rafmacalaba/datause-encoder-data huggingface dataset:
A subcomponent of the **VAX** _sinksr_ that may be economically interesting is the domestic value-added that is finally absorbed by the importer country _r_ itself: The **VAXIM** _sr_ includes the value-added produced in _s_ and absorbed in _r_ and that factors in the bilateral exports between the two countries. The measure can be used for instance in the analysis of bilateral trade balances to assess how reciprocal final demand helps activate bilateral exports and production in the two countries.<sup>15</sup> The **DAVAX** _sr_ measure developed within the source-based approach is a subcomponent of the **VAXIM** _sr_ as it includes only the value-added produced in _s_ and directly absorbed in _r_ , without any possible re-export (and re-import) by _r_ .<sup>16</sup> The source-based measures and the sink-based ones can be used in different contexts to address different issues. Nevertheless, it is important to reaffirm that i) at the bilateral level, the domestic and foreign contents are the same in the two breakdowns;<sup>17</sup> ii) the ‘value-added’ and ‘double counted’ terms of the two decompositions differ only at the bilateral level and when summing across the destinations of a given exporter we obtain exactly the same results (i.e. see Appendix C for a for-

> 15The **VAXIM** _sr_ indicator, as any other measure based on a country-level perspective can be summed across bilateral importing partners to get an aggregate indicator for the exporting country _s_ . Then, the **VAXIM** _sr_ can be particularly useful, for instance, when we are interested in decomposing the overall trade balance of a country by its bilateral positions. When the analysis focuses exclusively on a given bilateral relation, it might be more appropriate to resort to the approach presented in Section 4.1.

> 16Neither the **VAXIM** _sr_ , nor the **DAVAX** _sr_ correspond to what Koopman et al. (2014) define as the ‘exports absorbed by direct importers.’ Indeed, as we show in Section 5, these subcomponents are not correctly identified in Koopman et al.’s (2014) decomposition.

> 17In both the decompositions the domestic content of exports (i.e. the sum of the domestic value-added and the domestic double counted) corresponds to the ones defined by Koopman et al. (2010).

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further than just looking at household investment in tutoring by considering the situation where households can make a joint decision on whether to enroll their children in school and to send them to tutoring classes.

Third, we explore the hypothesized child quantity-quality tradeoff in the context of Vietnam, a country that has undergone rapid change in fertility and educational attainment. The total fertility rate decreased steadily from 6 births per woman in the 1970s to 4 births per woman in the late 1980s and to just under 2 births per woman currently (World Bank, 2012). And over the past two decades, the average number of years of schooling for the adult population has increased rapidly, from 4 in 1990 (Barro and Lee, 2012) to 6.6 in 1998 and 8.1 in 2010 (VLSS, 1998; VHLSS, 2010).<sup>6</sup> The Government of Vietnam has paid much attention to family planning and has promulgated policies over the past fifty years encouraging (and in the case of government employees, requiring) families to restrict their number of children to one or two, but to our knowledge, our study is the first to investigate rigorously the quantity-quality tradeoff in the context of Vietnam.

In this paper we focus on households’ investment in their children rather than children’s outcomes, because doing so may provide a more direct test of the quantity-quality tradeoff hypothesis (see, for example, Caceres-Delpiano (2006) and Rosenzweig and Zhang (2009) for a similar approach). In the context of Vietnam, private tutoring as a new measure of the households’ investment in the quality of their children appears more appropriate than traditional measures (such as education expenditures or private school attainment) for two reasons. First, Vietnam’s education system is mostly public with more or less uniform

> 6 Unless otherwise noted, all estimates from the Vietnam Living Standards Surveys (VLSSs) and Vietnam Household Living Standards Surveys (VHLSSs) are authors’ estimates.

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# **_iv. Industry characteristics correlated with responsiveness to GQ_**

The ASI data permits studying the industry related characteristics of the plants most responsive to connectivity. To this end, we replicate equation 1 splitting the regression with sub-samples partitioned by median industry characteristics. Critically, each age group is well-represented across industry characteristics (Annex Table 5) so the previous results for young plants are not simply capturing newly arrived industries – the relevant characteristic is, in fact, youth.

This said, there are significant differences in the stimulative effect of connectivity across industry characteristics within age category. Table 3 shows that responsiveness is almost entirely concentrated in capital intensive industries for all measures of activity in young plants and for output in mature plants (Panel B), and to a lesser extent in land intensive industries (Panel C). There is less clear differentiation for human capital-intensive industries where responsiveness is higher only for output and plant size measured by employee count (panel D).

Consistent with the strong results for capital intensity, the table suggests that plants most responsive to connectivity are those producing durable goods (category including wood products; paper products; leather; textiles; rubber plastic products; motor vehicles, panel E). In particular, output is significantly more responsive for all age categories, while plant size is also significant for the young. Similar results are observed for sectors with strong backward and forward value chain linkages (panel F; e.g., textiles; wearing apparel; office computing; radio, television communication; motor vehicles); and for those that are the least amenable to remote work (panel G).

This said, responsive sectors are also low in contractual intensity (panel H), that is, the proportion of a sector’s intermediate inputs that require relationship-specific investments and differentiated products; and where relationship stickiness, as measured by firm to firm relationship durations, is low (panel I) particularly for output and firm size in the young plants.<sup>13</sup> Together, these patterns are suggestive of a more “anonymous” internal offshoring behavior, that is, young plants can become parts of value chains that do not require proximity to clients to tailor intermediate inputs and may be substituted by other providers relatively easily.

> 13 Based on Martin et al. (2023). This is a measure of stickiness in business relationships constructed at the product-level using firm-to-firm relationship duration data. The higher degree of stickiness translates into a lower probability of switching and longer firm-to-firm trade relationships, conditional on match quality.

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<!-- Start of picture text --> Wildfire<br>Drought<br>Landslide<br>Extreme heat<br>Coastal flood<br>River flood<br>0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%<br>HIG MED LOW VLO Non coastal No data<br><!-- End of picture text --> Source: Authors based on AECM survey; Think Hazard.

**Within CGSs’ portfolios we estimate that 24-31 percent of guarantees are towards sectors that have elevated exposure to climate change and weather variability.** Since our classifications are both at a NACE 1 level, we use our largest sample covering 84 percent of total guarantees. For the classification by Lazo et al. (2011) based on US weather variability impact, we find that the combined exposures of CGSs in our sample to these sectors is EUR 65 billion (24 percent of total guarantees in the sample). This is driven primarily by manufacturing (EUR 29 billion) and agriculture (EUR 28 billion). For the classification obtained from Skougaard et al. (2017) on relevant sectors from a climate change perspective in Europe, we find that the combined exposure of CGSs in our sample to these sectors is EUR 83 billion (31 percent of total guarantees in the sample). This is driven primarily by agriculture (EUR 28 billion) and accommodation and food services (EUR 27 billion).

_4.3 Potential losses in adverse scenarios_

**We find that for transition and physical risk scenarios the annual expected loss on the guarantee portfolio could increase by EUR 181 million and EUR 128 million, respectively.** For our transition scenario the outcome is calculated for 2025, which represents the time horizon for which the ECB (2022) obtained the highest increases in default rates. After 2025 the annual expected loss declines. For our physical risk scenario (“hot house world”), the highest increase in default rates is observed in 2050, with the expectation that financial losses would keep increasing afterwards. Comparing our results to baseline expected losses, the transition scenario represents a peak 8.9 percent increase in the annual expected losses on the guarantee portfolios of CGSs in

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without serious consultation with indigenous communities. The management plan called for the prohibition of hunting and fishing and the relocation of some villages away from a strictly protected area.

These recommendations have been eliminated under the present biosphere reserve scheme. Instead, attempts are being made to involve communities and leaders in forest management and in the various employment opportunities signified by the park and a growing tourist trade. The WWF has provided support for almost 10 years and expects to continue to do so. Other support issues from US-AID, UNESCO and RENARE. Darien will continue to be exposed to the attentions of the mining and logging industries and the colonisation that may be precipitated by the extension of the PanAmerican Highway (WWF 1988a).

## 6.4. RIO PLATANO - HONDURAS

The Rio Platano Biosphere Reserve was established in 1979 and became a world heritage site in 1980. It covers almost all the watershed of the Rio Platano: 525,000 ha on the Caribbean coast of Honduras. At the time of its creation there were 4,450 inhabitants, mostly Miskito Indians but with a few small Payas and Ladino villages. At that time, Rio Platano was Inaccessible by road (Glick & Betancourt 1983).

The reserve is divided into a core area (319,000 ha) to be used for research, education and limited tourism, and a buffer zone (207,000 ha) to be used for sustained use experimentation. Later, a cultural zone will be inserted in the core area, covering the settled areas and archeological sites.

Since establishment, the costs of reserve planning and operations have been supported by the Honduran Renewable Natural Resources Directorate (RENARE), the Honduran Ecological Association (AHE), WWF-US, UNESCO and CATIE. Accomplishments include:

- Infrastructure, administration and guards in the northern area: the main centre of population.

- Gathering of support from reserve inhabitants through adult and child education.

- Resource protection in the northern sector.

- Training in management methodologies.

- Involvement of residents in planning and management.

- Preparation of a long term management plan.

- Census and studies of established populations and methods of resource utilisatLon

# (Honduran Ecological Association 1987)
This question tackles the issue of predictability of corruption within bureaucracy. For instance a bureaucracy in which the income from corruption is shared among all the members, acts like a monopolist that jointly maximizes bribe income. Thus, the briber is subject to less uncertainty (although possibly to higher amounts of bribes). Conversely, if the level of organization of corruption within the bureaucracy is low, the bribee is subject to more uncertainty and blackmailing from many different officials who participate in the delivery of the service.

The sample was truncated in the same way as question 15.

The results of this question show that uncertainty resulting from this source is highest in the Latin America and CIS, (about 55 percent), followed by Africa, and than by MNA and CEE. This kind of problem seems to be almost absent in developed countries.

_Question 177: Uncertainty about receiving the service after paying a bribe_ Question 17 attempts to determine predictable versus unpredictable corruption from still another angle. It asks if paying a bribe usually means that the service is delivered as agreed.

The sample was truncated the same way it was explained in question 15.

<!-- Start of picture text --> 17. "If a firm pays the 90 - .- . . .. .<br>required "additional payment" 8<br>the service is usually also<br>delivered as agreed." 70<br>This is true 60<br>(1) always D 5<br>(2) mostly 40<br>(3) frequently 2<br>(4) sometimes 2 30-<br>(5) seldom D<br>(6) never 2 20<br>10 i<br>World LDC DC SSEA MNA CEE LAC SSA CIS<br>Percentage of firms who ticked (1), (2), or (3) for question 17<br><!-- End of picture text --> In Asia and the CEE and CIS more than 80 percent of businessmen thought that there was little uncertainty about the delivery of the service after paying a bribe. Overall in all regions at least about 70 percent of surveyed businessmen thought that there was little uncertainty about service delivery after "the wheel was greased." This percentage is the lowest in Africa (but still well above 60 percent).

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wages.

We pin down the Cobb-Douglas labor shares from the ratio of an industry’s wage bill over the industry’s value added (which comes from national input-output tables<sup>13</sup> ). The wage equation multiplier _A_<sup>_i_</sup> is calibrated such that the aggregate labor allocation reflects the observed average wage in the data from each country. Finally, the fixed utility parameters, _η_<sup>_i_</sup> , are calibrated by matching the simulated labor allocations with the labor allocations observed in the data.

# **3.4 Simulations**

We simulate the effect of China on each country with a one-time change in the world prices of manufacturing, mining and agriculture at the same time. We assume that China’s growth in exports and imports causes the price faced by Latin American exporters to change, since producers face perfectly elastic demand in a perfect competition setting. Consistent with this, we assume that Argentina, Brazil and Mexico are small open economies, i.e. they take prices as given. However, the difference between the vulnerability and opportunity indices gives us the change in net exports but not in prices. Therefore, we need to map the change in net exports (which is endogenous in our model) to a exogenous price change.

The price effect of China is endogenous estimated with the calibration of the model. The calibration is performed with the estimated moving-costs parameters and the other parameters computed from the observed data as discussed above. In the first iteration, we shock the model with a guess of the price effect of (only) one sector and we use it to calculate the reduction in net exports over time (see equation 12). Then we compare the change in net exports with the difference between the opportunity and vulnerability indices we described previously (see equations 1 and 2). If the change in net exports equals the difference between the indices we stop. If the change in exports is not equal to the difference between indices we apply another price reduction. The algorithm tries different price shocks until it finds an equilibrium where

> 13We used the IO table of 2003 for Mexico, 2005 for Brazil and 1997 for Argentina. The sources are the INEGI, IBGE and INDEC respectively.

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characteristics ( _Hjt_ ). This specification allows patent reform to affect not only the level of patenting but also its growth rate over time, which is reflected in the inclusion of an interaction term of the reform dummy and the time trend.

# **3. Data Sources**

# _3.1 Data from BEA Surveys_

Data on U.S. multinational firms comes from the U.S. Bureau of Economic Analysis (BEA) annual Survey of U.S. Direct Investment Abroad and the quarterly Balance of Payments Survey.<sup>21</sup> The survey forms concerning MNE activity capture extensive information on measures of parent and affiliate operating activity like levels of sales and R&D expenditures. MNEs must also report the value of royalties paid by affiliates to parents for the sale or use of intangible property. American tax law requires that foreign affiliates make these payments. The reported figures on the value of intangible property transferred include an amalgam of technology licensing fees, franchise fees, fees for the use of trademarks, etc. However, the aggregate data indicate that intangible property transfers are overwhelmingly dominated by licensing of industrial products and processes.<sup>22</sup> Depending on the particular circumstances, firms may have an incentive to misrepresent the value of a technology transfer to avoid taxes even though they are

> 21 The forms firms are required to complete vary depending on the year, size of the affiliate, and U.S. parent’s ownership stake.  The most extensive data are collected in benchmark years – 1982, 1989, 1994, 1999.  BEA uses reported data to estimate universe totals when surveys cover only larger affiliates or when only certain affiliates provide information on particular survey forms.  To avoid working with estimated data, only affiliates required to provide all the information associated with a particular analysis are considered in this paper.  Additional information on the BEA data can be found in Mataloni (1995). 22 Furthermore, in each manufacturing industry except food manufacturing, this kind of licensing accounts for between 80% and 99% of total royalty payments from affiliates to parents.  Even in food manufacturing, technology licensing accounts for more than 50% of the total.

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Table 3: Estimated changes in labor income

|Males|Workers reporti<br>decline in earnin<br>due to COVID<br>(percentage)|ng a<br>gs|Average income cha<br>Q4 versus Q3 FY20<br>(percent)|nge,|
|---|---|---|---|---|
|Agriculture||18||-33|
|Industry - Informal||46||-19|
|Industry - Formal||26||-4|
|Services - Informal||51||-28|
|Services - Formal||22||-5|
|Females|||||
|Informal||22||-19|
|Formal||8||0|

Source : Authors’ calculations using LFS data. Note: Income changes are based on a total monthly income variable in nominal terms.

As mentioned, an important objective of this analysis is to look at the role that cash transfers played in supporting households’ incomes. For that purpose, we model the emergency expansion of the main cash transfer programs (Takaful and Karama) described in the previous section. We identify recipients of these programs in HIECS using the targeting rules and adjust the number of households receiving and the size of the transfer as a response to COVID-19. As noted, Takaful targets households with children under 18, while Karama targets the elderly poor, orphans, widows, and people living with disabilities. The selection of beneficiaries is conducted through geographical and categorical criteria, with proxy means testing (PMT).<sup>12</sup> We also simulate the emergency cash transfer to informal workers that was paid starting in April 2020. The grant of EGP 500 per worker was paid monthly for three months to around 2 million informal workers registered in the workforce databases of the Ministry of Manpower across governorates.<sup>13</sup> A relative allocation using HIECS survey weights indicates that the grant was paid to about 12.1 percent of Egypt’s informal workers. Since the distribution rules are not clear, we randomly selected informal workers in the updated HIECS dataset to reach the size of the informal worker population that benefited.<sup>14</sup> 12 The targeting rules are applied using the Fiscal Incidence Tool constructed with the Ministry of Finance. The PMT targeting formula relies on a set of household demographics and assets to identify poor households.

13 The first payment was processed in April 2020 via post offices (4,000 branches), the Agriculture Bank of Egypt (1,100 branches), and 600 schools that also served as payment sites – a total of 5,700 outlets. Beneficiaries received a free ATM card with their first payment to cash their second and third payments at post offices and/or banks. To avoid overcrowding and ensure safety, accepted beneficiaries were notified via SMS regarding the location and time to visit to collect their first payment and ATM card.

14 The following caveat concerning the analysis should be kept in mind. It is unclear from LFS data whether there could be some double counting of the targeted transfers to workers. This means that the income loss reported in LFS could have been bigger if respondents included those transfers, and the reported results may be overestimating the importance of the cash transfers in smoothing the impact.

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