rafmacalaba/data-use-mentions-extended huggingface dataset:
levies are managed by _Instituto de Desarrollo Urban_ (IDU), and their unilateral management is perceived as “non transparent”. Further, until recently the property tax valuation performed by the Cadastre was not consistent with IDU determined benefit from a betterment project. With recent updates to the cadastral database, it is possible now for IDU to use the same property values that are recorded in the Cadastral. Efforts are currently being done in this line, so that all data collection efforts are centralized in the Cadastre, and other institutions can benefit from these efforts. Second, betterment levies have the potential for producing regressive effects. In general, the majority of betterment projects end up occurring in more affluent areas of the city because of their high capacity to pay; some projects (e.g. highway overpasses) may decrease property values. Finally, interadministrative coordination is deficient in many cases. Even though IDU works with the Planning Department on betterment project planning, the projects are not always internally consistent with the city’s Master Plan.

# _Betterment Levies in Peru_

The experience in Peru provides a counterpoint to Colombia’s betterment levy process. Betterment projects in Peru are concentrated in metropolitan Lima and are empowered by Legislative Decree No. 184 of 1981. While betterment levies have become a widely used form of revenue collection in Colombia, they have yet to gain traction in Peru, which illustrates unique implementation challenges to metropolitan Lima. From 1990-3, more than 500 public works projects were undertaken in Lima, but only 31 projects used betterment levy financing (Huayapa 2001: 4). To determine the benefit of projects, local authorities choose among two methods, or a combination of them.

26
30 financial development is a good predictor of future economic development. Evidence on the relationship between financial structure and the functioning of the financial system, however, is more inconclusive.

# B. The Level of Financial Development and Growth: Cross-Country Studies

Consider first the relationship between economic growth and aggregate measures of how well the financial system functions. The seminal work in this area is by Goldsmith (1969). He uses the value of financial intermediary assets divided by GNP to gauge financial development under the assumption that the size of the financial system is positively correlated with the provision and quality of financial services. Using data on 35 countries from 1860 to 1963 (when available) Goldsmith (1969, p. 48) finds: (1) "... a rough parallelism can be observed between economic and financial development if periods of several decades are considered"; and (2) "... there are even indications in the few countries for which the data are available that periods of more rapid economic growth have been accompanied, though not without exception, by an above-average rate of financial development." Goldsmith's work, however, has several weaknesses: (a) the investigation involves limited observations on only 35 countries; (b) it does not systematically control for other factors influencing economic growth (Levine and David Renelt 1992); (c) it does not examine whether financial development is associated with productivity growth and capital accumulation; (d) the size of financial intermediaries may not accurately measure the functioning of the financial system; and (e) the close association between the size of the financial system and economic
Few studies attempt to obtain elasticity estimates across income groups. On Bangladesh, Nargis et al. (2014) estimate total price elasticities of demand using data from wave 1 (2009) and wave 2 (2010) of the International Tobacco Control Bangladesh Survey. They find that the price elasticity of cigarette − consumption is higher among people of lower socioeconomic status based on a housing index ( 0.75 − − for the poorest group, 0.40 for the medium group, and 0.36 for the richest group). A similar pattern is found in India and South Africa.

In countries with a variety of tobacco products, the impact of changes in cigarette prices also depends on the potential substitution by other tobacco products. In the case of Bangladesh, it may be important to assess the potential substitution of bidis, which are also smoked, are significantly cheaper, and are widely consumed by the poor. Anecdotal evidence and cultural features suggest that, once a person starts smoking cigarettes, they will not go back to consuming bidis. Although this may be true among the large majority, there is limited evidence of the extent of this substitution across consumption deciles, particularly among extreme poor households. To complement the existing price elasticity estimates, price elasticities for cigarettes and other tobacco products across consumption deciles are estimated using the HIES 2016/17. Specifically, a system of demands is estimated using a quadratic almost ideal demand system (AIDS) (Banks, Blundell, and Lewbel 1997; Deaton and Muellbauer 1980; Mas-Colell, Whinston, and Green 1995). For tractability, the focus is on estimating a set of demands for five tobacco products (cigarettes, bidis, betel leaf, betel nut, and rolled betel leaf). A few products that are consumed by fewer than 4 percent of households are not included (tobacco leaf, gul, and other smoked tobacco, khoer, lime, and other smokeless products). The models incorporate a set of demographic controls, as well as a control for urban and
lesser extent, VAT and excise taxes. These taxes, and particularly the PIT, are consequently the main focus of this paper. However, because of the need to provide an assessment for IDA countries of the progressivity of the entire tax system, the paper also undertakes an examination of the extent to which aggregate tax revenue data – which is available for a larger number of countries in a timely manner – can be used to assess the likely degree of progressivity of tax systems in IDA countries.

It should also be borne in mind that, beyond computation of progressivity metrics, there are additional ways to help assess whether countries are taking steps to increase the progressivity and fairness of their tax systems. For example, many countries are currently implementing reforms to their international tax rules to limit the extent to which individuals and companies that operate in multiple jurisdictions can avoid or evade tax. These may include unilateral measures, or those undertaken as part of current multilateral efforts to prevent base erosion and profit shifting (BEPS) activities, address the tax challenges of digitalization (including the proposed adoption of a global minimum tax), and enable the exchange of taxpayer information amongst tax administrations. While beyond the scope of this paper, assessment or stocktaking of the various steps that IDA countries have taken to implement such measures would be informative.

This paper is structured as follows: Section 2 briefly introduces various concepts of tax progressivity and progressivity measurement. Sections 3-5 then consider the three main approaches to measuring tax 4 There indeed remains considerable academic debate regarding the incidence of the CIT. See also, e.g., Gale and Thorpe (2022). Harris (2009) finds that even if labor bears the majority of the CIT, it remains progressive. While empirical attempts can be made to allocate the CIT to taxpayers based, for example, on tax return microdata specifying capital income (see, e.g., Nunns, 2012; Rohaly et al., 2005), this uncertainty regarding incidence, and hence the appropriate amount
# 5.3 Sample sizes and desian

Some of the measures that would be required from WHS country studies can be estimated from quite small samples. One example is service coverage and use. Collecting information on rarer health problems, for example mortality or adult morbidity requires much larger samples. Moreover national estimates are often of limited use to health planners who require information on the sub8roups of the population that particular programmes or geographically localised initiatives are aimed at. Many of the most important and policy-relevant research issues involve examination of the interactions between different determinants of health, for example factors that inhibit the use of services (Hobcraft 1984). Furthermore, if the WHS adopts the plan to repeat the studies in order to measure change, this again requires an increase in sample size.

Two relevant findings from the assessment of the World Fertility Survey (Cleland and Scott 1987) are that sample-size related fieldwork costs represent only a moderate part of total expenditure on a programme of international surveys and that rigorous methodologies, and in particular extensive training, can produce high-quality information even when large samples are interviewed. These findings, comibined with the multiple advantages to be gained, suggest that the country health studies should aim to cover samples of several thousand households. This would be adequate to investigate child mortality, to carry out detailed and disaggregated studies of the more common diseases and of service use and to measure substantively significant changes in programme coverage and health over a five year period. In large countries that are ecologically diverse or have a federal system of government it is likely that detailed geographical breakdown of the results would be needed if they were to be of use for health planning. This would indicate a correspondingly larger sample.

One issue that will require particular attention in the design of samples for a WHS is the extent to which thev are clustered. The loss of efficiency that results from cluster sampling is particularly severe in the case of health. This reflects the localised transmission of infectious disease and the fact that many services (eg. the 38
# **Attrition Robustness—Bounds**

Table A23: Robustness of impact on SRH behavior index to differential attrition

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1 (Safe Spaces)|0.20***<br>(0.08)|0.22***<br>(0.08)|0.13*<br>(0.07)|0.19**<br>(0.08)|0.20***<br>(0.08)|0.20***<br>(0.08)|0.21***<br>(0.08)|
|T1+Leaders|0.13|0.29***|-0.13*|0.04|0.14|0.14|0.14|
||(0.09)|(0.09)|(0.08)|(0.09)|(0.09)|(0.09)|(0.09)|
|T2 (Safe Spaces + IGA)|0.05|0.22***|-0.13|0.01|0.05|0.05|0.04|
||(0.08)|(0.06)|(0.09)
Policy Research Working Paper 10324

# **Abstract**

An increasing number of regional trade agreements contains provisions that ease access to visas among member countries, which reduces the administrative cost of crossing the border. Combining United Nations data on bilateral stocks of immigrants in the period 1990–2020 with World Bank data on the content of 279 regional trade agreements, this paper presents robust evidence of a positive effect of visa provisions in regional trade agreements on bilateral migration: the presence of visa provisions in regional trade agreements increases the bilateral stock of immigrants by 5.9 percent. This result is robust to an instrumental variable strategy addressing the endogeneity problem. The effect of the inclusion of visa provisions in regional trade agreements is particularly effective among country pairs with different income levels (such as North-South). For this type of country pairs, the presence of visa provisions in regional trade agreements increases the bilateral stock of immigrants by 13 percent. Finally, the paper shows that the effectiveness of visa provisions in regional trade agreements reduces with the anti-immigration sentiment of voters in the destination.

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 anthonin.levelu@dauphine.psl.eu, amm223@georgetown.ed, and gianluca.orefice@dauphine.psl.eu.

_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
procurement.

The evidence on the border effect and on the trade effects of TAs and their provisions is confirmed in three sets of robustness checks, whose results are reported in the Appendix. Tables A2 and A3 show that the estimates of the gravity models are similar when we use an alternative “narrow” definition of government procurement, which excludes purchases recorded in the “Health” and “Education” columns in the TiVA input-output tables. Results are confirmed also if we estimate the gravity models using the full yearly panel (Tables A4 and A5).<sup>24</sup> Finally, we confirm our baseline findings when the dependent variable is further disaggregated by the components of the goods and services sectors listed in Table A1. In Tables A6 and A7, the regressions control for country-industry-year fixed effects, consistent with an industry-level gravity model, while we maintain country-pair fixed effects, which reflect the assumption that trade costs vary across services and goods but not within each of the two aggregates. The estimates are close to the baseline ones in Tables 1 and 2. One – difference is that the results for goods are even weaker than in the baseline e.g., WTO GPA membership is now negatively associated with cross-border procurement.

Table 1: PPML Gravity estimates, Goods

||(1)<br>Gov.|(2)<br>Priv.|(3)<br>Gov.|(4)<br>Priv.|(5)<br>Gov.|(6)<br>Priv.|(7)<br>Gov.|(8)<br>Priv.|(9)<br>Gov.|(10)<br>Priv.|
|---|---|---|---|---|---|---|---|---|---|---|
|Same country|
limitation, general disability question and other types of questions. Table 1 gives the list of countries and surveys with the WGSS between 2009 and 2018. In total, 32 countries, 46 data sets and 52 data set-years have included the WGSS between 2009 and 2018. The WGSS seems to have been adopted in Asia and in Sub-Saharan Africa more than in other regions. Further, it has been adopted in a variety of surveys, including international ones such as the Demographic and Health Survey (DHS), the Household Income and Expenditure Surveys and the LSMS (Malawi HIS, Nigeria GHS, Tanzania NPS, Uganda NPS). It has also been adopted in thematic surveys such as the Survey of Water, Sanitation, and Hygiene in Tajikistan. In six countries (Bangladesh, Ethiopia, Liberia, Nigeria, Tanzania, Uganda), the WGSS was used in multiple years for the same survey. Results are presented for one decade (2008-2018), with more data sets with the WGSS in recent years: 40% of data set-years with the WGSS were for the 2009-13 and 60% in 2014-18 periods, suggesting an increasing adoption of the WGSS in recent years.

> 3 We did not cover the UNICEF Multiple Indicator Cluster Surveys.

10
the reaction function at high and low values, and whether the reaction function is different for headline and core inflation.<sup>22</sup> All estimated reaction functions include the output gap and inflation, but in an augmented version we also include the lagged policy rate, the percentage change in exchange rate, and the budget deficit or government borrowing.

A number of earlier papers have estimated reaction functions for the RBI (see Appendix A4). These studies find that the output gap is important (Hutchison et al 2013, Mohanty and Klau 2005) but that the exchange rate also matters, especially from the late 1990s when it became more flexible. Inflation in general has a much smaller coefficient, both absolutely and relative to the Taylor rule benchmark of 1.5.

These analyses typically use quarterly data, since quarterly GDP growth is available from 1997; we follow this standard practice.<sup>23</sup> For inflation, we use the WPI inflation until 2013 and the CPI inflation thereafter, since these are the inflation rates monitored by the RBI.

21 This is consistent with Ball, Chari and Mishra (2016) who show that changes in headline inflation feed into expected inflation and future core inflation. Raj et al (2020) evaluate several possible measures of core inflation and similarly find that headline inflation does not converge to core inflation.

> 22 Rangarajan (2020) suggests that inflation targeting in India is flexible in the sense that “what inflation targeting demands is that when inflation goes beyond the comfort zone, the exclusive concern of monetary policy must be to bring it back to the target level. When inflation is within the comfort zone, authorities can look to other objectives.”

> 23 Papers estimating reaction functions at a monthly frequency use the industrial production index as a proxy for output, which we regard as unreliable.

11
and surveyed. This provided a first data point on migration for those contacted, as well as helped plan the logistics for in-person surveying. We then conducted face-to-face surveys, attempting to interview in-person all youth interviewed in the baseline survey. These surveys asked detailed questions about migration episodes and attempts, work, well-being, and the influence of the COVID-19 pandemic. We also administered an elder survey in each of the 391 settlements, during which the most knowledgeable elder (generally the village leader) was interviewed. The third step was an extensive tracking approach through a second round of phone surveys for all 24
to check the accuracy of [their] own forecasts,” while 75 percent strongly agreed that “WEO forecasts are valuable inputs to the economic policy process in [their] country.” 6 For more information on Consensus Forecasts, visit  https://www.consensuseconomics.com/; for more information on Focus Economics Forecasts, visit https://www.focus-economics.com/regions/middle-east-and-north-africa.

7 The analysis focuses analyses on 2010–2020 because systematic World Bank January GEP forecast data are only available for this period. Note that in the paper, we do not provide trends of the private sector’s forecasts given their limited coverage of countries and years.

5
between survey incomes and national accounts incomes in 27 OECD countries, finding discrepancies in annual growth rates of 0.32 percentage points in the United States and 0.55 percentage points in Germany.

A number of studies have systematically reviewed the discrepancies between survey and national accounts data. The most complete reviews were conducted by Ravallion (2003), Karshenas (2001, 2003) and Deaton (2005), who all assess the discrepancies globally with a sample of household surveys and national accounts data from 1980s and 1990s. They document significant HHS - NAS gaps, but their estimates varied substantially from each other and they were limited by relatively small samples of matched NAS and HHS data. Since these global assessments, the availability of household survey data in poorer countries have expanded considerably and many countries have revised both their survey and national accounts data and methods. We now also have better metadata on the types of household surveys and their comparability, which can help us better understand discrepancies.

The main contributions of this paper are threefold. We compile a data set of 2,095 household survey means from 166 countries matched to corresponding national accounts aggregates. Using this much larger compilation of matched NAS and HHS data, with broader geographic coverage and with temporal coverage stretching from 1965 to 2019, we revisit the HHS - NAS gaps and update the findings of Ravallion (2003), Karshenas (2003) and Deaton (2005). Second, we overcome the heterogeneity often seen in household surveys by extending the analysis to a subsample of the data containing only comparable spells, which is particularly important for understanding the discrepancies in estimates of growth. Third, we illustrate how the discrepancies in levels can lead to divergent representations of how living standards, poverty, and inequality differ across countries and over time.

Our findings suggest that disparities in income and consumption measures between surveys and national accounts are much larger than found by both Ravallion (2003) and Deaton (2005). On average, across all countries, we find that per capita consumption means
4. Data and Estimation Strategy 4.1. Data Demographic and Health Surveys (DHS) have been carried out in a number of developing countries as part of the Measure DHS project, a reputable USAID-funded project aimed essentially at providing detailed, reliable information on fertility, family planning, maternal and child health and mortality. The second and third DHS carried out in Nepal took place in 2001 and 2006, respectively, and are repeated cross-sections, not panel data. In 2001, six out of 257 sampling units had to be dropped from the sample for security reasons (Ministry of Health et al., 2002, p.6). But in 2006, conflict was nearly over everywhere, and so data collection could proceed without hindrance.

For each DHS, a national sample of households is first interviewed using a household questionnaire collecting usual individual demographic and education data, as well as household-level socio-economic information such as ownership of durable goods and housing materials. The demographic characteristics of individual members are then used to determine which members are eligible for individual interviews, namely all women aged 1549 (DHS 2006) or all ever-married women aged 15-49 (DHS 2001), as well as a subset of males aged 15-59. The data used for the education analysis comes from the household questionnaire, whereas that used for the marriage study comes from individual interviews with eligible women.

Summary statistics, by district conflict intensity and specification subsample, can be found in Table 3.

Another national dataset carried out in Nepal during the relevant period is the Nepalese Living Standard Survey (NLSS) of 2003/2004. Given the timing of the conflict, the DHS is generally more useful for the present analysis since data collection occurred later. As a consequence, the outcomes of interest (namely, education and marriage) are more likely to be realized for cohorts exposed to the conflict in 2006 than in 2003/2004. In addition, since the conflict was raging at the time of the NLSS data collection, there were more difficulties with data collection than