rafmacalaba/data-use-mentions-extended huggingface dataset:
and map 1 shows the changes in the leave-out wage ratio in Brazil and in the analytical sample between 2011 and 2016.

The raw wage ratio has been closing in Brazil, indicating a convergence between male and female wages in formal sector employment (appendix A, figure A1). Additionally, the dispersion of the raw gender wage ratio across municipalities has narrowed. The leave-out wage ratio has also risen, but dispersion in the leave-out ratio has not increased, suggesting that the narrowing of the distribution of gender ratios across municipalities may be driven by changes in the industrial composition of female employment, which is excluded from the leave-out measure by design. The populationweighted average municipal change in the leave-out wage ratio in 2011–16 was 0.002, which implies that average earnings opportunities among women did not change relative to the opportunities among men over the period. The raw wage ratio increased over the period, suggesting that the share of male employment rose the most in sectors in which earnings were growing rapidly.

That the wage data only include formal sector employees and do not consider the 35 percent of the Brazilian labor force that is self-employed or informal is a limitation (Ulyssea 2018). However, it is the potential wage, not the actual wage that affects a woman’s bargaining position in the household (Aizer 2010). Thus, changes in the gender wage gap in the formal sector may plausibly affect all women. Additionally, to consider how excluding informal workers from the analysis may bias the results, the nationally representative National Household Survey (Pesquisa Nacional por Amostra de Domicílios, PNAD) is used in the analysis to contrast the gender wage ratio between formal and informal laborers. The result is the finding that the informal sector is more equitable than the formal sector in terms of wages, suggesting that the gender wage ratio is underestimated in the case of the country as a whole (appendix A, table A1). The results of the survey indicate that women are only slightly more likely to be in the formal sector than
**Table 2: Two Different Measures of New Firms**

|||N<br>|umber of f<br>|irms<br>||
|---|---|---|---|---|---|
||newly|newly|Gap year|(yearentered-|yearregistered)|
|year|registered|entering|0|1|2|
|2003|4,925|4,160|100%|0%|0%|
|2004|5,021|4,804|86%|14%|0%|
|2005|8,739|8,604|90%|10%|1%|
|2006|8,885|8,376|89%|10%|1%|
|2007|8,931|9,532|86%|13%|1%|
|2008|8,568|8,859|91%|7%|2%|
|2009|7,456|7,542|93%|5%|1%|
|2010|7,151|7,500|93%|5%|1%|
|2011|6,383|6,686|95%|3%|1%|
|Total|66,059|66,063|91%|8%|1%|

Source: Data from Serbia’s Financial Accounts Registry As shown in table 2, for most firms, the year of registration and year of entering the database are the same, but in some cases, they differ by one or maximum two years. We believe these differences are due to administrative delays in reporting financial accounts. We perform our analysis using both measures and find equivalent results either way. Table 3 presents the number of new firms based on their reported year of registration by commercial court and year
Table 3: Impact of Migration Policy Instruments

|**Migration cycle**|**Migrant**<br>**Migrant’s family**<br>**Sending community**<br>**Receiving community**|
|---|---|
|**Pre-departure**<br>-<br>Facilitate more migration||
|-<br>Bilateral actions|_Fostering migration:_Strong evidence of substantial more migration and income and consumption increase<br>of participating households from the New Zealand Recognized Seasonal Employer program; 49 bilateral<br>migration agreements by the Philippines with 25 destination countries, but little research to say how much<br>new migration they generate and whether it is causal.|
|-<br>Unilateral actions|_Hindering migration_: Countries with restrictions on rights of women to migrate or requiring all citizens to<br>get government permission to travel have 5 to 6 percent less migrants per capita than countries with<br>similar income, population and governance levels without these restrictions. Higher passport costs are<br>associated with less migration (with the cost of a passport exceeding 10 per cent of per capita income in<br>some countries)<br>_Fostering migration:_Little effect of unilateral actions to assist people by reducing the information barriers,<br>the frictions in jobs search or documentation barriers.|

-

- Training to inform people for better migration decisions

- Pre-departure orientation (language, rights, customs, skills, ...)

No rigorous evaluations available

- Financial literacy training Raised savings and investments

No rigorous evidence No rigorous evidence
Compared to the baseline year of 2001, residents were more fearful of crime by 0.17 sd. These fears are not necessarily unfounded, as we find some weak evidence of changes in levels of violence in their parishes. Compared to 2001, a 1-SD increase in refugee presence in 2011 is associated with a 1.26 percentage point increase in likelihood of a violent event, and in 2016, a 1.11 percentage point increase. These findings are in line with our predictions for Uganda. As in Global North contexts, we recognize that out-group members can elicit fears and insecurity. It is unclear from the ACLED dataset, however, whether these violent events involve refugees. It is also possible that ACLED underreports violent incidences that are not reported by the media. Recent scholarship on the relationship between refugees and violent conflict finds that hosting generally has null effects on conflict (Zhou and Shaver, 2021); when conflicts do occur, refugees tend to be the victims (Savun and Gineste, 2019). Nevertheless, by 2020, like with Afrobarometer respondents reporting feeling more safe, these fears of crime reverse with a negative effect of -0.13 sd.

As we theorize, the positive externalities for local communities (in the form of improved service delivery), generated by Uganda’s integrative approach to hosting refugees, generally balance out these fears, which do not generate a backlash against refugees and inclusive migration policies. Improving basic services is of the utmost importance to host communities in developing contexts regardless of who is providing them (Sacks, 2012).

All the results reported here use our main specification of the Nearest + 20km exposure measure (which takes into account not only the nearest settlements, but also all settlements within 20km) and the subset of parishes that are within 150km of a settlement. In SI Section S4, we present the regression tables for all of the results shown in Figures 5 and 6, along with their robustness specifications. These tables display the effects across all three measures of exposure
fixed effects, which control for all time-invariant market specific determinants of prices, βt are year fixed effects, and εit are other time-varying, location-specific shocks to prices. Coefficients γm capture the monthly impact of disaster on prices, interpreted as the 100*γm percent change in prices associated with a standard deviation of the weather index.

# **2.2 Data**

# _Household-level data_

Household-level information is used to construct both outcome variables, such as household per capita consumption, children’s school attendance, among others, as well as control variables, including demographic structure, family composition, school attainment, gender and age of household heads, and area of location, etc. These data come from the national household survey of living conditions ( _Inquérito aos Orçamentos Familiares_ , known as IOF for its acronym in Portuguese), collected over a 12-month survey period by the National Statistics Office of Mozambique (Instituto Nacional de Estatistica, INE). We use three waves of the IOF survey: the IOF 2002/03 (collected between July 2002 and June 2003), the IOF 2008/09 (collected between September 2008 and August 2009) and the IOF 2014/15 (collected between August-2014 and July2015). The 2002/03 and 2008/09 IOFs are cross-sectional surveys whereas the latest one, the IOF2014/15, was designed and implemented as a panel survey but used as pooled cross section for the purposes of this analysis.<sup>1</sup> All IOF surveys are representative at the national, rural-urban, and provincial levels. The information collected by these surveys captures the main variables included in the regression analysis, such as household welfare (total, food and non-food consumption, and poverty status), education, labor outcomes, health, morbidity, food security and possession of assets. The IOF 2002/03 interviewed 8,700 households and provides the baseline information for shocks that occurred between 2003 and 2007. The IOF 2008/09 visited 10,832 households and provides the baseline
WPS3435

# **POPULATION AGE STRUCTURE AND THE BUDGET DEFICIT**

## **Derek H. C. Chen***

The World Bank 1818 H Street, N.W. Washington D.C. 20433 U.S.A.

This paper focuses on the effects of age-structure changes on the size of budget deficits of national governments. More specifically, it determines whether differences in age structure can account for the observed differences in budget deficits across countries as well as across time. Via an extension of the untested theory of negative bequest motives advocated by Cukierman and Meltzer (1989), this paper argues that the commonly accepted notion that population aging tends to increase the budget deficits of economies is theoretically consistent. However, preliminary results from country and time fixed-effects panel regressions, estimated from 1975 to 1992 over 55 developed and developing countries, indicate statistical evidence for this postulation is present only in the developing countries but not in the developed countries.

### **JEL Classification Numbers: E62, H30, J14**

#### World Bank Policy Research Working Paper 3435, October 2004

_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._

*The Knowledge for Development Program of the World Bank Institute.
Proposition 1 establishes that when using a _household-level_ Paasche index, one inclusive of all items (food and nonfood), then using a single or multiple index approach leads to the same real consumption h h aggregate: xSI = xMI. In other words, the choice of the method is irrelevant for the estimation of poverty and inequality indexes, as well as for any other moment of the empirical distribution function. The situation described by Proposition 1 corresponds to the conditions assumed by Deaton and Zaidi (2002).

Does such a Paasche index exist in practical work? Arguably, it is unlikely for two main reasons. First, household survey data that are typically used for welfare measurement do not include information on prices faced by each household. Rather, households within a defined geographical area are associated with same set of prices, either because expenditure data collected at household level are matched with prices from a common market in the area or because prices are proxied by unit values.<sup>3</sup> In either case, the lack of household level price data leads to r≠H, and therefore xSI ≠xMI. Second, the ideal scenario of full coverage of prices for all items included in the consumption aggregate (i.e. k= K ) is rarely realized, either because not all items are sold in the market of reference (in case household questionnaires are complemented by market level questionnaires) or because is often impossible to collect information on quantities consumed for non-food items and hence is not possible to proxy prices with unit values.

By relaxing the assumptions of Proposition 1, we obtain a new theoretical result, that clarifies how important is, in practice, the choice between the use of one deflator (SI) versus two deflators (MI).

# **Proposition 2 (Distributional bias).**

Assume (r, k, kf, knf, α, αf, αnf) = (r, k, kf, knf, α, α, α ), and k
Policy Research Working Paper 9167

# **Abstract**

Do poor households shop in a way that leaves money on the table? A simple way to maximize consumption, conditional on available cash, is to avoid regularly purchasing small amounts of nonperishable goods when bulk discounts are available at modestly larger quantities. Using two-week transaction diaries covering 48,501 purchases by 1,493 households in Tanzania, this paper finds that through bulk purchasing the average household could spend 8.7 percent less without reducing purchasing quantities. Several explanations for this pattern are investigated, and the most likely mechanisms are found to be worries about over-consumption of stocks and avoidance of social taxation. Contrary - to prior work, there is little indication that liquidity con straints prevent poorer households in the sample from buying in bulk, possibly because the bulk quantities under examination are not very large.

This paper is a product of the Knowledge and Strategy Team, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at bmd28@cornell.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
insurance, air travel, and automobiles (Brynjolfsson and Smith 2000; Brown and Goolsbee 2002; Orlov 2011; and Scott Morton, Zettelmeyer, and Silva-Risso 2001). There is evidence of productivity gains in matching service providers and job seekers too. Based on firmlevel data from ten OECD countries across four industries—hotels, restaurants, taxis, and retail trade—Bailin Rivares et al. (2019) find that the average service provider in countries with high online platform development experienced larger productivity increases vis-à-vis the average service provider in countries with low online platform development. Evidence from job platforms in the United States and Germany suggests that online job searchers were re-employed about 25 percent faster than non-online job searchers (Gürtzgen et al. 2021; Kuhn and Mansour 2014). In Norway, the use of online platforms is estimated to have reduced the duration of job vacancies and the share of firms with unfilled vacancies (Bhuller, Kostøl, and Vigtel 2020).<sup>5</sup> For developing economies, much of the evidence of ICT lowering the costs of matching buyers and sellers has been shown in studies of international trade. Based on data for 60 countries, Freund and Weinhold (2004) find that a 10-percentage point increase in growth of web hosts for the

> 4 Numerous cross-country empirical studies have found a positive association between the adoption of ICT (computers, hard disks, internet cables, and the like) and growth in GDP or GDP per capita (e.g., Colecchia and Schreyer 2002; Niebel 2018; Stanley, Doucouliagos, and Steel 2018; Vu 2011). Others have also found a causal relationship between broadband penetration and growth (Arvin and Pradhan 2014; Czernich et al. 2011; Edquist et al. 2018).

> 5 Despite the widespread availability of products on e-commerce platforms, substantial price dispersion remains due to remaining search costs, partial product information, lack of competition, and inefficient design of online platforms (Baye, Morgan, and Scholten 2004; Choi, Dai
an agrarian reform program, including a land reform; and, finally, the deregulation of domestic markets for agricultural goods – were important drivers of the observed agricultural performance.<sup>5</sup> However, the increase in agricultural productivity was accompanied by a massive lay-off of hired labor and by important changes in the size distribution of farms. According to the agricultural census from 1996, the number of small farms declined dramatically and agricultural employment shrank by 23 percent between 1986 and 1996, although these figures should be taken with some caution (Helfand and Rezende 2004). Our analysis based on the 1997 and 2001 household surveys (PNAD) suggests that this decline in agricultural employment has continued after 1996. In 2001, agriculture accounted for 20.6 percent of employment in Brazil down from 24.2 percent in 1997.

> 5 See Helfand and Rezende (2004) and Dias and Amaral (2002) for details.

6
2) different sample size (OECD only versus pooled sample/all observation); (3) different distributional assumptions (GLM versus OLS versus Ordered Probit); (4) different robustness tests (reweighting observations to eliminate outliers); and (5) the inclusion of different control variables (Basic Controls, All additional Controls, Coordinated Capitalist Economies; see above and Hamilton 2012 for details).

Regression Model 1 of Table 4.03 is the simplest model possible, and conveys how the additive index of limited government (higher EDD/NEDD ratio) affects the level of perceived rent extraction utilizing only the most basic control variables, and restricted to the sub-sample of OECD countries. The results, which are significant at the 1% level and consistent with the theoretical expectations of the model, suggest that more limited government (a higher EDD/NEDD ratio) is associated with less perceived rent extraction. Regression Model 2 is identical to Regression Model 1, but also includes a control for ‘coordinated capitalist economies’ in which peak organizations play a critical role in policy-making (Hall and Soskice, 2001). These may, therefore, provide an alternative incentive for public policy-makers to minimize their rent extraction (Olson, 1981). While this control has the expected negative sign (more peak organizations engender less rent extraction) the results are insignificant and do not alter the basic result of the Regression Model 1. Here, a higher EDD/NEDD ratio is associated with less rent extraction. Utilizing the factor analysis measure of limited government (higher EDD/NEDD ratio), Regression Model 3 yields the same qualitative results, indicating that measurement error due to miss-specified weights may not be a major problem. Once again, the dependent variable, assuming it is ordinal and discrete, rather than interval and continuous (Regressions 4 and 5) has no effect on the results which are still significant at the 1% level, and have the theoretically anticipated sign. Utilizing the pooled dataset and all possible determinants of rent extraction identified in
children.<sup>18</sup> Figure 5.1 shows that students learn to divide along an S-shaped learning trajectory, with a locally linear interval from Grades 6 to 10. Figure 5.2 shows how often this locally linear interval appears at the subnational level, using 2012 ASER data for 31 Indian states. We compare observed learning trajectories to a projected linear trend and find remarkable alignment, indicating local linearity across most states in that year. We see this trend repeated across nearly all states and all years from 2008 to 2012 (see Annex 1, Figure 3 for all results).

> 18 Note that this is comparing different cohorts of students at different grades, not the same students over time.

26
of the nini population, and almost all of them (29.7 percent of all ninis) are young males still living with their parents, with over half of that group not actively searching for work. These patterns suggest that it may be wise to target anti-dropout/employment programs (depending on the age profile and individual context) at both young male and female ninis who are living with their parents and are not searching for work, perhaps because they lack skills, information, or motivation. In contrast, the nature of the nini phenomenon among women starting a household with children is intuitively very different: it could reflect a rational personal choice, and reducing the number of ninis in this category will likely involve different policies, including child care and perhaps teenage pregnancy prevention programs.

> 11 One caveat on the issue of children: due to a limitation of the SEDLAC harmonized data, we are unfortunately unable to identify the parentage of children unless they are those of the household head. We attempt to overcome this limitation by identifying those ninis who live with at least one child aged 5 years or under (the age range most likely relevant in prompting parents to stay at home to care for children) as an approximation for those that have children in this age range. Thus, for example, when we analyze trends for ninis who decide to start their own household with children, we are actually including any nini who is either a household head, partner of the household head, or married or in a civil partnership, and who is living with at least one child age 5 or under.

14
labor, stable income or employment; (4) school age family members receive lower secondary school education; (5) have access to clean water and stable sources of energy; (6) have access to primary public health services. Decree suggests that implementing ministries should divulgate its provisions to local governments. The extent to which village heads adhere to these criteria when selecting beneficiaries in practice depends on several factors, such as success in disseminating the decree and village heads training on it, potential differences in interpretation of some of these criteria (e.g. stable employment) and village heads’ access to information about these criteria for all households in the village. Lastly, village heads may still select on a different criterion, as in Basurto, Dupas and Robinson (2019), especially given that there are no formal checks of accuracy in place.

We study the outcomes of village heads selection process in 85 villages across 7 provinces in northern and southern Lao PDR where the RMG program was implemented.<sup>8</sup>

# 3. Data

To understand how village heads determined household eligibility and to assess the quality of their decisions in terms of targeting the poor, RMG baseline data collection included two targeting assessment components. First, in addition to collecting data on RMG and WL households that form the treatment and control groups for the impact evaluation, we administered the same survey to a Random Sample (RS) of village households with a woman of eligible age to participate in the RMG program (limited for simplicity in the random sample to ages 18-55). Households selected into the random sample could be replaced if they did not have a female household member of eligible age, if they had moved out of the village, if they could not be located after multiple attempts spanning at least two days, if they refused to participate, or if they were already part of the RMG or WL sample.<sup>9</sup> This sampling strategy enables comparison of household characteristics between the RMG-eligible and