rafmacalaba/datause-encoder-data huggingface dataset:
records included expenses of the business (36 percent), income after expenses (34 percent), number of customers (31 percent), and debts or debtors (31 percent). For those businesses who offered credit to their customers, 71 percent kept a written record of owed payments.

Interestingly, 31 percent of small business owners said they relied solely on themselves for business information, with the most common other responses being family members, spouses, and friends. Relatively few cited other business owners or support organizations, and very few belonged to any business networking groups. Indeed, 75 percent of business owners were unaware of any organizations that gave support and advice to small business owners. In contrast, the owners of larger enterprises were more likely to seek support from such organizations, and have sophisticated business networks.

# **_Interest in financial education, however, appears to be widespread_**

The FinsScope surveys give cause for optimism with regard to the take-up of financial education programs in Sub-Saharan Africa, in spite (or because) of the low levels of financial literacy. For instance, in Tanzania, most people surveyed (80-85 percent) were interested in learning more about interest rates, savings, loans, insurance, and a range of other topics, suggesting a keen interest in financial education. The level of desired financial knowledge is also high in Nigeria. In the baseline survey of South African mineworkers described in Cole et al. (2010), about 90 percent of respondents felt they would benefit from a financial education course.

In Malawi, the majority of adults are interested in learning more about how credit and interest rates work, how to save and keep money safe, how to manage budget, and how to obtain property and life insurance. A near majority are also interested in learning about technologyrelated financial matters, such as transferring airtime on cell phones, using cell phones for banking, using ATMs to transfer or withdraw money, or using the internet for banking. Importantly, the majority of Malawians are also interested in learning how to start a business, suggesting that business training programs might also be successfully targeted towards potential entrepreneurs as well.

On the other hand, as the discussion of the program evaluations in the next section makes clear, both financial literacy and business training programs frequently struggle with attracting sufficient take-up. A professed interest in financial education may not be enough to ensure 21
**Figure 3: Candidate Members of the EU (Bulgaria, Romania, and Turkey)**

<!-- Start of picture text --> Port efficiency<br>1<br>0,5<br>IT infrastructure 0 Customs regimes<br>Regulatory policy<br>EU15 Bulgaria Romania Turkey<br><!-- End of picture text -->

# **Benchmarking the Relationship between Economic Development and Trade Facilitation**

The new members of the EU as a whole have exhibited rapid economic growth in the last several years despite the relatively weak performance of Western Europe and the world economy. Among the EU8, real GDP growth was approximately 2.5 percent in 2001 and 2002, and over 3 percent in 2003 (World Bank, 2004). Along with income convergence (though a large gap still exists), the EU8 have also made substantial progress in other fields such as in reduction in inflation.

9
same as the estimate over the period between baseline and follow-up.

These results show that some youth decided to forgo undertaking traditional apprenticeship to participate in formal apprenticeship, again pointing to substantial windfall effects. Overall, 54.4 percent of youth in the treatment group are in apprenticeship at follow-up, compared to 17.9 percent of youth in the control group. Most youth in the control group are in traditional apprenticeship (16.1 percent out of 17.9 percent), while most youth in the treatment group are in formal apprenticeship (50.8 percent out of 54.4 percent). The fact that youth in the control group were able to find traditional apprenticeship positions by themselves through the private market, and that some formal apprentices substituted out of traditional positions, thus creates a windfall effect that mitigates the net program impacts on the share of youth in apprenticeship.<sup>27</sup>

# **3.2 Intake of Apprentices and Substitution Effects in Firms**

We now turn to the other core research question of whether the program induced indirect employment effects among firms. The analysis is based on a survey module asking employers to list all apprentices who have worked in the firm over the course of the experiment, including those who left the firm since the randomization. We can thus measure flows of apprentices in and out of firms between the start of the experiment and the follow-up survey. We can also distinguish between formal and traditional apprentices. Table 2 (upper panel) documents the impact of the program on the flow of apprentices into firms since the date of the randomization. The program led to an increase in the total number of apprentices that entered by 1.08 new apprentice per firm over the course of the experiment. Yet the total number of youth who entered formal apprenticeship in these firms increased by 1.398. As such, the program induces a significant substitution effect: fewer traditional apprentices were hired as additional formal apprentices entered firms. Substitution effects were of moderate magnitude, however, with (1.398-1.08)/1.398 = 0.227 informal apprentice substituted per formal apprentice placed.

The net increase in formal apprentices in treatment firms can be contrasted with the number of apprenticeship positions offered by these firms. On average, firms offered 2.51

> 27Additional results are presented in Table A7, which documents the time evolution of participation in apprenticeship using information from a retrospective calendar of occupations covering the four quarters before the follow-up survey.

19
The decomposition analysis based on Gini and CI is not as neat as the decomposition of GE(0) or _V_<sup>_T_</sup> because of the existence of _GIR_ . The definition of within-group is somewhat _ad hoc_ because splitting one commune into two communes with the same distribution of the FGT measure will reduce the within-group component and increase the residual. Yet the CI is suitable for examining the magnitude of the between-group inequality and has some unique attractions because of its direct relation to the potential gains from geographic targeting. While we have seen that the share of between-group inequality is not very large, it has not been clear whether geographic targeting can be still effective. We now try to answer this question.

# **6.3 Concentration curve and geographic targeting**

Let us now interpret the concentration curve in the context of geographic targeting. Suppose that we want to reduce the total FGT measure by the proportion OG in Figure 8. Because everyone is malnourished on the portion OJ in the individual-level concentration curve, we need to bring the proportion OD of the total population out of malnourishment. Hence, the vertical axis can be interpreted as the rate of reduction in FGT, and the horizontal axis can be interpreted as the proportion of the population targeted.

In this setup, we assume that those who receive assistance are completely brought out of malnourishment. If the _per capita_ cost of assistance is fixed and normalized to the reciprocal of the total population, the horizontal axis also represents the cost of FGT reduction. Fixed _per capita_ cost may be a reasonable approximation when the child nutrition program involves direct aid in fixed amount in a relatively large scale. Distribution of micronutrients may fall in this category. We shall relax this assumption in the subsequent discussion.

Suppose now that the FGT parameter is greater than zero so that the concentration curve looks like in Figure 9(a). In this figure, OE is the proportion of total malnourished children to the total population ( _i.e. P_<sup>0</sup> ). The dashed line OKB is the commune-level concentration 28
|DJ HRITF Health AF|Emre Ozaltin|
|---|---|
|First Macroeconomic Stabilityand Fiscal Resilience DPO|Hans Anand Beck|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|StrengtheningPrimaryHealth Care for Results|Peter Okwero|
|ElectricityTransmission and Reform Project|Sunil W. Mathrani|
|ElectricityTransmission and Reform Project|Sunil W. Mathrani|
|ElectricityTransmission and Reform Project|Sunil W. Mathrani|
|ElectricityTransmission and Reform Project|Sunil W. Mathrani|
|ElectricityTransmission and Reform Project|Sunil W. Mathrani|
|ElectricityTransmission and Reform Project|Sunil W. Mathrani|
|ElectricityTransmission and Reform Project|Sunil W. Mathrani|
|Vietnam-Partnershipfor Market Readiness|Thu Thi Le Nguyen|
|Vietnam-Partnershipfor Market Readiness|Thu Thi Le Nguyen|
|Vietnam-Partnershipfor Market Readiness|Thu Thi Le Nguyen|
|Vietnam-Partnershipfor Market Readiness|Thu Thi Le Nguyen|
|Vietnam-Partnershipfor Market Readiness|Thu Thi Le Nguyen|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Health System Strengtheningand Support Project|Ahmet Levent Yener|
|Carbon Asset Development - Methane Recoveryfrom Waste Mgm|t Katelijn Van den Berg|
|Carbon Asset Development - Methane Recoveryfrom Waste Mgm|t Katelijn Van den Berg|
|Carbon Asset Development - Methane Recoveryfrom Waste Mgm|t Katelijn Van den Berg|
|Carbon Asset Development - Methane Recoveryfrom Waste Mgm|t Katelijn Van den Berg|
|Carbon Asset Development - Methane Recoveryfrom Waste Mgm|t Katelijn Van den Berg|
|Guatemala EITI Post-Compliance I|Susana Moreira|
|Tanzania Education and Skills for Productive Jobs Program(ESPJ)|Xiaoyan Liang|
|Tanzania Education and Skills for Productive Jobs Program(ESPJ)|Xiaoyan Liang|
|Tanzania Education and Skills for Productive Jobs Program(ESPJ)|Xiaoyan Liang|
|Tanzania Education and Skills for Productive Jobs Program(ESPJ)|Xiaoyan Liang|
|Tanzania Education and Skills for Productive Jobs Program(ESPJ)|Xiaoyan Liang|
|Tanzania Education and Skills for Productive Jobs Program(ESPJ)|Xiaoyan Liang|
|Tanzania Education and Skills for Productive Jobs Program(ESPJ)|Xiaoyan Liang|
tasks, as skill-biased technology substitutes for routine work, following the work presented in Acemoglu and Autor (2011). The authors propose a two-factor model where high-skilled and low-skilled jobs are imperfect substitutes and technology complements both types of workers.<sup>6</sup> In their framework, “routine-biased technological change,” also known as the routinization hypothesis first introduced by Autor, Levy, and Murnane (2003), is a main driver of job polarization.<sup>7</sup> The theory predicts that computers substitute for routine tasks and complement non-routine tasks. Therefore, the process of automation reduces the relative demand for routine tasks and raises the relative demand for non-routine tasks, contributing to job polarization by reducing employment opportunities in occupations that require routine tasks.

Therefore, though digital technologies can increase economic output, such technological change may leave some workers worse off (Brynjolfsson and McAfee 2011). Goos, Manning, and Salomons (2009) find evidence for such a relative decrease in routine tasks across many European Union countries. Böckerman, et al. (2016) also test the routinization hypothesis using data from Finland and conclude that the adoption of computers in the workplace changes the demand for tasks within the firm toward non-routine skills. Akerman, et al. (2015) find suggestive evidence that broadband internet adoption in Norway complements skilled workers in executing non-routine tasks and substitutes for unskilled workers performing routine tasks, consistent with the routinization hypothesis.

Research related to the routinization hypothesis in the developing world is scarce. Messina, et al. (2015) analyze the task content of jobs in Bolivia, Chile, Colombia, El Salvador, and

> 6 The authors argue that, in order to have a clear view about the effects of technical change on the labor market, it is important to propose a continuum of tasks. For this reason, the authors make a distinction between tasks and skills. Under this model, skill refers to the worker’s capability for performing various tasks. Workers with a given skill level can change their set of tasks in order to respond to changes in labor market conditions and technology.

> 7 Like our work that follows, the authors classify tasks into two main groups: routine tasks and non-routine tasks. Routine tasks are rule-based activities that, once codifed, can be executed by a machine. Non-routine tasks either require intuition and problem-solving skills for the more abstract, cognitive, non-routine tasks, or situational adaptability and in-person interactions for the more manual, non-routine tasks.

8
<!-- Start of picture text --> Figure 5: Expenditures on Innovative Property (% of GDP)<br>1.35%<br>1.20%<br>1.05%<br>0.90%<br>0.75%<br>0.60%<br>0.45%<br>0.30%<br>0.15%<br>0.00%<br>2000 2002 2004 2006 2008<br>Science and enginnering R&D Mineral exploration<br>Copyright and license costs New product development costs in the financial industry<br>New architectural and engineering designs R&D in social sciences and humanities<br><!-- End of picture text --> Nonetheless, it is striking that even if we assume that Brazil‘s financial services industries spend only half as much as their US counterpart on product development (that is, only 10 percent of costs), total Brazilian spending on new financial products would still be as high as expenditure on R&D across all industries. Further, it is unlikely that we are underestimating R&D given that our data source for R&D expenditures, the PINTEC surveys, are comparable to the innovation surveys used to estimate R&D expenditures in the US and EU. Thus, compared to those advanced economies, R&D in the traditional sense –conducted largely by manufacturing firms – is a smaller component of innovation-related spending in Brazil. For instance, even though manufacturing has a smaller share in GVA in the US<sup>19</sup> (13 percent for US versus 17 percent for Brazil in 2008), total business spending on R&D in the US is considerably larger than that on new financial product development (CHS 2005).

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

> 19 Source: World Development Indicators.

21
<!-- Start of picture text --> Attrited in 09<br>35<br>Original sample Supplementary sample<br>(05-07 surveyed)<br>348 Re-surveyed in 09<br>313<br>Re-surveyed in 09<br>Additional households 244<br>(added in 07 survey)<br>389<br>Attrited in 09<br>145<br><!-- End of picture text -->
6 and girls, or, less commonly, the birth-order of the first girl, and the number of children. Although such evidence is not an indication of conditionality of size on the proportion of girls, it is hard to think of causal mechanisms emanating from size. Therefore, in the _absence_ of the technology of pre-selection, such evidence would provide some idea about the presence of gender bias. However, pro-boy adult preferences do not always result in additional births because the fertility-stopping rule is unlikely to be homogenous across couples. For some couples, the disadvantage of an additional female birth may outweigh the benefits of an additional male birth. Such couples are likely to stop at a lower parity, even though that decision would be based on son preference<sup>6</sup> , see Clark (2000). Note, however, that such an outcome is also consistent with daughter preference. Therefore, as pointed out by Leung (1991), the correlations evidence can indicate the presence of child gender bias, but _not_ its direction; a sensible approach for obtaining the evidence for the latter would be through an examination of household internal allocation _conditional_ on gender demographics. This provides the motivation for the test of the child number hypothesis of gender bias by the model of adult goods consumption adopted in this study. Based on this, the child gender demographic groups below are, therefore, defined over the _number_ of children, not their age.

Provided one takes into account these issues, the Rothbarth model remains rather attractive if the focus of analysis is on child welfare or _inequality among children_ . The model is well understood, and there is broad consensus on its effectiveness for estimation of child cost, e.g. Gronau (1988), a cogent critique of equivalence scales models, regards it as ‘the only’ theoretically consistent model among them. Indeed, the case for its application to child gender bias is even stronger since this would not involve obtaining estimates from equalizing the adult goods expenditure of the base and selected families, which is believed to result in the underestimation of the child cost scales, Gorman (1979). This will not be an issue if one is solely concerned with the differential expenditure effects of boys as compared to girls. Finally, since the model’s predictions can be tested on a single cross-section budget survey, it has a relatively modest data requirement. These features compare favorably with, for instance, the very demanding requirements of

> <sup>6</sup> Suppose a couple with two girls and no boy most prefers to have two boys and one girl. The couple might regard (an approximate) 50% risk of a third girl sufficiently high to stop having more children.
Kendall, J. (2008), Local Financial Development and Growth, _World Bank Policy Research Working Paper No. 4838_ La Porta, R., Lopez-de-Silanes, F., Shleifer, A. and Vishny, R. (1998), Law and Finance, _Journal of Political Economy_ , Vol. 106(6), pp. 1113-1155, December.

Mian, A. (2006), Distance constraints: The limits of foreign lending in poor economies, _Journal of Finance_ , Vol. 61(3), pp. 1465-1505, June.

Petersen, M. and Rajan, R. (1995), The effect of credit market competition on lending relationships, _Quarterly Journal of Economics_ Vol. 110, pp. 407–443.

Rousseau, P.L. and P. Wachtel (2001), Inflation, Financial Development and Growth, _Economic Theory, Dynamics and Markets: Essays in the Honor of Ryuzo Sato_ , Deventer, Kluwer.

Rousseau, P.L. and Wachtel, P. (2002), Inflation thresholds and the finance–growth nexus, _Journal of International Money and Finance_ , Vol. 21(6), pp. 777-793, November _System of National Accounts_ (SNA, 1993) Tejerina, L. and Westley, G. (2007), Financial Services for the Poor: Household Survey Sources and Gaps in Borrowing and Saving, _Sustainable Development Department Technical Papers Series_ , Washington D.C. Inter-American Development Bank Tornell, A. and Westermann F. (2003), Credit Market Imperfections in middle income countries, _NBER Working Paper 9737_ World Bank (2008a), _Banking the Poor: Measuring Banking Access in 54 Economies_ World Bank (2008b), _Payment Systems Worldwide: a Snapshot. Outcomes of the Global Payment Systems Survey 2008_ World Bank (2009), _Doing Business_ World Council of Credit Unions (2008), http://www.woccu.org/publications/statreport 39
and administrative support jobs is below $3 per hour, the contracts being outsourced to India represent relatively skilled work that involves programming and technical skills.

Thus, the descriptive data suggest a special role for diaspora connections in sending work to India. The next sections more carefully quantify this role when taking into account potential confounding factors (e.g., the types of projects being outsourced), finding that this special role persists. But we also should not lose sight of the absolute quantity of the shares. Ethnic Indians in the United States account for about 5% of the U.S.’s outsourced work to India. The average across the top 20 countries is 7%, falling to 3% when excluding the UAE. While ethnic Indians are more likely to send work to India, the rise of India to be the top worker source on oDesk also appears to have much broader roots than diaspora connections.

The unpublished appendix provides additional descriptive statistics. The top company contacts that send work to India display significant heterogeneity in terms of their geographic location and the overall degree to which they rely on India for outsourcing work. These company lists also highlight that, while much of the diaspora’s effect comes through the small actions of many individuals, the actions of a few can have an enormous impact. In particular, there is one company contact in the UAE that accounted for 906 of the UAE’s 989 contracts to India. This outlier is an ethnic Indian entrepreneur who uses oDesk for placing and managing outsourcing work, much of which is sent to India. Studies of diaspora networks often speculate about the concentrated importance of single individuals (e.g., Kuznetsov 2009), and oDesk provides some of the first quantifiable evidence of this concentration. This individual accounts for 7.7 times more contracts being sent to India than the next highest company contact and 2.4 times the volume from the Netherlands, the sixth-ranked country in Table 1.

# **4. Persistence in Outsourcing Patterns**

Our analysis of diaspora connections on oDesk involves three steps. This section begins by describing the persistence in the geographic placement of contracts by company contacts. This persistence emphasizes the important role of initial contracts, which we analyze in greater detail in Section 5. Section 6 then considers wage and performance outcomes.

Table 2 describes the key path dependency that company contacts display in the way they engage with India on oDesk. The sample includes all first and second contracts formed by 11