rafmacalaba/datause-encoder-data huggingface dataset:
reforms alone suffice to solve the aging problem? Simulations indicate that the answer is "no".

More basic reforms would move away from a straight PAYG system to a partially funded system that smooths contributions over time. In addition, partial funding can enhance economic growth by increasing capital accumulation. While China's rate of voluntary saving is very high now, it may not be so high in the future, so policies that augment long term saving may be desirable. If the savings are well invested, this ultimately raises the affordable benefit or lowers the required contribution rate.

This leads directly to a key issue--how should the funds be managed to maximize the returns? Who should choose the investment managers? What incentives and constraints will the managers face? Should the funds be publicly or privately controlled? Another important question is the choice between defined benefit and defined contribution plans. In a defined benefit plan, pensions are promised that usually depend on the number of years worked and the wage in the last few years of employment, but the future contribution rate needed to pay for these promises-and therefore their credibility--is unspecified. In a defined contribution plan the contribution rate is defined and the pension ultimately depends on accumulated contributions plus investment returns, but future interest rates and benefit amounts are uncertain.

In Part II the entire system is assumed to be defined benefit and any funds that accumulate are publicly managed. Part III investigates the effects of instituting a multi-pillar system that includes a modest mandatory tax-financed basic (defined) benefit plus a mandatory fully funded defined contribution (individual account) scheme. The first pillar is publicly managed and designed to provide a social safety net through redistribution targeted toward low income workers, while the second pillar requires people to save in their own individual accounts and is privately managed. Thus the multi-pillar system combines publicly and privately managed components, that are pay-as-you-go and defined benefit, funded and defined contribution, respectively. (See World Bank 1994, which describes this system and its advantages in a more general context).

Many Chinese officials consider such a system desirable--but implementation has been stalled by the transitional costs that would be implied. Shifting to a multi-pillar system would require paying off the implicit debt (honoring the 2
Data permitting, a satisfactory approach might be to develop a fully structural model in which heterogeneous firms decide whether or not to enter the textile market, then select a destination (i.e. EU or US or both) and finally decide under which trade regime to export (i.e. under a preferential regime with fixed costs associated with proving origin, or under MFN with no fixed costs).<sup>9</sup> The alternative to a structural model is to ‘let the data speak’ in a less ambitious framework. In the Appendix, we sketch such a model in which a representative apparel producer sells all its production either to the US or the EU market or to both under preferential status (these are the two main export destinations for AGOA beneficiaries). The producer sells differentiated products (or since we do not have firm data, heterogeneous firms sell a homogenous product to both markets with fixed entry costs to each market). The firm uses textiles as an input and faces a downward sloping demand curve in each one of the two destination markets. Under the single transformation (‘third country provision’) rule introduced by the Special Rule, the firm chooses its textiles from the low-cost suppliers while under the double or triple transformation rules, it is forced to purchase textiles from the high-cost partner. The comparative statics of the model show that export sales to a market respond positively to: (i) a fall in tariffs (i.e. to an increase in preferential access under AGOA to the US), and (ii) a relaxation of the rule of origin which lowers its production costs.

# **4. Data and Econometric Strategy**

# **4.1. Specification and Data**

_Specification_ The model sketched above suggests that, after controlling for idiosyncratic factors in each market, export sales of individual apparel products towards the EU and US 9 This is the route followed by Cherkashin et al (2010). They rely on cross-section data only for estimation which does not allow them to tackle directly the effects of change in RoO as we do here. Their identification relies on assuming (rather than estimating) that costs associated with meeting origin requirements raise unit production costs by 15%, that obtaining a quota license to sell to the US under the MFA costs 7%, that decisions about entry into each market are made separately, that expenditures on Bangladeshi goods come entirely at the expense of expenditures from other exporters. In any case, to fit a structural model to the exports of apparel by several African countries to the EU and US markets would require firm-level data which was collected by the authors of the Bangladesh study but that are not available for any of the AGOA beneficiaries.

9
Policy Research Working Paper 6063

# **Abstract**

The enforcement of stringent intellectual property rights in the pharmaceutical sector of developing countries generates considerable controversy, due to both the extensive research investment and the public policy importance of this sector. This paper explores the likely effects of enforcing product patents on prices and utilization of drugs in the Central Nervous System market in India. The Central Nervous System segment is the second largest therapeutic category in terms of retail sales in the world and is one of the fastest growing segments in India. Using information on product patents granted by the government and panel data on pharmaceutical prices and utilization from 2003–2008, the paper finds limited evidence of overall price increase following the introduction of product patents. However, there appear to be heterogeneous effects on prices by the type of product patent granted on drugs, implying the need for a careful examination of the product patent portfolio.

This paper is a product of the Research Support Unit, Development Economics. 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://econ.worldbank.org. The author may be contacted at agoyal3@worldbank.org.

_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
# **Box 1: Definitions of Key EU-SILC Variables Used in the Analysis**

**Total disposable household income** is the sum for all household members of gross personal income components (including gross employee cash or near cash income, gross non-cash employee income, gross cash benefits or losses from self-employment, value of goods produced for own consumption, unemployment benefits, old-age benefits, survivor benefits, sickness benefits, disability benefits, and education-related allowances) plus gross income components at the household level (including imputed rent, income from rental of a property or land, family/children related allowances, social exclusion not elsewhere classified, housing allowances, regular inter-household cash transfers received, interest dividends, profit from capital investments in unincorporated business, income received by people aged under 16) minus interest paid on mortgage, regular taxes on wealth, regular inter-household cash transfers paid, tax on income and social insurance contributions (including tax adjustments-repayment/receipt on income, income tax at source, and social insurance contributions). **Equivalent household size** is computed assigning a weight of 1 to the first household member aged 14 years and older, 0.5 to each additional household member aged 14 years and older, and 0.3 to each household member aged 13 years or less. **Equivalized disposable income** is computes as total disposable household income / equivalent household size. **Benefits** include unemployment, old-age, survivors, sickness, disability, education, family benefits, other social exclusion, and housing allowances. **Taxes** include regular taxes on wealth, taxes on income and social insurance contributions, as well as employer’s social contributions. **Post tax-benefit incomes** (Table 4) are the same as equivalized disposable incomes **Post tax incomes** (Table 4) = Equivalized disposable incomes – equivalized benefits **Pre-tax benefit incomes** (Table 4) = Equivalized disposable incomes – equivalized benefits + equivalized taxes **Pre-transfer incomes** (Chart 7) = Pre-tax benefit incomes **Post-transfer incomes** (Chart 7) = Equivalized disposable incomes

9. Section 5 analyzes key factors that help explain the observed variation across EU8 countries in level of public support for redistribution, highlighting the important role of factors like peoples’ economic background and relative success, whether they associate poverty with factors within / outside the control of those afflicted (e.g. laziness/lack of willpower vs. injustice in society).

10. Section 6 examines the role played by differences in education levels and labor force participation rates in explaining income inequality: in particular the analysis shows that while these factors play an important role in explaining observed regional disparities within countries, they fail to explain the large differences in living standards observed between EU countries.

11. Finally, Section 7 concludes with a discussion of some of the main policy implications of the findings presented in the paper.

6
**Policy, Research, and Exiorna far**

# **Trade Policy**

WPS 536 This papera product of the Tr?ic Policy Division, Country Economics Department- is part of a larger effort in PRE to study the impact of agricultural pricing and trade policies, and is a by-product of the Comparative Study of the Political Economy of Agricultural Pricing Policies in Developing Countries. Copies are available free from the World Bank, 1818 H StreetNW, Washington, DC20433. Please contact Sheila Fallon, room NIO-025, extension 37947 (15 pages). A household's nutrition level or status depends intake. Such a view overlooks the fact that only partly on its nutrient intake (calories, households have the _choice_ of spending increprotein, vitamins, and the like). It is also a ments in food expenditures on nutrients but function of: intake. Such a view overlooks the fact that households have the _choice_ of spending increments in food expenditures on nutrients but prefer to spend it on other food attributes. It also ignores the fact that these other food (and nonfood) attributes may also contribute to nutritional status (for example, food freshness and cleanliness, refrigeration, and so on).

* Non-nutrient food attributes that affect nutrition, such as the freshness, cleanliness, and storability of foods purchased.

* Privately provided inputs such as the time and care taken to prepare food to ensure that it is not contaminated or spoiled.

In urban areas, nutritional and health status can probably best be raised through the provision of publicly provided inputs (sewerage, potable water, and so on).

* Publicly provided inputs, such as potable water, sewerage, electricity, nutritional information, and **the** like.

In rural areas, nutritional and health status depend largely on household inputs - which depend on income. So raising the rural household's income can raise its nutritional and health status.

No matter how closely related, food adequacy (measured by nutrient intake) and nutrition level are not the same thing. The problem of food adequacy may or may not reveal itself as a nutrition problem; and a nutrition problem may or may not be the result of an inadequate supply of food.

One of the best ways to raise farm income is to reduce taxes on agricultural production; another is to increase public spending on factors that raise land and labor productivity in rural areas. Schiff and Valdes argue that agricultural export-led growth has real potential for creating jobs, reducing poverty, and thereby contributing to improvements in the nutritional status of the poor.

The fact that nutrient intake does not increase with income is not itself a cause of concem, though it is viewed that way by some who identify nutrition exclusively with nurient Thc PRE Working Paper Scrics disseminates the findings of work under way in the Bank's Policy, Rcscarch, and Extemal Affairs Complex. An objectivc ofthc scrics is to get thcsc findings outquickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official Bank policy.

Produced by the PRE Dissemination Center
- Kaboski, J. P. & Townsend, R. M. (2012). The impact of credit on village economies. _American Economic Journal: Applied Economics_ , 4(2), 98–133.

- Karlan, D., Osei, R., Osei-Akoto, I., & Udry, C. (2014). Agricultural decisions after relaxing credit and risk constraints. _The Quarterly Journal of Economics_ , 129(2), 597–652.

- Karlan, D. & Zinman, J. (2009). Observing unobservables: Identifying information asymmetries with a consumer credit field experiment. _Econometrica_ , 77(6), 1993–2008.

- Karlan, D. & Zinman, J. (2011). Microcredit in theory and practice: Using randomized credit scoring for impact evaluation. _Science_ , 332(6035), 1278–1284.

- Karlan, D. & Zinman, J. (2018). Price and control elasticities of demand for savings. _Journal of Development Economics_ , 130, 145–159.

- Karlan, D. & Zinman, J. (2019). Long-run price elasticities of demand for credit: evidence from a countrywide field experiment in mexico. _The Review of Economic Studies_ , 86(4), 1704–1746.

- Karlan, D. S. & Zinman, J. (2008). Credit elasticities in less-developed economies: Implications for microfinance. _American Economic Review_ , 98(3), 1040–68.

- Keen, M. (1990). Welfare analysis and intertemporal substitution. _Journal of Public Economics_ , 42(1), 47–66.

- Khandker, S. R. (2005). Microfinance and poverty: Evidence using panel data from bangladesh. _The world bank economic review_ , 19(2), 263–286.

- Lagakos, D., Mobarak, A. M., & Waugh, M. E. (2018). The welfare effects of encouraging rural-urban migration.

- Lane, G. (2020). Credit lines as insurance: Evidence from bangladesh.

- Lerva, B. (2022). The monetary value of externalities: Experimental evidence from ugandan farmers.

- McKenzie, D. (2012). Beyond baseline and follow-up: The case for more t in experiments. _Journal of development Economics_ , 99(2), 210–221.

- McKenzie, D. & Woodruff, C. (2008). Experimental evidence on returns to capital and access to finance in mexico. _The World Bank Economic Review_ , 22(3), 457–482.

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THE CENTRAL AFRICAN REPUBLIC’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 22. Private investment in the Central African Republic and select African countries**

Average per year between 2002 and 2007 <!-- Start of picture text --> 9<br>8<br>7<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>Water Transport Power ICT<br>Percentage of GDP<br>Senegal Kenya Uganda Nigeria Liberia Sierra Leone Mozambique Tanzania Rwanda Ghana Zambia Burkina Faso Mali Benin Seychelles South Africa Cameroon Niger Lesotho Gabon Madagascar Guinea Malawi Mauritania Cote d'Ivoire Zimbabwe Angola Burundi Congo, Rep. Mauritius Chad Botswana Togo Swaziland Namibia<br>Sao Tome and ... Guinea-Bissau Central African ...<br>DRC Congo, Dem. ... Equatorial Guinea<br><!-- End of picture text --> _Source:_ AICD calculations. _Note:_ GDP = gross domestic product; ICT = information and communications technology.

The transport sector accounts for the largest of total annual financial flows to infrastructure in the CAR (60 percent, table 20). Spending on maintenance and rehabilitation in the transport sector is only one-fourth of total financial flows to the sector. Evidence suggests that countries that spend too little on maintenance will end up with larger rehabilitation liabilities, often resulting in the need for emergency works to restore the functionality of critical infrastructure. On the other hand, countries with large investment programs may have fewer resources left over to address road maintenance needs. This is a worrisome finding because if high capital spending comes at the expense of lower maintenance expenditure, then the condition of the network will only deteriorate over time (Gwilliam and others 2009). The transport sector is significantly reliant on ODA funds, which are mostly allocated to this sector (figure 19, table 20). On average around 45 percent of financial flows to transport come from ODA. The high volatility of ODA flows has contributed to the volatility of public investment in the sector. ODA commitments were reduced during the conflict and reached their peak in 2006, when the peace agreements were signed. After 2006 ODA commitments to the sector were severely reduced and have been stagnant since (figure 21).

Spending in the power sector ($26 million) is evenly distributed between capital investment and the O&M of existing assets. Most of the spending in ICT ($13 million) has been devoted to capital investments as the greatest expansion of ICT services has taken place since the end of the conflict (table 20).

Resources in the water and sanitation sectors have been mainly channeled to financing capital investment. Total financial flows to the water supply and sanitation sectors averaged $10.8 million, of which about $7.6 million was dedicated to capital investment (table 7).

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compared to a reduction of 15.8% for the small states. The greater reduction for the former was certainly not due to the reduction in the brain drain which was in fact greater for small states (13.6% versus 4.4%). Rather, it was due to a significant increase in the average emigration rate from 1.1 to 1.5% or by 36%, compared to a 2% increase for small states.

Sixth, the schooling gap for high-income countries remained constant between 1990 and 2000 at about 1.26 and fell for the world as a whole from 3.316 to 2.993 or by 8.8%. The world average schooling gap was equal to that for small states in 1990 and some 6% greater in 2000. Seventh, note that the reduction in the schooling gap should be considered a benefit for source countries in the sense that the difference between the skill intensity of emigration _M h_ / _M_ and that of the population as a whole ( _N h_ + _M h_ ) /( _N_ + _M_ ) decreases (see equation 4). The reason is that the brain drain should be less harmful for source countries because of their _relatively_ greater supply, either because of a reduction in the share of skilled labor in migration or because of an increase in the share of skilled labor in the population (including the migrants themselves). This was the case for all country groupings except for high-income small states and high-income countries as a whole.

Eighth, skilled immigrants are defined as foreign-born workers with university or postsecondary training living abroad. This definition does not distinguish between education acquired in the home or in the host country. Rosenzweig (2005) shows on the basis of US survey data that migration of children represents an important fraction of total migration for certain countries. On average, 18 percent of permanent resident aliens immigrated to the US before age eighteen, and over 25 percent immigrated before age twenty. Among these, some are highly-skilled today, having most likely acquired a higher education after coming to the US.

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<!-- Start of picture text --> Figure 5e. World export of groundnut oil (1000 metric Figure 5f. Market shares in world groundnut oil<br>tons)<br>550 0.90<br>Post NAFTA and URAA<br>0.80<br>500<br>0.70<br>450 0.60<br>0.50<br>400<br>0.40<br>350 0.30<br>0.20<br>300<br>0.10<br>250 0.00<br>200<br>Senegal Argentina USA Brazil<br>150<br>76 78 80 82 84 86 88 90 92 94 96 98 00 02<br>World Groundnut Oil Export<br><!-- End of picture text --> The decline in African country shares in world groundnut markets has significantly reduced the contribution of groundnut products in export earnings of many countries. As Table 4 shows, the importance of groundnut products as a source of export earnings has declined dramatically in Senegal and South Africa and in Malawi since the early 1980’s. It has only increased in Gambia significantly in Gambia where it accounted for 84 percent of total good exports in 2000-02.

Table 4 also depicts the changes in the volume and value of groundnut exports, for shelled (raw edible) groundnuts and groundnut oil. The volume exported of raw edible groundnuts decreased significantly in Malawi, Nigeria and South Africa and quasi-stagnated in Senegal and Gambia. As a result of declining and quasi-stagnant volumes, shelled groundnut export earnings dwindled, but the extent of the decline suggests that unit values have decreased for Malawi, Gambia and Senegal. This is confirmed in Figure 6. The export performance of groundnut oil is more contrasting. Senegal and Nigeria have increased both their volume and value of exports while South Africa significantly exited the groundnut oil market.

**Table 4. Share of groundnut products in total merchandise exports**

|||Nigeria|South Africa|Senegal|Gambia|Malawi|
|---|---|---|---|---|---|---|
|Shelled gr. export volume|1980-82|1,026|41,333|2,725|27,333|14,867|
|(metric ton)|2000-02|412|34,830|2,915|27,939|662|
|Shelled groundnut exports|1980-82|400|29,730|2,145|11,743|12,333|
|(1000 US$)|2000-02|204|22,875|1,371|5,763|436|
|Gr. oil export volume|1980-82|0|22,667|82,693|7,651|0|
|(metric ton)|2000-02|1,287|1,519|98,879|8,633|0|
|Groundnut oil exports|1980-82|0|14,071|60,285|6,400|0|
|(1000 US$)|2000-02|797|1,053|63,007|6,333|0|
|Share of gr. In total exports|1980-82|0.003|0.21|16.17|59.62|4.65|
|(%)|2000-02|0.006|0.08|8.16|84.64|0.10|

**Source** : Production and groundnut exports data, FAOSTAT; Total good exports, WDI **Note** : The share of groundnuts in total good exports inlude export of groundnut meal

12