rafmacalaba/datause-encoder-data huggingface dataset:
# **2. Cotton Oil in the Context of the Global Edible Oil Market**

Ranked by oil content, cotton seeds are the lowest among key oilseeds after corn (Figure 5). Ranked by its yield per unit of land, cotton oil averages 325 liters per hectare, twice as much as corn. Other edible oils have much higher yields, how‐ ever, the highest being palm with 6,000 liters of oil per hectare (Figure 6).

The global production of cotton oil is small compared to that of other in‐ ternationally traded edible oils, accounting for only 3.3 percent of total fats and oils supplies, and the global cotton oil market is very thin, with only 3 percent of global production traded internationally. During 2006‐08, global production of the major 17 fats and oils averaged 147 million tons. Two vegetable oils, palm and soybean, dominated the market, accounting for 50 percent and 70 percent of global output and exports, respectively (Table 2). Cotton oil production averaged a little more than 5 million tons during the same period.

Cotton oil is traded at about the same price level per ton as sunflower and corn oil, and a little higher than palm and soybean oil (Figure 7). Because cotton oil is a close substitute for other edible oils, its price depends on, and reflects, the availability and trade policies of such oils. Cotton oil prices move in concert with the edible oil index (Figure 8).<sup>**5**</sup> Between the mid‐1980s and the early 2000s, they averaged US$600 per ton in nominal terms. They increased by 270 percent be‐ tween January 2007 and July 2008, but declined sharply afterwards. During the first quarter of 2010 they averaged about US$700 per ton.

Historically, prices of cotton and other edible oils have followed the same path as those of other agricultural commodities. They were fairly stable before the first oil shock, doubled during the oil shock, and then declined until the mid‐ 1980s. They entered a period of relative stability until 2005, then increased as part of the overall commodity boom. The World Bank’s index of nominal prices of ed‐ ible oils reached 340 (2000=100) in July 2008 but then declined sharply to about 225 during the first quarter of 2010. Even so, it remains more than double the 2000 level.

> **5** Substitutability among edible oils comes from the consumption side, as various oils can be used for the same purpose. Substitutability among grains, by contrast, comes mostly from the produc‐ tion side, where inputs, especially land, can be shifted from one crop to another.

**_Page 9_**
# **6 Empirical strategy**

## **Data**

This paper is based on data from the Indonesian Family Life Survey (IFLS), an ongoing, longitudinal survey of individuals, households and communities. Fieldwork for the second wave of the survey was completed by December 1997, nine months prior to the introduction of the healthcard program. The third wave of the survey was fielded in 2000. The analysis presented here, therefore, reflects the experience of at least fourteen months of the program. The 1997 survey (IFLS-2) covered 7,619 households, which included 10,429 children. In the 2000 round (IFLS-3), a total of 10,435 households consisting of 11,307 children were interviewed. 7,704 children were interviewed in both IFLS-2 and IFLS-3. The analysis in this paper is restricted to panel respondents aged 0 to 15 years old. Table 2 provides information on the number of children in each survey and the number of panel children. Attrition is limited in IFLS surveys as a lot of attention is paid to ensuring high re-contact rates. Households that moved between one wave and the next are followed up even when they move to a different province. Of the original IFLS-1 households, around 95% were re-interviewed in IFLS-2 and IFLS-3.

Table 2 about here The household survey contains a wide range of information regarding household members’ incomes and assets, education and consumption, which are vital for matching healthcard owners with suitable control households. Information about the quality of living conditions and housing were also collected. A separate section of the survey asked 23
when such participatory governance initiative is organized by the state and integrated within the state’s political and governance institutions, citizens talk not only to their peers, i.e. have mutual conversation, but also talk to state officials, local bureaucrats, elected leaders of village level political institutions and experience their verbal participation as talking to the state. As evidence from village assemblies shows, now so called “subalterns” (Spivak 1988) can speak to the state in a pubic setting in their own “vernacular voices” (Hauser 1999) and without having to rely on mediating middlemen. Leaving its substantive implications aside for a moment, we must recognize that this is an important measure in which democracy has been procedurally enhanced, and that procedural enhancement must precede substantive enhancement. _Therefore, examining how citizens talk to the state should be recognized as an important analytical agenda in the study of oral democracy._ Talking to the state can take various rhetorical forms, ranging from the sophisticated use of reason and factual information to narrating personal travails and verbally petitioning the state for public and private goods. In this regard the model of _oral democracy_ intends to make an important sociologically minded intervention by arguing that the analytical focus should be on revealing the entire array of rhetorical styles in use and to examine if particular styles are associated with particular advantages and disadvantages experienced by particular groups in a stratified society, i.e. with “durable inequalities”.<sup>5</sup> Another related focus should be on understanding how various rhetorical styles are socially evaluated by citizen-peers and by authoritative figures of the state.<sup>6</sup> Therefore, rather that a priori privilege only one rhetorical style and deem all others as detracting from democracy, _the focus should be on revealing the plethora of oral styles and oratory strategies in use and understanding their correlates (i.e._ 12
**Figure 5. Level of GDP per capita and share of urban informal employment**

<!-- Start of picture text --> 100<br>BEN<br>90<br>80 NERTCDGNBTGOBFAMLIGIN SEN CIV<br>BDI UGA<br>70 MWILBR CMRSTP GHA<br>SLE<br>60 ZMB AGO<br>ZWEKEN GAB<br>50<br>NGA<br>40<br>SWZ<br>30<br>20 ZAF<br>10<br>0<br>0 2000 4000 6000 8000 10000 12000 14000 16000<br>GDP per capita, PPP (constant 2017 USD)<br>Informal urban employment (%)<br><!-- End of picture text --> Source: Own elaboration based on GMD data and World Development Indicators (World Bank, 2021). Notes: Informal employment includes unpaid workers, LE-SE and informal wage employees.

The GMD data allow us to observe short-term informality dynamics in five countries. Using comparable data from Cameroon, Ghana, Liberia, Uganda and Zambia that was collected at least two years prior to the most recent survey, we calculate the distribution of urban informal workers by employment types for previous years. Since the time between observations differs by country, we generate the average annualized change in the share of workers in each employment type.

Non-parametric estimates find that informality trends are not uniformly increasing or decreasing across this subset of African countries over the short term, suggesting that the urban labor force does not uniformly move toward formality. As indicated in Table 1, the share of urban informality decreased in three of the five countries with annual rates of change ranging from –0.5 percent in Cameroon to –5.0 percent in Liberia. In contrast, informality increased in Uganda by an annualized 4.1 percent and in Zambia by an annualized 0.9 percent. The composition of the informal sector changed in different ways across countries.<sup>45</sup> These short-term trends may be happening within longer-term patterns of changes in the structure of employment with a growth in wage employment and declines in self-employment.<sup>46</sup>

> 45 Kiaga and Leung (2020) also find non-monotonic movements toward formality over a long-period time series.

> 46 A cross country analysis of 59 countries over 16 years found that as countries become less poor, certain types of formal and informal jobs types are displaced by formal sector wage employment. The  share of wage employment steadily increased with GDP per capita for low and middle-income countries, due almost solely to increases in formal wage employment, which accounted for about 20 percent of all employment types in

17
Thus, the number of bilateral export flows of Kenya was only 10 percent of that of Korea. The next column shows the number of potential bilateral flows for the given products exported by each country. The number of potential flows for Kenya is around threequarters of that of Korea. The final column shows the extent to which each country is exploiting the available export opportunities, the index of export market penetration. Kenya is currently exploiting less than 4 per cent of the potential bilateral flows for the products that it exports. Korea on the other hand is exploiting almost 30 percent of the available export opportunities.<sup>7</sup>

|**Table 5:**|**Export market penet**<br>Number of products<br>exported in 2004|**ration- a comparison of**<br>Actual number of export<br>relationships in 2004|**Kenya and Korea**<br>Potential number of export<br>relationships in 2004|<br>Export market<br>penetration|
|---|---|---|---|---|
|Kenya|2148|6789|179426|3.78|
|Korea|2930|66983|237584|28.19|
|Ratio|73.3|10.14|75.52||

What could explain why countries such as Kenya exhibit a much lower number of bilateral trade flows for the given products that they export than countries with higher levels of income per capita? Here the recently developed model of trade with heterogeneous firms (Melitz (2003)) is useful in highlighting critical parameters that can limit the number of trade flows. In the Melitz model there is a distribution of firms within a country with differing productivities and hence marginal costs. There are fixed costs of entering markets (both the domestic and overseas markets) and there are variable trade costs that exporters must incur (such as transportation, tariffs).

For every market in the world, including the domestic market, local firms face a cut-off condition defined as the highest marginal cost at which firms can enter the market. Since sales to the domestic market do not incur trade costs the domestic cut-off marginal cost will determine the number of firms that enter the local market, conditioned by domestic demand. Exporters need not necessarily serve the local market since local demand may not exist or be sufficient. However, in activities with scale economies, producing for the

> 7 Again, conclusions remain with different thresholds for exports. For example, for export flows in excess of $10000, Kenya exports about 24 per cent of the number of products exported by Korea but has only about 4 percent of the bilateral export flows. The index of export market penetration is 0.8 percent for Kenya and 14.9 percent for Korea.

15
<!-- Start of picture text --> Upward mobility of baseline non-salaried workers (compared to rural)<br>14<br>12 2<br>=34<br>zof<br>Boe 082<br>073<br>06 061 ° .059<br>° 49 Pre-covid cohort<br>os ® Covid cohort<br>Small city* Large city** Very large city***<br><!-- End of picture text --> <!-- Start of picture text --> Downward mobility of baseline salaried workers (compared to rural)<br>0<br>-.05 + ons<br>a£<br>QPo-a3°<br>3= -12 “13<br>a<br>-15<br>@Pre-covid cohort<br>“2 TM Covid cohort<br>Small city* Large city** Very large city***<br><!-- End of picture text -->
Table 11: Effects of Electricity Subsidies on Consumption in Ghana

|||Resid|ential||
|---|---|---|---|---|
||Dep. var:|Logof ele|ctricitycon|sumption|
||(1)|(2)|(3)|(4)|
|1(non-lifeline)_×_postsubsidy|-0.162***<br>(0.014)|-0.165***<br>(0.014)|-0.173***<br>(0.009)|-0.173***<br>(0.010)|
|Customer type Trends|No|Yes|Yes|No|
|Climate Ctrls|No|Yes|No|No|
|Customer FE|Yes|Yes|Yes|Yes|
|Month FE|Yes|Yes|No|No|
|District-Month FE|No|No|Yes|Yes|
|R-squared|0.812|0.812|0.808|0.802|
|Mean dep. Var|45.144|45.145|175.043|175.044|
|Obs|9140330|9140330|9140330|9140330|

Notes: Dependent variable is the log of monthly electricity consumption. Climate Ctrls include the monthly average temperature and total precipitation. Standard errors clustered at district-customer level in parenthesis. _∗_ Significant at 10 percent level _∗∗_ Significant at 5 percent level _∗∗∗_ Significant at 1 percent level 37
13.

markets by the late 1970s, and there is very little variation across periods in the relative importance of the various export marketing mechanisms. The export marketing patterns for this subsector parallel more those of Japan and non-pribumi Indonesian firmns than they do those of the remaining three Korean (and the Colombian) subsectors. For the rest, the Korean survey results illustrate vividly how export marketing channels evolve - how SME exports get going in individual subsectors, and how the transactional environment for export marketing "thickens" as the number of SME exporters proliferates.

Table 7 organizes the subsectoral data on the relative importance of various marketing - mechanisms into three time-related subgroups the time of the field survey; and firms' initial period of entry into export markets, with initial export entry in turn disaggregated between pioneer SME exporters and SMEs that moved into international markets only once the industry had established its role as an exporter. As the table shows, the initial imnpetus for exports in the - three subsectors came primarily from resources already within the country from export traders, from coilective marketing support institutions, and from exporting firms themselves. Traders/subcontractors played the leading pioneer role for auto parts SMEs, and the second most inportant role in electronic parts and factory automation SMEs. Their prominent early role can be interpreted as an important spillover for Korean SMEs from being active in a country with a strong export profile, insofar as it was the country's earlier export success. (typically by larger firms) that brought these traders/subcontractors onto the scene. Collective marketing support leads among pioneer electronic parts SME exporters, and has a significant subsidiary role in auto parts. Direct marketing efforts by firms provided the critical initial impetus in the factory automation subsector, and also scored high among autoparts pioneers. In aU three subsectors the role of direct marketng declines for the export start-up of follower exporters, but picks up again for current exports.

Over time, initiatives of foreign buyers come to the fore. Buyer initiatives are identified in Table 7 as the least important mechanism for initial export entry by pioneer SMEs in the auto and electronic parts subsectors, and second least important for factory automation. But information appears to spread rapidly as Korean firms come on line as a primary international
adoption indicators at very low levels of development. For the latter, we compute the fitted values at the minimum and 20<sup>th</sup> percentile levels of income per capita in the common sample of 149 observations.

Table 3 shows the regression results for equation (1), which assumes that the relationship between the incidence of payment systems and the level of development is log linear. As we move towards more digitized payment technologies, Table 2 shows that the slope coefficient decreases up to the point of it being negative in stage 3. On the other hand, the value of the constant increases, perhaps suggesting that poorer countries are early adopters of digital payment technology. The predicted values at minimums confirm this result, but we see that it holds only under the 20<sup>th</sup> percentile after which traditional banking accounts become more prevalent.

**Table 3. Regression results: Log-linear specifications**

|RHS Variables:|Stage 1 LHS<br>Variable:<br>Bank accounts|Stage 2 LHS<br>Variable:<br>Digital payments|Stage 3 LHS<br>Variables:<br>Mobile money|
|---|---|---|---|
|log_gdppc|0.172***<br>(0.0125)|0.100***<br>(0.0123)|-0.028***<br>(0.00957)|
|year2017|0.0336<br>(0.0258)|0.0784***<br>(0.0254)|0.0888***<br>(0.0198)|
|Constant|-1.127***<br>(0.110)|-0.645***<br>(0.108)|0.300***<br>(0.0844)|
|Observations|149|149|149|
|AdjustedR<sup>2</sup>|0.563|0.340|0.146|
|Min. log_gdppc||6.70||
|**Predicted minimum**|**0.040**|**0.063****|**0.161*****|
|20<sup>th</sup>percentile log_gdppc<br>||7.64||
|**Prediction at 20**<sup>**th**</sup>**perc.**|**0.201*****|**0.157*****|**0.135*****|

<u>Source: Authors’ calculations. Notes: Standard errors in parentheses (*** p<0.01, ** p<0.05, * p<0.1).</u> LHS = Left-Hand Side Variables in equation (1). RHS = Right-Hand Side variables in equation (1).

The goodness of fit is largely decreasing as we move across the stages, suggesting that we are capturing a declining portion of the variance for more recently introduced payments mechanisms. This finding implies that the log-linear specification is more appropriate for the stage 1 model than for the latter two stages. Table 4 presents the results for the quadratic specifications. The Adjusted statistic is comparable across specifications, and higher values indicate a preferred functional form. In the RR<sup>2</sup> case of Stage 1, only the quadratic term is significative but the linear one is not. The Adjusted RR<sup>2</sup> 12
financial savings prior to the 1990s. A client investing in “títulos/cedulas de capitalización” would essentially be required to open an account for at least one year in exchange for participation in periodic lotteries in which he could gain a multiple of his own contributions to the account, as well as the opportunity to borrow against those “títulos” and to receive a (low) return for his investment. The sociedades de capitalización would in turn invest these funds in debt and equity securities, subject to the same investment regime as insurance companies. The recommendation would eliminate this type of vehicle by obliging existing firms to convert themselves into (or be absorbed by) other types of financial intermediaries.

**Table 15: Size and Ownership of Sociedades de Capitalización (December 2005)**

||**Total Assets**<br>**(Col$ billion)**|**Market Share**|**Ownership**|
|---|---|---|---|
|Bolivar|493|33%|Grupo Bolivar|
|Capitalizadora Colpatria|419|28%|Mercantil Colpatria|
|Cedulas Colon de Cap. Colseguros|275|18%|Allianz|
|Capitalizadora Suramericana|258|17%|Grupo Sindicato|
|Capitalizadora Colmena|62|4%|Fundacion Social|

_Source: Superintendencia Financiera, own analysis._

**The perceived benefits of this recommendation outweigh the costs, although the impact on the financial system is very small.** In particular, sociedades de capitalización are an inefficient vehicle for savings given their low absolute returns (often negative in real terms); the existence of the lottery mechanism has been their biggest attraction. Their elimination would permit the channeling of those resources to the banking sector, although there is a minor risk that the relevant population segment (lower- to middleincome) might instead decide to marginally reduce its financial savings if they are not offered financial products that they consider attractive. However, the lack of flexibility and product innovation, combined with the development of more efficient instruments by the financial system, has already led to the progressive decline of these entities and few inflows of new business. As can be seen in the above Table, there are currently five sociedades de capitalización whose total assets amount to around Col$1,500 billion or US$650 million (0.5 percent of GDP or 1.7 percent of bank deposits). Implementation of this recommendation would be relatively easy for regulators given their small size and relative ‘isolation’ with the rest of the financial system<sup>41</sup> , while a carefully managed transition path for existing client contracts (some of which are set to expire within 8-9 years) would facilitate the exit process of these entities.

# **_G. General Reform 1: Legal Framework_**

**Recommendation: Review and revise the legal framework for the financial system in terms of hierarchy, consistency and breadth of coverage** . A reform effort to

> 41 In fact, two of the five companies are apparently in the process of exiting the industry.

31
|||**Tab**|**le 5: Females i**|**n 20-29 age gr**|**oup**||||
|---|---|---|---|---|---|---|---|---|
|Dependent variable: Female<br>workers|**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|**(8)**|
|Maternity leave<br>(logs)*Females: 20-29 yrs.<br>old (%)|**0.538**<br>**(0.717)**|**2.421****<br>**(1.001)**|**2.502*****<br>**(0.828)**|**2.759*****<br>**(0.585)**|**2.733*****<br>**(0.580)**|**2.737*****<br>**(0.578)**|**2.939*****<br>**(0.580)**|**3.423*****<br>**(1.230)**|
|Maternity leave (logs)|-1.111|-21.763***|-12.128|-23.202|-24.061|-23.394|-35.886|-23.794|
||(4.644)|(8.304)|(32.570)|(21.629)|(21.804)|(21.663)|(29.789)|(52.162)|
|Females: 20-29 yrs. old (%)|-3.420|-11.347**|-11.972***|-12.011***|-11.891***|-11.859***|-12.668***|-27.535|
||(3.358)|(4.764)|(3.972)|(2.743)|(2.711)|(2.714)|(2.693)|(24.728)|
|Govt. Funded Y:1 N:0||-39.319***|-43.424***|-43.583***|-41.888***|-41.739***|-45.524***|-69.219***|
|||(12.800)|(12.210)|(10.152)|(10.058)|(9.988)|(9.737)|(21.140)|
|Maternity leave (logs)*Govt.||9.983***|10.777***|9.889***|9.513***|9.481***|10.522***|15.682***|
|<br>Funded Y:1 N:0|||||||||
|||(2.801)|(2.661)|(2.233)|(2.213)|(2.196)|(2.175)|(4.724)|
|Maternity leave (logs)*% of<br>females in total adult|||-0.206|-0.023|0.004|-0.008|0.192|0.871|
|population (5 yr. avg.)|||||||||
||||(0.635)|(0.445)|(0.446)|(0.443)|(0.581)|(0.640)|
|% of females in total adult|||2.436|10.264***|10.084***|9.798***|9.571***|2.546|
|population (5 yr. avg.)|||||||||
||||(3.001)|(3.109)|(3.119)|(3.088)|(3.595)|(4.678)|
|GDP per capita (logs)||||4.195***|4.357***|4.191***|2.946**|28.428|
|||||(0.595)|(0.583)|(0.576)|(1.421)|(20.747)|
|Growth rate of GDP per<br>capita (%, annual)||||0.399**|0.406**|0.408**|0.305*|0.245|
|||||(0.176)|(0.171)|(0.171)|(0.160)|(0.156)|
|Females in adult population||||-8.539**|-8.433**|-8.101**|-8.982**|-5.117|
|<br>(%)|||||||||
|||||(3.826)|(3.839)|(3.799)|(3.593)|(4.019)|
|Number of workers (logs)||||-0.066|-0.421|-0.519*|-0.483*|-4.856|
_Page 6_ Figure 5: Iniant Mortality (per thousand) <!-- Start of picture text --> 100<br>80 -<br>60 -l<br>Argon Brazil Chile CRica Mex Peru Korea Talw Spn Sweden<br><!-- End of picture text --> <!-- Start of picture text --> L. Amer Asia Europe<br><!-- End of picture text --> 8aurce: World Bank Figure 6: Maternal Mortality 1980--(per 100,000) <!-- Start of picture text --> 350<br>300<br>250 . X<br>160<br>0<br>Argon Brazil Chile CRica Mex Pefu Korea Spain Sweden L. Amer Asia Europe<br>Oeorte. World fansk<br><!-- End of picture text -->