rafmacalaba/data-use-mentions-extended huggingface dataset:
There is a substantial variation in the total share of informal workers across countries and sectors. According to the World Bank Group (2021), the scale of the informal economy varies substantially among emerging markets, developing economies, and their regions. For example, in 2018, the share contributed by the informal sector ranged from around 10 percent to 68 percent of GDP, while informal employment measured in terms of self-employment ranged from near-zero to 96 percent of total employment. In particular, the highest share of informality is observed in some countries in the Sub-Saharan Africa region, in which informal employment constitutes more than 90 percent of total employment. There is also a considerable variation across industries: among the nine industries in this study, agriculture, trade, and construction have on average the highest levels of informality accounting respectively for 68, 50 and 34 percent of total employment. The lowest informality rates on average are observed in utilities (12 percent), finance (16 percent), and other services (20 percent). Also, due to its capital-intensive production the mining sector employs very few workers and accounts for less than 5 percent of total employment in many countries. Hence, the number of informal workers in this industry is insignificant in the broader picture of total informal employment.

Other variables used in the regressions are the capital-labor ratio, share of sectoral value added in total GDP, share of imported intermediate goods in total intermediate goods, and emissions from intermediate usage of imports and domestic products in a metric of carbon dioxide equivalent. The latter is a dependent variable in the regressions which is divided by the value added to take into account the size of the sectors. All these indicators are obtained from the GTAP data set which provides data for 65 sectors and 141 countries and world regions for the year 2014. Country mapping between the I2D2 and GTAP data shows that only 70 developing countries are represented in both databases and thus are included in the sample for estimations. Among the GTAP indicators, the capital-labor ratio is computed by dividing
<mark>exposure to natural disasters and climate variability; social, economic, and institutional characteristics of households and regions that affect their adaptive capacity; and health, livelihood, food security, and demographic characteristics that determine sensitivity to climate change impacts.</mark>

# **<mark>From concept to choice of variables</mark>**

<mark>A number of judgments have to be made when translating the concepts into estimates of vulnerability at the sub-national level; this is particularly so for adaptive capacity. For example, does migration and urbanization reduce or increase vulnerability? Vincent (2004) interprets growing urbanization as a sign of weak rural resilience and therefore high vulnerability. However, in the Tajik context, migration is accompanied by remittances vital to the livelihoods of the household members left behind. At least to the migrant households, remittances help reduce vulnerability. We therefore treat remittances as adding to income diversification and improving adaptive capacity. We construct a variable measuring the extent of diversification of non-agricultural income sources at the household level which we believe to be a good indicator of how well communities have already adapted: well- diversified communities (including those with remittance incomes from migrants) are displaying adaptive behaviors and might be expected to continue to do so in the future.</mark> <mark>A well-educated population with reasonable and diversified income sources and developed institutional structures is better able to manage risks and prevent biophysical impacts from translating into human impacts. We therefore also include in the adaptive capacity sub-index average per capita household consumption and the share of population with education above secondary.</mark><sup>1</sup> <mark>Institutional strength and stability are also important for determining the coping range of a population. Governance and political stability are important criteria here but, unfortunately, no direct indicator is available at the sub-national level. However, three good proxies for institutional strength are available in our data and all contribute to adaptive capacity:</mark>

- <mark
1,715 were born in Venezuela and considered recent migrants.

> 2EPEC stands for _Encuesta a Personas en Movilidad Humana y en Comunidades Receptoras en Ecuador_ , which can be translated as Survey of Migrants and Receiving Communities in Ecuador.

> 3To be specific, Ecuador is administratively organized into 221 cantons. To implement the survey, the cantons were subdivided into _sectors_ classified according to the density of Venezuelans estimated using mobile phone data (described in detail in Olivieri et al. (2020)). About 190 sectors were randomly selected and, within those, households were also selected for the interview at random. By virtue of the sampling strategy, the survey is nationally representative of the target populations and the three strata of sectors defined by low, medium and high density of Venezuelan migrants.

4
# **International Migration and Household Well-Being**

# Evidence from Uzbekistan

William Seitz<sup>1</sup> JEL: F22, F24, J61, J64, I31, I32 Keywords: Migration, Remittances, Uzbekistan, Listening to the Citizens of Uzbekistan, HighFrequency Panel Survey, Poverty, Subjective Well-being

> 1 The World Bank; Poverty and Equity Global Practice; wseitz@worldbank.org
occupations: (a) those that can be performed from home and require internet; (b) those that can be performed from home without the use of internet; (c) those that cannot be performed from home and do not require internet; and (d) those that cannot be performed from home but do require internet. In the United States, 33.3 percent of all jobs can be done from home and require internet -e.g. fall into group (a), while a further 3.3 percent can be performed from home without internet usage -e.g. fall into group (b).

> 5 In addition, it is not clear how the tasks required to perform an occupation are the same across economies at different levels of development. Using PIAAC (Programme for the International Assessment of Adult Competencies) data at the country level to assess the variations in the task content of occupations, Hatayama, Viollaz and Winkler (2020) observe changes in the ranking of countries in terms of their jobs’ amenability to working from home. However, both measures are highly correlated and most of the lower income developing countries do not have data on the task content of their jobs (the PIAAC survey covers mostly OECD countries), we apply the DN2020 index to all countries. The results from PIAAC countries using the Hatayama, Viollaz and Winkler’s (2020) methodology are very similar and available upon request.

7
Finally, it is worth exploring why the GWP results (and the new World Bank and FAO numbers) tell a positive story at the global level. One clear pattern is that events in the largest developing countries heavily influence any appraisal of global trends, not only because of the obvious influence of their sheer size on global trends, but also because many large countries are characterized by limited food inflation, rapid economic growth, or both. The first of these is not surprising. Large countries are very reluctant to rely heavily on significant food imports and are more likely to impose export restrictions and set aside significant food reserves. For example, China, India, Indonesia, and Vietnam all imposed some restrictions on grain exports in 2007 or 2008, and Nigeria abolished a 100 percent tariff on rice imports (Headey and Fan 2010). Of course, the effect of these attempts to insulate domestic markets on global poverty is ambiguous given that effective trade restrictions by large countries may protect their own poor but may hurt the rest of the world’s poor by spurring further international food inflation. Another domestic policy factor that may explain the apparent reduction of food insecurity in some of the larger developing countries is the spread of major social safety net programs in these countries, particularly India’s National Rural Employment Guarantee Scheme. However, in addition to these factors, strong economic growth in most of the world’s largest developing countries clearly provides a plausible explanation for the largely favorable trends in self-assessed data in these countries.

To examine disposable income issues more explicitly, we deflate nominal economic growth in recent years by changes in the food CPI rather than by an overall price index (as we did in some of the regressions in tables 6 and 7). This indicator is clearly an imperfect indicator of food security because poor people also spend money on nonfood items (but not much on fuel, which is the major source of nonfood inflation) and because mean GDP growth is often not 33
Grain Production in China_ , MacMillan, London, 1994.

27 A household survey in Zouping County, Shandong Province, collected between 1990 and 1994, shows that, when controlling for household off-farm employment, the effect of per capita land on incomes increases by approximately 10%. This result may be due to the effect of moving labor out of agriculture. As labors move off the land, other resources may be more efficiently allocated and the returns to land also increase. Controlling for employment, a one _mu (Chinese measure, equaling 1/15_<sup>_th_</sup> _of a hectare)_ increase in per capita land leads to a 36% increase in per capita household income. See Cook, S., “Employment, Enterprise and Inequality”, from Cook, Sarah, Shujie Yao and J. Zhuang, ed., _The Chinese Economy Under Transition,_ MacMillan (London) and St. Martin’s (New York), 2000.

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or mortgage are also much more likely to have a household member with higher education. We find that selfemployed households are not more likely to be indebted than households with wage income, which confirms that the more risky (self-employed) households are not more exposed to bank debt.

**Table 4.4.  Household Characteristics and Use of Credit**

||Full sample|A<br> <br>yes|ll househ<br>Credit car<br>no|olds (n=23<br>d<br>Sample<br>test|'525)<br>yes|Mortgage<br>no<br>Sample<br>test|Househol<br>yes|ds with mortg<br>FX mortgag<br>no|age (n=1'114)<br>e<br>Sample test|
|---|---|---|---|---|---|---|---|---|---|
|Income (USD)|4,107|5,702|3,559|***|5,744|3,957<br>***|6,219|5,381|**|
|Self employed||||||||||
|(1=yes)|0.13|0.13|0.13||0.14|0.14|0.11|0.17|***|
|University degree||||||||||
|(1=yes)|0.19|0.25|0.16|***|0.30|0.18<br>***|0.34|0.27|**|

Source: LITS survey and authors‟ calculation. Note: The
& Kopp, R. E. (2018). An Economist's Guide to Climate Change Science. _Journal of Economic Perspectives_ , _32_ (4), 3-32.

Hyland, M., & Russ, J. (2019). Water as destiny–The long-term impacts of drought in sub-Saharan Africa. _World Development_ , _115_ , 30-45.

<mark>Islam,Asif Mohammed & Hyland,Marie Caitriona, 2018. "The Drivers and Impacts of Water Infrastructure Reliability : A Global Analysis of Manufacturing Firms," Policy Research Working Paper Series 8637, The World Bank.</mark> Klein Goldewijk, K., Beusen, A. & Janssen, P. _Long-term dynamic modeling of global population and built-up area in a spatially explicit way: HYDE 3.1_ . The Holocene **20** , 565–573 (2010).

Kummu, M., Taka, M., & Guillaume, J. H. (2018a). Gridded global datasets for gross domestic product and Human Development Index over 1990–2015. _Scientific data_ , _5_ , 180004.

Kummu M, Taka M, Guillaume JHA (2018b) Data from: Gridded global datasets for Gross Domestic Product and Human Development Index over 1990-2015. Dryad Digital Repository. <u>https://doi.org/10.5061/dryad.dk1j0</u> 9
Improving data collection can facilitate better policies to enhance migration for development.<sup>29</sup> The development community can further leverage remittance flows for development by making them cheaper, safer and more productive for both the sending and the receiving countries. An ―International Remittances Agenda‖ would involve: (1) monitoring, analysis and projections; (2) improving retail payment systems through use of better technologies and appropriate regulatory changes; (3) linking remittances to financial access at the household level; and (4) leveraging remittances for capital market access at the institutional or macro levels (Ratha 2007).

As the labor market becomes increasingly global, the educational policies in developing countries will need to be revised to invest in skills that are needed within the country as well as in the global labor markets. On the other hand, the race for talent has led some destination country institutions to actively engage in recruitment of highly educated migrants, such as doctors. However, attempts to regulate skilled-worker mobility, or so-called ―ethical recruitment policies‖, does little to address the underlying causes of emigration decisions, and often leads to unintended adverse consequences (Clemens 2009). The freedom of mobility should thus be allowed for all skill-levels, while complementary measures can be developed to foster service provision and skill development in the source country.

Recruitment companies account often for the majority of the cost of migrating, especially when it comes to low-skilled migrants (Lucas 2005, p. 278) that can leave the migrant in debt, lower wages than promised, long hours and unsafe working conditions (see e.g. Chammartin 2005). Facilitating migration through safe and legal channels through better monitoring of recruitment processes and bilateral coordination will help to protect the rights of the migrants and fight exploitation and trafficking (UNDP 2009, p. 103). Providing knowledge about the migration process and language of the destination

> wide discrepancies were discovered between the true estimated remittance flows and the figures reported in the balance of payment statistics to the
one might expect it to face an exogenous international price of masks; in practice, we do not observe changes in the border price of masks. Despite this, we observe that large, statistically significant gaps emerge between domestic and border prices following mask mandates. We interpret this growing wedge between domestic and international mask prices as being potentially explained by either quantity restrictions on mask imports generated by international export restrictions on masks, or a reduced elasticity of demand for masks coupled with importer market power.

Second, domestic mask prices began to fall toward pre-COVID-19 levels starting in May, 2020, coinciding with the peak of domestic manufacturing of masks that followed initial licensing of manufacturers on April 17.<sup>2</sup> This coincidence provides suggestive evidence that domestic manufacturing decreased mask prices, but is insufficient to establish causality—alternative explanations that could have caused the observed decreases in the price of masks include increases in mask imports or decreases in demand for masks due to the reuse of masks. Establishing causality from these time series is even more challenging when COVID-19 infections are an outcome, as they were trending upward in Rwanda from March through August (just as they were globally), independent of domestic mask manufacturing. In Section 3, we therefore isolate exogenous variation in exposure to mask manufacturing across subDistricts to estimate the impacts of mask manufacturing on purchases of domestically manufactured masks, mask prices, and COVID-19 infections.

> 2We observe the licensing status and the imports of all firms in the EBM data. Though we cannot definitively rule out domestic manufacture by non-licensed EBM firms, we do not expect firms to formally record non-licensed production activity.

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The system of pensions (retirement, widow, orphan, and disability), health insurance, work injury, non-pension disability benefits, and unemployment benefits constitute Turkey’s traditional model of social security. They are all linked to employment in the formal sector and are financed by employer and employee contributions. The widow and orphan pensions correspond to survivors’ benefits when relatives receive the retirement pension of the deceased person.

Retirement pensions amount to 6.2 percent of GDP and a fifth of total spending, and this increases to a quarter when adding in widow and orphan pensions. Contributory disability and unemployment benefits constitute a very small share of the overall contributory pension system, under 1 percent of total spending.

Finally, an important program within Turkey’s system is the Minimum Subsistence Allowance (AGI), with a budget almost as high as the social assistance transfers. The AGI program is the exclusion of tax for formal employees who are over 16 years of age, with the size of the benefit depending on marital status and the number of children, but not on level of income. AGI functions as a tax allowance by subtracting the amount of the entitled transfer from the payroll tax paid by the employee. The AGI is paid to the employee by the employer on behalf of the state and deducted from the employer's income tax. We treat AGI as a transfer instead of a tax allowance in the analysis.

# **3. Methodology**

To study the distributional impact of fiscal policy in Turkey, we use the CEQ methodology (Lustig 2018). The CEQ is a comprehensive incidence analysis that uses data from household surveys and national accounts to assess the impact of taxes and public transfers on household poverty and inequality. The approach has been applied in over 70 countries, which allows to benchmark Turkey’s performance with relevant peer countries.<sup>8</sup> The method is based on an accounting approach; it adds and subtracts taxes and transfers to household per capita income to measure income
shows that surviving firms do not sacrifice labor quality in order to gain monopsony power. With regards to firm size categories, the difference in the magnitude of the coefficient between small and medium firms is very large for the surviving firms. Given that the coefficient for small firms is negative in column (4) emphasizes how small firms are more likely to use monopsony power in order to remain in the market.

# **6 Conclusions**

The gains from trade, either potential or realized, have been an enduring topic of interest over the past two decades. Improvements in productive efficiency have been the most investigated area in the literature. However, market power can distort the gains of trade. Therefore, this article examines the impact of trade openness on market power in order to gain a broader understanding of how trade openness and firm behaviour that could affect gains from trade. The article uses firm-level data to compute markups and degree of monopsony power.

Analysis of the trends in firm-level markups reveals different dynamics on the products and labor markets. Markups computed on materials gradually reduced over the decade, while those on labor followed an upward trend. To draw causal inference regarding the impact of trade openness on market power, insights from Bartik instrument strategy are used to design a quasi-experimental estimation method, which is robust to endogeneity and anticipation of trade policy, as well as trade policy uncertainties.

The results show that trade openness reduced market power on the product market through increased competition; firm’s price-cost margin decreased from 1 _._ 63 to 1 _._ 06.But wWhile market power decreased in the product market, it increased in the labor market through the firms’ degree of monopsony power. In the aftermath of trade liberalization, less productive small and medium firms compressed their real wages as a cost-saving strategy. Though the lack of a formal theory to explain the underlying mechanism is a shortcoming of this article, it is conjectured that this wage-compression strategy was made possible by a combination of factors such as lack of alternative
# **VI. Summary, Conclusion and Policy Implications**

Rice is a staple in Sierra Leone with an annual per capita consumption of 104kg—among the highest in the Sub-Saharan Africa region. Sierra Leone has ideal agroclimatic conditions for growing rice, including abundant rainfall, naturally fertile soils, sunlight and river basins; and nearly three-quarters of the country’s 5.4 million hectares is suitable for rice production. Sierra Leone has a natural comparative advantage in the production of rice and up until the mid-1950s it had been a net exporter of rice. However, except for a few instances in the immediate post-independence period, the country has not been able to achieve sustained self-sufficiency in rice production and consequently has spent an average of US$108.6 million on rice importation over the past 10 years.

The past efforts to reestablish sustained self-sufficiency in the rice sector have been mostly disappointing. Sierra Leone’s agricultural development policy has, since independence, focused on the achievement of self-sufficiency in rice, among other objectives, with most of the government support targeting smallholders but with minimal results. Questions have been raised about the impact of the waiver of the ECOWAS tariff on imported rice. These are key questions that have partly motivated this paper. The challenge is regarding what balance should be struck between the positive effects on consumer welfare of the lower price consequent on the waiver versus the adverse effects on producer welfare of the lower price, which mutes the supply response. The policy issue is complicated by the fact that some producers are also consumers when own-production falls short of household demand particularly during the “hunger season.”<sup>16</sup> The analysis in this study makes use of a programming model designed to produce a consistent quantitative framework for the Sierra Leone rice sector in order to simulate the effects of policy interventions as well as the potential impact of technical progress in the sector. The model is largely based on survey information collected in 2016. Importantly, the model is disaggregated across the five rice
A possible explanation for the good performance of unit-context models under the considered experiments could be due to estimated random effects, where _σ_ ˆ _ac_<sup>2</sup><sup>_>σ_ˆ</sup> _a_<sup>2,whichcoincideswiththe</sup> better performing scenario in subsection 3.1. Although this observation is likely a coincidence since the performance of unit-context models depends on the particular covariates included in the model and on the shape of the target indicator. Under the Mexican data with the covariates used, the unit-context model performs rather well. However, the method considerably lags all others for estimation of the welfare mean by area. A similar result is observed in the results presented in subsection 3.1.<sup>45</sup> Under the simulations of column 3 of Table 2, the gains in MSE for the unit-context methods appear to come in municipalities with larger populations.<sup>46</sup> This is expected because in our sampling scenarios, municipalities with a larger population are more likely to be included in all the samples. For example, in the census there are 16,293 PSUs spread over 1,865 municipalities. The median municipality in the created census has 7 PSUs, and the median municipality in a given two-stage sample is only represented by one PSU. Consequently, it is not surprising the unit-context variants under-perform relative to unit models in terms of bias and MSE in municipalities with smaller populations, as can be observed in Figure 16. For municipalities with larger populations, and hence those likely to consist of more PSUs and more of these PSUs in the sample, direct estimates for FGT0 are more precise and unit-context models begin to catch up to unit models (see Fig. 32 in the appendix).

Under the simulations from a 1% SRS by PSU, shown in Table 2, column 4 and in the appendix Figures 29 and 30, we notice the unit models ( _CEBa_ ) present a slight upward bias that seems