rafmacalaba/datause-encoder-data huggingface dataset:
# **Social spending**

Contributory non-pension benefits and direct transfers are all progressive, reducing both poverty and inequality (Table 4). Abstracting from old-age pensions, contributory benefit programs are progressive in both relative and absolute terms – that is, they represent a larger share of the budgets of the poor, and are pro-poor, as most of the benefits are concentrated at the bottom 40 percent of the distribution for almost all categories of benefits with the exception of sickness benefits, which are more concentrated at the top. In particular, 57 percent of maternity benefits<sup>10</sup> and 52 percent of unemployment benefits go to the bottom 40 percent of the distribution, while only 37 percent of sickness benefits do so (Figure 8).

Figure 8. Concentration of Social Protection Programs <u>(by market income plus pensions quintiles)</u> <!-- Start of picture text --> 100%<br>90%<br>80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Contributory Non-contributory<br>Poorest 2 3 4 Richest<br>Source: World Bank estimates based on Croatian PIS and HBS data for 2014.<br>benefits<br>benefit benefits benefits<br>Maternity/parental Unemployment Disability related Sickness benefits Social asisstance Child benefits Education related Other benefits All Direct Transfers<br><!-- End of picture text --> In terms of non-contributory transfers, all are progressive in relative and absolute terms (they are pro-poor as a larger share of benefits goes to the bottom of the distribution) as demonstrated by negative concentration coefficients (Table 4). In particular, 84 percent of social assistance benefits, and 55 percent of child benefits are devoted to the bottom 20 percent of the distribution (Figure 8). Education benefits are perhaps the least well-targeted, with 49 percent of all benefits going to the top 60 percent of the distribution, likely because these are designed as performance-based stipends and not meant to target the bottom of the distribution. In assessing how education and health spending benefit the poor, we have to caution that our analysis does not address the quality of such spending. We use government expenditure data on the various forms of education and health services to estimate unit costs of these programs. The analysis thus assumes that the actual

> 10 Note that the sample of households receiving maternity benefits in the survey is small, so this result should be interpreted with caution.

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1993 in over 37 _xian_<sup>_6_</sup> across 17 provinces (out of 28) in China. In all, 57 relatively poor villages across rural areas were chosen to evaluate the program, with 38 villages chosen as treatment villages where the program was implemented and the other 19 villages used as a control group (i.e. without intervention).' The data collected relate to the year 1996, three years after program implementation. Several qualitative case studies in a few villages have been carried out to assess the impact of this program (Dai and Peng, 1996; Lin, 1997) and the findings suggest a positive program impact in terms of reducing preferred family size, reducing gender bias, and increasing women's participation in community life.

The community program has both economic and social dimensions. The program involved agricultural seminars and extension services, organised cultural and entertainment activities (e.g. dancing groups, chess clubs and reading groups), and political meetings. One of the special features of this project is its emphasis on the development of human and social capital rather than providing financial aid. Therefore, direct financial support from central or local government is very limited. Village leaders in the treatment group were given seminars on the importance of community development, women's participation and their impact on women's fertility attitudes. Women were given priority access to agricultural extension services initiated and supported by local government, including information on new farming technology, and training and technical assistance. Agricultural technicians were invited to give advice on farming techniques mostly suitable for local conditions and on various productive activities to which woman are better suited. Based on the principle of self-sufficiency and self-development, financial resources for setting up village libraries, reading rooms or social and entertainment facilities come mainly from the taxation of village enterprises and/or reallocation of village general funds.

> _6A xian_ is a collection of neighbouring villages.

> 7 Program organisers claimed that the choice of villages participating in the program was made randomly, but we also test this in our analysis.

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consisting of a single tradeable commodity. For each such project in each country considered, we forecast the magnitudes needed in (6) over the average future period when the payoff from this project will accrue. For illustrative purposes, we have chosen this to be five years from the time the investment is made. The risk aversion parameter p must be fixed exogenously as explained above, and we show the results for two alternative values, p - 1 and 2.

The data needed to implement the method consist of time series of the world prices of a group of commodities and the real exchange rates, commodity outputs, and GNP for a large group of countries. The maximum period covered was 1961-87; for some countries a smaller period had to be used. World price data were obtained from the World Bank's International Economics Department, International Commodity Markets Division, and are the international prices of standard types of commodities in major markets (see Annex 1 for specific sources and definitions). These prices are deflated to 1980 U.S. dollar values with the IMF's "World Consumer Price Index", a GDP-weighted average of country consumer price indices.

We use a simple GDP-deflator-weighted real exchange rate. The real local currency per U.S. dollar rate is defined as the nominal local currency per U.S. dollar rate multiplied by the ratio of the U.S. GDP deflator to the national GDP deflator. The price indices, deflators and the nominal exchange rates were obtained from the IMF's International Financial Statistics Yearbook. The GDP deflator is not available for all countries over the entire period 1961-87. This would have forced the exclusion of a few countries (Burkina Faso, Cameroon, Cote D'Ivoire, Niger, Senegal, Sudan and Bangladesh) from the analysis. In those cases we have
age z-score of –2.5 was imputed to them. For the rest of the sample of children who had died, an average height to age z-score of –4 was imputed<sup>7</sup> .

Even though these imputations are based on the upper bound estimates of Pelletier and others (1995), they result in only modest changes in the overall mean. The largest changes are observed for the 1992 sample because mortality rates are highest in that year (see bottom panel of table 2). Had all the children who died survived, the total mean height-for-age z-score for boys would change from –1.91 to –2.01, a 4.9 percent change. The impact of imputations is smaller for 1998, at 3.6 percent and 2005, at 4.1 percent. For girls, the imputations change the total mean from –1.86 to –1.95 in 1992, a 5.1 percent change, and by 3.3 percent for 1998 and 4.09 percent for 2005. The change in height-for-age z-score is slightly larger in percentage terms in 2005 than in 1998 (although the absolute value of the change is smaller) in keeping with the lower mortality rate.

Recent studies by Pelletier and Frongillo (2003) and Black and other (2008) indicate that globally among children younger than 36 months the proportion of deaths associated with malnutrition declined to 37 percent in the late 1990s and early 2000s because of the effect of expanded coverage of immunizations, oral rehydration therapy, antibiotics, and other child survival interventions. Imputations of height-for-age z-scores corrected for contemporaneous mortality selection based on these estimates would yield smaller and statistically insignificant changes in the total mean for the 1998 and 2005 NFHS samples. While these more modest associations are not illustrated in table 2, the simulations that are shown demonstrate that the selectivity mortality would only have a large impact on observed anthropometrics if there were very large differences in anthropometrics between the children who died and those who survived. Current research on the association between mortality and malnutrition does not substantiate such large differences.

# **_Simulations Based on a Proportional Hazard Model_**

The simulations discussed in the previous section were based on imputations of a few categories of height-for-age data to the children in the sample who had died. It is more realistic to assume that children‘s anthropometrics and survival depend on their individual characteristics, prenatal conditions, health of the mother, and those of their household (Wolpin 1997). To approximate this, children who died were matched with children who survived past the age of 36 months using the estimated survival hazard as a matching score. The anthropometric scores of children who survived were then imputed

> **7** Boerma et al (1992) demonstrate that the differences in malnutrition between the children who died after the measurement and who survived a specified time period in longitudinal studies in Indian states of Tamil Nadu and Punjab were relatively small: height-for-age z-scores of 60 percent of dead children were lower than -2 SD from the mean compared to 50 percent among survivors.

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Akin, J.; Hutchinson, P. and Strumpf,K. 2005. Decentralisation and government provision of public goods: The public health sector in Uganda, The Journal of Development Studies, 41:8, 1417-1443, DOI: 10.1080/00220380500187075 Alesina, Alberto, and Eliana La Ferrara. 2005. Ethnic Diversity and Economic Performance. Journal of Economic Literature 43: 721-61.

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Asher, Sam, and Paul Novosad. 2017. Politics and Local Economic Growth: Evidence 36
_Figure 13: Poverty Projections at LIC extreme poverty line ($2.15, 2017 PPP) and growth based on GDP current prices (CPI adjusted) and 2009 poverty baseline using different passthrough rates_ <!-- Start of picture text --> 100%<br>80%<br>60%<br>42%<br>40% 35%<br>28% 28% 28%<br>22% 23% 21%<br>19%<br>17%<br>20% 15% 15% 14%<br>12% 12% 12%<br>8%<br>2% 2% 6%<br>0% 5% 9% 10% 10% 11% 9% 8% 8% 11%<br>2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020<br>Unit Passthrough Clonflict Adjusted Passthrough Passthrough=0.7<br>Poverty Rate<br><!-- End of picture text --> _Source_ : World Bank staff calculations, based on WDI and CBS data _Figure 14: Poverty Projections at LMIC international poverty line ($3.65, 2017 PPP) and growth based on GDP current prices (CPI adjusted) and 2009 poverty baseline using different passthrough rates_ <!-- Start of picture text --> 100%<br>80%<br>71%<br>65%<br>58% 58% 57%<br>60%<br>51% 51%<br>49%<br>47%<br>43%<br>40% 40% 40%<br>40% 36% 36% 35%<br>29%<br>24% 31% 33% 32% 33% 34%<br>29% 29% 28%<br>20%<br>13% 23%<br>15%<br>14%<br>0%<br>2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020<br>Unit Passthrough Clonflict Adjusted Passthrough Passthrough=0.7<br>Poverty Rate<br><!-- End of picture text --> _Source:_ World Bank staff calculations, based on WDI and CBS data
workers.<sup>19</sup> This concluding section outlines policy directions that could be tailored to any context, as we do for Bihar, for reform leaders and international partners to consider in their investments in public health systems. The following three elements characterize these policy directions:

- **Infuse messages into management meetings in health bureaucracies** : the Bihar survey found that across all cadres of health workers, there are regular meetings held with district and block-level management (75 percent of sub-center ANMs say they have weekly meetings; 86 percent of ASHAs say they have at least monthly meetings with the MOIC at the Block PHC), and a significant proportion of health workers are part of WhatsApp groups (39 percent of village-ANMs and 52 percent of block-ANMs say they belong to a health workers’ WhatsApp group.). Evidence-based messages about the need for professionalism and motivated service delivery can be crafted for sharing at meetings that are already happening organically and provide an institutionalized space for strengthening peer-to-peer norms.<sup>20</sup> In the Bihar and India context in particular, this involves a radical shift away from the culture of "scoldings" and disciplining, towards encouragement and recognition of health workers as professionals whose services are urgently needed for the good of society.

- **Newspaper and TV campaigns** : Bihar provides a context in which readership of Hindi-language daily newspapers provides a platform to share complex messages that require reading and discussion among people. As discussed above, newspaper reading is already happening as a way of finding out local, Bihar-specific news, and thus presents an organic platform that external agents can use to disseminate credible, databased messages. At the same time, the relative importance of TV viewing among the poorer groups of respondents in villages suggests a role for inserting Bihar-specific in-

> 19The survey on which this paper draws was designed to understand the management environment in which health workers perform their tasks, and did not have scope to address the important area of professional training. We thank Hemant Pawar and the World Bank’s India country team for highlighting the need for better preservice and in-service training of health workers. Our paper can be used to craft complementary governance interventions so that better trained health personnel are motivated to use their training for health impact.

> 20Contrast this against the lack of such institutionalized space for social accountability–86 percent of citizens respond that they have never heard of a village committee on health and nutrition.

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**Table 2: Manufacturing value added as percent of GDP (constant prices) regressions**

||Panel|A: All SSA|Panel B: Low|-exporting countries|
|---|---|---|---|---|
||Coefcients|Marginal Efects|Coefcients|Marginal Efects|
|_Panel A: Regression Estimates_|||||
|Population (logarithm)|2.827**|-0.039|3.122**|-0.011|
||(1.148)|(0.031)|(1.437)|(0.035)|
|Population squared (logarithm)|-0.104***||-0.102**||
||(0.040)||(0.049)||
|GDP per capita (logarithm)|3.576***|0.042***|2.328***|0.055***|
||(0.899)|(0.007)|(0.859)|(0.011)|
|GDP per capita squared (logarithm)|-0.200***||-0.113**||
||(0.057)||(0.053)||
|Intercept|-36.523***||-36.887***||
||(9.767)||(12.278)||
|_Panel B: Lind & Mehlum (2010) U Test_|||||
|Slope at minimum GDP per capita (logarithm)|1.229***<br>(0.244)||0.958***<br>(0.238)||
|Slope at maximum GDP per capita (logarithm)|-0.732**<br>(0.366)||0.043<br>(0.257)||
|Lind & Mehlum (2010) Test statistic|2.180<br>[0.015]||0.31<br>[0.377]||
|Observations|1540|1540|1293|1293|
|Number of countries|41|41|36|36|
|Country Fixed Efects|Yes|Yes|Yes|Yes|
|Time Fixed Efects|Yes|Yes|Yes|Yes|

Standard errors in parentheses and p-values in square brackets. Results based on fixed effects fractional logistic regressions in equation (2). _∗p <_ 0 _._ 10 _, ∗∗ p <_ 0 _._ 05 _, ∗∗∗p <_ 0 _._ 010
of errors are lowest for plots without a legal document (17%), followed by those with documents issued to men and women jointly (30%), individually to women (35%), and individually to men (54%). This is consistent with the notion that information on nature of land ownership documents held or owners’ identity may not be fully shared among household members (Ashraf 2009) with men generally more secretive about their documents and more likely to falsely claim having a document.<sup>17</sup> As mortgages and transfers are rare events, the sample sizes commonly used in household surveys may make it difficult to arrive at precise estimates, possibly magnifying the effect of measurement error. Of the plots registered by our survey households, 60 had a mortgage registered (with the entry dating from 2013 in 32 and from after 2013 in 28 cases). But only for 22 of these (37% of the total) did household survey respondents report existence of a mortgage or having taken out a bank loan. Routine availability of administrative data can thus help reduce measurement error by cross-checking survey information against registry entries and by stratifying household survey samples, allowing to combine data and make inferences on distributional aspects, heterogeneity of impacts, and the extent to which land or credit market activity triggered processes such as gentrification that are impossible with administrative data on their own.

# **4.4 Interpreting the results**

If, as suggested by the above figures, policy reform lowered barriers to titling, one would expect to see differences in observable characteristics between plots registered in pre- and the post-reform periods. To test this, we regress the type of titling (systematic/sporadic before or after the policy change) on geographic plot attributes in particular distance to CBD and size. Results in appendix table 2 suggest that plots that entered the registry sporadically before reform were larger and closer to the CBD while focus thereafter shifted towards smaller plots (a coefficient much larger in absolute terms than for systematic adjudication).

Concerns about negative distributional impacts as a result of biased access to information (Jansen and Roquas 1998) or a fixed cost element for registering transfers or mortgages (Carter and Olinto 2003) have long been raised in the literature. Although available data limit our ability to explore this, assuming that smaller plots more distant from the CBD are less valuable allows us to test the link between these proxies for plot value and land or mortgage market participation by interacting right hand side variables in equation (3) with parcels’ distance to the CBD, average parcel size at block level, or the interaction of the two. Results, as reported in appendix table 3, suggest that, if anything, smaller and more distant plots are more likely to be transferred and, to a lesser extent, mortgaged.

> 17 While more detailed analysis (e.g., by linking errors to survey respondents’ identity) is beyond the scope of this paper, the role of measurement error is consistent with what was found in studies such as Deininger _et al._ (2020b).

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# **IV.** COMMODITY **MODEL** APPLICATIONS IN **THE** BANK

How have commodity model developments and applications within the Bank served Bank purposes and paralleled developments within the modeling profeb3ion itself? In other words how has Bank research been integrated with the development and application of the range of commodity modeling methodologies just discussed? The history of modeling activities at the Bank indicates that the majority of these methodologies has been employed by the Bank at one time or another. To understand these applications, it is thus interesting not only to examine earlier modeling efforts, but also to emphasize the more recent atteript to operate the models in a way so as to produce regular quantity and price forecasts over time.

In the discussion which follows the early model history is presented first for single commodity models and then for multiple commodity models. Current mc.del applications are then divided according to the above econometric market modeling methodology and the mathematical programming methodology. Eergy market conditions recently experienced have featured such special modeling problems that this class of models is considered separately. Early Model History Among the earliest modeling work at the Bank, cocoa and rubber models were completed in the late 1960's in an effort to analyze commodity market stabilization.

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Suryahadi, A. (2001). International economic integration and labor markets: The case of Indonesia.

# **Annex A: Data**

# _Sakernas_

The Sakernas data, also known as the National Labor Force Survey (Survei Angkatan Kerja Nasional), is a comprehensive dataset for Indonesia. It is a survey conducted by the Indonesian Central Bureau of Statistics (Badan Pusat Statistik or BPS) and provides detailed information on various aspects of the labor force in the country. The survey is typically conducted bi-annually and collects data from households across Indonesia.

The Sakernas data covers a wide range of topics related to employment, unemployment, and labor force participation. It includes information on individuals' demographic characteristics, educational attainment, occupation, industry, employment status, working hours, wages, and other relevant labor-related variables.

For this study, we built a repeated cross-sectional dataset between 1993 and 2014 using the August rounds of data. We harmonized industry codes to the Klasifikasi Baku Lapangan Usaha Indonesia (KBLI) 1990 classification, the Indonesian industrial classification based on ISIC Revision 2.

# _UN COMTRADE_

The UN Comtrade dataset, officially known as the United Nations Commodity Trade Statistics Database, is a comprehensive international trade database maintained by the United Nations Statistics Division (UNSD). This dataset provides detailed information on global merchandise trade, encompassing the import and export of goods and services between countries and regions. In this study, we limit the analysis to trade in merchandise only, since data on trade in services is very limited for the pre-2000s period.

# _UN Statistics Division (ISIC-HS Concordances)_

The UN Statistics Division (ISIC – HS) concordances refer to a set of tables or mapping systems that establish a link between two international classification systems: the International Standard Industrial Classification of All Economic Activities (ISIC) and the Harmonized System (HS).

ISIC is a global standard for classifying economic activities. It provides a hierarchical structure that categorizes industries based on their primary economic activities. ISIC codes are used for various statistical and analytical purposes to group economic activities into meaningful categories. ISIC codes exist under four different classifications and levels of disaggregation. In this study, we use the nine-sector classification consistent with Revision 2.

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