rafmacalaba/data-use-mentions-extended huggingface dataset:
We conducted a randomized control trail (RCT) in Tbilisi, Georgia, to answer each of these questions. The experiment compares the efficiency of three types of information treatments: (1) receiving a pamphlet with information on pollution harms and avoidance behavior, (2) receiving a pamphlet and daily text messages with information on outdoor air pollution in one’s neighborhood, and (3) receiving a pamphlet, daily text messages on indoor and outdoor air pollution levels, and an indoor air pollution monitor. We surveyed households twice before and approximately two months after the treatment. The questionnaire contained questions about socioeconomic status, knowledge about air pollution, avoidance behavior, a cognition exercise, self-reported health, and willingness to pay for protective devices. To ensure that information on air pollution is as accurate as possible, we installed outdoor pollution monitors throughout Tbilisi, multiplying the number of outdoor monitors within the city by 10 for the duration of the intervention. Indoor air pollution monitors were also distributed to nearly 150 randomly selected households. Data from these indoor monitors provides insight into the extent of exposure of households that are representative of Tbilisi inhabitants.

We find that providing information in a pamphlet has no significant impact on our measured outcomes. Receiving daily text messages impacts knowledge of air pollution and the adoption of avoidance behavior. However, only the most intensive information treatment - receiving information about both indoor and outdoor pollution levels - leads to changes in avoidance behavior that result in health improvements during the intervention. These improvements appear to be driven by the fact that households who receive information about indoor air pollution levels reduce their level of indoor cigarette smoking. Consistent with some existing work (Greenstone et al., 2021), but contrary to others (Greenstone et al., 2023; Ahmad et al., 2023), we find that providing information and access to indoor air quality monitors (IAQMs) does not change households’ willingness-to-pay for either IAQMs or indoor air purifiers.

To examine the extent of infiltration in Tbilisi, we combine the data
|enous regressors||0.000411|5.89e-07|

Source: Authors’ calculations based on World Economic Outlook database 2019.

Robust standard errors in brackets.*** p<0.01, ** p<0.05, * p<0.1.Underidentification tests. Ho: matrix of reduced form coefficients has rank=K1-1 -underidentified. Ha: matrix has rank=K1-identified. Weak identification test. Ho: equation is weakly identified. Weak-instrument-robust inference. Tests of joint significance of endogenous regressors B1 in main equation. Ho: B1=0 and overidentifying restrictions are valid.
Similarly, according to the 2001 United Kingdom Census, health professionals are also only 6.9 percent of the tertiary-educated migrants from developing countries who came to the United Kingdom after age 24, with this number increasing to 10 percent if one also includes non-professional positions in healthcare occupations. In South Africa, the 2001 Census shows health professionals to be 8.2 percent of tertiary-educated immigrants from developing countries who arrived after age 24, and 14.1 percent of those with masters degrees or higher.

> 1 We take ―developing country‖ to refer to all countries which are not classified by the World Bank as ―high income‖ -- that is, which have 2009 Gross National Income per capita of $12,195 or lower.

4
higher costs are more than offset by higher net interest margins and higher not-interest income (section 4), resulting ultimately in higher profitability. Indeed, the higher wages paid by listed banks could simply reflect a more skilled labor force, required to develop more sophisticated and profitable lines of business. The higher profit ratios suggest that this strategy has paid off. Finally, we note that listed banks have lower ratios of loss loan provisions to loans, although the coefficient is not significant.

All in all, these results imply that listing generates higher costs but that these costs are more than compensated by higher revenues and profits. As noted before, the stricter governance and disclosure requirements imposed on listed banks could be driving these results. This interpretation is consistent with a recent survey of bank governance in MENA (OECD (2009)), which concludes that corporate governance of non-listed banks is generally poor, particularly those that are family controlled – these banks tend to engage heavily in connected lending and perform poorly as a result. This would suggest that MENA regulators should encourage or even mandate listing, as some countries already do. However, there is also a possibility that our results could be affected by selection bias: better managed and more successful banks may be precisely those banks that decide to list.

# _Bank structures and performance_

Finally, we complement the analysis of ownership and performance by focusing briefly on the impact of size and balance sheet structures on performance. We note that larger banks tend to be more profitable, as indicated by higher returns on assets and equity, although only the latter variable is statistically significant, and none of the profit indicators is significant in the weighted regressions (Appendix C). Larger banks tend to have lower ratios of interest income to assets and lower net interest margins, results that are consistent with their larger securities portfolios, although most of the relevant coefficients are not statistically significant. Most importantly, larger banks have lower cost ratios, despite paying higher wages on average. This result is essentially due to a
one group increases without decreasing the coverage rates of other groups, the HOI increases; and (iii) redistribution of opportunities—when the coverage rate of a vulnerable group increases for a constant overall coverage rate, there is a decrease in inequality and an increase in the HOI. To compute HOI for a particular opportunity for the children of a country, household survey data are essential. To allow computation of HOI for education and health opportunities, the survey must have a minimum set of information, at the individual (child) or household level, as appropriate. Examples of these would be whether the child is attending school, grade level and last grade completed, and health

7
, 2012. The New Geography of Jobs. Houghton Mifflin Harcourt.

- Morten, M., 2019. Temporary Migration and Endogenous Risk Sharing in Village India. Journal of Political Economy 127, 1–46. https://doi.org/10.1086/700763

- Mu, R., van de Walle, D., 2011. Left behind to farm? Women’s labor re-allocation in rural China. Labour Economics, Labour markets in developing countries 18, S83–S97. https://doi.org/10.1016/j.labeco.2011.01.009

- National Bureau of Statistics, 2023. STATISTICAL COMMUNIQUÉ OF THE PEOPLE’S REPUBLIC OF CHINA ON THE 2022 NATIONAL ECONOMIC AND SOCIAL DEVELOPMENT [WWW Document]. URL https://www.stats.gov.cn/english/PressRelease/202302/t20230227_1918979.html (accessed 3.7.24).

- National Bureau of Statistics, 2019. 2018 Migrant Workers Monitoring Survey Report [WWW Document]. URL http://www.stats.gov.cn/tjsj/zxfb/201904/t20190429_1662268.html (accessed 9.18.20).

- National Development and Reform Commission (NDRC), 2019. Key Tasks for New Urbanization Construction in 2019 [WWW Document]. URL

- https://www.ndrc.gov.cn/xxgk/zcfb/tz/201904/t20190408_962418.html (accessed 3.8.24).

- Naughton, B., 2004. The Western Development Program, in: In Holding China Together: Diversity and National Integration in the Post-Deng Era. Cambridge Univ. Press, New York, pp. 1–25.

32
_Social Development_ Two aspects of social development are considered: human development and income inequality. For ranking countries in terms of their achievements on human development, we solely rely on the United Nations' index on human development. This index incorporates life expectancy, adult literacy, educational enrollments and per capita GDP in purchasing power parity terms. Egalitarian nature of the society is captured by an inverse rank on the Gini coefficients estimated by Deininger and Squire (1996). Table 3 shows that fiscal decentralization is positively correlated and statistically significant with both the indices.

# _Institutional Environmentfor Macroeconomic Management_

It is frequently argued that a decentralized public policy environment of the type found in developing countries contributes "to the aggravation of macroeconomic problems" (Tanzi, 1996, p.305). In the following, we reflect upon the available empirical evidence on aspects of institutional framework for monetary and fiscal policies to form a perspective on this issue.

# _Institutional Settingfor Monetary Policy_

Monetary policy is clearly a central function and best entrusted to an independent central bank (Shah, 1994, p.<sup>1</sup> 1). The critical question then is whether or not independence of central bank is compromised under a decentralized fiscal system. One would expect, a priori, that the central bank would have greater independence under a decentralized system since such a system would require clarification of rules under which a central bank operates, its functions and its relationships with various governments. For example, when Brazil in 1988 introduced a decentralized federal constitution, it significantly enhanced the independence of the central bank (Bomfim and Shah, 1994). On the other hand, in centralized countries the role of the central bank is typically shaped and influenced by the Ministry of Finance. In an extreme case, the functions of the central bank of the U.K., the Bank of England, are not defined by law but have developed over time by a tradition fostered by the U.K. Treasury.

For a systematic examination of this question, we
|8|5|13|||
|And recorded in ofcial registers|6|4|10|_D_<sup>_CNDD_+1</sup><br>_i_|_D_<sup>_FNL_1</sup><br>_i_|
|Not declared but matched with registers|1|7|8|||
|Total matched with registers (declared or not)|7|11|18|_D_<sup>_CNDD_+2</sup><br>_i_|_D_<sup>_FNL_2</sup><br>_i_|
|**Totals**||||||
|Households belonging to a faction (without matches)|28|21<sup>∗</sup>|49|_R_<sup>_CNDD_+1</sup><br>_i_|_R_<sup>_FNL_1</sup><br>_i_|
|Households belonging to a faction (with matches)|29|28|57|_R_<sup>_CNDD_+2</sup><br>_i_|_R_<sup>_FNL_2</sup><br>_i_|

_Notes_ : Authors’ analysis based on data described in the text. For two households, there were two persons reporting to have ties with the FNL. In one household, both declared to be demobilized in 2009 but none was officially recorded. In another household, there was one recorded ex-combatant, while his brother had not received anything. The related dummies take the value one for each case but the return variable is restricted to one for both cases.

We argue that the second definition is the most appropriate for two reasons. First, the matching exercise with official demobilization registers should capture respondents who feared reporting that there is an ex-combatant in their family. Second, cross-checking self-reported demobilization status with official demobilization registers should exclude households who wrongly 17We undertook this matching exercise using generalized Levenshtein edit distance, which is the total number
migrants from entering. With more and more migrants gathering at the border and a deterioration of the humanitarian situation in refugee camps along the Balkan Route, the German government decided in August 2015 allow refugees from Syria to seek asylum in Germany without applying the Dublin Regulation (Deutsche Welle, 2017). What followed was the large migration wave that is displayed by the shaded area in Figure 1(a). Following the migration wave, in 2016 Germany became the country hosting the largest number of refugees in Europe. Within Europe, Germany hosted the majority of Syrians (in 2020 around 59%), followed by Sweden (11%). The large number of Syrians going to Germany was mainly due to the country’s open door policy vis-a-vis Syrians (UNHCR, 2021). However, there are seven countries in the Middle East, Central Asia and Africa that have been hosting much larger numbers. The number of refugees hosted in Turkey stood at over 2.5 million, and the numbers in Pakistan and Lebanon exceeded one million (UNHCR, 2016).

As shown in Figure 1(b), in late-2016 the number of asylum seekers dropped to its pre-2014 levels. The reasons for this drop were the closing of several borders along the Balkan Route and, most importantly, an agreement between the EU and Turkey in 2016, in which Turkey agreed to prevent migrants from moving to the EU in exchange for a payment of six billion Euro and an agreement that the EU would re-settle one Syrian refugee from Turkey in exchange for every non-Syrian migrant who is turned away by the EU. (Kiris ̧ci, 2021).<sup>1</sup> Despite the many challenges of integrating refugees in the labor market, the situation five years later paints a rather optimistic picture. The government invested heavily in language training, which allowed many refugees to acquire language skills that are critical for the integration in the labor market. Survey data shows that in 2018 around 50% of all refugees were in employment
# **Table 6. Percentage of firms in each quartile of predicted probability of formality by group, ordered by quartile one, pooled ELMPS 2012 and 2018**

|**Profil**<br>**Group**|**e**<br> <br>**Firm**<br>**Size**|<br>**Firm Age**|**Capital**|**Non-rel. out of**<br>**HH hired**|<br>**Quartile of Ln(Reven**<br>**per Worker)**|**ue**<br>**Owner's Education**|**N**<br>**(Obs**|**.)**<br>**% of**<br>**Informal**<br>**Firms in**<br>**Group**|**% of Firms in Each**<br>**Quartile of**<br>**Predicted**<br>**Probability**|
|---|---|---|---|---|---|---|---|---|---|
||||||||||Q1 Q2 Q3 Q4|
|1|1|Less than 5<br>years|All capital (Aggregate)|No|1 & 2 (Aggregate)|Below secondary|72|6.7|80.9 13.9 3.6 1.7|
|2|1|Less than 5<br>years|<5K|No|1|Secondary|28|2.6|67.6 32.4 0.0 0.0|
(iii), the poverty line used for estimating poverty rates in EICV3 is based on EICV1 data and valued at January 2001 prices (RWF 64,000), while the poverty line used for estimating poverty rates in EICV4 is based on EICV4 data and valued at January 2014 prices (RWF 159,375). Thus, condition (iii) will hold if the two poverty lines satisfy the following equation:</mark> To check whether this is the case, we need an estimate of the inflation rate between January 2001 and ����� January 2014, i.e. π����� . This is not directly available from the data. We therefore split this into two components; the inflation rate between January 2001 and January 2011 and the inflation rate between January 2011 and January 2014, i.e.

����� There are two sources of data available for each of these inflation rates. In the case of π����� , we can either use the COLI estimated in NISR (2015) or the WDI (World Development Indicators) 2018 data. In case of the former, we take a population weighted average of the COLIs across all regions for January 2011, and ����� ������ � approximate π����� � �π����� ����. Using EICV3 data, this comes out to be 2.05 (see Appendix table A1). Interestingly, this number is the same as the inflation rate from WDI.

> 9 Strictly speaking, the non-food COLI for EICV3 is first estimated for January 2011 as the base month and then adjusted to January 2001 as the base month when aggregating it with the food COLI (NISR 2012).

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Finally, in Panel D of Table 8 I revisit a potential source of heterogeneity in multipliers discussed in Kraay (2012), based on cross-country differences in the extent to which government spending is aidfinanced. An important component of the neoclassical mechanism for a positive government spending multiplier operates through wealth effects: when spending increases, private agents are poorer by the present value of the current and future tax obligations required to finance the increase in spending. According to this mechanism, private agents react by consuming less, investing more, and providing more labour input, so that output increases. The key point here is that the magnitude of this wealth effect depends on the size of the burden of current and future tax obligations associated with the increase in government spending. This burden is smaller in countries where a greater proportion of government spending is financed by aid flows from abroad that do not need to be repaid, and as a result, the neoclassical mechanism predicts a smaller spending multiplier in more aid-dependent countries.

To investigate this possibility in this large set of developing countries, I divide each sample in half at the median level of official development assistance (ODA) as a fraction of GDP, and then estimate spending multipliers separately in the two subsamples. The OLS estimates of the multiplier display the pattern suggested by the theory, and are consistently larger in the low-aid sample. However, the differences are not large. Turning to the 2SLS estimates, in the IDA sample of countries I do again find the same pattern, with a larger multiplier in the less aid-dependent subsample of these IDA countries (0.59 versus 0.43 in the more aid-dependent subsample). Unfortunately, however, in the full and high disbursement samples of countries, identification is extremely weak in the less aid-dependent groups. As a result, the multipliers are very imprecisely estimated, to the point of being meaningless, and it is not possible to draw any conclusion about differences in multipliers by the degree of aid dependence.

Summing up, the novel DRS loan-level data on
raised considerably, especially pensions to farmers, while coverage of pension rights was also extended to returning immigrants with no record of contributions to social security programs. Another source of increased government spending was support to loss-making public corporations. The combined deficit of these entities rose from 2 to 5.5 percent of GNP between 1979 and 1985. In addition, many private sector firms were unable to meet the competitive challenge of European firms that followed the dismantling of tariffs (Giannitsis 1993). Many of these firms were declared “problematic” and relied on financial support from state-controlled banks for their continuing survival.

The effect of these policies was a massive increase in the public sector borrowing requirement that reached 17.7 percent of GNP by 1985. The level of general government debt rose from 39 percent of GDP in 1980 to 73 percent in 1985.<sup>14</sup> External debt grew from 16 percent of total debt in 1980 to 31 percent in 1985. Most of the external debt was of a long-term nature, mostly syndicated loans from international banks, with little exposure to interest rate and refinancing risk. However, being denominated in foreign currency, it was exposed to foreign currency risk and suffered from the periodic devaluations of

> 14 Data from the 1987 OECD survey show that on a net basis the general government debt rose from 27 percent of GNP in 1979 to 63 percent in 1985. Adding the debt of public corporations brought the total to  85 percent of GNP, which was one of the highest ratios in the OECD area. Particularly disquieting was the speed at which the total public debt had grown, having soared in relation to GNP by nearly 55 percentage points between 1979 and 1985.

25
# **_(b) Elasticity-based approach_**

An elasticity-based approach recognizes that the remittances may grow faster than incomes in the host country, i.e. the elasticity of remittances with respect to the host country may be greater than 1 (Ratha, Mohapatra and Silwal 2010). For example, during the pre-crisis period, remittances grew faster than GDP of remittance-source countries because of a number of factors, including improvements in remittance technologies, falling costs, and steady increase in migrant stocks. The World Bank has used elasticitybased estimates in its most recent projections. Some recent studies have used similar elasticity-based estimates for estimating remittance flows to specific regions that have gaps in official data on remittances.<sup>6</sup> Consistent with the view that remittances would grow at a lower, more “sustainable” rate, in the post-crisis period (2010 and beyond), the elasticity of remittances ( _Rj_ ) with respect to migrant incomes ( _MYj_ ) is assumed to be half of the precrisis period (2003-08), with an upper bound of 3 and lower bound of 1. These remittance elasticities are used to forecast remittance outflows from each remittance-source country in 2010 and beyond using the latest available forecasts of GDP from the World Bank, using the following formula: The forecasts for remittance inflows for country _i_ were calculated by adding up the share of remittances to country _i_ in the remittance outflows from country _j_ ( _rij_ ) for all remittance-source countries.

In later versions, the bilateral migration matrix developed by Ratha and Shaw (2007) was updated with immigrant stock data from various sources to provide the most

> 6 In the absence of timely and reliable official data on remittances for most Sub-Saharan African countries, Barajas and others (2010) use the elasticity of remittances to income computed by Singh, Haacker and Lee (2009) and the IMF’s GDP estimates to estimate the extent of decline in remittance flows to Sub-Saharan Africa in 2009.

8
more time while cooking (with little children at their side), than in comparison with older children and adult males, who spend more time outdoors.

**<u>Table 5.1: Health Risks of Indoor Air Pollution</u>**

||**Odds Ra**|**tios(OR)**|
|---|---|---|
||“Low”|“High”|
|Acute RespiratoryIllness(ARI)|1.9|2.7|
|Chronic obstructive pulmonary disease (COPD)|2.3|4.8|
|_Source:_Desai et al (2004).|||

The NFHS-3 reports that 90 percent of rural and 32 percent of urban households use solid fuels for cooking in India. The national weighted average is about 71 percent.

To estimate the health effects of indoor air pollution from the odds ratios in Table 5.1, baseline data for ARI and COPD need to be established. These data are presented in Table 5.2, along with unit figures for disability adjusted life years (DALYs) lost to illness and mortality. The hypothetical level against which damages are calculates is a situation in which there is no exposure to indoor air pollution and the odds ratio is one.

**Table** **<u>5.2: Baseline Data for Estimating Health Impacts</u>**

||**Baseline**||**Source:**|
|---|---|---|---|
||Urban|Rural||
|Female COPD mortality rate (% of total female<br>deaths)|9.|5%|WHO estimate for India,<br>Shibuya et al (2001)|
|Female COPD incidence rate(per 100 thousand)||79||
|ARI 2-week Prevalence in Children under 5years|22%|