rafmacalaba/datause-encoder-data huggingface dataset:
The previous finding of more on-farm tree planting in forest rich environments is confirmed in the multivariate setting. The generally positive association between nearby tree cover and presence of trees on farms merits further analysis, especially using panel data, to better understand how farmers respond to changes in the availability of forest resources—by increasing the density of trees on their farms as forest resources decrease (Arnold and Dewees, 1995) or by continuing agroforestry systems which may already have an integral relationship with nearby forest (e.g. Brottem, 2011; Degrande et al., 2006). Onfarm trees also tend to be more prevalent in environments where the temperature is higher. Overall, geoclimatic variables were found to be very important. They accounted for around for 18.5% and 31% of the total variation in the adoption of fruit trees and tree cash crops respectively (Tables 6a and b). This result buttresses previous findings about biophysical conditions as key drivers of farmer decisions to adopt and maintain trees on-farm (Pattanayak et al., 2003; Place and Garrity, 2015). Surprisingly, no systematic correlation was found across countries with population density (or soil fertility).

Finally, country fixed effects also explained an important share of the variation (more than 40% for adoption). This underscores the importance of national level institutions and policies in shaping whether farmers decide to adopt trees on their farms or not. In many countries, forest regulations create disincentives for on-farm tree management (Place and Garrity, 2015; Ribot, 1999). But changes to such regulations can spur changes in practice as shown in the recent regreening in Niger, which has been catalyzed by political openings and reforms to colonial-era forest and rural policies that allowed local innovation in land management (Sendzimir et al., 2011).

# 4 Concluding Remarks

In this paper we used nationally representative household-level data to explore and compare the prevalence and economic contribution of trees on farms across five African countries. Three main findings emerge. First, trees on farms are widespread across the continent and comprise a key component of agricultural-forest landscapes. The East African countries of Tanzania, Uganda and Ethiopia had especially high incidence of trees on agricultural lands, with about a third to more than half of rural households reporting on-farm trees. Fruit trees and cash crop trees were the two most popular types of trees while trees for timber and fuelwood were much less prevalent (reported by 5% of respondents). The proximity of most households with trees on farms to forests and the high incidence of intercropping 14
# **C.2.2 SNNPR**

Table C.2: SNNPR – MTI Implementation

|**Language**|**Year**|**Region**|**Grades**|**Fracti**<br>**MT Speakers**<br>**Living in Region**|**on of:**<br>**Region Speaking**<br>**Language as MT**|
|---|---|---|---|---|---|
|Sidamigna|1992|SNNPR|1-4|0.99|0.18|
|Wolayitigna|1992|SNNPR|1-4|0.97|0.11|
|Hadiyigna|1993|SNNPR|1-4|0.96|0.08|
|Gedeogna|1993|SNNPR|1-4|0.73|0.04|
|Kembatigna|1993|SNNPR|1-4|0.92|0.04|

_Source_ : Author’s analysis based on information from Boothe and Walker (1997) and Zenebe Gebre (2014). _Note_ : SNNPR = Southern Nations, Nationalities, and Peoples’ Region; MTI = mother tongue instruction; MT = mother tongue.

Unlike the other regions in the Ethiopia, SNNPR introduces new languages of instruction at two points within the time period MTI is considered. The timing of the 1992 implementation is denoted by brackets in Appendix Table (C.5); however, the following year two additional languages are introduced. This will have the effect of introducing two weights one for the 1992 set of languages ( _wz,_ 1992) and another for the 1993 languages ( _wz,_ 1993). The magnitude for each two introductions is offset by one year, this yields the familiar calculation of the maximum impact for the on time entrants: A.14
actions, a percentage much lower than the general average of 52.8% and lower than the average for China and India (80% and 63.6% respectively).

Table 6 Number of AD Cases in Brazil with Final Determinations, Grouped by Exporting Country or Bloc

|Country/Bloc|Cases|Accepted|(%)|Price<br>undertaking|(%)|Rejected|(%)|
|---|---|---|---|---|---|---|---|
|USA|29|10|34.5|1|3.4|18|62.1|
|China|25|20|80.0|0|0.0|5|20.0|
|India|11|7|63.6|0|0.0|4|36.4|
|Russia|8|4|50.0|0|0.0|4|50.0|
|South Africa|6|4|66.7|0|0.0|2|33.3|
|Germany|6|4|66.7|0|0.0|2|33.3|
|United Kingdom|6|4|66.7|0|0.0|2|33.3|
|Mexico|5|4|80.0|0|0.0|1|20.0|
|Ucraine|5|2|40.0|0|0.0|3|60.0|
|Bangladesh|4|2|50.0|0|0.0|2|50.0|
|Japan|4|2|50.0|0|0.0|1|25.0|
|South Korea|4|1|25.0|0|0.0|3|75.0|
|Spain|4|2|50.0|0|0.0|2|50.0|
|France|5|3|60.0|1|20.0|1|20.0|
|Argentina|3|1|33.3|1|33.3|1|33.3|
|Canada|3|1|33.3|0|0.0|2|66.7|
|Kazhakstan|3|2|66.7|0|0.0|1|33.3|
|Chile|3|1|33.3|1|33.3|1|33.3|
|Subtotal|134|74|55.2|4|3.0|56|41.8|
|Other|59|28|47.5|1|1.7|30|50.8|
|Total|193|102|52.8|5|2.6|86|44.6|

Source: DECOM, SECEX, MDIC Reports, several years. Author's calculations.

Note: In the actions against the European Union, only Member countries exporting to the Brazilian market were included. In the case of the former URSS, such a detailed breakdown was not possible.

It is widely recognized that the adoption of certain methods may lead to a more protectionist approach to the use of antidumping measures. In particular, the choice of the normal value is a crucial issue in the determination of a greater (or smaller) dumping margin. Table 7 lists some specific indicators. It should be pointed out that in 41.4% of accepted cases, preliminary duties 25
|**Table 1– Set of urban indicators used by FCM**|
|---|
|Ecological footprint|
|Recreationalwaterquality|
|Low birthweightbabies<br>Personal & community health|
|Teenbirths|
|Prematuremortality|
|Work hourslost|
|Suicides|
|Infant mortality|
|Community affordability<br>Personal financial security|
|FamiliesreceivingEI/Socialassistance|
|Economic dependencyratio|
|Lone parent family|
|Incidence of lowincomefamilies|
|Children livinginpoverty|
|Income gap|
|Youthoffenders<br>Personal safety|
|Violentcrimes|
|Property crimes|
|Injuries and poisonings|

47
26 3D PRINTING AND TRADE As a second exercise, we exploit product level characteristics to identify heterogenous effects of 3D printing on trade. This allows to study the extent to which the impact of 3D printing on trade in the previous sections depends on the product characteristics of hearing aids. Specifically, we investigate if product weight plays a role in the decision of localizing production closer to consumers versus concentrating the production in one location. Intuitively, for products like hearing aids that are light and hence have lower transport costs, incentives to localize production closer to consumer should be lower than for heavier products. Ideally, we would also like to identify how the impact of 3D printing on trade varies based on the interplay between economies of scale intensity and product weight. Unfortunately, data on scale elasticities is available only for a limited number of 2-digit sectors (see Bartelme, Costinot, Donaldson and Rodriguez-Clare, 2018).

To formally test for differential impacts of 3D printing on trade in heavy and light goods, we augment equation (1) by an interaction term between Ikt(3Dprinting 2007) and product k’s log of weight. The weight of product k is defined as the median unit weight of HS 6-digit products corresponding to a 4-digit SITC product.<sup>18</sup> The unit weight measure for printable sectors varies from 52 grams for spectacles (SITC 8842) to 98 kilograms for machine tools for deburring (SITC 7316). Before describing the results from this specification, it is important to stress some caveats. First there may be an aggregation bias, if some products in a category are light and others are heavy. In addition, the effects could be misidentified if weight is a determinant of technology adoption. Moreover, it is possible that the technology could affect product weight as it may allow to design new structures that are lighter and use less material.

With these caveats in mind, Figure 11 presents the results on the impact of 3D printing on exports and imports as a function of product weight. Panel A shows that the impact of 3D printing on exports decreases with product weight. Exports of lighter products such as spectacles increased the most after the technology became available while the impact becomes insignificant for heavier product such as aircraft and spacecraft parts. Results in Panel B suggest that the availability of 3D printing led to a statistically significant decrease in import of heavy printable products, mainly machineries. The results suggest that 3D printing is more likely to lead to fragmented production for products that are light and, hence, cheaper to trade. On the other hand, there is some evidence that the technology could be used to produce goods closer to consumers for products subject to high transport costs.

18 We calculate unit weights with HS 6-digit data, instead of SITC 4-digit, as the information is provided on a more detailed degree of disaggregation.
valuable contribution, but there is little sign as yet that this has led to new weights. Consider, for example, the oldest of the mashup indices still in use, the HDI. Its weights were set 20 years ago, with equal weight to the (scaled) sub-indices for health, education and GDP.<sup>23</sup> Equality of the weights was, of course, an arbitrary judgment, and it might have been hoped that the weights would evolve in the light of the subsequent public debate. But that did not happen. The weights on the three components of the HDI (health, education and income) have not changed in 20 years, and it is hard to believe that the HDI got it right first go.<sup>24</sup> Setting initial weights and revising them in the light of subsequent debate would point to the need to know the tradeoffs in the most relevant space for understanding what the weights really mean. The fact that the industry of mashup indices has often assigned weights in what can be thought of as ―secondary spaces‖—such as rankings or poverty measures, rather than the space of the underlying primary dimensions—does not make it easy for the debate to proceed on a well-informed basis. Indeed, given the opaqueness about the tradoffs in the primary dimensions built into most mashup indices it can be argued that users (including policy makers) may end up tacitly accepting, and acting upon, tradoffs that they would find objectionable when revealed.

Subjective questions in surveys can also offer useful clues as to the appropriate weights, although this type of data raises its own problems, such as stemming from psychological differences between respondents, including latent heterogeneity in the interpretation of the scales used in survey questions.<sup>25</sup> Ravallion and Lokshin (2002) discuss how subjective data on perceived economic welfare can be used to calibrate a composite index based on objective variables; the tradeoff between income and health (say) is chosen to be consistent with subjective

> 23   The weights on the HDI‘s primary dimensions have varied over time due to (often seemingly arbitrary) changes in the bounds used for scaling the indices. However, as noted already, the weights on the HDI‘s core dimensions have never been explicitly identified or discussed in the HDRs. See Ravallion (2010b).

> 24   In switching to a geometric mean in the 2010 HDR, the weights on the three achievement variables changed, though their logs are still equally weighted.

> 25  These can stem from ―frame of reference‖ effects, whereby a person‘s perception of the scales depends on the set of their own experiences and knowledge. (This is also called ―differential item functioning‖ in the literature on educational testing; see, for example, Angoff, 1993.) In one of the few tests for such effects Beegle et al. (2009) use vignettes to anchor the scales and find that regressions using subjective welfare data are quite robust to this problem (using survey data for Tajikistan).

16
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Sanyal, Paromita and Vijayendra Rao, 2019 _Oral Democracy: Deliberation in Indian Village Assemblies_ ,” Cambridge University Press, Cambridge UK Schiller, Robert, 2019, _Narrative Economics: How Stories go Viral and Drive Major Economic Events_ , Princeton University Press, Princeton.

Sharan, MR, 2021, _Last Among Equals: Power, Caste and Politics in Bihar’s Villages_ , Westland Press, Delhi Sharan MR and Chinmay Kumar, 2021, “Something to Complain About: How Minority Representatives Overcome Ethnic Differences,” mimeo, Department of Agricultural and Resource Economics, University of Maryland Singh, Bhrigupathi, 2015, _Poverty and the Quest for Life: Spiritual and Material Striving in Rural India_ , University of Chicago Press, Chicago and London <mark>Small, Mario Luis. 2009, “`How Many Cases Do I Need?’: On Science and the Logic of Case Selection in Field-Based Research.”</mark> _Ethnography_ <mark>10, no. 1 (March): Pp: 5–38.</mark> <mark>Small, Mario Luis, 2011, “How to Conduct a Mixed Methods Study: Recent Trends in a Rapidly Growing Literature,”</mark> _Annual Review of Sociology_ , 2011, Vol. 37, pp. 57-86 Small, Mario Luis, 2018, “Rhetoric and Evidence in a Polarized Society,” Coming to Terms with a Polarized Society Lecture Series, Institute for Social and Economic Research and Policy, Columbia University, New York, March Srinivasan, TN, “On Studying Socio-Economic Change in Rural India,” Chapter 10 in P. Bardhan (editor) _Conversations Between Economists and Anthropologists_ , Oxford University Press, Oxford and Delhi Stephens-Davidowitz, Seth, 2014, “The cost of racial animus on a black candidate: Evidence using Google search data,” _Journal of Public Economics,_ Volume 118, Pp; 26-40 <mark>Thaler, Richard H.</mark> 2016. "Behavioral Economics: Past, Present, and Future." _American Economic Review_ , 106 (7): 1577-1600.

Udry, Christopher, 2003, “Fieldwork, Economic Theory and Research on Institutions in Developing Countries,” mimeo.

White, Howard, 2008, “Of Probits and Participation: The Use of Mixed Methods in Quantitative Impact Evaluation,” _IDS Bulletin_ 39:98-109 Woolcock, Michael, 2021, “On Folklore and ‘Folklore’ (QJE): Forging Dialogue, Reconciling Tradeoffs,” _Development Impact Blog_ , February 23<sup>rd</sup> World Bank, 2021, “Helping Communities to Gain the Ability to Collect and Analyze Their Own Data,” Spotlight 1.1. _World Development Report 2021, Data for Development._ The World Bank Group, Washington DC 23
relationships but rather associations between these important variables. Nevertheless, it offers preliminary evidence and builds motivation for further research.

This paper contributes to the existing literature on capital market development by shedding light on how issuer composition changes as stock markets grow. Our findings have important implications for policy makers seeking to improve access to financing for firms. A broad and diverse set of issuers reflects a well-functioning stock market, one that is able to meet various financing needs in the underlying economy. As our results show, however, this may not naturally follow capital market growth. Our findings therefore highlight the need to go beyond headline growth indicators to ensure stock markets are more inclusive on the issuer side. On this front, it may be worth focusing on market liquidity, especially in low- and middle-income countries. For sectoral diversity, however, our results suggest the need to have more targeted measures that go beyond market size and liquidity.

The remainder of the paper is structured as follows. Section 2 provides a literature review. Section 3 and section 4 describe the data and methodology, respectively. Section 5 presents empirical results and section 6 provides concluding remarks.

# **2. Literature review**

Empirical research examining the relationship between issuer composition and stock market growth is limited. There is some related research, however, that studies aspects of issuer composition. For example, Bae et al. (2021) use three decades of stock market capitalization data of firms listed on domestic stock exchanges in 47 countries to examine the relationship between stock market concentration and a number of economic outcomes, such as competition, innovation, and economic growth. Their results indicate that highly concentrated stock markets, especially those dominated by a small number of large and successful firms, are associated with less efficient capital allocation, sluggish initial public offerings and innovation activity, as well as slower economic development.

Literature on how issuer composition evolves as capital markets develop in low- and middleincome countries is even scarcer. There is some evidence that issuer composition is related to countries’ economic development, with Beck et al. (1999) finding that high-income countries tend to have deeper, more active, and more diverse stock markets. Country-specific studies include Black et al. (2012), who find that the initial increased diversification of issuers in Australia’s capital markets, especially in the case of a sectoral shift from non-financial corporations to bank issuers, was largely induced by the 1980s deregulation of the banking system followed by the introduction of a floating exchange rate and abolition of capital controls. Post 1980s, the uptake of private issuances was mostly driven by increased issuance of bonds by commercial banks. In the 4
32

**Table 5:  Community Radio Effects on Village Exposure to Education and Health Programs** <u>(</u> _Commune fixed effects, robust p-values in parentheses_ <u>)</u>

|||N<br>|umber of Pr<br>|ograms:<br>|||
|---|---|---|---|---|---|---|
||Education|Health|Education|Health|Education|Health|
|Community radio received by|20.52|126.3|38.61|129.4|||
|village (# stations)|(0.04)|(0.01)|(0.00)|(0.01)|||
|Within-commune community|||||35.86|87.30|
|radio received by village (#<br>stations)|||||(0.15)|(0.00)|
|Out-of-commune community|||||19.96|127.7|
|radio received by village (#<br>stations)|||||(0.04)|(0.01)|
|All radio received by village (#|19.28|2.768|||19.26|2.821|
|stations)|(0.00)|(0.88)|||(0.00)|(0.88)|
|Public radio received by village|||0.522|-50.11|||
|(# stations)|||(0.97)|(0.33)|||
|Commercial radio received by|||6.438|25.25|||
|village (# stations)|||(0.39)|(0.33)|||
|Religious radio received by|||67.08|-43.35|||
|village (# stations)|||(0.01)|(0.49)|||
|Observations<br>|210|210|210|210|210|210|
|_R_<sup>_2_</sup>|0.90|0.80|0.91|0.81|0.91|0.80|

Note: Standard errors clustered at commune level. Each column regresses the number of education or health programs received by a village, as determined by information supplied by the radios that broadcast to the village, on the number of different types of radio stations received by the village. The regressions control for commune fixed effects and therefore capture only intra-communal variation in village access to education and health programming.

The second issue in discussing mechanisms of radio effects is whether this information influences literacy outcomes through accountability or behavioral channels. If through accountability, then villages with greater access should see greater government provision of those inputs that matter for child literacy and more evidence of collective action. For every village school, enumerators collected information on the following: the average pupil-teacher ratio across classrooms, the number of available textbooks reported per enrolled pupil, the share of teachers that
79 about 2 percentage points less than the average for non-CPA countries. However, the divergence between projected and actual budget deficit seems to be comparable for the two sets of countries. The average budget deficit to GDP ratio for the CPA group of countries came down slowly from 9.7% in 1986 to about 9.3% in 1987, against a projected figure of 8.5%. The record of subsequent years is similar - the actual figures of 1988 to 1991 were consistently one or more percentage points higher than projected or targeted deficit. Until 1989, the record of non-CPA countries with regard to the - budget deficit is similar projected values are less than actual outcomes. After 1989, the non-CFA countries on average succeeded in reducing their budget deficits as projected by PFPs, although the actual deficits are still slightly higher than the average level in the CFA group of countries. This ;neans that even though the level of deficit on average is still higher in non-CFA countries than CFA countries, the trend seems better for non-CFA countries. It is worth noting that Senegal is responsible for much of the improvement in CFA budget deficits in 1991.

The PFP projections on current account balance for CFA countries also shows a narrower gap for this group of countries in comparison to non-CPA countries. Both groups of countries, however, have had a similar record in regard to projections on the current account balance. The current account gap for CPA countries was, however, higher than what was projected for all the years except 1991. For both groups, if terms of trade adjustments were made, the gap would have been much less, even less than what was projected. As for investment ratios, the projection records of CFA and non-CFA countries are comparable. But in the case of savings ratios, the records of CFA and non-