rafmacalaba/datause-encoder-data huggingface dataset:
7 In contrast to approaches which focus on products in the core group, defrnitions of manufactures have been used for compilition of trade data which iuclude some highly processed food, beverage, tobacco, animal and vegetable oils and (refined) petroleum products. UNIDO, in pardcular, extensively utilized this approach which added thirty-two, three and four-digit SfTC items to the core group (see Appendix Table 1)." In addition, UNIDO deleted pearls and precious stones (also dropped by the World Bank in MR(87)), developed cinematographic fim, and works of art and antiques from its derfintion of manufactures. UNIDO's objectives in utilizing this defnition was to reconcile the major differences that existed between production and trade series for manufactures, and also to include important fabricated goods excluded from the limited core definitions. In terms of product coverage, the result was quite close to the IBRD and C ATT series on manufactures output (i.e. GATr(2) in Table 1).12 For this reason, the following analysis frequently contrast results from the UNIDO (trade nd output) defimition of manufactures with those for the IBRD/UNCTAD/GATT definition.

A question of considerable importance concems the influence of these different defiitions on production and trade data series and empirical studies that employ the statistics. For a test, trade statistics for 72 developing countries were drawn for 1987 directly from United Nations Series D trade tapes. These data were then used to compute the total exports (in United States dollars) of each country as well as exports

**"** As noted, the different definitions have been due to a reluctance to classify processed foods (consumables) as manufactures, but it should be noted that consumables are included in the core definitions. For example, SITC 5 contains materials like vitamins and provitamins (541.1), food dyes (532.1), gelatin (599.5) and various pharmaceuticals (541.4).

12 Since the GATT(2) definition was in terms of ISIC industries an available concordance was employed to identify matched SITC products. The latter were then used to tabulate trade statistics from the UN Series D tape.
If discretionary exceptions to tariff-cutting formulas are to be allowed—as they have been in the Doha proposals—however, the design of these exceptions is important, and should take into account political-economy considerations, and the implications of the proposed exceptions for the market access of partner countries. The product exceptions allowed in the Doha proposals for agriculture involved only limits on the number of tariff lines, a totally inadequate discipline. As shown by Jean, Laborde and Martin (2011), this approach allows members to apply small cuts to products that are both important and for which large cuts in applied tariff rates would be required by the formula. As we have seen, this resulted in the cuts in applied tariffs being reduced dramatically relative to the formula cuts—particularly in high-income countries. As they showed, moving to disciplines on the share of trade covered would have sharply reduced the adverse consequences of exceptions for the negotiations. Constraining the impact of flexibilities by limiting the trade volume on which they could be applied was shown by Jean, Laborde and Martin (2011) to be very helpful in reducing their adverse impacts on market access. Perhaps a better— but still potentially feasible—approach would be to constrain the use of flexibilities by their impact on a mercantilist trade restrictiveness index of the type proposed by Anderson and Neary (2003). Alternatively, a cost for flexibilities might be incorporated by requiring countries to negotiate exceptions from the general tariff formula via request-and-offer negotiations.

# 4.2 What Might Make an Agreement Feasible?

Using the Agricultural Market Access (AMA) proposals and the Jean, Laborde and Martin (2011, 2014) framework, we examine the implications of the tariff-cutting formulas for welfare and market gains versus political costs. For this analysis, we assume that consumer preferences can be represented using a CES function covering all goods, and that policy makers ignore any impacts of their tariff changes on world prices. Table 6 displays for all WTO members as a group, and for selected countries, the expected effects of the formula (scenario C in Table 3), and of the formula plus flexibilities (scenario D in Table 3) relative to a proportional cut in bound tariffs leading to the same market access outcomes. All relevant variables for policy makers (welfare gains, market access concessions i.e. import increases, and political costs) are expressed as a percentage of the scenario C effects (the strongest market opening, before introducing product flexibilities). We also characterize each scenario using the ratios that characterize different policy makers: efficiency gain per unit of political cost for the **benevolent policy maker** , welfare gain per unit of market access for the **social planner** ; and political cost per unit of market access for 18
of reserves may reflect conservative reserving in the face of long delays in settlement or it may be caused by excessive reserving in order to understate profits and lower tax liability. As concerns the unearned premium reserves, their appropriate level depends on the periodicity of premium payment. Policies with premiums paid annually require higher unearned premium reserves than those where premiums are paid on a monthly or quarterly basis. Companies specializing in the latter type of policies, such as medical insurance, would tend to report lower levels of reserves.

Reserving policies take account of the reserves established by reinsurers. The unearned premium reserves may have to be increased in the future under new required reserving practices. The level of the outstanding claims reserves implies that on average claims are settled in less than 6 months. The vast majority are probably settled within a few weeks of reporting but larger and more complicated and disputed claims may take much longer.

**Table 8: Performance of General Insurance, 1997-2002**

||1997|1998|1999|2000|2001|2002|
|---|---|---|---|---|---|---|
|Gross Premium Income (GPI) (mn JD)|69.94|85.11|85.05|87.90|103.04|128.40|
|GPI Growth (%)||21.7|-0.1|3.3|17.2|24.6|
|Reinsurance Ratio %|41.5|40.5|39.7|41.5|38.6|37.8|
|Loss Ratio (NIC/NEP) (%)|78.6|77.2|78.9|80.9|81.6|75.9|
|Net Commission (% GPI)|-3.1|-2.6|-3.1|-2.5|-2.3|-2.6|
|Total Expenses (% of GPI)|17.5|16.8|17.6|18.5|16.2|13.8|
|Traditional Combined Ratio (%)|93.0|91.4|93.5|96.8|95.5|87.1|
|Net Combined Ratio (% of NEP)|103.3|101.8|103.3|108.0|106.2|95.8|
|Underwriting Result (% of NEP)|-3.3|-1.8|-3.3|-8.0|-6.2|4.2|
|Unearned Premium Reserves (% of NEP)|46.7|42.6|42.2|43.0|40.5|42.1|
|Outstanding Claims Reserves (% of NEP)|33.7|30.4|31.5|34.9|35.4|35.0|
|Total Reserves (% of NEP)|80.4|73.0|73.7|77.8|75.9|77.1|
|Outstanding Claims Reserves (% of NIC)|42.9|39.4|40.0|43.1|43.4|46.1|

Source: Insurance Commission Expense ratios amounted on average for all branches to 14 percent of gross premiums. They were much higher for credit insurance, probably in part because of its very low volume and in part due to the nature of the business: for credit insurers the objective is to utilize underwriting techniques so as to avoid claims altogether, just as a bank seeks to eliminate loan losses. The result is high underwriting expenses and low claim ratios. Several lines benefited from net commission income, i.e. commissions received from reinsurers exceeded the commissions paid to local brokers and agents. This is a usual occurrence in developing countries and reflects the large reliance on reinsurance, especially in fire, marine and general accident policies.

Insurance performance varies considerably across individual lines (Table 9). Fire, marine and general accident policies tend to produce positive results, whereas motor, 12
Instead, in most countries, the wealthiest quintile was 9 percentage points more likely than the poorest to use their savings to cope with the economic impacts of the pandemic. For instance, in Indonesia, 42 percent of households in the top 20 used their savings to cope with lower labor income losses, compared to 26 percent among the poorest quintile. Thus, while the pandemic may have had sweeping impacts across the welfare distribution, among those that have experienced a shock, poorer households have been forced to rely on coping mechanisms that may have more severe consequences for their future prospects.

Figure 10. Poorer households that experienced labor income losses were more likely to sell assets or increase debt than the wealthier counterparts <!-- Start of picture text --> Sold assets or increased debt to cope<br>100<br>80<br>60<br>40<br>20<br>0<br>Pooled Indonesia Lao PDR Mongolia Myanmar Philippines Vietnam<br>Q1 Q2 Q3 Q4 Q5<br>Relied on savings to cope<br>80<br>60<br>40<br>20<br>0<br>Pooled Indonesia Lao PDR Mongolia Myanmar Philippines Vietnam<br>Q1 Q2 Q3 Q4 Q5<br>Reduced food consumption to cope<br>100<br>80<br>60<br>40<br>20<br>0<br>Pooled Indonesia Lao PDR Mongolia Myanmar Philippines Vietnam<br>Q1 Q2 Q3 Q4 Q5<br>Percent of households who<br>experienced labor income losses<br>Percent of households who<br>experienced labor income losses<br>Percent of households who<br>experienced labor income losses<br><!-- End of picture text --> Note: Coping mechanisms that involve selling assets or increasing debt include: selling farm or non-farm assets, crediting purchases, delaying payments, and borrowing from friends, family, moneylenders, or other sources. 95% confidence intervals for difference from Q1 are shown (rather than from zero). The pooled regression is unconditional; results including country and period fixed effects are similar. Source: HFPS 23
mothers, but private preschools have a small and statistically significant effect if we control for district trends. The presence of any preschool-aged child still negatively affects maternal employment, albeit with smaller magnitudes: -0.034 compared to -0.051 for public preschools in DDD and -0.025 to -0.042 for private preschools. This suggests that some of the reduction in the likelihood of working when taking care of a young child is attributable to individual career and familial preferences. It seems puzzling that eligible mothers with access to an additional public preschool per 1,000 children would have worked more than non-eligible mothers. This may suggest that, controlling for individual preferences, mothers with a young child have greater financial needs and would have been more motivated to work had they been afforded alternative childcare services.

# **_5.2 Alternative specifications_**

Our preschool data were obtained from PODES, which is only available in 9 years of 28 years in our constructed panel. The most conservative approach is to restrict the analysis to PODES years only, as in Table 2. Our second approach is to infer preschool data in-between PODES years using the closest upper year available. Lastly, we can fit a linear projection between non-missing PODES years. Table 3 reports the estimates of the three empirical strategies with the three treatments of missing PODES years. All regressions include district, year, mother’s age fixed effects and an urban residence dummy; and <u>do not</u> include district-specific trends. Columns 1-3 repeat the estimates from Table 2 without district trends. Columns 4-6 report estimates when we infer inbetween PODES years and columns 7-9 report estimates when we fit a linear projection between non-missing PODES years. Across the board, we note that the general story and overall statistical significance do not change whichever preschool data we use. In the restrictive approach of using only PODES years, we introduce identification issues in the DDD-FE strategy, as we can only leverage variations as mothers transition in and out of eligibility over time, potentially giving up the statistical power to detect small effect sizes in subsequent analyses.<sup>18</sup> In fitting a linear projection, we can either use preschool densities directly or we can separately fit linear projections for preschool counts and children populations. We opt to project preschool densities directly.

> 18 In results not shown, we find that women are 2.2 percentage points more likely to become agricultural workers if exposed to better public preschool access. The effect is statistically significant at the 10 percent level, but the statistical significance no longer holds after adjusting for multiple hypothesis testing. Inferring preschool data inbetween PODES years substantially increases the sample size needed to detect the effect. We note that women are 2.9 percentage points more likely to become agricultural workers. The effect is statistically significant at the 5 percent level and stays significant after multiple hypothesis testing adjustment.

17
Table 10

**AFP Investment** Portfolio

||12/95|9/96|
|---|---|---|
|Bonds*|33.8|0.0|
|Financial sector bonds|0.0|33.5|
|Term deposits|33.2|11.5|
|Corporate bonds|0.0|10.7|
|Treasury bills|0.0|9.4|
|Securitized instruments|0.0|7.3|
|Government bonds|0.0|6.1|
|Mortgages|3.9|6.0|
|Coffee savings bonds|6.3|5.6|
|Rural development|9.4|3.3|
|bonds|||
|Equities|0.7|0.4|
|Others|12.7|6.2|

*government, financial sector, and corporate bonds

Source: Superintendencia Bancaria The calculation of the minimum rate of return for mandatory pension funds in Colombia is very complicated. It is determined as a composite of the AFP industry's average performance and the performance of a reference portfolio defined by the superintendency. Half of the minimum return is determined as 90 percent of the weighted average performance of all pension funds. In calculating the average, the maximum weight of any one AFP may not exceed 20 percent. The other half of the minimum return is calculated as the weighted average of (i) 90 percent of the performance of the country's three stock exchanges taking into account the percentage of pension assets invested in equities (but at least 5 percent) and (ii) 95 percent of the return achieved by a reference portfolio, which in its composition takes into account the existing average portfolio of the AFP industry.

The performance of the mandatory pension funds is calculated as annualized rate of return during the last 36 months (24 months in the case of severance funds). During the first three years of a pension fund's existence, the rate of return will be calculated for the period since the start of operations. Compliance with the minimum rate of return will be checked by the Superintendency on a quarterly basis. If an AFP underperforms the benchmark, the shortfall has to be covered through the stabilization reserve, which is established as described above.

In Colombia, AFPs are required to publish their returns both gross and net of commissions (but not net of insurance premiums). This rule applies to mandatory and voluntary pension funds as well as to severance funds. Nominal gross and net returns are reported by the APFs and published by the superintendency quarterly.

Nominal returns have been relatively stable given that fixed income securities make up the largest part of the AFPs' portfolios. On average, the annual nominal return has been 35.7 percent from the start of the AFP system to March 1997. The returns of the individual APFs for the same 33
Table 6. Model With Interaction Between Inequality and Initial Income (Difference-GMM Estimation)

|Dependent Variable is:|||Δ<br>|ln(yit)<br>|||
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Inequality Variable is:|Market Gini|Net Gini|Market Gini|Net Gini|Market Gini|Net Gini|
|Sample:|All Co|untries|Excluding<br>Coun|Transition<br>tries|Excluding<br>Coun|East Asian<br>tries|
|ΔInequalityit|20.00***<br>(4.11)|23.68***<br>(3.56)|19.30***<br>(4.13)|24.43***<br>(3.86)|19.28***<br>(4.29)|23.41***<br>(3.93)|
|ΔInequalityit|-2.71***|-3.35***|-2.63***|-3.47***|-2.61***|-3.32***|
|*Δln(yit-1)|(0.53)|(0.48)|(0.54)|(0.52)|(0.55)|(0.53)|
|Δln(yit-1)|0.26***<br>(0.08)|0.35***<br>(0.09)|0.27***<br>(0.08)|0.38***<br>(0.11)|0.26***<br>(0.07)|0.37***<br>(0.10)|
|AR(1) test, p-value|0.00|0.01|0.00|0.00|0.00|0.00|
|AR(2) test, p-value|0.75|0.51|0.97|0.51|0.83|0.58|
|Hansen J-test, p-value|0.15|0.20|0.14|0.30|0.11|0.29|
|Country FE|No|No|No|No|No|No|
|Time FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|614|614|590|590|595|595|

Note: The method of estimation is difference GMM. Standard errors are shown in parentheses. The instrument for Δ _Inequality_ is Δ _Residual Inequalityit =_ Δ _Inequalityit – α_ Δ _ln(yit)_ , where α measures the effect that ln(yit) has on _Inequality_ . *Significantly different from zero at the 10 percent significance level, ** 5 percent significance level, *** 1 percent significance level.

31
We can then summarize the decision in an expected present value framework as follows: Firm _f_ will register if the discounted present value of profits in the registered state Π<sup>_R_</sup> minus profits in the unregistered state Π<sup>_NR_</sup> is larger than the costs, both direct and indirect, e.g. monetary, time and information costs as well as taxation and compliance. Clearly, the difference in profits between the two states accounts for the lower cost of capital, when registered, and the ability of a registered business to access additional markets and a potentially different (and larger) set of players.

If firms are credit constrained, then the monetary _FEES_ can contribute substantially to the inability to register. We should expect, other things equal, less constrained firms to register; a similar argument would apply to time constraints, due to the size or business process of the firm. However, we also need to consider that the availability of information may or may not be highly correlated with the degree of credit to which a firm has access. The intervention we implement in this work aims mainly at increasing the amount of information on registration available to the firm. At the same time, one can think, that by informing firms’ owners about the process, the information also modifies the expectations regarding all the components of costs on the right-hand-side of the inequality. There are other reasons why the first three terms on the right-hand-side of the inequality might be affected by the intervention; in particular _FEES_ are going to be reduced because an intermediary will not be needed, and better knowledge of the actual registration process would also reduce the time it would take to register ( _TIME_ ).

Notice that the registration reform implemented by the Bangladeshi authority, discussed below, is orthogonal to our intervention. The effects of such intervention need not be homogeneous in the population of firms. Indeed, one can conjecture that small-scale production firms will probably not register as the fixed cost of registration will outweigh the benefits, however bigger (unregistered) firms oriented toward bigger markets might be affected positively by the intervention. It is however an empirical issue as there are a large number of conflicting forces at play.

# **3 Context: The Business Registration Reform in Bangladesh**

In 2009-2010, Bangladesh implemented a major information and communication technology (ICT) based business registration reform initiative.<sup>1</sup> Prior to this reform, registering a business required on average 42 days (against the international best practice of 1 day) to complete an 18 steps process of registration. This would require on average 4-5 visits to the agency, sometimes 10 visits, and a 4-5 week payment process of registration fees through a stamp duty

> 1For the details of the reform see World Bank Group (2013).
# **Whose Power Gets Cut? Using High-Frequency Satellite Images to Measure Power Supply Irregularity**<sup>**1**</sup>

Brian Min University of Michigan Zachary O’Keeffe University of Michigan Fan Zhang World Bank

# **Key words:  Power outages, load shedding, nighttime lights, remote sensing, DMSP, India**

1 This paper is part of a broader analytical effort to assess the cost of power sector distortions in South Asia conducted by Office of the Chief Economist of the South Asia Region. The authors are grateful to Chris Elvidge, Kim Baugh, Yue Li and Virgilio Galdo for providing access to the data. We thank Martin Rama and Kwawu Mensan Gaba for helpful comments on the methodology of the study. Priyamvada Trivedi and Fatima Najeeb provided excellent research assistance. Financial support from the Partnership for South Asia Trust Fund is greatly appreciated.

1
collected data from about 2,800 households sampled across 17 districts and 150 villages. Roughly 60 percent of the households surveyed were farm households and a considerable fraction of these operated multiple plots. The survey was designed to provide detailed information at the plot level on land characteristics (soil type, irrigation, and so forth), land tenure (including characteristics of tenants and owners and details of the contracts), and production activities. These data were collected for the two main agricultural seasons, kharif (May-November) and rabi (November-May). The main cash crops, cotton, rice, and sugarcane, are grown in kharif, while the main food crop, wheat, is grown in rabi.

To provide evidence on the holdup problem, we want to focus on an activity that is, in the fi rst place, at least partly an investment. Moreover, we would like this investment to be relationship speci fi c and noncontractible. Last, but not least, it must be relatively easy to measure. Farmyard manure (FYM) meets all of these criteria.

FYM, composed largely of cattle dung, provides variable amounts of the three principal soil nutrients, nitrogen, phosphorous, and potassium. Equally, if not more, important than its role as a nutrient source, FYM improves the quality of the soil by increasing aeration, water retention, structure, and ability to retain nutrients (Government of Pakistan, 1997; Gaur, 1992). Further, these bene fi ts of FYM are long-lasting.<sup>5</sup> Extended fi eld trials in India cited by Gaur (1992) show that the marginal effects of FYM on grain yields persist for at least three years following the initial application.<sup>6</sup> Chemical fertilizers, meanwhile, are used extensively in Pakistan, but they leach from the soil relatively quickly and hence their productivity effects are essentially limited to the season of application.

Because FYM, once applied and incorporated into the soil, is not portable, it is a relationship speci fi c investment in the purest sense. By contrast, investments like experimentation with new farming techniques or seed varieties, which have an aspect of general human capital, can be transferred, at least in part, to another landlord-tenant relationship. Still, there are other, larger scale, purely speci fi c investments that farmers undertake in rural Pakistan, such as constructing irrigation and drainage canals, clearing land, and digging wells. However, these fi xed investments are, for the most part, contractible; the tenant or some other party can be paid to do them for the landlord. It is, to be sure, an interesting question as to whether contractible investment is underprovided on tenanted land, but it is not one that speaks directly to the holdup problem.

> 5 This feature of FYM has been exploited by Jacoby, Li, and Rozelle (2002) in their study of the incentive effects of land expropriation in rural China. Besley (1995) also includes manuring among the investments he examines.

> 6 The marginal effect of FYM in succeeding cropping seasons averaged 50-63% of the effect in the inital season over the three years of the experiments.

4