rafmacalaba/data-use-mentions-extended huggingface dataset:
the number of dwellings to pass in order to reach the first sampling unit. Interviewers then selected every other dwelling in that direction applying a systematic random sampling method until all 26 surveys within the EAs were completed. A total of 4,559 dwellings were approached; 3,942 (86.5%) participated in the study. All of those that did not participate could not be reached after four attempts.

# **2b. Data**

Experienced interviewers, who were trained over six days on the study objectives and content, use of smartphones and interview technique, conducted one-to-one interviews. Pilot testing and mock interviews were conducted with all instruments. Oral rather than written consent was obtained because of the high illiteracy rate, but each household was left with a consent form with details of the study, respondents’ rights and confidentiality, and contact details in case of any concerns. Interviewers and respondents were always matched based on gender. Supervisors analyzed the collected surveys on a daily basis, identifying outliers, giving feedback on data collection, and addressing any questions.

The survey is a multi-topic one and collected data on several aspects of young women’s and adolescent girls’ lives in Jharkhand. Key individual level demographic characteristics include the adolescents’ age, marital status, education status (attainment, attendance, dropouts), employment status (firm type, place of work, sector, earnings) as well as a host of psychological variables.

The main psychological variables relevant to this paper include education and labor market aspirations, self-efficacy, depression, and hope. Aspiration measures are single 4
medium density, but are weak in districts with low density. The medium-density findings may suggest that GQ upgrades helped activate intermediate cities, where some observers believe India’s development has underperformed compared to China.

Our project contributes to the literature on the economic impacts of transportation networks in developing economies, which is unfortunately quite small relative to its policy importance. The closest related study is Datta (2011), who evaluates the impact of GQ upgrades using inventory management questions contained in the World Bank’s Enterprise Surveys for India in the years 2002 and 2005. Even with the short time window of three years, Datta (2011) finds that firms located in non-nodal districts along the GQ network witnessed a larger decline in the average input inventory (measured in terms of the number of days of production for which the inventory held was sufficient) relative to those located on other highways. He also finds that firms in districts closer to the GQ network were more likely to switch their primary input suppliers vis-à-vis firms farther away. These results suggest improved efficiency and sourcing for establishments on the GQ network after its upgrade.

Beyond India, several recent studies find positive economic effects in non-nodal locations due to transportation infrastructure in China (e.g., Banerjee et al. 2012, Roberts et al. 2012, Baum-Snow et al. 2012). These studies complement the larger literature on the United States (e.g., Fernald 1998, Chandra and Thompson 2000, Michaels 2008, Duranton and Turner 2012, Baum‐Snow 2007, Lahr et al. 2005)<sup>1</sup> , those undertaken in historical settings (e.g., Donaldson 2010, Donaldson and Hornbeck 2012), and those focusing on other developing or emerging economies (e.g., Brown et al. 2008, Ulimwengu et al. 2009). A related literature considers non-transportation infrastructure investments in developing economies (e.g., Duflo and Pande 2007, Dinkelman 2011).<sup>2<
total business spending on R&D in the US is considerably larger than that on new financial product development (CHS 2005).

Our estimates suggest that Brazilian firm expenditures on R&D have risen in the initial years, dropped significantly, and then have been rising relatively constantly. Between 2000 and 2008, total expenditures on science and engineering R&D ended up remaining fairly constant at roughly 0.6 percent of GDP.

> 19 Source: World Development Indicators.

21
# **3.1 Multidimensional poverty**

We create a multidimensional poverty (MDP) index inspired by the OPHI MDP based on a synthetic household survey dataset (SHSD) supplemented by three other variables (see below).

# **_3.1.1 Synthetic household survey data_**

Recently, a synthetic household survey dataset (SHSD), representing the location (latitude/longitude) and socioeconomic characteristics of almost 43 million people (10.25 million households) across 19 districts and 150 Upazilas in the coastal zone, was developed using both detailed Census data, household survey microdata and spatial microsimulation techniques (Rubinyi et al., 2022). The SHSD provides the best source of information on the deprivations that Bangladeshi households face on a high spatial resolution, and includes information on housing types, access to water, energy and sanitation, and educational data. The details on the SHSD are included in Appendix A; here we only describe how we have constructed the MDP indicators that we use throughout our work. The original SHSD is based on Census 2011 data, which are projected to 2020 to take into consideration that the population has grown and households have experienced improved living standards over this 10-years period, and hence, face lower MDP.

# **_3.1.2 Multidimensional poverty indicators_**

We construct a new MDP index for the coastal zone of Bangladesh based on nine indicators (see Table 1). The MDP combines variables across the different dimensions that contribute to a households’ wellbeing. These variables are grouped into 3 categories (Education, Living standards, Health) in line with the OPHI MDP. Six of the variables from the MDP can be generated from the SHSD. However, the SHSD still captures only a limited number of dimensions of poverty, for example it does not provide information on health indicators. As such, two additional variables are derived from the accessibility analysis (Section 3.4), access to hospital and health facilities, and another measure, child stunting
and this holds back aggregate employment and productivity growth (Ohnsorge and Yu 2022). Indeed, greater policy distortions have been associated with smaller firm size which, in turn, has been associated with slower aggregate employment growth (Bento and Restuccia 2021; Restuccia and Rogerson 2017). In cross-country studies, smaller establishment sizes have been associated with institutional features that discourage productive firms from hiring labor (Bento and Restuccia 2021; Hsieh and Klenow 2014).

We include the average establishment size for the services and manufacturing sectors among the correlates. The data is from Bento and Restuccia (2021).

# **Human capital**

Human capital growth, including improvement in education, training, and health, plays an important role in the shift from agriculture to non-agriculture activities (Lee and Malin 2013; Porzio, Rossi, and Santangelo 2022). A workforce that has inadequate education, training and/or health care (hence, weak human capital) makes sectoral shifts more challenging. We include literacy rates, government spending on education as a percent of GDP, and the gender gap in secondary education attainment to capture a country’s level of human capital. These data are drawn from the WDI.

# **Gender-related laws**

Finally, laws that promote gender equality (in the workplace, in pay, and in marriage) can increase women’s employment, while laws that protect women’s mobility have been shown to increase women’s willingness to travel for better work opportunities (Braunmiller et al. 2023a; 2023b; Roy

> 5 We also tested for significant correlations with population density and the urban population share but found none.

15
and Scholz 2014). We find that that the existence value of the Amazon rainforest is considerable and possibly comparable to carbon benefits (Song, Huang et al. 2015).

# **2. Methods**

# _2.1 Survey approach_

Measuring intrinsic economic values requires using survey-based approaches, as intrinsic values cannot be observed from market prices or behavior (Freeman III, Herriges et al. 2014). A widely used current approach to eliciting WTP involves conducting choice experiments. They are frequently used for environmental valuation and empirical evaluations of individual preferences and decision making more generally (Louviere, Hensher et al. 2000; Siikamäki and Layton 2007; Train Kenneth 2009; Hensher, Rose et al. 2015; Newell and Siikamäki 2015). Choice experiments view the objects of choice, in this study alternative Amazon protection plans, as bundles of attributes.

We measured WTP for two attributes addressed by Amazon protection, avoided loss of forest area, and reduced risk of species extinctions, by conducting random population surveys in the U.S. and Canada (1,024 respondents from the U.S. and 377 respondents from Canada). By conducting experiments, we elicited individuals’ choices between sets of different Amazon protection options, each with specified forest losses and species extinction risks between now and 2050 achievable through new policy interventions. Each option also involved different expected costs to the household. WTP for the protection of Amazon rainforest, the measure of its economic value (Louviere, Hensher et al. 2000; Freeman III, Herriges et al. 2014), is implicit in the choices. For example, if a person selects a program that yields certain environmental benefits but also carries specific costs to that individual, we know that this person’s WTP for the 4
children in Nigeria (Azomahou and Yitbarek 2016; Razzu and Wambile 2021). Northern Nigeria has some of the poorest educational attainment rates for older adults. Only 40 percent of 30-34-year-olds have ever attended school in the North East and North West zones, compared to 90 percent in the South East and South West regions of the country.

Another factor that may contribute to low school enrollment and deficient learning outcomes is that the region is also characterized by a strong adherence to traditional norms. The formal legal institution of Shari’a law applies in most northern states, covering social, civil, and criminal matters (Suberu 2009; Human Right Watch 2014). This has reinforced social norms that encourage early marriage and childbearing for Muslim adolescents and in the process create additional barriers to education. This is also reflected in attitudes toward education for women and labor force participation of mothers. According to the World Values Survey (2017 -2021), in Nigeria, 42% of respondents believes that university is more important for a boy than for a girl and 41% believes that pre-school children suffer if the mother works. These adverse norms contrast with those observed in other countries where education plays a more prominent role, such as Kenya, where the proportions of the population holding these views are 18% and 23%, respectively.

Further, the emergence of the militant terrorist group Boko Haram, which translates as ”Western education is forbidden”, creates an additional barrier for school enrollment and attendance. As a result, the predominant forms of schooling available to young children in the north include: 1) Qur’anic schools, which exclusively focus lessons on Islamic theology and religious texts, or 2) Islamiyya schools, which also cover Islamic subjects but follow a more typical school structure with regularized time schedules.<sup>2</sup>

# **3 Entertainment Education**

Entertainment education (EE) encompasses a wide umbrella of interventions that use entertainment media with the goal to positively reshape attitudes and promote behavioral change.
$US|<br>free imports<br>(no duty<br>applied)<br>‘000$US|free<br>import<br>share of<br>category<br>total<br>|share of<br>total<br>processed<br>food<br>imports|EU<br>average<br>rate of<br>pro-<br>tection,<br>all extra-<br>EU trade|
|---|---|---|---|---|---|
|Animal products|92|0|0.0|0.0|16.0|
|Vegetable oils and fats|104,029|26,506|25.5|10.0|37.7|
|Dairy products|99|0|0.0|0.0|18.4|
|Processed rice|1,176|0|0.0|0.1|38.6|
|Sugar|37,818|0|0.0|3.7|36.7|
|Food producs nec|891,547|5,287|0.6|86.1|11.6|
|Beverages and tobacco|1,208|394|32.6|0.1|20.3|
|TOTAL|1,035,968|32,188|3.1|100.0|15.2|

source: WTO integrated database (trade) and GTAP database (protection) 28
combine information from several different sources. Such models may be a promising avenue for monitoring changes in a region’s economic circumstances, particularly in the midst of sudden, large shocks when more traditional survey data are not (yet) widely available.

The remainder of this paper is organized as follows: section 2 introduces the data and empirical methodology, section 3 describes trends in measures of well-being, section 4 presents the results of our analysis, and section 5 concludes this study.

# **2. Data and Empirical Methodology**

The analysis uses two types of data: (1) high-frequency phone surveys measuring household well-being during the COVID-19 crisis, and (2) real-time metrics of mobility, internet search activity, pollution, and night-time lights. We use the regionally aggregated high-frequency phone survey (HFPS) data as the dependent variable for the prediction based on real-time metrics.

# 2.1 Household Well-Being Measures from the HFPS

The HFPS data cover 59 developing countries.<sup>3</sup> The process of fielding the surveys for each country was done in conjunction with national statistics offices to ensure appropriate weighting and population representation. Enumerators contacted households by phone and followed up with individuals in subsequent waves. Surveys were either carried out by recontacting respondents from a previously fielded nationally representative survey or through random digit dialing (RDD). Lower-income countries primarily opted for the former, while middle-income countries with more widespread phone coverage were more likely to use RDD. In cases where previous survey respondents were re-contacted, weights were constructed to account for the selection bias due to only interviewing households with phones who responded to the survey. However, respondents tend to be heads and the weights did not

> 3 The HFPS includes 8 countries from East Asia and Pacific (Indonesia, Cambodia, the Lao People’s Democratic Republic, Myanmar, Mongolia, the Philippines, Solomon Islands, and Viet Nam), 8 from Europe and Central Asia (Armenia, Bulgaria, Croatia, Georgia, Poland, Romania, Tajikistan, and
# **Table 11. Variable definitions**

|**Variables**|**Source**|**Variable definition**|
|---|---|---|
|Dependent variable:<br>Net FDI inflows (%GDP)|**UNTCAD**<br>**database on**<br>**FDI.**|FDI are on a net basis (capital transactions’ credits less debits between direct investors<br>and their foreign affiliates), or net acquisitions of assets (outward FDI) and net<br>incurrence of liabilities(inward FDI)|
|**Macroeconomic variables**|||
|Growth rate|**WDI**|GDP per capita growth at 2005 constant prices|
|Openness|**WDI**|It is measured as the exports plus the imports divided the GDP of one particular<br>country in a given year|
|Inflation|**WDI**|Inflation as measured by the consumer price index reflects the end-of- percentage<br>change in the cost to the average consumer of acquiring a basket of goods and services|
|**Infrastructure and human c**|**apital**||
|Infrastructure|**WDI**|Number of telephone and mobile phone line subscription|
|Human capital|**WDI**|Enrollment in tertiary education (%)|
|**Institutions**|||
|Law and order|**PRS Group:**<br>**International**<br>**Country Risk**<br>**Guide(ICRG)**|The "law" sub-component assesses the strength and impartiality of the legal system,<br>and the "order" sub-component assesses popular observance of the law.|
|Government stability|<br>**PRS (ICRG)**|
municipalities that showed all zeros in all outcomes in all years were excluded. RAIS data were missing for one additional municipality. Brasília, the capital city, was also excluded because wages for government positions are occasionally coded to Brasília, and this anomaly might generate a small amount of noise in a typical municipality, but would certainly generate a great deal of mismeasurement in Brasília. Municipalities were also removed that had any missing data to establish a balanced panel. Of Brazil’s 5,570 municipalities, 4,205 remained that had viable observations. However, 75 percent of the homicide observations, 76 percent of the overnight hospitalization observations, and 57 percent of the reports were zeros. This suggests that changes in levels of violence in the smallest municipalities result in a large amount of noise because violent events are rare occurrences. The observation of a violent event in a small municipality

> 10 Unlike the  violence registry for women, not all incidents of violence against men are included in the SINAN registry.  Reports of men experiencing non-family, interpersonal violence or violence within the community are excluded.

14
**<u>Table 4: Expansion of registry infrastructure and information campaigns over time</u>**

||**Kigali city**||**Prov**<br>|**ince**<br>||
|---|---|---|---|---|---|
|||**South **|**West**|**North **|**East**|
|Covered with SLM Batch I (Q3, 2014)|0.18|0.40|0.07|0.03|0.05|
|Covered with SLM Batch II (Q2, 2015)|0.73|0.55|0.21|0.21|0.16|
|Covered with SLM Batch III (Q3, 2015)|0.82|0.81|0.59|0.57|0.57|
|Covered by land week I (Q3, 2014)|0.19|0.25|0.39|0.29|0.24|
|Covered by land week II (Q2, 2015)|0.33|0.18|0.23|0.19|0.22|
|Distance to DLO (km)|6.95|12.57|12.43|11.58|14.85|
|Ratio of urban to rural pop.|2.04|0.19|0.19|0.14|0.09|
|No. of obs.(cells)|161|532|538|414|503|

_Source:_ Rwanda Natural Resource Authority (RNRA) for sector land managers and land week coverage, National Institute of Statistics, Rwanda for population numbers.

19
|World Bank East<br>Asia & Pacific<br>harmonized<br>household survey<br>collection|Ex post<br>harmonized|World Bank|World Bank’s<br>East Asia &<br>Pacific region|HBS, HIES,<br>multipurpose surveys|Accessible only to World Bank staff via World<br>Bank Microdata Library.|
|ECAPOV|World Bank Europe<br>and Central Asia<br>harmonized<br>household survey<br>collection|Ex post<br>harmonized|World Bank|World Bank’s<br>Europe &<br>Central Asia<br>region|HBS, HIES,<br>multipurpose surveys|Accessible only to World Bank staff via World<br>Bank Microdata Library.|
|EUROSTAT-<br>HBS|Eurostat HBS Public<br>Use Files|Ex post<br>harmonized|European<br>Commission –<br>Eurostat|European<br>Union|HBS|Details available on the Eurostat microdata<br>website.<sup>39</sup>|
|HBS|Household Budget<br>Survey|National survey –<br>raw data|National<br>governments|Global|HBS|Survey-specific|
|HEIDE|World Bank<br>Household<br>Expenditure and<br>Income Data for|Ex post<br>harmonized|World Bank|World Bank’s<br>Europe &<br>Central Asia<br>region|HBS, HIES,<br>multipurpose surveys|Details of the HEIDE data set can be found in<br>the World Bank Microdata Catalog, and can<br>be found by searching for HEIDE in the study<br>description.|

> 35 The World Bank Microdata Catalog can be accessed at <u>http://microdata.worldbank.org/index.php/home</u> and
impoverishing health expenditures are computed using (the code underlying) the Stata module FPRO (Eozenou and Wagstaff 2018). Where health expenditure data are individual-level, the data are aggregated to the household level. A household is defined as incurring catastrophic expenses if its out-of-pocket health expenditures strictly exceed the 47 PovcalNet can be accessed at http://iresearch.worldbank.org/PovcalNet/povOnDemand.aspx.
> POLICY RESEARCH WORKING PAPER 2381

# Summary findings

Agenor and Aizenman examine the extent to which permanent terms-of-trade shocks have an asymmetric effect on private savings.

Using a simple three-period model, they show that if households expect to face binding constraints on borrowing in bad states of nature (when the economy is in a long trough rather than a sharp peak), savings rates will respond asymmetrically to favorable movements in the permanent component of the terms of trade-in contrast with the predictions of conventional consumption-smoothing models.

They test for asymmetric effects of terms-of-trade disturbances using an econometric model that controls for various standard determinants of private savings. The results-based on panel data for nonoil commodity exporters of Sub-Saharan Africa for 1980-96 (a group of countries for which movements in the terms of trade have traditionally represented a key source of macroeconomic shocks)-indicate that increases in the permanent component of the terms of trade (measured using three alternative filtering techniques) indeed tend to be associated with higher rates of private savings.

This paper is a product of Economic Policy and Poverty Reduction, World Bank Institute. Copies of the paper are available free from the World Bank, 1818 H Street, NW, Washington, DC 20433. Please contact Tanya Loftus, room J4-282, telephone 202-473-63 17, fax 202-676-98 10, email address tloftus@worldbank.org. Policy Research Working Papers are also posted on the Web at www.worldbank.org/research/workingpapers. Pierre-Richard Agenor may be contacted at pagenor@worldbank.org. June 2000. (38 pages) _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas ahout 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 entirely those of the authors. They do not necessarily represent the_ **_view_** _of the World
The Global Database on Intergenerational Mobility (GDIM) compiled by this study significantly expands the evidence base on intergenerational mobility in education by providing estimates for 153 countries representing about 97 percent of the world’s population born in the 1980s.<sup>2</sup> For 114 countries, or 87 percent of the world’s population, estimates of mobility span four decades: from those born in the 1950s to those born in the 1980s. The 1980s cohort, those born between January 1, 1980 and December 31, of 1989, represent the youngest generation of adults who would have completed their education at the time of data collection (as most survey data used are from 2010 or later). For each country we identified the survey data best suited for the estimation of intergenerational mobility in education.

We consider two concepts of IGM. Absolute mobility measures the share of individuals who surpass the education of their parents. Relative mobility captures the degree to which individual socioeconomic success is independent of the socioeconomic success of one’s parents. We will focus on mobility in education for several reasons.<sup>3</sup> Firstly, human capital is a key aspect of economic well-being. Secondly, intergenerational data on education is more widely available than on income. Thirdly, the estimation of educational mobility involves fewer methodological challenges. Unlike income, the level of education, once acquired, does not vary across an individual’s lifecycle. Fourthly, individuals can report their parents’ education level with a high degree of precision, whereas the same is not true for income, making it possible to study mobility in education without panel data. A limitation of focusing on education mobility is that it does not capture distortions in the labor market, such as the extent to which access to good jobs is contingent on the socioeconomic background one is born into.

Our database makes it possible, for the first time, to paint a truly global picture of intergenerational mobility. This in turn allows us to test whether insights