rafmacalaba/datause-encoder-data huggingface dataset:
income groups, and it is a key driver of the lower proportion of GDP devoted to public spending on education outlined in Figure 3 (see Box 6).<sup>6</sup>

# **Box 6: Key Drivers of Overall Levels of Public Spending**

Governments mainly finance public spending through tax and other domestic revenue streams, concessional aid, and net borrowing. The combination of sourcing for public spending will depend on a country’s specific context and overall level of development. On the whole, tax revenues tend to be higher in wealthier countries. For example, in 2014 **–** 17, average tax revenues for low-income countries were 15 percent of GDP compared to 19 percent in high-income countries.

The gap in total government revenues (from tax revenues, social contributions, and other revenues such as rent, **–** fees, and income from property, but excluding grants) is much bigger between these two income groups. In 2014 17, average total government revenues were 31 percent of GDP in high-income countries compared to only 18 percent in low-income countries. Overall levels of deficit financing also differ among income groups. For example, in 2014 **–** 17 government budget deficits (net borrowing) were 3 percent of GDP on average in low-income countries compared to 1.4 percent and 2.6 percent in lower-middle and upper-middle income countries, respectively.

# **Total Official Development Assistance (ODA) as a Percentage of GDP (%), 2002–2017**

||2002**–**05|2006**–**09|2010**–**13|2014**–**17|
|---|---|---|---|---|
|**Income Groups**|||||
|LIC|1.1|1.1|0.9|0.8|
|LMIC|0.9|0.9|0.7|0.6|
|UMIC|0.5|0.6|0.6|0.5|
|HIC|0.1|0.1|0.1|0.1|
|**Regions**|||||
|AFR|1.0|0.9|0.7|0.6|
|ECA|0.2|0.2|0.2|0.2|
|LCR|0.2|0.2|0.1|0.1|
|SAR|0.6|0.7|0.5|0.3|
|EAP|1.9|2.1|1.9|1.7|
|MNA|0.4|0.6|0.5|0.5|

_Source:_ World Bank calculations using OECD Creditor Reporting System and World Bank online databases.

_Note:_ Overseas development assistance is measured as gross disbursements, and figures only include countries that received some assistance. Income groups are defined by country income group classification in 2017. LIC = low-income country, LMIC = lower-middle-income country, UMIC = upper-middle-income country, and HIC = high-income country. AFR = Africa, ECA = Europe and Central Asia, LCR = Latin America and Caribbean, SAR = South Asia, EAP = East Asia and the Pacific, and MNA = Middle East and North Africa.

While overall levels of official development assistance (ODA) have been declining over the last 15 years, such aid provides an important source of education funding for low- and middle-income countries (see table above). Given average levels of public spending on education, ODA on average made up about 21 percent of total public education spending in low-income countries. However, this average masks large disparities among different low-income countries. For example, in 2017 Malawi received ODA for education equivalent to 2.4 percent of GDP compared <u>to Madagascar’s 0.4 percent.</u>

> 6 Average public spending as a percentage of GDP in lower-middle income countries was 24 percent in 2014 **–** 17 (see Annex Table A2).

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||•<br>PNC for mother received from a medically trained provider|
|---|---|
||**Family Planning (FP)**<br>•<br>Use of any FP methods among married women (15- 49 years)<br>•<br>Use of Modern FP methods among married women (15-49 years)|
||**Vaccination coverage**<br>•<br>12–23 months old children receiving all basic vaccinations (i.e., BCG, three doses of<br>pentavalent (DPT-HepB-Hib), three doses of oral polio vaccine, and one dose of<br>measles vaccine)|
||**Care-seeking for sick under-5 children**<br>•<br>Children with diarrhea treated at a facility<br>•<br>Children with Acute Respiratory Infection (ARI) treated at a facility<br>•<br>Children with fever treated at a facility|
|Quality of care<sup>1</sup>|**Adequate ANC quality**(adequate quality indicates – a woman reported of receiving all given<br>below services in one visit)<br>•<br>Weight measured during ANC<br>•<br>BP measured during ANC<br>•<br>Urine sample taken for ANC<br>•<br>Blood sample taken during ANC<br>•<br>Ultra-sonogram conducted during ANC<br>•<br>Informed of signs of pregnancy complications during ANC|
||**Adequate quality for newborn PNC (**adequate quality indicates – a woman reported of her baby<br>receiving all given below services in one visit).<br>•<br>Examined the cord<br>•<br>Counselled on danger signs<br>•<br>Assessed temperature<br>•<br>Counselled mother on feeding<br>•<br>Observed feeding<br>•<br>Assessed weight|
||**Adequate essential newborn care at birth (**adequacy indicates – a woman reported of her baby<br>receiving all given below services at birth).<br>•<br>use of a safe delivery kit/ bag or boiled blade<br>•<br>nothing applied to the cord or only chlorhexidine applied<br>•<br>after the cord is cut and tied, cord dried within 5 minutes after birth<br>•<br>bathing delayed 72 hours or more<br>•<br>immediate breastfeeding|
|Health/nutrition<br>outcomes|<br>**Under-five Child nutrition**<br>•<br>Stunting (i.e., more than 2 standard deviations below the median for height-for-age)<br>•<br>Wasting (i.e., more than 2 standard deviations below the median for weight-for-height)<br>•<br>Underweight (i.e., less than 2 standard deviations below the median for weight-for-age)<br>**Source**: DHS|

**Table 3: Demand-side determinants***

|**Variables**|
|---|
|Household access toimproved sanitation facilities|
|Household access to improved drinking water|
|Household access to hand washing|
|Household wealth status in quintile|
|Age of mother at childbirth|
|Age at marriage|
|Education status|
|Employment status|

1 Quality of care indices consisted of equally weighted averages of their component variables.

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for European exporters.<sup>1</sup> Since 2009, trade liberalization on the Serbian side has been following a gradual and predictable liberalization schedule and by 2013, most EU imports enter tariff-free. The EU is a main market for inputs for Serbian firms, and its importance is further amplified as European foreign direct investment locates in Serbia to produce for the European market, especially after this trade agreement came into force. One key example is the decision of Fiat, an Italian car manufacturer, to locate its worldwide production of the car model _Fiat500_ in Serbia in 2010, which requires them to import components from many countries. Serbia also signed another trade agreement with its neighbors in the Western Balkans regions in 2006 but these markets are less important as input sources.

We show that Serbian importers are increasing in their intensive and extensive margins between 2006 and 2015, using data on Serbian firms from the Business Registries Agency (BRA) combined with data provided by the Serbian Customs Administration. Table 1 presents the total value of Serbian imports between 2006 and 2015 as well as the average imports of a firm-origin country pair and the total number of firm-origin country pairs. Over the period, all three measures are increasing, which suggests that the increase in total imports is due to both increases in the intensive margin (value of firms’ imports from each of their source countries) and extensive margin (number of countries firms source from). Serbian firms are increasingly making sourcing decisions that cross international borders. The sourcing choice of the firm is significant because the basket of inputs and sources it chooses impact production costs, product quality, and subsequently the competitiveness of the firm. Both margins are incorporated in our empirical framework, which we describe in detail below. The increases in the intensive margin are incorporated into firm learning (with a lag, as in Fernandes and Tang (2014)) because changes in other firms’ imports from a source act as a signal to the non-importers about the potential savings and quality of inputs from that source. Changes to the extensive margin, that is, firms entering into new source markets for their inputs, represent the outcome that our analysis seeks to explain through

> 1Customs duties for all industrial and agricultural products from Serbia were abolished by the EU in 2000 with the application of the Autonomous Trade Measures.

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M2/GDP and LL/GDP were .62% and .90%, respectively -- figures substantially similar to those for pre-1990 FSALs.<sup>13</sup>

**Table 2.1**

|**Cha**<br>|**nges**in Performance<br>FS<br>|Indicators Over Tim<br>ALs<br>|e, FSALs and Non-F<br>**Non-**<br>|SALs<br>**FSALs**<br>|
|---|---|---|---|---|
|Indicator|Pre-1990|Post-1990|Pre-1990|Post-1990|
||(% Change, 3 Yrs.<br>After Intervention)|(% Change, 3 Yrs.<br>After Intervention)|(% Change, 3 Yrs.<br>After Intervention)|(% Change, 3 Yrs.<br>After Intervention)|
|**As a %**of GDP:|||||
|M2|+5.43 (6.41)*|+3.09 (5.46)|-1.17 (4.30)|+2.78 (7.25)|
|Liquid Liabilities<br>|<br>+6.32 (6.90)<br> <br>|-0.25(7.12)<br>|+1.03 (2.10)<br>|+4.47 (8.74)<br>|
|Dep Bank Pr Cred|<br>+4.38 (8.43)|-0.23 (5.66)|4.48 (2.02)|+0.45(11.3)|
|Non Bank Pr Cred|<br>-0.04 (1.35)|-1.14 (1.68)|-0.66 (1.26)|+0.19 (0.49)|
|Cen Bank Pr Cred|-0.06 (0.19)|-0.04 (0.08)|-1.97 (3.66)|+0.001 (.003)|
|Fixed Cap. Fonn.|+0.06 (2.14)|+3.84 (5.83)|+0.93 (2.72)|-0.28 (4.69)|
|**As a % of GDP**|||||
|**(Outliers**<br>|||||
|**Omitted)'**<sup>**4**</sup>**:**|||||
|M2|+4.13|+1.17|-1.17|+0.62|
|Liquid Liabilities|_+5.00_|-0.25|+1.03|+0.90|
|Dep Bank Pr Cred|<br>+2.22|-0.23|-0.48<br>|+0.45|
|Non Bank Pr Cred|<br>-0.04|-1.14|-0.66|+0.19|
|Cen Bank Pr Cred|-0.06|-0.04|-0.48<br>|+.001<br>|
|Fixed Cap. Form|+0.06|+0.19|+0.93|-0.28|

* Standard Deviations in Parentheses

The only remaining performance indicators that do not tip in favor of pre-1990 FSALs are the average improvement (that is, decline) in central bank credit to the private sector as a percentage of GDP (CB/GDP), which favors pre-1990 non-FSALs, and the figure for fixed capital formation relative to GDP (FCF/GDP), which favors post-1990 13 The average improvements associated with pre-1990 FSALs are, of course, also sensitive to individual observations. Excluding the largest observed improvement from the calculation (namely Mexico, whose improvement on these measures ranged from 1420%), the average change for pre-1990 FSALs in M2/GDP, LL/GDP, and DBPC/GDP was 4.13%, 5.00%, and 2.22%, respectively. These figures are substantially higher than the corrected figures for post-1990 FSALs and all non-FSALs.

**14** As discussed in the text.

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# **4.2. Physical and human capital**

The reform scenarios assume increases in private investment above the 17.7% of GDP in the baseline, based on reforms such as an improved business environment and greater access to credit. In the moderate reform scenario, we assume that private investment will increase to the 75<sup>th</sup> percentile of private investment among high income countries (20.4% of GDP over 2015-19) in the span of 10 years. While private and public investment are perfectly substitutable in the LTGM-NR, the investment rate is formed by combining an increase in private investment with an unchanged 4.7% of GDP rate for public investment (so total investment is 25.1% of GDP). The ambitious reform scenario is similarly calibrated but targets a private investment rate at the 90<sup>th</sup> percentage of HI countries, which results in private investment increasing to 25% of GDP by 2033 (Figure 12) (so total investment at 29.7% of GDP) **.** Increases in investment bring a large boost to growth. Figures 16 and 17 show that improvements in investment are projected to spur GDP growth by 0.5 and 1.1 percentage points on average in the moderate and ambitious reform scenario respectively in the entire period to 2050.

For human capital, we raise levels to match those seen in the 75<sup>th</sup> percentile of high-income countries (HIC). In the moderate scenario, we set targets based on median values from available data for HIC countries, resulting in Expected Years of Schooling at 13.6, Quality at 0.83, Adult Survival Rate at 0.94, and Fraction of Children Under 5 Not Stunted at 0.94.<sup>14</sup> In the ambitious scenario, we aim for even higher targets, aligning with the best values observed in HIC countries. Both moderate and ambitious reforms can enhance the Human Capital Index, but with a delay as illustrated in Figure 13. This delay arises because these reforms influence today's children, who take time to enter the workforce.

**Figure 12. Private Investment to GDP ratio path**

**Figure 13: Human Capital growth path**

<!-- Start of picture text --> 27%<br>25%<br>23%<br>21%<br>19%<br>17%<br>15%<br>2024 2027 2030 2033 2036 2039 2042 2045 2048<br>Baseline Moderate Ambitious<br><!-- End of picture text --> <!-- Start of picture text --> 2.0%<br>1.6%<br>1.2%<br>0.8%<br>0.4%<br>0.0%<br>2024 2027 2030 2033 2036 2039 2042 2045 2048<br>Baseline Moderate Ambitious<br> Source: LTGM simulations using LTGM-HC extension<br><!-- End of picture text --> Source: LTGM simulations using LTGM-HC extension 14 We assume the reforms are implemented immediately through the education and health systems. However, the reforms take some time to have their full effect in Figure 13 because it takes time for healthier and bettereducated children to become more productive workers. Older children who have completed part of their education already are only partially treated.

17
products—using the 6-digit Harmonized System (HS) codes—, destinations/origins, and quantity. Export values are Free on Board (FOB) and import values are cost, insurance, and freight (CIF). To benchmark Argentina’s export performance, we employ the Exporter Dynamics Database (Fernandes, Freund, and Pierola 2016). The data set contains an array of indicators computed from firm-level information on the characteristics and dynamics of exporters at different levels of disaggregation.

We compute the following corresponding indicators for Argentina at the country-year level: number of exporters; average/median size of exporters; number of destinations per exporter; export market shares concentration; entry and exit rates; and survival rates.<sup>3</sup> This is the information used in the next section. In order to estimate the export premiums of exportersimporters, we split the sample between only-exporters and exporter-importers. Following recent literature (Arkolis, Costinot, and Rodriguez-Claire 2012; Pierola, Fernandez, and Farole 2018), we identify exporters that directly import intermediate products or capital goods, identified according the United Nations Broad Economic Classification (BEC). The rest of exporters are considered only-exporters. Figure 1, panel a, shows the evolution over time of the number of firms, by type. The total number of exporters declined significantly between 2007 and 2015. The total fell by 30 percent—around 5,100 firms stopped exporting altogether. Since 2015 the total number of exporters has stagnated at around 9,500 firms.

Exporter-importers dominate the trade landscape in Argentina, in terms of both number of firms and export value. The share of firms that export and import increased from 57 percent in 2007 to 63 percent in 2018. These firms represent the bulk of export value. In 2007 they accounted for 92 percent of export value, whereas in 2017 they represented 94 percent of the export value (figure 1, panel b).

> 3Details on the cleaning procedures for the Argentina raw data are presented in appendix A. The definitions of the indicators employed in the analysis are shown in appendix B. Countries included in the sample are listed in appendix C.

5
hoc benchmark based on the world, this alternative indicator (corresponding to the _δc_<sup>_k_fixed</sup> effects) aims to determine whether _c_ is relatively better than other individual countries at producing _k_ compared to other goods.<sup>7</sup> We apply Costinot et al.’s (2012) econometric estimation procedure on data from BACI in 2000 and estimate the _δc_<sup>_k_fixed effects for each exporter-hs6 product pair.We recompute the</sup> pairwise proximity index for two goods (Equation 1) when defining a country _c_ as exporting a good _k_ with RCA if _δc_<sup>_k>_0.</sup>

# **Product density**

Our main variable of interest is density, which measures, for each locality-product pair, the density of links to the local productive structure. As indicated by Hidalgo et al. (2007) and Kali et al. (2013), density for good _i_ and locality _l_ (Density<sup>_l_</sup> _i_<sup>)iscalculatedastheaverageof</sup> good _i_ ’s bilateral proximities with the other goods that locality _l_ exports with comparative advantage. The indicator is calculated using the Chinese customs data aggregated to the city level: The numerator above is the sum of good _i_ ’s proximities to the products _j_ in which locality _l_ has RCA ( _RCA_<sup>_l_</sup> = 1), whereas the denominator is the sum of proximities to all of the other products that exist in the world product space. For robustness, we check that the results continue to hold when we use the Chinese instead of the world product space as the reference to calculate the local RCAs.

9
_24_ _One example of how tills could influence and stimulate growth is, of course, in the area of labor markets. It is importanc to distinguish between the kind of pollcies that might stimulate the underlying growth path, raise total factor productivity and polIcies that could help us to better absorb some of the under-utilized resources in the labor market._ _That is, create some kind of level shifts if labor markets began to function better, which presumably would be associated with low inflation, and would allow policies to become if not more expansionary then, certainly in many countries, become less restrictive. So while this may not, over a longer period, raise the underlying growth race, I think it might temporarily allow us to grow at a faster rate than the underlying potential rate of growth._ _However, it is very important also to look at the other side of that coin, the opposite side. I think there are some uncertainties and risks. And just to mention a few, I think, for example, that there is a major risk that we underestimate the pressure on demographic consumption and, therefore, the potential impact on the aggregate factors... investment ratios in the industrial countries, and to some extent also in developing countries. Alchough for other reasons, because or demographic developments, in the industrial countries linked to the aging of populations, this is going to become a very critical factor in determining how the overall pie is being shared and therefore how much of aggregate income will be invested in the future._ _And if there were no other factor, I would definitely say that in the case of Japan, this would clearly suggest that the aggregate savings ratio and investment ratio and therefore, potential growth rate necessarily would have to be reduced in the future relative to what was experience in the 1950s and 1960s._ _Environmental damage..._ _Likewise, the one area where I believe a lot of research is necessary and probably will be done in coming years is the question of how the environmental constraint is going to affect the productivity of capital. How large a share of new investment in the years ahead will be reserved, so to speak, to try to limit the degree of further environmental damage._ _There may well be other reasons to be concerned that we may not even be able to maintain this underlying long-term secular growth trend in the future._ _MR. BANETH: Growth is like a bicycle. Lf it slows down too much, it may fall. And I personally believe that because of both political and social restraints, as you fall below or try to stay at 2.5 percent, the long-term outcome may in facc be much slower growth._ WP/PROCISF:Jsq
# 5. Conclusion

This paper reported on how a rapid household survey was employed to inform municipal social policy in Cali, Colombia. While drawing on similar surveys in other cities and countries, the questionnaire was developed together with the local administration, academia and several civil society organizations. The survey needed to collect quantitative data on access and welfare as well as qualitative data on satisfaction levels and budget priorities within the city. Implementation time of the survey was short and costs were modest.

In the Cali context, a number of important new characteristics of poverty emerged from the city survey. For example, unemployment rates were found highest for the young with a completed secondary school degree, pointing to an important mismatch between the quality of education and the demands of the local labor market. Food insecurity surfaced as a serious concern for the poor with almost a third of the poorest population quintile experiencing hunger while the coverage of nutrition programs was found to have been minimal. And the survey was also the basis for the construction of a city poverty map, which showed that pockets of extreme poverty existed in _comunas_ that were overall quite well off.

For the formulation of municipal social policy, the analysis of the survey proved especially insightful with respect to the distribution of city expenditures, service evaluation and population priorities. We found that, from a geographical perspective, all different types of city expenditures were distributed in an anti-poor way, favoring those areas in the city already quite well off. Satisfaction with city services varied considerably across different service types (with environmental cleanliness judged the worst) but relatively little across income groups. This result was also mirrored in budget priorities where a clear ranking of population preferences emerged, independent of the poverty status of the respondents. And the ranking cast considerable doubt on the metro project favored by the city administration at the time the survey was fielded.

Rapid city surveys can be an important tool for local social policy formulation. Apart from examining the specific local characteristics of poverty and social exclusion, population preferences and the distribution of city expenditures, such surveys can also be used, if applied regularly, to monitor social developments in the city over time.

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By at least one assessment, the growth cost of direct poverty<sup>alleviation is</sup> likely to be small provided that (and it is an important<sup>proviso) there are no</sup> significant macroeconomic imbalances (Bourguignon, 1991).<sup>HPAthrows little</sup> light on the prospects for a development strategy which<sup>combines support-led</sup> security at an early stage with growth-mediated security<sup>in the longer-term.</sup> It would be interesting to know if any of the countries<sup>identified in HPA as</sup> examples of growth-mediated security would have been examples of support-led security at some earlier time when they were<sup>much poorer.</sup> Related to this, a number of questions are left begging<sup>about the role</sup> of public action in promoting equitable growth in private<sup>incomes-</sup> not as an end in itself, I hasten to add, but as an instrument for<sup>higher ends</sup> ("increasing utility" or "expanding capabilities",<sup>as you prefer). Very</sup> little attention is given to the identified examples<sup>of growth-mediated</sup> security (Hong Kong, Singapore and South Korea). I would<sup>expect that, with</sup> the sustained periods of equitable growth experienced<sup>by these countries,</sup> capabilities requiring private consumption goods have expanded<sup>greatly for the</sup> poor, as have those requiring public provision.<sup>There are numerous questions</sup> about how public action can help here. To give just<sup>one example, scant regard</sup> is given in HPA to the policy issues which arise<sup>in achieving pro-poor</sup> technical progress in agriculture.<sup>3</sup> The fact that HPA throws little light on these questions<sup>is oddly</sup> asymmetric with the earlier analysis of famines.<sup>For example, the same basic</sup> issues of cost-effectiveness, such as targeting<sup>versus uniformity, that HPA</sup> covers quite adequately in the context of famine relief<sup>policy, also arise in</sup> the formulation of longer-term social sector<sup>policies, but are hardly</sup> mentioned in that context.

28