rafmacalaba/data-use-mentions-extended huggingface dataset:
**Decoupling and recoupling**

# **1. Introduction**

Emerging markets (EM) advocates often emphasize their newly gained resilience to external shocks. Resilience, however, can be interpreted in several ways. In particular, it is expected to manifest differently according to whether it refers to economic performance, market interdependence, or the link between markets and economic activity. In this paper, we revisit the debate surrounding the different varieties of EM decoupling to document the recent behavior (in both the pre-crisis bonanza and the turbulent crisis period) on these three fronts, discuss the economic factors underlying the specific patterns in each case, and draw market and policy implications from these findings.

In particular, we examine decoupling: (i) in the traditional sense, namely, business cycle synchronicity and sensitivity to the world economy (real decoupling); and (ii) as cross-market financial interdependence (financial decoupling), in the sense of the “betas” of EM credit, equity and currency returns to returns on the global market portfolio, as well as within-EM betas (a typical feature of the 1990s); Finally, we center the debate around EM financial integration to the world (as the deepening of financial capital inflows) and its impact on financial ties of EM assets to those in the developed world.

The discussion is centered on EM assets. More specifically, we look at a sample of countries that represents what is usually labeled as emerging markets in the financial industry, following the Morgan Stanly Capital Index benchmark (MSCI) for individual countries and groups of countries, and focus our analysis on equity and, to a lesser extent, currency and hard currency sovereign bonds. As a comparison group, we include in the study a sample of advanced markets detailed in the Appendix.

We find that: (i) on the real front, rather than actually decoupling from the world, EM have diversified away from the US and the euro zone into emerging Asia (through international trade and the growing economic importance
# **2.2.2 Fiscal Rules**

To prevent excessive spending and ensure fiscal sustainability in anticipation of the future diamond depletion, the government has, over time, set various fiscal rules, both formal and informal. First, the “Principle of Sustainable Budgeting” was introduced in 1994 with the intention of ensuring all mineral revenue to be invested productively or saved, and not used for consumption. This led to the construction of the Sustainable Budget Index (SBI), defined as the ratio of non-education, non-health recurrent expenditure to non-mining revenue. Although it is not a legal requirement, an SBI of no greater than unity is targeted in order to ensure non-investment expenditure to be financed by non-mineral revenue and conserve the country’s wealth.

Another fiscal “rule”, introduced in 2006 as part of the Mid-term Review of National Development Plan 9 (MTR NDP9), sets the maximum government expenditure at 40 percent of GDP, to be consistent with the projected medium-term government revenue. The MTR NDP9 (para. 68) also targeted increasing the share of development spending in the budget to 30 percent by 2008/09. Furthermore, under Section 20 of the Stock, Bonds and Treasury Bills Act (Chapter 56:07, 2005), the government’s total domestic debt and guarantees cannot exceed 20 percent of GDP. Similarly, the stock of government foreign debt and guarantees is limited to 20 percent of GDP.

Adherence to the fiscal rules has enjoyed mixed success. Although the SBI fell below unity immediately after its introduction in 1994/95, the effect has not been long-lasting (Figure 4); the SBI exceeded unity in 2001/02, when exceptionally high SACU revenue during 1999/00-2000/01 came to an end.<sup>9</sup> In 2003/04, however, the measures to raise domestic revenue, coupled with across the board cuts in all expenditures, resulted in a dramatic fall in the SBI. Nonetheless, some views that it was the
# **5.2     The impact of devaluation on the trade balance**<sup>**7**</sup>

This section empirically addresses the question of whether a real exchange rate depreciation will improve the balance of trade in Ethiopia (Haile, 2015a). The analysis is based on annual data for Ethiopia covering the period 1980-2013 and employs multi-equation time-series approach. A real devaluation could improve the balance of trade via increasing exports and discouraging imports. Currency depreciation should positively impact on exports of the country because they are more competitively priced than identical products from other countries, all else being equal. There is, however, no clear-cut theoretical relationship between movements in the exchange rate and the trade balance. The reason for this is that exports may not strongly respond to exchange rate changes while the value of imports may not significantly decline as the country now pays higher price for a given quantity of imports. This is nonetheless an empirical issue and should be settled based on thorough empirical analysis.

There are some preconditions that should be fulfilled for the benefits of a real devaluation to materialize. In particular, the well-known Marshall-Lerner (ML) condition must hold for a devaluation of the birr to improve the trade balance position of the country. The ML condition states that an exchange rate devaluation (or depreciation) will have favorable impacts on the balance of trade only if the responses of export and import demand to the devaluation-induced price changes are sufficiently strong. Technically speaking, the sum of export and import demand elasticities should be greater than one in absolute value. A real depreciation would lead to an increase in the quantity of exports and a decline in the quantity of imports, and thus have a net positive impact on the trade balance. Specifically, a depreciation renders the cost of foreign goods higher relative to the cost of domestic goods, which instigates foreign consumers to buy more of the country’s exports and domestic consumers to buy fewer imported goods, thereby resulting in a positive quantity effect on the balance of
# Discrimination Toward Migrants During Crises<sup>*</sup>

Marisol Rodr ́ıguez Chatruc<sup>†</sup> Sandra V. Rozo<sup>‡</sup>

**JEL Classification:** D72, F2, O15, R23

**Keywords:** migration, COVID-19, attitudes, priming, altruism

> *We thank the editor, Chris Parsons, the two anonymous reviewers, and Berk Ozler for useful suggestions. We are also grateful to Andr ́es Barinas, Tatiana Hiller Zapata, Camila Cort ́es, and Mar ́ıa Jos ́e Urbina for excellent research assistance. USC IRB approval UP-20-00479. This study is registered in the AEA RCT Registry with the unique identifying number: AEARCTR-0006182. The views in this paper are strictly those of the authors and should not be attributed to the Inter-American Development Bank or the World Bank, its executive directors, or its member countries. Rodr ́ıguez acknowledges funding from the Inter-American Development Bank. Rozo acknowledges financial support from the Research Support Budget at the World Bank.

> †Inter-American Development Bank, email: marisolro@iadb.org

> ‡Development Research Group, The World Bank, IZA, CEGA - University of California Berkeley, CESR - University of Southern California. email: sandrarozo@worldbank.org
This is an important advantage for the empirical analysis, as most of the evidence on intergenerational educational mobility in India and China currently available are based on data that suffer from truncation due to coresidency restrictions used to define household membership. Emran, Greene, and Shilpi (2018) summarize 13 studies on intergenerational educational mobility in developing countries, only two of which use data not affected by coresidency bias.<sup>28</sup> While Emran, Greene and Shilpi (2018) provide evidence of substantial downward bias (average 18 percent) in the IGRC estimate from the coresident sample in rural India, we are not aware of any similar estimate for rural China. In online appendix A, we provide evidence on the extent of coresidency bias in rural China in a widely used household survey: the Chinese Household Income Project (CHIP). In particular, we compare the estimates from the CFPS (without any sample truncation) with those from the CHIP 2002 for the overlapping age cohorts. The evidence shows that the IGRC estimate from the CHIP 2002 is 25 percent smaller because of truncation of the sample arising from coresidency restrictions (see Table A.2 in the online appendix). A comparison of CHIP 2002 with the CFPS is also of independent interest, because CHIP 1995 and 2002 have been used by many researchers to study intergenerational mobility in China.<sup>29</sup> For a more complete discussion, please see online appendix A.

We use the 1999 round of the REDS and the first round of the CFPS in 2010. From the REDS data, we obtain the relevant information for our analysis on all father-son pairs irrespective of residency status at the time of the survey. For the CFPS data, we restrict to rural communities subsample, given our focus on intergenerational mobility in rural areas, and use the family roster to obtain a complete list of father-son pairs that includes all sons of the household head irrespective of their residency status at the time of the survey.

The main samples for our analysis
35|-0.17|
|Uruguay|0.49|0.35|0.32|-0.17|
|Gabon|0.33|0.36|0.12|-0.20|
|N. Zealand|0.88|0.66|0.60|-0.29|
|Venezuela|0.78|0.55|0.34|-0.44|
|UAE|1.65|1.49|0.50|-1.15|
|Kuwait|3.02|0.71|0.41|-2.61|
|Qatar|3.18|1.55|0.56|-2.62|
|_Memo/_|||||
|_Saudi Arabia_<br>_Memo/_|_0.23_|**_0.71_**|_0.27_|_0.04_|

_Former Soviet Union/E. European countries with data only since 1990_

||_1990_|_2008_|_Change_|
|---|---|---|---|
|_Moldova_|_0.27_|_0.11_|_-0.15_|
|_Georgia_|_0.33_|_0.19_|_-0.14_|
|_Serbia/Montenegro/Kosovo_|_0.22_|_0.12_|_-0.10_|
|_Ukraine_|_0.26_|_0.16_|_-0.10_|

Source: Authors‘ calculations based on Maddison data.

In addition, many low-income countries are still trapped in poverty, and they are failing to achieve the MDGs. While the global headcount poverty MDG (MDG 1) is likely to be achieved, many countries remain off-track—in particular, countries in Sub-Saharan Africa are not likely to meet the MDG for halving headcount poverty (Figure 7(a) and (b)). In addition, 11
# **Employment in the Informal Sector**

12. Mongolia's official employment statistics reveal much about the changing size of the informal sector, despite the fact that they were not designed to capture informal sector employment. Ironically, it is for precisely this reason that they tell so much. After a brief review of the labor market and the sources of employment data, this section will argue that the official statistics mask a large increase in informal sector participation, and the argument will be supported using the results of the informal sector sample surveys. The sample surveys will then be combined with elements of the official employment data to estimate that 105,000 to 130,000 people are engaged in the informal sector in Ulaanbaatar.

### **Background on Employment Statistics in Mongolia**

13. Every _duureg/soum_<sup>_9_</sup> in Mongolia has an Employment Regulation Office'" (ERO) which serves two functions: (i) distribution of unemployment benefits to officially registered unemployed people who meet the criteria laid out in the relevant laws; and (ii) employment broker, attempting to match unemployed people with job openings. Under the new law on unemployment benefits, which went into effect on January 1, 1995, an unemployed person may be eligible to collect unemployment benefits after having paid contributions to the unemployment insurance fund for at least two years - the new law thus became fully operational on January 1, 1997, after the new law had been in effect for two years.

14. Under the previous law, those eligible for unemployment benefits could collect 3 months wages from their former employer, via the ERO. Under the new law, employers and employees each make
Duflo, E., Dupas, P. & Kremer, M. 2015. "School governance, teacher incentives, and pupil–teacher ratios: Experimental evidence from Kenyan primary schools," _Journal of Public Economics_ , Vol. 123(C), 92‐110.

The Economist. 2014. “China’s Economy: Poverty Elucidation Day.” Oct. 20, 2014.

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Edward, P. and Sumner, A. 2013. “The Future of Global Poverty in a Multi‐Speed World: New Estimates of Scale, Location, and Cost.” _King’s International Development Institute, King’s College London._ Ferreira et al. 2015. “A Global Count of the Extreme Poor in 2012: Data Issues, Methodology and Initial Results.” _World Bank,_ Policy Research Working Paper 7432.

Fiszbein, A. et al. 2009. _Conditional Cash Transfers: Reducing Present and Future Poverty._ Washington, DC: World Bank.

Gertler, P. et al. 2012. “Investing Cash Transfers to Raise Long‐Term Living Standards.” _American Economic Journal: Applied Economics,_ Vol. 4, No. 1, 164‐192.

Gill, I. and Kharas, H. 2007. _An East Asian Renaissance: Ideas for Economic Growth._ Washington, DC: World Bank.

Gilligan et al. 2009. “An Impact Evaluation of Ethiopia’s Productive Safety Net Program.” _Mimeo, International Food Policy Research Institute_ . Washington, DC.

Gockowski, J. 2012. “Policy‐led Intensification and Returns to Input Use among Ghanaian Cocoa Farmers.” _Sustainable Tree Crop Program of the International Institute of Tropical Agriculture._ Government of Ghana. 2013. “The Livelihood Empowerment Against Poverty (LEAP) Programme.” _Ministry of Gender, Children and Social Protection,_ Briefing Paper.

Greatrex H. et al. 2015. “
35

# **VIII. Lessons for GCC Countries**

This paper assesses the impact of foreign labor management policies on labor outcomes in Singapore and Malaysia, two countries characterized by robust economic growth and significant foreign labor. Are there lessons applicable to GCC countries, where foreign labor force shares ranging from 50 to 90 percent are much higher than in Singapore and Malaysia? Several conclusions emerge from this analysis. The first involves the fact that managing foreign labor not only requires immigration controls but also a conducive macroeconomic environment and mutually reinforcing labor market institutions regarding wage and employment policy, as well as a capacity to enforce immigration rules. As is demonstrated by Kuwait's recent experience, it is not enough to establish a stable macroeconomic climate with favorable investment incentives (necessary but not sufficient conditions).

Singapore and Malaysia benefit from more diversified economic structures relative to the oildependent GCC economies. Moreover, the,East Asian economies' private sectors have been integral to overall economic growth, especially with respect to manufactured exports that are competitive on international markets. Without comprehensive policies that address these related issues, measures to control foreign labor flows are likely to be ineffective. Policy changes must be considered within the context of the theory of second best; i.e. correcting one distortion will not necessarily lead to a welfare improvement if other distortions remain. In the Bahrain context of distorted public employment and pay policies, for example, it may take a large increase in the price of work permits to induce a significant shift in private employment toward Bahraini nationals. The solution to stem the influx of foreigners into GCC countries is complex; firm- or micro-level data on employment and wages would be useful in estimating labor demand elasticity in order to quantify the likely employment response to various policy measures.

It is notable that both Singapore and Malaysia face difficulties in setting the price and quantity of work permits in their highly regulated immigration systems where permit types vary according to nationality, skill level, and sector of employment, enforced with the help of high
.58|0.8|
|No. of elderly (age > 64)|0.31|0.6|
|Age (15-29)|0.36|0.48|
|Age (30-49)|0.4|0.49|
|Age (50-64)|0.16|0.36|
|Age (>64)|0.08|0.28|
|N(unweighted sample size)|4,770,735||

Source: Thai Labor Force Survey (1997 - 2005) Notes: N = unweighted sample size (individual respondents) for 32 quarters from 1997-2005. Mean and Std. Dev. are calculated using population weight given by the survey.
- Transfers: Evidence from the Supplemental Nutrition Assistance Program. _American Journal of Agricultural Economics 97_ (2), 390–404.

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- Butters, R. A., D. W. Sacks, and B. Seo (2020). How do national firms respond to local shocks? Evidence from excise taxes. Working Paper.

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- or underreporting for module 1 (14-day long list), depending on the food group. The relevant scatterplot in figure 2 suggests that the net overreporting error is greater for consumption items of relatively low value. As the benchmark value increases, the net error approaches zero and then turns negative at high-value items, signifying that the items largest in value suffer from underreporting. The same directional pattern is apparent for module 2 (7-day long list), on which each food group in table 5 displays net overreporting. Figure 2 suggests that particularly high relative errors are associated with foods with a consumption value below the median.

The usual month shows the same error gradient as the other two recall modules, although, here, the net error for most food items is negative (as is true of the food groups listed in table 5). The magnitude of this error rises with the benchmark consumption value, suggesting that the highest value consumption items are associated with the greatest degree of underreporting. This likely indicates that either recall error dominates in the value reporting in this module, or rule of thumb value reporting on the usual month induces negative errors that grow in magnitude with consumption value. Finally, for the diary modules, and in contrast to the three recall modules analyzed, there is little systematic reporting error with respect to value. Clearly, the bigger challenge with the household diaries is ensuring the recording of any consumption for some food groups (the incidence), rather than recording accurate consumption values conditional on incidence.

Besides consumption incidence and value, we investigate three other dimensions of the individual food goods: the frequency of market purchase, the share of consumption of home production, and whether the food is storable or perishable. Table 7 lists the mean proportional errors relative to the benchmark for these three characteristics for each of the five modules. Often any difference in mean error across each characteristic is not statistically significant, in part because the power of the test is relatively low: there are 14
summarizes the data on “net coverage” rates from the most recent household surveys, which refer to the proportion of individuals actually enrolled at the level that corresponds to their age, according to the structure of each country’s education system. In general, these rates are quite high in primary, but decline at LS and especially at US. For US, the highest rate is observed in Panama, where 53 percent of youth in the 15-17 age group is actually enrolled at this level. In Honduras and Guatemala, only 27 and 20 percent of this age group, respectively, are enrolled in US.

These results reveal that there are considerable numbers of US age youth in Central America who are still enrolled in school but overage, and not enrolled at the US level as would be expected. This is illustrated in Figure 11, were each country is compared to the average of Latin America, where at US age, 24 percent are already out of the schooling system, 6 percent are still attending primary, 37 percent are attending LS, and only 33 percent are actually attending US as expected. The only country in Central America with better indicators is Costa Rica, where overall enrollment is higher: only 17 percent are out of school, and the proportion of US age individuals actually attending the expected level is 40 percent—7 points above the Latin America average. Panama shows a similar rate of overage as the Latin America average, but has lower proportions out of school and enrolled in US. El Salvador shows a different picture. In this case, overage is lower (at 26 percent) and enrollment in US is higher (37 percent), but the proportion out of school (38 percent) is significantly above the Latin America average. Honduras, Guatemala, and Nicaragua show a

> 12 Data for Panama is not presented here, since the household survey does not allow identifying whether attendance is in public or private schools.

10
a wide coverage of countries over a log period of time. This data comes from the World Bank’s World Development Indicators (WDI).

# **3.2 Data on Trade Flows**

We collect data on bilateral trade flows from the Observatory of Economic Complexity (MIT). This database covers 215 countries over the period 1962-2014. The data are classified according the 4-digit Standard International Trade Classification (SITC), Revision 2. Only products and commodities are considered. Then, we aggregate these bilateral trade flows at the country-level.

To classify trade flows into final and intermediate goods, we use a concordance table from SITC Rev. 2 to Broad Economic Categories (BEC).<sup>4</sup> We then classify goods into five categories: primary, semi-finished goods, parts and components, capital goods, consumption goods, and a residual category called goods non-specified. We group these categories into intermediate and final goods as follows: intermediate goods are primary goods, semi-finished goods, parts and components; and final goods are consumption goods and capital goods.

# **3.3 Measures of GVC participation based on Value Added**

One of the main purposes in this paper is to identify production linkages between countries. Recent advances in data collection and theoretical decomposition of trade flows have shown the various ways of measuring GVC participation.<sup>5</sup> In this paper, we use the recent GVC indicators from Borin and Mancini (2019). They offer a new toolkit for value-added accounting of trade flows at the aggregate, bilateral, and sectoral levels that can be used to investigate a broad set of empirical questions—including in this case an assessment of the global inflation synchronization.

Based on this gross and value-added decomposition, we analyze the association between inflation co-movement and several indices of GVC participation and trade which are as described below.

> 4The concordance table from SITC Rev2 to BEC can be found on the UN Trade Statistics webpage: https://unstats.