rafmacalaba/datause-encoder-data huggingface dataset:
|Prohibit discrimination on<br>ethnic grounds in recruit-<br>ment in the public sector?<br>Yes|Labor Code<br>(1992), Art. 8<br>Para. 3<br>Protection<br>Against Dis-<br>crimination<br>Act (2004),<br>Art. 12<br>Civil Servants<br>Act (1999),<br>Art. 7 Para. 6|<br>Yes|Ley Federal para<br>Prevenir y Eliminar<br>la Discriminación<br>(2003), Art. 9 Para.<br>III. Ley Federal del<br>Trabajo (1970),<br>Arts.3, 133|Yes|Code du Travail<br>(2011), Art. 9, and Art.<br>478 Constitution du<br>Royaume du Maroc<br>(2011), Art. 31|Yes|Equal Treatment Act<br>(1994), Sec. 5(1)|Yes|Constitution of the<br>United Republic of Tan-<br>zania (1977), Art. 22 (2)<br>Employment and Labour<br>Relations Act (2004),<br>Arts. 7(1), 7(4)(g)|<br>Yes|Decree No.<br>10/2012/QH13<br>Labor Code<br>(2012), Art. 5<br>Para. 1<br>Decree No.<br>05/2011ND-CP<br>on Ethnic Minori-<br>ties Work, Art. 7<br>Para. 1<br>Decree No.<br>58/2010/QH12<br>Law on Public<br>Employees<br>(2010), Art. 21<br>Paras. 1, 5<br>Decree No.<br>22/2008QH12 on<br>Cadres and Civil<br>Servants (2008),<br>Art. 38 Paras. 1, 4|
|---|---|---|---|---|---|---|---|---|---|---|---|
|Prohibit discrimination on<br>ethnic grounds in recruit-<br>ment in the private sector?<br>Yes|Labor Code<br>(1992), Art. 8<br>Para. 3<br>Protection<br>Against Dis-<br>crimination<br>Act (2004),<br>Art. 12 Para.<br>1|Yes|Ley Federal para<br>Prevenir y Eliminar<br>la Discriminación<br>(2003), Art. 9 Para.<br>III. Ley Federal del<br>Trabajo (1970),<br>Arts.3, 133|Yes|Code du Travail<br>(2011), Art. 9, and Art.<br>478 Constitution du<br>Royaume du Maroc<br>(2011), Art. 31|Yes|Equal Treatment Act<br>(1994), Sec. 5(1).<br>The exception is Equal<br>Treatment Act (1994), Sec.<br>5(3)|<br> <br>Yes|Employment and Labour<br>Relations Act, (2004),<br>Art. 7(4)(g)|Yes|Decree No.<br>10/2012/QH13<br>Labor Code<br>(2012), Art. 8<br>Para. 1|
|Prohibit an employer from<br>asking about an individual’s<br>ethnicity during the re-<br>cruitment phase?<br>Yes|Protection<br>Against Dis-<br>crimination<br>Act (2004),<br>Art. 12 Para.<br>1|No||No||No||No||No||
|Prescribe equal remunera-<br>tion for work of equal<br>value for individuals be-<br>longing to ethnic minori-<br>ties?<br>Yes|Protection<br>Against Dis-<br>crimination<br>Act (2004),<br>Art. 14 Para.<br>1|Yes|Constitución Políti-<br>ca de los Estados<br>Unidos Mexicanos<br>(1917), Art. 123<br>Para. VII<br>Ley Federal del<br>Trabajo (1970),<br>Art. 56|<br>Yes|Code du Travail<br>(2011), Art. 9 and Art.<br>478.|Yes|Equal Treatment Act<br>(1994), Sec. 5 (1)(e), (h)|Yes|Constitution of the<br>United Republic of Tan-<br>zania (1977), Art. 23 (1)<br>Employment and Labour<br>Relations Act (2004),<br>Art. 7(10)|<br>Yes|Decree No.<br>10/2012/QH13<br>Labor Code<br>(2012), Arts. 5<br>Para. 1 (a), 8<br>Para. 1 , 90 Para.<br>3|

Anti-Discrimination Law and Shared Prosperity 42
work as laborers in the nonfarm sector. The extremely poor and nonpoor rural populations receive 26-34 percent of their total income off-farm. Remittances account for 14 percent of the extremely poor’s total income. This is 6 percentage points fewer than the share of remittances (20 percent) in the total income of the richest 20 percent of the rural population.

This section shows that the rural poor receive the largest share of their total income from agricultural activities such as farming and agricultural labor. Rural-dwellers also work as laborers in the off-farm sector. The poor and nonpoor in rural areas receive 26-34 percent of their total income off-farm. Remittances from friends and family in urban areas and abroad account for around 14 percent of poor people’s total income, slightly less than that of the nonpoor.

# **5. Poverty and Income Inequality**

As Section 2 shows economic growth is important, but it is not the sole component of a poverty alleviation strategy. Programs need to ensure that the poor can take advantage of job opportunities and protect some vulnerable groups that are not able to participate fully in the economy. In order to design these programs, information on the poor is needed. This section addresses headcount poverty and its depth, other poverty indicators, and income inequality. Due to a lack of data and information, this section does not address the broader issues of inequality of assets and opportunities.

Figure <u>5.1: Indigent Poverty Rate (P0) in Haiti by Location and Region, 2001</u> <!-- Start of picture text --> Northwest<br>Grand-Anse<br>South<br>Center<br>Artibonite<br>Northeast<br>North<br>Southeast<br>West<br>Rural<br>Urban<br>Metropolitan<br>Total Haiti<br>0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0<br>Source: Own calculations based on HLCS 2001.<br><!-- End of picture text --> 21
As elaborated in Modebaze and Eroyants, our estimates of the ad valorem equivalents of the barriers against foreign direct investment in Armenian services sectors is based on a survey of the regulatory barriers in services in Armenia. As listed in table 4, our estimates are as follows: banking, 5.6 percent; insurance, 15.8 percent; pipeline transportation, 0 percent; rail transportation, 0 percent; air transportation, 106.8 percent; and telecommunications, 0.3 percent. The CASE team did not conduct a survey of the barriers in Armenia. Rather they assumed that the barriers in Armenia are 25 percent lower than in Ukraine. The estimates for Ukraine were done by the Institute for Economic Research with guidance from Jesper Jensen, and were done using the same methodology as ours in Armenia. The resulting estimates by CASE of the ad valorem equivalents of the barriers against foreign direct investment in Armenian services sectors were considerably higher than the present study, with the exception of air transportation. The CASE study estimates are as follows: banking and insurance, 18 percent; transportation, 12 percent; and telecommunications, 4.5 percent.

Regarding the second issue, the CASE study assumed that commitments to foreign investors in services as part of a DCFTA with the EU will be extended to all services suppliers, i.e., that the preferential commitments will become multilateral. The assumption that the commitments will be multilateral implies substantially larger estimated gains for two reasons. First, the cost reduction from foreign suppliers is for all FDI, not just the EU share. Second, in our framework, since commitments are preferential, the gains from liberalizing with the EU come at a cost of some lost varieties of services from foreign suppliers. We have shown that there is an imperfect competition analogy in preferential liberalization of services to the trade diversion issue in goods. By assuming all commitments are multilateral, there is no trade diversion.

# (ii) **Border costs** .

The CASE study assumes that border costs amounted to 10.6 percent of the value of imports and exports, and that these costs would fall by 50 percent as a result of the DCFTA (see pages 149-150). The CASE study was conducted based on 2007 data. Although we are close to CASE in the estimate of the border costs in 2007, the Costs of Doing Business data shows that border costs have fallen in Armenia between 2007 and 2010. We estimate that border costs are only 8.9 percent of the costs of importing and exporting in 2010. Moreover, no rationale is provided for the assumption of a fifty percent cut in border costs. We assume that border costs of land-locked Armenia will not fall below those of Georgia and Ukraine, who have ports. Based on these assumptions we estimate that border costs will fall between 2.2 percentage points and 2.5 percentage points, depending on destination country and imports or exports. This compares with the larger assumed cut by the CASE study of 5.3 percentage points. Had we assumed the same cut in border costs 116
rate movements that make domestic exports more competitive, then we should observe changes in these variables before the expansion.

We identify and examine 92 episodes of export surges. An export surge is defined as a significant and sustained increase in manufacturing export growth from one 7-year period to the next 7-year period. We focus on manufactures for two reasons. First, expansion in the manufacturing sector has been associated with strong growth in developing countries (Jones and Olken 2008 and Johnson, Ostry, and Subramanian 2006). Second, we want to avoid surges due to commodity price booms. We use data for both developing and developed countries in order to distinguish whether there is a fundamental difference between surges in the two types of countries. We examine movements in trade policy and macro variables, such as the exchange rate, GDP growth, savings, investment, foreign demand, and consumption before and after the surges begin. We also examine the type of countries that have surges and the reorientation of exports during the surge.

We identify four important characteristics of export surges. First, surges are more likely in open economies or economies that are liberalizing. Second, surges are preceded by a large depreciation of the real exchange rate and lower exchange rate volatility. Third, in developing countries, the real depreciation is large enough so as to leave the exchange rate undervalued by 20 percent on average. And fourth, the extensive margin—the discovery of new products and new markets—is important for export surges in developing countries, accounting for 25 percent of total manufacturing exports growth in the 7 years of the surge.

3
# Tables and Figures

_Table 1: Real Wages and Firm Size_

|VARIABLES|(1)<br>ln(wage)|(2)<br>ln(wage)|(3)<br>ln(wage)|(4)<br>ln(wage)|(5)<br>ln(wage)|(6)<br>ln(wage)|(7)<br>ln(wage)|
|---|---|---|---|---|---|---|---|
|Large|0.340|0.335|0.276|0.180|0.252|0.162|0.118|
||(0.0116)|(0.0114)|(0.0118)|(0.0125)|(0.0149)|(0.0124)|(0.0160)|
|Female||||||‐0.167|‐0.176|
|||||||(0.0103)|(0.0121)|
|Large X Female|||||||0.0314<br>(0.0214)|
|Urban||||||0.243<br>(0.0130)|0.235<br>(0.0136)|
|Large X Urban|||||||0.0427<br>(0.0206)|
|Large X Decade<sup>a</sup>|||||‐0.0872<br>(0.0189)|||
|Observations|1,281,234|1,278,100|1,234,681|912,116|912,116|907,619|907,619|
|R‐squared|0.815|0.824|0.832|0.851|0.851|0.855|0.855|
|Country‐Years|69|69|66|60|60|58|58|
|Unique Countries|25|25|23|22|22|20|20|
|Country‐Year FE|YES|YES|YES|YES|YES|YES|YES|
|Industry FE|NO|YES|YES|YES|YES|YES|YES|
|Occupation FE|NO|NO|YES|YES|YES|YES|YES|
|Mincer Controls|NO|NO|NO|YES|YES|YES|YES|

a) normalized so 2000 = 0.

Notes: Wage is hourly, in real US dollars. Large indicates that the employer has more than 100 employees. Mincer controls include age, age squared, and dummies for completion of primary, secondary and tertiary education. Female indicates that the worker is female. Urban indicates the worker lives in an urban area. Heteroskedasticity robust standard errors in parentheses.

8
studies suggest immigrants mostly displace natives to yield a zero net benefit.<sup>12</sup> Outside of the United States, positive net impacts are observed in several European countries for national diversity on innovation.<sup>13</sup> Our perspective is that the weight of the evidence points to high‐skilled immigrants boosting innovation and productivity—mainly through the increased quantity of skilled individuals pursuing innovative work—and we are sure this debate will persist for some time.

Researchers, following studies like Peri and Sparber (2011), are now developing a deeper understanding of the types of skills that port well across countries (such as STEM, computer programming, and academic research) and the underlying traits of these skills (such as weaker dependence on local culture and language, limited returns to local experience). Developing this granularity has helped researchers better identify and interpret wage and employment implications of high‐skill mobility on native workers. To illustrate, imagine a scenario in which high‐skilled migration pushes American engineers to leave their occupations. Instead, those Americans move to marketing, where they receive a substantially higher wage and, more importantly, they work together with the migrant engineers. Does this scenario present the negative consequences of migration, with Americans crowded out of engineering jobs? Is it a story of a positive complementarity, in which migration allows immigrants and natives to specialize in occupations based on their comparative advantages and increase their joint productivity? Or perhaps without the presence of foreign engineers, the engineering work would have shifted abroad and Americans would have moved to marketing anyway, but perhaps would be less productive due to geographic distance from the engineering staff now abroad? These implications are not easy to assign and will be a focus of impactful research ahead.

Finally, skilled migrants serve as effective conduits for many forms of multi‐directional exchange in a networked world: trade, foreign direct investment, finance, knowledge, technology, cultural norms and political views (for example, Parsons and Winters 2014; Saxenian 2002, 2006). Terms like “brain drain” and “brain gain” are now used to label settings where the gains to the sending

> 12 For example, Matloff 2003; Hira 2010; Borjas and Doran 2012; Doran et al. 2014; Bound et al. 2015a.

> 13 For example, Ozgen et al. 2011; Bosetti et al. 2013; Parrotta et al. 2014; Breschi et al. 2014, 2015; Nathan 2015.

16
lower prices. Furthermore, transparent procurement processes will help reduce corruption (World Bank 2016a). In this context, this section benchmarks two different aspects of procurement:

**Figure 19 Public investment management, by SSA income groups**

<!-- Start of picture text --> Appraisal Score<br>2.50<br>2.00<br>1.50<br>1.00<br>0.50 LIC (21)<br>Evaluation Score 0.00 Selection Score LMC (6)<br>UMC (5)<br>Managing Score<br><!-- End of picture text --> _Source: Dabla-Norris, Brumby, Kyobe, Mills, and Papageorgiou (2012)_ First, the procurement life cycle of infrastructure projects which covers the following dimensions: (i) needs assessment, call for tender, and bid preparation, (ii) bid submission phase, (iii) bid opening, evaluation, and awarding phase, (iv) content and management of the procurement contract, (v) performance guarantee, and (vi) payment of suppliers. The rationale and areas covered in these six stages of the procurement process are described in World Bank (2016a).

Second, the regulatory frameworks and practices governing the project cycle of public-private partnerships (PPP). It involves the following dimensions: (a) preparation of PPPs (activities that precede and inform the decision to launch a PPP procurement process), (b) procurement of PPPs (evaluates the selection process of private partners), and (c) contract management of PPPs (well-established and comprehensive PPP contract management framework that enables smooth implementation). These data allow the benchmarking of PPP practices that promote transparency and fair competition (World Bank 2016b).

Figure 20 benchmarks the different stages of the procurement life cycle of infrastructure projects by the public sector in SSA vis-à-vis other developing regions, namely, EAP and LAC (panel A). The region is outperformed by both EAP and LAC in the initial stages of the procurement cycle —that is, needs assessment, call for tender, and bid preparation, as well as bid submission. On the other hand, the score on performance guarantee in SSA is comparable to that of LAC and outperforms that of EAP. Looking at the income groups within the region, LICs and LMCs have comparable scores in the different stages of the procurement cycle, and they tend to outperform UMCs in two areas: bid opening, evaluation and award, and performance guarantee (panel B).

_Infrastructure in Sub-Saharan Africa - 36_
**Table 13: Breakdown by Types of Government Support, El Salvador**

||Percentage<br>perm full-ti<br>since D|change of<br>me workers<br>ec 2019|Decreased tot<br>temp w|number of<br>orkers|Decreased to<br>operat|tal hours of<br>ions|Anticipate f<br>arrears on ou<br>liabili|alling in<br>tstanding<br>ties|
|---|---|---|---|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|**(8)**|
|Received national or local|0.572|0.192**|-0.189|-0.466|0.472|-1.225|-0.536|-1.259|
|government support|||||||||
||(0.415)|(0.088)|(1.216)|(1.004)|(1.089)|(1.076)|(0.860)|(0.959)|
|Cash transfers|-0.016|0.331***|0.665|0.372|-1.352**|-2.232***|0.165|0.662|
||(0.180)|(0.076)|(0.813)|(1.259)|(0.612)|(0.799)|(0.525)|(0.721)|
|Wage subsidies|-0.504|-0.455***|-0.273|-0.487|-1.297|0.178|-0.397|0.304|
||(0.390)|(0.112)|(1.174)|(1.176)|(1.446)|(1.592)|(0.841)|(0.882)|
|Average change in monthly<br>sales compared to one year|-0.079|0.442***|-2.800***|-5.714***|-2.032**|-1.044|-2.586***|-3.274**|
|ago|(0.117)|(0.144)|(0.889)|(1.649)|(0.915)|(1.621)|(0.813)|(1.373)|
|Decreased demand for<br>products or services compar|-0.014|0.453***|-0.075|-0.049|1.383***|1.329|-0.596|-0.551|
|to one year ago|(0.066)|(0.136)|(0.658)|(1.765)|(0.384)|(1.009)|(0.800)|(0.626)|
|Decreased supply of inputs<br>compared to one year ago|0.091|-0.325***|2.343**|4.534**|0.588|-0.420|-0.684*|0.197|
||(0.093)|(0.117)|(0.990)|(2.102)|(0.397)|(1.012)|(0.365)|(0.499)|
|Decreased liqdt or cash flow<br>avail. since COVID-19 began|1.021|0.075|-1.494**|-4.635**|-1.030|1.181|1.060**|0.887|
||(0.623)|(0.075)|(0.686)|(1.973)|(0.860)|(0.736)|(0.473)|(0.996)|
|Overdue on obligations to<br>financial institutions|-0.106|-0.704|-0.135|-1.722**|-0.500|-0.765|1.233*|0.218|
||(0.138)|(0.493)|(0.463)|(0.776)|(0.532)|(1.066)|(0.659)|(0.506)|

48
WPS3230

# **India:  Why Fiscal Adjustment Now**

Brian Pinto and Farah Zahir<sup>1</sup>

## **_Abstract_**

India’s growth performance has been impressive over the last two decades. But its sustainability has been in question, first with the 1991 fiscal-balance of payments crisis (BoP), and then again after 1997/98, when fiscal deficits returned to the 10 percent of GDP range and government debt grew. This paper analyzes the deterioration in India’s public finances and presents evidence suggesting that, in the absence of a fiscal adjustment, low inflation and high reserves may have been pursued at the expense of long-run growth and poverty reduction. Resolving this inflationexternal vulnerability-growth policy trilemma requires fiscal adjustment. In making its case, the paper shows, first, that fiscal fundamentals have weakened after 1997/98 even when compared with the pre-1991 crisis period. This has continued in spite of the recent record lows in interest rates. Second, the fiscal stance is not conducive to long-run growth and poverty reduction because capital spending has been cut to accommodate higher interest payments and other current spending, with expenditures on the social sectors stagnating. Third, without a fiscal adjustment, the debt burden is likely to reach unmanageable levels by the end of the Tenth Plan period. In contrast, a phased adjustment beginning now and focusing on a relatively small set of reforms is likely to improve debt dynamics substantially over the same horizon, while also promoting faster growth and poverty reduction.

## World Bank Policy Research Working Paper 3230, March 2004

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> 1 Both authors are at the World Bank.  We are grateful to Michael Carter and Sadiq Ahmed for encouraging us to write this paper.  It liberally draws on _India – Sustaining Reform, Reducing Poverty_ , a World Bank Development Policy Review released in July 2003.  In revision, the paper has benefited substantially from comments from the peer reviewers Shantayanan Devarajan, Kalpana Kochhar, Mihir Rakshit and Suresh Tendulkar.  Helpful comments were also received from Ijaz Nabi and Stephen Howes.
# **3 Data**

As mentioned before, equations (1) and (4) determine the set of variables needed to estimate the inter-sectoral elasticities of substitution. In general, our variables are given by the set of instruments required to estimate equation (4), and a second set of variables required to estimate equation (1). We performed the estimations using the information available for the period comprehended between 1990 – 2003 using the information available of the following countries: Brazil, Canada, China, Colombia, Germany, India, Indonesia, Japan, Mexico, Turkey and the United Kingdom. The selection of the countries is based on the relative importance of trade with the U.S. and the country representation according to the region that the country belongs too.

Taking this into account, our data are obtained from three sources. Data related to value of imports, tariff levied at the product level in the U.S., price of the product and transport costs of the product per country of origin are obtained from the U.S. Import Database. As it is known, the import data are reported at the ten digit level of the Harmonized System classification but, we proceed to use the information at the six digit level. At this level we were able to classify the products within industrial sectors; given by the ISIC rev. 2 industrial classification at the four digit level.

Input requirements calculated by equation (5), are obtained using the information available in the Input Output tables compiled in the GTAP database. As expected, input requirements are calculated at the two digit gtap - industrial where A is the _N_ × _N_ matrix of required intermediate goods (N is the number of sectors). _D_ is final demand, and _VA_ is value added which is composed by labor compensation ( _WL_ ) and other (which we assume as capital). Therefore: where _VA_ is the matrix of sector value added as a fraction of sector output.

> 8 If we assume that imported and domestic intermediate goods have different prices over time we need to decompose the input-output matrix into its domestic and imported component. See Appendix A.

9