rafmacalaba/data-use-mentions-extended huggingface dataset:
Table 7: Vehicle ownership and carbon emissions

|Dependent variable|(1)<br>CO2 emissions per capita<br>from transport(log)|(2)<br>CO2 emissions per capita<br>from transport(log)|(3)<br>CO2 emissions per capita<br>from transport(log)|(4)<br>CO2 emissions per capita<br>from transport(log)|
|---|---|---|---|---|
|Average Number of cars per household (log)|0.355***<br>(0.034)||0.391***<br>(0.058)||
|Average Number of motorcycle per household (log)||0.156***<br>(0.013)||0.300***<br>(0.038)|
|Constant|0.080**|0.182***|-0.858***|-0.860***|
||(0.040)|(0.038)|(0.166)|(0.140)|
|Country FE|Yes|Yes|Yes|Yes|
|Observations|1,646|1,550|193|162|
|Number of countries|194 (IRF data)|194 (IRF data)|19 (LSMS survey)|19 (LSMS survey)|
|R-squared|0.982|0.980|0.947|0.946|

Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

**Extensive margin: rising incomes, vehicle ownership, and CO2 emissions** Figure 20 uses the change in predicted probabilities from Figure 19 and
Notteboom, Coeck and Van den Broeck (2000). Third, Cullinane et al. (2004) point to the high degree of fluctuation of efficiency over time documented from a sample of 25 container terminals, including some in developing countries. This point is also made by Estache et al. (2004) when discussing the impact of the demand shock due to the East Asia crisis on the Mexican ports located on the Pacific coast of the country. Fourth, based on the Indian experience, De and Ghosh (2002) document the role of the access to capital and its degree of use to the level of efficiency of the sector comparing data from 1981-1982, and 2000-2001 for 12 Indian ports. Fifth, there are many factors driving the efficiency of a port. A few of the papers try to assess systematically the various sources of changes in efficiency. This is the case of Estache et al. (2004) for instance which computes a Malmquist TFP growth index and then relies on a distance function to decompose it into technical, scale and efficiency changes.

From a reform viewpoint, the main lessons are the following. First, the results on the relevance of ownership and the impact of reforms suggest that private ownership tends to improve efficiency in the sector in developing countries. Indeed, Cullinane, et al. (2002) show this in their analysis of 15 Asian container ports during the 1989-1998 period and Notteboom, Coeck and Van den Broeck (2000) reach similar conclusions. Second, increased competition and decentralization of port authorities improves efficiency as shown by Estache et al.. (2002 and 2004) in the case of Mexico. Third, benchmarking is a realistic regulation mode for the sector. Many of the papers are concerned with benchmarking some specific ports or port systems. Tongzon (2001) for instance compares the Australian ports to a set of best practice international ports for 1996 using a DEA. Estache et al. (2002) for instance shows how efficiency measures can be used to promote yardstick competition in
initially remains in the home country (possibly still in the household of his parent) while the migrant is temporarily gone; ( _ii_ ) because they have left children behind in the home country to be looked after by grandparents, possibly after the spouse has joined the migrant at destination;<sup>24</sup> ( _iii_ ) because he and his spouse are from the same home country and thus retain stronger ties to it than if the migrant marries a foreigner; ( _iv_ ) because they can make more of a complete contract with the migrant and his spouse that involves funding migration and getting insurance/remittances in return–whereas if it is with an unmarried migrant, there is a party that then joins the family that is not part of the initial contracting arrangement and could lead to renegotiation. Finally, as argued in section 5.2, it is probably easier for the married migrant to visualize who will also benefit from migration (spouse and children left behind) and than for the unmarried migrant to picture the potential wife and children he might have at destination.

These factors put together could dominate the lower psychic costs of the unmarried son’ migration and the higher probability to intermarry with a U.S. native that translates into higher earnings at destination (and for a longer duration) compared to the married migrant _i ∈ F_ . Table 1 reveals that this applies to only one out of five male migrants who get married after migration.

# **5.3.1 Descriptive evidence from the ENOE**

We draw on data from the 2005Q1 to the 2018Q4 rounds of the ENOE, a rotating panel survey conducted by the INEGI in Mexico, to examine the probability of migrating to the U.S. for married and unmarried men aged 18 to 40 who co-reside with both parents at baseline. The ENOE, which interviews households for five consecutive quarters, allows observing the occurrence of a migration episode from variations in the household roster across interviews, coupled with questions to remaining household members about
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employment than the intensive cultivation practices required by the new varieties; multiple cropping made use of normally underemployed workers and increased the number of work days per worker per year.<sup>19</sup> 3.48 Vlhile the adoption of new rice varieties. led to a short-term increase in demand for labor, the long-term trvc-l ' -lining share of the labor force in agriculture is an expected par: ';e structural transfcrmation. As the economy of a country shliUts from primarily agricultural to industrial, worke,s migrate to -5naLi jobs. Does crop diversification, with its associated marketing and pr. essing industries, accelerate this process by providing new opportunities? Or are there short-run risks that a shift out of rice cultivation would simply throw large numbers of hired laborers out of work? There is some concern among governments that a p.rogram of crop diversification would have adverse effects on rural employment in the short run, before the longer-term process of creating jobs in industries, whether urban or rural, is under way.

3.49 The answers to such questions cannot be known without studying the use of labor for different crop systems as well as the indirect demand for labor created by the farm households' consumption and investment that is stimulated by crop incomes. Most of the information about direct labor use comes from farm surveys, and it is difficult to draw general conclusions from them because of the differences among countries, even regions, in use of family labor, hired workers, wage rates, sharecropping arrangements, harvesting contracts, land tenure, and other factors. For rice alone, the number of labor-days per hectare to bring in a crop varies considerably, from a low of 20 days in the Sind, in Pakistan, to more than 340 days in West Java, with no absolute consistency in greater labor rec-irements for high-yielding varieties compared with traditional varieties. As mentioned previously, however, the large gains in labor use for rice came with increased multiple cropping.

19/ See Barker
a two-step procedure and deflated by household-specific Paasche indices, as described above. This yields a food poverty line of R$258 in 2018 urban Southeast prices. In the alternative specification, an additional step has been taken to assign calories to food items registered in the POF household expenditure questionnaire on frequent purchases (POF 3). The cost per calorie in this alternative scenario is minimally higher, leading to a food poverty line of R$259 in 2018 urban Southeast prices. Moving from assigning calories to 1,413 items accounting for 86.6 percent of total expenditures on food consumed at home to 4,020 items accounting for 98.6 percent of total expenditures on food consumed at home, following our approach, leaves the cost per calorie estimation and thus the food poverty line largely unchanged.

**Table 4. Food poverty line – Main and alternative specification, in 2018 urban Southeast prices**

||**Main specification**|**Alternative imputation (using**<br>**broad foodgroups)**|
|---|---|---|
|**Cost per calorie**|0.0040|0.0041|
|**Food poverty line**|R$258|R$259|

_Source:_ Own calculations using POF 2017/18.

_Note:_ Main specification estimates the cost per calorie based on assigning food items in POF to the TBCA and imputation for food items at the 5-digit level (i.e., steps 1 and 2 described above). The alternative specification extends the imputation to larger food groups based on categorization by IBGE (2020).

14
Annual growth (percentage)<br>Annual growth (percentage)<br><!-- End of picture text --> _Source:_ Penn World Table 9.0, World Development Indicators, United Nations, and the author’s estimates. _Note:_ Variability measured by the standard deviation of mean income growth. Country regressions over the period 1980–2014. Similar results are obtained using the following periods instead: 1990–2014, 2000–2014, and 2005–2014. The total number of countries used in this estimation is 150. The number of NROC and ROC economies is 104 and 46, respectively. The number of countries in the classification LOGCs, MOGCs, and HOGCs are 8, 117, and 25, respectively.

37 Despite the inclusion of two global factors affecting mean income growth, the model in Equation (1) does not disaggregate the idiosyncratic components affecting the country performance of growth of mean income. Besides, note that all the idiosyncratic random forces are captured via the error term in Equation (1). This error term, however, could include omitted global components as well.

Page **42** of **45**
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Nevertheless, they are likely to remain lower than in Asia. Because, first, the requirement for irrigation equipment and construction will be small and, second, lower population densities mean that<sup>implement suppliers</sup> require a larger geographic area to support a minimum scale of operation. This leaves them more vulnerable to competition from high volume<sup>urban</sup> suppliers.

132. The forward linkages from agriculture to processors and distributors are currently far larger than the backward linkages. Available data shows them to be at least ten times greater than the backward linkages. Food processing is one of the most important,<sup>with beer</sup> brewing as the largest single non-farm activity in many countries.<sup>Milling</sup> is also considered important, but, overall, distribution of agricultural products is the largest of the non-farm linkages. Retailing is a very labor intensive activity and accounts for a great majority of<sup>employment in</sup> West Africa.

133. In a situation where farm incomes are increasing, the consumer linkages derived from these increases have the potential to<sup>bean important</sup> stimulant to the growth of the rural non-farm economy. As per capita incomes rise, the demand for higher quality foods and<sup>local services</sup> typically increases more rapidly than that for food grains. The Asian experience suggests that the production of these commodities is<sup>labor</sup> intensive, hence rural employment increases quite rapidly with per capita farm income increases. Evidence in Africa is scanty.<sup>But available data</sup> suggest that because. this linkage depends on a combination of high
20 20. Wagstaff A, Van Doorslaer E. Progressivity, horizontal equity and reranking in health care finance: a decomposition analysis for The Netherlands. _Journal of Health Economics_ 1997; **16:** 499-516.

21. Wagstaff A, van Doorslaer E. Catastrophe and impoverishment in paying for health care: with applications to Vietnam 1993-98. _Health Econ_ 2003; **12** (11).

22. Xu K, Evans DB, Kawabata K, Zeramdini R, Klavus J, Murray CJ. Household catastrophic health expenditure: a multicountry analysis. _Lancet_ 2003; **362** (9378) **:** 111-7.

23. Van Doorslaer E, O'Donnell O, Rannan-Eliya RP, et al. Paying out-of-pocket for health care in Asia: Catastrophic and poverty impact. EQUITAP Working Paper #2, Erasmus University, Rotterdam and IPS, Colombo, 2005.

24. Chou S-Y, Liu J-T, Hammitt JK. National Health Insurance and Precautionary Saving: Evidence from Taiwan (China). _Journal of Public Economics_ 2003; **87** (9-10) **:** 1873-94.

25. Phua KH. Attacking Hospital Performance on Two Fronts: Network Corporatization and Financing Reforms in Singapore. In: Preker AS, Harding A, eds. Innovations in Health Service Delivery: The Corporatization of Public Hospitals. Washington DC: World Bank, 2003.

26. Rannan-Eliya RP. Status of National Health Accounts in Asia-Pacific Region: Results of the APNHAN Survey 2001. Colombo: Health Policy Programme, Institute of Policy Studies, Sri Lanka, 2001.

27. Lim MK. Health care systems in transition. II. Singapore, Part I. An overview of health care systems in Singapore. _J Public Health Med_ 1998; **20** (1) **:** 16-22.

28. Leung GM, Wong IO, Chan WS, Choi S, Lo SV. The ecology of health care in Hong Kong (China). _Soc
the HIECS survey)

- Household income per capita (modified to wealth per capita quintile for the DHS survey)

- Location of residence (rural/urban)

- Region of residence (Upper Egypt, Lower Egypt, Metropolitan Egypt, or Frontier Governorates).

# **3. Evolution of Opportunities for Children in Egypt, 2000-2009: Time Trends and Regional Comparisons of the HOIs** **_Aggregate HOI Trends_**

_Improvements in Opportunities for Children_ . As illustrated in Table 2,<sup>18</sup> the overall HOI for children between 9 and 15 years, _IOHa9-15-Housing Services_ – the aggregate of all 5 human opportunities in housing and on education – increased from 35 points in 2000 to 72 points in 2009. This means an improvement of 37 points for the whole period, and a quite satisfactory annual rate of progress of 4.1 points per year. Similarly the aggregate HOI for housing for children between 0 and 4 years, _IOHa0-4-Housing Services_ , experienced substantial progress from 49 to 83 points during the decade. In contrast, the other aggregate HOI for children in the range 0-4 years of age, _IOHa0-4-Nutrition & ECD_ , performed very poorly and stayed at merely 14 points. In brief, the aggregate performance of access to opportunities of basic housing services is quite satisfactory for

> 16 Figure A-1 in the appendix shows the number of opportunities (maximum 6 or 7) reached by children in the age groups 0-4 years of age and 9-15 years of age.

> 17 An alternative way of building aggregate indices would be to average all 16 HOIs across the whole population. However these ”mash-up” indices suffer serious limitation (Ravallion, 2010). A solution to this critique is to build a multidimensional opportunity index for a children cohort with an appropriate threshold (minimum number of opportunities)..

> 18 School attendance was not available for 2000.

10
be seen in the reports made by the Financial Superintendence of Colombia

# iii. Assumptions

In the present paper, no modeling of tax evasion, either direct or indirect, is performed. This exercise is due to a _de jure_ approximation, rather than _de facto._ In the remainder of the document when the term informality is used for the modeling of indirect taxes, this is due to the modeling of the non-payment of VAT established by law for all such commercial agents belonging to the simplified regime,<sup>32</sup> since belonging or not to the simplified regime depends on the income of the establishment, which is unknown, the assumption made in this paper is that the establishments classified as “informal” do not exceed the amount established by law. It is important to emphasize that what is sought with this treatment is to have an estimate of the incidence of VAT considering that the effective rate is lower than the statutory one (it is greater than zero for the VAT paid on inputs, but it also does not become equal to the statutory rate) and given that the economic effect is the same as when the establishment evades payment of the tax, the term informality is used for convenience in the literature.

In terms of taxes, only those that accrue to a person's income, namely income tax, and social security contributions, were considered. For income tax, income was classified according to its nature and per the five income types stipulated in the tax statute in force in 2017: labor, pensions, capital, non-labor, and dividends. We use information from DIAN administrative records to clean the income for each income type; precisely, the data used was the percentage of deductible and exempted income. This was considered because the survey does not ask for many of the deductible items, and when applying the

> 32 An economic agent belongs to the simplified regime if it meets the following characteristics: (i) The total gross income derived from the commercial activity of the previous year
4 paper we attempt to describe ways and means by which such reforms affect various interest groups (including government agencies and users), and how each group may affect the implementation of each reform. We also attempt to develop an approach to estimate the political risks associated with implementation of institutional reforms in the water sector. We first describe ways in which political impacts and political risks were handled in the literature dealing with various reforms and economic adjustment projects. The survey of the literature provides some needed qualitative relationships observed over the years in various countries. Then we propose a procedure which can be used to calculate the political risks, expressed as the likelihood of achieving a given reform. We use available data from the NDP project in Pakistan (World Bank, 1997) to apply our framework; and make inkages to the political economy of the water and drainage sector as they are reflected through the NDP project. We focus on the major institutional reforms and the main.interest groups associated with the NDP. We conclude by providing for risk mitigating and management that should assist the government of Pakistan to cope with the political risks of the various reforms in the NDP.

# **POLITICAL ECONOMY OF REFORMS, POLITICAL INFLUENCE AND POLITICAL RISK ASSESSMENT**

To be able to assess the political risks associated with institutional reforms, it is necessary to know how the stakeholders (also called interest groups or players) are affected by the reforms, what their interests are, and their ability to impact the reforms. A quantitative evaluation of risk can be estimated once the extent of the political effects on the institutional reforms is known.

Although the literature contains a rich set of studies on the political economy of institutional reforms in general (Paul, 1990; Azis, 1994; Bromley, 1989; Nelson, 1992; Haggard et al., 1995; Rose-Ackerman, 1997; Stallings and Brock, 1993), and in the agricultural sector in particular (Bhalla, 1991; Brandao and Carvalho, 1991; Garcia, 1991; Nabi, 1986;
In the revisited original‐sample villages in 2007, 20 households were resampled per village from the 1994/95 sample and the split households (defined below) were included. In the new villages, 24 households were sampled in each village. The 2010 survey followed the sample households in all 98 villages.

Between the surveys, some household members separated from the original 2007 households to start their own new households or to join other households. In the survey, a split household is defined as a new household in which (i) a member of the original household became the head of a new household, and (ii) the household resides in the same village. The above two conditions define split households in this study; household members who moved out of the original village or simply joined other households within the village are not called splits in the survey. From 2007 to 2010, 9.25% of the 2010 households were split households under the above definition. 12.97% of the sample individuals recorded as household members in 2007 migrated out, i.e., either moved out of their village or joined other households. The proportion is 11.82% once the group is restricted to those aged 20‐55 in 2007.

Anthropometry data were collected in both 2007 and 2010. Child’s height, weight, and his/her mother’s weight were measured in the field. In addition, birthweight was recorded from official sources. However, the age coverage differs between the two rounds. In the 2007 round, children aged 0 to 6 were covered, and the 2010 round extended the age range to cover children aged up to 12. Figures 3a and 3b plot heights and weights over the two rounds, respectively, to show their dynamics. Following the standard procedure, we calculated the height‐for‐age z scores for children aged 0 to 12 and the weight‐for‐age z scores for children aged 0 to 10. In the panel analysis, we use the
**Figure 1: Southern Africa’s rising working-age population share is expected to remain higher than that of Sub-Saharan Africa in coming decades, and will not peak for most countries before 2050**

Working-population share (percent) <!-- Start of picture text --> 70<br>Botswana<br>Lesotho<br>Namibia<br>South Africa<br>65 Swaziland<br>Sub-Saharan Africa<br>60<br>55<br>50<br>45<br>1950 60 70 80 90 2000 10 20 30 40 50<br><!-- End of picture text --> Source: Authors’ estimates Note: Data from UN (2015). The value for Sub-Saharan Africa is a weighted average. The working-age population is defined as people aged 15-64.

**Figure 2: Total dependency ratios in Southern Africa have declined much faster than the rest of Sub-Saharan Africa since the 1980s and are now below the regional average**

Total dependency ratio <!-- Start of picture text -->
1.1<br>Botswana<br>Lesotho<br>Namibia<br>1.0 South Africa<br>Swaziland<br>Sub-Saharan Africa<br>0.9<br>0.8<br>0.7<br>0.6<br>0.5<br>0.4<br>1950 60 70 80 90 2000 10 20 30 40 50<br><!-- End of picture text -->

Source: Authors’ estimates Note: Data from UN (2015). The value for Sub-Saharan Africa is a weighted average. The total dependency ratio is the ratio of the number of children (peopled aged less than 15 years) and aged (people aged over 64 years) to the number of people of working-age (15-64 years 6
to these elasticities, one need to know how climate will change in the future, what the GPD per capita (or income) trajectory would be in the absence of climate change, and how population will grow. In general, papers in this section differ with respect to how they estimate these elasticities and the type of information they use about future projections.

# **_2.1 Backward looking approach_**

A number of recent studies have opted for a ―backward looking‖ approach to analyze the effects of climate change on economic activity, and ultimately on poverty. These studies, mimicking the approach emphasized in the growth and development literatures, examine the relationship between climate and aggregate economic variables in cross-sections of countries or regions. One advantage offered by this approach is that by examining aggregate outcomes directly, it is possible to avoid relying on _a priori_ assumptions about which mechanisms to include in the climate-economy interactions and how these mechanisms might interact, and ultimately influence macroeconomic outcomes. Another advantage derived by the use of cross-sectional data is that they yield estimates of the long-relationship between climate and aggregate output taking into account historical adaptation.

One such study is by Dell et al. (2009) who use cross-sectional data from 134 countries to examine the effects of temperature on the level of GDP. Their output-climate elasticity estimate, based on historical data, reveals that each additional degree Celsius is associated with a statistically significant reduction of 8.9 percentage points of per capita GDP. The authors also provide evidence of this elasticity at the sub-national level by considering the temperatureincome relationship using data at the municipal level for twelve countries in the Latin America and Caribbean region. Remarkably, they find a negative relationship between income and temperature when looking within countries, and even when looking within states within countries.<sup>3</sup> However, they make no attempt to either simulate the impacts of the predicted temperature increase on income, or estimate its effect on poverty.

In a similar vein, Andersen and Verner (2010) examine the