rafmacalaba/datause-encoder-data huggingface dataset:
Polay nning, and Resrch World Develpment RepW.

Finarcial deregulation in recent years has vastly increased the ability of financial markets to allocate international capital efficiently. It has also sparked explosive growth in financial transactions and resulted in a restnictured, more competitive, and less costly financial services industry.

But deregulation has proceeded so rapidly that tlie volume of purely financial transactions now greatly exceeds that of transactions driven by international trade in goods and services. Financial activity is now "delinked" from other factor markets and increasingly driven by speculation for short-term profits nather than by broader economic activity.

This new pattem has led to growing economic uncertainty and instability. Markets now run around the clock and respond so rapidly that there is a growing danger of chain reactions that could precipitate global market failures.

Deregulation has also made the conduct of national monetary policy more difficult and the monitoring of markets more complex. For the United States, deregulation has increased the abillity to borrow abroad, thus contributing to fiscal laxity. In that country, there is a need for a single regulatory agency to coordinate the supervision of related financial activities -- to lessen the risk of compounded market failures.

Some countries, such as England, have moved to strengthen the capitalization of baniss and securities firns. Others (Canada, France, Italy, and Spain) are making progress. But there is acute need for improvement in the United States, where many large banks are unearcapitalized in relation to their exposure on LDC loans.

Regulators in the major trading nations need to address the possibility of a full-scale breakdown of the financial system.

This is a background paper for the 1988 World Development Report. Copies are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Rhoda Blade-Charest, room S13-060, extension 33754.

The PPR Working PEtper Series disseminates the findings of work under way in the Bankes Policy, Planning, and Research Complex. An objective of the series is to get these fmdings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank.

Copyright C\ 1988 by the International Bank for Reconstruction and DevelopmnentlThe World Bank
Our results suggest that investment promotion efforts lead to higher FDI inflows to developing countries. We find that targeted sectors receive more than twice as much FDI as non-targeted sectors. This magnitude is plausible, given that many sectors receive small amounts of FDI in absolute terms. For instance, in 2004 the median sector-level inflow of US FDI to developing countries in our sample that received some US investment was 11 million dollars. Thus, the increase of 155 percent estimated in our analysis would translate into additional 17 million dollars of FDI.

As sector targeting is a choice of the IPA, the targeting decision could be a response to earlier experience of the sector, which could present a reverse causality problem. However, when we exclude countries that reported in the Census that the targeting decision was based on the past success or failure in attracting FDI to the sector, our results hold. In addition, we find no evidence suggesting that targeting took place in sectors with relatively high or low inflows in the years preceding targeting.

A series of robustness checks supports our conclusions. First, we show that the results hold if we exclude services sectors and utilities. This gives us confidence that our findings are not driven by simultaneous opening to FDI and targeting of services industries where entry of foreign investors was restricted in the past. Second, we demonstrate that controlling for the past stock of FDI does not affect the estimated coefficients. Third, to address the concern that FDI flows may be a poor reflection of actual activities of foreign investors (Lipsey, 2007), we demonstrate that our results hold if we use sales or employment of US affiliates abroad as our dependent variable.

The significant positive effect of investment promotion found in the sector-level analysis is confirmed when we examine country-level data. The information on country-level FDI inflows comes from the IMF _International Financial Statistics (IFS)_ covers the 1972-2005 period. In this case, our variable of interest is the existence of an investment promotion agency, deduced from the establishment year reported by each agency. The magnitude of the effect is almost identical to that found in the sector-level exercise.

As we are concerned about the potential endogeneity of IPA existence with respect to FDI inflows, we also use the instrumental variable approach. As our first instrument, we employ the 4
**Table 40. Governance drivers of political risk: Accessibility of laws**

|VARIABLES|(1)<br>OLS|(2)<br>OLS|(3)<br>OLS|(4)<br>OLS|(5)<br>Ologit|(6)<br>Ologit|(7)<br>Ologit|(8)<br>Ologit|
|---|---|---|---|---|---|---|---|---|
|Services|0.0438|0.0419|||0.0949|0.0926|||
||(0.0578)|(0.0575)|||(0.110)|(0.112)|||
|Export % of sales|-0.00154**|-0.000653|-0.00139*|-0.000622|-0.00285**|-0.00138|-0.00253*|-0.00128|
||(0.000750)|(0.000784)|(0.000765)|(0.000793)|(0.00143)|(0.00154)|(0.00152)|(0.00162)|
|Share of sourcing via imports|0.00109|0.000745|0.00141*|0.00104|0.00197|0.00154|0.00256|0.00202|
||(0.000799)|(0.000796)|(0.000820)|(0.000819)|(0.00150)|(0.00153)|(0.00159)|(0.00162)|
|High-income source country|-0.00266|0.0376|0.00948|0.0445|0.00271|0.0880|0.0158|0.0945|
||(0.0842)|(0.0868)|(0.0839)|(0.0861)|(0.164)|(0.176)|(0.167)|(0.180)|
|>250 employees|-0.00853|0.00994|-0.0178|-0.00536|-0.0112|0.0299|-0.0279|0.00214|
||(0.0712)|(0.0725)|(0.0694)|(0.0708)|(0.135)|(0.140)|(0.134)|(0.141)|
|Cumulative inv. >US$10M|-0.0410|-0.114|-0.0506|-0.124*|-0.0784|-0.229*|-0.107|-0.253*|
||(0.0693)|(0.0713)|(0.0687)|(0.0701)|(0.130)|(0.138)|(0.132)|(0.140)|
|Years in country|0.000838|0.000520|0.000853|0.000661|0.00189|0.000870|0.00207|0.00141|
||(0.00238)|(0.00231)|(0.00233)|(0.00230)|(0.00472)|(0.00475)|(0.00485)|(0.00487)|
|Level of foreign ownership (%)|-0.00309**|-0.00223*|-0.00302**|-0.00213*|-0.00608**|-0.00463*|-0.00609**|-0.00463*|
||(0.00122)|(0.00135)|(0.00118)|(0.00127)|(0.00247)|(0.00278)|(0.00243)|(0.00267)|
|Country fixed effects||X||X||X||X|
|Subsector fixed effects|||X|X|||X|X|
|Observations|2,424|2,424|2,424|2,424|2,424|2,424|2,424|2,424|
|R-squared|0.014|0.045|0.041|0.071|||||

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

The dependent variable in all models is an ordered categorical variable corresponding to responses to the following question: "In general, how much of an obstacle were the following factors in this country? [Accessibility of laws and regulations]". Higher numbers denote more significant obstacles. Subsector fixed effects are at the ISIC A38 level.

Coefficients for constants (for OLS), cut points (for ordered logit), and fixed effects not shown in table.

57
WPS3945 on migration, rather than on remittance levels. Data on remittances are also likely to be very noisy. The main econometric challenge for the paper lies in dealing with the endogeneity of the migration decision. Migration is not randomly assigned to households and many of the same characteristics which in fl uence the decision to migrate are likely to also affect the household’s ability to invest in schooling, the perceived returns from such schooling, and the labor market activity of children.

We use two strategies to address this potential endogeneity problem. The fi rst is to identify selection in the migration decision by using instrumental variables. Since any number of unobserved community characteristics, such as local labor market conditions or school quality, could affect the returns to schooling and the propensity to migrate, we need an instrument that varies across households within a village. We use the prevalence rates of migration in the population, at the village level, as our main instrument for migration and use a feature of migration that is particular to the context we study to obtain household level variation in our instrument. Mobility and seclusion restrictions on women typically require the presence of an adult male in the household. Households with a single adult male are therefore much less likely to undertake migration. We can therefore interact the village migration network with the number of adult males in a household (males above age 20) to obtain an instrument which varies at the household level. The identi fi - cation argument, then is that the incidence of migration, at the census level, interacted with the number of adult males in the household, should affect a household’s opportunity to send a migrant but is unlikely to be correlated with unobservable household or child attributes that affect the costs or returns to education, conditional on household demographic characteristics and village fi xed effects to clean out the potential effects of any time invariant unobserved village characteristics. We show that conditional on appropriate demographic characteristics, the number of adult males exercises no in fl uence on any outcome of interest.

Our second strategy is to con fi ne attention to migrant households and to use information on the year of initial migration and the child’s age on the survey date to examine differences in educational outcomes for siblings, differentiated by their attained age before the fi rst migration episode for the household. This allows us to exploit the fact that many schooling decisions are time sensitive and have sustained impacts on educational attainment. For example, in the context we study, children typically begin elementary school at age 6 or 7 and children who have not initiated formal schooling by age 9 rarely enter the formal schooling process. We can test, therefore, whether children in migrant households 3
# **4. ALTERNATIVE MEASURES CONTROLLING FOR AGE OF**

# **ENTRY**

The previous data on international skilled migration define skilled immigrants as foreign-born workers with university or post-secondary training. However, this definition does not account for whether education has been acquired in the home or in the host country and thus leads to a potential over-estimation of the intensity of the brain drain as well as to possible spurious cross-country variation in skilled emigration rates.

As shown by Rosenzweig (2005) on the basis of US survey data, child migration can represent an important fraction of total immigration for certain countries as over 18 percent of permanent resident aliens immigrated to the US before age 18, and over 25 percent immigrated before age 20. Among those who arrived before age 18 or 20, some are highlyskilled today, having most likely acquired education once in the US. Should we include them as part of the ''brain drain''?

As explained, existing brain drain data sets are built according to a broad definition in that they include all foreign-born workers with tertiary schooling; for example, Mexican-born individuals who arrived in the US at age 5 or 10 and then graduated from US high-education institutions later on are counted as highly-skilled Mexican immigrants. This can be seen as providing an upper bound to brain drain estimates.

In contrast, it has been suggested that only people with home-country higher education should be considered as skilled immigrants (Rosenzweig 2005). This must be considered as a lowerbound measure of the brain drain. Indeed, except for those arrived at very young age, most of the immigrants who then acquired host country tertiary education arrived with some level of home country pre-tertiary schooling. In addition, some of them would still have engaged in higher education in the home country in the absence of emigration prospects.

In this section, we use immigrants' age of entry as a proxy for where education has been acquired. Data on age of entry are available from a subset of receiving countries which together represent more than three-quarters of total skilled immigration to the OECD. Using these data and a simple gravity model, we estimate the age-of-entry structure of skilled immigration to the other OECD countries. This allows us to propose alternative measures of the brain drain by defining skilled immigrants as those who left their home country after age 12, 18 or 22, and to do so for both 1990 and 2000. These corrected skilled emigration rates, which can be seen as intermediate bounds to the brain drain estimates, are by construction 21
NFHS questionnaire asked mothers whether their pregnancy with a particular child was desirable or not--in the form of the following question: _In the time you became pregnant with (Name) did you want 1) to become_ _pregnant then 2) to wait until later 3) no more children at all?_ The distribution of the answers to this question (for three years of the survey) is shown in Table 7. Across the different rounds of the survey, the birth of about 20 percent of children could be considered unplanned--that is, the mothers of these children either wanted to have children later or did not want to have more children at all. There are no significant differences in the shares of desirable pregnancies of boys and girls because parents cannot select the sex of the child at the time of conception<sup>16</sup> .

We use these data to test the ‘unplanned pregnancy’ hypothesis empirically. We estimate the probability of a child being born in a certain month of the year as a function of the ‘desirability’ of a child and a wide set of controls.

Prob( _M ik_ = 1) = _f_ (<sup>**_η_**</sup> **_k_** _Di_ + π _k X i_ + ε _ik_ ), _k_ = 1,...,12 , (7) where _Di_ is the ‘child desirability’ dummy, that is equal to one if a mother wanted to have that child when she became pregnant, and zero otherwise. A significance of coefficients on the ‘child desirability’ dummies (<sup>**_η_**</sup> **_k_**<sup>’s) would indicate the concentration of unwanted</sup> pregnancies in some months of the year. Table 8 shows that for the 1992 and 1998 samples, ‘child desirability’ had virtually no effect on the probability of children being born in a certain month of the year. In 2005, boys who were wanted by their parents were more likely to be born in May, June and September. For girls in the 2005 sample, the ‘desirability of birth’ increased their likelihood of being born during the summer months and in January, February, April, and November. These patterns of births would result in a variation in health outcomes, very different from those observed.

A mother’s opinion about the ‘desirability’ of her child at the time of conception could be subject to recall errors. Such measurement errors would attenuate the coefficients of interest. To address this issue, we instrument the ‘desirability of birth’ variable with the gender composition of older siblings in the household. Our exclusion restriction is based on the argument that the genders of the siblings would affect the

> **16** Though the observed ratio of desired boys and girls could be influenced by selective abortion after conception.

17
**Table 6.  Summary Statistics for SADC and Comparator countries:** **<u>2001-2006 average.</u>**

||SADC<br>Mean|Non-SADC<br>Mean|Non-SADC:<br>similar income countries<br>Mean|
|---|---|---|---|
|Real growth rate of GDP per capita|2.261|3.128|3.102|
|GDP per capital, USD real|1,289.358|7,248.203|1,229.144|
|FDI per capita|36.599|202.808|63.167|
|FDI/GDP|0.037|0.068|0.041|
|Rulelaw|0.991|1.181|0.946|
|Control_CR|0.651|0.834|0.661|

28
PROVISION OF WATER TO THE POOR IN AFRICA good quality service because it is not constrained by network hours of supply and often offers good water pressure and more flexible hours, albeit at a higher price than standpipes connected to the network that are managed by community organizations or local leaders (Maputo: SAL 2007; Dar es Salaam: Materu and Mkanga 2006). It would be useful to have data on the coverage provided by each modality (i.e. connected to the main network vs. independent from the main network) in order to assess the future potential of each option. It would be equally interesting to have information on the income level of the households currently covered by this source.

# Case study of the evolution of water sources: Mozambique

The case of Mozambique provides an interesting example of how various segments of the water market interact over time. In Maputo and several other cities in Mozambique, periodic surveys of the water market were carried out over a 10 year period in tandem with its water sector reform. First, a 2006 consumer assessment confirmed that poorer peri-urban households were more likely to depend on higherpriced re-sold yard tap water and on standposts. The assessment grouped households into poverty quintiles using standard factor analysis of 21 variables of household assets and indicators of wealth (figure 1.3).

Second, the series of consumer assessments showed that the number of people reliant on formal house and yard tap connections has continued to decline since 1996 to a low of 23 percent of peri-urban residents’ primary water source. However, because of long-term improvements in the financial and management aspects of the utility (currently under a lease contract), in recent years the sector has made improvements to bulk water supply, thus increasing the availability of water in urban systems. The utilities have also been able to attract funding and are about to undertake a large new wave of network expansion, which should have a substantial impact on these figures.

Between 2001 and 2006, independent providers who supply small piped systems connected to boreholes (SSIPs) increased their market share to 23 percent from 9 percent, largely in the outer periurban areas where use of standpost water has also declined (figure 1.4).<sup>13</sup> Consumers reported that SSIPs provided a very efficient service and responded more quickly for a request for a connection than did the utility, Aguas de Maputo. On the other hand, SSIPs were priced higher than some other sources and out of reach of the lower quintiles. Purchases from neighbors’ taps continued to grow, accounting for 26 percent of peri-urban water sources.

> 13 Data are also available for 1996. However, because the 1996 data also included a center urban area that was not included in the later surveys, the 2001 and 2006 surveys provide a better comparison.

12
We therefore strongly recommend that inference account for the method of randomization. Moreover, the results suggest that the common use of re-randomization methods should be rethought, since the method often performs worse than pair-wise matching in terms of balance and power, and requires more complicated statistical analysis to account for the effect of re-randomizing.

The paper also discusses the use and abuse of tests for baseline differences in means, the impact of balancing observables on achieving balance on unobservables, and the issue of how many (and which) variables to use for stratifying or matching. The downside of balancing on many variables or matching is a loss in the degrees of freedom available for averaging out the variation coming from unobservables when estimating the variance.

This paper draws upon a large clinical trials literature, where many related issues have been under discussion for several decades, drawing out the lessons for development field experiments. It complements several recent papers in development on randomized experiments.<sup>3</sup> The paper builds on the recent handbook chapter by Duflo, Glennerster and Kremer (2006), which aims to provide a “how to” of implementing experiments. Our focus differs, considering how the actual randomization is implemented in practice, and considering matching and re-randomization approaches not discussed in this recent work. Finally, we contribute to the existing literature through new simulations which illustrate the performance of the different methods in a variety of situations experienced in practice.

Whilst our focus is on field experiments in development economics, to date the field with most active involvement of researchers in randomization, randomized experiments are also increasingly being used to investigate important policy questions in other fields (Levitt and List, 2008). In common with the development literature, the extant literature in these other fields has often not explained the precise mechanism used for randomizing. However, it does appear that re-randomization methods are also being employed in some of these studies. The ongoing New York public schools project being undertaken by the American Inequality Lab is one such high-profile example. The

> 3 Summaries of recent experiments and advocacy of the policy case are found in Kremer (2003), Duflo and Kremer (2004), Duflo (2005) and Banerjee (2007).

- 5 -
26 Across all countries, ECE’s priority suffered from the _competing priority_ of preparing students taking high-stakes examinations. Of 116 countries that responded to UNESCO, UNICEF, and the World Bank’s (2020) survey only six countries with high-stakes examinations at the end of the secondary cycle reported canceling them outright in 2020, and 11 reported introducing alternative assessments. The majority of countries either postponed the examinations or implemented them with some combination of staggered administration, social distancing, and reduced curricular content. In Liberia, the government decided in June to reopen schools immediately for older grades in preparation for regional examinations, while the return to school for ECE through Grade 5 would wait for next academic year. In Jamaica, MOEYI prioritized students preparing for the Primary Exit Profile (PEP) examination, which determines placement in selective secondary schools, and for regional examinations such as the Caribbean Secondary Education Certificate (CSEC). Key informants in Ethiopia and the Punjab also reported a government preference for focusing reopening and distance learning provision for the students taking examinations most immediately.

# **Issue Characteristics**

The final category captures the extent to which the features of the policy challenge itself - maintaining continuity of learning in ECE during the pandemic – enable or impede its prioritization by policy makers. The availability and strategic deployment of _credible indicators_ facilitates recognition of the issue as a problem and enables actors to monitor progress toward addressing it. The availability of _effective interventions_ also favors political prioritization; it is easier for an issue to gain traction when cost-effective, readily implementable, and evidence-based solutions are available.