rafmacalaba/datause-encoder-data huggingface dataset:
features. And as expected from La Porta, Lopez-de-Silanes, and Shleifer (1999), most of the cross-listing firms that are widely held, to start with, are from English common law countries.

When I examine the change in ownership structure over time, I find that there is a small decline in the percentage of voting rights held by the controlling shareholder in cross-listing firms as compared to a benchmark sample of firms that do not cross-list. This decline is largest for firms from countries with poor investor protection (the French civil law countries) and for firms that start out with initial owners as a state or another corporation. Interestingly, I find that the decline decreases with time. The mean voting rights held by the controlling shareholders decrease in the year of cross-listing and for three years thereafter. However, the controlling shareholders start reconsolidating their position in the fourth and fifth years after cross-listing.

The decline in voting rights around the time of cross-listing is not large enough to result in a widely-held ownership structure, suggesting little evidence of any convergence-related movement. This persistence in concentrated ownership patterns, even after listing on US markets, lends support to the path-dependence theory of ownership structures.

Although most of the companies continue to be controlled by an ultimate owner on cross-listing, I document a high incidence of changes in the identity of the controlling shareholder. Controlling shareholders in 35% of the sample of cross-listing firms approach US markets as a way to divest their stake and sell their control block. Several reasons contribute to why a US listing might facilitate such a sale, including greater visibility (Baker, Nofsinger, and Weaver (2002)), superior earnings forecasts (Lang, Lins, and Miller (2003), and higher valuations (Doidge et al. (2003)). I elaborate on the reasons in the next section of the paper. Many of the exiting controlling shareholders happen to be either the state or a family and the new entrants are predominantly widely held corporations. Further, I find that more than half of the control changes are to foreign controlling owners.

I then turn to firm and country-level data to get a better understanding of which characteristics influence a change of control in companies on cross-listing. I use the Worldscope 3
<mark>Strobl, C., Hothorn, T., & Zeileis, A. (2009). Party on!.</mark> <mark>Strobl, C., Boulesteix, A. L., Zeileis, A., & Hothorn, T. (2007). Bias in random forest variable importance measures: Illustrations, sources and a solution.</mark> _<mark>BMC bioinformatics</mark>_ <mark>,</mark> _<mark>8</mark>_ <mark>(1), 1-21.</mark> <mark>Tibshirani, R. (1996). Regression shrinkage and selection via the lasso.</mark> _<mark>Journal of the Royal Statistical Society: Series B (Methodological)</mark>_ <mark>,</mark> _<mark>58</mark>_ <mark>(1), 267-288.</mark> <mark>Varian, H. R. (2014). Big data: New tricks for econometrics.</mark> _<mark>Journal of Economic Perspectives</mark>_ <mark>,</mark> _<mark>28</mark>_ <mark>(2), 3-28.</mark> <mark>Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed.</mark> _<mark>Educational psychologist</mark>_ <mark>,</mark> _<mark>47</mark>_ <mark>(4), 302-314.</mark> <mark>Zhao, P., & Yu, B. (2006). On model selection consistency of Lasso.</mark> _<mark>The Journal of Machine Learning Research</mark>_ <mark>,</mark> _<mark>7</mark>_ <mark>, 2541-2563.</mark> 22
ANGOLA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE countries and three times above the international benchmark of 20 percent. EPAL revenues covered only 72 percent of total costs in 2009 vis-à-vis 81 percent in 2005. Despite an increase in connections per employee from 25 in 2005 to 34 in 2009, EPAL’s labor productivity is just one-third of the average for utilities in resource-rich countries and well behind the international benchmark of 200 connections per employee.

The burden of EPAL’s inefficiencies has increased over time. By comparing key performance indicators of the utilities for which data are available against those of a well-performing utility or norm, we are able to quantify—in monetary terms—the key inefficiencies affecting each utility. Here three types of hidden costs are considered: first, utilities unable to collect 100 percent of their bills (collection inefficiencies); second, utilities incurring losses on their water distributional network above the norm of 20 percent of production (losses); and, third, utilities whose average effective tariffs are not enough to cover the cost of producing a cubic meter of water (underpricing). On this basis, the hidden costs of EPAL grew from 98 percent of revenues in 2005 to 132 percent in 2009. The largest source of hidden costs were high distributional losses, followed by low collection rates. In absolute terms this represents an almost threefold increase in losses, from $45 million in 2005 to $125 million in 2009 (table 14). When compared to the performance of other southern African utilities, EPAL’s hidden costs are among the highest in the region (figure 18).

**Figure 18. Benchmarking the hidden costs of EPAL against those of selected countries in southern Africa**

<!-- Start of picture text --> Percentage of revenues<br>a. EPAL’s hidden costs b. Hidden costs of select water utilities in southern Africa<br>140 350<br>120 300<br>100 250<br>80 200<br>60 150<br>40 100<br>20 50<br>0 0<br>Collection inefficiencies Underpricing Distribution losses Collection inefficiencies Underpricing Distribution losses<br>Percentage of revenues Percentage of revenues<br><!-- End of picture text --> _Source:_ Derived from Banerjee and others (2008b) and Briceño-Garmendia, Smits, and Foster (2009).

In the rural context, water supply is provided mainly by wells and boreholes that do not guarantee the provision of safe water. Around 50 percent of rural dwellers are supplied by water coming from 4,000 wells and boreholes countrywide (figure 19). Many of these are not working due to shortages of spare parts or fuel for pumps (USAID 2009). Low rural-road accessibility and the slow process of clearing mines left over from the civil war make it harder to develop rural water supply systems. The government has launched an ambitious rural strategy aimed at increasing water supply coverage to periurban and rural areas to 80 percent by 2012.

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with the survey instrument was above 98%.<sup>6</sup> In the second and third surveys, we also elicited information for a shorter reference period, i.e., last week before the survey.<sup>7</sup> As the measurement of child labor statistics could be affected by how child labor definitions are operationalized in the survey design questionnaire (e.g., Bardasi et al. 2012), we employ a relatively long rather than a short questionnaire design. Specifically, the survey contains 12 questions that aim to elicit information about the specific farm and non-farm labor activities. The most important questions refer to work at the household farm, as this activity accounts for most children work in rural Ethiopia (Guarcello and Rosati 2007). A typical labor question asks: “ _Did [name] work any time in the household farm in the last [..] days?”_ Since the keyword “work” can have a different meaning for respondents, we supplement this question with a detailed, standard explanation of the concept of work by using a set of typical farming activities which is read aloud to the respondents: planting, watering, weeding, mulching, seeding, fertilizing, handpicking cherry coffee, cattle herding. This question is followed by an ‘intensive margin’ question, “ _how many hours in the last [..] days did [name] spend working on the household farm?”_ 8 It is worth noting that household chores such as fetching water and/or firewood, house cleaning, cooking, and child and elderly care are explicitly treated and explained as activities that do not belong to farm work. This approach aims to provide children and proxy respondents a clearer description of what constitutes child work at the farm.

# **2.3 Timeline and Sample Attrition**

Fieldwork took place from July 2015 to January 2017. As the variation in work activities across the year depends on the agricultural calendar, we implemented the same survey design experiment 10
7 <!-- Start of picture text --> ROYALTIES AND OIL PRICES<br>percentaQe chancQes<br>350<br>300<br>250<br>200<br>150<br>100<br>-50 , , , , ,<br>1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991<br>0 ROYALTIES + OIL PRICES<br><!-- End of picture text --> Figure 2 80% of revenues from PDVSA. The royalty is one-sixth of the gross oil revenue which is the product of total production times world oil prices. According to this formula, royalty revenues should closely correlate with world oil prices. Statistical analysis showed that they do not. Figure 2 plots royalties and world oil prices, showing royalties not to be responsive to world oil price changes, particularly during the period 1977-85. For most of the years during the period 1971-91 the percentage changes in royalties have been below the percentage changes in world oil prices. Regression analysis also showed that world oil prices explain only 23% of the volatility in royalties and that a 10% change in world oil prices is translated into a 3.6% change
24 occur and historical statistics can become the bread-and-butter of day-to-day microprudential risk management (i.e., help price risk across borrowers, institutions, and instruments). Accordingly, the main role of the agency supervisor is to put in place the necessary apparatus for markets to conduct their monitoring role effectively. Once this is done, his only residual role is one of compliance checking and crime policing (misrepresentation, fraud, looting, etc.)

|**Table 2. A Sy**<br>|**nthetic Overview of R**<br>|**egulatory Issues**<br>|**and General Pol**<br>**Paradigm**<br>|**icy Responses**<br>|
|---|---|---|---|---|
|**_Dimensions_**|**_Issue_**|**Agency**|**Externalities**|**Mood Swings **|
||_What is the market_<br>_failure?_|Betting with<br>someone’s else<br>money|Opportunistic<br>behavior that<br>conflicts with the<br>socialgood|Acting upon<br>weak information<br>or biased<br>perceptions|
||_What should ex-ante_<br>_prudential norms do?_|Align incentives<br>through skin in<br>the game|Align incentives<br>through<br>internalizing<br>externalities|Temper moods<br>and domesticate<br>creativity|
|**_Foundations_**|_Can risk be priced?_|Yes|Probably not<br>fully (one<br>hundred year<br>floods)|Probably not<br>(unless Moses-<br>like supervisor)|
||_How effective is market_<br>_discipline?_|Potentially very<br>effective|Ineffective<br>(inability to<br>estimate or<br>withstand<br>systemic risk)|Ineffective<br>(inability to<br>comprehend or<br>withstand<br>systemic risk)|
||_What is the role of the_<br>_supervisor?_|Enhancer of<br>market discipline-<br>crime police|Crowd manager-<br>fireman|Scout-moderator-<br>fireman|
|**_Scope_**|_Should the line in the_<br>_sand be redefined?_|No|Yes|Not necessarily|
||_Does fair value_<br>_accounting help?_|Yes, it is<br>fundamental|No, it exacerbates<br>externalities|No, it<br>exacerbates<br>mood swings|
|**_Focus_**|_Are systemic liquidity_<br>_norms needed?_|No|Perhaps Yes|Probably Yes|
||_How important to look_<br>_at the system?_|Not important|Very important|Fundamental|
|**_Dnamics_**|_Should prudential and_<br>_monetary authorities_<br>_coordinate?_|Not really|Tightly|Very tightly|
|**_y_**|_Are dynamic, macro-_<br>_prudential norms_<br>_needed?_|No|Yes, rule-based|Yes, judgment-<br>based|
# **1. Introduction**

Child education is of fundamental importance to all governments, as shown by the inclusion of universal primary school enrollment as one of the Millennium Development Goals. Thus educational economics has long investigated the determinants of child education (e.g. see Becker, 1965; Becker and Tomes, 1976; Leibowitz, 1974; Tansel, 1997, Black et al., 2005).

Sometimes investment in childhood education loses out to the use of child labor. In developing countries, when families are faced with poverty they often turn to their children to provide additional income (Basu and Van, 1998, Swinnerton and Rogers, 1999, Grootaert and Kanbur, 1995) and so make the decision to forego their children‟s education explicitly to generate more current household income (Edmonds, 2003; Edmonds and Turk, 2004; Beegle, Dehejia, and Gatti, 2005).

Other parental characteristics, apart from income, also influence children‟s enrollment. For example, there is a clear correlation between high levels of education in parents and the enrollment and achievements of their children (e.g., Behrman et al., 1999; Glick and Sahn, 2000).

Childhood characteristics also matter. For example, historically girls have been less likely to attend school than boys (World Bank, 2001), although this gap has been closing (United Nations 2008). Another factor that can limit children‟s education is the presence of a disability. In fact, Filmer (2008) found that childhood disability was a better predictor of school enrollment than gender and other socio-economic characteristics. Evidence in Vietnam also points towards lower enrollment in school for people with disabilities (Mont and Cuong, 2011).

Yet, little is known about the effect of parental disability on child education. Parental disability could potentially be associated with poor education outcomes among children for a few reasons. Disability can result in lower labor productivity and less income. Some evidence suggests a strong association with poverty (Braithwaite and Mont 2009, Hoogeveen 2005, Yeo and Moore 2003), primarily through the effect on employment (Mitra and Sambamoorthi 2008, Contreras et al. 2006, Eide and Loeb 2006, 2
monopoly power in tax setting to region B, and no power to region A (where, in the limit, the carbon quota price is zero).

To recapitulate, the c-a-t solution is, in “almost all” cases, less attractive to the importing (and climate policy defining) block than either of the tax solutions. This leads the fuel importer (and main consumer) to prefer tax solutions over a c-a-t solution in climate policy, in a wide set of circumstances. The only exceptions are found to be when ex post substitution possibilities under a cap solution are “very good” for the importer (when fuel 2 has a “very high” carbon content), and the fuel exporter at the same time has high aversion (perhaps, unrealistically high) against carbon emissions.

The immediate policy conclusion is that major fuel-importing and -consuming countries should, on balance, choose tax solutions over cap solutions. The main problem with choosing a c-a-t solution is that it leaves them more vulnerable to adverse strategic manipulation of fuel prices by monopolistic exporters. Other implications may be less obvious. One might in particular be tempted to conclude that the importing block ought to maintain a substantial output of high-carbon fuel (coal), so as to diminish the strategic pricing power of fuel exporters, thus making a c-a-t solution “optimal”. But this would also have unwanted side effects including that of increasing overall carbon emissions. While not studied here, a further analysis of such cases is clearly warranted for future work.

This paper takes my previous analysis of tax and cap behavior by major fuel-consuming and exporting blocks, in Strand (2009a), several steps ahead. Many issues are however left unaddressed. First, the model is rigid in its sharp separation between fuel consumers and exporters; and in assuming full cooperation within each block of countries and no cooperation across blocks. My initial conjecture is that relaxing these assumptions need not alter the model fundamentally; in particular, it should not to alter the derived balance between tax and 32
Policy Research Working Paper 8676

# **Abstract**

The labor force of each industrial country is being shaped by three forces: ageing, education and migration. Drawing on a new database for the OECD countries and a standard analytical framework, this paper focuses on the relative and aggregate effects of these three forces on wages across different skill and age groups over 2000 to 2010. The variation in the age and educational structure of the labor force emerges as the dominant influence on wage changes. The impact is uniform and egalitarian: in almost all countries, the changes in the age and skill structure favor the low-skilled and hurt the highly skilled across age groups. Immigration plays a relatively minor role, except in a handful of open countries, like Australia and Canada, where it accentuates the wage-equalizing impact of ageing and education. Emigration is the only inegalitarian influence, especially in Ireland and a few Eastern European countries which have seen significant outflows of high-skilled labor to Western European Union countries.

This paper is a product of the Development Research Group, Development Economics. 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://www.worldbank.org/research. The authors may be contacted at cozden@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
guidelines and official recommendations ( _ibid._ ), we report on three subscales, separated into ‘internalizing problems’ (emotional and peer symptoms, 10 items), ‘externalizing problems’ (conduct and hyperactivity symptoms, 10 items), and a scale of prosocial behavior (5 items). To capture respondents’ personality traits, The Big Five Scale measures five core dimensions of personality. The five broad personality traits measured are extraversion, agreeableness, openness, conscientiousness, and neuroticism. Evidence of the Big Five as being relevant (and associated with life outcomes) has been growing, beginning with the research of Fiske (1949) and later expanded upon by other researchers including Norman (1967), Smith (1967), Goldberg (1981), and McCrae and Costa (1987). We use the short 15 item Big Five Inventory (BFI-S) (Lang et al. 2011), with three items per personality trait. Like the indicators of cognitive skill, all measures of socioemotional outcomes are standardized.<sup>20</sup> We also collected information on five labor market outcomes. We ask whether a respondent is currently working (yes or no) and the age at which she or he first started working. We moreover construct a binary indicator of whether a respondent’s main work activity is cognitively demanding. We categorize an occupation as such if it requires at least occasional use of reading, writing, mathematics, or a computer (according to the respondent). Our survey also asked for respondents’ income; our analysis reports on (the inverse hyperbolic sine of) yearly earnings and (the inverse hyperbolic sine of) a respondent’s daily reservation wage, i.e., the minimum wage or payment for which a respondent is willing to accept work (both are reported in US dollars, a currency commonly used in Cambodia). Our last set of outcomes includes six indicators of socio-economic status and wellbeing. We assess subjective social status using a “MacArthur community ladder”.<sup>21</sup> Respondents were shown a picture of a ladder with ten rungs and were told that 20For further discussion on these measures, and their psychometric and statistical properties, see Danon et al. (2018). In addition to the measures we report on here, we collected data on respondents’ level of grit (Duckworth and Quinn 2009) and their growth mindset (Dweck 2000). We do not report on results for these measures because of their poor psychometric properties in our data. The inclusion of either of these measures does not substantively change our results. 21For a description and bibliography of papers that use MacArthur ladders, see the MacArthur Foundation’s Network on SES and Health website: http://www.macses.ucsf.edu/Research/Psychosocial/subjective.php.

16
motivate our choice of Colombia as a representative case study. Compared to other middleincome economies, Colombia is a richer country that grows at a slower rate. However, these differences are not substantial, and we can consider Colombia a representative middle-income economy.

Colombia’s emissions are half as large as the average middle-income country (on a per-capita basis), which is partly explained by the extensive use of hydroelectricity in Colombia. Electricity access is also high and comes close to 100 percent. Low carbon intensity and good availability of electricity make a strong case for electric vehicles to help decarbonize the economy.

The Colombian government has set an ambitious goal to reduce its greenhouse gas emissions by 20% by 2030 under the Paris Agreement commitments (Law 1844, 2017). To help achieve this commitment, the government intends to have 600,000 electric vehicles on the road by 2030.<sup>11</sup> Table 3: Summary statistics of Colombia’s economy in 2019

|**Variable**|**Colombia**<br>**Mi**<br>**Co**|**ddle Income**<br>**untries**|
|---|---|---|
|GDP per capita (current US$)|6425.0|5480.3|
|GDP growth (annual %)|3.3|4.6|
|CO2emissions (metric tons per<br>capita)|1.6*|3.7*|
|Access to electricity (% of<br>population)|99.8|93.5|
|Renewable energy consumption|||
|(% of total final energy<br>consumption)|30.7*|20.4**|

Note: Calculations are based on the World Bank Open Data. Middle-income countries are defined based on the World Bank country classification for 2021.<sup>*</sup> Latest data available for 2018.<sup>**</sup> Latest data available for 2015.

The government has recently adopted and proposed several tax policies to promote the uptake of hybrid and electric vehicles. First, starting in 2017, the sales tax on new vehicles was reduced from 19 percent to 5 percent for hybrid and electric vehicles; the sales tax for gasoline vehicles remains at 19 percent. In 2017, Colombia also reduced import tariffs from 35 percent to 0 for electrics and 5 percent for hybrids; tariffs for gasoline vehicles remain at 35 percent. Initially, the

> 11 See https://www.worldenergy.org/news-views/entry/electric-mobility-is-a-reality-in-colombia [last accessed: February 2022].

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