rafmacalaba/data-use-mentions-extended huggingface dataset:
and transmission mechanisms, such as in the ILO (2020) and Vos et al. (2020) studies. In addition, some studies adjust prepandemic poverty lines using different scenarios of per capita income or consumption contraction or, alternatively, actual information on per capita GDP reduction (Sumner et al., 2020; Diop and Asongu, 2020). But these methodologies make strong distributional or structural assumptions,</mark> which lead the results to be sensitive to the choice of methodology.<sup>2</sup> <mark>In this study we follow a different approach, which applies a macro-micro simulation that combines pre-COVID-19 household surveys microdata with 2020 data on sectoral employment levels, sectoral GDP, private consumption, and remittances. With this information, we simulate the transmission of the COVID-19 shock via three channels – job loss, labor income declines, and changes in remittances— on household per capita income (or consumption) and the shares of poor, vulnerable, and middle-class populations in each country during 2020. We present projections for</mark>

> 2 For example, ILO (2020) projects that, using the 3.2 USD-a-day poverty line, the number of poor workers in 2020 will increase between 8.8 million and 35 million persons in 138 low- and middle-income countries compared to preCOVID-19 estimates. Sumner et al. (2020) project short-term increases in poverty of between 85 million and 580 million persons with respect to 2018 values for more than 150 countries using different poverty lines. Vos et al. (2020) predict an increase of between 12 million and 22 million in the number of extreme poor people (1.9 USD-a-day poverty line) in 30 countries of mainly Sub-Saharan Africa and South Asia in 2020. For 50 African countries, Diop and Asongu (2020) show increases of between 19 million and 26 million additional poor people in 2020 using different poverty lines.

2
They estimate breakeven prices of $0.55 to $3.70 per ton of CO2 depending on the site and level of harvest reduction required.

Marseni et al. (2014) analyze eight REDD+ pilot projects in two districts (Chitwan and Gorkha) in Nepal. They attempt to catalogue, and to the degree possible measure, the opportunity costs associated with accepting REDD+ payments to generate carbon credits. Costs are mainly in terms of foregone forest product collections (fuelwood, grass, fodder, timber, grazing), but also include time costs. They note that within the community forestry context, to participate in REDD+ there are large meeting and forest management time costs (e.g. fire control, planting thinning, pruning, cleaning, weeding). They note that the average payment of $1,734 across the eight sites does not cover estimated opportunity costs. They also note that a price of $10/ton of CO2 (at that time the EU Emissions Trading Scheme average price) would not even cover average meeting time opportunity costs. They do not estimate breakeven costs, but express doubt that REDD+ can be truly cost effective.

Pandit et al. (2017) examine the economics of carbon sequestration in Nepal using household survey data from 47 CFUG REDD+ pilot sites in two of Nepal’s 75 districts. Half the sites are in the plains of Nepal (i.e. the Terai) and half in the hills. They estimate net benefits of the REDD+ program (as was done by Marseni et al., 2014), but also calculate average breakeven carbon prices. They find that if the opportunity cost of unharvested fuelwood is taken into account, at a carbon price of $10 per ton no CFUGs receive positive net benefits. Assuming that biomass would not have otherwise been set aside as an environmental “safeguard,” they find that the average Terai<sup>6</sup> CFUG opportunity cost ranged from $50 to $74
what affects trade or investment success is due to a very wide range of causal factors, but where are the best measures of these factors? Most analyses using indicators only look at selected subsets of indicators, and one can question how these indicators have been selected.

Aware that different sets of factors matter in different country contexts, policy advisors have developed broader frameworks (starting with Doing Business) that would offer a more comprehensive picture, guiding policy makers in their reform efforts, and helping them identify and prioritize where action is needed. There is a plethora of tools and a large industry serving prospective investors and policy makers to assist them in identifying priority markets and factors impacting them, illustrating the complexity of the environment facing them and therefore the difficulty to reduce it to the key factors that would majorly impact their decisions. The exercise is not without challenges, as noted by Kraay and Tawara (2013). Their research finds significant shortcomings when attempting to identify sets of policy indicators that could be particularly correlated with specific (desired) policy outcomes. They find that sets of policies identified for one outcome do not correlate well with closely related and similar outcomes, thus suggesting that any attempt to identify partial effects of specific policies and to pick a subset of variables could be spurious.

A recent framework was developed for a new strategic exercise in the World Bank Group, the Country Private Sector Diagnostics (CPSD), designed to inform support efforts to mobilize private sector initiative for development. To guide the understanding about the extent of factors constraining private

> 5 For a discussion, see Hausmann and Klinger (2008).

2
## _Indirect Taxes and Subsidies_

Both VAT and excise taxes increase inequality and poverty regardless of gender. Although VAT and excise taxes are unequalizing for both men and women, VAT appears to be more unequalizing for men, suggesting that the burden of VAT falls more on men, possibly because men consume more alcohol and tobacco, which have higher VAT (EPHI 2016). The poverty-increasing effect of indirect taxes is higher than that of direct taxes for both men and women. However, indirect taxes are poverty-increasing mainly for women. The poverty-inducing effect of VAT is stronger for women and the effect of excise tax is stronger for men (Table 6). The findings suggest that people near the poverty threshold consume both food and non–food items that are subject to indirect taxes.

Indirect subsidies are unequalizing mainly because of the effect of wheat subsidy. Although unequalizing, the wheat subsidy appears to be poverty-reducing for both women and men. However, kerosene subsidy has little effect on inequality- and poverty-reduction.

## _Education_ and Health Spending

Public spending on education is unequalizing and poverty-reducing. The unequalizing effect is mainly the result of how much is spent on secondary and tertiary education (Table 6). The povertyreducing impact on girl students is powerful. Disaggregating the results by level of education, regardless of gender, spending on primary education has been found to be equalizing and poverty-reducing. Importantly, primary education has dramatically reduced poverty for girls. Both secondary and tertiary spending, though unequalizing, reduce poverty. Health spending is for both genders equalizing and poverty-reducing (Tables 6), though more so for women than for men.

# **5. Conclusion**

Using the Commitment to Equity methodology, this study investigates differences in the welfare impact of taxes and government spending on men and women in Ethiopia. It analyzes the incidence, progressivity, and pro-poorness of various taxes and transfers and their effect on income mobility, poverty and inequality. The study uses data from the 2018/19 Ethiopia Socioeconomic Survey, which collected individual level information
(World Bank, 2014). This study in Jharkhand expands on this evidence base by including social-emotional variables in a youth survey alongside of more conventional aspirations, education, and employment modules to enable more in-depth analysis of the relationships between these factors. We find that individual psychological factors like self-efficacy and mental health are important determinants of girls’ educational and employment aspirations. This suggests that such hidden forms of human capital may constitute critical targets for interventions aimed at altering girls’ educational and economic trajectories.

We also identify factors that correlate with girls’ level of self-efficacy. We find that individual and household level factors like age, previous training experience, and an “enabling” environment—i.e., one where girls enjoy family/social support, feel connected and have empowered parents and other successful role models to look up to, appear to be important in boosting their sense of self-efficacy. We argue that these findings could usefully inform the design of programs aimed to boost female educational and labor market outcomes.

# **References**

Angrist, J. and V. Lavy (1999) “Using Maimonides’ Rule to Estimate the Effect of Class Size on Scholastic Achievement”, _Quarterly Journal of Economics_ , 114(2), pp. 533-575 Baldacci, E., B. Clements, et al. (2008). "Social Spending, Human Capital, and Growth in Developing Countries." World Development 36(8): 1317-1341.

Bandura, A. (1977) “Self-efficacy: Toward a Unifying Theory of Behavioral Change”, _Psychological Review,_ 84, 191-215 Barry, M. M., Clarke, A. M., Jenkins, R., & Patel, V. (2013). A systematic review of the effectiveness of mental health promotion interventions for young people in low and middle income countries. BMC Public Health, 13(1), 1.

Becker, B. E., and Luthar, S. S. (2002) “Social-Emotional Factors
At different poverty thresholds, the paper finds little statistically significant difference between the diary and recall arms. Household characteristics such as employment and education are vital in explaining observed differences in food and total consumption expenditure.

The study is limited in the following ways. First, the implementation of the survey used separate teams for the diary and recall arms, which could explain some of the observed differences in consumption expenditure across the three designs. The analysis did not correct for this. Second, the non-availability of conversion factors forced respondents to report food consumption in standard units, which is very restrictive and difficult, especially for respondents and enumerators with low cognitive prowess.

# **References**

- <mark>Battistin, E., De Nadai, M., & Krishnan, N. (2023). The insights and illusions of consumption measurements.</mark> _<mark>Journal of Development Economics</mark>_ <mark>,</mark> _<mark>161</mark>_ <mark>, 102991.</mark>

- <mark>Bee, A., Meyer, B. D., & Sullivan, J. X. (2012).</mark> _<mark>The validity of consumption data: are the consumer expenditure interview and diary surveys informative?</mark>_ <mark>(No. w18308). National Bureau of Economic Research.</mark>

- Backiny-Yetna, P., Steele, D., & Djima Y.I. (2017). The impact of household food consumption data collection methods on poverty and inequality measures in Niger. _Food Policy_ , 72, 7-19

- Beegle, K., De Weerdt, J., Friedman J., Gibson, J. (2012) **.** Methods of household consumption measurement through surveys: Experimental results from Tanzania. _Journal of Development Economics_ , 98(1), 3-18.

- Belghith, B.H
Policy Research Working Paper 8694

# **Abstract**

This paper takes a first look at the trade effects of China’s Belt and Road Initiative, also referred to as the New Silk Road, on the 71 countries potentially involved. The initiative consists of several infrastructure investment projects to improve the land and maritime transportation in the Belt and Road Initiative region. The analysis first uses geo-referenced data and geographical information system analysis to compute the bilateral time to trade before and after the Belt and Road Initiative. Then, it estimates the effect of improvement in bilateral time to trade on bilateral export values and trade patterns, using a gravity model and a comparative advantage model. Finally, the analysis combines the estimates from the regression analysis with the results of the geographical information system analysis to quantify the potential trade effects of the Belt and Road Initiative. The paper finds that (i) the Belt and Road Initiative increases trade flows among participating countries by up to 4.1 percent; (ii) these effects would be three times as large on average if trade reforms complemented the upgrading in transport infrastructure; and (iii) products that use time sensitive inputs and countries that are highly exposed to the new infrastructure and integrated in global value chains have larger trade gains.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at mruta@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
> are significant at the 10% level.

# **6 Conclusions**

This paper has provided novel evidence that robots increase plant level efficiency, value added and employment in a large developing country experiencing a robust increase in imports of robots. Moreover, we find evidence of positive employment spillovers from downstream automation, within manufacturing and across other sectors.

The positive employment impact of automation in Indonesia contrasts with the evidence not only from advanced economies but also from emerging ones, such as Mexico (Artuc et al., 2019) and China (Giuntella and Wang, 2019). In these countries the increase in labor demand driven by higher productivity is not sufficient to offset the labor displacement effect of robots. While a systematic investigation of the reasons behind this difference is beyond the scope of this paper, we discuss two candidate explanations.

The first is related to the evidence that the productivity impact of robots is subject to diminishing returns to scale (Graetz and Michaels, 2018). In a country with a low initial density of robots, their adoption may result in particularly large productivity increases that could offset the labor displacement effect. This low initial density seems to apply to Indonesia, which in 2011 - the first year we have the data for the 3 countries - recorded 0.018 robots per thousand workers, versus 0.04 in Mexico and 0.1 in China.<sup>37</sup> This

> 37These numbers are obtained by combining IFR data on robots’ stock with ILO data on total employment across all sectors.

38
Policy Research Working Paper 7826

# **Abstract**

A spatial econometric model is used to link road upgrading to forest clearing and biodiversity loss in the moist tropical forests of Bolivia, Cameroon, and Myanmar. Using 250meter cells, the model estimates the relationship between the rate of forest clearing in a cell and its distance to the urban market, with explicit attention given to road quality and simultaneity, terrain elevation and slope, the agricultural opportunity value of the land, and its legal protection status. Forest clearing is found to be most responsive to the distance to the nearest urban market, especially with secondary roads with lower typical speeds. Using the estimated forest-clearing response elasticities and a composite biodiversity indicator, an index of expected biodiversity loss from upgrading secondary roads to primary status is computed in each cell. The results identify areas in the three countries where high expected biodiversity losses may warrant additional protection as road upgrading continues. In addition, the results provide ecological risk ratings for individual road corridors that can inform environmentally sensitive infrastructure investment programs.

This paper is a product of the Environment and Energy Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at sdasgupta@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
association (%)|62.81|91.00|39.72|
|Household size (average)|6.61|6.84|6.42|
|Nord Kivu|516|229|287|
|South Kivu|643|293|350|

Source: Our own computation based on survey data.

and 83.91% of the adopters of CTA were female. At the time of the survey, the average age of the SSCBT was 36 years. The average household size of respondents (both adopters and non-adopters) was 6 people per family; about 95% of respondents were living in urban areas and had spent an average of about 9 years in cross-border trade. The educational level of the SSCBTs was different between adopters and non-adopters. Whereas 55.5% of the non-adopters had at least primary school level of education, only 46% of adopters had a similar level of education. However, at least 54% of adopters reached secondary education against 44% of non-adopters. In addition, the majority of respondents, both adopters and non-adopters have a fix place in the market where they sell their goods. The adoption rate in the two provinces is 44.3% and 45.5% in North Kivu and South-Kivu, respectively. To implement the CTA, the GLTFP worked with mass media (radio and television), officials, existing SSCBTs’ associations and groups of interest to spread the awareness and sensitize SSCBTs in order to organize themselves in groups. In DRC, the dissemination of CTA was implemented in only a few selected markets and regions. This means that the overall population of SSCBTs was not equally exposed to the CTA (the instrument for the policy intervention was not randomly distributed). On the other hand, SSCBTs exposed to the CTA had full control over their decision to adopt or not to adopt (i.e. the receipt of the treatment is endogenous). According to the impact assessment literature, the most plausible assumption to make in
80 85 90 95 00<br><!-- End of picture text --> _Source:_ Author’s elaboration based on data from Banco de Guatemala. Data for 2002 (2003) is GDP growth preliminary (estimated). Historical events are taken from Luján (2000).

_External shocks and the civil war, 1975-1985._ A second period starts shortly after the deterioration of the terms of trade and the international oil crisis. In 1976 a major earthquake affected Guatemala. After 1977, social tension culminated in a full-scale civil war that reached genocidal proportions in the early 1980s. Consequently, growth declined dramatically. Apart from causing immense human sorrow, these events destroyed human life and physical capital. They also imposed high costs for long-run growth.

> 5 An excellent review of the rise and fall of the Central American integration process for 19501999 can be found in de La Ossa (2000).

-4-
material welfare at least in the short term, especially for groups with large stakes in the old economic system. Standard economic and social statistics are unlikely to do justice to the significance of this adjustment and to capture adequately the empowerment dimension.

In view of these shortfalls of objective welfare measures, a substantive volume of research has emerged over the last decades that uses people’s own assessments to get at notions of individual well-being. The underlying idea is to rely on individuals and households themselves to define the level of well-being. Even though precise definitions of these concepts still remain elusive, psychologists and economists have used self-assessments as proxy measures of welfare and well-being. The approach has become so successful that subjective questions are now routinely included in household surveys, along with objective measures.

|The distinguishing feature of subjective measures is that they are based on a<br>person’s self-assessment. This raises the question whether they are consistent<br>and change systematically with objective measures. For example, a person’s<br>self-assessed economic situation may stay unchanged even though her con-<br>sumption increases, either because her expectations have increased or because<br>her position relative to her reference group has remained the same. To avoid<br>such pitfalls in the assessment of well-being across a group of individuals on<br>the basis of subjective indicators, one needs to assume that individuals:<br>e are able to understand and answer consistently questions about own situa-<br>tion, and<br>e provide responses that are comparable.<br>While some evidence suggests that these conditions typically hold within a<br>common cultural context, it is generally difficult to verify these assumptions.<br>Furthermore, the reliability of any given welfare indicator can be severely<br>undermined by measurement problems (Deaton (1997)). Therefore, it is im-<br>portant to validate whether observed changes are real or reflect data problems<br
recent years, it remains very scarce for South Asia.<sup>2</sup> Temporary migration from South Asian countries differs from other contexts studied by the return migration literature in several respects. First, low-skilled workers from South Asia can only migrate on the basis of temporary contractual arrangements in the main destinations, primarily the Gulf countries and Southeast Asia, and have to return once their contract expires. Second, South Asian migrants are employed in very low-skilled brawnbased occupations at destination, which could limit human capital accumulation overseas as evidenced in other contexts, and reduce incentives to take up similar work after returning home. Third, the upfront monetary costs of migration from the region are very large relative to wages both at home and at destination (Ratha and Seshan 2018), which can reduce the

> 1For a recent review of the literature on this question, see Bossavie and Ozden (2022).

> 2To the best of our knowledge, the only exceptions are Arif (1998) and Ilahi (1999) who use data from the 1980s and 1990s in Pakistan, and more recently Bossavie, Gorlach, et al. (2021) and Bossavie, Gorlach, et al. (2022) in Bangladesh.

2
several of these drivers. Saiedi, Brostrom & Ruiz (2020) find some evidence that perceived failings of the traditional financial system contribute to the adoption of crypto-assets. However, using U.S. Survey of Consumer Payment Choice data Auer and Tercero-Lucas (2021), document that crypto-asset adoption in the United States is not driven by distrust in the regulated financial system and conclude that adoption is mostly driven by speculation. In addition, they also find that crypto-assets users tend to be educated, young, and digital natives. By analyzing on-chain Bitcoin transaction data, Baur, Lee and Hong (2018) and Athey et al (2016) also find that bitcoin transactions mostly reflect speculative activity. However, more recently Graf von Luckner et al (2021) study data from a centralized exchange and challenge the view that Bitcoin is only used for speculation. They find evidence that at least 7 percent of bitcoin transactions reflect its use for domestic transactions and 11