rafmacalaba/datause-encoder-data huggingface dataset:
owns the dwelling. Because only one ID can be entered, it does not allow for joint ownership by spouses or those in a consensual union. It does ask questions about who else outside of the household may be joint owners, such as parents, grandparents, or siblings, but it does not have information on joint ownership if both people are household members. Thus, we recommend adding space for a second ID to allow recognition of joint ownership by spouses or those in a consensual union.<sup>29</sup> The Guatemala questionnaire asks if the household holds a document of ownership; if so, it asks which household members’ names are on the documents. Thus, it gives individual level data but only if the household has documents. If someone in the household owns the dwelling but no documents are held, it is not possible to determine which household member is the owner, thus losing valuable information. Thus, we recommend simply switching the order of these questions, asking which household member owns the dwelling before the question about documentation of ownership.

The measure of value that is most useful for comparative estimates of wealth across surveys is that of the potential sales value. Of these three questionnaires, only that for Vietnam asks this question.<sup>30</sup> In the Guatemala questionnaire, the valuation question is posited in terms of how much the household would have to pay for rent on a monthly basis for a similar dwelling. The Ghana questionnaire does not ask about the value of the dwelling at all.

The Vietnam questionnaire asks whether anyone in the household has any other dwelling, but does not follow up with any individual level ownership questions. For the valuation of these additional dwellings, it only asks about the money received from renting these. We recommend including a question in all surveys about the individual owner(s) and the value of any additional dwellings.

_Beyond the minimum questions._ Questions about the sources and timing of acquisition enable researchers to analyze the age and gender patterns of housing acquisition, which can shed light on security of tenure. Such questions may also help identify how policies and institutions can better serve women, for instance, reforming credit policies for home ownership or allocating funds for legal literacy so that women are informed about their marital or inheritance rights. Two of the surveys already ask about acquisition of the dwelling; refinement of these questions could provide more useful data for a gender analysis of housing.<sup>31</sup> The questions about acquisition of the dwelling in the Vietnam questionnaire focus at the household level. Questions include how the household acquired the dwelling, and if the household built the dwelling, whether the household received any assistance in building it. If the individual owner were identified previously, the acquisition information could be correlated with the gender of the owner. Separating the inheritance response into inheritance from owner’s parents and inheritance from owner’s spouse’s parents would be an easy way to obtain additional information on inheritance patterns.

31
**Table B3. Deprivation proportions by Venn diagram region in Figure 4: urban and rural populations**

|||Urb<br>|an<br>||Ru<br>|ral<br>|
|---|---|---|---|---|---|---|
||2005|2011|Change|2005|2011|Change|
|money poor|0.41|0.31|-0.10***|0.46|0.34|-0.11***|
|health quality deprived|0.75|0.68|-0.07***|0.83|0.77|-0.06***|
|education deprived|0.26|0.16|-0.10***|0.80|0.58|-0.22***|
|_Distribution of the population_|||||||
|not deprived|0.12|0.19|0.07***|0.02|0.07|0.05***|
|only money poor|0.08|0.08|0.00|0.01|0.03|0.02***|
|only health quality deprived|0.33|0.39|0.06***|0.11|0.22|0.11***|
|only education deprived|0.03|0.03|0.00|0.07|0.09|0.01|
|money poor, health quality deprived|0.21|0.18|-0.03**|0.06|0.10|0.04***|
|health quality, education deprived|0.11|0.07|-0.04***|0.34|0.28|-0.06***|
|education deprived, money poor|0.03|0.02|-0.01|0.06|0.04|-0.02*|
|allthree deprivations|0.10|0.04|-0.06***|0.32|0.17|-0.15***|

**Table B4. Deprivation proportions by Venn diagram region in Figure 5: urban and rural populations**

|||Urb|an||Rur|al|
|---|---|---|---|---|---|---|
||2000|2011|Change|2000|2011|Change|
|money poor|0.36|0.26|-0.10***|0.45|0.30|-0.15***|
|information source deprived|0.33|0.15|-0.18***|0.86|0.62|-0.25***|
|sanitation deprived|0.54|0.53|-0.01|0.93|0.45|-0.48***|
|_Distribution of the population_|||||||
|not deprived|0.28|0.33|0.05***|0.01|0.19|0.17***|
|only money poor|0.09|0.09|0.00|0.00|0.06|0.05***|
|only information source deprived|0.05|0.02|-0.03***|0.03|0.19|0.16***|
|only sanitation deprived|0.20|0.33|0.13***|0.08|0.11|0.03***|
|money poor, information source deprived|0.04|0.02|-0.02**|0.02|0.11|0.09***|
|information source, sanitation deprived|0.11|0.06|-0.05***|0.43|0.21|-0.22***|
|sanitation deprived, money poor|0.10|0.10|0.00|0.04|0.03|-0.01|
|allthree deprivations|0.13|0.04|-0.09***|0.39|0.10|-0.28***|

33
_Tmy-2_ with corresponding coefficients _β1_ and _β2_ allows us to explore if the impacts of SWC structures established a year ago ( _β1_ ) are significantly different from those put in place two years ago or longer ( _β1+β2_ ).

The results reported in Table 6 suggest that, for all the indices considered here, the impact of interventions undertaken two or more years ago is two to three times larger than that of more recent interventions. Variation also emerges between treatment types and outcome indicators: for SWC activity on cultivated land, the immediate impacts on all indices are negative, possibly because establishing new conservation structures requires removal of existing vegetation and time for regrowth. SWC activities on degraded land and new tree plantings, on the other hand, have immediate and positive impacts across the board, with coefficient estimates marginally larger for new tree planting.

While lack of information on the location or timing of interventions makes it difficult to pinpoint the effect of, say, terracing in specific settings so as to tease out heterogeneity in impacts, e.g. by slope or pre-project levels of land degradation, it is possible to assess the extent to which the impacts of different types of treatment vary with time by interacting _Tmy-1_ with the season in which outcome variables are observed to obtain estimated impacts of SWC activities on the outcomes in different seasons. The resulting coefficients and t-tests for significance of differences between them (table 7) point to inter-seasonal variation in estimated impacts by a factor of two to three.<sup>14</sup> The variation is most pronounced for the LSWI. The type of benefits observed also differs for SWC on cultivated and on degraded land. Together with tree plantings, interventions on cultivated land have the most impact on water-holding capacity and vegetative cover (NDVI/SAVI) in the rainy season, followed by the pre-rainy and the dry seasons. In the dry season the estimated impacts are greatest for SWC activities on degraded land.

# **_4.2 Time Variation and Impacts on Flow and Sediment Load_**

The modest magnitude of estimated coefficients and the paucity of benchmark estimates in the literature may raise concerns about whether, beyond their statistical significance, the estimated coefficients are economically meaningful in terms of having reduced the amount of runoff and soil erosion. To address this, we used the fact that at five hydrological stations, each located at the point of discharge for a microwatershed, from 2010 through 2015 daily data were collected on the volume of water flows (in m<sup>3</sup> /s) and the amount of sediment they carried (in t/d). Complementing the notation in equation (1) by indexing stations by _s_ and each day in year _y_ by _d_ allowed us to estimate the short-term impact of different types of SWC activities on water flow and sediment load by estimating a regression of the form

> 14 As appendix table 2 illustrates, estimated effects also vary by season and length of treatment.

13
Rosser, A. (2013) ‘Towards a Political Economy of Human Rights Violations in Indonesia’, _Journal of Contemporary Asia_ , 43 (2), pp.243-256.

Rosser, A. (2015a) ‘ <mark>Law and the Realisation of Human Rights: Insights from Indonesia’s Education Sector‘,</mark> _<mark>Asian Studies Review</mark>_ <mark>, 39, 2, 194-212.</mark> Rosser, A. (2015b) ‘Realising Rights in Low Quality Democracies: Instructive Asian Cases’, _Asian Studies Review_ , 39 (2), pp.180-193.

Rosser, A. (2016) ‘Neo-liberalism and the Politics of Higher Education Policy in Indonesia,’ _Comparative Education_ , 52 (2), pp.109-135.

Rosser, A. (2017) _Litigating the Right to Health: Courts, Politics and Justice in Indonesia_ , Honolulu: East West Center.

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Rotman, A. (2004) ‘Benin’s Constitutional Court: An Institutional Model for Guaranteeing Human Rights,’ _Harvard Human Rights Journal_ , 17, pp.281-314.

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Santos, B. de. Souza. (2002) ‘Law, The State and Urban Struggles in Recife’ in B. de. Souza Santos (ed.) _Toward a New Legal Common Sense_ . London: Reed-Elsevier, pp. 378-397.

Santos, B. de Souza and Rodriguez Gravito (eds.) (2005) _Law and Globalization from Below,_ Cambridge: Cambridge University Press.

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# **6. Conclusions**

There has been much public debate about India‘s Mahatma Gandhi National Rural Employment Guarantee Scheme since it was introduced. There have been many media reports and some selective surveys, covering at most a few states and/or selected districts. This paper uses India‘s National Sample Survey of 2009/10 to test some of the claims that have been made in past debates using data for all the major states of India. We have focused on a distinctive and important feature of MGNREGS: the guarantee of employment at the stipulated wage rates.

We confirm expectations that the demand for work on MGNREGS tends to be higher in poorer states. This appears to reflect the scheme‘s built-in ―self-targeting‖ mechanism, whereby non-poor people find work on the scheme less attractive than do poor people.

However, actual participation rates in the scheme are not (as a rule) any higher in poorer states where it is needed the most. The reason for this paradox lies in the differences in the extent to which the employment guarantee is honored. The answer to the question posed in our title is clearly ―no.‖ Rationing is common, but far more so in some of the poorest states.

We do not find that the local-level processes determining who gets work amongst those who want it are generally skewed against the poor. There are sure to be places where this is happening (and qualitative field reports have provided examples). But it does not appear to stand up as a generalization. We do find evidence that the poor fare somewhat less well when it comes to the total number of days of work they manage to get on the scheme. However, despite the pervasive rationing we find, it is plain that the scheme is still reaching poor people and also reaching the scheduled tribes and backward castes.

Participation rates on the scheme are higher for poor people than others. This holds at the official poverty line, but the scheme is also reaching many families just above the official line. It is only at relatively high consumption levels that participation drops off sharply. This should not be interpreted as indicating that well-off families in rural India are turning to MGREGS. There may well be shocks that are not evident in the household consumption aggregates. And there may be individual needs for help that are not evident in those aggregates.

18
17 subsidization. Since the 1980s, however, food consumer subsidization in Asia, Latin America and Europe’s transition economies has gradually disappeared and been replaced by a small degree of taxation.

# [Insert Figure 3 about here]

Assistance to import-competing farmers is typically well above that for the export producers (Table 1), and conversely for consumers of farm products. This means there is an anti-trade bias in the structure of agricultural distortions. In the case of developing countries where the import-competing NRA is positive and the NRA for exportables is negative, the two tend to offset each other such that the overall sectoral NRA is close to zero. Such a sectoral average can thus be misleading as an indication of the extent of distortion within the sector. It can also be misleading when comparing across countries that have varying degrees of dispersion in their NRAs for different farm industries.

# [Insert Table 1 about here]

Of most relevance for this paper is the instrument level NRA and CTE data. Table 2 summarizes the contributions of different policy measures to the overall estimated NRAs and CTEs for the two periods 1981-84 and 2000-04. It show that trade measures always account for the largest share of the total NRA for both developing and high-income countries, and even more so for the total CTE because direct domestic consumer subsidies/taxes, as distinct from the indirect ones provided by border measures, are relatively rare. The dominance of border measures in both CTEs and NRAs ensures that the two price distortion indicators are highly correlated. For all focus countries, covered products and available years in the panel set, the coefficient of correlation between NRAs and CTEs is 0.93.

# [Insert Table 2 about here]

The Distortions to Agricultural Incentives database also includes measures of so-called decoupled support and other non-product-specific assistance. These measures account for one-third of the aggregate NRA of all focus countries in 2000– 04, and even more in high-income countries. Because decoupled payments and nonproduct-specific supports are not reported at the product level in the database, they are not captured in the ITRI and IWRI estimates. However, they are clearly important for the overall story of agricultural policy — especially in high-income countries where there has been a move to forms of support decoupled from production in recent
expected returns, but agents may hold liquidity because on occasion they are able to make a profit by buying assets at fire-sale prices (Allen and Gale, 1994, 1998; and Allen and Carletti, 2008).

To study the rebalancing effects of short-termism, we conduct event studies with unique data from the Superintendency of Pensions on daily asset holdings of pension funds. We use two types of events relevant to pension fund managers: (a) the relaxation of regulatory constraints and (b) the occurrence of crisis periods. We focus on pension funds because we do not have high frequency (daily) portfolio data for other Chilean institutional investors. However, as we show below, pension funds experience significantly less outflows than mutual funds and, therefore, should be especially able to use their liquidity to take advantage of market opportunities in turbulent times instead of meeting redemptions. Furthermore, there were many regulatory changes related to pension funds that constitute interesting events to analyze.

_Relaxation of Regulatory Constraints._ The current legislation limits the amount of foreign assets held by PFAs. This threshold has been expanded from 16% to 45% of total assets through six amendments since 2002, increasing 4% on March 1, 2002 and 5% in each of the remaining cases.<sup>17</sup> Data on portfolio composition indicate that these limits have been binding most of the time for Chilean PFAs (Raddatz and Schmukler, 2008), a fact that is consistent with the historical lobbying efforts of PFAs in favor of increasing these limits. Since these regulatory changes have typically been announced in advance, PFAs could accumulate liquidity prior to the deregulation to take advantage of such changes. In other words, if PFAs hold liquidity to take advantage of investment

> 17 The remaining dates are May 29, 2003, March 1, 2004, August 9, 2007, December 18, 2007, and April 24, 2008.

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**Coefficient Plot: Lack of Information by Date**

<!-- Start of picture text --> funcioncuandpupuscuantpuedestoquitvanfinvanisi incrementpreguntcuandpupuscuantantesnoticidondpuedverdesteestoquittiendanvansihaygasdarwtfmestavani incrementgeneralfuncioncuandcuantantespuedverdquitvangasdarfinvanisi incrementcuantantespuedtonyquitgasvasi preguntfuncioncontrolcuandcuantverdestovanvasi generalformatcuandcuantantesdondesteestoquitvanvasi<br>poblacionracionalizpreguntbeneficigobiernurl_linkexplicparecestadustedahorrmedicommesmasquepaggaspocesotodfunmecredejleñ dollar_amounteconombeneficigobiernentiendurl_linkgasolinmañanfamiliparecustedahorrtortillafectcalorquedapagmedipreciquercomestaculpbienmesmaspaisquehabaunhoypagsubdosvospochacesopassactodfunsercrevidleñdicsigasimihadijtuel dollar_amountpoblacionbeneficigobiernalcanzcambimillonmejorparecnoticicalorapagcomculpbienpaistienquehubdanaguhaypagsubdoshacesopasfunmecreleñdicasi gobiernahorrmedipreciquercomculptienquedanhayhoypagsubvoslicuwtfmeleñha beneficiarisiguiententiendurl_linkparecustedapagculpmastienquedanhaypagsubgasdarmeviddejha presidencialpregunturl_linkministrmanejcambireducoficinquedprecicommeschictienquehaypagsubgasvezdartodmediccajasi<br>January 2011 April 2011 May 2011 August 2011 May 2012 August 2012<br><!-- End of picture text --> Figure 13: The top 100 or fewer coefficients associated with “lack of information” over time. The blue indicates positive coefficients and the red negative. This graph demonstrates topic drift during the sample period. The scales of each graph are not constant over time. Source: Author’s calculations.

_La Prensa Grafica_ . Furthermore, we were able to provide deeper insights in to prominent content of these subjects with our results suggesting that the short-lived distributor strikes in May 2011 and the public’s views of the distributors, in general, may have influenced the negative public perception of the reform more than previously acknowledged.

We also provided some methodological suggestions for those researchers wishing to undertake similar studies, noting the difficulties in obtaining a representative, a baseline of tagged tweets, and in making inferences from small samples. We also gave methodological suggestions for improving results by avoiding over-fitting, performing feature engineering, and iterating from preliminary results back to the taxonomy stage. Overall, we were able to provide a more nuanced understanding of the public debate on the El Salvador propane gas subsidy reform.

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Table 3: Emission Factors, 100‐Year Global Warming Potentials, and biogas plant values at a carbon price of $10/tCO2e.

|Pollutant|Emission<br>Factor (g of<br>Pollutant/Kg<br>of wood)|100‐year<br>Global<br>Warming<br>Potential<br>(tCO2e)|Tonnes of<br>CO2e saved<br>per Kg of<br>wood|Annual<br>tCO2e<br>saved per<br>biogas<br>plant|Annual<br>value of<br>CO2e/biogas<br>plant (USD)|Discounted<br>value of<br>savings at<br>2% discount<br>rate over 15‐<br>year life in<br>USD.|
|---|---|---|---|---|---|---|
|CO2|1358|0.5|0.000679|0.679|6.79|87.24649917|
|BC|0.7|900|0.00063|0.63|6.3|80.95036005|
|OC|1.9|‐46|‐0.0000874|‐0.0874|‐0.874|‐11.2302563|
|SO2|0.1|‐76|‐0.0000076|‐0.0076|‐0.076|‐‐‐<br>0.976544026|
|CO|76|1.8|0.0001368|0.1368|1.368|17.57779247|
|NMVOC|6.9|8.8|0.00006072|0.06072|0.6072|7.802072798|
|CH4|4.9|28|0.0001372|0.1372|1.372|17.62918952|
|N2O|0.1|265|0.0000265|0.0265|0.265|3.405054828|
|**TOTAL**|||**0.00157522**|**1.57522**|**15.7522**|**202.4041685**|

Sources: Emission factors: (Pandey et al. 2014), Table SI3. Global Warming Potentials: IPCC (2013), Appendix 8.A, except for SO2 which is from Grieshop et al. (2011).

Notes: The GWP for CO2 is adjusted to account for partly sustainable harvesting of wood. Annual wood saving per plant is assumed to be 1000 kg in the 5<sup>th</sup> column and the carbon price assumed for the 6<sup>th</sup> column is $10/tCO2e.

Using a carbon price of $10/tCO2e, we get the annual value of savings in USD per biogas plant to be about $16. This carbon price is about 20% lower than the average of $12 per ton CO2e price during 2014 in California. Since the price floor in the quarterly auctions in California in 2014 was $11.34 and is set to rise at 5% plus the inflation rate annually, our assumed $10 price is quite conservative.<sup>14</sup> A 6‐cubic‐meter plant (the most commonly installed size) costs about $400 to install and has an expected life of 15‐20 years. Assuming a long‐term social discount rate of 2% per year, the carbon value of a biogas plant is found in the last column of Table 3 to be $200. Thus, a subsidy greater than 50% could be financed

> 14 See <u>http://calcarbondash.org/</u> and <u>http://www.edf.org/california‐cap‐and‐trade‐updates.</u> Accessed January 29, 2015.

13