rafmacalaba/datause-encoder-data huggingface dataset:
# **Methodology**

The income-poverty measures are designed to count the poor and to diagnose the extent and distribution of poverty. The income-poverty measures proposed by Foster, Greer, and Thorbecke (1984) are used throughout the paper. These are the headcount rate (P0), poverty gap (P1), and squared poverty gap (P2) measures. The former measures the magnitude of poverty and the latter two poverty measures assess both poverty magnitude and intensity.

The headcount rate is defined as the proportion of household heads (not the whole population) below the poverty line. One concern applying the P0 measure is that each individual below the poverty line is weighted equally and, therefore, the principle of transfers is violated. A limitation of the measure is illustrated by the fact that it would be possible to reduce the P0 measure of poverty by transferring money from the very poor to lift some _richer_ poor out of poverty, hence increasing social welfare according to the measure. P0 takes no account of the degree of poverty and it is unaltered by policies that lead to the poor becoming even poorer.

One measure of poverty that takes this latter point into account (at least in weak form) is the poverty gap measure (P1). P1 is the product of incidence and the average distance between the incomes of the poor and the poverty line. It can be interpreted as a per capita measure of the total economic shortfall relative to population. P1 distinguishes the poor from the not-so-poor and corresponds to the average distance to the poverty line of the poor. One problem with the poverty gap, as an indicator of welfare is that, poverty will increase by transfers of money from extreme poor to less poor (who become nonpoor), and from poor to non-poor. Furthermore, transfers among the poor have no effect on the poverty gap measure.

The P2 measure of poverty is sensitive to the distribution among the poor as more weight is given to the poorest below the poverty line. P2 corresponds to the squared distance of income of the poor to the poverty line. Hence, moving from P0 towards P2 gives more weight to the poorest in the population.

This paper sets its poverty bar very low. To define “extreme poverty” or indigence it uses a US$1 a day poverty line, which is annually 2,681 gourdes.<sup>3</sup> Those that earn a per-capita income above US$1 are above the indigence line and therefore not extremely poor. The poverty lines used for rural, urban, and metropolitan areas are identical, as consumer price index data do not exist for different regions or locations in Haiti. This may overestimate poverty in rural areas slightly.

> 3 The conversion is based on the 2000 PPP. The questionnaire asks for information about income in the last 12 months and self-consumption in the last week (which is multiplied by 52 to obtain the annual selfconsumption).

4
conclusions 33 Expected benefit of ASP (1 month Samurdhi top-up) by return period & beneficiary group <!-- Start of picture text --> Cost of ASP<br>after 50-year flood All Samurdhi enrollees<br>(no targeting)<br>25 $14.3M Annual cost = 1.43MProgram BCR = 2.0<br>10<br>All affected<br>5 (perfect targeting)<br>Annual cost = 306K<br>Program BCR = 1.2<br>$3.5M<br>Affected and PMT 887<br>(perfect targeting)<br>Annual cost = 60K<br>Program BCR = 3.5<br>$676K<br>Samurdhi enrollee and affected<br>(perfect targeting)<br>Annual cost = 48K<br>Program BCR = 2.4<br>$532K<br>1<br>10 25 50 100 500 1000<br>Return period [years]<br>Avoided wellbeing losses [mil. US$]<br><!-- End of picture text -->

**Figure 12:** Expected benefit of four ASP responses to precipitation flooding, by disaster magnitude (return period) and inclusive of all districts in Sri Lanka. Benefit is the expected reduction to wellbeing losses with ASP, compared to a scenario with no post-disaster support. Note: both axes are logarithmic.

(BCR = 2.4). Finally, a new social protection system targeted at poor (PMT ⩽ 887), flood-affected individuals delivers the greatest return (BCR = 3.5) at a cost of US$60K per year.

These cost and benefit estimates are based on simple coverage criteria, applied uniformly to all districts. In practice, criteria for post-disaster support may vary by province and disaster magnitude. This framework can model all such complexities, to the and of the household and hazard up granularity representativeness survey maps used as inputs.

# 5 conclusions

This paper has presented the results of a risk assessment based on an expanded framework, which includes in the analysis the ability of affected households to cope with and recover from disaster asset losses and uses “wellbeing losses” as its main measure of disaster severity. This framework adds to the three usual components
Uruguay has a de jure and de facto floating exchange rate regime. Besides, the level and composition of reserves and FX debt, showing an exact match, improve the sovereign’s resilience to external exchange rate shocks.

# **IV.III. Countries with Net FX Liability Positions**

# **A. Ghana**

Government debt is above 70 percent of GDP but in a downward path with increasing share of domestic debt. Concessional funding has been a significant source of the external financing program but since 2013 Ghana has been active in issuing USD-denominated bonds in the international capital markets. External debt represents slightly more than half of the government’s overall debt portfolio (55 percent, see Table 12).

**Table 12 – Ghana: Composition of Debt**

_<mark>as of end December 2016, millions USD</mark>_

||Amount|Percent|
|---|---|---|
|Domestic Debt|12,776|45.3|
|External Debt|15,442|54.7|
|Total|28,218|100.0|

Ghana’s external debt is 2.35 times greater than the stock of its foreign exchange reserves. USD reserves cover more than half of the country’s USD-denominated debt. However, Ghana has almost no reserves in EUR to cover a sizeable amount and share of EUR-denominated debt (USD 1.6 billion and 11 percent respectively, see Table 13).

**<mark>Table 13 – Ghana: Composition of Foreign Currency Debt and Reserves</mark>**

_<mark>as of end December 2016, millions USD</mark>_

|||USD|EUR|CNY|GBP|SDR|Other|Total|
|---|---|---|---|---|---|---|---|---|
||USD mil. eq.|5,244|33|-|68|1,164|72|6,581|
|Reserves|Percent of total|79.7|0.5|-|1.0|17.7|1.1|100.0|
||Percent of GDP|12.3|0.1|-|0.2|2.7|0.2|15.4|
||USD mil. eq.|9,176|1,631|268.7|-|3,434|933|15,442|
|External Debt|Percent of total|59.4|10.6|1.7|-|22.2|6.0|100.0|
||Percent of GDP|21.4|3.8|0.6|-|8.0|2.2|36.1|
|Concentration|Ratio FX debt/ reserves|1.75|49.42|n/a|n/a|2.95|12.96|2.35|

Source: 2017 MTDS report and Bank of Ghana 2016 Annual Report _Applied FX Rate: End December 2016 4.2002GH/USD_ 21
- Volpe Martincus, C. and J. Carballo (2008): “Is export promotion effective in developing countries? Firm-level evidence on the intensive and the extensive margins of exports,” _Journal of International Economics_ , 76, 89–106.

- ——— (2010): “Beyond the average effects: The distributional impacts of export promotion programs in developing countries,” _Journal of Development Economics_ , 92, 201–214.

- Wooldridge, J. M. (2007): “Inverse probability weighted estimation for general missing data problems,” _Journal of Econometrics_ , 141, 1281–1301.

- World Economic Forum (2016): “The Global Enabling Trade Report,” World Economic Forum and the Global Alliance for Trade Facilitation .

- Zia, B. (2008): “Export incentives, financial constraints, and the (mis)allocation of credit: Micro-level evidence from subsidized export loans,” _Journal of Financial Economics_ , 87, 498–527.

30
https://doi.org/10.1007/s11187-011-9374-z Beck, T, Demirguckunt, A., & Maksimovic, V. (2008). Financing patterns around the world: Are small firms different? _Journal of Financial Economics_ , _89_ (3), 467–487. https://doi.org/10.1016/j.jfineco.2007.10.005 Beck, Thorsten. (2005). Financial and legal constraints to growth: does firm size matter? _The Journal of Finance_ , _LX_ (1). Retrieved from

- http://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.2005.00727.x/full

Beck, Thorsten, Demirgüç-Kunt, A., & Singer, D. (2013). Is Small Beautiful? Financial

- Structure, Size and Access to Finance. _World Development_ , _52_ , 19–33. https://doi.org/10.1016/j.worlddev.2013.05.014

- Blackburn, K., & Sarmah, R. (2006). _Red Tape , Corruption and Finance_ (Center for Growth and Business Cycle Research Discussion Paper Series No. 82). University of Manchester.

Boyd, J. H., Levine, R., & Smith, B. D. (2001). The impact of infation on financial sector performance. _Journal of Monetary Economics_ , _47_ , 221–248.

Brixiová, Z., Kangoye, T., & Tregenna, F. (2020). Enterprising Women in Southern

- Africa: When Does Land Ownership Matter? _Journal of Family and Economic Issues_ , _41_ (1), 37–51. https://doi.org/10.1007/s10834-020-09663-2

- Chakravarty, S., & Xiang, M. (2013). The international evidence on discouraged small businesses. _Journal of Empirical Finance_ , _20_ , 63–82.

https://doi.org/10.1016/j.jempfin.2012.09.001 Claessens, S. (2006). Access to financial services: A review of the issues and public policy objectives. _World Bank Research Observer_ , _21_ , 207–240. https://doi.org/10.1093/wbro/lkl004

- D’agostino, G., Dunne, J. P., & Pieroni, L. (2016). Corruption and growth in Africa.

31
25 Nielsen, L. T. 1993. "Understanding N(d1) and N(d2): Risk-Adjusted Probabilities in the Black-Scholes Model". _Journal of the French Finance Association 14 (1)._ Perry G. 2009. Beyond Lending: How Multilateral Development Banks Can Held Developing Countries <u>Manage Volatility. Center for Global Development.</u> Ross M. 2012. The Oil Curse: How Petroleum Wealth Shapes the Development of Nations. Princeton University Press.

van der Ploeg F. 2011. “Natural Resources: Curse or Blessing?” _Journal of Economic Literature 49 (2)._ van der Ploeg F. and S. Poelhekke. 2010. “The Pungent Smell of Red Herrings: Subsoil Assets, Rents, Volatility and the Resource Curse”. _Journal of Environmental Econcomis and Management 60 (1)._ World Bank. 2010. “Uganda Oil White Paper: Development of Oil Resource in Uganda.” Processed.

Yépez-García, R.A. and J. Dana. 2012. “Mitigating Vulnerability to High and Volatile Oil Prices: Power Sector Experience in Latin America and the Caribbean”. World Bank.
6 Taking further the comparison of the composition of Hungary'. exports to the EC-12 with Hungary's exports to the world for 1987 (Table 4), there are **some** triking differences. For example, only 16 percent of Hungary's exports to the sorld are food items whereas nearly 25 percent oZ its exporta to the EC-12 are food items. Again, among the large trade items there is a much higher shar- of basic manufactures (SITC 6) and miscellaneous manufactures (SITC 8) in Hungary's exports to the EC-12 than to the world. However, when it comes to n-chinery and transport equipment (SITC 7), these make up 33.9 percent of Hungary'.J export. to the world but only 12.7 percent of its exports *o the EC-12. This appears to be related to the inclusion in world exports of transport equipment (buses) which are exported to the USSR. These products are relatively uncompetitive in the EC. Certainly, tariff rates seem high against Hungary in this sector but other trade barriers that Hungary faces in the EC-12 are not discriminatory against Hungary in this sector. On the contrary, NTB's have been Hspecially aimed at Japanese autos. Moreover, as we shall see in Section IV there is greater protection in other large export sectors. However, it .s notable that almost half of Hungary's exports to the USSR are machinery and transport equipment -- mostly buses. (Indeed mcre than 80 per cent of Hungary's exports of buses are to other CMEA countries). Thus, Hungary's world figures were somewhat distorted by the special trade arrangements within the CMEA and its remains to be seen how these will now change.

Table 4. Commodity composition of Hungary's exports to the world and the EC-12, 1987.

|Product|world|EC-12|Difference as%<br>of world Share|
|---|---|---|---|
|Total Export (Sm)|9571|1912||
|Share in total (percent)|<br>100.0|100.0||
|0|16.0|24.9|+55.6|
|1|1.6|0.8|-50.0|
|2|4.3|8.0|+86.0|
|3|4.2|3.6|-14.2|
|4|0.8|0.4|-50.0|
|5|11.6|13.7|+18.1|
|6|13.7|18.4|+34.3|
|7|33.9|12.7|-62.5|
|8|12.0|15.3|+27.5|
|9|1.8|2.1|+16.6|

Source: COMTRADE
# **1. Introduction**

The 2008 global financial crisis has resulted in declining demand for goods and services, decreasing availability of external finance, declining investments, and reductions in remittances, forcing firms around the world to face insolvency. For instance, in 2009, the number of corporate bankruptcies in Japan was 13,306, an increase of 4.9% from 2008 (Teikoku Databank, 2010<sup>i</sup> ); the number of corporate bankruptcies in the U.K. was 94,135, an annual increase of 5.88% (Ministry of Justice, 2010<sup>ii</sup> ); and the number of corporate bankruptcies in Germany was 32,687, which represents an 11% annual increase from 29,291 insolvencies in 2008, though the volume of debt more than doubled (Statistisches Bundesamt Deutschland, Jahrbuch, 2009<sup>iii</sup> ). In the United States in 2009, 60,837 businesses declared bankruptcy, representing a 40% increase in filings from 2008 (American Bankruptcy Institute, 2010<sup>iv</sup> ).

During previous financial crises in Russia, East Asia, and Argentina, attention turned to the importance of bankruptcy laws that supported the efficient resolution of financial distress (Claessens, et al., 2003). This same shift of attention is happening today, as policymakers have become concerned about the effectiveness of existing bankruptcy laws, which encompasses both the usefulness of reorganization and liquidation laws, as well as efficiency of the judicial system to uphold the laws in court.

Despite the frequency of insolvency and firm closure, the usage of legal procedures associated with bankruptcy vary significantly around the world, due to differences in legal traditions, accounting standards, regulatory frameworks, and macroeconomic factors (Claessens and Klapper, 2005). For instance, bankruptcies are less common in countries with concentrated banking systems and in firms with single banking relationships, and are more common in firms with more complex capital structures (Babchuck, 1988). Furthermore, the laws in some countries 2
Akerman, Anders, Ingvil Gaarder, and Magne Mogstad. 2015. “The Skill Complementarity of Broadband Internet.” _Quarterly Journal of Economics_ 130 (4): 1781–824.

Albanesi, Stefania, Antonio Dias da Silva, Juan Francisco Jimeno, Ana Lamo, and Alena Wabitsch. 2023. “New Technologies and Jobs in Europe.” CEPR Discussion Paper No. 18220, Centre for Economic Policy Research, Paris.

<mark>Antón, José-Ignacio, David Klenert, Enrique Fernández-Macías, Maria Cesira Urzì Brancati, and Georgios Alaveras. 2022. “The Labour Market Impact of Robotisation in Europe.”</mark> _<mark>European Journal of Industrial Relations</mark>_ <mark>28 (3): 317–39.</mark> Aranda-Jan, C.B., Mohutsiwa-Dibe, N. and Loukanova, S. 2014. “Systematic Review on What Works, What Does Not Work and Why of Implementation of Mobile Health (mHealth) Projects in Africa.” _BMC Public Health_ 14: 188.

Aron, Janine. “Mobile Money and the Economy: A Review of the Evidence.” _World Bank Research Observer_ 33 (2): 135–88.

Artuc, Erhan, Paulo S. R. Bastos, and Bob Rijkers. 2023. “Robots, Tasks and Trade.” _Journal of International Economics_ 145 (November): 103828.

Arvin, B. Mak, and Rudra P. Pradhan. 2014. “Broadband Penetration and Economic Growth Nexus: Evidence from Cross-Country Panel Data.” _Applied Economics_ 46 (35): 4360–69.

Asongu, Simplice A., and Jacinta C. Nwachukwu. 2018. “Comparative Human Development Thresholds for Absolute and Relative Pro-Poor Mobile Banking in Developing Countries.” _Information Technology & People_ 31 (1): 63–83.

Asongu, Simplice A., and Nicholas M. Odhiambo. 2019. “How Enhancing Information and Communication Technology Has Affected Inequality in Africa for Sustainable Development: An Empirical Investigation.” _Sustainable Development_ 27 (4): 647–56.

Atasoy, Hilal. 2013. “The Effects of Broadband Internet Expansion on Labor Market Outcomes”, _ILR Review_ , 66(2): 315-345.

Autor, David H. 2015. “Why Are There Still So Many Jobs? The History and Future of Workplace Automation.” _Journal of Economic Perspectives_ 29 (3): 3–30.

Autor, David Caroline Chin, Anna Salomons, and Bryan Seegmiller. 2024. “New Frontiers: The Origins and Content of New Work, 1940–2018.” _Quarterly Journal of Economics_ 139 (3): 1399– 465.

Autor, David H., and David Dorn. 2013. “The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market.” _American Economic Review_ 103 (5): 1553–97.

Autor, David H., Lawrence F. Katz, and Melissa S. Kearney. 2006. “The Polarization of the U.S. Labor Market.” _American Economic Review_ 96 (2): 189–94.

24
tentative reform has been preceded by often intense debate and political dueling among reformers of all stripes, as well as between the reformers on the one hand and more orthodox elements in the Party opposed to the progressive dismantling of socialism in China on the other.

Although early reforms mainly affected the agriculture sector where dissatisfaction with communist institutions was most pronounced,<sup>5</sup> arguably the most far reaching reforms have impinged on industrial enterprises in the urban areas, particularly those in the coastal provinces. In the first half of the 1980s, the dramatic improvement in agricultural performance became the principal determinant of growth in GDP. Thereafter, regionally targeted policies ensured that growth was largely driven by the increase in industrial output and productivity (see Table 1) with industries located in cities along the Eastern coast contributing a disproportionately large share. And the competitiveness of these industries depends not just on reforms introduced by the center but on the efforts of the municipal authorities themselves to improve the municipal business environment, as well as on the readiness of firms to grasp market opportunities.

**Table 1: Contribution to GDP Growth by Sector**

||1980-<br>84|1985-<br>89|1990-<br>94|1995-<br>99|20002001 2002 2003|
|---|---|---|---|---|---|
|Agriculture|25.9%|9.9%|15.3%|8.8%|5.0% 5.9% 5.6% 4.2%|
|Industry|43.5%|51.8%|59.2%|60.6%|60.4% 56.0% 62.8% 63.9%|
|Of which Manufacturing|33.2%|42.4%|39.5%|39.2%|47.0% 39.4% 44.9% 53.6%|
|Services|30.6%|38.4%|25.5%|30.6%|34.6% 38.1% 31.6% 31.9%|

_Source_ : Author calculation using data from WDI

> 5 The commune system inflicted great hardship especially in the less fertile areas of the country.  By the late 1970s, the strength of grass roots opposition forced a loosening of the commune imposed restraints in Anhui and Sichuan. In Anhui, the first steps from the team-based system back to household farming in the Fengyang region were supported by Party Secretary Wan Li. Zhao Ziyang backed similar moves to the household responsibility system in Sichuan (Hutchings 2001; Perkins and Yusuf 1984).

5
_Gender Equality and Economic Development: The Role for ICTs_ 26 Jorgenson, Dale W. and Kevin Stiroh (2000). “Raising the Speed Limit: U.S. Economic Growth in the Information Age.” _Brookings Papers on Economic Activity_ . Vol. 1, pp. 125-211.

Kirk, Dudley and Bernard Pillet (1998). “Fertility Levels, Trends, and Differentials in Sub-Saharan Africa in the 1980s and 1990s.” _Studies in Family Planning_ . Vol. 29, No. 1.

Klasen, Stephan (1999). “Does Gender Inequality Reduce Growth and Development? Evidence from Cross-Country Regressions.” _Policy Research Report on Gender and Development Working Paper Series_ , No. 7, the World Bank, November.

Krueger, Allan B. and Mikael Lindahl (2000). “Education for Growth: Why and For Whom?” _National Bureau of Economic Research Working Paper No. 7591_ .

Oliner, Stephen D. and Sichel, Daniel E. (2000). “The Resurgence of Growth in the Late 1990s: Is Information Technology the Story?” _Journal of Economic Perspectives_ . Vol. 14, No. 4 (Fall), pp. 3-22.

Pilat, Dirk and Frank C. Lee (2001). “Productivity Growth in ICT producing and ICT-Using Industries: A Source of Growth Differentials in the OECD?” _STI Working Paper 2001/4_ . Organisation for Economic Co-operation and Development.

Productivity Commission (1999). _Microeconomic Reform and Australian Productivity: Exploring the Links_ . Research Paper, AusInfo, Canberra.

Reardon, James, Ron Hasty and Barbara Coe (1996). “The Effect of Information Technology on Productivity in Retailing.” _Journal of Retailing_ . Vol. 72, No. 4, pp. 445461.

Schreyer, Paul (2000). “The Contribution of Information and Communication Technology to Output Growth: A Study of the G7 Countries.” _STI Working Paper 2000/2_ , Organisation for Economic Co-operation and Development, Paris.

Smith, Lisa C. and Lawrence Haddad (2000). “Explaining Child Nutrition in Developing Countries: A Cross-Country Analysis.” Research Report 111, International Food Policy Research Institute. Washington D.C.

Temple, Jonathan (1999). “A Positive Effect of Human Capital on Growth.” _Economics Letters_ . Vol. 65, pp. 131-134.
than other households in these parishes, especially when the comparison group is limited to households in the Census who do not have children aged 6 or older (column 4).

A sub-sample of 3,153 children was used for the analyses in this paper: First, we selected 3,854 children who were between the ages of 36 and 71 months of age at the time of the survey—the TVIP was not administered to younger children. Second, because the TVIP is administered in Spanish, we excluded 79 children whose mothers spoke a language other than Spanish (even if they spoke Spanish as well), or who were reported by their mothers to speak a language other than Spanish.<sup>7</sup> This selection ensures that Spanish was the primary language of children being tested. An additional 552 children were excluded because of missing information on the control variables used in the analyses. In most cases, missing values were due to noncompletion of the health assessments, either because children were not present in the household at the time of the interview or the mother refused permission for the health assessment, most often for the blood draw required to measure hemoglobin. The children excluded due to missing information are similar to those who were not excluded: Tests that the two groups live in households with the same average levels of wealth and parental education could not be rejected. Finally, we excluded 70 children who were present at the time of the interview but were not administered the TVIP. The group of children who did not take the TVIP was on average younger (by 7 months) and belonged to families with significantly less wealth and lower parental education. It is likely that children in this group would have performed poorly on the TVIP had they been tested. If so, the statistics we show below on means and medians of test scores are biased upward.

<u>Measures: Descriptive statistics are shown in Table 2. Our outcome measure is a child’s</u> score on the TVIP. The TVIP is a test of receptive language that is frequently used to evaluate Spanish-speaking pre-school children (Munoz et al., 1989; Umbel et al., 1992). Children are shown a series of slides, each of which contain four pictures, and asked to point to or otherwise identify a picture that corresponds to a word stated by the interviewer. Later slides are gradually more difficult, and the test stops when the child has made six mistakes in the last eight slides. Test items have been selected for their universality and appropriateness to Spanish-speaking

> 7 On a national scale, 6.1 percent of the population of Ecuador consider themselves “indigenous”, and 4.6 percent speak a language other than Spanish (León, 2003).  However, younger adults are less likely than older adults to speak a language other than Spanish, and the provinces covered by the baseline do not have particularly large concentrations of indigenous populations—especially the three provinces on the coast.  For both of these reasons, it is not surprising that our sample includes few families that are not exclusively Spanish-speaking.

6