rafmacalaba/datause-encoder-data huggingface dataset:
Our instrumental variable approach follows Currie and Moretti (2003) and Carneiro and others (2007) among others. We propose to use the availability of girls’ schools in the mother’s birth village as an instrument for her education. We obtain the birth village using verbal recall in interviews with mothers, and match this with the census directory of villages and data on schooling availability. The first-stage of this instrumental variable specification shows that the presence of a girls’ school in the birth village of the mother at the time that she was of primary school-going age leads to a 11 point increase in the percentage of mothers with primary education. In years of education, the instrument adds 0.61 years of education for a mother. Given the very low levels of overall female education this effect is fairly large. Like in the previous literature using a similar instrument, the correlation remains after controlling for a full set of mother’s age indicators and county ( _teshils_ in Pakistan) of birth fixed-effects.<sup>3</sup> A prominent characteristic of the Pakistani educational environment leads us to believe that this instrument effectively captures the marginal effects of maternal education. Specifically, public schools in Pakistan are gender segregated, and at the time that the mothers in our sample were of school age, the only viable schooling options were public schools for girls. In previous applications of similar instruments in other countries, access to education affects the educational attainment of _both_ girls and boys; discerning which of these channels affected the outcome in question is then critical. In our case, the presence of a girls’ school affects the educational attainment of girls (the mothers in our sample) thus varying only female education levels. We believe that this could somewhat attenuate the possibility that our results are driven by simultaneous improvements in the education levels of fathers, which would be the case if schooling availability was not gender specific. To our knowledge, this is the first application of schooling availability at the birth village level in a _gender-segregated_ schooling setting as an instrument for parental education in a lowincome country context.

Encouragingly, the instrument also passes the falsification tests of the type discussed in Currie and Morretti (2003). Specifically, the presence of a girls’ school in the birth village does not affect the mother’s education if it was built after she had passed primary school going age. In our specifications, the effect of

> 3 A _tehsil_ in Pakistan is roughly the administrative equivalent to a county in the US.

4
**Table 9 Breakdown of Education Programs by Area**

|_Area_|_Number of programs_|
|---|---|
|Social sciences|2,953|
|Education|744|
|Humanities, arts|648|
|Services|455|
|Agriculture, forestry|383|
|Computer sciences|358|
|Health care|269|
|Engineering, industrial vocations|194|
|Otherprograms|40|

_Source:_ European Trend Chart on Innovation, 2001

- Government R&D spending is small, both as a percent of GDP (0.48%), in absolute terms, and relative to other NMS’s.  For example, such countries as Finland and Denmark with twice the population generate 100 times as much R&D spending as Latvia.

**Figure 29 Gross domestic expenditure on R&D (GERD) as % of GDP, 2001**

<!-- Start of picture text --> Romania<br>Latvia<br>Bulgaria<br>Lithuania<br>Estonia<br>Slovakia<br>Poland<br>Turkey<br>Hungary<br>Czech Rep.<br>Slovenia<br>EU<br>Ireland<br>Finland<br>Denmark<br>US<br>0,00 0,50 1,00 1,50 2,00 2,50 3,00 3,50 4,00<br>Public R&D expenditures Business expenditures on R&D<br><!-- End of picture text --> _Sources_ : EUROSTAT, R&D statistics and Trendchart.

In 2001 Latvia invested $81million in R&D, four times as much as in 1995, but roughly equal to what Ford, General Motors, Siemens or Ericsson spend in one week and a fraction of what they spend per researcher.<sup>**37**</sup>

> 37 Another interesting comparison is with Oxford University in the UK which has 2500 researchers in science and medicine, 2000 doctoral students in various scientific disciplines and an annual research

45
- 54 -

Figure 5 Caloric Intake Distributions <!-- Start of picture text --> Cumulative percent of population<br>100<br>80 0<br>40-<br>20-<br>0<br>1 1.5 2 2.5 3 3.5 4 4.5<br>calories per person per day (thousands)<br>1984 - - 1987<br><!-- End of picture text -->
Some studies, such as Faini and de Melo 1990; Green and Villanueva (1991) and Serven and Solimano (1991), have shown that the debt burden has an adverse effect on investment.

ii) **_The Market-based Menu Approach._** The realization that the diversity of external creditors precluded the possibility of using a single option for reducing a debtor country's external debt obligations (with tax, accounting and regulatory factors, along with the long term business interests of banks in a particular region playing a key role). This resulted in the need to devise debt restructuring "packages" consisting of different market-based menu of options such as new money, cash buybacks, debt equity swaps, among others. Papers presented at the World Bank Symposium on "Dealing with the Debt Crisis" (See Husain, Ishrat and Ishac Diwan (1989)) tackled the viability of such an approach to dealing with the debt burdens of the severely-indebted middle income countries and examined country case studies (e.g., Brazil) that had adopted this approach in their agreement with commercial bank creditors. A seminal paper by Bulow and Rogoff (1988) distinguished between the "average price" and "marginal price" of a debt buyback operation to evaluate the benefits of a debt reduction operation to the debtor.

iii) **_The secondary market price_** _of developing_ **_country debt._** With increasing importance in debt renegotiations between a debtor country and its commercial banks, this led to an urgent preoccupation in the profession to devise models which forecast the secondary market price of a country's debt. The secondary market price (SMP) of a country's debt is crucial in the context of debt reduction. It has played a vital role in determining the price at which a buyback will occur. Although the sovereign debt paper of a country is traded at a discount on its face value, there are a variety of actions a debtor country can take to affect their future ability to make resource transfers, e.g., exchange rate adjustment, investment, budgetary policies, etc. This will in turn trickle down to the secondary market price for its debt. Krugman (1988) has stated that the secondary market discount is just another aspect of the fact that new lending is unprofitable when viewed in 12
# **Figure 15. LAC: Investment growth slowdown**

_Partly due to weak overall economic growth, investment growth slowed sharply during 201015. The investment slowdown was broad-based across various sectors and across both private and public investment. Investment growth is expected to remain low and may decline further in the short to medium term_ .

# **A. Quarterly investment growth**

# **B. Regional investment growth**

<!-- Start of picture text --> Percent, year-on-year Percent<br>20 15 1990-2008 avg 2003-08 avg<br>LAC Central America EMDE<br>15<br>10<br>10<br>5<br>5<br>0<br>0<br>-5<br>-5<br>-10 -10<br>SA MCC LAC EMDE<br>C. Share of countries with investment D. Share of countries with contracting<br>growth below its long-term average investment<br>Percent Percent<br>75 75<br>50 50<br>25 25<br>0 0<br>2010 2011 2012 2013 2014 2015 2010 2011 2012 2013 2014 2015<br>E. Investment growth by sectors F. Composition of investment growth<br>Percent Percent 2003-08 2010-15<br>25 2003-08 2010-15 20<br>20<br>15<br>15<br>10 10<br>5<br>5<br>0<br>0<br>-5<br>El Honduras Mexico Nicaragua Peru Uruguay<br>Chile Colombia Mexico Salvador<br>Sources: Haver Analytics, International Monetary Fund, Oxford Economics, World Bank.<br>2010Q1 2010Q3 2011Q1 2011Q3 2012Q1 2012Q3 2013Q1 2013Q3 2014Q1 2014Q3 2015Q1 2015Q3 2016Q1 2016Q3 2011 2013 2015 2011 2013 2015 2011 2013 2015 2011 2013 2015<br>Machinery Overall Machinery Overall Machinery Overall<br>Construction Construction Construction Private Public Private Public Private Public Private Public Private Public Private Public<br><!-- End of picture text --> <!-- Start of picture text --> D. Share of countries with contracting<br>investment<br>Percent<br>75<br><!-- End of picture text --> A. GDP-weighted averages. Includes quarterly data for Bolivia, Brazil, Chile, Colombia, Costa Rica, Guatemala, Mexico, Nicaragua, Paraguay, Peru, and Uruguay. Central America includes Costa Rica, Guatemala, Mexico, and Nicaragua.

- B. Averages weighted by investment levels. “SA” stands for South America. “MCC” stands for Mexico, Central America, and the Caribbean.

E. For Chile, 2003-08 data begins in 2004.

- F. Figure shows growth rates of gross fixed capital formation in constant 2010 U.S. dollars.

29
the impacts that might otherwise have been expected. But it is also possible that aid programs have taken this into account, and are designed to overcome this contradiction; or that federal institutions somehow resolve it internally. Alternatively, the theory could simply be wrong. These are intriguing empirical questions with important implications for institutional theory and development policy, about which much evidence is available from a broad range of countries, but which as far as we know are unexplored in the academic literature.

This paper asks: Can an aid-funded program succeed in reducing inequality in a federation? This is an empirically subtle question with powerful implications not just for inequality, but for development more broadly. We seek to answer it with evidence from Ethiopia’s Promotion of Basic Services (PBS) program. Jointly financed by the Ethiopian government (50%), and donors (50%) such as the World Bank, the UK Department for International Development, and others, PBS finances basic services in education, health, agriculture, water supply and rural roads. As primary responsibility for such services lies with the country’s regional, city and _woreda_ (district) governments, PBS funds are channeled through Ethiopia’s intergovernmental fiscal transfer mechanism to subnational governments, where they are invested. Its main effect is to pump about $1 billion per year, mostly through woredas, into social investment in Ethiopia, making it the largest donor-supported program in the world.

In addition to hosting PBS, Ethiopia is a particularly good empirical context in which to study issues of accountability and inequality for three reasons: (1) The country’s size and recent development experience give it a natural prominence; (2) Its geographic and socio-cultural diversity are among the highest in the world, providing natural sources of variation that a study such as this can exploit analytically; and (3) Its recent political history features dramatic changes in institutional structure and accountability.

Ethiopia has achieved impressive development results in recent years. That progress includes rapid and significant improvements in basic service delivery indicators. An Overseas Development Institute study (2010) found that Ethiopia was making the third-fastest improvements of any country towards reaching the Millennium Development Goals (MDGs). The latest Ethiopia Demographic and Health Survey data show that child mortality has fallen from 123 per thousand in 2005 to 88 in 2010, and primary net enrollment rates rose from 68 percent in 2004/2005 to 82 percent in 2009/2010. Such progress on basic service delivery is coupled with an impressive growth record over the past decade. GDP grew on average 11 4
# **2.1 Quality of Life, Poverty, and Inequality**

This paper would prefer the broad view of poverty as unacceptable deprivation in human well being, including not only insufficient income and consumption, but also voicelessness, powerlessness, and the lack of basic needs such as education, health, nutrition, and security. However, data are not available for all these measures of poverty in Paraíba, so for quantitative analysis this paper accepts a much narrower definition of poverty as insufficient income. This section analyzes quality of life and the relationship between income and other household characteristics, but does not attempt a more comprehensive quantitative analysis of other forms of deprivation or social exclusion. Finally, it does not address the broader issues of inequality of assets and opportunity. This paper also sets its poverty bar very low. To define “extreme poverty” it uses the indigence, or “food only”, poverty line—those with sufficient income to buy basic food are above the line. The headcount poverty ratio (P0) is the proportion of those below the indigence line to the total population.

The Quality of Life Index ( _Índice de Qualidade de Vida-_ IQV) is a composite index containing 21 indicators of socio-economic well-being related to outcomes in sectors such as education, health, and water supply. In 1991 and 2000, the IQV index is highest in the Federal District and lowest in Alagoas (Figure 2.1). The length of the bar in Figure 2.1 indicates the advance made in a state during 1991-2000. Hence, the bottom of the bar shows the IQV in 1991 and the top the IQV in 2000.

**<u>Figure 2.1: The Quality Of Life Index, 1991-2000</u>**

<!-- Start of picture text --> 0.85<br>0.80<br>0.75<br>0.70<br>0.65<br>0.60<br>0.55<br>0.50<br>0.45<br>0.40<br>0.35<br>0.30<br>Source: IPLANCE data.<br>DF SP SC RJ RS PR MG ES RR GO MS MT AP AM PA RO TO SE RN BA AC PE CE PB PI MA AL Nordeste Brasil<br><!-- End of picture text --> Figure 2.2 reveals that during the 1990s, many of the northeastern states have improved greatly (30.1 percent). Paraíba experienced an increase of 37 percent in IQV, which is the largest increase of a single state in Brazil and nearly double that of Brazil (14.7 percent).

5
# **Climate Change, Agriculture and Food Security in Tanzania**

_Channing Arndt, William Farmer, Kenneth Strzepek and James Thurlow_<sup>_1_</sup> _Keywords_ : climate change; agriculture; food security; crop model; CGE model; Tanzania. JEL Codes: O440, Q180, Q540 _Acknowledgements_ : Thanks to Will Martin for leadership in the overall effort and valuable comments. Seminar participants in Dar Es Salaam and the World Bank also provided useful comments. All errors and omissions are the responsibility of the authors. The research on which this study is based was supported by the Trust Fund for Environmentally and Socially Sustainable Development (TFESSD).

> 1 Arndt: University of Copenhagen (channing.arndt@econ.ku.dk); Farmer: Tufts University (whfarmer@gmail.com); Strzepek: Massachusetts Institute of Technology (strzepek@mit.edu); Thurlow: United Nations University - World Institute for Development Economics Research (thurlow@wider.unu.edu).
<!-- Start of picture text --> 30% —§—S_—_as_,.- 40% | -—aas _A<br>25% ona. hd<br>20% 7% ;<br>15% ona. * U<br>: 4% See =+— - . ~ a~./<br>10% 304 rd 7<br>AS<br>5% 2% © —says4yly<br>O% 1% =2S<br>D8 | a a a<br>SrBHSIIGSAIsSsNOt HwOoOorwnwWoerSe aAwaTwMowormIRR RAR tTSBSSSS8oor oomoTrT883885888Nm Ot 8<br>BVWO- PublicPCr og VVDI- Private FCP @NSOLN? GFOF —s— Investrnent-Machinery ---#--- Investment- Vehicles<br>oonao%0 |__4 inflation andlendinginterestrates 3p4o%‘o nen| ne mk<br>70% ll 35% v7 350 mk<br>aoy50% _— I,Hil SN— 25%20% te — spa NetA 250 mk nk<br>so% 4Ay 6% Locmc<br>oy J rom Nee stm<br>fox. sy cer<br>mom9, LLLPTL LET LLLP TLL om0, Lek<br>OoaeTrwooOsnonooaeseoecsesosen- wWOorH_ nA UBO TO oO He OMDRBSHDSHOSHSSoOSSSS555 NMTwOOrOMorA aMTwo or<br>i a a a a a a a) ect et ee ee a es a a as a<br>@eeeee Consumer prices(% change pa; av) ——— Tatal investment (% GDP)<br>—— Lending interest rate (%) ~----== Exports per capita (const 1994 Mk)<br><!-- End of picture text -->
Eastern European countries, as compared to 11.9% for Western European countries. This difference reflects the recent emergence of a large number of private firms in the transition economies.

Djankov et al. (2002) have data on the procedures that are officially required for an entrepreneur to obtain all necessary permits, and to notify and file with all requisite authorities, in order to legally operate a business. These data refer to 1999. These procedures include (i) obtaining all the necessary permits and licenses, and (ii) completing all the required inscriptions, verifications and notifications to enable the company to start operation. To make the procedures and companies comparable across countries, the survey assumes that the company is a limited liability company, i.e., a corporation, and the founders complete all procedures themselves (without intermediaries). This means the entry barriers are likely to be more onerous for small firms where this is likely to be true. We report in Table 3 column 5 the direct costs of setting up a new business expressed as a percentage of per capita GNP in US dollars. We find large variations in the cost of entry, varying from a high cost of 86 percent of GNP per capita in Hungary to a low cost of 1 percent of GNP per capita in Finland and the UK.

In Table 4, we present entry rates by country and a selection of industries based on groupings of 2-digit NACE codes. The highest entry rates are in communications (telephone, wireless, etc.), computer services, and services, and the lowest entry into the manufacturing of chemicals, construction, and transportation. The industries with high entry rates are generally those related to the high-tech sector, which experienced global growth over the late 1990s. Industries with lower entry rates are those that similarly faced a global decline in the late 1990s (construction) as well as traditionally more concentrated industries (such as transportation).

As a comparison, we calculate 1-year entry rates in the United States from the Dun and Bradstreet (D&B) database of over 7 million corporations. We consider D&B statistics over 1998-99 for corporations and U.S. employment only (instead of total employees internationally), for better comparison to the Amadeus data. We refer to this variable as EntryUS. Table 4 presents 14
_Beyond Unequal Development_ and form part of the dependent population. Fourth, GDP statistics often under-report informal sector activities in which lower income groups are involved. Family-based or public-based redistribution is thus needed to reach these segments. Fifth, GDP is a commodity or "opulencebased" measure of economic welfare that does not include non-market goods (such as political freedom, the psychological value of belonging to community, etc.) and bads (environmental degradation, crime, urban congestion) that also centrally affect human well-being. Sixth, unlike traditional social policies that had a political constituency in the urban working-class, in the strong unions of the middle class (teachers, doctors) and in other interest groups, the new social policies have as beneficiaries poor and vulnerable groups with a weak voice and feeble political organization; this creates tenuous political incentives for active poverty reduction beyond that provided by economic growth and may be an important factor behind chronic poverty.

Another main piece of the new strategy of social policies is targeting. The emphasis on precisely defining the beneficiary groups is a reaction to social policies that often reached, at a high fiscal cost, the non-poor (the middle class and the rich). A basic principle of targeting is to focus social policy on the poor avoiding reaching the non-poor<sup>1 5</sup> . In this context, targeting is more effective in terms of reaching the "real" poor, and at a substantially reduced fiscal cost than untargeted, broad-based, social policy.

However targeting is not problem free either. First, targeting makes the beneficiary a passive "victim" rather than an active agent with policy responses and choices'<sup>6</sup> . Second, informational and incentives problems are serious. Delimiting the beneficiaries and their poverty features that needs to be addressed is not easy (e.g. an information problem). Reaching with the

> **15** See Cornia and Stwart (1996) on an interesting discussion of two types of "errors" in targeting, the E-error (excessive coverage, e.g. reaching the non-poor) and the F-error (failure to reach to poor).

> 16 See Sens (1996) on this.

-23-
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items in the 66<sup>th</sup> round that are dropped.<sup>9</sup> While these differences may balance out on average, and may not result in any significant change to the total consumption aggregate, they may also point to potentially deeper comparability issues with the consumption data. Moreover, even if mean values are not much affected, these changes could affect different parts of the consumption distribution differently, and could thus still have a bearing on poverty estimates.

The discussion above evokes a similar, but much larger, poverty debate that took place in India in the early 2000s. In the late 1990s, the National Sample Survey Office (NSSO) revised the questionnaire of the NSS in 1999/2000 (55<sup>th</sup> round) in an attempt to bring estimates of household consumption from the survey in line with those from national accounts. In particular, these revisions include changing the recall period for household durables and education expenses from a 30-day interval to a 365-day interval, and using both the traditional 30-day recall period as well as a new 7-day recall period for food items. The Government of India published estimates showing that the headcount poverty rate fell by 10 percentage points between 1993/1994 and 1999/2000. Independent researchers, however, noted the possibility of non-comparability of the published consumption data, and applied a variety of methods to adjust for this. A variety of estimates were produced with some suggesting a rate of decline ranging from only somewhat lower than the official estimates (Deaton and Dreze, 2002; Tarozzi, 2007) to one estimate suggesting a mere three percentage point decline in poverty during the decade of the 1990s (Sen and Himanshu, 2005; see also Kijima and Lanjouw, 2003). As is powerfully argued in the book “The Great Indian Poverty Debate” (Deaton and Kozel, 2005), concerns about comparability can greatly complicate assessments of poverty trends.

> 9 Compared with the 61th round, the share of the new items added in the 66th round is approximately 0.1 percent and equals the share of the items that are dropped from the former. This implies greater comparability between these two survey rounds.

8