rafmacalaba/datause-encoder-data huggingface dataset:
# D. Access policy framework index for Pakistan and comparators, 2015

||**India, AP I **|**ndia, Odisha **|**India, Raj **|**Pakistan **|<sup>**International**</sup><br>**benchmark**|
|---|---|---|---|---|---|
|**Regulation of New Connections**|**75%**|**66%**|**77%**|**48%**|**65%**|
|Roles of regulator,utility,rural electrification agencyclearlydefined|1.00|1.00|1.00|0.00|93%|
|Utilities have regulatoryobligation to connect new customers|1.00|1.00|1.00|0.00|94%|
|Regulatory entity has authority to approve connection charges for<br>new customers|1.00|1.00|1.00|0.00|71%|
|Connection charges are set usingshallow entry|0.00|0.00|0.00|NAP|58%|
|Governmentprovides subsidyfor new connections|1.00|1.00|1.00|1.00|53%|
|Connection has to beprovided in a specified time|1.00|1.00|1.00|1.00|94%|
|Regulatoryentitymonitors tiem taken toprovide new connections|NAV|0.00|1.00|1.00|44%|
|Regulator has authority to levy penalties for not connecting customers<br>on time|NAP|NAP|1.00|0.00|71%|
|Time taken toprovide connectionspubliclyavailable|0.00|0.00|0.00|0.00|24%|
|There are connection charges|1.00|1.00|1.00|1.00|94%|
|Customerpays limited connection charges|0.50|0.25|0.25|0.25|43%|
|Connection charge ispubliclyavailable|1.00|1.00|1.00|1.00|71%|
|**Regulation of solar home systems**|**100%**|**100%**|**100%**|**0%**|**66%**|
|Minimum technical standards and post-installation warranty<br>requirements for solar home systems|1.00|1.00|1.00|0.00|71%|
|Regulator reviews and approves prices of surplus SHS sales of<br>electricityto thegrid operator|1.00|1.00|1.00|0.00|62%|
|**Regulation of mini-grids**|**67%**|**67%**|**67%**|**0%**|**44%**|
|Privatelyowned mini-grids legallyallowed to operate|1.00|1.00|1.00|0.00|81%|
|Clear options for mini-grid operator when the interconnected grid<br>reaches the area,includingcompensation|0.00|0.00|0.00|0.00|7%|
|Subsidy or other mechanism to help mini-grid operators recover their<br>costs|1.00|1.00|1.00|0.00|47%|

# E. Corporate governance- accountability index for Pakistan and comparators, 2015

||**Oriss**|**a, India**|**AP, **|**India**|**Raj**|**, India**|**Pak**|**istan**|**International**|
|---|---|---|---|---|---|---|---|---|---|
|**Corporategovernance**|**WESCO**|**CESU**|**APSPDCL **|**APEPDCL **|**JVVNL**|**JDDVNL**|**LESCO**|**KE**|**benchmark**|
|**Accountability**|83%|25%|50%|50%|67%|67%|67%|100%|60%|
|Private orpublic shareholders appoint board|||||||||36%|
|Transparentprocess exists for Board selection|||||||||36%|
|Board members cannot be removed at will|||||||||29%|
|Chairperson & CEO are separatepositions|||||||||75%|
|Function of CompanySecretaryexists|||||||||82%|
|Board Sub-Committees for different issues|||||||||68%|
|Audit committee of the Board|||||||||71%|
|Board Code of Conduct exists|||||||||64%|
|Requirement to declare conflicts of interest|||||||||75%|
|Utility has carried out any third party<br>transactions in last fiveyrs|||||||||46%|
|Minorityshareholders' rights areprotected|||||||||39%|
|Utility publishes an Annual Report|||||||||93%|

Satisfactory result Unsatrifactory result NAP Not applicable NAV Not available 70
|-49-|
|---|

Preoaration ReRort, a report of the FAO/World Bamk Cooperative Programme, No. 107/87 CP-CMR 24 (2 vols). Rome: Food and Agriculture Organization.

|FORTMANN<br>1982|, L.<br>Women's Work in a Communal Setting: The Tanzanian Policy of<br>Ujamaa, in Bay ('.982).|
|---|---|
|FURGUSON<br>1985|, A. E. and N. HORN<br>Situating Agricultural<br>research in a Class and Gender Context: The<br>Bean/Cowpea Collaborative<br>Research Support Program, Culture and<br>AnthroR01gg'<br>(Spring): 1-10.|
|HENN, J.<br>1983a|K.<br>Feeding the Cities and Feeding the Peasants: What Role for<br>Africa's Women Farmers? World DeveloRment 11(12): 1043-1055.|
|HENN, J.<br>1983b|K.<br>Women in the Rural Economy: Past, Present and Future, in &frican<br>Women South of the Sahara. London: Longman.|
|HONADLE,<br>1985|C. H., and J. VANSANT<br>ImRlementation<br>for Sustainability:<br>Lessons from Integrated Rural<br>DeveloRment.<br>West Hartford, CT: Kumarian Press.|
|INSTITUT<br>1982|E DE RESEARCH AGRONOMIQUE (IRA)<br>Agro-Socio-Economic<br>Survey of Farmers in the North West Province.<br>Bambili, Cameroon: Institute for Agronomic Research.|
|JONES, C.<br>1981|C.<br>Women's Legal Access to Land, in Lewis (1981).|
|KABERRY,<br>1952|P.<br>Women of the Grassfields:<br>A Study of the Position of Women in<br>BameWda. British Cameroons. London: HMSO, Colonial Research<br>Publications.|
|KNUDSON,<br>1981|B. and B. A. YATES<br>The Economic Role of Women in Small Scale Agriculture in the<br>Eastern Caribbean: St. Lucia. Barbados: University of the West<br>Indies.|
|KOONS, A.<br>1988|<br>Reaching Rural Women in the Northwest Province: A Presentation<br>of<br>More Ways in Which Women are Not Men. mimeo.|
|LEONARD,<br>1986|D. K.<br>Putting the Farmer in Control: Building Agricultural Institutions,<br>in Berg and Whitaker (1986).|
|LEONARD,<br>1977|D.K.<br>Reachinf the Peasant Farmer: Organization<br>Theory and Practice in|
therefore employ a strategy that is a bit unusual, we check to see how the method behaves in other Caribbean markets. We apply the same techniques to data from three Caribbean island nations - DOM, JAM, and BHS - and calculate implied � _τJA_<sup>_k_’s for</sup> those countries’ imports from the U.S.<sup>36</sup> If our estimating strategy were to falsely attribute some unusual feature of exports from the Southeastern U.S. to the JA, we would expect to see the same pattern of � _τJA_<sup>_k_’s for at least one of these countries.As</sup> the bottom of Figure 1 shows, none of the three countries’ imports exhibit the same pattern we observe in PR. Relative to PR, the predicted distribution of implied � _τJA_<sup>_k_’s</sup> is compressed for all three countries. In DOM, PR’s nearest neighbor, the distribution of predicted JA tariff-equivalents is tightly compressed around zero, except for some air-shipped products with large negative _τ_ � _JA_<sup>_k_’s.TheestimatesforJAMare</sup> somewhat noisier, with no significant tendency for _τ_ � _JA_<sup>_k_’storisewithweight.The</sup> BHS estimates are noisier still, but the distribution remains compressed relative to PR, and the relationship of _τ_ � _JA_<sup>_k_’s to weight is negative rather than positive.These</sup> estimates all support the argument that the shipping characteristics’ effects on PR’s imports reflect consequences of the JA rather than some artifact of our procedures.

Our estimates of _τ_ � _JA,t_<sup>_k_returnvaluesforallfinalproducts,includingthosethat</sup> typically travel by air. Since the reference air-shipped product is at the median of the weight-to-value ratio for air-shipped products, our procedures predict positive values of _τ_ � _JA,t_<sup>_k_forroughlyhalfoftheproductsthatarriveinPRbyair.To</sup> avoid attributing positive JA trade costs to air-shipped goods, we multiply � _τJA,t_<sup>_k_by</sup> the product’s share of PR’s import value arriving from the U.S. by sea: _<u>τ</u>_<sup>_~~k~~_</sup> _JA,t_<sup>=</sup> _τ_ � _JA,t_<sup>_k×V shr_</sup> _JA,t_<sup>_k_,where</sup><sup>_V shr_</sup> _JA,t_<sup>_k_isthevalueshareofPR’sproduct</sup><sup>_k_imports</sup> arriving from the U.S. in an oceangoing vessel in year _t_ .<sup>37</sup> The values of _<u>τ</u>_<sup>_~~k~~_</sup> _JA,t_<sup>that</sup>

> 36We report tables with the associated coefficients for each country in Appendix A.

> 37Recall that the _V shrtk_<sup>used in the regressions comes from U.S. imports, not U.S.-PR flows.We</sup> include the subscript _JA_ here to indicate that we are using U.S.-PR flows in this adjustment.

31
Hemorrhage, pregnancy-induced hypertension (toxemia), sepsis, obstructed labor and abortion (spontaneous or induced) are the mai! direct caUSea of maternal death and cause most of the serious illnesses from which women survive. Unfortunately, few data are availabie to document the incidence and severity of morbidity in representative populations. Harrison's studies in Zaria, Northern Nigeria are an important exception - providing detailed inZormatio the patients seen in a large hospital (Harrison, 1985). Moreover, .. cal studies have verified the common observation that many serious c iolications occur for eve-v maternal death. Harrison (1987) estimates that taere are at least ten major complications for each maternal death. Bhatia (1985) reported more than sixteen cases of morbidity for each death in an Indian study.

Hemorrhage from all causes is more likely to .-zcur in older women with many children (Population Reports, 1984). By enabling women to have fewer children, family planning lowers the risk of this common and lifethreatening complication. Pregnancy-induced hypertension is least common among women in their twenties having their second and third child. Family planning prevents morbidity in this case by allowing couples to avoid pregnancy at the extremes of the reproductive cycle, and by allowing them to have fewer pregnancies. Sepsis is also more common in very young women and in older women with many children, so family planning can prevent this complication in the same way (Population Reports, 1984).

Women with unwanted pregnancies at any age frequently resort to primitive induced abortion with its high risk of infection, hemorrhage and death. Those who survive may have a permanent health impairment such as chronic pelvic inflammatory disease which may result in permanent infertility. Family planning can prevent many of these unwanted pregnancies.

Family planning obviously cannot prevent obstructed labor in a woman with a severely contracted pelvis, unless she avoids pregnancy altogether. But it can reduce the incidence of life-threatening complications of this sort.

Table 1 sets forth the interventions recommended for use at the primary and first referral levels, to reduce maternal mortality and morbidity in developing countries.

# Health Benefits of Fewer Children

Other things being equal, the woman who has two or three children is likely to enjoy better health than her counterpart who has seven or eight. This is even more likely to be the case for a poor woman in a developing country. The principal reason is that women work extremely hard in - developing countries in agriculture, raising livestock and small animals, carrying water, cooking, other domestic chores and childrearing. For many women in developing countries, this translates Into ar; exhausting day of 14-16 hours work. In general, more children means more work, more fatigue and less opportunity for rest and recreation. (More children usually means less opportunity for economic and other non-domestic roles that may increase a woman's income, education or both and thereby her health). But there is
_5_ market to speak of. Instead, there was a pervasive sense of "occupation rights" that continues to play an important role in people's attitudes towards housing in Russia. For many Russians, there are few incentives to privatize their housing.

# **The Structure of the Analysis**

In addition to this introduction and a final section that lays out the paper's broad conclusions and some policy prescriptions, this paper consists of two major sections devoted, in turn, to housing privatization and to developments in the housing market.

Section 1 presents an examination of housing privatization and the various factors that have influenced its course in the former Soviet Union. Although the focus of the section is on Russia, a brief, opening look at housing privatization in several other former Soviet republics provides a basis of comparison for the Russian experience. The bulk of Section 1 that deals with Russia treats first Moscow, where the most important factors influencing privatization (those related to the property itself, and to the demographic profiles of those privatizing) are examined in detail. After that, the privatization processes in two other Russian cities (Vladimir, an oblast center not far from Moscow, and Gorodets, a small town in Nizhny Novgorod oblast) are presented in a manner consistent with the analysis of the analogous processes in Moscow.

Section 2 presents findings related to the development of the housing market, a process intimately associated with but also distinct from privatization. It examines aspects of the primary and secondary markets for housing in Russia, and links the present situation in the housing market with households' housing needs and financial capabilities. Household motivations for changing housing are examined in the context of the choice between market and non-market methods (the latter, loosely, refers to vestiges of the old Soviet system of allocation of housing), and the demographic profiles are established of those households that prefer one or the other methods to solve their housing problems. Section 2 also presents results of potential sources of household financing for the purchase of housing (again, on the basis of findings of household surveys)-for example, willingness to take out a loan-and concludes with a look at trends in household mobility in Russia.
Research Components of Uorld Bank Education Projects, since 1982.

|Arnaitry<br>and Loan/Credi<br>Number|t<br>roved|<br>Research Components|Current Status of Studies, including<br>Completed Documents/Data|
|---|---|---|---|
|||(due March 1989) (pare. 3.15 p.11 Annex 3-13).||
|AFRICA Ethiopia CR 1873-ET|1988|Seventh Education . Pre-investment<br>studies to include:(i)<br>testing of rural health<br>training programs for medical students;|No information<br>supplied.<br>|
|||(ii)<br>establishment<br>of physicat property<br>maintenance system in higher education<br>(para. 3.29 p.27).||
|AFRICAEthiopia CR1520-ET|1985|Sixth Education. No research component.||
|AFRICAGhanaCR1744-GH|1987|Education Sector Adjustment.<br>No research<br>component.|Confirmed.|
|AFRICA Guinea-Bissau<br>CR 1914-GUB<br>|1988<br>I|Basic Education Development.<br>(i) Studies on prospects of private education<br>in Guinea-Bissau.|No information<br>available|
|AFRICA Guinea CR 1341-CUI|1983|Second Education. (i) Studies on Vocational<br>Training development;<br>(ii)<br>tracer stjdy of graduates of IPSs and<br>agro-zootechnic<br>faculties (para. 2.07 p.14).<br>(iii) Study to plan the development<br>of the<br>teacher training system (para. 2.16 p.17).<br>(iv) comprehensive<br>definition of future<br>sector strategy;|(i) and (ii): not received.<br>(iii): short proposals mude in framework of<br>preparation<br>of future projects;<br>(iv) ODeclaration<br>of Sector Policy" adopted by<br>Goverrnent in September 1989;<br>(v) two simutation studies by IREDU working out<br>cost implications<br>of the "PASE"|
|||(v) interim financing of adjustment<br>program.||
|AFRICA Kenya CR 1673-KE|1986|Sixth Education. No research component.||
|AFRICA Lesotho CR 1512-LSO<br>|1985<br>I|Fourth Education. Provisions for: (i) analysis<br>jof staff utilization<br>and facilities<br>at|<br>No information<br>for project (i).|

29
see Bamberger et al. (2006), Biemer and Lyberg (2003), and United Nations Statistical Division (2005).

Finally, although all the distributions in PovcalNet originate from household surveys, PovcalNet’s estimation do not always use this microdata directly. In cases where microdata are not available or when the World Bank has not been authorized to share these data publicly, PovcalNet uses grouped data (such as quintile or decile shares) and poverty is estimated using a parameterized Lorenz curve, following the computational procedures suggested by Datt (1998), applying methods suggested by Kakwani (1980) and Villasenor and Arnold (1989).<sup>25</sup> Although studies have found that such methods based on grouped data do fairly well at estimating poverty at low poverty lines, consistently and without bias, microdata is generally more accurate and ensures consistency with national data sources (Minoiu and Reddy, 2009). A strength of the current update is therefore that it relies on a much larger share of microdata for recent poverty estimates (after 1990) than previous versions of PovcalNet: grouped data is now used only for six of the 131 countries covered.<sup>26</sup>

# **_3.2 Inter-temporal price adjustments_**

Because prices can change rapidly, inter-temporal price deflators are essential for comparisons of real standards of living over time. Since official PPPs are only available for the benchmark years of the ICP, inter-temporal price deflators are necessary to adjust welfare measures for changes in prices between the survey year and the ICP benchmark year.<sup>27</sup> Similarly, to estimate an international poverty line based on national poverty lines, inter-temporal price

> 25 In cases where only grouped data is available, PovcalNet bases its poverty estimates on parameterized Beta Lorenz Curve or General Quadratic Lorenz Curve, proposed by Villasenor and Arnold (1989) and Kakwani (1980), respectively. Further details on the computational application and methods used in PovcalNet is documented in Datt (1998). The performance of the methods relative to microdata is reviewed in Minoiu and Reddy (2009).

> 26 The countries for which grouped data is used for the 2012 estimate are China, Iran, Maldives, Trinidad and Tobago, and St. Lucia.

> 27 Alternatively (and equivalently), the international poverty line can be converted to local currency in the ICP base year, and deflated by a temporal deflator to the survey year. The World Development Indicators (WDI) does provide extrapolated PPPs for private consumption using official CPIs, but these are not used in poverty measurement, in part due to the decision to use inter-temporal measures of price change that differ from the WDI CPIs for a selection of countries.

16
<!-- Start of picture text --> Figure 2. PSD focus in WBG financial operations in post-conflict countries<br>50<br>Sierra Leone (1999)<br>5<br>5 40<br>e2<br>Se Rwanda (1994)<br>oa<br>aE 39 5S SSS SSS SS SSS SSS SSS: SSS SSS SSS SSS=SS====<br>$3 Timor Leste (1999)<br>5aw Afghanistan (2001)<br><!-- End of picture text --> <!-- Start of picture text --> vo<br>a<br>£oe& 20 —_ se ati (2004)—<br>“3a<br>< 1 SF ee Sr ree eee ee CC<br>5S<br>0<br>0-3 4-6 7-9 0-3 46 7-9 0-3 46 7-9 03 4-6 0-3<br>Years elapsed since end of conflict<br>Source: World Bank Project Portal. Dates in brackets are for year when major conflict ended. See text for methological caveats.<br><!-- End of picture text -->
- [19] Harvey, A.C. (1989). _Forecasting, Structural Time Series Models and the Kalman Filter_ . Cambridge University Press.

- [20] IEA (2016). Extended World Energy Balances. IEA World Energy Statistics and Balances (database). DOI: http://dx.doi.org/10.1787/data-00513en (Accessed on 23 June 2016).

- [21] Inglesi, R. (2010). Aggregate Electricity Demand in South Africa: Conditional Forecasts to 2030. _Applied Energy_ , 87(1), 197-204.

- [22] Jamasb, T. (2006). Between the State and Market: Electricity Sector Reform in Developing Countries. _Utilities Policy_ , 14(1), 14-30.

- [23] Johansen, S. (1995). _Likelihood-Based Inference in Cointegrated Vector Autoregressive Models_ . Oxford University Press.

- [24] Joseph, K. L. (2010). The Politics of Power: Electricity Reform in India. _Energy Policy_ , 38(1), 503-511.

- [25] Joutz, F. L., Maddala, G. S., and Trost, R. P. (1995). An Integrated Bayesian Vector Auto Regression and Error Correction Model for Forecasting Electricity Consumption and Prices. _Journal of Forecasting_ , 14(3), 287-310.

- [26] Luger, R. (2004). Exact Tests of Equal Forecast Accuracy with an Application to the Term Structure of Interest Rates. _Bank of Canada Working Paper 2004-2._

- [27] Lütkepohl, H. (2005). _New Introduction to Multiple Time Series Analysis_ . Springer.

- [28] Makridakis, S., Andersen, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R., Newton, J., Parzen, E., and Winkler, R. (1982). The Accuracy of Extrapolation (Time Series) Methods: Results of a Forecasting Competition. _Journal of Forecasting_ , 1(2), 111-153.

- [29] Makridakis, S., Chatfield, C., Hibon, M., Lawrence, M., Mills, T., Ord, K., and Simmons, L. F. (1993). The M2-competition: A Real-time Judgmentally Based Forecasting Study. _International Journal of Forecasting_ , 9(1), 5-22.

19
<!-- Start of picture text --> Shareholders' Meeting<br>(supreme authority)<br>Administration Supervisory Board<br>Expert Team Expert Team ~~~~~~(executive The Boardboard)<br>Legal Department Legal Department _ Chairman of ~~~~~the Board _ Uzeftepsispetsia"(Iteral Audit)<br>Central<br>GeoyDepartment on<br>Production f<br>and Operations<br>. Deputy Chairman<br>I st Deputy Chairman (Economics) DepDrn<br>Director General of JSC _ l _ Dpuy_<br>"Uzgeoneftegasdobycha" .D/rucpartment s an oD Chairman<br>finance aed "Uzoefaegas-<br>mes artment of organisationoflabour ishchitaminot<br>.oil and gas JSC_CetaI . _ Departmnent of<br>extraccutn "Uzgeonefte a Acouspersonell avd<br>gas processing gasdobycha" Unit lsca eeomn oil and gas industry |<br>Deparement ofen<br>l Geology, l JSC l | Departmnent ofi<br>Deprtet oft |and drilling o e neeppro "Uzbumeftegas DepartFergmaeoil o securitiesand college<br>|technolog<br>oil refining construction of gas JoPd and<br>iDeputy | Chairman & I .LI I JSC l l IDeputy Chairman Coml { | iu JSC "Uznefte-u eatet||operational departmnent |<br>IFi"Uzr1efOeproduct" prg niti Ch rt ofIU gasstrog<br>I Department ofll SC | technical progress and OVES I is<br>marketing and sales | 7 "Uzneflegasmash" |||relations with foreign Hz"zvnesh-ssvaUPT "<br>Department of I I countries nelgs "U feasvz<br>material i SC l l ieateto OAOi<br>and teclhnical l l l Uztrasgas" nesmn "U7zNIPlneflegas"<br>l l ~~~service i SC I lI Dorme<br>Ll Department of § | | ~~"Umieftepererabotka" DprmnonEdiatonial House |<br>| oil refining } 1 IT | M ~~~~~~~~~~~~~~construction of gas Journale<br>l l | ~~~~~~~~~Shurtan Comiplex I<br><!-- End of picture text -->

Figure i: Organizational Chart **of** Uzbekneftegaz
# **1. Introduction**

People migrate to improve their well-being, whether through an expansion of economic and social opportunities or a reduction in persecution. Yet, a large literature suggests that migration can be a very stressful process, with potentially negative impacts on mental health. To the extent that these mental health changes reduce the net benefits of migration they are of potential interest to economists, especially because there are strong economic arguments for increasing international migration (World Bank, 2005).

To truly understand the effect of migration on mental health one must compare the mental health of migrants to what their mental health would have been had they stayed in their home country. The existing literature is not able to do this and typically settles for comparing the mental health of migrants to that of natives in the destination country, which takes no account of any preexisting differences between these groups. Even where comparisons are made between movers and stayers from the same country (e.g., Ödegaard, 1932), they have not been able to take account of potential selection biases. These biases will occur if unobserved characteristics that increase the propensity to migrate are also associated with either higher or lower risks of mental health disorders.

This paper overcomes the selection problems affecting previous studies of the effect of migration on mental health by examining a migrant lottery program. The Pacific Access Category (PAC) under New Zealand’s immigration policy allows an annual quota of Tongans to migrate to New Zealand in addition to those approved through other migration categories as skilled migrants and family streams. Many more applications are received than the quota allows, so a lottery is used by the New Zealand Department of Labour to randomly select from amongst the registrations. A unique survey conducted by the authors in these two countries allows experimental estimates of the mental health effects of migration to be obtained by comparing the mental health of migrants who were successful applicants in the lottery to the mental health of those who applied to migrate under the quota, but whose names were not drawn.

The results show large positive effects of migration on mental health, especially for women and for individuals with low mental health. Thus, rather than there being a mental health cost 2