rafmacalaba/datause-encoder-data huggingface dataset:
# **Reference**

Arnold. J, Mathenge. J, Dihel. N, and Strychacz. (May 2011) The Role of Clearing and Forwarding Agents in Reforming the EAC Logistics Sector, Africa Trade Policy Notes # 17, World Bank.

European Logistics Association (ELA). ELAQF Qualification Standards 2014.). Accessed at http://www.elalog.eu/elaqf-qualification-standards FIATA. FIATA Model Rules for Freight forwarding Services. Accessed at <u>http://fiata.com/uploads/media/Model_Rules_07.pdf</u> Gleave. S, Frisoni. R, Dionori. F, Vollath. C, Tyszka. K, Casullo. L, Routaboul.C, Jarzemskis. A, Tanczos. K (2013) Development and Implementation of EU Road Cabotage. European Union.

Governemnt of Brazil (1998) Lei 9611/98 | Lei no 9.611, de 19 de fevereiro de 1998, Transporte Multimodal de Cargas.

Government of Germany (1998) HGB Commercial Code: Freight business; Forwarding business; Warehousing business, §453HGB Government of Germany (1998) HGB Commercial Code: Freight business; Forwarding business; Warehousing business, §458HGB Government of Nepal (2006) The Act Made to Provide for Multimodal Transportation of Goods. Nepal Gazette, Volume 56.

Government of Netherland. Dutch Civil Code Book 8 – Transport Law and means of Transport. Accessed at <u>http://www.dutchcivillaw.com/legislation/indexb88.htm</u> Government of South Africa (2009) The National Land Transport Act. Government Gazette, No. 32110. April 8, 2009.

Government of the USA. Code of Federal Regulations No. 46 - #515 regulations affecting ocean shipping in foreign commerce. Accessed at <u>http://www.ecfr.gov/cgi-bin/text-idx?rgn=div5&node=46:9.0.1.2.10</u> International Air Transport Association. IATA Cargo Agency conference Resolutions Manual - Resolutions 803; Cargo agency rules recommended practice 1630 Cargo security.

Japan External Trade Organization (JETRO). Accessed at http://www.jetro.go.jp/world/japan/qa/import_04/04A010132.

Kunaka C, Mustra M., and Saez. S (2013a) Trade Dimensions of Logistics Services A Proposal for Trade Agreements, Policy Research Working Paper 6332. World Bank.

Kunaka C, Tanase V, Latrille P, and Krausz P (2013b) Quantitative Analysis of Road Transport Agreements. World Bank.

Ministry of Commerce of the People’s Republic of China (2004) Detailed rules for implementation of regulations of China on the administration of international freight forwarding industry No.82, Chapter 1, Article 2, 2004.

Ministry of Transport in Japan. Maritime Transportation Law 1949 Ministry of Transport in Japan. Freight Forwarding Business Laws 1989 35
# **Table 6: Costs of Applying for the RSE**

||All W|orkers<br>Cost in|Ambrym<br>Vatu|/Tanna|
|---|---|---|---|---|
|_Item_|_Mean_|_Median_|_Mean_|_Median_|
|Local transport (from home village to nearest port or airfield)|2783|1500|5418|3000|
|<br>Boat fare to Port Vila|1737|0|5527|5000|
|Airfare to Port Vila|1309|0|4165|1000|
|Passport|5357|5000|6136|7000|
|Police Clearance|1229|1000|1545|1000|
|Medical check-up|3100|3000|2573|3000|
|<br>Visa|16666|15000|16300|18000|
|Airfare to New Zealand|49563|64000|52000|55000|
|Other|259|0|273|0|
|**Total RSE Costs**|**82003**|**89900**|**93938**|**97500**|
|**Total RSE Costs Excluding Half Airfare**|**57221**|**57900**|**67938**|**69000**|
|Note: 1USD = 91.80 Vatu (April 2008).|||||

## **Table 7: RSE Applicant reasons given for Applying**

|Reason|Very Important<br>Percent saying that in|Important or Very Important<br>their decision the reason was:|
|---|---|---|
|To earn money for school fees|91|98|
|To earn money to build a better house in Vanuatu|89|99|
|To earn money to start a business in Vanuatu|80|98|
|I could work abroad but my children could stay in school at home|65|84|
|Improve my English|64|96|
|Gain working skills|61|98|
|To earn money to pay for social responsibilities in my village|53|89|
|I don't want to leave Vanuatu permanently, but this gives me some time<br>in both Vanuatu and NZ|46|69|
|To earn higher wages|43|84|
|My family asked me to go|43|81|
|Other|41|51|
|Experience a different lifestyle|36|70|
|My community or church asked me to go|31|40|
|I have a health problem and wanted to consult a NZ doctor|24|41|
|As a way of getting links to NZ to give a path to permanent residence|23|57|
|I could still keep my job in Vanuatu|22|63|
|Less cultural restrictions on what I can and cannot do|21|56|
|Havingfamilymembers alreadyin New Zealand|12|28|

## **Table 8: RSE Non-applicants reasons given for not applying**

|Reason|Very Important<br>Percent saying that in|Important or Very Important<br>their decision the reason was:|
|---|---|---|
|I do not know what the requirements are|55|78|
|I am happy living in my home village|46|63|
|I can not afford the costs of applying for the RSE|44|65|
|I do not want to move away without my family|35|60|
|I have an on-going business I can not leave for 7 months|30|43|
|The seasonal work in New Zealand is too hard for me|29|42|
|I do not think the chances of getting selected are very high|29|55|
|I think I can earn more money staying in Vanuatu|27|47|
|I do not feel my English ability is good enough|24|51|
|Social obligations in my village that do not allow me to leave|21|43|
|I do not want to go temporarily, and will wait until a permanent option|16|39|
|I alreadyhavepermission to work in NZ through another category|10|34|

- 38 -
<!-- Start of picture text --> Sectoral shares as percentage of GDP<br>80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%ee<br>0%<br>1970 1975 1980 1985 1990 1995 2000 2005 2010<br>GDP share agriculture —@=—GDP share manufacturing —*—GDP share services<br><!-- End of picture text --> <!-- Start of picture text --> Electricity access and generation capacity<br>80% 0.08<br>70% 0.07<br>60% 0.06<br>50% 0.05<br>40% 0.04<br>30% 0.03<br>20% 0.02<br>10% 0.01<br>0% 0<br>1970 1975 1980 1985 1990 1995 2000 2005 2010<br>eelectricity_access —@simple generation capacity (sgc)<br><!-- End of picture text -->
# **Annex 3: Further analysis of unit value differentials in developing country imports**

Table A3.1: Unit Value Simulation: Percentages of agricultural imports from individual countries with unit values at least 15 percent less than the unit value of imports from all sources – by importing <u>country</u>

|Importer|Imports from all<br>countries*<br>($ '000)|% Imports<br>coming<br>from DCs|% of Impo<br>value 15<br>more below<br>imports fro<br>from<br>Industrial<br>countries|rts with unit<br>percent or<br>unit value of<br>m all sources<br>from<br>developing<br>countries|
|---|---|---|---|---|
|Brazil|1,504,351|99|47.8|4.4|
|China|9,608,243|59|0.2|2.4|
|India|1,309,936|56|0.1|0.3|
|Indonesia|2,275,094|26|2.5|24.0|
|Malaysia|2,489,827|66|1.2|14.0|
|Mexico|4,589,471|5|3.2|7.8|
|Allabove countries|21,776,922|48|1.8|5.7|

* Imports of the countries in the sample: Brazil, China, India, Indonesia, Malaysia and Mexico

For the six developing countries whose import data were examined, the unintended consequence this exercise has brought forward would be authorization for restrictions on almost 6 percent of agricultural imports from developing countries, on about 2 percent of agricultural imports from developed countries – at least one restriction on more than half of the tariff lines.

68
grants them permanent residence. Thus, graduate training of foreign students may have long-lasting impacts on innovation capacities.

On a negative note, Borjas (2002) speculates that foreign students in the United States benefit the economy to the tune of $1 billion a year, but this gain is more than offset by the costs of taxpayer-financed grants and subsidies at public universities. In another paper Borjas (2004) finds a strong negative correlation between the enrollment of native men in U.S. graduate programs and the enrollment of foreign students. Institutions which experienced the largest increase in foreign enrollment were also institutions that experienced the steepest fall in the enrollment of native males.

For our purposes the interesting aspect of this claim is that Borjas seems to suggest that domestic and foreign graduate students are highly substitutable and display similar characteristics. In fact, other information indicates that this assertion is questionable. Although data on the quality of domestic graduate student applicants compared to their international counterparts are not readily available, results from TIMMS and other international tests indicate that the native U.S. student pool for engineering and science programs is likely to be limited due to lower math and science achievement.<sup>13</sup> This suggests that student populations are not readily substitutable and that university technical training programs may have increased their demand for foreign students.

As a result it is not surprising that a recent study indicates that there has been a sharp drop in the proportion of PhDs in science and engineering awarded to U.S.-born males between the early 1970s and 2000 (Freeman et al., 2004). In 1966 these students accounted for 71 percent of science and engineering PhD graduates, while six percent 7
forecasts of economic growth.<sup>23</sup> We take the difference in annualized growth rates of survey means and national accounts as our measure of the gap (or ‘error’ in the growth forecast literature). A negative value indicates that survey means grew slower than the national accounts measures.

The distribution of the gap is presented in Figure 4, showing a large variation in differences in growth rates between the two sources. To check for systematic differences, we estimate these differences in growth rates by subgroups of countries, time periods and spell lengths, for each type of survey (income and consumption).<sup>24</sup> The main results are presented in Table 2. Overall, growth rates in surveys are, on average, lower than in national accounts. However, the difference is not statistically significant for the overall sample which pools both income and consumption for all countries and time periods. For the subsamples of lower middleincome countries, as well as the 1990s, survey means grow more than one percentage point slower than HFCE in national accounts on average, a difference that is statistically different from 0 at the 95%-level. The gap in growth rates is also larger when looking only at longer, comparable spells for each country (with four-to-six-year spells).

The gaps in growth rates between surveys and national accounts are larger and more robust when looking at the subsamples consisting of only survey consumption means. Overall, we find that the average growth rate for consumption means in surveys in our full sample is 0.53 percentage points less than HFCE and 0.43 percentage points less than GDP growth. The difference is particularly large in middle-income countries. For income means, the differences in growth rates with respect to national accounts are smaller and mostly statistically insignificant. Notably, we observe a positive gap for high-income countries, where survey means grow faster than HFCE. This is despite the North America region (where both the US and Canada are also considered high income) showing income surveys grow more slowly than HFCE. Additional

> 23 The growth forecasting literature is concerned with assessing the precision and bias of forecasts in predicting actual growth rates. Similarly, we are interested in understanding the precision and bias of national accounts growth rates in predicting actual survey growth rates. For an example of the growth forecasting literature, see Artis and Marcellino (2001).

> 24 We estimate subgroup averages by running a simple regression of the growth rate gap on a constant, analogous the preceding assessment of differences in levels. The estimation approach readily allows application of various weights and robust clustered standard errors.

18
average. Because of the preliminary results suggesting that low-income countries are different, we also report averages for the richest and poorest tercile of countries (each tercile has 39 observations). To ease the reading, we set _ADRt_ to 1 in for the period 1970-1974. It can be seen that the ADR ratio is quite stable fluctuating around the value of 1 for the whole sample, even though the small decline could be taken to suggest that barriers to trade have been increasing in relative terms, leading countries to shift trading patterns towards closer partners.

As suggested by the systematically higher estimates of the elasticity of trade to distance for developing countries in the meta-analysis, we also report separately the potential and actual distance of trade for the poorest third (39 countries) in the 124 in the sample with all countries in the sample.<sup>16</sup> By selecting all trade of the poorest countries rather than trade with only the remaining (85) countries, we are addressing directly the issue of whether their trade is becoming more regionalized, regardless of the partners.

Figure 3 shows a higher potential trade for the poorest countries, reflecting larger dispersion in incomes for this group. More interesting is the large fall in the average distance of trade for this group implying that poor countries have increased trade relatively more with nearby than with distant partners. For this group the average distance of imports fell by more than 15% from 7200 kms in 1970-1974 to 6000 in 2005-2006.

c.i.f), are taken from UN-COMTRADE (via WITS), divided by the US deflator. We use import data as it is well-recognized that they are more accurately reported by the customs authorities. For developing country, we use mirror estimates, i.e. export data reported by partner countries. GDP and population are taken from the World’s Bank World Development Indicators 2008. Distance measure is from the Centre d’Etudes et de Prospectives et d’Informations Internationales (CEPII). The simple distances are calculated following the great circle formula, which uses latitudes and longitudes of the most important city (in terms of population).

16 The list of countries is given in appendix A1, table A1.1. The computation of terciles was carried out by splitting the country in three groups on the 1970-2006 average. We then checked if the classification would have changed if we had used beginning or end-ofperiod GDP figures. Concerning for instance the poorest tercile, compared to the list reported in table A1.1, China and Sri Lanka would have been included in this group at the beginning of the period (instead of Haiti and Zimbabwe) while Ivory Cost Only would have been included in this group (instead of Pakistan) at the end. Note that the poorest tercile matches perfectly the low-income country group as defined by the World Bank in 2006.

15
same decade to all countries in the same geographical region as the actual borrower. I then construct my instrument by aggregating these predicted loan-level disbursements on previously-approved loans to the country-year level. By construction, aggregate predicted disbursements reflect only the combination of country-specific loan approval decisions from previous years with typical disbursement profiles, based on averages taken across many loans to many countries. My identifying assumption is that these loan approval decisions do not anticipate future shocks to growth, and under this assumption, changes in aggregate predicted disbursements will be uncorrelated with the error term in Equation (1). I can therefore use changes in predicted disbursements as an instrument for changes in total government spending when estimating the government spending multiplier based on Equation (1).

# **3.  Data**

I work with loan-level data drawn from the Debtor Reporting System (DRS) database maintained by the World Bank. The DRS database contains information on loan commitments, terms, disbursements, and repayments, for all external loans contracted or guaranteed by the government in the borrowing country, beginning in 1970. The DRS data are, in principle, comprehensive in their coverage of all individual external public and publicly-guaranteed debt obligations, from all creditors, and for all countries that borrow from the World Bank. This is because annual reporting to DRS is mandatory for World Bank clients: a country must be in good standing with respect to these reporting requirements in order for new projects for that country to be considered by the Board of Directors of the World Bank.<sup>6</sup> Countries are required to report basic information on the amount, terms and purpose of new commitments, drawings and repayments on existing loans, and details of loan restructurings when applicable.<sup>7</sup> Loan-level transactions reported in DRS are confidential. However, the aggregation of this loan-level data to the country-year level provides the basis for country-level debt data published by the World Bank in its annual Global Development Finance publication.<sup>8</sup>

> 6 See the World Bank's Operational Manual, BP14.10, available at: http://web.worldbank.org/WBSITE/EXTERNAL/PROJECTS/EXTPOLICIES/EXTOPMANUAL/0,,contentMDK:20064540~ menuPK:4564187~pagePK:64709096~piPK:64709108~theSitePK:502184,00.html

> 7  Details on reporting requirements can be found in the World Bank Debtor Reporting System Manual, available at <u>http://siteresources.worldbank.org/DATASTATISTICS/Resources/drs_manual.doc.  These loan-level transactions</u> are typically provided as paper records or in spreadsheet format, and staff in the Development Data Group of the World Bank enter it manually into DRS.

> 8 To my knowledge, the loan-level data in DRS has been used only in a handful of previous scholarly papers, all of which are focused in one way or another on alternative characterizations of the financial value of concessional loans (Chang, Fernandez-Arias, and Serven (2002), Dikhanov (2004), and Dias, Richmond, and Wright (2011)).

10
# **1 Introduction**

The global financial crisis and the critical issue of sovereign debt solvency faced by many advanced economies, including the European Union members, have recently raised the question of how countries can pursue macroeconomic stabilization policies while maintaining the growth of public debt on a sustainable path. A mechanical solution that has been proposed in the literature is that countries pursue fiscal stimulus measures during a downturn in the economic cycle (bust) followed by fiscal contraction (and debt reduction) in a period of recovery in the economic cycle (boom). In other words, countries are encouraged to pursue a counter-cyclical fiscal policy. The convenience and usefulness of counter-cyclical policy for debt management and macroeconomic stability has been analyzed, theoretically, by Christiano et al. (2011) and Nakata (2011). They used a stochastic model with sticky prices and found that the optimal policy in such a context is counter-cyclical. However, the literature confirms that fiscal policy is not always counter-cyclical: it remains procyclical<sup>1</sup> in many countries, particularly in developing countries (Gavin and Perotti (1997), Tornell and Lane (1999), Alesina and Tabellini (2005), Talvi and Vegh (2005), Diallo (2009), Thornton (2008), Frankel et al. (2013), Bova et al. (2014)). An interesting question that emerges in this framework is how to reduce the pro-cyclicality of fiscal policy and promote more counter-cyclical policies, pledge of fiscal discipline.

A large body of the literature addressing the cyclicality of fiscal policy relates it to exchange rate regimes and aims at finding which type of regime (rather fixed exchange rate regimes or more flexible ones) has disciplining effects on fiscal policy. In the recent period, especially in the context of the global financial crisis and of the European sovereign debt crisis (Bergman et al. (2016)), fiscal rules, instruments used to guide fiscal actions, have started to gain more and more interest. Fiscal rules are defined as “agreements designed to mitigate the deficit bias and promote fiscal discipline by constraining budgetary aggregates through numerical limits” (Schaechter et al. (2012)). In 2015, 89 countries had adopted national and supra-national rules to govern their fiscal policy (IMF Fiscal

> 1Fiscal policy is considered pro-cyclical when government chooses to increase public spending and reduce taxes during an economic boom, but to reduce spending and increase taxes during an economic recession.

2
**Portfolio Flows to Emerging Markets Complementary or Compefitive?** * * {~~~~~ **.**

# INTRODUCTION

The 1990s have seen a rapid increase in portfolio investment flows to emerging markets. According to the World Bank's _World Debt Tables, 1993-94,_ gross portfolio investment flows to developing counties increased from $7.5 billion in 1989 to about $36.8 billion in 1992. The level of gross portfolio flows to these markets during 1993 is estimated to be $55.8 billion'. Recent estimates of gross portfolio investment flows in developing counties (See Gooptu (1993) and World Bank (1993a)) show that, although the magnitudes involved are large, these flows have been going to a few developing countries. For example, between 1989 and 1992, five countries accounted for over twothirds of the cumulative total gross portfolio investment flows to developing countries, namely, Argentina, Brazil, Mexico, South Korea and Turkey (See Ahmed and Gooptu (1993))2.

Previous studies on internationa **l** inkages between stock markets have focused prnmarily on those of the industial countres and have examined equitb retune rather than equity s. This is a result, until recently, of the non-availability of relevant data on portfolio flows over a long enough time period to allow for meaningful applications of econometric techniques. This paucity of portfolio flows data has been especially critical in the case of developing countries. Researchers have used a variety of methodologies to examine the intemational capital market linkages. For example, Hilliard (1979) and Levy and Samat (1990) have examined the contemporaneous and lagged correlatons in the rates of return across equity markets. Hilliard (1979) analyzed the effect of the OPEC Embargo (July 1973 to April 1974) on the behavior often equity market retum indices.

> **1 Source:** Wodd Bank, **_WorldDebt Tablis._** _1993-94._ Volumc 1. Table 1.5, p. 21.

> 2 **ThCS** estmats exclude **the uNew Moncy bonds hat** were **issued** in Brady-type debt and debt service (DDSR) padgca smce **tihy wcre** part of a concerted debt resuctiog operations and not truly voluntay private capitla fiom abmad.

3