rafmacalaba/datause-encoder-data huggingface dataset:
and Tobago, British Gas, and EOG Resources Trinidad) which accounted for 95% of production (IMF Article IV, 2012).

Increased international competition to attract FDI is one of the main features of the 30 years period analyzed. In the 1980s and 1990s, T&T was able to maintain its position as a top performer if terms of the amount of investments it was successful in attracting. In the 2000s, however, the number of countries showing very attractive profiles for FDI as well as the diversity of profitable sectors for FDI significantly increased. As a result, T&T faced increasing competition and no longer succeeded in being as successful in terms of FDI received. Thus, in the overall ranking based on available data, the country fell from the 10<sup>th</sup> position out of 145 countries in 1990 to the 83<sup>th</sup> position out of 175 countries by 2011.

<!-- Start of picture text --> Figure 4.2: Evolution of FDI in Trinidad and Tobago Figure 4.3: Net Foreign Direct Investment Inflows in<br>(as a share of GDP) T&T by country of Origin<br>20.0 (in Millions of US Dollars)<br>18.0<br>3000<br>16.0 Canada<br>14.0 2500 India<br>12.0 Germany<br>10.0 2000 United Kingdom<br>8.0 United States<br>1500<br>6.0<br>4.0 1000<br>2.0<br>0.0 500<br>-2.0<br>0<br>2005 2006 2007 2008 2009 2010<br>Source: IMF-WEO Source: ECLAC<br>1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011<br><!-- End of picture text --> As discussed above, FDI in T&T has been mostly concentrated first in the oil sector and at a later stage in the gas sector. This transition helped the economy to diversify its energy sector but not the non-energy sector (ECLAC, 2003). Later, the country succeeded in attracting new investments in other sectors but this contributed to only slightly expand the numbers of economic sectors in the economy. Not having a developed non-energy tradable sector will probably limit future growth due to lack of externalities in production, lack of forward and backward linkages, shortages of learning by doing and lack of entrepreneurship. Consequently, the country has taken measures to stimulate the non-resource based economy.

# _<u>4.2 Public Policies</u>_

Over the last decades, the Government of T&T took measures directly aimed at encouraging FDI inflows into the energy and non-energy sectors. FDI were also implicitly understood as a strategic means of diversification since it was believed FDI would also act as a source of revenue for investments in physical and human capital, which the country required in order to support the development of other sectors. The economy maintained strong tax incentives (bilateral investment agreements, double taxation treaties, and reciprocal regulatory agencies 16
# 2 Estimating AVEs of NTBs

To obtain AVEs of NTBs we fi rst estimate the quantity-impact of NTBs on imports and then we turn into the transformation of quantity effects into price effects.

## 2.1 Estimating the impact of NTBs on imports

The theoretical foundation for this kind of studies is the n-good n-factor general equilibrium model with log-linear utilities and log-linear constant returns to scale technologies (see Leamer, 1988 and Leamer, 1990). One of the speci fi cations commonly used (e.g., Leamer, 1990, Harrigan, 1993, Tre fl er, 1993, Lee and Swagel, 1997 and Wang, 2001) and adopted in this study is the following: where mn,c is import value of good n in country c;<sup>5</sup> αn are product dummies that capture any good speci fi c effect; Cc<sup>kare k variables that provide country characteristics; more precisely as in Leamer’s</sup> (1990) comparative advantage approach we used relative factor endowments (agricultural land over GDP, capital over GDP and labor over GDP), as well as GDP to capture economic size. We also introduced two gravity type variables: a dummy for islands and a measure of the average distance to the world of each countries (i.e., the import-weighted distance to each trading partner); α<sup>k</sup> c<sup>are</sup> parameters in front of the variables that capture country characteristics; Coren,cs is a dummy variable indicating the presence of a core NTB; logDSn,c is the log of agricultural domestic support, which is continuous and measured in dollars (for a description of NTB data, see subsection 3.1.1); β<sup>Core</sup> n,c is the parameter that captures the impact that a core NTB imposed on good n in country c has on imports of good n in country c; similarly β<sup>DS</sup> n,c<sup>istheparameterthatcapturestheimpact</sup> that agricultural domestic support granted to good n in country c has on imports of good n in country c. tn,c is the ad-valorem tariff on good n in country c; εn,c is the import demand elasticity; and fi nally μn,c is an i.i.d. error term.

This model allows for both tariffs and NTBs to deter trade with effects that vary by importing

> 5 Note that (1) is only de fi ned for strictly positive values of mc,n. If mc,n = 0, the log(mc,n) is not de fi ned. To avoid sample bias we added 1 to all mc,n values (which are measured in thousand of dollars).

5
**Table 2:** Aggregate effects from closing gender employment gaps while increasing the share of skilled women in the working-age population in 10 ppts. Changes relative to the baseline (baseline scenario = 1).

|Country|_s_|_L_|_k_|_y_|_wU_|_wS_|Output<br>per<br>person.<br>Short<br>run.|Output<br>per<br>person.<br>Long run.|Output<br>per<br>person.<br>Change<br>in _L_<br>alone.|
|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|**YEM**|1.38|1.88|1.083|1.083|1.070|0.831|1.909|2.036|1.88|
|**TUN**|1.11|1.49|1.024|1.024|1.029|0.935|1.451|1.525|1.49|
|**EGY**|1.11|1.58|1.024|1.024|1.029|0.935|1.528|1.618|1.58|
|**DZA**|1.06|1.61|1.012|1.012|1.015|0.966|1.540|1.630|1.61|
|**QAT (adj)**|1.18|1.09|1.037|1.037|1.045|0.902|1.115|1.131|1.09|
|**PSE**|1.08|1.72|1.015|1.015|1.025|0.947|1.617|1.746|1.72|
|**IRN**|1.00|1.62|1.000|1.000|1.000|1.000|1.515|1.620|1.62|
|**ARE (adj)**|1.14|1.16|1.010|1.010|1.056|0.901|1.141|1.171|1.16|

Figure 8 summarizes the effect on output per person under the two different scenarios in the long run (when physical capital fully adjusts), with and without changes in the educational attainment of women. Increases in the share of skilled women would generate additional gains of around 8 pp in Algeria, 9 pp in Tunisia, 12 pp in West Bank and Gaza, and 15 pp in Egypt. The median long-run increase in GDPPC in the region is 45% with current educational attainment of women, and 57% when educational attainment of women also increases.

17
contour is equal to w2/w1. Equating the values of AF weights to the marginal rate of substitution of u at z (the slope of the dashed line in Figure 7) does not make sense. Instead, AF parameters (weights w, cutoffs z and identification threshold k) should be selected in a way that the identification contour best approximates indifference curve u (Decerf, 2023b). A similar point can be made for PX weights.<sup>65</sup> <!-- Start of picture text --> x2 Union x2 Intersection<br>z<br>z2 z<br>u u<br>x1 x1<br>z1<br><!-- End of picture text -->

**Figure 7:** AF weights are not marginal weights of substitution

The fact that multidimensional poverty weights are not mere marginal rates of substitution casts serious doubts on seemingly natural methods to select their values. This is clearly the case for methods whose objective is precisely to uncover marginal rates of substitution. For instance, AF weights cannot directly be selected from the methodology proposed (in another context) by Benjamin et al. (2014b) because its aim is to uncover average marginal rates of substitutions for non-monetary dimensions. They can neither be selected directly from the coefficient values obtained from OLS regressions on subjective well-being data.<sup>66</sup> Also, it is unclear whether directly asking subjects for their preferred AF weights would yield meaningful results. Indeed, the link between AF weights and the shape of the identification contour is not trivial.

Rather, we outline a “weights selection” method whose objective is to yield interpersonal well-being comparisons that are best in line with preference u. This method is in line with the spirit of Maasoumi and Xu (2015). For Objective 1, we would like to select ˆ parameters such that the indicator most reliably yields u > u(ˆxi) whenever u > u(ˆxi). Assume that u is defined from an arbitrarily selected reference vector z, which may differ from the cutoff vector z.<sup>67</sup> Hence, we have u = u(z). The information on preference u

> 65It is possible to select PX weights such that the slope of the intermediate section of its identification contour (recall Figure 5) corresponds to the marginal rate of substitution of u at z. However, the shape of the identification contour must be a good approximation of the whole indifference curve u. The PX parameters (weights w, cutoffs z and identification threshold k) must also be selected in a way that the implicit zj<sup>edefiningitsverticalandhorizontalsegmentsmakesense.</sup>

> 66Such method could consist in running an OLS regression of subjective well-being data on the components of achievement vectors and then selecting AF weights so that they correspond to the relative values of the regression coefficients.

67 For instance, for the WB’s MPM, the reference vector z could be defined as living on the extreme IPL without suffering any additional deprivation. That is, z is defined from one of the extreme deprivation 34
Figure 8. Progressivity of Indirect Taxes (Kakwani Index) <!-- Start of picture text --> 0.50<br>0.45<br>0.40<br>0.35<br>0.30<br>0.25<br>0.20<br>0.15<br>0.10<br>0.05<br>0.00<br>Sales Tax Excise Customs Green tax<br><!-- End of picture text --> _Source_ : World Bank staff estimation using BLSS 2017.

Figure 9. Marginal Contribution of Indirect Taxes to Change in Poverty and Gini <!-- Start of picture text --> Green tax<br>Customs<br>Sales Tax<br>Excise<br>-0.5 0 0.5 1<br>Change in Poverty Headcount Change in Gini<br><!-- End of picture text --> _Source_ : World Bank staff estimation using BLSS 2017.

Indirect transfers are progressive and poverty-reducing. The Kakwani index exhibits progressivity for indirect social transfers and positive redistributive effects (figure 10, figure 11). In absolute terms, education benefits accrue slightly more among households in the bottom of the distribution: for example, 12.1 percent go toward those in the bottom 10 percent. This is likely because those households have more children and are less likely to send them to private schools.

Health benefits are highly evenly distributed across the distribution, with households across all deciles accruing around 10 percent of total health spending (figure 12). This likely reflects the fact that health services are almost exclusively funded and delivered by the public health care system.

Figure 10. Progressivity of Indirect Transfers (Kakwani Index) <!-- Start of picture text --> 0.50<br>0.45<br>0.40<br>0.35<br>0.30<br>0.25<br>0.20<br>0.15<br>0.10<br>0.05<br>0.00<br>Health in-kind transfer Education in-kind<br>transfer<br><!-- End of picture text --> _Source_ : World Bank staff estimation using BLSS 2017.

Figure 11. Marginal Contribution of Transfers to Change in Poverty and Gini <!-- Start of picture text --> Health in-kind Transfer<br>Education in-kind<br>Transfer<br>0 2 4 6<br>Change in Poverty Headcount Change in Gini<br><!-- End of picture text --> _Source_ : World Bank staff estimation using BLSS 2017.

21
the two countries. Finally, the paper examines the underlying mechanisms for African migration to foster African trade (both international and intraregional trade). To carry out this study, we rely on a new data set on international bilateral migration recently released by the World Bank for the years 1980, 1990, 2000 and 2010. This data set is the first to cover such a long time span and to include every country in the world.

Our findings point first to a substantial positive effect of the African diaspora on African exports that is higher than the average effect of migration on exports at the world level. This could be partly explained by the prevalence of, on average, weaker institutions in Africa, since we also find that the weaker the institutions in the countries of origin, the more migrants contribute to trade. Second, our findings show a stronger effect in the case of differentiated goods, suggesting migrants also play an important role in reducing information costs, which should affect differentiated products more than commodities. Moreover, the positive effect of the African diaspora on intra-African exports appears to be stronger when migrants are established in geographically and ethnically distant countries. The paper would thus suggest that through migration trade barriers hampering African trade could be further reduced, namely that it would help enforce contract, reduce information costs, and lower cultural barriers.

The remainder of the paper is organized as follows. Section 1 describes the patterns of African migration and exports. Section 2 reviews the literature. Section 3 presents the data and the empirical methodology. Results are then discussed in Section 4 and finally some policy conclusions are drawn.

# **1. AFRICAN MIGRATION AND EXPORTS: AN OVERVIEW**

# **1.1 AFRICAN MIGRATION**

Between 1980 and 2010, the population of African migrants in the world has more than doubled and reached about 30.6 million in 2010 (according to the latest available information 4 on bilateral migrants provided by the World Bank). However, despite this sharp increase in migration from African countries, the population of African migrants represented barely 3 percent of Africa’s total population in 2010. At the same time, African migrants represented only 17 percent of the total population of migrants from the developing world (by comparison, migrants from Asia represented a third of all migrants from developing

> 4 In this paper we focus on international African migration, namely inter-country movements of people within the continent, as well as movements from the continent towards the rest of the world.

3
previous categories. It is first broken into other investment equity<sup>53</sup> and other investment debt. Other investment debt is then disaggregated as follows: currency and deposits, loans (including use of IMF credit and loans), insurance and pensions,<sup>54</sup> trade credit and advances, other accounts payable/receivable, and SDR allocations.<sup>55</sup> Other investment debt as a whole, and each of its component instruments, is broken down into asset and liability flows, and then further broken down by institutional sector. However, there is no sectoral breakdown of Other Investment Equity.

**Reserves:** Reserve Assets are external assets held by the Central Bank or Monetary Authority that are readily available for use to meet Balance of Payments financing needs. These include foreign currency, convertible gold, SDRs, and other reserve assets. Thus, this component is an asset flow of the public sector only.

While in principle the structure of the BOP data contains all the ingredients required to compute each type of flow for each sector, with the exception of direct investment, in practice there are some countries which do not exhaustively provide these breakdowns, especially for earlier years.<sup>56</sup> Table A1 highlights the coverage by flow type and sector in the quarterly BOP data.<sup>57</sup> For each component, the table displays the number of countries 53This is equity investment that is not direct investment or reserve assets, and is not in the form of securities. Equity securities are captured under portfolio equity. This category, introduced with the BPM6 version of the BOP data, is sparsely reported.

> 54This includes non-life insurance technical reserves, life insurance and annuities entitlements, pension entitlements, and provisions for calls under standardized guarantees. This component is likely also small, and very sparsely reported.

> 55SDR holdings (as opposed to SDR allocations) are included in reserve assets. A one time increase in SDR allocations occurred in the 3rd quarter of 2009 for all IMF member countries, so those flows are removed.

> 56Table A3 lists the BOP variables required to compute each type of capital flow by sector. Variable names are as they are found in the bulk public download of the BP6 version BOP data, as of May 2016. The Balance of Payments data also includes International Investment Position (IIP) data, which is the stock equivalent of the BOP flow measures. Variable names for IIP construction by sector are also included, for reference.

> 57Some items in the BOP data are available back to 1948, but this applies to very few of them. For this table, we consider data only from 1980 onwards. The annual BOP data does have somewhat better coverage. For instance, when shifting from quarterly to annual frequency, the number of countries with full coverage of portfolio debt liability flows over 1996-2014 goes from (1,21,13,19) to (4,32,18,27) for central banks, general government, banks,

54
In the development of the traffic light stress test the Life and Pension Insurance Division was supported by other divisions, including the Banking Division with its superior expertise in this area.

The Credit and Market Risk Division informs pension supervisors on the evaluation of credit and market risks and the Mortgage Credit Division informs about real estate risks. The Insurance Mediators and Consumers Division is responsible for supervising the fitness and probity of the boards of directors and management of pension institutions.

**Figure 6  Staff of the Danish FSA (fte)**

<!-- Start of picture text --> ( )<br>190<br>185<br>180<br>175<br>188<br>170<br>181<br>165 174<br>171<br>160 166<br>155<br>2001 2002 2003 2004 2005<br><!-- End of picture text --> Source: Danish Financial Supervisory Authority Internal procedures of the supervisor have been formalized through the development of supervision manuals and written internal procedures related to the most important legal tasks. The procedures for the application of the traffic light system have also been stipulated in detail in internal manuals. The traffic light system is seen as the starting point of important discussions on risks instead of a rigid capital adequacy test.

The budget of the DFSA is covered by fees from regulated entities based both on gross premiums and member contributions, and on the size of the balance sheet less base capital. The budget of the DFSA amounted in 2004 to about € 18 million. 18 percent was contributed by pension institutions, 49 percent by banks, and the rest by other financial institutions.

# **2. Licensing and Authorization Criteria**

All financial institutions are required to obtain an authorization from the DFSA according to current EU directives. An application must be accompanied by various documents, including a memorandum of association and a business plan. The technical basis (i.e. framework for setting premiums, provisioning and profit-sharing) for insurance must be added if the application is for a life insurance and pension license. The supervisor may refuse to approve the technical basis.

The application must specify the types of pension products the applicant intends to offer, the basis for calculating and adjusting pension contributions, benefits and technical provisions, the rules for the distribution of profits, losses and administration costs, the policy on reinsurance, the rules on the information that members must provide for an 12
|Province|Families<br>surveyed|Population|Annual<br>income per<br>family (in<br>pesos)|Annual income<br>per capita (in<br>pesos)|Average annual<br>income per<br>capita relative<br>to the mean|
|---|---|---|---|---|---|
|Villalpando|5|20|5509|1377.15|5.65|
|Villalpando|3|12|6569|1642.333|6.73|
|_Total_|_3945_|_15780_|_975.72_|_243.94_|_1_|

Note: People (and families) ranked by per capita income within each province. Total gives the overall (Old Castille) mean. Old Castille is composed of five provinces: Villarramiel, Paredes, Palencia, Frechilla, Villalpando. Family size assumed to be 4 throughout.

**Income distribution data.** Family annual income estimates (in pesos) from five locations in the Palencia region, part of what is now Castilla y León: Frechilla (13 income classes) and Villalpando (11 income classes); Palencia city, Paredes de Nava, and Villarramiel (9 income classes each). These data were kindly provided by Leandro Prados, who used them recently in Álvarez-Nogal and Prados de la Escosura (2006), which in turn were taken from Yun Casalilla (1987: p. 465) and Ramos Palencia (2001: p. 70).

**Population and area.** Population of 1,980,000 and area of 89,061 km<sup>2</sup> are from Lees and Hohenberg 1989: pp. 443 and 445).

**Urbanization rate. T** he 1750 estimate from Lees and Hohenberg (1989: p. 443).

**Mean income in $PPP** . GDP per capita for Spain, in 1990 international dollars interpolated between 1700 and 1820, from Maddison (2001: p. 264).

# **REFERENCES**

Álvarez-Nogal, Carlos and Leandro Prados de la Escosura (2006), "Searching for the Roots of Spain's Retardation (1500-1850)," _Universidad Carlos III Working_ _Papers in Economic History,_ Madrid.

Lees, L. H. and P. M. Hohenberg (1989), “Urban Decline and Regional Economies: Brabant, Castile, and Lombardy,” _Comparative Studies in Society and History_ 31 (July).

Maddison, Angus (2001), _The World Economy: A Millennial Perspectives_ , Paris: OECD Development Centre.

Ramos Palencia, Fernando (2001), _Pautas de consume familiar en la Castilla_ _Preindustrial: El consume de bienes duraderos y semiduraderos en Palencia 1750-1850_ , University of Valladolid doctoral thesis.

Yun Casalilla, Bartolomé (1987), _Sobre la transición al capitalismo en Castilla: Economía y sociedad en Tierra de Campos 1500-1830_ , doctoral thesis (Salamanca).

63
greater economies of scale but also may enjoy reduced stringency of standards. The implications of such mutual recognition di¤er sharply for ...rms within the region from those in excluded countries, as summarized below: Proposition 3 When region H harmonizes standards at minfsj : j 2 Hg and imposes restrictive rules of origin, then

- (i) intra-regional trade increases at the expense of imports from the rest of world;

- (ii) in the rest of the world, type L countries see a larger decline in their exports to region H if cl > g1(ck).

# Proof. See Appendix B.3.

In contrast, when the bene...ts of mutual recognition are open to all ...rms, the results in certain respects mirror those presented in Proposition 1. As in the case of upward harmonization, all ...rms reap the bene...ts of increased economies of scale due to market integration. But there is now an additional bene...t arising from the downward adjustment of the standard in certain countries. Although both of these e¤ects may encourage entry and boost total trade, they are asymmetrically distributed between exporter countries. Type K ...rms with larger ...xed costs tend to bene...t more from scale economies whereas type L ...rms with a higher variable cost of compliance derive greater bene...ts from reduced stringency of the standard. When there is a signi...cant downward adjustment of the standard, the rise in exports of countries of type L may be greater than that of type K.

Proposition 4 If region H harmonizes standards at minfsj : j 2 Hg and does not impose restrictive rules of origin, then

- (i) imports of region H from type K countries –both within the region and in the rest of the world –increase, whereas those from type L countries increase if cl < g�(ck);

- (ii) the increase in the total imports of region H from excluded type L countries is greater than that of excluded type K countries if cl > g2(ck) and<sup>P</sup> H<sup>dsj< �</sup>  ̄<sup>s.</sup>

# Proof. See Appendix B.4.

14