rafmacalaba/datause-encoder-data huggingface dataset:
Latin American experiences confirm that the dumping and injury criteria required by WTO rules are generous. To keep the number and the degree of restrictions in check, the governments often had to depend on the discretionary authority they retained<sup>8</sup> . The economic content of the rules did not create political capital that governments could use to explain a negative response to a request for protection; governments had to use political capital otherwise gained to explain why protection was not given to a petitioner that the rules found to be deserving.

# **VIII. RECOMMENDATIONS FOR WTO RULES**

The country studies reviewed here demonstrate that the WTO rules on safeguards and antidumping have proven to be essential and that the courage and skill of policy managers have proven to be indispensable in the sweeping trade liberalization that has taken place in Latin America trade policy over the past quarter century.

In this final section, we ask how the WTO rules could have been even more useful and more supportive of the liberalization that these countries set out to achieve. To be effective, a policy manager must master the technicalities, but we have found that the effective use of safeguards and antidumping mechanisms is as much art as science. In areas of economic policy in which the advice to “follow the rules” has perhaps been overemphasized, we will restrict ourselves to general observations; we leave the crafting of negotiating proposals to people with expertise in such work.

One might identify two objectives with respect to how international rules might shape domestic processes through which governments make decisions to impose protection. From perhaps an ideal perspective, one might hope that they would guide a country to identify those interventions that add more to the national economic interest than they take away. Eliminating distortions, in theory, follows from this perspective.

The experiences studied here show, however, that there are instances in which other considerations make it impossible to avoid what might be an economically unsound trade intervention. In those situations, good policy becomes a more pragmatic matter, a matter of

> 8. Although the discretionary authority that counties retained and the political review processes that countries superimposed over technical determinations in a number of instances led to a reduced level of restriction, there were few instances in which no restriction was imposed after an affirmative determination.

38
A peculiarity of the West-African context is the widespread fostering of children who are temporarily sent away from their biological parents to be raised in another family.<sup>7</sup> The reasons for child fostering have been studied by several researchers (Isiugo-Abanhie, 1985; Bledsoe, 1990; Ainsworth, 1996; Akresh, 2009; Beck et al., 2011). These include insurance against idiosyncratic shocks to family income, education (i.e., children in rural households are sent to live with their urban kin members where there are schools), kinship fostering (i.e., as part of the obligations between members of the same extended family), and child labor. As argued by some demographers, high fertility is also made possible by the social institution of fostering, through which the costs of childrearing are partly shared with the extended family (Isiugo-Abanhie, 1985; Bledsoe, 1990). Fapohunda and Todaro (1988) argue that ‘ _the presence of parental surrogates in the extended family alleviates problems of incompatibility between child care and work and, thereby, lowers the opportunity cost of children._ ’ (p. 572). According to Smith (2004), the traditional high value associated with having many children (that allow larger kinship networks) might partly motivate the slow transition to lower fertility in Nigeria, even though families start lamenting the increasing costs of raising children due to modernization.

# **3 Data and descriptive evidence**

I use the 2008 Nigeria Demographic and Health Survey (NDHS), a representative cross-sectional dataset of women aged 15 to 49 in Nigeria. It contains individual-level information on women’s birth histories, household composition, biological children living in the household or elsewhere, birth intervals, marital status, and other individual and household characteristics.

Summary statistics for the sample of women aged 15 to 49 with at least one child ever born are reported in table 1.

The mean number of children ever born is 4.35.<sup>8</sup> This does not reflect completed fertility especially for younger women in the sample: the total fertility rate is in fact 5.7 births per woman (NPC and ICF Macro, 2009). As noted in the previous section, high fertility is strongly desired. This is reflected both in the high number of births and desired fertility: 63 percent of women express

> 7Child fostering is a widely accepted and practiced social institution in many parts of Sub-Saharan Africa. LLoyd and Desai (1992) analyze data from 16 DHS survey around the world and find that the percentages of children aged 10–14 living away from their mothers ranges from 0.9 in Tunisia, 4.2 in Sri Lanka, 5.7 in Brazil, 24 in Senegal, 29.4 in Ghana, and 40.9 in Liberia. Isiugo-Abanhie (1985) argues that ‘nowhere is it as institutionalized as in parts of West Africa’ (pp. 56).

> 8The number of children ever born includes children who have died.

8
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Huang, J., A. Gulati, and I. Gregory, eds. 2017. _Fertilizer Subsidies: Which Way Forward?_ IFDC/FAI report. https://ifdcorg.files.wordpress.com/2017/02/fertilizer-subsidieswhich-way-forward-2-21-2017.pdf.

Islam, M., & Beg, S. (2021). Rule-of-Thumb Instructions to Improve Fertilizer Management: Experimental Evidence from Bangladesh. _Economic Development and Cultural Change_ , _70_ (1), 237-281.

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# **SUMMARY**

Agriculture is an important pillar of economic development in Africa and many countries in the region face significant socio-economic and technological challenges to promote growth in rural areas. In addition, climate change has been recognized as an important factor that has the potential to threaten development efforts in the agricultural and rural sector in many African countries, in particular in regions with a high percentage of rainfed cropping systems.

The detailed analysis of current cropping areas in Africa presented here reveals significant climate sensitivities of cropland density and distribution across a variety of agro-ecosystems. Based on empirical climate–croplands relationships, cropland density responds positively to increases in precipitation in semi-arid and arid zones of the sub-tropics and warmer temperatures in higher elevations. As a result, marginal increases in seasonal precipitation lead to denser cropping areas in arid and semi-arid regions. Warmer temperatures, on the other hand, tend to decrease the probability of cropping in most parts of Africa (the opposite is true for increases in rainfall and decreases in temperatures relative to current conditions).

While current climate–cropland relationships allow the geographic delineation of temperature and precipitation sensitivities, projections of climate parameters derived from coupled Atmosphere-Ocean General Circulation Models (AOGCMs) provide a sound basis for assessing the impact of future climate. Despite discrepancies and uncertainties in climate model output, the analysis suggests that cropland area in Africa is likely to decrease significantly in response to transient changes in climate. The continent is expected to have lost on average 4.1% of its cropland by 2039, and 18.4% is likely to have disappeared by the end of the century. In some regions of Africa the losses in cropland area are likely to occur at a much faster rate, with northern and eastern Africa losing up to 15% of their current cropland area within the next 30 years or so. Gains in cropland area in western and southern Africa due to projected increases in precipitation during the earlier portions of the century will be offset by losses later on. In conjunction with existing challenges in the agricultural sector in Africa, these findings demand sound policies to manage existing agricultural lands and the productivity of cropping systems.

3
with

- _(7) PZ = I, X1 ITIIT_

- (8) _QV =IN - PV_

and

> For any integer m, let _Im_ be an m xl vector of ones. The idempotent matrix Qv transforms the original variables into deviations from individual means, and Pv transforms original variables into a vector of individual means.

# **4. Data and Estimation Results**

# _(i) Dataset_

In order to perform this analysis, a primary dataset was recently collected with detailed information on several hundreds industrial plants in Zhenjiang, covering the period 1993 to 1997. In 1997, the total number of plants included in our sample is 640. Of these, 26% are state owned enterprises, the majority being collectively-owned enterprises. Most of the plants in the dataset are medium and small enterprises, with only 4% of the enterprises being large. These large plants, however, account for approximately one third of the total value of output of the enterprises in the dataset. A further breakdown indicates that the timber processing, the food processing and the petroleum processing industries represent the largest number of sectors in our dataset with 17.2%, 15.6% and 10.2% of the plants, respectively.

Table 1 describes the water pollution discharges of the firms in 1997. In brackets is the number of firms on which the entry has been computed (since the information was not always available for all the firms in the dataset). Note that a large proportion of the 13
(Tables B3 and B4).

As shown by Ib ́a ̃nez et al. (2024), the regularization program led to improvements in household consumption, income, and overall health, including mental health for adults who participated. These positive changes in economic and health conditions are inconsistent with any potential increase in domestic violence. Additionally, the program did not result in a disproportionate increase in female income compared to male income. Our analysis found no evidence of genderbased differences in the program’s effects on either income or consumption. Therefore, we can confidently rule out higher domestic violence as a factor underlying the observed effects.

These results reinforce our interpretation that empowerment—especially female empowerment— propels the patterns. Once their fear of deportation and other repercussions drops significantly, these migrants report more crimes to the police. This is particularly true for crimes such as domestic violence and sex crimes that disproportionately affect women. Qualitative interviews with Venezuelan migrants reinforced our sense that having the PEP migratory status empowered them to report human rights abuses without fearing punishment.

# **V. B What do PEP holders say about filing crime reports?**

We also leverage data from the Venezuelan Refugee Panel Study (VenRePs) that interviewed a representative sample of Venezuelan PEP holders and non-holders in 2021 to examine the PEP’s effects on migrant welfare.<sup>18</sup> One survey question asked respondents if they had reported being a victim of a crime to the police or any other institution. The responses are in Figure 4. Results for the full sample are in the left panel and by gender in the right panel. First, the results show strikingly low reporting rates across the board for migrants who were victims of a crime. Second, they confirm that migrants with the PEP reported crimes at higher rates than migrants without the PEP. In fact, 9.9 percent of household heads with PEP reported a crime; this number is lower for those without PEP (8.7 percent).

Third, the results by gender confirm our main conclusions by showing small differences between men with and without the PEP (of less than one percent) and more substantial differences for 18See Ib ́a ̃nez et al. (2024) for details of the sampling strategy.

29
measurements and analysis of personality traits in empirical studies (Dal Bo, Finan, and Rossi, 2013; Callen et al., 2015).

The insights from this paper are also relevant for various strands of the wider literature. In light of the large debate about whether the worldwide increase in schooling is leading to measurable and sustained gains in learning (Pritchett and Beatty, 2015), having widely comparable measures of cognitive abilities, that can be measured for adults, outside of the classroom, and in a variety of settings, is arguably key. Certain large data collection efforts covering wide and heterogeneous populations, such as the Young Lives Surveys or the World Bank STEPS surveys (Pierre et al., 2014), are now including measures for noncognitive abilities and personality traits. Increasingly such measures are also included in targeted surveys for impact evaluation purposes, most directly when interventions aim to change noncognitive traits (Bernard et al., 2014; Groh, McKenzie, and Vishwanath, 2015; Blattman, Jamison, and Sheridan, 2016; Ghosal et al., 2016; Adhvaryu, Kala, and Nyshadnam, 2016) but also when changes in noncognitive abilities are seen as potential mechanisms to explain changes in final outcomes (Blattman and Dercon, 2016). Other recent work focuses on the long-term impact of external factors during childhood on noncognitive outcomes of adults (Leigh, Glewwe, and Park, 2015; Krutikova and Lilleor, 2015). Finally, there is a renewed interest and widening literature on learning, technology adoption and agricultural productivity in developing countries (Jack, 2011; de Janvry, Sadoulet, and Suri, 2016), for which having reliable measures of agricultural knowledge and learning is key.

The paper is organized as follows: the next section provides more information about the context, the instrument and the implementation of the survey experiment. Section 3 provides the description of, and rational for, the calculation of the improved constructs, and discusses reliability and internal consistency. It also shows predictive validity results, using agricultural yield and practices as outcome variables, and comparing results with the naïve and the improved constructs. Section 4 presents additional analysis related to measurement error and derives lessons and practical recommendations for skills measurement. Section 5 concludes and the appendix provides more details on methodologies and data, as well as additional empirical results.

# **2. THE SETTING, THE SAMPLE, AND THE QUESTIONNAIRE DESIGN**

# **2.1. Setting**

6
criteria related to education, sector of occupation, or job sponsorship. To be eligible to apply for PEP, Venezuelan forced migrants only needed to: (i) have previously registered in RAMV; (ii) reside in Colombia by August 2018, when the PEP decree was issued; (iii) have a valid Venezuelan ID or other proof of Venezuelan citizenship; and (iv) have no criminal record or deportation order. PEP processing was free and migrants had to submit applications online. According to official records, 442,462 Venezuelan forced migrants registered in RAMV, and 64 percent of them (281,307 individuals) applied for PEP. The RAMV registry was implemented in 441 of the 1,122 municipalities in Colombia, including those with the highest number of Venezuelan migrants. The RAMV census was advertised on social media, in local newspapers, and through local organizations to support forced migrants.

# **III DATA**

We estimated PEP’s impacts using data from the first wave of the Venezuelan Refugees Panel Survey (VenRePS) that was administered to 2,232 households of forced migrants in Colombia. This section describes the sampling frame, data collection process, and outcomes measured by VenRePS. The methodological design was informed by a qualitative study conducted through 42 semi-structured phone interviews with forced migrants who had and had not registered in RAMV. The purpose of this study was to identify potential challenges to building a sample of RAMV and non-RAMV migrants, and to understand the factors that influenced one’s decision to register (or not) in the RAMV and PEP. Some lessons for the design of the sampling frame and data collection protocol are briefly mentioned below, while the overall results of the qualitative study can be found in Romero and Uribe (2021).

# **III. A Sampling frame**

It is challenging to design sampling frames for forced migrants because they are a vulnerable and hard-to-reach population. This is particularly true in Colombia, where there are no and Venezuelan are mobile and refugee camps migrants highly dispersed throughout the country. For this reason, we drew the sample to be representative of four geographical regions that host the largest share of Venezuelan forced migrants, according to the latest pop11
|||Free cash,liquid assets, committedfacilities as % ofdebt service|
|---|---|---|
|||Debt maturing within 12 months as a % of self liquidity and committed<br>facilities|
|||Free cashandliquid assets as % ofoperating expenditures|
|||Cash operating surplus / interest expenditures|
|||Payables as a % oftotalexpenditures|
|||Receivables as a % oftotal revenues|
||Debtmanagement||
||Interestrate/ currency|/ counterpartyrisks|
||Use ofderivatives||
|**7.**|**Debt Burden**||
|||Interest payments as a % of operating revenues|
|||Debt service as a % ofoperatingrevenues|
|||Direct debt as a % ofoperatingrevenues|
|||Net direct debt as a% ofoperatingrevenues|
|||Net taxsupported debt as a % ofconsolidated operatingrevenues|
|||Netfinancial liabilities as % consolidated operatingrevenues|
|||Direct debt as a % of local GDP|
|||Total public sector debt as a % of combined public sector revenues|
|||Direct debt plus guaranteed debt, as a % ofoperatingrevenues|
|**8.**|**Off balance sheet lia**|**bilities**|
||Financial healthofpu|blic enterprises|
||Quasi-government pr|ograms|
||Public-private partner|ships|
||Bailout ofprivate com|panies|
||Source: Standard & P|oor’s (2009)|

44
and: _Log_ ( _Invitj_ ) = _c_ + _β_ 3 _Smalli ∗ Inflationjt_ + _β_ 4 _NoFinanceijt_ + _β_ 5 _NoFinanceijt ∗ Inflnjt_ + _β_ 6 _Smalli ∗ NoFinanceijt_ + _β_ 7 _Smalli ∗ NoFinanceijt ∗ Infljt_ + _β_ 8 _countryj ∗ yeart_ + _β_ 9 _firmi_ (12) The intensive margin deals with the difference in investment levels between large and small investing firms. Therefore, the dependent variable for the intensive margin is the log of real investment. Firms that do not invest drop out of the sample. These regressions aim at assessing whether, conditional on investing, inflation has a differential impact on investment in large and small firms. In the first specification, _AggInvjt_ is the real aggregate investment of country _j_ . The _AggInvjt_ and _Inflationjt_ variables control for macroeconomic condition of country _j_ at time _t_ . In the second specification, the _countryj ∗yeart_ fixed effects capture macroeconomic condition of country _j_ at time _t_ .

In all specifications and regressions, we weight the firms by their representative weights (recall that the sample is collected by a stratified random sampling strategy), so that the weighted sample is truly representative. We also cluster the standard error at the country level, since investment of firms in a country can be correlated, and adopt robust standard errors (i.e. allowing the variance of the error terms to vary).

# **4.2 Results: Extensive margin**

This section present the results for the extensive margin: we calculate the differential impact of inflation on the decision to invest in small and large firms. The dependent variable is the dummy variable which takes the value of 1 if the firm invests. We are mostly interested in the coefficients of the _SmallInflation_ interaction, and we highlight significant coefficients. Overall, we see that higher inflation disproportionately discourages small firms to 20