rafmacalaba/datause-encoder-data huggingface dataset:
- 20 -

became an attractive source to finance needed urban investments.U' However, the overwhelming proportion of foreign loans was requested for central, rather than for local government agencies. In Lat;n American countries, national laws virtually exclude subnational governments from direct access to external borrowing. In fact, since foreign exchange must be rationed, both the national planning authorities and the foreign lenders prefer to direct external credit to public enterprises because their functions generally involve a foreign component and because they view the supervisory activities associated with external loans as a means to introduce better pricing and financial discipline. Therefore, little external borrowing was made availabla to subnational entities and it was mostly limited to capital expenditures. Domestic borrowing was also viewed as inappropriate for city governments because it could induce improvident local administrators to undertake expenditure decisions which would restrict flexibility in their future budgets and leave them vulnerable to the uncertainties of the market and exchange rates.

2.04 Expenditure Effects of the Recession. Yet, the increasing demands of urbanization and the job protection policies in force in most Latin American countries allowed for no significant reduction in recurrent expenditures. The initial reluctance of many national governments to participate in financing the basic operating expenditures of local authorities was gradually overcome by the realization that this would disproportionately penalize the poorest areas of the countries. In Argentina or Brazil for instance, it soon became a necessity to avoid unwanted reductions of nationally valued activities like education and health services or social security payments. New capital formation, which was more easily deferrable, was restrained for an extended period, aggravating the already sizeable backlog of unmet demand for physical facilities. Moreover, the reduced volume of new investments was accompanied by a decline of maintenance expenditures of the existing capital stock, accelerating replacement needs.

17/ The progressive increase in World Bank Loans is shown below: Table 2.3 World Bank Lending in Social Sectors to LAC countries

||1978-82|* 1983|<br>1986|<br>1985|<br>1986|<br>1987|<br>1988|
|---|---|---|---|---|---|---|---|
|Urban Development|<br>177.6|46.2|191.2|86.9|369.5|325.0|<br>764.0|
|Water Supply and||||||||
|Sewerage|204.5|424.2|<br>28.6|163.9|175.0|64.0|<br>252.3|
|Education|62.6|<br>59.8|<br>68.0|195.8|10.0|<br>84.9|<br>88.3|
|Population, Health||||||||
|& Nutrition|_7.6|33.5|<br>5.5|-|96.0|-.QJ.|<br>109.0|
||452.3|563.7|345.3|446.5|650.5|483.9|1.213.6|
|*Annual Average||||||||

Source: The World Bank Annual Report, 1988.
is reduced due to the employment guarantee, the share of total inputs allocated to each of the crops approaches the ratio of the deterministic scenario. Interestingly, this effect holds independently of whether credit constraints reduce total input allocation or not.<sup>17</sup>

# **3 Data**

When estimating the insurance effect of the NREGS, one must take into account considerable variation in the quality of implementation of the program across states (Dutta et al., 2012). The section above highlighted the importance of households’ expectations about future income streams. Therefore it seems plausible to observe insurance effects only in states in which the demand for employment has been sufficiently met, already in the early years of program implementation.

Given these considerations, the model specified above is tested using the Young Lives Survey (YLS) data for Andhra Pradesh. Andhra Pradesh is particularly suited to studying the question of interest because it is one of the best performing states in India in terms of the number of workdays generated per household and meeting the demand for work (Dutta et al., 2012). Regarding outreach, only Chhattisgarh, West Bengal, Madya Pradesh and Rajasthan reached higher proportions of rural households in the financial year 2009/10.<sup>18</sup> The YLS data set covers 3,019 households living in six different districts, 17 subdistricts (blocks) and 87 villages. The selection process of districts for the YLS ensured that all three geographical regions were surveyed, as too were the poor and non-poor districts of each region, such that the YLS is broadly representative of the population of Andhra Pradesh (Galab et al., 2011).<sup>19</sup> Three rounds of interviews have been conducted

> 17C.f. appendix A for a detailed derivation of this result.

> 18At the same time, Andhra Pradesh has been a forerunner in terms of innovative approaches to the implementation of the NREGS. First, it has a lot of experience with performing social audits to increase accountability within the scheme. Second, it was one of the first states to cooperate with IT enterprises to strengthen the efficiency of administrative processes. To increase transparency, entries on muster rolls and the number of workdays generated per job card holder etc. are publicly accessible. Nonetheless, the program continues to be implemented in a top-down manner in Andhra Pradesh. Usually, work is not generated upon demand, rather work applications are only accepted if there is work available (c.f. (Desai and Joshi, 2015; Muralidharan, Niehaus, and Sukhtankar, forthcoming).

> 19This is in reference to the State of Andhra Pradesh in 2013, prior to its division into the states of

11
Finally, cash transfer programs may improve children’s health, thus increasing their capacity for work _and_ school participation. Indeed, Kandpal et al. (2016) find that _Pantawid_ helps to keep the youngest children healthy, one of the stated aims of the program. In treatment villages, children up to the age of 5 (for whom extensive health data, including anthropometric indicators, were collected) were less likely to be stunted, more likely to eat protein-rich food, and more likely to receive preventative health services. Older children’s health may have improved due to increased household expenditure on health and nutrition. The program also required regular deworming for older children, which may have improved schooling outcomes (Baird et al., 2016; Bleakley, 2007; Miguel and Kremer, 2004). If this mechanism were driving our results, we would expect improvements in child health to have similar effects on work for pay outside the household and work without pay inside the household. However, we do not observe an impact on the latter. In addition, Appendix Table 10 shows no significant association between parent-reported offer of deworming pills at school to children aged 10 to 14 and child labor supply in the control areas. Deworming was offered at school, with 75 percent of 10-14 year olds in control areas being offered them; we do not find any effect of the deworming offer on regular school attendance. Moreover, as we discuss below, similar programs in other contexts, including _Prospera_ in Mexico, improved child health without increasing child work.

_The impact of more generous education subsidies_ The evidence presented above suggests that the increase in child work is largely the result of a partial grant for the full cost of education. This observed increase in children’s participation in paid work contrasts with evidence from other cash transfer programs, which document either a significant decrease or no change in child labor as a result of the transfer (reviewed in de Hoop and Rosati, 2014). However, Table 8 shows that, in virtually all of the programs studied, the transfer amount exceeded the full cost of education. The Philippines thus appears to be the first CCT program to experience a slight rise in the rate of child work, and is one of the few that did not fully cover the cost of education.

21
**Figure 7: Probability density distribution of PSI and power outages reported by IHDS**

<!-- Start of picture text --> Kernel density estimate Kernel density estimate<br>-2 0 2 4 5 10 15 20 25<br>psi outage<br>kernel = epanechnikov, bandwidth = 0.1009 kernel = epanechnikov, bandwidth = 0.7083<br>.2<br>1<br>.8<br>.15<br>.6<br>.1<br>Density Density<br>.4<br>.05<br>.2<br>0 0<br><!-- End of picture text -->

# **V. Variations in Power Outages across India**

Table 4 ranks all states by the mean level of PSI in 2013. In this section, we describe anecdotal evidence which comports with these rankings. Power supply reliability as measured by PSI was highest in West Bengal, a state that has been recognized for its progress in reforming its power sector.<sup>4</sup> In 2013, it recorded a power surplus for the first time (though much of it was driven by a drop in industrial demand). Speaking to a reporter, the principal secretary for West Bengal’s department of power, Malay Kumar De, said, “Political interference at the local level is totally absent here. We don’t have a power rationing or shortage situation.”<sup>5</sup> Areas with severe power reliability problems have also received media attention. For example, a news article on the ongoing load shedding situation in Madhya Pradesh identified particularly poor service in Harda and Hoshangabad districts which had been receiving only 10 and 13 hours of power a day, respectively.<sup>6</sup> These

> 4 World Bank. 2009. _West Bengal Power Sector Reforms: Lessons Learnt and Unfinished Agenda._ Washington, DC. <https://openknowledge.worldbank.org/handle/10986/12375>

> 5 “Power thieves prosper in India’s patronage-based democracy.” _Washington Post_ . 4 October 2012.

> 6 “No end to state’s power woes.” _Times of India_ . 27 August 2014.

17
to be ill-suited to corn or soy production in the temperate zones where much of the world’s corn and soybeans are grown. However, on Asian croplands where two or three crops are grown in succession each year, wheat can be substituted for rice as a dry-season irrigated crop when its relative price increases.

# **Prices of fertilizers and fuels**

Worldwide adoption of modern high-yield plant varieties and a decline in the opportunities for expansion of cultivated area have increased the demand for fertilizers. Prices of some fertilizers rose faster than any agricultural commodity price in the last few years, reflecting short run supply constraints, energy costs, transport costs, and a 100% export tax imposed by China on all fertilizers.<sup>5</sup> Recently, maize farmers and ethanol producers in the United States have blamed fertilizer and oil prices for high grain prices.

The case of potash, a major fertilizer ingredient, is instructive. As Figure 8 shows, potash prices did not really form a spike until well into 2008, after most of that year’s crops were in the ground. It is clear that grain prices associated with previous harvests preceded fertilizer price movements, rather than vice versa. Although there have been reports that farmers are reducing fertilizer applications, worldwide fertilizer supply is not likely to have diminished. There may of course have been reallocations to biofuel production and high-value crops. Reductions in fertilizer use should show up as yield or acreage reductions, but yields in 2008 generally appear to have been good.

Given a few years to invest in capacity, fertilizer supplies can expand. But for fertilizers dependent on minerals deposits, increased demand might generate sustained higher prices and greater rents rather than higher supply. Injudicious advice to further subsidize particular uses of such inelastically supplied fertilizers will, if heeded, certainly increase the profits of their producers. Subsidies will have little effect on supply in the short run, but will divert global supplies from unsubsidized uses to less efficient subsidized uses, reducing overall production efficiency.

> 5 Bloomberg.com April 17, 2008 (http://www.bloomberg.com/apps/news?pid=20601082&sid=a2QZ._5PDbEs, last accessed July 9, 2009).

– 12 –
construction/other services sector firms was obtained from the implementing contractor and largely based on firms registered with AISA. The sample used in the paper is based on a total number of 410 firms, with 34% from manufacturing, 16% from retail, 18% from construction and remaining 33% from other sectors (see Table 1 for details). Around two-thirds of the firms in the sample are small (5 to 19 employees), another one-quarter being medium sized (20 to 99 employees) while the remaining are large (more than 99 employees) in size. Majority of firms are from Kabul representing almost a third of the sample. Mazar-eSharif has the second highest number of firms at 18%. The rest of the regions, Herat, Kandahar, and Jalalabad each have 17% of firms.

**Table 1: Descriptive Statistics of Dataset**

||**ES2014 (Formal)**|**ES2008 (Formal)**|**IES2008 (Informal)**|
|---|---|---|---|
|**Total firms**|**410**|**647**|**419**|
|**Sector (share inpercent)**<br>||||
|Manufacturing|34|19|25|
|Retail|16|16|25|
|Construction|18|28|11|
|OtherServices|33|37|38|
|**Size (share inpercent)**<br>||||
|Lessthan 5|0|2|13|
|Small(5 – 19 employees)|69|62|78|
|Medium(20 –99 employees)|25|26|8|
|Large (Morethan99 employees)|6|10|2|
|**Region (share inpercent)**||||
|Kabul|31|31|25|
|Kandahar|17|12|11|
|Herat|17|13|12|
|Jalalabad|17|11|14|
|Mazar-e-Sharif|18|14|13|
|Other|0|20|26|

_Source: World Bank Enterprise Surveys 2014, 2008 and World Bank Informal Enterprise Survey 2008._ Data from 2008 consist of firms from both the formal and informal sectors. Formal firms are defined as firms that are registered with a central government body i.e. AISA and/or any Government Ministry, such as the Ministry of Commerce, Ministry of Economy, Ministry of Education, and so on. Informal firms, on the other hand, are firms not registered with a central government body, or with any other organization except for local municipality, business association or union. The sample proposition was split between 60% formal enterprises and 40% informal enterprises. The sample of formal firms was sourced from AISA, list of firms interviewed in a previous ES and other local sources (e.g. NGOs, local AISA and/or ACCI (Afghanistan Chamber of Commerce and Industries)). For informal firms, local 9
Figure **10:** Financial Consequences in the U.S. of Clinton Deficit Reduction Program and Maastricht Agreement <!-- Start of picture text --> U.S. Nominal Effective Exchange Rote U.S. Inflation<br>ly 7 -- D- 5 0.8<br>a -I!~~~~~~<br>j...~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~0.4<br>0.2<br>I i:'- .2 ~ ~ ,.a.-.X-5 el A E<br>_ | 1 ~~~~~~~~~~~~~~~~-& -E - C4 -&C<br>114 1994o Ih 2000 2 00* f a 4 200 2010 ' 1 liai ia o 2002 ceo 204 IZ09 2n04<br>Year Year<br>U.S. Share Market Value U.S. 10-Year Bond Rate<br>S _4,-&F-iS____6--<F- 12 F 0.} -------------------- ---------<br>YeorAYcar<br>02.6<br>It 0.3*re ~ N _^---A-s 1 ilF<br>et~~ ~~~~~ ~ ~~~~~~~~~~~~~ . E--- 1i 6. A<br>rYo -eor<br>19§4 1OCZ 1902 2QCC W02 20dJ 200 2002 tO10 2012 102< loss l9§a 2ooo zeW3 250 =6c 7Xola "12<br>_.~~ _. __<br><!-- End of picture text -->
Brazil’s absence form global production networks and resulting density of domestic value can only in part be explained by the relative distance (geographical as well as institutional) from major economic centers – like other LAC countries. However it is also in large part a result of policy decisions past and present on trade and local content (World Bank, 2014; Canuto 2014).

**Figure 9: Domestic value added in all exports Figure 10: Domestic value added in** **<u>(percent)</u> manufacturing export (percent)**

<!-- Start of picture text --> Russian Fed. Brazil<br>Brazil United States<br>United States Indonesia<br>Australia<br>Japan<br>Norway<br>Indonesia Norway<br>Japan Australia<br>South Africa South Africa<br>Chile China<br>New Zealand<br>New Zealand<br>Canada<br>Turkey Chile<br>India Canada<br>China Turkey<br>Mexico EU<br>EU<br>Korea<br>Israel<br>Iceland Mexico<br>Korea Israel<br>0 20 40 60 80 100 0 20 40 60 80 100<br><!-- End of picture text --> Source: World Bank 2014.

The high level of domestic value added in exports shows that the fragmentation of the production process along cross-border value chains, a very important part of the second wave of globalization (Baldwin, 2011), has largely bypassed Brazil.

In part this can be explained by the difficulty encountered by firms attempting to trade across Brazil’s borders. Brazil’s precarious logistics and high transaction costs related to international trade are incompatible with the logic of cross-border value chains.

Over the past decade Brazilian firms have also faced serious competitiveness challenges, such as real appreciation and defensive trade policy reactions (Canuto ,Cavallari, Reis 2013a, Canuto, Cavallari, Reis, 2013b). This means that only the most efficient firms or larger firms benefitting from significant 10
Table 3. Preference for Equality (Ordered Probit): 1999-2001 (Robust z-statistics in parentheses)

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Age<sup>1</sup>|-3.5|-6.243|-5.711|-5.854|
||(1.82)|(3.33)**|(3.05)**|(3.05)**|
|Age-squared<sup>1</sup>|29.472|56.717|49.115|53.623|
||(1.44)<br>|(2.82)**<br>|(2.44)*<br>|(2.60)**<br>|
|Female|-0.045|-0.03|-0.035|-0.029|
||(4.32)**|(2.93)**|(3.45)**|(2.77)**|
|No. of Children|0.001|0.018|0.017|0.016|
||(0.16)<br>|(5.09)**<br>|(4.95)**<br>|(4.50)**<br>|
|Married|0.022|-0.013|-0.006|-0.03|
||(1.88)|(1.13)|(0.54)|(2.62)**|
|_Education_|||||
|Incomplete Technical/Vocation Education|0.033|0.072|0.063|0.094|
||(1.66)|(3.73)**|(3.26)**|(4.90)**|
|Complete Technical/Vocation Education|0.141|0.215|0.19|0.212|
||(8.28)**|(13.09)**|(11.61)**|(12.63)**|
|Incomplete Secondary Education|0.113|0.173|0.119|0.113|
||(5.83)**|(9.44)**|(6.46)**|(6.02)**|
|Complete Secondary Education|0.171<br>|0.193<br>|0.174<br>|0.163<br>|
||(10.49)**|(12.71)**|(11.43)**|(10.24)**|
|Incomplete University Education|0.214|0.266|0.254|0.258|
||(11.01)**|(14.33)**|(13.67)**|(13.52)**|
|Complete University Education|0.255|0.326|0.292|0.278|
||(14.77)**|(20.17)**|(18.01)**|(16.54)**|
|_Income_|||||
|Lower Income|-0.039|-0.017|-0.024|-0.023|
||(3.20)**|(1.40)|(1.98)*|(1.86)|
|Higher Income|0.113<br>(9.40)**|0.119<br>(10.34)**|0.123<br>(10.65)**|0.115<br>(9.62)**|
|_Labor Force Status_|||||
|Part-Time Employed|-0.039|-0.04|-0.058|-0.059|
||(1.89)|(2.01)*|(2.93)**|(2.87)**|
|Self-Employed|0.094|0.055|0.063|0.045|
||(5.50)**|(3.25)**|(3.73)**|(2.61)**|
|Unemployed|-0.072<br>|-0.106<br>|-0.098<br>|-0.092<br>|
||(3.34)**|(5.03)**|(4.69)**|(4.30)**|
|Retired|(0.07)|(0.11)|(0.10)|(0.12)|
||(3.68)**|(5.40)**|(5.33)**|(5.95)**|
|Other|-0.026<br>|-0.056<br>|-0.049<br>|-0.071<br>|
||(1.77)|(3.96)**|(3.48)**|(4.89)**|
|_Country Group Dummies _<sup>_2_</sup>|||||
|Post-socialist economies||0.092|||
|||(8.16)**|||
|Developing countries||0.147|0.142|0.174|
|||(12.63)**|(12.14)**|(9.00)**|
|Central and Eastern Europe|||-0.061<br>475**|-0.194<br>974**|
|Baltics|||(.)<br>0.09<br>**|(.)<br>0.03<br>|
|Other Former Soviet Union (FSU)|||(2.84)<br>0.423<br>|(0.86)<br>0.316<br>|
|_Other country-level control variables_|||(24.71)**|(13.09)**|
|Per capita income (in PPP terms)<sup>1</sup>||||-0.004<br>|
|||||(5.70)**|
|Gini coefficient||||-0.01<br>|
|||||(11.94)**|
|Observations|63,874|63,874|63,874|61,281|
|Country Dummies|Yes|No|No|No|

* significant at 5 percent; ** significant at 1 percent Note: Dependent variable is a 10-point scale from 1 (Preference for equality) to 10 (Preference for inequality). 1Age and per capita income divided by 1,000, to produce sufficently large coefficients for display.

2Where country dummies are ised, the benchmark country is the U.S. Where country group dummies are used, the benchmark group are the advanced economies.

14
# Social transfer multipliers in developed and emerging countries: The role of hand-to-mouth consumers<sup>�</sup>

Jessica Bracco Luciana Galeano Universidad Nacional de La Plata University of Michigan Pedro Juarros Daniel Riera-Crichton Georgetown University World Bank Guillermo Vuletin<sup>y</sup> World Bank April 13, 2021 Abstract This paper estimates the macroeconomic e¤ects of social transfer payments to individuals for a sample of 23 developed and Latin American countries. The ...ndings show that the social transfer multiplier is 0.3 in developed countries, but 0.9 in Latin American economies. The paper studies the role of hand-to-mouth consumers, who have no access to ...nancial markets and a high marginal propensity to consume, as a ...rst order factor to explain the heterogeneity in the size of social transfer multipliers. Using survey-based data from the Global Findex dataset, the paper ...nds that the average share of the population living hand-to-mouth is 23 percent in developed economies versus 60 percent in Latin American countries. This evidence is interpreted with a two-agent New Keynesian model. The ...ndings show that the di¤erence in the share of hand-to-mouth consumers explains 80 to 90 percent of the di¤erence in the estimated social transfer multipliers. The paper also documents that the share of hand-to-mouth individuals in emerging countries is in general 47 percent which suggests that a larger social transfer multiplier may be expected for this type of economy.

Keywords: ...scal transfer, social transfer, ...scal policy, ...scal stimulus, government spending, multiplier, hand-to-mouth, emerging markets.

JEL Classi...cation: E62, E63.

> �We would like to thank Martin Ardanaz, Leopoldo Avellan, Yan Carrière-Swallow, Fernando Castaño, Manuela Cerimelo, Antonio David, Guillermo Falcone, Roberta Gatti, Margaret Grosh, Chadi Habib, Alejandro Izquierdo, Norman Loayza, Nora Lustig, Jorge Neyro, Ha Nguyen, Steven Pennings, Carola Pessino, Emilio Pineda, Francisco Pizzi, Andrew Powell, Martin Rama, Diego Rojas, Oscar Valencia, and Lucila Venturi for helpful discussions. We would also like to thank seminar participants at the World Bank, the Inter-American Development Bank, and Universidad Nacional de La Plata. We also thank Ivana Benzaquen, Jose Andree Camarena, and Irene Ezran for excellent research assistance. The views expressed are those of the authors and do not necessarily represent the views of the World Bank, its Executive Board, or its management.

> yCorresponding author. Email: gvuletin@worldbank.org. Website: www.guillermovuletin.com