rafmacalaba/datause-encoder-data huggingface dataset:
As is widely accepted, import data tend to be more reliable than export data, especially for developing countries, and so we have used mirror statistics from importing countries to put together the dataset. The dataset spans a period of 20 years from 1985 to 2005, sufficient to undertake meaningful survival analysis. Utilizing the COMTRADE database, we chose all importers that report consistent data at our desired level of disaggregation over the entire sample period. This means, however, that the number of importers in our data set is less than in previous studies.<sup>4</sup> We were, however, mindful to include only countries that reliably report annual import information so as to exclude the possibility that apparent export births and deaths were not the result of a country failing to report in a particular year.

Inevitably, some of the available data are left or right censored. This is the case for about a quarter of the flows in our sample. Left censoring implies that we observe flows in the first year of our sample period but do not know for how long they have been in existence. Right censoring implies that we observe flows in the final year of our sample but do not know how long they will continue to exist. The latter type of censoring is less of a problem since the estimation techniques use the information on the time of survival up to the censoring point but do not make any inference upon what happened to the spell subsequently. Left-censoring is a more serious problem. Econometric techniques that deal with left-censored spells efficiently typically have to rely on strong additional assumptions or supplementary data which is not available in our case.5 We have therefore decided to exclude left-censored observations from our dataset.

> 4 The need for consistent import data over 21 years means that most African countries and transition economies are absent from the importer group. The COMTRADE database revealed that the largest sample of importers could be obtained for data reported according to the Standard International Trade Classification (SITC) as opposed to the Harmonised System that has been more recently introduced. Working with the SITC allows for the longest possible time dimension. As the SITC has been twice revised during our sample period, we combined the data using the backwards concordance to Revision 1. In general backwards concordance leads to more consistent product level data over time but at the price of less detail. There is an issue regarding a small number of product categories that are joined together in subsequent revisions. There are around 100 categories where backward concordance appears to be problematic as shown by the appearance of zeros in the aggregate of imports from all countries in our sample. Including these product categories may therefore introduce some bias into the analysis of survival. On the other hand, the fact that these product categories are aggregated over time suggests that they have become less important and indeed may contain important information. An extreme example is the product code for steam engines.

> 5 See, for example, D’Addio and Rosholm (2005)

5
There is a gap in the current literature on condom use that this study helps to fill. There is not a lot of information available about condom use in extramarital situations, especially using nationally representative samples from many different countries in Africa. In addition to establishing baseline condom use by men and women inside marriage, this study compares condom use for married males and females outside their marriage to condom use by unmarried males and females. In almost all of countries included, reported condom use by married males in extramarital intercourse is similar to reported condom use by unmarried males. However, in over half of the countries, married females report using condoms in extramarital sex significantly less than unmarried females. This is of great concern because of the increased possibility of becoming infected or infecting their multiple partners with HIV. Based on the data on discordant couples (de Walque 2007) discussed earlier that shows females are likely having more extramarital sex than they are reporting, the low levels of condom use during extramarital sex by married females seen in this analysis is even more troubling.

# **_Reasons for lack of condom use_**

There are many possible reasons for low condom use across Africa that are often intertwined with traditional belief systems about sex, reproduction, and gender roles. Bond and Dover (1997) explain cultural attitudes surrounding sex and condom use based on research on migrant workers in rural Zambia. The importance of sex in order to procreate, that ejaculation into the female is fundamental to the enjoyment of sex by both partners, and how sexual intercourse relates to beliefs about being a virile male and fertile 8
1. **Agriculture and Rural Development**

# **The MENA Economies**

Situated at important crossroads between Africa, Asia, and Europe, the countries of the Middle East and North Africa (MENA) forn one of the largest groups of developing countries in the world economy,' Also, with the initiation in recent years of a peace process between Israel and its Arab neighbors the region has increasingly moved to the foreground of the world economy, as private businessmen and public officials in the region have begun to look more earnestly to the region's potential for enjoying higher sustained growth and greater economic development.<sup>2</sup> Although MENA includes a number of oil-rich countries such as Saudi Arabia, Kuwait, Qatar, and United Arab Emirates, it comprises mainly middle-income developing countries whose per capita income levels and economic performance, including in regard to indicators of social welfare, fall appreciably below the mean levels of countries in other regions at similar rungs of the development ladder globally (Tables 1 and 2). Moreover, the circumstances and lackluster economic performnance of the populous low-to-lower-middle-income countries in MENA -- Iraq, Syria, and Yemen in the Middle East, and Egypt, Morocco, and Sudan in North Africa -- are the subject of considerable international concern, including as measured by large shipments of international food aid to some prominent MENA countries.<sup>3</sup> ' The countries comprising MENA are indicated in the tables accompanying this section. In the main, the countries are those specified in the World Bank's _World Development Report_ series, with the addition of four countries: Cyprus and Turkey in the Middle East, and Mauritania and Sudan in North Africa.

2 Fischer et al. (1993), for instance, estimate that reduced military expenditures in the Middle East would release productive resources amounting to about 10 percent of GDP per annum and yield an increase in economic growth of 1-to-2 percentage points in the countries of the region. See also Fishelson (1989) and Fischer (1993).

3 In 1993, Egypt received international food aid shipments of cereals amounting to nearly 500 thousand mctric tons, followed by Jordan, Morocco, and Sudan with shipments of between 200 and 250 thousand tons each. See FAO (1994).
impact in depriving Rwanda of its most skilled inhabitants. This is true independent of the omitted variable bias.

# **References**

- Akresh, Richard and Damien de Walque. 2008. “Armed conflict and schooling : evidence from the 1994 Rwandan genocide”. World Bank Policy Research Working Paper

- 4606, The World Bank, Washington, DC.

- André, Catherine and Jean-Philippe Platteau. 1998. Land Relations under unbearable stress: Rwanda caught in the Malthusian Trap. _Journal of Economic behaviour and Organisation_ , 34, 1– 47

- Bundervoet, Tom. 2009. Wealth, Density and Political Power: the 1993 Killings in Burundi, _Journal of Peace Research_ , forthcoming

- Chrétien, Jean-Pierre. 2000. Afrique des Grands lacs : deux mille ans d'histoire , Paris, Aubier.

- De Lame, Danielle. 1996. Une Colline entre mille ou me calme avant la tempete,

- Transformations et Blocages du Rwanda Rural, Musée Royale de l’ Afrique Centrale, Tervuren

- de Walque, Damien. 2005. “Selective Mortality During the Khmer Rouge Period in Cambodia”, _Population and Development Review_ 31 (2): 351-368.

- de Walque, Damien. 2006. “The Socio-Demographic Legacy of the Khmer Rouge Period in Cambodia, _Population Studies_ , 60 (2): 223-231.

- Gakidou, Emmanuela and Gary King. 2006. “Death by Survey: Estimating Adult Mortality without Selection Bias from Sibling Survival Data.” _Demography, 43(3), 569-585._

- Heuveline, Patrick. 2001(a). “Approaches to Measuring Genocide: Excess Mortality During the Khmer Rouge Period.” In D. Chirot and M. Seligman, eds., _Ethnopolitical Warfare. Causes, Consequences and Possible Solutions._ Washington D.C.: American Psychological Association.

- Heuveline, Patrick. 2001(b). “The Demographic Analysis of Mortality Crises: The Case of Cambodia, 1970-1979.” In H. E. Reed and C. B. Keely, eds., _Forced Migration and Mortality_ . Washington, D.C.: National Academy Press.

- Kalyvas, Stathis. 2006. The Logic of Violene in Civil War, Cambridge University Press, Cambridge

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# **Box V.1: The** Education Budget **in** Mali

Mali's public budget has three main components: the national budget, the regional budgets, and special accounts (budgets annexes). The national budget, in turn, has three categories: ministries; "general outlays" (charges communes), essentially subsidies and transfers; and equipment. Capital expenditures figure mainly under the equipment rubric, but they are included in some of the ministerial budgets. The equipment budget also includes a substantial portion of recurrent expenditures.

Education expenditures, defined as those related to the formal education system managed by the Ministry of Education, are scattered in several places. It takes careful detective work to determine the true size and composition of the education sector budget. More than 80 percent of primary education is financed through the regional budgets. The "charges communes' rubric includes subsidies to private schools, as well as local and foreign transportation costs incurred by students, teachers, and Ministry of Education officials. The following table shows how the sector's recurrent budget is pieced together.

|1988 Pub|lic**Recurrent**Expe<br>Budget<br>|nditure on Edu<br>ary Source:<br>|cation**(FCF**<br>|**A mfi.)**|
|---|---|---|---|---|
|Subsector|Ministry of<br>Education_(@°!_|Charges<br> Cornmunes|Regional<br>Budgets|3[otal (To)|
|Primary Ed.<br>|415 (3.2)<br>|253<br>|3,154|3,822 (21.6)<br>|
|Secondary Ed.<br>|8,347 (64.0)<br> <br>|649<br>|--|8,996 (51.0)<br>|
|Teacher Training<br>|<br>853 (6.5)<br>|22<br>|--|875 (5.0)|
|Higher Ed.<br>|2,508 (19.3)<br>|539|--<br>|3,047 (17.2)<br>|
|Administration<br>|910f7.)<br>7.<br>|--<br>|3<br>|913 (5.2)<br>|
|Total<br>|13,033 (100.0)<br>|1,463|3,157|17,653 (100.0)<br>|
|Percentage of<br>|(19.4)<br>|||(26.2)|
|Total Recurrent|Budget||||

This example shows how seriously the government's financial commitment to education may be underestimated if the analysis is limited to the budget of the line ministry. In Mali, the line ministry represents 19 percent of total public recurrent expenditure, whereas the comprehensive sector budget accounts for 26 percent. More important, the sector budget shows a more rational intrasectoral distribution of resources, even if heavily skewed against primary education.

Snurce: Serge Cuenin, "Analyse des Depenses Budgetaires Relatives a I'Education", IREDU, September 1989 (background paper for MALI Education Sector Consolidation Project. IDA Cr. 2054-MLI).

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- 5 -

when young reduce savings because it shortens the length of the earning life and increases the debt to be reimbursed. In the tradition of the life-cycle approach, the model assumes that people are selfish because they only care about their own welfare excluding that of the next generation (see Modigliani (1980)). However, this assumption does not affect the sign of the relationship between education and savings. A similar negative correlation would be obtained if selfish parents "purchase," in exchange for education financing, a promise by children to provide assistance in old age (see Kotlikoff and Spivak (1981)). In that case, people would reduce savings, other things equal, because they expect old-age support from their children. If altruism parents care about the welfare of their children and thus behave as if their planning horizon is infinite, they would provide free education financing (grant) to their children. 5 The resulting impact on savings is again likely to be negative, because they will consume less during their earning life or reduce their financial bequest. Reduced bequest would lower the disposable income of the young and, thus, decreased their savings. **6** We do not here intend to confront these three hypothesizes which would require desegregated (household or individual surveys) data, generally unavailable in developing countries.

So far the model is similar to the life-cycle hypothesis with the exception that the individual will invest in education in the first period of his life. Notice that, for simplicity, the level of investment in education is assumed to be exogenous. Rather than to make endogenous the individual choice by using the approach developed by Azariadis and Drazen (1990) or d'Autume and Michel (1994), we prefer in this paper 5. In the absence of voluntarily intergenerational altruism, this role can be played by the government which may subsidize education through lump-sum taxes, implying a financial transfer from the current to the next generation (see Lucas 1988). The intervention of the government may also modify individual choices as recently discussed by Glomm and Ravikumar (1992), in particular taxes on production or on consumption may have different impacts on savings. This issue is beyond the scope of this paper, but it would interesting for further research to examine closely the impact of public and private education on national savings.

6. This is traditional discussion (e.g. Blinder (1976)) whether human or financial wealth is the medium for intergenerational transfers. In a macroeconomic perspective, this is important because bequests in human form (education) entail either consumer expenditures in the national income, or withdrawals from the labor force, whereas financial bequests constitute national savings.
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plot size, however, male plot managers use more male hired labor than female plot managers, but the difference is not significant.

# _South East and South South_

Although for the South East and South South regions we also observe differences in value of harvest per hectare favoring male managed plots (Table 4), the difference is not statistically significant. However, we still want to understand the factors influencing where differences do occur and again provide descriptive statistics of the characteristics of managers and input use.

In the two southern regions, female plot managers are more likely to be non-Muslim and have less years of schooling compared with male managers. Male managers are more likely to be from households with larger family sizes and have significantly more household adult male and female labor pool.

Unlike the North sample, significant differences in the land size managed by male and female plot managers are not found. On average, male managers are from households who used extension services and have higher value of agricultural capital. While we do find that men are more likely to use herbicide, we find no differences in fertilizer, herbicide or pesticide use per hectare between male and female managed plots. However, we do find significant differences in the use of labor. Male managed plots are more likely to use male family labor and have significantly more days of male family labor compared with female managed plots. Although, female managed plots are more likely to use female family labor, there is no statistically significant difference between days of female family labor used on plots between the two groups. For hired labor, male managed plots are more likely to use hired male labor and have significantly more days of hired male and female labor. However, once we normalize for plot size, these differences in days of hired labor are no longer statistically significant.

# **3. Assessing gender differentials**

The traditional method for examining differences in agriculture productivity between men and women is by estimating a yield function that models the value of output per hectare as a function of a set of factors that influence production as well as an indicator of the gender of the plot manager (Quisumbing, 1996). The motivation for taking this approach is to determine if any differences between male and female managed plots can be explained through factors other than gender (although they may, in turn, be driven by gender relations). A common approach in the literature is to use the gender of the head as the gender indicator, but with the GHS-Panel data we are able to identify the gender of each plot manager within a household. This allows the use of the manager’s gender rather than that of the household head who may not be the primary decision maker on the plot. We examine the yield function for plot _i_ under the management of plot manager _j_ : 8
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markets where they face familiar competitors, potentially facilitating collusion (Ghemawat and Thomas, 2008).

**Demand.** Population, income, and construction investment determine demand. In our sample cement expenditure itself accounts for 1.3 percent of GDP on average, or 13.5 percent of construction investment. We consider several alternative estimates of a demand curve, where _Qit_ , the total quantity of cement in each economy _i_ and year _t_ , is a function of the price _Pit_ (measured in US dollars, for comparability across countries) and exogenous market characteristics **D** _it_ :

The market price elasticity of demand (expressed as a positive number) is _η ≡−_<sup>_∂_</sup> _∂P_<sup>_<u>Q</u>_</sup> _i_<sup>_<u>i</u>_</sup> _QPii_<sup>=</sup> _−α_ 1. To account for potentially endogenous prices that could bias our estimate of _−α_ 1, we exploit the international data and use cement exports to the world of the nearest neighboring country as an instrument for the cement price in a country. These exports proxy for the availability of low-cost imports. Intuitively, if a firm in country _i_ prices too high, competitors can import cement from country _i_ ’s neighbor, especially if the neighbor exports large cement volumes. The threat of imports from the neighbor therefore shifts the price _Pi_ , but is plausibly unrelated to unobserved local demand _ξit_ .<sup>10</sup> The neighboring country is identified using the minimum of the bilateral distances between country centroids reported by Head and Mayer (2014). The first stage relationship between prices and exports of the nearest neighbor is shown in Figure 5. Though there is substantial variation in prices within countries whose neighbor does not export, all countries with a neighbor who exports substantial quantities have lower prices, which is consistent with our argument about the relevance of the instrument.

The identifying assumption behind this instrument is that exports of the nearest neighbor are related primarily the size of the neighbor’s domestic market and available factors, rather than unobserved local demand _ξit_ . Genesove and Mullin (1998) use a similar approach to identify the elasticity of demand for sugar in the United States, instrumenting for the United States price with the volume of sugar imports to the United States from Cuba in a time series.

> 10We experimented with alternative cost shifter instruments, namely the prices of diesel and electricity. Using these prices as instruments for the cement price, the estimated elasticity was not statistically different. We prefer the neighbor’s exports to these candidate instruments because the specification with the price of electricity had fewer observations due to limitations of the ICP electricity price series, leading to larger standard errors, and because of concerns that diesel is a complement to cement, and so enters directly into demand. In Section 5, we evaluate the sensitivity of markups to beliefs about violations of the exclusion restriction related to the neighbor’s exports.

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|Author (Year)|Study Type & Location|Participants|Diet Assessed|Nutrition, health<br>outcomes assessed|Key fndings|
|---|---|---|---|---|---|
|Alhazami et al<br>(2013)|SRM of 15 cohort studies, 2<br>from China, rest from HICs|Adults 20-90<br>years|Healthy and unhealthy<br>dietary patterns, highest<br>vs. lowest adherence<br>(assessed by FFQ n=14;<br>dietaryhistoryn=1)|T2DM|Reduced risk of T2DM for healthy<br>dietary patterns (RR 0.79, 95% CI 0.74,<br>0.86); increased risk for unhealthy<br>dietary patterns (RR 1.44, 1.33, 1.57)|
|Esposito et al.<br>(2014)|Meta-analysis of 18<br>prospective cohort studies<br>(20 cohorts), 4 regions (the<br>United States 2, Europe 5,<br>Australia 1,Asia 5)|Adults 20-90<br>years<br>n=21 372|Healthy dietary patterns<br>(Mediterranean, DASH,<br>AHEI)|T2DM|Participants with the greatest<br>adherence to healthy diets were less<br>likely to develop T2DM (RR 0.80; 95%<br>CI 0.74, 0.86)|
|McEvoy et al.<br>(2014)|SRM of 33 studies (19<br>cross-sectional, 12<br>prospective cohort, 2<br>nested case control)<br>included Mexico, the<br>Islamic Republic of Iran,<br>India,and China|Adults<br>n=309 430|Dietary patterns(healthy/<br>prudent vs. unhealthy/<br>western)|T2DM|Those in the highest category of<br>healthy/prudent diet lower risk for<br>T2DM (OR 0.85; 95% CI 0.80, 0.91).<br>Highest vs lowest category of<br>unhealthy/western diet had increased<br>risk (OR 1.41; 1.32, 1.52)|
|Lee and Park<br>(2017)|SRM of 14 studies (12 cross<br>sectional, 2 cohort),<br>included India; Barbados;<br>Pakistan; China; Taiwan,<br>China|_Not stated_|Vegetarian diet|T2DM|Vegetarian diet is inversely associated<br>with T2DM risk (OR 0.73; 95% CI 0.61,<br>0.87)|
|Sarsangi et al.<br>(2022)|SRM of 16 prospective<br>studies, 1 from the Islamic<br>Republic of Iran, rest from<br>HICs|n= 759 806|Mediterranean diet|T2DM|Greater adherence to Mediterranean<br>diet associated with reduced risk of<br>T2DM (RR 0.83; 95% CI 0.77, 0.90),|
|Yu et al. (2022)|SRM of 19 studies (8 cohort,<br>11 RCTs), includes China,<br>South Asia, the Middle East,<br>and HICs|Adults 18-87y<br>(n=1034)|White vs Brown rice<br>intake|T2DM|Found a positive association between<br>white rice intake and risk of T2DM (RR,<br>1.16; 95% CI 1.02, 1.32). Findings also<br>suggest that brown rice is inversely<br>associated with risk of T2DM (RR 0.89;<br>95% CI 0.81, 0.97 (based on limited<br>data)|
|Carter et al.<br>(2010)|SRM of 6 prospective cohort<br>studies, 1 from China, rest<br>from the United States|Adults 30-74<br>years<br>(n=223 512)|Fruit and vegetable intake|T2DM|Greater intake of green leafy<br>vegetables associated with reduced<br>risk of T2DM (hazard ratio0.86, 95% CI<br>0.77, 0.97); no signifcant benefts of<br>increasing consumption of vegetables,<br>fruit,or fruit and vegetables combined.|

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