rafmacalaba/data-use-mentions-extended huggingface dataset:
**5.** CONCLUSION

# **5.1 Policy implications**

A number of implications for policy are suggested by this analysis. Many, but not all, of these options are already being considered, or imp'e'~mented in pilot forms by the Government of Orissa. A number of these initiatives are also expected to be of relevance to other states:

- **_Gender and land rights:_** women's access to and effective control over land may be enhanced through joint land titling. This measure is rather limited in scope, since ideally what need to be promoted are women's independent land rights. But while the principle of joint titling is readily accepted at the level of the Government of India, it has yet to be realized in practice in Orissa. In focus group discussions, village women assert that their bargaining power vis a vis their husbands and in-laws would be enhanced considerably by joint title over land. The common objection that this may make it more difficult for women to escape from abusive marriages was for them a second order consideration.

- **_Organization_** _of_ **_land administration:_** a critical assessment of the respective roles and responsibilities of the Department of Revenue and the Board of Revenue appears warranted, in order to identify overlapping functions and areas where coordination between the two could be streamlined for increased efficiency. In the context of the ongoing computerization of land records, it will also be important critically to assess the particular responsibilities of the local-level Revenue Inspector. Many of the presumed advantages of computerization will not be realized unless limiting constraints on RIs' time and the incentive structure within which they work are addressed.

- **_Land_** _records_ **_and registration:_** at present, there is little or no coordination between the maintenance of land records, which is the responsibility of revenue inspectors and tehsildars; and land registration, which is the responsibility of sub-registrars. Measures to coordinate and integrate these two
was conducted from September 2019 to March 2020 and included 601 firms. Three follow-up phone surveys focusing on a subset of questions (including about sales and employment) were conducted in June and July 2020 (June 2020 round), December 2020 to February 2021 (December 2020 round), and July to September 2021 (July 2021 round). The response rate was 96.1 percent in the June 2020 round and 95.1 percent in the other rounds. Questions about changes in firm sales used a ‘pre-pandemic’ level of the same month in 2019 (to address concerns about seasonality across the calendar year) and changes in employment (both permanent and temporary) were based on a ‘pre-pandemic’ level of February 2020.

The survey samples of formal firms were largely based in urban areas, had 20–100 workers, and were mainly involved in retail, manufacturing (other than food), and other services (excluding agricultural inputs and equipment). The distribution of firms by location is Kitwe (100, 16.6 percent), Livingstone (105, 17.5 percent), Lusaka (294, 48.9 percent), and Ndola (102, 17.0 percent). By firm size, it is small (231, 38.4 percent), medium (250, 41.6 percent), and large (120, 20.0 percent)<sup>3</sup> . By primary activity, it is manufacturing (121, 33.9 percent), retail (123, 20.5 percent), and other services (194, 32.3 percent).

# **3.1.2 Tax administrative data**

There are three main types of tax in Zambia; corporate income tax (CIT), personal income tax (PIT), and VAT. CIT in Zambia is taxed in accordance with the principal activity of the business. The CIT rates range from 10 percent for incomes earned from agriculture to 40 percent
**Table 2. Pros and Cons of Pricing Options for Natural Gas**

|_Price based on_|_Pros_|_Cons_|
|---|---|---|
|Costs|*Reflects costs.<br>* Prices are related to costs at the wellhead in most<br>countries with a competitive natural gas market.|_*_No marginal cost of extracting<br>Mexican natural gas because it is a<br>byproduct of oil.<br>* Does not reflect the opportunity cost<br>of selling Mexican natural gas in the<br>North American market.|
|Comparisons<br>with other fuel<br>prices|*Reflects prices in international markets.<br>*Prices of substitutes are economically related.<br>* There are price series data.|*Potential prices of substitutes<br>subsidized in non-explicit ways.<br>*International markets of substitutes<br>have different dynamics to the natural<br>gas market.<br>* Accounts for opportunity cost of other<br>markets, not the natural gas marlcet.|
|A benchmark|*Considers the opportunity cost of Mexican<br>natural gas in the North American market.<br>-The relevant benchmark, the Houston Ship<br>Channel, is a liquid market, it has an associated<br>hedging market, it is close to the physical<br>connection to the Pemex pipeline system.<br>* Methodology has some similarities with prior<br>Pemex methodology.<br>* Marginal costs of imported gas and domestic gas<br>are the same at the arbitrage point.|*Brings disturbances from U.S.<br>weather into the Mexican market.|

The economics of transportation is key to understanding the market for natural gas and the way the CRE's netback formula works. The Mexican pipeline system looks like a "Y,
perspectives of developed and developing countries in international trade disputes. This paper provides empirical evidence to inform discussions of these issues through a case study of aflatoxins standards and trade in food between Africa and Europe.

Based on the Food and Agriculture Organization's cross country survey on food safety standards, we develop an econometric method to statistically measure the trade flow effect of standards imposed through domestic regulation. The results are then used to calculate potential export revenue gains and losses with changing standards. We examine trade in cereals, fruits, nuts and vegetables between 15 member states of the European Union and 9 Africa countries in the ten years prior to 1998. Instead of identifying cost elements to comply with the standards, this paper examines changes in trade flows, as they are a direct consequence of differing approaches to regulation which intersect debate on how best to address these issues within the rules based system of the WTO.

# **II. Regulations on aflatoxin contamination and international standards**

Aflatoxins are a group of structurally related toxic compounds which contaminate certain foods and result in the production of acute liver carcinogens in the human body. They were discovered in 1960 following the deaths of 100,000 turkeys in the United Kingdom and high incidences of liver disease in ducklings in Kenya and hatchery trout in the United States (U.S. Food and Drug Administration, 2000).

The major aflatoxins of concern are designated B 1, B2, G 1, and G2, and these toxins are usually found together in foods (UNDP<sup>2</sup> -FAO<sup>3</sup> , 2000). Aflatoxin B 1 is usually predominant and the most toxic of the four categories and has been identified in corn and corn products, groundnuts and groundnuts products, cottonseed, milk, and tree nuts such as Brazil nuts, pecans, pistachio nuts, and walnuts (FAO-WHO<sup>4</sup> , 1997).

4
commitments seldom go beyond countries’ applied policies, the explicit liberalization resulting from the agreement was limited to a few members and a few areas.<sup>2</sup> Figure 2: Services Trade Restrictiveness Indices for TPP Countries Doha Offers, TPP Commitments and Applied Policy <!-- Start of picture text --> Overall STRI<br>BRN MYS CHL SGP MEX VNM CAN USA PER JPN AUS NZL<br>Doha TPP Policy<br>Note: For Brunei, applied policy information is missing.<br>Absense of a bar means the score is zero<br>100<br>75<br>50<br>25<br>Services trade restrictiveness index<br>0<br><!-- End of picture text --> Note 1: BRN =Brunei, MYS =Malaysia, CHL = Chile, SGP= Singapore, MEX= Mexico, CAN= Canada, VNM = Vietnam, USA =United States, PER = Peru, JPN= Japan, AUS = Australia; NLZ = New Zealand. Note 2: The country STRI is an aggregate score of indices for services sectors covered, the country STRI comprises STRIs of five major sectors, financial, telecom, retailing, transportation, and professional services. These five sectors contain different subsectors and the relevant modes.

Source: Gootiiz and Mattoo (2017) , drawing on the World Bank TPP database, http://iresearch.worldbank.org/servicetrade/TPPservices.htm.

> 2 However, in comparing TPP commitments with the policy status quo, our measures may underestimate the liberalizing impact of the TPP in two ways.  First, the TPP negotiating process could already have induced changes in applied policies over the course of the negotiations; for example, Mexico’s telecommunications policy was reformed in 2013, and Malaysia carried out several reforms between 2009 and 2013 in financial services, telecommunications, and professional services.  Second, some of the TPP commitments specify liberalization several years after
The absence of risk pooling in the RM market keeps insurance costs high. Public pension plans benefit from the cross-subsidization of longevity risk: citizens who die early essentially support those with a longer life span. In contrast, when a mortgagor passes away, no more than the individual’s outstanding loan balance has to be returned. Given these constraints on risk pooling, FHA-sponsored insurance programs may have to retain relatively high premia to be financially sustainable (Shan, 2011).

On the demand side, concerns about old-age financial literacy and consumer protection are a key constraint. Reverse mortgages are a relatively complex financial product that many young people struggle to understand. An industry survey from the 2010s reveals that of 1,000 Americans surveyed, 70% failed a 10-question quiz on RM (Reversemortgages.com, n.d.). The elderly face greater challenges in financial decision-making as their cognitive skills decline. They are more vulnerable to fraud (particularly from family and/ or caregivers) and other types of financial abuse than society overall (American Association for Justice, 2017, G20/OECD Task Force on Financial Consumer Protection 2019). One common example of RM fraud in the 1990s is that of contractors who offer house repairs without a down payment to elderly people. The contract offered turned out to be an RM with exorbitant origination and house repair fees (Caplin, 2002). Fraud opportunities and perverse incentives may be even more salient, in particular in the case of RM which are ‘sale-and-leaseback agreements’ where the lender has a financial interest in a short lifespan of the counterparty.

High RM adoption rates among poor elderly people make consumer protection concerns even more salient. Data from the United States suggest that over the last decade, poor elderly homeowners have become a key target group for RM lenders. Only 2% of the elderly homeowner population at large have an RM, but market penetration reaches over 5% for the lowest income quintile and even 17% for lowincome households of age 90 and above (Nakajima & Telyukova
offer short-lived benefits and are seen to be justified by their provision of insurance or emergency relief such as public works and cash transfer schemes.

The criticisms of econometric targeting could reflect either methodological inadequacies or informational/data limitations. On the former, standard regression-based calibration of the PMT score will tend to work less well toward the extremes of the distribution of household consumption. By its design, a standard regression line passes through the means of the data. The residuals will be positively correlated with the dependent variable (more so the higher the variance of the residuals given exogenous regressors).<sup>8</sup> One can expect the method to have a tendency to overestimate living standards for the poorest and underestimate them for the richest, though the degree to which this is problematic for targeting accuracy is unclear. Indeed, it is theoretically possible that the PMT method predicts that nobody lives below a poverty line for which even a sizable share of the population is deemed to be poor based on observed consumptions. Another possibility is that the variables used are not sufficiently good proxies for household consumption. In other words, that there is an information problem.

The paper aims to provide a systematic assessment of the reliability of econometric targeting as a tool for social policies aiming to reduce poverty. We assess what appears to be the most common form of what we call “Basic PMT,” as well as some alternative methods using extra covariates and methods that are arguably more appropriate when it is recognized explicitly that the PMT is for antipoverty policy making. A natural counterfactual for assessing any form of PMT is a uniform allocation—the same for everyone. Various other counterfactuals of interest to policy makers are examined. The study also considers less finely-targeted options to econometric targeting, which are uniform only within stipulated categories.

While Latin America has attracted the bulk of the past research on PMT, we study the method using survey data for the world’s poorest region, Sub-Saharan Africa (SSA). This is also the region where existing
The Benefits of India’s Rural Roads Program in the Spheres of Goods, Education and Health: Joint Estimation and Decomposition

# Clive Bell<sup>_∗_</sup>

(Appendix by Jochen Laps) First version: January, 2010. This version: August, 2012

**Abstract**

All-weather rural roads usually improve not only villagers’ terms of trade, but also their educational attainments and health. Obtaining empirical estimates of the benefits generated by the first is straightforward, not so those generated by the others. The object of this paper is to estimate the relative sizes of their respective contributions to total benefits in connection with the all-India rural roads program _Pradhan Mantri Gram Sadak Yojana_ , using an overlapping generations model featuring the production and consumption of goods and the formation of human capital in the presence of both morbidity and mortality. Based on survey evidence from upland Orissa in India and Bangladesh, as well as elements of more usual forms of calibration, the model yields a ratio of commercial to non-commercial benefits of about two-to-one in the first generation, falling to three-to-four in the second. This is broadly consistent with the valuations expressed by respondents in the Orissa survey, who ranked the latter benefits at least on a par with the former.

Keywords: Rural roads, transport costs, education, health, India JEL Classification: E62, O19, O12 Sector Board: Transport

> _∗_ University of Heidelberg, INF 330, D-69120 Germany. This paper was prepared as part of the documentation for a World Bank loan proposal in connection with PMGSY. The views expressed herein are not, however, necessarily those of the World Bank or its Board.

1
in Annex 6). Setting the aggregation parameter to unity in equation (1) yields the arithmetic average as a special case of the CES with weights. We are therefore not stepping outside the framework we have consistently employed thus far. However, the aggregation of scores from ρρ different modes is different from the aggregation of measure scores because in any sector one mode of supply will invariably be more important than others, so that the symmetric treatment of measure scores is no longer appropriate for this step of the aggregation.

The weights for aggregating scores by mode of supply follow largely the ones employed in the previous World Bank STRI database, although certain modifications have led to a slight re-balancing of modal weights. First, unlike the treatment of Mode 4 in the previous World Bank STRD, in which Mode 4 restrictions were confined to professional services sectors only, we now consider policy measures affecting the movement of persons (e.g. prohibition of, or quotas on, intra-corporate transferees) in _all_ subsectors.<sup>27</sup> This coverage is consistent with the OECD policy area “Movement of People” that cuts across all sectors and increases the comparability of restrictiveness scores across both projects.

Second, the more comprehensive coverage of policy measures in this update also improves modal coverage directly or indirectly. For instance, Mode 1 is now covered as well in distribution (wholesale/retail), rail and road sectors, respectively (only Mode 3 used to be covered in the previous World Bank STRD). In international air transportation (both passenger and air cargo), the WTO’s “Worldwide Air Liberalisation Index” (WALI) as of 2012 is used to cover Mode 1. The WALI results had to be rescaled to the scaling used in the STRI: rescaled_WALI = (50 - WALI) * 2. This is an imperfect approximation of policy restrictiveness. WALI does not reflect the MFN policy, but rather is a synthetic measure of openness which relates to all services agreements an economy may have signed
- 21 -

# **Figure 5: Total Fees over Contributions – Hungary and Other Countries (%)**

<!-- Start of picture text --> 40%<br>35%<br>30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>1 3 5 7 9 Years of operation11 13 15 17 19 21 23<br>Argentina Bolivia Chile El Salvador México Perú Uruguay Hungary<br><!-- End of picture text --> Note: Contributions and costs are net of death and disability insurance for Latin American countries Source: AIOS and own calculations on HFSA raw data

**Figure 6: Total Fees over Assets – Hungary and Other Countries (%)**

<!-- Start of picture text --> 14%<br>12%<br>10%<br>8%<br>6%<br>4%<br>2%<br>0%<br>1 3 5 7 9 11 13 15 17 19 21<br>Years of operation<br>Chile Argentina Bolivia Costa Rica El Salvador Mexico Peru Uruguay Hungary<br><!-- End of picture text --> Note: Costs are net of death and disability insurance for Latin American countries Source: AIOS and own calculations on HFSA raw data 45. If operating and asset management fees are kept at their current levels of 6.5 percent of contributions and 1 percent of assets, total fees in Hungary would compare unfavorably with other reforming countries in the long-run. As shown in Figure 7, total fees over contributions would increase to more than 35 percent in 30 years, driven primarily by the fixed asset management fee of 1 percent charged on the increasing assets. Total fees over assets would converge to about 1.2 percent, as shown in Figure 8, an
**Figure 5 Distribution of Firm Population, Employment, and Value-added, 2007**

<!-- Start of picture text --> Firm population Employment Value added<br>million firms millions of individuals billions of 2005 US$<br>2.6 5.6 8.3 3.1 0.7 0.3 23.9 46.7 35.5 15.4 5.9 2.0 1,715 3,099 1,583 332 53 32<br>1% 9% 0%1 % 9% 0%1 5% % 0% 1% 4% 0% 2% 9% 0% 11%2% 0% 43% 38% 20% 31% 29% 22% 45% 43% 28% 43% 41% 27% Large(250+)<br>14%<br>19% 24% 26% 17% 29% Medium<br>18% 23% (50–249)<br>90% 89% 94% 95% 89% 87% 16% 15% 18% 19% 24% 21% 23%<br>23% 27%<br>19% 22% 17% 19% 15% 20% 26% Small(10–49)<br>44%<br>35% 31%<br>22% 23% 24% 24% 20% 19% 21% 16% 17% Micro(1–9)<br>EU15 EU12 EU15 EU12 EU15 EU12<br>North Continental South Continental South North North Continental South Continental South North North Continental South Continental South North<br><!-- End of picture text --> _Source:_ World Bank staff calculations based on Eurostat.

The EU15 South also suffers from unfavorable domestic business environments. In comparison to rest of the EU15, the EU15 South rated consistently lower in regulatory indices and in outward FDI (Figure 6
**Table 9: Cellulosic biomass in China**

||Generat<br>Mill|ion Potential<br>ion tonnes|Current Utilization|
|---|---|---|---|
||Current(2008/2009)|2020(estimated)||
|Agriculture residues|650.55<sup>a</sup>(2010)|679.22<sup>b</sup>|15% for burning, 15% for<br>returning to the field, 24% for<br>fodder, 43% for fuel wood, 3%<br>for industry use.|
|Forest residues|854.56<sup>d</sup>(2010)|965.39<sup>b</sup>|Part of bush residues was used<br>to feed, fiber, etc.|

Note: a. data from Chang, et al. 2012

# **3.4.2 Supply cost**

The production cost of 2<sup>nd</sup> generation biofuels is full of uncertainties. Production cost for 2<sup>nd</sup> generation biofuels in the literatures range between USD 0.60/liter and 1.30/liter (4937.4 and 10697.7 Yuan /tonne<sup>4</sup> ) (Ralph, et al, 2010). The pilot scale cost in China is about 7845 Yuan/tonne based on the techno-economic analysis of 300 tonnes project (Table 10). The supply cost is higher than that of gasoline, and lacks of comparative economic advantage. The feedstock cost is relative low, about 19.8% of total production cost. This is partly because the feedstock requirement of 300 tonne demonstration project is not very high. With the increase of production scale to deployment & commercialization stages, the feedstock price will inevitably increase due to long collection
based on a large-scale, cross-country survey that investigates how people think about these subsidies and what other policy measures they would prefer. The survey includes a randomized experiment whereby respondents receive information treatments highlighting one of the three common arguments against energy subsidies—that they are an inefficient use of government resources (efficiency argument), that they benefit the rich more than the poor (equity argument), or that they damage the environment (environment argument). Specifically, respondents are randomly allocated into four groups; each of the first three groups is provided with information treatments about the negative impact of subsidies on efficiency, equity, or the environment, and the final group receives no information (the control group). These information treatments present recent country-specific data from the IEA and other international organizations. Before receiving the treatments, respondents provide background information on themselves, including their household energy consumption, knowledge of energy subsidies, and views about how much the government can be trusted. After the treatments, respondents were asked a series of questions about their support for subsidy reform, both in the absence of any other policy (unconditional support) and if accompanying policies such as cash transfers were immediately implemented (conditional support). Heterogeneous treatment effects are examined based on respondents’ prior beliefs (“priors”), such as their perception of their relative income; they are also examined between subsets of countries based on the main type of energy source that is subsidized. Additional analysis leveraging experimental variation is conducted to examine whether support for reform is influenced by the existing level of subsidies within countries and the level of the potential price increase from reducing subsidies.

The survey was conducted in all middle-income countries where at least 1 percent of GDP was provided in energy subsidies in 2022, at least 5 million adults have access to the internet, and fiscal incidence analysis exists based on recent estimates about the distribution of energy subsidies. The 12 countries that meet these criteria—Angola, Argentina, Bangladesh, Bolivia, Ecuador, Egypt,<sup>3