rafmacalaba/data-use-mentions-extended huggingface dataset:
**Table 5.** Technical quality of infrastructure services, by country income group

||Electricity<br>(1999)|Water<br>(1997-01)|Telecoms<br>(1997-00)|Transport<br>(1997-00)|Housing<br>(1994-00)|
|---|---|---|---|---|---|
|Income group|_Transmission and_<br>_distribution losses_<br>_as percentage of_<br>_total output_|_Percentage of urban_<br>_households with water_<br>_access that get water from_<br>_piped or well water source_|_Reported_<br>_phone faults_<br>_per 100 main_<br>_lines_|_Percentag_<br>_e of total_<br>_roads_<br>_paved_|_Percentage of_<br>_structures built to_<br>_last 20 years_|
|Low|24.1<br>(33)|89.4<br>(48)|77<br>(48)|28.6<br>(59)|76|
|Lower middle|16.2<br>(31)|84.5<br>(18)|42.9<br>(38)|46.9<br>(46)|94|
|Upper middle|13.6<br>(23)|n.a.|25.3<br>(27)|55.1<br>(33)|97|
|Best<br>practice<br>in OECD|8–12|100|<5|>80|100|

Note : Figures in parentheses indicate the number of countries for which data are available. Source: USAID Demographic and Health Surveys; World Bank, _World Development Indicators_ , various years; International Telecommunication Union; Angel, 2000.

New investment also requires policy
In 1993-2003, the shift of labor into higher-productivity sectors contributed on average only 0.8 percentage point to overall productivity growth of 7.7 percent per year. On the other hand, “organic” productivity growth in industry, contributed a spectacular 5.2 percentage point to _overall_ productivity growth (2/3 of the total).

Concerns about the quality of China’s macroeconomic data warrant caution. However, as illustrated in the Annex, data issues are unlikely to change the conclusions of the paper materially.

Table 2. China: sectors' contribution to overall labor productivity growth (1978-2004) (average annual increase, in percent)

||1978-93|1993-2004|
|---|---|---|
|Labor productivity 1/|6.7|7.7|
|From shifts in employment b/t sectors|1.2|0.8|
|From organic productivity increase in sectors|5.5|7.0|
|Agriculture|1.0|0.5|
|industry|2.7|5.2|
|Services|1.4|1.1|

_Sources: NBS, and authors' estimates._ 1/ Artithmetic average, implying small differences with geometric averages used in the rest of the paper.

The important roles of capital and industry in China’s economy are of course related. Industry requires more physical capital per worker than the service sector, and, accordingly, the share of income distributed to workers is lower in industry than in the services sector. Indeed, countries where industry is more important tend to invest more.

The growth pattern described above generated very high GDP growth for China with only moderate urban employment growth, strikingly at odds with the theoretical expectation and most analyses/assumptions of what has happened in China. Indeed, the persistence and widening of large sectoral labor productivity gaps and the lower-than-expected flow of labor in the presence of those gaps points to market imperfections and/or
. See, however, Hazans (2011a; 2011b) for a simultaneous analysis of informal dependent employment, informal self-employment, unemployment and inactivity.

In Eastern Europe (but not elsewhere), workers who are return migrants are more likely to be employed informally. This is consistent with the idea that a substantial part (although not necessarily a majority) of return migrants might be ―negatively selected‖ out of homecountry‘s labor force, and their return is an evidence of not being successful abroad as well. It is enough if the proportion of such low-productivity workers among return migrants would be substantially higher than the informality rate among stayers, which is about 5% in the Eastern Europe, and such a situation is quite a likely outcome; Hazans (2008) shows that about 25% of return migrants are negatively selected.

> 26 This result does not apply to Hungary, Romania, and Slovenia. However, at least for the former two countries, this might be due to data limitations: It is well documented (see e.g. Kahanec et al., 2010; Kahanec and Zimmermann, 2011), that informal employment is common among Roma population across Eastern Europe. Yet this minority group is severely under-represented in ESS samples for Hungary and Romania.

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7 students to about CNY 3,000 (about US$500) on Grade 9 students per term. On average, tutoring spending is around CNY 1,600 (about US$250) per term for Grade 9 students, compared with CNY 950 (US$150) for Grade 7 students.

Figure 3.17 Household tutoring expenditure per term <!-- Start of picture text --> 3,500<br>2,977<br> 3,000<br> 2,500<br>2,031<br> 2,000 1,781 1,642<br> 1,500<br>867 950<br> 1,000 570 700<br> 500 369 293 396 276<br> -<br>city center city outskirt city/rural Town outside rural Total<br>bordering city<br>Grade 7 Grade 9<br><!-- End of picture text --> _Source_ : Authors’ calculation based on the CEPS.

Household tutoring expenditure is highly associated with student school performance. While parental education and household location (urban versus rural) are naturally correlated with household tutoring spending, parents tend to spend less on tutoring when their children’s performance rank in class is higher (Figure 3.18). Gaining an edge in Zhongkao serves as a strong incentive for households to spend more on improving their children’s school performance. In contrast, household economic condition, which normally has a strong wealth or income effect on spending, does not appear to have significant effect on tutoring spending.

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WPS3656

# World Bank Lending and Financial Sector Development

Robert Cull Laurie Effron<sup>•</sup>

## **Abstract**

Using a new database of World Bank loans to support financial sector development, we investigate whether countries that received such loans experienced more rapid growth on standard indicators of financial development than countries that did not. We account for self-selection with treatment effects regressions, and we also use propensity score matching techniques. Our results indicate that borrowing countries had significantly more rapid growth in M2/GDP than non-borrowers, and swifter reductions in interest rate spreads and cash holdings (as a share of M2). Borrowers also had higher private credit growth rates than non-borrowers in treatment effects regressions, but not in standard panel regressions with fixed country effects. On the whole, however, the results indicate significant advantages for borrowers over non-borrowers in terms of financial development.

## JEL Classifications: F33, G21, O16

Keywords: International Financial Institutions, Development, Banking

## World Bank Policy Research Working Paper 3656, July 2005

_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 entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> • We thank Thorsten Beck, Gerard Caprio, Stijn Claessens, George Clarke, Charles Goodheart, Greg Ingram, James Hanson, Patrick Honohan, Daniel Lederman, David McKenzie, Caglar Ozden, Kyle Peters, and Colin Xu for helpful comments, and Maria del Pilar Casal, Sarojini Hirshleifer, and Gulmira Karaguishiyeva for excellent research assistance.  Authors are World
also true that-in multiple-country portfolios-the decision<sup>20 21</sup> about which country<sup>to withdraw from belongs to the managers.</sup>

> 20 Investors obviously determine the withdrawal country in the case of single-country funds.

> 21 There are two drawbacks to this data set. First, here we use data only from Latin American funds. In the future, it will be interesting to study the behavior of managers **by** considering a broader set of mutual-fund types. Second, our data do not provide a complete picture of managers' responses to liquidity squeezes because we do not have information on funds' credit lines with banks. Funds mired

> in redemptions may have resorted to using such credit lines.

21
LSMS-ISA panel to explore labor market effects from large farm establishment.<sup>7</sup> Second, to account for inter-temporal variability in climatic conditions, we rely on gridded 0.1’ rainfall data publicly available from NOAA since 1980 to compute long-term mean and standard deviation of precipitation for each pixel. Calculating z-scores and matching them to kebeles then allows us to determine for each year if a kebele experienced drought (z<-1), a flood (1<z), or ‘normal’ conditions (-1≤z≤1).

# **2.4 Analytical approach and estimating equations**

As we have a census of the country’s large farms in 2014, we use time variation in smallholder kebeles’ proximity to large farms (generally or growing specific crops) in 2003/4-13/4 period to test if smallholders’ improved seed/fertilizer use, yields, employment, or resilience are affected by large farm presence. To do so, we construct, for every year, either the distance from every smallholder kebele to the next large farm of any kind (growing the same crop) or, as a measure of exposure, total large farm area (with the same crop) in a concentric circle with inner and outer radius of 0 to 25, 25 to 50 and 50 to 100 km from the kebele.

Formally, denote kebeles by _i_ , distance bands by _d_ , crops by _k_ and time by _t_ . The simplest specification then uses _dit_ or _dikt_ the distance between the centroid of kebele _i_ and the next commercial farm (or the next farm growing crop _k_ ) with squared distance to allow non-linear effects to estimate a regression of the form: ���� ��������� �������� �������� ��� ��� ����� (1) where _Yikt_ is the outcome of interest, i.e. either
as nested|Exogenous|
|**IFs**|Energy demand is estimated as<br>a function of the energy<br>demand per unit GDP and<br>total GDP, with adjustments<br>related to energy prices and<br>energy efficiency|Aggregate|Exogenous|
|**PHOENIX**||Ground transportation differs from air and water<br>transport in that we allow for substitution away from<br>conventional transport to hybrid electric (HEV)<br>and/or biofuel backstop technologies when they are<br>cost competitive. The elasticityof substitution is 1.2|Exogenous|
|**WorldScan2**|Production sectors using<br>energy as intermediate input<br>and households consuming<br>energydirectly.|Aggregated|Exogenous|

17
taged regions, providing pre-primary education, teacher training and mentoring for female students<sup>1</sup> , led to an increase of more than one-third in Grade 4 learning outcomes between 2014 and 2016, enabling these regions to overtake the rest of the country (Asim et al., 2019).

There is substantial evidence that reducing class sizes can lead to improved test scores, although the evidence is mixed and dependent on context and the size of classes before and after reductions. In high-income countries, Angrist and Lavy (1999), exploiting a class size limit of 40 in Israel to conduct regression discontinuity analysis, estimate that reductions in class size can induce substantial improvements in test scores for older primary school students (Grade 4 and 5); however, later analysis using more recent data suggested no impacts on learning from the class size reduction (Angrist et al., 2017). Similarly, Kreuger (1999), analyzing longitudinal data from the United States, finds reductions in class size associated with improvement in standardized tests of at least four percentile points; however, Hoxby (2000), conducting further analysis on similar data, finds no significant impacts on learning from class size reduction. Analyzing cross-country data from 47 countries with pupil fixed effects, Altinok and Kingdon (2011) conclude that the negative effects of class size are small and observed in a minority of countries.

Turning to low- and middle-income countries, where class sizes tend to be significantly larger, Muralidharan and Sundararaman (2013) combine experimental and panel data and estimate that the addition of contract teachers to schools in India to reduce pupil-teacher ratios (PTRs) led to an improvement in student learning of 0.15-0.16 standard deviations (s.d.) in math and language tests. In addition, Duflo et al. (2015) conduct an experimental evaluation of a similar intervention in Kenya found that the apparent benefits of class size reduction only for students in the classes taught by contract teachers and not for students in other
experiments involve randomly allocating respondents into two groups. They are then shown a list of statements and asked to state the number of statements (but not which specific statements) are true in their case. The list shown to the ”treatment” group includes one extra statement about the sensitive issue (e.g., not paying all the taxes that they owe). While it is not known which specific respondents have agreed with the statement on the sensitive issue, differences in the average number of statements reported as true between the treatment and control groups can be used to estimate the prevalence of the sensitive response. If respondents do not engage in sensitive activities, the mean number of items should be the same between the control and treatment groups. The double list experiment approach is an extension of the traditional single list experiment: respondents complete two list experiments sequentially and are randomly allocated to the treatment group in one of the two.

The double list experiment included as part of the WBES is shown in Table 1. Respondents were randomly assigned to either Group A or Group B. Each group was given two list questions to respond to, but with a slight variation between the groups. Group A received the treatment in List 2 while being the control for List 1 (note the statement about taxes in Group A’s List 2). Group B had the opposite arrangement, receiving the treatment in List 1 while serving as control in List 2. The treatment is the inclusion of a sensitive item asking about tax evasion, specifically “This establishment does not pay all the taxes it is required to pay.” The exact location of this statement in the list of statements was randomized. This text is identical to what was used in previous studies asking directly about tax evasion and has been trialed as part of single list experiments on firms in other middle-income countries (e.g., see Dom et al., 2022). The other statements in the double list experiment were carefully determined to minimize the risk that
Komives, Whittington, and Wu "Infastructure Coverago and the Poor: A Global Perspective" Acknowledgements: We would like to thank Penelope Brook for her insights and support throughout this project, and Diane Steele for her help in assembling the LSMS data sets. We would also like to thank Margaret Grosh and Paul Glewwe for introducing us to the LSMS data sets and for their long commitment to ensuring both the quality and the accessibility of the data from these unique household surveys.

22
there is an evidence gap for high-stakes academic settings among older students. Garg et al. (2020) identify that hot days during the agricultural growing season are associated with both lower agricultural yields as well as lower test scores for younger students in rural India. They provide suggestive evidence of the introduction of a workfare program weakening the effects of high temperatures on test scores. Zhang, Chen, and Zhang (in press) find that the prevalence of high temperatures at the time of a low stakes cognitive test evaluated during household surveys in China is associated with reduced cognitive performance, especially for older and less educated respondents. In high stakes settings, evidence from China suggests that that high temperatures during the day of the exam are negatively associated with test performance (Graff Zivin, Song, Tang, & Zhang, 2020).

Existing studies either provide evidence on the impacts of heat on cognitive performance in high-stakes settings in rich countries or in lower-stakes settings in middle income countries.<sup>2</sup> Our paper fills a gap in the literature examining the direct impact of heat

> 1See, for example, Graff Zivin, Hsiang, and Neidell (2018); Park, Behrer, and Goodman (2021); Park, Goodman, Hurwitz, and Smith (2020). For a broad overview of this literature see Park and Heal (2016).

> 2On the separate, but related, question of school attendance, Randell and Gray (2019) study 29 tropical countries, which include 11 African countries (excluding Ethiopia), and find negative impacts of prenatal exposure to higher-than-average temperatures on years of schooling completed. Furthermore, they find that these effects are pervasive across all income groups; especially in the case of West and Central Africa. They

2
LPG. In several low- and lower-middle-income countries, rising income shifted many households from wood to charcoal rather than to LPG or electricity. In Kenya and Nigeria, a greater proportion of the rich cooked with kerosene than the poor (Figure 3). The corresponding urban and rural results are shown in Figure A2.3 and Figure A2.4 in annex 2 with an associated commentary.

**Figure 3  Difference between the top and bottom quintile in the percentage of people citing different forms of primary energy for cooking**

<!-- Start of picture text --> Electricity<br><!-- End of picture text --> <!-- Start of picture text --> Biogas+solar<br><!-- End of picture text --> _Source_ : World Bank staff calculations using household survey data _Note_ : For each energy category, the number shown is obtained by subtracting the share of the population in the bottom quintile from that in the top quintile. Others = mostly agricultural residues and dung.
Henderson, and Tsui 2008). Raw Herfindahl index scores for industries for Beijing and Tianjin fell between 1993 and 2001, while normalized Herfindahl index scores increased, suggesting that industry structure in the PRC has become more specialized, and differentiated from the national average.

However, even with the increasing concentration of economic activities in large cities, the PRC may still be underconcentrated and underurbanized. Evidence from the 2000 Census suggests that the PRC was underurbanized. The PRC ranked low in a worldwide comparison of developing and large countries with respect to the share of its population living in large cities. Its population Gini coefficient, which in this context means the area between the 45 degree line and the Lorenz curve as a measure of the aggregated population share of its cities, is remarkably low for a large country. Formal restrictions of the hukou system combined with limited access to housing, education, and health care for migrant labor has discouraged migration, while rural industrialization through the promotion of TVEs has retained labor in rural areas. Au and Henderson (2006) estimate the efficient sizes of cities in the PRC as a function of each city’s manufacturing over service ratio, as well as a variety of control factors. They find that the populations of 85% of prefecture-level cities in the PRC are smaller than their efficient sizes, and 43% of prefecture-level cities lie below the 95% confidence intervals generated by their models. Both results suggest that cities in the PRC are significantly undersized.

# **B. Rural-Urban Integration**

The initial chasm between the rural and the urban in the PRC was deep and wide. After the 1949 Revolution in the PRC, the country’s leaders promoted the development of heavy industry and implemented a planned economic system that fixed prices and allocation of all inputs. Labor allocation was conducted by the Bureau of Labor and Personnel (Cai, Park, and Zhao 2008). Agriculture was collectivized in self-sufficient communes by 1957, and any excess grains the commune produced were prohibited from being traded. In line
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menting large gains in consumption and income for displaced migrants who took up the regularization program.

# **II.C Legal service access for migrant children and adolescents in Colombia**

In Colombia, migrant children and adolescents, irrespective of their migration status, are afforded basic access to emergency health services and education, although the latter comes without the possibility of graduation. A summary of the rights available to Venezuelan migrant children and adolescents in Colombia, categorized by their migration 1. status, is presented in detail in Table Children and adolescents with regularized status enjoy full access to all social services. In contrast, undocumented minors encounter barriers, including limitations on obtaining a bachelor’s degree, accessing technical or technological education, affiliating with subsidized public health insurance, and registering for the principal administrative survey (Sisb ́en), which facilitates eligibility for means-tested programs. These disparities in service access could profoundly influence the life chances and well-being of migrant children from varied backgrounds.

Table 1. Legal Rights and Services for Venezuelan Children and Adolescents in Colombia

||Regular|Irregular|
|---|---|---|
|**Education**|||
|Food and school bus service|✓|✓|
|Primary and secondary|✓|✓<sup>_a_</sup>|
|Promotion across levels|✓|✓|
|Bachelor’s degree upon completion|✓|No|
|Technical or technological education|✓<sup>_b_</sup>|No|
|**Health**|||
|Emergency care|✓|✓|
|Public health programs|✓|✓|
|Vaccines|✓|✓|
|Prevention campaigns|✓|✓|
|Affliation subsidized regime|✓|No|
|**SISBEN**|||
|Registry|✓|No|

_Notes:_ (a) Children without a valid ID must register at the local secretary of education prior to enrollment, (b
[0.804]|[0.868]|[0.778]|

Source: RUMiC Migrant Survey 2015 and 2016, RUMiC Information Intervention Field Experiment, 2016. Notes: The additional variables included in Model 1 are a vector of city fixed effects; in Model 2 we also add individual level controls (age, gender, education, marital status, number of children, dummies for selfemployment, dummy for working and an interaction between self-employment and lagged (2015) dependent variable and dummy for “willingness to remain in the city permanently if policy permits.”), while Model 3 adds firm level controls (pre-treatment firm size and ownership indicator variables ) as well. Robust standard errors clustered at workplace of household head are in parentheses. P-values are in brackets. Significance codes: *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.

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