rafmacalaba/datause-encoder-data huggingface dataset:
(2016) to construct income components from the raw data that are comparable over time. We dene labor income as the sum of wages and (taxable) pensions.<sup>5</sup> Self-employment income is the sum of sole-proprietorship (Schedule-C) and partnership income. In the baseline, capital income is dened as the sum of dividends, (taxable) interest, rents, estate income, royalties, and prots from S-corporations.<sup>6</sup> Because negative incomes can result in top shares for the distribution of capital or labor income that are greater than one, we drop observations which are negative in labor, self-employment or capital income.<sup>7</sup> Self-employment income reects returns to both human and physical capital, so it needs to be split between labor and capital. In the baseline, we allocate two-thirds of self-employment income to labor and one-third to capital. While these weights are arbitrary, they are similar to earlier literature, close to factor shares found in national accounts (Gollin, 2002; Feldstein, 2008; Elsby et al., 2013; Karabarbounis and Neiman, 2014), and intermediate compared with more extreme weights considered in the robustness checks (Appendix A.5).<sup>8</sup> Table 1 presents summary statistics for the baseline income denition. The number of observations is 87,000 per year on average.

In Appendix A.5, we show that our results are robust to several alternative income denitions. First, instead of dropping negative observations, we set them to zero (similar to Saez and Stantcheva, 2017). Second, we include capital gains, which are an important income source at the top. The tax data only report realized capital gains, which are lumpy because realizations respond to changes in the tax code or asset prices. An accruals-based approach changes the timing of capital gains in the short run, but the long-run trend remains

> 5 Stock options are taxed as wage income when they are exercised.

> 6 S-corporations are businesses with few shareholders that are taxed at the personal instead of the corporate level. Including S-corporation prots with capital is similar to CBO (2012), and tries to address the shift of corporate income to the personal sector following the Tax Reform Act of 1986 (TRA86) (see below). Since we only include income that is taxable at the personal level, our denition of capital income excludes undistributed corporate prots.

> 7This aects on average 7.5% of the (weighted) sample, due to negatives in self-employment (4.9% of self-employment incomes are negative) and/or capital income (3.0% of capital incomes are negative). The median total income of the excluded observations is similar to the 70th percentile. Using the same dataset, Auerbach and Hassett (2002) also drop observations with negative adjusted gross income.

> 8Johnson (1954) attributes 65% of non-farm entrepreneurial income to labor. Kaymak and Poschke (2016) include 64% of entrepreneurial income with labor income. Piketty et al. (2018) allocate 70% of non-corporate business income to labor.

6
# **Table 3 - Basic Results for Development Outcomes ( Ordinary Least Squares) Equality** **<u>of Opportunity Measures versus Inequality of Outcomes Measures</u>**

|Regression|Dep|endent Variable: Loga|ritm of Per Capita Income|,Average 2005-|2010|
|---|---|---|---|---|---|
||OLS|OLS<br>OL|S(Comparison Sample)|OLS|OLS|
|Human Opportunity Index*|0.038***|||0.038***|0.042***|
||(0.004)|||(0.005)|(0.004)|
|Gini Index, Average 1960-2010||-0.050***|-0.047**|0.005|-0.005|
|||(0.013)|(0.016)|(0.013)|(0.012)|
|Americas - LAC plus Canada and United States|||||0.656**|
||||||(0.191)|
|Europe and Central Asia|||||0.273|
||||||(0.182)|
|Middle East and Africa|||||1.101<br>(0.738)|
|constant|7.163***|10.140***|11.308***|6.915***|6.664***|
||(0.287)|(0.538)|(0.580)|(0.675)|(0.664)|
|R-sqr|0.587|0.093|0.135|0.599|0.647|
|Number of Observations|63|152|59|59|59|
||0.000|0.000|0.000|0.000|0.000|
|Regression|Dep|endent Variable: Loga|ritm of Per Capita Income|,Average 2005-|2010|
||OLS|OLS<br>OL|S(Comparison Sample)|OLS|OLS|
|Dissimilarity Index*|-0.094***|||-0.090***|-0.097***|
||(0.012)|||(0.013)|(0.013)|
|Gini Index, Average 1960-2010||-0.050***|-0.047**|-0.004|-0.018|
|||(0.013)|(0.016)|(0.013)|(0.013)|
|Americas - LAC plus Canada and United States|||||0.624*|
||||||(0.271)|
|Europe and Central Asia|||||0.159|
||||||(0.225)|
|Middle East and Africa|||||0.863|
||||||(0.832)|
|constant|10.672***|10.140***|11.308***|10.706***|11.030***|
||(0.156)|(0.538)|(0.580)|(0.444)|(0.468)|
|R-sqr|0.508|0.093|0.135|0.522|0.557|
|Number of Observations|63|152|59|59|59|

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

*Average Mathematics, Reading and Science Outcomes Level 2 - PISA 2009

22
**Figure 3: Conditions to ensure credible commitment in high sunk-cost industries**

<!-- Start of picture text --> Credible enforcement<br>High-level procedural<br>constraints<br>Substantive<br>(legal)<br>constraints<br><!-- End of picture text --> _Source: derived from Levy and Spiller (2006)_ How can these conditions be addressed in practice in the context of the EIZ? A number of traditional legal approaches to managing risk in international investments may form part of the solution. First, bilateral and multilateral investment treaties may play a role in mitigating the risk that any one of the member countries of EIZ renege on their commitment to the EIZ (and thus to individual foreign investors in the zone). Investment treaties legalize a government’s commitment to fair treatment toward foreign investors, requiring among other things national or most-favored-nation (MFN) treatment of in-country foreign investors and protection of contractual rights. Such investment treaties are normally enforced through the provision of independent dispute resolution mechanisms. In the context of BITs, the theoretical literature suggests that national governments will uphold their commitments out of concern to maintain their reputation, both with the bilateral partner and more widely (Goldsmith and Posner, 2005). However, there is certainly no guarantee that BITs alone will ensure commitment. Indeed, Wellhausen (2010) finds that since the 1990s there has been a huge growth in bilateral investment treaties but also a huge growth in the number of “expropriation incidents”<sup>21</sup> and investment arbitration, suggesting that even if BITs do contribute to greater investment in the short term, they may not offer a solution to the commitment problem.

A second element of the solution may reside in the use of political risk insurance. This can be provided through private markets or, for example, through the World Bank’s Multilateral Investment Guarantee Agency (MIGA). MIGA guarantees can also to a degree be effective in securing a binding commitment from governments due to the reputational risk they would expose themselves to should they renege, and the implications this might have on their access to finance through the World Bank and other IFIs.

A third element may be the use of international dispute resolution mechanisms, normally involving binding arbitration, can play a role in helping to offset such project-related commitment risk. Such

> 21 “Expropriation incidents” defined as “forced divestment of equity ownership of a foreign direct investor” as per Kobrin in Wellhausen (2010)

21
mothers and fathers does not yield any significant impact or difference, the comparison between CCTs and UCTs indicates that conditional cash transfers increase the number of preventive visits, while UCTs do not and that difference is statistically significant. By linking the payment of the cash transfers to regular visits to the health center for children under age 6, the CCTs achieved their objective of increasing preventive health care. We describe these impacts in more detail in Akresh, de Walque, and Kazianga (2016).

Preventive routine visits are self-reported by the parents and were directly in the CCT arms were directly conditioned upon. In the next columns, we investigate whether the cash transfers had further impacts on health outcomes which with the exception of self-reported outcomes are also more objectively measured. In column 2, we use a biomarker collected only during round 3 that provides a more objective measure of child health. In particular, we measure the C-reactive protein (CRP) level on each child aged 0 to 5 which we collected using venous blood samples (Zeba et al. 2013). The level of CRP rises when there is inflammation throughout the body. Cash transfers to the mothers and conditional cash transfers decrease significantly the level of CRP indicating a reduction in infections. This effect is not present when the transfers are given to fathers and when they are unconditional and those differences across transfer types are statistically significant.

While our dependent variables in columns 1 and 2 were only collected at the final followup (round 3), the remaining dependent variables (columns 3-6) have been collected in each round. Because we follow a value added specification requiring the children to be present at the baseline and follow-up rounds, our sample for those dependent variables for the round 2 analysis is limited to children aged 12-60 months and for round 3 to ages 24-60 months.

In column 3, we analyze the probability of being ill in the last 30 days as reported by the parents a measure of the general health of the children. The cash transfers appear to have an impact in reducing illness episodes. At round 2, that reduction does not vary according to the gender of the recipient, but CCTs have a statistically stronger impact than UCTs. At round 3, transfers to fathers are the only ones to reduce illness and the difference with transfers to mothers is statistically significant, while both CCTs and UCTs decrease children’s illnesses.

Finally, we measure the effect of the cash transfers on anthropometrics in the last three columns of Table 4. Our dependent variables are weight-for-age z-scores, arm circumference for age z-scores and height-for-age z-scores. These three measures can, respectively, be interpreted 16
7 place on average 2.19 years after the award of the contract. 13 This was for concessions granted for about 20 to 30 years and that had a five year period for a tariff review (for concessions granted under a price cap regime). Table 2 also shows that the choice of the regulatory regime matters. In particular, Table 2 shows that a price cap regime strongly increases the probability<sup>of</sup> renegotiation well ahead of the scheduled tariff revision-which usually was scheduled<sup>forthe</sup> end of the fifth year after the award of the contract. Hybrids regimes did, as expected, better<sup>than</sup> pure price caps, but not as well, in terms of renegotiations, as rate of return regimes.14 While Table 3 shows the important role operators have in initiating the renegotiations,<sup>it</sup> is also interesting to analyze the extent to which the regulatory regime is correlated with<sup>the</sup> originator of the request for renegotiation. Essentially, in 2 out of every 3 contracts, the change<sup>is</sup> requested by the operator. This is a significant proportion. Within the context of this paper, the obvious next question is the extent to which the request for renegotiation is driven<sup>by thechoice</sup> of the regulatory regime. Table 4 provides the answer.

**Table 3: Who initiated the Renegotiation? (% of total requests)**

||BothGovernmentandOperator|Government|Operator|
|---|---|---|---|
|All sectors|13%|36%|61%|
|WaterandSanitation|10%|24%|66%|
|Transport|16%|27%|57%|

Source: Guasch (2003) When examining the data on the regulatory regime, Table 4 shows that the initiator of renegotiations, was overwhelmingly (86%) the operator when under a price cap regime, corroborating our hypothesis. The percentage drops considerably (26%) when the operator was under a rate of return regime, as expected under our hypothesis. Table 4 might<sup>implythatthe</sup> efficiency gains achieved by the operators may not have been large enough to provide them with

> **13** It was 3.3 years-accounting for construction lag time- in the transport sector and 1.6 years in the water sector (Guasch, 2003)

> **14** It may be useful to point out that the adoption of a hybrid regimes was generally the result of renegotiations of contracts initially subject to a price cap regime. Indeed, in general, the main change in the regime<sup>wasanincreasein</sup> the number of cost categories that enjoyed automatic pass-through. In sum, the initial price cap choice has tended to be short lived in Latin America, in particular in the transport and in the water and sanitation sector.
# **Coalition-Building Incentives, By Type and Target Constituency** (categories drawn from Wilson, 1973)

|MATE<br>Exclusive<br>|RIAL<br>Individual<br>|SPECIFIC SOLIDARY<br>____________________|COLLECTIVE SOLIDARY<br>_______________________|PURPOSIVE<br>Goal-Oriented<br>*|
|---|---|---|---|---|
|"Corruption<br> <br>Insurance"<br> <br>|Econ benefits<br>of improved<br>economy|Data/information banks<br>—on corrupt agencies,<br>officials|Prestige, improved image<br>-domestically, internationally|Reform as public<br>good|
|||—on best practices|Enhanced autonomy for<br>|Better governance|
|Information|Security from||organizations, press,||
|-vulnerability|better|Research products|opposition leaders,<br>|Fair political,<br>|
|assessments|governance||civil society groups|economic processes;<br>social equity|
|-prevention<br>within orgs<br>-legal and tech-<br>nical advice<br>_Prime constituenc_<br> <br>|_ies_<br>_:_<br>|Rewards, recognition<br>|Sociability, fellowship,<br>mutual encouragement<br> <br>|Stronger economic,<br>social institutions<br>Enhanced Rule<br>of Law<br>|
|Small firms,<br> <br>domestic<br> <br>entrepreneurs<br> <br>and investors<br>|Citizens<br>generally<br>Civil society,<br>NGOs|Professional coalition<br>staff, researchers<br>Benefactors, financial<br>supporters<br>Anti-corruption<br>"champions"|Mass membership<br>Journalists<br>NGO leaders<br>Government elites<br>|Mass membership<br>NGOs<br>Aid/lending partners<br>Democracy groups<br>and supporters|

_____________________________________________________________________________________________________________________

* Ideological and Redemptive sub-types of purposes not recommended

13
<mark>Eckel, C. C., & Wilson, R. K. (2004). Is trust a risky decision?.</mark> _<mark>Journal of Economic Behavior & Organization, 55</mark>_ <mark>(4), 447-465.</mark> <mark>Greig, F., & Bohnet, I. (2009). Exploring gendered behavior in the field with experiments: Why public goods are provided by women in a Nairobi slum.</mark> _<mark>Journal of Economic Behavior & Organization, 70</mark>_ <mark>(1-2), 1-9.</mark> <mark>IFC, 2018. “Aligning Expectations: The Business Case for Digital Financial Services.”</mark> <mark>IFC, 2018. “Granting Access: Leveraging Social payments to Expand Digital Financial Inclusion in Côte d’Ivoire.”</mark> <mark>Izaguirre, J. C., Kaffenberger, M., & Mazer, R. (2018). It’s time to slow digital credit’s growth in east africa.</mark> _<mark>CGAP Blog</mark>_ <mark>.</mark> <mark>Karlan, D., McConnell, M., Mullainathan, S., & Zinman, J. (2016). Getting to the top of mind: How reminders increase saving.</mark> _<mark>Management Science</mark>_ <mark>,</mark> _<mark>62</mark>_ <mark>(12), 3393-3411.</mark> <mark>Lusardi, A., & Mitchell, O. S. (2011).</mark> _<mark>Financial literacy and planning: Implications for retirement wellbeing</mark>_ <mark>(No. w17078). National Bureau of Economic Research.</mark> <mark>Lyman, Timothy, Ivatury, Gautam, and Staschen, Stefan. 2006. Use of Agents in Branchless Banking for the Poor: Rewards, Risks, and Regulation. Consultative Group to Assist the Poor (CGAP), Focus Note No.38. CGAP: Washington, D.C.</mark> <mark>Maitra, P, S Mitra, D Mookherjee, A Motta and S Visaria. 2017. “Financing Smallholder Agriculture: An Experiment with Agent-Intermediated Microloans in India,”</mark> _<mark>Journal of Development Economics</mark>_ <mark>127: 306-337.</mark> <mark>Maitra, P, S Mitra, D Mookherjee and S Visaria (2016), “The Distributive Impacts of Microloans for Smallholder Agriculture,” mimeo, Boston University.</mark> Mani; Anandi; Mullainathan, Sendhil; Shafir, Eldar; Zhao, Jiaying. 2013. “Poverty Impedes Cognitive Function.” _Science._ 341 (6149): 976-980.

<mark>Prina, S. (2015). Banking the poor via savings accounts: Evidence from a field experiment.</mark> _<mark>Journal of development economics</mark>_ <mark>,</mark> _<mark>115</mark>_ <mark>, 16-31.</mark> <mark>Schaner, S. (2015). Do opposites detract? Intrahousehold preference heterogeneity and inefficient strategic savings.</mark> _<mark>American Economic Journal: Applied Economics</mark>_ <mark>,</mark> _<mark>7</mark>_ <mark>(2), 135-74.</mark> <mark>Schaner, Simone. (2018). “The Persistent Power of Behavioral Change: Long-Run Impacts of Temporary Savings Subsidies for the Poor”,</mark> _<mark>American Economic Journal: Applied Economics,</mark>_ <mark>10(3): 67-100.</mark> <mark>Schilbach, Frank. 2019. "Alcohol and Self-Control: A Field Experiment in India"</mark> _<mark>American Economic Review</mark>_ <mark>109(4): 1290-1322.</mark> <mark>Shah, A. K., Mullainathan, S., & Shafir, E. (2012). Some consequences of having too little.</mark> _<mark>Science</mark>_ <mark>,</mark> _<mark>338</mark>_ <mark>(6107), 682-685.</mark> 22
- 10 -

years. The feasibility sturdy recognizes the fact that the discharge at the Thac Mo Reservoir has increased since the construction of the original dam. The Alaknanda River does not seem to have a significant time trend component.

Figure 2. Observed Monthly Hydrology (Vishnugad Pipalkoti, India) (Upper Kotmale, Sri Lanka) <!-- Start of picture text --> 1970m1 1975m1 1980m1 1985m1 1990m1 1995m1 2000m1 2005m1 1950m1 1960m1 1970m1 1980m1 1990m1 2000m1<br>Year and month Year and month<br>200<br>3000<br>150<br>2000<br>100<br>Hydrology Hydrology<br>(mil. m3 per month) (mil. m3 per month)<br>1000<br>50<br>0 0<br><!-- End of picture text --> (Thac Mo, Vietnam) <!-- Start of picture text --> 1975m1 1980m1 1985m1 1990m1 1995m1 2000m1<br>Year and month<br>1500<br>1000<br>Hydrology<br>(mil. m3 per month) 500<br>0<br><!-- End of picture text --> In addition to hydrology, both precipitation and temperature series are also apt to exhibit considerable seasonality. However, it is common that the former has more irregularities than the latter (Figure 3).<sup>2</sup>

> 2 In these time series borrowed from the NOAA database, some observations are missing in the 1990s.
|To pursue an interest, hobby, or passion|||-0.022|-0.022|-0.031|-0.032|
|---|---|---|---|---|---|---|
|of mine|||(0.02)|(0.02)|(0.02)|(0.02)|
|I was unhappy with my previous job|||-0.009|-0.009|-0.010|-0.011|
||||(0.02)|(0.02)|(0.03)|(0.03)|
|To have a work and life balance|||0.015|0.014|0.015|0.019|
|satisfying my needs|||(0.02)|(0.02)|(0.02)|(0.02)|
|Role model was a man (Unconditional)||||0.023**|0.015|0.016|
|||||(0.01)|(0.01)|(0.01)|
|_Non-Cognitive Skills_|||||||
||||||0.020**|0.020**|
|Generalized self-efficacy|||||(0.01)|(0.01)|
|E S|||||-0.006|-0.006|
|rror management core|||||(0.01)|(0.01)|
|Entrepreneurial identity|||||-0.010**<br>(0.00)|-0.011**<br>(0.00)|
|Career Fit Confidence: More Committed|||||-0.008**|-0.008**|
|to staying in sector|||||(0.00)|(0.00)|
|Career Fit Confidence: Good|||||-0.002|-0.002|
|relationships in sector|||||(0.01)|(0.01)|
|Constant|0.169***|0.211***|0.117***|0.113***|0.143**|0.165**|
||(0.03)|(0.03)|(0.04)|(0.04)|(0.06)|(0.07)|
|Observations|10,691|10,628|7,958|7,958|5,113|5,113|
|Region FE|NO|NO|NO|NO|NO|YES|
|Adjusted R-squared|0.01|0.01|0.02|0.02|0.03|0.03|

In Table 5, we investigate further the role of husbands in helping women to cross over, restricting analysis to the 75 percent female owners/managers whom are married. We include variables that capture the different types of help the husband could provide to his wife’s business.

Among married women, seeing an opportunity in the market, to make more money and to be more independent are positively associated with a female crossing over into a male-dominated sector. These reasons are particularly pertinent in the developing economies<sup>21</sup> and these finding are consistent with the results of the Global Entrepreneurship Monitor where the likelihood of necessity being cited as the reason for starting a business declines with higher economic development (GEM, 2016).

Additionally, we explore the role of the husband in the business. There is some literature which examined a husband’s role in women’s careers, concluding that husband’s impact women’s choices and career aspirations (Still and Timms, 1998; O’Neil and Bilimoria, 2005; Vanhala, 2005). In Ethiopia, women entrepreneurs fare better with support from their husband. Eighty-three percent of married women said their husband helped in the business in some way (mainly by contributing start-up money) and women were more likely to enter into more profitable male-dominated sectors when their husband was an entrepreneur himself (Alibhai et al. 2017). Wolf (2018) classifies the husbands of Ethiopian business women into three

> 21 Appendix D shows these results separately for developed and developing countries.

14
<!-- Start of picture text --> 100% |<br>90% |<br>~jo)jo) 60% | = Rudimentary++<br>S som | Informality<br><!-- End of picture text -->

<!-- Start of picture text --> 100% |<br>90% |<br>~jo)jo) 60% | = Rudimentary++<br>S som | Informality<br>2 40% | TMModern<br>—Oo 30% | Informality.<br>S 20% | = Formality<br>10% |<br>0% ©<br>2010 2020 2030 2010 2020 2030 2010 2020 2030<br>100% |<br>90% |<br>roxo|<br>=<br>S 56 0% || m InformalityRudimentary<br>& aoy | TM Modern<br>—So 30% | Informality.<br>S 20% TM Formality<br>10% |<br>2010 2020 2030 2010 2020 2030 2010 2020 2030<br><!-- End of picture text -->