rafmacalaba/datause-encoder-data huggingface dataset:
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Figure 20 confirms that rising fuel prices would be detrimental to the fight against poverty, while the decrease in remittances would not cause as high an increase in poverty, as a considerable share of remittance-receiving households are relatively well-off. In addition, given the manner in which the transfers are financed under the scenario _trnsfrpoor_ , the aggregate poverty rate and the poverty gap do not decrease by much. However, our scenario fares considerably better in terms of reducing income inequality. (Therefore the main message of the _trnsfrpoor_ scenario is clear: without sacrificing much in terms of growth, it is feasible to increase the welfare of poorer households.

# **Figure 20. External shock and transfer scenarios: Poverty and inequality in 2010 (%-age point deviation from** **_base_ )**

<!-- Start of picture text --> 3.0<br>2.5<br>2.0<br>1.5<br>1.0<br>fuelpwm<br>0.5 remitdecr<br>0.0 trnsfrpoor<br>-0.5<br>-1.0<br>-1.5<br>Headcount poverty Poverty gap (P1) Gini<br>(P0)<br><!-- End of picture text -->

## **4.4 Combination of scenarios with and without additional transfers**

The final two scenarios are combinations of changes included in the scenarios discussed above. The scenario _allgrw_ is a combination of _agrpweff_ , _indupweff_ and _transeff._ Thus, productivity is enhanced across most of the economy – the only exceptions are the public sector and part of private services -- and almost all goods (agricultural and industrial) export prices are higher than under _base_ .

Lastly, _allgrw-tr_ scenario is identical to _allgrw_ except for one addition: government transfers increase according to the specifications of the _trnsfrpoor_ scenario.

Table 14 confirms that the combination of shocks that _allgrw_ represents would bring about greater prosperity and significantly lower poverty rate than under _base_ scenario. What is more, we see that the increase in transfers under rapid growth conditions does not dent the growth rate more than under more moderate growth conditions of the preceding section. Figure 21 verifies that the GDP growth paths of the two scenarios are almost identical. What about the feasibility of the growth rates given the past development of Moldova? As the main long-run driving force of economic 32
the U.S. tariffs applied to Latin American goods by 25 percent. Using the results provided in the fi rst column of table 5, we fi nd that the joint political organization of importers and exporters decreases the U.S. tariffs applied to Latin America by 18 percent. Clearly, lobbying is a relevant force in the trade relations between the U.S. and Latin America.<sup>43</sup> Additional Robustness Results The results shown in the last section use data on agriculture and manufacturing to check whether lobbying by U.S. importers and Latin American exporters increases tariff preferences. Most of the literature, however, does not use data on agriculture. Therefore, an interesting exercise is to test whether the results discussed above are sensitive to the exclusion of data on agricultural goods. The methodology employed to obtain the results in table 7 is analogous to that used in table 1. The only difference is that in table 7 the agricultural sector is excluded.<sup>44</sup> The results presented in this table are similar to the ones discussed above. Again, the coefficients of interest have the predicted sign and are signi fi cant at the 1% level. Moreover, the structural parameters a and γ are signi fi cant at the 1% level and have similar values to the ones shown in table 1. Thus, the inclusion of agricultural goods is not essential to the results obtained in this paper.

Mitra, Thomakos and Ulubasoglu (2003) suggest that more disaggregated elasticities should have higher values, and this assertion could imply lower estimates of the parameter a. Since we are fi rst to use elasticities data organized at the HS 6-digit level, this might be behind our results. In table 8 we adopt the same methodology used in table 1, but employ data organized at the ISIC 3-digit level. The method discussed by Dickens (1990) is used to control for heteroscedasticity problems. Most of the coefficients of interest have the predicted sign and are also signi fi cant. Again, the estimates of the structural parameter are comparable, in most cases, to the ones shown in the previous section. Thus, the level of aggregation of the data and the inclusion of agricultural goods seem not to affect substantially

> 43The mean MFN tariff in the sample used to construct table 1 is 6.3 percent. In the case of table 3 it is 9.7 percent.

> 44Similar results are obtained using similar methodology to the results shown on tables 3 and 5.

30
infrastructure, institutional transparency and good governance, and domestic regulations (cf. Wilson, 2005). All of these factors can impact trade performance through the cost channel.<sup>2</sup> Estimates in the existing literature suggest that the gains from trade facilitation are large. Wilson et al. (2005) use econometric estimates from a gravity model to show that improved trade facilitation in a sample of 75 countries could increase trade by 10%, or $377bn. For the AsiaPacific region, Wilson et al. (2002) estimate that improving trade facilitation along four dimensions could increase intra-APEC trade by around 10% ($280bn). Using the GTAP computable general equilibrium (CGE) model, Hertel and Keeney (2006) find that the worldwide gains from improved trade facilitation ($110bn) are of comparable magnitude to the results of full liberalization of goods and services trade ($150bn).<sup>3</sup> Moreover, the authors’ results indicate that the benefits of trade facilitation reforms are strongly skewed towards developing countries— particularly in Asia.<sup>4</sup> It is important to note that the above studies treat trade facilitation measures as affecting only the marginal costs of trading across borders. However, there are many instances in which exporters will also have to pay a fixed cost in order to access foreign markets. Examples include making contact with shippers and freight handlers, establishing the necessary pro forma paperwork, setting up a foreign distribution network, and adapting manufactured goods to comply with foreign technical regulations. To the extent that trade facilitation measures can reduce both

> 2 Recent work has shown that both “hard” and “soft” infrastructure (i.e., institutions) matter for trade performance: see Francois and Manchin (2007).

> 3 These figures do not account for the costs involved in carrying out trade facilitation reforms. Those costs are substantial, and do not apply in the same way to trade policy reforms—which are essentially “free” in terms of direct resource requirements. However, recent work on road infrastructure by Shepherd and Wilson (2006), and Buys et al. (2006) shows that trade gains can still be quantitatively large even once costs are netted out.

> 4 A number of other CGE studies arrive at similar results using alternative assumptions as to underlying economic behavior: see e.g., Walkenhorst and Yasui (2003), Francois et al. (2005), and Decreux and Fontagné (2006).

- 3 -
# **Ghana**

<!-- Start of picture text --> Prevalence among females 15-24 (%) Spectrum estimates<br>National Antenatal Sentinel National Demographic and Incidence in Antiretroviral<br>Surveillance Surveys Health or AIDS Impact Surveys adults 15-49 (%) coverage (%)<br>1990 - - 0.22 -<br>1991 - - 0.25 -<br>1992 - - 0.29 -<br>1993 - - 0.34 -<br>1994 - - 0.36 -<br>1995 - - 0.37 -<br>1996 - - 0.37 -<br>1997 - - 0.34 -<br>1998 - - 0.31 -<br>1999 - - 0.28 -<br>2000 - - 0.25 -<br>2001 - - 0.23 -<br>2002 3.8 - 0.20 -<br>2003 3.2 1.2 0.18 -<br>2004 2.5 - 0.17 3<br>2005 1.9 - 0.15 5<br>2006 2.5 - 0.14 12<br>2007 2.6 - 0.13 15<br>2008 1.9 - 0.11 -<br>2009 2.1 - 0.10 28<br>2010 1.5 - 0.08 36<br>2011 1.7 - 0.07 47<br>2012 - - 0.05 58<br><!-- End of picture text --> <u>ANC data sources: Ghana HIV Sentinel Survey Report 2007, Ghana UNGASS Report 2008, Ghana Country AIDS</u> Progress Report 2012 <u>National DHS and AIS data source: Ghana DHS 2003</u>

|**Study reference**|**Incidence rate/100**<br>**personyears**|**Time frame of**<br>**study**|**Study/Trial**<br>**population**|**Region**|
|---|---|---|---|---|
|Petersonetal.,PLoS One2007|1.09|2004-2006|Women in microbicidetrial|Kumasi and<br>Accra|

55
# **Table 8: First stage selection equation**

||Men<br>(1)<br>Wage<br>worker<br>Heckman|(2)<br>Wage<br>worker<br>Heckman‐<br>Hotz|Women<br>(3)<br>Wage<br>worker<br>Heckman|<br>(4)<br>Wage<br>worker<br>Heckman‐<br>Hotz|
|---|---|---|---|---|
|Years of schooling 1 to 7|0.00|0.00|‐0.02|‐0.02|
||(0.019)|(0.019)|(0.020)|(0.020)|
|Years of schooling 8 to 11|0.02|0.01|**0.06*****|**0.06*****|
||(0.016)|(0.016)|**(0.021)**|**(0.022)**|
|**Years of schooling 12 to 17**|**0.08*****|**0.07*****|**0.10*****|**0.10*****|
|**Short**|**(0.019)**<br>**‐0.23****|**(0.019)**<br>**‐0.23****|**(0.033)**<br>**‐0.39*****|**(0.033)**<br>**‐0.39*****|
||**(0.091)**|**(0.091)**|**(0.113)**|**(0.113)**|
|Proxy|‐0.16*|‐0.16|‐0.12|‐0.12|
||(0.098)|(0.098)|(0.115)|(0.116)|
|Married|‐0.10|‐0.10|‐0.20|‐0.20|
||(0.138)|(0.138)|(0.125)|(0.124)|
|Number of children|‐0.06**|‐0.06**|‐0.04|‐0.04|
||(0.026)|(0.026)|(0.030)|(0.030)|
|Community mean distance to primary school||‐0.02||‐0.00|
|||(0.026)||(0.026)|
|Community mean distance to secondary school||0.00<br>(0.010)||‐0.01<br>(0.012)|
|Community mean distance to nearest all‐season road|no|yes|no|yes|
|� : Districts|yes|yes|yes|yes|
|Observations|1,404|1,404|1,525|1,525|

Standard errors, clustered at the household level, in parentheses; *** p<0.01, ** p<0.05, * p<0.1. All regressions include control variables: age, age squared, and a constant 34
**Table 1:** Summary statistics

||mean|median|st. dev.|min|max|N|
|---|---|---|---|---|---|---|
|# children ever born|4.35|4|2.76|1|18|23751|
|# daughters ever born|2.12|2|1.72|0|12|23751|
|# sons ever born|2.23|2|1.76|0|12|23751|
|# children alive|3.53|3|2.15|0|15|23751|
|# daughters alive|1.74|1|1.42|0|10|23751|
|# sons alive|1.79|2|1.45|0|11|23751|
|frst child dead|0.18|0|0.39|0|1|23751|
|frst daughter dead|0.08|0|0.27|0|1|23751|
|frst son dead|0.10|0|0.31|0|1|23751|
|frst-born girl|0.48|0|0.50|0|1|23751|
|frst-born boy|0.52|1|0.50|0|1|23751|
|currently married|0.90|1|0.30|0|1|23750|
|currently divorced or sep|0.03|0|0.16|0|1|23750|
|ever divorced or sep.|0.12|0|0.32|0|1|23751|
|currently widowed|0.03|0|0.18|0|1|23750|
|ever widowed|0.05|0|0.22|0|1|23751|
|living with husband|0.90|1|0.30|0|1|21652|
|frst union|0.86|1|0.34|0|1|23050|
|polygynous husband|0.34|0|0.47|0|1|21690|
|live in female headed hh|0.14|0|0.34|0|1|23751|
|female head|0.10|0|0.31|0|1|23751|
|age|32.13|31|8.61|15|49|23751|
|age at frst marriage|17.69|17|4.63|7|45|23153|
|age at frst birth|19.36|19|4.44|9|44|23751|
|husband’s age|42.49|40|11.29|15|96|21457|
|contraceptive use|0.16|0|0.36|0|1|23751|
|wants another child|0.63|1|0.48|0|1|23598|
|wants no more children|0.22|0|0.42|0|1|23598|
|urban|0.32|0|0.47|0|1|23751|
|woman’s eduyrs|4.91|4|5.26|0|22|23735|
|husband’s eduyrs|6.16|6|5.79|0|21|22657|
|catholic|0.10|0|0.30|0|1|23575|
|other christian|0.37|0|0.48|0|1|23575|
|muslim|0.51|1|0.50|0|1|23575|
|hausa-fulani|0.34|0|0.47|0|1|23617|
|igbo|0.12|0|0.33|0|1|23617|
|yoruba|0.17|0|0.37|0|1|23617|
|weight-for-height|-0.55|-0.68|1.21|-4|5.92|22986|
|body mass index|23.07|22.14|4.66|12.1|59.81|23115|

_Notes._ 2008 NDHS. Using sample weights.

the desire for another child. Although knowledge of any contraceptive method is widespread, current use among currently married women is much lower but increasing over time: from 6% in 1990, 13% in 2003, to 15% in 2008.<sup>9</sup> Despite relatively low levels of contraceptive use, most pregnancies are ‘wanted’ by the vast majority of women: 88 percent of women with births in the five years

> 968% of all married women and 90% of all married men know of at least one method of contraception, and 29% (45%) of all married women (men) reported ever using a method of contraception. Among women currently using contraception, about two-thirds are using a modern method (mostly male condom, injectables and pills), while one-third use traditional methods (rhythm method and withdrawal are the most common).

9
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This is an important advantage for the empirical analysis, as most of the evidence on intergenerational educational mobility in India and China currently available are based on data that suffer from truncation due to coresidency restrictions used to define household membership. Emran, Greene, and Shilpi (2018) summarize 13 studies on intergenerational educational mobility in developing countries, only two of which use data not affected by coresidency bias.<sup>28</sup> While Emran, Greene and Shilpi (2018) provide evidence of substantial downward bias (average 18 percent) in the IGRC estimate from the coresident sample in rural India, we are not aware of any similar estimate for rural China. In online appendix A, we provide evidence on the extent of coresidency bias in rural China in a widely used household survey: the Chinese Household Income Project (CHIP). In particular, we compare the estimates from the CFPS (without any sample truncation) with those from the CHIP 2002 for the overlapping age cohorts. The evidence shows that the IGRC estimate from the CHIP 2002 is 25 percent smaller because of truncation of the sample arising from coresidency restrictions (see Table A.2 in the online appendix). A comparison of CHIP 2002 with the CFPS is also of independent interest, because CHIP 1995 and 2002 have been used by many researchers to study intergenerational mobility in China.<sup>29</sup> For a more complete discussion, please see online appendix A.

We use the 1999 round of the REDS and the first round of the CFPS in 2010. From the REDS data, we obtain the relevant information for our analysis on all father-son pairs irrespective of residency status at the time of the survey. For the CFPS data, we restrict to rural communities subsample, given our focus on intergenerational mobility in rural areas, and use the family roster to obtain a complete list of father-son pairs that includes all sons of the household head irrespective of their residency status at the time of the survey.

The main samples for our analysis consist of children aged 18 - 54 in the 1999 REDS survey, and 29 - 65 in the 2010 CFPS survey. This ensures that we focus on the same age cohorts of children who went to school mostly during the 1980s and 1990s. It is important to recognize that such an analysis for the overlapping age cohorts is meaningful for education, as most of the children under focus (29-65 years old in 2010) in China have completed their schooling by 1999, even though the information was gathered later in 2010. The

> 28The exceptions are Fan et al. (2019) and Azam and Bhatt (2015).

> 29Two of the authors of this paper, M. Shahe Emran and Yan Sun, used CHIP 2002 data to analyze the effects of farm and nonfarm occupations on intergenerational educational mobility in rural China (see Emran and Sun (2015b)). We decided not to publish that paper because of the worry about the biases due to sample truncation arising from coresidency. This paper replaces Emran and Sun (2015b) and the conclusions on rural China here supersede those in Emran and Sun (2015b).

15
development and political stability in the developing world. However, the stagnation of the Japanese economy, with rising fiscal deficits and debt, has made it increasingly difficult in recent years to generate the same level of public support for ODA as in the past. To be sure, in absolute terms, public support for ODA remains high, relative to other major donor countries. Even so, according to a recent opinion poll, those who favored "more ODA" declined from 41 percent in 1991 to 28 percent in 1998; those who favored "less ODA" rose from 8 percent to 19 percent over the same period (Katada 2000). Certainly, there is declining support for the large size of ODA that Japan has provided to developing countries.

Within Japan, some of the criticisms of the current administration of ODA include<sup>20</sup> :

- It lacks a coherent national strategy.

- It lacks transparency and efficiency.

- It fails to strictly follow the principles embodied in the ODA Charter of 1992, in particular, that ODA should not go to countries, such as China, with large military spending and weapons of mass destruction.

- It is biased towards hard infrastructure and places insufficient emphasis on soft infrastructure and social sector development.

- It is not participatory and does not promote partnership with other stakeholders in the international development community, including other bilateral donors and civil society.

- It is "faceless" and does not benefit Japan or its taxpayers commercially, diplomatically or otherwise.

As a result of these and other criticisms, and given the current economic realities, a budget cut has been proposed for ODA since FY1998. However, the outbreak of the East Asian Crisis postponed the cut's implementation.21 The government finally made the decision and curtailed the ODA budget for the first time in FY2001 (covering April 2001March 2002) by 3 percent for the general account and 4 percent for the overall allocation. The cut is almost entirely accounted for by a reduction in the MOF allocation for the MDBs and ODA loans (for the general account), and more than accounted for by a 7 percent reduction in ODA loans (for the overall budget). It is expected that the tight budgetary stance will continue, especially in the provision of concessional loans. It should be noted, however, that Japan is not the only country that has cut its ODA budget in recent years. In fact, budgetary support for ODA has been declining in many donor countries, including the United States.

Looking beyond the domestic scene, from the standpoint of the international development community, Japan will need to improve the effectiveness of ODA. A recent World Bank report on aid effectiveness concludes that recipient countries _must_ reform economic policies and institutions in order to achieve growth and poverty reduction through aid flows (World Bank 1998). Data support the view that countries with _strong_

> **20** These criticisms are compiled from various Japanese newspaper articles on Japanese ODA.

> 21 All of the increase in ODA in 1998 and 1999 was allocated to the crisis-affected East Asian countries.

15
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