rafmacalaba/data-use-mentions-extended huggingface dataset:
areas but increased it in others (though not significantly). From our results, it appears that China’s new health insurance schemes (private schemes, including coverage of schoolchildren) have also increased the risk of high levels of out-ofpocket spending on health. Where we find evidence of health insurance increasing the risk of ‘high’ out-of-pocket expenses, the marginal effect is of the order of 15-20 percent; in the case of ‘catastrophic’ expenses, it is even larger.

**Corresponding author and contact details:** Adam Wagstaff, World Bank, 1818 H Street NW, Washington, D.C. 20433, USA.  Tel. (202) 473-0566. Fax (202)-522 1153. Email: <u>awagstaff@worldbank.org.</u>

**Keywords:** Health insurance; financial risk; China.

World Bank Policy Research Working Paper 3741, October 2005 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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org.

**Acknowledgements:** Our thanks to Agbessi Amouzou, Shengchao Yu and Lei (Lydia) Liu respectively for their help preparing the China Health and Nutrition Survey data, the Gansu Survey of Children and Families (GSCF) data, and the Health VIII baseline survey data.  Wave 1 of the GSCF was funded by The Spencer Foundation Small and Major Grants Programs, while Wave 2 was funded by grants from the Fogarty International Center at the National Institutes for Health and the
countries and of 0.2% for non-BRI countries, to Kyrgyz Republic, the country that has the highest trade cost reductions, with reductions of 10.2% for BRI countries and 5.9% for non-BRI countries. To capture improvements in internal logistics and transportation, the diagonal element of the estimated improvements is assumed to apply to the domestic trade and transport services used to produce individual commodities. For example, if the domestic, i.e. diagonal, estimate of improvements in trade and transport is 5%, intermediate demand for the relevant trade and transport commodities in each sector is assumed to decline by 5% relative to output, i.e. the inputoutput coefficient is adjusted downwards by 5%. In the current configuration of the input database,

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# **3.5.3. Australia**

NECA fulfills many of the tasks of an independent market monitor for the Australian electricity market. It periodically prepares market analysis reports that are released to the market using data on bids, schedules and output levels released by the National Electricity Market Management Company (NEMMCO) on its web-site that day after the market operates. Although NECA’s authority as the National Electricity Code administrator comes from the ACCC, NECA satisfies the independence criteria described above. Australia also has a number of other market monitoring entities. The Australian Bureau of Agricultural and Resource Economics (ABARE) is a government economic research agency noted for its independent research and analysis. It periodically prepares reports and analyses of Australian energy markets, including electricity. The National Competition Council was established by all Australian governments in November 1995 to act as a policy advisory body to oversee the implementation of National Competition Policy (NCP). It oversees competition policy as it is applied to the electricity industry. The Productivity Commission, the Australian Government's principal review and advisory body on microeconomic policy and regulation, conducts public inquiries and research into a broad range of economic and social issues including: competition policy, productivity, the environment, economic infrastructure, labor markets, trade and assistance, structural adjustment and microeconomic reform. It has also been an active participant in the Australian electricity reform process. The public availability of wholesale market data has allowed each of these entities to provide an informed perspective on conditions in the NEM to the ACCC and public at large.

# **4. Conclusions**

One positive outcome from the California electricity crisis is that a market monitoring process is currently being put in place throughout the US to ensure that such a sequence of events will not occur again. Although there are still problems with interested parties gaining access to data from the wholesale market to perform the necessary analyses, FERC is currently working to put in place a market monitoring process that is forward-looking, fully integrated with and supported by its
by many small investors who buy and hold these securities—and so reducing liquidity in the secondary market. But for that risk to materialize, retail investor demand would have to be very high, accounting for a substantial part of domestic debt. Moreover, holdings of government securities are already concentrated among a few dealers and tax-exempt institutional investors that tend to buy and hold.

The development of the Expanded Small Investors Program has not included a thorough assessment of the retail investor base, which limits the authorities’ ability to project demand. Although activity under the original program suggests high demand by retail investors, the amounts were not large. But the old system ran on intranets in bank branches, so its outreach was much smaller than under the enhanced program.

# _Credibility and risks_

Perhaps a more important risk facing the authorities in implementing the Expanded Small Investors Program is the need to build credibility and trust among retail investors. Any problems during the program’s early stages will significantly reduce future demand for its services. The program’s business model is based on partnerships among public and private bodies, as discussed further below in the section on the program’s structure. Although the liability for each party in the event of a system or operational breakdown is unclear, as the issuer of the securities the Treasury will bear the reputation risk.

# **Issues in gauging success and setting goals**

Measuring the program’s success and monitoring its progress require clear goals. The program’s primary goals include broadening the investor base for government securities and offering a reasonable savings product through bank and development bank branches—but using a common, cheaper electronic platform provided directly by the Treasury.

If the main goal is to diversify holdings of public debt and build the retail investor base, the obvious metric to monitor is growth in the number of new retail accounts and investors. Given the approach being taken with the Registry of Scripless securities—where securities are registered at the investor level—monitoring this growth will be feasible.

Another
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as South Africa, Chile, Singapore, and Malaysia have a dominant or a very important contractual savings sector.

**Figure 3: Contractual savings in system financial assets (%,1996)**

<!-- Start of picture text --> tO0% - 1 _ l 1 |<br>90%<br>70%<br>60% *<br>50% EI 6||<br>40% |l | X l1 l<br>30% il l<br>20X %ll<br><!-- End of picture text -->

**Source:** 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.

Figure 4 shows the positive correlation between the financial assets of contractual savings institutions and market capitalization as a fraction of GDP for a cross section of OECD and non-OECD countries in 1996 (the positive relation is very stable for different years). Those countries with a more developed contractual savings sector are also countries with more developed stock markets. Furthermore, Figure 5 indicates a positive relationship between contractual savings development and the liquidity of the capital markets (measured by value traded over GDP).

Figure 6 explores the relationship between **changes** in contractual savings as a fraction of GDP and **changes** in market capitalization over GDP for the same countries between 1990 and 1996. Figure 7 presents a similar relationship between **changes** in contractual savings and **changes** in value traded as a fraction of GDP. It is clear that those countries that were able to develop their contractual savings sector also show a higher growth in their stock markets in terms of capitalization and value traded in the same period. The same conclusions are reached with estimates using panel data for 26 countries and with about 300 observations. **'**<sup>**5**</sup> savings institutions belong to the household sector. Of course
lower moisture and ash contents and volatile matter, and higher fixed carbon correspond to higher calorific value of the coal. So, lignite has lower calorific value than sub-bituminous and bituminous coal, and (sub) bituminous coal has lower calorific value than anthracite. Normally, only the organic parts of the coal are burned during the combustion process, whereas carbon dioxide and water vapor are produced as by-products. The inorganic parts of coal usually do not burn but stay in the ash as by-products.

**Table A2.5** : Gross calorific values (kcal/kg) of commonly used fuels for brick making process in India and Nepal

|Fuel type|(Weyant et al.,<br>2016)|(Kumar<br>and<br>Maithel, 2016)|(PSCST,<br>2015)|(SMSEE,<br>2017)|(Prajapati et al.,<br>2019)|
|---|---|---|---|---|---|
|Coal|6,483 (6,254)<sup>a</sup>|4,000 – 7,000|-|4,000 - 5,500<br>a|-|
|Wood chips|-|3,500 – 4,500|-|-|-|
|Sawdust|4,000<sup>a</sup>|3,500 – 4,500|-|-|2,961<sup>e</sup>|
|Coffee husk|-|4,300 – 4,500|-|-|-|
|Mustard stalk|4,007|-|3,985|-|-|
|Biomass briquettes<sup>b</sup><br>|-|-|3,155<sup>c</sup>|-|3,277<
the Census ceased reporting the classi...cation of capital expenditures into new and used. Thus, after that year, proxies for the intensity of the resale market RES could not be constructed. However, even in 1992, it is not possible to construct RES for a large number of industries. To ensure that the three cross-sections are comparable in terms of their sample size, the variables used for the 1992 crosssection are averages of 1987 and 1992. Summary statistics for the key variables are provided in the appendix.

Under rental payments, RK; manufacturing establishments are requested to report payments made for the use of all items for which depreciation reserves would be maintained if they were owned by the establishment–e.g., structures and buildings, production equipment and transportation equipment. Establishments also report: the depreciation, DK; charged during the year against ...xed assets; their new expenditures for buildings and equipment NK; the value of all used plant and equipment UK purchased during the year; and their ...xed depreciable assets K: To facilitate estimation, we drop r since it is just a normalization.<sup>9</sup> We also restrict the length of the period � at the end of which the entrant exercises its disinvestment option, to being the same across industries and set it equal to one year. Then, we can compute UK the following proxies: REN =<sup>RKDEP=DKandRES=</sup> K<sup>;</sup> K<sup>;</sup> UK + NK<sup>:</sup> To estimate equation (15), we set m = 4 and thus employ the four-...rm concentration ratio C4. These concentration ratios were taken unadjusted from the Census listings. For each four-digit industry, the Census also reports the values of the truncated Her...ndahl index H, representing the sum of squared market shares of the largest 50 ...
by displacement events more than doubled from 34 million in 1997 to 82 million in 2020 (UNHCR, 2020): 1 percent of the world’s current population (1 in 95 people) has been forcibly displaced. Over a third of these people end up as refugees in a foreign country. Understanding the conditions under which host countries are successful (or not) at integrating those who are forced to flee their homes is a humanitarian and economic priority that has important theoretical and policy implications.

Our study builds on three relatively separate strands of research on how the presence of migrants and refugees affects host communities. The first uses public opinion data and election returns 5
, cellular, phone, computer, and calculator.

Table 11c: Impacts of PROSPERA on Type of Secondary School: 6<sup>th</sup> Graders Enrolled in Indigenous Primary Schools in 2008 Nearest Neighbor Matching Models

|||Enrollment<br>||
|---|---|---|---|
|Variables|7thgrade Telesecondary|7thgrade General school|7thgrade Technical school|
||Propensity score matching|with exact matching on age|and state|
|Girls|0.097***|-0.011|-0.083***|
||(0.017)|(0.0098)|(0.019)|
|Observations|4,931|3,931|3,931|
|Boys|0.105***|-0.018*|-0.087***|
||(0.017)|(0.009)|(0.018)|
|Observations|4,751|4,751|4,751|

Note: Estimates significance level *** p<0.01, ** p<0.05, * p<0.1. We report standard errors in parenthesis. Variables which enter the propensity score include: age, number of siblings, household size, lives with mother, lives with father, health problems, whether currently working, household ownership of DVD, television, MP3 player, cellular, phone, computer, calculator, student teacher ratio, whether the school has a computer, whether the school has rooms with more than one grade, average teacher education levels and marginality index components. Community level variables include the margination index, proportion illiterate, proportion of households without piped water, proportion without electricity and proportion without drainage.

As was the case for the sample of children in medium to very high areas of poverty, the impact of the program is to increase
**FIGURE A.4: TRADE WAR TARIFFS AND EXPORT CHANGES, WITH FIXED EFFECTS**

<!-- Start of picture text --> Panel A Panel B<br>Bystanders' Export Value to US Bystanders' Export Value to China<br>2015-17 2017-19 2015-17 2017-19<br>.2 .3<br>.15 .2<br>.1 .1<br>.05 0<br>0 -.1<br>0 .05 .1 .15 .2 0 .05 .1 .15 .2<br>∆ ln T(US,CH) ∆ ln T(CH,US)<br>Pre-period: β =-0.12 (0.11). Post-period: β =0.20 (0.11). Pre-period: β =-0.01 (0.18). Post-period: β =-0.06 (0.20).<br>Panel C Panel D<br>Bystanders' Export Value to RW Bystanders' Export Value to RW<br>2015-17 2017-19 2015-17 2017-19<br>.1<br>.1<br>.05<br>.05<br>0<br>0<br>-.05<br>-.05<br>-.1<br>-.1<br>0 .05 .1 .15 .2 0 .05 .1 .15 .2<br>∆ ln T(US,CH) ∆ ln T(CH,US)<br>Pre-period: β =-0.00 (0.09). Post-period: β =0.15 (0.09). Pre-period: β =0.12 (0.08). Post-period: β =0.30 (0.08).<br>ln X(i,US) ln X(i,CH)<br
household. The Moscow survey demonstrates that the higher the level of education, the greater the inclination to privatize one's dwelling. The privatization rate among respondents with a graduate academic degree was 53%; among those with a university education, 45%; and among respondents without higher education, 28%.

d. **_Household income_** is another factor influencing privatization. In the low-income group we find childless families and single pensioners, while in the high-income group there are households with children. The desire to bequeath their housing to heirs stimulated privatization rates in the low-income group that were higher than among high-income households.

On the face of it it would appear that the low-income groups were the gainers, judging by the degree to which they engaged in privatization. However, this is not so because they mainly privatized low-cost, lowquality dwellings. However, as will be shown later on (Fig. 1.2 below), over time the high-income group in Moscow appears to be becoming more involved in the process of privatization.

# **Recent trends in housing privatization** in Moscow

In 1995, Muscovites privatized only 3% of the overall number of apartments. The fourth wave of the Moscow Longitudinal Household Survey conducted in late 1995-early 1996 showed that the reasons for privatizing and the agents involved had experienced some changes while some characteristics of the process remained unchanged, as demonstrated by Tables 1.9 to 1. 11 which show the dynamics in privatization in Moscow between 1994 and 1996.
and value flexible work arrangements, including both those related to flexible time schedules and changes in work roles and assigned tasks, and that providing such arrangements serves to delay retirement.<sup>72</sup> Particularly in HICs but also in some middle-income countries, COVID-19 has given rise to structural changes in the organization of work, with a rapid move towards more home-based and flexible solutions for many white-collar jobs, as well as a shift to independent work, that over the long run may benefit working conditions for mature workers.<sup>73</sup>

**Family and the availability of care services also matter for labor market participation, especially for**

**women.** Grandmothers all over the world hold a central responsibility for the care of their grandchildren, and hence support the labor market participation of the parents of these children. Towards the end of working life, many are also caring for elderly parents or even their spouse. In Europe, one-third of grandparents provide regular care and women who do are also less likely to be working.<sup>74</sup> Care obligations are even more prevalent in L/MICs, where three in four elderly people live in the same household with members of younger cohorts, compared to one in four in HICs, and where formal care services are often lacking in supply and quality.<sup>75</sup> A study of time use allocation in a set of OECD countries, China, and India, showed that the time share allocated to paid work fell successively as of age 45-50 across the sample, whereas unpaid work was highest when people were in the their late 30s (likely related to child bearing and rearing), and again increased after age 60.<sup>76</sup> In countries with significant outmigration, whether international or intranational, grandparents may be the main caregivers in so-called “skipped-generation” households consisting of only older people and children.<sup>77</sup>
in poor households is low. On average, the members of poor households who are of working age (1859 years old, students excluded) worked for only 54% of the year. Eurostat defines work intensity as the ratio of the total number of months that working-age household members have worked during the income reference year and the total number of months the same household members theoretically could have worked in the same period.

> 20 The labor activity rate in Romania is low compared to the average EU level. According to the Eurostat for the age group 20 – 64, the labor activity rate is 77% for men and only 59% for women.  Only in Italy, and Greece female labor activity rate is lower than in Romania.

> 21 Here, we assume the family of two adults and one child.

19
well as the conceptual advantage of capturing the combined restrictiveness of multiple measures in a well-defined and theory-consistent way. An additional improvement relates to the consideration of regulatory and competition policy measures. This improved methodology will be described below.

# **Basic principles**

The construction of the STRI follows the same steps as in Borchert et al. (2012):

- 1) the **selection** of key restrictions entering the STRI; 2) the **determination** of the level of restrictiveness of individual measures (or bundles of measures if they are conceptually intertwined, which we call ‘synthetic measures’); and

- 3) the **aggregation** of measures into indices at the sector-mode level, sector level, and economy level, respectively.

While the Services Trade Policy Database (STPD) described in the previous section has a very broad coverage of measures, the index is based on a subset of key restrictions on trade in services, approximately 115 regulations and policies. The selection of key restrictions entering the quantification exercise was driven by a number of considerations: 1) to cover the most significant restrictions – this was based on the previous analysis conducted by the World Bank as well as expert advice; 2) to respond to recent regulatory developments perceived as having a discernible impact on trade in services, e.g. screening policies, restrictions relating to cross-border data flows; 3) to ensure comparability with the 2008-2011 World Bank exercise; and 4) to adapt to – and be consistent with – the coverage of measures in the OECD database, which served as a fundamental source of information for economies covered by both the STPD and the OECD STRI. The list of measures selected for the construction of the STRI is provided in Annex 5.

Trade policies are assessed by looking at specific types of measures for each subsector and mode. For example, for commercial banking, we obtain separate measures for cross-border supply,

> 18 Accessible at https://www.worldbank.org/
(2018) also argue that firm-level studies tend to underestimate the positive effect of FDI on economic performance. In their view, the sum of vertical and horizontal spillovers measured in microeconomic studies underestimates the overall benefits of FDI because technologies and managerial competencies may travel across industries which do not belong to the same supply chain.

There are endogeneity issues associated with measuring the link between FDI and growth. On the one hand, the fact that countries with brighter growth prospects are more likely to attract FDI flows can generate a positive bias, leading to an overestimation of the positive effect of FDI on growth. On the other hand, standard measurement error can lead to an attenuation bias. Measurement error might have become particularly important in recent years as FDI data are affected by multinational firms’ strategies aimed at minimizing their global tax bill through the reallocation of headquarters, profit shifting, or the use of shell companies as special purpose vehicles. As there is no reason why these “phantom FDI” (Damgaard et al. 2019) should stimulate economic growth, their inclusion in FDI statistics is likely to create a downward bias in the estimated relationship between FDI and growth. Moreover, FDI flows also include cross-border intragroup lending, making them closer to portfolio flows (Blanchard and Acalin 2016).

Existing work tried to address endogeneity by instrumenting FDI flows with their lagged value, the real exchange rate, country size, political stability, and institutional quality (see Borensztein et al., 1998 and Alfaro et al., 2004). There are, however, doubts about the validity of these instruments as they are likely to have a direct effect on GDP growth. In this paper, we propose a new instrument that addresses this concern.

4