rafmacalaba/data-use-mentions-extended huggingface dataset:
(2011) found signs that the process of economic growth is changing in India, making urban economic growth more pro-poor in the post-reform period up to 2005-06. It is important to know whether this pattern has continued in more recent data—to assess whether stronger linkages from urban economic growth to rural poverty reduction have continued, alongside a more economically diversified rural economy.

For the purpose of this paper, we have compiled a new data series on poverty and related data spanning 60 years, extending the period of analysis in past research.<sup>22</sup> With the benefit of nearly two decades of post-1991 data, we believe there is now sufficient data for the post-1991 period to test the poverty implications of the new rate and pattern of growth in post-reform India. Attribution to reforms _per se_ is problematic, but further scrutiny of the emergent properties of the changing growth process with respect to poverty reduction is clearly important.

The sectoral structure of NDP growth in the post-1991 period is also of interest, as is the role played by population urbanization, including the Kuznets process that has been so influential in past thinking about the distributional implications of economic growth in poor countries.<sup>23</sup> We provide a decomposition of poverty reduction by sector of NDP and a decomposition method that allows us to identify the difference between population urbanization effects with constant within-sector distribution (as in the Kuznets process) versus changing within-sector distributions.

This enquiry delivers the most robust evidence to date that economic growth has not only come with a lower incidence of absolute poverty in India but that there has been an acceleration in the pace of progress against poverty in the post-1991 period. The new pattern of growth has brought greater benefits to India’s poor. While there has been rising inequality within the rural and (especially) urban sectors, growth within sectors has delivered sufficient gains to poor people to mitigate the higher inequality. Population urbanization played a role, but not in the way assumed by the Kuznets process. Instead we
Policy Research Working Paper 10267

# **Abstract**

High aspirations for their future motivate youth to strive toward them and achieve better outcomes. However, the influence of perceived constraints on the motivational power of aspirations is unclear: do high aspirations motivate independently of constraints or only when expected constraints seem workable? This paper explores this question with a gender lens and using a large, cross-sectional survey of adolescent students in Indonesia. The findings show that most students aspire to high education levels, but only half of the students expect to complete the level to which they aspire. Although girls have higher aspirations than boys, girls are less likely to expect to achieve their aspirations. Years of aspired education are strongly correlated with better current schooling outcomes (grades and attendance), and while expectations are also associated with better schooling outcomes, the relationship is nonlinear. Aspirations seem to motivate students despite their perceived constraints, unless there is a large gap between their aspirations and expectations. Although there are similar patterns for boys and girls, aspirations are more correlated with boys’ attendance, and expectations are more strongly related to boys’ grades and attendance. Students cite both mental barriers and economic constraints to achieving their aspirations, especially the latter for girls. The results suggest that both male and female Indonesian students could benefit from programs that boost aspirations and address psychological and economic constraints.

This paper is a product of the Gender Innovation Lab, East Asia and the Pacific 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 hjohnson1@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
context of generational change, may limit the scope for mechanization and thus contribute to a reversal of the inverse relationship, making some farms (or, more accurately, plots) too small for efficient cultivation (Foster and Rosenzweig 2010). Recent innovations in crop breeding, tillage, and information technology also may make agricultural production more knowledge-intensive, thus eliminating part of small farmers’ traditional advantage. Most studies use cross-sectional evidence or short panels; longitudinal data at the household level could improve understanding of the relationship between farm size and productivity by allowing researchers to test how that relationship evolves in response to changes in technology and market functioning.

To provide such insights, this paper draws on panel data from close to 5,000 farm households in 17 Indian states over a 25-year period (1982–2008). We use panel regressions for the early (1982–1999) and late

> 1 We thank Jikun Huang, Keijiro Otsuka, Futoshi Yamauchi, and seminar participants at International Association of Agricultural Economists Triennial Conference in Milan, Italy, 2015 for helpful comments. Funding from DFID, the Bank’s Knowledge for Change Program, the Bill & Melinda Gates Foundation, and the CGIAR Research Program on Policies, Institutions, and Markets (PIM) is gratefully acknowledged.

2
# **1. Introduction**

Investment promotion agencies (IPAs) stand out as one of the most favored policies by countries to attract foreign direct investment (FDI). Between 2002 and 2018, the number of national and subnational IPAs registered in the World Association of Investment Promotion Agencies (WAIPA) grew from 112 to 170 (Heilbron and Kronfol, 2020). These IPAs also receive considerable public funding. A survey of IPAs in Latin America and the OECD found the median IPA in these countries manages a budget of US$7 million, has 100 employees, and performs roughly 40 different promotional activities. Resources available to IPAs in certain countries can exceed US$200 million and 1,000 employees (Volpe Martincus and Sztajerowska, 2019).

Despite the proliferation of IPAs in the last two decades, their impact on stimulating economic development has varied considerably across countries. On average, IPA activity is often associated with greater FDI inflows in targeted sectors (see for example Charlton and Davis, 2007; Harding and Javorcik, 2011). High-profile cases have further illustrated the influence that investment promotion can have in attracting FDI and shaping economic development, as shown in the cases of Malaysia, Costa Rica and Morocco (Freund and Moran, 2017). Yet, in many other developing countries, IPAs have failed to replicate these examples and have made little impact in attracting FDI (Heilbron and Kronfol, 2020).

To better understand what drives these differences in IPA performance, this paper brings together new data on sectoral FDI and IPA characteristics. It uses this to construct a structural gravity model framework with country-interaction effects that evaluates the effectiveness of each country IPA’s sectoral targeting on their FDI stock in that sector. Results from this model are then used to define two groups: highperforming IPAs (those with positive, significant effects in attracting FDI) and other IPAs (those with insignificant or negative, significant effects). It then considers which IPA characteristics significantly differ between the two groups, and in turn, reflects
Economic Surveys_ 34 (4): 753–92.

Aker, Jenny C. 2010. “Information from Markets Near and Far: Mobile Phones and Agricultural Markets in Niger.” _American Economic Journal: Applied Economics_ 2 (3): 46–59.

Aker, Jenny C., and Isaac M. Mbiti. 2010. “Mobile Phones and Economic Development in Africa.” _Journal of Economic Perspectives_ , 24 (3): 207–32.

Aker Jenny C., Christopher Ksoll, and Travis J. Lybbert. 2012. “Can Mobile Phones Improve Learning? Evidence from a Field Experiment in Niger.” _American Economic Journal: Applied Economics_ 4 (4): 94–120.

Aker Jenny. C., and Christopher Ksoll. 2019. “Call Me Educated: Evidence from a Mobile Phone Experiment in Niger”. _Economics of Education Revie_ w 72: 239–57.

Aker Jenny C., Rachid Boumnije, Amanda McClelland, and Niall Tierney. 2016. “Payment Mechanisms and Anti-Poverty Programs: Evidence from a Mobile Money Cash Transfer Experiment in Niger”. _Economic Development and Cultural Change_ 65 (1): 1–37.

23
the context of the emergence of new trade partners for the countries in the region, most notably China (De La Torre _et al_ ., 2011). Changes in terms of trade, were not homogeneous across the region – while they increased on average during the 2000s for South American countries and Mexico, they decreased for those in Central America.<sup>15</sup> The regressions discussed below incorporate an index of “net barter terms of trade” (source: World Bank World Development Indicators) to capture the average effect of the recent evolution of international prices in the region, although it is possible that these average effects mask the heterogeneity of

> 12 See for instance Galiani and Sanguinetti (2003) and Galiani and Porto (2010) for Argentina; Ferreira, Leite and WaiPoi (2007) for Brazil; Gill and Montenegro (2002) for Chile; Attanasio _et al._ (2004) for Colombia; and Harrison and Hanson (1999) for Mexico.

> 13 Even if a country has a comparative advantage in terms of unskilled labor, inequality can increase after trade liberalization. Atolia (2007) develops a dynamic Heckcsher-Ohlin model in which increasing inequality arises from trade liberalization in the short run because of asymmetric speeds of adjustment between the export and import sectors. The asymmetry generates a transitory capital accumulation that increases the relative wages of skilled workers because of capital-skill complementarity in production.

> 14 The authors are grateful to Miguel Szekely for sharing his series of tariffs for the region.

15 Galiani et al. (2011) study the distributive effects of terms of trade shocks. In their model, besides a non-tradable good, there are two tradable goods, one intensive in natural resources and another – an industrial good, for instance – intensive in unskilled labor. As in a typical Dutch disease model, an increase in the international price of the natural resourcesintensive good induces higher demand (and higher prices) for the non-tradable good, and a re-allocation of resources away from the production of the importable industrial
SENEGAL’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# Roads

## **Achievements**

The existing network of 18,063 km of roads is adequate to provide basic regional, national, and international connectivity, linking Dakar to international border crossings and provincial capitals in the interior. This is generally true even if Senegal’s road density indicators, both for classified and total network, are lower than African averages for low- and middle-income countries (table 3). This reflects an efficient network design that has given priority to connecting Dakar and other relatively large cities (with a population of 50,000 or more) to major ports as well as provincial capitals and cities (with populations of over 25,000).

**Table 3. Senegal’s road indicators**

||Unit|Low-income<br>countries|**Senegal**|Middle-income<br>countries|
|---|---|---|---|---|
|Total road network density|km/1,000 km<sup>2</sup>of arable land|132.1|**93.8**|318.4|
|Classified road network<br>density|km/1,000 km<sup>2</sup>of arable land|88.2|**81.4**|278.4|
|Rural Accessibility Index—<br>HH survey|% of rural population within 2 km of all-season road|34.1|**29.0**|62.7|
|GIS rural accessibility|% of rural population within 2 km of all-season road|23.1|**25.7**|31.5|
|Paved road traffic|AADT|1,341.1|**944.9**|3,797.7|
|Unpaved road traffic|AADT|38.5|
As we are mainly interested in looking at how the division of output across public and private goods affects performance, we work with data on real government consumption and real aggregate physical investment. These are expressed as fractions of GDP and are taken from the Summers-Heston data set. These data are based on international prices or purchasing power parity values and facilitate cross-country comparisons over time. The transformation to international prices is not innocuous. Using national prices to get real expenditure ratios gives quite significantly different measures of govermrnent size -- as indicated by _Table I_ -- particularly for low income countries with a large non-tradable sector and large labour intensive components in government consumption. For these countries, using international prices rather than deflating by constant 1987 US dollar values increases the government consumption ratio substantially.

These size measures obviously only capture the fiscal actions of government. But governments also provide a key component of the overall institutional environment, encompassing the rule of law, the protection of property rights and the effectiveness of its bureaucracy. Such institutions set the rules of the game for the players in an economy and are hence critical in determining the ability of any private sector to function effectively. Recent empirical evidence suggests that the consequences of stable property regimes can be very significant, possibly equivalent in magnitude to the effect of education in determining growth '. Similarly, surveys of entrepreneurs in developing countries that have looked at the effects of instability -- where rules themselves are subject to frequent Keefer and Knack (1995).

8
|3.0|3.2|

Source: Own calculation based on Central Bank data.

**Table 24**

||**System Uquidity in**<br>|**Seleted Countries as of June 1**<br>|**997**<br>|
|---|---|---|---|
||Ratio of Short-terrm Debt<br>to Foreign Reserves|Short-term Debt<br>as Percentage of Total Debt|Ratio of Broad Money<br>to Foreign Reserves|
|Korea|3.0|67%|6.2|
|Indonesia|1 .6|24%|6.2|
|Thailand|1.1|46%|4.9|
|Philippines|0.7|19%|4.9|
|Malaysia<br>|0.6<br>|39%|4.0|
|Source: Goldstein (|1998), p<sup>11</sup>.|||

19 The Dresdner Scheme is a special arrangement between Dresdner Bank in Germany and the Central Bank of Turkey, to attract deposits of Turkish workers residing in Germany. The Central Bank of Turkey sets the interest rates offered under the scheme, with the Dresdner Bank acting as an agent to facilitate remittances back to Turkey.
, _V_ initially increases in absolute size as _w_ is increased, but subsequently declines as _w_ is increased further. This reflects two opposing tendencies: an ‘averaging effect’, which tends to increase _V_ as _w_ is raised (the

> 10  The VLSS measure of consumption reflects food and nonfood consumption during the previous 12 months.  The procedure used for both years is described in detail in the VLSS 1998 basic information document, which is downloadable from <u>http://www.worldbank.org/lsms/country/vn98/vn98bif.pdf.</u>

> 11  These are defined in local currency units in the base year—RMB or Yuan and 1989 in the case of China, and Dong and 1993 in the case of Vietnam.  In both cases, the values are per person, and are annual figures.
2019, or Bircan and Saka, 2019, on political lending)). Hence, when it comes to banking, ownership does matter and privatization decisions are critical for economic outcomes. It is, however, important to consider that the argument for bank privatization does not mean that there is no residual role for SOCBs, especially in developing economies. In large countries, only SOCBs are likely to be willing to serve customers in remote areas and in chronically underserved segments such as agriculture, though this argument may be losing power as digital technologies increasingly permeate the banking industry. Another argument for the government to keep limited direct ownership of banks is that SOCBs exhibit less procyclical lending behavior than private banks (Bertay et al., 2015), which is crucial especially for small open economies. Being a second-best solution, it would be important to ensure that these banks are subject to the same supervisory requirements as private banks to avoid distortion and monitor accountability.

This paper aims to revive the public policy and academic debate around bank privatization by analyzing the following questions: What are the key trends and drivers in bank privatization in recent years? Does privatization affect banks’ performance and business models? What methods of privatization are prevalent and what maximizes post-privatization performance? Under what institutional, market and regulatory circumstances does privatization lead to stronger bank performance, if any? What are the implications of privatization on banking sector employment and credit provision and composition?

This paper complements the existing empirical literature on bank privatization by using a novel and up-to-date data set, which covers a large set of countries. Specifically, our data set covers 70 countries during 1995-2017 and allows to compare the pre- and post-privatization profile of banks and to analyze the associations between sale events and various bank-level measures such as financial performance, business model, and distributional effects. Stylized facts presented in this paper show that bank privatization did accelerate sharply post-2000, driven primarily by developments in China and India, and remained constant following the GFC. While the number of privatizations increased, the average
require panel data and that is why the ELMPS for Egypt and the ENOE for Mexico are appropriate data sets for the analysis. All transition matrices describe transitions among five different labor market states: public sector employment, private formal sector employment, private informal sector employment, unemployment, and out of labor force. The computation of transition matrices for each individual country follows standard procedures. By construction, the sample is restricted to individuals interviewed in both rounds. The transition matrices are disaggregated by sex. Panel weights are used.

A frequency gap exists between the six-yearly ELMPS and quarterly ENOE. Even with the panel structure of the ENOE, one can at most compute annual transitions. Six-yearly transitions from Egypt and annual transitions from Mexico are clearly not comparable, as individuals not only have far more time to transition but also age to different extents. In the absence of data that allow for directly comparable transition, harmonization is in order.

In principle, we can either infer continuous-time transition intensity matrices for both labor markets or simulate in discrete time six-yearly transition matrices in Mexico based on annual ones. However, the former approach is riddled with issues that make it less reliable and can only be imperfectly addressed by existing techniques.<sup>10</sup> We therefore opt for simulation. In the simulations, we assume labor market transitions in each period to be discrete-time Markov processes. That is, the transition probability for each worker from one state to another depends on and only on her initial state. Hence, Markov processes are “memoryless,” as each individual’s history is irrelevant. This is unlikely to be entirely accurate, as the probability of one’s transition would depend on whether, or to where, one has recently transitioned but delivers a feasible solution to the problem of comparability.

Further, we assume the transition probability matrix in each period to always be the empirical annual transition matrix observed from 2005 Q1 to 2006 Q1. This assumption is unlikely to be entirely accurate as well. Individuals age and change
on age, gender, and region to mirror the country’s populations. To get a quota sample and optimize recruitment, we updated the ad placement in real-time based on participating Facebook users’ characteristics to ensure proper representation of each demographic group in the final sample using marketing applications such as the Virtual Lab (Rao et al., 2020) and RevealBot (RevealBot, 2024). For example, if a subgroup was underrepresented and had higher attrition or non-response, then the budget for ads targeting that demographic subgroup was automatically increased to better approximate the required sample for that subgroup.<sup>4</sup> Across all studies, the final sample included 229,886 responses in 28 studies with an average of 7,800 responses per online study. Only participants who had not received the COVID-19 vaccine were included in the experiment ( _n_ = 123,720), which is the focus of the results reported in this paper. No

> 4 For example, we recruited participants in Iraq targeting ads based on a combination of gender, age group, and governorate. This combination created x strata for recruitment with each stratum reflecting a combination of these three characteristics. For instance, one set of ads targeted women aged 40-49 who lived in the governorate of Baghdad while another set of ads targeted men aged 40-49 who lived in the governorate of Baghdad with quota targeting based on the latest available population data. During data collection for the study, if the proportion of participants from this demographic group in the study sample was lower than its proportion in the broader population, the recruitment ads were dynamically adjusted to spend more money to better target this population and increase its proportion in the study sample.

6
think. Where these conditions are not present, student learning is likely to be impeded. This is especially the case for boys, who may require a greater degree of behavioral support and guidance from adults to engage fully with schoolwork in a structured classroom setting in a single-gender school environment. Where such support and guidance are lacking, boys appear to fall behind in their learning and are at risk of being held back for a year to a greater degree than girls who similarly lack a positive school climate. This may be related to gendered differences in societal expectations (Ridge and Jeon 2020) and, as indicated by the NALO data, greater support for learning for girls at home (Ridge and Jeon 2020). Teachers can help to create positive learning environments and encourage active student participation in their learning by, for example, integrating students’ interests into the lesson material where possible and remaining alert to the effects of stereotypes, such as boys being more suited than girls to science and mathematics, and girls being more suited to reading, that may negatively affect how students engage with lessons and how teachers communicate with their students (Brozo et al. 2014; OECD 2015). It is also important that lessons are challenging but at a level that students can realistically engage with and understand; where basic prerequisite learning has not been solidified, teachers are likely to find themselves covering more advanced topics with limited student engagement or understanding (Niemiec and Ryan 2009). Other practices that teachers can integrate into their teaching in order to create a positive learning environment include offering students choices, providing rationales for decisions made or where choices cannot be offered, encouraging students to ask questions and to offer their perspectives, listening to and acknowledging students’ contributions, and offering constructive feedback on how students can improve (Teixeira et al. 2020).

A supportive school environment is important for boys’ learning, but support for learning in the home is also crucial. By the time students begin attending school, they have been growing, developing, and