rafmacalaba/datause-encoder-data huggingface dataset:
4 Chapl'er 2

# Overall Patterns and Trends

Frcm the 1950s until the mid-1960s, net FDI flows to devLloping _countries_ remained at relatively low leveis of $2 billion dollars or .ess a year. During this period there was substantial disinvestment--some voluntary, some forced--ir petroleum, mining, agriculture, and manufacturing. Beginning in the late 1960s annual net flows increased until they reached a peak in 1981 of $'5.3 billion, or about one-half percent of th-. developing countries' GDP. These increased flows of FDI were responses to the combination of ec nomic growth and industrialization in several large developing countries, more hospitable policies in some of the host countries, and more flexible policies on the part of investors.

The four-year period from 1983 through 1986 was marked by lower levels of annual flows of $10.2 billion to $11.2 billion (SDR9.7 billion to SDR9.2 billion). In the latter part of the decade, however, there was a modest reversal, with annual flows exceeding $15 billion (see table 2-1 for additional details on the absolute magnitudes of the flows).

Table 2-1: Absolute Magnitudes of FDI Flows to All Developing Countries, 1975-88

|Year|SDRs|Current U.S.<br>dollars|Constant U.S.<br>dollrars|
|---|---|---|---|
|1975|5.4|6.3|10.0|
|1976|4.1|4.8|7.6|
|1977|5.5|6.7|7.4|
|1978|6.1|8.0|9.9|
|1979|7.9|10.3|11.3|
|1980|8.6|10.9|10.9|
|1981|13.1|15.3|15.2|
|1982|12.3|13.6|13.8|
|1983|9.7|10.2|10.5|
|1984|10.3|10.1|10.7|
|1985|11.6|12.7|13.4|
|1986|9.2|11.2|10.0|
|1987|11.d|16.7|13.6|
|19888|1?.7|18.5|13.9|

a. Preliminary figures.

Source: IMF
Table 6. Exports, 2007 (%, unless otherwise noted)

|Sector|Supply-Use<br>Table|Authors'<br>balanced table|
|---|---|---|
|Agriculture, hunting, forestry and fishing|1|1|
|Mining and quarrying|8|10|
|Manufacturing|68|66|
|Electricity, gas and water supply|1|1|
|Construction|1|1|
|Wholesale and retail trade and repair|||
|Hotels and restaurants|1|1|
|Transport, storage and communications|10|10|
|Financial intermediation|1|2|
|Real estate and professional services|4|4|
|Public administration and defence|1|1|
|Education|2|2|
|Health and social work|1|1|
|Other social and personal services|0|1|
|Total|100|100|
|Total (million Dram)|518529|528637|
|Source: Authors' calculations based on data<br>of the Republic of Armenia|from National Sta|tistical Office|

Table 7. GDP by sub-sector, 2007

|Sector|Share(%)|
|---|---|
|**Transport, storage and communication**|**100.0**|
|Transport via railways|5.9|
|Other land transport|17.8|
|Transport via pipelines|3.6|
|Air transport|20.7|
|Supporting and auxiliary transport activities; activities of travel agencies|7.0|
|Post and courier activities|0.5|
|Telecommunications|44.4|
|Source: National Statistical Office of the Republic of Armenia||

Table 8. Assets by sub-sector, 2007

|Sector|Million AMD|Share(%)|
|---|---|---|
|**Financial intermediation**|**1372961**|**100.0**|
|Banking|1355959|98.8|
|Insurance|17002|1.2|
|Source: Central Bank of Armenia|||

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# **1. Introduction**

Japan in the 1950s through the 1990s and China since the late 1970s have followed similar— and similarly successful—strategies of promoting economic growth through rapid acquisition of advanced foreign technology and expansion of manufactured exports. While other Asian countries have done likewise, in some cases with exports growing as rapidly and for as long, Japan and China have presented special challenges to the GATT/WTO trading system because their shares of world exports have been so large and the associated bilateral trade imbalances with the United States so conspicuous. In both political and economic terms, these large imbalances seem to contradict the GATT/WTO principle of reciprocity, which involves a balance of market-access concessions across major players in the system.

During their respective periods of rapid export growth, Japan and China each accounted for a major share of total world exports. As of 2007, China’s share of world merchandise exports had soared to 8.9%, less than Germany’s 9.7% share but topping the U.S. share of 8.5% as well as Japan’s 5.2%, in each of the latter three cases from a much larger economy (WTO 2008b). Given the sharp drop in global import demand following the 2008 onset of the global financial crisis, China may not surpass Japan’s 1980s peak of around 10%. However, U.S. imports from China in 2008 ($337.8 billion) still exceeded their level in 2007 ($321.5 billion); the 2008 bilateral trade imbalance ($266.3 billion) also exceeded 2007’s record figure, although only by $10 billion.<sup>1</sup> Unlike the principles of most favored nation treatment (Article I) and national treatment (Article III), there is no “Article” of the GATT 1947 clearly identifying reciprocity as a GATT principle. However, the Articles that govern how countries _renegotiate_ concessions—in particular Articles XXVIII and XIX—do contain explicit language about reciprocity, and the GATT/WTO practice of reciprocity has typically resulted in a balance of market-opening concessions across the major players in the system.<sup>2</sup> But if a large economy such as Japan or China pursues an export-led growth strategy, the resulting increase in exports disturbs the initial “balance of concessions,” i.e., the reciprocal market-access outcome. The major trading partners that receive the increased exports may then seek ways to rebalance the bargain.

> 1 Morrison (2009), Table 1. These data refer to trade in goods only. Bilateral trade in both directions dropped sharply in early 2009 relative to the corresponding period in 2008.

> 2 Economic analyses such as Bagwell and Staiger (1999, 2002) treat the GATT/WTO as a self-enforcing agreement and focus on outcomes sustained through each member’s recognition that any country can seek to amend the initial bargain. From the perspective of sustainability and in light of the constraints that self-enforcement implies, the rule of reciprocity then feeds back to the conduct of initial negotiations.  See discussions in Bown (2002a, 2002b).

2
does the reforms independently of the others (independent policies), a second scenario in which all Western Balkan economies coordinate and implement the reforms at the same time (cross-economy coordination), and a third scenario in which economies also gain EU accession (cross-economy coordination + Full EU accession).<sup>3</sup> According to the Trading across Borders indicators, measured by The World Bank as part of the Doing Business Report, the time in hours to import goods and fulfill the border and documentary compliance is three hours (28%) higher in the six Western Balkan economies than in the high-income OECD countries. Therefore, on the counterfactual, we assume that an economy that implements the package of trade facilitation reforms mentioned above will be able to reduce by three hours the waiting time at the border. As shown by the model estimates, this intervention would be similar to lowering tariffs by around 2%. Figure 4 plots the aggregate effects of reducing border-crossing times. On average, welfare (real income) increases between 1.5%-3.0% in the Western Balkans in the long run. The most significant result is that if there is coordination among them, welfare increases by 8% more relative to the counterfactual in which each economy implements the reforms independently. Similarly, if economies are part of the EU, the gains are amplified by an additional 6%.

Thus, the simulation reveals three important key messages. Firstly, the impact of these trade facilitation reforms on welfare is positive and significant in all Western Balkan economies. Second, if economies adopt a coordinated approach to the trade facilitation reforms, the benefits are 8% larger. Additionally, if the Western Balkan economies become EU members, and assuming that this leads to a reduction in trade costs of 4% and of migration costs of 3% as suggested by Caliendo et al. (2021), the gains associated with the reduction of waiting times at the border are even greater, leading to welfare gains approximately 6% larger than relative to the reforms implemented under a non-membership scenario. Therefore, a clear policy implication is that collaboration and coordination of the reform agenda and a clear path to EU accession will maximize the welfare gains from these interventions.

> 3The results of the counterfactuals depend on the initial trade-linkages, and migration shares. As shown by Hulten (1978), the effect of a reduction in trade costs depends on the time-saving formula. In particular, it affects more the regions that have greater trade-linkages with the regions in which the trade cost decreaseS. In a series of recent papers, Baqaee and Farhi (2020) have looked at reallocation effects originating from distortions and second-order effects.

14
relative restrictiveness of individual measures can be inferred from the estimated coefficients of the policy variables, and the overall restrictiveness in the sector-mode can be calculated as a weighted average of these variables using these coefficients as weights. In this method, however, the estimated restrictiveness is conditional on the sample used and framed in terms of the chosen dependent variables.

Using the same subscripts as in section 3.1, let <sup>ˆ</sup> _jk_ denote the estimated coefficient on policy variable _k_ in sector _j_ , and let _xcjk_ denote the corresponding policy variable (typically a dummy variable taking the value of one if country _c_ applies a policy measure _k_ in sector _j_ ). At the sectoral level, the index is then computed as where the last term merely serves to normalize the index on the range from 0 to 100, making it comparable to the STRI of section 3.1.<sup>17</sup> Sectoral scores are aggregated across all sectors _j_  _J_ using the same weights _w j_ as before (see Annex 1, Table A.1): We illustrate this methodology in Section 6, using the results from a regression of global foreign direct investment flows across ten services sectors on policy barriers (and other controls). One difficulty is the paucity of internationally comparable data on outcomes, especially for natural candidates such as the price of the service (ideally controlling for quality differences). Even when we do have data on certain outcomes, such as the level of access to the service, the fact that our policy data is available only for a single point of time obliges us to conduct cross-country analysis and limits our ability to control for non-policy related differences across countries; see e.g. Borchert et al. (2012) who quantify econometrically the effect on market structure and access to services of policy measures in

> 17  Lubotsky and Wittenberg (2006) consider the case in which _k_ alternative proxy variables are available to measure the true effect of one latent, unobserved factor (e.g. policy restrictiveness), and devise a strategy for combining those proxies optimally so as to minimize attenuation bias.  This is different from a situation in which policy measures may be _additive_ in terms of restrictiveness, thus their framework does not directly apply to our context.

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## where

and k is the number of coefficients, q<sup>thebandwidth,andk(-)theKernel</sup> function, which is included to ensure<sup>thatQis a positivesemi-definite.The</sup> Bartlett Kernel is used in this study: The bandwidth is the Newey-West<sup>fixedbandwidth,whichis basedon</sup> the number of observations: which is equal to 3 here.

# 4 Empirical **Results**

We estimate equations (4) or<sup>(5)usingquarterlydataforfourcountries:</sup> Chile, Korea, the Philippines, and Turkey.<sup>8Theregressionresultsarepre-</sup> sented in Table 1. The rate of change of the real exchange<sup>rateisnot</sup> included in the regressions for Korea<sup>andPhilippinesbecauseitscoefficient</sup> had a wrong sign and was statistically<sup>insignificant.</sup> In order to decide on which price<sup>formation equationissuitableforeach</sup> country, we use an F test. Equation<sup>(4)isacceptedif onecannot rejectthe</sup> null hypothesis that _,31_ = **,**<sup>**3**</sup> **4** =<sup>_,35_=0 and that the coefficientsof the lagged</sup>

> 8See the Appendix for data sources and results of unit root tests.

> 9Because the data are quarterly, seasonal effects are captured by including seasonal dummies, in all regression equations.<sup>Thecoefficientsof thesevariablesarenotreported</sup> to save space.

13
insignificant and negative when customs and trade regulations are treated as endogenous (see Table 9).<sup>26</sup> _Internet Use_ . Previous work on low and middle-income countries in Europe and Asia has shown that manufacturing enterprises that are connected to the Internet export more than nonconnected enterprises.<sup>27</sup> A similar relationship appears to hold for the African enterprises in this study. Enterprises that used the Internet to communicate with customers and suppliers were considerably more likely to export than other enterprises were. The impact appears to be large. The point estimate of the coefficient suggests that the average enterprise would export about 11 percentage points more of its output if it had an Internet connection than if it did not. One concern about this variable is that it might be endogenous—the high cost of international communications in Africa might encourage exporters to get Internet connections rather than Internet connections making it easier for enterprises to export. The main results in this paper, however, are robust to the exclusion of this variable.

_Human capital of management_ . Human capital of management might affect whether enterprises export or not. For example, managers with university degrees might be more likely to have contacts abroad—especially if they obtained their degrees outside of their home countries—or might be more willing to overcome bureaucratic barriers to exporting.<sup>28</sup> To test whether this is the case, the regressions include a dummy variable indicating whether the manager has a university degree. In the regressions that treat trade and customs regulations as exogenous and that substitute average customs and trade regulations for enterprises in that sector (see Table 8), the coefficient is positive, but statistically insignificant in most specifications. When trade regulations are treated as endogenous, the coefficient remains positive, but increases

> 26 This is consistent with results for five African countries (including Tanzania and Kenya) presented in Söderbom and Teal (2003).

> 27 Lal (2004) shows that Indian firms that use e-business technologies more intensively were more likely to export than other firms were.  Using data from manufacturing enterprises in 27 low and middle income countries in Eastern Europe and Central Asia, Clarke (2001) shows that enterprises that were connected to the Internet exported more than other enterprises, even after controlling for self-selectivity bias.

> 28 Wood and Jordan (2000) argue that human capital in management—and in particular connections with potential international partners—might partially explains the difference between Uganda and Zimbabwe with respect to exporting.

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# **TRADE IN HEALTH SERVICES: WHAT’S IN IT FOR DEVELOPING COUNTRIES?**

Olivier Cattaneo World Bank

# **Key words**

WTO, Trade, Health services, GATS, Medical tourism, Medical travel, Movement of health personnel, Brain drain, Health shortages, Regulation of health services.

# **JEL classifications**

F13, F14, F15, F16, F22, F24, H51, I11, I18, J61.
_25_ _Table_ **_6:_** _Directions of shipments originating informer Yugoslav republics in 1987 and 2000 (in percent)_

||Exportsto<br>otherrepublics<br>in1987|External<br>exportsin<br>1987|Exportsto<br>formerrepublics<br>in2000|Other<br>exports<br>in2000|Exportsto<br>republics,Index<br>2000<br>1987=100|
|---|---|---|---|---|---|
|Bosnia and Herzegovina|55|45|34|66|62|
|Croatia|57|43|26|75|46|
|Macedonia(FYRMacedonia)|55|45|27|74|49|
|Montenegro|59|41||||
|Serbia(includingKosovoand<br>Vojvodina)|43|57||||
|Serbia|46|54|29|71|63|
|Kosovo|68|32||||
|Vojvodina|69|31||||
|Slovenia|48|52|14|86|29|
|Average|56|44|26|86|46|

_Source:_ for 1987 calculated from data in Uvalic (2000) and for 2000: Bosnia and Herzegovina from National Statistics and IMF; and for other countries-National Statistics.

Hinic (1994) and Uvalic (1993) draw the conclusion that, since the former Yugoslav republics traded with each other more than with the outside world, the level of economic interdependence among Yugoslav republics was "... greater than usually sustained on the basis of purely political arguments".<sup>33</sup> In other words, economic forces bound them very closely together independently of political ones. But considering that they were then part of the same state with the same currency and laws applying across the whole territory, intemal trade as measured by the share of exports to other republics in total exports amounting to 56 percent was rather small. In fact, the average share was well below the average for EU-members in the 1990s. Intra-EU exports accounted on average for 60 percent of total exports originating in EU member countries in 1990-95, although the EU was then neither a unitary state nor a fully integrated economic grouping.

Considering that exports to other former republics are no longer internal trade but foreign trade, much lower current levels of trade among former Yugoslav republics should come as no surprise. The emergence of borders was bound to increase dramatically the cost of trading. Consider that despite FTA the United States-Canada border imposes barriers to arbitrage equivalent to 2,700 kilometers (Engel and Rogers 1996). Inserting more than one border together with less efficient customs services increase these costs rather dramatically.

In addition, the violent dissolution of the former SFRY was bound to contribute to the suppression of trade going beyond the impact of a shift from intemal to extemal trade. Yet, excluding Slovenia, the share of exports to former Yugoslav republics fell by between 44 percent for Croatia and 37 percent for Serbia (including Vojvodina in 2000). In comparison with other cases of the dissolution of a state, this does not seem to be an unusual or steep contraction. In fact, the average share of this trade in 2000 amounting to 46 percent of its level in 1987 is not 33 As quoted in Uvalic (2000).
- Pauwelyn, J. (2008). New trade politics for the 21st century. _Journal of International Economic Law 11_ (3), 559–573.

- Pflueger, C. and P. Yared (2024). Global hegemony and exorbitant privilege. Technical report, National Bureau of Economic Research.

- Ruta, M. (2023). The rise of discriminatory regionalism. _Finance and Development_ .

- Staiger, R. W. (2022). _A World Trading System for the Twenty-First Century_ . Ohlin Lectures. Cambridge, MA: The MIT Press.

- Staiger, R. W. and A. O. Sykes (2011). International trade, national treatment, and domestic regulation. _The Journal of Legal Studies 40_ (1), 149–203.

- Staiger, R. W. and A. O. Sykes (2021). The economic structure of international trade-inservices agreements. _Journal of Political Economy 129_ (4), 1287–1317.

- Staiger, R. W. and G. Tabellini (1987). Discretionary trade policy and excessive protection. _The American Economic Review_ , 823–837.

- Thoenig, M. (2023). _Trade policy in the shadow of war: A quantitative toolkit for geoeconomics_ . Centre for Economic Policy Research.

- Wolff, A. W. (2023). Discarding a utopian vision for a world divided: The effect of geopolitical rivalry on the world trading system.

43
Diaz Alejandro, Carlos (1985). “Good-by Financial Repression, Hello Financial Crash,” _Journal of Development Economics,_ Vol. 19(1-2), (September) 1-24.

Eichengreen Barry, Andrew Rose, and Charles Wyplosz (1996) “Contagious Currency Crises: First Tests.” February, _Scandinavian Journal of Economics_ 98(4):463-84.

Fang, C., J. Schumacher, and Christoph Trebesch, (2021). Restructuring Sovereign Bonds: Holdouts, Haircuts and the Effectiveness of CACs” _IMF Economic Review_ , forthcoming.

Farah-Yacoub, Juan, Clemens Graf von Luckner, and Carmen M. Reinhart (2021). The Eternal External Debt Crisis: A Long View on Systemic, Regional, and Idiosyncratic Episodes,” World Bank mimeograph, forthcoming.

Frankel, Jeffrey, and Andrew Rose (1996), “Currency Crashes in Emerging Markets,” _Journal of International Economics,_ Vol. 41(3-4), November, 351-366.

Gelpern, Anna, Sebastian Horn, Scott Morris, Brad Parks, and Christoph Trebesch (2021), “How China Lends: A Rare Look into 100 Debt Contracts with Foreign Governments,” <mark>Peterson Institute for International Economics, Kiel Institute for the World Economy, Center for Global Development, and AidData at William & Mary.</mark> Ghosal, S., and Miller, M., (2017). “A new bargaining perspective on sovereign debt restructuring” VoxEU, April 17.

Gorton, Gary (2010) _Slapped by the Invisible Hand: The Panic of 2007_ (New York: Oxford University Press).

Graf Von Luckner, Clemens, Josefin Meyer, Carmen M. Reinhart, and Christoph Trebesch, (2021). “External Sovereign Debt restructurings: Delay and Replay,” Vox EU, March.

Haber, Stephen. (2005.) Mexico’s experiments with bank privatization and liberalization, 19912003 _, Journal of Banking and Finance_ 29: 2325–2353.

Horn, Sebastian, Carmen M. Reinhart, and Christoph Trebesch (2019). “China’s Overseas <u>Lending,”</u> NBER Working Paper 26050, July 2019.

International Monetary Fund (2020). _World Economic Outlook,_ October.

Kaminsky, Graciela, and Carmen M. Reinhart, (1999). “The Twin Crises: The Causes of Banking and Balance-of-Payments Problems,” _American Economic Review_ , Vol. 89 No. 3, June, 473-500.

<!-- Start of picture text --> .<br><!-- End of picture text --> Kaminsky, G. L., and Vega-García, P. (2016). Systemic and idiosyncratic sovereign debt crises. Journal of the European Economic Association, 14(1), 80-114.

Kindelberger, Charles (1978). _Manias, Panics, and Crashes: A History of Financial Crises_ (New York: Basic Books).

Laeven, Luc and Fabian Valencia (2013), “Systemic Banking Crises Database”, _IMF Economic Review_ , Vol. 61, June, 225-270.

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