rafmacalaba/data-use-mentions-extended huggingface dataset:
classification methodology will need to be introduced carefully, perhaps alongside existing methods.

Other classification schemes have been proposed, for example using cluster analysis techniques, or using methods based on the construction or use of appropriate indices to replace or supplement the use of GNI per capita. For example, Nielsen (2011) and Vázquez and Sumner (2012 and 2014) consider the use of measures of poverty, inequality, and human development. Other candidates proposed include the Human Development Index of the United Nations Development Program and the Multidimensional Poverty Index of the Oxford Poverty and Human Development Initiative. However, some of these composite indicators and methods also attract criticism, including the arbitrariness in weighting patterns, the implicit trade-offs between components, and their practicality when based on indicators with poor geographic coverage and update frequency. Analyses of these alternatives have not been attempted here, though it can be argued that they can also produce abrupt or inexplicable changes in classifications from one period to the next. It is also important to note that classifications based on such approaches would “decouple” the analytical classification of countries from the Bank’s operational guidelines.

Different classification schemes are already in use by other international agencies; selected groupings are presented in Annex 2, including those used in the Human Development Report of UNDP, the World Economic Outlook of the IMF, and the World Economic Situation and Prospects report of the United Nations. The UN statistical convention of developing and developed regions and the UN operational categories of Least Developed Countries, Land Locked Development Countries, and Small Island Developing States are also listed, since these are commonly used.

# **8. Conclusion**

This paper reviews the methodological details of the current income classification of the World Bank, highlighting its pros and cons. A classification based on GNI per capita covers almost all countries in the world and can be updated on an annual basis. While critics argue that the thresholds of the Bank’s income classification are dated and yet used by many for policy purposes, it should be emphasized
this model than the other two. Thus, the time from group formation to first loan disbursal can be as little as a few davs to a few weeks.

# **Program Performance**

This section reviews program performance as measured by sustainability and outreach. Sustainability is measured by the program's arrears rate, its cost per unit outputs, and the size of the subsidy required to sustain operations. Outreach is measured by the volume of annual lending and savings activities (scope) and the population it serves (depth of market penetration).

_Sustefinability._ PHBK Table 21 experienced early Arrears Rates for PHBK Program problems with high arrears. However. Fiscal Year recent repayment 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 performance has been Number of credits 17.2 21.1 29.0 19.9 11.5 12.9 sound. Information on ovcrduc percent of the share of the PHBK number of credits portfolio at risk was not outstanding available. However, the Volume of payments 5.0 14.2 13.3 16.5 8.7 5.7 program's ratio of overdue percent of program's raho of volume of loans number of credits outstandinga _ overdue to number of credits outstanding41 a/ Overdue payment is defined as a paymen **t** hat is one day late or more. climbed sharply over the two years from fiscal 1990/91 (April 1990 to March 1991) to fiscal 1992/93. By the end of fiscal 1992/93, loans in arrears accounted for 29 percent of outstanding loans. This figure has since declined, and stood at 13 percent in 1995/96 (Table 21 ).42 The volume of late payments as a share of the volume of outstanding loans rose from fiscal 1990/91 to 1993/94 and then declined. This rate was 5.7 percent in fiscal 1995/96. Data do not allow for a calculation of the program'
produces grain) can provide a foundation for sustainable crop management. Modest application of nitrogenous fertilizer to monoculture maize was effective at doubling yield, but a rotation system with semiperennial legumes reduced the variability of yields, produced grain with 45 to 70 percent higher protein, and improved nitrogen recycling. Across sites, profitability and farmer preferences, expressed by spontaneous adoption, were in accord with these findings.

_Other Crop Management Practices_<sup>_5_</sup> Extension efforts increasingly emphasize the use of more legumes, intercropping, organic manure, reduced tillage, herbicides and agroforestry, and there are some indications that farmers are adopting such practices (Holden and Lunduka 2010a). Intercropping may also be rising in some maize-based systems. Based on panel data collected by Tegemeo Institute of Egerton University, Ariga and Jayne (2010) found a rising trend in the proportion of maize area planted in more complex intercropped patterns from the mid 1990s.

Experience from many African countries has shown that seasonal labor availability is an important constraint on the acceptance of improved management practices such as plant spacing and weeding that are relatively labor intensive. If these are recommended as a package with fertilizer and seed, the profitability of other components is also affected. Even where land is in short supply, seasonal labor shortages often decisively influence farmers' choice of technology for several reasons: hand-hoe agriculture demands a great deal of labor, off-farm work is

> 5 Technologies and management practices to reduce post harvest losses should be added to the list of opportunities for improving the efficiency of the maize supply chain. Various estimates put post harvest losses for maize grown by smallholders in the humid tropics of Africa at 15-20%.

10
quarters of 2010. On the other hand, rainfall was substantially above average in the third quarter of 2011, and close to exactly average in the third quarter of 2014. As mentioned above, favorable rainfall may have contributed to the strong growth in survey consumption between 2009-10 and 2011-12, but did not continue in the summer of 2014.

# **III Empirical Methodology**

## **A Econometric Model**

The specification of the model is based on the small area estimation (SAE) methodology originally proposed by Elbers, Lanjouw, and Lanjouw (2003). This methodology generates a joint distribution of economic welfare and independent variables in the target data set, where a welfare measure is not available. The process consists of two steps. The first involves estimating the relationship between economic welfare and explanatory variables in the source data set, in which a welfare measure is available. The parameters are then used to simulate economic welfare into the target data set.

The first step in this analysis is to estimate the relationship between household per capita consumption expenditure (the measure of economic welfare) and other explanatory variables, in the three available source data sets with consumption data. The explanatory variables are those that are available in both the source and target data sets. The regression is a log linear specification relating per capita consumption expenditure to household and regional variables using the 2004-05, 2009-10 and 201112 surveys (equation 1).<sup>25</sup> The welfare measure is _ycht_ , which is household per capita expenditure for a household in cluster _c_ and household _h_ , interviewed in survey round _t_ . A cluster is a primary sampling unit (PSU) as defined in the NSSO surveys. For all surveys, _ycht_ is measured in 2011 rupees using separate CPI indices for urban and rural areas.<sup>26</sup> The _X_<sup>_h_</sup> vector in equation (1) consists of an intercept plus household level demographic variables, labor market variables and expenses on
the weight of home-based mobility in both metropolitan areas. Also travel for work and education specifically (“compulsory travel”) had reached (AMBA) or even exceeded (Bogota) pre-pandemic levels, while non-compulsory travel remained at 10-11 percent below the 2019 level.

**_Figure 9:_** _Recovery of “compulsory” versus “non-compulsory” travel_

<!-- Start of picture text --> a. Bogota b. AMBA<br>3%<br>2019 vs 2020<br>2019 vs 2021<br>-1%<br>-11% -10%<br>-11%<br>-17%<br>-17%<br>-27%<br>Compulsory Non-compulsory<br>Compulsory Non-compulsory<br>Source: Authors based on CDR data<br><!-- End of picture text --> Mobility within Bogota associated with residents in other municipalities continued to fall in 2021, so that on weekdays its share was 20 percent lower than in 2019. Relatedly, average distances traveled remained much below the 2019 level and mobility became significantly more spatially dispersed compared to both 2019 and 2020. In contrast, in AMBA, average distances traveled in 2021 were already _above_ those recorded in 2019 (+3.2 percent) – in other words, the trends had more than fully reversed compared to 2020. Similarly, after an initial strong increase in spatial dispersion of travel, 2021 saw a partial reversal, with more trips recorded per OD pair compared to 2020. Also in contrast to Bogota, the trip generation of residents living in the Province of Buenos Aires traveling to CABA increased a lot compared to 2020 although it did not yet fully recover.

One of the more permanent imprints on mobility behaviors left by the pandemic – those still observable nearly two years later – was in terms of modal choices. Some of the changes in modal choices introduced by the "deep 14
# Conclusion

There is policy and academic demand for a measure of education quality that is comparable across countries and over time. The growth of international standardized achievement tests is a huge step in this direction. However, the countries that participate in these tests are often high and middle-income countries. This limits the ability to track, compare, or understand education patterns in developing countries – the countries that often have the most to gain from quality education and human capital formation.

One option is to wait to make comparisons for low-income countries to participate in international assessments. Although this is a worthy aspiration and we hope it occurs, it will take time and render a rich array of retrospective data null, limiting longitudinal data analysis. Alternatively, we can use a rigorous approach – albeit with caveats – to harmonize available learning data across different types of international and regional assessments. This is the approach we take in this paper, creating a Harmonized Learning Outcomes (HLO) database. Until there is a global proficiency assessment for numeracy and literacy, and to enable rich longitudinal panel data analysis, the harmonization of existing learning assessments provides the next best alternative to compare education quality on a global scale. Moreover, as more countries join international and regional assessments, and do so for longer, the accuracy and robustness of the harmonization exercise will improve.

We build a globally comparable database of 164 countries/territories from 2000-2017, approximately two-thirds of which are in developing economies, representing more than 98 percent of the global population. While our methodology has limitations, our robustness tests indicate that this dataset produces similar results to each underlying assessment used, as well as Item Response Theory (IRT)-linking methodologies where there is overlap. We include double the number of countries of any individual assessment or IRT-linking methodology while demonstrating consistent estimates where there is overlap.

We contribute to the literature in several ways. This is the most current and expansive cross-country dataset on education quality, including the most developing countries. We include, for the first time, the
of households to the sample at midline causes differential attrition to become significant for T1 at midline since fewer households were added to this group (Column 3). The overall level of child attrition is around 10% at both midline and endline, and mostly due to seasonal migration.

**3.2.3 Quality of CPS and other preschools**

We construct measures of preschool quality based on data from two sources, classroom observations and parent reports.

# **_Preschool Quality Measures_**

We use the teacher survey and classroom observation tools to assess how new CPS compare to SPS and IPS in terms of structural and process quality. We compare the different preschools in three dimensions of structural quality (teacher characteristics, equipment, classroom setting) and two dimensions of process quality (curriculum and pedagogy, teacher-child interactions).

Individuals quality measures are summarized using aggregate measures for each of the five dimensions of structural and process quality, calculated as the first principal component of individual variables (Table 4, panel “Preschool comparison”).

> 25This is probably due to the fact that setting up an HBP takes much less time than building a CPS.

15
KPIs, measured in days or simple counts, are relatable to policy makers and practitioners concerned with the performance of key logistics hubs or gateways, such as ports or airports.

# Digitization and new opportunities: massive tracking data

Since the first release of the Logistics Performance Index in 2007, the data ecosystem of supply chains has changed radically. Tracking data is now abundant, and at least for some modes, from globally consistent sources. Much of this change is driven by digitization of supply chains where shipments and assets are located in real time. This knowledge allows the owner of the goods, or its agent, to make timely decisions on purchasing, inventory management, routing or rerouting. Digitization has transformed supply chain management techniques and improves operational efficiency and flexibility and reduces costs across supply chains.<sup>6</sup> Supply chain data interoperability across the supply chain participants is essential to supply chain digitization: Third-party logistics operators should exchange seamlessly with carriers (e.g., shipping lines). Industry initiatives to normalize supply chain data or create shared tracking repositories are critical to the fast adoption of digitization. For instance in the area of container shipping, the Digital Container Shipping Association<sup>7</sup> promotes common standards, while the now discontinued TradeLens was an attempt of a common digital platform.

Digitization of supply chain operations generates massive granular high-frequency datasets. The volume of information on cargo, vessel and vehicle movements in time and space offers new opportunities to analyze supply chains and logistics services provision at the national level and globally.

To construct the new set of indicators for the LPI 2023, the World Bank collaborated with external data providers in the logistics industry. The data comprised high-frequency, micro-level datasets, namely: (i) dwell time and connectivity of containerized trade based on consignment activities from TradeLens (ii) speed of international parcel movements from the Universal Postal Union (UPU); (iii) air cargo tracking from Cargo iQ (IATA); (iv) container lines shipping
<!-- Start of picture text --> Total Manufacturing<br><!-- End of picture text --> Radio, television and communication equipment <!-- Start of picture text --> Rubber & Plastics<br>Chemicals<br>Paper<br>Textiles<br>Food & & Beverages<br>OECD FDI<br>Restrictiveness 0 0.05 0.1 0.15 0.2<br> authors’<br>62010 62006 §2003 1997<br><!-- End of picture text --> <!-- Start of picture text --> Food & & Beverages<br><!-- End of picture text --> Source: BPS, OECD FDI Regulatory Restrictiveness Index, and authors’ calculations.
context of Turkey, households with a food consumption score greater than 42 were considered to have “acceptable” food consumption, those with FCS greater than 28 and smaller than or equal to 42 were considered to have “borderline” food consumption, and those with FCS of 28 and below were categorized in the “poor” food consumption group.

# _c) Reduced Consumption Coping Strategies Index (rCSI)_

The Reduced Consumption Coping Strategies Index is used to assess the level of stress faced by a household due to food shortage. It is measured by combining the frequency and severity of the different food consumption-based strategies households are engaging in, which are a subset of the Coping Strategies Index (CSI) that is comprised of a more detailed context specific list of food related coping strategies (Maxwell and Caldwell 2008). The rCSI includes coping strategies that are more universal across settings, has greater application in comparing across different contexts and correlates with other indicators of food security as well as the more detailed CSI index.

The rCSI is calculated using five standard strategies and a seven-day recall period. The five standard coping strategies (and their severity weightings) are: relying on less preferred, less expensive foods (1); borrowing food 11
# **1 Introduction**

While the returns to credit and other benefits of financial inclusion have been of central interest in academia and policy, relatively less attention has been paid to the limits of private sector incentives to achieve financial inclusion. In deciding whether to issue credit to a new borrower, a profit-maximizing lender must consider the costs of screening the borrower and issuing the loan, how much debt the borrower can reliably service, and how long the borrower will remain a customer. This final consideration is typically framed based on whether a borrower will eventually join a competing lender after the initial lender has incurred the cost of establishing her reliability (e.g. Petersen and Rajan, 1995), but in principle this form of competition could occur even before the first loan is issued. If lenders are more likely to approve borrowers already approved by their competitors, then lenders that incur the cost of evaluating new or underserved borrowers may not reap the resulting benefits. This phenomenon whereby lenders free ride on the screening efforts of their competitors reduces the incentive to expand credit access and financial inclusion and might warrant policy intervention.

We demonstrate that free riding in loan approvals has a large impact on market outcomes. Specifically, we worked with a large Peruvian bank interested in expanding credit access to small and medium enterprises (SMEs). Our partner bank adopted a new screening technology and determined which SMEs to lend to based on a scoring rule with a strict threshold. Borrowers above the threshold were automatically granted a loan, whereas borrowers below the threshold were offered a loan only if a loan officer deemed it appropriate. Borrowers above the threshold also received more attractive loan terms. Exploiting this threshold along with administrative data from our partner bank and credit registry data from Equifax Peru, we document several findings.

While applicants _without_ prior credit histories who score above the threshold were more likely to receive a loan than those who score below it, three-quarters of the additional loans were issued by competing financial institutions rather than from our partner bank. Because the
Croke et al. (2016) Reasonable people may disagree about statistical methods for analyzing data. However, at a minimum, it seems clear that implementing MDA generates child weight gains in some circumstances. Since the null hypothesis of a common zero effect is rejected, MDA must have positive impacts in at least some environments. This implies that if one accepts the standard view that anthelmintic drugs have no substantial negative side effects, the expected effect of deworming on child weight is positive.

Applying standard approaches from the _Cochrane Handbook_ to a larger set of studies yields an estimated average effect of deworming on weight of 0.134 kg [95% CI: 0.031,0.236], corresponding to an estimated average effect of 0.301 kg [CI: 0.071, 0.530] among those with worm infections. While this effect is modest, it is substantial relative to the cost of deworming, and suggests that deworming is many times as cost effective as widely implemented school-feeding programs at enabling weight gain among school age children in low-income populations. Moreover, the findings that deworming improves nutrition in at least some environments implies that the literature on the long-run educational and economic impacts of deworming cannot be dismissed on _a priori_ grounds, and this literature suggests that the expected benefits of MDA greatly exceed the cost.

Our results also suggest that the data from studies of mass deworming are consistent with the data from studies of deworming of those known to be infected, given the much lower prevalence and intensity of infection in MDA studies than in test-and-treat studies, and the substantial confidence intervals around both the MDA and test-and-treat estimates.

A key lesson of this paper is that large samples are needed to have adequate statistical power to pick up a minimum detectable effect (MDE) that corresponds to what would be needed to form a policy judgment that the expected benefit of deworming is less 28
Rates, Thailand, 2007:Q1 – 2010:Q4** Source:  Thailand Socio-Economic Surveys of 2007, 2008, 2009, and 2010.  Shaded area marks period of recession.

The results of a more formal test are shown in Table 6: we regress the age-specific enrollment rates on binary variables representing each quarter, and test whether there is a difference from one year to the next. We are able to separate private from public schools. The only measurable Losers and Winners in Recession: Thailand 2008-09 21
**Figure 2.1: Left: Wind diagram for Bangladesh; Right: Climate diagrams for Dhaka: Seasonality governed by the monsoon (2000-2017).**

<!-- Start of picture text --> 25 35 400<br>30 350<br>20<br>300<br>25<br>15 250<br>20<br>200<br>10 15<br>150<br>10<br>100<br>5<br>5 50<br>0 0 0<br>Average wind speed<br>Precipitation (mm)<br>Max. and min. wind speed<br>Temperature (C)<br>Wind speed (km/h)<br>Average monthly temperature (°C) Total Monthly Precipitation (mm)<br>January February March April May June July August September October November December January February March April May June July August September October November December<br><!-- End of picture text --> _Source: authors based on ERA5 data Note: All values represent averages over the period 2000-2017._ Lightning data from the NASA Lightning Imaging Sensor (LIS).

Nor'westers – a type of Severe Local Convective Storms (SLCS) – occur in Bangladesh between April and May, when humidity and temperatures rise. They are the South Asian equivalent of Derecho events in the USA<sup>13</sup> . They cause considerable damage to assets and livelihoods as they result in short, intense, and very localized thunderstorms, combined with lightning and strong wind gusts. They are known in Bangladesh as Kalbaisakhi – which translates roughly to “evil summer”. By reviewing thousands of local newspaper reports, Yamane et al. (2010) compile a database of 2,324 SLCS events covering the years 1990 to 2005. Their data illustrates the strong seasonality of SLCS, the majority of which are concentrated in April and May (Figure