rafmacalaba/datause-encoder-data huggingface dataset:
28

**Figure 13. Types of Employment for Youth (aged 15 to 24) and Adults (aged 25 to 64)**

<!-- Start of picture text --> Unpaid<br>15-24 25-64<br>family<br>w orker/ Unpaid<br>apprentic family Self-<br>e Self- worker/ employed<br>31% employed apprentice 56%<br>33% 4%<br>Day<br>laborer<br>9%<br>Day<br>laborer Wage Wage<br>8% earner earner<br>28% 31%<br><!-- End of picture text --> Source: EPCV 2004.

_Differences between those living in urban and rural areas are striking for young women who are employed_ (Table 17). In rural areas, 43.6 percent of them work as unpaid family labor or apprentices, compared to only 11.4 percent in urban centers. Self-employment is also less common for urban young women than it is for rural ones (respectively 45.3 percent and 28.3 percent). They are indeed more likely to be wage earners (45.7 percent).

**Table 17. Types of Employment for Youth by Gender and Living Area (in percentages)**

||_M_<br>|_ale_<br>|_Fem_<br>|_ale_<br>|
|---|---|---|---|---|
||_Rural_|_Urban_|_Rural_|_Urban_|
|_Wage earner_|22.4|49.5|8.6|45.7|
|_Day laborer_|3.7|16.8|2.5|14.6|
|_Unpaid family worker / apprentice_|38.8|14.5|43.6|11.4|
|_Self- employed_|35.1|19.1|45.3|28.3|
|_Total_|100|100|100|100|

Source: EPCV 2004. Total might not always exactly amount to 100 due to rounding.

# **_3.4 Earnings Determination_**<sup>11</sup>

_This section presents an analysis of earnings of the self-employed and wage-earners._ Unfortunately, as the EPCV 2004 data does not include information on the number of hours worked, this section does not investigate underemployment issues.

> 11 Data on individual earnings in the EPCV 2004 survey are provided either by day, week, or month. However, given inconsistencies observed in the orders of magnitude between these three categories, this section is based on monthly earnings only. The present analysis on earnings thus includes 78 percent of the self-employed and 93 percent of all wage earners. Finally, earnings were not adjusted to take into consideration regional differences in standards of living.
- 44 -

# TABLE 273 TRADE REFORM SCENARIO FOR THREE GROWUPS OF CAPITAL GOODS PRODUCTS (in Z of World Output Prices)

|GROUP 1||Present|Year 1|Year 2|Year3|Year 4|Year 5|
|---|---|---|---|---|---|---|---|
|Output||131|131|131|125|112.5|100|
|Inputs|: Materials|63|57.5|52|46.5|41|35|
||Services|13|13|13|13|13|13|
||Total|76|70.5|65|59.5|54|48|
|Value A|dded|55|60.5|66|65.5|58.5|52|
||Labor|19.5|-----|--------|---<br>Unchang|ed-------|--------|
||Interest|8.5|-----|--------|---<br>Unchang|ed--||
||Depreciation|6.5|-----|--------|---<br>Unchang|ed-------|--------|
||Pre-Tax Profit|20.5|26.0|31.5|31.0|24.0|17.5|
|GROUP 2|(asXof Output'|15.6|19.8|24.0|24.8|21.3|17.5|
|Output||157|150|137.5|125|112.5|100|
|Inputs|s Materials|64|58|52|46|40|33|
||Services|16|16|16|16|16|16|
||Total|80|74|68|62|56|49|
|Value A|dded|77|76|69.5|63|56.5|51|
||Labor|31.5|------|-------|---<br>Unchange|d-------|--------|
||Interest|13.5|-----||Unchange|d-------|--------|
||Depreciation<br>|6.5<br>|------<br>|-------<br>|---<br>Unchange<br>|d-------<br>|--------<br>|
||Pre-Tax Profit|25.5|24.5|18.0|11.5|5.0|-0.5|
||(as I of Output)|16.2|16.3|13.1|9.2|4.4|-0.5|
|GROUP 3<br>Output||150|150|137.5|125|112.5|100|
|Inputst|Materials|85|77.5|70|62.5|55|48.5|
||Services|15|15|15|15|15|15|
||Total|100|92.5|85|77.5|70|63.5|
|Value A|dded|50|57.5|52.5|47.5|42.5|36.5|
||Labor|43.5|--<br>|-|Unchange|d-------|--------|
||Interest|20.5|------|--------|--<br>Unchange|d-------|--------|
||Depreciation|6|-----|-Unchan|ged-----|--------|--|
||Pre-Tax Profit|-20.0|-12.5|-17.5|-22.5|-27.5|-33.5|
|Memo Item|: Cash-Flow Subsidy|(14.0)|(6.5)|(11.5)|(16.5)|(21.5)|<br>(27.5)|

80. Due to the one-two year time lag between the binding impact of the respective tariff reductions on output and inputs, the profitability of *unprotected* firms (Ist Group) increases during the first three years before reaching a level that is higher than they currently enjoy/. Similarly, the
publications/the-world-factbook/geos/np.html#. Accessed: April 05, 2019.

- Cunha, F. and Heckman, J. (2007). The technology of skill formation. American Economic Review, 97(2):3147.

- Currie, J. and Moretti, E. (2003). Mother's education and the intergenerational transmission of human capital: Evidence from college openings. The Quarterly journal of economics, 118(4):1495 1532.

- Currie, J. and Moretti, E. (2007). Biology as destiny? short-and long-run determinants of intergenerational transmission of birth weight. Journal of Labor economics, 25(2):231264.

- Currie, J. and Vogl, T. (2013). Early-life health and adult circumstance in developing countries. Annu. Rev. Econ., 5(1):136.

- Dewey, K. G. and Begum, K. (2011). Long-term consequences of stunting in early life. Maternal & child nutrition, 7:518.

- Do, Q.-T. and Iyer, L. (2010). Geography, poverty and conict in nepal. Journal of Peace Research, 47(6):735748.

- Domingues, P. and Barre, T. (2013). The health consequences of the mozambican civil war: An anthropometric approach. Economic Development and Cultural Change, 61(4):755788.

- Forsdahl, A. (1977). Are poor living conditions in childhood and adolescence an important risk factor for arteriosclerotic heart disease? Journal of Epidemiology & Community Health, 31(2):9195.

- Gluckman, P. D., Hanson, M. A., and Beedle, A. S. (2007). Early life events and their consequences for later disease: a life history and evolutionary perspective. American Journal of Human Biology, 19(1):119.

- Gluckman, P. D., Hanson, M. A., Cooper, C., and Thornburg, K. L. (2008). Eect of in utero and early-life conditions on adult health and disease. New England Journal of Medicine, 359(1):6173.

- Golden, M. (1994). Is complete catch-up possible for stunted malnourished children? European

28
26 correlated with inequality. The elasticity of murder with respect to inequality within or between racial groups is insignificant. Robbery, on the other hand, exhibits the common characteristic of property crimes - it is highly correlated with mean expenditure in the jurisdiction.

# **VI. Conclusions**

Both theoretical and empirical papers in the crime literature have called for an analysis of crime at a smaller level of geographical disaggregation than countries, states or large metropolitan areas. When the unit of analysis is large, not only is there loss of information regarding relative welfare levels across neighborhoods, but also the fact that individuals may travel to conduct criminal activities is ignored. In this paper, utilizing data on crime and welfare in all police station jurisdictions in South Africa, we have analyzed the effect of local inequality on crime. Although, the contribution of this paper is mainly empirical, we have also suggested a pathway for the generation of property crimes in a jurisdiction that takes into account the distribution of welfare in the surrounding area, and not just within its own borders.

Starting with property crimes, the empirical results indicate that inequality is highly correlated with both burglary and vehicle theft, but once mean expenditure in own jurisdiction and unemployment in the catchment area are controlled for, this correlation becomes smaller for burglary and disappears completely for vehicle theft. Property crime is strongly correlated with mean expenditure in the jurisdiction, indicating that returns from crime are major determinants of property crimes. If wealthier communities have more effective protection from crime, the elasticity of residential burglaries with respect
northern cities, and about 500 in southern cities. These amounts are far above the country’s own air-pollution standard of 100.

Since the mid-1980s there has been marked improvement in air quality, cutting the level of air pollution roughly in half. Progress was achieved by moving industry out of inner cities and shifting home heating from coal to gas. The average city in the south now meets the annual average standard. There has been progress in the north as well, though pollution levels there remain far higher. Even with this progress, however, air pollution levels in China are well above those in other locations in the developing world (Figure 10). China has 20 of the 30 most air-polluted cities in the world. While the use of coal in inner cities has declined, motor vehicle use has been growing rapidly, creating a new source of air pollution.

A recent study by the State Environmental Protection Agency and the World Bank for the first time used Chinese epidemiological data to estimate the excess mortality and morbidity caused by air pollution (World Bank 2007b). The same study also carried out an innovative “willingness to pay” survey of residents in Chongqing and Shanghai to assess how much people valued the benefits of reducing air pollution. This study estimated that the health costs of air pollution amount to 3.8% of GDP. Many of the measures to control air pollution, on the other hand, are relatively inexpensive. Key measures are to get the worst polluting vehicles off the road, shift bus and taxi fleets to natural gas, and invest in public transport rather than individual car use.

An area where China could learn from Africa is the pricing of gasoline. Despite being the second largest importer of petroleum after the U.S., China maintains a controlled and relatively low price for gasoline. During 2000-2004 China’s diesel price 19
-9

Table i is reproduced from the WDR, and presents the World Bank's assessment of the state of poveirt y ir. the developinlg world in 198'. Apart from income povferty, the WDR concentrates on achievements in three key social indic.atois -- under 5 nortality, lite expectancy and net primary enrollment rate. The IHDR, as might be expected, considers a broader range of social indicators. Wlile there is some disagreemnent on specifics, the broad picture painted by the two repoits is remark.,hly consistenit. Thu: on life expectancy both reports arrive at a figure for<sup>all developing countries of 62 years in</sup> the mid 1980s, and this compares wiTh a<sup>figure for 74 years for the developed</sup> countries. However, the average figure<sup>of 62 years hides considerable</sup> variations, ranging from a low of 50<sup>years in Sub-Sahatan Africa to a high of</sup> 67 in East Asia and even 71 in the newly<sup>liberalizing countries of Eastern</sup> Europe. Just as there are variations<sup>between regions, there are variations</sup> between countries within regions. Table<sup>2 is reproduced from the HDR and</sup> shows that countries such as Chad have life<sup>expectancies of 46 years. Of</sup> course, even within countries there are<sup>variations, but the available data</sup> does not permit us to pursue this level of detail.

One social indicator discussed by the HDR<sup>that is not highlighted by the</sup> WDR is access to safe water. Table 3<sup>reproduces some of their numbers.</sup> Overall, in 1986 only 55% of people in the<sup>poor countries of the South had</sup> access to safe water, and this average<sup>also hides considerable variation.</sup> Countries like Mauritius and Sing-,,ore reach<sup>100%while others like Ethiopia</sup> and Mozambique register 16%. The lowest is<sup>Kampuchea with only 3%.</sup> Both reports present figures on a number of other<sup>indicators, but the</sup> general conclusion should be clear. It is that<sup>in the position of the poor in</sup>
<!-- Start of picture text --> 100<br>90<br>80<br>70<br>z<br>5 «60<br>a<br>&o 020<br>pa<br>=<br>C7)<br>2 40<br>o<br>a<br>30<br>10 aa<br>oa BBBBEBEEA SEs SB<br>2010 2011 2012 2013 2014 2015 2016 2017 2018 2019<br>@ Green Occ. in Green Sectors TM Green Occ. in Non-green Sectors<br>@ Non-green Occ. in Green Sectors @ Non-green Occ. in Non-green Sectors<br><!-- End of picture text -->
# **1 Introduction**

How do differences in the local business environment influence location of industry within countries? How do the benefits of a good business environment compare to benefits from good market access and agglomeration economies from industry clustering? And, can improvements in the local business environment enhance industrial activity in geographically (and historically) disadvantaged cities? Finding answers to these questions is important for assessing the role of local policies or interventions in terms of influencing investment flows and industrial activity, particularly in small and medium sized cities. To examine these questions, we start from micro-foundations by analyzing location decisions of individual firms.

We follow a modeling approach to evaluate what factors matter when a firm is considering a location to start production. Using firm level data collected in the 2003 round of the Investment Climate Survey (ICS) for India, we find that the local business environment has a significant bearing on location decisions. Predatory enforcement of business regulations reduces the probability of a business locating in a city. In comparison, better access to finance and to land and greater availability of infrastructure attract firms to a city. However, firms are also attracted by agglomeration economies from clustering of firms in their own industry. This means that new firms will choose to locate production in areas that are already established centers in their line of business. As a result cities that cannot offer the benefit of agglomeration economies to potential entrants may have to offer an even better policy environment to compensate for deficiencies in their economic geography.

2
Policy Research Working Paper 7055

# **Abstract**

India’s manufacturing sector has undergone many spatial adjustments since 1989, including, for example, the organized sector’s migration to rural locations, the powerful rise of informal manufacturing within cities, and the development of intermediate cities for manufacturing. This paper investigates the impact of these spatial adjustments for electricity usage in India’s manufacturing sector. Striking spatial differences in energy usage exist, and whether spatial adjustments exacerbate or alleviate energy consumption strains is important for issues ranging from reducing India’s power blackouts to stemming rising pollution - levels. Using detailed surveys for the organized and unor ganized sectors, the analysis finds that electricity usage per unit of output in urban plants declined steadily during 1989–2010. In the rural areas, by contrast, electricity consumption per unit of output for organized sector plants peaked in 2000 and thereafter declined. Decomposing the observed trends in aggregate electricity usage from 2000 onwards, the paper finds that most reductions in electricity usage per unit of output came from reductions in existing sites of activity (defined through state-industry-urban/ rural cells). The second biggest factor leading to reduced usage was lower usage in fast-growing sectors. By contrast, spatial movements of manufacturing activity across India did not significantly change usage levels and may have even increased them. This appears to have been in part because of the split nature of the mobility, with organized and unorganized sectors migrating in opposite directions.

This paper is a product of the Macroeconomics and Fiscal Management Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at EGhani@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
and auditing, deficiencies in the legal framework, shortcomings in corporate governance, and relatively inexperienced bank management and bank supervisors.<sup>10</sup> These deficiencies are likely to be particularly damaging during a crisis by contributing to greater uncertainty and pessimism among market participants. As noted earlier, deficiencies in accounting and auditing are likely to result in market participants assuming the worst during a crisis.

Finally, and most important, there is persuasive empirical evidence indicating that the banking systems in the CEE countries have been highly unstable during the transition to a market economy, clearly much more unstable than their EU counterparts. Box 1 summarizes information from Lindgren, Garcia, and Saal (1996) that vividly documents the serious banking problems experienced by the CEE countries in recent years. As evidence that these problems have been endemic to transitional economies in general, box 2 presents similar information for the forner Soviet Union.

**Box 1. Recent Banking Problems** in **Selected CEE Countries**

_Bulgaria (1991-present)._ About 75 percent of non-government loans were nonperforming in 1995, leaving many **banks** insolvent. Runs on banks have been **reflected** in pressure on reserve money and a queue of unsettled interbank payments.

_Czech Rpu 99J-presenK_ In 1993-94, 38 percent of bank loans were nonperforming. Three small banks were closedin 0193-4 **one failed iin** 195, and another in 1996.

_Hungary (1987-present)._ Eight banks accounting for _25_ percent of financial system assets became insolvent. At the **end of 19** 3 percent of total **loans were** probleatic. **There** have **ben** two depostor runs.

_Poland (1991-present)._ Sixteen perent of loans were classified as losses, 22 percent as doubtful, and 24 percent as _Romania (1990-present)._ Five major state-owned banks had 35 percent of their accrued interest overdue as of June _30,_ 1994.

_Slovak Repulic (1991.95)._ Loans classified as nonstandard were high at the end of August 1995. There were no runs or major bank clsures, but ail five majorW state banks required government-sponsored restructuring operations.

_Slovena :(1992-94)._ Three banks, withvtwo thirds of the banking system's assets, were restructured during this period. Thepercentage of bad loansV isnot known. Bank rehabilitation was completed in 1995.

Source: Lindgren, Carl-Johan, Gillian Garcia and Matthew 1. Saal. 1996, _Bank Soundness and Macroeconomic Policy_ International Monetary Fund.

10. In general, the entry of foreign banks into individual CEE countries has tended to reduce some shortcomings by introducing "good bank standards" into these countries.

21
**Figure 7: Currency composition of allocated reserves of Figure 8: Net foreign purchases of South African monetary authorities reporting to IMF COFER domestic government bonds**

<!-- Start of picture text --> 6 10 ZAR bn ZAR bn 200<br>USD trn Possible<br>8 WGBI<br>5 Other 6 inclusion<br>announced<br>Daily 150<br>CHF 4<br>4<br>2<br>GBR<br>0 100<br>3<br>JPY<br>-2<br>2 EUR -4<br>50<br>-6<br>USD<br>Cumulative<br>1 -8<br>(rhs)<br>-10 0<br>0<br>Source: IMF (COFER database) Source: Johannesburg Stock Exchange data via<br>Bloomberg<br>1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012<br><!-- End of picture text --> If sustained, even small changes in the asset allocations of major investors not traditionally focused on EM debt would significantly drive up demand, given the scale of assets under management in the investment industry. According to the EM debt and currency team at Investec, there are US$80 trillion in conventional AUM globally and allocations to EM debt remain modest (e.g. estimates of an average of 2.2% of AUM allocated by pension funds in the U.S., U.K. and Europe); a reallocation to EM debt of just 1% of assets would therefore generate inflows of US$800bn.<sup>16</sup> It is probably impossible to make a reliable prediction of future global asset allocation and foreign demand for EM local currency debt. What is clear, however, is that there is a multiplicity of sources of this demand, and there is evidence that a powerful “virtuous cycle” in EM policies, macro dynamics, foreign participation and market development, of the kind described by Burger et al (2008) has been at work, and may in fact have been reinforced by the global economic and financial market turmoil of the last few years. It is not unreasonable to expect this to continue, though only time will tell how persistent the key underlying demand-side forces of increasing global economic and financial integration and diminishing home investment bias will prove to be.

# **5. Considerations for EM debt managers**

What does the trend towards growing foreign investor participation mean for the managers of EM public debt?

One positive implication is a higher payoff for generally sound debt management. The strong appetite for EM debt means that improvements in economic policies and management, including debt management, can be rewarded with significant offshore demand for the issuer’s paper. This can lower reliance on foreign currency borrowing and thus reduce currency risks to the public debt portfolio, as well as lower onshore borrowing costs.

This said, EM local currency debt remains a risky asset from the perspective of foreign investors. Consequently, there is no room for complacency on the part of debt managers, particularly as the supply of competing EM debt rises as new countries join the ranks of EM domestic bond issuers, the perceived credit quality of existing issuers improves, and economic development and public investment funding

> 16 Investec, _Emerging Markets Debt: the next 10 years_ , Paper 7, (May 2012)

**10**