rafmacalaba/datause-encoder-data huggingface dataset:
increased 22 percentage points between<sup>1996 and 2000(from 59 percent to 81percent).</sup> One example is the export of electronic<sup>circuits of whichforeignaffiliates'sharegrew</sup> from 78 percent of total exports in<sup>1996to 93percent in 2000with Intel and Samnsung</sup> being two major exporters. **5** On the positive side, there is also the<sup>potential for China to increase its own</sup> outward investment in ASEAN. The<sup>possibilities for this areexplored later in the</sup> discussion of intraregional production<sup>networks.</sup>

# **Intraregional FDI**

Compared to the EU and NAFTA, intra-ASEAN<sup>flows make up a smallershare of</sup> total flows. Figure 4.7 below shows<sup>intra-EU investmentincreasedfrom51percentin</sup> 1997 to over 60 percent in 1999. In<sup>2001,thelargest shareof the EU'sFDI flows went</sup> to other EU members.<sup>56</sup> Figure 4.7

**Intra- and Extra-EU FDI Flows**

<!-- Start of picture text --> 70<br>60<br>50<br>40 - 11 5 A EI.<br>* =nflows frm =ts.U<br>OTotal tntra-EU flows<br>IL 30 L l<br>10<br>1995 1996 1997 1998 1999<br>Note: Intra-EU figures represent the average of inward and outward flows as declared by Member States.<br><!-- End of picture text --> Source: UNCTAD, World Investment<sup>Report2001,Figure1.8.p.18.</sup> In the first seven years of NAFTA<sup>(1994-2000), averageFDI inflowsto Canada</sup> were US$21.4 billion and to Mexico<sup>were$11.7billion, which were four times and three</sup> times, respectively, the average annual<sup>amounts receivedin the seven years prior to</sup> NAFTA. In order to take advantage of the enlarged<sup>market that Mexico'smembership</sup> in NAFTA provides, a number of TNCs<sup>haveestablishedor upgraded productionin that</sup> 23
Table E.6: Impact heterogeneity based on initial levels of antisocial behavior

||||Ther|apy only|Cas|h only|Assign|ed to both|
|---|---|---|---|---|---|---|---|---|
|Outcome|Round|Coefcient on:|Coef.|Std. Err.|Coef.|Std. Err.|Coef.|Std. Err.|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
||2–5|Treatment indicator|-0.188|[.072]***|-0.088|[.073]|-0.257|[.072]***|
|Antisocial behaviors|w|Interaction term|-0.159|[.092]*|-0.056|[.089]|-0.235|[.077]***|
||12–13m|Treatment indicator|-0.023|[.078]|0.104|[.078]|-0.190|[.071]***|
|||Interaction term|-0.037|[.096]|0.209|[.101]**|-0.179|[.075]**|

_Notes:_ We regress our family index of antisocial behaviors on baseline level of antisocial behaviors, treatment indicators, and interactions between treatment and baseline antisocial behaviors, controlling for baseline covariates and block fixed effects. Robust standard errors in brackets. *** p<0.01, ** p<0.05, * p<0.1 3. Non-agricultural low-skill wage labor, which includes contract work, carloading, car-washing, peim-peim riding, carrying loads, guarding, housecleaning, and construction 4. Agricultural work, which includes farming and fishing, 5. Illicit work, which includes selling drugs, stealing, gambling, gold rubber, and scavenging.

Table E.7 reports ITT estimates on the average of the two weeks of data. While we generally observe no changes in overall average hours worked per week (the one exception is those assigned to cash only work approximately 15% more hours per week in the short-term), treatment effects how participants allocate their time. In the short-term, all three treatments cause participants to shift from illicit work to non-agricultural low-skill business. Those assigned to both therapy and cash experience the largest decline in illicit work. Time spent in illicit work falls 38% 2–5 weeks after implementation relative to the control group, and is 17% less than the control group one year later (although the latter is not statistically significant). Although the cash-only group more than doubles its weekly hours spent in non-agricultural low-skill business in the short-term, these effects phase out 12–13 months later.

# **F Survey data validation details**

## **F.1 Variables**

We selected six variables for validation, all with recall periods of two weeks. We chose outcomes with varying degrees of salience (or memorability) and potential social stigma and experimenter bias. The variables were:

1. _Stealing._ The survey asked how many times in the last two weeks the respondent stole someone’s belongings or deceived or conned someone of money or goods.<sup>19</sup> Based on our fieldwork, we hypothesized that stealing would be the most salient and least socially desirable of all six measures.

> 19The survey also measured more serious forms of theft, such as armed robbery, but our qualitative validation focussed on non-violent theft.

xlvi
Policy Research Working Paper 7510

# **Abstract**

In April 2014, the Government of Benin launched the entreprenant status, a simplified and free legal regime offered to small informal businesses to enter the formal economy. This paper presents the short-term results of a randomized impact evaluation testing three different versions of the entreprenant status on business registration decisions, each version including incremental incentives to registration: (i) information on the new legal status and its benefits, (ii) business training, counseling services, and support to open a bank account, (iii) tax mediation services. The study included 3,600 informal businesses operating with a fixed location in Cotonou, Benin, which were randomly allocated between three treatment groups and one control group. One year after the program launch, all versions of the program had significant impact on formalization rates. The impact was 9.1 percentage points in the first treatment group; 13 percentage points in the second group; and 15.8 percentage points in the last group. The program had a higher impact on male business owners, with more education, operating outside Dantokpa Market, in sectors other than trade, and that before being offered the incentives to formalization had characteristics similar to businesses that were already formal. Data from a second follow-up survey, which is expected to take place in March 2016, will explore the impacts on other outcomes, like business performances or access to banking.

This paper is a product of the Trade and Competitiveness Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at msantini@ifc.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
Bodenhorn, Howard (2003). “Short-term loans and long-term relationships: relationship lending in Early America,” _Journal of Money, Credit and Banking_ 35: 485–505.

- Budina, Nina, Harry Garretsen, and Eelke de Jong (2000). “Liquidity Constraints and Investment in Transition Economies: The Case of Bulgaria,” _Economics of Transition_ 8: 453–475.

- Cressy, Robert and Otto Toivanen (2001). “Is there adverse selection in the credit market?” _Venture Capital_ 3: 215–238.

- CGAP (Consultative Group to Assist the Poor) and WBG (The World Bank Group) (2010). _Financial Access 2010: The State of Financial Inclusion Through the Crisis_ , Washington, DC: CGAP and the World Bank Group.

- de la Torre, Augusto, Maria Soledad Martinez Peria, and Sergio Schmukler (2010). “Bank Involvement with SMEs: Beyond Relationship Lending,” _Journal of Banking and Finance_ 34: 2280-2293.

- Degryse, Hans and Patrick Van Cayseele (2000). “Relationship lending within a bank-based system: evidence from European small business data,” _Journal of Financial Intermediation_ 9: 90–109.

- Dietrich, Andreas (2010). “Explaining Loan Rate Differentials Between Small and Large Companies: Evidence from Switzerland,” _Small Business Economics_ , Forthcoming.

- Duan, Naihua (1983). “Smearing estimate: A non-parametric retransformation method,” _Journal of the American Statistical Association_ 78(383): 605-610.

- EC (European Commission) (2009). _European SMEs Under Pressure: Annual Report on EU Small and Medium-Sized Enterprises 2009_ , Brussels, Belgium: European Commission.

- Galindo, Arturo and Fabio Schiantarelli (2003). “Credit Constraints and Investment in Latin America,” RES Working Papers 4305, Inter-American Development Bank, Washington D.C.

- Gros, Daniel and Marc Suhrcke (2000). ‘Ten Years After: What is Special About Transition Countries?’ European Bank Working Paper N. 56.

- Hallberg, Kristin. 2000. “A Market-Oriented Strategy for Small and Medium-Scale Enterprises,” Discussion Paper 40, International Finance Corporation.

- Harhoff, Dietmar, and Timm Korting (1998). “Lending relationships in Germany - Empirical evidence from survey data,” _Journal of Banking and Finance_ 22: 1317–1353.

- Hartwell, John M. (1947). “Interest rates by loan size and geographical region,” _Journal of the American Statistical Association_ 42: 242–245.

16
<!-- Start of picture text --> Relationship Between Full-Time Employment for an Employer and GDP<br>300<br>ca=oSBz250}200| . “. . =/ee"Ee -. . ]<br>@Es3 150)100 | . ots tT ie La."3" =<br>ao3= so} iolieLte “ .atonea, ,oy Te =e<br>a ee<br>° a 20 40 6o ao 100<br>Percentage of Workforce Employed Full Time for an Employer (2009 and 2010)<br>Speanman’s rho=-.85 (p<.(W1; N=127)<br><!-- End of picture text -->

<!-- Start of picture text --> Relationship Between Unemployment Rate and GDP<br>300 .<br>~250}- ..<br>od8Ss wor Seeeptegt=aa8atiaw | " .<br>@°3 10100 naea angeteete ! i . .anual . .<br>Fe]4B9 50 a)roa i | me| a snot. o*<br>0<br>° 5 10 15 20 25 30 35 40<br>Percentage of Workforce Unemployed (2009 and 2010)<br>Spearman's rho = -.16 (N=127)<br><!-- End of picture text -->
substantial fixed costs of compliance: Maskus et al. (2005) report an average of $425,000 per firm, or 4.7% of value added, based on a survey of over 600 firms in 16 developing countries. For firms in the textiles and clothing sectors, the mean investment cost required to comply with technical requirements is 2.7% of firm sales. The range is very wide, however, running from 0.01% to 44.1%. This suggests that the firm-level impacts of standards can vary drastically, thereby making a heterogeneous firms approach particularly attractive.

After setting out a baseline scenario without harmonization, I modify the model to take account of product standard harmonization covering two of the three countries only. Harmonization lowers the fixed costs of exporting from one harmonizing country to another such that they are at the same level as the costs of domestic market entry. This reflects the fact that under harmonization, domestic producers in both harmonizing countries produce goods satisfying the same standard, and they can therefore export them inside the harmonization zone without paying any further adaptation costs. From the perspective of the third (non-harmonizing) country, harmonization means that it is only necessary to pay one fixed cost (not two) in order to access both foreign markets. Using numerical simulations, I show that harmonization thus defined raises the export marginal cost cutoff in the two harmonizing countries vis-a-vis each other, and also in the non-harmonizing country. Foreign harmonization therefore makes it easier for producers in the third country to overcome the cost hurdles associated with exporting, which in turn results in increased export variety due to the association of each firm with a distinct product variety. Although the level of compliance costs imposed by the harmonized standard as compared with pre-existing national standards has the potential to limit or even reverse this outcome, simulations show that the thirdcountry impact is positive even when compliance with the harmonized standard is moderately more burdensome.

<u>necessity for export sales. Note that I do not consider the role that standards can play on the consumption</u> side (Fischer and Serra, 2000; Ganslandt and Markusen, 2001), nor reductions in information costs for exporters (Moenius, 2004). There is also an emerging body of case study evidence on this point. World Bank (2005) shows that management capacity and strategic decisions are an important determinant of how developing country firms react to changes in foreign product standards. The logic of the Melitz (2003) model presented here suggests that the cost increases associated with such changes will be felt most acutely by relatively unproductive firms, which may drop out of markets as a result. 6
# **1   Introduction**

Hygiene is essential to the public health mission of reducing the transmission and consequences of disease. The two leading causes of childhood mortality worldwide are diarrheal disease and acute respiratory infections,<sup>4</sup> accounting for two-thirds of the deaths of children under age five.<sup>5</sup> Both of these categories of illness are closely associated with inadequate hygiene. In addition, chronic parasitic infections and diarrhea can lead to anemia, which further hinders children’s development.<sup>6</sup> The provision of safe water and sanitation, and improved hygienic behaviors more generally, has the potential to alleviate the proximate causes of these illnesses and thereby improve health.<sup>7</sup> Medical evidence suggests that the hands are the main transmitters of diarrhea and respiratory infections. As such, they constitute disease vectors carrying respiratory microorganisms and fecal material into the domestic environment of the susceptible child.<sup>8</sup> Health experts recommend handwashing with soap as a critical action in protecting public health because it is a mainstay in infection control.<sup>9</sup> Yet, rates of handwashing with soap at critical times remain low throughout the world, even when both soap and water are available.<sup>10</sup> In a sample of developing countries, the observed rates of handwashing with soap 4 Thirty-five percent of these deaths are due to diarrheal disease and 32 percent are due to acute respiratory infections. It was estimated that 21 percent of deaths in the 42 countries with the highest mortality are due to pneumonia (Black et al. 2003).

5 WHO 2002.

6 Curtis and Cairncross 2003.

7 See, for example, Esrey et al. 1991 and Galiani et al. 2005.

8 Hendley et al. 1973, WHO 2003.

9 Most parasites live and breed in feces and are transmitted to humans when ingested or through the hands. Parasitic infestations pose serious threats to young children and are a cause of child mortality (World Bank 2005). Among those who survive, parasitic infestations are associated with diarrhea and micronutrient malnutrition, which often leads to iron-deficiency anemia, protein-energy malnutrition, and enlargement of the liver and spleen (see, among others, Anderson and May 1991; and Hesham et al. 2004). Currently, anemia, which leads to slow cognitive development, is a widespread global health problem (see, among others, Nokes et al. 1992, and Pollit 1990). In addition, some respiratory tract infections, including the SARS-causing corona virus, are transmitted via the fecal-oral route or simply on hands (World Bank 2005). Hence, adequate handwashing is a primary barrier to the transmission of enteric pathogens, as hands can be cleansed of viruses and bacteria by washing with soap (Curtis and Cairncross 2003), (Faix 1987; Ansari et al. 1989; Luby et al. 2001; Gibson et al. 2002; Montville et al. 2002; Larson et al. 2003).

10 Scott et al. 2003.

2
Table 3: Balance: Household characteristics

||Full sample||R|D sample|||
|---|---|---|---|---|---|---|
||Coef. (SE) [p]|Dep. var.||Coef.|(SE) [p]||
||(1)|(2)|(3)|(4)|(5)|(6)|
|HHH female|0.041|0.221|0.045|0.044|0.043|0.041|
||(0.025)|(0.416)|(0.046)|(0.050)|(0.046)|(0.050)|
||[0.094]|969|[0.326]|[0.378]|[0.345]|[0.412]|
|HHH age|0.5|47.5|2.1|0.7|1.4|0.3|
||(0.8)|(14.5)|(1.4)|(1.8)|(1.4)|(1.9)|
||[0.497]|967|[0.127]|[0.694]|[0.298]|[0.863]|
|HHH completed primary|0.069|0.287|0.128|0.102|0.119|0.099|
||(0.025)|(0.453)|(0.047)|(0.062)|(0.047)|(0.062)|
||[0.005]|966|[0.006]|[0.097]|[0.012]|[0.111]|
|HHH worked of farm|0.023|0.410|-0.039|-0.019|-0.024|-0.011|
||(0.027)|(0.493)|(0.051)|(0.064)|(0.050)|(0.064)|
||[0.392]|969|[0.441]|[0.763]|[0.631]|[0.868]|
|# of plots|0.61|5.19|0.20|0.35|0.36|0.40|
||(0.18)|(3.38)|(0.36)|(0.46)|(0.36)|(0.46)|
||[0.001]|969|[0.582]|[0.448]|[0.319]|[0.382]|
|# of HH members|0.17|4.89|-0.00|-0.03|-0.01|-0.03|
||(0.11)|(2.16)|(0.21)|(0.25)|(0.22)|(0.25)|
||[0.104]|969|[0.985]|[0.917]|[0.971]|[0.908]|
|# who worked of farm|0.10|0.77|0.01|0.03|0.01|0.04|
||(0.05)|(0.85)|(0.08)|(0.10)|(0.08)|(0.10)|
||[0.039]|969|[0.909]|[0.799]|[0.906]|[0.722]|
|# of HH members (15-64)|0.20|2.60|0.26|0.17|0.24|0.15|
||(0.08)|(1.45)|(0.15)|(0.16)|(0.16)|(0.16)|
||[0.007]|969|[0.090]|[0.300]|[0.128]|[0.349]|
|Housing expenditures|-2.3|49.2|-5.6|-16.7|-6.5|-18.6|
||(6.9)|(127.4)|(14.9)|(19.0)|(14.7)|(19.1)|
||[0.739]|962|[0.707]|[0.380]|[0.658]|[0.328]|
|Asset index|0.11|-0.12|0.15|0.06|0.13|0.04|
||(0.05)|(0.99)|(0.12)|(0.13)|(0.12)|(0.13)|
||[0.034]|967|[0.215]|[0.647]|[0.291]|[0.738]|
|Omnibus F-stat [p]|3.9||2.1|0.9|1.7|0.9|
||[0.000]||[0.028]|[0.536]|[0.073]|[0.514]|
|Site FE|||X||X||
|Distance to boundary|||X|X|X|X|
|log area|||||X|X|
|Spatial FE||||X||X|

_Notes:_ Column 2 presents the mean of the dependent variable and the standard deviation of the dependent variable in parentheses, for sample plots in the main discontinuity sample that are outside the command area, and the total number of observations. Columns 1 and 3 through 6 present regression coefficients on a command area indicator, with standard errors in parentheses, and p- values in brackets. Column 1 uses the full sample, while Columns 2 through 6 use the discontinuity sample. Columns 5 and 6 use specifications (1) and (2), respectively.

with 2015, adoption of irrigation does not appear to trend, but exhibits meaningful seasonality. Differences remain around 3pp - 6pp in the rainy seasons, and 19pp - 26pp in the dry seasons.

20
**Table 18**

**Estimated LKP Earnings Adjusted for Subsidies and Bad Debt Expenses**

|**Units**|**Earningys Measure**|**1993**|**1994**|**1995**|
|---|---|---|---|---|
|Three of four**units**|||||
||_Adiusted rcal ROA (percent_|-22.3|-8.8|-5.2|
||Adjustcd real ROE (percent)|-33.3|-9.7|-2.8|
||Subsidv Dependencv Index' (percent)|104|41|24|
||Currcnt interest rate (percent)|160|160|160|
||Reqtuired interest rate to cover all costs<br>including**mi**rket return on equity (pecent)|325|225|198|
|Best performning unit|||||
||Adjusted rcal ROA (percentli|-0.2|-0.9|4.9|
||Adiusted rcal ROE (percent)|5.6|3.1|11.9|
||Subsidy Dcecndencv Index (percent)|0|1|**4**|
||Currcnt interest rate|160|160|160|
||Rcquiredintcrest rate to coNer all costs<br>including<br>market<br>return onequity(percent)_|160|176|154|

a/ The percent incrcase in **the** intcrest ratc that is reqwred if the units were to be fully self-supporting including paying a market ratc of return to equity holders.

In 1995, the program would have had to charge a 198 percent annual interest rate to completely eliminate all program subsidies and pay liability and equity holders a market return on their investments. This rate is higher than the rate required for BKK and P4K, but below the rate required for PHBK. It is about 24 percent higher than the rate the units currently charge.

Again taking into account the additional expenses above, the best performing LKP unit could have provided an adjusted real return to equity holders of fronm 3 to 12 percent since 1993 . This unit's subsidy dependency index would have varied from I0 to -4 percent over the last three years (Table 18). The interest rate required to eliminate all of the unit's subsidies ranged from 154 to 176 percent.

_Outreach Scope._ The district of Dompu has four LKP units for its six sub-districts. When the units were founded, the district had only 4 sub-districts. District leaders hope to be able to create new units for the new sub-districts, but have no firm plans for doing so. Units serve 34 of the 45 villages (76 percent of villages) in the sub-districts where they are located.

48
the importance of the opportunity cost of leisure in the decision to sell at the market. This result is similar to that reported in Fafchamps and Hill (2005). However, when the interaction term is included (for instance in column 3, Table 5), we fi nd that wealth’s e ff ect on gaining market access dominates over its e ff ect on shadow cost of labor. While the relative strength of the two opposing e ff ects of wealth may vary from country to country, the regressions in the context of India underscores the need for separating the two out.

# 4.2 Robustness

The results on the impact of market facilities so far relate to one particular measure of market facilities. An alternative index of market facilities can be constructed using factor analysis. Speci fi cally, we construct the principal component factors of the 14 di ff erent facilities that were utilized to construct Fi used in regressions so far.<sup>14</sup> The factor analysis indicates that the principal component factors account for almost all of the variations leaving small amount of unexplained variance (“uniqueness"). We used the predicted fi rst principal component as an index of market facilities (F<sup>pc</sup> ).<sup>15</sup> Since by construction, the principal factor component has a mean of 0 and standard deviation of 1, there are some values of the facility index which are negative. We add an arbitrary constant to the principal factor component to make the facilities index (F<sup>pc</sup> ) a positive number for all observations. The regression results using this facility index (F<sup>pc</sup> ) is presented in column 1 of Table 6. The results again con fi rm the positive e ff ect of market access index on probability of sales at the market. Similar to results presented in column 4 of Table 5, the interaction of market access with wealth has a negative coe ffi cient which is highly statistically signi fi cant (t=3.71). Comparison of results in column

> 14 This is done by using stata command factor with option pcf.

> 15 The scoring coe ffi cients suggest that variations in three market facilities ( parking space, whether market has a bank or not, and whether it has weighing facilities or not) contributes most in the construction of the market facility index using factor analysis.

22