rafmacalaba/datause-encoder-data huggingface dataset:
Table A2: Effects of Peers and Role Models on Financial Investment on Childrens Education

|Father Edu|0.115***<br>(0.012)|0.115***<br>(0.012)|0.117***<br>(0.012)|
|---|---|---|---|
|Peer Edu|0.159***|0.161***|0.155***|
||(0.051)|(0.051)|(0.050)|
|Role Model Edu|-0.066***|-0.067***|-0.066***|
||(0.017)|(0.017)|(0.017)|
|HH Rural (=1)|0.584|0.570|0.564|
||(0.486)|(0.486)|(0.479)|
|Father Edu_×_Rural|-0.063***|-0.063***|-0.063***|
||(0.013)|(0.013)|(0.013)|
|Peer Edu_×_Rural|-0.133**<br>(0.056)|-0.133**<br>(0.055)|-0.128**<br>(0.055)|
|Role Model Edu_×_Rural|0.053**|0.053**|0.052**|
||(0.022)|(0.022)|(0.022)|
|Number of School Age Children||-0.041**<br>(0.017)|-0.040**<br>(0.017)|
|Ability Index|||0.016<br>(0.026)|
|Ability Index Sq|||0.002<br>(0.003)|
|Constant|-0.416|-0.359|-0.484|
||(0.448)|(0.450)|(0.451)|
|Observations|15766|15766|15766|

Notes: Standard errors are clustered at the community level (*** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1). The dependent variable is educational expenditure adjusting for inflation. Inflation rates are calculated using price of rice separately for rural and urban areas. The peer and role model measures in Panel C are only based on district level. A peer is someone who was born in the respondents district within _±_ 3 years of respondents birth. A role model is someone who was born in the respondent’s district but is within _±_ 3 of respondent’s father age and belongs to top 50 percent education level within that age group of that district. All regressions include wave fixed effects. Rural and urban are defined based on location of household at the time of survey. Cognitive ability index is expressed in percentile; it is constructed taking the first principal component of Raven Test and two memory memory tests net of age and age square.

2
<!-- Start of picture text --> 12,000 10,892<br>10,000<br>8,532<br>8,000<br>2 6,000<br>4,353 4,743<br>4,000<br>2,000<br>463 698 20 87<br>. =<br>Hydro Thermal Small plants Cogeneration<br>@2005 2010 2015<br><!-- End of picture text -->
There are several potential reasons explaining why high unemployment rates do not seem to have had an effect on wage growth. First, workers may have strong bargaining power and were thus able to obtain nominal increases of their compensation above current inflation, particularly during the (historically) low inflation period of the late 1990s.<sup>2</sup> Another explanation may be that excessive labor market rigidity creates barriers to entry of new (or unemployed) individuals in the job market. Finally, it may be that a significant share of current unemployed may be waiting for better job offers given that their reservation wages are too high.

Labor market rigidity, which may be due to excessive workers bargaining power and or excessive regulations, does not seem to be a major issue for Jamaica, at least if one considers the available empirical evidence. Table 2 shows that, apart from relatively high firing costs, Jamaica’s labor market seems fairly flexible. In particular, the 22.6 score on the collective relation index, puts Jamaica below the score of the US (25.8) and very close to that of the UK (18.5). The latter is the lowest value in the sample considered in Botero et al (2004), thus indicating that Jamaican collective relation laws are comparable to the UK ones, which allow high flexibility in settlements of collective dispute. Jamaican unionization rates have decreased to about 16% in the first half of the 1990s from just below 30% twenty years earlier.<sup>3</sup> As estimated by Heckman and Pages (2003), non-wage costs of labor market regulations are low in Jamaica relative to the rest of Latin America and Caribbean. For Barbados, Trinidad and Tobago, and Jamaica—the three Caribbean countries included in their survey of studies on Latin America— the authors conclude that “the effects of job security on employment are statistically insignificant and the signs are positive in some cases.” Despite this evidence pointing towards a comparatively flexible labor market in Jamaica, some signs of regulatory issues can still be identified. In their study on labor markets and regulations in the Caribbean, Downes et al (2000) found for the case of Jamaica some negative effect on aggregate employment stemming from the imposition of minimum wages<sup>4</sup> . Additionally, recent IMF reports list further reform of the labor markets among the most urgent structural reforms the government should adopt (IMF 2004a, IMF 2004b). In particular, the reports cite that government spending on public wages exceeds 12% of GDP (in 2003), signaling very high public sector employment level; besides, high redundancy costs, according to private

> 2 The observed nominal wage growth during the 1990s suggests that workers have been setting their wage targets through backwards-looking expectations—nominal wage increases tend to be higher in the years following periods with high consumer price inflation.

> 3 See Forteza and Rama (2001).

> 4 The authors use aggregate employment and specify a coverage-weighted minimum wage index, so their aggregate data include many workers whose wage and employment are unlikely to be affected by changes in minimum wages.

4
<!-- Start of picture text --> Backward integration (FVA) Forward integration (DVX) GVC Participation Rate<br>(oo) fe) 9<br>oG<br>£ oa<br>nn<br>3 3<br>3 3<br>tinQ- <¢ite} 9)<br>2 ON ot<br>$ 2g >6<br>= xs}<br>oe Eu .<br>“ re) re}<br>GE 62)<br>1990 1995 2000 2005 2010 2015 1990 1995 2000 2005 2010 2015 1990 1995 2000 2005 2010 2015<br>Year Year Year<br>Oil Exporters——— Resource Rich, Non-Oil Exporters Oil Exporters ——Resource Rich, Non-Oil Exporter Oil Exporters ——Resource Rich, Non-Oil Exporters<br>=——= Resource Poor Countries =——= Resource Poor Countries === Resource Poor Countries<br><!-- End of picture text --> <!-- Start of picture text --> Exporters<br><!-- End of picture text --> <!-- Start of picture text --> Resource Poor<br><!-- End of picture text --> <!-- Start of picture text --> Resource Poor<br><!-- End of picture text --> <!-- Start of picture text --> Resource Poor<br><!-- End of picture text -->
49 some technicians are acquired through internal promotion. Finally, managers are primarily sought from other firms, both in Senegal and in Europe.

A recent study of the employment practices in Senegal's state owned firms was performed by Lachaud (1987). In his detailed investigation, Lachaud finds that the access to public sector jobs varies across occupations: education appears to be the important prerequisite for higher level positions, while personal contacts appear to be the principal avenue for obtaining less skilled jobs.

# 53 Workers' Views of Unions

The vast majority of Senegal's industrial workers are unionized. Within our sample, 83 percent of all workers belong to a union; in 1963, within Pfeffermann's sample, the figure was 72.8 percent (See Pfeffermann [1968] Table 39, p. 301). However, these numbers do not accurately reflect the strength and effectiveness of the unions as seen from the workers' perspective. When asked "What are the main advantages of union membership?" the responses of workers were unenthusiastic and sometimes very criticaL Judging from their expressions, most workers feel that the unions are not doing very much. Even so, workers were unlikely to criticize the unions when given the opportunity; in our questionnaire most of them gave the answers they felt "should be given." In trying to discover the reason for this conformity, it appears to us that few workers criticized the unions because the unions are closely aligned with the government and our questionnaire, although guaranteeing respondent anonymity, was officially approved by the government census office.

The worker responses which we obtained are consistent with those from the 1963 survey by Pfeffermann (1968, pp. 301-304) in which simflar questions were asked. To the question "What are unions there for?" 71.3 percent of the workers in 1963 identified "protection against bosses and defense of interests," which is strikingly similar to the 69.7 percent of our sample that identified some form of union protection (see Table 5.3). When asked about their general opinion of unions, 48.5 percent of the workers interviewed in 1963 had no opinion and 31.7 percent criticized unions. (About 20 percent did not answer this qucstion because they were not union members.) When asked "Who initiates strikes?" 52.3 percent of the workers interviewed in 1963 answered
account at a post office.<sup>4</sup> In our sample, we focus on the over 65,000 individuals who were interviewed in 60 of these countries.<sup>5</sup> Appendix 1 lists all the countries included in our sample.

The Global Findex data allow us to distinguish between three types of account ownership: an account at a financial institution only, accounts at both a financial institution and the post office, and an account at the post office only. Within our sample of countries that offer postal accounts, we find that 49.9 percent of adults have an account at either or both institutions, 11.6 percent of adults have an account at the post office, and 2.8 percent of adults have an account at the post office only (5.6 percent of account holders).

Figure 1 shows a wide variation in overall account ownership between high income and developing countries. While account penetration is close to universal in the developed countries included in our sample (90 percent), on average, only 44 percent of adults in developing countries offering postal financial services report having an account.<sup>6</sup> However, beyond account penetration, we are interested in the types of accounts owned by individuals. In most of countries in our sample, account ownership at a formal financial institution only is the most common type of account ownership, followed by account ownership at both a financial institution and post office. Having a post office account only is typically the least common.

One exception to that general pattern is Japan, where 80 percent of adults in Japan report owning an account at the post office. Japan is also the only country where owning an account at both a financial institution and the post office is the most common type of account ownership (77 percent). The gap between the share of post account ownership in Japan and the countries with

> 4 For seven countries (Algeria, Congo, Rep., Egypt, Arab Rep., Greece, Morocco, Tunisia, and Yemen, Rep.) the data is for 2012 instead of 2011 because of data quality issues in the 2011 round.

> 5 We drop Madagascar from our sample because more than 20% of the population is not sampled and Taiwan, China because no country-level post office information is available.

> 6 This compares to 89 percent account penetration in high income countries and 41 percent account penetration in developing countries for the full sample of countries in the Global Findex database. The data are population weighted.

5
**Chart 1: Defying Comparative Advantage (Exports), 1991 and 2005**

<!-- Start of picture text --> IRL<br>MEX<br>GBR<br>INDPHLIDNCHNTHA THAMYSZAFBRA MEXKORMYS C HLPRTHUNIRL I SRPESPKOR R GBRISTF DEU R R JPN E ASPJPNDEUFRAUSA USA<br>CHN BRA<br>IND PHL CHL<br>IDN<br>6 7 8 9 10 11<br>Log per capita GDP (PPP, constant $)<br>1991-small font; 2005-larger font<br>21<br>20<br>19<br>18<br>Export sophistication and income of destination countries<br><!-- End of picture text -->

# _Source: UN COMTRADE_

This chart plots a measure that combines the sophistication of a country’s exports with the average income level of the destination countries of these exports (described in greater detail in the text). The dotted (dashed) line is the fit of the relationship between this measure and per capita GDP in 1991 (2005). The fit is based on a larger sample of countries than shown by the country symbols in the text. The smaller (larger) font relates to observations for 1991 (2005).

12
**<u>Table 6.1 IV estimated impact on enrollment and child development outcomes (Poor children at baseline)</u>**<sup>**a**</sup>

||IVMode|l:Baseline|IVMod|el:Midline|IVMod|el:Endline|
|---|---|---|---|---|---|---|
||Actua|l Batch 1|Actual|Batch 1|Actua|l Batch 1|
||Coeff|Robust SE|Coeff|Robust SE|Coeff|Robust SE|
|**Enrollment in ECED Programs**|||||||
|Was child enrolled in project playgroups in survey year (1=Yes)|0.160***|(0.040)|0.237***|(0.059)|0.235***|(0.070)|
|Was child enrolled in non-project playgroups in survey year (1=Yes)|-0.015|(0.015)|-0.032|(0.029)|-0.047|(0.035)|
|Was child enrolled in Islamic Kindergarten in survey year (1=Yes)|-0.008|(0.011)|-0.019|(0.025)|-0.068*|(0.038)|
|Was child enrolled in Kindergarten in survey year (1=Yes)|-0.015|(0.017)|-0.053|(0.055)|-0.072|(0.077)|
|Was child enrolled in any ECED programs in survey year (1=Yes)|0.122***|(0.045)|0.075|(0.058)|0.006|(0.049)|
|Was child enrolled in Primary school in survey year (1=Yes)|NA|NA|0.014|(0.013)|0.004|(0.010)|
|Cumulated number of months of project playgroup|1.517***|(0.386)|3.450***|(0.781)|4.438***|(1.168)|
|Cumulated number of months of non-project playgroup|-0.153|(0.151)|-0.418|(0.363)|-0.852|(0.536)|
|Cumulated number of months of Islamic Kindergarten|-0.077|(0.109)|-0.267|(0.330)|-0.814|(0.568)|
|Cumulated number of months of Kindergarten|-0.145|(0.172)|-0.645|(0.648)|-1.247|(1.262)|
|Cumulated number of months of any ECED programs|1.142***|(0.439)|2.120**|(0.911)|1.524|(1.269)|
|Cumulatednumberof months of Primary school|NA|NA|0.142|(0.134)|0.353|(0.669)|
|**Standardized Child Development Outcomes**|||||||
|EDI: Physical Health & Well-Being|0.100|(0.116)|0.100|(0.102)|0.041|(0.115)|
|EDI: Social Competence|0.190|(0.132)|-0.079|(0.081)|-0.036|(0.102)|
|EDI: Emotional Maturity|0.066|(0.114)|0.089|(0.095)|0.111|(0.107)|
|EDI: Language & Cognitive Development|0.066|(0.055)|0.042|(0.087)|-0.047|(0.043)|
|EDI: Communication & General Knowledge|0.019|(0.083)|-0.090*|(0.054)|-0.032|(0.122)|
|SDQ: Emotional Symptoms|-0.189*|(0.100)|-0.031|(0.103)|0.025|(0.112)|
|SDQ: Conduct Problems|-0.113|(0.106)|-0.039|(0.097)|-0.152|(0.116)|
|SDQ: Hyperactivity & Inattention|0.011|(0.108)|-0.069|(0.095)|-0.053|(0.108)|
|SDQ: Peer Problems|-0.036|(0.115)|0.005|(0.112)|-0.083|(0.105)|
|SDQ: Pro-social Behavior|0.026|(0.112)|0.077|(0.103)|-0.124|(0.118)|
|SDQ:Total Difficulties|-0.145|(0.106)|-0.047|(0.098)|-0.095|(0.115)|

Notes: *** p<0.01, ** p<0.05, * p<0.1;<sup>a</sup> IVs are two dummy variables indicating original batches 2 or 3 with original batch 1 as a reference group. Each row is the result of a separate regression. Models are estimated separately for baseline, midline and endline. Controls include: child’s age, gender, household size, household wealth and mother’s education level. Robust standard errors are clustered at the village level. Sample size for each year varies from 760 to 763.

34
# **Seasonal and Extreme Poverty in Bangladesh: Evaluating an Ultra-Poor Microfinance Project**

## **1. Introduction**

Microfinance is part of a strategy to mitigate the moral hazard problems of lending by adopting innovative methods such as group-based lending.<sup>2</sup> It is also a strategy to reduce poverty by targeting the poor, who are often excluded by regular financial institutions because of a lack of sufficient physical collateral. In recent decades, microfinance has successfully reached a large percentage of the poor, especially women. Yet it has not reached as many ultra-poor as one would like to include among its clientele (Webb, Coates, and Houser 2002; Datta 2004).<sup>3</sup> Bangladesh is a good example. Despite the country’s overwhelmingly large proportion of ultra-poor, microfinance reaches not more than 20 percent (Khandker 1998, 2005). While a recent survey found coverage as high as 40 percent in certain areas of the country (InM 2009), service coverage of marginal and small farmers is small, with agriculture representing only about 10–15 percent of the microfinance lending portfolio. Also microfinance institutions (MFIs) have limited coverage in such areas as the northwest region

> 2 Besides covariate risk, rural lending is subject to problems of asymmetric information, incentive to repay, and enforcing loan contracts (Stiglitz 1990).

> 3 Although the terms _ultra-poor_ , _extreme poor_ , and _hard-core poor_ are often used interchangeably, for targeting purposes, MFIs specifically designate the ultra-poor based on landholdings, income, and employment as defined in section 2 of this paper.

2
# **The ASEAN Free Trade Agreement:**

# **Impact on Trade Flows and External Trade Barriers**<sup>*</sup>

Hector Calvo-Pardo University of Southampton Caroline Freund World Bank Emanuel Ornelas London School of Economics

> * We are grateful to the Asian Development Bank for very helpful assistance in obtaining the data on ASEAN preferential liberalization employed in this paper, and to Matias David Horenstein and Nathan Converse for excellent research assistance. We thank Richard Baldwin, Robert Barro, Fukunari Kimura, Marcelo Olarreaga, Jong-Wha Lee and participants of the Hong Kong workshop on “Quantifying the Costs and Benefits of Regional Economic Integration” and the Geneva workshop on “Empirical Determinants of Regionalism” for helpful comments. This paper reflects the views of the authors and does not reflect the views of the World Bank.
more appropriate because regulatory restrictions to portfolio composition are mostly defined at the fund type level instead of the PFA level, which is not the case for trades.<sup>64</sup> The turnover statistics are positive by construction so the hypothesis that they are greater than zero is meaningless, but they can be used to test for differences across PFAs, fund types, and time. Proper testing, however, requires some additional considerations. First, although the natural unit of analysis is each specific portfolio held by a PFA, there are some regulatory restrictions that apply to the PFA as a whole and induce correlation in the changes in composition of all of its funds. Thus, we cannot safely treat the funds of a same PFA as independent observations. Second, as discussed above, our sample includes PFAs and fund types that exist in different periods of time because of entry, mergers, exit, and regulatory changes. To the extent that there are periods with intrinsically different levels of turnover we can incorrectly attribute them to differences in turnover across PFAs or funds that exist in different periods.

# **Appendix 4: Alternative Momentum Measures**

The standard momentum statistics described in Section 5.3 have two shortcomings when applied to the Chilean pension fund data. First, they were developed to compare funds that operated over the same period of time. In contrast, the Chilean data include funds that operated in different moments because of entry, exit, and merging activity. The comparison of funds that do not completely overlap is complicated by the presence of important aggregate and regulatory events during the period that affect only those funds in operation at the time of the event. Second, as mentioned in multiple occasions, trading activity in Chilean PFAs is very infrequent and most of the changes in portfolio allocations are passive. This makes the interpretation of the first two measures difficult.

There are several ways of dealing with these potential shortcomings. The differences in the periods of operation of the funds in our sample could be addressed by focusing only on those funds in continuous operation during a sub-sample of the data, but this would lead us to disregard an important amount of data and lose power in all of our

> 64 Instead of adjusting the lagged weight by relative returns, it is also possible to use past prices to value the contemporaneous portfolio so that changes in prices do not affect turnover. Results are similar to those produced by the other methods and are available upon request.

48
# **Appendix S2: List of Variables in Model**

## **Positive variables:**

|_CCi_,_t_|Cash crop output|
|---|---|
|_CPINFUt_|Nonfood consumer price index urban|
|_CPINFRi_,_t_|Nonfood consumer price index rural<br>|
|_CRi_,_t_|Rural consumption|
|_CUt _|Urban consumption|
|_EXPNUTi_,_t _<br>|Exponential of nutrient stock<br>|
|_EXPORTt _<br>|Total exports<br>|
|_EXTRACTi_,_t _|Crop extraction of nutrients|
|_Fi_,_t_|Food output|
|_FDIt _|Foreign direct investment|
|_FSURPi_,_t _|Food surplus by region|
|_FTOTt _|Total food production|
|_GNPt _|National output value|
|_GOVWRi, t_|Rural government wage bill in region_i_<br>|
|_GOVWRURt _|Total rural government wage bill|
|_GOVWUt _|Urban government wage bill|
|_GWBILLt _|Totalgovernment wage bill|
|_IMPORTt _|Total imports|
|_INPUTi_,_t _|Modern agricultural input use|
|_KCCi_,_t _|Capital in cash crop production|
|_KMt _|Capital in manufacturing|
|_KPRp_,_i_,_t _|Rural capital stock in sector in period|
|_KPUp_,_t _|Urban capital stock in sector in period|
|_KROADi_,_t _|Road length|
|_KSRi_,_t _|Capital in rural service|
|_KSUt _|Capital in urban service|
|_LABCOSTp_,_t _|Public labor force cost in sector_p_|
|_LCCi_,_t _|Labor in cash crop production|
|_LFi_,_t _|Labor in food production|
|_LFARMi_,_t _|Farm labor|
|_LGt _|Total government labor|
|_LGRi_,_t _|Rural government labor|
|_LGUt _|Urban government labor|
|_LMt _|Labor in manufacturing|
|_LRi_,_t _|Labor in rural area|
|_LROADi_,_t _|Rural road building labor|
|_LSRi_,_t _|Rural services labor|
|_LSUt _|Urban services labor|
|_LUt _|Labor in urban sector|
|_Mt_|Manufacturing output|
|_MPCCi_,_t _|Marginal product of labor in cash crop production|
|_MPFi_,_t _|Marginal product of labor in food production|
|_PCCRi_,_t _|Price of cash crop in rural region|
|_PFRi_,_t _|Price of food in rural region|

51
This is illustrated in Table 7, which assembles information from three municipalities, two from Liaoning and one from Shaanxi, whose situations are not atypical. Table 8 assembles data from townships in four provinces to show that, at the bottom of the administrative hierarchy, townships have to “share” revenues from these taxes with the counties after the provinces and municipalities have taken their cuts, again, with strikingly different treatment across provinces.

The multiple claims by different levels of government to the few revenue-rich taxes point to the potential for tension that is inherent in the present system of tax assignment and tax sharing. Under conditions of fiscal stress, the temptation for higher levels to “grab” revenues is undoubtedly great, and the Constitution provides no protection for the lowest levels of government.

**Table 7.  Multiple Claims to the Main Taxes, 2003**

|**Government level (**|**Tax Share in Percent)**||<br>|**Tax**<br>|**Type**<br>||
|---|---|---|---|---|---|---|
||||VAT|BT|EIT|PIT|
|Central Government|||75|0|60|60|
||Provincial Government||10|30|20|15|
||Anshan Municipality|municipal level|5|30|5|10|
|Liaoning Province||county level|10|40|15|15|
||Panjin & Yingkou Municipalities|municipal level|6|28|8|10|
|||county level|9|42|12|15|
||Provincial Government||7.5|30|20|20|
|Shaanxi Province|Hanan Municialit|municipal level|2.5|10|..|..|
||yg py|Liquan county|15|60|..|..|

Sources: World Bank (2006a); Zhao et al. (2005).

16