rafmacalaba/datause-encoder-data huggingface dataset:
24

# CHAE III DUCATQN

Of all social indicators, educational data<sup>have probably displayed the</sup> strongest expansionary trends over the<sup>last three decades. In most developing</sup> countries, enrollments have increased at<sup>all levels of education, soaring</sup> especially at the primary level. The absolute<sup>number of children enrolled in</sup> primary schools in the developing world<sup>increased by almost 200 million</sup> between 1965 and 1985.19 Yet, in spite of the tremendous progress<sup>accomplished so far, there</sup> remain many problems associated with<sup>education in developing countries.</sup> First, the spectacular increase in absolute<sup>enrollment figures hides the even</sup> larger increase in population growth.<sup>Therefore, the target of Universal</sup> Primary Enrollment (UPE), heralded by<sup>many in the 1960s, has remained so far</sup> an empty promise, with some 150 million<sup>children still out of school in</sup> developing countries by 1985.20 Second, enrollment figures conceal attendance<sup>data. Often, children</sup> officially registered in school do<sup>not show up in class. Not so infrequently</sup> either, teachers may display high levels<sup>of absenteeism. Governments are also</sup> sometimes known to inflate enrollment<sup>figures, considered as a sign of their</sup>

> 19Lockhoed, Verspoor and others, Improving Primary<sup>Education in Develoning</sup> Coun&rIss: A Review of Poligy Options<sup>(Washington,</sup> D.C.: World Bank, 1990). 20Lockheed, Verspoor and others (1990), op. cit.
hypothetical nature of the contingent valuation surveys can be kept to the minimum, as it is real project under preparation.

A multiple-stage stratified random sampling approach was adopted to select sample in Qiubei County. In the first stage, based on the project area and beneficiaries, geographical boundaries (e.g. districts, urban and rural) were determined so that the sample can cover all the geographical areas and spatial representations of the project. Qiubei County was therefore selected in this first stage. After considering the survey cost and the population covered in Qiubei, a total sample size of 500 was determined. In stage two, Qiubei County was further divided into several functioning zones based on their relations to the project implementation and the impacts by the project, and a list of representative functioning zones were chosen to conduct the survey. In stage three, those selected functioning zones were further divided into communities, and a number of communities were randomly selected to conduct the survey. In stage four, a list of households in each community was obtained with the help of local project workers, and the team randomly picked households from the list to ensure the principle of representation in sampling. The sample sizes were determined to be proportional to the population sizes of different categories. **Table 2** illustrates the detailed sampling statistics in Qiubei. We obtained totally 507 relatively well-filled questionnaires. Among them, 245 coming from the urban areas: 100 coming from the Qiubei county town (County government area, Donghu, Zhenxing, Xiazhai, Qiaotoucun / Xiaoxinzhai / Shuizhai), and the rest of sampled respondents from rural area (82 from 8 villages within the lake area, 125 from 56 villages around the lake, 200 from remaining rural districts in the county).

Specifically trained enumerators from Yunnan Environmental Information Center conducted in-person interviews. Care was taken that only the head of a household was interviewed, who should be well aware of overall income and expenditure of the household, and who can decide about additional expenditures. Neutrality as well as anonymity of the survey was ensured at the beginning of each survey. About 50% of the interviews were conducted with a one-on-one, traditional personal interview format, where an enumerator read the questionnaire and recorded down the answers. Another 50% of the interviews were conducted with a group setting, where 4 to 6 respondents sit together in a room and wrote down their answers independently while an enumerator read the questionnaire and provided instructions; the answers of the respondents were not shared with each other and privacy and anonymity were ensured. With a group setting, the potential interviewer effect may be reduced but the completeness of the questionnaire answers may suffer. Each individual interview lasted approximately 20-30 minutes, and each group interview lasted about 40-50 minutes. At the end of each field day, field coordinators checked the returned questionnaires for completeness and accuracy according to a quality checklist.

7
_of Labor Economics_ , 27(3):349–383, July 2009. URL https://ideas.repec.org/a/ucp/ jlabec/v27y2009i3p349-383.html.

James Heckman and Flavio Cunha. The Technology of Skill Formation. _American Economic Review_ , 97(2):31–47, May 2007. URL https://ideas.repec.org/a/aea/aecrev/ v97y2007i2p31-47.html.

Jennifer Hunt. The Impact of Immigration on the Educational Attainment of Natives. _Journal of Human Resources_ , 52(4):1060–1118, 2017. URL https://ideas.repec.org/a/uwp/ jhriss/v52y2017i4p1060-1118.html.

- Peter Jensen and Astrid Wrtz Rasmussen. The effect of immigrant concentration in schools on native and immigrant children’s reading and math skills. _Economics of Education Review_ , 30 (6):1503–1515, 2011. doi:10.1016/j.econedurev.2011. URL https://ideas.repec.org/a/ eee/ecoedu/v30y2011i6p1503-1515.html.

- Alan B. Krueger. Experimental Estimates of Education Production Functions. _The Quarterly Journal of Economics_ , 114(2):497–532, 1999.

- Alan B. Krueger and Diane M. Whitmore. The Effect of Attending a Small Class in the Early Grades on College-Test Taking and Middle School Test Results: Evidence from Project STAR. _Economic Journal_ , 111(468):1–28, January 2001. URL https://ideas.repec.org/a/ecj/ econjl/v111y2001i468p1-28.html.

- Helen F. Ladd and Edward B. Fiske. Weighted student funding in the Netherlands: A model for the U.S.? _Journal of Policy Analysis and Management_ , 30(3):470–498, June 2011.

45
# **CONCLUSION: THE NEED TO FOCUS ON IMPLEMENTATION, COMPLIANCE AND ENFORCEMENT**

The main conclusions of the report can be summarized as follows: 69. **_Romania performs quite well on the PMR indicators, showing a significant improvement since 2002: out of the 15 low-level indicators underlying the overall PMR, Romania has achieved best practice in seven._** These comprise most of the ones falling under _barriers to entrepreneurship_ (licenses and permits systems, communication and simplification of rules, administrative burden for corporations, legal barriers to competition and antitrust exemptions), and two of the four that make up _barriers to trade and investment_ (discriminatory procedures and regulatory barriers). In these indicators Romania performs better than the OECD average and on a par with the best OECD countries. A third one – tariffs - has now been brought down to the EU average.

70. **_Romania could still achieve significant progress in the extent of control the state still exerts over the economy._** Indeed, as Figure 19 demonstrates, Romania is still far from the OECD average, let alone best practice,<sup>12</sup> with respect to the size of the public enterprise sector (although as noted above, this may well be driven by the estimation techniques used in this). More importantly, Romania is also far from best practice relative to the nature of the _control of public enterprise by legislative bodies_ , notably through the government’s share in Petrom. On the _scope of the public enterprise sector_ , the existence of _price controls_ and reliance on _command and control regulation_ performance is close to the OECD average. Finally, in the areas of foreign ownership barriers and sector specific administrative burden, it is already better than the OECD and very close to best practice on all three counts.

**Figure 19. Remaining gaps compared to the OECD average**

<!-- Start of picture text --> Romania Ow nership barriers<br>OECD average 5.0<br>4.0<br>Size of public sector 3.0 Sector specific burdens<br>2.0<br>1.0<br>0.0<br>Scope of public enterprise<br>Direct control<br>sector<br>Use of command & control Price control<br><!-- End of picture text --> 71. Concerning the use of command and control regulation, concrete steps could be for the Government to issue guidance and training on using alternative to traditional regulation – which as Annex Table A2.5 shows, is the principal remaining improvement

> 12 In the PMR system “best practice” would correspond to an indicator value close to zero, meaning that no regulatory restrictions are imposed.

27
The achieved sample of 475 schools was further screened for this analysis. First, data from the two "private schools" strata (17 schools) were not included in this study. Second, only grade five classes from complete primary (grades 1-6) and complete primary and secondary (grades 1- 10) schools were retained, reducing the sample by 39 schools that reported alternative grade configurations. Schools with alternative configurations were excluded because they represented "unofficial" school types. The final analytic sample contained 419 schools.

# Procedure=

Students were administered a science test, a mathematics test, and a background questionnaire. Teachers completed several instruments, including a background questionnaire, information about their teaching practices and characteristics of their randomly selected class. Data about the school were provided by a school administrator. Although very many measures were collected in the IEA study, only those used in this paper are described below.

Because of the size of the student sample and the focus of the research.on teacher practices and classroom organization effects on average student achievement, all data have been aggregated at the classroom level. The effects of teaching practices or classroom organization on within-class variations in achievement have not been addressed in this paper. Nor does this paper address the issue of the relative impact of individual or grouplevel variables on achievement. Its purpose is to compare effects of 18
taxes would be set so as to achieve national air quality standards for sulphur oxides and particulates based on the U.S. Environmental Protection Agency emission standards for new sources. Terkla uses the mid-seventies estimate from the public finance literature of $0.35 for the marginal welfare cost of a dollar of labor income tax revenue. For the marginal welfare cost of corporate income taxation, he takes $0.56 per dollar from Feldstein's (1978) twoperiod life cycle model. The estimates of marginal welfare loss are consistent with figures generated more recently from a computable general equilibrium model of Ballard, Shoven, and Walley (1985).

Terkla's argument is important since so many developing countries currently raise revenue from a very narrow tax base with highly distortionary commodity taxes (The World Bank, 1990). The efficiency value of pollution taxes is best viewed as an element in the instrument choice debate. The argument is relevant whether or not the polluting inputs and outputs are already taxed as part of the country's revenue base. Suppose all taxable goods in the economy are initially taxed (for revenue-raising purposes only) so that the marginal excess burden (exclusive of the impact on environmental quality) is the same across taxable commodities. If good X is a particularly polluting commodity, either in its use as an input to production or through its consumption as a final good, its use can be curbed in two ways: a quantity restriction on polluting emissions or an increase in the per unit tax levied on 59
overdue payments.<sup>3</sup> 1 These findings are consistent with hypothesis 5 that bribe extraction is higher when the firm is vulnerable to threats by the utility employees.

**_Enterprise_** _Size._ European Bank for Reconstruction and Development (1999, p. 125-126) finds small enterprises in Eastern Europe and Central Asia generally paid higher total bribes (i.e., to all sources not just than large enterprises. Consistent with this, and even after controlling for other factors that might affect corruption, we find that small enterprises generally pay higher bribes than large enterprises (see Figure 3). Enterprises with fewer than 50 enterprises paid about 1.5 percentage points as bribes to utilities po of revenues than enterprises with more than 500 I employees, while enterprises with

<!-- Start of picture text --> 2.0-<br>1.5 -7 |that<br>1.0 --<br>0.5 | | | _utilities)<br>0.0 . . . . _<br>Less than Between Between Between Between<br>9 10 and 49 50 and 99 100 and 200 and<br>199 499<br><!-- End of picture text -->

Figure 3: Coefficients on enterprises size dumrnies in regressions on bribes paid to utilities as percent of revenues (relative to enterprises with over 500 employees).

Data Source: The World Business Environment Survey (WBES) 02000 The World Bank Group.

Note: Graph shows coefficients on size dummies from regression shown in column I of Table I. Omitted category is enterprises with more than 500 employees. Consequently, coefficients can be interpreted as the additional percent of revenues paid by enterprises of that size over a similar enterprise with more than 500 employees, between 50 and 500 employees paid about 1.0 percent of revenues more in bribes (see Figure 3). The differences between the amounts paid by enterprises of different sizes are statistically significant.<sup>32</sup>

**_Ownership_** _of_ **_Utilities._** Consistent with hypothesis 2, enterprises paid lower bribes to utilities in countries where the fixed line telecommunications and electricity distribution were privately owned (see Table 3). In the regression that excludes the measure of enterprise profitability (i.e., margin), the coefficients on both dummy variables are statistically significant.

> 31The index variable is coded as I for substantial, 2 for manageable, 3 for modest and 4 for none.

> 32 The null hypothesis that enterprises of all sizes pay similar share of revenues in bribes can be rejected at less than a 1 percent significance level (X2 (5) = 30.37, Prob.> X<sup>2</sup> is 0.00).

18
commercial banks in the system were sound enough to assist substantially in the resolution of the small banks. The RTC's success was helped by the fact that most of the assets to be disposed of were real estate loans/or assets or mortgage loans that could relatively easily be bundled and securitized or sold via bulk sales. Moreover, a deep and sophisticated capital market and a recovery in the real estate market also proved advantageous for the RTC as did an effective organizational and governance structure and skilled personnel. Despite succeeding in selling the 26 banks, the Spanish Guarantee fund proved to be less successful in disposing of the assets that had been carved out prior to the sale of the institutions, and part of the assets remain with the Fund even today. Despite an overall benign macro-environment and rising real estate prices, asset disposition was hampered by an inadequate legal framework and administrative obstacles (Table 2). For examples, the fund did not have the legal title or they were not registered for some of the real estate assets.

Both Fobaproa and APT were also not successful in achieving their broader objectives, i. e. helping to build a more robust banking system as the Mexican banking system remains weak and one of the two banks that were cleaned up in the Philippine case appears to be in financial distress again. In addition, Fobaproa's repeated loan purchases at Mexican banks coupled with debt relief for borrowers, led to a general deterioration of the payment discipline and asset prices. Moreover, loan growth did not recover and remained strongly negative in Mexico. In contrast, banking sector solvency problems did neither reoccur in Spain nor in the US.

**Table 2 GDP and Real Credit Growth**

|||GDP gro|wth (in pe|rcent)||Rea|l credit gr|owth (in pe|rcent)|
|---|---|---|---|---|---|---|---|---|---|
||Year of AMC<br>establishment|One year<br> <br>prior|Year of<br>set up|One year<br>after|Two years<br>after|One year<br>prior|Year of<br>set up|One year<br>after|Two years<br>after|
|Finland|1993|-3.55|-1.18|4.55|5.06|-8.95|-10.59|-10.63|-3.82|
|Ghana|1990|5.09|3.32|5.31|3.89|100.44|-16.73|-20.55|41.76|
|Mexico|1995|4.42|-6.17|5.18|6.71|27.93|-30.70|-36.70|19.56|
|Philippines|<br>1987|3.42|4.31|6.75|6.21|-21.12|17.04|5.26|11.41|
|Spain *|1980|0.04|1.30|-0.18|1.57|-0.60|2.20|2.00|2.79|
|Sweden|1992|-1.66|-1.42|-2.22|3.34|-9.21|-2.38|-23.06|-6.23|
|USA|1989|3.82|3.36|1.23|-0.93|5.63|5.35|0.23|-2.10|

_Source:_ IMF, International Financial Statistics. * For Spain: Year when the Deposit Guarantee Fund was granted legal powers for bank restructuring.

12
from daughters (51.4%) than from sons (67%).

Wives are likely to contribute more to old age support than husbands inside the household. The SSCCW survey asked urban husband and wife separately on who is the main provider of certain types of house work, including home service to the elderly. Conditional on existing need of home service to the elderly, 40% of husbands and 57% of wives said they were the main service provider in the house. Husbands seem to have a bias in exaggerating their role as the main contributor: while only 39% of husbands admitted that their wives being the main provider of old age support, 57% of wives claiming themselves being the main provider. Similarly, 23% of wives credited their husbands as the main contributor of old age support in the house, while 40% of husbands credited as such themselves. Unfortunately, this question was not asked in the rural sample, but rural couples were more likely to live with the husband's parents at the time of marriage (59% rural, 31% urban, according to husband's answer), and it is quite rare to live with the wife's parents in both rural and urban areas (5% rural, 6% urban, according to husband's answer). At the time of the survey, fewer rural couples were still living with the husband's parents (29% rural and 39.9% urban), but this is partly because more rural parents have passed away, and rural parents have more children to live with so that the probability of living with a particular child would be lower.

To recap, the survey data conrm that rural parents rely more on their children for old age support, and old age support is typically provided by son and daughter-in-law. Between the couple, the wife is more likely to provide home services to the elderly if such need arises. All these suggest that parents have strong incentives to participate in the choice of daughter-in-law, especially in the rural areas.

# 3.3 Key Variables

The question on matchmaking methods asked how an individual met his or her spouse initially. There are four original categories in the data: introduced by parents or relatives, by friends, by themselves, and by other means. We dene a dummy of _ParentMatch_ equal to one if the husband has been matched by the introduction of parents or relatives and 0 if otherwise. We cannot distinguish parents from relatives partly because the distinction is not available in the data, partly because relatives are an integrated part of the parents' social networks to facilitate the search process. A perhaps more debatable decision is that we do not dierentiate couples initially introduced by friends from those who met by themselves. The reason is that these two groups are similar: in both cases, it is the young people themselves, not their parents, that conducted the search process and bore the search cost. And indeed, empirically these two groups are very similar.

16
# **Table 5. Tier 1 and Tier 2 capital and common equity**

The dependent variable is the quarterly stock return. See Table 4 for a detailed description of the estimated model. The sample period for the stock return is Q1-2006 to Q1-2009. All control variables are lagged one year. Crisis is a dummy variable that takes value one from Q3-2007 to Q1-2009. Tier1 (Tier2) is Tier1 (Tier2) capital scaled either by riskweighted assets (RWR) or total un-weighted assets (LR). Tier1 capital includes shareholder funds plus perpetual, non-cumulative preference shares, plus retained earnings. Tier2 capital includes subordinated debt, hybrid capital, loan loss reserves, and valuation reserves. Common equity is shareholders fund and other capital total regulatory capital minus common equity. We report estimates for the whole sample and the sample of large banks. Large banks are defined as banks with total assets above 50 billion US $. Standard errors - - clustered by bank are reported in brackets and the p <u>value for the test of significant difference between the pre crisis and crisis coefficients in parentheses.</u>

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
||Whole s|ample|Large|banks|Whole s|ample|Larg|e banks|
||**RWR**|**LR**|**RWR**|**LR**|**RWR**|**LR**|**RWR**|**LR**|
|Tier1*PreCrisis|0.024|0.110*|-0.092|0.061|||||
||[0.046]|[0.061]|[0.129]|[0.149]|||||
|Tier2*PreCrisis|0.074|0.006|-0.106|-0.252|||||
||[0.055]|[0.072]|[0.145]|[0.178]|||||
|Tier1*Crisis|0.117|0.154|0.264|0.603***|||||
||[0.080]|[0.108]|[0.186]|[0.210]|||||
||(0.120)|(0.623)|(0.041)|(0.003)|||||
|Tier2*Crisis|0.051|0.058|0.131|0.415|||||
||[0.098]|[0.188]|[0.257]|[0.350]|||||
||(0.809)|(0.810)|(0.369)|(0.115)|||||
|Common equity*PreCrisis|||||0.015|0.048|-0.005|-0.003|
||||||[0.018]|[0.034]|[0.089]|[0.143]|
|Other capital*PreCrisis|||||-0.097***|-0.079|-0.053|-0.214*|
||||||[0.034]|[0.059]|[0.083]|[0.112]|
|Common equity*Crisis|||||0.114**|0.165**|0.283**|0.617**|
||||||[0.044]|[0.067]|[0.126]|[0.278]|
||||||(0.047)|(0.014)|(0.012)|(0.035)|
|Other capital*Crisis|||||-0.015|0.002|0.324**|0.561*|
||||||[0.076]|[0.102]|[0.144]|[0.293]|
||||||(0.407)|(0.251)|(0.008)|(0.015)|
|Controls*Crisis|x|x|x|x|x|x|x|x|
|Controls*PreCrisis|x|x|x|x|x|x|x|x|
|Country*Year FE||||||x||x|
|Nber. Obser.|4049|3726|827|736|3654|3700|745|748|
|R squared|0.23|0.23|0.32|0.33|0.23|0.23|0.32|0.32|

Note: (*), (**) and (***) stand for statistically significant at the 10%, 5 % and 1 % level, respectively. Robust standard errors 22