rafmacalaba/datause-encoder-data huggingface dataset:
practice then, almost all micro and small enterprises are informal to some extent. The creation of _Fundempresa_ in 2002 does not seem well-known to firms in 2007. Only 10 percent of firms in our sample say they know what _Fundempresa_ is and what its purpose is, and only 18 firms are registered with it.

Therefore for most firms in our sample, formality consists of first registering for a municipal license, and then registering for a tax identification number (NIT). 57 percent of firms in our sample have a municipal license, and 29 percent a NIT. Only 14 of the 134 firms with a NIT do not have a municipal license. Recent years have seen improvements in the time taken to obtain municipal licenses in some municipalities. Coupled with greater interaction with municipal officials, our focus group surveys revealed that most firms seemed aware of the process necessary to get a municipal license and felt enforcement was stronger at the municipal level. In contrast, no such efforts have been made to simplify the process of obtaining a tax identification number, and, as we will show, many firms do not have good knowledge of this process. As a result, we believe that most firms failing to have a municipal license do not have one as a result of informed choice, whereas some firms without tax identification numbers do not have one as a result of imperfect information. The result is that we will be able to identify the impact of a tax identification number, but not that of a municipal license.

Our survey firm conducted 12 focus group interviews of firms across different sectors and size groups (Encuestas y Estudios, 2007). Firms in the focus groups were asked what they themselves understood formality to be. For the majority of members of our focus groups, formality means _dar facturas_ or providing formal receipts, for which a NIT is required. Others mentioned being registered at the municipal level and paying municipal fees. The measures of formality this paper focuses on are therefore the one firms themselves see as defining what it means to be formal.

We asked firms in our focus groups and in the main survey what they saw as the main benefit of having a NIT. One-quarter of surveyed firms with a NIT said the main benefit was to increase their customer base, through being able to issue tax receipts. Clients can

- 8 -
and employee would have an interest in underreporting for social 2 insurance purposes. There does not seem to be a similar incentive to underreporting for SMI and census purposes. This would explain why the SII averages are systematically lower than the SMI and census averages for the whole period but it would not explain why the discrepancy has been increasing strongly, in particular during the 1970s.

During the years of accelerating inflation and increasing marginal withholding tax rates for wages and salaries there appears to have been a tendency to substitute money wages with wages in kind or fringe benefits not liable to income taxation and social insurance contributions. This would clearly slow the increase in money wages as reported to both tax and social insurance authorities but it is not clear whether it would not have the same effect for the census and survey questionaires.

A problem is, finally, as mentioned above, that the average wages are computed by the IIS on wages subjected to social insurance contributions and not on total wages. The point is here that Turkish social insurance (as does for instance the U.S. social security) charges contributions at a fixed percent of wages but only up to an upper limit which until 1977 remained nominally unchanged at an amount of TL 200 per day (U.S., DOHEW, SSA, Social Security Programs Throughout the World, Research Report No. 50, Washingtcen D.C., Dec. 1977, pp.<sup>2 3 4</sup> -<sup>35</sup> ). This upper limit was in 1960 more than 10 times the average SII wage. In

- 48 -
delivered upon the creation of the business (e.g., business-plan writing, business planning). Beneficiaries participated in business-skill training workshops organized locally where other family members could attend, but were not conditioned on attendance.

The conditionality of all three interventions requires that the primary female of the household attend group meetings and collect payments while school-age children attend school regularly. The mean household yearly income in 2005 is approximately $1,312 US dollars (21,000 Cordobas); program benefits range from US$270 to US$470 for household with one eligible child (per household) in cash plus in kind services which signify approximately 25 to 45 percent of annual household incomes.

# **V. Data and stylized facts**

We use a two-round panel (2005 and 2006) data-set<sup>5</sup> from a detailed household survey designed for the program. The data contain information for 4,200 households in six municipalities located in the north-central part of Nicaragua. The households in this region are mostly subsistence farmers who rely on basic grain agriculture and some animal farming activities; agricultural participation of children is not uncommon and overall child labor, including domestic activity, is commonplace. Table 1 provides descriptive data on child labor by age and gender and illustrates how a large part of working children are employed on family farms and family enterprise while the majority engage in domestic chores.

The second round of data was collected 9 months after the program was implemented, 3 months before it concluded which may influence why some of the benefits in parts of the program (particularly the vocational training course) had not been completely delivered. The panel allows us to observe various outcome variables at<sup>_p_</sup> 1<sup>based on the income conditions of the household</sup> at<sup>. We can observe the same household over a years’ time which can help us separate changes</sup><sup>_p_</sup> 0 of child labor over time that are attributable to exogenous changes such as the conditional cash transfer program under evaluation here and other economic environment or labor market changes.

We disaggregate work hours from a dichotomous outcome to actual time (hours) use. The data has detailed information on activity types worked, to include domestic chores<sup>6</sup> . Methodologically, the use of hours versus binary outcomes allows for a more robust estimation approach and more accurate investigation of the research question.

> 5 The attrition rate is only 2% which is a result of extensive tracking of individuals and households throughout various regions were people had moved to.

> 6 Kruger and Berthelon (2007) find that excluding domestic work from child labor calculations biases findings in favor of girls and against boys.  In other words, it appears as if girls work less because most of their work in their sample in Brazil  is in the house; the outcomes are reversed once they account for this labor.

12
|Started or increased remote work|0.208*|0.001|-0.816*|-1.284*|-0.004|-0.053|-0.011|0.016|
|---|---|---|---|---|---|---|---|---|
||(0.114)|(0.096)|(0.444)|(0.750)|(0.588)|(0.620)|(0.279)|(0.444)|
|Exporting directly (at least 10%<br>of sales)|-0.065|-0.092|-0.286|-0.001|-0.983|-0.552|0.186|1.602**|
||(0.080)|(0.099)|(0.541)|(0.782)|(0.637)|(0.786)|(0.716)|(0.628)|
|Constant|-1.196*|0.139|-2.337***|-2.607|0.624|-0.118|-0.939|-2.493***|
||(0.654)|(0.262)|(0.555)|(1.642)|(0.385)|(0.952)|(0.873)|(0.947)|
|Number of observations|632|262|553|223|643|264|632|261|
|r2_w|0.328|0.376|||||||
|r2_b|0.032|0.007|||||||
|r2_o|0.011|0.025|||||||
|rho|0.760|0.835|||||||

Notes: This table reports panel regressions with individual firm fixed effects for the El Salvador COV-ES data. Columns 3 through 8 report marginal effects from logistic regressions. Sampling weights from the ES are used. Standard errors are shown in parenthesis. All standard errors are clustered at survey strata, and *, **, *** denotes the significance level at 10%, 5%, and 1%, respectively. See Section 6 for more details.

45
||**(i)**|**developing=1**<br>**(ii)**|**all controls**<br>**(iii)**|**types of FR**<br>**(iv)**|
|---|---|---|---|---|
|GNI|0.01|0.01|0.03*|0.03**|
|Employment|0.06*|0.04|0.02|0.05|
|**Aggregate demand:**|||||
|Private cons|0.04**|0.04**|0.04**|0.05**|
|Gov cons|-0.00|-0.00|0.01|0.01|
|Aggregate inv|0.03**|0.04***|0.03***|0.03***|
|Priv investment|0.05**|0.05***|0.06|0.07*|
|Gov investment|-0.03|-0.02|-0.03|-0.03|
|Exports|-0.03**|-0.03**|-0.05***|-0.04***|
|Imports|0.02|0.02|0.02|0.02*|
|**External sector:**|||||
|Trade balance/GDP|-0.04**|-0.05***|-0.04*|-0.04*|
|Current account/GDP|-0.02*|-0.02*|-0.02|-0.02|
|Terms of trade|-0.00|0.00|0.00|0.01|
|**Monetary/Fiscal policy:**|||||
|Inflation|-0.03***|-0.03**|-0.03**|-0.03**|
|Real int rate|0.03**|0.04**|0.03|0.03|
|Fiscal balance/GDP|-0.04|-0.01|-0.06*|-0.05*|
|Public expenditures|0.00|-0.02|-0.00|0.01|
|Public revenues|-0.03|-0.01|-0.07**|-0.07*|
|**Source:**|Table A2|Table A6|Table A10|Table A14|

Note: * p<0.10, ** p<0.05, *** p<0.01 The main results are:

1. Smaller countries have significantly less procyclical aggregate and private investment, employment and private consumption.

2. Smaller countries are also characterized by a significantly less countercyclical trade balance and current account, with this correlation being largely driven by more procyclical exports.

3. Real interest rate is more countercyclical in small countries.

4. Lastly, in smaller countries’ inflation tends to comove more strongly with output.

Next, we study the cyclicality patterns of macro aggregates with the real interest rate. Table 6 summarizes the results when size is measured by population. Again, the results based on labor force and land area are presented in appendix B.

Our results suggest that real interest rates are roughly acyclical with the key macro variables, with exception of inflation, in large economies. However, real interest rate tends to comove negatively with GDP and private investment; and positively with current account, on average, in small economies. Inflation comoves negatively with the real interest rate, and more so in small economies.

**Table 6. Cyclicality of key macro aggregates with real interest rate, by population**

22
# **2. Experimental Design and Data**

The experiment was a collaborative effort among Microcred Senegal (Microcred), MasterCard Foundation, the World Bank and the International Finance Corporation (IFC). Microcred is a microfinance institution that offers microcredit as well as savings products. After entering the Senegalese market in 2007, Microcred quickly became one of the four largest microfinance institutions in Senegal. Having focused on lending to micro, small and medium entrepreneurs in the past, Microcred has shifted focus over time to cater to low income individuals, the illiterate, women, youth and rural residents. The institution’s agent network was launched in 2014 and is growing rapidly to support this vision. More than 500 agents currently complement a network of 37 branches serving clients all over Senegal in all large cities and several smaller ones as well as increasingly also in rural areas.

Despite the arrival of Microcred, Senegal remains below the average for Sub-Saharan Africa in terms of financial inclusion. According to the Global Findex Database (DemirgucKunt et al. 2015) only 11.9 percent of the adult Senegalese population have a bank account and only 6.6 percent of adults report saving at a financial institution.<sup>8</sup> Saving informally using savings clubs or non-relatives is more common and done by 29 percent. These numbers are lower than those reported in a census we conducted in the study of peri-urban areas with closer proximity to financial institutions. According to this census, 46 percent of households reported having a savings account (see Panel A of Table 1).

Our study sample consists of 2,200 individuals from nine different survey areas located in the suburbs of the capital Dakar (6 areas), in Thies, the third most populous city (2 areas), and in a village outside of Thies (1 rural area).

These areas were chosen because Microcred was planning the rollout of its agent network there. Once agents were selected by Microcred, we identified suitable populated areas that were equidistant to Microcred branches and agents. Figure 1 shows an example of the two survey areas in Thies. Each survey area is located between the Microcred branch and a Microcred agent and is typically 1-1.5 square kilometers in size.

# _2.1 Census and Baseline Data_

Between September and October 2014 basic socio-demographic and financial data were collected from every household in the study areas. The enumerators revisited the household up to four times at different hours during the day in case the household was unavailable.

> 8 The regional averages for Sub-Saharan Africa are higher at 28.9 percent and 15.9 percent, respectively.

7
Lopez, Ramon, Vinod Thomas, and Yan Wang, 1998, “Addressing the Education Puzzle: The Distribution of Education and Economic Reform,” Policy Research Paper No. 2031 (Washington: The World Bank).

- Mackinnon, John and Ritva Reinikka, 2000, “Lessons from Uganda on Strategies to Fight Poverty,” Policy Research Paper No.2440 (Washington: The World Bank).

- Mooji, Jos, and S. Mahendra Dev, 2004, “Social Sector Priorities: An Analysis of Budgets and Expenditures in India in the 1990s,” _Development Policy Review_ , Vol. 22, No. 1: pp. 97-120.

- Mosley, Paul and John Hudson, 2001, “Aid, Poverty Reduction and the ‘New Conditionality,’” mimeo.

Musgrave, R.A., 1985, “A Brief History of Fiscal Doctrine,” in A.J. Auerbach and M. Feldstein, eds., _Handbook of Public Economics_ (Amsterdam: North Holland).

- OECD DAC, 1999, _DAC Scoping Study of Donor Poverty Reduction Policies and Practices_ (Paris: OECD).

- Perotti, Roberto, 2002, “ Public Spending on Social Protection in Columbia: Analysis and Proposals,” mimeo.

Pradhan, Sanjay, 1996, “Evaluating Public Spending: A Framework for Pubic Expenditure Reviews,” World Bank Discussion Paper No. 323 (Washington: The World Bank).

Ravallion, Martin, 2003, “On Measuring Aggregate “Social Efficiency” Policy Research Paper No. 3166 (Washington: The World Bank).

Roseboom, Johannes, 2002, “Underinvestment in Agricultural R&D Revisited,” _Quarterly Journal of International Agriculture_ , Vol. 41, No. 4 (2002): pp. 297-316 Schneider, A., 2003, “Who Gets What From Whom? The Impact of Decentralisation on Tax Capacity and Pro-Poor Policy,” IDS Working Paper 179 (Sussex: Institute of Development Studies, University of Sussex).

Schultz, T. Paul., 2002, “Wage Gains Associated with Height as a Form of Health Human Capital,” _American Economic Review_ , Vol. 92, No. 2 (May): pp. 349-53.

- _____, 1997, “Assessing the Productive Benefits of Nutrition and Health: An Integrated Human Capital Approach,” _Journal of Econometrics,_ Vol. 77, No. 1 (March): pp. 141-58

- Self, Sharmistha and Richard Grabowski, 2004, “Does education at all levels cause growth? India, a case study,” _Economics of Education Review_ , Vol. 23: pp. 47-55.

Swaroop, Vinaya, 1999, “Public Expenditure Reviews: Progress and Potential,” PREM Notes No. 20 (April).

25
Table 4: Are gender labor practices of suppliers of FDI firms different from those of other domestic firms?

|||<br>|<br>Dependent vari|<br>able is firm-leve|<br>l:||
|---|---|---|---|---|---|---|
||number of<br>female<br>workers|number of<br>female<br>workers|number of<br>female<br>administrative|<br>number of<br>female<br>administrative|<br>number of<br>female non-<br>administrative|<br>number of<br>female non-<br>administrative|
||||workers|workers|workers|workers|
||(1)|(2)|(3)|(4)|(5)|(6)|
|FDI suppliers dummy|-46.66|-46.17|0.761|1.099|-47.12|-46.07|
||(58.37)|(67.79)|(1.515)|(1.292)|(60.45)|(69.90)|
|Firm size (log of total sales)||44.61***||1.534***||42.26**|
|||(7.005)||(0.0812)||(7.239)|
|Exporter dummy||21.94||0.648**||13.16|
|||(15.71)||(0.177)||(17.90)|
|Other apparel dummy|||||||
|Apparel woven dummy|||||||
|Textiles dummy|||||||
|EPZ dummy||-63.91||-3.216||-58.25|
|||(67.77)||(2.094)||(67.45)|
|Observations|113|112|117|116|106|105|
|R-squared|0.002|0.043|0.004|0.286|0.003|0.039|

Notes: robust standard errors in parentheses clustered by industry-location. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.

Table 5: Are gender labor practices of customers of FDI firms different from those of other domestic firms?

|||<br>|<br>Dependent varia|<br>ble is firm-leve|<br>l:||
|---|---|---|---|---|---|---|
||number of<br>female<br>workers<br>(1)|number of<br>female<br>workers<br>(2)|number of<br>female<br>administrative<br>workers<br>(3)|<br>number of<br>female<br>administrative<br>workers<br>(4)|<br>number of<br>female non-<br>administrative<br>workers<br>(5)|number of<br>female non-<br>administrative<br>workers<br>(6)|
|FDI customers dummy|253.7*|154.7|2.584*|2.054*|276.3*|161.7|
||(127.3)|(107.3)|(1.345)|(1.071)|(145.1)|(116.3)|
|Firm size (log of total sales)||194.6**||1.466***||205.0**|
|||(67.07)||(0.249)||(81.25)|
|Exporter dummy||-250.5||-1.311**||-244.5|
|||(141.1)||(0.566)||(176.7)|
|Other apparel dummy||-102.4||5.100***||-328.5|
|||(309.8)||(1.194)||(335.3)|
|Apparel woven dummy||58.21||1.126*||64.41|
|||(56.28)||(0.568)||(73.68)|
|Textiles dummy|||||||
|EPZ dummy||484.7||-0.532||509.1|
|||(292.3)||(0.696)||(332.2)|
|Observations|293|290|248|245|239|236|
|R-squared|0.041|0.259|0.036|0.120|0.044|0.255|

Notes: robust standard errors in parentheses clustered by industry-location. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively 15
Policy ReseaRch WoRking PaPeR 4706

# **Abstract**

The authors explore the relationship between transaction costs and generalized trust. Using panel data from 2,100 households in 135 rural communities of the Philippines, the paper shows that where transaction costs are reduced (proxied by road construction), there is an increase in generalized trust. Consistent with the argument that generalized trust is built through repeated interactions, the authors find that the individuals most likely to engage in exchange exhibit an increase in trust after road construction. These results suggest that, rather than being an input to economic growth, trust might be a product of reduced transaction costs (which also favors growth).

This paper—a product of the Social Development Department, Sustainable Development Network—is part of a larger effort in the department to understand the determinants of both formal and informal social capital. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at jlabonne@ worldbank.org and rchase@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
BURKINA FASO’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 19. Burkina’s power costs are among the highest in Africa**

<!-- Start of picture text --> 45<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>Operating Costs Capital Costs<br>$ cents per KwH<br><!-- End of picture text --> _Source:_ Eberhard and others 2008.

**Figure 20. Power price in Burkina are among the highest in Africa**

<!-- Start of picture text --> 50<br>45<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>KWh<br>$ cents per<br><!-- End of picture text --> _Source:_ Briceño-Garmendia and Shkaratan 2010.

# Information and communication technologies

## **Achievements**

Compared with peers, the GSM coverage is larger than in other LICs, while penetration is average. The coverage of the mobile network increased from 19 percent of the population in 2001 to over 60 percent in 2007. Mobile penetration increased from 5.3 users per 100 habitants in 2005 to 16.8 in 2007, and to 29 users in 2009 (table 14).

The Internet market also expanded significantly (figure 21). In 2005 the number of Internet users per 1,000 people was 0.187, and the international Internet bandwidth (bits per second per person) was 0.006; in 2007 these figures increased dramatically to 7.5 and 14.6, respectively.

31
- 17 -

**<u>Table 4. OLS and SUR estimation results with precipitation predicted by AR models</u>**

||OLS|OLS|SUR||||
|---|---|---|---|---|---|---|
||Cost overrun|Project delays|Cost ove|rrun|Project|delays|
||Coef.<br>Std. Err.|Coef.<br>Std. Err.|Coef.|Std. Err.|Coef.|Std. Err.|
|ln_rain_<sup>_eAR_</sup>|0.415 (0.767)|0.576 (0.315) *|0.415|(0.671)|0.576|(0.208) ***|
|ln_rain_<sup>_a_</sup>_/ rain_<sup>_eAR_</sup>|-0.755 (1.326)|0.141 (0.469)|-0.755|(1.170)|0.141|(0.363)|
|ln_rain_<sup>_t_</sup>_/ rain_<sup>_a_</sup>|0.536 (0.768)|1.646 (0.357) ***|0.536|(0.590)|1.646|(0.183) ***|
|ln_cost_|0.824 (0.806)|1.193 (0.281) ***|0.824|(0.811)|1.193|(0.251) ***|
|ln_length_|-1.902 (0.810) **|-0.878 (0.296) ***|-1.902|(0.678) ***|<br>-0.878|(0.210) ***|
|ln_lane_|2.642 (3.586)|0.263 (1.710)|2.642|(3.836)|0.263|(1.189)|
|ln_thickness_|-0.331 (0.621)|-0.514 (0.184) ***|-0.331|(0.564)|-0.514|(0.175) ***|
|ln_gravel_|-0.244 (0.258)|-0.042 (0.142)|-0.244|(0.327)|-0.042|(0.101)|
|ln_bitumen_|0.960 (0.373) ***|-0.014 (0.094)|0.960|(0.278) ***|<br>-0.014|(0.086)|
|ln_earth_|0.570 (0.274) **|-0.269 (0.100) ***|0.570|(0.299) *|-0.269|(0.093) ***|
|ln_brick_|0.092 (0.465)|0.010 (0.107)|0.092|(0.353)|0.010|(0.109)|
|ln_gabion_|-0.082 (0.236)|-0.172 (0.071) **|-0.082|(0.202)|-0.172|(0.063) ***|
|ln_exavate_|-0.156 (0.144)|0.076 (0.049)|-0.156|(0.149)|0.076|(0.046) *|
|ln_cement_|0.041 (0.253)|-0.164 (0.073) **|0.041|(0.248)|-0.164|(0.077) **|
|D(_postqualify_)|5.536 (2.646) **|0.712 (0.630)|5.536|(2.102) ***|<br>0.712|(0.652)|
|Constant|-18.822(8.785)**|-15.069 (3.090)***|-18.822|(9.485)**|-15.069|(2.941)***|
|Obs.|145|145|145||145||
|R-squared|0.547|0.722|0.547||0.722||
|_F_-statistic|10.74|26.83|||||
|Chi-2|||175.35||377.38||
|No. of dummy variables:|||||||
|Project districts|18|18|18||18||
|Breusch-Pagan test of|||||||
|independence|||6.490|**|||

Note: Standard errors are shown in parentheses. *, **, *** indicate the statistical significance at the 10%, 5% and 1%, respectively.