rafmacalaba/data-use-mentions-extended huggingface dataset:
countries in the latter period of the sample, and the sharp shift away from dependence on exports of commodities towards reliance on exports of manufactures.

**Figure 1. Average nominal rates of assistance to agriculture, five year averages 1955-2004**

<!-- Start of picture text --> 70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>1955-59 1960-64 1965-69 1970-74 1975-79 1980-84 1985-89 1990-94 1995-99 2000-04<br>-10<br>-20<br>-30<br>HIC & ECA HIC & ECA, incl. decoupled payments Developing countries<br>percent<br><!-- End of picture text --> _Source_ : www.worldbank.org/agdistortions The extent of taxation of developing countries in the early period of the sample is understated by the data on nominal rates of assistance presented in Figure 1, as the agricultural sector was also taxed indirectly by the protection provided to the non-agricultural sector. This raised input costs both directly through increases in the price of inputs, and indirectly through increases in the prices of nontraded goods and wages—the so-called real exchange appreciation resulting from protection. The full extent of the taxation of developing-country agriculture is shown using the Relative Rate of Assistance in Figure 2. This shows that a very large share of the reduction in the total burden of taxation of agriculture reflects reductions in the protection provided to other sectors. Sub-Saharan Africa is today the only developing country region where farmers still confront net taxation relative to other sectors. Matters are made worse because of weaknesses in infrastructure, inefficient logistics, etc. that result in high transport-related costs, reduce the pass-through of world market prices, and therefore the extent to which higher prices 10
Figure 6 provides a graphical overview of our results that are obtained when we vary both the target survey sample and the base survey sample. The former ranges from 10 to 100 percent of the sample, while the latter ranges from 10, 20, 30 to 100 percent of the sample (which helps make the graph less crowded). Since the combined TA sample contains 2,110 observations, we consider a range of 211 to 2,110 observations for the target survey sample size. Given the sample size of 4,644 households for the TZNPS 2020/21, we explore the predictive accuracy of imputation models using a base survey sample ranging from 464 to 4,644 observations.

Figure 6 illustrates that when using only 10 percent of the base survey (464 observations) to construct the models, most of the estimates for different target survey samples (indicated by the dotted blue line) fall outside the 95 percent CI of the true poverty rate (represented by the light gray zone). These estimates also display more variation, especially for smaller samples of the target survey. Increasing the sample size of the base survey from 10 percent to 20 percent (930 observations) (the dotted light green line) results in a dramatic improvement in the performance of the models, with almost all the estimates falling inside the 95 percent CI of the true poverty rate. Further increasing the base survey to 30 percent (1,393 observations) (the dotted orange line) slightly improves the imputation accuracy. Yet, estimates using larger sample sizes of the base survey (not shown) result in marginal improvement, as seen with the 100 percent sample of the base survey (the dotted black line).<sup>21</sup> In general, the predictive performance of the models stabilizes at the minimum sample size of around 1,000 observations for the target survey (close to 50 percent of the sample) and a similar

> 21 For example, a further increase in the size of the base survey
governing the storage policy. The policy is not designed to operate as a price band, with stocks released to prevent high prices; rather, stocks are released in a fixed amount every period to supply the PDS. In contrast, the trade policy mostly truncates high domestic prices. Together both policies are extremely effective in stabilizing the domestic price, because of the complementarity between the instruments. Trade policy prevents public stocks from being exported when the world price spikes, preventing any leakage from the operation of the storage policy to the world market.

**Table 3. Unpacking current policies, statistics (quantities in million tons)**

|**Variables**|**Laissez‐faire**|**Tradepolicy**|**Storage policy**|**Both instruments**|
|---|---|---|---|---|
|**Indiaprice(Rs/t)**|||||
|**Mean**|9,809|9,527|9,882|9,486|
|**CV(%)**|14.39|10.68|10.12|3.13|
|**Quantile 10%**|8,223|8,307|9,417|9,417|
|**Quantile 90%**|11,544|10,910|11,085|9,417|
|**RoWprice(US$/t)**|||||
|**Mean**|200.5|202.3|199.7|202.5|
|**CV(%)**|20.70|23.99|19.57|23.28|
|**Quantile 10%**|160.2|160.2|159.8|160.3|
|*
of including a mine. Nevertheless, since size may correlate with potential unobserved district characteristics, in the analysis we control for it.

# **Methodology**

Our identification relies upon comparing producing and non-producing districts that are spatially close and institutionally similar. We do so by means of several exercises. Our baseline case considers all districts from departments with mining activity (excluding the department of Lima), and compares socioeconomic outcomes of producing districts with, in turn, outcomes of non-producing districts in non-producing provinces and outcomes of non-producing districts in the same province of each mining district. We use information from the 1993 Census to control for district characteristics in 1993, prior to the mining boom, so that our baseline regression is as follows: where, _p_ denotes the province, _d_ the district, Ipd[PD] a binary variable that takes a value of one if the district is producing, Ipd[NPDPP] a binary variable that takes a value of one if the district is nonproducing in a producing province, Xpd a set of time invariant and 1993 district characteristics, and νd, νp, εpd department, province, and district error terms.

Under this specification, we consider two types of “treatment” districts: producing districts and non-producing districts in producing provinces; and one type of “control districts”: non-producing districts in non-producing provinces. Therefore, without province fixed effects, the estimates of β0 and β1 refer to the respective impacts on the two types of treatment districts with respect to control districts. When we introduce province fixed effects, however, the dummy Ipd[NPDPP] (associated with β1 ) drops out, and the estimate of β0 refers to the additional impact on producing districts with respect to non-producing districts in the same province.

Using the specification in (1), we first perform a diagnostic analysis to check the possibility of pre-treatment differences. Drawing from the 1993 Census, we use the 1993 district averages of illiteracy rate and index of basic necessities uncovered (the two dependent variables for which information
December of 2017. The security crisis was compounded by an economic crisis, which was triggered by the plunge of oil prices in the international market in 2014.

Using data from the 2017-18 Rapid Welfare Monitoring Survey (SWIFT), this study sheds light on the level of resiliency of the PDS program during this recent period of conflict and economic crisis. First, it explores if internally displaced households are less likely to access the PDS benefits and the characteristics associated with access. Second, the study tries to establish a causal role of the PDS program in mitigating welfare losses among the displaced population by measuring the program’s impacts on nutrition (calorie intake and food consumption), its spillover impacts on non-food expenditure including education, and its overall impact on vulnerability to poverty and subjective life assessment using a regression framework and a matching approach.

The analysis finds that compared to non-displaced households, displaced households fare poorly across all measures of welfare. IDPs have lower daily calorie intake and are more likely to face hunger, and they are 18 percentage points more likely to be poor (relative to the poverty rate of 15 percent of nondisplaced). More important, even those who are not in poverty are more vulnerable to falling into poverty, with the probability 17 percentage points higher for displaced households. By their own assessment, their current living conditions are far worse than before January 2014, the onset of the latest wave of displacement.

Access to PDS, however, plays an important role in mitigating the welfare loss. Displaced households that retain the PDS benefits have higher food and non-food expenditures, thus, have lower odds of being in poverty than those who lost access during the displacement. Similarly, the displaced PDS beneficiaries have significantly lower level of vulnerability to poverty, and have higher calorie intake and thus are more food secure than the displaced non-beneficiaries. Although they have a greater total calorie intake, the PDS beneficiaries consume significantly fewer calories from non-ration food than the comparison displaced non-beneficiaries. Combining the program’s positive impact on non-food consumption
|

_Sources:_ EC 2007; Undeclared Work in an Enlarged Union (Renoy et al., 2004); Statistics Estonia.

# **3. The Role of Taxes According to Opinion Polls**

13. In a survey, launched by the EU Commission, individuals in EU member countries were asked to report on undeclared work, defined as all remunerated activities (in-kind or cash), which are in principle legal but are not declared to tax authorities or social security institutions (EC 2007a). According to this opinion poll, the most frequent reasons for taking part in undeclared work in the new EU member countries are that salaries in the regular sector are too low. Taxes and social security contributions are also often mentioned as being an important motivator for working informally. In Hungary and Lithuania about 30-35 percent of respondants mentioned taxes as the most important reason for carrying out undeclared work, whereas taxes was the most important determinant for less than 10 percent of the respondants in Slovenia, Romania, Slovakia and Bulgaria (Figure 1).

14. The European Employment Observatory (EC 2007a) confirms the importance of taxes for carrying out undeclared work. It finds that that:

- In Hungary, high income taxes together with social security contributions are seen as providing strong incentives for undeclared work;

- In Lithuania, the combination of relatively low salaries and high taxes including social security contributions are regarded as the main drivers for undeclared work;

5
sup> An important summary statistic on GVC engagement that can be constructed using this type of information is the value added to gross output ratio (Johnson and Noguera, 2012).

A drawback from the perspective of learning about the GVC integration of firms or industries in sub-Saharan countries is that most widely-used datasets tend to focus on larger and more developed economies. However, we will demonstrate that two existing and freelyavailable data sources can be effectively used to study GVCs in sub-Saharan Africa. The first data source is the World Bank Enterprise Surveys (WBES). It contains firm-level responses to surveys conducted at semi-regular intervals in almost all developing countries. Across all subSaharan economies and survey years, the WBES provides access to responses from a total of 35,902 firms between 2002 and 2018. In most countries, more than one survey has been conducted over this period, which makes it possible not only to gauge the average level of GVC engagement in each country, but also its growth over time.

More details on the type of information contained in the WBES, both in terms of sample coverage and included variables, will be discussed in Section 2.1. Given the wide range of

> 1 A broad overview of the literature studying GVCs using case studies can be obtained from the list of publications of the Global Value Chain Initiative: https://globalvaluechains.org/

> 2 Timmer et al. (2015) illustrates the construction of one particular global input-output table, the WIOD, and the possible applications of this research tool using the global automotive industry as an example.

2
# III. **Mutual** Fund Investment

Different data sources are needed to study the role of institutional investors. Unlike the data on capital flows, which the World Bank collects on a regular basis, no agency has complete information on institutional investors. Companies and institutions like the **OECD,** the Securities and Exchange Commission **(SEC),** the Investment Company Institute, Morningstar, Emerging Market Funds Research, Frank Russell, **AMG** Data Services, Lipper Analytical Services, and State Street Bank have partial information on institutional investors. One can obtain a general picture only **by** analyzing and combining the different pieces of data, coming from various places.

This paper contributes to the literature not only **by** compiling information from different sources and displaying it in a systematic way, but also **by** presenting new evidence. The data from the World Bank and the BIS can be found in previous publications in a very similar format. The data from other sources are new evidence, although part of the data are displayed in a different format in some of the existing papers. The Appendix Table summarizes the data sets used in this paper and their sources.

# **IH.a** Size **of Mutual Funds and** Institutional Investors

Institutional investors-including mutual funds, pension funds, hedge funds, and insurance companies-are a growing force in developed markets. Table 1 shows that institutional investors held almost **$11** trillion in the United States alone in **_1995._ U.S.** institutions of these four types held more than **_50_** percent of the assets held **by** institutions across the world. When individual investors choose their portfolio allocation to emerging

**_7_**
# **Are power tariffs equitable and affordable?**

## **c. Can African households afford power services?**

Based on information reported in household surveys, on average power bills absorb almost 6 percent of total household budgets. For most countries the share falls below 3 percent; however in a few cases (such as Malawi and Mozambique) it can be as high as 10 or even 20 percent (figure 18). This share is relatively stable across quintiles.

<!-- Start of picture text --> Figure 18. Existing household spending on electricity<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>National Poorest Q2 Q3 Q4 Richest<br>quintile Quintile<br>Below 3% 3-5% 5-10% Over 10%<br><!-- End of picture text --> _Source:_ Adapted from Banerjee and others (2008).

In order to gauge whether power is affordable, two types of evidence can be considered.

One possible measure of affordability is non-payment of services. Based on household surveys, we can compare across quintiles the percentage of households that report _paying_ for power against the percentage of households that report _using_ service. Those using without paying include both clandestine users who steal power from the network and formal customers who fail to pay their bills. Overall, about 40 percent of people connected to electricity do not pay for it (figure 19). Nonpayment rates range from about 20 percent in the richest quintile to about 60 percent in the poorest quintile. A significant nonpayment rate, even among the richest quintiles, suggests that a culture of nonpayment exists in addition to affordability issues.

28
across wealth strata. We study this dispersion, focusing on its implication in the context of efforts to use household poverty data to target undernourished individuals.<sup>13</sup> A number of recent papers review the existing evidence on the nutritional impacts of income growth and income support to poor households. On the first, as already noted, several papers find low income effects, particularly in the short-term (Grogan and Moers 2016; Haddad et al. 2003; Smith and Haddad 2015). With respect to the second, Alderman (2015) and Ruel and Alderman (2013) conclude that social safety nets targeting poor households with food or cash transfers (whether conditional or unconditional) have generally had limited impacts on children’s nutritional status. The papers speculate that this may be because the targeted households are not those that have young children in the right age range. They do not question the practice of targeting poor households to reach undernourished

> 11 There has been far less focus on inequalities in malnutrition among women.

> 12 The online addendum to Bredenkamp et al. (2014) provides concentration indices across 80 developing countries for child undernutrition using the wealth index as the ranking variable. The median for stunting is -0.15.

> 13 We do not use the concentration index here as there is greater interest in this context in points on the concentration curve.

6
Policy Research Working Paper 5591

# **Abstract**

This paper aims to investigate empirically how international migration and remittances in Indonesia, particularly female migration, affect child outcomes and labor supply behavior in sending households. The authors analyze the Indonesia Family Life Survey data set and apply an instrumental variable estimation method, using historical migration networks as instruments for migration and remittance receipts. The study finds that, in Indonesia, the impacts of international migration on sending households are likely to vary depending on the gender of the migrants. On average, migration reduces the working hours of remaining household members, but this effect is not observed in households with female migrants. At the same time, female migration and their remittances tend to reduce child labor. The estimated impacts of migration and remittances on school enrollment are not statistically significant, but this result is interesting in that the directions of the effects can be opposite when the migrant is male or female This paper is a product of the Poverty Reduction and Economic Management Unit, East Asia and Pacific Region. 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://econ.worldbank.org. The author may be contacted at TNguyen16@worldbank.org.

_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
ine¢ cient in transmitting information. Because corn markets are considered to be well-functioning markets, in the sense that prices and transactions are transparent, centralized, and very liquid, it is surprising and interesting to ...nd that they might not always behave as one would expect in a classical supply-demand model with inventories and utility and pro...t-maximizing agents. This raises several relevant questions regarding macroeconomics, ...nancial markets and industrial organization. First, if a very well developed market fails to deliver fully informative prices, what can then be said regarding other markets, where illiquidity, information asymmetry and search costs are more relevant? Moreover, since these results are found for quarterly data, the implications for business-cycle accounting could be important. In several developing countries commodity markets such as corn have a signi...cant impact on overall GDP and exports. If the prices that are being used for measurement are not market-clearing ones, important distortions could be taking place. Also, since annual prices do not di¤er from fundamentals as much as quarterly ones do, another potential question arises: Should we produce national accounts using prices measured at quarterly, annual, or some other frequency? How much time do markets need to become fully informative? Many business-cycle theorists believe that shocks on the real side of the economy, such as shocks to TFP and commodity prices, trigger and propagate economic ‡uctuations. Commodity price shocks clearly play important roles in developing nations today, particularly resource exporters and have also played a large role in economic ‡uctuations in the past. Economists and policy makers believed, for example, that the commodity-price declines in the late 1920s and early 1930s contributed to the length and severity of the Great Depression. In 1933, the Roosevelt administration’s e¤orts to raise commodity prices, particularly prices of farm products like corn, formed the centerpiece of its e¤orts to resurrect the economy. These results have implications for the sources of shocks and the accuracy of the interpretation of
pc and Prob of being in each VAM cat<br>Prob VAM 1 Prob VAM 2 Prob VAM 3<br>.5 .6 .7 .8 .9 .5 .6 .7 .8 .9 1 .5 .6 .7 .8 .9<br>Prob VAM 1 Prob VAM 2 Prob VAM 3<br>Tot Exp pc 07 Fitted values Tot Exp pc 07 Fitted values Tot Exp pc 07 Fitted values<br>Prob VAM 4 Prob VAM 5<br>.5 .6 .7 .8 .5 .6 .7 .8 .9<br>Prob VAM 4 Prob VAM 5<br>Tot Exp pc 07 Fitted values Tot Exp pc 07 Fitted values<br>600 600 600<br>400 400 400<br>200 Tot Exp pc 200 Tot Exp pc 200<br>0 0 0<br>600 600<br>400 400<br>200 Tot Exp pc 200<br>0 0<br><!-- End of picture text --> Source: Authors from World Bank (2010) APER database. Note: each figure depicts the association between the estimated probability of vulnerability across municipalities pertaining to the respective vulnerability category, 1 to 5 (as described in footnote 4 above).

9
control agency (BAPEDAL) has very few inspectors but allocates much of their time to its JAGATIRTA program for complaint response. And, as we will show, China's provincial and local regulators respond annually to more than 100,000 citizen complaints.<sup>4</sup> Are complaints a good substitute for direct monitoring? To date, this question has not been systematically addressed. Complaints are undoubtedly a source of low-cost information, since polluting facilities are often apparent to their neighbors even if they are invisible to government agencies. There are also compelling social and political arguments for agency responsiveness to citizen complaints about polluters. However, there are good reasons for skepticism about complaint-driven resource allocation.

Plaintiffs may lack sufficient information to distinguish between 'nuisance' emissions and those which are truly hazardous. Colorless, odorless toxics and heavy metals may escape notice altogether. Furthermore, some individuals or communities may have higher propensities to complain than others, regardless of the objective situation. If regulators respond passively to complaints, aggressive plaintiffs may capture most of the available resources.

In this paper, we use a new panel data set to assess the role of citizen environmental complaints in China's pollution control system.<sup>5</sup> Section 2 describes the pattern of complaints and agency responses. Section 3 develops a testable model of

> 4Complaint response systems in Brazil, China and Indonesia are familiar to the authors from collaborative work with FEEMA, CETESB, BAPEDAL and China's National Environmental Protection Agency (NEPA).

> 5In this paper, the term "province" refers to provinces, autonomous regions and municipalities which are directly affiliated with the central government

3