rafmacalaba/data-use-mentions-extended huggingface dataset:
Over the past three or four decades, the Arab world has experienced a massive expansion in educational attainment. According to the Barro and Lee educational attainment dataset, seven out of the top 20 countries in terms of increase in number of years of schooling from 1980 to 2010 were Arab countries (Barro and Lee 2013).<sup>1</sup> Jordan, the subject of this paper, had the seventh highest increase in educational attainment in the world, with an increase of about five years in the average years of schooling over the period. This increase is widely believed to be attributable to a massive public investment in the supply of schooling in the postindependence period in the context of a state-led development model, which virtually guaranteed employment in the public sector for graduates (Assaad 2014; Saleh 2016). The rapid increase in educational attainment has continued unabated despite the fall in returns to education that accompanied the demise in the state-led model and its employment guarantee schemes (Pritchett 2001). A slew of recent literature on the drivers of the Arab Spring protests, some of which occurred in Jordan, has identified the low economic returns to this massive increase in education as the single most important cause of the uprisings (Goldstone 2011; Campante and Chor 2012a, 2012b, 2014; Sanborn and Thyne 2014).

Another way to view the connection between low return on education and youth frustrations is that the rapid intergenerational mobility in education has failed to yield similar mobility in either income or social status. This delinking between educational and occupational mobility has been documented for Egypt by Binzel and Carvalho (2013). While there is no similar work on Jordan, this article contributes to this agenda by documenting the first step in this process, which is the link between public investment in schooling and the educational mobility across generations.

> 1. This is based on version 2.0 of the Barro-Lee dataset for educational attainment among the total population 15 and older.

2
political parties to mobilize their constituencies along ethnic lines. These patterns remained resilient in the post-conflict environment with the APC party strongly associated with the Temne and Limba groups in the north and the west, while the SLPP is strongly associated with the Mende, Kissi and Sherbro groups in the south and east (Kandeh, 1992). This rigid ethnic make-up of the two main political parties implies that citizens’ views about local councillors’ trustworthiness might be driven by their ethnic membership and/or political allegiances regardless of the quality of services they receive.

Taking into account the salience of ethnic politics in Sierra Leone, we used the NPS self-reported data on ethnicity to identify whether the respondent belongs to the majority ethnic group. Following Glennerster, Miguel and Rothenberg (2010, 6-7), we then use the 2004 Census data to calculate the share of the total population size of an enumeration area that belongs to various ethnic groups. Using these shares, we calculate the standard ethno-linguistic fractionalization index (ELF). Figure 7 also shows that the level of ethnic

> 9We did not create an index out of these variables since factor analysis suggests that the questions about involvement in various organizations tap different behavioral concepts.

14
is important for the mechanism in the model.<sup>20</sup> I calibrate the process of simulated RERs to match those in the data (in the GE model in the online appendix RERs are driven by TFP shocks). For the US+10 country calibration, I estimate the variancecovariance matrix of the RERs of the same top 10 trade partners as in the empirical work. For the symmetric three-country model, I calibrate the RER process to match the correlation of the bilateral RER and competitors’ RERs of ≈ 0.4 (with equal RER variances) in the sample of countries and time period in the empirical component.<sup>21</sup>

**Elasticities** Two of the most important parameters to calibrate in the AB model are the within-sector (ρ) and between-sector (η) elasticities, because the gap between η and ρ determines the strength of the variable markup mechanism (in trade models with fixed markups η = ρ). I discipline the size of this gap based on evidence from Edmond, Midrigan and Xu (2015; henceforth EMX), who note that Equation 10 and Equation 11 imply a linear relationship between the inverse markup μ<sup>−</sup> ijk<sup>1and market share sijk, such that μ−</sup> ijk<sup>1= b0+b1s</sup> where b0 = (ρ − 1)/ρ and b1 = − �η<sup>−1</sup> − ρ<sup>−1�</sup> . EMX estimate b0 and b1 using Taiwanese manufacturing data and use the ratio<sup>ˆ</sup> b1/<sup>ˆ</sup> b0 = −0.78 which pins down a tight relationship of η = [ρ<sup>−1</sup> + 0.78(ρ − 1)/ρ]<sup>−1</sup> . I
|0.415*|-0.025|-0.203*|-0.186*|
||(0.206)|(0.014)|(0.101)|(0.092)|
|Green management ECA|-0.313***|-0.073***|0.072***|0.315***|
||(0.037)|(0.009)|(0.009)|(0.037)|
|Green management MENA|-0.398***|0.024***|0.195***|0.179***|
||(0.054)|(0.006)|(0.025)|(0.025)|
|Observations||17,|902||
|Clusters||3,|022||

Note: This table shows the average marginal effect estimates of credit constraints and green management on the number of green investments, based on ordered logistic IV regression with the categories based on the number of green investments as a dependent variable. Regression controls for the locality-level credit market controls (log local banks’ average asset size in a 15km radius and the number of bank branches in a 15km radius); indicators for no firms in other sectors in a 15km radius with data on credit constraints and green management; population size class; and region and sector fixed effects. In Panel B, estimated coefficients for all firm-level covariates as well as log local banks’ average asset size in a 15km radius and the number of bank branches in a 15km radius are allowed to vary by region. Table 4 provides the first stage of the IV regressions. Locality-clustered bootstrapped standard errors in parentheses. ***, **, * - statistically significant at 1%, 5%, and 10%, respectively.

Source: Enterprise Surveys
11 receipt of severance pay among eligible employees across firm ownership, however, in the Sakernas (2008) survey. Generally, eligible employees who received severance pay steadily increases with the wage level in both surveys.

While only a limited number of job separators actually received severance pay, those who did were generally satisfied with their payment. Only the IFLS (2007) survey specifically addresses employee satisfaction with respect to severance pay. Of the four levels of satisfaction identified in the survey, 68.6 percent stated that they were either very satisfied or satisfied with their compensation while only 28.9 percent indicated they were dissatisfied and just 2.5 percent stated that they were very dissatisfied with the severance pay they received.

On the first aspect of non-compliance, the proportion of eligible formal sector employees who receive a payment, two-thirds of all eligible employees who separated from a job did not receive their severance payment. The second aspect is the proportion of the entitlement amount that is actually received. It is to this aspect that we now turn. The conclusion we draw from the survey data is that employers who make a severance payment actually pay less than the amount to which their employees are entitled.

Table 3 shows the amount of legally entitled severance pay and actual payments by a set of employee and job characteristics. These calculations are based on weighted data from the IFLS (2007) survey. The mean monthly wage among recipients was 968,892 IDR; the severance entitlement amounted to 9,361,576 IDRs of which about 40 percent had actually been received to date (3,607,587 IRDs). Part of both totals, however, could be associated with long-service compensation as well as severance pay.

The average amount actually received by women and men as a proportion of the legal entitlement is nearly identical: 0.3937 and 0.3816, respectively. Both legally entitled severance pay amounts and actual severance pay received increases with age. The proportion of actual receipt to the legally entitled severance pay ranges from 0
>4 .45<br>.4<br>3.9<br>.35<br>3.8 Job Satisfaction<br>Hours Worked (log) .3<br>3.7 .25<br>3.6 .2<br>.64 .5<br>.62<br>.45<br>.6<br>.58 .4<br>.56 .35<br>Self-Employed<br>.54<br>Reservation Wage (log) .3<br>.52<br>.5 .25<br><!-- End of picture text --> _Notes:_ Each graph depicts the bias-corrected estimator 200 days around June 8, 2018, when the RAMV census closed, and the mean squared error (MSERD) optimal bandwidths. Confidence intervals are at the 95% significance level.

70
and local governments in Uzbekistan provided substantial support to teachers and students during COVID-induced school closures. This support could be one of the reasons why students in Uzbekistan did not experience substantial learning losses, at least in mathematics in basic education, in contrast to learning losses observed in other countries.

Besides government efforts, parents in Uzbekistan engaged significantly with their children to ensure continuity in learning. The recent PIRLS 2021 (Mullis et al. 2021) results provide additional information about the role of parents during the pandemic. Interestingly, 57 percent of parents of attending students declare that they engaged in reading activities even before schools started –one of the highest shares among participating countries. Parents also provide other support, for example, books (83 percent compared to an international average of 71 percent) and online instruction or tutoring (65 of parents versus 50 percent). However, authorities in Uzbekistan were right to rely on television broadcasts for instruction since the country lags far behind others in providing digital devices and digitally-based learning activities.

Success with the distance education modality in Uzbekistan seems to be supported by international experience. Remote instruction through phone call tutorials, SMS messages, and other measures, were found to be effective in reducing learning loss during the pandemic in a five-country study of multiple scalable models (Angrist et al. 2023). Uzbekistan’s model is more like blended learning since the local teachers also participated. Using technology to individualize content to students or bolster teacher capacity to deliver lessons is promising. Blended teaching programs combine modern online teaching and traditional offline instruction by partially replacing or supplementing in-person instruction with remote lectures, such as live broadcasted lessons, pre-recorded lecture videos, and TV shows. Studies provide evidence suggesting a positive role of hybrid teaching programs in improving educational outcomes in underserved regions where local teachers may not fully master the subject matter they are expected to teach or may not have sufficient teaching skills to deliver effective lectures (Beg et al. 2019; Bettinger et al. 2020; Bianchi et al. 2022; Borghesan and
<br>per worker|IDN exports<br>per worker *<br>ICT|
||(1)|(2)|(3)|(4)|
|Global demand for foreign products|0.000259<br>(0.000)***|0.000264<br>(0.000)***|0.000226<br>(0.000126)*|-0.00002<br>(0.000)|
|Global demand for foreign products *|||0.000190|0.000240|
|Share of hhlds with computer|||(0.000463)|(0.000109)**|
|ICT at the province level|No|Yes|Yes|Yes|
|Province level controls|Yes|Yes|Yes|Yes|
|Province and year FE|Yes|Yes|Yes|Yes|
|Observations|165|165|165|165|
|R-squared|0.979|0.979|0.979|0.981|
|F-stat|10.66|11.03|5.75|4.06|

Source: Authors’ calculations based on Sakernas 2005-2010 and 2011-2015, Susenas 2005-2010 and 2011-2015, and UN Comtrade database 2005-2010.

Notes: OLS regressions. Indonesian exports per worker in thousands of USD at 2010 prices and global demand for foreign products in millions of USD at 2010 prices. ICT variable at the province level is the share of households with computer. Province controls include the age structure of the population, share of urban population, real GDP per capita, minimum wage level, gender and educational composition of employment. All models control for province and year fixed effects. Robust standard errors between parentheses clustered by province. ***, **, and * indicate significance at 1%, 5%, and 10% confidence levels, respectively.

27
_</sup>|-0.000|0.007<sup>_∗_</sup>|
|lnESTABLISH|0.028<sup>_∗∗∗_</sup>|0.016|0.034<sup>_∗∗∗_</sup>|
|lnGDPE|0.464<sup>_∗∗∗_</sup>|0.367|0.733<sup>_∗∗∗_</sup>|
|lnGDPI|0.030|0.115<sup>_∗_</sup>|-0.209<sup>_∗∗_</sup>|
|No. of Observations|632363|425766|201772|
|No. of Clusters|9003|5518|3441|
|_χ_<sup>2</sup>|34860.962|25055.355|16534.468|
|Prob _> χ_<sup>2</sup>|0.000|0.000|0.000|

_∗ ∗∗ ∗∗∗ p <_ 0 _._ 1, _p <_ 0 _._ 05, _p <_ 0 _._ 01. The dependent variable is _Pr_ ( _Survivaljist >_ 0) in all cases. All models include exporter, importer, industry and year fixed effects which are not reported. Standard errors are clustered by exporter-importer pair.

# **5.2 Evidence from cross-country firm-level data**

The results presented to this point have used disaggregated product-level data to study the trade effects of institutional quality. A potential drawback of the product-level data used so far is that they do not provide information on the actual number of exporting firms. More specifically, we have (for instance) used the number of 6-digit HS product groups traded within a 3-digit ISIC sector as a measure of the extensive margin of countries exports. This could potentially bias the
# **How Resilient Was Trade to COVID19?**<sup>*****</sup>

## **Maria Bas (University of Paris 1, CES)**

## **Ana Fernandes (World Bank)**

## **Caroline Paunov (OECD)**

**Keywords:** exports, vulnerability, resilience, COVID-19, shock, high-frequency data. **JEL codes:** F14, F61, D20.

* We thank Siddhesh Kaushik, Ganeshkumar Sathiyamoorthy, Mohammad Shahbazi, Sandra Topalovic and Maurice Nsabimana for helping us to access high-frequency trade data. We thank Roman Zarate Vasquez for obtaining data on road transportation times and Natalia Camelo, Bishakha Sharman, and Irene Iodice for excellent research assistance. Comments by Cristina Constantinescu and participants at the Paris-1 research-in-progress seminar (March 2021) and the Empirical Trade Online Seminar (ETOS) (April 2021) are gratefully acknowledged. This paper has benefited from support from the Umbrella Facility for Trade trust fund financed by the governments of the Netherlands, Norway, Sweden, Switzerland and the United Kingdom. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the OECD, the International Bank of Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the countries they represent. All errors are our responsibility.
centralized school registry compiling the information of all new students enrolled in EMS. Due to teachers’ limited availability to participate as tutors, the math tutoring could not start during the first semester, therefore displaying an even lower participation or attendance rate (very close to zero).

2. _The original project design did not include a communication strategy_ . There was a substantial level of confusion regarding the program’s objectives and content among principals, teachers and students. Lack of information about the program’s objective and limited familiarity with counselling and psychological support were quickly filled by stigma, labeling PODER as a program to help “problem students”. Stigmatization was a serious problem affecting attendance rates and the ultimate effects of the program.

3. _Use of out-of-school hours_ . The CBT workshops and math tutoring were planned to be held during out-of-school hours. This was particularly challenging for students who had to arrive earlier at school or stay longer since many of the students in our sample, especially those in the afternoon shift, combine school with work.

4. _Lack of incentives_ . The design of PODER was based on the voluntary participation of students and teachers. Lack of incentives combined with a strategy that rely on implementation during out-of-school hours was, perhaps, the single most important factor behind the low participation rates.

All these complex implementation challenges were compounded by the student-level randomization creating treatment and control groups within each school. This factor increased the role played by stigmatization and introduced further complications to the implementation of the Program, particularly in a large school setting. As it is shown in Figure 2, the take-up rates for the math tutoring were close to zero, therefore, _de facto_ , PODER consisted in a CBT-based intervention aimed at improving socio-emotional skills, improving math test scores and reducing school dropouts.

Despite the significantly low take up or compliance rates, the qualitative evidence presented in Cuevas and Silveyra (2018) shows that among those who had direct experience of the intervention there is a strong appropriation and willing to continue with the CBT-based workshops
window after the event.)

> 1 We used the first principal component of the 8 large industrial country real TB rates as a proxy for the world rate. '9 The model employed is equivalent to that of equation (1') in the next section below, with k1.

> 20 The criterion for a break was three forecast errors in four consecutive months each statistically significant at least the 1 per cent level. (A single data outlier in the level of interest rates could have triggered a break if the criterion had required only two significant forecast errors).

13
# **1. Introduction**

Sustained export growth is a major economic goal for most developing and developed economies. The link between strong export performance and strong growth performance is obvious in the case of China in the last two decades, following on the evidence for other East Asian economies in earlier decades. Following a shift in the theoretical trade literature to models where firm heterogeneity plays a critical role in shaping trade flows such as those of Melitz (2003) or Bernard, Eaton, Jensen, and Kortum (2003), a burgeoning empirical trade literature has explored the increased availability of very disaggregated exporter-level datasets from customs agencies and several stylized facts have been uncovered for multiple countries.<sup>1</sup> For example, studies such as Eaton, Eslava, Kugler, and Tybout (2008) for Colombia and Amador and Opromolla (2013) for Portugal document a tremendous degree of churning in export markets, with a large proportion of exporters in a given year not having exported in the previous year.<sup>2</sup> Understanding the micro-economic dynamics behind episodes of strong export growth can help to identify the types of policies that can promote export growth.

In this paper we examine the microeconomics behind the dramatic export boom experienced by Turkey from 2002 to 2008 as well as the underlying forces for the strong contraction ensuing from the 2008-2009 global financial crisis and for the recovery thereafter. Turkish exports grew by 265% between 2002 and 2008, a very strong export performance compared to the average for peers in the same income group (Brazil, China, Mexico, and South Africa) whose exports grew by only 212%. Interestingly, Turkey was much more negatively affected by the global financial crisis than its peers since its aggregate export growth between 2002 and 2011 was 279% while that of peers at the same income level was 294%.<sup>3</sup> This was also a period when Turkey’s exports experienced a structural shift away from traditional textiles and clothing towards
**APPENDIX 2- Variables Definitions and Data Sources.**

**(s/y)t** = private saving rate = (private savings/ GNDI)t

_private savings =_ gross national savings - public sector savings _gross national savings,_ Source: WB "World Savings Database" Rev. 3.00.

_public sector savings(1)_ for CHL, KOR, MEX, MYS, TUR - savings of the nonfinancial public sector (= consolidated central government + state and local governments + non financial public enterprises) computed as revenues minus consumption - Source: WB "World Savings Database" Rev. 3.00. (2) for IDN savings of the consolidated central government computed as revenues rninus consumption - Source: WB "World Savings Database" Rev. 3.00. (3) for Ghana - savings of the consolidated central government computed as buget surplus plus public investment - Source: Ghana-Quarterly Digest of Statistics (4) for Zimbabwe - savings of the consolidated central government computed as buget surplus plus public investment - Source: World Bank National Accounts + Easterly database.

_GNDI: GNP_ + External Transfers - Source: WB "World Savings Database" Rev. 3.00. yt = log of real per-capita income = ln(GNDI/ population*defl), _population:_ Source WB BESD database.

-, = inflation rate =Aln(deflt+j).

- _defl:_ implicit consumption price deflator year average- Source: WB "World Savings Database" Rev. 3.00.

rt = real interest rate = (1) for IDN, KOR, MYS rt = In (1+ it') - Aln(defl,+1<sup>) (2) for CHL,</sup> GHA, MEX, TUR, ZWE r, = 0.5(ln (1+ itd) + 0.5( ln (1+ it_ld)) - Aln(deflt+i)). _ia_ =
(2008): “Son Biased Sex Ratios in the US 2000 Census,” _Proceedings of the National Academy of Sciences of the United States of America_ , 105, 5681–5682.

- Ambrus, A., E. Field, and M. Torero (2010): “Muslim Family Law, Prenuptial Agreements, and the Emergence of Dowry in Bangladesh,” _Quarterly Journal of Economics_ , 125, 1349–1397.

- Anderson, S. (2003): “Why Dowry Payments Declined with Modernization in Europe but Are Rising in India,” _Journal of Political Economy_ , 111, 269–310.

- ——— (2007): “Why the Marriage Squeeze Cannot cause Dowry Inflation,” _Journal of Economic Theory_ , 137, 140–152.

- Anderson, S. and C. Bidner (2015): “Property Rights over Marital Transfers,” _The Quarterly Journal of Economics_ .

- Anukriti, S., S. Bhalotra, and H. Tam (2016): “On the Quantity and Quality of Girls: New Evidence on Abortion, Fertility, and Parental Investments,” _IZA Discussion Paper_ .

- Banerjee, A., E. Duflo, M. Ghatak, and J. Lafortune (2013): “Marry for What? Caste and Mate Selection in Modern India,” _American Economic Journal: Microeconomics_ , 5, 33–72.

- Becker, G. (1981): “A Treatise on the Family,” _Harvard University Press_ .

- Bhalotra, S., A. Chakravarty, and S. Gulesci (2016): “The Price of Gold: Dowry and Death in India,” _IZA Discussion Paper 9679_ .

- Bhalotra, S. and T. Cochrane (2010): “Where Have All the Young Girls Gone? Identification of Sex Selection in India,” _IZA Discussion Paper No. 5381_ .

- Bhalotra, S. and A. van Soest (2008): “Birth-Spacing, Fertility and Neonatal Mortality in India:
TT<sup>WW</sup> TT<sup>AA</sup> province-level information on the number of ISAF troops by the contributing nations and on the localization of Provincial Reconstruction Teams (PRTs). Placemat issues also include information on the number of Afghan National Army (ANA) troops and on ISAF and ANA major units. Although information on PRTs is systematically reported, information on ISAF major units at the provincial level is only available from 2011 onwards. Combat troops are measured per 1,000 inhabitants in the province. Foreign aid is proxied by development assistance commitments. The data come from the Development Assistance Database (DAD), the main publicly available source of information on development assistance DD in Afghanistan. Data are available by donor and sector, at the provincial level. They can be disaggregated 13