equilibrium in the theoretical model corresponds to the sub-period of series. Furthermore, the normalised co-integrating coefficients are greater than unity 8 , hence the possibility of instability in the theoretical model.

Stationarity and Co-integration Tests:

In this section the stationarity of all variables is tested. The data was divided into sub-periods Level variables are used in the co-integration estimations 9 . However, with a structural dummy both model 1 (LREXC, LRV1, LRFASS) and model 2 (REXC, LRV1, LRFLIAB) co-integrates as discussed in the next section.

Co-integrating analysis:

In this section we investigate the co-integrating analysis as a long-run relationship(s) between real exchange rate (LREXC), real stock return(LRV1), capital inflows (real foreign assets (LRFASS) and capital outflows (LRLIAB) over the period 1994m01-2003m10. We used the Johansen multivariate technique in our co-integration analyses (Johanson (1988) and; Pesaran and Smith (1998) and others). We first performed a co-integration analysis with constant term entering un-restrictively but with a trend term restricted to lie in the co-integration space.

We found that the trend term is insignificant in the co-integration relations. We also included 9 The first difference variables had not co-integrated. The Eigen value tests of model 1 suggests that the real exchange rate, real stock values, real foreign assets (capital inflows) are co-integrating as reported in Table 5 with the lag length of VAR=1 11 . A one percent increase of LRFASS reduces the LREXC by 1.26 percent, implying appreciation of the currency, or depreciating less than it would have otherwise.

Model 2, which includes real exchange rate, real stock values and real foreign liabilities (capital outflow). also co-integrates as reported in Table 6. A one percent increase of foreign outflows (LRLIAB) increases the foreign exchange by 11.047 percent, implying depreciation of the domestic currency. During the outflow, the real stock markets return (LRV1) is worth more (2.5%) than during inflow (DLRFASS) case. This suggests that capital inflows increase the stock market returns as it enters into the country (with the expected increase), (0.17) and it moves out when the return is high (2.50) and is expected to fall, due to disliked government policies. The asymmetric effects of capital inflows and outflows confirm the theoretical discussion on hysteresis [START_REF] Gazioglu | An Emerging Market, Volatility of Real Exchange Rate : The Turkish Case[END_REF][START_REF] Gazioglu | A Non-Linear Currency Substitution Model of Hysterisis in Debt and Consumption[END_REF][START_REF] Gazioglu | Capital Flows to an Emerging Market: Turkish Case study[END_REF]. Though the coefficients of LRV1 in both model 1,2 are smaller than unity, the coefficients of LRFASS and LRFLQAB are greater than unity. This indicates a greater influence of capital inflows on real exchange rates than the stock market returns. The estimated coefficients also have the theoretically expected signs. Therefore, our empirical estimates confirm our theoretical model.

Impulse responds analysis:

It has been pointed out that impulse respond analysis is important in co-integrating systems (Pesaran andPesaran (1997), Lutkpohl andReimers (1992)). In figures 1and 2 we give the time plots of logarithms of real exchange rate, real stock market returns and capital inflows (model 1) and capital outflows (model 2) respectively. Here, we provide the general impulse 10 For each model 1 and 2 we found non-normal residuals. The residual of each equation in which 2001M2 is an outlying observation. Therefore, we included impulse dummy for D0201(Hendry and Juselius ( 2001)). After we included D0201 in VAR(1) un-restrictively, equations perform normal distribution and showed no autocorrelation and heteroscrdicity (Pesaran and Pesaran (1997) 11 The lag lenth of VAR for each system is determined by Schwarz Bayesian Criterion. 14 response (IR) functions12 to examine the dynamic effects; that is medium and short-run effect of a shock on a given variable on all the other variables in the system.

We assess the dynamic effect of a rise in capital inflows and outflows instabilities on Figure 3 has the impulse responses of the Model 2. Figure 3a and 3c shows their similarities. One SE shock in the equation LREXC increases (LRV1) and decreases (-LRFLIAB). Appreciations increase the capital outflow (figure 3a).

One SE shock in the equation LRFLIAB (outflow) will decrease (as -LRFLIAB) the value of LRV113 . Outflows (-LRFLIAB) reduce the (LRV1) from (-0.03 to -0.10) in Figure 3c.

Conclusions and Policy Implication:

The paper investigates the contribution of capital inflows and outflows to financial crises. A theoretical model based on the behaviour of representative utility maximising agents in various intertemporal stock-flow constraints is introduced. The model suggests that an exogenous shock increases capital inflows, leading to real exchange rate appreciation (a fall) and a fall in stock market prices in the long term.

Our empirical results confirm the asymmetric impact of capital inflows (foreign liabilities)

and capital outflows (foreign assets). Real assets have a greater impact than real liabilities on the real exchange rates. The asymmetric impact of inflows and outflows of capital on international indebtedness creates the "Debt Trap".

Policy implication of asymmetry effect of capital flow is a controversial issue.

  to large bailout packages. The structure of the banking sector played an important role in the Turkish Financial crisis(Metin-Ozcan (2004).

  Figure 2 shows the number of banks during 1995-2005. In 2005 the number of banks reduced to 48. A substantial restructuring has taken place after 2000.

Figure 2 :1

 2 Figure 2: Number of Banks

Figure 3 Figure 4

 34 Figure3shows the number of branches of bank for the period 1995-2005. The number of branches increased from about 6000 in 1995 to 8000 in 2000. This number had fallen back to 6000 in 2005. It is clearly observed that there has been overexpansion of the banking sector, before the 2001 currency crisis. The South American experience was to be repeated in Turkey. The currency crisis was coupled with banking crisis to constitute the overall financial crisis.

Figure 4 :

 4 Figure 4: Branches (Sube ) and employment (Personel): 2002/4-2005/4

  of domestic firms, V d ), V X d d& , is equal to the domestic proportion of the change in the stock market valuation of these shares,

  depend on the percentage of shares under foreign ownership in the domestic market.

  adopted a 'Structural VAR' model as it overcomes the identification problem of VAR estimation (Garratt A, K Lee, M.H.[START_REF] Garratt | A Structural Co-integrating VAR Approach to Macroeconometric Modelling" mimiograph[END_REF]). The 'Structural VAR' is our econometric model. A full macro-model was introduced behind the econometric analysis.The macro dynamic model has long-term properties for the stability of the equilibrium.Our theoretical framework suggests that several variables can identify structural macro variables. A theoretical model is important as it provides a mechanism for determining how the dynamic variables are expected to behave, both in the short and long term. Previous empirical work has only investigated the relationship between exchange rate and stock market prices and the importance of international debt has been ignored. The basis of our theoretical model is to test whether the dynamic model driven by the theory confirms the dynamic behaviour of the Turkish data. The following procedure has been applied for simplifying the estimation: a) We solve the 3 by 3 dynamic system and obtain the stability conditions. The detail of its proof can be found in[START_REF] Gazioglu | Stock Market, Financial Crisis and Capital Flows in an Emerging Market: The Turkish Case[END_REF] 7 Teak (2003) suggested increasing daily traded volume of in stocks staring 01/03/1986 ending 06/12/98 (in US $) in Brazil.

  data used in this work are from the Turkish central Bank for the period 1994:02 to 2003:10. Graph 1 plots the logarithm of real values of the variables, real exchange rate, (RLEXC), real stock returns (RLV1), real foreign assets (RLFASS), and real foreign liabilities (RLFLIAB). It is noticeable that the real stock market return started to fall after the introduction of an exchange rate based stabilization programme in December 1999, supported by the Breton Wood Institution in order to tackle inflation and public debt. Appendix 1 provides the details on the definitions and the sources of data. This indicted that the confidence of investors to the Currency Board had fallen. Fall of real stock returns seems to create some of the conditions for the forthcoming crisis in November 2000 and February 2001. We also observe that the gap between the foreign liabilities and assets disappears from the beginning of 2001, as a result of the financial crisis. Between the dates 1994:1-2001:02

,

  using Romers' Narrative 'VAR Approach'. The whole period is 1994:02 to 2002:09, and the sub-periods are 1994:02 to 2000:11 and 2000:12 to 2003:10. We also put dummy to 2000M11 and 2001M2 to test structural brake for estimates of the entire period.

a

  Dummy 10 (D0201) for the crisis date, February 2001 to account for structural break. This entered restrictively to co-integrating space.

  variables in the system by examining the generalized IRs to a positive unit (one standard error (SE) in capital in and outflows respectively; in model 1 and 2. In figure 2, as expected, short and medium run responses are negative on LRV1. A positive LREXCH shock (depreciation) leads to reduction of the value, LRV1 (Figure 2, a). One SE shock in the equation to LRV1, will increase the capital inflows, LRFASS (Figure 2.b). A generalised impulse response to one shock for LRFASS ( an increase of capital flows) increases the value of LRV1 as inflows are invested in the stock market (Figure 2.c).

Figure2

  Figure2 (Model 1) a)

Turkish Banking Sector.

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  direction. During the empirical investigation, the focus is on unstable Eigen values, which are greater than unity. This paper argues that the percentage of shares under foreign ownership in any domestic stock market is a key indicator of vulnerability in the domestic stock market. The theoretical macro-model includes the dynamics of this important indicator. It is worth noting that liberal foreign exchange policies have applied since 1989, so foreign investors are free to buy and sell in the Istanbul Stock Market (ISM) as much as they wish.Foreign portfolio investment in the Istanbul Stock Market (ISM or IMKB) increased from $33,654 million in 1996 to $83,069 million in 1999 and to $ 111,157 million in 2000. Since 1996 foreign investment levels have been growing very rapidly 7 . Furthermore, the percentage of shares owned by foreign investors is around 50 percent of the total market, which is quite high.

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Table 1

 1

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reports the summary of the Augmented Dicky Fuller (ADF) test of the real stock market returns (RLV1), Real Foreign Assets (RLFASS) and Real Foreign Liabilities (RLFLIAB). For the period 1994:2-2003:10 the real exchange rate, the capital inflows and outflows are I (0) and stock market return is I (1) as reported in Table

2

.

8

implying outside of the unit circle.

Table 2 : Testing for Unit Roots (ADF test): Logarithm of real exchange rates (RLEXC), real stock return (RLV1), real foreign liabilities (RLFLIAB), real foreign assets (RLFASS), : 1994:M01-2003:10 (Akaike information criteria (AEC),

 2

	Level	Variables RLEXC	with intercept -3.349(3) 8 **	With intercept and trend -3.143(3)(**)
	First difference DRLEXC	-7.882(4)***	-7.868(1)(***)
	Level	RLV1	-1.916(1)	-1.439(1)
	First difference DRLV1	-8.633(0)***	-8.707(0)*** l
	Level	RLFLIAB	-4.774(0)(***)	-10.496(0)
	First difference DRLFLIAB	-5.400(4)(***)	-5.525(4)(***)
	Level	RLFASS	-3.326(2)(**)	-8.868(0)(***)
	First difference	DRLFASS	-7.967(3)(***)	-7.949(3)(***)

Notes to Table

1

: Critical values (with intercept) for 1%(***), 5%(**), 10%(*) are 3.496, -2.890 and -2.582 respectively. Critical values (with intercept and trend) for 1% (***), 5%(**), 10%(*) are -4.051,-3.455, and -3.153 respectively.

691 7,837 6,908 6,106 5,966 6,106 6,247 EMPLOYMENT IN BANKING SECTOR 1995 1999 2000 2001 2002 2003 2004 2005 A. Commercial banks 138,694 168,558 164,845 132,274 118,329 118,607 122,630 127,857 1. State banks

  short-term foreign capital by restricting their re-entry if was taken out in short period in the previous period. Whether this can be applied in Turkey is the political will of the government.

	Table 1 Figure: 1
	Banks Operating in Turkey	1995 1999 2000 2001 2002	2003	2004	2005
	A. Commercial banks	55	62	61	46	40	36	35	34
	1. State banks	5	4	4	3	3	3	3	3
	2. Private banks	32	31	28	22	20	18	18	17
	3. Banks under TMSF 4. Foreign Banks Real Foreign Liability B. Investment & Development Banks Real Foreign Assets	18 13	8 19 19	11 18 18	6 15 15	2 15 14	2 13 14	1 13 13	1 13 13
	1. State banks	3	3	3	3
	2. Private banks 3. Foreign banks real exchange rate	7 3	13 3	12 3	9 3
	F o r P e e r R e v i e w F o r P e e r R e v i e w F o r P e e r R e v i e w F o r P e e r R e v i e w 68 81 79 61 Number of Branches in Banking Sector TOTAL 1995 1999 2000 2001 A. Commercial banks 6,219 7,660 7,807 6,889 6,087 5,949 6,088 6,228 54 50 48 47 2002 2003 2004 2005 2. Private banks 3,240 3,960 3,783 3,529 3,659 3,594 3,729 3,799 3. Banks under TMSF 714 1,073 408 203 175 1 B. Investment & Development Banks 25 31 30 19 19 17 18 19 1. State banks 9 12 11 4 4 2. Private banks 12 16 16 12 3. Foreign banks 4 3 3 3 3 TOTAL 2. Private banks 63,010 92,366 70,954 64,380 66,869 70,614 76,880 78,806 3. Banks under TMSF 19,895 6391 5886 4,518 403 395 4. Foreign Banks 2,985 4,185 3,805 5,395 5,416 5,481 5,880 10,610 i e w 6,244 7,72,699 72,007 70,191 56,108 40,158 37,994 39,467 38,046 v e R 12 r e 4. Foreign Banks 104 121 117 233 206 209 209 393 e 1 P 1. State banks 2,875 2,865 2,834 2,725 2,019 1,971 2,149 2,035 F o r Real stock returns
	B. Investment & Development Banks	6,099 5,430 5,556 5,221 4,942 4,642 4,533 4,401
	1. State banks	5,245 4,336 4,456 4,322 4,174
	2. Private banks	716 1,027 1,021	822	691
	3. Foreign banks TOTAL	138 144,793 173,988 170,401 137,495 123,271 123,249 127,163 132,258 67 79 77 77 Malaysia was
	the only country that refused to borrow from the IMF and introduced capital control on the

Table 5

 5 Co-integrating Results of Model 1: Influence of foreign Asset Inflows (LRFASS)

			10
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			6
			4
			2
			0
			94	95	96	97	98	99	00	01	02
						RLEXC		RLFLIAB
						RLV1		RLFASS
	____________________________________________________________________________
	Test of co-integrating rank
			LREXC		LRV1			LRFASS
	Eigenvalues	0.385		0.065			0.029
	Null hypotheses	r=0		r<=1			r<=2
	Max statistic	50.48		6.99			3.09
	95% critical value	21.12		14.88		12.98
	Trace statistic	60.57		10.08			3.09
	95% critical value	31.54		17.86			8.07
	Co-integration results (r=1)
	(Beta)	14	1		0.17 (0.128)		-1.260 (0.592) 15
	14 Standardized Eigen vector

Table 6

 6 Co-integrating Results of Model 1: Influence of foreign Asset Inflows (LRFLIAB)

	____________________________________________________________________________
	Test of co-integrating rank
		LREXC	LRV1	( -LRFLIAB)
	Eigenvalues	0.337	0.066	0.337
	Null hypotheses	r=0	r<=1	r<=2
	Max statistic	42.39	7.14	3.53
	95% critical value	21.12	14.88	8.07
	Trace statistic	53.05	10.08	3.53
	95% critical value	31.54	17.86	8.07
	Co-integration results (r=1)
	(Beta) (Alfa) 19 17	1 0.0198	2.50 (0.128) -0.49	-11.047 18 (0.592) 0.219

Page 20 of 23 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

	Submitted Manuscript
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See Obstfeld and Rogoff (1996, p.100) for a discrete time formulation.

We assume that there are a large number of homogeneous perfectly competitive domestic firms producing goods for both domestic and foreign consumption. It should be noted that trade in this model takes place because of comparative advantage rather than country differences in intertemporal consumption/savings behaviour.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

& & &(3)

& & & & & & & & & & & &

For detailed analysis see[START_REF] Gazioglu | Stock Market, Financial Crisis and Capital Flows in an Emerging Market: The Turkish Case[END_REF].

We used generalized IR function, because it does not depend on the ordering of the variables within the system. This is in contrast with the orthogonalized IR function which has solution depending on the order of the variables.

Note that I multiplied the negative values of liabilities with (-) to be able to take their logarithms.