rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 5618

# **Abstract**

Using household survey data, this paper estimates the mortality impact of improved water and sanitation access in order to evaluate the potential contribution of water and sanitation investment toward achieving the child mortality targets defined in Millennium Development Goal 4. The authors find that the average mortality reduction achievable by investment in water and sanitation infrastructure is 25 deaths per 1,000 children born across countries, a difference that accounts for about 40 percent of the gap between current child mortality rates and the 2015 target set in the Millennium Development Goals. According to the estimates, full household coverage with water and sanitation infrastructure could lead to a total reduction of 2.2 million child deaths per year in the developing world. Combining this analysis with cost data for water and sanitation infrastructure, the authors estimate that the average cost per life-year saved ranges between 65 and 80 percent of developing countries’ annual gross domestic product per capita. The results suggest that investment in water and sanitation is a highly cost-effective policy option, even when only the mortality benefits are taken into consideration. Taking into account the additional expected benefits, such as reduced morbidity, time spending, and environmental hazards, would further increase the benefit-cost ratio.

This paper is a product of the rospects Group, Development Economics. 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 author may be contacted at isabel. guenther@nadel.ethz.ch.

_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
_Empowerment index_ is the sum of the following outcomes: Compelled to spend money on husband or family (coded 1 if they answer no); not the only person with access to their firms’ money (coded as 1 if only they have access); has some money which they have sole control over and can spend how they like; do not need anyone’s permission to visit a friend, to travel to sell a business asset, to travel to a new location to work, to stay overnight in a different town, to work later than usual hours, to take out a loan, or to spend money on an investment for their business.

_Life Ladder Today_ and _Life Ladder 5 Years_ are measured by a standard 10-step Cantril ladder, where individuals are asked to imagine the best (step 10) and worst (step 1) possible lives for themselves, and then say which step represents their current position and where they will be in 5 years.

_Mental health_ is measured by the MHI-5 index of Veit and Ware (1983), coded so higher scores denote better mental health.

_Household durables index_ is the first principal component of dummy variables for ownership of 10 household assets (iron and heaters, fridge or freezer, fan, sewing machine, radio or CD player, TV or DVD player, motorcycle or scooter, car or van, oven, and gas cooker) and of the number of cows owned and number of goats owned.

_Number of new entrants_ is the number of firms operating in the market outside of our experimental sample that have opened since the baseline survey and training intervention.

_Total other firms_ is the total number of other firms operating in the market outside of our experimental sample (new entrants plus those pre-existing firms that were not included due to being absent from the market at the time of listing, or being dropped by our eligibility filters).

_Other firm profits_ is the total profits in the market of the other firms outside the survey sample.

_Weekly customers_ is the number of customers
firms, network-driven business practices, and inefficient markets, which, possibly, constrains foreign investors from fully exploiting their competitive advantages. That drawback may influence the type of FDI and nonequity mode of investment that is initially attracted, as well as domestic firms’ absorptive capacities. Empirical evidence is mixed. Firm-level data for 17 emerging countries, during 2002–05, reveal no evidence that the degree of corruption or red tape affects the extent of FDI spillovers (Gorodnichenko, Svejnar, and Terrell 2007). Evidence also shows that a country’s transparency has a U-shaped effect on FDI spillovers: countries with a medium level of transparency benefit least from FDI, whereas countries with low and high levels show stronger FDI spillovers (Meyer and Sinani 2009).

# **_Financial and Labor Markets_**

_Financial markets_ in developing countries may also be a factor in absorption of GVC spillovers (Alfaro and others 2010). Multinationals can have an ambiguous impact on access to finance for local firms: they may ease such access by bringing in scarce capital to developing countries; but if multinationals borrow locally, they may increase local firms’ financing constraints (Harrison, Love, and McMillan 2004). That, in turn, can influence local firms’ absorptive capacity, and well-developed markets may facilitate domestic firms’ absorptive capacity links (Aggarwal, Milner, and Riaño 2011).

_Low wages_ may be a way for countries to enter GVCs. According to firm surveys, costs (production, labor, transport, investment) and tax incentives are major drivers of lead firms’ decisions to invest or to source production in developing countries. Indeed, wage differentials have been primary drivers of the globalization of production. But costs encompass a wide range of drivers and the goal should be higher labor productivity and higher wages, allowing the country to remain cost competitive despite rising living standards (Taglioni and Winkler 2016).

_Labor market regulations_ may influence the effect of GVC integration on domestic firms through various channels. Higher absolute and relative labor market flexibility than
Policy Research Working Paper 5763

# **Abstract**

In the past three decades, emerging countries have gone through extensive decentralization reforms. Yet, there are no studies assessing quantitatively the relative importance of various factors known to affect the success of decentralization. This paper builds on a comprehensive dataset the authors constructed for Peru, which merges municipal fiscal accounts with information about municipalities’ characteristics such as population, poverty, education, and local politics. The paper then analyzes the leading factors affecting the ability of municipalities to execute the allocated budget using complementary methodologies, from least squares to quantile regression analyses. According to the existing literature and the Peruvian context, the analysis divides these factors into four categories: the _budget size and allocation process; local capacity; local needs;_ and _political economy constraints._ Although all four factors affect decentralization, the largest determinant of spending ability is the adequacy of the budget with respect to local capacity. The results confirm the need for decentralization to be implemented gradually over time in parallel with strong capacity building efforts.

This paper is a product of the Poverty Reduction and Economic Management Unit, Latin America and the Caribbean 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 author may be contacted at jrigolini@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
unequal income distributions experience slower growth. This finding is even stronger for initial unequal distribution of land in developing countries (Deininger and Squire, 1997). Birdsall and Sabot (1994) come to similar conclusions in comparing high inequality and low growth in Latin America and low inequality and high growth in East Asia, but they turn to political economy considerations to explain the different strategies in the two regions. In Latin America, the political elite has little incentive to invest in the well-being of the poor, but in East Asia the threat of communist insurgency led to government investment in the rural poor, in education and health and in rural infrastructure. Larrain and Vergara (1997), using data for 45 developed and developing countries, conclude that distributive inequalities give rise to social pressures and conflict, and these in turn generate greater instability in economic policies and lower investment. Rodrik (1997) also concludes on the basis of cross-country regressions that severe income 24
database (also known as AMADEUS for European countries) which is compiled by Bureau van Dijk Electronic Publishing (BvD). It covers 60 countries worldwide, including both developed and emerging countries. ORBIS has financial accounting information from detailed harmonized balance sheets and profit and loss accounts of all companies. In terms of coverage, the database is crucially different from the other data sets that are commonly used in the literature, such as Compustat (for the United States), Compustat Global, and Worldscope databases, in that 99 percent of the companies in ORBIS are private, whereas the data sets mentioned contain information mainly on large listed companies. A fundamental advantage of our data is the detailed 4
i.e. the reform was associated with an increase in sex selective abortion among first-generation women).

Taken together, these studies suggest that while reform in property rights is an important step towards improving the status of women and girls, it does not necessarily bring about _immediate_ positive change in parents’ valuation of daughters.

# _Pension schemes_

Another area of possible intervention is in social protection for the elderly. As highlighted previously, sons are preferred over daughters because they can support parents during old-age. In Hubei province in China, for example, nearly 50 percent of the respondents to a fertility survey stated that the primary reason to have a son was because they needed support during old-age (Davin 1985). It follows that when the State steps in as the main provider of support for the elderly, it obviates the economic need for sons as support during old-age. This, in turn, can erode some of the deep-rooted preference for sons.

Ebenstein and Leung (2013) provide some evidence of this using the case of China’s rural old-age pension program. In 1991, China established an alternative to the family-based system of elderly support in rural areas, by initiating a funded, defined-contribution pension plan. Individuals would have to voluntarily contribute to the pension plan, and these contributions could be supplemented with subsidies from employers and local communities. To estimate the causal impact of this new

> 17 Some evidence also suggests that the reform was associated with an increase in marital conflict and the incidence of wife beating (Anderson & Genicot 2015).

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# 1. **Introduction**

Although it is well known from anecdotal evidence that inventories are higher in developing countries, there are almost no systematic studies that attempt to explain this phenomenon or even to quantify the difference. This study uses newly-assembled data for 52 countries in the early 1970s and 1980s to draw out some stylized facts about the pattern of inventory holdings, and more recent data in Latin American countries for the 1990s shows that the problem persist.

The motivation for this paper is the magnitude of the holdings and the potential cost to the economy. U.S. businesses typically hold inventories equal to about 15% of GDP while inventory levels in many developing countries are often twice as large and for raw materials three times as large (Table 1). If the private sector interest rate for financing inventory holdings is 15%-20%, a conservative estimate in most developing countries, then the cost to the economy of the additional inventory holdings is greater than 2% of GDP. Suppose that firms in developing countries keep high levels of inventories in response to poor infrastructure, which we find in this study to be a key determinant. Then, as an example, consider that the total transport infrastructure stock in Bangladesh is about 2% of GDP' (World Bank 1994) while this figure is about 12% in the United States.<sup>2</sup> One year's worth of savings in inventory holding costs would be enough to double Bangladesh's infrastructure stock; the infrastructure improvement could pay for itself. At the firm level, the impact of these high levels of inventories is also enormous. Given the high cost of capital in many developing countries, cutting inventory levels in half

> 1 Rough calculation based on graphs of infrastructure stock per capita and composition of infrastructure. See World Bank [1994], figures 1 and 2.

> 2 Nonmilitary nonresidential net public stock in the United States in 1991 was $2.2 trillion with $700 billion of this amount
**Table 2. Validated CRIs (‘red flags’) and their definitions for Bulgarian public procurement data**

|**Indicator name**|**Indicator definition**|
|---|---|
|Single bidder contract|0 = more than one bid received<br>1 = one bid received|
|Call for tenders publication|0 = call for tenders advertised<br>1 = call for tenders not advertised|
|Procedure type|0 = open procedure<br>0.5 = negotiated/accelerated procedures<br>1 = non-open procedure type (for example, direct contracting)<br>(for detailed definition see Annex 3)|
|Length of submission period|Number of days between publication of call for tenders and submission<br>deadline<br>0 = from 12 to 183 days<br>0.5 = from 7 to 11 days<br>1 = from 1 to 6 days|
|Length of decision period|Number of calendar days between submission deadline and announcing of<br>contract award<br>0 = from 9 to 365 days<br>0.5 = from 5 to 8 days<br>1 = from 1 to 4 days|
|Buyer’s dependence|Shows the contracting authorities’ contract share rewarded to the same<br>supplier in a given year|

**Single bidding** indicates that a given tender only had one bidder during the procurement process, hence there was no competition for the contract. The lack of competition is one of the main signs of corruption in the public procurement system. Single bidding can be easily extracted from the data and has the key qualities necessary for an adequate indicator (Abdou, Czibik, Tóth, and Fazekas 2021).

**The length of the submission period** is the time difference between the first publication date of the contract notice and the deadline until which suppliers can submit their bids (bidding
the incidence of property ownership. Information on how property assets are acquired by both men and women would help in understanding where the gaps originate from and why they persist. Data on various dimensions of ownership – reported, legal and rights-based – could unpack what asset ownership means for the individual. Individuals may not be legal owners of property, but still enjoy decision-making power over how the property is used or to whom it is bequeathed. Data on the value of assets owned are useful to assess differences between men and women in property wealth. In addition, panel data of individual property ownership, or at least repeated cross-sections, would allow researchers to measure changes in women’s and men’s property ownership over time and support the identification of causal relationships. Emerging bestpractice standards (e.g. Doss et al 2013, 2020) for the collection of individual-level data on ownership, use and control of assets are an important milestone towards advancing this data collection and analytic agenda.

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units, i.e., Carabinieri (93,400) and the Public Security Guard (80,400), both under the authority of the Ministry of Defense, as well as the Finance Guard (64,100), under the authority of the Treasury Department and the Harbor Control.

# **Japan**

Data on Central Government, Non central government, Education and Health employment are taken from Public Management: OECD Country profiles, OECD 1992 and relate to 1991. Public education and health are the responsibility of non-central government. Military employment data include Central Staffs.

# **Netherlands**

Unemployment rate is taken from OECD Economies at a Glance - Structural Indicators, 1996 and relates to 1994. Paid employment in non-agricultural activities is drawn from the ILO's Yearbook of Labor Statistics 1995 and refers to 1994.

Data on Central Government and Non central employment are taken from Public Management: OECD Country profiles, OECD 1992 and relate to 1990. Public education provides for 28% of school-aged children, while private education provides for the rest. The central govemment finances almost totally private institutions, but is not directly responsible for the salaries of the teachers. Accordingly they are not included among the education employment data. Health services are provided jointly by the voluntary social networks, professional services, insurance organizations and the government at national and subnational levels. It has therefore never developed into a hierarchical organization in which professional services are managed and paid for by the government. For this reason, it has not been possible to obtain and include any reliable figure on health employment.

**New Zealand** Paid employment in non-agricultural activities is drawn from the ILO's Yearbook of Labor Statistics 1995 and refers to 1993.

Data on Central, Non Central Government and Education employment are taken from Public Manaaement: OECD Country profiles, OECD 1992 and relate to 1992. Note that Education employment figure includes health workers. Primary and secondary education is managed by community-elected boards of trustees and financed by block
# **Appendix 2.  Geographic Coverage of the Survey**

|Governorate|Number of Surveys Targeted|
|---|---|
|Abyan|87|
|Aden|65|
|Al Bayda|114|
|Al Hudaydah|147|
|Al Jawf|96|
|Al Mahrah|44|
|Al Mahweet|96|
|Amran|94|
|Dhale|116|
|Dhamar|140|
|Hadramout|70|
|Hajja|108|
|Ibb|155|
|Lahij|142|
|Mareb|94|
|Raymah|78|
|Sa'ada|141|
|Sana'a|125|
|Sana'aCity|180|
|Shabwah|125|
|Taiz<br>Notes: This table<br>surveys by gover<br>The geographic<br>approximately id<br>For example, in A<br>each month used<br>and 93 complete|204<br>presents the number of completed<br>norate in the November 2017 survey.<br>distribution of responses is<br>entical in each round of the survey.<br>byan, the monthly sample size for<br>in this analysis varied between 87<br>d surveys.|

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20 The second alternative scenario is based on similar higher national rates of growth, but this time thanks to faster rural development. This could be achieved by using foreign concessional loans to boost investments and productivity in agriculture, and by strengthening the links between the farm and nonfarm sectors. The rationale for promoting rural development comes of course from the fact that the elasticity of poverty to growth is higher in rural than in urban areas. This scenario assumes an annual rural GDP growth rate of 5 percent per year. The level of savings needed is the same than in the previous higher growth scenario. In 2008, the national headcount would be 3 points lower than in the base case scenario, which is not a very large gain. The proportionate gain (as compared to the base case scenario) is much larger for the poverty gap and the squared poverty gap, the later reaching 0.82 in year 2008, which should not be surprising since these measures better take into account inequality which increases less with rural growth than with urban growth. Note finally that an additional reason why there would be lower inequality in 2008 under the pro-rural scenario is because the between group component of inequality (with groups corresponding to households living in urban and rural areas) would be lower.

# **VI Conclusion**

Apart from a few exceptions (India and the United States), panel data techniques have not been used to analyze the relationships between growth, inequality, and poverty within single countries, apparently because two few observations are available to researchers. Yet, this constraint can be removed provided researchers are willing to conduct their analysis at the regional level. This was shown in this paper using data from Bangladesh. A regional panel was constructed for fourteen geographical areas, with data for five points in time between 1983 and 1996. This panel enabled us to estimate the impact of growth and inequality on poverty, as well as the impact of growth on inequality. Some of these results could not be obtained with standard methods of analysis relying
mirroring the fall in revenue and leaving the fiscal balance largely unchanged relative to the pre-disaster forecast.<sup>12</sup>

**Table 3. D Cyclone Evan on Samoa (December 2012): Deviations of macro-fiscal outcomes from projections made immediately prior to the disaster (percent of GDP)**

||**Samoa**||**Other**<br>**SIDS**|**Oceania**|
|---|---|---|---|---|
||2013|2014|2013|2014|
|GDP growth|-1.8|-1.6|0.2|1.0|
|<br>Govt Revenue|-10.4|-6.3|2.5|3.3|
|Govt Expenditure|-11.0|-4.9|-3.6|0.5|
|<br>Net Lending|0.6|-1.3|6.2|2.8|

_The figures in the table show the difference between the outcome for each variable and the projection made just before the disaster. Net lending is equivalent to the overall fiscal balance._ <u>Source: WEO database</u>

**Table 3.E Cyclone Pam on Vanuatu (March 2015): Deviations of macro-fiscal outcomes from projections made immediately prior to the disaster (percent of GDP)**

||**Vanuatu**||**Other**<br>**SIDS**|**Oceania**|
|---|---|---|---|---|
||2015/16|2016/17|2015/16|2016/17|
|GDP growth|-2.6|1.2|1.4|1.4|
|Govt
list randomization module in this paper.<sup>2</sup> The Philippines survey took place between March and August 2010 in Sorsogon Province. Sorsogon is a relatively isolated and rural province, located approximately 12 hours by bus from Manila. International migration rates are lower than the Philippines average as a result of this isolation, and so this location was chosen for an experiment designed to test several interventions aimed at lowering barriers to international migration (Beam et al, 2013). The sample was obtained by first selecting municipalities within this province, then randomly selecting baranguays (local administrative areas) and conducting a door-to-door listing of households in

> 2 An additional group of respondents were randomized into a Group C, which had the same first three questions as groups A and B, and then a fourth question asking about debt stress. We do not use this group in this paper.

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