rafmacalaba/datause-encoder-data huggingface dataset:
these debates, the issue of capital flight has been overlooked. Yet, without curbing capital flight, African countries will not be able to mobilize enough domestic resources and retain external resources to finance high levels of investment. Most importantly, flight capital and other forms of stolen funds held abroad constitute a source of substantial untapped resources that could contribute to boosting domestic investment. Thus African countries need to design strategies to repatriate flight capital, as an integral part of the national agenda for resource mobilization as a means of accelerating economic growth.

**Figure 3: Domestic investment in SSA and other developing regions – with effects of capital flight repatriation**

<!-- Start of picture text --> 30<br>20<br>10<br>0<br>SSA+ Low S.<br>SSA EA&P LAC MENA<br>25% Inc. Asia<br>GDI/GDP 18.9 29.6 21.1 24.2 23 19.4 27.4<br><!-- End of picture text --> Source: World Bank, World Development Indicators. Note: SSA + 25% = Gross domestic investment achieved following repatriation of 25 percent of the stock of capital flight.

Another important channel of growth effects of flight capital repatriation is through accelerated human capital accumulation arising from higher funding for education. Given the low levels of government revenue and the myriad competing needs for economic development, funding for education has been low in most African countries. The response has been generally to seek more assistance from international development partners in the form of aid and debt relief. Capital flight repatriation constitutes a major untapped source for boosting expenditures on education in order to bridge the skills gap that constitutes a critical constraint to private sector development and limits international competitiveness for African countries.

To provide an illustration of the potential gains from capital repatriation in terms of human capital investment, we assume that repatriation of capital flight benefits the country by allowing the government to increase expenditure on education. While some of the repatriated capital consists of stolen funds that would go directly into the government budget, a substantial fraction of capital fight is made of private assets earned legally but held abroad illegally in the sense that they were smuggled abroad or/and their owners do not pay tax on the assets. With regard to human capital investment, the repatriation of these private assets will generate benefits through tax revenue, which in turn will be used to finance education.

**16**
# 1. INTRODUCTION

Although the potential benefits of industrial pollution control are clear in many developing countries, policy makers continue to worry about the costs. It has been difficult to address this concern explicitly, because little empirical evidence has been available. In addition, information about abatement costs would be extremely useful for the design of cost-effective regulation. In this paper, we use a new plant-level database to produce such infornation for China. We estimate a joint abatement cost function for major water pollutants, and use the results to evaluate the economic efficiency of current regulation. We also use the econometric results to simulate the impact of an emissions charge system.

The paper is organized as follows. Section 2 provides an introduction to industrial pollution control issues in China. Section 3 uses the new dataset to develop measures of abatement and compliance for our sample of factories. In Sections 4 and 5, we specify and estimate an econometric model of abatement costs which is appropriate for simultaneous control of several pollutants. Section 6 discusses the policy implications of our results, while Section 7 summarizes the paper.

# 2. INDUSTRL4L POLLUTION CONTROL IN CHINA

Industrial air and water pollution in China have been major concerns for the past two decades. A recent assessment by the Chinese Research Academy of Environmenital Sciences (CRAES) has identified industrial pollution as the source of approximately 70% of China's total environmental pollution. Current estimates of human health damage from urban air pollution are very high for some areas.' Such high levels of damage are primarily due to the rapid growth of pollution-intensive industries, not to lack of effort by China's environmental regulators. Indeed, the pollution control program of China's National Environmental Protection Agency (NEPA) and the provincial Environmental Protection Bureaus (EPBs) is probably the most extensive in the developing world. According to CRAES (1994), pollution abatement in the past decade has been sufficient to maintain at least constant levels of industrial waste water discharge and flue dust emission from coal combustion. Total estimated emissions of suspended particulates have dropped from 13.5 million tons to 5.8 million tons. At the same time, industrial output has approximately quadrupled. The pollution intensity of output in certain key emissions categories has dropped sharply since 1985, at least in factories which are regulated by the environmental agencies.'

> ' See CRAES (1994), X. Xu (1994), and Z. Xu (1995).

2 One cautionary note is warranted here: regulatory coverage is bv no means universal. It seems to be particularly sparse for Township and Village Enterprises. the fastest-growing ownership class.

I
- shall assist the Medical Officer of Health/District Health Officer in carrying out School Medical Inspections and carry out medical inspections himself when directed to do so.

- shall carry out immunizations and worm treatment in schools.

# **_<u>Occupational Health</u>_** <u>(including Estate Health)</u>

- shall inspect all factories and work-sites in his area, identify health hazards, and advise on remedial measures;

- shall inspect all estates in his area, advise on environmental sanitation and the control of communicable diseases.

**_<u>Disasters and Epidemics:</u>_** Shall organize and supervise health activities related to environmental sanitation and prevention of communicable diseases during disasters and epidemics.

**_<u>Records and Reports:</u>_** Shall maintain records and submit reports per departmental instructions. **_<u>Health Education:</u>_** Shall plan and implement a programme of health education in his area and ensure community participation in health activities.

# **_<u>Team work</u>_**

- shall work and maintain cordial relations with the public health nursing sister and public health midwife of the area as a member of the health team.

- shall carry out any other duties assigned to him by his superior officer.

<u>Source: Sri Lanka Ministry of Health, Public Health Inspector’s Training Program, Kalutara, also</u> cited in Dalpatadu et al (2008).

20
**Table 4: School Construction and Child Socio-Emotional Difficulties (SDQ): Difference-in-differences estimates.**

||1966-1970|Maternal Cohort|Differe|nce in Dif|ferences|
|---|---|---|---|---|---|
||High INPRES|High-Low INPRES||||
||Mean|Gap||||
||||[1]|[2]|[3]|
|Prosocial behavior score (reversed) [z-score]|0.06|0.32|-0.17|-0.184|-0.183|
||||(0.071)|(0.071)|(0.071)|
||||[0.092]|[0.048]|[0.072]|
|spaceChild in top quartile of age-specifc prosocial diffculty dist. (%)|39.9|14.1|-4.746|-5.155|-5.132|
||||(3.205)|(3.131)|(3.121)|
||||[0.256]|[0.208]|[0.228]|
|Internalizing score (emotional and peer problems) [z-score]|-0.09|-0.19|0.013|0.015|0.016|
||||(0.106)|(0.107)|(0.106)|
||||[0.904]|[0.916]|[0.928]|
|spaceChild in top quartile of age-specifc internalizing diffculty dist. (%)|28.7|-8.9|-1.138|-0.98|-0.915|
||||(5.125)|(5.093)|(5.013)|
||||[0.820]|[0.868]|[0.868]|
|Externalizing score (behavioral and hyperactivity) [z-score]|-0.10|-0.20|-0.037|-0.055|-0.054|
||||(0.091)|(0.085)|(0.085)|
||||[0.692]|[0.532]|[0.520]|
|spaceChild in top quartile of age-specifc externalizing diffculty dist. (%)|30.5|-7.5|-0.778|-1.51|-1.512|
||||(4.807)|(4.371)|(4.433)|
||||[0.920]|[0.732]|[0.756]|
|_Controls (D-in-D’s)_||||||
|Caregiver district and year of birth FE’s|||YES|YES|YES|
|Treated cohort interaction with # school-aged children in 1973 (ln scale)|||NO|YES|YES|
|Child gender|||YES|YES|YES|
|Child-age FE’s|||YES|YES|NO|
|Child’s age(linearly,in months)|||NO|NO|YES|

Notes: Sample is 2,118 children. Standard-errors in parentheses are clustered at the district of maternal birth. Wild-bootstrap significance p-values in brackets.
**Table 8: Drought Impacts on Child Height-Age Z-Score* 100 by Country and Wealth Status OLS with Province  and Year of Survey Fixed Effects and Full Set of Controls**

||**Hei**|**ght-Age Z-Score***|**100(OLS with**|**Province and**|**Survey Year**|**FE)**|
|---|---|---|---|---|---|---|
||**All**|**Mozambique**|**Malawi**|**Zimbabwe**|**Tanzania**|**Zambia**|
|||**_Lowe_**|**_st(Poorest) W_**|**_ealthQuintile_**|||
|Drought: Birth Season|-19.62***|-46.55***|-1.27|-28.23***|-11.33|-25.00***|
||[-4.63]|[-3.33]|[-0.13]|[-2.71]|[-1.54]|[-3.18]|
|Drought: Season after Birth|-13.06***|-28.49**|-24.93***|-16.91|-17.60***|-0.81|
||[-3.32]|[-2.03]|[-2.67]|[-1.61]|[-2.64]|[-0.10]|
|Observations|11,605|1,517|1,941|2,179|3,302|2,666|
|||**_Secon_**|**_d and Third W_**|**_ealthQuintile_**|**_s_**||
|Drought: Birth Season|-10.92***|-29.02***|6.07|-28.42***|5.05|-28.70***|
||[-3.46]|[-3.50]|[0.95]|[-3.59]|[0.90]|[-3.97]|
|Drought: Season after Birth|-6.72**|7.66|-18.96***|-3.80|1.40|-23.08***|
||[-1.96]|[0.58]|[-3.06]|[-0.54]|[0.23]|[-3.26]|
|Observations|20895|3238|4097|3282|6328|3950|
||,|, <br>**_Fourt_**|, <br>**_h and Richest_**|, <br>**_WealthQuintil_**|, <br>**_e_**|,|
|Drought: Birth Season|0.42|4.15|12.55*|-35.32**|-2.92|2.72|
||[0.08]|[0.25]|[1.72]|[-2.32]|[-0.32]|[0.15]|
|Drought: Season after Birth|-14.40***|-17.93|-15.38*|-6.48|-11.66|-35.52*|
||[-2.76]|[-1.02]|[-1.91]|[-0.44]|[-1.22]|[-1.80]|
|Observations|8,317|1,601|2,338|877|2,859|642|
|||**_Full_**|**_Sample: All W_**|**_ealthQuintiles_**|||
|Drought: Birth Season|-10.73***|-31.29***|6.62|-29.02***|-0.75|-27.75***|
||[-4.22]|[-4.09]|[1.49]|[-5.28]|[-0.18]|[-5.54]|
|Drought: Season after Birth|-9.08***|-6.59|-19.23***|-7.31|-6.39|-18.34***|
||[-3.50]|[-0.70]|[-4.31]|[-1.33]|[-1.46]|[-3.38]|
|Observations|40,817|6,356|8,376|6,338|12,489|7,258|

Notes: *** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are clustered at the DHS cluster level. This table uses the same specification as Table 7, except the dependent variable is the height-age Z-score.

31
<!-- Start of picture text --> ©<br>‘<br>be} ws ee<br>°<br>1975 1980 1985 1990 1995 2000 2005 2010<br>birth year<br>--------- 95% Cl <= share of male births<br>2008 NDHS. Survey weights used. All births from women's fertility histories.<br><!-- End of picture text --> <!-- Start of picture text --> © Ny<br>ane ne —_—<br>$<br>1965 1970 1975 1980 1985 1990 1995 2000 2005 2010<br>birth year<br>mooreo-= 95% Cl —————= 1990 ~amme 1999 ===e== 2003 ———= 2008<br>NDHS 1990, 99, 03, 08. Survey weights used. All births from women's fertility histories.<br><!-- End of picture text -->
of countries can be used to calibrate macroeconomic models for example, but should not be used for econometric analyses. Finally, most attention should be paid to the data for the imputed cells. Aggregating bilateral corridors by origin, destination or region should not pose problems. However, it is clearly not appropriate to use those imputed bilateral data in a gravity model since they are estimated using a gravity model of migration in the first place. Relatedly, and as it is always the case during empirical work, users need take seriously the issue of measurement error. Although our primary raw data comprise the majority of worldwide migrant stocks, imprecision no doubt exists for those cells for which we impute data and is likely to be more severe for smaller corridors. Such imprecision needs to be taken into account when these imputed numbers are included directly in an estimation.

# **7 References**

Anderson, J., (2011): The Gravity Model. Annual Review of Economics, 3 (1), pages 133-160. Artuc, E., (2013): PPML estimation of dynamic discrete choice models with aggregate shocks. World Bank Policy Research Working Paper no. 6480, World Bank, Washington, DC.

Artuc, E., S. Chaudhuri and J. McLaren (2010): Trade Shocks and Labor Adjustment: A Structural Empirical Approach. American Economic Review, 100 (3), pages 1008-1045.

Barro, R.J. and J-W. Lee (2001): International Data on Educational Attainment: Updates and Implications. Oxford Economic Papers, 53 (3), pages 541-63.

Beine, M., F. Docquier and C. Ozden (2011): Diasporas. Journal of Development Eco42
significant increase in the range of the distribution and the sizable difference between the median and mode of the distribution of urban household per capita expenditure, and much higher coefficient of variation in the latter round.<sup>13</sup>

**Table 1: Empirical distribution characteristics**

|||**_1994_**|||**_1998_**||
|---|---|---|---|---|---|---|
|_Statistics_<br>(000)|_Urban_|_Rural_|_National_|_Urban_|_Rural_|_National_|
|**Mean**|219.9|64.4|94.6|303.1|94.4|141.5|
|Median|129.7|40.4|53.8|168.7|63.7|79.4|
|Mode|32.7|27.0|27.0|40.6|45.6|45.6|
|SDV|2938.6|1242.5|2075.5|68677.5|17062.5|42071.2|
|CV|1.4|1.93|2.2|22.66|18.1|29.74|
|Range|5853.5|1633.9|5861.1|15310.4|2764.9|15321.8|

Sources: Authors' calculations (based on household Priority Surveys).

# **lII. Concepts and Estimation procedures**

To assess the dynamics of poverty, we use the Foster-Greer-Thorbecke (FGT, 1984) class of poverty indices- which has the attractive attribute of being additively decomposable. The Gini index is used to assess the dynamics of income inequality. Although not additively decomposable, this measure is more sensitive to changes around the median of the distribution of income where the bulk of the poor is concentrated.<sup>t4</sup> To specify these measures, let _Y_ be the real per capita household expenditure corrected for regional variations in the cost of living and inflation over the sample period. Suppose that individuals and household members are ranked according to their expenditure, producing the following rank order: where z is the poverty line, _n_ is the total population and q is the number of poor. Further, assuming that household weighted coefficients are represented by wi, then the welfare indices are estimated from the following equation:

> 13 Note that the coefficient of variation is a much better measure of spread for distributions of income which have large means.

> 14 One could have selected the Theil index which is sensitive to changes in the top of the distribution to reflect large income variance and occurrence of large observations in the extreme tails; however, this measure, while capturing the income variance effect, fails to fully account for the poverty effect at the lower end of income distributions.

_5_
# **5 The Millennium Village Project’s Currently Planned Impact Evaluation Design**

The evidence in the previous section illustrates that the mid-term MVP evaluation report cannot provide good estimates of the effects of the program’s effects. In this section we consider whether the future stages of the MVP evaluation will produce rigorous impact estimates. Any impact evaluation of the project must assess the degree to which it has achieved or is likely to achieve its stated goal. The goal of the MVP is that of “providing immediate evidence that, by empowering communities with basic necessities and adequate resources, people in the poorest regions of rural Africa can lift themselves out of extreme poverty in five years’ time and meet the Millennium Development Goals by 2015” (MVP 2010a).

Five years after the first Millennium Village intervention began, the project released details of its plans for evaluation of the project’s effects.<sup>17</sup> The study protocol (MVP 2009) calls for assessing child mortality as the primary indicator for the program and also details a number of secondary indicators. The core of the evaluation is a program of data collection in one comparison village cluster for each of 10 MV sites (the protocol excludes the Sauri, Kenya and Koraro, Ethiopia sites from the evaluation plan).<sup>18</sup> The protocol mentions only briefly the mid-term evaluation report (MVP 2010c) described in Section 4, stating that “[i]nterim analyses post year 3 collection will be conducted to assess changes from baseline at MVP sites, as well as to compare levels of primary and secondary outcomes between matched intervention and comparison villages.” The mid-term report includes a subset of indicators specified in the protocol, along with additional indicators, and does not present all indicators for all sites.<sup>19,20</sup>

> 17 Millennium interventions began in Sauri, Kenya in late 2004.  The study protocol document was registered with the ClinicalTrials.gov registry site in May 2010.

> 18 What we describe here is the section of the protocol related to evaluation of program effects. Separate sections of the protocol not discussed here describe a process evaluation and measurement of the program’s costs.

> 19 The protocol lists 10 sites for the evaluation and excludes the sites established in 2005: Sauri, Kenya and Koraro, Ethiopia. Sauri is, however, included in the mid-term evaluation report, along with four of the sites listed in the protocol. According to the calendar in both the protocol and the evaluation report, interim assessments for 4 other sites should have been completed by the first half of 2010.

18
Violence in the United States.” _Journal of Family Violence_ 33 (4): 239–49. https://doi.org/10.1007/s10896-018-9954-7.

IRB (Immigration and Refugee Board of Canada). 2017. “Brazil: Domestic Violence, Including Legislation, Recourse and Support Services Available to Victims (2014– January 2017).” Document 1036584 (January 20), Research Directorate, IRB, Ottawa. https://www.refworld.org/docid/589440134.html.

- Kendall, Tamil. 2020. “A Synthesis of Evidence on the Collection and Use of Administrative Data on Violence against Women.” Background Paper (January), UN Women, New York.

- Kotsadam, Andreas, and Espen Villanger. 2020. “Jobs and Intimate Partner Violence: Evidence from a Field Experiment in Ethiopia.” CESifo Working Paper 8108, Munich Society for the Promotion of Economic Research, Center for Economic Studies, Ludwig Maximilian University and Ifo Institute for Economic Research, Munich.

- Litwin, Ashley, Elizaveta Perova, and Sarah Anne Reynolds. 2019. “A Conditional Cash Transfer and Women’s Empowerment: Does Bolsa Família Influence Intimate Partner Violence?” _Social Science and Medicine_ 238 (October): 112462. https://doi.org/10.1016/j.socscimed.2019.112462.

- Macmillan, Ross, and Rosemary Gartner. 1999. “When She Brings Home the Bacon: Labor-Force Participation and the Risk of Spousal Violence against Women.” _Journal of Marriage and Family_ 61 (4): 947–58. https://doi.org/10.2307/354015.

- Manser, Marilyn, and Murray Brown. 1980. “Marriage and Household Decision-Making:

- A Bargaining Analysis.” _International Economic Review_ 21 (1): 31–44. https://doi.org/10.2307/2526238.

- Mele, Marie. 2009. “The Time Course of Repeat Intimate Partner Violence.” _Journal of Family Violence_ 24 (8): 619–24. https://doi.org/10.1007/s10896-009-9260-5.

- Ministry of Health (Ministério da Saúde, Brazil). 2016. _Viva: Instrutivo Notificação de Violência Interpessoal e Autoprovocada_ , 2nd ed. Brasília: Departamento de Vigilância de Doenças e Agravos Não Transmissíveis e Promoção da Saúde, Ministério da Saúde. http://bvsms.saude.gov.br/bvs/publicacoes/viva_instrutivo_violencia_interpessoa l_autoprovocada_2ed.pdf.

Munyo, Ignacio, and Martín Antonio Rossi. 2015. “The Effects of Real Exchange Rate Fluctuations on the Gender Wage Gap and Domestic Violence in Uruguay.” IDB 23
-17-

otherwise, all other generally applicable taxes and payments not so expressly named therein. This should include that:

- (a) rightsholders under PAs will pay applicable taxes on profits (Ig revenues) from petroleum operations"'. This may be either a specific petroleum profits tax (including additional profits tax [APT], as applicable) or the generally applicable profits tax rate;

- (b) under a PA which is a PSC, the rightsholder may comply with its obligation in (a), above, by having its tax liability borne by the State partner on its behalf. This wil be reflected in the production splits available to each party'<sup>5</sup> ;

- (e) under a non-PSC PA, a royalty (ceiling and floor may be set in the PL) will be payable (as set from time-to-time by Regs, consitent with the PL, or as negodiated in the PA)<sup>1</sup> ';

- (d) other payments, such as annual rentals, contract adin on fees, sigature and/or production bonuses may also be payable (as may be negotiated in the PA), as well as any import and export taxes; and

In the new Stats of the FSU, this has been a prevalent problem from the outset, creting a signifcant disincntive to desired foreign investment In the sector. Under various tasks of the Technical Coopeton Program and the ensuing petrobum nding program, considerable progress has been made on this tax policy materin both Russia and K khstn.

is .The rightshoklers progressive production shars will be signiftcantly ower, being not of taxs to the host Stow. For the purposes dofthe forebn tax credit for US and UK-based rhtholders, It s equally importan **t** hat production **shares** received on a "deemed taxpaid basis" include a transparent mechanism by which the applicable tax incesent Is ackmlly and demonsably remiltd to the host State's tax authorities.

16 . Despite a minority "hybrid" practice to the contray (e.g. as was Iintialiy proposeld In Loan No. 2152 ZN), the majority practice Is not to have a royalty payable In a PSC PA armngeenL
1-a

# CPI Y'FLAT:'C AND INFLAT:CN 7REND ARGENTLNA

<!-- Start of picture text --> 2~~~~~~~~~~~~~~~~ - 5i<br>70<br>X 60<br>' 50<br>.<br>.- 4.0<br>20 17 EM .<br>+o~~~LAT lol| .<br>0<br>1982 1983 19841 1985 1986 1987 1988 1989<br><!-- End of picture text -->

SOURCE: [5CICACORES CZ COTU'ITURA <!-- Start of picture text --> G b)<br>BRAz:L<br><!-- End of picture text --> <!-- Start of picture text --> 60.<br>50 _<br>4.0<br>3 0<br>20<br>K<br>10<br>-- 0 __ _ __ _<br>1982 1983 198+ 1985 1986 1987 1988 1989<br>SOURCZ: CORJUNTURA ECONOMIC.A<br><!-- End of picture text --> NOTI: INTVATTON TREND - CPI(t)/[CPI(t-12i 41/12)-I)