rafmacalaba/data-use-mentions-extended huggingface dataset:
informal. Exploring this in greater detail is an important area for follow-up research with potentially far-reaching implications for Ukraine’s future development.

The paper is structured as follows. Section 2 provides conceptual and methodological background by discussing evidence of the aggregate impact of the invasion and details of constructing the sample frame and ways to infer the size of the informal sector. Section 3 provides evidence from our data at household and farm level for 2021 and 2022 to show how asset positions and factor market participation changed with the invasion. Section 4 provides evidence on how direct and indirect war effects changed land allocation, profitability, and productivity by farm size. Section 5 concludes and draws out policy implications.

# **2. Motivation and context**

This section discusses studies that assessed the impact of the Russian invasion of Ukraine on agricultural exports and global food security, the channels through which such impacts could come about, and the micro data underpinning such estimates. It highlights how representative farm level data can complement existing data sources and, by providing information on economic factors at a more granular level, informs estimates of negative conflict impacts and ways to try and minimize them.

4
**Table 4: Summary Statistics derived from classroom observation instruments (Level 1 variables)**

|||Al|l|||Ru|ral||Ur|ban and|Semi-Urb|an|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Mean|SD|25 ptile|75 ptile|Mean|SD|25 ptile|75 ptile|Mean|SD|25 ptile|75 ptile|
|**SDI**|||||||||||||
|Share of time teaching|0.85|(0.25)|0.81|1.00|0.8378|(0.25)|0.79|1.00|0.90|(0.20)|0.91|0.99|
|Share of time teaching and learnin|0.75|(0.28)|0.61|0.98|0.74|(0.28)|0.60|0.98|0.78|(0.28)|0.62|0.98|
|Good teacher demeanor|0.67|(0.23)|0.57|0.86|0.68|(0.23)|0.57|0.86|0.63|(0.20)|0.57|0.75|
|Good pedagogical practice|0.56|(0.18)|0.49|0.69|0.56|(0.17)|0.49|0.69|0.55|(0.19)|0.48|0.
Table (G2) Impacts of the Program on Assimilation Gap

|**Outcomes**|**Treatment**|**(se)**|**Treatment**<br>***Refugee**|**(se)**|**Refugee**|**(se)**|**ctrl. mean**|**(sd)**|**N**|
|---|---|---|---|---|---|---|---|---|---|
|Housing Expenditure (PC) PPP|30.02|(97.82)|-38.97|(93.38)|-31.25*|(18.05)|57.04|(274.59)|2,491|
|Log total consumption (PC) PPP|-0.13|(0.22)|0.17|(0.25)|-0.83***|(0.07)|7.76|(0.68)|1,482|
|CESD Score|-0.24|(0.16)|0.41|(0.30)|-0.05|(0.05)|0.02|(0.99)|2,471|
|Child Strengths and Diffculties|-0.24|(0.32)|0.59|(0.39)|-0.01|(0.11)|0.01|(1.00)|1,321|

**_Notes_** :

- The table shows the regression results on pre-specified main outcomes using the 2022 neighbor survey data _and_ 2021 refugee survey data. Each row is its own dependent variable.
to nd the right balance between promoting necessary changes in legal rules and investing to increase the eciency of the judicial institutions in charge of enforcing. Judicial decisions in bankruptcy are often inuenced by the goal to preserve employment in nancially distressed rms. Araujo et al. (2021) construct a new court-level measure of pro-labor bias based on the text of judicial decisions and exploit the random assignment of cases to courts within judicial districts in the state of São Paulo in Brazil to study the eect of pro-labor bias on labor market outcomes. They motivate their focus on Brazil for a number of reasons. First, Brazil has relatively strict labor-protection laws and a judicial system often described by local observers as biased in favor of debtors and workers. They cite survey evidence that shows that a large fraction of the Brazilian Judiciary perceives itself as having a redistributive role. Second, according to the data collected for the paper, there is a large degree of variation in the degree of pro-labor bias across Brazilian courts dealing with bankruptcy cases. They nd that workers of rms assigned to high-pro-labor courts experience 4.4 percent lower post-bankruptcy earnings. They also try to identify what explains the negative eect of pro-labor bias on workers' earnings. They show that courts with higher pro-labor bias tend to facilitate the continuation of insolvent rms, by either rejecting liquidation requests at a 27
Occasionally, the RBL borrowing entity is a joint-venture between the SOE of the borrowing country and a commercial company from the lender side or a special purpose vehicle (SPV) that has been formed. In 2008, a consortium of Chinese companies led by Sinohydro and China Railway Engineering Corporation (CREC) formed the joint-venture company Sino Congolaise des Mines (Sicomines) with DRC’s state-owned mining company La Générale des Carrières et des Mines (Gécamines). The Chinese companies owned 83% of the copper/cobalt venture. This newly formed joint venture company, Sicomines, then borrowed from the Eximbank [#9]. This loan also has an explicit financial guarantee from the government to 10 11 repay the loan in case the designated revenues were not sufficient to fully repay the loan. As the modified loan agreement states : Article 10.3. « The Democratic Republic of Congo has guaranteed repayment of the debt, in line with the current Convention on Collaboration, through the granting of mining concessions or concessions for other natural resources to SINOHYDRO if repayment of the loan due to JV Minière falls short of the repayment needed to cover its investment in the Infrastructure Projects. » Article 13.3.4. « In the case that JV Minière has not been reimbursed for the investments and interests from the Infrastructure Projects within 25 years of the start of the loan, the Government of the Congo is committed to paying the outstanding balance by any means necessary. » Loans taken by Republic of Congo’s Société Nationale des Pétroles du Congo (SNPC) from commodity traders were kept off the Ministry of Finance’s books. The IMF and other observers became aware of these loans in June 2017 as soon as SNPC experienced difficulties servicing them.12 [#19] [#21] [#22] Publicly available data on sovereign guarantees that support SOE debt is sparse (see section 5/b). It was therefore difficult to ascertain how commonplace such arrangements were.

# c. RBLs by type of lender

From our
|796|8.7|
|Turkmenistan|36.2|6712|5.4|
|Uzbekistan|67.8|2128|31.9|

Table 2: Sectoral shares of GDP (percent)

||Primary|Manufacturing|Non‐tradables|
|---|---|---|---|
|China‐3|14.7|40.7|44.7|
|Kazakhstan|20.5|34.7|44.8|
|Kyrgyzstan|17.3|19.0|63.7|
|Pakistan|29.5|24.9|45.6|
|Tajikistan|29.4|23.3|47.3|
|Turkmenistan|37.0|28.0|35.0|
|Uzbekistan|21.8|33.2|45.0|

**_Trade:_** Trade values are reported on a country to country basis, using value data from the BACI database of CEPII, 2016, www.cepii.fr (Gaulier and Zignago 2010). These data are split by sector into agricultural and mining trade (primary production) and manufacturing and services trade.  For the countries we consider, the trade data report the value of total trade in business services to be just 1.4% of the value of total trade in manufacturing, and we combine this trade and business services

10
Focusing on mutual funds offers important advantages. First, mutual funds, unlike other types of institutional investors, such as hedge funds, pension funds, and individual international investors, face regular reporting requirements. Thus, asset-level portfolios for mutual funds can be constructed and traced over time since their inception. Second, the structure of mutual fund families allows us to make within-family comparisons of the behavior of “specialized funds,” which can invest only in certain countries or regions, and “global funds,” which can invest anywhere in the world and thus have access to a larger set of instruments (more firms from more countries). Knowing that a fund within a mutual fund family holds certain stocks is an indication that the transaction costs to hold them are not exceedingly large and that those stocks are indeed desirable (at least to other fund managers within the same family). Moreover, information about those stocks has already been collected at the family level and, in principle, might be available to all managers in that family. Therefore, the relevance of information sharing, transaction costs, and industrial organization aspects discussed in the literature can be analyzed by comparing portfolios across funds within the same mutual fund family and across families. In addition, the returns of specialized funds can be compared to those of global funds, shedding light on the payoffs of different investment strategies.

We collect portfolio holding and return data for the universe of actively managed open-ended U.S. mutual funds established to purchase assets around the world. The data on holdings contain asset-level annual portfolios between 1991 and 2005. We work with a total of 499 fund families and 1,904 funds. The total number of fund-year observations is 8,420 and the total number of asset-level holdings for all funds in all years is 1,359,750. The portfolio holdings have been matched to identify the country to which each stock belongs, tracking holdings over time. We use daily returns at the fund level between September 1989 and June 2006 for 36 fund families
of the country could also help to uncover an underlying relationship between school attendance and the severity of violence. However, there is little evidence of this being the case. Column (8) separates fatalities into those involving Al-Qaeda in the Arabian Peninsula (AQAP), a prominent terrorist organization operating in Yemen (e.g., OCHA 2019a), and the rest of conflict fatalities; and column (9) estimates the impact violence has separately in regions controlled by the IRG and in regions controlled by DFA forces. However, again, there is little relationship between school attendance and the location of violence in either case.

Combined, there appears to be little evidence of school attendance being correlated with the location of violence in the year of surveys analyzed. However, it is important to note that following the onset of conflict, school attendance did significantly drop across the entire country relative to the last nationally-representative estimate from the 2014 Household Budget Survey (e.g., WFP 2019b). Thus, these results do not imply that the location of violence has no effect 25When using the number of fatalities as the independent variable instead of the natural logarithm, there is a positive relationship that is statistically significant at the 5 percent level. However, this is entirely driven by 39 observations in one district that had 613 conflict fatalities in one month, which is the highest number of district fatalities for any month in the sample. If these 39 observations are dropped, the variable is right-censored at the second greatest number of fatalities in a month (483), or the independent variable is the natural logarithm of conflict fatalities, there is little evidence of any relationship between school attendance and the severity of violence. Importantly, this district with 613 conflict fatalities in one month is well-represented in every other survey in addition to the survey in which there were 613 conflict fatalities, and in each of those other surveys, the district remained one of the most violent in the country.

> 26All logit specifications estimated use only the most recent
J. (2013). Economic growth, comparative advantage, and gender differences in schooling outcomes: Evidence from the birthweight differences of Chinese twins. _Journal of Development Economics_ , 104:245–260.

- Solon, G. (1999). Intergenerational mobility in the labor market. In Ashenfelter, O. and Card, D., editors, _Handbook of Labor Economics_ , volume 3 of _Handbook of Labor Economics_ , pages 1761–1800. Elsevier.

- Solon, G. (2004). A Model of Intergenerational Mobility Variation over Time and Place. In Corak, M., editor, _Generational Income Mobility in North America and Europe_ , pages 38–47. Cambride University Press.

- Stiglitz, J. (2012). _The Price of Inequality_ . W. W. Norton Company.

- Torche, F. (2015a). Intergenerational Mobility and Equality of Opportunity. _European Journal of Sociology_ , 56(3):343–371.

- Torche, F. (2015b). Intergenerational Mobility and Gender in Mexico. _Social Forces_ , 94:5633–587.

38
the 2015 and 2016 waves. In the 2016 survey round, the information inervention end-line, 28.3 percent of respondents from the 2015 baseline had attrited from the sample.

# **3.2 Information Intervention**

To provide relevant information to migrants randomly selected for treatment, pamphlets were developed through extensive consultations with relevant program managers and staff responsible for administering health insurance and pension programs in each city. This pamphlet discusses city-specific features of health insurance and pension programs, and summarizes program rules, which vary significantly across cities and for different categories of employment (e.g., wage employment and self-employment). In discussions with local bureaucrats, the rules, premiums, and the benefits for each type of worker (as shown in Online Appendix A.2) were verified. Online Appendix A.3 provides an example of the easy-to-understand pamphlet provided as a guide to workers in Dongguan. In addition, the pamphlets use lay terms to highlight the risk-management benefits of participating in pension and health insurance programs.

The information intervention was implemented between early December 2015 and the end of January 2016. The city-specific information pamphlets were distributed to a randomly selected sample of 35% of the 2015 RUMiC sample in 12 of 15 survey cities (and the randomization was done within cities). As the Shanghai RUMiC sample size is significantly larger than the rest of the cities, we randomly selected 25% rather than 35% of the 2015 sample for treatment. This decision was driven by cost and time considerations.<sup>10</sup> The information intervention was implemented by 33 enumerators, of which 64% were university students (either undergraduate or graduate) and the rest were RUMiC survey firm enumerators.<sup>11</sup> In each city, enumerators received classroom and field training from one of the coauthors over a two day period. In the intervention, enumerators first presented a small gift and an information pamphlet to each of the randomly selected sample respondents. After a short introduction, the enumerator
# **Abstract**

Malnutrition is associated with an inadequate diet, poor health and sanitation services and insufficient care for young children. A combination of income growth and nutrition interventions are therefore suggested to adequately tackle this issue (Haddad et al. 2003), yet evidence to support this claim is often not available, especially for African settings. This paper evaluates the joint contribution of income growth and nutrition interventions towards the reduction of malnutrition. Using a four round panel data set from northwestern Tanzania we estimate the determinants of a child’s nutritional status, including household income and the presence of nutrition interventions in the community. The results show that better nutrition is associated with higher income, and that nutrition interventions have a substantial beneficial effect. Policy simulations make clear that if one intends to halve malnutrition rates by 2015 (the MDG objective), income growth will have to be complemented by large scale program interventions.

**Keywords:** nutrition, program evaluation, income growth, Tanzania, MDG

ii
# **Table 3.1.1 : Additional Argentine Data Included in AD-ARG-v1.0.xls**

|**Column**|**Variable Name**|**Description**|
|---|---|---|
|**In AD-AR**|**G-Master:**||
|**U.**|**INIT_GP**|The government publication initiating the investigation|
|**V.**|**P_GP**|The government publication containing the preliminary finding|
|**W.**|**P_MEASURES_GP**|The government publication containing the preliminary measures|
|**X.**|**P_AD_DUTY**|The preliminary antidumping duty imposed with details on the<br>measure(s).|
|**Y.**|**F_GP**|The government publication containing the final finding|
|**Z.**|**F_MEASURES_GP**|The government publication containing the final measures|
|**AA.**|**F_AD_DUTY**|The final antidumping duty imposed with details on the measure(s).|
|**AB.**|**F_AD_MARGIN(min)**|The final minimum dumping margin found|
|**AC.**|**F_AD_MARGIN(max)**|The final maximum dumping margin found|
|**AD.**|**DUTY_RULE**|Either FD- Full duty or LD- Lesser Duty, where full duty implies the full<br>dumping margin was imposed as an antidumping duty while lesser duty<br>implies that the antidumping duty imposed was less than the full margin.<br>_Source:_Nogués and Baracat (2005)|
|**AE.**|**METHOD**|Methodology used to determine the dumping margin (
# **5.  Further Robustness Checks**

I next address a variety of potential concerns about the robustness of the benchmark estimates of the multiplier presented in Table 4. Given the noisy and highly-imperfect data on government spending and output in many of the developing countries that comprise my sample, a first concern is that the results in Table 4 might be driven by a small number of influential observations. To investigate this possibility more systematically, I use a procedure suggested by Hadi (1992) to identify influential observations in the reduced-form and first-stage regressions (the ratio of the corresponding two slope coefficients being the 2SLS estimate of the multiplier). I then re-estimate the OLS, first-stage, and 2SLS regressions, excluding these influential observations. The results of this first robustness check are reported in the first three columns of Table 6. The OLS estimates of the multiplier change very little relative to the benchmark results. The 2SLS estimates of the multiplier are virtually unchanged once influential observations are removed, ranging from 0.37 to 0.39, and moreover they are slightly more precisely estimated than before. This is in part due to an even stronger first-stage relationship after removing influential observations in the IDA and high-disbursement samples, in which the first-stage F- statistics jump to 41.2 and 30.3, respectively.

A second potential concern is that I am estimating multipliers using data on total government _spending_ , whereas much of the theoretical and empirical literature on multipliers has focused on government _purchases_ , i.e. total spending less interest payments and net transfers. Unfortunately, data on the disaggregation of total government spending into purchases, interest payments, and net transfers is not available for the large set of developing country-year observations included in this paper. As a first partial step towards addressing this concern, I use readily-available data on interest payments on external public and publicly-guaranteed debt to net out this portion of interest expenditures from total government spending.<sup>21</sup> I then re-estimate the spending multipliers using this proxy for government
Kubota, Isao. "Roles that Governments Play in Developing, Developed States." Japan Times, (June 17, 1996), p.<sup>1 5</sup> .

- Linz, Juan J., Seymour Martin Lipset, and Bunger Pool. "Social Conditions for Democracy in Latin America." Latin American Barometer Survey Analysis. New Haven, Conn.: Yale University.

- Magdoff, Harris. Imperialism: From the Colonial Age to the Present. New York: Monthly Review Press, 1983.

- Marx, Karl. Capital. A Critique of Political Economy. vol. 1., New York: International Publishers, 1966/1967.

- Mazumdar, Krishma. "An Analysis of Causal Flow Between Social Development and Economic Growth: The Social Development Index," in The American Journal of Economics and Sociology, vol 5, no 3, (July, 1996), 361-381.

Milliband, R. State in Capitalist Society. New York: Basic Books, 1969.

- Mokoli, Mondonga M. "La Democratie dans le F6odalisme: Tout le Noeud du Blocage de la Transition Vers la Troisieme Republique au Zaire." in Bulletin de la Faculte de Droit, no 3, (septembre 1994), 83-104.

- Mokoli, Mondonga M. State Against Development: The Experience of Post-1965 Zaire. Westport, Conn.: Greenwood Press, 1992.

- Mokoli, Mondonga M. The Transition Towards Democracy in Post-1990: Contradictions and Dilemma. San Francisco, London, and Bethesda: International Scholars Publications, 1997.

- Moore, Barrington Jr. Social Origins of Dictatorship and Democracy: Lord and Peasant in the Making of the Modem World. Boston: Beacon Press, 1967.

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- Nelson, Joan M.,
analysis to receive the same forethought. Impact evaluators frequently face a lack of cost data and lack of standards for performing analyses. Moreover, some economists—the discipline that churns out most of the IE work in international development—relate that Cost analysis does not “feel like” microeconomics, and together with a lack of training in Cost analysis methods and the challenge of getting it right even if the data are available, make the cost of doing the analysis greater than the benefit—from the researcher’s perspective (Evans, 2016). Together, these factors conspire to expose researchers to risk of costly critique from peer reviewers—convincing many to avoid the exercise altogether.

When it is performed, VFM analysis often seems to come as an afterthought, with cost data inquiries sometimes made well after a project has been closed. This is reflected in the general lack of detail on VFM analysis in impact evaluations, including those done at the World Bank and on Bank projects where cost data should be easier to procure, and Cost analysis should be more valued than analysis done as academic exercises.

For example, of the less than 19 percent of World Bank impact evaluations that include any type of Value for Money analysis, only 13 percent—or less than 2.5 percent of World Bank impact evaluations—reported unit costs of inputs. When cost data are not explicitly available, they are estimated—sometimes borrowing from other studies— but more frequently without meaningful details of how Costs were estimated. Such ex post data collection is prone to recall bias and underestimating expenditures (Evans and Popova 2016). About two-fifths of the World Bank’s impact evaluations do not indicate which cost elements are included in the analysis. Apart from the very real challenges of using accurate cost data, it is extremely rare for World Bank IE-VFM studies to indicate parameters used for basic assumptions in Cost analysis: discount rates, exchange rates, or time horizons, for example. In general, there seems to be a clear disconnect between the