rafmacalaba/datause-encoder-data huggingface dataset:
# **II.2.2** Building coastal terrain models (DTM)

Coastal terrain models were derived from the CIAT SRTM 90 meters digital elevation model (DEM) data (Version 2), released in 2005.<sup>10</sup> Zipped data files were downloaded from the CIAT website, and then converted into raster format, and mosaiced in terms of country boundaries in the ArcGIS environment.

# **II.2.3** Identifying inundation zones

Inundation zones were derived from the coastal terrain model (DTM) by setting the value of pixels in the DTM to 1 for the different SLR scenarios examined in this study. Pixels that are apparently not connected to coastlines, such as inland wetlands and lakes, were masked out manually.

# **II.2.4** Calculating exposure indicators

Estimates for each indicator were calculated by overlaying the inundation zone with the appropriate exposure surface dataset (land area, GDP, population, urban extent, agriculture extent, and wetland). Exposure surface data were collected from various public sources. Unless otherwise indicated, latitude and longitude are specified in decimal degrees. The horizontal datum used is the World Geodetic System 1984 (WGS 1984). For area calculation, all units are projected to World Equal Area.

For the exposure grid surfaces, two GIS models were built for calculating the exposed value. Because the values of the pixels in GDP and population surfaces are respectively in millions of US dollars and number of people, the exposure is calculated by multiplying the exposure surface with the inundation zone and then summing up by multiplying grid count and value. Exposure indicators, such as land surface, urban extent, agriculture extent and wetland are measured in square kilometers.

# **II.2.5** Adjusting absolute exposure indicators

For exposure indicators such as land area, population and GDP, which have measured country totals available, the exposed value is adjusted to reflect its real value by using the following formula:

> 10 Shuttle Radar Topographic Mission.

8
# Contents

|1|Intr|oduction . . . . . . . . . . . . . . . . . . . . . . . . . .|. . . . . . . . .<br>3|
|---|---|---|---|
|2|Met|hodology . . . . . . . . . . . . . . . . . . . . . . . . . .|. . . . . . . . .<br>6|
||2.1|Step 1 - Emigration stocks . . . . . . . . . . . . . . .|. . . . . . . . .<br>6|
||2.2|Step 2 - Emigration rates . . . . . . . . . . . . . . . .|. . . . . . . . .<br>13|
||2.3|Speci...c assumptions in release 1.0 . . . . . . . . . . .|. . . . . . . . .<br>14|
|3|The|database<br>. . . . . . . . . . . . . . . . . . . . . . . . .|. . . . . . . . .<br>15|
||3.1|Gross results . . . . . . . . . . . . . . . . . . . . . . .|. . . . . . . . .<br>22|
||3.2|Comparison with previous study . . . . . . . . . . . .|. . . . . . . . .<br>26|
|4|Key|indicators . . . . . . . . . . . . . . . . . . . . . . . . .|. . . . . . . . .<br>28|
|5|Con|clusion . . . . . . . . . . . . . . . . . . . . . . . . . . .|. . . . . . . . .<br>34|

2
of which strengthened the administrative capacity of the JPO and reduced delays in examination and the granting of patents.

Perhaps the best example of a reform that changed both the substance of the law and its administration is the reform that took place in Mexico in 1991.<sup>41</sup> The preceding IPR legal regime was effectively abolished and a completely new legal system with a new administering institution was established. Whereas the implicit goal of the previous IPR regime had been to limit the ability of patent holders to control access to their patented technology, the goal of the new regime was explicitly to ensure adequate protection to incumbent patent holders. Patent protection was expanded to incorporate pharmaceutical and chemical products. Previous restrictions on terms of licensing technology were abolished, allowing these terms to be determined at the discretion of the contracting parties. Legal tools were introduced to aid in the prosecution of patent infringement, including inspections of the facilities of potential infringers, the seizure of goods and closure of facilities involved in infringement, and the effective prohibition of parallel imports.

The Brazilian patent reform of 1997 was of a similar nature. In addition to significant legal changes, the reform also introduced guidelines for judges to use in the determination of damages as a result of infringement. Judges were also provided with additional means to stop illicit activities including powers to grant preliminary injunctions to seize infringing products and close down infringing production.<sup>42</sup> Spain’s

> 41   While such surveys also have their problems, it is worth pointing out that surveys of multinational managers (such as the _World Competitiveness Report_ , issued by the World Economic Forum) tend to give high marks to the _effective enforcement_ of the new IPR regime in Mexico.

> 42   From the perspective of multinational pharmaceutical companies, the Brazilian reform process took a step backward in 2000, when the Health Ministry took steps to block the granting of new pharmaceutical products.  According to our sources, these difficulties persist to the present.

31
|**Table 2: Summary Statist**|**ics of Inter**<br>|**national Pat**<br>|**ent Flows by **<br>|**High-IP Clus**<br>|**ter**<br>|
|---|---|---|---|---|---|
||**Min.**|**Mean**|**Std. dev.**|**Max**|**Obs.**|
|**Total Patents**||||||
|Including Zeros|0.00|55.08|2,521.43|563,592.80|322,014|
|Positive Flows Only|0.01|349.08|6,339.55|563,592.80|50,810|
|**Analytical Instruments (AI)**||||||
|Including Zeros|0.00|6.90|336.34|62,740.98|322,014|
|Positive Flows Only|< 0.01|65.13|1,031.84|62,740.98|34,094|
|**Biopharmaceuticals (BIO)**||||||
|Including Zeros|0.00|0.19|6.67|1,914.34|322,014|
|Positive Flows Only|< 0.01|1.90|21.12|1,914.34|31,839|
|**Chemicals (CHEM)**||||||
|Including Zeros|0.00|2.53|98.98|25,112.73|322,014|
|Positive Flows Only|< 0.01|22.20|292.66|25,112.73|36,643|
|**Information and Communicati**<br>|**ons Techno**<br>|**logy (ICT)**<br>||||
|Including Zeros|0.00|15.95|745.95|135,309.85|322,014|
|Positive Flows Only|< 0.01|161.79|2,370.51|135,309.85|31,754|
|**Medical Devices (MED)**||||||
|Including Zeros|0.00|1.43|46.20|11,019.49|322,014|
|Positive Flows Only|< 0.01|13.85|143.06|11,019.49|33,304|
|**Production Technology (PT)**||||||
|Including Zeros|0.00|4.98|257.73|67,061.03|322,014|
|Positive Flows Only|< 0.01|41.86|746.19|67,061.03|38,311|
|**Other**||||||
|Including Zeros|0.00|13.47|592.92|114,855.77|322014|
|Positive Flows Only|< 0.01|91.97|1,547.02|114,855.77|47,161|

_Notes_ : Data reflects bilateral patent applications data for the years 1995–2015. Categories reflect groupings of NAICS industry that we define based on a US Department of Commerce classification of sectors with above-mean patenting intensity (patents per industry employee).

13
Appendix: DescriRtion of Data Sources.

The "Jorld Bank's Debtor ReRorting System provides the following inforaation on a loan by loan basis: debtor country, creditor country, month of loan origination, month of loan maturity, loan amount, and the interest rate spread. The selected loans are to the private sector, denominated in U.S. dollars, and specify the spread above LIBOR. Some loans with multiple creditor countries are included in the sample if the debtor country imposes a uniform interest withholding tax on all outgoing bank interest payments.

Information on the country's debt outstanding, and debt service are derived from the Debtor ReDoQting System as well.

Tax rates are compiled from the following sources: Comnorate Taxes. A Worldwide Summary (previously called CorDorate Taxes in 80 Countries), Price Waterhouse (New York), various issues.

International Tax Summaries, Coopers and Lybrand (Wiley, New York), various issues.

Country information and tax treaty information from the following publications of International Bureau of Fiscal Documentation in Amsterdam: African Tax Systems, Looseleaf, E. de Brauw-Hay and F. Butzelaar-Mohr, editors.

Taxation in Latin AmerLca, Looseleaf, P. Masson-Parodi, editor. Taxes and Investment in_Latin America, Looseleaf, J. van Hoorn, Jr., editor.

For some years, tax data has been interpolated or extrapolated, as tax rate information is not available for all years for all countries. However, tax rates, and especiallv internationally negotiated tax rates, tend to vary little from year to year.

18
# **Tables and Figures**

## **Table 1. Descriptive Statistics** **_Using Program-Level Data from the WBSCPS and Administrative Sources_**

|**Variable**|**Mean**|**Std.**<br>**Dev.**|**Min.**|**Median**|**Max.**|**Obs.**|
|---|---|---|---|---|---|---|
|**Panel A. Programquality determinants**|||||||
|_Infrastructure_|||||||
|Has enough equipment or tools for practice|0.72|0.45|0|1|1|2,103|
|Program offers at least one online class|0.35|0.48|0|0|1|2,103|
|_Training and curriculum_|||||||
|Teaches numerical competencies|0.80|0.40|0|1|1|2,103|
|Promotes work under hardship or pressure|0.84|0.36|0|1|1|2,103|
|Curriculum is fixed|0.70|0.46|0|1|1|2,103|
|Time assigned to practical training (%)|46.45|16.56|4|50|80|2,072|
|<br>Graduation requirement|||||||
|Test|0.40|0.49|0|0|1|2,103|
|Thesis or research project|0.37|0.48|0|0|1|2,103|
|Internships outside institution are mandatory|0.58|0.49|0|1|1|2,103|
|Remediation support|||||||
|Remediation classes before starting the program|0.51|0.50|0|1|1|2,103|
|Remediation classes during the program|0.57|0.50|0|1|1|2,103|
|Years since last update to curriculum|2.91|2.69|0|2|25|1,946|
|More than once per year:|||||||
|Analyze student performance to solve problems|0.86|0.35|0|1|1|2,103|
|Collect student satisfaction data|0.69|0.46|0|1|1|2,103|
|_Costs_|||||||
|Annual tuition (2019 PPP USD)|2,244|1,762|0|2,367|25,515|2,103|
|HEI has received funding from|||||||
|<br>Private sector|0.20|0.40|0|0|1|2,103|
|Government|0.34|0.47|0|0|1|<br>2,103|
|_Link with productive sector_|||||||
|Engagement with firms|||||||
|Somebody in charge of industry relations|0.82|0.38|0|1|1|2,103|
|Industry has agreements with HEI to hire program grads|0.39|0.49|0|0|1|2,103|
|Industry has agreements to train faculty|0.35|0.48|0|0|1|2,103|
|Collect data on employment or employers' satisfaction|0.56|0.50|0|1|1|2,103|
|Communicate with local firms about their needs|0.52|0.50|0|1|1|2,103|
|Job search assistance|||||||
|HEI trains students for job interviews|0.69|0.46|0|1|1|2,103|
|HEI provides job market information|0.81|0.40|0|1|1|2,103|
|<br>HEI has an employment center|0.60|0.49|0|1|1|2,103|
|_Faculty_|||||||
|Number of faculty|20.00|18.70|1|15|200|2,076|
|<br>Percent of faculty|||||||
|<br>with BA degree|82.20|29.40|0|100|100|2,043|
|with graduate degree|48.60|32.60|0|43|100|1,998|
|working full-time|38.40|30.30|0|31|100|1,987|
|with 5yrs+ industry experience|55.70|33.10|0|56|100|1,988|
|<40 years old|40.00|29.20|0|34|100|1,961|

41
property management throughout the region, and that gives the sense that Heller’s argument has considerable force. More than a decade after reform began, in only a few countries in the region, e.g. the Czech and Slovak Republics, Hungary and Estonia have effective ownership structures developed even though in most places the rule of law is now in place.

# **Is Capitalism So Mysterious?**

Hernando de Soto’s most recent book, _The Mystery of Capital_ , makes a widely cited claim that secure property rights to land is in fact the answer to the mystery of why capitalism is such a productive economic system in the West. A corollary of this argument is that the absence of secure tenure explains the failure of capitalism to take off in the developing world. He makes a compelling case, at least at first reading, that property rights as embodied in titles are an essential mechanism for converting assets to usable wealth. Titles, de Soto argues, “capture and organize all the relevant information required to conceptualize the potential value of an asset and so allows us to control it.”<sup>24</sup> He estimates that if developing countries could provide secure property rights to residential property, they would be able to effectively “unlock” $9.3 trillion of what he calls “dead capital” blaming the absence of such well-defined property rights for the failure of capitalism in the developing world. As noted earlier, his views in this regard echo those of the early Bank research on this topic and would appear to confirm them.

However, on closer study, the strength of de Soto’s claims seems problematic. Though there is good reason to agree that improving property rights should be an essential part of any reform process, a growing body of analysis reviewed by Woodruff (2001) argues that titling programs should be carried out in conjunction with the changing spectrum of property rights definitions that characterize tenure in developing countries.

> 24 De Soto (2000). p. 47

21
Annex 3: <u>Gabon - Detailed results for impact of food price increase on headcount index in sample of West and Central African Countries</u>

|||||**25% increase**|**50% increase**|**25% increase**|**50% increase**|
|---|---|---|---|---|---|---|---|
||**Share in**|||**Upper**<br>**bound**|**Upper**<br>**bound**|**Lower**<br>**bound**|**Lower**<br>**bound**|
|**Food item**|<br>**total**<br>**consumption**|**Proportion**<br>**of Consumers**|**Baseline**<br>**Headcount**|<br> <br>**Impact**<br>**(Cons. only)**|<br>**Impact**<br>**(Cons. only)**|<br>**Impact**<br>**(Cons.& Prod.) **|<br>**Impact**<br>**(Cons.& Prod.) **|
|||||**Gabon National**||||
|Rice|3.0|91.4|**32.7**|33.2|33.8|33.2|33.8|
|Casava|1.9|86.4||33.0|33.2|32.8|33.0|
|Maize|0.3|40.0||32.7|32.7|32.7|32.7|
|Wheat|3.9|93.5||33.4|34.2|33.4|34.2|
|Palm oil and groundnut oil|1.7|90.6||33.0|33.2|33.0|33.2|
|All|10.7|97.3||34.5|36.7|34.3|36.2|
|||||**Gabon Urban**||||
|Rice|3.1|92.1|**29.8**|30.3|30.9|30.3|30.9|
|Casava|2.1|84.1||30.1|30.4|30.0|30.3|
|Maize|0.3|33.5||29.8|29.8|29.8|29.8|
|Wheat|4.2|94.8||30.5|31.4|30.5|31.4|
|Palm oil and groundnut oil|1.6|90.1||30.0|30.3|30.0|30.3|
|All|11.3|97.1||31.7|34.0|31.6|33.8|
|||||**Gabon Rural**||||
|Rice|2.5|88.5|**44.6**|44.9|45.1|44.9|45.1|
|Casava|1.0|95.7||44.6|44.7|44.2|44.0|
|Maize|0.2|65.8||44.6|44.6|44.6|44.5|
|Wheat|2.9|87.9||45.1|45.8|45.1|45.8|
|Palm oil and groundnut oil|2.0|92.6||44.8|44.9|44.8|44.8|
|All|8.4|98.2||45.9|47.8|45.2|46.2|

Source: Authors’ estimation using country household survey data 22
_Annex 2 Table 2: Food prices (ln) and program saturation in nationally representative data; Model with cutoff at saturation of 65 percent_

||Share of food<br>expenditures|Saturation|Saturation*Above<br>cutoff|Above cutoff|N|<br>Saturation +<br>Saturation*Above<br>cutoff|
|---|---|---|---|---|---|---|
|Rice, raw regular<br>milled|0.191|0.078 ***|-0.252 ***|0.245 ***|N|<br>-0.174 **|
|Other raw rice and||(0.013)|(0.088)|(0.067)|8370|<br>(0.086)|
|grains|0.074|-0.157|0.474|-0.456||0.318|
|||(0.100)|(0.654)|(0.506)|8555|<br>(0.640)|
|Roots and tubers|0.011|0.241 ***<br>(0.050)|0.771 **<br>(0.351)|-0.519 *<br>(0.270)|8487|1.012 ***<br> <br>(0.344)|
|Eggs (fresh)|0.018|0.089 ***<br>(0.016)|0.154<br>(0.110)|-0.070<br>(0.085)|8551|0.242 **<br> <br>(0.107)|
|Eggs (processed)|0.001|0.093 ***<br>(0.025)|0.424<br>(0.284)|-0.284<br>(0.218)|6449|0.517 *<br> <br>(0.283)|
|Fish (fresh)|0.058|-0.009<br>(0.014)|0.332 ***<br>(0.095)|-0.249 ***<br>(0.072)|8530|0.323 ***<br> <br>(0.093)|
|Fish (processed)|0.023|-0.066 *<br>(0.038)|0.638 **<br>(0.290)|-0.512 **<br>(0.223)|8479|0.572 **<br> <br>(0.285)|
|Meats (fresh)|0.035|0.019<br>(0.012)|0.029<br>(0.080)|-0.004<br>(0.062)|8510|0.048<br> <br>(0.079)|
|Meats (processed)|0.011|1.652 ***|-4.552 *|2.523||-2.901|
|||(0.330)|(2.692)|(2.064)|8242|<br>(2.657)|
|Fruits (fresh)|0.021|-0.178 ***<br>(0.031)|0.091<br>(0.207)|0.017<br>(0.160)|8512|-0.087<br> <br>(0.203)|
|Vegetables (fresh)|0.046|0.054 ***<br>(0.017)|0.160<br>(0.109)|-0.060<br>(0.085)|8561|0.214 **<br> <br>(0.107)|
|Rice and grains<br>processed|0.021|<br>0.176 ***|<br>-0.429|<br>0.213||<br>-0.253|
|||(0.049)|(0.316)|(0.245)|8555|<br>(0.310)|
|Coffee, cocoa, tea|0.025|<br>0.114 ***|<br>-0.262|<br>0.219||<br>-0.149|
|||(0.042)|(0.277)|(0.214)|8559|<br>(0.271)|
|Sugar|0.016|-0.504 ***|0.590 ***|-0.360 ***||0.086|
|||(0.026)|(0.174)|(0.135)|8529|<br>(0.170)|
|Milk Products|0.007|0.071|0.527|-0.456||0.598|
|||(0.058)|(0.429)|(0.328)|8117|<br>(0.422)|

note: *** p<0.01, ** p<0.05, * p<.1. Standard errors in parenthesis. Each row corresponds to a separate regression. Observations are at the village-food item-year level and pooled across the years 2009, 2012, and 2015. All models include year and village fixed effects. Prices are calculated as unit values, see text for details.

Source: 2009, 2012, and 2015 Family Income and Expenditure Surveys and Department of Social Welfare Administrative Data on _Pantawid_ Program Enrollment 73
Turning to patterns in median loan growth rates and comparing them with the median asset growth rates (Figure 8b), some interesting observations emerge. While Commercial SOFIs expanded lending more in the period 2007-2011, the growth rate is roughly equal among all SOFIs post 2011. This may reflect the ability of Commercial SOFIs to react faster to periods of crisis, expanding and contracting their direct lending portfolio as needed (a more flexible instrument compared to on-lending). In addition, Commercial SOFIs median asset growth rate post 2011 surpasses the 2007-2011 period, while the median loan growth rate falls – this may suggest an expanded role in investment instruments such as government bonds etc. Meanwhile, Development SOFIs median asset growth falls significantly post 2011, but the median loan growth rate remains unchanged – possibly reflecting a continued focus on loans emanating from narrower policy mandates.

The breakdown by geographic areas points to significantly higher median asset and loan growth rates in East ECA compared to the other two regions (noting that most SOFIs operating in East ECA are Commercial SOFIs). Benchmark Europe and West ECA, characterized more by Development SOFIs, witnessed slowdowns in the asset growth rates post 2011 – possibly scaling back from the immediate post GFC support (Figure 8c). However, while West ECA sustained the median loan growth rates post 2011 (and at rates proportionally higher than that of median asset growth), Benchmark Europe experienced negative median growth rates in the period 2011-2015 (Figure 8d).

**Figure 8: Assets and loans growth rates (2007 through 2015)**

<!-- Start of picture text --> By type<br>8a. Median asset growth rates of SOFIs 8b. Median loan growth rates of SOFIs<br>Commercial Development Commercial Development<br>2007/2011 2011/2015 2007/2011 2011/2015<br>160% 160%<br>100%<br>120%<br>80%<br>60%<br>80%<br>40%<br>40%<br>20%<br>0%<br>0%<br>-20% -20%<br><!-- End of picture text --> 23
job for a long time sacrifice their subsequent wage growth. In all columns, the complementarity between schooling and experience remains robust.

The next analysis uses national achievement test scores explicitly to proxy unobserved abilities (Table 9). Since a preliminary analysis showed that the interaction between test scores and years of experience is insignificant, I interact test scores with the interaction of schooling and experience to investigate whether ability changes the complementarity between schooling and experience. Columns 1 and 2 use mathematics test scores, with province and school dummies respectively. Mathematics test scores significantly augment the schooling-experience complementarity. The linear effect of the scores is insignificant. The estimates of the complementarity are quite similar between the two columns. Columns 3 and 4 use English test scores. Interestingly, English test scores do not significantly alter the complementarity, in contrast to mathematics test scores, pointing to a qualitative difference in the functionality between the two subjects.

The above findings are consistent with the occupational upgrading observed in Figures 4b, 5 and 6. Good performers in national achievement tests tend to experience higher wage growth along with labor-market experience but the premium seems to come from their occupational mobility to more professional occupations. Ability, measured by test scores, augments the complementarity between schooling and experience, which is attributed to the upward upgrading of their occupations.

# **6. Conclusions**

This paper has examined wage dynamics and occupational mobility using panel data of adolescents’ labor market behavior and outcomes from the Philippines. The study shows, first, that returns to labor market experience are large, nearly a half of the conventional estimate of returns to schooling. Second, returns to experience are higher if educational attainment and/or test score is higher. Third, ability, measured by test scores, positively influences the upgrading of occupations toward more skilled categories, although educational attainment plays an important role in determining the first occupation. The complementarity between schooling and experience is greater among good performers who showed high test scores; education and ability augment gains from accumulating labor market experiences.

High unemployment rate among youth is a typical phenomenon of developing country labor markets. Mismatch and turnover are quite common at the early stage of their labor market experiences in those countries. The current evidence from the Philippines showed the importance of academic achievements, measured by both years of schooling completed and test scores, in upgrading their occupations to realize higher returns in the labor market and thus augmenting gains from accumulating labor market experiences.

11