rafmacalaba/data-use-mentions-extended huggingface dataset:
Table 8: Weather index insurance costs and payments

|(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|
|Year|Amount Insured|Premium Payments|Indemnity Payments|Loss Ratio - (4)/(3)|
|(MXN 000)|(MXN 000)|(MXN 000)|(MXN 000)|(%)|
|2005|662,017|100,900|105,084|104|
|2006|874,768|103,032|21,529|21|
|2007|913,875|116,196|40,426|35|
|2008|1,456,329|239,549|84,509|35|
|2009|1,516,464|215,372|216,490|101|
|2010|1,202,618|240,493|217,220|90|
|2011|1,980,761|424,359|406,930|96|
|2012|1,567,581|422,666|105,472|25|
|2013|1,828,452|468,743|150,033|32|

Note. Figures are calculated from policy data for all weather index policies. Amounts are in thousands of Mexican Pesos. The loss ratio in column 5 is calculated as indemnity payments (column 4) divided by premium payments (column 3).

32
currency devaluation, Azerbaijan’s local currency, the Manat, remained stable. However, what was felt in the economy and in particular in sectors such as trade and construction was the drop in oil prices. Sectors that remained more or less unaffected were those which are mainly independent from international markets such as agriculture. Thus, the vulnerability of the Azerbaijani economy mainly stems from the lack of diversification which will remain a challenge for the future (Hübner and Jainzik (2009)).

With respect to the banking sector, indeed most banks had to stop lending at some point and the quality of the loan portfolio deteriorated from 2.2 to 3.2 percent of loans being delinquent by more than 90 days in the first quarter of 2009 (Central Bank Azerbaijan (2009)). With respect to deposits, crisis-effects were visible as business clients increasingly withdrew their savings to keep their businesses going and households attempted to convert their savings from Manat to USD due to their fear that the Manat would devaluate. The Central Bank provided comprehensive stabilization measures in the third quarter of 2008 which included, among others, an emergency facility for liquidity support and a decrease in the refinancing interest rate from 12 to 3 percent (Hübner and Jainzik (2009)). And while the low financial intermediation would otherwise be considered unsatisfactory, it helped the banking sector to remain somewhat immune against the effects of the crisis as the sector as a whole is only integrated into global financial markets in a limited way. Nevertheless, those few banks which are globally connected directly felt the effects of the turmoil in financial markets. Apart from that, all Azeri banks had to deal with an increase in their customers’ risks when the economic crisis hit the country.

# **3 Institutional background, data and methodology**

# **3.1 The bank**

The data we use for the empirical analysis was generated using the Management Information System (MIS) of AccessBank Azerbaijan.<sup>**9**</sup
# **3. Data and Descriptive Statistics**

# **3.1.Data**

Different data sources are used on trade, incomes, labor market outcomes, and migration at the municipal level. First, the data on exports by municipality, year, and sector supplied by the tax authority of Mexico (Servicio de Administración Tributaria) cover each municipality in 2004– 14. Data are reported using the 2002 Harmonized System classification at the 4-digit level and converted to the International Standard Industrial Classification (Revision 4) classification using correspondence tables.<sup>4</sup> The poverty headcount ratios, Gini coefficients, and mean incomes by decile at the municipal level have been estimated using the poverty mapping methodology (Elbers, Lanjouw, and Lanjouw 2003). The data are available for 2000, 2005,

> 3 For example, Autor, Dorn, and Hanson (2013) estimate the impacts of import competition from China on local US labor markets by combining the initial local distribution of employment across sectors and nationwide changes in imports from China by sector. They instrument this variable using changes in Chinese imports by other highincome countries.

> 4 See UNDESA (2008); HS (Harmonized Commodity Description and Coding Systems) (database), Statistics Division, Department of Economic and Social Affairs, United Nations, New York, https://unstats.un.org/unsd/tradekb/Knowledgebase/50018/Harmonized-Commodity-Description-and-CodingSystems-HS.

6
# **1.  Background**

With a GDP per capita of around $100, Ethiopia is one of the poorest countries in the world. Life expectancy, literacy rates, and other indicators of human development are all extremely low. Spells of drought, with resulting famines, have a strong impact on the whole economy and have led over the past three decades to a high degree of output and income volatility (see Figure 2). Changes in rainfall have a substantial impact on consumption growth, which appears to persist for several years (Dercon (2004)). Domestic savings, at slightly above 2 percent of GDP in 2002, are too low to meet the country’s investment needs. As a result, foreign borrowing and foreign aid increased significantly during the 1990s.

After a long period of continuous deterioration due to detrimental economic policies pursued during the communist regime (1974-91), the downward trend in real income per capita was reversed in the 1990s. Real GDP grew at an average of 3.6 percent per year over the 1992-2002 period. This led to an increase of 1.5 percent in income per capita. By the end of the 1990s, the level of income was back to the all time high achieved in the early 1970s. As a result, poverty declined during the 1990s. However, the magnitude of this decline remains a matter of debate. Official sources, based on household surveys, indicate that the poverty headcount index was 44.2 percent in 1999/00 for the country as a whole, down from 45.5 percent in 1995/96, whereas inequality changed relatively little, with a Gini coefficient of 0.29 for 1995/96 and 0.28 for 1999/00 (see Federal Democratic Republic of Ethiopia (2002)). By contrast, Bigsten et al. (2003), in a study focusing on the period 1994-97 but with surveys of smaller size, found very different results. They decomposed changes in poverty into growth and redistribution
_Figure 8: The development of idiosyncratic versus covariate shocks_ <!-- Start of picture text --> Idiosyncratic over covariate shock ratio (2016-2019)<br>4.0<br>3.4<br>2.9<br>3.0 2.5 2.6 2.5<br>2.2<br>1.9 1.9 1.8 1.9<br>2.0 1.7 1.7<br>1.0<br>0.0<br>2016 2017 2018 2019<br>All Rural Urban<br><!-- End of picture text --> _Source: World Bank estimates based on EHPM (2016-2019)_

**To sum up, the decrease in vulnerability to poverty over time is connected to a parallel decrease in poverty.** Given the decrease in poverty, the share of households close to the poverty line is lower. Related to this development, a lower share of households switched their poverty status, which then also lowers the rate of households being vulnerable. Poverty-induced vulnerability decreased and risk-factors play a more significant role in vulnerability to poverty. These developments are not in contrast to parallel increases in operational vulnerability (Robayo-Abril and Barroso, 2022), given that operational vulnerability takes a static perspective towards vulnerability to poverty. Operational vulnerability and ex-ante vulnerability therefore do not reflect the same group of people.

# **6. Robustness Tests and Sensitivity Analysis**

**To validate our findings, we conduct several robustness tests and a sensitivity analysis.** First, we estimate several model specifications and compare their results to each other. Next, we account for potential measurement errors in the underlying income variable. We then take advantage of the fact that 50 of the included municipalities are autorrepresentative, meaning direct estimates from the household survey are representative for these 50 municipalities, given their sample size. This analysis is useful for the estimation of covariate vulnerability.
they are already posting in a group where the location is apparent, and thus such messages would not appear in the `Location Mentions` and `Return Date` datasets but would in the `Researcher Coded` dataset. For the image analysis we used all images posted in the `Researcher Coded` dataset groups, a final image set of 24,304 images. Of these images, 921 are from areas with both IDPs and returnees, 9,001 are from areas with only returnees, and 14,382 are from areas with neither. None of the `Researcher Coded` groups are from areas with only IDPs.

To better understand displacement and return flows rather than solely IDP settlement we incorporate monthly data from OCHA which is compiled from a variety of humanitarian actors following methodology agreed to by an inter-agency IDP task force (OCHA (2021)). This data contains information on displacement out of and return to communities starting in January 2019. Though this dataset, as discussed above, is somewhat smaller than the REACH dataset– especially in terms of return– it has increased granularity regarding the size of return and displacement movements. We associated the data with location by postal code for the seeded return and displacement datasets resulting in a displacement percentage dataset of 41,434 messages from 316 locations and a return percentage dataset of 62,434 messages from 184 locations.

# **4.3 Methods**

Our primary analysis uses unsupervised tools for text and image analysis. For text analysis, we use structural topic modeling (Roberts et al. (2014)) and seeded topic models using words from word2vec (Mikolov et al. (2013)). For image analysis, we use feature extraction and clustering to obtain ‘visual topics.’ Structural topic models identify topics in text data, assigning a probability of belonging in a topic to each word. We run two unseeded models: the `Location Mentions` model with a four-way variable identifying locations as ‘IDP only,’ ‘Returnee Only,’ ‘
!-- End of picture text --> Note: variances on types of Arab script poses specific challenges to the teaching and the assessment of learning in the Middle East region. Source: Author’s calculation. All underlying numbers can be found in table A.2 in the annex.

# Final remarks

This paper has expanded the concept of learning poverty, drawing from the poverty measurement literature to present axiomatic properties of poverty measures and building on the FGT family of poverty measures to provide an extension of distribution-sensitive measures of learning poverty. The paper has presented conceptual, numerical, empirical, and practical reasons why this extension can be useful for measuring the consequences of COVID-19 school closures and comparing those consequences over time and across countries.

Three simulation scenarios explored potential learning losses, expressed in terms of the World Bank/UIS learning poverty indicator. In the most pessimistic scenario, learning poverty in low- and middle-income countries was expected to increase 20 percent, or 10 percentage points, going from 53 to 63 percent. Most of that increase might occur in lower-middle-income and upper-middle-income countries, especially in East Asia and the Pacific, Latin America and the Caribbean, and South Asia. Africa, and the group of lowincome countries, both with the highest levels of learning poverty before the COVID-19 pandemic, could have the smallest absolute and relative increases in learning poverty due to COVID-19-related school closures. The small size of those increases simply reflects the magnitude of the learning crisis in those countries before the pandemic.

Building on the FGT class of poverty measures to complement learning poverty measures with measures of a learning poverty gap and learning poverty severity, the discussion showed that Africa is the only region where the learning poverty depth might increase more than the learning poverty breadth.

30
Anopheles mosquitos, but mosquitos ...nd it di¢ cult to survive in high altitude. We use the proportion of land above 1000 feet elevation, and proportion of land under water in a DSD as indicators of malaria susceptibility of a DSD. Thus the interaction of district level malaria with ‘inland water’in a DSD is expected to have a positive sign in the ...rst stage regression for LDO incidence, while the sign of the interaction of district malaria with elevation should be negative. We control for water body and elevation directly in the IV regressions to make the exclusion restrictions imposed on the interactions with district malaria prevalence more credible. Since we control for current malaria parasite infection (data for the year 1999) across DSDs, the historical malaria prevalence cannot pick up the e¤ects of recent malaria incidence. Note also that we

> 11 The 17 districts in 2002 correspond to 15 districts in 1937-41.

7
used land without title, and communally-used land (including that for village heads).<sup>17</sup> We examined whether lack of titling in private land was associated with heightened conflict, and found very mixed results. In most specifications the results were insignificant. In urban areas in the absence of provincial dummies the variable was actually associated with lower conflict. Rural results for NTT seemed to be more in line with expectations, but were not significant at the 5 percent level. The results underscore that formal title does not necessarily denote security of tenure, the absence of which could fuel conflict (World Bank 2003b).

We also constructed indicators from the PODES that are set to one if mining or forestry are the mains sources of household income. For both of these sectors, property rights are ill defined. We did not find any significant effects of these variables on conflict, except in the case of East Java, where villages that depended primarily on mining were associated with higher levels of conflict.

**_Hypothesis: Group diversity is associated with increased conflict._** The 2000 Population Census collects self-reported ethnic status, a first for Indonesian household questionnaires since before the start of the New Order.  Over 1000 different ethnic groups were reported.  We use the responses to these answers to construct a sub-district level indicator of ethnic diversity.  We were unable to develop village level measures because of the difficulty of matching the Census and the PODES at the village level.  The PODES provided a limited number of diversity measures at the local level, including the presence of multiple ethnic groups, whether there were different

> 17 Since only three quarters of villages provided a detailed decomposition of land use, we introduced a dummy to denote reporting and set the remaining values of this variable to zero.

26
Second, the bigger existing package of schemes for rural areas is not as important a factor as could have been expected in favor of rural governance. It is mentioned in Erein, Odisha and in the CTs in Bihar but the perception of trade-off depends on the social composition of the wards. In Erein, the loss of MGNREGS and IAY is seen as having a potential negative impact of becoming urban in the poor wards but this is not the case in wealthier wards. In Bihar, the inefficiency of MGNREGS, which has been stopped in the last six months according to our interviews, neutralizes the weight of public schemes. Rural schemes do not seem to make much of a difference, at least for the local elite.

A third difference, and an important one, between urban and rural governance is the bringing of urban bylaws and planning devices. In our case studies, except in Erein that is located in close proximity to a municipal corporation where urban planning and urban regulation apply, there is no direct reference to the trade-off related to urban norms. Conversely, in the statutory town of Jhanjharpur, the spatial expansion is partly driven by the absence of authorization for construction and cheaper land values in the surrounding villages.

Fourthly, access to better urban services, water, sanitation, solid waste management and drainage can be a major benefit of urban status since additional funds are provided for these. However, the analysis of census data on the growth of services (Table 6) does not necessarily corroborate that argument. The question of basic amenities is the main discussed topic in the governance debate. In Bishnugarh and Cherra, both the sarpanch believe that urban governance would automatically lead to better services and job opportunities, almost as a manifestation of faith that some external driver would change the settlement. This is shared by the residents and the elected members in Gopalpur whose preference is in favor of additional funds for urban services rather than rural public schemes. The Bihar case provides a more conflicting view and brings to the fore a facet of
consumers can have heavy nutritional and public health consequences given the reliance of the population, especially the poor, on fish as a key source of animal protein. Indeed, fish represents 47 percent of animal protein intake in Angola, 67 percent for the lower decile and 44 percent for the higher decile. The fishing sector has few forward linkages to the economy, only 2 percent of its supply is used as input and for 10 sectors out of 124. Hence, while cash transfers would help mitigate some of the impact, direct producer subsidy might be more efficient, provided it is well designed, given the strong and clear direct impact and the limited number of employers and workers in the sector (1.2 percent of the working force). In the transportation sector, the situation is different given the strong forward links the sector has with the rest of the economy, with 24 percent of sector’s supply used as inputs in 121 sectors out of 124. Here, given the importance of indirect channels, cash transfers are crucial to help households alleviate the impact of subsidy removal. Whether the cash transfer will be universal or targeted depends on the quality of censuses, surveys, and social registries. Still, simulations show that with 30 percent of the savings generated from subsidy removal (around 1 to 1.5 percent of GDP), the government could fully compensate for the increase in fishing and road transportation costs. This can be considered the upper boundary of the compensation package, regardless of the form and channels of this compensation.

# 6- Summary and policy implications

In response to the sharp rise in world oil prices in recent decades, many governments have introduced fuel subsidies to protect poor households. These subsidies are generally inefficient and generate significant socio-economic costs. In absolute terms, fuel subsidies benefit the rich more than the poor. In addition, they burden public finances, encourage over-consumption of polluting energies, and distort the allocation of production factors towards sectors benefiting from cheap fuel.

given the economic, social,
lack of absorption capacity in the informal sector. In addition, Ramachandran and Sasidharan (2021) find a

> 5 Other factors that can contribute to firms’ technology adoption include firm capabilities (including workforce quality; entrepreneurial ability and learning), linkages to FDI, access to finance, product market competition, access to infrastructure, and intellectual property rights policy. See Acemoglu and Akcigit (2012), Cirera and Maloney (2017), Cirera et al. (2022), Delera et al. (2022), and Verhoogen (forthcoming) for supporting evidence and reviews. At the country level, theory and empirical studies underscore the following factors that contribute to the speed at which a country adopts technologies: the country’s human and physical capital endowment (e.g., Chari and Hopenhayn 1991, Brezis, Krugman, and Tsiddon 1993; Basu and Weil 1998), type of government (or government capabilities; Cirera and Maloney (2017), degree of patent protection (e,g., Zheng, Huang and Yang 2020), and adoption of predecessor technologies (Comin and Hobijn 2004).

> 6 There are some studies analyzing value-chain linkages between formal and informal firms. For instance, Böhme and Thiele (2014) combine household and enterprise surveys from six West African countries to study value-chain linkages between formal and informal firms. They find evidence that informal firms are more likely to purchase goods from formal firms (i.e., backward linkage).

4
(reduced) stringency of pandemic-control measures and voluntary social distancing trigger a decrease (increase) in consumption expenditures, employment, business investment, and foreign demand for exports. Moreover, a decrease in business investment lowers the level of potential output by reducing the capital stock.

In addition, the impact of COVID-19 on activity is reinforced by the financial and commodity-price channels in the Oxford Global Economic Model. An endogenous reaction of financial conditions, proxied by movements in the CBOE Volatility Index (VIX), captures volatile financial market expectations surrounding the pandemic’s projected evolution (Figure 3.A-B). Specifically, higher risk premia raise corporate borrowing rates, exacerbating the rise in the cost of capital.

In all scenarios, shocks to financial conditions notably affect real activity domestically, and those that occur in major financial centers such as the United States are assumed to spill over to other countries via the model’s financial channels. Lastly, the endogenous response of oil prices to global demand outcomes in the Oxford Model provides an additional spillover channel and dimension of differentiation across all scenarios (Figure 3.C).

# 4. Pandemic Scenarios

# Baseline scenario

In the baseline scenario, following a sharp resurgence that began toward the end of last year, many economies succeed in reducing the daily number of infections in the first half of 2021. The reduction in caseloads is made possible by a combination of stringent lockdown measures as well as less costly pandemic-control policies such as social distancing guidelines and universal masking. In advanced economies and major EMDEs (including China, India, and Russia), inoculation with highly effective vaccines begins in the first quarter of 2021—first to vulnerable groups and subsequently to the general population— becomes widespread in the second half of 2021 (Figure 2.A). Voluntary and mandatory social distancing eases gradually through the remainder of the forecast horizon. The vaccination process is expected to be delayed by two quarters in most other EMDEs and by four quarters in LICs, owing to logistical impediments to vaccine production and distribution
movable property as a major impediment to granting credit to firms.<sup>46</sup> Both the seizure and sale of assets are currently very challenging processes in MENA.

- **It is highly recommended that MENA countries introduce reforms in the enforcement procedures of the different jurisdictions to align the region with international best practices.** The reform of enforcement procedures and in particular the introduction of out of court enforcement procedures has had a considerable impact in lending in a number of countries (India, Romania, Slovakia), sometimes by introducing private enforcement agents and regulated out of court enforcement. A variety of policy options are available to the governments, ranging from: (i) introducing new extrajudicial mechanisms to enforce debts; (ii) introducing fast track or expeditious procedures in court for debt collection processes; (iii) improving the capacity of existing institutions through the use of ADR or strengthening execution agencies; (iv) improving the mechanisms available to financial institutions to sale the secured assets, by granting more freedom in the disposition method (private sale or public auction).

> 46 According to the 2010 World Bank MENA SME Lending Survey to Financial Institutions.

36