rafmacalaba/datause-encoder-data huggingface dataset:
known, it adopted various provisions taken from the drafts of the Safeguards Agreement (SA) and others derived from NAFTA negotiations. However, the final drafting of the Safeguards Agreement underwent modifications and several of its final provisions turned out to be less stringent than the ones laid down in the Foreign Trade Act.

# **2. Institutional Reform: Creation of the Unit on International Trade Practices**

By the end of 1990, the Secretariat of Trade and Industrial Development (SECOFI, in Spanish) submitted to the consideration of the President an initiative to create an administrative body specialized in examining requests for applying contingent trade protection measures. The reason for its creation and strengthening was to ensure a technical, professional, non-discretionary, and disciplined administration of these mechanisms “so that they should neither interfere with nor revert the trade liberalization process.”<sup>35</sup> In January 1991, the Mexican government created the first body specifically concerned with antidumping issues, namely the International Trade Practice General Bureau (Dirección General de Prácticas Comerciales Internacionales or DGPCI).<sup>36</sup> It was commissioned with the task of strictly applying antidumping instruments when so justified, while preventing the antidumping system from becoming an obstacle to the trade liberalization efforts undertaken by Mexico.

The DGPCI’s capacity was reinforced when a practically new staff of highly qualified professionals was hired. Intensive training was given to new members engaged in investigations. As soon as the DGPCI was created, its staff conducted a broad comparative

> 35 Interview with Dr. Pedro Noyola Garagori, who submitted to the consideration of the President of the Republic the project to create a specialized department engaged in contingent protection instruments and who was responsible for drafting the new Foreign Trade Act. Dr. Noyola further explained that assigning contingent protection to a lowprofile, non-technical, discretionary and unprofessional area was too high a risk for the opening of the economy, since that decision might open up the path for anti-liberalization or protectionist forces and for the old guard within the government.

> 36 The first antidumping cases were filed with the area concerned with exchange controls, which in 1987 was still under the purview of the Commerce Bureau (Dirección de Comercio), reporting to the Under-Secretariat of Foreign Trade (Subsecretaría de Comercio Exterior), which was part of the SECOFI. Between 1986 and 1990, antidumping proceedings were initiated in various departments busy with other activities as well. In 1990, the Bureau of Countervailing Duties (Dirección de Cuotas Compensatorias) was created within the General Bureau of Foreign Trade Services (Dirección General de Servicios al Comercio Exterior) of the SECOFI.

11
# **Table A5.  Survey Methods’ Differential Effects on Employment and Work Status by Prevalence of Peers’ Informal Employment** **_Male Respondents Only_**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||All M|en|Adult|Men|
||Employed|Working|Employed|Working|
|LOA|0.009|0.004|0.010|0.014|
||(0.031)|(0.027)|(0.034)|(0.028)|
||[0.773]|[0.866]|[0.755]|[0.620]|
|ESR|-0.028|-0.027|-0.044|-0.046|
||(0.033)|(0.028)|(0.036)|(0.031)|
||[0.379]|[0.332]|[0.220]|[0.120]|
|LOA x Informal employment in the EA|-0.026|0.026|-0.051|0.008|
||(0.032)|(0.030)|(0.036)|(0.034)|
||[0.359]|[0.319]|[0.118]|[0.765]|
|ESR x Informal employment in the EA|-0.007|0.027|-0.046|0.006|
||(0.035)|(0.030)|(0.038)|(0.036)|
||[0.842]|[0.295]|[0.232]|[0.846]|
|LOA + LOA x Informal employment in the EA|-0.017|0.031|-0.041|0.022|
||(0.043)|(0.040)|(0.049)|(0.044)|
||[0.718]|[0.425]|[0.400]|[0.587]|
|ESR + ESR x Informal employment in the EA|-0.034|0.000|-0.090*|-0.041|
||(0.047)|(0.041)|(0.051)|(0.047)|
||[0.423]|[0.999]|[0.072]|[0.351]|
|Observations|1,119|1,119|818|818|
|Outcome(Control Group)Mean|0.735|0.832|0.773|0.869|

_Notes:_ This table presents treatment heterogeneity of including the LOA module (LOA) or enforcing selfreporting (ESR) by the prevalence of employment in the informal sector. This prevalence measure is estimated as the share of all men living in the same EA as the respondent and employed in the informal sector. This variable is estimated using the standard labor module (see the descriptive statistics and definitions of this indicator in Table A6). We present ITT estimates from Equation (2), where is the prevalence of youth employment measure (in SD), and the estimations of each survey method’s total effect. iihss The vector includes the variable and the list of control variables selected using a double-LASSO DD procedure for each outcome (see Table A3 in the Appendix for the variables selected). All estimations iihss iihss XX DD include EA (stratification variable) fixed effects. Each column is a separate dependent variable as defined in Section 3. The control mean refers to the mean of the control group for each outcome. Standard errors clustered at the household level are presented in parentheses, and the randomization inference _p_ -values are shown in brackets. *** _p_ <0.01, ** _p_ <0.05, * _p_ <0.1 42
46 indicated that they have no way of adjusting because the workweek is fixed by the Labor Code at forty hours. Most said that they use daily workers as a cushion or that they vary the number of hours of overtime. Only one manager said he used subcontracting as a means of adjustment.

|**TABL****_S.1_**<br>**SmegatModConamig Labdor**<br>**Regution**<br>**Aconfig to Managu**|
|---|
|Percent of<br>Constraint<br>Total Sample|
|Regulations on Layoff<br>61%|
|Regulation of Daily Workers<br>15%|
|Regulation on Hiring Expatriates<br>15%|
|Labor Service<br>8%|
|Regulation of Overtime Work<br>8%|

Source: Authors' survey of managers, 1986.

Are wages being set too high (or too low) relative to labor productivity? Most of the managers in our sample did not feel that wages reflect worker productivity. However, there is some consensus that the wage of the expatriates is either equal to or lower than their level of productivity and that the wages of unskilled workers are higher than or equal to their productivity.

When asked whether they would hire more labor if workers' salaries were reduced by, for example, 20 percent, 91 percent of the managers responded that they would not. Some managers also added that the wages of unskilled workers should not be lowered, as they are already at the Usocialy acceptable minimum" in terms of basic needs. Many stressed that the problem is not high wages but rather poor effort, lack of worker discipline, and low productivity.

_5.2.2 Recndrument and hTining_ We asked several questions about recruitment and learned that, in generaL it is not difficult to hire the unskilled and semi-skilled
top-5 (top-20) equity issuers stood at 51 (88) percent of the total during 1991-1998, their market share dropped to 19 (45) percent during 2007-2014 (Figure 3, Panel C). Similar patterns are also observed in debt markets. Respectively, the top-5 (top-20) bond issuers accounted for 69 (99) percent of the market in 1991-1998, which declined to 19 (51) percent in 2007-2014. For loan markets, while the top-5 (top-20) issuers captured close to 35 (67) percent of the market in 1991-1998, their shares dropped to 12 (32) percent during the last period. These concentration figures remain high, especially in equity markets where the number of issuing firms is relatively larger (there were 658 equity issuers, 146 bond issuers, and 483 loan issuers during 2007-2014).

Looking at the different countries in the region, there is considerable heterogeneity in market activity, with the bulk of trading concentrated within a limited number of countries. More specifically, the GCC states accounted for 82 percent, 91 percent, and 90 percent of the total value of issuances in equity, bond, and syndicated loan markets during 1991-2014 (Table 2, Panel B).<sup>8</sup> Those are rather high shares considering that such countries accounted for around 66 percent of the total region’s GDP during the same period. Saudi Arabia and UAE seem to be in the lead, with the latter accounting for almost 60 percent of bond issuances in the region. Among non-GCC nations, the Arab Republic of Egypt seems to have the most active markets, followed by Morocco in equity and loan markets and Tunisia in bond markets.

# **4. Which Firms Use Equity, Bond, and Syndicated loan Markets?**

To study which firms use capital and syndicated loan markets we merge the transaction-level data set, from SDC Platinum database, with balance sheet information for listed firms from Orbis. We compare

> 8 Almost 20 percent of bond issuances and 18 percent of loan issuances in the GCC countries are in the form of Islamic finance issuances, while such markets barely exist in the other Arab countries. In particular, Bahrain, Kuwait, Qatar, Saudi Arabia, and UAE have the most active Islamic finance markets in the Arab region, with around 13 (19) percent, 21 (21) percent, 18 (16) percent, and 57 (26) percent of their bonds (loans) in the form of Islamic issuances. It is worth mentioning, though, that Malaysia has the most active Islamic bond market in the world, accounting for 90 percent of all Islamic bond issuances in our sample (around 2,100 issuances.

12
**<u>Table 1. Basic statistics about the countries and surveys</u>**

||_GDP per capita_<br>_PPP_|_Population <$1 a_<br>_day_|_Under-5_<br>_mortality_|_Number of households_<br>_surveyed_|
|---|---|---|---|---|
|Burundi 2000|590|55|190|3,979|
|Cambodia 1999|1710|34|135|6,001|
|Cambodia 2000|1804|34|135|12,236|
|Indonesia 2003|3213|8|48|65,762|
|Jamaica 1998|3366|2|20|7,375|
|Jamaica 2000|3395|2|20|1,800|
|Mongolia 2000|1620|27|75|6,000|
|Mozambique 1996|700|38|206|8,250|
|Myanmar 2000|-|-|110|25,545|
|Romania 1995|5965|2|15|24,560|
|Sierra Leone 2000|464|-|186|3,916|

_Source_ : World Bank, World Development Indicators. Poverty rates are for the following years: Burundi 1998; Cambodia 1997; Indonesia 2002; Jamaica 1999 and 2000; Mongolia 1998; Mozambique 1996; Romania 1998. Under-5 mortality data are for 2000 except Romania which is for 1995.

The datasets covered in this study are all most closely consistent with an impairment definition of disability—and as such fall under ICF’s “body functioning and structure” domain. The definition does not include mental health, chronic illness or the inability to carry out specific activities. The latter approach is an alternative that is attractive since it is arguably easier to verify. Indeed, selective misreporting of morbidity has long been recognized as a potential problem in studies of the relationship between health and other socio-economic characteristics (Gertler, Rose and Glewwe 2000). To overcome this problem Gertler and Gruber (2002) use responses on questions regarding Activities of Daily Living (ADLs) when analyzing the impact of disability on household consumption in Indonesia, and Yount and Agree (2005) use ADLs when analyzing sex and gender differences in disability among older women and men in Egypt and Tunisia. The impairments reported in the surveys in this study are typically easily verified, for example blindness or missing a limb. Nevertheless it is possible that there is selective reporting in so far as some respondents and interviewers interpret blindness as partial sight whereas to others it means complete inability to see, for example. Or it is possible that mental disability is selectively recognized and reported by some respondents. Typically, however, selective reporting is assumed to operate such that higher socio-economic groups report higher morbidities. Under this assumption, the estimates reported below would be underestimates of the relationship between disability and poverty.<sup>4</sup>

> 4 Interestingly, Benitez-Silva, Buchinsky, Chan, Cheidvasser, and Rust (2004) find no bias in self-reported disability as compared to bureaucratic assessment among adult US social security benefit applicants.

3
Table 6. Instrumental Variable Probits for Likelihood of Employment, Nepal DHS, 1996-2006

||_Lik_|_elihood of Employ_|_ment_|_Likelih_|_ood of Self-Empl_|_oyment_|
|---|---|---|---|---|---|---|
||_(1)_|_(2)_|_(3)_|_(1)_|_(2)_|_(3)_|
|Interaction Terms (reference=conflict_1<br>|996)<br><sup>**</sup>|<sup>*</sup>||<sup>*</sup>|<sup>*</sup>||
|Conflict_2001_2006|0.799|10.692|-61.243|0.744|10.061|-55.379|
||(0.392)|(5.822)|(42.690)|(0.401)|(5.171)|(39.992)|
|Education (reference=no schooling)|||||||
|Some or all primary school|-0.102<sup>***</sup>|-0.105<sup>***</sup>|-0.064|0.154<sup>***</sup>|0.137<sup>**</sup>|0.183<sup>***</sup>|
||(0.032)|(0.034)|(0.048)|(0.056)|(0.058)|(0.053)|
|Some secondary school|-0.206<sup>***</sup>|-0.235<sup>***</sup>|-0.166<sup>***</sup>|0.067|0.012|0.097|
||(0.045)|(0.053)|(0.061)|(0.077)|(0.100)|(0.077)|
|Completed secondary school+|-0.280<sup>***</sup>|-0.300<sup>***</sup>|-0.236<sup>***</sup>|-1.130<sup>***</sup>|-1.152<sup>***</sup>|-1.049<sup>***</sup>|
||(0.070)|(0.068)|(0.084)|(0.110)|(0.106)|(0.166)|
|Age (reference=age<=20)|||||||
|20<age<=35|0.421<sup>***</sup>|0.386<sup>***</sup>|0.394<sup>***</sup>|0.024|0.011|0.022|
||(0.063)|(0.075)|(0.065)|(0.065)|(0.062)|(0.062)|
|age>35|0.633<sup>***</sup>|0.594<sup>***</sup>|0.599<sup>***</sup>|0.234<sup>***</sup>|0.223<sup>***</sup>|0.229<sup>***</sup>|
||(0.102)|(0.120)|(0.103)|(0.074)|(0.079)|(0.075)|
|Socioeconomic status|YES|YES|YES|YES|YES|YES|
|Household composition|YES|YES|YES|YES|YES|YES|
|Year and sub-region dummies|YES|YES|YES|YES|YES|YES|
|Wald test of exogeneity χ<sup>2</sup>|3.90<sup>**</sup>|2.23|1.38|5.72<sup>**</sup>|1.82|1.26|
|N|25,724|25,724|25,724|21,807|21,807|21,807|

Notes: Weighted to national level with weights provided by the Nepal DHS in each year. Standard errors, in parentheses, are clustered by regionyear. The notation<sup>***</sup> is p<0.01,<sup>**</sup> is p<0.05,<sup>*</sup> is p<0.10. In each regression we instrument for conflict with a binary variable for more- or lessforested interacted with a dummy that combines 2001 and 2006. Model (1) measures conflict as total mortality; Model (2) proxies for conflict as number of husbands migrated; and Model (3) proxies for conflict as number of women divorced, separated, widowed, or living with incapacitated husbands.

Source: Authors‟ calculations based on MHP/NE/MI (2007), MH/NE/ORC (2002), and Pradhan _et al._ (1997).

40
- 38-

# Table 13. Index of Pubic Subsidization of Education by Level (percent)

|Country|Year|Primary|Secondary|Higher|
|---|---|---|---|---|
|Argentina|1989|17|50|49|
|Bolivia|1989|6|10|20|
|Brazil|1989|3|1|30|
|Chile|1989|17|14|33|
|Colombia|1989|28|22|35|
|Costa Rica|1989|8|18|30|
|Ecuador|1989|14|26|22|
|El Salvador|1989|13|8|16|
|Honduras|1989|13|17|27|
|Jamaica|1989|13|49|n.a.|
|Mexico|1989|12|37|41|
|Paraguay|1989|14|13|21|
|Uruguay|1989|22|22|20|
|Venezuela|1989|36|30|44|

## Source: Based on Tables 10 and 12.

n.a. - not available.

Note: The subsidization index is defined as the percent by which the private rate of return exceeds the social rate.
# The Determinants of Farm Investment and Residential Construction in Post-Reform China*

# by Gershon Feder, Lawrence J. Lau, Justin Lin, and Luo Xiaopeng

# Table of Contents

|I.|Introduction|1|
|---|---|---|
|II.|Description of Study Areas and Surveys|3|
|III.|Factors Potentially hibiting Farm Investment|6|
||A. Farm size<br>B. Tenure security<br>C. Finance inadequacy|6<br>6<br>9|
|IV.|Patterms of Investment and Expenditure on Housing<br>and Durables in the Study Areas|13|
|V.|A Model of Household Consumption and Investment|20|
|VI.|Econometric Results|23|
|VIl.|Summary and Conclusions|32|
|Refe|rences|35|

* The paper benefitted from helpful comments by Richard Burcroff.
monitoring and entrenchment of rules in constitutions or supranational treaties. The work also finds that fiscal rules reduce deficits in countries with a tendency to especially high deficits. At the same time, however, the work finds that rules appear to _increase_ deficits in countries where fiscal policy would otherwise be especially prudent, perhaps because of the abovementioned tendency of rules to act like magnets.

# **III. FISCAL RULES IN THE WESTERN BALKANS**

**Five of the six countries of the Western Balkans already have fiscal rules in place** . The remaining one, North Macedonia, is considering their adoption as part of a reform of the organic budget law. Most of the existing rules were established after the increases in debt that occurred during the global financial crisis. Some countries’ rules have been inspired by the EU’s main debt and deficit rules, but the choices have also reflected local circumstances and concerns, and a wide variety of approaches is in evidence (Table 2). Most countries have a rule limiting debt, though the size and the nature of the limit varies. Also common are rules limiting the overall deficit (i.e., the deficit including interest and investment spending) or the current deficit (i.e., the deficit excluding investment spending). One country has a rule limiting the primary deficit (i.e., the deficit excluding interest). As in the EU, the main debt and deficit rules typically apply in principle to general government. Also as in the EU, debt appears in all countries to be measured at face value and to include loans and bonds but not liabilities such as accounts payable.<sup>4</sup> By contrast, the deficit rules generally apply to the cash deficit, not an accrual measure of the deficit as in the EU, while the definition of general government (which determines the institutional coverage of the rules) is in practice less rigorous than in the EU. Many of the rules come with an escape clause that allows for their suspension in extraordinary circumstances.

> 4 The measurement of debt differs from the ESA2010 or GFS2014 in most of the countries, which makes crosscountry comparisons difficult.

10
country (or each region) that yields a stipulated food energy requirement; a common figure is 2100 calories per person per day. To this is added an allowance for non-food spending, which is typically anchored to the non-food spending of people whose food spending (or sometimes total spending) is near the food poverty line. There is considerable scope for discretion in setting such a poverty line. Although the stipulated food-energy requirements are similar, there are (of course) multiple food bundles that can yield a given food energy intake, and some will be preferable to others in any given context. The non-food spending that is deemed adequate will also vary. The judgments made in setting the various parameters of a poverty line are likely to reflect prevailing notions of what poverty means in each country setting.

In converting these lines to a common currency we use the household consumption PPP’s from the 2005 ICP, as documented in World Bank (2008a) (although we consider alternative PPP’s later).<sup>15</sup> The 2005 ICP is clearly the most complete assessment to date of how the cost of living varies across countries. The ICP collected primary data on a region-specific list of prices for 600-1000 (depending on the region) goods and services, grouped under 155 “basic headings” deemed to be comparable across the 146 countries (including OECD countries). The prices were obtained from a large sample of outlets in each country. The world was divided into six regions for the 2005 ICP with different product lists for each. All regions participated, but the participation rate was lower for Latin America.

The 2005 ICP is a clear improvement over 1993—the last year used for global poverty measurement. The number of countries participating in the price survey is larger (146, as compared to 117 in 1993) and the surveys have been implemented on a more scientific basis. New methods were used for measuring government compensation and housing. Adjustments were also made for the lower average productivity of the public sector workers in developing countries (lowering the imputed value of the services derived from public administration,

> 15 The ICP price surveys started in 1968. Prior to 2000, the Penn World Tables (PWT; see, Summers and Heston, 1991) were the main source of the PPP rates for consumption derived from the ICP, as used in the Bank’s global poverty measures.  In 2000 we switched to the 1993 PPPs estimated by the Bank’s Development Data Group; the most recent results are reported in World Bank (2008).  There are methodological differences in these two sets of PPPs. The PWT used the Geary-Khamis (GK) method, while the Bank used the EKS method, which is the multilateral extension of the bilateral Fisher index. On the differences between the GK and EKS methods and implications for global poverty measures see Ackland et al. (2006). There were also improvements in country coverage and data quality in the 1993 PPPs as compared to PWT.  However, there were also a number of problems in the implementation of the 1993 ICP round in developing countries, as discussed in Ahmed (2003).

8
A12 shows that _T_ 2 reduced the main respondents’ attitudes (and their perceptions about the village inhabitants’) in favor of early marriage for girls.

# **6.3 Spillovers on Other Family Members**

Table 4 shows that the combined intervention _T_ 2 decreased early childbearing by 1.4 percentage points, a decrease of 13 percent. When considering the family members that also left home between baseline and as a result of or follow-up marriage childbearing responsibilities, the coefficient shows a decrease in childbearing and marriage of 3.9 percentage points, a decrease of 15 percent. While the combined intervention did not have spillover effects on school attendance for 6-12 year old siblings, it did decrease early insertion into the labor market for 5-20 old This decrease was in the order year siblings. of 2.4 percentage points, a decrease of 14 percent. The impact of _T_ 2 is significantly different from T1 for early marriage, early childbearing, and work outcomes. Similar to the results presented in Table 2, there is no significant difference between _T_ 1 and _T_ 2 in school attendance.

Table 4: Spillovers: Early Childbearing Marriage, School Attendance and Work

|||Early Chil<br>Marriage|dbearing<br>(_<_18 yo)|&|Sc<br>Attendan|hool<br>ce (6-12 yo)|W<br>past mon|ork in<br>th (5-20 yo)|
|---|---|---|---|---|---|---|---|---|
||Becomin<br>(Mem<br>at h|g a Parent<br>bers still)<br>ome)|B. Parent<br>(Adding<br>wh|+ Married<br>members<br>o left)|||||
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Any Treatment (T1 or T2)|-0.003||-0.004||0.016||-0.005||
||(0.007)||(0.017)||(0.016)||(0.012)||
|Videos (T1)||0.008||0.029||0.018||0.012|
|||(0.009)||(0.023)||(0.018)||(0.015)|
|Videos + Mobile apps (T2)||-0.014*||-0.039**||0.013||-0.024*|
|||(0.008)||(0.016)||(0.018)||(0.013)|
|Observations|9,201|9,201|9,201|9,201|5,876|5,876|8,121|8,121|
|R-squared|0.285|0.285|0.116|0.119|0.267|0.267|0.110|0.111|
|Covariates|YES|YES|YES|YES|YES|YES|YES|YES|
|Enumerator FE|YES|YES|YES|YES|YES|YES|YES|YES|
|Control Mean in F-up|0.108|0.108|0.263|0.263|0.741|0.741|0.172|0.172|
|T1 vs T2(p-value)||0.025||0.002||0.784||0.022|

Note: Column 1 and 2 show the results of linear probability models of the proportion of adolescents (under 18 at baseline) having a child. Column 3 and 4 use as dependent variable the same as in Column 1, adding the adolescents that left home at endline as a result of childbearing responsibilities or marriage. Column 5-8 show OLS regressions using as dependent variable the proportion of children 6-12 who are attending school, excluding the target child (Column 5 and 6) and the proportion of members 5-20 who worked in the past month prior to data collection. All regressions have clustered standard errors at the school catchment area level. The covariates considered in all regressions are: age of target child, gender of target child, education of household head (baseline), availability of food (baseline) and enumerator fixed effects. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1 27