rafmacalaba/datause-encoder-data huggingface dataset:
|IV<br>_Two girls_|(6)|0.038<br>(0.032)<br>167.24<br>3.536<br>(3.278)<br>67.53<br>0.072<br>(0.049)<br>133.3|0.071**<br>(0.028)<br>109.8<br>Yes<br>Yes<br>Yes<br>_red, Age at First birth_<br>cludes women aged 20<br>ith 2 or more children<br>** Indicates statistical<br>ge estimation.|
|---|---|---|---|
|**d Family**<br>IV<br>_Same-sex_|(5)|-0.001<br>(0.044)<br>92.89<br>3.620<br>(3.294)<br>66.87<br>-0.005<br>(0.071)<br>71.78|0.027<br>(0.038)<br>63.27<br>Yes<br>Yes<br>Yes<br>_ge, Age Squa_<br>f mothers in<br>ied women w<br>nce at 10%. <br> the frst-sta|
|**n-Extende**<br>OLS<br>—|(4)|-0.025***<br>(0.006)<br>-0.043<br>(0.462)<br>-0.027***<br>(0.009)|0.008<br>(0.005)<br>Yes<br>Yes<br>Yes<br>ovariates: _A_<br>The sample o<br>s of the marr<br>ical signifca<br>orresponds to|
|**No**|Obs.|4600<br>3133<br>3493|2923<br>llowing c<br>_oy 2nd_. <br> husband<br>es statist<br>uments c|
||Mean|0.165<br>16.31<br>0.414|0.057<br>clude the fo<br>_y 1st_ and _B_<br>includes the<br>s. * Indicat<br>luded instr|
|IV<br>_Two girls_|(3)|_: Mothers_<br>0.077*<br>(0.046)<br>104.76<br>6.982*<br>(3.564)<br>57.64<br>_: Fathers_<br>0.061<br>(0.071)<br>77.33|-0.012<br>(0.040)<br>57.09<br>Yes<br>Yes<br>Yes<br> the models in<br>icators for _Bo_<br>ple of fathers <br>ict fxed efect<br>istic of the exc|
|**Family**<br>IV<br>_Same-sex_|(2)|_Panel A_<br>0.020<br>(0.060)<br>71.02<br>7.532*<br>(4.303)<br>49.54<br>_Panel B_<br>0.107<br>(0.091)<br>61.30|0.044<br>(0.048)<br>50.66<br>Yes<br>Yes<br>Yes<br>ntheses. All <br>o include ind<br>old. The sam<br>ey and distr<br>. The F-Stat|
|**Extended **<br>OLS<br>—|(1)|-0.037***<br>(0.008)<br>-0.663<br>(0.715)<br>-0.013<br>(0.015)|0.009<br>(0.007)<br>Yes<br>Yes<br>Yes<br>l are in pare<br>) and (3) als<br>an 18 years <br>ted with surv<br>cance at 1%|
||Obs.|2804<br>1729<br>1967|1607<br>PSU leve<br>lumns (2<br>unger th<br>s estima<br>al signif|
||Mean|0.162<br>17.37<br>0.359|0.060<br>d at the <br>dels in co<br>hildren yo<br> model i<br>s statistic|
|t for Fertility:|t variable|**_of-farm_**<br>_F-stat FS_<br>**_r week_**<br>_F-stat FS_<br>**_of-farm_**<br>_F-stat FS_|**_ccupation_**<br>_F-stat FS_<br>xed-Efects<br>xed-Efects<br> errors clustere<br>_ucation_. IV Mo<br>with 2 or more c<br> years old. Each<br>%. *** Indicate|
|Method<br>Instrumen|Dependen|**_Worked _**<br>**_Hours pe_**<br>**_Worked _**|**_Second o_**<br>Survey Fi<br>District Fi<br>Controls<br>_Notes:_ Standard<br>and _Years of Ed_<br>to 49 years old <br>younger than 18<br>signifcance at 5|

45
Indonesia) with atomistic suppliers and imperfectly-competitive domestic traders adjust to policy changes, in this case the resuscitation of Madagascar’s marketing board and export tax. Comparing the two outcomes (actual and simulated) plausibly establish that farmgate prices got a substantial boost from the elimination of the export monopoly and tax. Once re-injected into estimates of the distribution of income, however, the induced producer-price changes failed to generate large effects. The reason, in our view, is simply that cash income is small in the overall consumption of rural households, so price changes can only have small effects unless implausibly large quantity reactions are assumed.

Section 2 describes and analyzes the evolution of the vanilla market in light of Madagascar’s policies. We start by describing the market failures and externalities that justify intervention (section 2.1) then recall the different phases in Madagascar’s policies (section 2.2). Section 3 turns to an assessment of the reforms’ effects. Section 3.1 analyzes evidence from Madagascar’s four household surveys, while Section 3.2 presents the results from the simulation analysis. Section 4 concludes.

# **2. Madagascar’s vanilla market**

Smuggled out of Mexico by Cortes in 1520, vanilla was introduced to the Réunion, then called Ile Bourbon, around 1793, but without the complementary bee that carried out the pollination. Vanilla production had to wait for the discovery of hand pollination in 1836. From then on, its cultivation for export to the Metropole was encouraged by colonial authorities, although for technical reasons, unlike other tropical crops its production could never be carried out in large plantations.

Low in bulkiness, vanilla has a high unit value and is highly differentiated across origins. Madagascar’s vanilla is considered high-quality because of its high vanillin content (1.5% to 2%), and substitutability is low between beans of different origins (“Bourbon”, which denotes beans from Madagascar, Comoros and Réunion, vs. the Mexican, Java, and Bali’s “Bourbon-like” quality). Vanilla is the only spice that benefits from a “Standard of Identity” helping to shield it from competition by substitutes. Synthetic vanilla, which is cheaper than the natural one, accounts for the bulk of the overall vanilla market (about 20’000 tons per year, of which natural accounts for 10-15%). Tonnages on the natural vanilla 5
**Figure 1: Informal Jobs in South Asia**

<!-- Start of picture text --> 4.8<br>4.6<br>India<br>4.4<br>4.2 Pakistan Morocco<br>South Africa<br>Brazil<br>4 Lebanon<br>Yemen Mexico<br>3.8 Egypt Iran<br>Algeria<br>3.6<br>Tunisia<br>Turkey<br>3.4 Syria<br>3.2<br>3<br>6 6.5 7 7.5 8 8.5 9 9.5 10<br>ln(GDP per capita), 2008<br>ln(informal share of non-agricultural employment)<br><!-- End of picture text --> Source: OECD, 2009. World Development Indicators, 2010.

Note: 48 countries with available data shown. Chart uses latest data on informal share of employment available (1995-99 or 2000-07). GDP per capita is in 2005 constant PPP international $.

**Figure 2: Informal sectors and poverty rates**

<!-- Start of picture text --> 100<br>90<br>India<br>80<br>70<br>Morocco Pakistan<br>60<br>Brazil<br>Mexico<br>50 Yemen South Africa<br>Iran<br>Egypt<br>40<br>Tunisia<br>Turkey<br>30<br>0 10 20 30 40 50 60 70 80<br>Share of population below poverty ($1.25/day, PPP)<br>informal share of non-agricultural employment<br><!-- End of picture text --> Source: OECD, 2009. World Development Indicators, 2010.

Note: 45 countries with available data shown. Chart uses latest available data on informal share of employment (1995-99 or 2000-07).

23
gaps.<sup>29</sup> In Subsection D, we present the robustness checks. We use the robustness exercises to test for factors that can lead to heterogeneity in the simulation results: the sample period, the thresholds that define the country typologies, and alternative measures for mean income growth rates.

# **_A. Poverty Headcount_**

Our results show that the poverty headcount projections vary substantially depending on the selection of the base period of the simulations (Figure 2).<sup>30,31</sup> These predicted median estimates of global poverty headcount for 2030 are 8.8, 8.0, 6.1, and 6.6 percent; these are the simulation outcomes based on country-samples for the periods 1980–2014, 1990–2014, 2000–2014, and 2005–2014, respectively. Our global poverty estimates show that a substantial decline in global poverty is very likely by 2030, both in relative and absolute terms (Figure 2 and Figure 3). When comparing the simulated median values, global poverty headcount is predicted to decline between 3 and 5 percent  or, in other words, between 80 million and 300 million people  in the 2015– 2030 period. These median estimates, however, are insufficient to reach the global target of 3 percent for extreme poverty headcount by 2030. Our empirical distribution of simulated outcomes suggests that the global 3 percent poverty target is reachable in 2030 with a probability of less than 2 percent (see Figure A 1, Panel A, Appendix A).

While the reduction in world poverty in the last 35 years is a significant achievement, its continued eradication in the following decades is expected to remain a substantial concern. If we consider the recent historical observations of income growth, inequality dynamics, and commodity prices to be useful information to predict the future performance of the income distribution, then our expectations for reducing poverty below the 3 percent threshold by 2030 should be very optimistic. To accelerate growth across the income distribution, we can explore alternative

> 29 The outcomes reported in Subsections A, B and C are based on per capita consumption growth rates, which were used to complement the country observations for household survey mean income or expenditures present in PovcalNet. 30 The poverty estimates use the $1.90 international poverty threshold in purchasing power parity (PPP) 2011 international U.S. dollars per day.

> 31 The detailed list of countries used in the simulations is provided in Table B 1 in Appendix B.

Page **19** of **45**
reflects the fact that the _SMCTRY_ coefficients embody all information about internal trade in gravity estimations when total output is known.

The idea in subsequent specifications (columns 2 and 3) is then to replace the _SMCTRY_ coefficient—as if it were unobservable—with observable country characteristics and gauge the explanatory power thereof. Equation (18) defines the empirical specification for decomposing the international border effect _β_<sup>ˆ</sup> _it,_<sup>_k_</sup> 6<sup>:</sup> Guided by the structural interpretation of _SMCTRY_ estimates from equation (16), we partition covariates into three groups. First, we chose the variables in vector _Wi_ under the assumption that they primarily affect internal trade costs _tii,t_ . These variables include internal distance, the domestic distribution/concentration of economic activity, an institutional index from the Worldwide Governance Indicators (WGI) as it relates to ‘policies and regulations that permit and promote private sector development’ (Kaufmann _et al._ , 2010), and—at the cost of losing some observations—the OECD’s Product Market Regulation (PMR) index (Koske _et al._ , 2014). Guided by specification (17) we define ( _γ_ 1 _−_ 1) and ( _γ_ 2 _−_ 1) as size elasticities giving the effect on relative cross-border trade costs of variation in _ηi,t_<sup>_k_and</sup> _θi,t_<sup>_k_respectively.Thestructuralinterpretationofthesefixedeffectsisofeffectivedemand</sup> size _E_<sup>_k_andeffectivesupplysize</sup><sup>_Yk_respectively.Noticethatthesizeis</sup> _i,t_<sup>(</sup><sup>_P k_</sup> _i,t_<sup>)</sup><sup>_σk−_1</sup> _i,t_<sup>(Π</sup><sup>_k_</sup> _i,t_<sup>)</sup><sup>_σk−_1</sup> defined at the sector level for each country _i_ , anticipating heterogeneity across sectors for given countries.

The variables in the second group ( _Zi,t_ ) are chosen based on the assumption that they predominantly affect the size of the border barrier _bi,t_ . The vector of variables includes economic size (current GDP in PPP terms and population), the ‘Rule of Law’ index taken from the Worldwide Governance Indicators, the number of procedures it takes to enforce contracts (from the World Development Indicators), and measures of digital infrastructure 26
## Introduction

The presence and persistence of substantial wage differentials between industries has been documented in a series of studies (see, for example, Krueger and Summers 1988; Gera and Grenier 1994). Interindustry wage differentials can result from: a) the normal functioning of competitive labor ruiarkets (compensating wage differentials or differences in human capital accumulation); b) institutional influences, mainly as a result of the presence (or absence) of a union; and c) efficiency wages paid in sorrme industries; that is, employers finding that they can increase profits by paying workers wages that are above market rate.

In section 2, I briefly discuss the above listed alternative explanations and the possibility of testing these explanations using a Guatemalan microdata set, the 1989 _Encuesta Nacional Socio-Demografica_ (ENS 1989). In section 3, Lucas's (1988) hypothesis of the extemal effects of human capital is tested using a two stage approach: in the first stage, wage functions for individuals are estimated to isolate internal effects of education, while in the second stage industry wage premiums are regressed on industry-specific characteristics and average human capital in each industry in order to isolate any external effects.

# Alternative explanations

If interindustry wage differentials are a result of a different mix of skills or job characteristics, then we would expect them to be smaller when a subgroup of workers that is homogeneous in terms of tasks performed is used than when one uses all workers. An obvious way to test the above is to separate the sample into white-collar and blue-collar workers.
# **Table A7: Bertelsmann Transformation Index (BTI)**

**Data Provider Description**

**Website Data Source Type Respondents Frequency Coverage Public Access Description**

Bertelsmann Foundation Nongovernmental organization headquartered in Berlin, Germany, with goal to study social challenges and problems and propose solutions. www.bertelsmann-stiftung.de Bertelsmann Transformation Index Expert Assessment Staff of Bertelsmann Foundation Every three years since 2003 Global sample of countries Yes We use data on the subcomponents of the Status Index (SI -- rating countries along dimensions of democracy and market economy status) and the Management Index (MI -- rating countries according to progress in achieving democracy and market economy status). Note that the MI rating captures information up to two years earlier. For instance, the BTI 2008 MI looked at events from 2005 to 2007. We have mapped them however only to 2007. Note also that the corruption variable was drawn from one of the sub-components of resource efficiency.

|**Voice and Accountability**|2007|2006|2005|2004|2003|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|---|---|
|Political Participation (SI)|X|X|X|X|X|X|..|..|..|
|Stability of Democratic Institutions (SI)|X|X|X|X|X|X|..|..|..|
|Political and Social Integration (SI)|X|X|X|X|X|X|..|..|..|
|**Political Stability and Absence of Violence**||||||||||
|NA|..|..|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||||
|Consensus Building (MI)|X|X|X|X|X|X|..|..|..|
|Governance Capability (MI)|X|X|X|X|X|X|..|..|..|
|Resource Efficiency (MI)|X|X|X|X|X|X|..|..|..|
|**Regulatory Quality**||||||||||
|Competition (SI)|X|X|X|X|X|X|..|..|..|
|**Rule of Law**||||||||||
|Rule of Law (SI)|X|X|X|X|X|X|..|..|..|
|**Control of Corruption**||||||||||
|Anti-Corruption policy|X|X|X|X|..|..|..|..|..|
|**Country Coverage**|**125**|**119**|**119**|**119**|**116**|**116**|**..**|**..**|**..**|
|**Year of Publication**|**2007**|**2005**|**2005**|**2005**|**2002**|**2002**|**..**|**..**|**..**|

45
Table XV: Reduced Form Effects of Past Political Institutions on Family Management

|Dependent: FM|(1)|(2)|
|---|---|---|
|ln_L_|-0.103<sup>_∗∗∗_</sup><br>(0.0044)|-0.100<sup>_∗∗∗_</sup><br>(0.0029)|
|Institutions|-0.013<sup>_∗_</sup><br>(0.0069)|-0.036<sup>_∗∗∗_</sup><br>(0.0091)|
|Institutions_×_ln_L_||0.007<sup>_∗∗∗_</sup><br>(0.0015)|
|Baseline Controls|X|X|
|Historical Controls|X|X|
|No. Clusters|39|39|
|_R_<sup>2</sup>|0.14|0.14|
|_N_|86844|86844|

Notes: Institutions is the Tabellini (2010) measure of political institutions between 1600 and 1850. All specifications include historical controls (urbanization rate in 1850, school enrollment in 1960) from that paper, as well as the baseline controls used in other specifications (log firm age, regional log gdp per capita, share of population that is college educated, as well as 3 digit SIC and country fixed effects). Standard errors are clustered at the regions reported in Tabellini (2010).

41
1975<sup>7</sup> (secondary schools were closed under the Khmer Rouge), their schooling levels can be considered as a good indicator of the social and educational status of their family (only a minority of Cambodian girls went to secondary schools in the 1960s and early 1970s).

Table 2 implements this strategy in order to look at the mortality differentials between 1975 and 1979 by socio-economic status. The comparison between the two first columns indicates that members of a family that lived in an urban area before 1975 were more likely to die, and that this difference exists for both genders. The two last columns establish that individuals who had a sister who attended secondary school prior to 1975 were more likely to experience excess mortality. This difference is however much larger, and only statistically significant, for males.<sup>8</sup> In the lower right corner, the table establishes that the difference by educational status of the sister is much larger and only significant among families of urban origin. Figures 4 and 5 further examine these differentials by birth cohort. Figure 4 establishes that, although the differential is higher for adults, the excess mortality among families of urban origin is present for all birth cohorts. This might be due to the fact that, as part of the Khmer Rouge “Year Zero” experiment, all major cities were evacuated by force and the urban population was relocated in the countryside. On the other hand, figure 5 shows that the differential by educational achievement of the sister prior to 1975 is concentrated among adults<sup>9</sup> , suggesting that educated adults have been especially targeted. Generally, in most developing countries, in the absence of violence targeted at them, it is expected that the urban and the educated experience a lower mortality.

# **_II.4 Infant and under-five mortality_**

In Table 1, constructed from sibling’s mortality data, the last row of each column shows the probability to die within the next five year period for individuals not yet born at the beginning, but who will be born during this five year interval. This can already give a raw measure of the magnitude of infant and child mortality. However, this estimate is not very reliable as, contrary to the estimates in the cells for older individuals, these children are not necessarily at risk from the beginning of the five year period. A better statistic would be the probability that each newborn survives his first year (infant mortality) and his first five years (under-five mortality). This measure can be calculated from the birth histories in the Cambodia Demographic and Health Survey, which records

> 7 According to the breakdown in birth cohorts made in this paper, this means women born before 1960.

> 8 Notice that the sample sizes are smaller in the last two columns because they only consider siblings of women born before 1960, while the two first columns consider siblings of women born before 1975. 9 The differences are only significant for the birth cohorts aged 30-34, 20-24 and 15-19 in 1975.

7
|P074586|2002|2019|5/9/2019|2 Closed|Serbia|
|---|---|---|---|---|---|
|P074591|2004|2004|6/18/2004|1 Closed|Mongolia|
|P074591|2004|2005|6/14/2005|3 Closed|Mongolia|
|P074591|2004|2006|1/24/2006|4 Closed|Mongolia|
|P074591|2004|2007|9/22/2006|5 Closed|Mongolia|
|P074591|2004|2008|9/11/2007|6 Closed|Mongolia|
|P074591|2004|2008|6/3/2008|7 Closed|Mongolia|
|P074591|2004|2009|3/26/2009|8 Closed|Mongolia|
|P074591|2004|2010|6/21/2010|9 Closed|Mongolia|
|P074591|2004|2011|6/27/2011|10 Closed|Mongolia|
|P074591|2004|2012|3/13/2012|11 Closed|Mongolia|
|P074594|2007|2007|6/5/2007|1 Closed|West Bank and Gaza|
|P074594|2007|2008|5/21/2008|2 Closed|West Bank and Gaza|
|P074594|2007|2009|12/22/2008|3 Closed|West Bank and Gaza|
|P074594|2007|2009|6/29/2009|4 Closed|West Bank and Gaza|
|P074594|2007|2010|12/25/2009|5 Closed|West Bank and Gaza|
|P074594|2007|2010|6/28/2010|6 Closed|West Bank and Gaza|
|P074594|2007|2011|6/10/2011|7 Closed|West Bank and Gaza|
|P074594|2007|2020|11/7/2019|8 Closed|West Bank and Gaza|
|P074595|2005|2005|3/31/2005|2 Closed|West Bank and Gaza|
|P074595|2005|2006|12/8/2005|3 Closed|West Bank and Gaza|
|P074595|2005|2006|6/27/2006|4 Closed|West Bank and Gaza|
|P074595|2005|2007|12/21/2006<br>|5 Closed|West Bank and Gaza|
|P074595|2005|2007|3/30/2007|6 Closed|West Bank and Gaza|
|P074595|2005|2007|6/25/2007|7 Closed|West Bank and Gaza|
|P074595|2005|2008|9/18/2007|8 Closed|West Bank and Gaza|
|P074595|2005|2008|11/12/2007|9 Closed|West Bank and Gaza|
|P074595|2005|2008|1/23/2008|10 Closed|West Bank and Gaza|
|P074595|2005|2009|12/19/2008|11 Closed|West Bank and Gaza|
|P074595|2005|2009|6/15/2009|12 Closed|West Bank and Gaza|
|P074595|2005|2010|9/18/2009|13 Closed|West Bank and Gaza|
|P074595|2005|2010|5/7/2010|14 Closed|West Bank and Gaza|
|P074595|2005|2011|1/29/2011|15 Closed|West Bank and Gaza|
|P074595|2005|2012|7/27/2011|16 Closed|West Bank and Gaza|
|P074595|2005|2012|1/15/2012|17 Closed|West Bank and Gaza|
|P074595|2005|2013|7/21/2012|18 Closed|West Bank and Gaza|
|P074595|2005|2013|3/27/2013|19 Closed|West Bank and Gaza|
|P074595|2005|2014|12/9/2013|20 Closed|West Bank and Gaza|
|P074595|2005|2014|6/9/2014|21 Closed|West Bank and Gaza|
|P074595|2005|2015|11/21/2014|22 Closed|West Bank and Gaza|
|P074595|2005|2015|4/28/2015|23 Closed|West Bank and Gaza|
|P074595|2005|2015|6/22/2015|24 Closed|West Bank and Gaza|
|P074595|2005|2016|12/18/2015|25 Closed|West Bank and Gaza|
|P074595|2005|2016|5/24/2016|26 Closed|West Bank and Gaza|
|P074595|2005|2017|11/23/2016|27 Closed|West Bank and Gaza|
|P074595|2005|2017|5/31/2017|28 Closed|West Bank and Gaza|
|P074595|2005|2018|12/16/2017|29 Closed|West Bank and Gaza|
<!-- Start of picture text --> Share of products where China is top 3 supplier<br>1<br>8<br>6<br>4<br>2<br>0<br>2017 = 2022 2017 = -2022 2017 ~=—.2022<br>All Tariffed goods Tariffed and lost market share<br>5 Al «= Strategic =) Other<br><!-- End of picture text -->
22 1969); and Sch"_-eter, Ausiness Cycs1n, vol. 1, pp. 93-97.<sup>The Syndicate</sup> Bank's experience supports Schumpeter's hypothesis that innovation is generally introduced by the rise to leadership of new men, setting up a new firm and with new plant (in this case, a new organization principle).

- 27.V. V. Bhatt, Structure of Financial Institutions (Bombay: Vora & Co., 1972), chap. 2.

28. V. V. Bhatt, Division of Public and Private Finance: Rescprch Program and<sup>Its</sup> Rationale, Domestic Finance Studies 43 (Washington, o.C.: World Bank, 1977),pp. 13-15.

29. Bhatt, Strueture of Financial Institutions, chap. 4.

30. Ibid., chap. 4.

- 31.V. V. Bhatt, Some AsRects of Financial Policies and Central Banking in Developing Ccwe._.L. EDI Seminar Paper 11 (Washington, D.C.: World Bank, 1974).

32. See Hicks, Capital and Growth, pp. 289-291. To quote: The beginning of a process of expansion might occur because of real factors (inventions and the like) raising the real prospective rate of profit. But it might also occur because of financial improvements, diminishing the size of our "gap," thereby permitting access to funds, for improvements which could have been made earlier, if the necessary funds had been forthcoming. It is not savings only that are required, but a channel of communication between potential savings and potential real investment. (p. 290) See also Schumpeter, Business Cycles, vol. 1. pp. 111-112; and John Hicks, Economic Perspectives (Oxford: Oxford University Press, 1977), pp. 78-79. What Schumpeter calls innovations and Hicks calls impulses require credit creation; the latter is, as Schumpeter observes, the "monetary complement of innovation."

- 33.Bhatt, Some Aspects of Financial Policies and Central Banking in Developing Countries.

- 34.Keynes, A Treatise on Money (London: Macmillan and<sup>Co., 1930), vol. 1, p.27.</sup>