rafmacalaba/data-use-mentions-extended huggingface dataset:
1. The shock is distributional neutral, and all children lose the same amount. In our intermediate scenario, this increases the share of children below minimum proficiency by 5 percentage points, to 45%. This share is 42% in the optimistic scenario and 49% in the pessimistic scenario.

2. The distribution skews, and the most disadvantaged students lose most. In this scenario, the share of children below minimum proficiency goes up by 10 percentage points (p.p.), to 50%. In our optimistic scenario, this goes up by 7 p.p., while in the pessimistic scenario, this goes up by 13 p.p. Note that the relative impact of the same (pessimistic scenario) is significantly larger when measured as the share of students (+34%) than when measured as the mean score (-6.1%), so a substantial mass of students near PISA Level 2 might fall below this threshold.

3. The distribution flattens, and students at the top pull ahead, while students at the bottom fall behind. Results fall in between the two extreme scenarios already mentioned.

The intermediate scenario of simulation 3 suggests that the share of students below this level will increase by 10 percentage points.<sup>67</sup> We use the PISA distribution database to simulate the effects of COVID-19 in terms of the share of children below this minimum proficiency threshold (figure 10). At present, 40% of learners fall below proficiency level 2 (their scores are lower than 407 PISA points).<sup>68</sup> This will be accompanied by a much larger effect in terms of the learning “gap” – the minimum learning required to secure a basic understanding of the material. A related measure – that of “severity” puts more weight on those farther from the threshold. The latter more than doubles even in the most optimistic scenario.<sup>69</sup> In regions such as ECA
demographic characteristics and health related controls.

# **3. Data**

The COVID-19 data is taken from the RIVM.<sup>8</sup> The first data snapshot includes all confirmed cases as of March 22 (a total of 4,004 with known residence out of 4,157 confirmed cases). A second snapshot of confirmed cases was taken on March 30 and includes 11,258 cases with known residence out of 11,750 confirmed cases. The confirmed COVID-19 hospital admissions are taken from the same source approximately 1 week after the first data snapshot (31 March, a total of 4,562 with known residence out of 4,712 admissions from a total of 12,595 confirmed cases). While some cases are reported immediately, a share of the cases follows a typical delay of up to 1-2 days after the actual case or hospitalization confirmation. Both the confirmed cases, as well as confirmed hospital admissions, are coded by residence (not by hospital addresses).

On March 31, approximately 37% of confirmed cases were also hospital admissions, highlighting that case detection is likely biased toward more severe cases.<sup>9</sup> Within one week, the number of hospital admissions exceeded the confirmed cases of the previous week, indicating that the time between confirmation and hospitalization likely spans only a few days. Cases are reported to the RIVM by the Municipal Health Service (GGD).The GGD is organized as collaboration between municipalities to provide base level public health service

> 8. https://www.rivm.nl/coronavirus-kaart-van-nederland-per-gemeente

> 9. For example, early estimates based on Chinese cases indicated that the hospitalization rate of elderly, the most vulnerable population, was only 18.4% (Verity et al., 2020).

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the cash equivalent of the subsidy than with subsidized inputs at current market and agronomic conditions, unless they are able to defer the selling of their output to the lean season.

# _Profitability of Government Recommended Rates of Nitrogen Application_

As a final exercise, the study investigates the profitability of fertilizer use at rates recommended by the Ministry of Agriculture and Food Security of Malawi (MoAFS). The government recommended rate of nitrogen application in maize production is 35kg/ha, 69kg/ha or 92kg/ha depending on the geographical location. The corresponding NUE of the nitrogen recommended rate was computed at the plot-level using the estimates from the production function estimated via the “plot” multilevel model. With this NUE and the prices of nitrogen and the various prices of maize, the MVCR of the government recommended rates is computed to be 1.77 at farm gate maize price, 2.89 at the lean season maize price, and 4.71 at import parity maize price (figure 7).

Thus, compared to the actual rate of nitrogen application, the government rate of application is about 116% to 119% more profitable depending on the price at which maize is valued (figure 7). These results also show that, compared to the actual rate of application, the number of gardens on which fertilizer is profitable is between 26 and 50 percentage points higher. Figure 8 reveals that the actual rate of N application on a majority (about 82%) of plots is lower than the government recommended rates. This suggests that fertilizer profitability can be improved by encouraging farmers to adopt the government recommended rates.

# **Conclusions and Policy Recommendations**

This study uses two-wave nationally representative household panel data from Malawi to estimate the profitability of fertilizer use. Specifically, the study assessed the extent to which 26
variable indicators for being employed in the years 2012 and 2006, according to the extended definition of labor force participation. The independent variable of interest Internet job search is the first difference in dummy variable indicators for Internet use for job search between the years 2018 and 2012. The regressions also control for the change in Internet access at home between 2018 and 2012. Regressions also include a vector of individual control variables first differenced between the years 2012 and 2006. The controls in first difference are the following: the change in dummy variables for being married, the change in three dummies for the individual’s educational attainment (primary or preparatory education, secondary education either general or vocational and above secondary education either post-secondary institute or university and above, and the reference category is no educational degree either illiterate individuals or literate individuals without any diploma), the change in dummy variable for rural areas as well as the change in dummies for the various geographical regions (Greater Cairo, Alexandria, and Suez cities, Urban Lower Egypt, Urban Upper Egypt, Rural Lower Egypt, and Rural Upper Egypt). The dependent variable mean is reported in the last row.

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evaluating the shifts in the steady state values of output, pollution, and consumption (Figure 8). The steady state for output is lower under a higher elasticity with regards to pollution. However, pollution is also lower in steady state, reflecting a lower output overall. The elasticity thus acts as a wedge in the model. This suggests that steady state production should be lower in countries that have a higher share of their labor exposed to pollution. There are thus potentially strong economic benefits from reducing emissions. The reduction in emissions, e.g., through a carbon tax, would lower pollution, which has co-benefits in terms of higher output and consumption.

# **6.1 Robustness**

We design our robustness check around a propensity score matching dataset (see Heckman et al. (1997)). This allows us to compare treated areas (the ones that built power stations) with control areas (those that did not build power stations). These areas would share similar characteristics in terms of wages, pollution, and labor productivity. Using this data set we test the strength of our exogeneity assumption, as well as whether the labor productivity responses are purely attributable to productivity effects and not also due to changes in marginal costs.

The propensity score matching is done in two steps. First, a logit model is estimated to determine the conditional probability (in this case the score) for a city to build a power station given its pre-treatment characteristics (i.e., real wages, labor productivity, pollution levels, and multi-level effects such as year, province and sector characteristics). In the second stage, the scores for creating the matched control sector group are based on a nearest-neighborhood matching with a replacement procedure: 13
Policy Research Working Paper 9656

# **Abstract**

Improving women’s economic status has been presented in theory as a protective mechanism against intimate partner violence. Using panel data from 2011–16 for the most populous 20 percent of municipalities in Brazil, the analysis tests if the gender wage gap is causally associated with three administrative measures of violence against women: homicides, overnight hospitalizations for assault, and incidents of domestic violence reported by attending health workers about patients. The analysis finds that a narrowing in the gender wage gap leads to a reduction of homicides of women, especially among younger women and in municipalities with a low Human Development Index. The impact on less severe forms of violence, also captured in medical reports, depends on the context. A reduction in the gender wage ratio triggers a decrease in reports in municipalities that have police stations specifically designed to address crimes against women, but it has the opposite impact in the absence of such services. The results suggest that while improvements in gender equality in the labor market curtail the most severe forms of violence against women, they need to be complemented by policies directly focused on women’s safety to reduce less severe violence effectively.

This paper is a product of the Office of the Gender Innovation Lab, Latin America and the Caribbean Region. 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 eperova@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
# **1. Introduction**

While there is a large literature on the investment and productivity effects of land rights formalization, the impact of individuals’ tenure security under traditional regimes has received little attention. This is a key knowledge gap because most of Africa’s rural land is managed under customary tenure and long-term rights by vulnerable groups such as women, migrants or herders may be the first to be attenuated in view of increasing land scarcity. To help fill this gap, we use unique survey data from Malawi to show that individuals’ long-term rights of bequest and sale significantly affect investment and cash crop adoption; that the gender of right holders matters, together with local institutional arrangements; and that effects may be obscured by measurement error associated with traditional data collection methods. We draw implications for policy and research in Malawi and beyond.

How individuals can access land or exercise their land rights has far-reaching implications for their well-being and ability to take advantage of economic opportunities. While formally documented rights are the norm in developed countries, across the developing world -especially in rural Africaformalization remains out of reach for the majority of the population. Instead, land is almost exclusively accessed through customary arrangements that are administered by traditional authorities. Individuals’ land rights in such systems depend on societal status (Honig 2017) and relationships with local leaders (Goldstein and Udry 2008).

The literature has long highlighted that, as long as land is relatively abundant, customary systems’ ability to flexibly adjust to changes in external conditions allows use of land as a social safety net (Andolfatto 2002) and for mutual insurance (Beck _et al._ 2019). Where risk is high and other mechanisms for insurance are absent, this is a key advantage (Bruce and Migot-Adholla 1994) that may well lead land owners to prefer traditional arrangements to more formal alternatives (Atwood 1990).

Yet, once land becomes scarcer, conflicts that are difficult for traditional authorities to resolve in a predictable way may exacerbate insecurity (Eck 2014) and leaders
Kranzer K, Simms V, Bandason T, Dauya E, McHugh G, Munyati S, et al. Economic incentives for HIV testing by adolescents in Zimbabwe: a randomised controlled trial. Lancet HIV. 2018 Feb;5(2):e79–86.

16. de Walque D, Dow WH, Nathan R, Abdul R, Abilahi F, Gong E, et al. Incentivising safe sex: a randomised trial of conditional cash transfers for HIV and sexually transmitted infection prevention in rural Tanzania. BMJ Open. 2012 Jan;2(1):e000747–e000747.

17. Packel LJ, de Walque D, Feeney KC, Balampama MP, Cooper JE, Kalolella A, et al. A randomized trial of cash incentives for sexual behavior change among female sex workers in Dar es Salaam. Soc Sci Med [Internet]. 2018; Available from: http://www.sciencedirect.com/science/article/pii/S0277953618301205 18. Dutta A, Barker C, Makyao N. Consensus estimates on key population size and HIV prevalence in Tanzania. Natl AIDS Control Programme NACP Minist Health Soc Welf. 2014.

19. Tanzania Ministry of Health and Social Welfare. 2010. HIV Behavioral and Biological Surveillance Survey Among Female Sex Workers in Dares-salaam, 2010. National AIDS Control Programme (NAC), Dar-es-Salaam, Tanzania .
The narrow range of the scores from 0 to 3 limits the possibility of capturing the heterogeneity of laws across countries given that there will be a lot of clustering around certain scores. The SIGI index goes beyond legal institutions and attempts to capture social institutions in general by combining data on laws from WBL with other measures from the OECD Gender, Institutions and Development (GID) database. In contrast the WBL measure of legal gender disparities proposed in this study relies only on data on laws and provides a wide range of scores given the measure is based on disparities in a wide number of laws.

There are several advantages of the WBL measure of legal gender disparities. First by narrowing down the focus to legal institutions, many conceptual and empirical issues are cast aside. For instance the problems of using earnings measures that include inconsistent methodologies of data collection across countries and patchy data are entirely avoided as laws are more precisely measureable. Conceptually what this measure tries to capture is well defined, so there is no combination of measures of different elements that may lead to some loss in clarity of interpretation. Furthermore, the measure presented is not an index. It is a simple summation of legal disparities, which on one hand does away with a lot of nuances, but on the other hand presents a measure that is easily replicable, and malleable to any particular need. Complexity and difficulty in replication are common problems with established indices, which then become inaccessible for various institutions including NGOs (Charmes and Wieringa, 2003). It is important to note that the measure is maintained by WBL, who are the primary data generators of legal disparities that are used by other indices. This is a unique advantage as it ensures the measure will be at the cutting edge of uncovering new laws and updating existing laws that may have important implications for gender equality.

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chairmanship may be selected based on the economic performance of the chairman’s state. Second, we find that the politically connected firm receives greater preferential treatment when its politician has stronger political power. Third, we show that the political rent does not vary with the firm size, contradicting the social purpose lending hypothesis predicting relatively more political lending for small firms. Finally, we run falsification tests by randomly assigning the state of each chairman and show that the political lending pattern disappears. Finally, we rerun the same specifications using the less relevant commissions when constructing the measure of political connection and find that the effect wanes.

Given the comprehensive coverage of our loan data, we estimate the economic cost of the documented political rents by focusing on the two dimensions that we can infer from the data. First, the deadweight loss from the increase in default loans is estimated to be 0.4 basis point of Mexico’s annual GDP. Given an OECD report that the cost of political rents averages about 5 percent of the total GDP, political lending comprises 0.08 percent of total amount of political rents in Mexico.<sup>6</sup> Second, we document evidence of additional distortion of commercial credit allocation: firms in

> 6 The report can be found at http://www.oecd.org/cleangovbiz/49693613.pdf.

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|<br>_(% of GDP)_||||(0.000)|(0.000)|(0.031)|
|Market Concentration|0.005<sup>**</sup>|0.008<sup>***</sup>|0.003<sup>**</sup>|0.006<sup>**</sup>|0.012<sup>***</sup>|0.005<sup>***</sup>|
|_(Herfindahl Index)_|(0.004)|(0.000)|(0.004)|(0.005)|(0.000)|(0.000)|
|Product Concentration|-0.020<sup>***</sup>|-0.016<sup>***</sup>|-0.011<sup>***</sup>|-0.020<sup>***</sup>|-0.019<sup>***</sup>|-0.012<sup>***</sup>|
|_(Herfindahl Index)_|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Secondary enrollment rate|0.009<sup>***</sup>|-0.004<sup>*</sup>|0.003<sup>***</sup>|0.008<sup>***</sup>|-0.006<sup>***</sup>|0.002<sup>***
i i 1 ∗log (I I i i (1) ii ii ii SSha aa = αα + BB IIaa ) + UU We include nation/year fixed effects in each regression and the regressions are population weighted. The data source for population is the World Development Indicators. In estimating equation (1), it is important to note that the within nation/year variation in durables ownership and the income at the specific quintiles allows us to estimate 1. The nation/year fixed effects control for nation specific durables prices. BB In Tables 2 and 3 we report our estimates and the lowest income category is the omitted category. Consider column (1) where we report the automobile ownership regression results. A doubling of personal real income increases the probability of owning a vehicle by .139*log(2) or 9.6 percentage points. This functional form embodies diminishing returns to scale and highlights that the growth in durables ownership is most affected by low-income nations growing richer. We find similar magnitude income effects for air conditioners and refrigerators, washing machines, cell phones, computers, and televisions.

# **The Environmental Implications of the Growth of Middle Class Consumption**

Rising electricity consumption does not result in more greenhouse gas emissions if a nation’s electricity grid is quite green. To measure each nation’s grid we use data from 2014 from the World Development Indicators database. We take U.S. emissions factors for coal fired power plants, natural gas and oil fired power plants and weight these by nation specific shares to yield the national emissions factor. In Table 4, the electricity grid emissions factor is measured in 1,000 pounds of carbon dioxide per MWh. The formula for this variable is based on 2.21*share of power from coal + 0.91*share of power from natural gas + 2.13 * share of power from oil. While these emissions factors are based on U.S. data, there is little reason to believe that
potential positive and negative effects on local collective action and governance. On one hand, emigration may provide an “exit valve”, allowing people to leave underperforming communities rather than staying to improve local institutions (Goodman and Hiskey, 2008; Hirschman, 1970; Sellars, 2019). On the other hand, remittances may enable more local investment (Escribà-Folch et al. 2015; O’Mahony 2013), and knowledge transfers may positively influence local governance and public goods provision (PérezArmendáriz and Crow, 2010; Pfutze, 2012). The net impact of out-migration on rural governance and public goods in China remains an important empirical question and an understudied topic.

A growing literature on public goods provision in rural China has focused on various formal institutions, such as village elections and fiscal policies, and informal ones like lineage groups, as determining factors, but lack attention to the impacts of out-migration. To explore the relation between migration and public goods provision, we use the 2003-2017 RCRE village survey data. The survey covers investment in eight public goods categories: agricultural land improvement, electricity, roads, irrigation and drinking water, ecological forest, elementary schools, immunization, and New Rural Cooperative Medical Insurance spending. A locally weighed regression (Figure 1) shows a negative correlation between per capita public goods investments (excluding New Rural Cooperative Medical Insurance) and the share of village labor force that has migrated out of the county. However, preliminary multivariate regression models do not yield a strong causal association. Further research is needed to understand this negative relationship and whether out-migration may play a causal role.<sup>23</sup>

**Split Families and the Left-Behind.** The movement of labor from low productivity agriculture to urban employment has been a key to China’s growth, contributing to poverty alleviation and consumption growth for poor rural households and communities. However, the impacts of migration extend far beyond these economic benefits. Nearly two-thirds of China’s roughly 150 million rural migrants are not joined by their
use of a difference-in-difference approach providing a stronger identification than can currently be found in the literature. Furthermore, the paper identifies resilient households to draw conclusions for social protection programs and policies.

The next section of this paper presents the data and methodology in more detail. Section 3 presents descriptive results followed by results from the identification on inflation impacts on urban livelihoods in South Sudan. Section 4 concludes with a discussion and policy recommendations.

# **2. Data and Methodology**

# _2.1. Data_

This paper makes use of three waves of panel survey data from the High Frequency South Sudan Survey (HFSSS; Table 1).<sup>3</sup> Wave 1 of the HFSSS was conducted largely before prices exploded, while waves 2 and 3 were implemented in the period of high inflation, and wave 4 was conducted when prices had escalated. We use location- and time-specific price differences to quantify the impact of high inflation on poverty and other livelihood indicators. The panel analysis in this paper is restricted to urban households, as it aims to identify factors that make households resilient. While the restriction to urban areas limits the scope of this paper, the panel analysis allows to gain better understanding of the impact of inflation. For urban areas, waves 1, 2 and 4 provide household panel data. The panel data will be used to analyze within-household dynamics in times of high

> 3 The High Frequency South Sudan Survey, funded by DfID, was conducted by the World Bank in collaboration with South Sudan’s National Bureau of Statistics, to monitor welfare and perceptions of citizens in all accessible areas of South Sudan.

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