rafmacalaba/datause-encoder-data huggingface dataset:
**Table A2: Share of households farming crops.**

||Mean|Std. Err.|_N_|
|---|---|---|---|
|**Burkina Faso**||||
|pre-COVID|69.4|1.4|1,968|
|2020/07|71.3|1.4|1,965|
|2020/08|74.6|1.4|1,860|
|2020/10|71.0|1.4|2,013|
|2021/07|69.8|1.4|1,924|
|2023/01|63.7|1.7|1,668|
|2024/01|52.8|1.8|1,832|
|**Ethiopia**||||
|pre-COVID|56.9|1.5|3,247|
|2020/07|70.4|1.2|3,058|
|2020/08|69.0|1.4|2,835|
|2020/09|68.2|1.4|2,770|
|2020/10|67.7|1.4|2,703|
|2021/01|70.0|1.6|2,077|
|2023/01|66.5|4.5|764|
|2024/02|59.7|2.6|2,566|
|**Malawi **||||
|pre-COVID|80.3|1.4|1,726|
|2020/06|89.6|0.9|1,729|
|2021/02|90.8|0.9|1,560|
|2021/06|85.7|1.3|1,541|
|2023/04|87.8|1.4|1,317|
|2023/06|88.9|1.1|1,345|
|**Nigeria**||||
|pre-COVID|69.2|1.5|3,267|
|2023/06|75.2|1.4|2,429|
|**Tanzania**||||
|2023/11|66.2|1.6|1,988|
|**Uganda**||||
|pre-COVID|70.2|1.5|2,224|
|2020/06|78.6|1.3|2,225|
|2020/08|78.5|1.3|2,197|
|2020/10|75.6|1.4|2,144|
|2020/11|75.9|1.4|2,135|
|2021/11|78.8|1.4|1,948|
|2023/01|71.4|1.7|1,665|
|2023/08|72.9|1.6|1,765|
|2023/10<br>Note: Share of house|72.3<br>holds farming|1.6<br>crops. All mean|1,729<br>s in percent.|

23
Wells, Jonathan C., Ana Lydia Sawaya, Rasmus Wibaek, Martha Mwangome, Marios S. Poullas, Chittaranjan S. Yajnik, and Alessandro Demaio. 2020. “The Double Burden of Malnutrition: Aetiological Pathways and Consequences for Health.” _The Lancet_ 395 (10217): 75–88. <u>https://doi.org/10.1016/S01406736(19)32472-9.</u>

# WHO. 2019. “Healthy Diet.” Cairo.

https://apps.who.int/iris/bitstream/handle/10665/325828/EMROPUB_2019_en_23536.pdf.

- ———. 2020. “Healthy Diet Fact Sheet.” 2020. https://www.who.int/news-room/fact-sheets/detail/healthydiet.

- WHO, and UNICEF. 2021. “Indicators for Assessing Infant and Young Child Feeding Practices: Definitions and Measurement Methods.” Geneva.

https://apps.who.int/iris/bitstream/handle/10665/340706/9789240018389-eng.pdf?sequence=1.

- WHO, UNICEF, and FAO. 2021. “Report of the Technical Consultation on Measuring Healthy Diets: Concepts, Methods and Metrics.” Geneva.

- World Bank. 2020. _Obesity: Health and Economic Consequences of an Impending Global Challenge_ . _Obesity: Health and Economic Consequences of an Impending Global Challenge_ . https://doi.org/10.1596/978-14648-1491-4.

World Cancer Research Fund, and American Institute for Cancer Research. 2018. “Continuous Update Project Expert Report 2018. Recommendations and Public Health and Policy Implications.” https://www.wcrf.org/wp-content/uploads/2021/01/Recommendations.pdf.

Zaharia, Sonia, Shibani Ghosh, Robin Shrestha, Swetha Manohar, Andrew L. Thorne-Lyman, Bernard Bashaasha, Nassul Kabunga, et al. 2021. “Sustained Intake of Animal-Sourced Foods Is Associated with Less Stunting in Young Children.” _Nature Food_ 2 (4): 246–54. https://doi.org/10.1038/s43016-02100259-z.

Zhang, Bei, Liyuan Pu, Tian Zhao, Li Wang, Chang Shu, Shan Xu, Jing Sun, Ruijie Zhang, and Liyuan Han. 2023. “Global Burden of Cardiovascular Disease from 1990 to 2019 Attributable to Dietary Factors.” _The Journal of Nutrition_ , March. https://doi.org/10.1016/j.tjnut.2023.03.031.

Zhuo, Ming, Ze Chen, Mao-Lin Zhong, Ye-Mao Liu, Fang Lei, Juan-Juan Qin, Tao Sun, et al. 2022. “The Global Disease Burden Attributable to a Diet Low in Fibre in 204 Countries and Territories from 1990 to 2019.” _Public Health Nutrition_ 26 (4): 1–12. https://doi.org/10.1017/S1368980022001987 24
28 developing backward linkages and investing in efforts to facilitate and enhance their economic impact.<sup>13</sup>

# **5. Summary and Suggestions for Further Research**

# **5.1 Summary**

The attraction and facilitation of MNC investments constitutes a key component of the development strategies of most developing and emerging economies. One of the main reasons for this is that host economy governments expect that domestic firms will benefit from the entry and operations of MNC affiliates through the materialization of productivity spillovers. The large body of empirical evidence indicates that spillovers within a single industry are of limited economic importance. In contrast, evidence on positive spillovers between industries is more prominent; in particular, a number of studies identify productivity spillovers among domestic firms that produce inputs for industries with a large participation by MNC affiliates. These findings indicate that backward linkages between MNC affiliates and local suppliers constitute the main channel transmitting productivity spillovers.

However, the evidence on backward spillovers is also mixed and indicates that these spillovers do not occur automatically and are context specific. This is an important policy issue, given that host economy governments often dedicate considerable resources to attracting and facilitating MNC affiliates and promoting linkages between foreign firms and local suppliers. More case studies would help us better understand what policy interventions have proven effective in a particular country and industry context.<sup>14</sup> Furthermore, there is a growing recognition that host economy governments need to design and implement a variety of soft industrial policies to foster linkages and their impacts.

The convergence of the evidence identifying productivity spillovers through backward linkages as the main productivity effect from MNC affiliates, in combination with the policy choices that host economy governments are currently facing, motivates the need for a fresh survey of empirical studies on backward linkages. The available evidence on linkages and productivity spillovers is particularly rich, stemming from different research fields that provide evidence and insights into drivers of the level of

> 13 For concrete examples of such policies and their impact, see the _World Development Report 2020_ on global value chains (World Bank 2020, 178).

> 14 Ongoing research by the World Bank Group’s Investment Climate unit, “Global Value Chains: An Investment Perspective,” should help shed more light on this question (publication forthcoming). The research examines not only what policies promote linkages and integration of local firms in international production networks, but also what combination and sequence of specific policy interventions and measures yield better results.
The randomization among eligible schools is critical for our study: it ensures that the three successive cohorts are statistically comparable, which in turn ensures unbiased estimates of the eect of the program. In this process it is crucial that the control group contains only schools that were judged as eligible but were not selected to receive funding by the randomization process until a later date.

# 3 Data and Balance

In order to gather data for this study, three waves of surveys were administered to students and their families, teachers, and principals in these schools. A baseline survey was conducted at the start of the 2009-2010 academic year (in November), right as the rst round of grants were able to be executed. Subsequent surveys took place in November 2010 at the beginning of the 20102011 academic year (rst follow-up), and in May 2011 at the end of the 2010-2011 academic year (second follow-up).

At baseline, we administered written assessments in mathematics and French to a random sample of 6 children in each of grades 2 and 4, and an oral reading assessment (similar to Early Grade Reading Assessment, or EGRA) to a random sample of 3 of those 6 children in grades 2 and 4. Importantly, the same tests were administered across all waves. In addition, we randomly selected 2 of the 3 children in each grade who took all three assessments, and conducted a household survey that included demographic and nancial information on all household members. Finally, we collected classroom and school level information by surveying the school principals and the teachers of the students in our sample.

In the rst follow-up, we surveyed and tested the same children again (at the start of 3rd and 5th grade, respectively) and their households, teachers and principals. Schools who received grants in the rst cohort answered a set of questions on the use of the extra funds. To examine the possibility that funds were disproportionately channelled to students preparing to enter secondary school, we also administered written assessments in mathematics and French to a random sample of children who were in 6th grade at follow-up, and also surveyed their teachers.

In the second follow-up, we re-surveyed and tested the same children who were tested at baseline and rst follow-up. In addition, in the second follow-up we administered the Peabody Picture Vocabulary Test (PPVT) to children and their mothers. We did not collect general school 7
ing variables, no education and 7 to 8 years of education, are negative. One interpretation of the education rank variables is that the government was actively trying to place family planning programs in areas where the population is less educated but not overwhelmingly lacking in education. Presumably those with more education are likely to live in areas where there are other means of obtaining family planning services or have lower desired fertility. The F-test for all instruments being jointly equal to zero is 6.14. Despite the low number of observations, the F-test indicates that the instruments perform well.

# **4.1 Effect on Fertility**

Table 4 presents the results for the effect of access to family planning in 1990 on the number of children ever born by 2004.<sup>19</sup> Models I and II assume that program placement is exogenous and estimate the effect of family planning using OLS. Models III and IV treat program placement as endogenous and use the predicted probability of access to a family planning program from Table 3.<sup>20</sup> Models I and III estimate the average effect of access to family planning services on children ever born across all women in the sample. Because the effect of access is likely to vary by age, Models II and IV include interactions between family planning access and the five year age group dummies.

The average effect of access to family planning on children ever born is negative and strongly statistically significant for both OLS and IV estimations. The OLS estimate indicates that providing family planning reduces the number of children ever born by 0.7 children. Taking account of program placement leads to an even larger estimated impact of access to family planning with fertility falling by 0.9 children. Given the sample’s average, the effect is equivalent to an approximately 20 percent reduction in the number of children born per woman.

That the IV estimates are larger than the OLS estimates is in line with the results of earlier studies using longitudinal data (Rosenzweig and Wolpin 1986; Pitt et al. 1993). These studies found that fixed effects estimates were larger than OLS estimates indicating a downward bias in OLS estimates. The larger IV effect can be taken as an indication of a compensatory approach to allocation of programs, where resources are provided to less-endowed areas with higher fertility.

The results for family planning access interacted with age groups suggest that access to family plan-

> 19Table A-1 shows the full results.

> 20 Choosing a different cut-off year does not substantially change the results for years immediately around 1990. The results for other years are available on request.

14
32 country other than those that have signed the Code and which the U.S. judges to have fulfilled the provisions of the Code.

In addition to this restriction of the benefits of the Code, the U.S. is by far the largest initiator of countervailing duty actions. Table 1, which is drawn from data compiled under the direction of Michael Finger at the World Bank, shows that of 460 countervailing duty cases by all countries over the first seven years of the decade, 281 of them were in the United States. Chile accounted for 140, nearly all prior to March 1983, and virtually all not sustained. (Finger and Nogues, 1987, p.713.) Chile's actions followed a very rapid dismantling of other trade barriers in that country, and have been regarded by some other countries as misuse of the CVD provisions of the Code.1/ Table 1 also shows that the major initiators of countervailing duty cases had relatively few actions taken against them. To a large extent this is due to the fact that the most subsidized exports of the United States and Europe are agricultural products that injure industries not in the importing countries, but in other exporters. In such circumstances there is little or no incentive in the importing country to take countervailing duty initiatives. It is also true that many non-initiators use other forms of barriers to imports, often in a concealed form and with considerable bureaucratic discretion, instead of the highly transparent countervailing duty procedures.

The targets of CVD actions form a much larger set of the countries than the initiators. With or without the Chilean cases , Brazil is the most

1. It is reported that Chile ceased to initiate countervailing duty actions following threats of retaliation. (Finger and Nogues, 1987, p.713n.)
Short-term losses of labor and human capital are less of a concern in situations where emigrants are mostly low-skilled and where the domestic supply of low-skilled labor is high. This is the case of many low and middle-income migrant-sending economies which are experiencing demographic bulges and where domestic job creation has not kept pace with the expansion of the mostly low-skilled labor supply. Emigration helps to alleviate labor market pressures by providing additional employment opportunities for workers from these countries, like many migrant-sending countries in East, South and Central Asia (Farole, Cho, Bossavie, and Aterido 2017; Ahmed and Bossavie 2022), as well as other low and middleincome countries.

# **4.2 Human capital accumulation by temporary migrants while abroad**

In the medium term, temporary migration can effect human capital stock in origin countries when temporary migrants accumulate human capital while abroad and then return home. In the two-dimensional skill model, theoretically, the ”brain drain” resulting from highskilled emigration may be mitigated and even reversed by the skills brought back home by return migrants (Dustmann and Glitz 2011). Temporary migrants indeed can acquire additional skills overseas which are rewarded in the home country (Borjas and Bratsberg 1996; Dustmann and Weiss 2007; Dustmann, Fadlon, and Weiss 2011), creating a potentially positive overall effect even in the presence of initial emigration (Dos Santos and Postel-Vinay 2003). It has also been argued that the migration experience may act as a signaling device of workers’ productivity to employers in home labor markets, further increasing their labor market gains (Reinhold and Thom 2013).

The empirical literature tests for the accumulation of human capital by estimating the wage premium earned by return migrants. A critical element of such reduced-form estimations is to properly account for the double selectivity of emigration and return migration, so that estimates only capture the effects of the past migration experience, and not differences in unobservable characteristics between migrants and non-migrants (Wahba 2015). The vast majority of the papers, with varying degrees of rigor in accounting for the double selectivity of return migration, find a positive wage premium earned by returning migrants. This has been reported for Hungary (Gang and Yun 2000), Albania (De Coulon and Piracha 2005), Romania (Ambrosini, Mayr, Peri, and Radu 2015), Ireland (Barrett and Goggin 2010), Mexico (Reinhold and Thom 2013), several West African countries (De Vreyer, Gubert, and Robilliard 2010) and the Arab Republic of Egypt (Wahba 2007; Wahba 2015).<sup>12</sup> Wahba (2015)

> 12The study by Gang and Yun (2000) for Hungary, however, only finds positive effects for female return

21
where S3 �b1; b�2; b�3 denotes the residual sum of squares of the model with four regimes � � and three threshold parameters. In models with m + 1 > 2 regimes, the estimates of the m threshold parameters can be done sequentially by using the estimated threshold parameters obtained in the model with m regimes as suggested by Bai and Perron (1998) in the context of multiple changepoint models. In this paper, we limit our analysis to a model with 4 regimes at the maximum given the computational cost of such models. Thus, a sequential procedure based on F1, F2 and F3 allows to determining the number of regimes<sup>4</sup> .

The second issue consists of determining the threshold variable. Few technical constraints are imposed to the choice of the threshold variable. The only constraint is that the threshold variable can not be time invariant. Therefore, this choice is mainly an economic issue. If we want to assess the idea that the infrastructure investments have a network character, it implies that the threshold variable should be an indicator of the completion of the network. In this perspective, a natural candidate for the threshold variable is the existing level of available infrastructure. According to Fernald, a low level of capital (relatively to the population or to the workforce for instance) indicates that the construction of the network is not completed and may imply a high a productivity of stocks, and a high level of stocks may imply, if the network is built, a null or low marginal productivity. Two choices are then possible: the threshold variable can be de...ned as the level of infrastructure stock or as the level infrastructure stock per worker (or per capita). The second variable allow to avoid the scale e¤ects in the network. Thus, our ...rst speci...cation is based on the following threshold variable: Another solution for the threshold variable would consists in using the lagged level of GDP per worker, i.e. qit = yi;t�1: It is necessary to use the lagged value of yit in order to avoid a simultaneity since this variable is the endogenous variable of our regressions. This speci...cation corresponds to a heterogeneity between ”rich”and ”poor ”countries as suggested by Canning and Bennathan (2000). However, contrary to Canning and Bennathan, our heterogeneity is endogenous in the sense that it is the the threshold variable yi;t�1 (and the threshold parameters �j) which determine the list of countries included in the di¤erent regimes of productivity. Besides, in our speci...cation a country with low productivity (which belongs to regime 1 for instance) in the beginning of the period can have a medium or high productivity at the end of the sample period (i.e. belongs to the regime 2 or 3). Therefore, we consider a second model with:

> 4 The codes for the estimation and inference procedures are done with Matlab. All codes are available upon request.

9
24 average pre-Uruguay Round MFN tariff on products exported by Kenya was 4.88 percent. However, once preferences are accounted for the average applied tariff actually facing Kenyan exports was slightly more than 0.11 percent -- which implies an average preference margin of 4.76 percentage points. However, as a result of the Uruguay Round, MFN tariffs on the products exported by Kenya will be reduced to 2.88 percent -- which means a 1.99 percentage point reduction in Kenya's margin of preference. In the case of Cape Verde and Somalia even larger reductions occur as preference margins fall by 10.3 and 12.8 percentage points respectively. A 12 percentage point reduction in MFN tariffs for two line items (Rock Lobster and Cigars) accounts for Cape Verde's results while Somalia's preference reduction is almost entirely due to a reduced tariff on bananas. Appendix Tables A2-1 through A2-49 present similar, but more detailed information for broad groups of products (separate tabulations are show for the EU, Japan and United States) exported by each African country along with full information as to the basis for these computations.

For the 44 African countries combined pre-Uruguay Round MFN tariffs averaged 4.56 percent while the "aplied' duties (which account for preferences) were some 4.25 percentage points lower. As a result of the Uruguay Round the average MFN tariff on products exported by Africa was reduced to 2.68 percent -- which resulted in an average 1.78 percentage point reduction in preference margins. Aside from Somalia, Cape Verde, Rwanda and Uganda the preference margin reductions were modest (all under three percentage points).

A key question concerns the magnitude of the export earning losses Sub-Saharan Africa will experience as a result of the Uruguay Round erosion of their trade preferences. A recent World Bank study (Yeats 1994) provides relevant information. Specifically, this investigation determined that African export losses would total about one-quarter billion dollars _if Africa's trade preferences were fully eroded_ (i.e., MFN tariffs were reduced to the level of tariff preferences). The Cote d'lvoire accounted for about one-fourth of the African losses ($57 million of this country's annual exports would be displaced) with Mauritius and Kenya each recording declines of about $25 million. However, these figures overstate the actual Uruguay Round effects since preferences were reduced, but not fully eliminated. Based on what occurred it appears that actual African trade losses would be in the range of $100 million annually in the EU, Japan and United States which represents approximately one-half of one percent of total annual exports.
Insurance companies must be established under Tunisian law and must be majority owned by Tunisian interests. Four of the resident companies have extensive foreign participation. ranging between 44% and 48%, although this is in most cases divided between 2 or more companies. Divided minority foreign participation implies relatively small stakes and limited managerial involvement. This results in fewer benefits for the local companies concerned in terms of transfer of financial technology, product innovation. and enhanced risk and investment management.

**Table 3**

|**Insura**|**nce Premiums by**|**Line, 1990 a**|**nd 1993**||
|---|---|---|---|---|
||1990||199|3|
||PREMIUMS<br>(MD)|%|PREMIUM<br>(MD)|S<br>%|
|MOTOR|_55.5_|32.8|83.8|32.8|
|GROUP HEALTH|33.3|19.7|52.3|20.5|
|TRANSPORT|18.6|11.0|25.0|9.8|
|FIRE|17.0|10.1|24.1|9.4|
|WORK ACCIDENT|16.4|9.7|22.1|8.6|
|MISCELLANEOUS|16.2|9.6|32.4|12.7|
|LIFE|12.0|7.1|15.9|6.2|
|TOTAL DIRECT|169.0|100.0|255.6|100.0|
|ACCEPTED REINSURANCE|3.8||5.6||
|TOTAL PREMIUMS|172.8||261.2||

Source: Ministry of Finance, Direction Generale des Assurances and F.TU.S.A.

The insurance industry is dominated by state owned companies, which account for 47% of total 1993 premiums (based on the 13 resident companies that engage in ordinary life and/or nonlife business). The share of state-owned companies has suffered a slight fall in recent years. State-owned companies used to enjoy a strong preference by state entities and other state-owned companies but in recent years there has been a gradual defection of public sector business to private companies, which appear to charge higher premiums but offer a better service.

Market concentration is quite high as the three largest companies control almost 57% of the market (Table 2). The Herfindahl index of concentration was 1654 in 1993. down from 1789 in 1990. This is close to the limit of 1800 used by US authorities in blocking mergers for anticompetitive reasons<sup>4</sup> . The small decline in the index reflects the gain of market share by the two private companies among the big three insurers at the expense of the largest company, which is state owned. It is notable that El 4 As the experience of Canada. the Netherlands and other high income countries shows, high concentration per se is not incompatible with competitive efficiency if the market is contestable by potential new entrants. In most developing countries, it is the combination of high concentration, dominant state ownership and restrictive regulations that tends to have adverse effects on the degree of competition, innovation and overall efficiency.

4