rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 10621

# **Abstract**

This paper provides a detailed descriptive analysis of patterns of urbanization across Sub-Saharan Africa for the year circa 2015. Despite the rapidity and importance of Sub-Saharan Africa’s urbanization, little is known about the anatomy of patterns of urbanization across the region due to a lack of detailed and accurate official data on urban settlements and populations. To address this gap, the paper applies a modified version of the “dartboard” algorithm to high-resolution gridded population data for the region, which is derived from digitized maps of the footprints of all buildings in the region from very high-resolution satellite imagery. This allows for a consistent definition of urban areas across all countries in the region, overcoming the measurement problems that arise from relying on official definitions of urban areas, which vary markedly across countries. Using this definition, the paper presents evidence on key empirical regularities that are related to disparities across the urban hierarchies, such as the extent of urban primacy and Zipf’s law, as well as on the internal structures of cities, such as population density gradients and the number of centers that cities possess. The paper also analyzes how these characteristics are related to key country characteristics. Finally, the paper compares the results with those that arise from the use of an alternative definition of urban areas—the degree of urbanization.

This paper is a product of the Urban, Disaster Risk Management, Resilience and Land Global Practice and the Poverty and Equity Global Practice.. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at mroberts1@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
48 1993 to 9 percent in 1998. The largest increase occurred in parts with their share in EU-external imports of parts of chairs (82119) growing from 6 percent in 1993 to 50 percent in 1998 with the Czech Republic capturing 19 percent and Slovenia 16 percent of EU imports (Appendix Table 11).

Table 19: Trade in furniture, 1993 (A) and 1998 (B) (in **million** of US dollars and percent)

||Bulg|ari|aCze|chR.|Esto|nia|Hun|gar|y Latv|ia|Lith|uan|ia<br>Pola|nd|Rom|ani|a Slov|aki|a Slo|venia|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||<br>A<br>|<br>B|<br>A<br>|B|<br>A<br>|<br>B|<br>A<br>|<br>B|<br>A<br>B|<br>|<br>A<br>|<br>B|<br>A<br>|B|A|B|A<br>|B|A|B|
|Final products<br>exports|15|26|147|219|9|84|90|120|10|34|10|34|519|1,223|291|342|52|94|100|124|
|Partsexports|1|7|60|412|<br>3|31|38|151|<br>1|11|<br>1|13|77|287|11|45|<br>13|43|<br>93|343|
|<br>Partsimports|4|7|<br>34|150|<br>1|10|24|75|<br>1|5|<br>1|7|<br>35|126|<br>3|<br>10|<br>5|50|18|<br>54|
|Final exports<br>minus<br>parts|11|19|113|69|<br>8|74|66|45|<br>9|29|<br>9|27|484|1,097|287|332|46|44|83|70|
|imports<br>Final products<br>impons|20|21|94|123|3|34|93|114|<br>9|26|<br>9|22|85|<br>187|11|<br>36|17|36|22|110|
|Memo: shareo<br>percent)|F(in||||||||||||||||||||
|furniture<br>exports<br>in EU-<br>oriented<br>manufactur|2.2<br> <br>es|1.8|3.9|4.3|7.9|9.4|3.1|1.8|6.6|7.1|4.2|4.0|9.0|10.5|16.1|7.7|4.8|2.5|5.7|8.7|
|exports|||||||||||||||||||||
|Of final&parts<br>inimports from|1.8<br>|1.3|1.8|1.6|1.6|1.8|1.8|1.2|3.0|2.0|2.3|1.4|1.2|<br>1.2|0.6|0.7|1.4|1.5|1.1|2.6|
|EU<br>OverallBalanc<br>(US $ million)|e-8|5|<br>79|358|<br>8|71|11|82|<br>1|14|<br>1|18|476|1,197|287|341|42|51|153|303|

Source: derived from trade data as reported by the EU to the UN COMTRADE database.

Slower growth in imports of parts from the EU than in CEEC-10 exports of parts may indicate an ongoing process of switching from the assembly of furniture to also producing parts. While the growing involvement in production of parts affects each CEEC, some have moved faster in that direction. In terms of the change in share of furniture parts in exports of total furniture exports, this appears to be the case of the Czech Republic, Latvia and Romania. Parts account for the bulk of total 'furniture' exports from Slovenia (70%) and from the Czech Republic (63%).

Another indication of integration of CEEC-10 into the EU-furniture manufacturing and distribution is the values of RCA indices in exports and assembly. With the exception of Romania, other CEEC-10 have a 'double' comparative advantage at least in one 'part' category and two or more 'final product' categories (Appendix Table 12).

# 6. 'NETWORKS' AND OTHER PRODUCTION SHARING ARRANGEMENTS IN EU-CEEC TRADE

How large is trade between CEEC-10 and the EU that can be attributed to 'dividing up the value chain' of production? It seems that most of trade falling within networks, which mainly
- 16 -

origin.'<sup>7</sup> In other words, close to 90 percent of the exports of South Africa and Mauritius did not meet the rules of origin requirement.

Given the fact that the LBDCs will be subject to the same rules of origin in 2004, the above serves as a cautionary reminder about the likely effects for the poorer countries after 2004; in other words, export growth may be considerably muted for the LBDCs after 2004 as the rules of origin kick in.

Finally, it is interesting to compare the performance of SSA countries with those in the Caribbean which have received preferential access similar to AGOA. Data for 2001 indicates that about 55 percent of the apparel exports of Caribbean countries benefited from preferential access compared with 9-14 percent for Mauritius and South Africa. One reason that Caribbean countries found it profitable to import yam from the United States and avail themselves of the preferential access, a course that Mauritius and South Africa evidently found not to be profitable, appears to be the lower transport costs.

# VI. **OVERALL** ASSESSMENT AND CONCLUSIONS

AGOA's impact can be evaluated against two possible benchmarks. The first is current trade and the other is "what might have been"-that is, trade that would have resulted had all restrictions on SSA's exports been eliminated. Our estimate of what AGOA will entail for aggregate sub-Saharan African exports is presented in Table 14 below.

The fourth column of Table 14 presents our estimates of projected trade under AGOA. We would note two important caveats here. First, our estimates are sensitive to the supply capacity of SSA, which we capture in our assumption about the supply elasticity. For the apparel sector, we assume an average export supply elasticity of 1 for South African and Mauritius and 5 for the other countries. For the non-apparel sector we assume an average export supply elasticity of 2 for the region as a whole.Y Second, we do not have enough information to estimate precisely the impact of the rules of origin requirements in the nonenergy non-apparel sector. Therefore, we present two estimates, reflecting two different 17 Of course, this share should be close to 100 percent but may not be for three reasons. First, it is possible that certain exporter-specific certification requirements prevented full exploitation of the tariff preferences for the least developed beneficiaries. Second, Lesotho and Madagascar obtained their certification in March/April so that exports prior to that period could not benefit from AGOA. Third, knit-to-wear items (which are important for Madagascar) were not accorded the preferential access until August 2002.

18 It should be noted that in general equilibrium, the export response will be more muted and hence aggregating the effects based on large sectoral export elasticities may overstate the overall benefits.
Returnees, who had significantly less livestock to begin with, lost less but still about half their animals. The loss in the value of consumer durables is less, but none the less very significant. Using prices from the 2012 Mercuriale (INSTAT 2012) to value assets and assuming that a ‘yes’ response meant ownership of at least 1 durable good, the IDPs and refugees lost at least<sup>14</sup> 60% of the value of their assets, and returnees about 20%.

**Table 7: Consumer durables and livestock owned before the crisis and in June 2014**

||**IDP**|**s**|**Refug**|**ees**|**Return**|**ees**|
|---|---|---|---|---|---|---|
||**Before (%)**|**June (%)**|**Before (%)**|**June (%)**|**Before(%) **|**June(%)**|
|Ventilator|56|27|33|1|65|51|
|AC|9|1|11|2|8|6|
|Radio/Cassette Player|79|44|74|22|55|38|
|CD/DVD Player|62|27|51|4|50|36|
|TV|82|59|60|18|78|69|
|Refrigerator|44|13|17|0|30|25|
|Bicycle|17|4|21|3|13|7|
|Motorbike/scooter|47|21|41|5|41|32|
|Car/Motorized Vehicle|8|3|17|6|7|5|
|Mobile Phone|92|89|86|74|95|94|
|Tropical livestockunits|108|7|428|109|28|15|
|**Total n**|**100**||**181**||**220**||

Source: Listening to Displaced People Survey, 2014/EMOP 2011.

Despite the loss of consumer durables due to the crisis IDPs, refugees and returnees still own more or similar amounts than the average population in the North did prior to the crisis. This is demonstrated in Figure 8, which presents the lower bound of the value of consumer durables owned by IDPs, refugees and returnees after the crisis, as well the lower bound of the value of consumer durables of households in the three regions of the north (Gao, Timbuktu and Kidal) prior to the crisis in 2011. The value of assets owned by IDPs and refugees is comparable to that of households between the 3<sup>rd</sup> and 4<sup>th</sup> wealth quintile. The value of assets owned by returnees is higher and comparable to that of households in the 4<sup>th</sup> wealth quintile.

> 14 The value is a lower bound because we only measure whether or not a household has a durable good. So for households who own more than one of a given durable good, the value assigned to them is the equivalent of one durable good.

15
15 While it is well documented that formal bank credit is seldom available to African farmers for input purchases, the working hypothesis is that farmers use tied credit with output and input traders and other sources of informal credit to finance the purchase of external inputs, while processors front inputs or cash for inputs in case of contract farming and cash cropping. The findings presented here contradict this, pointing to the important role of off‐farm income and crop sales instead. While this should not be taken as proof of credit constraint as such, it does highlight the importance of the nonfarm sector for agricultural modernization and the intimate links between agriculture and off‐farm employment, to which we return below. Broader (nonagricultural specific) rural development investments and policies will benefit agricultural development through different channels. In fact, the most common purpose of credit to a farming family in Africa is to finance the start‐up costs of non‐farm enterprises (or to finance consumption). This may be partially to help finance input purchases and increase agricultural productivity, an area for further investigation.

# _Market participation is widespread, but the extent of agricultural commercialization remains limited, without_

_clear benefits for nutritional outcomes._ Taking the share of the gross value of crop sales to the gross value of total agricultural production, i.e. the crop commercialization index, as their measure of market participation or agricultural commercialization, Carletto, Corral and Guelfi (2017) find that farmers sell on average around 20‐25 percent of their crop output (a bit less in Malawi, slightly more in Uganda and Tanzania). Conditional on sales the rates amount to 20, 40 and 33 percent in Malawi, Uganda, and Tanzania respectively, indicating that while most farmers sell some crops in these three countries, the marketed shares remain limited. Conditional on planting and selling, 11, 37 and 30 percent of the value of _food_ crops is commercialized in Malawi, Tanzania and Uganda respectively (Figure 6). Unsurprisingly, commercialization rates rise with harvest size, but they are not confined to the traditional cash crops (which are fully commercialized). And even though they are less likely to sell, when they sell, female farmers tend to sell larger shares.

Figure 6: Food crop commercialization remains limited <!-- Start of picture text --> 100 95.3 97 97.4<br>90<br>80<br>70<br>60<br>50<br>36.7<br>40<br>29.5<br>30<br>20 11.3<br>10<br>0<br>Malawi Tanzania Uganda<br>Food crops Non‐food crops<br>value share of crops sold (%)<br><!-- End of picture text --> Source: Carletto, Corral and Guelfi, 2017.
this paper, we use panel data from Bosnia and Herzegovina to examine youth unemployment over the 2001 to 2004 period.

Three main conclusions are supported by this analysis: First, it is clear that young people face several barriers in transition to work in Bosnia and Herzegovina, consistent with recent findings reported (World Bank 2006). This difficulty is reflected in high incidence of unemployment among youth compared to adults. It is also reflected in long duration in the transition from school to work. Younger workers are also more likely to go into inactivity or unemployment or are less likely to transition out of inactivity, holding other things constant.

Second, initial spells of unemployment or joblessness appear to have lasting unfavorable effects. Early difficulties in the transition to work have dynamic implications and could reduce the ability to better integrate youth into the labor market. The micro evidence indicates that the experience of joblessness raises the probability of experiencing another spell by up to 30 percent even after 2 years despite controlling for age, education, marital status and location. Being previously unemployed also lowers future wages by an average 10 percent. There is no evidence, however, that the youth are at a greater risk of scarring, or suffer disproportionately worse outcomes from initial spells of unemployment and joblessness, compared to other age groups. If anything, the wage and unemployment scar may be larger in magnitude for much older workers.

Third, educational attainment is generally associated with more favorable labor market outcomes. Educated workers are less likely to be jobless and are less likely to transition from employment into joblessness. However, the penalty from jobless spells may also be higher for more educated workers. We speculate that this may be due to stigma or signaling, consistent with previous findings.

17
<!-- Start of picture text --> Legend<br>Production share (%)<br>(J0.4-14<br>(14-24<br>(] 24-34<br>(J 3.4-4.5<br>45-55<br>(MM) 5.5-65<br>Mos5-75<br>MH 75-85<br>ai MM 3.5-9.6<br>GB 9.6- 10.6<br>MM 116-126<br>A MM 106-116<br>0 250 km<br>a<br><!-- End of picture text -->
because China can retaliate---for example, by dumping its vast holdings of U.S. treasury paper---and cause disruption in Western markets.

In the context of climate change, the bargaining dynamic between the United States and large developing countries has been dominated by discussions of financial transfers to developing countries. How much money are we talking about? It is estimated that full compensation to developing countries for cutting current emissions by 30 percent would entail net financial transfers by the rich countries of about $430 billion in 2020, about 1.5 percent of their GDP, and about $3.3 trillion by 2050. Most of these flows would go to the four largest emitters. China and India would receive about $75 and $50 billion, respectively, in 2020 and about $600 billion and $175 billion, respectively, in 2050 (Jacoby and others 2008)---an event that is hard to imagine from a political point of view, especially given that in recent years, China has in effect been writing checks to the U.S. government by financing its deficits.

If financial compensation in the form of public transfers from today’s rich to poor is ruled out, what about private capital flows to developing countries? An article of faith in climate change discussions is that private resource flows to developing countries from the trading of emissions allocations can alleviate the costs to developing countries from emissions reductions (Stern 2009). As the _Financial Times_ editorialized, “In the actual world, a global scheme of tradable emissions quotas is the best solution” because trade in these quotas would automatically generate the transfers that could offset the costs imposed on developing countries.<sup>14</sup> When all countries take on binding commitments to reduce emissions, capital flows will be generated through international trading of emissions allocations. How much countries gain is determined entirely by their emissions allocation. For large financial transfers to materialize, countries such as China and India would need to receive large allocations of emissions rights. Yet the heart of the climate

> 14. _Financial Times_ (2010).

20
the child is indeed not deprived of any dimension or is in fact deprived in the dimension where the information is missing.

# 5.2 Chronic Poverty and intergenerational poverty regression analysis

## 5.2.1 Chronic Poverty

The chronic poverty analysis in Figure 40 a and b presents large differences across regions, as well as an urban rural divide, with higher levels of chronic and transient child poverty in rural and northern regions. Whereas in urban South East over 80 percent of the children are never poor, this holds only for about 9 percent of the children in the rural North West. In rural areas in the North West of the country 43 percent of the children are chronically poor, defined as living in households that were always poor during the three waves of the GHS spanning from 2010-2016 with an additional about 47 percent of children transitory poor, meaning, considered poor at least once within the three waves. Compared to an earlier aggregate chronic poverty estimate by Dang and Dabalen (2019), this study’s twice higher chronic poverty estimate over a longer period seems alarming and requires further research.

Figure 41 a: Chronic Poverty Status (USD 1.90$ International Poverty Line) <!-- Start of picture text --> Chronic Poverty Status (USD 1.90$ International Poverty Line)<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>aggregate urban rural<br>never poor transitory poor chronic(always) poor<br><!-- End of picture text --> Figure 41 b) Chronic Poverty Status by Geographic Region - (USD 1.90$ International Poverty Line) <!-- Start of picture text --> Chronic Poverty Status by Geographic Region - (USD 1.90$ International Poverty Line)<br>90%<br>80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br> NC urban NC rural NE urban NE rural NW urban NW rural SE urban SE rural SS urban SS rural SW urban SW rural<br>never poor transitory poor chronic(always) poor<br><!-- End of picture text --> Source: Authors’ estimates based on GHS Waves 1-3 53
# WPS4108

## **Trade Liberalization, Employment Flows and Wage Inequality in Brazil**<sup>**1**</sup>

Francisco H.G. Ferreira, Phillippe G. Leite and Matthew Wai-Poi<sup>2</sup>

- **Abstract:** Using nationally representative, economy-wide data, this paper investigates the relative importance of trade-mandated effects on industry wage premia; industry and economy-wide skill premia; and employment flows in accounting for changes in the wage distribution in Brazil during the 1988-1995 trade liberalization. Unlike in other Latin American countries, trade liberalization appears to have made a significant contribution towards a reduction in wage inequality. These effects have _not_ occurred through changes in industry-specific (wage or skill) premia. Instead, they appear to have been channeled through substantial employment flows across sectors and formality categories. Changes in the economy-wide skill premium are also important.

- **Keywords:** Trade liberalization and inequality; employment flows; Brazil.

**JEL Codes:** D31, F16, J31

### World Bank Policy Research Working Paper 4108, January 2007

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> 1 Paper commissioned for presentation at the UNU-WIDER Conference on “The Impact of Globalization on the Poor in Latin America,” Rio de Janeiro, 23-24 September 2006.

> 2 Ferreira and Leite are at the World Bank’s Research Department. Wai-Poi is at Columbia University. We are grateful to Nina Pavcnik and Norbert Schady for kindly sharing their constructed industry concordance with us; and to Gustavo Gonzaga, Will Martin, Nina Pavcnik, Guido Porto, Martin Ravallion and Erik Thorbecke for helpful conversations or comments.