rafmacalaba/datause-encoder-data huggingface dataset:
discrepancies could be lessened with more detailed micro-level household data and more detailed administrative information on how particular elements of the system operate. While acknowledging the limitations of the CEQ methodology with the existing data for Cambodia, the analysis does provide useful insights into the operation of the tax and benefit system in Cambodia.

# **5. Potential Reforms and Policy Direction**

To enhance the poverty-reducing effect of fiscal policy, the following Conditional Cash Transfer (CCT) simulations provide examples of potential policy reforms which could address the challenges of the current system. Each reform scenario has a specific cost and scale of poverty reduction. As presented earlier, the IDPoor equity card presents a useful device for targeting CCT towards households at the lower end of the income distribution. The card can be combined with other features of households, such as their demographic characteristics, location, or access to facilities to further narrow down the groups of recipients. In countries where such a program is not in place, targeting often relies only on the latter information which often makes targeting less precise and means that significant proportions of benefits are often allocated towards richer households.

Increasing the amount of targeted cash transfers to households with children under 3 has a sizable poverty-reducing effect. Simulations demonstrate increasing cash transfers targeted to IDPoor households with young children from about US$ 63 per year (US$ 190 over 1,000 days) to US$ 200 per year would reduce the poverty rate by 0.11 percentage points. Similarly, a targeted cash transfer of US$ 400 per year would reduce the poverty rate by 0.23 percentage points. Policies calibrated to the same total costs but implemented in a universal fashion (i.e., without the use of the IDPoor equity card to identify eligibility), thus allocating lower average values to the households which fulfill the demographic requirements, have a much smaller poverty-reducing effect.

Table 6: Poverty reduction and cost of four CCT scenarios aimed at IDPoor households

|**CCT scenario**|**Design**|**Poverty**<br>**reduction(pp)**|**Cost (millions**<br>**US$/year)**|
|---|---|---|---|
|CCT Version 1|200 US$ per year/child under the age of 3 in<br>households identified bythe IDPoor equitycard|-0.113|16.5|
|CCT Version 2|20 US$ per year/child under the age of 3|-0.062|15.7|
|CCT Version 3|400 US$ per year/child under the age of 3 in<br>households identified bythe IDPoor equitycard|-0.230|32.9|
|CCT Version 4|40 US$ per year/child under the age of 3|-0.113|31.4|

Source: Authors’ calculations based on CSES 2019/20 and fiscal data.

<mark>insurance, and salary taxes potentially stems from the high degree of progressivity of tax contributions and lack of highest earners in the data.</mark> 29
Policy ReseaRch WoRking PaPeR 4690

# **Abstract**

In determining domestic water prices, policy makers often need to use information about the demand side rather than only relying on information about the supply side. Household surveys have frequently been employed to collect demand-side information. This paper presents a multiple bounded discrete choice household survey model. It discusses how the model can be utilized to collect and analyze information about the acceptability of different water prices by different types of households, as well as households’ willingness to pay for water service improvement. The results obtained from these surveys can be directly utilized in the development of water pricing and subsidy policies. The paper also presents an empirical multiple bounded discrete choice study conducted in Chongqing, China. In this case, domestic water service quality was seriously inadequate, but financial resources were insufficient to improve service quality. With a survey of about 1,500 households in five suburban districts in Chongqing Municipality, this study shows that a significant increase in the water price is feasible as long as the poorest households can be properly subsidized and certain public awareness and accountability campaigns can be conducted to make the price increase more acceptable to the public. The analysis also indicates that the order in which hypothetical prices are presented to respondents systematically affects their answers, and should be taken into account when designing survey instruments.

This paper—a product of the Sustainable Rural and Urban Development Team, Development Research Group—is part of a larger effort in the department to address environmental governance issues in the developing countries. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at hwang1@ worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Department of Commerce (Adm inistration) issued final negative determinations. It held that the Czechoslovakian and Polish exports of wire rod had not received any "bounty" or "grant" under the terms of section 303, so that counterva iling duties on those items were not applicable.

The Administration concluded that, as a m atter of law, section 303 was inapplicable to non-market economies.<sup>47</sup> The Court of International Tr ade reversed, holding that the Administration's determination was contrary to law. The su bstantive issue in this case, here on appeal from the Court of Internati onal Trade, is whether the countervailing duty provisions in section 303 of the Tariff Act of 1930, as amended, _19 U.S.C. §1303_ (1982), apply to alleged subsidies gr anted by countries with so-called non-market economies for goods exported to the United States. The Ad ministration held that section 303 does not apply to non-market economies. The Court of Appeals for the Federa l Circuit reversed the ruling of the Court of Internationa l Trade and upheld the Adm inistration's determination that U.S. countervailing dut y laws should not apply to im ports from NMEs.<sup>48</sup> The U.S. Uruguay Round Implementing Act of 1994 did not explicitly change the U.S. jurisprudence described above, but Article 29 of the Subsidies Agreem ent concerns “Transformation into a Market Econom y,” and provides for a grace period of nonapplication for some subsidy rules, after which it seems the normal subsidy rules will apply.<sup>49</sup> A recent study analy zed the im pact of fore ign subsidization on the US steel in dustry (Blonigen and Wilson, 2007). The study covered data on 37 different steel products from 22 different foreign countries to the US market from 1979-2002. T he results provide strong evidence of both cyclical and structural excess capacity effects for exports to the US market. However, the effects are confined to such a narrow rage of country-product combinations that is un likely that such e ffects were a significant factor in the misfortunes of US steel firm s over the past deca des. The US steel indu stry fought hard and filed 241 CVD cases during 1980-2003, among which 78 cases (32 percent) were considered affirmative, and countervailing duties were charged. However, these duties only affected a small percentage of the total imports to the US steel market (Blonigen and Wilson, 2007).

# **VI. The First U.S. CVD Case on China**

# **A. CFSP Case Review: A Chronological Description**

On October 31, 2006, the NewPage Corporation of Dayton, Ohio, a U.S. manufacturer of glossy paper, filed a petition with DOC and ITC alleging that an industry in the United States is materially injured or threatened with m aterial injury by reason of subsidized a nd less than fair value (LTFV) imports of CFSP from China, Indonesia, and Korea. In the petition, NewPage

> 47 49 Fed. Reg. 19370, 19374 (1984).

> 48  Georgetown Steel Corp. v. United States, 801 F 2d 1308 (Fed Cir 1986).

> 49 John H. Jackson, p. 336, supra note 8.

21
- 54 -

financial covenants; and (ii) to raise consumer prices by certain amounts in order to decrease the overall fertilizer subsidy. No covenants proposed a link with international prices.

# B.3 Discussion of Adjustments to Efficiency Prices

15. At the producer price level there is only one relevant nonefficiency objective: financial viability. However, this has a somewhat broader interpretation in the fertilizer sector than it does in others. The argument is made that current international prices do not reflect long-run equilibrium for the industry. This implies that existing firms would alternate between periods of large profits and periods of losses or possibly even closure in favor of imports. In order to ensure continued financial viability for the industry most countries have developed cost-plus pricing systems for fertilizer at **the** factory gate.

16. The problems of cost-plus pricing are well recognized: a lack of incentiv, to minimlze costs, a tendency to build 'gold plated" plants, the difficulty of measuring managemnt performance, etc. Examples of many of these problems are cited in the SARs reviewed. However, the general tendency has been to tinker with the cost-plus systems (e.g., to base prices on normative rather than actual costs for each plant, to target capacity utilization rates with bonuses for exceeding them, etc.) rather than to devise a system based on estimates of long-run efficiency prices or to compare the inefficiencies and administrative costs of the existing system with the costs of closing and reopening plant as the international market dictates.

17. At the consumer price level, both income distributional and fiscal objectives are important. In all five countries farmgate prices were below border prices, and in three countries they were below ex-factory prices. All three of the latter had major fiscal problems created by fertilizer subsidies, and two mentioned allocative inefficiencies resulting from inappropriate price differentials between different types of fertilizer. Two projects included covenants requiring increases in consumer prices in order to reduce fertilizer subsidies.

# B.4 Discussion of Cost Recovery Issues

18. Because of the cost-plus systems for ex-factory fertilizer prices, cost recovery at the plant level was good in four of the five cases reviewed. Three of the SARs did not include financial covenants. The other two included covenants on debt equity (60:40 in both cases), current ratio (1.2 and 1.4) and debt coverage (1.2 and 1.3).
<!-- Start of picture text --> Proportion of teenage birth and union by cohort<br>All girls aged 15-20<br>99<br>°<br>8re) ° 5 ° 8<br>ae of SERS° fo) aw6 ees ° % o Toe<br>S| PoCQP PW oo CCHS, BS boF 2 cf 9° E<br>8 64. ® 5 %o 0609 6 ° G0 O90 RS —s—.6 &<br>Ke) fe) Oa Oona 2 © 6? © C09 Ke)<br>se 5 combo 5 os Sao OSD - gO 5 &<br>O'-6 > “oO o. 0 OS®<br>4 ° re} o®<br>o 4 ° 8° of 4<br>3 3<br>1955 1960 1965 1970 1975 1980<br>Birth cohort<br>© Birth between 15-20 © Union between 15-19<br>Note: the vertical line represents the first cohort subject to the 1985 reform.<br>Proportion of teenage birth and union by cohort<br>All girls aged 15-20 with at least Secondary Education<br>99<br>8<br>5° 0° 8<br>7} B25 Proxy B99 00 7<br>£ 64° 0S CR GH BWE—LP_—94 6<br>£Go 5 16 oO” onaes 2) Q, dle° oS5 £<br>— af . “e209 D0 6-4 £<br>° Oo a ole} oO °<br>x 34S o O° °oe& eae0%, 409s SO73| &<br>0 ° Xe) °&a9 ae &o+Fo0<<br>1955 1960 1965 1970 1975 1980<br>Birth cohort<br>© Birth between 15-20 » Union between 15-19<br>— Linear Fit — Linear Fit<br><!-- End of picture text -->

Note: the vertical line represents the first cohort subject to the 1985 reform.
**Annex 1: Empirical distribution of income across expenditure decile**

||**Nat**|**ional level**|**Ur**|**ban areas**|**R**|**ural areas**|
|---|---|---|---|---|---|---|
|**Decile**|**PS-94**|**PS-98**|**PS-94**|**PS-98**|**PS-94**|**PS-98**|
|1|1.8|1.8|.10|.10|3.2|3.3|
|2|2.6|2.7|.10|.40|4.7|4.9|
|3|3.2|3.4|.20|.50|5.7|6.1|
|**4**|3.9|4.1|.60|.90|6.6|7.0|
|**5**|4.7|4.8|.80|1.0|7.9|8.4|
|6|5.7|5.8|1.5|2.0|9.2|9.4|
|7|7.3|7.2|2.9|3.5|10.9|10.8|
|8|9.8|9.5|6.3|6.0|12.6|12.8|
|9|15|14.4|16.1|15.6|14.1|13.3|
|10|46.1|46.2|71.4|70|25.0|23.9|
|**All**|100|100|100|100|100|100|

**Annex II: Absolute deviation between mean per capita expenditure decile expressed as fraction of the poverty line**

||**Nat**|**ional level**|**Ur**|**ban areas**|**R**|**ural areas**|
|---|---|---|---|---|---|---|
|**Decile**|**PS-94**|**PS-98**|**PS-94**|**PS-98**|**PS-94**|**PS-98**|
|**1**|-.591|-.655|-.557|-.647|-.592|-.655|
|**2**|-.397|-.475|-.391|-.466|-.397|-.475|
|**3**|-.256|-.338|-.251|-.341|-.256|-.337|
|4|-.108|-.211|-.098|-.204|-.109|-.208|
|5|.071|-.058|.081|-.065|.069|-.057|
|6|.314|.133|.321|.139|.313|.132|
|7|.672|.405|.699|.427|.665|.398|
|8|1.251|.854|1.307|.861|1.228|.851|
|9|2.451|1.812|2.506-|1.878|2.410|1.43|
|10|9.652|8.032|10.015|8.794|8.892|6.446|

23
Beyond these mostly negative labor market trends, has the labor market been buoyant and can we observe positive developments that could point to a structural transformation of the economy setting the conditions for further growth? The period observed could be a period of economic restructuring with declines in employment and participation explained by increases in productivity and competitiveness. A simple decomposition of GDP growth into productivity, employment and population growth shows indeed that productivity growth is the single factor that explains better GDP growth followed by the growth in the working age population while changes in employment had a negative effect on growth (Table 1). This decomposition helps to explain the jobless growth story. Morocco has moved in the right direction in terms of growth policies and has become a more modern economy but these positive developments have not been able to be sufficiently strong to outweigh the growing working age population or sufficiently inclusive to expand employment.

**Table 1 – GDP Growth decomposition into productivity, employment and working age population (2006-2010)**

||Percent of total change in<br>per capita value added<br>growth|
|---|---|
|Total Growth in per capita GDP (value added)|100|
|Growth linked to output per worker|97.17|
|Growth linked to changes employment rate|-23.53|
|Growth linked to changes in the share of population of working Age|26.36|

Source: Authors’ calculations based on the Job Generation and Growth (JoGG) decomposition tool (World Bank) and HCP (2000-2010).

The question we want to address in the rest of the paper is whether this particular development pattern has resulted effectively in better occupations and better jobs and whether these changes have been homogeneous across population groups or rather unequal with winners and losers resulting, as a consequence, in a more segmented labor market.

# **3. Data, tools and framework**

The paper uses the panel component of the Moroccan Labor Force Survey (MLFS). The MLFS is a household survey covering all residents on the national territory. The sample size is 60,000 households, 40,000 urban and 20,000 rural, and contains information on all household members, approximately 270,000 individuals every year. This sample is divided into four equal independent sub-samples of 15,000 households each interviewed quarterly. Each sub-sample is representative at the regional level and by urban and rural areas. Sampling is a random three-stage process.

Starting from 2006, half the households are re-interviewed every quarter, which makes the survey a quarterly panel survey with one time lag of one year. And since 2007, interviews are conducted all year long by means 7
and publicly owned firms across 34 Western and Eastern European countries. The database includes up to 10 years of information per company, although coverage varies by country. Amadeus is especially useful because it covers a large fraction of new and small- and mediumsized companies (SMEs) across all industries. The Amadeus database is created by collecting standardized data received from 50 vendors across Europe. The local source for this data is generally the office of the Registrar of Companies.

The Amadeus database includes firm-level accounting data in standardized financial format for 22 balance sheet items, 22 income statement items and 21 financial ratios.<sup>8</sup> The accounts are transformed into a universal format to enhance comparison across countries. Although EU harmonization in accounting standards and practices has improved the comparability of accounting formats across countries in Europe, differences in accounting practices remain and these transformed accounts should therefore be interpreted with the necessary caution. We use IMF-IFS period average exchange rates to convert all accounting data into U.S. dollars.

In addition to financial information, Amadeus also provides other firm-level information. First, we use information on the year of incorporation to calculate the age of the firm. Second, we use firm-level employment to calculate the contribution of new and small firms to employment creation. Third, Amadeus includes the national industry code and assigns companies a 3-digit NACE code – the European standard of industry classification – which we use to classify firms and construct industry dummy variables.<sup>9</sup> In our analysis, we use NACE codes at a 2-digit level so that we have a sufficient number of firms per industry.

_1.2 Sample selection_

> 8 The coverage of these specific items varies across countries.  For example, many firms in Latvia and Russia have turnover variables missing and most firms in Slovenia and Croatia only report total liabilities and do not include a breakdown of their debt structures.

> 9 The NACE codes follow the NACE Revision 1 classification.

8
# **1 Introduction**

During the last century, India has experienced an almost continuous increase in the overall ratio of males to females, mainly because of excess mortality of girls.<sup>1</sup> During the last three decades, the ratio of males to females at birth has also increased as prenatal sex determination techniques became available, enabling parents to abort fetuses of an unwanted sex.<sup>2</sup> Although our understanding of the determinants of sex selection has improved, there is one important relationship that is still not well understood: the relationship between fertility and sex selection.

Research has been constrained by the absence of direct information on the use of sex-selective abortions; few questionnaires ask about sex selection, and those that do show signs of serious under-reporting (Goodkind, 1996). In the absence of direct information on sex-selective abortions prior research has relied on a simple method for determining the use of sex selection. With data on births one can estimate the effects of various characteristics on the probability of having a son, using the sex of the children born as the dependent variable.<sup>3</sup> In the absence of any interventions the probability of having a son is approximately 0.512 and this probability is independent of genetic factors (Ben-Porath and Welch, 1976; Jacobsen, Moller and Mouritsen, 1999).<sup>4</sup> With the sex of a fetus random, a statistically significant effect of one or more variables on the probability of giving birth to a boy therefore indicates that sex selection has been used. The main advantage of this method is ease of use; simple OLS or logit can be used to estimate the determinants of the probability that families with a specific set of characteristics will have a boy for a given parity birth.

This method does, however, suffer from two major issues. First, it does not take into account

> 1 See Murthi, Guio and Dreze (1995) and Dyson (2001).

> 2 See Das Gupta and Bhat (1997), Sudha and Rajan (1999), Arnold, Kishor and Roy (2002), Retherford and Roy (2003) and Jha, Kumar, Vasa, Dhingra, Thiruchelvam and Moineddin (2006). India is not alone; both China and the Republic of Korea have seen significant changes in the sex ratio at birth (Zeng, Tu, Gu, Xu, Li and Li, 1993; Park and Cho, 1995).

> 3 Examples of studies that have used this approach are Retherford and Roy (2003), Jha et al. (2006) and Abrevaya (2009).

> 4 Poor nutritional and health status of women may lead to relatively more girls being born, probably as an evolutionary response to maximise reproductive success (Trivers and Willard, 1973; Wells, 2000). Empirical evidence from Ethiopia and from cross-country data supports this hypothesis (Klasen and Wink, 2002; Gibson and Mace, 2003). See also the discussion for India in Bhaskar and Gupta (2007).
procedure, whilst those in panel set 11 were sampled under a new frame and revised listing procedure (see Daho, 1992, for a further discussion).

The household size estimlates reflect closely this change in the sampling frame and listing procedures. The initial sampling frame and listing procedures applied to 1985, 1986 and half the 1987 sample. Pooling these observations (that is, panel data sets 1-8), mean household size is 7.77 for the country as a whole. If the other half of the 1987 sample is pooled with the 1988 sample (i.e., taking all observations derived under the revised sampling frame and listing procedures, which entails combining panel sets 9-14), the mean household size is 6.26. As a rough indicator, this suggests that 83 percent of the 1985-88 decline (from 7.98 to 6.16) is 'explained' by the change in the sampling procedures. It seems that the procedures used in listing the 64 households in 1985 and 1986 were biased towards a selection of larger households in the PSU. The exact reason for this is not clear, but the fact that larger dwellings are more noticeable and prone to selection than smaller dwellings must have led to a bias in the listing. Indeed, mean _dwelling_ size recorded in the CILSS was significantly higher in 1985 and 1986 than in 1987 and 1988.

Coulombe and Demery (1992) have applied tests for statistical significance of differences in mean household size, which support that the revision in sampling procedures was responsible for most of the decline. One of the most telling comparisons is between mean household size in the two halves of the 1987 sample. This was 7.36 for set 8 (see Table 4), which formed the second panel and which is based on the original sampling procedures, and only 6.54 for set 11, which was enumerated under the revised sampling procedures. This difference is statistically significant at the 99 percent level. (The difference between data sets 8 and 11 was also statistically significant for each region, except Abidjan).

Whilst the evidence strongly points to the existence of sampling bias in the early years of the survey as the explanation of much of the observed decline in household size, it 9