rafmacalaba/datause-encoder-data huggingface dataset:
14 workers also face high severance pay costs if they lay workers off. Finally, firms with revenues exceeding 500,000 LKR per quarter or 1.8 million LKR per year must also register for VAT. The VAT tax rate is 20% of value-added for most goods, with producers of some goods paying a lower 10% rate and others exempt entirely.

# **2.1 Formality Levels in Practice**

Figure 1 summarizes the percentage of firms which reported being registered with each of the four government entities according to the number of paid employees in the firm. The data come from the baseline of the Sri Lanka Longitudinal Survey of Enterprises (SLLSE), collected by the authors between January and May 2008. The survey contains 2,865 enterprises, and is representative of enterprises in the 31 largest cities and towns (outside the Northern province which was inaccessible due to civil conflict). A door-to-door listing exercise of households was carried out, to ensure the survey was able to detect both formal and informal firms. The vast majority of enterprises have zero paid workers, and we see that only 23 percent of these non-employers are registered at the local (P.S. / UCMC) level and only 20 percent are registered at the DS Division level. Less than 1 percent of the non-employers report being registered for VAT. Registration at all four levels rises quickly with firm size, so that 75 percent of those with 5 paid employees are registered with the P.S. or UCMC and 68 percent with the DS. However, the percent registered then appears to plateau, with approximately 70 to 80 percent registered with the DS for firms with 6 to 20 employees. There are fewer firms in the SLLSE sample as the number of paid workers grows, making the point estimates more variable at larger firm sizes. Registration of at least some of the workers of the firm with EPF/ETF is less common in firms with fewer than 5 workers, but also increases rapidly with firm size so that 87 percent firms with 10 employees have registered at least some of their workers. VAT registration is the least common, but also grows with firm size, so that about half of firms with 10 or more workers are registered for VAT.

Among those firms with 1 to 10 paid workers which were not registered with any of the four government entities, only 23 percent said they had ever considered registering their business; the majority of the remainder said they felt their businesses were too small to have to register. There is often a presumption that the informal sector faces a high level of de facto fees in terms of fines, penalties and bribes which arise from operating without a license. However, this does not appear to be the case in Sri Lanka: fewer than 0.5 percent of unregistered firms with 1 to 10 paid workers reported paying a fine, penalty or bribe in the last year because of their unregistered status. Indeed, most informal firms report having little interaction with officials at all: only 5 percent reported receiving a visit from a Pradeshiya Saba official, 2 percent from a DS official, and 1 percent from a tax official in the past year.

6
# VII – References

Ajwad, Mohamed Ihsan, et al. "The skills road: skills for employability in Uzbekistan." (2014).

Beine, Michel, Frédéric Docquier, and Maurice Schiff. "International migration, transfer of norms and home country fertility." _Canadian Journal of Economics/Revue canadienne d'économique_ 46.4 (2013): 14061430.

Borjas, George J. "The labor demand curve is downward sloping: Reexamining the impact of immigration on the labor market." _The quarterly journal of economics_ 118.4 (2003): 1335-1374.

Bouton, Lawrence, Saumik Paul, and Erwin R. Tiongson. _The impact of emigration on source country wages: evidence from the Republic of Moldova_ . The World Bank, 2011.

Cantore, Nicola, and Massimiliano Calì. "The Impact of Temporary Migration on Source Countries." _International Migration Review_ 49.3 (2015): 697-726.

Clemens, Michael A. "What do we know about skilled migration and development?." _Policy Brief_ 3 (2013).

Clemens, Michael A., Çağlar Özden, and Hillel Rapoport. "Migration and development research is moving far beyond remittances." _World Development_ 64 (2014): 121-124.

Dustmann, Christian, Tommaso Frattini, and Anna Rosso. "The effect of emigration from Poland on Polish wages." _The Scandinavian Journal of Economics_ 117.2 (2015): 522-564.

Hanson, Gordon H. "The economic consequences of the international migration of labor." _Annu. Rev. Econ._ 1.1 (2009): 179-208.

Mountford, A. (1997). Can a brain drain be good for growth in the source economy? Journal of Development Economics, 53(2), 287–303 Rapoport, Hillel. "Migration and globalization: what’s in it for developing countries?." International Journal of Manpower 37.7 (2016): 1209-1226.

Stark, O., Helmenstein, C., & Prskawetz, A. (1997). A brain gain with a brain drain. Economics Letters, 55(2), 227–234.

Stillman, Steven, et al. "Miserable migrants? Natural experiment evidence on international migration and objective and subjective well-being." _World Development_ 65 (2015): 79-93.

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to higher stages of processing, with machinery replacing textiles and clothing as a major export category, there has been a recovery in the total service intensity of China’s exports, from a low of 8.7 percent in 1997 to 17.3 percent in 2007.

Table 11: **Services share of total exports (excluding trade and transport)**

|||1992|1995|1997|2001|2004|2007|
|---|---|---|---|---|---|---|---|
|Gross|Brazil|0.009|0.011|0.074|0.091|0.067|0.086|
||China|0.128|0.038|0.018|0.021|0.027|0.033|
||Korea|0.035|0.058|0.067|0.056|0.049|0.069|
||USA|0.120|0.141|0.147|0.174|0.172|0.193|
|Direct VA|Brazil|0.020|0.024|0.146|0.179|0.124|0.152|
||China|0.245|0.073|0.026|0.032|0.062|0.073|
||Korea|0.060|0.101|0.115|0.107|0.094|0.130|
||USA|0.172|0.179|0.211|0.243|0.253|0.284|
|Total VA|Brazil|0.240|0.231|0.272|0.323|0.242|0.243|
||China|0.194|0.152|0.087|0.104|0.156|0.173|
||Korea|0.189|0.231|0.263|0.282|0.260|0.280|
||USA|0.274|0.266|0.308|0.324|0.327|0.346|

Brazil and China actually stand out as some kind of outlier, in terms of value added trends. For the world as a whole, we have seen that the direct value added content of exports in manufacturing has been falling since 1992. This fits with the concept of vertical disintegration of production along geographic lines, with trade flows rising in gross terms because of shipment of intermediate goods. Yet this is not the case for Brazil and China for the manufacturing sector as a whole. From Table 12 and Table 14, the total domestic value added for other manufacturing has risen from 60.6 to 70.1 between 1992 and 2007 for Brazil and from 51.5 to 67.6 percent for China in the same time period. In Korea it fell from 62.7 percent to 47.3 percent, and in the United States it stayed constant. Total value added content in exports in machinery fell for all four countries between 1992 and 2007. Similarly, in transport equipment alone (not in the table), this rose from 28.7 to 40.6 percent for China, while it stayed constant in Brazil, fell about 7 percent in the United States and increased only marginally in Korea. Brazil’s service intensity has risen over the period (from Table 11), but the driving force is likely linked to import substitution and FDI policies as well. This can be seen from Table 12, where direct domestic value added exports in other manufacturing rose from 60.6 percent to 70.1 percent 20
SYS-REVIEW/HI-LMIC

# **<<B>>** _Health Status_

Surprisingly, only six studies reported on health measures. It is presumed that health insurance would induce greater access for the insured and thereby lead to better health. With the exception of the study on the health insurance scheme from Colombia (Miller et al. 2009), no study reported that supply-side improvement accompanied the introduction of insurance. If health insurance implementation is not accompanied by a significant improvement in the quality of supply and does not lead to greater utilization, then we should not expect health improvement. Financial protection is the main aim of insurance. However, if a range of health outcomes improves or death rates decline for the insured, then it is possible that we can attribute better health outcomes to health insurance.

Mensah et al _._ (2010) show lower levels of infant death, although these levels are not statistically significant. Wang et al. (2009) use EQ-5D, a standardized index value instrument for use as a measure of a wide range of health conditions, to report on a community-based health insurance program in China. They find that the scheme had positive effects on health status for all insured people and for the poor. Measuring regional changes, Dow and Schmeer (2003) find no correlation in changes in infant mortality as regional insurance uptake improves. For Nicaragua, Thornton and Field (2010) show no improvement in health. Sosa-Rubi et al _._ (2009b) examine Mexico ́s SP insurance and show improved glucose control among diabetics with insurance than those without insurance. Lei and Lin (2009) find no improvement in health status for the China’s NCMS.

# **<<A>>Discussion and Conclusion**

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Page 24 BO: 7 The Limited Suppaly o Girls' Secondary Schools in Kenva At the time of independence in Kenya, far fewer women than men had any education. In Kenya as elsewhere, as incomes have increased,<sup>the disparity</sup> between girls' and boys' educational attainment has decreased -- but girls still tend to drop out of school sooner than boys. One-third<sup>of the girls and two-</sup> fifths of the boys complete primary school. Fewer than<sup>half of those boys and</sup> girls go on to secondary school. About 9 percent of<sup>girls and 12 percent of boys</sup> finish.

Girls and boys generally go to primary school together,<sup>but some</sup> still go to separate secondary schools. At the<sup>secondary level, girls are at</sup> a disadvantage because more are obliged to go to<sup>schools that receive less</sup> government support and charge higher fees. Despite<sup>faster expansion recently</sup> in girls' places at the supported secondary schools, the schools still don't have places for all of the girls who qualify.

<!-- Start of picture text --> Kenya Girls' Secondary Enrollment<br>('000)<br>Government Goverment<br>Maintained Assiste Unaided Total<br>Yer MHF %FF M F %F M F IF M F %F<br>1980 129 61 (32.1) 48 48 (50.0) 72 59 (45.0) 249 168 (40.3)<br>1985 135 74 (35.4) 50 40 (44.4) 84 52 (39.2) 259 176 (40.4)<br><!-- End of picture text --> <!-- Start of picture text --> Source: World Bank 1989a<br><!-- End of picture text -->
above the 1991 level in four of the seven countries and progress was also visible in the remaining three countries.

Relatively to other CIS countries, the CIS-7 suffered from a much worse recession in industry while they show a better performance in agriculture (table 2.1). It is also evident that the industrial recession has not been clearly reversed during the recent growth period which is an opposite trend to what it can be observed in other CIS countries during the same period.

**Figure 2.1 GDP growth (1991=100)**

<!-- Start of picture text --> Industry Agriculture<br>160 140<br>140 120<br>120 AzerbaijanArmenia 100 AzerbaijanArmenia<br>100 Georgia 80 Georgia<br>80 Kyrgyzstan Kyrgyzstan<br>Moldova 60 Moldova<br>60 Tajikistan Tajikistan<br>40 UzbekistanCIS 40 UzbekistanCIS<br>20 20<br>1991 1992 1995 1996 1997 1998 1999 2000 2001 2002 1991 1992 1995 1996 1997 1998 1999 2000 2001 2002<br><!-- End of picture text --> Source: http://www.cisstat.com

**Table 2.1 Volume Indices of Agricultural and Industrial Output (1991=100)**

||1991|1992|1995|2000|2001|2002|2003|
|---|---|---|---|---|---|---|---|
|Industry CIS-7|100|70.2|43.1|47.7|51.1|54.0|47.8|
|Industry other CIS|100|87.6|56.0|70.8|77.3|82.0|89.3|
|Agriculture CIS-7|100|88.6|78.1|82.8|92.4|97.8|98.0|
|Agriculture other CIS|100|98.8|76.4|67.3|73.5|74.5|74.5|

Source: http://www.cisstat.com The relatively better performance of agriculture in the CIS-7 has been achieved thanks to small farming rather than through the re-organization of agriculture into large and better productive private industrial complexes. Land reforms have been fairly successful in distributing land to a large number of people (see section 5) and the privatization process that saw the dismantling of large _Kolkhoz_ and _Sovkhoz_ and the distribution of land and assets to members resulted in an effective and relatively egalitarian redistribution process, at least in comparison to urban areas and industrial enterprises. In Armenia in 1997 over 99% of agricultural output was produced by household plots.

Small farming is also not a phenomenon limited to rural areas. The 2001-2002 Georgian Household Budget Survey found that almost 60% of all households had access to land including over 30% of households in urban areas. However, the average land size used for agriculture per household was very small, about 0.8 hectares.

**Second** , the decline in industry is mainly explained by the decline in industrial manufacturing. Manufacturing output collapsed during the recessional period and continued to decline very significantly during the growth period (table 2.2). This is perhaps the most worrying trend from a welfare and employment perspective. Historically and worldwide rapid reductions in poverty and increases in employment have been closely associated to the development of the manufacturing sector. That is because the development of manufacturing during the early development stages is

14
# **_Differences in Welfare Distributions_**

We begin with a set of figures (figure 3.3) summarizing the distribution if welfare differences within the leading Southeast region and within the lagging Northeast region of Brazil and specifically between metropolitan and urban areas and between urban and rural areas.

**Figure 3.3: Welfare differences within the Southeast and Northeast regions**

<!-- Start of picture text --> (a) (b)<br>Southeast: metro-urban gap in log welfare ratios Southeast: urban-rural gap in log welfare ratios<br>Brazil 2002/2003 Brazil 2002/2003<br>0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100<br>percentile percentile<br>(c) (d)<br>Northeast: metro-urban gap in log welfare ratios Northeast: urban-rural gap in log welfare ratios<br>Brazil 2002/2003 Brazil 2002/2003<br>0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100<br>percentile percentile<br>.6<br>.5<br>.5<br>.4<br>.4<br>.3<br>.3<br>log (metro w.r./urban w.r.) log (urban w.r./rural w.r.)<br>.2 .2<br>.7 .7<br>.6<br>.6<br>.5<br>.5<br>.4<br>log (metro w.r./urban w.r.) .4 log (urban w.r./rural w.r.) .3<br>.3 .2<br><!-- End of picture text --> As it can be easily inferred, the difference in welfare ratios between metropolitan and urban areas within the SE region has a U shape, meaning that welfare differences are higher at the bottom and at the top of the distribution of welfare in the leading region. In contrast, the differences in welfare between urban and rural areas in the SE region increase almost monotonically with the level of welfare. Within the NE region, the lagging region of Brazil, the difference in welfare between metropolitan areas and urban areas is also higher at higher level of welfare suggesting that the wealthier households in the metropolitan areas of the NE are much better off than the wealthier households in the urban areas of the NE. Lastly, the differences in welfare between households in the urban and rural areas of the Northeast suggest that the differences are larger primarily among relatively wealthier households (above the 50<sup>th</sup> 17
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Both the relative importance of policies and also their explanatory limits are suggested by the figures in table 4. Under a relatively good policy environment (as measured by a single policy variable), the probability of a 'flop' project--with a negative ERR--is about one-third that under a more distorted regime. As measured by two policy variables (fiscal deficit and trade openness), this probability is about one-eighth that under a more distorted regime. By contrast, the probability of a 'very successful' project--ERR greater than 20 percent--can be between one-and-a-half and twice as high under a relatively undistorted environment, as measured by single or multiple variables. Yet, even under a relatively undistorted policy regime, there is still a 20 to 30 percent probability that the project will not be 'satisfactory'.

These figures suggest that economic policies are important. They also raise an important question: why is it that a significant fraction of projects do not become highly successful--or even satisfactory-in the face of an enabling policy environment? First, not all aspects of an economy's policy framework can be captured by any set of variables. In addition, many other economy-wide factors determine project performance. -- Supportive public investments matter (as discussed in section below); so does the quality of governancel<sup>9</sup> including the legal and regulatory framework. And of course, project-specific inputs are critical, including technical analysis, project management, and--in many sectors--beneficiary participation.<sup>20</sup> Finally, failure of some projects--and by extension of some firms--is part and parcel of decision making under risk and uncertainty and thus of the dynamism of any economy. Risk-taking in undistorted economies will unavoidably also result in some failures, but in many more successes as well.<sup>21</sup>

> 19 An ongoing study (Isham, Kaufinann and Pritchett 1995) under the World Bank's review of aid effectivenesi **s** testing the significance of selected aspects of govemance on project performance. 20 See the recent set of OED Annual Reviews (e.g., World Bank 1 994a) for detailed analyses on other determinants of project performance, and Isham, Narayan, and Pritchett (1995) for an analysis of the effect of beneficiary participation on performance of rural water projects. **21** This point is lost in the growing "industry" of project evaluative reports in intemational organizations, where each failed project is often regarded as an isolated, unambiguously negative occurrence (to be avoided in the future). In these reports, no thought is given to the question of risk-taking under uncertainty and interlinked decisions. In fact, the right strategy can result in a number of successful projects for each failure, so that the "optimal" failure rate is higher than zero.
# **3. PATTERNS OF TRADE PERFORMANCE**

## **3.1. Main world regions**

What does decomposing exports as explained above say about countries’ and regions’ export competitiveness in recent years? Table 1 shows averages of the year-on-year change for each indicator, broken down by major region of the world, covering the entire period of data availability, i.e. in the period going from the first quarter of 2005 to the first quarter of 2013 (2005q1-2013q1).<sup>13</sup> On average, annual export growth percentage change was at double digit figures in most of the developing world. It was highest in South Asia (14.6%), followed in the order by the Eastern Europe and Central Asia (10.8%), Sub-Saharan Africa (10.7%), East Asia Pacific (10.4%), MENA (10.2%) and Latin America and the Caribbean (9%). Annual export growth rate was over the half for advanced economies from the OECD (5.4%).

Export performance (i.e. export growth stripped of compositional effects or pull factors) was strongest in East Asia and the Pacific and in South Asia, with 13.8% and 13.4% annual growth respectively.<sup>14</sup> In both cases, such impressive export growth was achieved on the back of important competitiveness or “push” supply-side factors. In particular, export market share growth excluding composition effects was 6.8% annually in South Asia. It outperformed all other main regions in the world on average, but developments have been quite erratic over time (see Figure 1). Looking at the decomposition of the push effect in price and volume components, it appears that South Asia’s performance was almost entirely driven by volumes growth, while prices have played a somewhat negative role. With respect to composition effects, South Asia showed an almost neutral specialization. Meanwhile the East Asia and Pacific region showed a neutral geographical specialization but a sectoral composition that has weighed negatively on the overall export performance, suggesting a specialization in products and sectors that on average have had a relatively low growth over the eight past years.

> 13 The indicators are provided with a quarterly frequency and the tables reported in this paper present year-on-year changes (i.e. relative to the same quarter of the previous year). Since the underlying bilateral export data are available from 2005 onwards, the first data point in our database is relative to 2006q1 and reports the percentage change of each variable relative to 2005q1. Similarly the data-point relative to 2006q2 quantifies the change over the 2005q2-2006q2 period. The last data point (2013q1) refers to changes between 2012q1 and 2013q1. The quarter on quarter version of the database, available online, contains instead data-points from 2005q2 to 2013q1. The 2005q2 data-point refers to changes that took place between 2005q1 and 2005q2. The 2013q1 data point refers to changes between 2012q4 and 2013q1.

> 14 Export growth net of compositional effects is not reported in the table but it is easy to gauge. It is obtained by subtracting the geographical and the sectoral effect to the export growth. In the case of East Asia Pacific this is therefore we compute 13.8=10.4-0.3+3.7.

14
assessed, as is the likelihood of encountering corrupt of officials <u>and other groups’</u> _Source: The World Bank, 2012_

# **(iv) Government Effectiveness Cluster/Governance Dimension**

Substantively, the GE captures the same underlying notion of the abuse of public power by policy makers as do the CPI and the CC. However, it is qualitatively different in that it measures the extent to which corruption takes place via _unit cost increases,_ rather than the level of bribes. Thus, while measures that compose the CPI and CC are likely to capture the ability of public policy makers to rent-extract via extortion and bribes, the GE is more likely to capture the extent to which public officials abuse their office by reducing their workloads, gold plating their benefits, etc. The GE is developed using the same methodology as the CC but is qualitatively focused on bureaucratic corruption (World Bank, 2010, online): _“Government Effectiveness (GE) – [is designed to capture] perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies.”_ As Table 3 indicates, the GE is composed of almost the same representative sources as the CC. However, unlike the CC, the focus of the GE is very much on corruption in the bureaucracy (e.g. ‘bureaucratic quality’; see Table 3). In fact, only one of the five representative sources of the GE is not exclusively focused on bureaucratic corruption: ‘quality of the supply of public goods: education and basic health and the capacity of political authorities to implement reforms’ (see Table 3). Of course, if bureaucrats are accountable to elected officials, then it is anticipated that the GE will be highly correlated with both the CC and the CPI. While the GE, therefore, is substantively not focused on political corruption directly, it is likely to be correlated with measures of political corruption because of the relationship between politicians and bureaucrats.

16