rafmacalaba/datause-encoder-data huggingface dataset:
||Colombia|Peru|Philippines|Vietnam|<sup>International</sup><br>benchmark|
|---|---|---|---|---|---|
|**Regulatory Substance**|**81%**|**83%**|**95%**|**85%**|**76%**|
|**Tariff Regulation**|**92%**|**100%**|**93%**|**83%**|**77%**|
|_Regulatory Frameworkfor Tariffs_|100%|100%|86%|100%|90%|
|_Determination of Tariffs_|83%|100%|100%|67%|64%|
|**Quality Regulation**|**100%**|**100%**|**92%**|**71%**|**75%**|
|_Quality of Service Standards_|100%|100%|100%|75%|82%|
|_Quality of Service Enforcement_|100%|100%|83%|67%|68%|
|**Market Entry Regulation**|**50%**|**50%**|**100%**|**100%**|**77%**|
|_Permitting New Entrants_|50%|100%|100%|100%|90%|
|_PPA Approvals_|50%|0%|100%|NAP|57%|

Note: Scores based on index developed for the Rethinking Power Sector Reform Project. For more details go to project website at http://www.esmap.org/rethinking_power_sector_reform

# _3.4.2.4 Quality Regulation_

As regards quality regulation, there are specific quality of service standards formally written and publicly available for quality of product, supply, and commercial service. Utilities are legally required to meet these standards and they take them seriously and generally comply with them. There are rewards and penalties incorporated in the performance incentive scheme under the performance-based rate setting. Penalties are incorporated in the next tariff setting thus, all users are affected, and they are always enforced in practice. Also, it is disclosed to the public whether utilities have met the standards. As regards quality of service enforcement regulated entities are required to report on a periodic basis on different indicators, such as SAIDI, SAIFI, other service interruption indicators, and voltage indicators. According to the survey, these indicators are independently validated and reviewed by ERC.

All measurements of the quality or reliability of the power supply are made publicly available. The information, broken down monthly, has to be collected and supplied to the ERC annually. In addition to the monthly figures, the cumulative performance total against each index must also be provided, from the start of the corresponding calendar year until the end of the month for which each index was measured. The ERC intends to annually publish the information disclosure data for all Regulated Distribution Systems. Finally, formal measurements of overall customer satisfaction are required and are indeed undertaken in practice through customer surveys carried by utilities (more than once a year).

Summing up, the Philippines’ performance on quality regulation is very good (92 percent), with its weakest area being Quality of service enforcement (83 percent). There is a comprehensive quality regulatory framework, with specific and publicly available require information, including processes and consequences of non-compliance. The main limitations are the fact that utilities are not required to use an automated information management system to measure the quality or reliability of the power supply. Here too the score for the Philippines is above the international benchmark but is below the scores for Colombia and Peru (table 11).

49
# Table 7

# EFFECTS OF FOUR PERCENT SUSTAINED INCREASE IN MONEY BASE TARGET, ON THE ECONOMY OF SHOCK ORIGINATING REGIONS

|P<br>E<br>R<br>I<br>||Uni|ted Sta|tes||||German|y||||Japan|||Larg|e Indus|Other<br>triali|zed<br>Coun|tries|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|0|||||||||||||||||||||
|S|GNP|PGNP|KERM|RS|CURBL|GNP|PGNP|<br>ER|RS|CURBL|GNP|PGNP|<br>ER|RS|CURSL|GNP|PGNP|<br>ER|RS|CURBL|
|1988|0.82|0.22|-4.48|-0.34|4.96|1.68|0.47|-4.38|-0.15|-0.41|0.87|0.48|-4.43|-0.31|1.32|1.01|0.48|-3.90|-0.27|2.90|
|1989|0.90|0.62|-4.11|-0.28|5.79|1.64|1.36|-4.19|-0.06|-0.59|1.00|1.30|-4.14|-0.19|2.68|1.33|1.26|<br>-3.73|-0.14|6.73|
|1990|0.75|1.20|-3.86|-0.24|5.87|1.01|2.31|-4.10|-0.05|-0.20|0.80|2.17|-4.09|-0.12|3.11|1.08|2.06|-3.71|-0.08|7.68|
|1991|0.56|1.90|-3.70|-0.18|5.38|0.38|3.06|-4.05|-0.05|0.75|0.49|2.87|-4.18|-0.07|3.07|0.62|2.65|-3.74|-0.08|7.95|
|1992|0.40|2.64|-3.61|-0.12|4.50|-0.04|3.50|-4.03|-0.07|1.58|0.23|3.31|-4.33|-0.05|2.89|0.20|2.94|-3.78|-0.10|7.89|
|1993|0.26|3.36|-3.58|-0.05|3.24|-0.23|3.63|-4.01|-0.08|2.03|0.07|3.48|-4.47|-0.05|2.64|-0.03|2.77|-3.80|-0.13|7.78|

GNP = Gross National Product PGNP = GNP Price Deftator NERN = KERN Weighted Effective Exchange Rate RS = Short-Term Interest Rate CUtRBL * Current Account Balance The numbers in GNP, PGNP, NERN and ER are percentage deviation from the baseline. RS is the change in the level.

CURBL is in billions of dollars.

'0
**Table 8a. Probability of being in school in the 6th grade, 1994 (Being at school in the 4th grade)**

|**Variable**<br>**Coefficient**<br>**St**|**d. Error**<br>**t-Statistic**|Prob.|
|---|---|---|
|**Native**<br>**schools**|||
|Constant<br>0.499|0.148<br>3.379|0.001|
|Control<br>0.115|0.174<br>0.660|_0.510_|
|Factor-<br>Characteristics<br>ofcommunity<br>& family<br>0.125|0.078<br>1.599|0.110|
|Factor<br>- Characteristics<br>of school<br>& system<br>-0.067|0.076<br>-0.876|0.381|
|N<br>769|||
|Log likelihood<br>-500.106|||
|F-statistic<br>15.597||0.000|
|Chi-square<br>62.386||0.000|
|Obs with Dep=l<br>493|||
|Obs with Dep=0<br>276|||
|Ex-ante<br>probability<br>64%|||
|Estimated<br>probability<br>(at means)<br>64%|||
|Estimated<br>probability<br>without<br>PARE<br>(control)<br>62%|||
|PARE<br>contribution<br>- percentage<br>gain probability|3%||
|**Rural**<br>**schools**|||
|Constant<br>0.496|0.144<br>3.441|0.1%|
|Control<br>0.271|0.168<br>1.613|10.7%|
|Factor<br>- Characteristics<br>of community<br>& family<br>0.184|0.076<br>2.419|1.6%|
|Factor-<br>Characteristics<br>of school<br>& system<br>0.121|0.075<br>1.617|10.6%|
|N<br>825|||
|Log likelihood<br>-519.618|||
|F-statistic<br>23.752||0.0%|
|Chi-square<br>95.010||0.0%|
|Obs with Dep=1<br>549|||
|Obs with Dep=0<br>276|||
|Ex-ante<br>probability<br>67%|||
|Estimated<br>probability<br>(at means)<br>67%|||
|Estimated<br>probability<br>without<br>PARE<br>(control)<br>62%|||
|PARE<br>contribution<br>- percentage<br>gain probability|7%||

Source: Own calculations.

Table 9 summarizes the results on test scores. The PARE program - when adequate and fully implemented - could cause an increase in performance for the average student in the range of 19 to 38% amongst rural students. For native students, the percentage change could be much larger, anywhere from 45 to 90%. If consideration is taken of the factors affecting supply, such as the performance of teachers, principals and supervisors, on the plausible assumption that this performance is in part a product of the program, the total impact could be even larger.

12
2009. Similar to the analysis performed for Jordan, we define the sample as women and men aged 15 or more in 2006 and up to 64 in 2009. The sample includes 4,261 women and 3,641 men who were present in both waves of the survey. We define an indicator of household internet adoption or continuation between 2006 and 2009 as the explanatory variable of interest and the change in labor force participation as the outcome variable. Table 9 shows that women’s labor force participation increased from 49 to 52 percent between 2006 and 2009, while men’s rate improved from 78 to 84 percent. Internet access at the household level moved from approximately 20 to 37 percent.

In Chile, the public fixed telephone network has been the most significant component of the internet access infrastructure at the beginning of the 2000s (Cominetti C. (2002)). Our hypothesis is that access to a fixed telephone line at that time is a good predictor of the distance to the system’s backbone in future year, and thereby to internet access. We propose to use the share of households in each province that had a fixed telephone line in 2002 as an instrumental variable for the indicator of internet adoption or continuation between 2006 and 2009. We used information from the national 2002 Census which shows that this share ranged between 0.13 and 0.75.

We estimate OLS and IV models using individual and household observable characteristics in 2006 as control variables. We include the same set of regressors as in the previous models for Jordan –age, educational level, marital status, indicator of urban area, household size, and per capita household income. Models include region fixed effects and standard errors are clustered at the province level. Our main results appear in Table 10. Panel A presents the second stage estimates, while Panel B summarizes first stage results. The share of household that in each province had a fixed telephone line in 2002 is a good predictor of internet access or continuation between 2006 and 2009, and the F statistics of the first stage passes the usual threshold. Panel B shows an increase in women’s labor force participation under OLS, but the effect disappears when we perform the IV estimation. For men, the effect of internet adoption or continuation is negative but not significant in any case. This 14
average of December to February, spring is the average of March to May, summer is the average of June to August, and fall is the average of September to November.

Socio-economic data is obtained from the Household Income and Expenditure Survey (HIES) administered by China National Bureau of Statistics in 2001. There are more than 50,000 observations in the HIES. We have selected a sub-sample from only those counties for which we have climate data (from meteorological stations located in these counties). Our final sample has 8,405 households in 915 villages in 124 counties in 28 provinces.

The HIES includes a number of household and village characteristics. Irrigation data were collected at the village level. Information about crop choice was collected at the farm level. Nine major crops were identified: cotton, maize, oil crops, potato, rice, soybean, sugar, wheat and vegetables. Additional household variables include the education level of members of the farm household, each family’s land area, the number of family laborers that belong to the household. Additional village variables include indicators about the topographical environment of each village (e.g., if it is located on a plain or in a mountainous region), the share of cultivated area that is irrigated in the village, membership in associations, extension service, and access to markets (e.g., the presence of paved roads between the village and key services; the distance to each township’s government).

To account for soils, we downloaded a soil map from FAO’s website. There are three major soil types—clay, sand and loam soils. The final set of soil variables for our analysis was created by generating a variable measuring the share of cultivated area with each type of soil.

# **IV. RESULTS**

In this section, we report the results concerning irrigation choice and crop choice across farmers operating under present situation. This is a cross sectional analysis exploring how the range of current climate across China affects choices of irrigation and crops today.

7
(b) Postings and Physician Preferences Table 2 presents the UCT survey results on the perceived the prevalence of parallel systems. A high percentage of respondents in both states agreed with statements about managing initial and post transfer postings through “unofficial financial dealings.” In general, a higher percentage of (post- reform) State A respondents considered parallel systems to influence post-transfer than (pre-reform) State B respondents. However, a higher percentage of State B respondents considered these systems to affect initial postings than their State A counterparts.

|**Table 2. Postings in States A**<br>**Unmatched Count Technique(UCT) Sur**<br>|**and B**<br>**vey Results, 2011**<br>**UCT Score**<br>|**(%)**<sup>**a**</sup>**; (CI)**<sup>**b**</sup><br>|
|---|---|---|
|**Summary Statement**|**State A**|**State B**|
|Desired place of initial postings can be obtained through|65.3|81.4|
|unofficial financial dealings|(45.6-85.0)|(67.0-94.9)|
|Desired place of post-transfer postings can be obtained|89.1|67.8|
|through unofficial financial dealings|(65.5-112.8)|(48.9-86.6)|

aThe UCT scores represent the proportion of respondents (medical officers) who agreed with the specific statements in comparison to a control group not provided the same statement. The statements did not ask whether the respondents participated in such behaviors. b95% confidence interval.

Table 3 displays the results of the perception survey on posting preferences, processes and parallel systems. Using political connections appears to be the most effective route to secure a desired posting in both states (about 85 percent of respondents in both states) or avoid an undesirable one. The counseling policy is welcomed by physicians in post-reform State A. Over 70 percent of respondents agree that it has increased the transparency of posting practices. However, results suggest systematic deviations from formal processes and the DH does not divulge full information during counseling. It is common knowledge among State A respondents that the DH suppresses highly desirable locations near urban areas during counseling (86 percent). DH officials maintain that desirable vacancies are not revealed in order to first fill less desirable rural and tribal ones. But only about half of respondents consider this the reason. The findings suggest that the reform measures are not regularly applied, or can be readily bypassed through parallel systems. Most respondents (81 percent) consider that highly coveted postings are suppressed to enable an alternate posting process based on political influence and financial transactions.

9
the required level) leads to a reduction by _x_ % in production.

The parameter _ψ_ also depends on the heterogeneity of produced goods and services within each sector of the model. If _ψ_ = 0, all businesses in one sector produce the same goods or services, and one business that cannot produce can be replaced by another business of the same sector. As a consequence, model inventories consist of only one type of goods (or of perfectly substituable goods). Production is thus impaired only if the inventory of one sector production is totally empty. If _ψ_ = 1, then businesses from a sector produce different goods and services that are not perfect substitutes. Model inventories include thus many different (and imperfectly substituable) goods. A reduction by _x_ % in the sector _i_ inventory of goods _j_ represents thus a situation in which some goods produced by the sector _j_ are scarce and reduce production in sector _i_ , while other goods produced by sector _j_ are still available in inventories. For instance, if sector _i_ is the manufacturing sector and sector _j_ is “mining and extraction”, a reduction in the manufacturing-sector inventory of mining goods can mean that the manufacturing sector is lacking iron, even though sufficient oil supplies are available. In such a situation, even a small reduction in inventory can lead to a reduction in production by the manufacturing sector.<sup>4</sup> The choice of _ψ_ is therefore a crucial one, which represents assumptions about scales and heterogeneity in the economic system. First, the choice of _ψ_ may be different if the model represents a small economy that is entirely affected by the event ( _ψ_ would then be low), or a large 4 As an illustration of how difficult it can be to find alternative suppliers, The New York Times (2011a) explains that Ford had to deal in March 2011 with a shortage of a metallic pigment that comes from a plant in the evacuation zone around Japans Fukushima Daiichi nuclear plant. It reports that _“Ford, which has stopped taking orders for vehicles to be painted tuxedo black and is building fewer models in several red hues, is studying whether it can get a substitute from another supplier, according to a company spokesman, Todd Nissen. But making such a switch is not simple, Mr. Nissen explained, because each component on a vehicle undergoes complex testing, and swapping in a new paint could result in mismatched portions or a less durable finish. In addition, finding replacement parts in the proper color later on could be impossible.”_ 15
significant, however.

The treatment offer reduced total monthly earnings among female participants in garment making by almost 11 GHS (15 percent) compared with the control group, although the p-value is just outside the threshold for marginal significance. The reduction in total earnings was driven by noisy reductions in wage earnings and self-employment income. Although the estimated coefficients on farming and apprenticeship income are positive, the magnitudes are negligible and statistically insignificant.

# **4.2.2 Material Well-Being**

We present results on durable household assets, personal consumption expenditure on a limited set of items (such as phone calls), savings, loans, and migration in Table 6. These indicators enable us to examine broad measures of individual welfare. Our durable household assets index measured whether the household in which the respondent lived owned any of the following items: a radio, television, car, motorbike, and refrigerator, with the restriction that these items had to be functioning at the time of the endline survey (Column 1). Previous studies constructed similar indices based on householdowned durable assets for measuring poverty and conducting welfare analysis (Booysen, Van Der Berg, Burger, Von Maltitz, & Du Rand, 2008; Filmer & Scott, 2008). Although the overall (full-sample) treatment effect on durable household assets is positive, it is not statistically significant. For male participants in construction, however, the intention-totreat estimate is negative and insignificant. Among female participants in cosmetology the program offer increased assets by 0.1 _σ_ (p-value _<_ 0.05), but this is not very robust to multiple testing adjustments. The estimated effect among female participants in garment making is small (0.03 _σ_ ) and insignificant. Overall, these results could be driven by the greater propensity for cosmetologists to finish training and shift into self-employment, leading to greater asset accumulation.

Because of time and budget constraints, we could not field a full detailed consumption module. Rather, we measured personal consumption expenditure as the sum of the respondent’s expenditures on phone credit, personal items, and eating out during the week before the endline survey (Column 2). We do not find any evidence that the program altered spending patterns on these items. Further, we do not find any evidence that the program had an effect on savings behavior or borrowing activity (Columns 3 and 4).

Finally, we examine whether the program led to greater migration (Column 5). Migration can be viewed as an investment, where migrants move to pursue economic opportunities. For the full sample we find that the program offer increased the probability of 18
combined share in the estimated reference price of cane in each state , and on average for the three states, are shown in Annex 18. The averages for the three states are illustrated in Fig 2 1. The steep increase in the share of the costs of the tradable inputs in the reference price of sugarcane in 1985 and 1986 was due to the decline in world sugar prices in those years and the corresponding decline in the reference price of cane to very low levels. The changing weighted average NPC of the tradable inputs was mainly influenced by the nominal protection of fertilisers, but also partly reflects changes in the NPC of seeds which was assumed to equal the cane NPCs.

Figure 21: **TRADABLE INPUTS USED IN SUGARCANE FARMING: AVERAGE NPCs AND SHARE** OF **TRADABLE INPUT COST IN REFERENCE PRICES** <!-- Start of picture text -->
1.20  ...  ... ..... ..  . . . ...  .<br>0  0.80  -- - -- - ---------<br>0.60  - . . . . .NPC<br>O  -in-  ~~~~~~~~~~~~~~~~~~~~~~~OIRIOR<br>_  0.40  ------  ----------  -----  - - .......  ........  ''~  '-''-  .....  ~ ''''~-  ......... ''  'dF  O RO<br>o.2 0  -- -- - -- -- - -----  .. ....  ...........l<br>0.00<br>1981  1982  1983  1984  1985  1986  1987  1988  1989  1990<br>Crop years<br><!-- End of picture text -->

Sources and notes: Annex 18. NPC is the weighted average NPC of the tradable inputs used in cane farming. OIR is the total value of the tradable inputs used in the three states valued in reference prices. OR is the total value of cane output in the three states valued in reference prices.

The EPCs in each of the three states and the weighted average of the three, which we use as an approximation of the all-India average EPC, are given in Table 13 and the state level EPCs are plotted in Fig 22. On average during this period effective protection was much higher in UP than in the other two states, but this is principally due to the assumptions made in estimating the reference price of sugar in UP, discussed previously. Another reason is that during 1985-87 the minimum reference prices used for cane in UP (also discussed previously) were lower than in Mahrashtra and TN and the reference processing margin there (value added in reference pricessee Annex 18) was squeezed more than it was in the other two states.

49
**Table 21: Annual value added per worker (in million LCU) in presumed comparative advantage industries by age group of enterprises ‐    weighted estimates of totals at 2000 prices) , UBI 2002 and UBI 2009‐**

|**_A. All comparative_**|**_advantage industr_**|**_ies_**|**_E. Comme_**|**_rcialfarming_**|
|---|---|---|---|---|
|Age Group|Annual val<br>worker|ue added per|Annual value|added per worker|
|(years)|2002|2009|2002|2009|
|< 5|2.6|15.7|4.6|7.5|
|5 to 10|3.8|25.3|2.9|6.6|
|More than 10|3.0|20.2|1.2|11.5|
|Total|3.0|20.1|2.1|9.8|
|**_B. Comparative adva_**|**_ntageprimary ind_**|**_ustries_**|**_F. Food an_**<br>**_industry_**|**_d beverages_**|
||Annual val|ue added per|||
|Age Group|<br>worker||Annual value|added per worker|
|(years)|2002|2009|2002|2009|
|< 5|4.3|7.8|2.1|10.2|
|5 to 10|2.8|6.6|4.2|76.6|
|More than 10|1.3|10.7|6.7|30.5|
|Total|2.1|9.3|4.0|33.9|
||||**G. The**|**garments**|
|**_C. Comparative advanta_**|**_ge manufacturing_**|**_industries_**|**industry**||
||Annual val|ue added per|||
|Age Group|<br>worker||Annual value|added per worker|
|(years)|2002|2009|2002|2009|
|< 5|2.0|22.7|1.5|42.1|
|5 to 10|4.0|50.5|0.9|5.3|
|More than 10|5.6|22.0|1.2|2.2|
|Total|3.5|27.1|1.3|15.9|
|**_D. Comparative advant_**|**_age services_**||**H. Land tran**|**sport services**|
||Annual val|ue added per|||
|Age Group|worker||Annual value|added per worker|
|(years)|2002|2009|2002|2009|
|< 5|4.3|2.5|4.6|2.8|
|5 to 10|6.2|7.8|6.5|4.8|
|More than 10|8.8|163.9|8.9|28.4|
|Total|6.4|99.7|6.7|19.3|

58