rafmacalaba/datause-encoder-data huggingface dataset:
The same reasoning carries over when one moves from a finding based on one population to another population. The fact that the choice of a woman leader of the village council in Bengal and Rajasthan led to the better provision of public goods does not mean that you have reason to expect this will be true in Bihar, Bahia or Bahrain, or, for that matter, in Bengal and Rajasthan tomorrow, because tomorrow’s population is a different one. At least, if we were as fastidious about deducing conclusions as the practitioners of randomized control trials want us to be, we could not draw those conclusions about other places and other times. That would be like drawing lessons from biased samples. This, in an interesting converse way, is related to an important problem noted by Deaton (2010). Even if we learn the facts from properly controlled randomized trials, if the intervention is then to be made not on a random draw from the population but to a speciallyselected group, we should be prepared for failure.<sup>9</sup>

# **3. A Limited Causality Claim**

The claim that can be made, but after some prior assumptions are made, is that randomized trials can establish certain ‘circumstantial’ causalities. The prior assumption that we need is to accept the determinist claim that the universe proceeds by causality and so the future that lies ahead of us is as determined as our history. To state this more precisely, assume time progresses in pixels, instead of a continuum, so that for each point of time, there is a well-defined immediate previous point of time. Let X be the set of all possible states of the world at all possible points of time. Further, X is a Cartesian product of n sets, X1, X2, ... , Xn, where each of these sets consists of all possible states of some particular feature of the world. Thus X1 could consist of positions of the sun; X2 could be states of the weather, etc. Hence, at any point of time, an x ε X is a full description of the

> 9 A stark example of this is provided by Worrall (2007). The drug, benoxaprofen, for arthritis and muscular skeletal pain, passed the test of randomized trial very well. But when the drug was tried on actual patients it was found to cause a disproportionate number of deaths. What later became clear is that this is a drug that is not used on a random sample of people, but pre-dominantly on the older persons and they are the ones most likely to get an adverse reaction. This powerful argument is also discussed and elaborated upon by Deaton (2010).

9
**Table 8. Comparative Statistics, Natural Resources (% of total exports)** _2010-2014_

||||SSA<br>Leader|World Excl. SSA<br>(75thpercentile)|MIC<br>Leader|LIC<br>Leader|
|---|---|---|---|---|---|---|
||4|SSA Average|2.81%|1.74%|3.90%|1.51%|
|Growth|15|SSA oil RR|3.13%|2.07%|4.23%|1.84%|
||0.0|SSA non-oil RR|2.85%|1.78%|3.94%|1.55%|
||-|SSA non-RR|2.76%|1.70%|3.86%|1.47%|
||4|SSA Average|2.26%|1.40%|3.14%|1.22%|
|Caital|12|SSA oil RR|2.52%|1.66%|3.41%|1.48%|
|p|0.0|SSA non-oil RR|2.29%|1.43%|3.17%|1.25%|
||-|SSA non-RR|2.23%|1.37%|3.11%|1.18%|
||3|SSA Average|0.97%|0.60%|1.34%|0.52%|
|TFP|05|SSA oil RR|1.08%|0.71%|1.46%|0.63%|
||0.0|SSA non-oil RR|0.98%|0.61%|1.36%|0.53%|
||-|SSA non-RR|0.95%|0.58%|1.33%|0.51%|

_NOTE: The estimations are calculated based on the results from regressions in Table 5 Columns [4] [5] and [6]._ Finally, we report the actual gains from improved international trade integration over at 10-year span (2010-14 vs. 2000-04) and 20-year span (2010-14 vs. 1990-94) in terms of growth of output per worker, growth of capital per worker and TFP growth. In the case of trade openness, growth of output per worker increased by 0.3 percentage points over the past 10 years whereas growth of capital per worker and TFP growth accelerated by 0.1 percentage points and 0.2 percentage points over the past decade. The largest growth per worker increase over the past decade is attained by minerals and metals rich countries in the region (0.3 percentage points per year) while the physical capital and TFP growth gains over time are similar to those of the regional average (0.2 and 0.1 percentage points, respectively). In contrast, the indicators of trade integration deteriorated over the past decade across oil rich countries. Hence, growth decelerated by 0.2 percent due to lower trade volumes, and it contracted by 0.1 and 0.15 due to greater product concentration and higher dependence of natural resource exports.

_page 29_
total volunteer labor devoted to a project and thus gives the endogenous scale of any project.

For the volunteer process, to simplify, we assume a volunteer provides a fixed amount of effort at a cost _b_ . We start by assuming that _b_ is the same for all villagers. Heterogeneity in _b_ will help explain, in an obvious way, individual participation differences and could arise from differences in personal or psychic costs of participation and the like. Of course, heterogeneity in _b_ makes the full village solution more difficult. But if, say, _b_ increases with _x_ but at a slower rate, our comparisons of equilibria under the two regimes will not be qualitatively affected.

For the base case, a person volunteers if their private marginal product exceeds cost, or  _L_  1 _C xi_  _b_ . If a project is announced, total volunteer labor is _L_  (1  _s_ ) _N_ , where _N_ is the mass of people in the village and _s_ is the lowest valuation person to volunteer from the unit interval of valuations _x_ (assuming  _L_  1 _Ci_  _b_ ). This lowest valuation person to volunteer from the unit interval is given by the equation This defines an implicit function Note also that _db_ / _dC s_  0 . One might impose that any project has a minimum required labor _<u>L</u>_ or maximum _~~s~~_ , If this is imposed, _~~s~~_ cannot be exceeded if a project is to be viable.

12
savings and credit behavior across countries. We use indicators of a women’s legal ability to earn an income, as codified in laws and regulations, from the World Bank’s Women, Business and the Law (WBL) database. We also use measures of gender norms from the OECD’s Gender, Institutions and Development (GID) database. We find that women are significantly less likely to have an account, save, and borrow in countries with greater legal discrimination, even after controlling for other individual and country characteristics.

# **_Previous literature on Women and Financial Inclusion_**

While the role of well-functioning financial systems in addressing income inequality and promoting economic growth is widely recognized, relatively little is known about the observed gender gap in access to finance or the specific barriers that limit access to finance for women relative to men. Our paper is related to a small but growing literature on the gender gap in access to financial services. Previous literature has highlighted the intrinsic value of equal access to finance for women and its potential as a tool for initiating a “virtuous spiral of social, economic, and political empowerment” (Cheston and Kuhn 2002). In addition, barriers that constrain women’s access to finance, compared to men’s, limit (by approximately half) the poverty reducing and growth promoting potential of finance and may prove costly in terms of foregone development and potential macroeconomic gains (Narain, 2009).

Differential treatment under law or customs may also constrain women to enter contracts under their own name, including the opening of a bank account (IFC, 2011 and World Bank, 2012). Gender norms also often influence women’s access to the public realm and the level of autonomy that women enjoy in managing their own income stream. For example, restrictions on social mobility or interactions outside the home, especially across gender lines, may limit 3
Since most of the firms in our sample were unlikely to receive cross-border loans from the parents of multinational banks due to their small size, evidence on the local lending by the affiliates of foreign banks is likely to be more relevant for our study. For example, there is some evidence that foreign banks in ECA reduced their lending earlier and faster than domestic banks during the crisis (de Haas, Korniyenko, Loukoianova, and Pivovarsky, 2011; Mihaljek, 2010).<sup>4</sup> However, like foreign banks, domestic banks did eventually adjust their lending towards less risky loans by reducing loan growth to firms and households (Mihaljek, 2010) and the foreign banks that participated in the Vienna Initiative – a public-private partnership between European governments, multinational banks, and international financial institutions in which foreign banks were eligible for financial support in return for commitments that they would maintain their exposures and keep subsidiaries adequately capitalized in affected host countries – were more stable lenders than those that did not, and had loan growth rates on par with domestic banks by the end of 2009 (de Haas, et al. 2011). Supply-side evidence on credit provision by banks does not, however, provide information on the types of firms that received that credit and their likelihood of survival during the crisis, which is our focus.

To summarize, we offer firm-level (rather than bank- or country-level) evidence to study how firm (and country) characteristics affected reported financial constraints and the likelihood of survival during the recent financial crisis in the ECA region. Our data on reported financial constraints in 2008-9 and firm survival in 2009 are more reflective of the effects of the crisis than other studies that have analyzed pre-crisis access to credit in 2008 using the BEEPS data. Moreover, because the most recent crisis episode began in advanced economies rather than in the ECA countries themselves, we offer a fresh look at the role of foreign banks when their parents are under financial pressure.

The empirical results in this paper show that firms that had access to financing were better able to weather the crisis than firms that did not. Larger and older firms were less likely to

> sample of all syndicated loans to private borrowers from 2005 to 2009, de Haas and Van Horen (2011) find that geographic proximity, establishment as a subsidiary (rather than a branch), integration into a network of domestic co-lenders, and a history of syndicated lending to a particular country all enhanced the stability of foreign lending.

> 4 Evidence is from bank-level regressions for 1,275 banks in ECA in de Haas et al (2011) and from a survey of central bank governors in Mihaljek (2010).

4
7 <!-- Start of picture text --> FIGURE 1: UKRAINE<br>OVERALL ADMINISTRATIVE CONTROL INDEX<br>100<br>90<br>80<br>UKRAINE<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>CHILE<br>Ql Q2 03 04 01 02 Q3 04 01 02 Q3 Q4 Ql Q2 Q3 Q4<br>'92 '93 '94 '95<br>1992 1993 1994 1995<br>Table 1: Data for Overall Admintrative Control Index for Ukraine<br>Ql '92 Q2'92 Q3 '92 Q4'92 Ql'93 Q2 'Q3 Q3'93 Q492 '94 Q3 '94 Q4'94 Ql '95 Q2 '95 Q3 '95 Q4 '95<br>? EXCU GERATEDISTORTIONINDEX. FORE ALOCAIONDISORTON INDEX t00.0 t00.0 100.0 99.0 ....... 99.7 44.4 41.4 40.5 aso 3. 43.4 211 34 2. 60 9.3 9 44. , , 9. .6 .6126.5 76 23.6 00 l. 165 113 O . 58 0 ..... 10. 41<br>.EXPORTRESllCTION INDEX 68.1 79.8 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~.579 74.1 7 _.__._ .. __ ....__ _7 . _ ......_ ........_F__.._I . 75.4 ........ ..- . .......92.0 . _._ . 61.5 ., _ _ ... .... ........ . 45.5 43.2 .. ....... 68.1 57.4 ......... 51.3 ................51.3 51.3<br>DOETCRD ERSRTO_IDE 55. 55g.1 55.1. 55.1.- 52.0 52. 52.0 52.0 39.0 39.0 39.0 391 3 2.0 29.0 290 2.<br>RETAEL PI1CE CONTROLS 77.3 75.3 75.4 14.4 5.0 11.0 37.0 90.0 50.0 80.0 80.0 27.5 22.5 14.1 14.1 14.1<br>HOLESALE PRICE cONTROLS 74.0 74.0 170 170 1 6.0 16.0 5 71. 71. 71. 43.0 31.0 28.9 28.9 23.4<br>OVERALLADMN.CONTROL IDEX 79.0 71.4 62.6 50.0 47.0 '"'35.2 46.2 _ 74.0 65.5 .3 57.9 35.2 25.2 24.1. 2.2 2.0<br><!-- End of picture text --> Table 1: Data for Overall Admintrative Control Index for Ukraine
links. While one may be concerned that Baier and Bergstrand do not allow for political-economy forces to play any role in their model and empirics, the analyses of Ornelas indicate that this is probably not a big problem after all.

It is worth noting, however, that the results of Ornelas (2005b, c) apply to FTAs, and it is unclear whether they generalize to CUs. Since the (limited) empirical evidence suggests that external tariffs do not change (Estevadeordal et al. 2008) and that export prices of outsiders fall (Chang and Winters 2002) after the formation of CUs, it may well be that trade-diverting CUs are more likely to be politically viable. Research on this topic is needed.

# **4. Multilateralism and Regionalism**

As multilateralism and regionalism proceed in tandem, a central question is whether the spread of regionalism will help or harm the multilateral trading system. The impact of RTAs on members’ incentives to liberalize vis-à-vis non-members is only one factor in the assessment of regionalism. In fact, countries’ unilateral responses to preferential liberalization may be a deceptive signal of the whole impact of RTAs on the multilateral system. For example, FTAs may induce members to reduce their external tariffs while at the same time lowering their incentives to engage in broader multilateral trade agreements. Conversely, the rise of regionalism could simply reflect the successes—or the failures—of multilateralism. We look at each of these issues in turn.

25
common time periods and because treatment for STIs offered by the RESPECT study begins after R1, the STI outcomes are better proxies of recent sexual activity. We thus begin with 1,210 female study participants in R2, where we have 868 women who are observed in each round. Women where data are missing in either R3 or R4 are labeled as "Ever Out" and total 119, while women who are not interviewed in R2, but enter the study in R3 or R4, are labeled as "Entering In" and total 194. Given the unbalanced nature of this panel, one concern might be that attrition (or those entering the sample) may affect our estimates. For example, women who are very sick maybe less likely to be interviewed and more likely to have both food insecurity and higher rates of STIs. To examine this possibility, we follow Fitzgerald _et al._ (1998) and see if lags of STIs and negative shocks predict attrition or entering the sample (see Appendix Table A1a). We find no statistically significant relationships between STIs, negative shocks, or attrition. While there is a marginally significant association between lagged STIs and entering into the sample, there is no corresponding relationship with shocks.

Using individual-level fixed effects, our estimates are generated from individuals that appear in at least two rounds of data collection. Of the 1,210 women at R2, 134 only appear once between R2 to R4. Our analytical sample thus includes the 1,076 women that appear at least twice in rounds 2 through 4. In this sample, we find no significant associations between lagged STIs, shocks and whether an individual appears in the study (see Appendix Table A1b).

In Table 1, we present descriptive statistics of our analytical sample of 1,076 women. Many of the women are in their early to mid-20’s and 82% are married.<sup>12</sup> The primary occupation is agriculture, with 75% citing this as their primary source of income. About 19% of the sample report being in the lowest SES group (as defined previously).

Based on the self-reported data, a vast majority of women in the sample are monogamous, with the mean number of recent partners (past four months) being close to 1. A small percentage (8%) have engaged in transactional sex (paid sex) recently, and this figure is close to the 12.5% of women who are sex-workers in Busia, Kenya, as

> 12 Marriage rates are stable throughout the study, hovering between 82 to 84% of the sample in any given round, new marriages occur at a rate of less than 1% in any round.

9
<!-- Start of picture text --> 0.04 (2012)<br>Low Mid<br><!-- End of picture text --> <!-- Start of picture text --> BE Micro (0-5<br>employees)<br>BSmall (6-20<br>employees)<br><!-- End of picture text --> <!-- Start of picture text --> M25<br>Bétolo<br>ee 15<br>q @litols<br><!-- End of picture text -->
home environment by 0.155 SD (measured by a combination of the FCI and HOME indicators, constructed using a principal component analysis). This estimate remains statistically significant even after accounting for multiple hypothesis testing. All results are robust to the inclusion of additional controls (see Table A8 in Appendix 2).

Statistically significant changes are found in Affection but not for Interaction, measured by the PBC nurturing scales. We find that NEP-I leads to a decrease in negative discipline (-0.077 SD), measured by the PBC discipline scale, but this estimate cannot be distinguished from zero with multiple hypothesis testing. Impacts of NEP-B on these variables are positive, but smaller in magnitude than those of NEP-I, and never statistically significant.

Regarding caregiver perceptions, we find that NEP-I significantly increases perceived self-efficacy (measured by the Parental Sense of Competence Scale) by 0.1 SD, and parental perceived impact of own behavior on child development by 0.1 SD, results which are robust to multiple hypothesis testing. We also find that perceived social support from friends and the community is also increased by 0.082 SD. While we find no statistically significant impacts of NEP-B or NEP-I on parental attitudes towards child-rearing measured through parental styles, and we see statistically significant impacts of NEP-I on the average age at which parents believe their children would be able to achieve key language developmental milestones in 0.1 SD.

Finally, we find no significant impacts of NEP in caregiver mental health (CESD) or stress (PSI).

# 5.2 Instrumental Variables

We now discuss IV estimates of the impact of participating in NEP-B and NEP-I on child and household outcomes. Based on information from administrative program records, the overall participation rates in NEP-B was 24.9% and in NEP -I was 30.8% among eligible individual. There is also imperfect compliance in the control group. The original plan was to start offering the program to the control group one year after the start of the study and given the delay of the baseline, part of the control group eventually received treatment. 4.8% of caregivers assigned to the control group were able to access the program, and attended at least one session of NEP-B. 5.0% of caregivers in the control group attended at least one session of NEP-I.

15
about 8 percent of the total employment (see table 1.5); these clusters have become the main economic driver of the provincial economy. In the town of Xiqiao (Guangdong), the textile cluster accounted for 60 percent of Xiqiao’s total GDP, 30 percent of the textile fabrics market of Guangdong Province, 11 percent of the domestic market, and 6 percent of the global market, employing about 43 percent of Xiqiao’s population.<sup>19</sup>

**<mark>Table 1.5    Cluster Employment as a Share of Total Employment in Guangdong Province, 2001–07</mark>**

|_2001_||_2002_|_2003_|_2004_|_2005_|_2006_|_2007_|
|---|---|---|---|---|---|---|---|
|Cluster||||||||
|employees|52.95|182.29|241.74|266.74|370.71|—|431.48|
|Total employees|4,058.63|4,134.37|4,395.93|4,681.89|5,022.97|5,250.09|5,402.65|
|Cluster||||||||
|employment (%)|1.30|4.41|5.50|5.70|7.38|—|7.99|

_Sources:_ Chapter 6 of this volume and Guangdong Statistical Yearbook 2009. _<mark>Note:</mark>_ <mark>— = no data available</mark> .

Although the total employment in the clusters in China as a whole is hard to gauge, employment is likely to be much higher in cluster than in the SEZs, because most of the clusters are in labor-intensive sectors.

# Cluster Formation

Each cluster has its own development trajectory and was formed in a different way. By examining many of them, however, we may be able to identify some common elements that led, in varying degrees, to their formation:

- _The Open Door policy and reform._ Almost all the clusters were formed after China’s opening up. The reforms and Open Door policies provided a macroenvironment that allowed the private sector to flourish and foreign investment to enter China. Before the reforms, all private businesses were officially forbidden.

- _Long history of production or business activities in a particular sector._ Business activity in a given sector  preceded many Chinese clusters. For example, the Wenzhou  footwear cluster in Zhejiang Province has a long history of shoemaking, dating back to 422 AD, and has built up local production  capacity over time;<sup>20</sup> the textile industry in Xiqiao, in Guangdong Province, first prospered during the Tang Dynasty (618–907 AD)  and peaked in the Ming Dynasty (1368– 1644 AD)  and thus had accumulated strong capacity in silk and yarn production before the reform;<sup>21</sup> and the toothbrush  industry in Hangji, Jiangsu Province, dates back to the Qing Dynasty (1644–1911 AD) (Wang 2009).

- _Proximity to major local markets and infrastructure._ In general, most of these

26
In sum, we find evidence of a compositional effect in China’s exports during the Great Recession. The sectors that contributed most to the export collapse are those where vertical specialization is more prevalent.<sup>21</sup>

# _6.1.2. Trade cost effect_

Next, we want to investigate if there is evidence of a trade cost effect in China’s trade during the Great Recession. As we have shown in Section 5, intra-GPN trade is generally more sensitive to trade costs than regular trade. If trade costs have risen significantly during the Great Recession, we therefore should find that processing exports have consistently dropped more than non-processing exports from the first quarter of 2008 to the first quarter of 2009.

To adequately control for compositional effects, we conduct the analysis at the most disaggregated level in China’s trade data – the HS 8-digit level. Specifically, we examine whether, at the HS 8-digit level, there is evidence that the share of China’s processing exports in total exports has significantly declined from the first quarter of 2008 to the first quarter of 2009. The results are presented in Table 9. In line with the trade cost effect, the t-test on equality of means finds that the share of processing exports in total exports was significantly lower in the first quarter of 2009 than a year earlier.

# **[Table 9 about here]**

In sum, we find evidence of a trade cost effect in China’s exports during the Great Recession. After controlling for compositional effects, processing exports have consistently dropped more during the Great Recession than non-processing exports.

# _6.1.3. Bullwhip effect_

Finally, we want to investigate whether there is a bullwhip effect in intra-GPN trade. In other words, we want to analyze if the percentage decline in China’s processing imports exceeded the percentage decline in processing exports during the Great Recession. A first indication of a bullwhip effect is that, despite China’s relatively robust economic growth

> 21 In line with this result, Aziz and Li (2008) demonstrate that China’s increasing specialization in electronics exports has led to an overall rise in the income elasticity of China’s exports.

31