rafmacalaba/datause-encoder-data huggingface dataset:
favorably with the previous situation in which water providers were unable even to cover operating costs, and is mainly the result of subsidy targeting and setting limits<sup>on</sup> subsidized consumption.

**Table 1: Water consumption subsidy: beneficiaries and subsidy amounts in 1998**

||Beneficiary users<br>|<br>|Subsidy<br>||**Expenditure as a**<br> <br> <br>|
|---|---|---|---|---|---|
|Region|Number|% of population|Average amou<br>Ch$|nt in % of bill|%<br>of<br>family<br>income (%)|
|I|19,096|21.1|7,247|73<br>82|2.9<br>2.9|
|II|25,051|24.6|8,257|80<br>_75_|2.8<br>3.2|
|III|17,147|30.5<br>____________|6,172<br>______|70<br>~ ~75|4.0<br>7.5|
|Iv|21,902|18.4|4,209|60<br>62<br>62|5.5<br>6.4<br>6.7|
|v|63,034|19.1|2,927|60<br>65<br>60<br>60<br>60<br>75|4.3<br>3.6<br>4.4<br>4.2<br>3.8<br>4.7|
|VI|17,681|15.5|2,740|60<br>60|6.0<br>4.8|
|VIl|27,706|21.4|3,427|60<br>64<br>72|6.7<br>7.3<br>_5.8_|
|vIII|63,925|22.0|3268<br>________ ____|60<br>___<br>65|5.7<br>6.2|
|IX|35,816|31.9|4,236|60<br>72<br>60|9.5<br>11.9<br>12.0|
|x|25,883|24.6|3,731|65<br>65<br>_75_|7.8<br>_5.5_<br>5.9|
|xi|6,002|35.2|5,389|80<br>75|_5.4_<br>3.8|
|XII|6,255|18.1|3,759|60<br>60|4.7<br>4.7|
|Metropolitan|103,001<br>1|10.4<br>1|1,970|50<br>1~~<br>~|3.6<br>~~~~~~~~~~~50<br>I2.9|
|**PAIS**<br>|432,499<br>|17.4|||_5.5_|
|**Source: Bl**|**anlot (1999)**|||||

Although the subsidy program has been improved over time, the goal of no family spending more than 5% of its income on water and sanitation services has not yet been achieved. At the aggregate level, the target has almost been reached: the after-subsidy bill for 15m<sup>3</sup> 12
# **TABLE 7**

||Residential<br>Conn.per<br>Employee|Energy Sold<br>per<br>Employee|Distribut.<br>Losses|Coverage|Energy Sold<br>per Conn.|Duration<br>of<br>interrupt's|Frequency<br>of<br>interrupt's|OPEX per<br>Connection<br>(in dollars)|OPEX per<br>MWH sold<br>(in dollars)|Avg Resid.<br>Tariff<br>(in dollars)|Avg Indust.<br>Tariff<br>(in dollars)|Cost<br>Recovery<br>Ratio|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|Dummy Transition of|0.124***|0.159***|0.045***|-0.012***|0.054***|-0.010|0.031|-0.269|-0.293|0.041**|0.070***|-0.006|
|PSP|(0.012)|(0.014)|(0.013)|(0.003)|(0.005)|(0.033)|(0.038)|(0.225)|(0.227)|(0.018)|(0.022)|(0.060)|
|Dummy Post Transition|0.062***|0.030***|-0.118***|0.001|-0.007|-0.276***|-0.332***|-0.213***|-0.179***|0.019|-0.027|0.194***|
|of PSP|(0.009)|(0.011)|(0.012)|(0.002)|(0.005)|(0.024)|(0.023)|(0.036)|(0.044)|(0.012)|(0.021)|(0.050)|
|Regulatory Governace|0.236***|0.226***|-0.077***|0.005*|-0.029***|-0.274***|-0.248***|-0.495***|-0.373***|0.154***|-0.074***|0.150***|
|Index (ERGI)|(0.013)|(0.016)|(0.013)|(0.003)|(0.007)|(0.036)|(0.038)|(0.069)|(0.076)|(0.021)|(0.028)|(0.042)|
|Utility FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Utility Specific<br>Time trend|Yes|Yes|No|Yes|No|No|No|No|No|No|No|No|
|Observations|1859|1840|1983|1247|2337|1030|924|841|850|1655|831|660|
|Number of utilities|181|180|175|137|195|139|127|126|126|159|85|98|

Standard errors in parentheses

* significant at 10%; ** significant at 5%; *** significant at 1%

- 21 -
Figure 5: Validation with SICONFI data - payment <!-- Start of picture text --> CE MG<br>1500<br>600<br>1000<br>400<br>200 500<br>0 0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25> <-25 -20 -15 -10 -5 0 5 10 15 20 25><br>PB PE<br>300<br>1500<br>200<br>1000<br>500 100<br>0 0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25> <-25 -20 -15 -10 -5 0 5 10 15 20 25><br>PR RS<br>600<br>1000<br>400<br>500<br>200<br>0 0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25> <-25 -20 -15 -10 -5 0 5 10 15 20 25><br>SP % difference from SICONFI data<br>6000<br>4000<br>2000<br>0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25><br>% difference from SICONFI data<br>Frequency<br>Frequency<br>Frequency<br>Frequency<br><!-- End of picture text -->

**Notes:** This figure presents the percentage deviation in total amount of budget payments, at the municipality-year level, between our dataset and SICONFI, the public finance dataset of the Brazilian Treasury. Values are positive whenever the total amount in our dataset, aggregated from individual payments, is larger than that of SICONFI. See Table 1 for more details on our data coverage. We truncate observations at -25% to the left and at 25% to the right.

25
# Table 5. EFFECT OF IE ON GAP UP TO MIDTERM

|||DID|-OLS|||DI|D-RE|||DID|-FE||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**T (quarters with IE==1)**|-0.056***|-0.045***|-0.056***|-0.045***|-0.073***|-0.045|-0.073***|-0.045|-0.078***|-0.051*|-0.078***|-0.051*|
||(-4.86)|(-2.85)|(-4.83)|(-2.86)|(-3.15)|(-1.62)|(-3.16)|(-1.62)|(-3.07)|(-1.79)|(-3.08)|(-1.78)|
|**D (project with IE==1)**|-0.0069|0.035**|-0.0069|0.035**|0.0081|0.035|0.0081|0.035|||||
||(-0.83)|(2.09)|(-0.83)|(2.07)|(0.43)|(1.34)|(0.44)|(1.33)|||||
|**_TTL switch dummies_**|Y|N|Y|N|Y|N|Y|N|Y|N|Y|N|
|**_TTL UPI dummies_**|N|Y|N|Y|N|Y|N|Y|N|Y|N|Y|
|**_Polynomial of sector averages_**|N|N|Y|Y|N|N|Y|Y|N|N|Y|Y|
|**_Observations_**|7918|7918|7918|7918|7918|7918|7918|7920|7918|7918|7921|7918|
|**_Outcome mean_**|0.144|0.144|0.144|0.144|0.144|0.144|0.144|0.144|0.144|0.144|0.144|0.144|
|**_Effect in %_**|38.9%|31.3%|38.9%|31.3%|50.7%|31.3%|50.7%|31.3%|54.2%|35.4%|54.2%|35.4%|

_Note:_ Standard errors are clustered (sector and quarter level). T-stats are in parenthesis. All specifications include fixed effects for quarters of project life cycle, sector, fiscal year when project became effective, and country.

Significance level: * = 10 percent, ** = 5 percent, *** = 1 percent 32
Policy Research Working Paper 10140

# **Abstract**

Evidence indicates that land rights are strongly associated with several indicators of well-being and development outcomes, including access to credit, resilience to shocks, productivity, and bargaining power. Accurately capturing gender differences in land rights is thus critical for development policy, prompting the need to shift from household-level land rights data collection to collecting more and better individual-level data on land rights. The importance of individual land rights has been recognized in the Sustainable Development Goals (SDG) agenda, with the inclusion of two key indicators on land rights—SDG indicators 1.4.2 and 5.a.1. Although clear guidance exists for computing and monitoring these, the choice of data collection methods may influence the resulting indicators and the understanding of the underlying land rights. Specifically, research has shown that the use of proxy respondents in the collection of data on assets, including land, results in a biased understanding of men’s and women’s holdings vis-à-vis self-reporting. This paper uses data from a methodological experiment in Armenia to assess the implications of survey design—namely, respondent strategy and the level of disaggregation of land data—on the measurement of individual land rights and SDG indicator monitoring. The findings suggest that in the context of Armenia, the measurement of SDG 5.a.1 and 1.4.2 (a) is robust to respondent approach and data disaggregation level, driven largely by the high rates of documentation. Meanwhile, land rights that are less objective, such as the right to bequeath and perception of tenure security, are sensitive to these survey design choices.

This paper is a product of the Development Data 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/prwp. The authors may be contacted at sgourlay@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
# **Table A8: Impacts of mental health on labor outcomes – Excluding language skills variables**

|Dependent variable:|Employment<br>status|Weekly labor income<br>($1,000 AUD)|
|---|---|---|
||(1)|(2)|
|Standardized mental health<br>scores|-0.067***|-0.183***|
||(0.009)|(0.046)|
|_First stage of 2SLS (dependent va_|_riable is standardize_|_d mental health scores)_|
|Trauma experience*Year after<br>arrival|-0.045***<br>(0.009)|-0.066***<br>(0.016)|
|Kleibergen-Paap F stat.|17.692|19.635|
|AR 95-CIs|[-0.095, -0.032]|[-0.334, -0.123]|
|Dep. Mean|0.455|0.716|
|Other controls|Yes|Yes|
|Individual FE|Yes|Yes|
|Survey wave FE|Yes|Yes|
|Observations|3,687|3,687|
|Number of individuals|1,609|1,609|

_Notes:_ *** p<0.01, ** p<0.05, * p<0.1. Results of IV-Logit-FE model (marginal effects) in Column (1) and IV-FE model in Column (2). Standard errors in parentheses are clustered at the individual level. Control variables include age group dummy variables, marital status, household size, residence area, and home ownership. Mental health scores are the sum of the 6- item Kessler Psychological Distress Scale (K6), with a higher score indicating worse mental health. The scores are standardized to have a mean of zero and standard deviation of one. The critical value of the F-test from Stock and Yogo (2005) is 16.38.

40
effect of inequality on PPP, that is one of the principal motivations of this paper, requires an analytical framework that makes an explicit attempt to link consumer preferences with PPP movements.<sup>3</sup> One of the contributions of this paper is to provide such a framework.

The need to get a valid and reasonably general PPP specification stems from the fact that the ICP PPPs or, PPPs from other sources, are available only after discrete time intervals due to resource costs and administrative complexities in conducting PPP exercises, and that such time intervals between ICP exercises have been increasing. Yet, PPPs are required much more frequently, typically annually or even quarterly, as the international community and global agencies need to make cross-country poverty and real expenditure comparisons on a regular scale. This calls for a satisfactory PPP forecasting mechanism that generates PPPs between the ICP benchmark years. Examples of attempts to provide dynamic PPP mechanisms include Rambaldi, Rao and Ganegodage (2010), Rao, Rambaldi and Doran (2010), McCarthy (2013), Pelagatti (2010), Ravallion (2013a, 2013b) and Inklaar (2013).<sup>4</sup> The result of this study on the need to link inequality movements with PPP changes over time thus acquires considerable significance.

Another key motivation of this study is to subject the recently released 2011 ICP PPPs to robustness checks by comparing them with a set of counterfactual PPPs for 2011 that is obtained using an alternative methodology that is based on consumer preferences and using a data set that is similar to that used in the 2011 ICP study. In concentrating exclusively on the 2011 ICP, we depart from counterfactual exercises such as Jolliffe and Prydz (2015) and Inklaar and Rao (2015) that attempt to reconcile the 2005 and 2011 ICP results. A related motivation is the test of the underlying assumption in the ICP PPPs, and in their use in crosscountry welfare comparisons, that a single PPP number is valid for all the expenditure classes, namely, the poor, middle income and affluent households. While there is now widespread appreciation of the importance of constructing ‘subnational PPPs’, this study is motivated by the need to draw attention to the importance of constructing ‘subclass PPPs’ as well.

> 3 See Majumder, Ray and Sinha (2012, 2015a, 2015b) for recent attempts at estimating sub-national PPPs in India and Vietnam based on preference consistent demand systems.

> 4 See, also, Chakrabarty, Majumder and Ray (2015) for an attempt to move from the cross country framework of forecasting national PPPs to the intra-country framework of forecasting subnational PPPs using a dynamic stochastic specification.

5
- Auditors General should present their reports in an attractive form and devise active communications strategies

- Auditors General should take steps to measure their own performance

- The main of PACs work should be guided by the work of the Auditor General

# _Public Accounts Committees:_

- Parliaments should regard the PAC as their pre-eminent committee

- Senior opposition figures must be associated with the PAC’s work

- There should always be sufficient experience and seniority among the membership of the PAC

- Specially structured training be provided to PAC members

- It is crucial that the Chairperson of the PAC has the qualities to ensure that the PAC works effectively

- PACs must be adequately resourced to carry out their functions

- PACs, while not being bound to act unanimously, should strive for some consensus in their reports

- PACs should promote greater public awareness of their role

- PACs should consider using subcommittees for specific inquiries

- The Internet should be used to disseminate information on PACs

- Procedures for follow-up action in recommendations in PAC reports are critical

- Parliament should hold an annual debate on the work of the PAC

- PACs in smaller and developing parliaments need improved access to information technology

- A rational local method of allocating funding to PACs needs to be put in place to ensure that they have adequate resources

- Smaller Parliaments need to take innovative steps to expand the pool of personnel available to serve on the PAC

- Special attendance allowances, rather than a special salary, should be considered for PAC attendance

- Links between PAC websites should be developed

- The CPA should explore the potential for the use of a news group to encourage information exchange on PAC matters

- The CPA should examine what options exist for conferences of associations of PACs

- • A compendium of Commonwealth PAC practice be established to be managed by a CPA branch or Parliament

- Research should be undertaken into establishing a basis for making international comparisons of PAC performance

27
was even clearer, for example, in the establishment of a power station, usually conceived to serve the largest city, and only subsequently capable of also supplying smaller cities or the countryside. Still, Hirschman thought it important that “such a second benefit-spreading phase of projects [...] either be explicitly foreseen or at least its possible emergence be carefully watched and seized upon when it occurs.”<sup>37</sup> Hirschman also criticized the inadequate consideration of social and political factors in project analysis. In his opinion, many projects had encountered huge difficulties during their implementation because of too cursory an analysis of their political and social context. Regional, tribal, or center-periphery antagonisms, and the political power of specific interest groups, are important elements that affect the success or failure of a specific project.

In addition to the influence that social and political factors might have on a project, Hirschman was interested in studying the reverse as well: were there projects that would help the development of political skills and ease intergroup agreements? In their travels, the Hirschmans noted that irrigation projects often brought in new resources that initially were believed to be available in strictly limited quantities: irrigation almost immediately creates disputes over the distribution of water, and related problems of administration and coordination between engineers and farmers, as well as between various organizations such as farmers’ organizations, extension services, etc. At the same time, these problems may have an unexpected positive spillover, as they become “a veritable school for bargaining, adjustment, etc.”<sup>38</sup> The case of an electrification project in Uganda provided another example of possible community-building to come out of project management. In the town of Masaka, Indians and Africans lived completely separate lives, carrying on distinct economic activities and following different patterns of urban migration and settlement. The Indians all lived in town and could connect to the electric power network for a nominal fee; the Africans, on the other hand, lived scattered in the countryside, and in order to connect to the power network, they were required to make a capital contribution that could be more than five times the fee paid by the Indians. The Ugandan project of power distribution had thus highly exacerbated the conflicts between ethnic groups in the country. At the same time, Hirschman noted, there was room to restructure the project, bringing the Indians and the Africans together to cooperate in managing the project, or to coordinate in having the two communities manage the project in

> 37 Albert O. Hirschman, “A Study of Selected World Bank Projects – Some Interim Observations,” August 1965, World Bank Hirschman Folders Vol. 1.

> 38 “Ideas – Miscellaneous,” no date, Albert O. Hirschman Papers, Box 57, Folder 2.

18
We group these responses into the behavioral manifestations of political and social engagement. We also asked respondents a series of questions about their perceptions of their political and social status. For example, we asked respondents about their sense of personal agency, their ability to contribute to their community, the quality of their relationships, and their trust in a number of organizations and institutions. We list which indicators were asked in each survey in Table 2. We provide additional details on the specific question wording analyzed in the Appendix, Section B.

As noted above, self-reported measures of political and social behaviors may have a number of biases. We aim to limit these through our enumeration strategy and survey design. But bias likely remains. The structure of our survey data limits our ability to directly observe respondents’ motivations for their participation in some of the manifestations of empowerment. IDPs may report their intention to vote, for example, but have no way to note that they only vote due to clientelism which is pervasive in some of the contexts we study. While we cannot distinguish between such motivations, we expect that IDPs and vulnerable but not displaced communities face similar incentives.

|||**Behav**|**ioral**||||**Perception**||
|---|---|---|---|---|---|---|---|---|
|**Country**|Voting|Participate Civil Society|Talk Openly|Attend Meetings|Trust|Personal agency|AbilityContribute Community|Relationships|
|Iraq|||||||||
|Philippines|||||||||
|Uganda|||||||||

Table 2: Manifestations of Political and Social Engagement Captured in Surveys Our explanatory variables measure displacement status. First, we measure whether a respondent is displaced or has a history of displacement. We describe the specific measures we use within each case, but generally respondents either self-report these statuses. All three surveys include relevant control populations who are similarly at risk – including those who witnessed or experienced violence – but did not become displaced. Second, to analyze variation within displaced communities, we analyze variation in the context of displacement as our independent variables. For example, we measure whether IDPs are in camps or in urban settings (in Iraq) and whether IDPs are in urban or rural localities (in the Philippines). We use the sampling strata to make such determinations. We describe the specific measurement strategies for each case when describing the models below.

# **5 Results**

Differences in the design and sampling of each of the surveys provide different opportunities to analyze different elements of our theory. We thus analyze each country context separately and our 16
(MHHs) declined at a lower rate than for female-headed households (FHHs)<sup>5</sup> , but in Uganda, the reverse is true. For Ghanaian rural households, FHH poverty decreased by 38% while that for MHH fell by only 17%. In Uganda, MHH poverty fell by 20%, and FHH poverty fell by 12%. FHH poverty in Ghana was actually lower than MHH poverty by 1992. In Uganda, FHH poverty remained slightly higher than MMH poverty, though not significantly. Poverty rates for FHHs and MHHs are very close in Uganda for both years, as also shown for 1992 by Appleton (1996). The results for both countries add to existing evidence that female headship is not in itself a robust indicator of poverty.<sup>6</sup>

# _4.2 Rural Poverty by Sector and Gender_

Flow do rural poverty rates differ by activity? Many people were active in more than one activity, with agriculture being the dominant one, but not always the most important in terms of income. For both countries, almost 90% were active in agriculture to some extent, but only 60 to 70% were in agriculture exclusively. Almost a third of the rural population in both countries was active in both agriculture and non-farm activities, and the percentage is even higher for household heads of which 40% were active in both agriculture and non-farm _(Tables 3 and 4)._ Table 3 shows poverty statistics with three views on the agriculture/non-farm split: first by main occupation and whether the main occupation is in agriculture or non-farm; second, by whether the person works for any amount of time in agriculture or non-farm as

> 5 A recent paper by Bhushan and Chao (1997) makes the valid criticism that the poverty statistics by gender reported in the 1995 World Bank report were based on assumptions of equal household size and other assumptions that bias poverty findings downward for female headed households. We recalculated the poverty statistics using their criteria and find that the relative differences in poverty movement over time between male and female headed households are still the same as reported in the 1995 report. Our analysis is available upon request.

> 6 Louat et al (1993), Rosenhouse (1989) among others.

10