rafmacalaba/datause-encoder-data huggingface dataset:
21 The most trade-distorted products are sugar, milk and rice. The differences within the four groups of commodities in the extent to which their global trade has been taxed are considerable (see Appendix Figure 1). Among the grains it is rice trade that has been taxed most since the 1970s, while among the oilseeds and tropical crops it is sesame and sugar trade, respectively, that are taxed most. Feedgrain and oilseed trade, especially the major items of maize and soybean, has been taxed least among those crops shown, and at very low rates compared with livestock products, especially milk. Note, however, that the extent of distortions to trade has diminished more for livestock products than for crops since the 1980s when agricultural price and trade reforms began to be implemented in numerous countries (as chronicled in, for example, Anderson and Associates 2009).

In table 2 the 2000-04 TRI estimates are disaggregated to show their production and consumption components. This disaggregation follows equation (4a). Two points are worth noting from that table. First, the production and consumption components tend to be similar in magnitude, indicating that the main policy interventions are at the national borders of countries rather than behind-the-border domestic measures. Second, for those few products for which the TRI is negative, indicating that there is still some use of explicit or implicit trade-expanding measures, the disaggregation reveals possible reasons. In the case of cotton it is coming from pro-trade production measures (such as have operated in the United States), whereas in the case of millet and groundnuts it is coming from pro-trade consumption measures (such as import subsidies in Africa at desperate times of food shortages just prior to the next harvest,
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# Table 1: Descriptive Statistics and the Correlation Matrix

||_Mean_|_Std. Dev._|_SDGDP_|_SDCONS_|_SDINV_|_BANK_|_LLY_|_PRIVATE_|_PRIVY_|
|---|---|---|---|---|---|---|---|---|---|
|_SDGDP_|5.88|4.93|1|.85|.59|-. 349|-. 004|-. 210|-. 265|
|_SDCONS_|6.20|5.81|...|1|.65|-. 377|.08|-. 197|- .249|
|_SDINV_|14.0|8.93|...|...|1|-. 313|-. 116|-. 066|-. 293|
|_BANK_|.727|.200|...|...|...|1|.048|.375|.410|
|_LLY_|.147|.077|...|...|...|...|1|-.004|.253|
|_PRIVATE_|.714|.368|...|...|...|...|...|1|.170|
|_PRIVY_|.282|.219|...|...|...|...|...|...|1|
Several caveats apply to the analysis and suggest directions for further research. The CGE model in this paper is static, and it does not incorporate equilibrium unemployment (i.e., outcomes other than the standard setup with full employment). Moreover, available data were not sufficient to explore systematic differences in labor productivity between related formal and informal activities (i.e., productivity differences beyond differences in capital-labor ratios).

# **Acknowledgment**

The authors appreciate the help and cooperation of Frank Adoho and Ligbet Tomekpa Magloire for developing the social accounting matrix of Cote d’Ivoire, including informal sector accounts. Financial supports provided by the World Bank’s Carbon Finance Unit is also acknowledged.

# **References**

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35
difference with propensity score matching approach to address observed and time-invariant unobserved factors affecting program placement. The study finds a significant reduction in the incidence of waterborne diseases, but less clear effects on labor supply.

Other studies have also found positive impacts on women’s employment of access to non-water types of infrastructure, such as electricity.<sup>5</sup> However, these studies rely on strong assumptions about how infrastructure projects or resources are placed, relative to factors that might be correlated with women’s labor supply.

With respect to child outcomes, strong geographic effects on schooling and health have often been found in the literature, although their attribution to local infrastructure is often uncertain (Ginther et al., 2000). There is a small literature on the effects of improved water and sanitation on child health. Jalan and Ravallion (2003) find that child health outcomes (specifically the prevalence and severity of diarrhea) are better for Indian children living in villages with access to piped water than for those in observationally similar families in villages lacking such infrastructure. Using cross-country data, Fay et al. (2005) argue that access to basic infrastructure (piped water, sanitation, and electricity) reduces infant and under-five child mortality and the incidence of stunting in children. However, Ravallion (2007) questions the robustness of the Fay et al. findings based on a number of concerns with their methodology. An alternative approach for testing the Fay et al. hypotheses under weaker assumptions does not confirm their findings, though does point to a much more important role played by mother’s schooling in reducing infant and child mortality. Mangyo (2008) uses individual-level panel data from China to show that access to water in the home has a positive effect on child health, but only when mothers are relatively more educated.

The above discussion suggests that in examining the impacts of water infrastructure, it is crucial not only to control for geographic and community effects, but also to account for a range of individual and household variables that can affect intra-

> 5 Dinkelman (2009) examines the employment effects of an electricity roll-out program in South Africa, instrumenting for project placement with local variation in land slope. Women’s employment rates are estimated to increase by about 9.5 percentage points in treated areas, and more so for women with fewer child care responsibilities.  Men’s employment is not significantly affected. Grogan and Sadanand (2009) also examine the effects of electrification on rural female employment and earnings in Guatemala; instrumenting for the program, they find that women's earnings improved substantially from better access to electricity (around 60%), and that women also spent more time in market-based work.

7
can be considered the implicit subsidy amount paid by the debt ir country to the environmental group. It reflects the amount of the secondary market discount not captured by the country, assuming that the secondary market price somewhat reflects the true price of the debt.

# Debt-for-Nature Transactions

As shown in table 1, the total amount of debt (face value) converted in eight debt-for-nature swaps has reached only $79 million as of mid-1989. This is significantly less than other transactions in the secondary market for developing-country loans, which reached a level of $42 billion in 1988 (Debt and International Finance Division Quarterly Review, March 1989). Of the four countries who have debt-for-nature programs (Bolivia, Costa Rica, Ecuador, Philippines), Costa Rica has been the most active, retiring over $68 million (face value) of debt.

Table 1. Debt-for-Nature Transactions.

|---------------------------------------<br>Country|------------------<br>Date|------<br> <br>Costi|Face<br>Value|Local<br>Currency3|_<br>Organization<sup>4</sup>|
|---|---|---|---|---|---|
|---------------------------------------|------------------|---|||__--|
|Bolivia|7/87|<br>$100,000|<br>$650,000|$250,000|<br>CI|
|Ecuador<br>|12/87|<br>$354,000|$1,000,000|$1,000,000|<br>WWF|
|Costa Rica|2/88|<br>$891,000|$5,400,0005|$4,050,000|<br>NPF|
|Costa Rica|6/88|$5,000,000|$33,000,000|$11,000,000|<br>Netherlands|
|Costa Rica|6/88|$3,500,000|$24,500,000|$17,000,000|<br>Sweden|
|Philippines|1/89|<br>$200,000|<br>$390,000|$390,000|<br>WWF|
|Costa Rica|1/89|<br>$784,000|$5,6P-,000|$1,680,000|<br>TNC|
|Ecuador|4/89|$1,068,750|$9,000,000|$9,000,000|<br>WWF/TNC|

# Notes:

1. $US expenditure by environmental g-oups or governments to purchase the debt on the secondary market.

2. $US face value of the debtor country's external obligatione purchased by the environmental groups or governments on the secondary market.

4
single most important consumption item of both urban and rural households in Bangladesh. Rice purchase outlays average 12 percent of total monthly expenditures for urban households and 15 percent for the rural households, with a significant difference by household’s welfare level. As shown in Table 3, in rural areas rice purchases constitute around 22 percent of total expenditures of households in the bottom decile of total per capita expenditures, while they are 3 percent for households in the top decile. In addition to purchases, own consumption of self-produced rice accounts for about 6 to 11 percent of total expenditures for rural households at different welfare levels.

**<u>Table 3.  Dependence on rice in rural areas in Bangladesh.</u>**

||||_Decil_<br>|_es of t_<br>|_otal pe_<br>|_r capit_<br>|_a expen_<br>|_diture_<br>|_s_<br>||
|---|---|---|---|---|---|---|---|---|---|---|
||**1**|**2**|**3**|**4**|**5**|**6**|**7**|**8**|**9**|**10**|
|_(percent of all househo_|_lds)_||||||||||
|Net buyers of rice|87|80|78|76|68|71|66|59|60|65|
|Net sellers of rice|10|17|18|21|28|24|29|35|34|30|
|Agricultural wage|41|34|23|21|14|13|8|3|3|1|
|earners|||||||||||
|Landless households|71|62|58|54|44|46|42|34|30|40|
|_(percent of total incom_|_e or ex_|_pendi_|_tures)_||||||||
|Income from rice|9|12|12|13|16|14|16|17|16|12|
|production|||||||||||
|Expenditures on rice:|||||||||||
|-purchased|35|28|25|23|20|17|16|12|9|7|
|-self-produced|6|8|10|9|10|10|10|11|10|7|

Note: Landless are defined as functionally landless with less than 0.1 acres of cultivated land. “Agricultural wage earners” are defined as households with at least one member whose primary occupation is agricultural work for a wage. Source: 2000 HIES (only rural households).

When all rural households in Bangladesh are categorized into rice net sellers and net buyers, we find that, as expected, poverty incidence is higher among the net buyers than among the net sellers, with a 16 percentage point difference in poverty rates (Appendix Table A2). On average, 34 percent of Bangladeshi rural households can be classified as the net sellers of rice, with a strongly pronounced declining share of net buyers and increasing share of net sellers with income (Table 3). Half of rural households in Bangladesh are functionally landless, and on average 20 percent are agricultural wage earners. As expected, the share of landless households and agricultural wage earners among all rural households declines with income. Income from rice production is 13
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78
## **ANNEX I: QUESIIONNAIRE FOR EDUCATMON SECrOR TREATMENT IN PUBUC EXPENDrTURE REVIEWS**

## **L ITRODUCTION**

Country: Review Name: Number: Date:

# IL THE **EDUCATION** SECIOR IN THE MACROECONOMIC **CONTEXT**

# A. Justification and operational context of review

1. What is the focus of the report? To analyze the impact of education sector concerns on the overall public budget?

To analyze primarily the overall public budget with: education funding as a targeted area for budgetary concerns_ education as a minor area of concern_ not clear/not stated_ 2. Is the review multisectoral or on the education sector only? If multisectoral, what sectors are reviewed in separate chapters or sections?

# How is education treated?

an integral sectora minor sector_ barely mentioned_ not treated at all

# B. Assessment of country situation

1. Country situation at time of review Country income level: **LU** LMI UMI UI Classified as oil exporter? Yes/No Classified as "highly indebted"? Yes/No

2. Total government expenditure as a percentage of GDP? (For comparative purposes, data can be taken from World Development Report.)

- Year? _ Rising trend?_ _ Falling trend?

3. What is the overall macroeconomic situation of the country? Improving Stable_ Deteriorating-_ What is the time period for the analyis? Short term Long term 57
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Caliendo, L. and Parro, F., 2015. “Estimates of the Trade and Welfare Effects of NAFTA.” The Review of Economic Studies. 82(1): 1-44.

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De Soyres, F., Mulabdic, A., Murray, S., Rocha, N. and Ruta, M., 2018. “How much will the Belt and Road Initiative reduce trade costs?” Policy Research Working Paper 8614. Washington, DC: The World Bank.

<mark>De Soyres, F., Mulabdic, A. and Ruta, M., 2019. “Common transport infrastructure: A quantitative model and estimates from the Belt and Road Initiative.” P</mark> olicy Research Working Paper 8801. Washington, DC: The World Bank.

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Djankov, S. 2016. “The Rationale Behind China’s Belt and Road Intiative” in China’s Belt and Road Initiative: Motives, Scope and Challenges., Djankov, S. and Miner, S. editors. Washington, DC: Peterson Institution for International Economics https://www.piie.com/system/files/documents/piieb16-2_1.pdf Duranton, G. and Puga, D., 2004. Micro-foundations of urban agglomeration economies. Handbook of Regional and Urban Economics, Vol. 4, pp. 2063-2117.

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34
2007). The impacts of these measures on workers’ average months and real wages after the GFC presented in Appendix Table C4 are similar to those in Figure 1.

# _D. Heterogeneity across Worker Characteristics_

Our main results are obtained controlling for a rich set of worker characteristics; thus, they reflect adjustments to GFC firm shocks _within_ worker categories. In this section, we allow the impacts of GFC firm shocks to differ _across_ worker categories. To conduct this heterogeneity analysis, we modify Equation (2) to include the GFC firm shock interacted with indicator variables for different categories of workers: where all variables are defined as above and _categi_<sup>_m_</sup> identifies the _m_ = 1 _,_ ... _, M_ worker categories considered: males versus females, workers with higher education versus no higher education, young (under 50) versus old (50-65) workers, workers with high versus low previous formal sector attachment, and workers with different ability given by the terciles of estimated worker fixed effects from an Abowd et al. (1999) decomposition of worker wages into worker and firm components (described in Appendix B).<sup>32</sup> Equation (5) is a highly flexible specification given that all variables, including controls and fixed effects, are interacted with the worker categories.

Equation (5) does not allow for dynamic effects of the GFC firm shock for the focus to be on effects across worker categories. Hence it is useful to first examine the average effect of the GFC firm shock over the post-GFC period across all workers (thus ignoring all interactions). The estimates at the top of Table 2 indicate that a larger GDP decline in firms’ export destinations results in a significant decline in average months worked and average real wages in Brazil as an average in the post-2009 period.

Table 2 shows that a strong negative adjustment of employment and wages to GFC firm shocks is found only for less educated workers whereas for highly educated workers there is no adjustment. Older workers see a significantly larger decline of their months worked in face of more adverse GFC firm shocks. Appendix Table C5 shows that Brazilian workers with lower ability (in the first two terciles of the estimated worker fixed effects distribution) see a significantly more negative adjustment of their employment than workers with higher ability. Gender and previous formal sector labor attachment do not matter significantly for worker adjustment.

Taken as a whole, the findings on worker heterogeneity suggest that the more ”fragile”

> 32The worker characteristics are defined as of 2007.

15
# **Africa and Arab Gulf States: Divergent Development Paths and Prospects for Convergence**

Hippolyte Fofack<sup>1</sup> The World Bank Group, Washington DC JEL Classifications: B41, F32, F35, H63, O55

**Keywords** : Divergent development paths, institutional continuity, intergenerational accountability

> 1 An earlier version of this paper was presented at the Africa-Gulf Relationships Conference in Abu Dhabi, United Arabs Emirate in March 2009. The Conference was jointly organized by New York University Abu Dhabi Institute, NYU Africa House and the Emirates Center for Strategic Studies and Research. I am grateful to participants to the Conference for their valuable comments. I would also like to thank Pierre-Richard Agénor, Kevin Carey, Shanta Devarajan, Ibrahim Elbadawi, Auguste Kouame, Raj Nallari, Leonce Ndikumana, Kasirim Nwuke, Anver Versi and Yaw Nyarko for helpful comments and Nihal Bayraktar for excellent research assistance.