rafmacalaba/datause-encoder-data huggingface dataset:
3 Thorn and Vincent-Lancrin (2022) report that performance on the French national exams during the pandemic was similar to or even exceeded performance in 2019. Thus, e=0 is unrealistic. Thorn and Vincent-Lancrin (2022) find that, in studies for the US and UK, learning is somewhat hampered but not to the degree observed in the other studies. More generally, Donnelly and Patrinos (2021) explain that seven studies found evidence of student learning loss in developed countries, although developed countries are the countries where distance learning is likely to be the most efficient. We conclude conservatively that online instruction is imperfectly effective.

**School Closure Data.** UNESCO (2021) classifies school days as: (i) _open_ ; (ii) _closed_ (in which case remote learning options are almost always offered); or (iii) _partially open_ . According to their methodological note, _partially open schools_ are schools that are: “ _(a) open/closed in certain regions only; and/or (b) open/closed for some grade levels/age groups only; and/or (c) open but with reduced in-person class time, combined with distance learning (hybrid approach)_ ”. As there is limited information on which situation prevailed in the aggregate in each country in each year, i.e. (a), (b) or (c), we assume a hybrid system where half the students are present and half are online.

In the data, U.S. schools are coded as _partially open_ throughout the period since March 2020. Between March and May 2020, most schools were online. During the 202021 school year, hybrid learning dominated. At the beginning of the 2021-22 school year, many schools went online within a few weeks of opening due to COVID-19 outbreaks. While most schools are now fully open, the Omicron variant threatens to shift schools to online again.<sup>4</sup> Therefore, we believe that assuming a hybrid system in the case of partially open schools makes sense for developed countries.

# **D Calibration: Defining the Pandemic: Employment Shock**

**Severity.** We examine an increase in overall unemployment rates in the range of zero to 10 percentage points. This is achieved by varying _x_ between 0 and the value that leads to overall unemployment increasing by 10 percentage points in each economy. We arrive at this range for the following reasons. Note that the objective is to capture lost learning from work experience. Learning from work was lost in several ways.

One was that unemployment increased. Another was that labor force participation decreased. For example, for the U.S., the Pew Research Center computes an adjusted unemployment rate that counts workers who were not in the labor force based on two variables compared with the same month in the previous year - the participation rate and the number listed as “employed but absent for other reasons”.<sup>5</sup> While the official

> 4See www.edweek.org/leadership/a-year-of-covid-19-what-it-looked-like-for-schools/2021/03 and www.washingtonpost.com/world/2022/01/07/global-school-closures-omicron/, last checked 01-15-22. 5See www.pewresearch.org/fact-tank/2021/04/14/u-s-labor-market-inches-back-from-the-covid-19-
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Brixi, Hana Polackova, Ellen Marie Lust, and Michael Woolcock. 2015. _Trust, Voice, and Incentives: Learning from Local Success Stories in Service Delivery in the Middle East and North Africa_ . Washington, DC: World Bank.

Brown, D.S. and Mobarak, A.M., 2009. The transforming power of democracy: regime type and the distribution of electricity. _American Political Science Review_ , _103_ (2), pp.193-213.

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48
profits. However, if there is a significant fixed cost to any particular exporter pursuing a WTO dispute as a complainant, then within the set of all exporters of a disputed product to the respondent, we might expect higher-priced exporters to have the greatest capacity to take the lead in initiating WTO disputes, ceteris paribus. While the approach does not control for other important factors, there is no evidence of this in the data. If anything, the differences between the complainant, third party, and nonparticipant average price levels are _larger_ in global policy disputes than in partial policy disputes.

On the other hand, the result that the complainant has lower average export prices is not unexpected for partial policy disputes, though this is also likely due to policy endogeneity. Again consider WTO challenges to a respondent’s policy like antidumping, which makes up a considerable share of the partial policy sample of disputes. In these disputes, the respondent’s policy is deliberately applied against exporting countries whose import prices are too ‘low.’ And while the definition of low is typically made in relation to the exporter’s own sales in another market, it is also consistent with prices being low relative to other foreign export sources of those products (such as third parties and non-participants). Finally, for this subsample of ‘partial’ policy disputes, a further comparison of price changes between complainants and third parties would also need to address whether or not a particular country was excluded from the respondent’s policy application.

# **5. Conclusion**

This paper establishes a set of basic empirical facts on the product-level trade that is affected by the policies that trigger litigation under the WTO’s formal dispute settlement provisions. We construct a new data set that contains a mapping of WTO disputed policies to disaggregated trade data, and we use it to characterize the scope, levels, and changes to the trade values, market shares, volumes and prices of products that become subject to litigation.

Our most striking result is the wide variation of levels of affected trade and scope of targeted products across WTO disputes. Nevertheless, we also reveal sensible patterns in the trade data for the policies under dispute. For example, both high- and low-income complainants tend to suffer losses in foreign market access in the products under dispute once the data are scaled as market shares or in percentage terms. We also show the importance of addressing the differences between disputes challenging ‘global’ versus ‘partial’ policies, in terms of how the respondent’s policy treats noncomplainant trading partners. We find that, relative to partial policy disputes, global policies trigger smaller reductions in import values and volumes, and we even provide some weak evidence of larger 28
licenses. Draft laws and regulations have been prepared to implement the recommendations of the committee but have not yet been implemented as of mid-2007. In addition, restrictions on large scale outlets, shop opening hours and zoning restraints on business have been criticized as unnecessary burdens on business.

With respect to discriminatory restraints on foreign investors, Kenya requires that foreigners conduct business only in areas designated as general business areas. Local partners are encouraged, but not required. Expatriates employees are limited and the company must demonstrate that the skills are not available locally.

# **Ad Valorem Equivalence of Barriers to Foreign Direct Investment in Services Sectors.**

Estimates of the ad valorem equivalents of the regulatory barriers in services are key to the results. In order to make these estimates, we first commissioned a 54 page survey of the regulatory regimes in key Kenyan business services sectors, namely, insurance, banking, fixed line and mobile telecommunications services and maritime transportation services.<sup>14</sup> We supplemented this information based papers by: Kiptui (2007) on financial services; Ndaro (2007) or communication services; Helu (2007) on maritime services; Ochieng (2007) on transport services; and Oresi (2007) on railway services, all of which were presented at the conference on “Trade in Services” in Nairobi, Kenya on March 26, 27, 2007. The study by the World Bank (2007) provided additional detail on the key issues in the sectors and the Telecommunications Management Group (2007) provided extensive details in telecoms. Tarr (2007a, 2007b) summarized this information in his Kenyan policy notes on telecommunications and transportation.

Mircheva (2007) then estimated the ad valorem equivalents of barriers to foreign direct investment in fixed line and mobile telecommunications, banking, insurance and maritime transportation services. The process involved scoring a matrix of questions on the regulatory regimes in each sector to converting the information from the questionnaires and other sources into an index of restrictiveness in

> 14  We thank Ms. Sonal Sejpal of the law firm of Anjarwalla & Khanna Advocates for leading this research effort.

10
# Table of Contents

|Acknowledgments ......................................................................................................................................... 3|
|---|
|Introduction .................................................................................................................................................. 5|
|A. Balance Sheet Approach ‐ Joint Management of Assets and Liabilities ................................................... 7|
|1. Sovereign balance sheet ....................................................................................................................... 7|
|2. Rationale for the sovereign balance sheet ........................................................................................... 9|
|3. Coverage of Balance Sheet ................................................................................................................. 11|
|4. Assets and liabilities included on the sovereign balance sheet .......................................................... 12|
|5. Main issues related to the production of the sovereign balance sheet ............................................. 14|
|B. Framework to manage sovereign assets and liabilities .......................................................................... 16|
|1. Organizations responsible for managing assets and liabilities and their objectives .......................... 16|
|2. Risk management framework for assets and liabilities ...................................................................... 17|
|3. Reporting, performance evaluation and accountability ..................................................................... 18|
|C. Integration of asset and liability management considerations .............................................................. 21|
|1. Integrated framework for sovereign ALM .......................................................................................... 21|
|2. Governance arrangements supporting sovereign ALM ...................................................................... 25|
|3. Challenges and priorities of debt managers for sovereign ALM ......................................................... 27|
|Conclusion ................................................................................................................................................... 30|
|References .................................................................................................................................................. 32|
|Annex 1: List of respondent countries ........................................................................................................ 33|
|Annex 2: SALM Survey............................................................................................................................................35|

2
# **Table A9: Ordered Probit and Probit Regressions, 2006**

Financial Vulnerability Regressions (Marginal Effects)

|||**finburde**|**n**<br>|||**finvul**|||**arrea**|**rs1**<br>|
|---|---|---|---|---|---|---|---|---|---|---|
|**Country**|**mortgage**|**renter**|**Pseudo r**<sup>**2**</sup>|**t-test**|**mortgage**|**renter**|**Pseudo r**<sup>**2**</sup>|**t-test**|**mortgage**|**Pseudo r**<sup>**2**</sup>|
|_New EU Countries_|||||||||||
|Czech Republic|-0.0060 ***|0.0611|0.08|1.73 *|0.0101|0.0476 ***|0.17|-4.40 ***|-0.0293 ***|0.20|
|Estonia|-0.1187|-0.0445 ***|0.11|2.55 **|-0.0201 *|0.0218 *|0.12|-2.81 ***|-0.0469 ***|0.23|
|Hungary|0.0089 **|0.0097|0.07|2.23 **|0.0629 ***|0.0547 ***|0.11|0.43|-0.0323 *|0.09|
|Latvia|-0.0257|0.0393|0.08|1.08|0.0546 ***|0.0881 ***|0.11|-1.47|-0.0071|0.13|
|Lithuania|-0.0131 *|-0.0605 **|0.09|2.98 ***|0.0550|0.0223|0.10|0.60|0.0334|0.19|
|Poland|-0.1033|0.0861 ***|0.07|-1.43|0.0528 *|0.0464 ***|0.10|0.11|-0.0914 ***|0.10|
|Slovak Republic|-0.0033 *|0.0221|0.06|0.58|0.0520 ***|0.0917 ***|0.08|-1.53|-0.0260 **|0.09|
|Slovenia|0.1041 ***|0.0282|0.05|3.01 ***|0.0237|0.0351 ***|0.08|-0.41|-0.1353 ***|0.12|
|_EU-15 and Cyprus_|||||||||||
|Austria|0.0521 ***|-0.0137|0.05|5.29 ***|0.0169 **|0.0218 ***|0.20|-1.76 *|-0.0003|0.15|
|Belgium|-0.0133 ***|0.0971 ***|0.04|3.57 ***|0.0357 ***|0.0647 ***|0.18|-2.90 ***|-0.0153 **|0.14|
|Cyprus|0.1031 ***|-0.0289|0.09|5.73 ***|0.0979 ***|0.0349 *|0.11|2.52 **|0.1168 ***|0.13|
|Denmark|-0.0759||0.08||-0.0479 ***||0.17||-0.0101 **|0.16|
|Finland|0.0326 ***|0.0691 ***|0.05|2.02 **|0.0673 ***|0.1313 ***|0.19|-5.18 ***|-0.0470 ***|0.14|
|France|-0.0216 ***|0.0622 ***|0.04|0.54|0.0198 **|0.0822 ***|0.16|-7.33 ***|-0.0530 ***|0.12|
|Greece|-0.1043|0.0900 ***|0.08|-1.94 *|-0.1322 ***|0.0971 ***|0.15|-6.61 ***||0.20|
|Ireland|-0.0105 ***|0.2213 ***|0.10|-0.75|0.0137|0.1002 ***|0.22|-5.04 ***|-0.0582 ***|0.18|
|Italy|0.1994 ***|0.0195 ***|0.06|16.04 ***|0.0755 ***|0.0960 ***|0.12|-2.48 **|-0.0600 ***|0.09|
|Luxembourg|0.0423 ***|0.0651|0.07|2.71 ***|-0.0182 ***|0.0088|0.18|-3.73 ***|-0.0123 **|0.24|
|Netherlands|-0.1015 ***||0.05||-0.0459 ***||0.13||-0.0324 ***|0.14|
|Portugal|0.0564 ***|0.0416 ***|0.09|4.76 ***|0.0276 **|0.0094|0.06|1.46|0.0232 **|0.09|
|Spain|0.0746 ***|-0.0077|0.05|5.27 ***|0.0525 ***|0.0641 ***|0.09|-0.38|-0.0175 *|0.08|
|Sweden|-0.1002 ***|0.1002|0.05||-0.0822 ***||0.12||-0.0384 ***|0.14|
|United Kingdom|0.0054 ***|0.1043 ***|0.05|-0.07|0.0282 ***|0.1066 ***|0.20|-9.72 ***|-0.0650 ***|0.16|

Note: ***, **, * denote significance at the 99%, 95% and 90% levels respectively.

47
import concentration is a novel channel through which the curse materializes. An exciting avenue for future research would exploit data on prices, domestic consumption, and market concentration to estimate demand and evaluate the consequences of import monopolization for consumer welfare.

# 6 Concluding remarks

This paper identifies a novel channel for the ‘resource curse’: the monopolization of imports. Commodity export intensity is associated with more concentrated import markets, which can account for the higher price levels typically attributed to the Dutch disease. Trade policy measures and tariff evasion are mechanisms contributing to import market concentration.

While economies’ export orientation has been the focus of the trade and development literature, the role of imports and import market structure has been overlooked. Openness to imports is generally thought to increase competition in an economy, but this effect could attenuate severely in the presence of importer market power. Further research could explore which domestic value chains can emerge from more competitive import markets, especially in commodity export intensive economies.

Given the size of the import sector in developing countries, the policy agenda to demonopolize imports is paramount. Direct policy interventions to increase import competition include reforms that lower tariffs and remove NTMs such as quotas that restrict entry. The creation or strengthening of credible independent local bodies will help promote competition in general and in the import sector in particular. Fighting anti-competitive practices can prevent the perpetuation of oligarchies who constitute an important lobby and can seize control of liberalization attempts. Another integral part of a competition agenda is transparency and data availability. In many countries, barriers to entry into the import sector like licenses and the exact role of state-owned enterprises are not easily measured. The flow of funds between public banks and other state-owned enterprises is opaque and leads to 20
# **1. Introduction**

One of the most hotly debated policy questions with respect to the 2008 global crisis is how to stimulate business recovery. Because the crisis started in and severely affected the financial sector, the conventional assumption is that the recovery of the financial sector is a precondition to recovery in the corporate sector. While this conjecture appears reasonable, it has been challenged by observers in numerous crises across the world in recent years, in which real sector recovery preceded that of the financial sector (e.g. Calvo, Izquierdo, and Talvi, 2006a, 2006b; Claessens, Kose, and Terrones, 2009; Abiad, Dell’Aricia, and Li, 2011). Of particular interest are episodes characterized by Calvo et al. (2006a) as Systemic Sudden Stops (3S episodes) where output declines are associated with sharp declines in the liquidity of a country’s financial sector. These credit-less recoveries where external credit collapses with output but fails to recover as output bounces back to full recovery have been termed “Phoenix Miracles”.

Empirically, 3S episodes offer an unusual natural experiment since they provide an opportunity to observe how firms are affected in economies which have been subjected to a financial shock, which precedes or is contemporaneous with a recession. To date there has been little evidence at the firm-level on how corporations respond to crises in general. In 3-S episodes, in particular, it is not known whether the proposed mechanism in Calvo et al. (2006b) actually drives recovery in the corporate sector or whether firms register a recovery in sales and corporate activity preceding a recovery in external financing after a crisis.

The theory of Phoenix Miracles call into question many of the policies advanced to solve the 2008 US financial crisis since researchers have identified similarities between the US crisis and prior emerging market crises (e.g. Boone and Johnson, 2008; Krugman, 2009). Calvo and Kung (2010) label the US recovery as a new Phoenix Miracle while noting parallels between the US and past emerging market episodes. By contrast, Campello, Graham, Giambona, and Harvey (2011) and Campello, Graham, and Harvey (2010) use survey data to conclude that the US financial crisis limited but mostly did not preclude access to credit lines.

In this paper, we use a database of listed firms in emerging markets to analyze the recovery process after a financing crisis. Specifically, we ask whether recovery of the financial 2
for a given country is done in consultation with the government and most PA’s can claim government ownership. Most low-income countries have also done _Poverty Reduction Strategy Papers_ (PRSP’s). A PRSP is actually done by the government, though often with some financial support from aid donors. A large share of the work on either a PA or (though less so) a PRSP typically goes into the poverty measurement aspects (including poverty profiles). Both a PA and PRSP will typically lay out what is known about poverty in each country (the poverty profile as well as the aggregate poverty statistics and how they have changed over time). The PA’s and PRSP’s are clearly an important source of information on the accepted national poverty lines in developing countries (though they are confined to developing countries).

For the purpose of this paper we compiled a new data set of 88 national poverty lines from the most recent PA’s, PRSP’s and other sources over 1990-2005. The Appendix (Table A1) provides details. (In no case do the sources overlap with RDV.) In the source documents, each poverty line is given in the prices for a specific survey year (for which the subsequent poverty measures are calculated). In about three-quarters of the sample observations the poverty line was calculated from the same survey; in other cases (such as India) a pre-existing national poverty line was updated using the consumer price index.

The fact that the PA is a World Bank report raises two concerns. Firstly, it might be conjectured that these are external poverty liens, rather than poverty lines that are accepted by each country, thus raising a doubt about their interpretation as SSPL. However, the process of producing a PA entails (often extensive) consultation with the government of that country, including discussion is about the most appropriate poverty line. Thus, this new set of poverty lines has a stronger claim to be national poverty lines than those used by RDV, which were largely based on academic studies.

Second, it might be thought that the poverty lines that World Bank reports and PRSP’s use might be biased toward the Bank’s international poverty line. This is not a serious concern in our view. The PA’s (and PRSP’s) typically either use a pre-existing national poverty line or derive a new line, and in both cases the line has no obvious origins in the Bank’s “$1 a day” poverty line. Their aim is to use a poverty line appropriate to that country. In 80% of cases, some version of the “cost of basic needs” method has been used.<sup>14</sup> By this method, the food component of the poverty line is the expenditure needed to reach a food bundle, specific to each

> 14 This method, and alternatives, are discussed in detail in Ravallion (1994, 2008a).

7