rafmacalaba/datause-encoder-data huggingface dataset:
**14 |** P a g e

percent to 21.3 percent in this period. The latter have also displayed the increase in terms of value only second to iron and steel: the average LSG rate was 42 percent for automotive goods and 38 percent for machinery excluding automobiles as compared with 23 percent for total exports.

There is also a strong indication that producers of clothing and footwear has been able to find higher value added niche in this extremely competitive market in spite of high wages in BiH. The share of other consumer goods, dominated in past by textile and clothing and footwear, fell steadily from 47 percent in 2003 to 39 percent in 2006, despite the fact that BiH exporters of these products outperformed other suppliers and increased their presence in EU markets. It sharply increased in 2007 to 44 percent of total EU‐oriented exports. The share of other consumer goods in EU imports increased 17 percent in 2007 over 2006. The Borac’s—the largest clothing producer in BiH—contract to supply Hugo Boss at higher end clothing has probably contributed to this outcome.

**Table 8: EU imports from BiH in terms of end‐use products: their composition, share in EU imports, and dynamics in 2003‐07 (in percent)**

|||**Comp **|**osition o**|**f Impor**|**ts(%)**||**Shar**|**e in EU‐2**|**7 Import**|**s(%)**|**LS Growt**<br>**07(**<br>EU|**h 2003‐**<br>**%)**<br>EU|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Product|2003|2004|2005|2006|2007|2003|2004|2005|2006|2007|Imports|share|
|Agriculture,|||||||||||||
|Food & Feeds|15.0|13.5|11.0|10.1|10.7|0.143|0.153|0.148|0.160|0.160|13.6|2.7|
|Industrial Raw|||||||||||||
|Materials|18.7|22.1|21.6|21.6|17.4|0.468|0.533|0.575|0.492|0.376|21.6|‐5.2|
|Fuels|4.3|0.7|2.7|1.8|1.4|0.023|0.004|0.013|0.009|0.008|11.0|‐12.1|
|Machinery, excl.|||||||||||||
|automobiles|10.9|13.3|21.3|18.7|19.4|0.033|0.044|0.082|0.081|0.088|38.4|26.0|
|Auto and Parts|0.8|1.8|2.0|2.1|1.9|0.015|0.037|0.049|0.059|0.051|42.4|29.0|
|Iron and Steel|2.8|3.1|3.3|6.2|5.4|0.187|0.163|0.192|0.335|0.221|43.4|10.6|
|Other Consumer|||||||||||||
|Goods|47.6|45.6|38.1|39.4|43.9|0.119|0.131|0.120|0.132|0.155|20.2|5.3|
|All Goods|100|100|100|100|100|0.088|0.096|0.105|0.112|0.116|23.3|7.0|

Source: Derived from trade reported by the EU to the UN COMTRADE database.

Another evidence of the change towards more processed goods is the change in the composition of BH’s export specialization index (ESI<sup>6</sup> ) in EU markets. Although ESI with values exceeding

> 6 The ESI is a modified version of well‐known revealed comparative advantage (RCA) originally introduced by Bela Balassa (1965). While the RCA is the ratio of the share of a given product in BH’s total exports to the share of that same product in world imports, the ESI is the same ratio but not to the share in world imports but in a selected market, e.g. the EU’s total external imports. An ESI with a value that exceeds unity suggests a strong specialization in the product. An ESI value exceeding unity implies that BH is more specialized in exporting the product to, for instance, the EU than an average trading partner of the EU.
**Figure 9: Reduction in poverty from first-order effects of road improvement.**

<!-- Start of picture text --> 700,000<br>600,000<br>500,000<br>400,000<br>300,000<br>200,000<br>100,000<br>0<br>CE Juba ‐ Juba ‐ Juba ‐ Juba ‐ Juba ‐ Both All<br>Rumbek Wau Aweil Bor Malakal roads roads<br>Scenario A Scenario B<br>Reduction in Poverty<br><!-- End of picture text --> _Note: Scenarios A uses a lower bound estimate for the elasticity of reduction in the price gap relative to road improvement (-3.22) while scenario B uses the upper bound (-6.61)._ As visualized in Figure 9, upgrading the roads only in Central Equatoria would reduce poverty by 71,000 to 142,000 people, depending on the scenario. Adding Rumbek, Wau and Aweil to the upgraded road network could reduce the number of poor people by up to 438,000. A second road from Juba to Malakal could reduce poverty by up to 262,000 people. Both roads together have the potential to lift 558,000 people out of poverty. Finally, upgrading roads in all states would remove another 93,000 people from poverty. Reducing poverty by a 651,000 people translates into a reduction of the poverty rate by 8.9 percentage points, from 51.7 to 42.8 percent using the 2009 poverty estimate.

Second-order effects are likely to be even more substantial, although we are unable to estimate them with the data at hand. Several second-order effects would further contribute to an improvement of consumption for households. The reduction in prices would also increase trade volumes exacerbating price reductions and increasing consumption and production. This type of extensive margin of the gains from connecting markets is likely to be of a larger order of magnitude than the static effects we are capturing (Donaldson, 2014). Lower input costs would also reduce production costs. Hence, the overall impact of road improvement on poverty is likely to be considerably higher than that estimated by the first-order effects only.

# **5. Conclusions**

This paper has examined the possible welfare implications of increased market integration using the case of South Sudan. Market integration of spatially separated regions implies linkages among them through trade or through the possibility of trade, so that the forces of arbitrage make the longrun price differences that remain among them equal to the costs of trading. To tackle this issue, we examined the evolution of prices of specific food products across different cities in South Sudan, 26
for another, as Rodet (2010) demonstrates in the French Soudan. Even the abolition of slavery had failed to sever the cord that subordinated women to men and held them captive within the domestic realm.

One of the remarkable incidents of mass slave exodus as feared by colonial governments took place in the French Soudan or present-day Mali. Maraka Muslim merchants domiciled in Mali practiced plantation slavery. In the late 19<sup>th</sup> century the slave raids and wars of warriors such as Samory Toure of the Mandingo and Tieba of Sikasso had produced a flood of captives, many of whom ended on Maraka plantations. On Maraka plantations in 1905-6, thousands of slaves left the slave agricultural villages when word reached them that the French had abolished the legal status of slavery since 1903. As most of these slaves had been recently captured, they knew where home was, and the imposition of French colonial peace in that larger region encouraged the exodus of 1905-6. It is estimated that by 1908, about 200,000-500,000 had abandoned their masters (Roberts (1981)). _Colonial Economies: Settler, Concessionary, Mining and Peasant_ The scramble for Africa had taken place in the context of European economic crisis in the last quarter of the 19<sup>th</sup> century, and European merchants who agitated for more formal control of African territories envisaged economic relief from colonialism. For starters, African competitors, often chiefs, would be sidelined. The numerous taxes, duties, and gifts (‖dashes‖) that made the conduct of business expensive on the West African coast would be eliminated, as well as the problem of trust in credit networks. As colonial armies moved against African states, they were even dependent on commercial intelligence from European merchants on trade routes, measuring distances, possible supply lines, and other relevant matters. Preceding the 1874 British march on the Asante capital of Kumasi, the Colonial and War Offices in London had corresponded with Francis and Andrew Swanzy, leading merchants on the Gold Coast, on local geography, rivers and their tributaries, food supplies and the means of carrying food.<sup>2</sup> Another prominent West Coast trader, John Holt, had to be reined in by British officials in his protest against the German annexation of the Cameroons, which British merchants in Lagos considered part of the British sphere of influence. The German government formally complained to the British government that John Holt was inciting the natives in Cameroon to rebel, and that the British Vice Consul Buchan, also a

> 2 Unilever Archives, Liverpool, UAC/2/33/AG/1/2/5. C. B. Brackenbury from the War Office was effusive in his expression of gratitude to Swanzy in his letter of September 31, 1873: ―The information you are so kind as to give us is among the very best we obtain and we are really thankful for it.‖

20
The increase in CPS enrollment is fueled in large part by a large substitution from IPS to CPS (IPS enrollment was 24.7 pp lower at midline and 20.2 pp lower at endline) which was by design as the new CPS replaced the IPS (Table 6). There was also a more moderate reduction in SPS enrollment (SPS enrollments were 5.6 pp lower at midline and 5.2 pp lower at endline). This reduction in SPS enrollment may affect how to interpret our estimates. First, since SPS are expected to outperform IPS, the substitution would have the effect of driving down the ITT estimates of the impact of the program on child development, particularly in T2. Second, as detailed in Section 4.3, the bounds exercise relies on the assumption that _LATEac ≥_ 0. The reduction could be driven by two mechanisms: first, parents actually switching to SPS as a response to the program; second, the slight baseline imbalance in the availability of SPS (significant only in T2). Although we cannot empirically distinguish between these mechanisms, the consistency between the SPS availability and enrollment (Table 5 and Table 6) suggests that it is the imbalance that explains the result. In addition, the fact that SPS have higher quality than CPS makes it less likely that parents would switch. Both mechanisms would have the effect of driving down the ITT estimates of the impact of the program on child development, especially in T2.

Using the preschool enrollment data, we can calculate the share of _h-_ and _acompliers_ ( _Sac_ in Section 4.2). At midline, 52% of the sample are compliers, and 28% are _a-compliers_ . Therefore, the share of _a-compliers_ (among the compliers) is _Sac_ = 54%(=28/52) at midline. At endline, the total share of compliers goes down to 32% and is composed of a large majority of _a-compliers_ (81%).

In addition to enrollment on the day of the survey visit, we analyze two other indicators of enrollment: ever enrolled and duration of enrollment, both measured by the time of the endline survey (Table 7). Note that at endline about 25% of the children are enrolled in primary school and primary school enrollment appears to have been unaffected by the CPS construction. The impacts on ever enrolled are consistent with those for the day of the visit. The cross-preschool-type patterns confirms that much of this increase comes from a large reduction in the probability that children are ever enrolled in an IPS and a more modest reduction in SPS enrollment.

These results suggest that about 28% of the eligible children did not attend any school at any point in time even when a preschool was available in the village. When asked why they did not send their child to preschool, parents indicate two main reasons. First, many parents expressed difficulties bringing and picking up the child at preschool (51%). Parents also often declared being afraid to let children go to school by themselves (62%) or that the school was too far away (35%). Since CPS sessions were only given in the morning for two hours, those parents who had to work outside of the village (in fields far from the village or in a garment factory) and/or 25
||**Table 1.**|**Growth in**|**block gran**|**t transfers**|**to regional**|**governme**|**nts (billion**|**s of ETB**|**)**|
|---|---|---|---|---|---|---|---|---|---|
||**2005/06**|**2006/07**|**2007/08**|**2008/09**|**2009/10**|**2010/11**|**2011/12**|**2012/13**|<br>**2013/14**|
|Nominal|7.1|9.3|13.5|16.6|19.6|25.5|30.6|35.6|42.5|
|Real|22.2|25.4|29.3|26.3|30.2|33.4|29.8|30.6|33.8|
|Grant % of<br>total<br>expenditure|32.4|34.7|39.0|36.9|37.7|36.6|39.9|39.0|37.4|

_Source: Ministry of Finance and Economic Development (MoFED) and PBS Secretariat Note: Real amounts based on 2011 prices_

**<u>Table 2. Evolution of key indicators, 2006–2014</u>**

|**Indicator**|**Start of PBS**<br>**(2006)**|**2014**|**Source**|
|---|---|---|---|
|Child mortality 1-4 per 1,000|72|31|DHS|
|Contraceptive acceptance rate (modern method)|14%|40%|DHS|
|Access to antenatal care|28%|41%|DHS|
||||Education|
|Net enrolment rate for grades 1–8|77.5%|90%|Management<br>Information<br>System(EMIS)|
|Gross gender parity index for grades 1–8|0.84|0.92|EMIS|
|Improved sanitation|38%|66%|DHS|
|Cereal productivity in quintals per hectare|15|20|Agriculture Sample<br>Surveys|

30
ownership type of the producers of goods in all cases. An SOE middleman may be handling the goods of SOEs, domestic private enterprises, collective enterprises, or even foreign enterprises. The same goes for other domestic middlemen. This problem is endemic to any analysis involving export middlemen in which it is desired to identify a firm attribute. For example, exports of small and medium-sized enterprises (SMEs) may be handled by large-firm export wholesalers and vice versa (USITC 2010, Chapter 5). It is entirely possible that the organizational type of the producer exerts a separate, or complementary, effect on both the use of middlemen and the incentives for tax evasion. Thus, for example, if the production of steel in China is dominated by SOEs, the relationship between the SOE status of the producers and the use of middlemen or the likelihood of tax evasion is likely more complex than that explored in this paper. Analysis of this problem would require matched firm-level data on the attributes of producers and the wholesalers they use.

# **References**

Ahn, JaeBin, Amit K. Khandelwal, and Shang-Jin Wei, 2011. “The role of intermediaries in facilitating trade.” _Journal of International Economics_ 84: 73-85.

Akerman, Anders, 2013. "A Theory on the Role of Wholesalers in International Trade Based on Economies of Scope." Working paper.

Antras, Pol, and Arnaud Costinot, 2011. “Intermediated Trade.” _Quarterly Journal of Economics_ ,126: 1319-74.

Bernard, Andrew B., Bradford J. Jensen, Stephen J. Redding, and Peter K. Schott, 2010. "Wholesalers and Retailers in U.S. Trade", _American Economic Review_ 100(2), 408-413.

Bernard, Andrew B., Marco Grazzi, and Chiara Tomasi, 2011. “Intermediaries in International Trade: Direct versus Indirect Modes of Export.” NBER Working Paper No. 17711.

Bernard, Andrew B., Bradford J. Jensen, and Peter K. Schott, 2006. “Transfer Pricing by U.S.-Based Multinational Firms.” NBER Working Papers No. 12493.

Broda, Christian, and David E.Weinstein, 2006. “Globalization and the gains from variety.” _Quarterly Journal of Economics_ 121, 541-585.

Chandra, Piyush, and Cheryl Long, 2013. “VAT Rebates and Export Growth in China: Firm Level Evidence”, _Journal of Public Economics_ 102, 13–22.

30
districts, 468 schools were included in the MLSS sample and visited at least once, of which 444 were visited in both the baseline and endline rounds. On average, our sample includes 81 percent of the PPS required schools in each district – an average of 74 percent in the eight disadvantaged districts and 85 percent in the 17 comparison districts (see **Table 2** ).

### **Student Sample**

For test scores, we report student level scores from a longitudinal sample of students. As the MLSS is a longitudinal study, it employs both a cohort and longitudinal sample for students. A genderbalanced random sample of 25 Grade 4 students per school (13 girls and 12 boys) is selected at baseline. We then select 15 of these at random (8 girls and 7 boys) for retesting at endline. Students who have dropped out or transferred to other schools are traced to the new schools or their homes and complete learning assessment and a modified version of the student interview. Two students are additionally selected as a reserve sample to replace students who have died, left Malawi, or cannot be traced. We expect to trace 90 percent of the selected students at endline.<sup>18</sup> We compare the baseline and endline scores of each student to calculate student-level difference in learning.

## **Attrition**

There is no school level attrition. At student level, our final sample includes data from 6,940 students of an original longitudinal sample of 7,594 for the sampled schools (91 percent).

## **Summary statistics**

**Table 3** shows summary statistics for the key outcomes of interest for the schools in the eight disadvantaged districts and the 17 comparison districts.

# **Results**

## **Implementation of MESIP**

**Auxiliary teachers** . In total, 478 ATs (362 male and 116 female) were hired by schools in the eight disadvantaged districts (Ministry of Education, 2021). In most cases, these ATs served for 1-2 years before being deployed into the formal teaching workforce. As a custom, ATs were typically (but not exclusively) hired into the same schools in which they had served as ATs before MESIP closed, formalizing the improvements in staffing gained from their hiring.

> 18 In addition to this longitudinal sample, at endline the MLSS also selects a cohort sample of 15 students in Grade 4 at endline (8 girls and 7 boys) for testing. In this study, we focus on test scores for the longitudinal sample of students. In addition to testing, students complete a short interview at both baseline and endline.

16
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32
There are several reasonis to treat the comparison with caution. For one, the constellation of policies influencing growth may have differed across countries in ways that are not directly attributable to their different debt-management strategies. Moreover, there is the problem of sorting out the direction of causality. As we explained in Section 2, countries suffering more severe declines in income were more likely to default; now there is a suggestion that countries which defaulted enjoyed more rapid income growth. There is nothing incompatible in the two arguments, but two-way causation poses problems of identification. Even if the problems posed by the joint endogeneity of default and output growth can be solved, there is still the possibility that because production declined more dramatically before 1931 in countries which lapsed into default, the emergence of higher levels of unemployment and excess capacity may have offered more scope for output to snap back later. After suffering more serious terms-of-trade declines before 1931, the serious defaulters may have benefized from more rapid terms-of-trade improvements as international commodity markets recovered thereafter. In fact, however, Figure 3 while confirming the greater severity of the terms-of-trade shock suffered by the heavy defaulters immediately after 1929 suggests that, with the exception of 1934, the terms of trade of the two groups of countries subsequently evolved more or less in parallel.2jj Data limitations, along both the quantity and quality dimensions, preclude the estimation of a simultaneous-equations model to sort out these effects definitively. Our approach is to rely instead on a sequence of simpler descriptive analyses. None eliminates all of the problems acknowledged above, but all tend to point in the same direction.

19