rafmacalaba/datause-encoder-data huggingface dataset:
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Since the available data on military activity indicate that the fraction of GDP devoted to the military varies widely _both_ across countries and over time, our empirical methodology is designed to exploit these two dimensions of the data to overcome some of the shortcomings of past empirical work and obtain robust estimates of the effect of military expenditures on investment and economic growth. 1/ Specifically, we employ an econometric technique that was proposed in our earlier paper (Knight, Loayza, and Villanueva (1993)) to deal with time-series crosssection data.

To construct the panel data set we work with non-overlapping intervals of five years each. We have cross-sectional data covering output growth and several other variables in three separate five-year time periods: 1971-75, 1976-80, and 1981-85. Since data for all variables are available for 79 - countries, this gives us a relatively large panel-data sample of 79 x 3 237 observations on the dependent variables in equations (1) and (2). We measure the growth of per capita output over a 5-year interval, rather than a single year. This procedure provides a simple way of averaging out shortrun cyclical variations in the rate of capacity utilization, thereby helping to ensure that this variable approximates output growth at the average rate of capacity utilization in each five-year time period for each country in the sample. 2/ Similarly, the data for the investment ratio _sk_ are _i/_ In this paper, the term investment, by itself, refers to physical capital investment. When we refer to human capital investment, we say so explicitly.

_.Z/_ This follows the technique used by Phillips (1958) to ensure that his estimated relation between the rate of change of nominal wages and the level of the unemployment rate was approximately a phase line.
Table 6: Heterogeneity by gender and region

|||_Dependen_|_t variable:_||
|---|---|---|---|---|
|||current e|mployment||
||Females|Males|Rural|Urban|
||(1)|(2)|(3)|(4)|
|Dry shock (SPEI _< −_1_._5)|-0.0450***|-0.0227|-0.0749***|0.0506***|
||(0.0170)|(0.0139)|(0.0173)|(0.0156)|
|Wet shock (SPEI _>_ 1_._5)|0.0387|0.0413**|-0.0177|0.0710***|
||(0.0409)|(0.0195)|(0.0292)|(0.0246)|
|Controls|Yes|Yes|Yes|Yes|
|Full set of FEs|Yes|Yes|Yes|Yes|
|Observations|416,785|156,113|351,180|221,726|
|R<sup>2</sup>|0.227|0.279|0.258|0.234|

_∗ ∗∗ ∗∗∗_ **_Note:_ p** _<_ **0.1; p** _<_ **0.05; p** _<_ **0.01** . This table reports the coefficient estimates of the impacts of extreme weather conditions (wet and drought shock) on the probability of having a job conditional on restricted samples based on age group and gender. Two age group, 18-45 and individuals aged more than 45 years old are considered. Standard errors clustered at the grid cell-month-year level are reported in parenthesis.

33
**<u>Table 9: Maize, value chain assumptions</u>**

||**Yield**|||
|---|---|---|---|
|**Sector**|**(MT/Ha)**|<br>**Farm**|**Assembly**|
|||<br>**Rain-fed Ma**|**ize**|
|FAM-OPV|1.1|35kg saved OPV seed, 1x1<br>fertilizer, no chemicals, ox<br>cart to market, 85 days labor<br>(58 daysfamily)||
|FAM-low|1.50|25kg hybrid seed, 2x2<br>fertilizer, no chemicals, ox<br>cart to market, 90 days labor<br> (60 daysfamily)|Buy grain in small quantities at roadside from<br>many farmers, provide bags, short-term storage<br>and fumigation.|
|FAM-high|2.50|25kg hybrid seed, 4x4<br>fertilizer, no chemicals, hired<br>vehicle to market, 110 days<br>labor<br>(70 daysfamily)|Then 130km own transport into mill|
|||**Irrigated Ma**|**ize**|
|FAM-low<br>(irrig)|2.50|25kg hybrid seed, 2x1<br>fertilizer, no chemicals,<br>pumping costs and WUA fee,<br>ox cart to market, 100 days<br>labor(68 daysfamily)|Same as above, but assume less time to<br>assemble a sufficient quantity to justify|
|FAM-high<br>(irrig)|3.50|25kg hybrid seed, 4x4<br>fertilizer, no chemicals,<br>pumping costs and WUA fee,<br>ox cart to market, 115 days<br>labor(73 daysfamily)|delivery due to higher yields and concentrated<br>production.|

Fertilizer use expressed in 50kg bags basal (NPK) x 50kg bags top dressing (urea) per ha.

|**MK per MT**|**USD per MT**|**Product Form**|**Location**|
|---|---|---|---|
|**Farm gate price**<br>28,000|200.00|Loose grain|Roadside|
|**Assembled raw material**<br>45,000|321.43|Bagged grain|Into Mill|

57 **Farm-level analysis.** Key data from the farm level analysis of maize are summarized in the table below. In interpreting these results, it should be kept in mind that most small farmers in Malawi cultivate less than a full hectare of maize. On a national basis, only around 0.8 ha are available per farm household of which some land is usually given to a cash crop like tobacco or cotton. Assuming that a “typical” household only cultivates maybe 0.5 ha of maize, therefore, the actual costs and profits would be half of what are shown below. Or, to be more specific, half of a hectare of high-input rain fed maize provides an annual net profit of just USD 35.19 (MWK4,926) compared with half a hectare of high-input irrigated maize which returns USD 119.12 (MWK 16,676) or about 47% of Malawi’s 2007 per capita income.

24
The macroeconomics literature on gender inequality and development has grown rapidly since the early 1990s, when cross-country income data for a large sample of developed and developing countries became available. The papers reviewed in this section identify the effect of gender inequality on both development and economic growth using cross-country (or, sometimes, cross-country and cross-time) variations in gender inequality. The following subsections summarize findings from a large body of literature that aims to identify the effect of gender inequality on educational attainment and economic outcomes for both development and economic growth.

# **_2.1. Inequality in educational attainment_**

The seminal paper by Mankiw et al. (1992) highlights the cross-country correlation between human capital (measured by educational attainment), income, and growth. As a natural follow-up to this analysis, subsequent papers have attempted to separate the effect of male as compared with female educational attainment and to provide evidence on the relationship between gender inequality in schooling and economic growth.

Hill and King’s (1993) study is among the first to estimate the correlation between female education and the gender gap in primary and secondary enrollment on GDP per capita between 1975 and 1985. The estimated correlation is statistically and economically significant. Controlling for capital stock, the level of female education and the size of the labor force, countries with a female/male enrollment ratio lower than 0.75 have up to 25 percent lower GNP compared with similar countries with a lower level of gender inequality.

Knowles et al. (2002) is one of the few cross-country studies to estimate theory-based specifications. Following Mankiw et al. (1992), the authors augment the Solow model to incorporate female and male human capital separately and to estimate the effect of these types of human capital and of the gender gap on the steady-state level of income using long averages between 1960 and 1990. Their findings indicate a negative correlation between the size of the gap and income: controlling for male educational attainment, a lower level of female educational attainment is associated with lower steady-state income.

In line with the cross-country growth regression boom of the 1990s, most studies estimate the relationship between gender inequality in education and the growth rather than the 4
The SO also informed the community that the basis on which they would get funds for developmental activities is the number of households organized in a village, where a household is considered organized if at least one member (male or female) is an active member of a CO and has attended more than one CO meeting. A minimum of 40% of the village population needed to be organized in order to be eligible for the village development grant, with the size of the grant increasing with the number of households organized past the 40% cut-off, thus providing a strong incentive for broad mobilization. In addition, the inclusion of women and poor households in the mobilization and CO formation process was actively encouraged.

Once 40% of village households had at least one CO member, the village formed a Village Support Organization (VSO). This village institution comprises two elected members from each CO in the village. One of the main tasks of the VSO was the design and implementation of the Village Development Plan (VDP), a document that prioritized village development projects to be funded by the grant. The grant could be used for any productive purpose for the general benefit of the entire community including physical infrastructure, health, education, training, asset transfers and other livelihood activities. The amount of the grant varied from village to village depending on the total number of households and percentage of households that were organized in that village. On average, villages received a grant totaling 2,897,883 Pakistan rupees (PKR), or 10,482 PKR per household in the village. The VSO was also charged with the management of the grant and the active involvement of community members in monitoring and promoting transparency.

The MORE intervention was successful at encouraging broad participation from the community. On average, 59% of households in treatment villages were organized. Women were well-represented in the community mobilization activities, comprising 51% of CO members and 41% of VSO members per village, on average.

The timing of the intervention and data collection allows us to isolate the impact of community mobilization from the direct impacts of the village-level grants. In each treatment and control village, households were surveyed at baseline, after the 8
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29.

29. Though favorable, the international environment continues to present risks.Z/ These are partly financial: they are related to th¢ continued international imbalances between major countries, but also to domestic developments like the increase in debt-equity ratios. Another sort of risk is that failure to resolve trade issues may endanger the multilateral trading system. Either of these developments would create major shocks in the highincome countries, further set back efforts to reverse the decline of sub-Saharan Africa and Latin America, and have adverse consequences even for the NIEs. But these are not random risks: policies can avert them.

# H. Conclusion

30. The economies of the less developed countries seem to be following divergent paths. On the one side, are the dynamic newly industrializing countries, together with some countries at lo-wer levels of development largely in Asia, and on the other extreme are the retrogressing economies typically in sub-Saharan Africa. In between are the stagnating economies of the highlyindebted countries. The divergent patterns are closely linked to appropriate domestic policy regimes to ensure adequate investment levels, stability of incentives, and the ability to take advantage of buoyant OECD market opportunities. Highly-indebted countries have generally not been able to achieve the critical investment level for a number of reasons: (a) the need to generate an export surplus to service the debt, together with a lack of credibility by 2/ These are elaborated on further in the recent World Bank Short-Term Outlook (1989).
counterparts in accidents. The smaller impact of antena,tal coverage among the poor probably reflects a failure of poorer households to take full advantage of such programs and to comply less with the instructions of the staff delivering them. The pace of mortality decline among Vietnam's poor can be accelerated by coupling targeted programs (changing the x's for the poor) with measures such as behavioral change and communication (BCC) programs aimed at raising the impacts of these determinants (raising the /3's of the poor).

The potential impact of BCC and similar measures can be appreciated by considering what would happen if, in addition to implementing the three measures in Table 12, a program succeeded in equalizing the impacts of the x's across the poor and nonpoor, by replacing the /s of the poor with those of the nonpoor. Under this scenario, the U5MR for the poorest 25 percent of the population would fall not to 42.6%o as in Table 12, but to 36.1%o-a reduction of 28 percent below the 1998 rate. This suggests strongly that a strategy for accelerating the mortality decline among Vietnam's poor ought to focus not just on improving their coverage of health services and access to drinking water to this group, but also on enhancing the impacts among the poor of these key determinants of child survival.

# **Appendix.**

## **Computation of indirect estimates of infant and under-five mortality rates**

The indirect estimates pertaining to the 1989 Census, the 1994 ICDS and the 1997 DHS were computed by the authors using the computer program Q5 (United Nations 1983) using the data on children born and children surviving reported in Table 3.5 (p.32) of the 1997 DHS report (Government of Vietnam 1999). (The mortality estimates reported in the DHS report are computed using the direct method.) The "North" family of life tables was used throughout, as in Hill and others (1 999). The IMR and U5MR reported in Figure 3 (p. 46) of the MICs report (Government of Vietnam 2000) are used here. (Identical results are obtained if one passes through the computer program Q5 the data on children born and children surviving reported in Table 2.2 (p.92) of the MICS report.) The VLSS estimates are obtained using the sarme methods. One issue that arises in the context of both VLSSs is that of weighting. There are two issues. First, in both surveys fertility histories were obtained from only one woman of fertile age per household. If women in households with more than fertile woman are alike in their fertility histories to fertile women in the population at large, this will not create a problem. Desai (1998) has shown, however, that this is not the case. There are 31
- Jensen, Jesper and David G. Tarr (2012), “Deep Trade Policy Options for Armenia: The Importance of Trade Facilitation, Services and Standards Liberalization,” _Economics: The Open Access-Open Assessment E-Journal_ , Vol. 6, 2012-1. http://dx.doi.org/10.5018/economics-ejournal.ja.2012-1.

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- Kang, Joog-Soon (2000), “Price Impact of Restrictiveness on Maritime Transportation Services,” in _Impediments to Trade in Services: Measurement and Policy Implications_ , Christopher Findlay and Tony Warren (eds), London: Routledge.

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- Kee, Hiau Looi, Alessandro Nicita and Marcelo Olarreaga. (2008), "Import Demand Elasticities and <u>Trade Distortions",</u> _Review of Economics and Statistics_ , 90 (4), 666—682.

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- Kimura, Fukunari, Mitsuyo Ando and Takamune Fujii (2004a), “Estimating the Ad Valorem Equivalent of Barriers to Foreign Direct Investment in the Telecommunications Services Sectors in Tanzania .” Available at http://www.worldbank.org/trade/russia-wto.

- Konan, Denise Eby and Keith E. Maskus (2006), “Quantifying the impact of services liberalization in a developing country,” _Journal of Development Economics_ , Vol. 81, 142-162.

- Levy, Santiago and Sweder van Wijnbergen (1995), "Transition Problems in Economic Reform: Agriculture in the North American Free Trade Agreement," _American Economic Review_ , Vol. 85(4), September, 738-54.

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Marshall, J.N. (1988), _Services and Uneven Development_ , London: Oxford University Press.

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35
Policy Research Working Paper 5780

# **Abstract**

Using a cross-section of more than 40,000 manufacturing and services firms in 79 developing countries from the World Bank’s Enterprise Surveys Database, this paper assesses how firm location determines the likelihood and extent of exporting in developing countries. Descriptive statistics confirm higher export participation (but not intensity) for firms in core versus non-core regions, despite the finding that firms in the core assess many aspects of the investment climate more negatively.

Results from a probit model show that, in addition to firm-specific characteristics, both regional investment climate and agglomeration factors have a significant impact on export participation. Specifically, customs clearance and electricity quality matter for export participation for manufacturing firms. Although localization economies and export spillovers are associated with increased exporting, the opposite is found for urbanization economies for both manufacturing and services firms. The analysis finds that firm-level determinants of exporting matter more for firms located in non-core regions, while regional determinants and agglomeration economies play a larger role in core regions.

The findings point to the presence of congestion costs in the core, and suggest that policy interventions to target export participation are likely to have a greater impact if they are focused on core regions over non-core regions, where firm-specific factors predominate. Moreover, the importance of export spillovers and localization economies highlights the potential value of efforts to remove barriers to natural agglomeration both in core and non-core regions, for example through investments in infrastructure, the provision of social services, and regional integration arrangements.

This paper is a product of the International Trade Department, Poverty Reduction and Economic Management Network. 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 authors may be contacted at tfarole@worldbank.org and dwinkler2@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
appendix). Attendance is formally free of charge from first grade up to high school completion,<sup>7</sup> and below tertiary education there are few private schools.

There is a steep socioeconomic gradient in educational achievement <u>(Walker 2011), which</u> some worry might increase due to migration, not least due to widespread informal (and often illegal) payments to schoolteachers and other officials. The institutional causes of these are twofold: teachers’ wages are low and often delayed, and, socially, there is public tolerance of corruption and insufficient critical input of mass media. According to the 2013 Global Corruption Barometer, 37% of households in Moldova that came into contact with education authorities paid bribes in the 12 months before the survey and 58% of respondents perceived the education system to be corrupt or highly corrupt (Transparency International <u>2013). Similarly, in</u> the 2011 Citizen Report Card study, corruption is cited to be the most common difficulty when requiring services from public educational institutions, and paying bribes is the second most common way of solving problems after insistence, joint with using personal contacts. Another form of corruption in the education system is the acquisition of unnecessary tutoring from a child’s teacher <u>(Carasciuc 2001). This means that tutoring is often in a gray area between a</u> productive investment in students’ cognitive achievement and paying teachers informally. Besides seeking individual gains for one’s own child, there is an important social component to making illicit payments to teachers resulting from the interaction of parents, teachers, and school principals (ESP/NEPC <u>2010).</u><sup>8</sup> The less frowned upon kind of these payments are monetary transfers or in-kind “gifts” that are often collected by informal parental committees. Typically, they either supplement teachers’ wages or finance maintenance spending in schools. These expenditures face some of the organizational issues of public goods, including committees dissolving and payments stopping once the number of parents who are willing to contribute declines. There are only relatively blunt mechanisms to enforce payment (e.g., parents being excluded from the committee and teachers ignoring children in class). While payments can be seen as necessary to motivate teachers, there are widespread detrimental consequences such as especially motivated teachers providing

> 7. Moldova has compulsory schooling until the end of lower secondary schooling (roughly age 15).

> 8. ESP/NEPC <u>(2010) describes results from in-depth interviews on informal payments in seven ex-communist</u> countries. In that study, a majority of Moldovan parents report being pressured by both teachers and other parents to comply with informal payments.

6