rafmacalaba/datause-encoder-data huggingface dataset:
6 The pension systems in these countries are very large, with assets exceeding 100 percent of GDP in all cases, except for Mexico. The relatively small size of assets relative to GDP in the Mexican case is due to the lower coverage ratio and the fact that the Mexican system is much younger, having started operations only in 1998. However, the mandatory nature of contributions to individual accounts implies that that private pension system will continue growing at fast rates and increase its share in the financial sector.

Three countries have a large number of funds, ranging from 111 in Denmark to 1,000 in Australia and these funds may operate more than one pension plan. Many of these are occupational funds structured as non-profit trusts or foundations that were originally created on a voluntary basis and have been operating for several decades. They include single funds and larger multi-employer or industry-wide funds. Australia and Denmark also have several for-profit commercial institutions managing pension funds – including life insurance companies in the Danish case.

**Table 1:  Main Characteristics of the Four Private Pension Systems, Dec. 2005**

||Mandate|Coverage<br>(% of labor<br>force)|Assets<br>(% GDP)|Number of<br>Funds|Legal structure of<br>pension funds|Type of<br>Plan|
|---|---|---|---|---|---|---|
|Netherlands|Quasi-<br>mandatory|90|120|700|Occupational|Mostly DB|
|Denmark|Quasi-<br>mandatory|80|124|111|Occupational<br>and open<sup>1</sup>|Mostly DC with<br>absolute return<br>guarantee (DB-like)|
|Australia|Mandatory|90|104|1,004|Occupational<br>and open<sup>2</sup>|DC|
|Mexico|Mandatory|29|8|18|Open|DC with ceiling on<br>downsiderisk(VaR)|

_Notes_ : 1) Denmark: 44 corporate funds, 30 industry-wide funds, 37 life insurance companies; 2) Australia: 681 corporate funds, 86 industry-wide funds, 194 retail funds, 43 public sector funds. The figures do not include small funds. _Sources_ : Hinz and Van Dam (2006), Andersen and Van Dam (2006), Thompson (2006), Bernstein and Chumacero (2007), Rofman and Luchetti (2006) Mexico has only 18 funds currently licensed. The difference in the number of funds is a result of the different origins and characteristics of the Mexican system. The Australian, Danish and Dutch systems have their roots in voluntary arrangements with employers. Most funds were initially established with liberal licensing/authorization rules designed to encourage participation and coverage. By contrast, the Mexican system was established as a mandatory system of open funds subject to a strict regulatory framework, including much stricter licensing rules.<sup>4</sup> Dutch pension funds manage primarily DB plans – the Netherlands has been one the few countries that has successfully resisted the move towards DC plans. The Danish system is a DC system that offers benefit guarantees and operates on a risk-sharing (or profit-sharing) basis. The guarantees introduce a core liability and the risk of insolvency of the provider. Therefore, the Danish system exhibits some of the characteristics of a defined-benefit system, although it operates with more flexible rules than pure defined-
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DaRy (DaR ~~Total debt firms financially vulnerable in indicator Y, country c time t~~ Y ct Total debt of all firms, incountryc and time t
|**[6]**<br>**ar average)**|6.631***<br>(2.334)<br>-0.007<br>(0.051)<br>0.059***<br>(0.016)<br>0.290<br>(0.272)<br>0.086**<br>(0.036)<br>0.3<br>(0.201)<br>-6.618***<br>(0.980)<br>578 / 87<br>0.405<br>0.954<br>3.494|*** significant at 1%|
|---|---|---|
|**[5]**<br>**(t+1) (3-ye**|0.852<br>(0.803)<br>0.016<br>(0.058)<br>0.063***<br>(0.018)<br>0.273<br>(0.279)<br>0.077*<br>(0.041)<br>0.189<br>(0.205)<br>-6.754***<br>(1.049)<br>513 / 83<br>0.382<br>1.064<br>3.455|significant at 5%;|
|_ker_<br>**[4]**<br>**GDPpw**|2.584<br>(1.696)<br>-4.452<br>(3.271)<br>0.160***<br>(0.027)<br>-24.143***<br>(3.232)<br>0.033***<br>(0.008)<br>0.010<br>(0.179)<br>0.064***<br>(0.024)<br>0.157<br>(0.102)<br>-1.863**<br>(0.814)<br>1509 / 87<br>0.313<br>0.962<br>4.542|sured.<br>significant at 10%; **|
|_s Domestic Product Per Wor_<br>**[2]**<br>**[3]**<br>**(t+1)**<br>**∆%**|1.207**<br>(0.514)<br>-1.1520<br>(0.897)<br>0.582<br>(1.141)<br>0.157***<br>0.159***<br>(0.027)<br>(0.027)<br>-22.260***<br>-24.102***<br>(3.306)<br>(3.220)<br>0.038***<br>0.034***<br>(0.008)<br>(0.008)<br>0.02<br>-0.003<br>(0.178)<br>(0.180)<br>0.043*<br>0.063***<br>(0.024)<br>(0.024)<br>0.14<br>0.157<br>(0.103)<br>(0.102)<br>-2.182***<br>-1.847**<br>(0.824)<br>(0.818)<br>1431 / 81<br>1509 / 87<br>0.309<br>0.311<br>1.025<br>0.962<br>4.498<br>4.542|variable_y_.<br>which the dependent variable is mea<br>st standard errors in parentheses / *|
|**Table 4**<br>_Sample of 1974-2004_<br>_Dependent Variable: Percentage of Change of the Gros_<br>**Variables**<br>**[1]**|int1. Index (t)<br>0.683**<br>(0.325)<br>int1. Index_neg (t)<br>int2. Index (t)<br>int2. Index_neg ( t)<br>_Control Variables_<br>Lagged Dep. var.<br>0.156***<br>(0.028)<br>LGDP_HP_cycle (t)<br>-22.276***<br>(3.304)<br>∆Log(ToT)<br>0.038***<br>(0.008)<br>Population growth<br>0.02<br>(0.177)<br>Financial account to GDP<br>0.042*<br>(0.024)<br>Trading partners growth<br>0.14<br>(0.103)<br>GDPpw (t)<br>-2.155***<br>(0.823)<br>Observations / Countries<br>1431 / 81<br>R-squared<br>0.308<br>Mean Dep. var.<br>1.025<br>St Dev Dep. var.<br>4.498|Note:_y_(t, t+s) corresponds to the average over the period t to t+s of the<br>Except otherwise indicated, all controls are averages for the period over<br>All regressions included country fixed effects and Time dummies / Robu|
while the Igbo are Christians—there are also some mixed religion ethnic groups, the largest of which are the Yoruba and Igala. This cultural and religious diversity is reflected in the variety of customary practices and legal traditions regulating family law with bearing on marriage, divorce and inheritance, and thus, women’s welfare generally.

The sources of law draw on three main legal systems: English common law (including statutory law), customary law, and Islamic law. The indigenous law of Nigeria is customary law, with each ethnic group traditionally having its distinctive set of norms and laws (Oba 2011). Islamic Law applies to Muslims across the country, but is more enforced in the northern states where they are more numerous. The Constitution is the supreme law of Nigeria and formally recognizes both customary and Islamic law (Hallward-Driemeier and Hasan 2013). English common law is thus the default in the absence of customary or religious law (Emery 2005).

Muslims are concentrated in the northern part of Nigeria, which is poorer and more rural than the South where the majority of Christians are found.<sup>6</sup> Home to nearly half of the poor and only one-third of the total population, the North fares worse in terms of the availability and quality of public basic social and infrastructure services (World Bank 1996). These inequalities are reflected in worse social indicators with higher infant mortality rates and lower levels of assisted births, vaccinations, and contraceptive use on the health side, and lower primary and secondary enrollment ratios and eventual schooling attainments, on the education side (NPC and ICF International 2014).

Nigeria is also a country of extraordinary ethnic diversity. The population encompasses around 374 ethnic groups among which the largest: the Hausa-Fulani (31.3% of the population), Igbo (15.1%), and Yoruba (16.1%), are geographically concentrated in the northern, southeastern, and south-western parts of the country, respectively.<sup>7</sup> The other ethnic groups each account for small shares of the total.

Marriage is nearly universal and first occurs at young ages for many women: about 30 percent of all girls between the ages of 15 and 19 have been married at least once and the share rises to an even larger 41 percent in rural areas. By 35 virtually all women have been married, while men reach that milestone around age 40. The state of widowhood is considerably more

> 6 Nigeria is administratively structured into 37 states grouped into six geopolitical zones: North Central, North East, North West, South East, South South, and South West. The distribution by zone is as follows: (12.3, 23, 50.6, 0.1, 0.7 and 13.4%), (16.3, 5.1, 4.9, 23, 27.1 and 23.6%) for Muslims and Christians, respectively.

> 7 These and the statistics below are based on the pooled 2008 and 2013 DHSs. We discuss data sources in Section 3.

6
**Table A.1. Many Published RCTs of Small Firm Interventions do not discuss Firm Death**

|Author(s)|Type of<br>Intervention|Firm Size|Country|Sample Size|Time Frame<br>(approximate)|Attrition<br>Rate|Firm<br>Death/Survival<br>is an Outcome|Death Rate in<br>Control Group|Note|
|---|---|---|---|---|---|---|---|---|---|
|Angelucci et al. (2015)|microcredit|micro|Mexico|Total: 2,912|20 months|37%|yes|n.a.|a.|
|Atkin et al. (2017)|export promotion|micro|Egypt|Total: 219<br>Control: 145|2.5 years (S1)<br>15 months (S2)|28% (S1)<br>7% (S2)|no||b.|
|Beaman et al. (2014)|other|micro|Kenya|Total: 508|n.a. / n.r.|2-3%|no||c.|
|Berge et al. (2015)|business training<br>and cash grant|micro|Tanzania|Total: 644<br>Control: 199|3 years|2.6%|no|||
|Blattman and Dercon|business training|micro|Ethiopia|Total: 643|1 year|14%|no||d.|
|(forthcoming)|and cash grant|||Control: 358||||||
|Blattman et al. (2014)|cash grants|micro|Uganda|Total: 2,677|4 years|18%|no|||
|Bruhn et al.<br>(forthcoming)|management<br>consulting|micro,<br>small and<br>medium|Mexico|Total: 432<br>Control: 282|1 year|12%|no|3.3%|e.|
|Bruhn and Zia (2013)|business training|micro|Bosnia and<br>Herzegovina|Total: 445<br>Control: 148|1 year|11%|yes|36%||
|De Andrade et al.|formalization|micro|Brazil|Total: 1,348|1 year|36.8%|yes|14-16%|f.|
|(2016)|incentives|||Control: 689||||||
|De Giorgi and Rahman|formalization|small and|Bangladesh|Total: 3,000|2 years|n.r.|no|||
|(2013)|incentives|medium||Control: 1,500||||||
|De Mel et al. (2014)|business training<br>and cash grant|micro|Sri Lanka|Total: 624<br>Control: 224|2.5 years|7.9%|yes|17%|g.|
|De Mel et al. (2013)|formalization<br>incentives|micro<br>and small|Sri Lanka|Total: 520<br>Control: 105|31 months|11%|yes|n.r.||
|De Mel et al. (2012)|cash and in-kind<br>grants|micro|Sri Lanka|Total: 387|5.25 years<br>5.75 years|10% (5.25 years)<br>8% (5.75 years)|yes|29% (males)<br>26% (females)|h.|
|De Mel et al. (2009)|cash and in-kind<br>grants|micro|Sri Lanka|Total: 387|3 years|13.8%|no|||
|De Mel et al. (2008)|cash and in-kind<br>grants|micro|Sri Lanka|Total: 408<br>Control: 280|2 years|9.6%|no|||
|Drexler et al. (2014)|business training|micro|Dominican<br>Republic|Total: 1,193<br>Control: 387|1.5 years|13%|no|||

59
**<u>Bill and tax payment.</u>** <u>Mobile money services offer customers the opportunity to pay a variety</u> of bills including school fees, tuition, utility bills, and cable television bills. Paying utility fees tends to be free because banks accrue other benefits from having the utility company as their client. It is now possible to pay the electricity bill through mobile money in conjunction with real time bank reconciliations. The service enables subscribers to avoid disconnections that are caused due to delayed payment reconciliations.  Also, the National Water and Sewerage Corporation (NWSC) is phasing out payment of water bills and in their place deploy more customer friendly tools like mobile money and over the counter payments with partnering banks. The utility company has partnered with M-Sente, the mobile money product by Uganda Telecom to enable M-sente registered clients to pay their water bills.

Warid telecom in partnership with <mark>the Uganda Revenue Agenda (URA) a</mark> nd Orient bank enables tax payers to pay the government fees using the mobile phone. The initial phase will cover express penalties and will cover the rest of payments like passport fees, customs duty, court fees etc. Tax payers need to register for the company’s Warid Pesa service and use the service for all URA payments. <mark>According to observers, this service has great potential to reduce informality and grow government revenues.</mark> In 2010, the previous Zain (later Airtel) launched a service that allows parents to pay school fees via their mobile payment platform, eliminating the long queues at the bank branches for the payment of school fees just before the beginning of each new school term.

Limited understanding of the possibilities offered by mobile money services might be preventing Ugandans from adopting mobile money at a higher speed.<sup>27</sup> According to a survey of registered users of the largest mobile money service in Uganda, 61 percent of its registered users said that m-money “is for sending and receiving money,” 28 percent said it can be used “in many ways to manage money,” 7 percent believed that m-money “can be used for storing money” and 4 percent said “it can be used for payments.”

> 27 Intermedia (2012)

18
Henson, S.J., Loader, R.J., Swinbank, A., Bredahl, M. and Lux, N. (1999). _Impact of Sanitary and Phytosanitary Measures on Developing Countries._ Department of Agricultural and Food Economics, The University of Reading.

Henson, S.J., Brouder, A-M. and Mituulah, W. (2000a). Food Safety Requirements and Food Exports from Developing Countries: The Case of Fish Exports from Kenya to the European Union. _American Journal of Agricultural Economics_ , 82 (5), 1159-1169.

Henson, S.J. and Holt, G. (2000b). Exploring Incentives for the Adoption of Food Safety Controls: the case of HACCP in the UK dairy sector. _Review of Agricultural Economics,_ <u>22</u> (2), 407-420.

Hoekstra, T.M., Asila, A., Raburu, C. and Rambiri, O. (1991). _Report on a Census of Fishing Boats and Gear in the Kenyan Waters of Lake Victoria._ FAI, Rome.

Ikiara, M. (1999). _Sustainability, Livelihoods, Production and Effort Supply in a Declining Fishery: the Case of Kenya’s Lake Victoria Fishery_ . PhD Thesis, Amsterdam.

Jaffee, S. (2003). _From Challenge to Opportunity: The Transformation of the Kenyan Fresh Vegetable Trade in the Context of Emerging Food Safety and Other Standards._ World Bank, Washington DC.

Jansen, E. (1997). _Rich Fisheries-Poor Fisherfolk: The Effects of Trade and Aid in the Lake Victoria Fisheries._ IUCN, Nairobi.

JETRO (2003). _Food Sanitation Law in Japan_ . Japan External Trade Organization, Tokyo.

Jha, V. (2002). _Strengthening Developing Countries’ Capacities to respond to Health, sanitary and Environmental Regulations._ UNCTAD, Geneva.

Landell Mills (2001). _Strengthening of Implementation Capacity in Relation to safety and Sanitary Controls of Fish and Fishery Products_ . Landell Mills, Trowbridge.

LVFO (2000). Frame Survey March 2000. Lake Victoria Fisheries Organisation, Jinja.

LVFRP (1999a). Marketing Study. Lake Victoria Fisheries Research Project, Kisumu.

LVFRP (1999b). The Survey of Lake Victoria’s Fishers. Lake Victoria Fisheries Research Project, Kisumu.

McCormick, D. and Mitullah, W.V. (2002). _Institutional Response to Global Perch Markets: The Case of Lake Victoria Fish Cluster._ Paper presented at the conference Local Agri-Food Systems: products, Enterprises and Local Dynamics, Montpellier.

Medard, M. and Wilson, D.C. (1998). Changing Economic Problems for Women in the Nile Perch Fishing Communities of Lake Victoria. _Anthropologica_ , 38, 149-172.

81
testing of the survey instrument that asking about the period during the day for the activity, rather than the number of hours, was a more accurate way of understanding how a child‟s time is allocated. These time periods use the school schedule as a reference period and ask whether a child did a specific activity before school opened, during school hours, during school lunch break, after school closed, all day, or occasionally throughout the day. We use these periods to calculate the number of hours a child engaged in child labor activities.<sup>10</sup> The specific child labor activities we focus on in this paper include: household chores such as cooking, fetching water, sweeping, and doing dishes; tending for siblings or sick members; and engaging in farm labor.

Over 70 percent of children engage in child labor activities and spend on average 5.5 hours per day on them. Sixty percent of children perform household chores, and on average, over 3 hours per day are spent on these chores. There is significant variation in the amount of time spent on chores, suggesting that while the majority of children do them, there are some that are spending an entire day doing so, while other spend a limited time. The average number of hours spent tending for siblings or sick members in the household is 0.6 hours. Twenty-six percent of children engage in this activity, and for those children doing the activity, they spend over 2 hours per day doing so. On average one hour is spent on farm labor and 30 percent of children engage in this activity. For those working on a farm, they do so for an average 3 hours per day.

# _2.2 Rainfall and ArcGIS Interpolation_

To estimate our instrumental variables strategy described in Section 3.2, we need rainfall data for each of the 75 survey villages for each year from 1992 to 2003, which corresponds with the in utero and early childhood years for the primary school-aged children in our survey. Since none

> 10 Since the school day starts at 7:30am, ends at 5:00pm, and includes a lunch break of 2.5 hours during which children return home and another 30 minute break at school, we assign the following number of hours to correspond to each time period: 2 (before school opened), 6 (during school), 2 (during school lunch break), 2 (after school closed), 10 (all day), 0.5 (occasionally). To check the robustness of the correspondence between number of hours and time periods during the day, we also estimate several alternative variations, and results are consistent.

9
At the same time the incidence of low pay is quite high, comparable<sup>tothatin higher</sup> inequality transition economies, such as Hungary.<sup>28</sup> Specifically, the bottom decile worker earns 54 percent of<sup>themedian earnings</sup> which indicates a fair amount of wage flexibility at the lower<sup>endoftheeamings</sup> distribution (Table 17). For comparison, in Slovenia the bottom<sup>decileworkerearns</sup> some 60 percent of the median, which is characteristic of<sup>amoreegalitarianwage</sup> structure. Simultaneously, over 20 percent of all wage<sup>andsalaryearnersinCroatia</sup> eam less than two-thirds of the median, which means that the incidence<sup>of lowpay is</sup> quite high.<sup>29</sup> For instance in the EU countries, where wage inequality tends to be limited, the incidence of low pay rarely exceeds 15 percent.

**Table 17 Summary of earnings** _a)_ distribution, 2001

||Mean|Bottom<br>decile|Median|Top<br>decile|P10<br>PO|P90<br>P0|Decile<br>ratio|Ginicoeff.|
|---|---|---|---|---|---|---|---|---|
||Kuna||||%||||
|Allworkers(CBS)|3397|1626|3008|5270|54.0|175.2|3.2|0.274|
|Allworkers(FINA)b|)3448|1850|3454|4943|53.6|143.1|2.7|0.206|
|_Sector_|||||||||
|Publicsector|3838|2824|3886|4661|72.7|119.9|1.7|0.117|
|Privatesector|3124|1685|2805|5103|60.1|182.0|3.0|0.240|

# Note:

P1O denotes the eamings of the bottom decile relative to the median, expressed<sup>as apercentage.</sup> The decile ratio is the ratio of the top decile to the bottom decile,<sup>i.e.P90/P10.</sup> a) Gross earnings.

b) Legal persons only; February 2002 Source: FINA and Struktura zaposlenih prema visni prosjecne isplacene neto place i po djelatnostima<sup>uozujku2001,CBS.</sup> Author's calculations.

At the other extreme, the top decile worker earns 75 percent<sup>morethanthe</sup> median worker. This represents a lower premium for high<sup>skillsthanin mostother</sup>

**28** In this sub-section the terms high and low pay have a _relative_ rather<sup>than</sup><sup>_absolute_meaning,</sup> i.e. refer to wage inequality rather than the level. This is in contrast to<sup>theprecedingsub-section,where</sup> the focus was on the absolute level of wages. To illustrate the difference<sup>between these two concepts</sup>

(of absolute and relative wages), the wages are high in Croatia relative to<sup>other transitioneconomies;at</sup> the same time there is a relatively large number of workers who are low paid<sup>comparedwith the</sup> median worker, and a relatively small number of workers who are highly paid<sup>compared with the</sup> median worker.

**29** This figure can be inflated, however, by employers underreporting<sup>wages inorderto lowerthe</sup> payment of social security contributions.

_-51 -_
55 with the woman's marital status, plus a variety of more controversial identifying variables.

Khandker (1989) has subsequently examined the returns to schooling for both men and women based also on these Peruvian LSS data. He restricts his analysis to wage earners and identifies the sample selection probit equation by the fauily's land holdings, unearned income, **as** well **as** possibly **the** individual's marital status and. the education of his or her mother and father. The return estimw"tes appear to be relatively robust to variations in this list of identifying variables includod only in the sample selection equation. For the country **as** a whole, women's returns increase when controls are introduced for sample selection, and returns are then marginally higher for women than for men at the secondary and higher schooling levels. At the primary school level in the metropolitan **area** of Lima, however, **the** returns are low, and lower for women than for mon, 2 percent compared to 5 percent. This low level of private returns to women at the primary level is perhaps related to the frequency of domestic servants in this group, preponderantly women, whose income in kind (food and lodging) is difficult to evaulate and is often omitted from survey reports of wages. The same pattern has been noted elsewhere in metropolitan Latin America (see Schultz, 1968) and has led some researchers to exclude domestic servants from samples in estimating **wage** functions (Mohan, 1986).

The 1981 Socioeconomic Survey of Thailand provides another basis to **oval-** ute the effect of **sample** selection bias on the estimates of private rates of return 4o schooling for both women and mon. In this **case** two selection correction terms are incorporated into the analysis representing **the** probability of being in the labor force and being a wage earner. These selection