rafmacalaba/datause-encoder-data huggingface dataset:
WPS 3205

# **Poor People's Knowledge**

# **Helping Poor People to Earn from Their Knowledge**<sup>**1**</sup>

by J. Michael Finger

## **Abstract**

How can we help poor people to earn more from their knowledge rather than from their sweat and muscle? This paper summarizes a collection of essays that investigate the promotion of “poor people’s knowledge”—promoting the innovation, knowledge, and creative skills of poor people in poor countries, and particularly improving the earnings of poor people from such knowledge and skills. The collection is a modest attempt to look at the issue from the perspective of the economic value of poor people’s knowledge. It is about the knowledge poor people own, create, and sell rather than about what they buy. It is a collection of stories of attempts to increase poor people’s earnings from their knowledge.

The essays call attention to a broader range of knowledge that has commercial potential in developing countries, and bring an economic dimension into the discussion of traditional knowledge. They highlight the incentives for and concerns of poor people— which may be different from those of corporate research, Northern nongovernmental organizations (NGOs), or already successful entertainment stars. The essays demonstrate that the best answer is sometimes commercial rather than legal (for example, obtaining a formal patent or copyright protection), although in some instances standard legal approaches have been effective and it is useful to identify the problems in which legal innovation is really needed. In addition, there are many income-earning (rather than income-using) dimensions of culture.

### World Bank Policy Research Working Paper 3205, February 2004

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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org.

1 _Poor People’s Knowledge: Helping Poor People to Earn from Their Knowledge, e_ dited by J. Michael Finger and Philip Schuler. World Bank and Oxford University Press, forthcoming 2003.
perhaps due to the need for at least one woman in the household to be available to assume responsibilities such as cooking and cleaning and looking after children. Relatedly, a woman is more likely to work outside the home for pay if there is presence of adolescent girl(s) in her household, indicating that young girls could act as substitutes for working women’s domestic responsibilities.<sup>32</sup>

**Table 7. Explanatory power of “rational” factors on women’s work outcomes vs. that of social norms**

||**PAID WORK**|
|---|---|
|PNB Index - HH Roles|-0.08**<br>(0.03)|
|SNE Index - HH Roles|-0.05<br>(0.04)|
|PNB Index - Public Space|-0.01<br>(0.03)|
|SNE Index- Public Space|-0.01<br>(0.03)|
|Years of education|0.00**<br>(0.00)|
|Log of household's total income minus working females'|-0.03***|
|earned income (NPR)|(0.01)|
|Presence of other working-age women in HH in labor force|-0.12***<br>(0.03)|
|Indicator for adolescent girl(s) in respondent's HH|0.07*<br>(0.04)|
|Respondent is aware of non-network methods of job search|0.01<br>(0.03)|
|Constant|0.64***<br>(0.07)|
|Observations|2,000|
|Adjusted R-squared|0.05|
|Regional FE|YES|

_Notes_ : (1) Apart from the “rational” factors included and shown in the table, no additional variables were included as controls. (2) SEs clustered at the ward level. (3) Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

# What explains liberal beliefs around social norms?

What predicts liberal personal beliefs and social normative expectations among survey respondents? We explore this question by looking at the association between beliefs and norms and various observable household and individual-level characteristics of the respondents.

We find that a higher level of education is negatively and significantly correlated with conservative beliefs and social expectations, but only when it comes to norms around women in the public space ( **Table 8** ). This suggests that more educated respondents are not more likely than those less educated to hold more liberal beliefs and expectations around men and women’s household roles. However, they do tend to expect lower sanctions for norm transgression overall, compared to their less educated counterparts.<sup>33</sup>

> 32 In our sample, 35.05 percent of respondents have adolescent girl(s) in the household, and 26.65 percent of respondents report the presence of other working-age women in the household who are in labor force (excluding those studying).

> 33 We repeat the same OLS regression separately for women and men ( **<u>Tables A.13, Annex A</u>** <u>).</u>

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# 1. **Introduction**

After decades of neglect, the economics profession has rekindled its interest in geographical phenomena. Much recent work has been devoted to agglomeration effects across regions and countries (e.g. Krugman 1991b, Fujita, Krugman and Venables 1999a, Ciccone and Hall 1996). Apart from research focusing on cities (e.g. Henderson 1974, Lamnpard 1968, Abdel-Rahman 1994, Rauch 1993, Fujita, Krugman and Mori 1999b, Arthur 1988, Glaeser, Kallal, Sheinkman and Shleifer 1992, Ellison and Glacser 1997, Glaeser, Scheinkman and Shleifer 1995), most empirical work has remained at a fairly aggregate geographical level (e.g., Ciccone and Hall (1996), Radelet and Sachs (1998), Hummels (1995), Hall and Jones (1996) on countries; Desmet (1998) on European regions; Barro and Sala-I-Martin (1991) on U.S. states). Little attention has been devoted to more disaggregatel geographical units that have a predominantly rural character, such as villages or counties (see, however, Ciccone and Hall (1996), Ciccone (1997), Fafchamps and Helms (1996), Desmet and Fafchamps (2000)). This is somewhat surprising given that much of traditional economic geography focuses on spatially disaggregated phenomena such as the distribution of cities over space and their relationship with surrounding rural areas (e.g. von Thunen 1966, Isard 1956, Christaller 1966, Losch 1954, Dicken and LLoyd 1990, Jacobs 1969).

There is also little recent work by economists on the spatial distribution of economic activity across space in rural and urban areas of the Third World, in spite of a long tradition of research on regional issues among development economists. This is not to say that there has been no work on spatial issues. The contrast between cities and countryside has long attracted the attention of development economists, to the point that this contrast has become a fundamental organizing concept of all development theory (e.g. Lewis 1954, Harris and Todaro 1970). There has also been a lot of work on work migration, non-farm production in rural areas (e.g., survey by Reardon (1997); for Nepal, see Seddon, Adhikari and Gurung (1999)), and on the spatial 2
**Table 2: Impacts of mental health on other labor and life satisfaction outcomes**

|Dependent variable:|Labor force<br>participation|Permanent job|Skilled<br>occupation|Work in<br>agriculture|Number of work<br>hours per week|Life satisfaction|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Standardized mental health<br>scores|-0.035***|-0.011|-0.032***|0.056***|-10.146***|-0.602**|
||(0.005)|(0.007)|(0.007)|(0.008)|(1.691)|(0.301)|
|_First stage of 2SLS (depende_|_nt variable is stand_|_ardized mental he_|_alth scores)_||||
|Trauma experience* Year<br>after arrival|-0.023***|-0.039***|-0.039***|-0.039***|-0.058***|-0.058***|
||(0.006)|(0.009)|(0.009)|(0.009)|(0.016)|(0.018)|
|Kleibergen-Paap F stat.|35.644|17.692|17.692|17.692|19.635|79.537|
|AR 95-CIs|[-0.059, -0.025]|[-0.039, 0.006]|[-0.145, -0.017]|[0.028, 0.147]|[-20.869, -6.287]|[-1.003, -0.256]|
|Dep. Mean|0.418|0.163|0.135|0.746|32.836|7.597|
|Other controls|Yes|Yes|Yes|Yes|Yes|Yes|
|Individual FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Survey wave FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|7,768|3,687|3,687|3,687|3,687|6,392|
|Number of individuals|2,182|1,609|1,609|1,609|1,609|2,060|

_Notes:_ *** p<0.01, ** p<0.05, * p<0.1. Results of IV-Logit-FE model (marginal effects) in Columns (1)-(4) and IV-FE model in Columns (5)(6). Standard errors in parentheses are clustered at the individual level. Control variables include age group dummy variables, marital status, household size, language skills (listening, speaking, reading, and writing), residence area, and home ownership. Mental health scores are the sum of the 6-item Kessler Psychological Distress Scale (K6), with a higher score indicating worse mental health. The scores are standardized to have a mean of zero and standard deviation of one. The critical value of the F-test from Stock and Yogo (2005) is 16.38. Permanent job is defined as working fulltime/parttime with permanent contract (the reference group is fixed-term contract and casual employment). Skilled occupation is defined as jobs with occupational scales above medium.

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marital status, relation to the household head, and whether the person works in the public sector. _T_ corresponds to a vector of household controls, such as proportion of children in the household, proportion of elderly, proportion of potential beneficiaries to the SR, proportion employed, average education, average age, and socio-economic strata level. _S_ captures controls for the employment sector, as described in Appendix Table S3.

We are interested in _θ_ , the parameter for the indicator variable _post_ . A positive _θ_ indicates an increase in informal employment after the onset of the SISBEN interviews. We report the estimates of equation 1 in panel A of Table 3, where we show specifications including different sets of controls in each column listed in the note of the table. The estimates show a positive and significant effect of _post_ , with an increase in informality between 4.1 and 5 percentage points.<sup>19</sup> All specifications are clustered at the municipality-year level.<sup>20</sup> Next, we construct a proxy for the Poverty Index Score to assess whether the positive increase in informal employment is concentrated among the people who are eligible for the SR.

The variables needed to construct the Poverty Index Score calculated in the SISBEN are not available in the household survey, so we use a geographical socio-economic strata (SES) indicator as a proxy. When using the SISBEN dataset, we find that this indicator is a strong predictor of eligibility (significant at the 1% level). We identify as eligible people living in SES levels 1 and 2, and, for consistency with the SISBEN implementation process, we limit the sample to people living in strata levels targeted by the SISBEN (1-3). We estimate the following regression:

> 19To explore whether the effects are driven by self-employed workers or employees, we split the sample by each of these two groups, and we find consistent results across the two groups.

> 20We thank Josh Angrist for providing direction on the appropriate clustering level. The results clustered at the municipal level are consistent with those presented here but are less significant for panel C.

15
**Table 6. Engle-Granger Co-integration Results**

|Variable|Coefficient|Std. Error|t-Statistic||
|---|---|---|---|---|
|Constant|2.604|0.504|5.163||
|log(M1t)|0.415|0.020|21.272||
|log(e,)|0.174|0.046|3.784||
|log(PC,)|-0.253|0.051|-4.964||
|d,|0.107|0.052|2.042||
|R-squared|0.951|Mean depend|ent var|4.795|
|<br>Adjusted R-squared|0.947|<br>S.D. depende|<br>nt var|0.214|
|<br>S.E. of regression|0.049|<br>Akaike info cri|<br>terion|-5.940|
|Sum squared resid|0.126|Schwarz criter|ion|-5.761|
|Log likelihood|93.423|F-statistic||251.375|
|Durbin-Watson stat|0.596|Prob(F-statist|ic)|0.000|
|**Variable**|**Coefficient**|<br>**Std. Error**|**t-Statistic**||
|Constant|1.981|0.411|4.823||
|log(M2,)|0.392|0.015|25.650||
|log(e,)|0.257|0.038|6.838||
|log(PCt)|-0.225|0.042|-5.366||
|d,|0.122|0.044|2.764||
|R-squared|0.965|Mean depend|ent var|4.795|
|Adjusted R-squared|0.962|S.D. depende|nt var|0.214|
|<br>S.E. of regression|0.041|<br>Akaike info cri|<br>terion|-6.282|
|Sum squared resid|0.089|Schwarz criter|ion|-6.103|
|Log likelihood|103.158|F-statistic||359.022|
|Durbin-Watson stat|0.620|Prob(F-statis|tic)|0.000|
|**Variable**|Coefficient|**Std. Error**|t-Statistic||
|Constant|2.016|0.437|4.615||
|log(M3,)|0.411|0.017|24.065||
|log(et)|0.227|0.040|5.647||
|log(PC,)|-0.242|0.045|-5.363||
|d,|0.118|0.047|2.528||
|R-squared|0.961|Mean depend|ent var|4.795|
|Adjusted R-squared|0.958|S.D. depende|nt var|0.214|
|S.E. of regression|0.044|Akaike info cri|terion|-6.164|
|Sum squared resid|0.101|Schwarz crite|rion|-5.985|
|Log likelihood|99.806|F-statistic||317.734|
|Durbin-Watson stat|0.578|Prob(F-statis|tic)|0.000|

Note: d is a dummy variable included to capture the sharp increase in inflation in March 1997.

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suggests that it is not possible to discuss the relation between growth and poverty without discussing its effect on distribution. Has the rise in inequality beea so severe in the past that the percent in poverty could have risen and the average living standards among the poor diminished? Such results would have required severe inequality trends indeed, but it is important to understand that the forces driving inequality are similar to the forces driving poverty statistics. While rising inequality may not necessarily imply increasing poverty, it may imply a slow rate of escape from poverty. Thus, Section It will dwell at length on 19th century experience with inequality among the industrializing NICs of that time. This is a story about relatives, that is, the performance of the poor relative to the rich. Central to that story is understandirg the forces of supply and demand that kept the wages of the unskilled poor low. At the end of that section, we will also explore what happened to the living standards of the poor. This is a story about absolutes, that is, the rate of poverty reduction. It appears that the same forces of supply and demand which drove inequality also conditioned the rate of poverty eradication.

It should also be stressed that modern economic growth can affect poverty in both direct and indirect ways. The direct influence has already been stated: if incomes of the poor rise along with the average, then poverty can be said to have diminished. The indirect influence takes account of the fact that much of the poverty which we observe in both the 19th century and today occurs at predictable stages in an individual's life cycle. The incidence of poverty is greatest among those who are not full income earners like the aged, or among those subject to crisis like the sick or widowed. It is a mistake to infer that higber incomes have no indirect impact on such individuals who are cut off from the market economy. After all, even the working poor who receive higher incomes should be better able to save more for crises and old age. The

-3-
# **2 Secured Transactions: Legal and Institutional Framework**

- _2.1 Snapshot at Modern Secured Transactions Systems_

A modern and efficient secured transactions system should be built around the following principles or pillars that should be reflected in a secured transactions law:

- **Scope:** the types of legal structures that can be used to secure obligations (e.g. security interest, pledge, mortgage, etc.); the types of transactions that should be considered within the scope of the law (loans secured with movable property, retention of title, financial leasing, assignment of receivables, consignments, etc); the types of movable property that may be used as security; and the types of debtors who may give security in movable property.

- **Creation:** the legal requirements for giving and taking a right against movable property to secure an obligation.

- **Priority:** the rules that determine the relative rights among conflicting claims against movable property.

- **Publicity/registration of security interests:** the means of making a claim against movable property transparent to third parties, commonly provided by registration in a public registry, by taking possession or control of the movable property, by direct notice, or by other means. An efficient registry is characterized by having a single electronic database with all information about existing security interests in movable property, accessible to the general public in real time for a reasonable fee.

- **Enforcement:** the process for enforcing a claim against movable property when the debtor defaults on the secured obligation. Enforcement mechanisms should include the possibility of enforcing out of court.

The following sections provide an overview of standard modern international practices in these different areas and how do they compare with the current secured transactions frameworks in MENA. The main sources of data contained in the report are related to (i) internationally accepted practices on modern secured transactions systems (The World Bank Principles on Insolvency and Creditor’s Rights and the UNCITRAL Legislative Guide on Secured Transactions); (ii) Data survey from the World Bank Enterprise Surveys, Doing Business Report and SME Lending Surveys to Financial Institutions in MENA; (iii) country specific diagnostic reports from the World Bank Group and other multilateral organizations. Given the complexity of providing an overview of the secured transactions system in each country limiting the paper to a manageable size, the report focuses on general principles and how they are applied in the region.

9
(1999) conclude that there are usually negative effects of rewards on task interest and satisfaction in a similar meta-study. The current study differs from much of the work in psychology by estimating the impacts of external rewards in a real-world context rather than in laboratory experiments. We ultimately find evidence consistent with the first view: the introduction of the scholarship did not reduce the performance of either eligible (girl) or ineligible (boys) students in the program schools, up to a full year after the scholarship competition, nor did it reduce their stated enjoyment of school activities.

The remainder of the paper proceeds as follows. Section 2 provides background information on schooling in Kenya and on the scholarship program. Section 3 presents a model of incentives and study effort. Section 4 discusses the data set and sample attrition, and Section 5 presents the estimation strategy and the empirical results. The final section concludes.

# **<u>2. The Girls Scholarship Program</u>**

# **<u>2.1 Schooling in Kenya</u>**

Schooling in Kenya consists of eight years of primary school followed by four years of secondary school. While most children enroll in primary school – approximately 85% of children of primary school age in western Kenya are enrolled in school (Central Bureau of Statistics 1999) – there are high dropout rates in grades 5, 6, and 7, about one-third finish primary school, and only a fraction of these students enter secondary school. The dropout rate is especially high for teenage girls.<sup>2</sup> Admission to secondary school depends on performance on the official Kenya Certificate of Primary Education (KCPE) exam in Grade 8, and students take the exam quite seriously. To prepare for the KCPE, students in grades 4-8 typically take standardized exams at the end of each school year – although these exams are sometimes canceled, for example, due to teacher strikes or fears of violence during national election years. End-of-year exams are standardized in each district and test students in five subjects, English, Math, Swahili, Science, and Geography/History. Students must pay a fee to take the exam – we discuss implications of this fee below. Kenyan district education offices have a well-established system of exam supervision, with exam proctors 5
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32 So far, I have only referred to _indirect_ evidence – “smoking guns” – of inefficiencies in the Chinese growth path. In principle, these inefficiencies should also be reflected in estimates of total factor productivity (TFP) growth in the context of aggregate production functions – although calculations of this variable are probably even more hazardous in China than in developed countries.<sup>54</sup> Most such calculations indicate yearly rates of TFP growth in the interval 3-4 percent during the reform period. However, we may want to confine the calculation to contributions to output growth through better technology and organization in individual firms, sometimes called “multifactor productivity” (MFP) growth. In this case, it is reasonable to exclude both reallocation gains across sectors (basically shifts of labor from agriculture to other sectors) and improvement in human capital through education and training. Each of these two factors is often estimated to have contributed nearly one percentage point (per year) to the output growth rate in China during the reform period.<sup>55</sup> When these factors are excluded from calculations of TFP growth, we obtain figures (of MFP growth) approximately in the interval of 1.5 to 2.5 percent per year during the reform period.<sup>56</sup> Compared with the pre-reform decades, for which MFP growth seems to have been close to zero (OECD, 2005a), these figures appear to be fairly good. However, the picture requires modification in important respects. First, part of MFP growth during the reform period reflects once-and-for-all efficiency improvements in connection with the agricultural reforms in the period 1979-1984, as well as temporary productivity spurts in other sectors in the mid-1990s when prices were deregulated. Second, it would seem that much of the improvement in technology and organization in the manufacture sector, so far, is the result of the entry and expansion of non-mainland firms rather than improvements in a broad spectrum of domestic firms (Tseng and Zebregs, 2002; OECD, 2002, pp. 195-230).<sup>57</sup> Some

> 54 Indeed, Holz (2005b, section 4a) argues that there is no stable aggregate production function for China for the reform period.

> 55 For estimates of reallocation gains arising from the contraction of agriculture see, for instance, Borensztein and Ostry (1996); Woo (1998); and OECD (2005a, Table 1:4). Kuijs and Wang (2006b) conclude that these reallocation gains have gradually fallen in recent years; they argue that the contribution was 0.8 percentage points per year in the period 1993-2003.

> 56 For surveys of studies of TFP and/or MFP growth, see, for instance, Heytens and Zebregs (2003); Blanchard and Giavazzi (2005); OECD (2005a); and Wu (2006).

> 57 Whalley and Xin (2006) estimate that such firms contributed no less than 40 percent of China’s GDP growth in 2003 and 2004.