rafmacalaba/datause-encoder-data huggingface dataset:
The post‐disaster phase, for which we have reserved the term resilience, is especially critical for businesses in relation to their survival. This is a strong inducement for them to operate efficiently and recover quickly (recall our static and dynamic economic definitions of resilience). However, this does pose some problems for broader perspectives on DRM. Businesses are likely to be especially inward‐ looking and short‐sighted during recovery out of what they perceive as necessity. Longer‐term considerations and broader societal benefits may be pushed aside. Co‐benefits are less likely to fit into their decision‐making process at this stage. Moreover, even longer‐term opportunities to reduce their vulnerability through enhanced mitigation and the building of resilience capacity ahead of the next disaster will likely be considered of secondary importance. This may signal an even stronger need for government involvement in DRM at this stage to identify and help induce investments in the best long‐ term interests of society as a whole.

Incentivization of DRM for the private sector faces some serious obstacles. Disaster risk is a relatively minor consideration in many areas, such as construction loans, though it is a larger consideration for property appraisal. Insurance policies are property‐specific and do not consider the condition of the community in its entirety, which reaps the greater share of co‐benefits. Also, insurance premiums are such a small percentage of business costs that it is easy to overlook an even smaller incentive rate reduction. At the same time, globalization has led to even greater competitive pressures to consider all benefits, as well as costs, and has led to greater capital mobility, which has increased pressure to reduce investment risk.

Unfortunately, examples of private sector consideration of a comprehensive set of the co‐benefits of disaster risk management are limited. It is hoped this paper will help identify opportunities, as well as obstacles and ways to overcome them, to take co‐benefits into account in private sector investment decisions on DRM. In addition, it is intended to provide insight into ways policy makers can facilitate private sector actions by removing obstacles and providing incentives.

# **Acknowledgements**

The author is Research Professor in the Price School of Public Policy at the University of Southern California and Faculty Affiliate of USC’s Center for Risk and Economic Analysis of Terrorism Events (CREATE). He wishes to acknowledge the helpful suggestions of Swenja Surminski, Philip Schneider, Adrien Vogt‐Schilb, and Marianne Fay on earlier drafts of this paper.

# **References**

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Brugmann, Jeb. 2012. “Financing the Resilient City,” _Environment and Urbanization_ 24(1): 215–32.

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**School Resource and Performance Inequality Evidence from the Philippines**<sup>**1**</sup>

Futoshi Yamauchi<sup>2</sup> Suhas Parandekar<sup>3</sup> The World Bank

**Key Words** : School quality, Teacher quality, Resource allocation, Inequality, Philippines

**JEL Classifications: I21, I24, H52**

> 1 We would like to thank Luis Benveniste, William Martin, Lynnette Perez and Ken Vine for their useful comments. AusAID provided financial support. The opinions and conclusions expressed in this paper are those of its author and do not necessarily reflect positions of the World Bank and its member governments. Any remaining errors are the authors’.

> 2 Correspondence: Futoshi Yamauchi, The World Bank, 1818 H Street, NW, Washington D.C. 20433; Email: <u>fyamauchi@worldbank.org, Phone: 202 458 4262</u>

> 3 Suhas Parandekar, The World Bank, 1818 H Street, NW, Washington D.C. 20433.
Table 2: Characteristics of workers in employment and labor income (national level, age 15-64)

||2007|2009|2011|2013|2015|2017|2019|2020|2021|
|---|---|---|---|---|---|---|---|---|---|
|Activity Rate|73|74|74|72|69|70|74|74|72|
|Employment rate|69|72|72|70|67|68|70|68|69|
|Self-employed workers (%)|34|34|35|37|41|42|42|44|44|
|Workers in MSE (%)|33|30|30|26|25|26|27|28|25|
|Workers in public frms (%)|26|25|26|30|25|26|25|27|-|
|Real average monthly income|1,489|1,559|1,672|2,228|2215|2,105|2,124|2,113|2,070|
|Real average monthly income (for self-employed)|1,176|1,365|1,658|1,730|1923|1,644|1,686|1,735|1,490|

_Notes:_ Based on data from EH 2007-2021. We define workers in micro and small enterprises (MSE) for people who are employed in a firm with less than five employees, domestic workers and unpaid workers. Average income is in 2010 prices.

In constructing the index, we rely on the methodology proposed by Del Carpio et al. (2017). Due to data availability and the need for comparability across time, we include a reduced number of components in our study. Furthermore, given the specific focus on the Bolivian labor market, our index is designed to assess job quality not only for workers receiving wages, but also for those engaged in non-wage employment, who account for over 40 percent of the occupied labor force. The study covers individuals aged 15 to 64.

The Job Quality Index (JQI) comprises four dimensions that operate through seven components. Each dimension and component can be used independently to assess individual progress toward job quality in Bolivia. Table 3 presents the dimensions and components used to measure job quality. The four dimensions of the JQI are: i) Benefits and protection under labor law, ii) job-wage linkage, iii) career advancement and growth, and iv) level of productivity. These dimensions, as briefly explained earlier, have a legal foundation. Columns (1) to (4) outline the different components and describe the criteria for evaluating a good job.

**Social Security Benefits:** We define a proxy binary variable for social security benefits equal to one if the worker stated being registered to the Pension Fund Administration<sup>11</sup> (AFP) at the moment of the survey, even if the worker was not contributing at that time to the system. It is important to mention that both waged and non-waged workers may be affiliated with the pension system in Bolivia, regardless of their type of employment.

**Minimum wage compliance:** We define minimum wage compliance for full-time workers whose income per hour equals or exceeds the minimum wage per hour. As the

> 11Administradora de Fondos de Pensiones.

9
# **Table A11:  Economist Intelligence Unit (EIU)**

**Data Provider Description Website Data Source Type Respondents**

**Frequency Coverage Public Access**

**Description**

Economist Intelligence Unit Commercial business information provider headquartered in London, United Kingdom www.eiu.com Country Risk Service, Country Forecasts Expert Assessment Network of over 500 correspondents, reviewed for consistency by panels of regional experts Quarterly since 1997 - Democracy Index annually since 2006 Global sample of countries Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Democracy index is freely publicly available.

For the Viewswire Service we use data from last quarter of each year with exception of 1996 in which we draw data from first quarter of 1997.

||2008|2007|2006|2005|2004|2003|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|---|---|---|
|**Voice and Accountability**|||||||||||
|Democracy Index|X|X|X|..|..|..|..|..|..|..|
|Vested interests|X|X|X|X|X|X|X|X|X|X|
|Accountablity of Public Officials|X|X|X|X|X|X|X|X|X|X|
|Human Rights|X|X|X|X|X|X|X|X|X|X|
|Freedom of association|X|X|X|X|X|X|X|X|X|X|
|**Political Stability and Absence of Violence**|||||||||||
|Orderly transfers|X|X|X|X|X|X|X|X|X|X|
|Armed conflict|X|X|X|X|X|X|X|X|X|X|
|Violent demonstrations|X|X|X|X|X|X|X|X|X|X|
|Social Unrest|X|X|X|X|X|X|X|X|X|X|
|International tensions / terrorist threat|X|X|X|X|X|X|X|X|X|X|
|**Government Effectiveness**|||||||||||
|Quality of bureaucracy / institutional effectiveness|X|X|X|X|X|X|X|X|X|X|
|Excessive bureacucracy / red tape|X|X|X|X|X|X|X|X|X|X|
|**Regulatory Quality**|||||||||||
|Unfair competitive practices|X|X|X|X|X|X|X|X|X|X|
|Price controls|X|X|X|X|X|X|X|X|X|X|
|Discriminatory tariffs|X|X|X|X|X|X|X|X|X|X|
|Excessive protections|X|X|X|X|X|X|X|X|X|X|
|Discriminatory taxes|X|X|X|X|X|X|X|X|X|X|
|**Rule of Law**|||||||||||
|Violent crime|X|X|X|X|X|X|X|X|X|X|
|Organized crime|X|X|X|X|X|X|X|X|X|X|
|Fairness of judicial process|X|X|X|X|X|X|X|X|X|X|
|Enforceability of contracts|X|X|X|X|X|X|X|X|X|X|
|Speediness of judicial process|X|X|X|X|X|X|X|X|X|X|
|Confiscation/expropriation|X|X|X|X|X|X|X|X|X|X|
|Intellectual property rights protection|X|X|X|X|X|X|X|X|X|X|
|Private property protection|X|X|X|X|X|X|X|X|X|X|
|**Control of Corruption**|||||||||||
|Corruption among public officials|X|X|X|X|X|X|X|X|X|X|
|**Country coverage**|**150**|**150**|**152**|**127**|**125**|**120**|**120**|**120**|**120**|**120**|
|**Country coverage (democracy Index)**|**170**|**170**|**170**||||||||
|**Year of Publication**|**2008**|**2007**|**2006**|**2005**|**2004**|**2003**|**2002**|**2000**|**1998**|**1996**|

50
**Table 4: Only one or two migration corridors tend to be important for developing country migrants going to other developing countries**

<u>South-South migrant labor stocks in 2030 under baseline, millions of workers</u>

|**Origin Region**|**Brazil**|**OLAC**|**India**|**Pakistan**|<br>**OMI_Asia**|**LMI**<br>**Bangladesh**|**Host R**<br>**OLI_Asia**|**egion**<br>**CtrlAsia**|**MI_MENA**|**OFSU_OEE**|**OMI_SSA**|**LI_SSA**|**SthAfrica**|**Total to LMI**|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**_Native_**|_118.2_|_156.8_|_654.1_|_87.4_|_166.1_|_96.2_|_105.7_|_37.3_|_145.7_|_31.3_|_220.4_|_367.4_|_22.3_|_3231.4_|
|**Brazil**||0.12|||||||||0.01|||0.14|
|**OLAC**|0.08|1.91|||0.01|||||0.01|0.07|0.01|0.01|<br>2.14|
|**China**|0.01|0.03|||0.32||0.24|0.01|0.01||0.04|0.01||0.74|
|**India**||||1.70|0.25|0.56|0.38||0.04||0.04|0.04|0.01|<br>3.02|
|**Pakistan**|||0.63||0.01|0.01|0.02||0.02|||0.01||0.70|
|**Indonesia**|||||0.56||0.01||0.02|||||0.60|
|**OMI_Asia**|||0.12|0.01|0.16||0.24||0.03|||||0.60|
|**Bangladesh**|||2.29|0.03|0.05||0.03||0.02|||||2.41|
|**OLI_Asia**||0.01|0.55|0.04|0.20||0.03||0.32|||||1.20|
|**CtrlAsia**|||||0.01|||0.59|0.07|<br>0.38||||1.07|
|**MI_MENA**|0.01|0.02|0.01||0.01|||0.01|0.91|0.01|0.06|0.04||1.09|
|**OFSU_OEE**||0.01||||||0.68|0.02|<br>0.49||||1.25|
|**OMI_SSA**|||0.01||||||||0.50|1.33|<br>0.13|<br>1.98|
|**LI_SSA**|||0.02||||||0.03||3.26|3.06|<br>0.27|<br>6.64|
|**SthAfrica**|||||||||||0.04|0.16||0.21|
|**Total from LMI**|0.11|2.14|3.63|1.78|1.59|0.57|0.95|1.29|1.50|0.91|4.02|4.67|0.43|<br>23.86|

Note: Red entries: Stocks > 1 million workers; Orange: 0.5 to 1 million workers; Yellow: 0.1 to 0.5 million workers. Host regions with less than 100,000 migrant workers and individual stocks less than 10,000 migrant stocks are excluded. Totals include small stocks not displayed here. Displayed entries account for 98.4 percent of total LMI-toLMI migrant worker stocks.

Global real GDP in 2030 is US$57.9 billion lower than in the baseline under this scenario, and LMI GDP drops by a moderate 0.14 percent (Table 5). In some countries with a net increase in the total labor force (Bangladesh, Indonesia, China) GDP rises, but GDP per capita drops due to the net increase in the resident population. In other regions – notably in LI_SSA, OLI_Asia and OFSU_OEE - aggregate GDP drops despite a net increase of the labor force, as on balance foreign migrants with relatively high productivity are replaced by native return migrants with lower productivity. In contrast, in India, MI_MENA, Turkey and South Africa, the total labor force and the total population decline while the change in the composition of the labor force raises average productivity so that GDP per capita rises slightly compared to the baseline.

21
_“Our dream is a world free of poverty.”_ (Motto of the World Bank) _“The poor you will always have with you.”_ (The Bible, Matthew 26:11)

# **1.        Introduction**

People coming from different backgrounds define “poverty” differently even when in each individual’s eyes it is unmistakable in reality. This paper aims to describe the range of national poverty lines found across the world, to review the methods used to set those lines, and to provide a common framework for interpreting the differences.

Standard measures of income poverty combine a monetary measure of household “economic welfare” with a poverty line in the space of that measure, only below which people in that household are deemed to be “poor.” The most widely used measures of economic welfare are current income and expenditure on consumption, both of which are derived from sample surveys of households. Consumption is more commonly used in developing countries where income is often harder to measure, and probably a less reliable welfare indicator, given a degree of (predictable) income variability over time, notably (but not only) from agriculture.<sup>2</sup> In the compilation of national poverty lines for developing countries provided by Ravallion, Chen and Sangraula (2009), consumption was used as the welfare indicator in the poorest half of countries ranked by consumption per capita, with income-based measures only emerging above the median. Income is typically the preferred indicator in OECD countries.

The second ingredient, the poverty line, is clearly the more important reason in practice why definitions of poverty vary. Figure 1 gives the densities of both national poverty lines and private consumption per capita for 95 countries (developed and developing). These are either official national poverty lines or (when these could not be found) they are the lines set by Eurostat and the World Bank.<sup>3</sup> Both the poverty lines and consumption are converted to $US’s using purchasing power parity (PPP) exchange rates.<sup>4</sup> The range of poverty lines in Figure 1 is

> 2 It has also been argued that consumption is the more relevant indicator for developed countries; see Slesnick (1993) on measuring poverty in the US.

> 3 It is not clear whether the Eurostat lines can claim national relevance, and so one must be cautious in treating them similarly to other lines. This is less of a concern for the World Bank’s national lines. These are from the latest available country-specific “Poverty Assessments” (PA), which are official Bank documents. The process of producing a PA entails (often extensive) consultation with the government of that country, including discussion about the most appropriate poverty line.

> 4 I have used the PPP exchange rates for consumption from World Bank (2008). All poverty lines are for specific years (often tied to specific survey dates) and consumption data are for that year or as close as possible;

2
formalization status that offers potential benefits (like bank access), low transaction costs, and no implied future cost that is responsible for the high BRC take-up rates.

The remainder of Table 3 examines differences in take-up rates by gender, and by location. Takeup rates are similar by gender for business registration when offered alone, or with the banking information session. However, there is a significant difference in take-up of the business registration certificate when offered together with the TPIN assistance: only 58 percent of women obtain a BRC in this case, compared to 76 percent of male owners. Across all treatment groups, the main reason for not getting a BRC is that the business had closed, moved, or could not be located to offer the assistance.

Seventy-two percent of firms in treatment group three attended the bank information sessions. An important factor for the high take-up of these sessions was likely the close proximity of the sessions with the firms’ place of operations. Of the business owners who participated in NBS Bank information sessions, 89 percent of them opened bank accounts in the name of the business, resulting in 64 percent of all invited firms opening a business bank account.

# **4.1 Estimating Treatment Impacts**

To estimate the impact of the different treatments on outcomes of interest, we run the following ANCOVA specification for outcome _y_ : y�,� �α�β�Treat1� �β�Treat2� �β�Treat3� �λy�,� �∑δ�d�,� �∑���� θ�1�t�j� �ε�,� (1) Where _Treat1, Treat2,_ and _Treat3_ indicate whether firm _I_ was assigned to the BRC assistance, BRC+TPIN assistance, or the BRC + bank information sessions treatments respectively, _yi,0_ is the baseline value of the outcome of interest (included to increase power as per McKenzie, 2012), and the d�,� are randomization strata dummies (Bruhn and McKenzie, 2009). We pool results over all four follow-up surveys to further increase power, including survey round fixed effects θ�. The coefficients β�, β�, and β� then provide the intent-to-treat effects averaged over all post-treatment rounds. Since randomization was at the individual level within strata, we use robust Eicker-White standard errors for the ε�,�, clustered at the firm level. In addition to estimating the average effects, we allow for treatment interactions with gender to test whether impacts vary for male versus female business owners.

16
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be able to obtain inputs at reasonable costs, and also to sell their outputs at remunerative prices. Transportation costs, in particular, are crucial for them to decide whether or not to engage in certain activities. For instance, while China increased agricultural productivity in rural areas, investments in infrastructure, coupled with labor mobility, increased flows of labor and capital to urban centers and facilitated growth in the manufacturing and services sectors.

With respect to the durability of private capital, infrastructure plans, when they present an appropriate balance between capital and current expenditures (in such as way that they ensure rehabilitation and maintenance), can promote the profitability of all (public and private) existing investments and assets. This is a critical policy issue for many low-income countries. While many rural roads have been built in these countries, the cost of maintaining them in good condition has often not been considered as a priority in national spending plans. As noted earlier, expanding and maintaining the quality of public roads would enhance the durability of private vehicles and encourage mobility across regions and areas. Similarly, eliminating or reducing electricity outages may encourage private investments, because firms would be less concerned about the functioning (and durability) of their equipment and the need to prevent them from deteriorating in the longer term<sup>28</sup> . In practice, unfortunately, policymakers have a perverse incentive: given their higher visibility, new public investment projects are politically more attractive than economically crucial, but politically less rewarding, spending on infrastructure maintenance. It is therefore important to insulate maintenance budgets in public expenditure programs, and make them consistent with the overall investment budget.

As described at length earlier, when better access to schools and hospitals is provided to the population (not only to the ones in need but also to health and education workers), the quality of services is enhanced<sup>29</sup> . Thus, public infrastructure

> 28The need for increasing operations and maintenance expenditures, to ensure the durability of capital, may be equally important in middle-income countries (such as those in Eastern Europe and Central Asia) where infrastructure investments have already achieved wide country coverage. 29As noted earlier, recent surveys in a number of Sub-Saharan African countries show that around 60 percent of households in the bottom two income-quintiles find distance to health services a

37