rafmacalaba/data-use-mentions-extended huggingface dataset:
Table 3, we examine whether mayors’ characteristics matter for over-reporting. Since the PS is much more powerful than the mayor and faces tougher competition in the promotion tournament,<sup>37</sup> we expect that the effect, if any, should be limited to the PS. The first two columns examine whether the political cycle effects exist for mayors—by adding the demographic characteristics and career experience in place of those of the city party secretaries. Indeed, we do not find similar results for the mayors as for the PS. In columns 3 and 4, we add the controls for both the party secretary and the mayor to see if the political cycle effects remain robust for the PS once controlling for mayor characteristics. The inverse U-shaped political cycle effects are present only for the party secretary. The coefficients in columns 3 and 4 are almost identical to those in columns 5 and 6 of Table 2 without mayor controls. In the last column, we adopt a non-parametric specification on _YearsInOffice_ : we first round it down to the nearest integer and then group its values into six categories in years: 0-1 (the base

> 36 Due to the space constraints, we do not report the coefficients of city leader’s educational attainment and those of the city controls.

> 37 Ghanem, Shen, and Zhang (2020) find that the manipulation of city-level air pollution data is significantly associated with certain characteristics of party secretaries rather than those of the mayors. They also provide detailed explanations regarding the key role of party secretaries in the manipulation of those data.

18
, C. Dehlendorf, and A. Langer (2017). Defining quality in contraceptive counseling to improve measurement of individuals’ experiences and enable service delivery improvement. _Contraception 96_ (3), 133–137.

- Jain, A., K. Aruldas, A. Mozumdar, E. Tobey, and R. Acharya (2019). Validation of two quality of care measures: results from a longitudinal study of reversible contraceptive users in india. _Studies in family planning 50_ (2), 179–193.

- Johnson, E. J., M. Steffel, and D. G. Goldstein (2005). Making better decisions: from measuring to constructing preferences. _Health Psychology 24_ (4S), S17.

- Kassebaum, N. J., R. M. Barber, Z. A. Bhutta, L. Dandona, P. W. Gething, S. I. Hay, Y. Kinfu, H. J. Larson, X. Liang, S. S. Lim, et al. (2016). Global, regional, and national levels of maternal mortality, 1990–2015: a systematic analysis for the global burden of disease study 2015. _The Lancet 388_ (10053), 1775–1812.

- Lindo, J. M. and A. Packham (2017). How much can expanding access to long-acting reversible contraceptives reduce teen birth rates? _American Economic Journal: Economic Policy 9_ (3), 348–76.

- McKelvey, C., D. Thomas, and E. Frankenberg (2012). Fertility Regulation in an Economic Crisis. _Economic Development and Cultural Change 61_ (1), 7–38.

- Mestad, R., G. Secura, J. E. Allsworth, T. Madden, Q. Zhao, and J. F. Peipert (2011). Acceptance of long-acting reversible contraceptive methods by adolescent participants in the contraceptive choice project. _Contraception 84_ (5), 493–498.
the monetary deprivation of Syrian households, a module on household income and household expenditures was included in the survey. Based on this information, _the HNAP Socio-Economic situation report of the summer 2021 estimated that 98 percent of the Syrian population was living in extreme poverty_ (Figure 2). The poverty measure is obtained by taking the sum of all individual and household incomes obtained from employment only, converting it in per capita terms using household size, and then assessing whether this welfare indicator is below $1.90, a value converted in local currency using the exchange rate at the time of the survey.

> 10 The HNAP network presently consists of more than 30,000 community focal points and 475 full time staff on the ground in Syria. HNAP is implemented through local Syrian NGOs, with technical support from UN agencies. Information is collected across all regions inside Syria through face-to-face consultations and direct field observations. See Annex 2 for details.

> 11 Stratified random sampling is used to draw a 95% confidence / 10% margin of error sample at the subdistrict level and the number of household interviews per community (p-coded location) within a subdistrict was obtained by randomly sampling locations proportionate to population size, with replacement.

> 12 The main survey modules include questions on demographic characteristics of current household members and of members who have left the household, individual level basic information on labor market engagement (adult population) and school attendance (children below age 18); household level information on shelter, WASH, access to assistance, sources of income, copying strategies and priority needs.
# Measuring What Matters in Global Value Chains and Value-Added Trade

Alessandro Borin and Michele Mancini* _Keywords_ : trade in value-added; global value chains; inter-country input-output tables. _JEL classification_ : E16, F1, F14, F15.

*Bank of Italy. This paper is part of the World Bank World Development Report 2020 ‘Global Value Chains: Trading for Development’ project. The broad set of measures discussed in the paper and the source code will be available on the WDR2020 website. Sections 3 and 5 of this paper are largely based on the unpublished manuscript Borin and Mancini (2015), ‘Follow the value added: bilateral gross export accounting’, _Economic Working Papers_ , Bank of Italy, and on its updated version Borin and Mancini (2017), ‘Follow the value added: tracking bilateral relations in global value chains’, MPRA Working paper No. 82692. We would like to thank Robert Johnson for the valuable advices, as well as Pol Antràs, Pao-Li Chang, F. Paolo Conteduca, Gaaitzen De Vries, Stefano Federico, Alberto Felettigh, Aaditya Mattoo, Daria Taglioni, Giovanni Veronese and the WDR 2020 team for their insightful comments. The views expressed in this paper are solely those of the authors and do not necessarily reflect those of the Bank of Italy. The usual disclaimer applies.
pocket the profits (Van der Zwan, 2014). Thus, even though wage stagnation builds the backbone for low inflation rates and thus monetary stability (Hassel, 2006), it leaves lower income individuals at disadvantage, leading to rising inequality.

Second, there exists a strong relationship between credit markets and welfare policy. In fact, in several country cases, redistributive policies have increasingly been outsourced into financial markets (Crouch, 2009; Bohle, 2014; Ahlquist and Ansell, 2017). A prominent example of such a mechanism have been mortgage subsidies that allow households easier access to mortgages. As many of these programs come at a fraction of costs that would arise from new public housing construction (Hoek-Smit, 2008; Doling and Ronald, 2010; Bohle, 2014), they have become popular instruments to garner political support without incurring rising public debt levels.<sup>8</sup> Finally, from a political perspective, shifting gears towards an asset-based welfare system might produce perverse e↵ects and lead to further rounds of welfare state retrenchment. For example, Barth, Finseraas, and Moene (2015) show for a selected number of OECD countries how inequality leads to a shift of party politics towards more welfare cuts. Similarly, Ansell (2014) analyzes survey data from the United Kingdom and the United States and finds that homeowners are less likely to vote in favor redistributive policies as they can ‘self-insure’ against adverse economic shocks such as unemployment. Furthermore, enhancing private contributions into pension funds — which have been commonly used to relieve government-run pension funds from financial pressures — might further strengthen individuals’ leaning towards welfare and regulatory policies (Barth, Finseraas, and Moene, 2015; Alt and Iversen, 2017; Pagliari, Phillips, and Young, forthcoming). Pagliari, Phillips, and Young (forthcoming) show for US survey data that individuals with larger asset positions are more likely to be in favor of looser financial regulations. Taken together, we expect that these reinforcing mechanisms lead to an
variables that they have in common. Plausibly, the agricultural census is in comparison more informative of rural livelihoods.

Other poverty maps of Vietnam that have been constructed in the recent past include: Minot (2000) who combined the Vietnam Living Standard Survey (VLSS) from 1993 and the Agricultural Census from 1994 to estimate rural poverty at the province and district level; Minot _et al._ (2002) and Gian and van der Weide (2007) combined the 1998 VLSS and a 33 percent sample of the population census from 1999. Fujii and RolandHolst (2008) study the effects of Vietnam’s access to WTO on poverty. They too combine the 1998 VLSS and a 33 percent sample of the 1999 population census to estimate provincial poverty rates. Nguyen et al. (2007) attempt to bridge the three-year gap between the Vietnam Household Living Standard Survey (VHLSS) from 2002 and the 1999 population census to estimate poverty levels for 2002. Nguyen et al. (2005) and Nguyen et al. (2007) produce a district map of poverty and inequality of Ho Chi Minh City for the year 2004. Recently, most of these poverty maps, however, are out-of-date.

The paper is structured into seven sections. The second section describes data sources. The third section presents the method of small area estimation of Elbers _et al._ (2003). The poverty and inequality estimates and the models used for respectively the expenditure and income based measures are reported in sections four and five. Section six compares the estimates of expenditure based poverty to those based on income, and the poverty rate reported by the Ministry of Labour, War Invalids and Social Affairs. Finally, concluding remarks are presented in section seven.

# **II. Data**

# _II.1 Household survey and agricultural census_

The two data sources used are: The Vietnam Household Living Standard Survey (VHLSS) for 2006 and the 50 percent sample of the Rural Agriculture and Fishery Census (ARFC) for 2006. Both data sets
WPS3801

# **Neither a Borrower Nor a Lender:   Does China's Zero Net Foreign Asset Position Make Economic Sense?**

David Dollar and Aart Kraay The World Bank

**Abstract** :  China in the past few years has emerged as a net foreign creditor on the international scene with net foreign assets slightly greater than zero percent of wealth. This is surprising given that China is a relatively poor country with a capital-labor ratio about one-fifth the world average and one-tenth the U.S. level.  The main questions that we address are whether it makes economic sense for China to be a net creditor and how we see China’s net foreign asset position evolving over the next 20 years.  We calibrate a theoretical model of international capital flows featuring diminishing returns, production risk, and sovereign risk.  Our calibrations for China yield a predicted net foreign asset position of -17 percent of China’s wealth.  We also estimate non-structural cross-country regressions of determinants of net foreign assets in which China is always a significant outlier with 5 to 7 percentage points more of net foreign assets relative to wealth than is predicted by its characteristics.  China’s extensive capital controls can explain why its current net foreign asset position is far away from what is predicted by open-economy models and cross-country empirics.  It seems reasonable to assume that China’s international financial integration will increase over time.  We calibrate and predict different scenarios out to 2025.  These scenarios are necessarily speculative, but it is interesting that they typically imply negative net foreign asset positions between 3 and 9 percent of wealth.  What may be counter-intuitive for many policy-makers is that successful institutional reform and productivity growth are likely to lead to more negative net foreign asset positions than occurs with stagnation.  Starting from China’s zero net foreign asset position, it would take current account deficits in the range of 2-5 percent of GDP to reach any of these future net foreign asset positions.  These are not unreasonable deficits, but they require a large adjustment from the present 6 percent
income being more willing to pay, as in the case of Vietnam (Huyen and Van Minh 2014) and urban Bangladesh (Ahmed et al. 2016). The same studies found that workers with higher levels of education are willing to pay more for social insurance (Huyen and Van Minh 2014; Ahmed et al. 2016). Similarly, another study in urban Bangladesh found that the willingness to pay for health insurance among informal sector workers is higher for those who were exposed to an educational intervention on occupational solidarity and health insurance (Khan and Ahmed 2013), reflecting the important role of awareness and education. In some cases, the cost of the insurance premium has been found to affect the willingness to pay. For example, in Indonesia, 70% of informal sector workers in a survey of 400 households were willing to pay for national health insurance, but at a premium that was lower than the prevailing rate (Dartanto et al. 2016). A study in Togo also found that 92% of informal sector workers were willing to pay for mandatory health insurance, but would require subsidized premia (Djahini-Afawoubo and Atake 2018). A study on the willingness to pay for a hypothetical national health insurance scheme in Sarawak, Malaysia, found that more than 90% of respondents were willing to pay for this scheme (Ahmad, Ting and Zafar Ahmed 2018). The factors affecting the willingness to pay included education level and awareness or insurance literacy. Although these studies have sought to examine the question of affordability of (and therefore the potential need for subsidies for social insurance uptake), their reliance on stated preferences alone makes them susceptible to greater social desirability bias in response, as well as less effective to elicit the marginal valuation of particular job attributes (in this case social insurance coverage) holding other job characteristics constant. These limitations could potentially result in a gap between stated preferences and real-life choices.

This paper uses a vignette-based discrete choice experiment, which improves upon the contingent valuation method by assessing choices between scenarios
|11.507_∗∗∗_<br>[2.708]|7.377_∗∗∗_<br>[2.763]|4.941_∗∗_|[2.386]|2.634<br>[2.237]<br>59,130|Yes<br>Yes<br>Yes<br>is from the Min-<br>. The dependent<br>2008. All other<br>he district level.|
|---|---|---|---|---|---|
|With SGRY control<br>13.650_∗∗∗_<br>[3.126]|9.753_∗∗∗_<br>[3.166]|2.505|[2.395]|0.179<br>[2.318]<br>59,130|Yes<br>No<br>Yes<br>07. Program expenditure data<br>t and year-quarter fxed effects<br>05 and from July 2007 to June<br>uare brackets are clustered at t|
|13.322_∗∗∗_<br>[3.233]|9.215_∗∗∗_<br>[3.305]|2.574|[2.399]|0.177<br>[2.403]<br>59,130|No<br>No<br>Yes<br>from 2001 to 20<br>s include distric<br>2004 to June 20<br>dard errors in sq|
|**Dependent Variable: Real Earnings**<br>Without SGRY control<br>11.544_∗∗∗_<br>11.627_∗∗∗_<br>9.295_∗∗∗_<
“normal” growth (the pattern of observed weight gain) are added. This adjustment uses the 2 kilocalories per gram of tissue synthesis suggested in FAO (2001) combined with the average annual weight gain for each age and gender in the National Nutrition Monitoring Bureau data. Adjustments for the additional energy required by pregnant or nursing mothers are difficult due to lack of data, but energy requirements of infants themselves can be included. REE for infants (children under age 1) is set such that male babies have TEE of 650 calories and female babies have TEE of 600 calories, consistent with the (Indian Council of Medical Research 2009) report. Second, values outside of the 1% of the tails of the distribution are replaced with the percentile cutoff values prior to estimation.

# **B Estimation of Activity Levels (AL)**

Appendix Table S.2 lists the time-use survey activity codes and headings, the average share of time spent on the activity by rural and urban individuals, and the matched activity factors from FAO (2001). Estimates are not very sensitive to using alternative sources of activity factors, such as those developed for richer countries that tend to contain more detailed classifications of sports and exercise activities. Appendix Table S.2 includes the matched activities and activity factors from (Ainsworth et al. 2000) (used by (Cutler et al. 2003)) for comparison, and Appendix Table S.2 Panel C shows that the difference in activity levels using the measure used in the text and this alternative set of activity factors is quite small.

The estimates reported in the text make two additional assumptions about activity factors to derive activity levels. First, since the time-use data reports time spent on “related” or “other” activities within certain headings, one must assign an activity factor in these cases. The activity factor used in this case is equal to the average for the activities matched under the same heading. Second, since mode of travel is unobserved, the estimates use
Policy Research Working Paper 10658

# **Abstract**

The European Commission’s “NextGenerationEU” COVID-19 recovery package has underscored interest in the size of regional fiscal multipliers in Europe. While the objective of these funds is the long-term transformation toward more sustainable green growth and digitalization in EU economies, several recent papers have also focused on their short-term stimulatory effects and have estimated large short-term regional multipliers on historical EU structural and investment fund spending. This has contributed to a view that EU funds can boost growth substantially not only in the long term, but also in the short term in countries receiving large flows, particularly in Central and Eastern Europe. This paper reevaluates the evidence by estimating regional short-term multipliers using recent data on EU fund spending and a leave-one-out predicted disbursement schedule instrument. In contrast with much of the recent literature, there is little evidence of large relative GDP multipliers at either the national or subnational level in the short term. This is despite a strong response of regional investment to EU funds, which often increases euro for euro. The results suggest that expectations should be tempered on using EU structural and investment funds as a tool for short-term regional fiscal stimulus, and instead policy makers may want to focus on the long-term benefits of EU funds, in line with their original purpose.

This paper is a product of the Development Research Group, Development Economics and the Macroeconomics, Trade and Investment Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at ffiuratti@worldbank.org, dnikolova@worldbank.org, spennings@worldbank.org, and mschiffbauer@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

<!-
for a month each, plus the time of one consultant. The project preparation facility for the Ethiopia Family Health Project (1986, Case 5) funded a functional task analysis of service providers, developing somewhat further a methodology last applied in a Bank PHN project in the first Pakistan Population Project (1983) but not subsequently used. This time-and-motion study yielded detailed information about the divergence between providers' job descriptions and actual practices for a cost of less than US$40,000 and took about five months.

# Learning During Imalementation

Information was collected during this review about three types of learning which have been built into the implementation phase of Bank PHN projects. First, learning about the effectiveness of IEC; second, learning about the effectiveness of service delivery; third, learning about performance from routine service statistics collected through the program's management information system. In addition, a number of projects have funded surveys to collect basic demographic, health, and nutrition data during implementation, to fill gaps in knowledge and to provide baseline information against which to evaluate project progress later. The number and type of these surveys were not quantified in this review.
are members of the same geographic region as the province _i_ , and _GAWFi_ , _t_ for neighbor provinces that belong to a different geographic region.<sup>20</sup>

> Therefore, one province _i_ may have up to four different types of neighbor provinces according to the two criteria.<sup>21</sup> By construction, the weight of the growth rate of one neighbor province _q_ ( _impor_ tan _cei_ , _q_ , _t_ ) is equal to the ratio of its economic size to the total economic size of the group of the neighbor provinces, noted that the sum of such

# **Section 3: Spillover effects and regional growth**

In this section, we examine the spillover effects on regional growth by integrating the "neighbor performance" into the Solow-type growth model<sup>22</sup> using the panel data at provincial level of the period of 1978-1999 from the China Statistical Yearbooks. In order to examine the net effects of economic performance of the neighbors, we control the traditional growth determinants – the initial development level (<sup>_y_</sup> _i_ , _t_ − 1) , investment rate (<sup>_s_</sup> _i_ , _t_<sup>), demographic growth rate (</sup><sup>_n_</sup> _i_ , _t_<sup>). In order to capture the role of geo-economic</sup> position on regional growth, we introduce an indicator "peripheral degree", noted as _DPi_ , _t_ , which equals to weighted average distance of one province to the domestic economic center adjusted by the development level of the infrastructure<sup>23</sup> . The results are

> 20 Here, _M_ stands for the neighbor provinces that are members of the same geographic region of the

> province _i_ in question; while _F_ for the neighbor provinces that are members of a different geographic region.

21 In fact, not each province has all the four different types of
findings in manufacturing, this implies that the threshold of export participation might be lower, but differences in export intensity are more difficult to achieve in non-core regions. Other trade-related indicators show that the average time of inventory of the most important input is more than 20 days in the core compared to 12 days in non-core regions. While ownership variables show no significant difference, it is worth to point out the generally lower FDI share of services versus manufacturing firms.

Unlike manufacturing firms, there seem to be no significant differences between core and noncore regions with regard to technology. Regarding the workforce, the average number of permanent full-time employees is 70 percent in core-regions than non-core regions. The percentage of firms identifying labor regulations and labor skill levels as a major constraint is lower in the core for services firms.

12