rafmacalaba/datause-encoder-data huggingface dataset:
TABLE 9: AVERAOE COST OF CULTIVATION OF RAINFED COTTON, 1989/90.

|ITEM OF EXPENDTXURE|-----ACTUAL---<br>_RS./HA._|--<br>--<br>_%_<br>|----IPX----<br>RS./HA.|--|
|---|---|---|---|---|
|-------------------------------------------------------------------|||__|-------|
|LABOR CHAREBS|||||
|Preparatory Cultivation|240|2.3|240|2.5.|
|TraotorCharges|250|2.4|250|2.6|
|Sowing Charge.|100|1.0|100|1.0|
|Weeding/Intercultivation/|600|5.9|600|6.2|
|Fertilization Charges|||||
|Spraying charges|855|8.4|650|6.8|
|Harvesting Charges|1413|13.8|1837|19.1|
|Scouting Charges|0|0.0|300|3.1|
|COST OF INPUTS|||||
|__________________________|||||
|Seed|100|1.0|100|1.0|
|Farmyard manure|600|5.9|600|6.2|
|Chemical Fertilizers|1300|12.7|650|6.8|
|Pesticides|2850|27.9|2280|23.7|
|LAND LEASE TAXES|1500|14.7|1500|15.6|
|HIRING OF MACHINERY|120|1.2|120|1.2|
|MARRETING CHARGES|302|3.0|393|4.1|
|TOTAL|10230||9620||
|YIELD (QTLS./HA. KAPAS)|15.7||20.41||
|COST PER QUINTAL|651.6||471.3||
|REDUCTION IN COST||||27.7|

___________

-_____... __________________________________________________________..._________

NOTES: 1) The actual farmer practice is to go in for 19 pesticide sprays, on average. Under IPM'an average of 13 sprays per season are needed. Spraying costs Rs.50/hectare, lncludLng fuel. Under traditional practice, it **is assumed** that spraying costs 10% les. 2) Harvesting or the picking of Kapas costs Re.90 per quintal. 3) Under IPM techniques, scouting is carried out between 40 to 140 days of crop growth at 5 day intervals thus needing 20 scouting sorties each of which requires half a day of labor time. Wages of agricultural labourers are R.20/day. A skill charge of Re.5 per day is added. A charge of RR.50 is added for cost of pegboards and other materials 4) Based upon the PEG trials data, under the IPX strategy, yield **has** been Lncreased by 30% and pesticida expendltures reduced by 20%. S) The consumption of chemical fertilizers is reduced by 50%. This **is** consiatent with the findLngs of several studies (APAU, reomm _nded practices, Subba Rao at al., 1987).

Sourcet The basic cost of cultivatLon data is from, "The Guntur Cotton Report, 1990". However, some items of expenditure have been updated.
# **Table 6: Testing the significance of corporate sector vulnerabilities in the transmission of the 2007-2008 crisis**

Table shows results from regressing local market returns expressed in US dollars. Estimations include time dummies and country fixed effects. Robust standard errors, clustered at the country level, are shown in parentheses. *, **,*** denote significance at 10, 5 and 1 percent significance level, respectively.

|Variables|||Returns in|US$||
|---|---|---|---|---|---|
|US Stock Returns*Total Debt to Assets Ratio*Pre-Lehman|0.142*<br>(0.080)|||||
|US Stock Returns*Total Debt to Assets Ratio*Post-Lehman|0.0412<br>(0.072)|||||
|US Stock Returns*Firms with Interest Coverage<1*Pre-Lehman||0.184**<br>(0.074)||||
|US Stock Returns*Firms with Interest Coverage<1* Post-Lehman||0.0003<br>(0.062)||||
|US Stock Returns*Short-term Debt to Total Assets Ratio*Pre-Lehman|||0.084<br>(0.082)|||
|US Stock Returns*Short-term Debt to Total Assets Ratio* Post-Lehman|||0.060<br>(0.061)|||
|US Stock Returns*Return on Assets*Pre-Lehman||||-0.091<br>(0.058)||
|US Stock Returns*Return on Assets*Post-Lehman||||0.079<br>(0.054)||
|US Stock Returns*Cash to Total Assets Ratio*Pre-Lehman|||||-0.012<br>(0.093)|
|US Stock Returns*Cash to Total Assets Ratio*Post-Lehman|||||0.063<br>(0.054)|
|F-test null Pre-Lehman interaction=Post-Lehman interaction|3.19|9.56|0.11|9.09|0.96|
|F-test(p-value)|0.079|0.003|0.745|0.004|0.332|
|Observations|1287|1285|1284|1284|1265|
|R-squared|0.573|0.576|0.569|0.576|0.573|
|Number of countries|61|61|61|61|60|

30
The costs of migration are also likely to be lower for individuals who were immigrants to the country they attended secondary school in. These individuals may have an easier time gaining admission to an overseas country, and will likely experience lower assimilation costs. This is particularly relevant for the New Zealand sample, where 31 percent of top students were born outside New Zealand. It is less relevant for Tonga, where 7.8 percent of top students were born outside Tonga, and PNG, where only 2 percent were born outside PNG.

Adding uncertainty and multiple periods to the utility maximization problem will make the decision to emigrate also depend on risk preferences and the rate of time preference. We measure risk preferences by means of a question taken from the German Socio-Economic Panel, which asks individuals to state on a 11-point scale whether they are generally a person who is fully prepared to take risks or someone who tries to avoid taking risks. This has been used in the study of migration by Jaeger et al. (2007), and like them we are forced to assume that attitudes towards risks are intrinsic characteristics of individuals which are not affected by their migration decision. Although potentially problematic, one piece of evidence that might support this assumption is that we can not reject that the mean risk score is the same for each age group over the 21 to 30 age range, a range in which the rate of ever migrating is increasing strongly.

We measure patience by a dummy variable which takes the value one if an individual would accept $1100 in one year’s time compared to $1000 today. Since migration for both work and education can be construed as an investment with short-term costs required to be paid to achieve longer term gains, we might expect more patient individuals to be more likely to migrate. Again this is measured ex post, but we do not see the proportion who are patient changing with age over the 20s, when migration rates are increasing dramatically.

Finally, we consider macroeconomic variables which might explain why an individual graduating at one point in time might migrate, whereas another migrating at a later date might not. We consider two such variables. The first is the real effective exchange rate<sup>18</sup> over the age range where the incidence of new migration is highest. We take age range 22 to 25 for Tonga and New Zealand, and age range 25 to 28 for PNG. A

> 18 Source World Bank Central Database.

- 28 -
|11/5RHVouchers,<br>Nicaragua, 2000||No information|Avg. unitcostperconsultation was<br>negotiated at US$ 4.56|Notassessed|IACS (Central American Health <br>Institute) administered; donor<br>funding||Low middle<br>|income|
|---|---|---|---|---|---|
|ltongtermeash||||||
|12|Family<br>Allowance<br>Program<br>(PRAF)'s BMI<br>Voucher,<br>Honduras, 1990<br>onwards|USS 3.5mn per year (19<br>2005)|904 No information|Notassessed|Being funded mainly through<br>IADBwith somefundingfrom<br>Government ofHonduras||Low middle<br>jincome|
|13] Opportunidade<br>5, Mexico, 1997||$3.6 billion in 2007|30% of costs spent on targeting,<br>accordingtoone study|Notassessed|Funded via 1bn loanfrom<br>IADB - Oportunidades also has <br>won a significantcommitment<br>from the government<br>representing46.5% of<br>Mexico’s federal annual anti-<br>poverty budget (Also recently<br>approved 1.25bn funding via<br>WEfor2011-13)|Uppermiddle<br> jincome|
- [26] Nicita, A. and M. Olarreaga, 2007. Trade, Production and Protection 1976-2004. World Bank Economic Review 82(1), 165-171.

- [27] Ortega, D. and F., Rodriguez, 2003. Are Capital Shares Higher in Poor Countries?. Working Paper.

- [28] Park, W. and J.C., Ginarte, 1997. Determinants of Patent Rights: A Cross National Study. Research Policy N26 (3), 283-301.

- [29] Redding, S., 2002. Specialization Dynamics. Journal of International Economics, 58, 299-334.

- [30] Reppeto, A. and J. Ventura, 1997. The Leontief.Trefler Hypothesis and Factor Price Insensitivity, Working papers 97-113, Massachusetts Institute of Technology (MIT), Department of Economics.

- [31] Romalis, J., 2004. Factor Proportions and the Structure of Commodity Trade. American Economic Review, 94 (1), 67-97.

- [32] Samuelson, P., 1965. A Theory of Induced Innovations Along KennedyWeisacker Lines. Review of Economics and Statistics, XLVII, 444-464.

- [33] Schott, P., 2003. One Size Fits All? Theory, Evidence and Implications of Cones of Diversification. American Economic Review, 93 (3), 686-708.

- [34] Young, A. 1995. The Tyranny of Numbers: Confronting the Statistical Realities of the East Asian Growth Experience. Quarterly Journal of Economics, 100, 641-80.

29
# **<mark>V. Conclusions and Recommendations</mark>**

The national response to HIV/AIDS in Colombia is articulated through a health insurance system and is integrated into the broader area of public health (as per the PNSP), and more specifically, into the SRH area—which is one of the key national priorities in health. The SGSS guarantees the provision of health care to the population – with a growing degree of care coverage and an increasing proportion of public expenditures that have been gradually achieving a smaller proportion of out-of-pocket expenditures in health.<sup>56</sup> This system is integrated by a network of insurance companies and health care provider institutions that compete in a regulated market.

Due to the structural challenges that the health insurance system is currently facing, Colombia is now undergoing a process of rationalization and reform.<sup>57</sup> The existence of different affiliation and insurance regimes makes it an extraordinarily complex and fragmented system. In addition—and contrary to what might be expected—two-thirds of the insured belong to the subsidized regime, and only one-third actively contributes to the contributory insurance scheme.<sup>58</sup> On the other hand, the public health system component carries out collective interventions for health promotion and prevention—channeled through the local entities—which results in a certain degree of local variability in the type and quality of interventions used to respond to the HIV/AIDS epidemic across the country.

## **1. Efficiency of the HIV/AIDS Response in Colombia**

The epidemiological data presented in the Study suggest that the HIV/AIDS response in Colombia is succeeding in containing the epidemic. The prevalence of HIV/AIDS for the entire population of Colombia is low. However, the number of HIV cases reported has been gradually increasing among the groups where the epidemic is concentrated – mainly, MSM, FSWs, IDUs and pregnant women. In addition, Colombia is making a

> 56 ACEMI (Septiembre 2008) Modelo de Aseguramiento en Salud en Colombia. http://www.aplegis.com/documentosoffice/tutelaypila/LEGISCODESS.pdf.

> 57 Díaz Granados JM (8 Febrero 2011) El Aseguramiento en la Reforma. Foro Reforma Sistema de Salud. ACEMI. http://www.acemi.org.co/Comunicaciones/presentaciones/foro2011/05.pdf .

> 58 Clavijo S y Peña MO (Septiembre 2010) Reformas al régimen de salud: entre la emergencia social y el déficit estructural, EGOB Revista de Asuntos Públicos, num. 5, pp. 4-8.

53
<!-- Start of picture text --> 40 —Domestic demand<br>30 —p tic ren rae<br>20 ~-Imports---""~<br>10 “<br>0 -—*<br>“10<br>-20<br>-30<br>2012 2015 2018 2021 2024<br><!-- End of picture text --> <!-- Start of picture text --> 10<br>0<br>10<br>~<br>-20 =><br>-30<br>—Domestic production<br>-40 —Domestic procurement<br>-50 -- Exports<br><!-- End of picture text --> <!-- Start of picture text --> 3% |) agriculture construction<br>2% —pwt. tradable _non-tradabale<br>—other govt.<br>1%<br>0% = 7<br>1%<br>2<br>-3%<br>2012 2015 2018 2021 2024<br><!-- End of picture text -->

<!-- Start of picture text --> 4%<br>3% =<br>2%<br>0%<br>4%<br>agriculture construction<br>“2% | _ pvt tradable —pit. non-tradabale<br>-3% | —other govt<br><!-- End of picture text -->
# 4.6 An aggregate look at quality of facilities

The variables shown in the sections above can be combined using PCA to provide a composite indicator for each facility. The distributions of the raw PCA score can be seen in **Figure 12** . Public facilities score worse than private facilities on average and health clinics and health posts score worse than hospitals. Tanzania and Kenya are at the top end, while Niger and Nigeria show the worst outcomes. The differences between countries are large, with 92.5% of Nigeria’s facilities scoring below Kenya’s country average. However, variance decomposition also reveals substantial variance in-country, with almost two-thirds of the variance attributable to within-country differences (64.1%), compared to roughly one-third from between-country differences (35.9%), as shown in **Appendix Table A8,** and in line with the analysis of individual components of the PCA.

The characteristics of high and low performers, defined as the top and bottom 10% of this aggregate metric, respectively, are identified and the characteristics of these facilities are shown in **Table 6** . Kenya has the highest prevalence of high performers, with nearly 20% of facilities in Kenya identified as high performers. Public facilities are more likely than private facilities to be identified as low performers in all countries. Rural facilities are also more likely to be low performers, with all countries except Mozambique having a higher share of low performers in rural areas than in urban areas. The percent of facilities identified as high performers is generally higher in richer countries, as measured by GDP per capita.

_Figure 12: Distribution of PCA index scores by country_<sup>24</sup>

> 24 The PCA index here is renormalized to a minimum of zero, for ease of viewing results.

18
where is an error term, and ∆ denotes difference. The error correction representation of the selected ARDL model can be constructed by replacing the part of the lag of level μμ variables in equation (A3) with an error correction term ( _EC_ ).

# **A2. Data and estimation results**

Quarterly data on Cambodian exports to the EU and the US federal fund rate are obtained from the DOTS and the IFS databases published by the IMF, respectively. The EU’s GDP is used for its income, and its real value is calculated by using the GDP deflator. Both GDP and GDP deflator data for the EU are taken from the Eurostat database. The sample period of the estimation is from 1995Q1 to 2016Q4, based on data availability.

In the ARDL approach to cointegration, a statistical test to check the existence of the cointegration or long-run relationship among variables needs to be implemented in advance. Specifically, the F-test is used to test the null hypothesis of no cointegration, H0: _λ_ 1= _λ_ 2= _λ_ 3=0, against its null hypothesis, H0: _λ_ 1≠0, _λ_ 2≠0, _λ_ 3≠0. The computed F-statistic from this test is compared with its critical value available in Pesaran et al. (2001) for determining whether or not the null hypothesis should be rejected. Although the computed statistic does not support the existence of the cointegration relationship, its values varies significantly with different lag lengths. Following Bahmani-Oskooee and Nasir (2004) and Okada and Samreth (2013), the statistical significance of the error correction ( _EC_ ) term in the next estimation step may be examined to evaluate the existence of the cointegration relationship.

Equation (A3) in which the part of the lag of level variables is replaced by an error correction term ( _EC_ ) is estimated, using the ARDL approach to cointegration. The maximum lag order is set to four for this estimation.<sup>18</sup> Following Narayan (2004) and Okada and Samreth (2013), Schwarz Bayesian information criterion (SBIC) is used for selecting the optimal lag order. Based on SBIC, ARDL(1,0,0) is obtained. Table A1 presents the estimation results of the error correction model. From the table, the coefficient of the error correction term ( _ECt_ -1) is statistically significant and negative. Its

> 18 Setting maximum lag order to four is common in an estimation using quarterly data.

22
- **Conducting a regional Regulatory Services Audit.** This would enable countries to better understand each other current regulatory regime in services and better enable them to engage in these negotiations effectively.  Such an audit involves a diagnostic of what concessions (offer) could be made at low (e.g., binding status quo) or high (e.g., major reform required) costs.  Frequently, lack of coordination or information-exchange within different branches or ministries of a government could serve as an impediment to realizing the constraints/concessions available in trade negotiations.  A regulatory audit is an exercise that would promote better information flow between a government in identifying the status quo and strategy in services trade. This would also help assess whether negotiated agreements with third parties are less restrictive than negotiations among members within PAFTA.  In the World Bank’s regulatory audit for Maghreb, it was apparent that rules applicable to services trade with the EU or the US are often less restrictive than among Arab countries.  This is particularly so for movements of persons and capital.

- **Negotiating a pan-Arab agreement in services.** Looking forward, the regulatory audit exercise will help to assess the areas of expeditious collaboration among PAFTA members and areas where a special work program may be required.  Harnessing the knowledge of the strengths/weaknesses of their respective regulatory frameworks would also help members better design basic principles for regional liberalization. Establishing a regional database of the regulations pertaining to each services sector and country could also help regional negotiations by increasing the level of transparency and identifying the status quo and feasible results. This transparency exercise could be accompanied by training and other technical assistance to help PAFTA countries translate the collected information into negotiation positions (requests/offers).

- **Reinforcing statistical tools.** Access to reliable data on trade flows is essential to the identification of offensive/defensive trade interests and development of a broader trade strategy.  In this region, it appears that some countries have not developed a data management system for trade (particularly services trade).  The lack of data will impede the ability of countries to easily evaluate the current status and identify opportunities.  This can be resolved by developing services trade statistical capacity.  However, this process could be a more long-term approach that involves a substantial effort at data collection and data analysis.  Hence, this process could take place concurrently with other activities related to services negotiations but not hinder the overall process.

**To pave the way for complete services liberalization, a number of services sectors could become pilots for early regional liberalization.** Key candidate sectors for such early liberalization include (1) trade facilitation & transport, given the importance of facilitating trade

27
COST RECOVERY, EQUITY, AND EFFICIENCY IN WATER TARIFFS IN AFRICA

|Utility|Type of<br>tariff|Metering<br>ratio<br>(%)|Minimum<br>con-<br>sumption<br>(m<br>3)|Fixed<br>charge|Number<br>of blocks|Size of<br>1st block<br>(m<br>3)|Size of<br>nth block<br>(m<br>3)|Price<br>of 1st<br>block<br>($)|Price of<br>nth<br>block<br>($)|
|---|---|---|---|---|---|---|---|---|---|
|Windhoek|IBT|—|0|y|4|6|40+|1.01|1.94|
|Oshakati|IBT|96.5|0|y|3|10|40+|0.26|0.92|
|SEEN|IBT|96.8|0|n|1|0|0|0.39|0.39|
|FCT WB|Linear|23.6|0|n|2|30|30+|0.16|0.19|
|Kaduna WB|IBT|16.1|0|n|3|30|1000+|0.19|0.28|
|Katsina WB|IBT|6.5|0|n|6|5|500+|0.44|1.09|
|Electrogaz|IBT|98.7|0|n|4|20|60+|0.37|0.73|
|NWC Khartoum|IBT|—|0|n|1|0|0|0.64|0.64|
|NWC South Darfur|Linear|—|0|n|1|0|0|0.59|0.59|
|NWC Upper Nile|Linear|0.0|0|n|3|20|40+|0.37|1.46|
|SDE|IBT|117.3|0|n|2|15|15+|0.22|0.47|
|DAWASCO|IBT|70.5|0|n|2|5|5+|0.39|0.52|
|DUWASA|IBT|27.9|10|y|3|14|25+|0.00|0.51|
|MWSA|IBT|100.0|0|y|3|24|75+|0.24|0.28|
|NWSC|Linear|94.5|0|y|1|0|0|0.65|0.65|
|Drakenstein|IBT|60.7|0|y|7|6|1000+|0.00|1.86|
|Tygerberg|IBT|60.3|0|y|6|6|50+|0.00|1.86|
|eThekwini|IBT|66.4|0|y|3|6|30+|0.00|1.77|
|Johannesburg|IBT|52.4|0|n|6|6|40+|0.00|1.40|
|SWSC|IBT|—|6|n|4|10|50+|0.30|0.47|
|LWSC|IBT|33.3|0|y|5|6|170+|0.25|0.55|
|NWSC|IBT|—|0|n|4|6|50+|0.25|0.37|
|**MIC average**|78.2||||4.4|||0.23|1.50|
|**LIC average**|66.4||||2.9|||0.34|0.80|

_Source:_ AICD WSS Survey Database, 2007. _Note_ : MIC = middle-income countries; LIC = low-income countries. — = data not available.

Developing countries have often used the price of a first block as a social tariff or lifeline, so that the poor can have access to at least a minimum quantity of safe water at a subsidized price. Most of the policy debates over the impact of tariffs on equity revolve around this issue and whether it is actually serving the poor. The average price of the first block in African water utilities is about $0.32/m<sup>3</sup> . About 20 utilities charge less than $0.20/m<sup>3</sup> for the first block. South Africa is unique in that it has a free water policy, with the first 6 m<sup>3</sup> delivered at no charge. This gives small consumers the opportunity to meet their minimum consumption needs for free. (It is also the reason why the average first-block tariff shown in table 1 is lower in the MICs than in the LICs.) ELECTRA in Cape Verde is an outlier, with the first-block tariff amounting to $2.7/m<sup>3</sup> , followed by Oshakati in Namibia, which has a first-block tariff of just above $1/m<sup>3</sup> . In a number of countries with a minimum consumption charge—such as Cote d’Ivoire, Malawi (BWB), and Mozambique—the block structure begins with block two, and the price of block one is therefore zero.

The price of the last block in an IBT structure is often set with an eye on cost recovery and water conservation. In about one-third of utilities, the tariffs are set higher than $0.8/m<sup>3</sup> : of these, 13 have last5
Figure 3: Exposure of commuting zones: input tariffs <!-- Start of picture text --> Mean = 1.67 p.p., std = 2.40<br>6.84 − 37.60 5.17 − 6.84 4.02 − 5.17 3.24 − 4.02 2.74 − 3.24 2.16 − 2.74<br>1.82 − 2.16 1.39 − 1.82 0.96 − 1.39 0.46 − 0.96 0.00 − 0.46 No data<br><!-- End of picture text --> _Notes_ : This map displays the change in the baseline employment-weighted input tariff exposure for each commuting zone between December 2017 and December 2018. Darker colours represent more exposed areas.

ment composition as discussed in Section 3.3. Relative to the other two exposure measures, export tariff exposure shows a much greater concentration in the Great Plains and West, likely reflecting the concentration of agricultural products included in the retaliatory tariffs.

# **3.5 Classifying job adverts by occupation and skill**

The BGT job postings data provide information on the US SOC code of each of the postings (96% coverage). Examples at the 2-digit level include ‘Business and Financial Operations’ or ‘Food Preparation and Serving Related’; the full range is presented in Table 6 in the Appendix.

In order to investigate the impact of the tariffs on job postings by skill level, it is necessary to allocate postings into skill categories. Although the BGT data includes a variable for the minimum education level required in each job advert, the coverage is relatively low: only approximately 51 percent of postings have positive assigned minimum values of education.<sup>13</sup> In order to include the widest possible range of postings in the skill classification, we therefore instead use the available minimum education data to classify each SOC code by skill 13This could be due to challenges in scraping this type of information from online adverts, or because many adverts do not explicitly name a minimum education level.

19