rafmacalaba/datause-encoder-data huggingface dataset:
_Social Capital, Household Welfare and Poverty in Indonesia_ _50_

**Table 13: Social Capital and Household Welfare: Household versus Village Effects**

|Intercept|12.2974|(57.42)|
|---|---|---|
|_Social Capital Dimensions_|||
|Number of Memberships|0.0116|(1.78)|
|Heterogeneity Index|0.0030|(2.94)|
|Meeting Attendance|-0.0018|(0.74)|
|<br>Index of Participation in Decision Making|0.0025|(4.35)|
|<br>Cash Contribution Score|0.0080|(1.10)|
|Work Contribution Score|-0.0009|(0.28)|
|Community Orientation|-0.0002|(0.22)|
|Household Size|-0.0949|(10.07)|
|Years of Education|0.0319|(4.11)|
|Female Head of Household|-0.0432|(0.63)|
|Age of Head of Household|0.0314|(3.82)|
|<br>Age of Head of Household Squared|-0.0003|(3.38)|
|<br>Farmer Household|-0.2206|(5.17)|
|Jawa Tengah|-0.2348|(3.79)|
|<br>Nusa Tenggara Timur|-0.3151|(5.09)|
|_Village Variables_|||
|Past Community Involvement in Development Projects|0.1370|(2.47)|
|Number of Projects|0.0038|(1.27)|
|<br>Upland villages|0.0203|(0.51)|
|<br>Distance to Market (km)|-0.0045|(1.33)|
|<br>Diversity|0.0199|(0.49)|
|lNumber<br>of Observations|1137||
|l R-squared|0.25||
|<br>F-statistic|16.93||

Notes: Dependent variables is In (household expenditure per capita). Reported are OLS coefficients and t-statistics based on robust standard errors.

# **6.5 Conclusion**

In this section we attempted to get a step closer to the structural equations which underlie the reduced-form model of equation (1), by estimating the impact of social capital on variables portraying the ways in which social capital contributes to household welfare. We found that households with high social capital are better able to accumulate physical assets and savings and to obtain credit. This should help households cope better with the risk of income fluctuations. The number of memberships, the internal heterogeneity of associations, and active participation in decision making were the key dimensions. In contrast, when it comes to collective action, households belonging to
the efficacy of this intervention as a means for improving child survival. The evidence on measles vaccination and replacement mortality is considered from two different perslectlves in the following sections.

Convergence in"Survival Over Time If replacement mortality was evident, vaccinated children would be expected to experience improved survival in the shortrun relative to unvaccinated children, but comparatively higher mortality levels in the longer run, as they would remain highly vulnerable to death from other causes. The result would be a convergence between vaccinated and unvaccinaZed children in survival probabilities over time.

The authors of the Kasongo study presented evidence which they interpreted as providing support for this hypothesis. Their analysis indicated that while vaccinated children had improved survival chances during the ages 7-21 months, the primary risk period for measles and measles-related mortality, the survival advantage of vaccinated children tended to diminish at later ages (22-35 months). However, as Aaby, et al. (1981) showed in a reanalysis of the Kasongo data, too few deaths occurred in this study population in this older age group to support the authors' original conclusions. Instead, the most salient finding of the study remains the marked reduction in mortality among vaccinated children throughout the entire age span, w ch reductions ranging from 44 to 59 percent lower among children aged 7-35 months.

The study by Clemens, et al. (1988) in Matlab also considered the issue of replacement mortality in detail. First, the authors examined whether the protective efficacy of measles vaccination for cases and controls selected during the second half of the year-- cotresponding to after the measles season in Bangladesh-- might be negative, in contrast to cases and controls selected during or shortly after the primary measles season, when protective efficacy should be positive. The finding of a negative prctective efficacy dujring the period after the measles season would re¢lect higher replacement mortality among vaccinated children. The results, however, did not provide support for a replacement mortality effect, since the protective efficacy of vaccination was positive and significant during both periods. Second, the authors evaluated whether amon, cases and controls selected in 1982, there was evidence of a reduction in mortality among vaccinated children in the initial year, followed by higher mortality rates relative to unvaccinated children in thj ensuing two years (1983-84). The results provided no evidence oL a decline in the effect of measles vaccination with increasing time from vaccination, once again failing to provide evidence of a replacement mortality effect.

9
"wealth." This measure was constructed along the lines proposed by Filmer and Pritchett (Filmer and Pritchett 1999) through the use of Principal Components Analysis (PCA)l on a battery of indicators of dwelling characteristics and ownership of consumer durables (e.g., flooring material, roof material, number of rooms in relation to household size, type of drinking water source, and toilet type). The consumer durable questions included the household's ownership of a fan, a radio, a television, a bicycle, a car, a refrigerator, and so on. A PCA was undertaken on the full sample for each country separately, and the first principal component was retained and used to rank households and thereby children. In each case, the factor loading matrix was renormalized if necessary to ensure that the principal component was increasing in wealth.

**Table 1. Definitions of child health outcome variables**

|_Variable_|_Definition_|
|---|---|
|InfantMortality|The numberofdeathstochildren under12monthsofageper 1,000live|
|Rate (IMR)|births.Figures are basedonbirthsinthe10years precedingthesurvey.|
|Under-Five<br>|Thenumberofdeathstochildren underfiveyearsofageper1,000live<br>|
|MortalityRate<br>(U5MR)|births.Figures are basedonbirthsinthe10years precedingthesurvey.|
|Percentof|Percentofchildren whose height measurementismorethantwostandard|
|Children Stunted|deviationsbelow themedianreference standardfortheir ageasestablished|
|(LHFA)|bytheWorldHealthOrganization,theU.S.Centersfor DiseaseControl,and<br>theU.S.NationalCenterforHealthStatistics. Thefiguresare basedona<br>sampleoflivingchildren underthree,four,orfiveyearsofage,depending<br>onthecountry.|
|Percentof|Percentofchildren whoseweightmeasurementismore than twostandard|
|Children|deviationsbelowthemedianreferencestandardfortheir age as established<br>|
|Underweight|bytheWorldHealthOrganization,theU.S.CentersforDiseaseControl,and<br>|
|(LWFA)|theU.S.NationalCenterforHealthStatistics.The figuresarebasedona<br>|
||sampleofliving children underthree, four,orfiveyearsofage,depending<br>onthecountry.|
|Diarrhea|Percentofsurviving childrenunderthree, four,orfiveyearsold(depending|
|Prevalence(DIA)|onthecountry) whohaddiarrhoeainthetwoweeksprecedingthesurvey,<br>basedonmothers'reportsconcerningthepresenceofloosestools.|
|AcuteRespiratory|Percentofsurvivingchildrenunderthree,four,orfiveyearsold(depending|
|Infection|upon thecountry) whohadacough accompanied byrapidbreathinginthe<br>|
|Prevalence(ARI)|twoweeksprecedingthesurvey,asdefined and reportedby themother.|

Separate means for the child health outcome variables were computed in the study for each of five wealth quintiles, obtained by ranking households into five groups equal in size in terms of the number _of people._ Though these are quintiles in terms of people, they are not quintiles in terms of children relevant to the indicator in question. For example, in the case of under-five mortality, they are not quintiles of children at risk. We can get round this problem, however, using a summary measure of inequality.

X A PCA searches for the linear combinations of the variables selected that account for the maximum possible variance in the data.

4
**Table 3.1 Bids for the Santiago-Los Vilos concession**

|**Consortium**|**Toll offer expressed in pesos**|**Duration of the concession**|
|---|---|---|
||**of 12/94**|**offered (months)**|
|Trinela Ruta 5|1,000|276|
|Ica-Tecsa|1,044|300|
|Infraestructura 2000 S.A.|1,074|300|
|Consorcio Obras Viales|1,000|285|

|Source: MOP.|
|---|

The advantage of this scheme is that it gives MOP more control to set tolls. Therefore, potential inefficient traffic diversions associated with high levels of this variable are avoided. Conversely, low toll levels may also be undesirable if there are congestion problems on the highway.

# **3.2.1 Tendering mechanism and the financial viability of the concessions**

As the programme continued, the authorities became concerned about the financial viability of firms that bid too low (that is the minimum tariff and a short concession period). Calculations by MOP showed that the winning bids in several concessions implied a high risk of future financial instability for the franchise holder.

There are several reasons why firms may pursue such an apparent loss-making strategy. First, when several projects are going to be concessioned, firms may be interested in giving a signal of low cost or aggressive behaviour to other bidders in order to discourage some competitors from participating in future contests.

Second, when construction firms are the principal consortium partner, the chief interest in the project may derive from the ensuing construction contracts rather than the subsequent operation of the concession.! In this context, they may bid below costs in order to secure the construction contracts, disregarding the long-term financial viability of the concession, possibly because they can later pass on these costs to other consortium partner or creditors.

Third, firms may behave opportunistically. They bid low, and once they win the franchise, pressure the regulator to renegotiate the conditions of the contract. This strategy would not work if the government could commit to not renegotiate _ex-post._ However, this is nearly impossible for governments to do. If the concession runs into financial problems in the future due, for example, to low revenue flows, the government will find it difficult to let the concession fail. There are political problems associated with this event, and there are also the costs and delays in re-tendering the project. Therefore, bidding low and renegotiating afterwards may be a viable strategy for a potential concessionaire (a phenomenon called "low balling").

7 The issue of the potential perverse incentives of construction companies in road concessions is not well explored in the literature but some analysts mention this as a problem in several toll road programmes, including France and Mexico (see Gomez-lbafiez and Meyer (1993) and Gomez-lbafiez (1999)).

9
- 43 -

two large countries, India and China, it appears that the coal sector constitutes a net drain on government resources; while in the two smaller countries, Colombia and Morocco, the Bank projects were financed without any government loan or equity contribution.

||Av<br>Pe|erage<br>rcent UMn||Coma nt|g|
|---|---|---|---|---|---|
|Internal<br>cash generation|24|0 - 52|0 in|1case<br>(|China)|
|IBRD/IDA|39|35 - 48||||
|Other external<br>loans|6|0 - 28|0 in|2**cases**||
|Government loans|4|0 - 12|0 in|3cases||
|Government equity|26|0- 62|0 in<br>-other|2 cases<br>3case|; 31-62 in<br>s|

# B.5 Use of Pricin; Covenants

16. Four of the five projects included specific price covenants. In both Morocco and China, agreement **was reached** on a new principle for price determination: an import parity link and LRMC, respectively. In India extensive discussions on coal pricing were held (partly in connection with a sector report), and agreement was reached to review prices periodically in order to ensure the financial viability of the producing enterprise and provide "adequate" resource mobilization in the sector.

# C. THE MAJOR GAPS

17. Efficiency pricing is clearly relevant to the coal sector and is relatively straightforward to apply and implement. A guideline has been prepared by the Industry Department, and is being followed in the SARa. In **the** developing countries experience is mixed, but it appears that major changes in the way coal prices are set are being made in several countries. Compared to other sectors, the coal sector is particularly advanced in its handling of the institutional issues of price determination.

18. **The** areas **wher,** more analysis would **be** useful at the project level include:

- the relationship of consumer coal prices to those of competing energy products; the scope for using "rationing prices" (e.g., import parity) for **some** grades of coal that **are** in an **excess** demand situation in countries **where** coal production or transport capacity cannot be expanded in the short-run;
<!-- Start of picture text --> LBY: Growth of GDP and Credit Cycle Peaks<br>1967 1977 1987 1997 2007 2017<br>year<br>Growth of GDP Peak<br>C- Western countries and Japan<br>NOR: Growth of GDP and Credit Cycle Peaks ND: Growth of GDP and Credit Cycle Peaks<br>1967 1977 1987 1997 2007 2017 1967 1977 1987 1997 2007 2017<br>year year<br>Growth of GDP Peak Growth of GDP Peak<br>JPN: Growth of GDP and Credit Cycle Peaks GBR: Growth of GDP and Credit Cycle Peaks<br>1967 1977 1987 1997 2007 2017 1967 1977 1987 1997 2007 2017<br>year year<br>Growth of GDP Peak Growth of GDP Peak<br>150 1<br>100 .8<br>.6<br>50<br>percent<br>.4<br>0 local_peak_LBY<br>.2<br>-50<br>0<br>6 1 80 1<br>.8 60 .8<br>4<br>.6 40 .6<br>2<br>percent .4 percent 20 .4<br>local_peak_NOR local_peak_OMN<br>0<br>.2 0 .2<br>-2 0 -20 0<br>15 1 1<br>6<br>10 .8 4 .8<br>.6 2 .6<br>5<br>percent .4 percent 0 .4<br>local_peak_JPN local_peak_GBR<br>0<br>.2 -2 .2<br>-5 0 -4 0<br><!-- End of picture text --> 39
national level. Simulations with the Food and Agricultural Policy Research Institute (FAPRI) stochastic model of the U. S. agricultural sector indicate that additional ethanol production capacity results in an increase in corn prices but reduced prices for ethanol, corn by-products, and soybean meal. Corn production also increases, while corn exports, feed consumption, and stocks decline. Increased ethanol production results in more production and lower prices of corn by-products. Soybean meal prices are reduced by 10%. Livestock and poultry sector effects are relatively small in aggregate. Producers who can take advantage of lower corn by-products and soybean meal prices benefit, while those feeding rations heavily dependent on grain face higher costs. The taxpayer cost of farm programs is reduced by an average of $1.0 billion per year between 2011 and 2015. Increases in ethanol consumption could reduce tax revenue, given differences in the tax treatment of ethanol and regular gasoline. Net farm income exceeds baseline levels by an average of $298 million per year over 2011-2015. Higher corn receipts are partially offset by lower government payments. Rental payments increase, as do other production costs (FAPRI 2005). POLYSYS is another partial-equilibrium model of the U. S. agricultural sector that is used to simulate changes in crop and livestock supply and demand, farm gate prices, cash receipts, government payments, and net realized income in response to changes in policy, economic, or resource conditions. This model has been expanded to include markets for switchgrass, residues from corn and wheat and woody feedstock such as forest trimmings, and wood and mill wastes; and it also includes possibilities for conversion of pastureland and Conservation Reserve Program (CRP) land to cropland. This model was used to predict commodity prices in the production scenario of 86 billion gallons of ethanol in the United States by the year 2025 under certain assumption of yield for major food crops (corn, 195 bushels/acre; soybeans, 51 bushels/acre; and wheat, 53 bushels/acre) and energy crops (6 to 12 dry tonnes/acre) as well as assumptions of improved conversion efficiencies (89 gallons of ethanol per ton of cellulose and 3 gallons of ethanol per bushel of corn). This model predicts an increase of 13%, 6%, and 30% in the price of corn, wheat, and soybeans, respectively, in the year 2025. Major acreage 46
Policy Research Working Paper 10909

# **Abstract**

This paper provides novel evidence of the trade-offs policy makers face when designing simplified tax regimes for small businesses. First, it provides a comprehensive stocktaking of the main features of these regimes across Sub-Saharan Africa: they are adopted by two-thirds of countries, but their design varies greatly. Second, it draws on administrative and survey data for a thorough examination of a specific simplified tax regime. This analysis shows most small businesses lack knowledge about design features, such as the existence of a minimum exemption threshold, but they react strongly to increases in tax rates by lowering their declared turnover. Finally, the paper presents the results of an experiment that encourages taxpayers to pay fixed amounts—a potential alternative design of a simplified tax regime that aims for a better balance of the trade-offs facing policy makers. The findings show that providing simple guidance about how much small businesses with similar characteristics typically pay in taxes can increase revenue, but this reduces equity among taxpayers.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at choy@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility. worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G<br>R E<br>N<br>S<br>I P<br>Y E<br>K A<br>C A<br>R P<br>LI R<br>O E<br>O C<br>W R<br>H<br>S<br>P<br><!-- End of picture text --> _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
low. Singapore often appears as a special case in the simulations that follow. In addition to its small size, it is likely that the low values of _θ_<sup> ̄</sup> _i_ and _γi_ are responsible for the particular behavior of Singapore in our counterfactual analysis. At the other end of the spectrum, Indonesia has the higher transaction costs, which is consistent with the Doing Business indicators and recent literature (e.g. Barron and Olken, 2009).

**Trade costs:** In addition to transaction costs that are also incurred within borders, crossborder transactions face an additional burden. The nature and size of the extra cost affecting international transactions is the matter of an extensive debate in the trade literature (transport costs, asymmetric information, marketing cost, technical barriers, or cultural differences). There is however a consensus that these costs are large and have large effect on cross-border trade. While distance usually plays a key role in explaining the pattern of international trade (see Disdier and Head, 2008), distance is not as crucial for trade among Asian countries.<sup>38</sup> We therefore assume that cross-border trade costs are uniform across all country pairs in our sample. We fit the trade cost parameter by asking the model to replicate the global ratio of trade to output.

**Simulation results on other moments:** Before turning to the counterfactual results we briefly describe the benchmark equilibrium. By construction, our model is able to reproduce key indicators of fragmentation such as the gross-output-to-value-added ratio and values of _D_<sup>_∗_</sup> . Alternatively, we can examine how the fitted model fares in terms of other indexes such as indexes _D_ , _N_ and _N_<sup>_∗_</sup> described above.

Table 3 compares indexes from the model vs. data. In broad terms the magnitudes are consistent with the data, even though they are constructed in very different ways. These indexes from the data are computed at the industry level then averaged across industries. Index _N_ in the benchmark calibration is computed for the most downstream firm in the chain while index _D_ is a weighted average across firms weighted by value-added at each stage (same for _D_<sup>_∗_</sup> ).

Indexes _D_ and _N_ tend to be too high in our calibrated model (too much fragmentation), but they are strongly correlated with their data counterpart (86% correlation for _N_ and 44% correlation for _D_ ). With the exception of Singapore, the richest and poorest countries tend to be more downstream (lower index _D_ ) and have a smaller number of embodied stages (index _N_ ). With the exception of Singapore, middle-income countries in our sample such as Taiwan and Malaysia end up with the highest indexes _D_ and _N_ both in the calibrated model and the data.

> 38In a standard gravity equation of trade using the IDE-JETRO data, the coefficient for distance is not significant while the estimate border effect is large and significant, economically and statistically. Of course, this is a small sample of only 10 countries.

44
include second generation migrants. Both Western and non-Western immigrants are included in our definition of migrants, although the large majority immigrant students in the PRIMA sample are of non-Western origin (95%).

Student performance is measured by tests administered by the Dutch National Institute for Educational Measurement in Dutch language and mathematics. These tests were developed by the Dutch government testing agency to measure students’ readiness in the two topics. We standardize individual raw test scores in the dataset so that the mean is 50 and the standard deviation is 10. Within each classroom, all students are sampled as long as they are present the day of the test.

# **4.2 Descriptive Statistics**

Table 1 and Table 2 report student-level and grade-level summary statistics of our sample, respectively. Table 1 shows that immigrant students have low levels of parental education compared to native students, as it is the case in most European countries. In line with historical patterns of migration to the Netherlands, the largest groups of first -generation immigrants among our sample of primary school students are Turkish/Moroccans (27%) followed by students from the ex-Dutch colonies (7.5%). More than 43 percent of immigrant children have a father that did not study beyond primary school, as opposed to only 15 percent of native Dutch students. The proportion of immigrant students whose father did not study beyond primary school is particularly high among Turkish and Moroccan immigrants, which account for around one fourth of the total number of immigrants in our sample. AMong the Moroccan and Turkish students, 67 percent have a father who did not study beyond primary school, while this proportion is only 29 percent for immigrants from other countries. Table 1 shows that immigrant children in the sample perform on average 13