rafmacalaba/datause-encoder-data huggingface dataset:
Table 6 confirms the main results by focusing on the post-WWII sample and comparing the PPML estimation results with those of OLS and Probit models. In all three columns, bilateral trade exposure emerges as a key predictor of official rescue lending during crisis and disasters, both in terms of statistical significance and in terms of coefficient size. Specifically, in the probit model, an increase in bilateral trade exposure by one percent is associated with a 0.24 percentage point increase in the likelihood of a rescue loan. In the OLS model, an increase in trade exposure by one percent is reflected in a 0.40 percent increase in real commitment amounts. And finally, in the PPML model that captures both the intensive as well as the extensive margin, the estimated elasticity of rescue lending to bilateral trade exposure is 0.43 and statistically significant. The different models also show similar results with respect to distance, shared culture, and political allegiance (UN general assembly voting).

Taken together, our results reveal persistent patterns of financial rescue lending during disasters. The statistical significance and quantitative importance of bilateral trade and financial exposure suggests that official flows follow private flows. Countries seem to be most willing to cooperate financially, when private agents have significant “skin in the game” in the form of real economic or financial exposure to the crisis country. This finding points towards a substantial element of economic self-interest in financial cooperation across all eras of the international financial system. Cooperation is most likely to emerge during contagious crises and between closely integrated economies. A less charitable restatement is that smaller poorer countries with more limited spillover potential across borders are likely to receive less official finance even if their disasters are just as severe.

At the same time, cooperation seems to be impeded by informational asymmetries, as the likelihood of rescue lending decreases significantly with higher geographic and cultural distance. Besides economic exposure, political allegiance can help in overcoming these frictions.

# **6. Conclusion**

This paper quantifies and studies the scope and determinants of official, sovereign-to-sovereign lending over the past two centuries, based on an encompassing new database. We show that cross-border official lending has been an important force in international finance both in the previous two centuries and today. Official lending tends to spike during wars and severe financial crises with the most notable episodes in World Wars 1 and 2, under Bretton Woods and in the 1930s Depression.

Official cross-border loans and bailouts have also become much more institutionalized. Dozens of new official creditor institutions have been created since the 1970s, including, regional development banks. At the same time, bilateral and multilateral institutions lending continue to play an important role 35
wide range of countries, based on the matched importer-exporter customs transaction data from the World Bank’s Exporter Dynamic Database. Preliminary results show an upward trend in the DVAR for countries such as Bangladesh, Guatemala, Madagascar and Morocco. One common trait of these countries is their conducive trade and FDI policies that allow their participation in global value chains, similar to the case of China. This is clearly a promising avenue for future research.

# References

- [1] Ahmad, Nadim, Sonia Araujo, Alessia Lo Turco, and Daniela Maggioni (2013). “Using Trade Microdata to Improve Trade in Value-Added Measures: Proof of Concept Using Turkish Data.” in Trade in Value Added: Developing New Measures of Cross-Border Trade, Edited by Mattoo, Aaditya, Zhi Wang, and Shang-Jin Wei, World Bank.

- [2] Amiti, Mary, Oleg Itskhoki and Jozef Konings (2014). “Importers, Exporters and Exchange Rate Disconnect,”American Economic Review, 104(7): 1942-1978.

- [3] Antràs, Pol, Davin Chor, Thibault Fally, and Russell Hillberry (2012). “Measuring the Upstreamness of Production and Trade Flows.”American Economic Review Papers and Proceedings 102, no. 3: 412-416.

- [4] Antràs, Pol, and Davin Chor (2013). “Organizing the Global Value Chain.”Econometrica 81, no. 6: 2127–2204.

- [5] Autor, David, David Dorn, and Gordon Hanson (2013). “The China Syndrome: Local Labor Market E¤ects of Import Competition in the United States,”American Economic Review 103, no. 6: 2121-2168.

39
**Table 3.6c: Transition Matrices for the Recovery Period**

||||Secondqua<br>|rter 2010<br>||
|---|---|---|---|---|---|
||Inactive or|Inactive<br>|Employed<br>|Unemployed<br>|Total<br>|
||out|26,533,723|6,482,882|944,029|**33,960,634**|
|Second quarter 2009|Employed|5,423,962|36,760,882|1,159,437|**43,344,281**|
||Unemployed|574,547|1,408,068|382,459|**2,365,074**|
||Total|**32,532,232**|**44,651,832**|**2,485,925**|**79,669,989**|

**Source: Own estimates using rotating panels from ENOE.**

Therefore, even though the recovery seems to be creating more jobs, there is also more persistence in the recovery period in the three categories: that is, more people remain as inactive, employed, or unemployed.

_An econometric analysis of transition probabilities_ The previous section described probabilities of transition from one employment status to another. However, these probabilities do not indicate the effect that a particular characteristic, such as age or education, has upon the likelihood of moving from one status to another. The effect of a single characteristic upon employment transitions is known as conditional probability. It is called so because it defines the effect of having one characteristic instead of another (for example, being a woman) upon a particular employment transition (for example, finding a job), under the condition that all the other characteristics (age, education, and so forth) remain the same. Conditional probabilities are of analytical interest because they indicate whether certain traits involve propensities to lose or gain employment. This kind of probability is computed through an econometric technique using the same panel data described in the previous section.<sup>7</sup> Estimates for the conditional probabilities of becoming jobless before, during the recession and the recovery are shown in table 3.7. The table shows evidence about five main messages. First, males always had a lower probability of losing a job, rather than keeping a job, than females, but this advantage became larger during the recovery. Males were 2.9 percent less likely to become jobless, rather than keeping a job, than observationally equivalent females during the recovery, compared with 1.3 percent during the recession or 1.55 before the recession.

7 The conditional probabilities presented in this section were estimated through a multinomial logit model. The model estimated the transition probabilities of four possible states between two periods: staying in a job, staying jobless, finding a job, and losing a job. The base category is keeping a job; thus all the interpretations have to be made with respect to this category. The estimation made use of rotating panels from ENOE for the second quarters of 2008-2009 and 2009-2010, for individuals aged 18 to 65. Further details about the estimation procedures are available from the authors upon request.

23
# **References**

<mark>Global Coalition to End Child Poverty (2023) Are countries committed to ending child poverty by 2030? A review of VNR reports from 2017 to 2022</mark> Global Coalition to End Child Poverty (2022) <mark>Ending Child Poverty: A Policy Agenda</mark> ILO and UNICEF. 2023. More than a billion reasons: The urgent need to build universal social protection for children. Second ILO–UNICEF Joint Report on Social Protection for Children. Geneva and New York.

Munoz Boudet, Ana Maria; Buitrago, Paola; Leroy De La Briere, Benedicte; Newhouse, David Locke; Rubiano Matulevich, Eliana Carolina; Scott, Kinnon; Suarez Becerra, Pablo. 2018. Gender differences in poverty and household composition through the life-cycle: a global perspective (English). Policy Research working paper; no. WPS 8360. Washington, D.C. : World Bank Group Newhouse, David, Pablo Suárez Becerra, and Martin Evans. New global estimates of child poverty and their sensitivity to alternative equivalence scales. Economics Letters 157 (2017): 125-128.

<mark>Silwal, Ani Rudra; Engilbertsdottir, Solrun; Cuesta Leiva, Jose Antonio; Newhouse, David Locke; Stewart, David.</mark> _<mark>Global Estimate of Children in Monetary Poverty: An Update (English).</mark>_ <mark>Poverty and Equity discussion</mark> paper Washington, D.C.: World Bank Group.

<mark>UNICEF Innocenti – Global Office of Research and Foresight (2023). Too Little, Too Late. An assessment of public spending on children by age in 84 countries.</mark> World Bank. Poverty and Shared Prosperity 2022: Correcting Course. Washington, DC: World Bank. doi:10.1596/978-1-4648-1893-6. License: Creative Commons Attribution CC BY 3.0 IGO World Bank, UNICEF 2022. The Impact of COVID-19 on the Welfare of Households with Children. Washington, DC: World Bank. License: Creative Commons Attribution CC BY 3.0 IGO.

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Futures Series Working Papers). https://www.undp.org/publications/mitigating-poverty-globalestimates-impact-income-support-during-pandemic Garrote Sanchez, D., Gomez Parra, N., Ozden, C., Rijkers, B., Viollaz, M., & Winkler, H. (2021). Who on Earth Can Work from Home? _The World Bank Research Observer_ , _36_ (1), 67–100. https://doi.org/10.1093/wbro/lkab002 Gentilini, U., Almenfi, M., Blomquist, J., Dale, P., De, L., Giuffra, F., Desai, V., Fontenez, M. B., Galicia, G., Lopez, V., Marin, G., Mujica, I. V., Newhouse, D., Palacios, R., Quiroz, A. P., Alas, C. R., Sabharwal, G., Weber, M., Acar, A., ... Grun, R. (2021). _Social Protection and Jobs Responses to COVID-19 : A Real-Time Review of Country Measures_ .

https://doi.org/https://openknowledge.worldbank.org/handle/10986/33635 Gerard, F., Imbert, C., & Orkin, K. (2020). Social protection response to the COVID-19 crisis: options for developing countries. _Oxford Review of Economic Policy_ , _36_ (Supplement_1), S281–S296. https://doi.org/10.1093/oxrep/graa026 Hanna, R., & Olken, B. A. (2018). Universal Basic Incomes versus Targeted Transfers: Anti-Poverty Programs in Developing Countries. _Journal of Economic Perspectives_ , _32_ (4), 201–226. https://doi.org/10.1257/jep.32.4.201 Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. _Journal of Economic Literature_ , _47_ (1), 5–86. https://doi.org/10.1257/jel.47.1.5 Londoño-Vélez, J., & Querubin, P. (2020). _The Impact of Emergency Cash Assistance in a Pandemic : Experimental Evidence from Colombia_ .

Lustig, N., Pabon, V. M., Sanz, F., Younger, S. D., & Younger, S. (2020). The Impact of COVID-19 Lockdowns Inequality, Poverty and Mobility. _Center for Global Development_ , _October 2020_ .

29
# APPENDIX. Average Prices and Volume in Monitored Outlets of 19 Commodities in 132 Russian Cities.

<!-- Start of picture text --> Average Prices, Beef<br>(December 1991 -- August 1992)<br>140-<br>1 20 ------.......... ....................................................................<br>...<br>1~~~~~~~~~~~~~~~~~~~~00f- ft<br>e ..f..............................................................................<br>40 . ................................. ...............................................................<br>0 I I I I I I I I I I I I I I I I I I I III I I I I I I<br>Dec91 01/28 02/11 02/25 03(31 04/14 04/32 05/12 0602 06/16 06&30 07/14 07/28 08/11 08/25<br>Date<br>| Market Price - State Price<br><!-- End of picture text -->

31
**Figure 9: Air Traffic Capacity by Type of Route Composition in million seats, % of total (2013)**

<!-- Start of picture text --> a. Small Island States b. Caribbean Hub Countries<br>2.6, 10.3%<br>1.3, 5.2%<br>0.9, 36.0%<br>1.6, 64.0%<br>21.6,<br>84.5%<br>Domestic CGF Extra-regional Domestic CGF Extra-regional<br>c. Continental Caribbean d. Fragile States (Haiti)<br>0.4, 18.5% 0.0, 2.2%<br>0.0, 0.3%<br>1.2, 60.7%<br>1.3, 97.5%<br>0.4, 20.8%<br>Domestic CGF Extra-regional Domestic CGF Extra-regional<br><!-- End of picture text --> _Source: Authors’ calculation based on data by Diio (2014)._

# _ii. Domestic Routes_

## <u>Overview</u>

Domestic traffic is becoming an increasingly important element in Caribbean connectivity, surpassing in importance the share originated by direct connections among Caribbean country pairs. It is a highly concentrated market, though. The top three domestic routes hold as much as 80 percent of total domestic traffic (and as much as 50% of the entire seat capacity for travel originated in Caribbean for withinCaribbean service).

Three countries concentrate over 90 percent of the total Caribbean domestic traffic, as follows: the interisland travel of The Bahamas (1.5 million seats, 50 percent), and Trinidad and Tobago (1 million, 30 percent); and internal connections within Belize (0.4 million, 13 percent). The network within The Bahamas is comprised of 23 airport pairs, with traffic between Freeport and Nassau, the top route, having over 236,000 seats. By comparison, the densest route between two island countries, Trinidad and Barbados, has 289,000 seats, and the second to most dense, Trinidad and Grenada, only 187,000 seats.

33
Dix-Carneiro and Kovak Trade Reform and Regional Dynamics Figure 15: Individual Average Months Formally Employed, by Sector - Tradable Sector Worker Sample - 1990-2009 <!-- Start of picture text --> 12<br>10<br>Tradable<br>8<br>6<br>4<br>2<br>0<br>1990  1991  1992  1993  1994  1995  1996  1997  1998  1999  2000  2001  2002  2003  2004  2005  2006  2007  2008  2009<br>-­‐2  Nontradable<br>-­‐4<br>-­‐6<br><!-- End of picture text --> Each point reflects an individual regression coefficient where the dependent variable is the average number of months per year formally employed in the tradable or nontradable sector from 1990 to the year listed on the x-axis, calculated using RAIS. For all years, the independent variable is the regional tariff change reflecting tariff changes from 1990-1995 (described in the text), with various controls (described in the text). Positive (negative) estimates imply fewer (more) average months formally employed in the relevant sector for workers initially employed in regions facing larger tariff declines. Vertical bar indicates that liberalization was complete in 1995. Dashed lines show 95 percent confidence intervals. Standard errors adjusted for 112 mesoregion clusters.

54
<mark>market participants expect the US Federal Reserve to embark on another form of quantitative easing of monetary policy during 2012 and beyond in order to ensure that the US economy can fully recover despite the prolonged and complex delivering process related to high debts of households and homeowners. Similarly, given slow pace of economic growth in many other advanced economies, Bank of England, the Bank of Japan, and the European Central Bank have expanded their unconventional monetary interventions or have signaled their intention to maintain near zero or very low interest rates over the next two years. Carmen Reinhart and co-authors</mark><sup>84</sup> <mark>have suggested that this is likely to continue: in effect, it is a form of financial repression that relieves the government of its debt burden. With sluggish real economic growth, negative real interest rates can be the “solution” for stabilizing or lowering debt to GDP ratios.</mark> <mark>Based on the 2008-11 experience, these highly accommodative monetary policies, through quantitative easing and exceptionally low interest rates, in the advanced economies are likely to set off another round of massive capital flows from the advanced economies into emerging economies and thereby causing credit, asset and commodity price bubbles, as well as pressures on exchange rates of capital receiving countries to appreciate. Moreover, the sovereign debt problems in Europe and geopolitical risks in the Middle East (with the possibility of a sharp rise in oil prices) are major downside risks to the already fragile economic outlook for the advanced economies.</mark>

**Figure 9:  Policy Rates of Reserve Currency Central Banks, annual average, 1999-2011, %**

<!-- Start of picture text --> 7<br>6<br>Fed<br>5 ECB<br>BoE<br>4<br>BoJ<br>3<br>2<br>1<br>0<br>1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011<br><!-- End of picture text --> Sources: US Federal Reserve, European Central Bank (ECB), Bank of England (BoE) and Bank of Japan (BoJ).

> 84 For a summary, see Reinhart, Kirkegaard and Sbrancia (2011), and more detailed analyses in Reinhart and Rogoff (2010) and Reinhart and Sbrancia (2011).

37
**a. Change in the likelihood of receiving benefits by consumption deciles of 2005**

<!-- Start of picture text --> Rural areas Urban areas<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>Consumption decile in 2005 Consumption decile in 2005<br>95% confidence intervals 95% confidence intervals<br>40 40<br>30 30<br>20 20<br>10 10<br>Change in the likelihood of receiving benefits<br>0 0<br><!-- End of picture text --> Source: IHDS, 2005 and 2012

# _4.3. Vulnerability_

Although poverty has fallen, the mean income (658 rupees) and median income (516 rupees) for 2005 are very close to the poverty line (446 rupees). This raises the question: how vulnerable are those escaping poverty to the risk of falling into poverty? To identify the vulnerable population we use a threshold that comes from Dang and Lanjouw (2015), who define a vulnerability threshold of 760 rupees (expressed in 2004-05 All India Rural Rupees) for India. By constructing synthetic panels using NSS data, they derive this threshold as one that yields a probability of 20 percent of falling into poverty conditional on household and demographic characteristics over the seven year period.<sup>23</sup> In our data, this threshold lies around the 76<sup>th</sup> percentile of consumption per-capita.

We plot the poverty line and the threshold on the kernel estimates of the distributions of consumption per-capita for 2005 and 2012 (Figure 10). As the poverty rate has fallen, the percentage of vulnerable individuals (those between the poverty line and vulnerability threshold) has increased slightly, from 36 percent to 38 percent. Of those who climbed out of poverty between 2005 and 2012, 64 percent remained below the vulnerability threshold; and among those who remained non-poor in 2012, 38 percent fell below the vulnerability threshold. In other words, many of those who have moved or stayed out of poverty are still vulnerable to falling into poverty.

> 23 See Dang and Lanjouw (2015) for further methodological details.

25
processes, with the production system organized as a pyramid-style subcontracting system. This pyramid style of production, which relies heavily on subcontractors, is well-suited to Japanese-style silverware production, in which a variety of silverware is produced in limited quantities.

Parent firms, which receive orders for final products from trading houses or which engage in the production of final products at their own risk, consign several processes to the first-tier subcontractors, which in turn consign some processes to the second-tier subcontractors. First-tier subcontractors are generally engaged in such processes as shearing, rolling and other activities except for polishing. Second-tier subcontractors mainly specialize in polishing. The relationship among the parent firms, first-tier subcontractors, and second-tier subcontractors is quite flexible, since subcontracting arrangements are not formulated on an exclusive one-to-one basis.

The silverware and housewares industries had 148 and 127 parent firms, respectively, in 1991, according to statistics reported by the city office (Table 114). There were 182 and 265 first-tier subcontractors, respectively, plus 1014 second-tier subcontractors, who specialize in polishing for both silverware and housewares. Parent firms often undertake subcontracting business for other paient or trading firms. Parerrt firms ral-,ge in size from small firms with only one employee to medium-sized firms with more than one hundred employees, while first and second-tier subcontractors on average employ less than ten people.<sup>19</sup> Parent firms purchase inputs (such as stainless steel from metal producers) and inspect finished products. Since the quality of silverware depends largely on the quality of materials, silverware producers, especially the large ones, actively engage in the development of new materials. Smaller silverware manufacturers generally purchase materials from trading houses.

"'The following numbers indicate the importance of subcontracting in the silverware industry. In 1990 as many as 41.5 percent of the firrns in the industry consigned work to **other** firms; for medium-sized firms with 20 or more employees, 96.2 percent had such arrangements **ISman** and Medium Enterprise Agency **[19901.** pp. 58-59). The share of all firms engaged in subcontracting was 68.9 percent, while the **corresponding** share for firms with less than 20 employees was higher at 74.3 percent.

9
||Positive Behavioral<br>Expectations|2.1 The teacher sets clear behavioral<br>expectations for classroom activities and/or<br>routines|
|---|---|---|
||Facilitation of Learning|3.3 The teacher makes connections during the<br>day that relate to other concepts or children’s<br>daily lives|
|**Guided**<br>**Learning**|Checks for Understanding|4.3 The teacher adjusts teaching to the level of<br>the children|
||Feedback|5.1 The teacher provides specific comments or<br>prompts that help clarify children’s<br>misunderstandings|
||Critical Thinking|6.3 The children ask open-ended questions or<br>perform thinking tasks|
||Autonomy|7.3 Children volunteer to participate in the<br>classroom|
|**Socioemotional**<br>**Skills**|Perseverance|8.2 The teacher responds positively to children's<br>challenges|
||Social & Collaborative<br>Skills|9.2 Children collaborate with one another<br>through peer interaction|

# **_Reliability of Tools_**

The Cronbach’s alpha of the domains and overall scores for the AIM-ECD and Teach ECE are shown below in **Table 6** . Overall, the AIM-ECD demonstrates superb reliability with an overall alpha of 0.978 and excellent reliability for each domain. Overall Teach ECE segment scores were very good with a Cronbach’s alpha of 0.884, but individual domains were lower—while Guided learning demonstrated very good reliability (0.820), Socio-Emotional Skills was acceptable (0.771) and Classroom Culture was questionable/fair (0.651). These figures are similar, and slightly better, than reliabilities from a review of international Teach ECE data (Ding et al., 2023, 2024).

_Table 6. Cronbach’s Alpha of AIM-ECD Domain and Teach ECE Areas_

|**Tool**|**Domain/Area**|**Cronbach’s Alpha**|
|---|---|---|
|**AIM-ECD DA**|Early Literacy|0.938|
||Early Numeracy|0.964|
||Executive Functioning|0.943|
||Social Emotional|0.951|

12