rafmacalaba/datause-encoder-data huggingface dataset:
# **The Doha Development Agenda: What’s on the Table?**

Negotiations under the Doha Development Agenda have now been under way for almost seven years. In the areas where negotiations are most advanced, they have generated complex and detailed proposals which seek to balance the interests of the 152 WTO members. But this complexity and detail makes it difficult to judge what precisely Doha offers. Drawing on the results of a recent research project, this paper takes stock of what is currently on the table in goods and services, access for least developed countries, aidfor-trade and trade facilitation<sup>1</sup> .

The outlines of a potential agreement (WTO 2008a,b,c), emerging after seven years of negotiations, imply that Doha offers three key benefits: enhanced security of market access in goods and services; improved market access in agriculture and manufacturing; and the mobilization of resources to deal with the trade problems of least developed countries. WTO Members have offered to make large reductions in legally bound levels of protection in goods and services. These reductions cover tariffs on all goods, export subsidies and domestic support in agriculture, and market access and national treatment restrictions in services. However, given the large gaps today in all areas between legally bound and actually applied levels of protection, the reductions in bound levels of protection will lead to much smaller reductions in currently applied levels of protection.

For the least developed countries, the proposed “duty-free, quota-free” access will add significantly to the access they already enjoy under existing preferential access arrangements only if industrial countries do not exclude vital tariff lines. The initiatives on trade facilitation and aid for trade both play a valuable catalytic role in promoting reform and mobilizing assistance, but substantial effort is still needed to translate notional benefits into actual gain.

This paper does not attempt to be comprehensive. Rather the focus is on issues where analysis can improve our understanding. The main findings are presented in the text with supporting information in the annexes. Section I examines market access in goods, Section II agricultural export subsidies and domestic support, and Section III trade in services. Section IV assesses market access for Least Developed Countries (LDCs) and Section V the Aid-for-Trade initiative. Section VI covers trade facilitation.

## **_I. Market access in goods_**

A central goal of the WTO process is to improve the market access opportunities and the security of market access of its members. In this section, we first consider the reductions

> 1 This paper draws heavily on research by Blandford and Josling (2008); Bouët, Laborde and Mevel (2008); Gootiiz and Mattoo (2008); Laborde, Martin and van der Mensbrugghe (2008); Newfarmer (2008); and Wilson (2008). Support from the British-Swedish Multi-Donor Trust Fund for Trade is gratefully acknowledged.
# **_Testable Implication 2: One should not expect a significant difference in prices paid between pre- and post-qualification rules, unless under the latter system it is more likely that (competitive) bids qualify._**

In what follows we evaluate whether these testable implications hold true in our analysis of the effects of shifting from pre- to post-qualification in the practice of works procurement in Brazil.

# **_4.      Methodology_**

We assess the impact of _inversão das fases_ on three procurement outcomes: (i) average duration of a procurement process for public works; (ii) likelihood that one or more complaints are filed during a procurement process; and (iii) prices paid to contractors, as measured by the average size of awarded contracts. To do so, we adopt a difference-in-differences (DD) strategy, wherein changes in outcomes for a contracting entity located in a reforming state—São Paulo’s SABESP—pre- relative to post-reform are compared to those of a contracting entity located in a non-reforming state—Minas Gerais’ COPASA. In essence, COPASA serves as a control entity, such that its trend in outcomes pre- and post-reform is differenced out of the trend observed at SABESP, the treatment entity. Since São Paulo’s phase inversion law was enacted in 2008, we use procurement processes conducted in 2007 as our pre-reform sample, and processes conducted in 2009 as our post-reform sample.

# _4.1 Description and justification of the DD approach_

Formally, we estimate models of the following form: where _Yst_ is the outcome—either process duration (measured as the time, in days, between the opening of the first envelope and the granting of the award), complaint incidence, or award size—in state _s_ in year _t_ ; _SPs_ is an indicator for whether the project takes places in the treatment state, São Paulo; _Y2009t_ is an indicator for whether the project takes place in 2009 (i.e., post-reform); and **X** st is a vector of project characteristics, such as an indicator for the procurement process invitation mechanism ( _tomada de preços_ or _concorrência_ ), month of the year, and project type fixed effects. All _reais_ -denominated quantities are deflated to January 2007 _reais_ by the Brazilian construction price index.

The parameter _β_ captures any permanent differences in outcomes between São Paulo and Minas Gerais. For instance, _β_ includes any differences in the nature of public works or “productivity” levels at SABESP relative to COPASA. In turn, _γ_ embodies the trend in outcomes between 2007 and 2009 that is common to both entities. In turn, _δ_ —the difference-in-differences parameter of interest—measures the change in outcome at SABESP from pre- to post-reform above and beyond that observed at COPASA, net of Page | 13
# **Soil Fertility, Fertilizer, and the Maize Green Revolution in East Africa**

# **1. Introduction**

The low application of inorganic fertilizer in Sub-Saharan Africa (hereafter Africa) is one of the major constraints to achieving a Green Revolution in this region (IFDC, 2006). Although there have been many studies to ascertain the reasons behind the low application of the inorganic fertilizer, some competing hypotheses remain (Morris et al., 2007; Kelly, 2006). Market-based hypotheses suggest that farmers are responding to the high fertilizer price, which has been the result of high transportation and marketing costs in Africa (Jayne et al., 2003; Gregory and Bumb, 2006). Non-market based hypotheses emphasize farmers’ lack of knowledge on inorganic fertilizer and high yielding varieties, as well as financial constraints (surveyed in Morris et al. 2007).

One of the non-market constraints is the land degradation which could lower the returns to the fertilizer application (Adesina, 1996; Marenya and Barrett, 2007). Degraded soils have low capacity to hold water and external soil nutrients, and, thus, external fertilizers have low returns on degraded soils. The low returns on the degraded soils would force farmers to reduce the already low inorganic fertilizer application, which in turn may contribute to further land degradation (Smaling et al., 1997; Henao and Baanante, 2006; IFDC, 2006).<sup>1</sup> A recent study by Marenya and Barrett (2007) advances the research on this issue by employing plot level soil carbon content data in western Kenya and finds that the marginal return to the inorganic fertilizer is low and not profitable in maize production when the soil carbon content is low. Their results suggest that conventional policies to encourage farmers to use inorganic fertilizer would be ineffective on depleted soils. Their analyses, however, are based on cross sectional

> 1 Although there is a debate over the possible overestimations of the previous estimates of soil losses, many experts agree that the land degradation is a critical constraint to African agriculture (Koning and Smaling, 2005; Pender et al., 2006).

2
# **6 Conclusions**

In this paper, I use household-level panel data from Ethiopia to show that exogenous shocks to international coffee prices have significant effect on household consumption and investment in child human capital. For a household that produces only coffee, a 1% change in international coffee price would lead to 0.8% change in household consumption. This strong pass-through of coffee price shocks to household consumption implies that households do not have meaningful consumption smoothing options during periods of price shocks. I find that borrowing increases slightly during period of low coffee price, but it has limited effect on household consumption smoothing, perhaps because the size of the loans are too small or because direct loan for consumption is limited.

Moreover, I show that households (particularly male members) adjust their on-farm labor supply in response to coffee price changes. Households reallocate more fraction of their on-farm labor supply to non-coffee fields when coffee prices drop. While coffee price movement has no significant effect child labor (on-or off-farm labor), I find that periods of high coffee prices are associated decrease in enrollment of girls but not boys. A plausible explanation for this is that young girls might have to engage in more domestic work to allow their parents work more on- and off-farm. I also show that children who are in utero in coffee producing households during low coffee price periods have lower measures of weight-to-age and weight-to-height z-scores. These results on the effect of coffee price change on school enrollment of girls and child malnutrition imply that commodity price shocks not only affect current household welfare but it may also hamper future economic growth through its effect on human capital accumulation.

A major policy implication is that governments and NGOs should design effective means to shield producers from erratic change in commodity prices. For instance, innovative insurance schemes, such as commodity price indexed insurances (similar to weather indexed insurance schemes), may have a positive effect on welfare. Future studies that seek experimental evidence of the feasibility and effectiveness of these insurance schemes would be a step forward towards solution to this problem.

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tures of importance for developing countries, there has been surprisingly little research about the relative roles played by industrial structure versus national characteristics in developing countries. If skill-wage premiums vary systematically across industries, then industrial policies that favor one sector over another could have important consequences for closing the gap between the private and social returns to education, for reducing the scope of the brain drain due to emigration of highly educated workers, and for affecting the relationship between globalization and income inequality. Hence this paper can also be seen as a contribution to the literature on whether the industrial composition of exports matter for development (e.g., Hausmann, Hwang, and Rodrk 2005).

Our objective in this paper is to explore the industry-skill premium in Latin America and the Caribbean. We work with sixty four household surveys for sixteen countries covering over five million workers in the region. Following the literature on industry wage differentials (Dickens and Katz, 1986; Dickens and Lang, 1988; Gibbons and Katz, 1992), we allow the skill premiums to vary across industries, as in Galiani and Porto (2009).<sup>3</sup> Using the household surveys, we estimate and document the industry-specific skill premiums for sixty industries in each of the sixteen countries in the region.

We then work with those estimates to study econometrically the relationship between the industry-skill premiums and the level of sectoral exports. Brambilla, Lederman, and Porto (2009) review theories to explain a link between exports and the skill premium based on skillintensive activities associated with exporting. These include marketing activities as well as quality upgrades (labeling, warranties, certification) needed to export. Using firm-level data, the authors find support for such a link. In this paper, we generate additional supportive evidence for models of exports and skills. In cross-country, cross-industry regressions, we find a positive and statistically significant link between the industry-skill premium and the level of sectoral exports. This link, however, is not large in magnitude: doubling sectoral exports (a reasonable shock in our data) is associated with a 0.28 percentage point increase in the manufacturing-industry skill premium.

The related analytical issues have important policy implications. Most countries in Latin

> 3The existence of skill premiums at the industry level requires some sort of labor immobility. In Galiani and Porto, 2009, this is generated by union membership.

2
In Equation (1), can include household variables that capture not only household socio- jj demographic characteristics, but also preferences and attitudes that may shape household xx consumption patterns; can include household assets or incomes; and is the error term (Elbers jj jj _et al._ , 2003; Ravallion, 2016).xx<sup>12</sup> consists of the two components, a cluster random effects μμ jj ( ) and an idiosyncratic error term (μμ ), which are assumed independent and normally distributed given υυccjj , such that 2 ) and εεjj 2 ). jj ccjj jj υυjj jj jj εεjj xx υυ |xx ~NN(0, σσ εε |xx ~NN(0, σσ

The consumption data exist in the base survey (i.e., _j_ = 1, or survey 1) but are not available in the other survey(s). Our goal is to estimate consumption data from the base survey (j=1) for use in poverty estimates in the target survey (j=2), where the consumption data may not be available or of poor quality. The estimation process relies on two assumptions that must be met. Assumption 1 states that the sampled data in survey 1 and survey 2 are representative of the same population in each respective time period, and Assumption 2 assumes that changes in the distributions of the explanatory variables between the two periods can capture the change in the poverty rate in the jj next period. xx Given Assumptions 1 and 2, to obtain the imputed consumption for survey 2 we can replace 1 with 2 in Equation (1): 1 xx xx 2 1 2 1 (2) cc1 Put differently, Equation (2) applies the model parameter yy = ββ ′xx + υυ + εε 1 and the distributions of the error terms and 1 from the base survey to the 2 characteristics in the target survey to obtain ββ cc1 1 estimates of household consumption υυ εε 2 in the target survey (with the superscript indicating that xx yy

> 12 We suppress the index for households in the equations to make the notation less cluttered.

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# **Demand and Supply Curves in Political Markets:**

# **Understanding the Problem of Public Goods and Why Governments Fail Them**

Stuti Khemani<sup>1</sup> World Bank _JEL classification codes_ : H1, H41, H7, E1, _Keywords_ : public goods; political economy; institutions; norms; preferences

> 1 This paper has been invited by Ben Ross Schneider and Melani Cammett, Editors of the Cambridge Elements Series on the Politics of Development. I thank Melani Cammett and Luis Serven for really helpful comments on the first drafts, and Maya Eden and Rafael Martinez for discussion that helped to clarify the ideas in this paper. I thank Swati Raychaudhuri for assistance with the figures and tables. The opinions expressed here are those of the author and need not coincide with those of the World Bank or its Executive Directors.
<!-- Start of picture text --> HE High income: OECD «= HE. High income: nonOECD<br>EEE) Low income (Lower middle income<br>1) Upper middle income<br><!-- End of picture text --> <!-- Start of picture text --> HM High income: OECD «= NNN: High income: nonOECD<br>HEE Low income (Lower middle income<br>1) Upper middle income<br><!-- End of picture text -->
# Figure 3. Private Capital Flows to Latin American Countries in Sample,

<!-- Start of picture text --> ARGENTINA 1991-93 BRAZIL<br>CUMULATIVE 1991-93 CUMULATIVE 1991-93<br>PraRM Equy F1a, Private Long-Ternm Debt<br>52.9%<br>'flv.?a Larg-Thrm Debt<br>9.4%<br>72. t Portfolio Equity 1:10w _ Direct Foreign Invst<br>-20.8%36 26.5%<br><!-- End of picture text --> <!-- Start of picture text --> CHILE<br>CUMULATIVE 1991-93<br>Private Long-Term Debt<br>39.7%e<br>Porttollo Equity Flows<br>14.0%<br>Direct Foreign Invest<br>46.3%.<br><!-- End of picture text --> MEXICO CUMULATIVE 1991-93 <!-- Start of picture text --> Portfolio Equity Frows<br>Pr;vate Long-Term Debt<br>14.6%<br>DirectrignIst<br><!-- End of picture text --> Source: The World Bank, World Debt Tables 1993-94
DHS sample, and by only 2.5 percentage points in the LSMS sample.<sup>9</sup> Similarly, for locations close enough to the road networks, bringing an electric grid 10 km closer marginally increases the probability of working by 8 percentage points in the DHS sample, and 6 percentage points in the LSMS sample. Differences in estimates obtained from the two samples differ as both surveys cover different sets of countries. Our preferred estimates come from the DHS sample, which covers more countries.

The joint marginal effect of these two types of infrastructure is positive, indicating that roads and electricity play complementary roles in job creation in sub-Saharan Africa. In other words, there are significant employment gains that arise from providing both types of infrastructure simultaneously. The estimates of Table 4 in the Appendix imply that being closer to a main road increases the positive effect of being closer to an electricity grid on the probability of being employed. These effects are statistically significant at the 0.1 percent level. To put these estimates in perspective, using the DHS sample, Figure 6 shows that the impact of increasing proximity to the electric grid grows for households that are closer to the road, and vice versa - the impact of increasing proximity to roads grows for households that have greater proximity to the electric grid. Being 10 km closer to the electric grid increases the probability that an individual is working by more than 8.4 percentage points when the individual’s household is located next to a main road, but only by 4 percentage points when located 10 km away from the main road network. Similarly, being 10 km closer to a main road network increases the probability that an individual is working by more than 25 percentage points when that individual’s household is located next to the electric grid, but by only 21 percentage points when the household is located 10 km away from the electric grid.

Figure 6: Marginal impact of proximity to roads (left) and electricity (right) on employment <!-- Start of picture text --> Marginal impact of bringing Marginal impact of bringing<br>grid closer by 10 km road closer by 10 km<br>25 25.7<br>20 21.3<br>15<br>10<br>8.4<br>5<br>4<br>0<br>Distance to the other infrastructure<br>0 km 10 km<br>Increase in the likelihood to be employed (in percentage point)<br><!-- End of picture text --> The effects of roads and electricity on the number of hours worked in the last seven days are consistent

> 9Note that the coefficient on the variable ”Proximity to nearest road” measures its marginal effect for locations within zero km of the electric grid. Similarly, the coefficient on the variable ”Proximity to electric grids” measures its marginal for locations within zero km of the road.

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Policy Research Working Paper 8430

# **Abstract**

In fragile states and areas beset by insecurity and conflict, the time available for a face-to-face interview is typically limited. That prevents administering the lengthy household consumption expenditure surveys used for measuring poverty. This paper presents a new approach to obtain unbiased estimates of poverty when the time to conduct interviews is a binding constraint. The finite list of consumption recall items is partitioned selectively into a core module and algorithmically into nonoverlapping optional modules. Each household is systematically assigned the core module and randomly assigned one of the optional modules. Multiple imputation techniques are then used to estimate total household consumption. Based on ex post simulations, the approach is demonstrated to yield reliable estimates of per capita consumption and poverty using data from a regular household budget survey collected in Hargeisa, Somaliland. The approach is then applied to a survey conducted in Mogadishu where interview time could not exceed 60 minutes.

This paper is a product of the Poverty and Equity 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/research. The authors may be contacted at upape@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
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