rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 5069

# **Abstract**

China has seen a huge reduction in the incidence of extreme poverty since the economic reforms that started in the late 1970s. Yet, the growth process has been highly uneven across sectors and regions. The paper tests whether the pattern of China ́s growth mattered to poverty reduction using a new provincial panel data set constructed for this purpose. The econometric tests support the view that the primary sector (mainly agriculture) has been the main driving force in poverty reduction over the period since 1980. It was the sectoral unevenness in the growth process, rather than its geographic unevenness, that handicapped poverty reduction. Yes, China has had great success in reducing poverty through economic growth, but this happened despite the unevenness in its sectoral pattern of growth. The idea of a trade-off between these sectors in terms of overall progress against poverty in China turns out to be a moot point, given how little evidence there is of any poverty impact of non-primary sector growth, controlling for primary-sector growth. While the non-primary sectors were key drivers of aggregate growth, it was the primary sector that did the heavy lifting against poverty.

This paper—a product of the Director’s Office, Development Research Group—is part of a larger effort in the department to monitor and explain progress against poverty in developing countries. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at mravallion@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **5. Conclusions**

India cannot reasonably claim success for its ambitious National Employment Guarantee Scheme unless the scheme works adequately where it is presumably needed most, namely in the country’s poorest areas. We have focused on the role played by information in determining the scheme’s performance in one of India’s poorest states, Bihar. It is one thing to create rights under the law, but will that translate into rights on the ground, and better outcomes for poor people?

Our baseline survey indicates that while the vast majority of people in rural Bihar have heard of the scheme, there is little public awareness of even its most basic features. Few people understand that they have the right to request work. The fundamental principle of employment on demand is yet to sink in. Similarly, five years after the Act, people still know very little about other entitlements. And the overall participation rate is far lower than one would expect given the high incidence of poverty in rural Bihar, and associated demand for work on the scheme.

To test whether access to information is a key constraint on the scheme’s performance, we used a high-quality fictional movie to inform people of their rights under the law—to help ensure local public knowledge of households’ rights and of the scheme’s rules, and to point to the scope for local monitoring and addressing grievances.

We find that the information campaign changes knowledge and beliefs about a public program in this setting. The movie significantly enhanced people’s performance in tests about their rights and entitlements under the law. Perceptions of local processes related to the scheme also became significantly more positive for those who had access to the movie.

However, our results also caution that public awareness and positive perceptions are not sufficient for positive change. Indeed, our field trial indicates little discernible average impact on seeking and obtaining employment when needed. We do find a modest employment gain for illiterate participating individuals, though still far short of their desired employment. Learning one’s rights in this setting is not the same thing as being empowered to demand those rights or have them met. The movie did not significantly change aggregate objective outcomes, but appears instead to have created a “groupthink” within the treatment villages—a distortion to widely-held beliefs. Collective perceptions of program efficacy became more positive, but this did not translate into actual efficacy at the individual level.

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evaluations of **enterprises** participating in SME programs are rare, not only in Mexico but elsewhere in industrialized and developing countries as well. An exception are two impact evaluations of the CIMO program conducted by the Ministry of Labor and Social Welfare of Mexico (STPS), one in 1995 the other in 1997, that compared a group of program beneficiaries to a control group of SMEs outside the program.

This paper takes a second critical look at the methodology used previously to evaluate the CIMO program, taking advantage of the fact that the research team was provided access to the raw data collected for both evaluation studies. This re-examination of the CIMO data serves several purposes. First, it provides a broad description of the way in which STPS first designed and implemented the net impact evaluation study and then analyzed the data to arrive at conclusions regarding the impact of program participation on intermediate outcomes and on firm performance. Second, it asks whether the panel data could have been analyzed differently, to get more accurate estimates of the impacts of program participation that would allow calculation of reliable cost-benefit measures of CIMO interventions. Specifically, it addresses the apparent contradiction between the finding that program participation improved intermediate outcomes of CIMO firms, but was nonetheless associated with lower post-program levels of performance. To anticipate the results that follow, this paper concludes that the contradictory result is driven principally by self-selection of weaker firms into the CIMO program.

Section II provides a brief overview of the CIMO program, followed in Section III by a review of the methodology used by STPS in the two impact evaluations of the CIMO program (STPS 1995, 1997). Essentially, STPS adopted a quasi-experimental approach in which two groups of enterprises were followed over time – one group that benefited from the CIMO program and a control group that did not – to measure the impacts of CIMO on enterprise and worker performance. Section IV reports the findings for our re-examination of the data, where production functions were estimated that fully exploited the panel (longitudinal) nature of the firm-level data to measure the net impacts of program participation on productivity growth, taking into account potential biases from self-selection into CIMO. The paper concludes in Section V with comments on methodological and policy lessons gleaned from this exercise.

2
effects. It therefore serves as a check on reporting bias, to ensure that individuals who attended training are not just reporting that they do more of every perceived desirable financial behavior.

Table 4 examines whether the increase in knowledge about the costs of remitting lead to changes in behavior. We see that in the short-term, assignment to training leads to the Pacific Island and East Asian migrants being more likely to use information to compare remitting costs, and to be more likely to use the internet to compare costs, with no impact on keeping track of monthly expenses. However, the strongest impacts are found in the month right after the training, with no impacts on the use of the internet at 3 or 6 months. The impacts are positive, but not statistically significant for the Sri Lankan sample, which may reflect imprecision due to the smaller sample size, or the impacts of differential attrition by treatment status, or perhaps that the effects are weaker for this group since the majority already used one of the cheapest methods anyway.

# **3.3 Impact on Remitting Frequency and Amount**

Next we examine whether the financial literacy training had any impact on either the likelihood of sending remittances, or on the total amount remitted. Ex ante it is not clear what direction we should expect the effect of financial literacy training to be – the content on bundling transactions together into a few, less frequent, larger transactions would be expected to reduce the frequency of remitting while having no impact on the total amount sent, whereas content which stresses cheaper methods of remitting may lead individuals to be more willing to make smaller transactions and therefore increase frequency, and potentially also lead to individuals sending more remittances (Gibson et al, 2006; Aycinena et al, 2011).

Table 5 shows that the financial literacy training had no significant impacts on either the likelihood of remitting, or on the total amounts remitted for any of the three groups. Moreover, in some cases these are relatively precise zero effects. For example, averaging observations over all four follow-up surveys for the Pacific Island sample, the point estimate on the monthly frequency of remitting is -0.02, with a 95 percent confidence interval of (-0.077, +0.036). That is, we can rule out that the training had large positive effects on remitting frequency, and also rule out large negative impacts. Remittance amounts have more variation, but even so, we have a point estimate for the Pacific Island sample of an increase of NZ$4, with a 95 percent confidence 16
from duties collected (most recent studies employ this strategy, see Romalis 2007, p.424, Santos-Paulino and Thirlwall 2004, p.F51, and Clausing 2001, p.684).<sup>10</sup> The EC’s tariff schedule for alternative beneficiary groups does not vary across individual member countries of that group, thus it is sufficient to use one beneficiary country’s tariff schedule to infer the profile of market access that this group of countries faces in the EC market. For the ACP group, I consider the EC’s tariffs for Cote d’Ivoire to be representative for ACP members. This choice is as good as any since tariffs do not vary among ACP countries.<sup>11</sup> While the same holds in principle for GSP members as well, here the tariff profile differs to the extent that HS 6-digit tariffs are a trade-weighted average of HS 8-digit data. Information to correct for ‘under-utilization’ of preferences, to the extent possible, is taken from CEC (2003, Table T6) and CEC (2004, Table 1).<sup>12</sup> Table (1) collects summary statistics of all the variables. It is apparent that the dependent variable, the ratio of imports, exhibits tremendous variation as compared to the one of the regressors.

# **{ Table (1) about here }**

As residual GSP beneficiaries I consider Brazil, China, India, Thailand, Vietnam, Colombia and Tunisia, for which the hypothesis of intra-developing country trade diversion is tested. While there are certainly many more such countries which could have been selected, the country sample is chosen with a view to minimize missing observations due to zero trade flows. Recall that the estimation strategy requires that for any given tariff line a country must record exports to the EC _and_ to the US. Moreover, it is worth

> 10Under the current EC reporting regime data on duties collected per tariff line and country is not available. Even if it would be, duties from imports with and without GSP treatment would be lumped together (unless reported separately by import program), which renders this kind of calculation impossible for the EC.

> 11In the ancillary estimation of LDC–GSP diversion, I employ Bangladeshi tariff rates; Bangladesh is a LDC that is not simultaneously a member of the ACP group.

> 12The attempt to account for utilization rates in a fully detailed and country-specific manner is thwarted by the confidential handling of this type of data by the European Commission.

11
_The activities of an individual or a group aimed at initiating economic activities in the formal sector under a legal form of business._ However, few countries (i.e Denmark) maintain “active” registries that annually confirm that registered firms are still operating. Therefore, official registration data includes both businesses incorporated for economic activities, as well as those incorporated for tax or other non-business purposes (e.g. Shell companies). An additional limitation of the data is that it does not report the number of closed businesses. The reasons differ from country to country, but are mainly due to the fact that the registrars generally have no enforcement mechanisms to obligate businesses to report closures. Although the number of closed companies is essential to paint a clear picture of the economic and entrepreneurial activities of a country, it is not yet feasible to obtain comparable data (Nuci, 1999).

The WBGES database includes data on formal business registrations in 84 countries. The information was collected from business registries and other government sources via a survey and follow-up phone calls.<sup>4</sup> These other sources include statistical agencies, tax and labor agencies, chambers of commerce, and private vendors (such as D&B), which were used only when business registry data were unavailable or nonexistent.<sup>5</sup> The survey collected data on the year-end stock of total registered firms and new firms registered in the calendar year from 2003 to 2005.<sup>6</sup> Importantly, the definition of entrepreneurship includes only businesses that operate in the formal sector and to maximize comparability across countries of different legal and economic systems, the database includes only limited liability corporations (LLCs).

For the purpose of the analysis in this paper, the data is used to calculate the “corporate” entrepreneurship rate, which is defined as the number of newly registered companies as a percentage of the adult population.

> 4 The complete survey data and companion papers are available at:

> <u>http://www.ifc.org/ifcext/sme.nsf/Content/Entrepreneurship+Database.</u>

> 5 A complete list of sources is provided in Klapper, Amit, Guillen, and Quesada Delgado (2007).

> 6 For additional information, see Klapper and Quesada Delgado 2007, and Klapper, Amit, Guillen, and Quesada Delgado 2007.

5
(figure 7b) suggests little in the way of growth convergence clusters. The central mass is fairly tightly aligned along the 45 degree reference in both the pre- and post- 85 periods. We rerun the kernels with the other two neighborhood measures and again find no obvious visual regularities.

The overall Moran I using connectivity and the regional bands suggests a degree of spatial dependence in the pre-liberalization period, but over time this dependence has decayed-there has been a de-spatialization of growth rates in Mexico. Using the distance from the US neighborhood measure, however, we see no spatial dependence until the 19942002 period, coinciding with NAFTA.

Since this is the only evidence of spatial dependence in the post-reform period, the Moran scatterplots are calculated using this measure of neighborhood. The local Morans (table 6, figures 10a and b) at first glance seem to suggest that spatial growth patterns are dominated by the north/south dichotomy. In the 1970-85, all measures suggest positive co movements among border states with their neighbors in the third quadrant of _low_ growth states among _low_ growth states, but no other clusters. This border cluster disappears in the post-liberalization period, but Chiapas, Guerrero, Oaxaca Tlaxcala and Veracruz replicate its behavior in the post-trade liberalization period: low growth states among a group of low growth states. Additionally, the connectivity based Moran suggests that Mexico/DF aggregation significantly under performs in the early period in a time when its neighborhood was doing much better. These findings are consistent with the income convergence observed before liberalization and the divergence after. What is striking, however, is that we do not observe a northern pole of growth in the post- liberalization period as a whole with any of our definitions of space. Instead, there is mild evidence of a central cluster of high growth in the states of Aguascalientes and Guanajuato.

Dividing the post-85 period into post-GATT and post-NAFTA sub-period yields consistent but stronger results (figures 9a and b). During the first sub-period, the only major development is the extremely poor performance of southern states, especially, Chiapas, Veracruz, and Tlaxacla. Although some southern states such as Puebla were growing above average, other poor Central and Northern states like Hidalgo Nayarit and Zacatecas performed below average while rich states such as Aguascalientes, Quintana Roo and Chihuahua grew steadily. These tendencies are consistent with increased income dispersion 17
4,294 outlets). However, 286 of the remaining 4,281 outlets were found to be permanently closed by 2016 for reasons including destruction in floods, population shifts, or perennial lack of water in the channel.<sup>22</sup> Of the closed outlets, 29 occurred on 4 channels on which every other outlet was also closed, leaving us with 465 open channels. There are 103 open channels on which at least one selected outlet was closed, which is not a problem for us empirically, but in 15 cases the channel had no head outlets and in 2 cases no tail outlets. This leaves us 448 channels with _both_ head and tail outlet data, which our empirical strategy requires (see Appendix Table C.1 for channel characteristics by division). That we lose only two channels — to tail closure suggests that selection bias i.e., less water theft on average in observed — channels is unlikely to be a serious issue.

# **4.1.1 Lobbying influence variables**

Data are available on nearly a quarter-million irrigators on our final sample of 448 channels. Rather than consider the distribution of individual landholdings, however, we aggregate across brothers to obtain total “family” landownership. In particular, we sum (canal irrigated) land owned on each outlet across individuals sharing the same father’s name, yielding almost 150,000 family level observations. Given inheritance norms in Pakistan, patrimonial land is typically controlled by the sons. Using individual landholdings would imply that influence (as measured by economic stake) along a channel is diluted by a factor of _N_ once landownership passes from a father to his _N_ sons, which strikes us as extreme since, at a minimum, brothers are likely to cooperate on land-related matters and in many cases even designate one of their own as operator of their joint holdings. Figure 3 illustrates the distribution of family landholdings on all head outlets and all tail outlets pooled together. Average family landownership on head outlets is 8.4 acres, compared to 8.9 acres on tail outlets; the 98th percentiles are 45.8 and 47.5 acres, respectively. Thus, families with large

> 22In some cases, outlets had actually been closed years ago but the outlet lists provided to us by the irrigation department and used for sampling had not been updated.

17
# III. THE BASIC THEORETICAL MODEL

Based on the foregoing discussion,<sup>a realistic model of</sup> pesticide use in cotton (for the Guntur<sup>area) must incorporate the</sup> following key aspects: i) Positive externalies arising from<sup>an individual farmer's</sup> control of the primary pest on his field.

ii) Negative externalities within<sup>cotton, arising from the build-</sup> up of pest resistance.

iii) Negative externalities arising<sup>due to the migration of</sup> resistant pests, resulting in damage<sup>to non cotton crops in the</sup> Guntur area as well as to cotton and<sup>other susceptible crops in the</sup> more distant areas.

iv) An explicit consideration<sup>of Integrated PestManagement</sup> strategies.

An important issue which must be<sup>resolved is, what should be</sup> the length of a farmer's (and<sup>thesocial</sup> Dlanner's) Rlannina hokizon? Bioassay experiments have<sup>clearly shown that the build up</sup> of pest resistance takes place over several<sup>generations of pests.</sup> Evidence collected by entomologists<sup>indicates that as many as five</sup> generations of H. armigera can complete<sup>their life cycle in a</sup> single cotton growing season (as many<sup>as eight in Punjab, ICRISAT</sup> Symposium volume, 1981). Furthermore, the<sup>current season's level of</sup> resistance of the pests will depend<sup>upon the previous season's</sup> total "stock" of resistant pests. Thus<sup>to get the true social</sup> optimum, the model must be solved as<sup>a multiperiod one giving</sup> explicit consideration to the inter<sup>generational build up of pest</sup> 17
|**Table 12b. Shares of Busi**|**ness Services Sec**<br>_ad-valorem equiva_|**tors in the Re**<br>_lent, %_|**gions of Rus**|**sia Captured**|**by Multination**|**al Firms**||National|
|---|---|---|---|---|---|---|---|---|
|**Sector**|Northwest|Central|South|Volga|Urals|Siberia|Far East|<br>Average|
|Railway transportation|6.0|3.1|3.8|6.0|1.7|2.2|6.0|3.0|
|Truck transportation|10.0|6.5|6.2|10.0|3.1|4.7|10.0|5.0|
|Pipelines transportation|6.0|4.8|4.6|6.0|1.8|3.4|6.0|3.0|
|Maritime transportation|70.0|40.6|45.6|70.0|15.1|28.3|70.0|35.0|
|Air transportation|50.0|34.8|29.9|50.0|15.5|26.2|50.0|25.0|
|Other transportation|8.0|5.3|5.0|8.0|2.5|4.0|8.0|4.0|
|Telecommunications|30.0|19.8|18.8|30.0|8.8|15.1|30.0|15.0|
|Science & science servicing|20.0|8.9|10.0|20.0|7.0|8.8|20.0|10.0|
|Financial services|20.0|9.3|9.0|20.0|3.8|6.6|20.0|10.0|

47
|sole proprietor dummy|-0.543|0.115|0.0%|
|---|---|---|---|
|close corporation dummy|-0.220|0.087|1.1%|
|Manufacturing|-0.181|0.104|8.4%|
|VAT|0.232|0.120|5.3%|
|PAYE|0.227|0.101|2.5%|
|Adj. R2|0.438|||
|Mean of the dependent variable|7.768|||

|**Dependent Variable: Sensitivity analysis: LN Total cost of tax**<br>**board)**|**compliance (**|**-30% across**|**the**|
|---|---|---|---|
||Coeff.|Std. Error|Sig.|
|(Constant)|6.898|0.361|0.0%|
|LN full-time employees|0.088|0.035|1.3%|
|LN of q55 after imputed values were introduced (imputed "no|0.193|0.027|0.0%|
|answer")||||
|Share of activities completely outsourced|-0.634|0.130|0.0%|
|Share of activities partially outsourced|-0.123|0.126|33.1%|
|Guateng provincial dummy|0.178|0.075|1.8%|
|Western Cape provincial dummy|0.093|0.098|33.8%|
|sole proprietor dummy|-0.550|0.115|0.0%|
|close corporation dummy|-0.231|0.087|0.8%|
|Manufacturing|-0.176|0.104|9.3%|
|VAT|0.239|0.120|4.7%|
|PAYE|0.222|0.101|2.9%|
|Adj. R2|0.432|||
|Mean of the dependent variable|9.714|||

**Dependent Variable: Sensitivity analysis: LN Total cost of tax compliance (-40% across the board)**

||Coeff.|Std. Error|Sig.|
|---|---|---|---|
|(Constant)|6.774|0.362|0.0%|
|LN full-time employees|0.089|0.035|1.3%|
|LN of q55 after imputed values were introduced (imputed "no|0.194|0.027|0.0%|
|answer")||||
|Share of activities completely outsourced|-0.546|0.130|0.0%|
|Share of activities partially outsourced|-0.082|0.126|51.8%|
|Guateng provincial dummy|0.182|0.075|1.6%|
|Western Cape provincial dummy|0.105|0.098|28.4%|
|sole proprietor dummy|-0.558|0.116|0.0%|
|close corporation dummy|-0.243|0.087|0.6%|
|Manufacturing|-0.171|0.105|10.3%|
|VAT|0.246|0.120|4.1%|
|PAYE|0.216|0.101|3.4%|
|Adj. R2|0.424|||
|Mean of the dependent variable|9.656|||

44