rafmacalaba/data-use-mentions-extended huggingface dataset:
- Bank branches per 100,000 adults are more than 10<sup>3</sup>

- Life premium/GDP are greater than 2.0 percent or non-Life premium/GDP greater than 1.5 percent.

India and China were included in light of their large and growing middle classes and active approach.

Despite a wide diversity of approaches, common features are found in emerging markets, including the following:

- The preponderance (until recently) of single-premium investment-linked contracts as alternatives to deposits (thus leading to considerable volatility in Life Bancassurance revenue data in line with returns in equity markets)

- Bank dominance of consumer credit insurance and

- Their generally low share of non-Life markets.

Most of the countries listed either already have data privacy protection laws in place or are planning to introduce them. The Latin American and Maghreb countries have been influenced by historical links to the leading Bancassurance markets (France, Portugal, and Spain), and the EU Accession countries have been influenced by the presence of Western European insurers. The development of Asian Bancassurance has tended to be more country specific, although the global insurers have had some influence.

What non-Life business is written tends, naturally enough, to be associated with lending, mainly in relation to Motor loans and mortgages. In some of the higher income markets, Bancassurers are adopting sophisticated segmentation of their customer bases. This enables them to align better their marketing mixes (product, service level, point-of-sale environment) with income level (table 2.4). A major challenge will be the move from high-volume low-margin single-premium Life products to regular premium savings contracts.

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MULTILINGUAL CHILD ASSESSMENT nonoverlapping words of varying difficulty, with 27 Luo items, 32 Swahili items, and 34 English items. Administration ended when a child failed six of a set of eight items.

# **Expressive vocabulary**

We developed our own measure of expressive vocabulary after reviewing various expressive vocabulary tests and concluding that the stimulus words and/or pictures were not appropriate to the context (see details in **Appendix B)** . The assessment was a picture-naming task, in which children were presented with flash cards bearing a single illustrated stimulus item or object (noun) per card and were asked in the child’s preferred language, “What is this?” for each item. Children were not instructed as to which language to respond in, but responses in any language were accepted. We did not provide further instruction because code-switching during conversation is common in this area, and very young children may not be aware which language they are actually speaking for a given word. Thus, a child could respond to each item in the 20item test in English, Luo, or Swahili to score a pass for expressing the word verbally. Administration ended with three consecutive fails.

# **Other child-level assessments**

The Malawi Developmental Assessment Tool (MDAT) was created and validated for use in rural Malawi with children 1–84 months of age (Gladstone et al., 2010). It includes four 34item subscales (fine motor/perception, language/hearing, gross motor, social-personal), with many items adapted from existing Western tests (see details of our adaptation in **Appendix C** ). The MDAT is currently being used in various countries, including Mali, Sierra Leone, Rwanda, Burkina Faso, and Zimbabwe (M. Gladstone, personal communication, June 24, 2016). The western Kenya adaptation was initiated by the first, second, and fifth authors (HK, PK, and LCHF) for the Kenya Life Panel Survey (e.g.
03 to 2.4 in 2011-13, based on the sample registration system (SRS). In urban areas, the TFR was below replacement at 1.9 in 2011-13 (Registrar General of India, 2014). As a result, the number of children per household has fallen dramatically. The size of the average urban household in the National Sample Survey (NSS) during the period 2004-2011 declined from 4.3 to 4, and only a little over 26 percent of households had at least one child of pre-school age (under 6 years old) in 2011. Educational attainment has also increased across the board, despite rising concerns about the quality of education.

The Indian conundrum of low female labor force participation despite the existence of what are considered enabling factors, has garnered considerable attention among scholars and policy makers. Several studies and reportage have sought to explain these peculiar patterns. Some discussion focuses on the possible under-measurement of women’s work (Kapsos et al. 2014; IAMR and ILO 2013; Sudarshan and Bhattacharya 2009), while another set of explanations points to the fact that more women are now enrolled in educational institutions, which accounts for their unavailability for market work (Himanshu 2011; Rangarajan et al. 2011). However, enrollment in higher education does not explain low rates of employment for those who have completed schooling (e.g. women aged 25 and over) (Mahapatro 2013). Still other explanations point to an “income effect,” where women withdraw from the labor market as household income rises, especially in a culture where males are regarded as the main breadwinners (Klasen and Pieters 2015). The so-called U-shape where female labor force participation declines initially with economic development, but then flattens and rises again, reflecting structural economic shifts has also been implicated in explaining the Indian conundrum (Goldin 1994). Yet it is not clear at what point of rising incomes should the “U” veer upwards, as it has not done so for India as yet (Lahoti and
production of generic goods to avoid such investments. Such economies cannot rise on the valuechain of exports (Levchenko 2007, Amirapu 2021). Because of the relation with the ladder of value enhancement, foreign direct investment is positively correlated with the efficiency of legal institutions, which in turn is linked to higher economic growth (Sabir et al., 2019, Bénassy-Quéré et al., 2007).

Survey evidence from Senegal shows that firms are willing to pay higher legal fees to achieve faster delivery of justice, suggesting positive benefits of judicial reform (Kondylis and Stein, 2022). Several studies have shown a link between entrepreneurship rates and the efficiency of the judicial system, suggesting that an efficient judiciary promotes entrepreneurial activity (Ippoliti et al., 2015, Ardagna and Lusardi, 2009).

Active case management has been consistently highlighted as a necessary tool in the pursuit of court efficiency. The Indian judicial system is plagued by especially high disposition times across all levels. Gupta and Bolia (2020) use simple measures of judicial resources, namely, number of judges and staff members as inputs, and two outputs, number of civil and criminal cases disposed. The results identify specific courts that are efficient in disposing cases, especially courts that use active case management.

A study using data on disposition times in Italy shows that three policies can make a significant contribution to the efficiency of the system: active case management, break-ups of large courts of justice into smaller ones to exploit economies of scale and use of offsite technologies. These three measures reduce the disposition time by 30% (Peyrache and Zago 2020). Another study on Italy finds that the causal effects of business uncertainty from court delays on company turnover, hiring and dismissals are of significant negative direction, and of sizable magnitude (Bamieh et al, forthcoming). Other work using Italian court data studies the effects of court inefficiency on public work performance. Where courts are inefficient, proxied by disposition times, Coviello et al (2018) find that public works are delivered
061)_|
|Loan terms and conditions|||
|VF borrows to on-lend to members|0.187*|0.157|
||_(0.097)_|_(0.117)_|
|Memo items|||
|Number of observations<br>|808|661|
|R<sup>2</sup>|0.088|0.169|

Source: Village Fund Survey 2010, and SES 2009. Robust standard errors in parentheses. Stepwise regression uses p=0.2 cutoff for dropping variables. Right-hand column includes provincial dummy variables (not shown).

* p<0.05, ** p<0.01, *** p<0.001.

38
The role of finance may have been magnified since borrowing may become harder during times of stress. Recent evidence suggests that the trade-finance nexus seems to be one explanation for the trade contractions during both the Japanese slump and the recent U.S. financial crisis. Amiti and Weinstein (2011) show that during the Japanese crisis of the late 1990s and early 2000s, the lack of financing accounted for nearly one-third of the plunge in exports. Similarly, using monthly U.S. import data, Chor and Manova (2012) find that countries with tighter credit availability during the crisis exported less to the United States. Moreover, exports to the United States contracted more in sectors that are more heavily dependent on external financing. International evidence is in line with the findings from the U.S. Paravisini, Rappoport, Schnabl, and Wolfenzon (2015) match Peruvian customs and firm-level bank credit data to accurately measure the exogenous credit shocks, and estimate that a 10% contraction in credit supply from poorly performing banks translates into a 2.3% fall in the export volumes.

There is limited understanding of the channels through which credit constraints may affect or be affected by export status. Several studies based on Melitz (2003) show that more productive firms export as they can afford the fixed costs of exporting. But less attention has been dedicated to the nature of the fixed costs. Indeed many studies assume perfect capital markets and rule out the existence of credit to finance either fixed or variable costs. Two noteworthy exceptions are Chaney (2016) and Manova (2013) that introduce firm-level liquidity into a trade model of heterogeneous firms and link country-specific financial development to export status. The logic underlying these models is that in the presence of binding credit constraints, a high-productivity firm may still be unable to finance export costs and operate internationally, but there may be low-productivity firms that are financially unconstrained and able to export. The relationship between productivity and access to credit may alter the sharp prediction of the standard heterogeneous firms model so that
# Intra-national Trade Costs in Low- and Middle-Income Countries<sup>∗</sup>

Bernardo D ́ıaz de Astarloa<sup>†</sup> Nino Pkhikidze<sup>‡</sup>

**_Keywords:_** Trade costs, Price differential methodology, Travel distance, Kenya, Madagascar, Nigeria, Rwanda, Tanzania, Georgia.

**_JEL classi ication:_** R12, F1, O1, D02.

> ∗This paper was prepared as background research for the World Bank’s Shrinking Economic Distance Flagship Report. Ignacio Caro Sol ́ıs provided superb research assistance. For help and assistance in accessing price data, we thank the World Bank’s country teams and the national statistics offices of the research countries. We have benefited greatly from discussions with Matias Herrera Dappe, Roman Zarate, Theophile Bougna, Alejandro Molnar, Mathilde Lebrand, Aiga Stokenberga, and the participants of World Bank’s Workshop on Shrinking Economic Distance. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors.

> †Inter-disciplinary Institute of Political Economy, University of Buenos Aires. Email: `bernardo.diazastarloa@economicas.uba.ar` .

> ‡World Bank. Email: `npkhikidze@worldbank.org` .
2019), the program was highly successful at delivering the components, with 97% of the treatment households reporting being aware of the TUP program, and of those, the majority (99.5%), reporting having received program assets or services, compared to 3% in the control group. 96% of treatment households and 1.5% of control reported receiving livestock assets.

## **4.3.3 Attrition**

The lottery assigned 1,219 households into treatment (491) and control (728). Of these, 1,173 (96%) were surveyed at baseline.<sup>17</sup> The endline phone survey was successfully completed among 839 households, which implies an attrition of 31% with respect to baseline, and of 27% with respect to midline. While 17The difference is because the implementer conducted an ultra-poor re-verification for a sample of households when the survey firm already had started the baseline. For households located in villages where the baseline survey firm had already conducted data collection, the baseline was missed because they could not go back.

16
Table 1. Common Dimensions and Indicators of Job Quality

|_Dimension_|_Areas_|_Indicators_|
|---|---|---|
|Earnings|Wage income|• Wage income above a threshold*|
|Job benefits|Social protection|• Job registered with social security administration*<br>• Job provides health insurance*<br>• Job provides pension*<br>• Jobprovides eligibilityfor unemployment insurance*|
||Employment benefits|• Paid annual leave*<br>• Paid sick leave*<br>• Paidparental leave*|
|Job stability|Formal employment|• Employment is bound by written contract*<br>• Employment is permanent, not temporary*<br>• Employer is formal entity*|
||Tenure|• Employed in current job more than a certain number<br>ofyears*|
||Work-life balance|• Excessive working hours*<br>• Work intensity<br>• Unsocial hours / shift work<br>• Involuntary part time<br>• Would like to work more*<br>• Has a secondpaidjob*|
|Working<br>conditions|Physical health and safety|• Dangerous work environments (noise, vibrations,<br>drastic temperatures, and so on)<br>• Manual labor(moving heavy loads, painful or tiring<br>positions)<br>• Accidents a work|
||Job satisfaction|• Skills Match<br>• Work autonomy<br>• On-the-job learning and training<br>• Good relationships with colleagues|

* These indicators are available in most household and labor force surveys across regions of the world and are used in the proposed job quality measure.

The earnings dimension measures whether a job pays sufficiently to lift a family out of poverty and into the lower-middle class. Labor earnings are the main source of material well-being among most individuals, especially in developing countries. This dimension not only captures whether a job generates
magnitude of these effects varies by the type and number of measures used. In some cases, studies show effects that are comparable with the estimates found for cognitive skills (Bowles, Gintis, and Osborne, 2001; Heckman, Stixrud, and Urzua, 2006; Heineck and Anger, 2010; Mueller and Plug, 2006; Nyhus, and Pons, 2005).

Many studies have used the _Big Five personality traits_ —openness, conscientiousness, extraversion, agreeableness, and neuroticism (Goldberg, 1990) as proxies for noncognitive skills (Heineck and Anger, 2010; Mueller and Plug, 2006). Mueller and Plug (2006) used data from the Wisconsin Longitudinal Study and examined the effect of these five personality traits on earnings separately for men and women. They found that controlling for IQ, occupation, and a range of covariates, openness, agreeableness, and neuroticism had small albeit significant effects on earnings among men. In contrast, openness and conscientiousness significantly predicted earnings among women. Heineck and Anger (2010) used the Big Five personality measures to estimate the impact of noncognitive skills on labor market outcomes in Germany. In addition to the Big Five, they added measures of _locus of control_ and _reciprocity_<sup>_7_</sup> to their analytical model. Their results indicated that after controlling for cognitive abilities and several socio-demographic and job-related characteristics, personality was a significant predictor of earnings. Other research has also explored noncognitve skills outside of the Big Five. Heckman, Stixrud, and Urzua (2006) used the NLSY 1979 data, which included measures of individuals’ self-worth and individuals’ perceived degree of control over their lives, to determine the effect of these measures on labor market outcomes. They found small but significant effects (less than 1 percent) for these measures of noncognitive skills in predicting wages. Their findings suggest that the estimated effects of noncognitive skills on wages are as strong as those estimated for cognitive skills when one controls for schooling and family characteristics.

As technology changes, and its use continues
(s). We find that discriminatory laws increase the likelihood that firms with female participation in ownership will start an informal business; as anticipated, the relationship does not hold for enterprises that are solely owned by men. The global finding appears to be driven by the association between gendered laws and informality in three regions; specifically, Sub-Saharan Africa, the Middle East and North Africa and South Asia. When looking at the relationship between starting informally and subsequent performance, we find that, in general, there is a penalty associated with starting informally, which exists both for firms with female participation in ownership and for firms fully owned by men.

There are a number of ways that unequal laws as captured by the WBL indicators can influence a woman’s decision to engage in the formal or informal sector when undertaking a new entrepreneurial activity. For one, barriers in accessing finance due to direct discrimination or indirect restrictions in accessing assets may prevent women from having sufficient resources to start a business at the scale needed for the formal sector. Any such legal restrictions may force women to opt for small scale activities better suited in the informal sector. More draconian restrictions on women’s mobility may force female entrepreneurs into 3
economic growth. These results show negative effects in 2001-2015, whereas the positive effects found in Choi and Yi (2009) correspond to 1991-2000. Maurseth (2018) suggests that the greatest benefits of ICT adoption could lie a decade or more in the past. Similarly, Edquist et al. (2018) find that a 10 percent increase in mobile broadband (MBB) network adoption (measured as the percentage of total connections) causes, on average, a 0.8 percent increase in GDP but with a decreasing impact over time (disappearing 6 years after introduction), and it is smaller in magnitude in OECD countries.

More recently, studies have tried to address the question of whether there are additional economic impacts with the adoption of newer mobile technologies. Bahia et. al (2019) investigate the impact of the rollout of mobile broadband technologies on GDP growth from 2000 to 2017 across more than 160 countries. The period under analysis covers the deployment of 2G technology until the roll-out of 4G. The authors find that, in general, a 10 percent increase in the adoption of (any) mobile technology is associated with an increase in GDP between 0.5 and 1.2 percent. This impact is 15 percent higher when connections are upgraded from 2G to 3G, and 25 percent higher when transitioning from 2G to 4G. The study also notes that the impacts are larger in countries with high education levels, suggesting a relationship between human capital and the potential gains of ICT adoption. Concerns about endogeneity are addressed using structural equations models, dynamic panel data, and instrumental variables. Haftu et al. (2019) also find that the expansion of mobile phone subscribers in 40 Sub-Saharan African countries had a significant positive causal effect on increases in the region’s per capita GDP reported between 2006 and 2015. Explicitly, a 10 percent increase in mobile phone penetration in the region increases by 1.2 percent the GDP per capita. Contrary to these results, the authors find that internet penetration has not contributed to
services. The findings are based on a new and purpose-specific set of detailed enterprise-level surveys of both upstream logistics service providers and downstream intensive users of these business services, designed to allow econometric analysis of upstream-downstream linkage issues. In particular, the empirical analysis explores a particular but significant element of the debate of whether infrastructure services have a strong impact on economic development: what is the impact of innovative road freight services on downstream business users. The analysis then explores the extent to which the beneficial provision of innovative road freight services is associated with competition-related pressure.

The paper’s main findings are: (1) there are substantial downstream benefits from innovations in road freight services, both dampening cost increases and raising sales revenues of business users, and (2) increased intensity of competition in road freight services is significantly associated with the provision of innovative road freight services. Direct feedback from user enterprise managers indicates that costs for the median user were lowered by between 5 and 10% as a result of road freight logistics and sales were increased by between 10 and 15%. Regression results support the thrust of these direct survey responses by managers: there is a statistically significant negative association in the data between the use of logistics consultant services and cost increases, and a significant positive association between the use of JIT logistics services and sales revenue increases. Finally, there is a statistically significant positive association between increased competition in road freight services and the provision of innovative JIT logistics services.

The paper’s findings support both the claim that infrastructure services have a strong positive effect on economic development, and the policy claim that easing any remaining barriers to competition in upstream business services should be a priority. The paper’s findings, coupled with further research results along similar lines emphasizing linkages between infrastructure provision and downstream business users, would provide a strong case 18
of hosting refugees in Uganda on material welfare, measured by the consumption per adult equivalent. Our main outcome variable differs from studies such as Alix-Garcia and Saah (2009), Alix-Garcia et al. (2012), and Loschmann et al. (2019), which focus on market prices, host employment and household assets. Alix-Garcia et al. (2018) is one exception since they use cross-sectional data on consumption to validate their results based on night light indexes. Other studies on SSA using longitudinal data on consumption include Maystadt and Verwimp (2014), Ruiz and Vargas-Silva (2017), and Maystadt and Duranton (2018) on the Kagera region of Tanzania; and Alloush et al. (2017) on the Congolese refugees in Rwanda. However, all these studies investigate the economic impacts of refugees living in camp settings.

Uganda is an interesting case study. According to the unique Ugandan refugee policy, refugees are not settled in camps but rather live in settlements. According to Betts et al. (2017), Betts et 2
the World Governance Indicators (WGI) database, produced by the World Bank annually since 1996 for over 200 countries (Kaufmann et al. 2010). This indicator ranges from –2.5 (lowest) to 2.5 (highest).

We control for a country’s secondary enrollment rates and GDP per capita (in constant 2011 purchasing power parity dollars) using data from the World Development Indicators database (World Bank 2020a) and information from other sources. We use the economic complexity index at the MIT Lab and Harvard University (Hausman and Hidalgo 2012). We include the country fragility index produced by the Center for Systemic Peace in the State Fragility Index and Matrix (2018) data set (Marshall and Cole 2018). It ranges from 0 to 24, with higher values indicating greater state fragility. Table 1 displays the descriptive statistics for our main variables.

12