rafmacalaba/data-use-mentions-extended huggingface dataset:
places clinics in villages where the population articulates the greatest demand, these may be where health would have been good in any case, and therefore comparisons of health status in localities with and without a facility would _overstate_ the impact.

Some recent studies assess the effect of access to services on child or infant mortality using methods that take into account that the placement of facilities or services may vary systematically in response to local characteristics. Frankenberg (1993) controls for placement effects using a sample of pairs of randomly matched births from two different cohorts in a village in Indonesia and finds the presence of a maternity clinic or of a doctor reduces mortality, but also the presence of a health worker _increases_ the probability of death (statistically significant only at the ten percent level). Pitt, Rosenzweig, and Gibbons (1993) address the placement effect using a panel of matched districts in Indonesia and find that the share of villages in a district with a health center increases mortality (statistically insignificant) while the share of villages with a family planning clinic reduces mortality (also statistically insignificant).

There are many econometric studies of the impact of faculties which do not control for selective placement.'<sup>5</sup> Panis and Lillard (1994), after controlling for the potential endogeneity of facility _usage,_ find that delivering a baby within an institution, the likelihood of which increases with facility availability, reduces the probability that a child would subsequently die in Malaysia but find, puzzlingly, that the use of prenatal care insignificantly increases the

**IS** In her uncorrected estimates Frankenberg (1993) finds that more maternity clinics and health workers insignificantly reduce mortality while more doctors insignificantly increases mortality. In their uncorrected estimates, Pitt et al (1993) find that the presence of both health centers and family planning clinics raise mortality (insignificantly in the case of health centers).

16
data sources include the Bangladesh Demographic and Health Surveys (DHS) conducted from 2000 to 2014. Households were sampled within primary sampling units (also called clusters) which are geocoded. The GPS information from the Bangladesh DHS allows us to construct the salinity level in drinking water for the households located within the clusters.

Our results indicate that there is a strong U-shaped relationship between salinity and infant mortality. With fresh drinking water, the marginal effect of salinity measured by groundwater electricity conductivity (GWEC) on infant death is always negative. With brackish drinking water and slightly saline water, the negative effect is small. As drinking water becomes moderately saline, the predicted probability of infant death starts to increase, and the marginal effect becomes positive. The marginal impact of salinity is always positive when above 6ds/m. The relationship between drinking water salinity and neonatal death shows a similar pattern.

This paper proceeds as follows. In the next section we review the literature that motivates the study. In Section III we discuss the data used in this study while Section IV discusses methodology. In Section V we discuss the results and Section VI concludes.

# **II. Literature Review**

Copious literature exists on the determinants of Maternal and Child Health (MCH) as well as infant and neonatal mortality in Bangladesh. Rubayet et al. (2012) found that declines in neonatal mortality between 2000 and 2010 could be attributed to increases in coverage of key interventions, such as skilled attendance at birth and post-natal care, reductions in total fertility and changes in gross national income. However, other factors such as socio-economic and geographic inequality as well as frequent changes in government remain major challenges to future progress. It was also found that <mark>for participatory women's groups to have a significant effect on neonatal mortality in rural Bangladesh, detailed attention to program design and contextual factors, enhanced population coverage, and increased enrollment of newly pregnant women might be needed (Azad et al., 2010). Implementation of a sector-wide approach
recent historical observations of income growth, inequality dynamics, and commodity prices to be useful information to predict the future performance of the income distribution, then our expectations for reducing poverty below the 3 percent threshold by 2030 should be very optimistic. To accelerate growth across the income distribution, we can explore alternative

> 29 The outcomes reported in Subsections A, B and C are based on per capita consumption growth rates, which were used to complement the country observations for household survey mean income or expenditures present in PovcalNet. 30 The poverty estimates use the $1.90 international poverty threshold in purchasing power parity (PPP) 2011 international U.S. dollars per day.

> 31 The detailed list of countries used in the simulations is provided in Table B 1 in Appendix B.

Page **19** of **45**
Firm characteristics other than size and age have been shown to matter for firm growth as well. Ramachandran and Shah (1999) find that firms controlled by minority entrepreneurs, Asian or European, did better than those controlled by indigenous entrepreneurs.<sup>11</sup> Secondary and university education are highly significant and positive for African entrepreneur while none of the entrepreneurial variables were significant in the non-African model. Their interpretation of these results is that nonAfricans benefit from various advantages of being a minority such as access to informal networks, credit, informal contractual mechanisms etc. Networks that provide contractual mechanisms for access to credit, information and other inputs are beneficial for growth. For the African entrepreneurs education may serve as a substitute for access to these networks. Mengistae (1999) uses data from Ethiopian manufacturing firms to analyze whether there also are differences between indigenous ethnic groups. Controlling for the date of start-up, sector, time of observation, the education and prior experience of the entrepreneur, and unobserved establishment effects he finds that there is one group in Ethiopia that stands out, namely the Gurage. They started up larger and grew faster. Surprisingly enough the Gurage were the least educated ethnic group and also had least vocational training.

Related to the issue of firm growth is firm survival. Exit rates in African manufacturing are significant, and highest among the smallest firms (Söderbom, Teal and Harding, 2004; Van Biesebroeck, 2005b). The study by Söderbom et al. focuses on the role of total factor productivity in determining whether or not firms survive. The authors use a pooled panel data set of firms in Ghana, Kenya and Tanzania that spans a period of five years. They find that productivity impacts on firm survival among large, but not small, firms. Figure 2, taken from their paper, illustrates this finding. Standardizing productivity by the sample mean, the graph shows that exit rates among firms with 10 employees are relatively high and almost wholly invariant to productivity. In other words, being relatively productive
where V is the wind speed, V������ is the wind speed at and below which no damage occurs (set at 92.6km/h) and V���� is the wind speed at which half the property is destroyed (set at 203.7km/h).

The wind speed data we use follows Strobl (2012), which in turn is based on a wind field model developed by Boose, Serrano and Foster (2004), which in turn is based on Holland (1980). The base equation is given as: where V is the wind speed at point P , V� is the maximum sustained wind velocity anywhere in the hurricane, T is the clockwise angle between the forward path of the hurricane and a radial line from the hurricane center to the point of interest (the centroid of a Parish), P , V� is the forward velocity of the hurricane, R� is the radial distance from the center of the hurricane to point P , and G is the gust wind factor (water = 1.2, land = 1.5). Finally, F is a scaling parameter for surface friction (water = 1.0, land = 0.8), S is the asymmetry due to the forward motion of the hurricane (1.0) and B is the shape of the wind profile curve (1.2). These parameter values have been verified in Boose, Chamberlin and Foster, Landscape and Regional Impacts of Hurricanes in New England (2001) and Boose, Serrano and Foster (2004).

The source for the localized wind speeds is the IBTrACS database that provides the strength and tracks every 6 hours of all typhoons that affected Southeast Asia during the period.

As for earthquakes, the damage index and the different data sets are combined and a final data set with the nightlights, population and damage data are made, ref Figure 4. This is used for a case study of typhoon Haiyan
>15</sup> For each indicator, a higher score implies better performance and more attractiveness to foreign investors.

Figure 13 shows a comparison of FDI openness at the sector level.<sup>16</sup> A few patterns emerge from the data. First, in terms of foreign ownership restrictions, BRI countries, on average, are more restrictive than non-BRI countries and high-income OECD countries. Moreover, as shown in Figure 13, the degree of openness varies across sectors: service sectors such as construction, tourism, retail, media, banking, insurance and telecom tend to see more restrictions in BRI countries than in non-BRI or high-income OECD countries.

Second, BRI countries, on average, impose more restrictions and burdens than OECD high-income countries on starting a foreign business, accessing industrial land, and arbitrating commercial disputes. The gap from high-income OECD countries is particularly pronounced. For example, while the ease index of starting a foreign business is around 80 in high-income OECD, it is around 70 in BRI countries.

> 15 The value of each index is based on the average value of sub-indices.

> 16 Table A.5 reports the summary statistics of the Investing across Borders data.

21
|-|-|0.62|
|Argentina|0.81**e**|_|_|-|0.86'|
|Chile|0.95e|_-||-|1.20e|
|Germany|-|-|0.66|-|-|
|Spain|0.43|0.81|-|0.57|-|
|Sweden|-|0.34|_|-|_0.50_|
|Australia|-|0.38|-|-|-|
|New Zealand|-|-|-|-|0.97|
|Other European|0.41|0.49|0.46|0.42|0.70|

_Key:_ t Monthly beta, **e** Equity (not asset) beta.

> **6** Accounting data on a comparable basis was taken from Datastream. This was not available for all of the countries in the study.

27
## 3]

where the first term in ( )⋅ is the effect of a change in the price of sugar on factor prices _w i_ , and the second set of terms are the effect of a change in the price of sugar on all home goods that in turn affect the factor prices _w i_ .

The direct, [11], total, [12] and indirect effects [13] are computed empirically by linking the farm level model with the CGE model.

The logic of the above analysis applied to the function λ _t_ ( _P A ,W h,_ 1 _,_ ⋅⋅⋅ _h, T d,_ ) can also be used to determine the _direct, indirect and total effects_ of macroeconomic reform on the productivity of water at the farm level. This is the nature of the analysis with the empirical model in later sections of this paper.

# **OVERVIEW OF RELEVANT POLICY ISSUES IN MOROCCO**

We demonstrate the micro-macro linkage approach by applying it to the case of Morocco where irrigated agriculture is a major sector. Using Moroccan data we demonstrate the impacts of various policy interventions and external shocks.

Agriculture accounts for about 15 percent of Morocco's gross domestic product and employs about 40 percent of the country's labor force. Agricultural products account for an average of 19 percent of the country's total imports and about 18 percent of total exports. Of the 9.2 million hectares of arable land, ten percent is irrigated but the products from irrigated agriculture account for 75 percent of total primary and processed agricultural exports. Agriculture is a key sector in the domestic economy, and it is a major trade sector and thus prone to macro economic shocks and to the trade policies of the country's major trading partner, the European Union.

The irrigated sector consumes about 85 percent of the country's total available water supplies. Besides the uneven geographic distribution of Morocco's water resources, the country faces an uneven and erratic rainfall pattern with large
.561|

Source: Authors’ calculations.

Note: ***p<0.01, **p<0.05, *p<0.1. Poverty status results estimated using Probit, Consumption results estimated using OLS. Drought effect expressed in standard deviations of NDVI loss.

# 6. Discussion and conclusions

The results show that the 2016/17 drought severely affected consumption in rural households. The magnitude of the drought impact is generally in line with findings in the literature, but on the upper end of the reported effects. For example, Hill and Porter (2016) find that a moderate drought shock leads to a 9 percent reduction in consumption in Uganda, while this analysis finds an effect almost double that size. However, given the severity of the 2016/17 drought in Somalia, the results appear consistent.

Droughts are cyclical events in Somalia and the Horn of Africa region in general. Recently, severe droughts affected Somalia in 2011 and 1991. A renewed drought shock is therefore likely very to occur at some point in the future. The detailed results from the regression analysis allow to simulate how a renewed income shock of the same magnitude as the 2016/17 drought would affect rural households. To model another income shock, the quantile regression estimates of the drought’s effect on household consumption at different points along its distribution are applied to the SHFS data. Based on this simulation, a renewed income shock could increase rural poverty by nine percentage points, from 65 to 76 percent (Figure 6).

9
|0.186|_0.241_|
|Socializes with government officials or influentials (0/1)|Baseline|0.211|0.205|0.219|_0.816_|0.240|0.180|_0.253_|
|House has concrete floor (0/1)|Baseline|0.580|0.632|0.518|_0.118_|0.568|0.594|_0.720_|
|Cultivates 1 Ha or less (0/1)|Baseline<br>|0.503<br>|0.480|0.530|_0.432_|0.505|0.500|_0.934_|
|Used improved seeds in 2009/10 (0/1)|Baseline|0.676|0.680|0.671|_0.448_|0.682|0.669|_0.826_|
|<br>Used inorganic fertilizer in 2009/10 (0/1)|Baseline|0.482|0.477|0.488|_0.885_|0.458|0.509|_0.929_|
|Maize ield (Ks/acre) in 2009/10|Baseline|5552|5789|5269|_0886_|5280|5850|_0474_|
|y g<br>Head of household is a beneficiary (0/1)|Baseline|.<br>0.465|.<br>0.478|.<br>0.451|_._<br>_0.661_|.<br>0.468|.<br>0.463|_._<br>_0.929_|
|Number of Observations||734|400|334||384|350||
|P-value ofjoint F-test that all coefficients are 0<br>Note: In Panel A, we use village-level data from Village Survey
*|22.6|9.2|2.5|2.0|1.6|
|**Slovenia**|50.1|10.9|3.0|2.9|1.8|
|**Slovak Republic**|21.0|1.2|1.1|0.5|0.4|
|**Total**|16.0|7.5|3.3|1.4|1.1|

Source: Our elaboration on HFCS data.
14 higher among the rural poor. It was not possible to infer from the questionnaire what explains this odd result. The second largest difference was found in Zambia, where the difference was due largely to use of generators in rural areas. Lastly, in Niger the difference in access between definitions 1 and 5 was larger than 10 percentage points for urban households as well as for the urban poor. The greatest contributing factor was use of electricity as the primary source of energy by those who did not report connection to the grid, followed by use of generators (even among the urban poor); the survey did not ask questions about solar energy. The difference also exceeded 10 percentage points in rural Nigeria and rural Ghana. In rural Nigeria, it was due to generator ownership: nearly one‐fifth of all rural households own generators; the questionnaire did not ask about solar energy. In rural Zambia, the difference was due three‐fifths to generator use and two‐ fifths to solar panels.

Figure 3: Percentage of people using electricity according to different definitions of access <!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>Definition 1 Definition 2 Definition 3 Definition 4 Definition 5<br>Percentage of population<br><!-- End of picture text --> _Source_ : World Bank staff calculations using household survey data. _Note_ : For a descriptions of the five definitions of access, see page 6.

Only four surveys—Madagascar, Mozambique, São Tomé and Príncipe, and Togo—asked about quantities of electricity consumed. Recalling quantities of electricity consumed is even more challenging than recalling the amount spent, and the evidence of this challenge was clear in São Tomé and Príncipe, where 15 surveyed households reported electricity consumption of 1 kWh _a year_ , 11 of them
cohort and use these as weights – for example, all observations from children at an age of one month are assigned a weight equal to (1/# of observations with age = one month). This weighting makes possible the translation of our point estimates, which come from monthly observations, into aggregate changes in mortality risk across the whole full first year of an infant’s life.<sup>12</sup> The remainder of the columns in Table 2 separate out these one-year mortality results into impacts in the first month of life vs. in months two through twelve. Given a baseline neonatal mortality risk of 12.1 percent in the treatment group prior to the verdicts, columns 2 and 5 indicate large impacts, with statistically significant point estimates of -0.024 (or 19.5 percent) and -0.020 (or 16.2 percent), respectively. Meanwhile, the estimated mortality impact in months two through twelve is a much smaller and statistically insignificant -0.001 in both column 3 and column 6. Together, Tables 1 and 2 reveal that most infant mortality events are neonatal and that the environmental policy in question here is associated with large-magnitude reductions in neonatal mortality – on the order of 16-20 percentage points. The adverse effect of pollution beyond the first month is more likely to be captured by morbidity, which we do not observe over time. We thus focus exclusively on neonatal mortality for the remainder of this paper, touching on possible mechanisms of exposure in Section 5.

We explore the timing and geography of the verdicts’ impacts on neonatal health in Table 3, using the same child-month mortality panel as in Table 2. Columns 1-3 show results from neonatal mortality regressions using post-periods of different lengths, while column 4 shows results from simultaneous estimation of short-, medium-, and long-run policy impacts. Column 5 tests the robustness of the main effect to the use of all of India as a control group. All estimates are statistically significant at the five-percent
attend Almajiranci (Islamic school), a religious and non-formal system of education practiced in northern Nigeria.

# **5.1.1 Main outcome measures**

The main outcomes are the percent of children not attending school and learning outcomes (literacy and numeracy test scores) as pre-registered in the AEA registry of randomized control trials, see footnote 8. For both baseline and follow-up data collection we interviewed the household head and tested on literacy/numeracy skills a 6-9 year old child (referred as ‘target child’, as this child was invited to the community screenings and targeted by the interventions’ messaging) and a 6-12 year old sibling (referred as One child was selected at baseline if the house- ‘sibling’). per age group randomly hold had more than one child in each age category. Assignment was stratified by gender of the target child. To analyze the mechanisms through which our interventions may 14
mark>We relate measures of crime and disorder—specifically, the percentage of sales lost due to crime, theft and disorder—to measures of productivity based on the hypothesis that areas with higher levels of crime and conflict may experience lower productivity through a misallocation of either entrepreneurial talent or other resources. In South Asia, conflict- and crime-prone areas also typically have lower infrastructural stocks, higher levels of corruption, worse health outcomes, and a greater incidence of poverty (Ghani 2010, and Ghani and Iyer 2010).</mark>

# **_<mark>(2) Access to skills</mark>_** <mark>.</mark>

- **<mark>Worker training</mark>** <mark>. Studies show that firms' capacity to absorb and benefit from new technology depends on management and worker training (see Bell and Pavitt 1992).</mark>

- **<mark>Education and skills of the top manager/owner.</mark>** <mark>de Mel, McKenzie and Woodruff (2010) show the importance of firm owner characteristics such as ability, motivation and competitive attitudes to risk as a primary drivers of growth, based on a series of surveys of own account workers and owners of enterprises in Sri Lanka. Based on a follow-on representative survey of over 2,800 micro, small and medium privately-owned firms in Sri Lanka in 2008, de Mel, McKenzie and Woodruff (2009) show that owner ability (more educated individuals, higher logical ability), conditioning on firm size and other firm characteristics, has a significant and substantial impact on the likelihood of a firm innovating and higher profitability. We use measures of both education and business training to assess the relationship between education, skills and innovation.</mark>

10
<!-- Start of picture text --> Concentration of non-oil imports per worker 2009-2015<br>Governorates in Egypt<br>1 ag10 ow<br>a 18 44 oA KS 20<br>6<br>26<br>1 maid9<br>ai es S -<br>wet (2.1397204,4.2931247](4.2931247,9.0693976]<br>) |__]\( 1. 3 91313 1.6788064)6 7 88064 , 2. 1397204]<br>22 ei 4581951,1.3791313]<br>o<br>19 i<br><!-- End of picture text -->

Own elaboration with LFS data <!-- Start of picture text --> Concentration of non-oil imports per worker 2009-2017<br>Governorates in Egypt<br>a i, ee<br>1% 10B14 fr KS<br>. 6<br>16 26<br>"1 at5)<br>we , ee<br>wet (1.7117462,3.7098517](3.7098517,7.457817]<br>\~) |_]\ (1. 25337 946853 4 4 ,1. 7117462]4685344)<br>22 ‘a 9965215, 1.2533749]<br>es<br>19 4<br><!-- End of picture text -->

Own elaboration with LFS data
the right to inhabit is personal, and cannot be transferred or assigned to another individual.<sup>89</sup> It is important to underline that the condition of a usufructuary is substantially different from that of a household that lives in a property offered by another household for free. Granting a property free of charge to someone else implies a current transfer that, by its own nature, can be stopped at any time, and thus has no certain value for the future. The absence of any right suggests excluding them from the notion of wealth.

# **3. The data**

In this paper, we will use the data from the Bank of Italy’s Survey of Household Income and Wealth (SHIW), conducted in Italy since the 1960s to gather information on household income, consumption, wealth, and various aspects of household economic behavior. It has been conducted yearly on a national two-stage sample of 4,000 households up to 1984; since 1986 it has been carried out every two years (with some exceptions) using a sample of 8,000 households (Bank of Italy, 2022; Baffigi et al., 2016).

> 6 A similar example of “split property” is provided by the “rule of 99 years” in England and Wales where purchasing a leasehold property means buying the right to live in and use the property for the duration of the lease only (typically 99 years). As the lease term decreases, also the value of the property tends to decrease.

> 7 In cases in which the use rights of a property are obtained at the cost of a payment lower than that present value on the market (i.e. a subsidized rent), the present value of this difference could be considered as part of the household wealth as well. In practice, this can be the case only when the actual rent paid is largely lower than the market value and when the contract extends for a considerable period of time.

- 8