rafmacalaba/datause-encoder-data huggingface dataset:
- (land reform)?

- • To what degree do different people in households have access to and control over consumption goods and services?

- –

- <u>Society household and kinship groups:</u> • Have there been any changes in the roles that men and women (of different groups) have traditionally played? Why have these changes occurred and what are the impacts of these changes?

- Are women better or worse off today compared to the past? In what ways? Are women of different groups (differentiated by class, age, ethnicity, religion, etc.) better or worse off today compared to the past? In what ways?

-

- <u>Society community:</u> • How many and how diverse are the membership organizations that exist? What are the “rules” of community membership groups?

- • To what degree does social identity affect membership of community groups and associations?

- • Is there conflict between different groups in the community?

Analyzing the qualitative data normally produced using participatory tools can be difficult, especially when trying to incorporate the data into the predominantly statistical analysis of the individual survey. The analysis of this data often relies to a certain extent on interpretation and reflection. However, generating numbers from, or quantifying, the qualitative outputs of participatory approaches and tools is possible and can help when trying to combine the analysis with the data from the individual survey. Given that the information being analyzed will be from focus groups spanning a number of different sites, recoding the information should be systematic and should use consistent pre-determined formats and terminology where possible.

The analysis of the focus group discussion data will be crosschecked with data from the individual interviews. Crosschecking may produce contradictions that will also need to be explained or resolved.

Diversity is another important factor to consider when analyzing the data from focus groups and interviews. Diversity in responses can be seen as an indicator of empowerment, with diversity of behavior at the population level being a gross indicator of agency (of the ability to make choices), relative to homogenous behavior by the same set of people. Analysis of responses should therefore take into account the range of responses, as well as the average response (Davies 2000). For the focus group discussions, this means that accurate documentation of discussions is vital to record all views expressed before any consensus is reached by a group.

The need to analyze a diversity of qualitative factors for the existence of complex relationships may well benefit from the use of computer-based qualitative data analysis or thinking support software, such as NUD*IST, Creative Thinker, or Visual Concept, to enable alternative relationships to be visualized, documented, and assessed in an effective manner.

86
It is possible to empirically test the conditions under which IRT produces reliable estimates by examining differential item functioning (DIF). Sandefur (2016) equates SACMEQ and TIMSS results with IRT methods. Sandefur (2016) measures the DIF as the distance between the itemcharacteristic curve (ICC) for the reference population and actual responses for the focal group, an approach first proposed by Raju (1988). The resulting DIF is high, casting doubt on the IRT approach in a context with limited item overlap.

While IRT might not be a reliable approach when there is limited item-by-item overlap, we propose a few robustness tests in Section 5 where overlap is larger. We compare our results to the _Linking International Comparative Student Assessment_ (LINCS) project which uses IRT methods and has significant overlap in items for a subset of international studies focused on reading at primary school from 1970 onwards (Strietholt, 2014; Strietholt and Rosén, 2016). We conduct a series of additional robustness tests. Namely, we compare scores and ranks of our estimates relative to ranks and raw scores for the original tests used for linking. If our expanded HLO database can produce similar results to original scores and IRT methods where there is overlap, we gain confidence in our results as well as an expanded dataset.

We note that while mean scores might vary by linking methods, and should be caveated appropriately, ranks and relative performance are relatively robust. While Sandefur (2016) finds large variation on mean scores depending on the equating method chosen, the Spearman rank correlations of the country averages are .97 or higher.

In building globally comparable education quality estimates, we rely on classical test theory (Holland and Hoskens, 2003). Specifically, we use pseudo-linear linking and equipercentile linking. Below, we describe each, starting from a foundation of mean linking.

Suppose that a population of pupils, sampled from the target population _T_ , takes two different assessments _X_ and _Y_ . Here, we suppose that any differences in the score distributions on _X_ and _Y_ can be attributed entirely to the assessments themselves, since group ability is assumed to be constant.

The goal of linking is to summarize the difference in difficulty between two tests _X_ and _Y_ . We would like to link test _X_ on the scale of test _Y_ , which is a _Reference Test_ , while test _X_ is the _Anchored Test_ . For instance, we would like to link a test like _PISA 2003_ on another assessment like _TIMSS 2003_ . Therefore, _PISA 2003_ will be the _Anchored Test X_ while _TIMSS 2003_ will be the _Reference Test Y_ .

13
7 To monitor and evaluate progress of the Eco-farming project, a baseline survey of 2,700 households was conducted during the second half of 2009. This is the first phase in a larger effort to more accurately evaluate the impact of the project.<sup>10</sup> In total, 225 villages were selected, spread equally across 3 counties in each of the 5 provinces in which the project is active. Counties were stratified by physical and economic characteristics.<sup>11</sup> Within each county, two townships were selected purposively, and within each township, two project and three non-project villages.<sup>12</sup> Non-project villages were slightly oversampled (135 non-project versus 90 project villages) to ensure a sufficient number of pure control villages that have neither the World Bank supported nor the national biogas program. In both project and control villages, the survey randomly sampled households meeting the criteria to qualify for biogas subsidies. To also permit within project village impact analysis in the future, households were slightly oversampled in project villages—fifteen households in the project villages versus 10 per nonproject village. The survey instruments comprised a household questionnaire covering all aspects of fuel and energy consumption, experiences with biogas, and a range of socio-economic conditions as well as a village questionnaire covering infrastructure and socio-economic development.

The baseline data described above forms the information base for this paper. At the commencement of the Eco-farming project at the beginning of 2009, a number of households already owned a biogas digester. In particular, the sample contains 610 households (23%) with biogas installed, of which approximately 147 were provided as part of the Eco-farming project. The remainder received it with support from various government agencies or constructed it themselves. The study exploits this feature of the data to situate the current use of biogas within the overall energy mix in this part of rural

> continues. The smallholder digesters may also be filled with manure from the larger farms, as has been reported on a couple of occasions during our field visits.

> 10 Two follow up panel surveys are planned in the fall of 2011 and 2013 respectively.

> 11 The selected counties are Houqiuxian, Ningguoxian, and Taihuxian in Anhui province; Jjianjinqiu, Wanzhouqiu, and yungyianxian in Chongqing; Xingan, Pinglo, and Fangcheng in Guangxi; Lensuitangqiu, Wugangshi, and Yongdingqiu in Hunan; and Enshixian, Janshi, and Xiuenxian in Hubei.

> 12 Slightly fewer villages were selected in Guangxi Autonomous Region.
serially correlated within countries over time, then predicted disbursements on previously-approved loans in a given year may be correlated with contemporaneous loan approvals in the same year, which themselves may have direct output effects. In principle, a straightforward way of addressing this concern is to control for the commitment of new loans. Doing so, however, is complicated by the same basic problem that motivates my identification strategy -- loan commitment decisions are potentially endogenous responses to contemporaneous macroeconomic events. As a result, I cannot simply include contemporaneous loan approvals as an additional regressor in Equation (1). Instead, it is necessary to somehow distinguish between loans that are committed for cyclical reasons and those that are not. In Kraay (2012), I developed a coding of World Bank projects according to their cyclical motivation based on a reading of project documentation. Not surprisingly, I found that projects approved for cyclical reasons also typically disbursed much more quickly than projects approved for other reasons. Applying the same reasoning in this context, it is plausible that loans that ultimately take many years to disburse are less likely to have been approved for cyclical reasons, whereas it is more likely that fast-disbursing loans are cyclically motivated.

Accordingly, I construct a variable containing the total value of new loan commitments as a fraction of GDP in a given country-year, restricting attention to loans that ultimately take four or more years to fully disburse.<sup>22</sup> Based on the discussion above, I assume that these loans are unlikely to have been approved for cyclical reasons, and so I can include this variable as an additional exogenous control variable in Equation (1). The results are shown in the last three columns of Table 6. This proxy for anticipation effects enters positively in all three samples, and significantly so in the full sample and IDA sample. Importantly, however, doing so does not appreciably weaken identification, and the 2SLS estimates of the multiplier fall only slightly relative to the benchmark estimates. Taken together these results suggest some evidence in favour of the hypothesis that output responds to loan approvals, but that this channel has little effect on the estimates of the contemporaneous effects of government spending when the spending eventually occurs.

Another set of concerns has to do with further potential objections to my core identifying assumption that loan commitment decisions are uncorrelated with future macroeconomic shocks. A first and basic possibility is that, while loan commitments are made before subsequent shocks are realized, these shocks may be persistent, or otherwise predictable in some way. If, in addition, loan

> 22 This is the same threshold used in Kraay (2012) for World Bank-financed projects.  I obtain similar results considering loans that require at least three or at least five years to fully disburse.

22
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private domestic and foreign banks. So the general decline in spreads in Figure 1 cannot be attributable to the government banks.

**Table 8.  Spread Decomposition by Ownership Type**

|||Foreign||Priva|te Dom|estic|G|overnme<br>owned|nt|G<br>I|overnm<br>nfluenc|ent<br>ed|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||2000|2005|2007|2000|2005|2007|2000|2005|2007|2000|2005|2007|
|Average Lending Rate|16.61|11.21|10.46|21.30|14.90|16.75|46.34|65.59|27.91|25.86|23.57|27.01|
|Average Deposit Rate|3.76|1.83|2.09|7.42|4.15|3.81|6.13|2.59|2.08|7.89|2.07|1.20|
|Spread|12.85|9.38|8.36|13.88|10.75|12.94|40.21|63.00|25.83|17.97|21.50|25.81|
|Overhead Costs|4.11|2.50|2.40|4.37|3.68|3.80|20.92|18.32|9.37|8.71|8.31|9.25|
|Loan-loss Provisions|2.90|1.37|0.55|3.60|1.22|0.85|3.94|2.66|2.21|6.54|2.04|1.21|
|Reserve Requirement|0.42|0.20|0.23|0.82|0.46|0.42|0.68|0.29|0.23|0.88|0.23|0.13|
|Taxes|1.62|1.59|1.55|1.53|1.62|2.36|4.40|12.52|4.21|0.55|3.28|4.56|
|Profit Margin|3.79|3.71|3.62|3.57|3.77|5.50|10.27|29.21|9.81|1.29|7.65|10.65|

Source: Own calculations, based on CBK data In 2007, the spreads of the government-owned banks declined steeply, yet this is certainly due to the large injection of capital into NBK, which was used to clean up its large overhang of non-performing loans. NBK is by far the largest majority government-owned bank, and thus the injection has a sizable effect on the spreads for that ownership category. Even with the injection, the spreads for government-owned banks remain substantially above those for private banks, while those for the government-influenced banks are roughly similar. And the spreads for the government-influenced banks were actually increasing from 2005 to 2007.

It is also worth noting that both types of government banks pay less for their deposits than do private banks. This suggests that depositors are certain that they will be bailed out regardless of problems with the loan portfolios of these banks. Since these banks still comprise a large share of the banking sector (Table 2), this situation implies substantial misallocation of investable resources (savings). In addition, the existence of large government banks no doubt has a distortionary impact on the activities of private banks which could be effectively precluded 16
cost of opening the branch. Hence, higher levels of remittances might not be associated with more bank branches in the very smallest communities. In our empirical estimations, we consider this possibility by excluding those _municipios_ where the share of rural population (i.e., the percentage of the population residing in communities with less than 2,500 people) is 100 percent.

# **3. Data**

We draw on data from various sources. Data on the number of branches, number of accounts, and volume of deposits and credit for each of Mexico’s roughly 2,500 _municipios_ in the year 2000 come from the _Comisión Nacional Bancaria y de Valores_ (CNBV), the banking regulatory and supervisory agency in Mexico. Summary statistics for these and other key variables are shown on Table 1. We eliminate Mexico City, since many large firms maintain centralized accounts there and the aggregate data are affected by this. Also, to minimize the influence of outliers we eliminate observations in the top 1 percent of the distribution for the number of branches, number of accounts, and volume of deposits and credit.

There is an average of 1.79 bank branches per 100,000 people and 42.1 accounts per 1,000 people across all of the _municipios_ in our sample **.** Also, across all _municipios_ , the deposit to GDP ratio is 4.24 percent and the credit to GDP ratio is 0.65 percent.<sup>12</sup> But only 24 percent of _municipios_ in Mexico in 2000 have one or more bank branches. The lack of bank branches is particularly notable in _municipios_ in which all of the population resides in rural communities. Only 0.66 percent of _municipios_ where 100 percent of the population resides in communities with less than 2,500 people have bank branches.

Data on GDP per capita in 1999/2000 come from the _Consejo Nacional de Población_ (CONAPO), a Mexican government agency in charge of tracking population and other important statistics.13 The average GDP per capita in our sample is US$ 3,388. Note that the GDP data include remittance receipts. For the country as a whole, remittances represented only about 2 percent of GDP in 2000. While the effect of remittances on income levels is clearly much higher

> 12 Recall that the sample excludes Mexico City, which is the most banked city in the country, and includes _municipios_ with no banking activity. This explains why the ratios are much lower than those for the country as a whole.

> 13 GDP in 1999 pesos is divided by population numbers from the 2000 census converted into U.S. dollars and adjusted for purchasing power differences between Mexico and the US. See explanation provided by CONAPO at http://www.conapo.gob.mx/00cifras/6c.htm.

10
- 25 - Existence of drugs 20-100Z of UP Koro (IIN) 1987: 20% Bankass (I)HO) 1987: 52X [23) pp. 1-5[231 pp. I-5 Timbuktu (NSF) 1987: 29% [23) pp. 51-52 Goundam (NSf) 1987:<sup>24%</sup> 123) pp. 51-52 Dire (NSf) 1987: 40X (231 pp. Sl-52 Niafunko (HSF) 1987: 29% [23) pp. 51-52 Gourma-Rharous (ISF) 1987: 48% (231 pp. 51-52 Gao (NSF) 1987: 53X 1231 pp. 51-52 Bouret ("SF) 1987: 45X (231 pp. 51-52 lenaka (NSF) 1987:<sup>55X</sup> [23] pp 51-52 Ansongo (HSF) 1987:<sup>26%</sup> [23) pp. 51-52 Kidal (NSF) 1987: 947. (23] pp. S3-52 Timbuktu Region (NSF) 1987: 33% (23] _ppo_ 51-52 Giao Region (NSF) 1987:<sup>50X</sup> 1231 pp., 51-52 Prescription per episode CFAF 2.000-2,500 (PPN) Niono (1988): CfAf Kita (1985): CFAF 1.888<sup>2.600</sup> (6511601 Kita (1987): CfAf<sup>2.607</sup> f611 Kenieba (3986): CAFA<sup>2.323</sup> 1621 CfAf 200480 (NS) Timbuktu (NSF) 1987: CFAF 204 (231 pp. 55-59 Ga. (NSF) 1987: CfAF<sup>251</sup> 1231 pp. 55-59 Bankass (NON) 1987: CFAF 367 1231 pp. '-5 _Koro_ (NDO) 1987: CFAF<sup>581</sup> [231 pp. I-5 Private prescription and self-medicso.<sup>CfAF 2,800/inbab.</sup> (PPN) Estimation by difterence 'see text) DisLtri Utilizationno change # 60X of PB Education and culture staff [351 Proportion Average price of consultation increase of pay consultations 75% of P836Z CFAf 1.600 Education Education and culture and culture staff staff [35](35) _Druqgs_ Average cost Proportion of buyers 601 CfAF 5I000 (PPH) Education Education and culture and culture staff staff [351[35) CFAE 3.250 (HS) Utilization 2-3 oJoo of RP Official (cercles without a hospital) statistics: 0.25X (19] Didieni Oioila. Kangaba:<sup>1-3</sup><sup>**0/oo**</sup> [341 1.13 of UP Official statistics: 1.11 (cercles with a hospital) 9) 2.41 of PO Official statistics: 2.3% Education and culture staff: 2.4Z 1351 Existence of drugs S o/oo of RP 3A of UP 3X of PB Drugs CrAf 20,000 (PPN)/admissn. Point 6: from CfAF 20.000 (surgery gynecology)<sup>13.000 (medicine)</sup> to (231 pp. 95 ff.(231 pp.378489 Point 6: beh_en"CfAF<sup>14.000</sup> and 37.000 [b41 CtAf 7.000 (NS)/admission Nopti (MON) 1987:<sup>CFAF 4,500 in medicine</sup> CFAF 10.000 in surgery (23) pp. 95 ff.
resistance data in conjunction with crop yield data<sup>(for Guntur and</sup> other areas) in order to estimate the relationship between resistance and crop damage and thus obtain estimates of the externality costs, of the sorts described in Section VII. continuing crop damage studies will also enable the identification of realistic values of Economic Thresholds and<sup>thus determine if</sup> and when changes in threshold values are necessary.<sup>Note that this</sup> aspect of the research would require c2llaboration<sup>between</sup> entomologists and economists.

Second, research needs to address the quantification<sup>of the</sup> direct environmental costs from pesticides,<sup>mentioned in Section</sup> IX. Among other aspects, this could provide<sup>informatior. for</sup> decisions on managing or phasing out the environmentally<sup>most</sup> harmful pesticides.

Third, research is needed to examine the<sup>structure of the</sup> pesticides industry, with a special focus<sup>on the role of the "non</sup> standard" brand of pesticides and their formulators<sup>and of the role</sup> of pesticide retailers as de facto pesticide<sup>usage "experts"in</sup> influencing farmer decisions. The possible participation<sup>of the</sup> industry in setting up scouting services for an<sup>IPM program should</sup> also be addressed.

Next, it would be helpful to gather data<sup>on costs of</sup> production across as wide a variety of cotton<sup>farmers as possible.</sup> The aim of this would be to estimate the<sup>demand and supply</sup> elasticities for cotton and consequently, to<sup>estimate the the</sup> potential changes in cotton prices arising<sup>as a result of</sup> 102
-8-

12% annual real return on physical assets and circulating capital<sup>2</sup> . This figure is between 16% and 28% of the annual salary expenses on administrative personnel for these firms.

The price of tradeable physical equipment may seem to be similar in developing and in developed countries, since computer and telecommunications equipment is manufactured on a worldwide basis. However, other factors suggest that these costs may be larger in developing countries, because of larger transport costs, larger customs duties, and less competition in distribution leading to higher profit margins there. As importantly, service is more expensive and less reliable, raising the cost per unit of computing services.

On the other hand, office buildings should exhibit lower costs in developing countries because of the lower wages earned by construction workers. However, this effect must be corrected by the fact that such workers also exhibit low productivity. Regarding the opportunity costs of capital, the conventional wisdom is that it is higher in developing countres.

Regarding administrative costs, the wage levels of personnel needed to run a pension system may exhibit less international variation than average income levels. This is because the abilities needed to perform these tasks seem to be in more ample supply in developed than in developing countries. This hypothesis is not contradicted in the country evidence presented in this study, except for the case of the United States, which pays high salaries to workers in the Social Security Administration.

Some costs depend of the contribution rate itself. The costs associated with insurance and fund management are applied to a larger volume of funds when the contribution- rate is larger.

In the retirement phase of the pension life' cycle, services can be provided by insurance companies. These are costs that appear to be highly correlated with income levels. The margin charged by insuranCe companies and the fees charged by insurance brokers are usually expressed as a fraction of the insurance premium. We provide data below that suggests that these premium is quite similar in the United States and Chile, although average income levels in the United States is four times Chile's at current exchange rates. The reason for this appear to be two-fold: (a) the value of

> 2 This figure was obtained from the balance sheets of Provida, Santa Marfa and Habitua for the -year ended December .31, 1991, after., substracting Negotiable Securities and .Other Circulating -Assets. The resulting asset value is divided by, the number of. contributors in March 1992, multiplied by 0.12 and the result reduced to US dollars at the December exchange rate of Ch.S 374.51. The result is lowest for Provida (3.54) and highest for Habitat (6.56).