rafmacalaba/datause-encoder-data huggingface dataset:
prices being the most variable (see Kaminski and others, 2014). In addition to greater volatility, the annual rate of inflation between 2000 and 2014 in Malawi (15.4 percent) was 2.5 times higher than the Sub-Saharan Africa regional average (6.1 percent) (Dabalen and others, 2017).

Figure 1 presents monthly price data from 2009 to 2013 for staple foods from 72 markets across Malawi. Food prices in Malawi increased significantly between late 2011 and early 2013, which falls within the two waves of survey fieldwork. The price of maize increased steadily over this period, but also experienced a particularly sharp spike during the end of 2012. From 2009 through most of 2011, maize prices were stable, hovering around 40 to 50 kwacha per kilogram. In 2012, the price of maize began to climb slowly, but then in the short time between December and March of 2013, the price more than doubled, jumping from 65 kwacha per kilogram to 136 kwacha per kilogram. Other food staples experienced similarly large increases of prices between the waves of data collection. For example, from July 2011 to March 2013, the price of beans more than doubled, from 165 kwacha per kilogram to a peak near 380 kwacha per kilogram.

7
# **Appendix 2: Additional Details on Listing and Sample Selection**

Altogether 6,296 female-owned businesses in 161 markets were listed. After the census, three markets in Kakamega county were dropped because the number of women in these markets was too few. We then applied an eligibility filter to determine which women to include in the baseline survey. This filter required the women to have reported profits, and not to have reported profits that exceeded sales; to have a phone number that could be used to invite them for training; to be 55 years or younger in age; to not be running a business that only dealt with phone cards or m- pesa, or that was a school; that the person responding not be an employee; that the business not have more than 3 employees; that the business have profits in the past week between 0 and 4,000 KSH; that sales in the past week be less than or equal to 50,000 KSH; and that the individual had at least one year of schooling. These criteria were chosen to reduce the amount of heterogeneity in the sample (thereby increasing our ability to detect treatment effects), and to increase the odds of being able to contact and find individuals again. Applying this eligibility filter reduced the 6,296 individuals to 4,037 individuals (64%). Baseline surveys took place soon after the listing surveys in each county, between June and November 2013. Out of a target of 4,037 individuals, we were able to interview 3,537 (87.6%) in time to consider them for inviting to training.

38
# **Unpleasant Surprises: Sovereign Default Determinants and Prospects**

Luca Bandiera, Jesus Crespo Cuaresma, and Gallina A. Vincelette<sup>1</sup>

> 1 Luca Bandiera and Galliva Vincelette are from the World Bank’s Economic Policy and Debt Department and Jesus Crespo Cuaresma is Professor of Economic from the Vienna University of Economics and Business. The authors thank the anonymous reviewers for their insightful comments and suggestions on an earlier draft of this paper, as well as for comments received from participants at the World Bank‐AfDB Debt Management Conference in Tunis in March 2010 where this paper was presented. We have tried to duly incorporate them in this version of the paper. This paper was prepared for the Debt Management Facility Stakeholders Forum in Tunis, March 29‐30 2010, and is forthcoming in "Sovereign Debt and the Financial Crisis," eds. Carlos A. Primo Braga and Gallina A. Vincelette. World Bank. 2010"
# Figure 9. World poverty, 1820-2001

<!-- Start of picture text --> Number of people living on less than $1 per day (millions)<br>1,500<br>1,400<br>1,300<br>Bourguignon-<br>Morrisson<br>1,200<br>Chen-<br>Ravallion<br>1,100<br>1,000<br>900<br>1820 1840 1860 1880 1900 1920 1940 1960 1980 2000<br><!-- End of picture text --> Poverty incidence has been gradually declining throughout modern history, but in general population growth outstripped the decline in incidence so that the total number of poor people was actually rising. Even in the 1960-1980 period, which was reasonably good for developing countries, the number of poor continued to rise (Figure 9).<sup>1</sup> What is really striking about the past 20 years is that the number of extreme poor declined by 375 million, while at the same time world population rose by 1.6 billion. This decline in the number of poor is unprecedented in human history.

While the overall decline in global poverty is positive news, it should be noted that there has been very different performance across regions. While East and South Asia grew well and reduced poverty, Sub-Saharan Africa had negative growth between 1981 and 2001 and a rise in poverty: the number of extreme poor in Africa increased from 164 million (41.6 percent of the

> 1 It is difficult to take the survey-based estimates of poverty back before 1980.  Bourguignon and Morrison (2002) combine what survey data are available with national accounts data to provide rough estimates of poverty back to 1820.  The broad trend is clear: the number of poor in the world kept rising up to about 1980.

18
# **Table 8.  Sector Export Intensities by Regional Market: Exports of the Sector as a Percent of Production of the Sector** (in percent)

|Good|Central|Far East|North|Siberia|South|Urals|Moscow|St.<br>Petersb.|Tumen|North-<br>west|
|---|---|---|---|---|---|---|---|---|---|---|
|MAR|53|57|57|51|53|50|54|57|51|57|
|AGR|1|1|1|1|1|1|1|1|1|1|
|AIR|46|48|48|44|45|43|43|48|47|48|
|CHM|27|21|17|48|27|37|24|35|40|57|
|CNM|3|3|3|6|3|5|3|4|4|7|
|COL|23|23|23|23|23|23|||||
|CON|3|3|3|3|3|3|3|3|3|3|
|CRU||56|56|56|56|56|||56|56|
|ELE|2|2|2|2|2|2|2|2|2|2|
|FIN|1|1|1|1|1|1|1|1|1|1|
|FME|40|35|34|37|43|37|48|75||37|
|FOO|4|12|8|8|11|4|9|6|3|9|
|GAS||27|27|27|27|27|||27|27|
|HEA|0|0|0|0|0|0|0|0|0|0|
|HOU|1|1|1|1|1|1|1|1|1|1|
|MWO|11|25|14|48|25|18|45|32|12|27|
|NFM|44|45|48|43|58|55|62|67||79|
|OIL|32|32|32|32|32|32|32|32|32||
|OTH|12|12|12|12|12|12|12|12|12|12|
|OTI|15|15|15|15|15|15|15|15|15|15|
|PST|9|9|9|9|9|9|9|9|9|9|
|RLW|2|2|2|2|2|2|2|2|2|2|
|SCI|3|3|3|3|3|3|3|3|3|3|
|TMS|7|7|7|7|7|7|7|7|7|7|
|TPP|7|77|33|48|11|17|5|30|12|33|
|TRD|1|1|1|1|1|1|1|1|1|1|
|TRK|2|2|2|2|2|2|2|2|2|2|
|TRO|5|5|5|5|5|5|5|5|5|5|
|CLI|11|11|11|11|11|11|11|11|11|11|
|Total|364|534|474|545|488|477|397|459|357|510|

See Tables 1 and 2 for sector and region definitions.

Source: Roskomstat unpublished surveys and authors' calculations.

35
- 32 -

Table 6 Probit: Impact of 2olicies on the performance of all social proiects Dependent Variable: Dummy for unsatisfactory projects

||Model 1||Model|2|
|---|---|---|---|---|
|Variable|Coefficient|t|Coefficient|t|
|Currency over-valuation<br>Specification<br>1|||||
|Constant|-1.2093|-5.86|-1.0860|-4.18|
|M2BLACK|0.0043|3.02|0.0034|2.31|
|MSM2BLK|-0.6308|-1.26|-0.7680|-1.45|
|MGDPZ|||-0.0553|-1.81|
|MSGDP|||0.2497|1.01|
|Africa|0.2538|1.02|0.2559|0.95|
|EMENA|0.4128|1.49|0.4273|1.52|
|LAC|0.1482|0.54|0.0742|0.25|
|Log likelihood||-122.43||-119.23|
|Currency over-valuation|||||
|Specification<br>2|||||
|Constant|-1.2031|-5.77|-1.0764|-4.08|
|LNMBK1OA|0.1155|2.60|0.0877|1.91|
|MSLNB1OA|-0.5908|-1.17|-0.7545|-1.41|
|MGDPZ|||-0.0567|-1.85|
|MSGDP|||0.2793|1.10|
|Africa|0.1967|0.79|0.2153|0.80|
|EMENA|0.3945|1.43|0.4158|1.48|
|LAC|0.0401|0.14|-0.0082|-0.03|
|Log likelihood||123.56||120.06|
|Fiscal deficit|||||
|Specification<br>1|||||
|Constant|-0.9804|-3.95|-0.7188|-2.38|
|BALANK1|13.8350|1.64|14.5000|1.74|
|BALANK2|-2.3937|-0.96|-1.7313|-0.68|
|MSBALAN|-3.0331|-0.13|-0.3040|-1.13|
|MGDPZ|||-8.0807|-2.61|
|MSGDP|||0.3022|1.20|
|Africa|0.1299|0.52|0.1517|0.56|
|EMENA|0.2577|0.88|0.3514|1.18|
|LAC|0.1446|0.52|0.0521|0.18|
|Log likelihood||-126.12||-12018|
Policy Research Working Paper 6848

# **Abstract**

This paper utilizes a cross-country panel of 83 developing countries to examine how changes in cohort size are correlated with subsequent employment outcomes for workers at different ages. The results depend on countries’ level of development. In low-income countries, young adults that are born into smaller cohorts are less likely to work, but school attendance remains unchanged. In middle-income countries, young adults in smaller cohorts are less likely to be unemployed and more likely to work outside of agriculture. Neither pattern can be discerned among older adults, although the estimates are imprecise. In sum, reductions in cohort size are associated with moderate improvements in employment outcomes for youth in middle-income countries, but there is scant evidence that these improvements persist into adulthood.

This paper is a product of the Poverty Reduction and Economic Management Unit, South Asia Region. 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 dnewhouse@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
# Investor clout (2)

<!-- Start of picture text --> y= frontier u>=© frontier<br>9*3-° frontier<br>ute-° frontier<br>i/a ——<br>4i/(a + 3i)<br>0 ifa 2i/(a+i) 1<br>Government effectiveness (@)<br><!-- End of picture text --> Investor clout (2) <!-- Start of picture text --> cen eeecenencnneensecrscccecasenaeeneussoccsauaan<br>1 Strategic<br>city<br>Developer<br>city<br>i/a<br>Rural Conventional<br>area city<br>4i/(a + 3i)<br>0 ifa 2i/(a +i) 1<br>Government effectiveness (0)<br><!-- End of picture text -->
growth in the 1990s and their assets reached 9 percent of GDP by 1995. They invested heavily in government securities and accounted for almost 4 percent of government debt. Insurance companies probably held close to 1 percent of government debt, while pension funds, which had been allowed in the early 1990s to invest in government bonds through a special service of the central bank, probably held 3 percent of the total.<sup>20</sup> Thus, retail investors are estimated to account for 20 percent. The share of the banking system fell to 44 percent , while foreign investors accounted for 21 percent of the total (Table 3.6).

**Table 3.6: Holders of Government Debt, 1980-1995**

|(percent of total)|1980|1985|1990|1995|
|---|---|---|---|---|
|Banking System|83.9|69.4|62.9|43.9|
|Mutual Funds|0.0|0.0|0.0|3.9|
|Insurance Companies|0.0|0.0|0.0|0.8|
|Pension Funds|0.0|0.0|0.0|3.1|
|Retail Investors|0.0|0.0|17.0|20.2|
|Foreign Investors|16.1|30.6|20.1|20.6|
|Other Government Entities||||7.4|
|Total|100.0|100.0|100.0|100.0|

Source: Estimated on the basis of Bank of Greece, Ministry of Finance, IMF and OECD data.

# **3.4 The Search for Efficiency and International Integration (1996-2000)**

The attractiveness of government securities to domestic non-bank investors peaked in 1996 when they accounted for 79 percent of new issues (Table 3.7). A drastic change occurred in 1997 that was intensified in the remaining years of the decade. Institutional investors from other European countries became attracted to the high yields offered by Greek government securities, an attraction that was reinforced by the prospect of large capital gains that were likely to ensue from falling interest rates linked to economic convergence and eventual entry of Greece into the euro zone. The strong political commitment to achieve economic convergence and join the euro zone strengthened the credibility of government policy and paved the way for the successful integration with the euro markets.

Between 1997 and 2000, foreign investors acquired debt securities that amounted to 120 percent of new borrowings, while domestic non-bank investors sold securities equal to 65 percent of the same total (Table 3.7). Most of the increase in the holdings of foreign investors concerned drachma-denominated securities that were issued in the domestic market. During this period foreign debt rose by less than one-fifth of the total increase in the holdings of foreign investors.

> 20 This probably understates the total holdings of pension funds because it includes only those investments that are effected through the central bank and are reported in its annual report. It excludes any direct investments by pension funds that do not use the services of the central bank.

32
# **How Technology Adoption and Trade Are Shaping**

# **Indonesian Labor Markets**<sup>**1**</sup>

Mariana Viollaz<sup>i</sup> Francis Addeah Darko<sup>ii</sup> Andrew D. Mason<sup>iii</sup>

## **JEL: F17, N70, E24**

**Keywords: Technology adoption, Trade, Labor market**

> 1 This paper was produced as a background paper to the World Bank’s East Asia and Pacific regional study, “ _A Resurgent East Asia:  Navigating a Changing World”._

> i Centro de Estudios Distributivos, Laborales y Sociales (CEDLAS), Facultad de Ciencias Económicas (FCE), Departamento de Economía, Universidad Nacional de La Plata (UNLP). Calle 6 e/ 47 y 48, Piso 3, Oficina 322, La Plata, Provincia de Buenos Aires, Argentina. email: <u>mviollaz@cedlas.org</u>

> ii The World Bank, Poverty and Equity Global Practice, Jakarta, Indonesia. email: <u>fdarko@worldbank.org</u>

> iii The World Bank, Chief Economist Office (East Asia and Pacific), Washington, DC. email: <u>amason@worldbank.org</u>
# **Table** **<u>8: Estimated benefits from the policy change</u>**

|Quintile C|hange in probab<br>Adults|ility of falling sick<br>Children|Individual b<br>Adults|enefit (USh)<br>Children|Overall bene<br>Adults|fit (Mn US $)<br>Children|
|---|---|---|---|---|---|---|
|1|2.76%|4.54%|2475.91|1073.39|3.691|2.008|
|2|1.84%|3.39%|1792.52|874.48|2.447|1.470|
|3|1.39%|2.78%|1346.42|728.36|1.473|0.890|
|4|1.00%|2.20%|921.95|561.97|0.944|0.632|
|5|0.56%|1.61%|430.90|406.49|0.382|0.047|
|Total|1.46%|2.99%|1337.79|750.23|8.937|5.047|

Source: Own computation based on the regression results reported earlier.

26
The next three columns in Table 1 decompose the change in CE food demand annual growth rate into per capita consumption growth and population growth. Table 1 reveals that the annual average growth in per capita food demand has become increasingly important, rising from 0.55 percent per year in the 1980s to 0.69 percent per year in the 1990s and 0.72 percent in the 2000s respectively while annual average population growth has decreased, from 1.75 percent in the 1980s to 1.36 percent in the 1990s, and 1.15 percent in the 2000s.

To explore how CE consumption might evolve to 2050, we use projections for population and GDP (in PPP 2005 constant prices) from the Shared Socioeconomic Pathways (SSP) database developed by the International Institute for <mark>Applied Systems Analysis (IIASA)</mark> .<sup>9</sup> To provide a benchmark, we focus on the so-called ‘middle ground’ scenario (SSP2) for both GDP and population projection data. Over the period 2009-2050, the SSP2 projection suggests annual world per capita GDP growth of 2.4 percent and world population growth of 0.68 percent per year. This implies annual global GDP growth of 3.1 percent.

Figure 3a shows the growth of the global population in percent log-difference form. This illustrates clearly the rapid decline that has occurred, and is projected, in world population growth rates. However, measures of aggregate population growth mask differing regional population growth rates. Figure 3b shows the projected evolution of population between 1992 and 2050 by region. The proportion of the population living in the two poorest regions, namely the SA and SSA regions combined, is projected to increase from 36 percent in 2009 to 45 percent by 2050. China’s population, which accounted for about one-fifth of the world population in 2009, is projected to peak around 2030. Figure 3c reveals that nearly three-quarters of the increase in the global population is expected to be in SSA (44 percent) and SA (29 percent).

An important feature of equation (1) is its implied pattern of income elasticities for total food demand. While income elasticities of demand for individual food items generally decline as income rises (Timmer, Falcon and Pearson 1983), the shift in demand from starchy staples to livestock products may cause the income elasticity of total food demand measured in resource requirements to rise over some range. As shown by Gouel and Guimbard (2017), the elasticity of demand for starchy staples is generally low, even for low-income consumers, while the elasticity

> 9 https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=about

9
TABLE 3: GDP GROWTH AND CRIME AGAINST FIRMS – QUALITY OF GOVERNANCE AND VOTER TURNOUT INTERACTIONS

|Deendent variable|% of Losses Due to Crime Over|% of Losses Due to Crime Over|
|---|---|---|
|p|Sales|Sales|
||<br>Small and Mediu|m Firms sample|
||1<br>|2<br>|
|Real GDP per Capita Growth|-0.2469***|-0.3573***|
||[0.0742]|[0.0941]|
|Real GDP per Capita Growth x Quality of|0.2995**||
|Governance|[0.1338]||
|GDP per Capita Growth||0.4022***|
|x Voter Turnout||[0.1417]|
|Quality of Governance|-2.1963**||
||[0.8490]||
|Voter Turnout||-1.8393**<br>[0.7621]|
|Police per 100,000 persons|-0.0018***|-0.0010*|
||[0.0006]|[0.0006]|
|Firm with Female Owner|0.1739*|0.1736*|
||[0.0855]|[0.0849]|
|Real GNI per capita (in 100s)|-0.0033*|-0.0046***|
||[0.0018]|[0.0016]|
|GINI|-0.0192|0.0049|
||[0.0132]|[0.0099]|
|Population in Millions, Total|0.0032*|0.0040**|
||[0.0017]|[0.0019]|
|Small firm dummy variable|0.2432**|0.2455***|
||[0.0938]|[0.0844]|
|Large City or Capital dummy variable|0.1042|0.0859|
||[0.1047]|[0.0970]|
|Manufacturing firm dummy variable|-0.1662|-0.1717|
||[0.1198]|[0.1071]|
|Number of Countries|24|27|
|Number of Observations|8299|9160|

* significant at 10%; ** significant at 5%; *** significant at 1%, Standard errors in brackets clustered at the country level

25
# Intra-Sub-Saharan African Trade Is it too Little?

I) Introduction Official statistics suggest that trade among Sub-Saharan African" (SSA) countries as a whole, as well as among various regional groupings in SSA, is a small fraction of each country's total, and that share has remained roughly constant over the years (Table 1)1. Many observers of African affairs believe this level of intra-SSA trade is "too small" and should be expanded further and a number of regional schemes have been initiated with that goal.

African countries' regional trade shares could be "too small" either normatively, in comparison to an optimal level, or empirically. Empirically, trade shares could be either absolutely small or small relative to expectations. While intra-SSA trade is absolutely small, we ask, is it smaller than expected? For whatever reason intra-SSA trade is judged to be too little, there have not been many attempts in the literature to quantify how little is little. In order to decide whether trade among the members of a regional grouping is "too little", some model for the determination of the volume of bilateral trade must be specified. We are not aware of any such model for the sub-region. As a result, there is a gap in the existing literature between the intuition that intra-SSA trade is too little and the empirical evidence to support the intuition. This paper is a partial attempt to fill this gap. It is a partial attempt for we look at the question strictly from a positive point of view. We ask a simple question: Compared to a sample of other countries with roughly similar economic characteristics, do 'Sub-Saharan Africa comprises all of the African continent except for Northern African countries (Algeria, Egypt, Libya, Morocco, and Tunisia) and South Africa, which is excluded because its bilateral trade is affected by obvious political factors.

2 We will return in section IV to a discussion of the unreliability of official trade statistics.
- Matsumoto, Takuji and Yuji Yamada (2021). “Simultaneous hedging strategy for price and volume risks in electricity businesses using energy and weather derivatives”. _Energy Economics_ 95, 105101.

- McDermott, Grant R. and Øivind A. Nilsen (2014). “Electricity Prices, River Temperatures, and Cooling Water Scarcity”. _Land Economics_ 90, 131–148.

- Meng, Kyle C., Kimberly L. Oremus, and Steven D. Gaines (2016). “New England Cod Collapse and the Climate”. _PLOS ONE_ 11, e0158487.

- Miguel, Faruk, Alvaro Pedraza, and Claudia Ruiz-Ortega (2022). “Climate Change Regulations: Bank Lending and Real Effects”.

- Mori-Clement, Yadira (2019). “Impacts of CDM projects on sustainable development: Improving living standards across Brazilian municipalities?” _World Development_ 113, 222– 236.

- Mueller, Valerie, C. Gray, and K. Kosec (2014). “Heat stress increases long-term human migration in rural Pakistan”. _Nature Climate Change_ 4, 182–185.

- Münch, Florian and Fabian Scheifele (2022). “Nurturing National Champions? Local Content in Solar Auctions and Firm Innovation”. Rochester, NY.

- Muñoz, J. Ricardo and David J. Sailor (1998). “A modelling methodology for assessing the impact of climate variability and climatic change on hydroelectric generation”. _Energy Conversion and Management_ 39, 1459–1469.

- Nam, Kyung-Min et al. (2014). “Synergy between pollution and carbon emissions control: Comparing China and the United States”. _Energy Economics_ 46, 186–201.

- Neumayer, Eric and Richard Perkins (2004). “What Explains the Uneven Take-Up of ISO 14001 at the Global Level? A Panel-Data Analysis”. _Environment and Planning A: Economy and Space_ 36. Publisher: SAGE Publications Ltd, 823–839.

- Pan, An et al. (2023). “Can environmental information disclosure attract FDI? Evidence from PITI project”. _Journal of Cleaner Production_ 403, 136861.

48