rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 4 Average proportion (%) of intra-day trading volume for each type of investor**

This table reports the average proportions (%) of intra-day traded values for each of three classes of investors and classified by level of Active Share. Passive (active) investors is defined as those with Active Share below (above) 60%. The proportions are relative to the total trading value for the interval (Panel A) and relative to the total traded value of the day by each group (Panel B). The sample in Panels A and B include the period from February 9, 2012, to January 30, 2016, when the Colombian Stock Exchange synchronized its trading session with the New York Stock Exchange.

|Domestic|Individuals|Domestic|Institutions|Fore|ign||
|---|---|---|---|---|---|---|
|Trading intervals<br>Passive|Active|Passive|Active|Passive|Active|All|
|Panel A.|Relative to the|trade val|ue of the inte|rval|||
|9:30-10:30<br>6.3|30.0|29.9|20.9|5.3|7.5|100.0|
|10:30-11:30<br>6.0|26.1|32.8|19.5|6.9|8.8|100.0|
|11:30-12:30<br>5.8|24.0|34.0|19.5|7.7|8.9|100.0|
|12:30-13:30<br>5.6|23.7|33.6|19.4|8.4|9.2|100.0|
|13:30-14:30<br>4.9|22.9|31.4|19.6|10.3|10.8|100.0|
|14:30-15:30<br>5.5|23.6|29.8|18.6|12.0|10.6|100.0|
|15:30-15:55<br>6.0|24.8|30.2|19.0|10.7|9.2|100.0|
|Closing batch<br>5.4|20.9|23.2|10.7|30.9|9.0|100.0|
|Panel B. Relative|to the traded|value of t|he day by in|vestor gro|up||
|9:30-10:30<br>21.6|22.5|17.8|21.5|9.7|15.3|18.2|
|10:30-11:30<br>17.2|17.0|18.6|16.9|10.5|17.6|16.9|
|11:30-12:30<br>14.8|14.5|17.9|15.7|9.6|15.9|15.6|
|12:30-13:30<br>11.3|11.4|13.8|12.6|8.9|12.0|12.3|
|13:30-14:30<br>6.7|7.1|7.8|8.1|6.2|9.0|7.6|
|14:30-15:30<br>9.1|9.0|8.1|9.3|8.6|9.8|8.8|
|15:30-15:55<br>7.9|7.5|7.1|7.5|6.7|7.4|7.3|
|Closing batch<br>11.4|11.0|9.0|8.4|39.8|13.0|13.3|
|Panel C. Foreign|passive funds|traded va|lue in the clo|sing batc|h||
|2009|2010|2011|2012|2013|2014|2015|
|Relative to interval<br>7.7|12.8|22.1|27.7|34.5|41.3|39.6|
|Relative to day<br>28.2|32.5|36.3|34.9|43.0|39.3|41.2|

29
21 PHN 1991 Sector Review attention to these issues in most PHN operations has broadened in sope sufficiently, the quality and depth of institutional development work in the sector could benefit from further improvement. A review of the sector analyses contained in the SARs for each of the 28 operations approved during FY91 reveals that, in some cases, institutional assessments were not undertaken fully adequately as a part of upstream sector or project identification work. In some SARs, the treatment of institutions and organizations is more descriptive than analytical. Sustainability and long term strengthening of sector-wide institutions are not always sufficiently addressed. Sometimes overlooked are: institutional alternatives for service delivery and for IEC activities, the incentive framework for long-term organizational performance and interorganizational collaboration and issues of leadership and stakeholder support, aU of which are essential for sustainability. Yet _all_ 28 projects in their "benefits and risks" sections note that weak institutional and managerial capacity constitutes the greatest risk to project success and sustainabUity. The constraints to improving PHN treatment of management and institutional issues are as follows:

## c. _Lack of Thme_

3.46 Detailed attention to institutional and management issues takes time and competes with other rigorous input requirements for lending, supervision and sector work, all of which have very tight coefficients and which are closely monitored by management.

3.47 Chapter IV includes some suggestions on how these constraints might be alleviated.

# _a. Number and Skills Mix of PHII Staff_

3.44 The growth in PHN staff over the last five years has not kept pace with the dramatic growth in PHN operations, documented in Chapter II of this report. Furthermore, as the scope and complexity of institutional/managerial issues continue to grow, so will the need for management specialists working on the PHN sector. A review of the composition of preapprai-al and appraisal missions for the FY91approved operations reveals a deficiency in management and institutional development expertise.

## _b. Absence of Standards and Guidelrnes_

3.45 There are currently no official standards or guidelines in the Bank for analyzing and addressing institutional/organizational and management issues in the PHN sector, which could guide task managers in undertaking such work and Bank management in monitoring and evaluating it.
McKenzie, David (2017) “Identifying and Spurring High-Growth Entrepreneurship: Experimental Evidence from a Business Plan Competition”, _American Economic Review_ 107(8): 2278-2307.

McKenzie, David and Anna Luisa Paffhausen (2017) “Small Firm Death in Developing Countries”, _Review of Economics and Statistics,_ forthcoming.

McKenzie, David and Dario Sansone (2017) “Man vs Machine in Predicting Successful Entrepreneurs: Evidence from a Business Plan Competition in Nigeria”, _World Bank Policy Research Working Paper_ no. 8271 McKenzie, David and Christopher Woodruff (2008) “Experimental evidence on returns to capital and access to finance in Mexico”, _The World Bank Economic Review_ 22(3): 457-482 Rosenzweig, Mark and Christopher Udry (2017) “External Validity in a Stochastic World: Evidence from Low-Income Countries”, Mimeo. Yale.

Samphantharak, Krislert and Robert Townsend (2018) “Risk and Return in Village Economies”, _American Economic Journal: Microeconomics_ 10(1): 1-40.

Savva, Nicos and Niyazi Teneri (2015) “The Role of Equity, Royalty and Fixed Fees in Technology Licensing to University Spinoffs”, _Management Science_ 61(6): 1323-1343.

Singh, Nikita and Myshkin Ingawale (2014) _The Unreasonable Fellows_ . Random House India.

24
WPS 3295

# **The Home as Factory Floor: Employment and Remuneration of**

# **Home-based Workers**<sup>**1**</sup>

Wendy Cunningham and Carlos Ramos Gomez The World Bank _Home-based work, defined as non-professionals who perform market work from their homes, is an increasingly recognized form of employment in Latin America. The majority of the research on this segment of the labor force relies on small sample, qualitative data, which find that home-based workers are women, children, and adults with disabilities with low skills who work long hours for low wages. Using a large random sample, control groups of non-home-based workers, and including men in the analysis, this paper examines the home-based work sector in Brazil, Mexico, and Ecuador in 1999. The results show that in all three countries, women are over-represented among home-based workers, particularly older women, those with low levels of education, and those with children or spouses, unlike men for whom these factors do not matter. Female homebased workers earn 25-60 percent less per hour than do non-home-based working wome and they work one-third to one-half as many hours each week. Home-based working men, on the other hand, earn 0-17 percent less than do men who do not work from their homes, and they only work 10 percent fewer hours per week. The wage and work hour gaps for women are largely related to marital status, not the presence of children, suggesting that simply being the primary caregiver in the households, regardless of the actual time constraints (children) is the key factor to differences between home-based working women and those who work outside of their homes._

> 1 Prepared for the Latin American and Caribbean Annual Study:  “From Natural Resources to the Knowledge Economy .”  We would like to thank the Bank-Netherlands Partnership Program’s Economic Policy and Gender initiative, which provided funding for this study.  Also, thanks to William Maloney for valuable feedback.  All errors, of course, are the sole responsibility of the authors.
Besley and Burgess assessed the act by using sophisticated econometric methods to estimate a number of effects. They found that output, employment, investment, and productivity in formal manufacturing firms were lower in states that amended the Industrial Disputes Act in a pro-worker direction compared with other states. They also observed that output in informal manufacturing increased in those states, implying an informalization of the economy because of the legislation. Lastly, they estimated that urban poverty was higher in those states that had enacted pro-worker legislation. According to their calculations, urban poverty would have been 11% lower in West Bengal had it not enacted substantial pro-worker legislation, while Andhra Pradesh would have had 12% higher urban poverty had it not moved in a pro-employer direction. In their words (p. 124): “The battle cry of labor market regulation is often that pro-worker labor market policies redress the unfavorable balance of power between capital and labor, leading to a progressive effect on income distribution. We find no evidence of this here – indeed the distributional effects appear to have worked against the poor.” Despite the Besley-Burgess study’s clever design, empirical sophistication, and use of explicit social welfare criteria, it has nonetheless been subjected to a variety of criticisms. A number of these came from Bhattacharjea (2006), who raised points relating to the scoring of individual measures, the aggregation of measures, the omission of certain laws, and so on. These objections caused Bhattacharjea to take an “agnostic” position on the merits and demerits of the act. Anant et al. (2006) have raised other objections: that reading off directly from legal statutes to measure rigidities could be misleading; that the linkages between labor regulations and industrial outcomes might be weak; and that the lack of flexibility in organized employment is attributable only partially to labor laws. They noted as well that the data for the Besley-Burgess study ended just as India’s economic reforms took effect. But after stating these criticisms, they did nothing to improve upon the Besley-Burgess calculations.

A subsequent study that did in fact present new estimates is the paper by Ahsan and Pagés (2007). Building on the Besley-Burgess methods, Ahsan and Pagés distinguished between amendments concerning laws that affect firms’ flexibility in hiring and firing labor from those concerning the procedures and machinery for resolving labor disputes, disaggregated at the two-digit level, and assessed the effect of the increasingly 46
# **1 Introduction**

Economic performance in low-income countries is highly unstable. During 1965 to 1997, the standard deviation of output growth and the frequency of drops in real GDP larger than 3 percent were respectively two and five times larger in low-income countries than in high-income countries. This larger volatility and prevalence of negative shocks can become especially burdensome for lowincome countries because of their low average growth rates and high fraction of population living under poverty.

Among policymakers, external shocks, such as terms-of-trade fluctuations, international conditions, natural disasters, or aid volatility, are often explicitly or implicitly blamed for this volatile performance. Recent reports by the IMF, World Bank, and UNCTAD state that “ _exogenous shocks . . . can have a significant negative impact on developing countries’ growth, macroeconomic stability, debt sustainability and poverty_ ”, “ _low-income countries are particularly vulnerable to natural disasters, terms-of-trade shocks, and other adverse shocks_ ”, and that “ _the level and volatility of world commodity prices are an important influence on economic growth and the incidence of poverty in LDCs_ ”.<sup>2</sup> The focus on external shocks is understandable given some structural characteristics of lowincome countries, particularly the importance of primary commodities on their exports, their higher exposure to natural disasters, and their dependence on aid flows.<sup>3</sup> However, this simple list of structural features does not prove that external shocks are important, either in absolute or relative terms. Internal shocks resulting from conflicts, political instability, and economic mismanagement are a potentially important source of economic volatility, as suggested by the findings of Acemoglu et al. (2003) and Ahmed (2003). Also, the emphasis on external shocks seems to portray low-income countries as simple bystanders whose economic ailments are the result of factors beyond the reach of their policymakers, and gives a somewhat gloomy perspective of the prospects of these countries to achieve a sustainable and stable economic performance without experiencing major changes in

> 2See IMF (2003), World Bank (2004) and Unctad (2002) respepctively.

> 3Primary commodities, whose prices are significantly more volatile than those of industrial goods, represent about 85 percent of low-income countries’ exports, foreign aid represents about 11 percent of GDI for the average LIC, and, according to a widely cited report by the World Bank (World Bank (2000)), between 1990-1998 94 percent of the world’s major disasters occurred in developing countries. This emphasis has also received some support from the academic literature. For example, Easterly et al. (1993) state that: “shocks, especially those to terms of trade, play a large role in explaining the variance of GDP”.

1
Our robustness exercise revolves around three potential sources of biases in our results: the relationship between population attributes and trust; the impact of _non-foreign_ assistance on trust and the nature of reporting bias in our measure of the presence of foreign organizations.

# <u>Trust and Population Attributes</u>

# <u>Risk Aversion</u>

A substantial experimental (both field and lab based) literature studies the relationship between risk aversion and trust; although the general finding from this literature is not conclusive (see for instance, Eckel and Wilson 2004), it is possible that our results could arise from preexisting differences risk-aversion or the way that that the earthquake changed people’s risk attitudes.<sup>14</sup> If the experience of an earthquake increased risk aversion and increases in risk aversion lead to a loss of trust in other locals (relative to outsiders), we would observe the patterns documented above.

In our household survey, we asked respondents to play a hypothetical game (real money was not involved) where they had to select s single scheme from among a menu of risky options. Specifically, we posited that: _In every scheme, you have a 50/50 chance of making a small profit or a big profit. Out of these schemes, which one would you choose?_ The options started from a profit of Rs.50 regardless of the draw (0 risk) increasing in risk and return to Rs.0 with 50 percent probability and Rs.200 with 50 percent probability. The options were ordered in an ordinal fashion to represent higher risks. In Table 11, we add in household choices in this game as indicator variables, increasing in their risk attitudes, to the base specification. Note that there is a drop in the number of observations because 25 percent of our

> 14 For instance, Ben-ner and Putterman (2001): “Consider next the determinants of trusting. The main factors are A’s information about B (and his trustworthiness), A’s experience with trustworthiness in other transactions, and A’s preferences and dispositions, including but not limited to, her willingness to bear risk.”

28
**Figure 2.27 Morocco: Evolution of trade with Sub‐Saharan Africa, 2000‐2017 (In billions of dirhams and percent)**

<!-- Start of picture text --> Billions MAD<br>20 700<br>18<br>600<br>16<br>14 500<br>12<br>400<br>10<br>300<br>8<br>6 200<br>4<br>100<br>2<br>0 0<br>Imports Exports Export‐import coverage<br>%<br><!-- End of picture text --> _Source_ : Ministry of Economy and Finance, Foreign exchange office.

**Figure 2.28 Morocco: Geographical destination and to Sub‐Saharan Africa, 2001‐2017 (Percent of total exports)**

<!-- Start of picture text --> Angola<br>Mali<br>Guinea<br>Nigeria<br>Ivory Coast<br>Equatorial Guinea<br>Ghana<br>Mauritania<br>Senegal<br>0 5 10 15 20<br><!-- End of picture text --> _Source_ : Ministry of the Economy and Finance.

30
sunk costs of entry to produce hysteresis in trade flows. Beginning with the assumption that entry into foreign markets requires exporters to incur some sunk costs, these models demonstrate that temporary changes in market variables, such as exchange rates, can result in permanent changes in market structure and exports because of the entry and exit of exporters. While the hypothesized response in these models is clearly a micro process of entry and exit, empirical tests to date have relied on aggregate or sectoral data on trade flows and prices.

In this paper we develop an econometric model of a plant's decision to export and use it to test one of the key assumptions underlying the theoretical models of sunk cost hysteresis. We utilize micro data for a large group of manufacturing plants in Colombia from 1981-1989 and directly examine the determinants of a plant's export decision for consistency with the theory. The implication of the sunk cost models that we test is that past participation in the export market will have a significant effect on the probability of exporting in the current period. Equivalently, the presence of sunk entry or exit costs will lead to true state dependence in the export decision.

The econometric results, which control for both observed and unobserved sources of plant heterogeneity, indicate that prior export participation has a significant effect on the probability a plant exports. Equivalently, we reject the hypothesis that sunk costs are zero. The empirical results also reveal that the re-entry costs of plants that have been out of the export market for a year are substantially less than the costs of a first-time exporter. Beyond a one year absence, however, the re-entry costs are not significantly different than those ficed by a new exporter. This is consistent with the view that an important source of sunk entry costs for Colombian exporters is the need to accumulate information on demand sources, information that is likely to depreciate upon exit from the market.

While the results indicate that sunk costs are a significant source of export market persistence, both observed and unobserved plant characteristics also contribute to an individual plant's export 27
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Bransford, J. D., & Johnson, M. K. (1972). Contextual prerequisites for understanding: Some investigations of comprehension and recall. _Journal of Verbal Learning and Verbal Behavior_ , _11_ (6), 717-726.

- Brock, C. A. (1986). The Effects of Referential Questions on ESL Classroom Discourse. _TESOL Quarterly, 20_ , 77-59. http://dx.doi.org/10.2307/3586388

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Brophy, J. (1986). Teacher influences on student achievement. _American Psychologist_ , _41_ (10), 1069.

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Brophy, J., & Good, T. L. (1985). Teacher behavior and student achievement, In M. C. Wittrock (Ed.), _Third handbook of research on teaching_ . New York: Macmillan.

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Bruns, B., De Gregorio, S., & Taut, S. (2016). Measures of effective teaching in developing countries. _Research on Improving Systems of Education (RISE) Working Paper_ , _16_ (009). London.

Buhl-Wiggers, J., Kerwin, J. T., Smith, J. A., and Thorton, R. (2017). The impact of teacher effectiveness on student learning in Africa. Research on Improving Systems of Education (RISE) Working Paper.

<mark>Buhs, E. S., Ladd, G. W., & Herald, S. L. (2006). Peer exclusion and victimization: Processes that mediate the relation between peer group rejection and children's classroom engagement and achievement.</mark> _<mark>Journal of Educational Psychology</mark>_ <mark>,</mark> _<mark>98</mark>_ <mark>(1), 1-13.</mark>

- Burnett, P. C. (2003). The impact of teacher feedback on student self-talk and self-concept in reading and mathematics. _The Journal of Classroom Interaction_ , 11-16.

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44
The linear and quadratic regression show that larger displacement inflows are always correlated with larger NTL growth in settlement with higher initial NTL levels , at, 95% confidence interval level, see columns 3 and 4 of Table C.2.

The linear and quadratic regressions analysis on the settlements starting with lower initial NTL levels return mixed results. Table C.2. column (1) show that equation (4) is positive, i.e., the NTL growth increases with the Total Inflow, as the interaction term is positive. The linear regression suggests that a marginal increase in net inflows of persons would increase the NTL in places with medium-high levels of human activities, i.e., with NTL above 0.30. The quadratic regression displays interesting patterns:

- In outbound settlements, a reduction in the net outflows of displaced persons raises the NTL level in outbound areas with important human activity. A sufficient condition for a marginal decrease in outflows (i.e., an increase in Total Inflow) to be associated with an increase in NTL levels is that past NTL be larger than 0.9.<sup>10</sup>

- In inbound areas, a marginal increase in net inflows of persons would increase the NTL in places with small levels of human activities, i.e., with NTL between 0 and 0.29.

_Table C.2. Regression of NTL on net inflows of persons in settlement on two different samples (higher vs lower initial NTL levels)_

|||Y = NTL l<br>|evels<br>||
|---|---|---|---|---|
||Sample: Sm<br>|all initial NTL<br>|Sample: Lar<br>|ge initial NTL<br>|
|VARIABLES<br>|(1)<br>Linear|(2)<br>Quadratic|(3)<br>Linear|(4)<br>Quadratic|
|α1;Lagged NTL<br>|0.563***<br>(0.00947)|0.917***<br>(0.0210)|0.570***<br>(0.0911)|1.201***<br>(0.297)|
|α4;(Lagged NTL)<sup>2</sup><br>||-0.393***<br>(0.0147)||-0.392**<br>(0.164)|
|α2;Total Inflow<br>|-9.09e-07***|-4.09e-06***|1.55e-05**|-1.55e-05|
||(7.78e-08)|(3.87e-07)|(6.09e-06)|(0.000128)|
|α3;(Lagged NTL)*Total Inflow<br>|3.01e-06***|1.34e-05***|4.04e-06|0.000347|
||(1.67e-07)|(1.40e-06)|(5.61e-06)|(0.000285)|
|α5;(Lagged NTL)<sup>2</sup>* Total Inflow<br>||3.44e-06***<br>(9.64e-07)||-9.81e-05<br>(0.000161)|
|α6;(Total Inflow)<sup>2</sup><br>||1.39e<sup>−11</sup>***<br>(0)||-7.17e-10<br>(6.01e-09)|
|α7;(Lagged NTL)*( Total Inflow)<sup>2</sup><br>||-3.20e-11***<br>(0)||-1.32e-08<br>(1.29e-08)|
|α8;(Lagged NTL)<sup>2</sup>*( Total Inflow)<sup>2</sup><br>||-5.30e-11***<br>(0)||3.55e-09<br>(7.24e-09)|
|α9;Population in 2017<br>|1.06e-05***<br>(6.93e-07)|7.21e-06***<br>(6.44e-07)|7.83e-05**<br>(3.28e-05)|-1.92e-05<br>(2.04e-05)|
|α10;% agriculture in 2020<br>|-6.40e-05*<br>(3.40e-05)|-1.85e-05<br>(3.11e-05)|0.00769***<br>(0.00270)|0.00641***<br>(0.00207)|
|α0;Constant<br>|0.109***<br> <br>|-5.30e-11***<br>|-0.812**<br>|0<br>|
|10<sup>d NTLi,t</sup><br>dXi<br>= −4.09N<sup>−06 </sup>+ 1.34N<sup>−06</sup>NLi,t−1+<br>11Xf(NTL) with f(NTL) positive if NTL in [0,0.29]|3.44N<sup>−06</sup>NLi,t−1<br>2<br>+<br>and h(NTL) positive if|2. Xi(1.39e<sup>−11 </sup>−3.<br>NTL>0.9.|20e<sup>−11</sup>NLi,t−1−|5.30N<sup>−11</sup>NLi,t−1<br>2<br>) ≡h(NTL) + 2e<sup>-</sup>|