rafmacalaba/data-use-mentions-extended huggingface dataset:
## **CREATING A POVERTY MAP FOR AZERBAIJAN**

# **1. Introduction**

‘Poverty maps’, that is graphic representations of spatially disaggregated estimates of welfare, are being increasingly used to geographically target scare resources (Bigman and Deichmann 2002). There is also growing recognition that location itself is an important determinant of welfare, with the local agro-ecological resource endowment, access to input and output markets, and availability of educational and health facilities all influencing the well being of households. Conversely, household welfare may also have an important effect on the locality, for example local levels of consumer demand, patterns of cropping and deforestation. The development of detailed poverty maps in many settings is, however, hampered due to data constraints. Data on income or consumption are often unavailable and, where they are, direct survey estimates for small areas are likely to yield unacceptably large standard errors due to limited sample sizes. Census data offer the required level of coverage but do not generally contain the appropriate information. This has led to the development of a range of alternative methods aimed either at combining survey data with unit record data from the Census to produce estimates of income or expenditure for small areas or at developing alternative welfare rankings, such as asset indices, using existing census data<sup>2</sup> .

This study aims to develop a set of poverty maps for Azerbaijan which can be used by different users. Two alternative approaches are adopted. Firstly, a map is derived using imputed household consumption, combining information from the 2002 Household Budget Survey (HBS) with 1999 Census data (Section 2). Secondly an alternative map is constructed using an asset index based on data from the 1999 Census to produce reliable estimates of welfare at the district

> 2 <u>http://www.worldbank.org/poverty/health/wbact/health_eq_tn04.pdf.</u>

> See also <u>http://www.healthsystemsrc.org/publications/
Beneficiaries were selected based on a Proxy Means Test (PMT) (Del Ninno & Mills, 2014). The PMT formula was calculated from a regression of per capita consumption on basic household demographic and economic characteristics with data from a nationally representative survey (Katayama, 2010). A village-specific PMT eligibility threshold was then chosen so that 30% of the households were designated as beneficiaries in each village. Ex-post assessments of the targeting method show that the PPFS-CT targeting procedure is relatively efficient in reaching poor households (McBride, 2014). The transfers were delivered to a woman within selected households.<sup>10</sup> A distinct feature of the cash transfer pilot project is that it also promoted women’s participation in local saving groups known as _tontines_ . _Tontine_ members bring cash to a common pot each time they meet (daily, weekly or monthly). At each meeting, one member in rotation takes all the cash from the pot and invests it. _Tontines_ are an important vector for investments in rural Niger, and in Sub-Saharan Africa in general (Van den Brink & Chavas, 1997). The PPFS-CT encouraged beneficiaries receiving cash transfers to set-up _tontines_ , so that households could save and invest in productive assets. According to project managers, almost 90% of the beneficiaries took part to these _tontines_ during the program.<sup>11</sup> The pilot program has several other noteworthy features, which makes it particularly relevant to address knowledge gaps on the sustainability of transfer impacts on productive investments in low-income settings. First, the program targeted very poor, food insecure households in the rural Sahel, one of the poorest regions of the world where climatic shocks are recurrent.<sup>12</sup> Second, the program delivered small, regular, foreseeable, monthly transfers, which are distinct from the large transfers delivered as emergency response following seasonal shocks. Third, and most importantly, the transfers took place for 18 months between January 2011 and June 2012, and this limited duration
. With the aim of being as comprehensive as possible, the exercise covers central and subnational government expenditures, nonbudgetary vehicles (such as road funds and rural infrastructure funds), state-owned enterprises (SOEs), and public-private partnerships (PPPs) in which the asset ownership remains with the government. Although developed in the African context, the methodology is not specific to Africa but is relevant and applicable to any developing country.

The purpose of this guide is to document the data collection methodology developed for and tested with the AICD, thereby making it available to a wider community of practitioners, and promoting its further application, Any data collected using this framework can legitimately be benchmarked against the existing public expenditure database developed for Sub-Saharan Africa under the AICD.

When applying this methodology, several issues should be kept in mind. First, the SPI exercise focuses on the standardization of public spending across infrastructure sectors, aiming mostly at facilitating cross-sector aggregate analysis rather than providing tools for more nuanced sector-specific resource efficiency assessments. Second, despite heroic efforts by consultants in the field, some data may be missing. Even as public corporations and special funds are increasingly required to report their accounts, public records are not always comprehensive even when published. In particular, financial records for special funds financing rural infrastructure are frequently unavailable (for example, in Uganda) and SOE accounts rarely report cash flows, limiting the public knowledge of actual disbursements in capital projects.

8
,482|16,649<br>|6,827|316,636<br>|533<br>|
||[27,265]||[30,727]||[2,591,065|]|
|Thinks that it's difficult to know in advance|0.744|2,665|0.764|4,921|0.725|520|
|how much taxes she will have to pay|[0.437]||[0.424]||[0.447]||
|Ratio tax/ annual profit for all businesses<br>|0.051|3,482|0.072|6,174|0.128|445|
||[0.089]||[0.174]||[0.221]||
|Ratio tax/ annual profit for businesses|0.094|1,870|0.165|2,859|0.169|372|
|Notes: sources: listing‐baseline survey March<br>paying taxes|[0.104]<br>2014||[0.286]||[0.313]||

33
The finding that consultative procedures grant elites greater influence over allocation decisions results from the dominance of meetings by council members, who often overlap with pre-existing elites.<sup>17</sup> According to monitoring data collected during meetings, village council members had more influence than other attendees in the selection of projects in 98 percent of meetings. In 35 percent of meetings, the final choice of projects was made entirely by council members. This finding is consistent with Humphreys et. al. (2006), which observes discussion leaders‘ preferences to be a significant determinant of the outcomes of deliberative meetings.

One of the most important channels through which elites influence allocation outcomes is agenda setting. In both meetings and referenda, agenda-setting rules were identical, but the fact that the selection procedure was known in advance clearly affected the choice of the proposed projects. In particular, the council was more likely to propose projects that were preferred by elites if a meeting was mandated. This effect played a major role in these villages as, conditional on a project being proposed, male elite preferences had only a small effect on project choice.<sup>18</sup> As we would expect elites to be more likely to manipulate the list of proposed projects under referenda given their more circumscribed ability to influence the results thereafter, the result is somewhat surprising. Two complementary explanations are that, when setting agendas for meetings, elites compensate for expected attempts by villagers to change agendas during the meeting, while, when setting agendas for referenda, elites anticipate a broader political cost from diverging significantly from villager preferences given the immutable nature of the agenda.

The results indicate that female elites influence project choice only under meetings. Since female elites commonly share familial links with the male elites, this result is perhaps not entirely surprising. However, unlike male elites, who exhibit their influence primarily at the proposal stage, female elites have almost no influence on project proposal, but a significant impact on project selection and prioritization. The results also indicate
mobility. In particular, when income is measured on a per capita basis ( =1), there is always more aa upward unconditional mobility, regardless of the (different values for the) child parameter (Panel ee A). There is also mostly more upward conditional mobility, except for when the child parameter falls in the interval [0.09, 0.1] (Panel B). Yet when income is measured on a square-root scale, we have more upward unconditional mobility when the child parameter ranges from 0 to 0.03, a mixed situation when the child parameter ranges from 0.03 to 0.08, and even more downward mobility for the rest of the child parameter values. For conditional mobility, the square-root scale results in more downward mobility, for all values of the child parameter (Panel B). These results further emphasize the important role that equivalence scales have in determining estimation results with income dynamics.

# **6. Robustness Checks and Further Extensions**

# **6.1. Robustness Checks**

In addition, we examine a number of other robustness checks and extensions, which include income expectations, different reference groups, other satisfaction variables as dependent variables, measurement error in incomes, and no sample restrictions. We briefly summarize the results below.

Changes in household size or structure are typically expected and may affect subjective wellbeing well before their actual realization. We control for income expectations in the ( _t-1)_ period and find that this does not affect the estimates of baseline elasticity but slightly increases the child scale parameter up to 0.08 in the pooled model (Table 5, row 1).<sup>20</sup>

> 20 We analyze the answer to the following question in the RLMS “ _Do you think that in the next 12 months you and your family will live better than today or worse?_ ” The regression results are shown in Appendix A, Table A.7.

18
. As such, concerns about the ability of individuals to think about probabilities and alternative outcomes are likely to be less than with less‐educated respondents who are the focus of studies of smaller firms in developing countries. Only 17.4 percent of the sample is female, reflecting that males were much more likely to apply for the program.

In McKenzie (2015), I use this randomized assignment and follow‐up surveys to measure the impacts of this program. This is done separately for the new firm applicants and existing firm applicants, reflecting their different starting statuses. Winning is found to have large treatment impacts on both groups of firms. By the third follow‐up survey, new firm applicants are 37.3 percentage points more likely to be operating a firm, have 5.2 more workers per firm, and are 22.9 percentage points more likely to have a firm of 10 or 5
**Figure 10: Six-yearly transition matrices for females aged 20-53 in Mexico and Egypt**

||Private informal|**7**<br>22|21|2|47|21% (21%)|
|---|---|---|---|---|---|---|
||Private formal|7<br>**22**|21|2|47|19% (22%)|
|Mexico|Public formal|7<br>22|**21**|2|48|7% (7%)|
||Unemployed|7<br>22|21|**2**|48|2% (2%)|
||Out of labor force|7<br>22|21|2|**48**|50% (48%)|
||Private Inf|ormal<br>Private|Formal|Public|Unemployed|OLF|
||Private informal|**32**|2<br>2<br>2||62|9% (11%)|
||Private formal|18|**28**|17|3<br>34|1% (2%)|
|Egypt|Public formal|3<br>2||**84**||1<br>10<br>10% (10%)|
||Unemployed|8<br>2<br>4<br>**13**|||73|7% (5%)|
||Private informal<br>Out of labor force|9<br>1<br>1<br>5<br>Private formal|<br>Public|**84**<br>formal<br>U
same job—struggle to control for all other differences between the actors. They may also be subject to “demand effects” because actors are aware of their treatment status and do not have real incentives to perform well. Correspondence studies—where fictitious applications with different sounding names are sent to a possible discriminator like employers—can only measure coarse outcomes such as job application callback rates rather than actual job hiring (Bertrand and Duflo, 2017). In our setting, the daily name randomization eliminates omitted variable concerns, the name masking alleviates concerns about demand effects, and by studying real workplace interactions we can collect detailed outcome measures—e.g., the likelihood of purchase—and specifics of the interaction—e.g., bargaining behavior.

While customer discrimination may be a global phenomenon, it may be particularly important in the context of this study for a number of reasons. First, the share of women employed in the service industry in Sub-Saharan Africa has increased exponentially in the last decade. Identifying the scale of customer discrimination in these occupations will be increasingly relevant for female labor force participation in the long run. Second, social norms in Sub-Saharan Africa favor men over women as economic agents and in business, which may contribute to higher rates of customer discrimination. For example, data from the World Bank World Development Indicators (WDI) show that households in Sub-Saharan Africa are more likely to agree that men make better business leaders and that women have no say in decisions on large household purchases (Jayachandran, 2015). Finally, it is particularly timely to study these issues as gender inequity in the workplace has become a central policy goal for governments across the continent and international institutions alike (Bank, 2011; O’Donnell et al., 2020).<sup>2</sup> The results are striking: we find that randomly assigned female names reduce the likelihood that customers make any purchase, the number of purchases, and the value of the purchases. Specifically, the likelihood of
monitor village public goods and common property resources. The villages were sampled, following a natural experiment, to be matched by language and ecology across neighboring districts, which belonged to linguistically different states. Prior to 1956 these matched districts were part of the same state. Since the villages matched across the paired districts, spoke the same language, had the same ecological structure, the same caste structure, and had 300 years of shared history, they belonged to the same linguistic community. Everything else equal, they should have, therefore, had the same patterns of public discourse.

However, we found that deliberative meetings were very different in different states – which, because of the natural experiment, we could attribute to state government policy in implementing the 73<sup>rd</sup> amendment. Thus, we were able to show that deliberation – or what we call “oral democracy” to distinguish it from the kinds of deliberation theorized about in western countries – was possible in poor, highly unequal, contexts with low literacy, and that the quality of deliberation was less related to levels of inequality or literacy, but determined by state government policy. Moreover, our discourse analysis found that social distinctions were largely equalized within the context of these meetings because village elites were concerned about losing votes by suppressing voice. Thus, individuals from lower castes were just as likely to speak as those from upper castes, and topics raised closely matched the interests of the median voter in the village (Ban, Jha and Rao, 2012).

What characterizes these three research projects is their relatively small-N, which reflects the difficulty of analyzing narrative data. The transcripts of 300 village meetings in India, for instance, took me and my co-author ten years (with about two years of active work) to analyze; a process that required deep reading, careful coding, reflection, debate, analysis and writing. This trade-off is limiting, and in the next section I will discuss the advantages and disadvantages of machine learning tools, and
localities (respectively for the main and spillover samples). A common support cut-off is used, consistent with the identification strategy used to estimate equations 1 and 2. The experiment achieved satisfactory balance between the pooled treatment and control group, as well as between treatment modalities. There are few statistically significant differences, and they remain of small magnitude.

Table A7 illustrates how the study sample compares with the general population of individuals 18-65 years old in program districts.<sup>33</sup> Sample individuals live in larger households, are more likely to be female and not to hold a diploma. The activity rates, types

> 32This is in line with the composition of employment in Cˆote d’Ivoire, especially in rural areas (Christiaensen and Premand (2017)).

> 33This is based on data from a national employment survey.

16
and money laundering by high net worth individuals (“Swiss/Liechtenstein leaks”, “Mossack Fonseca Papers”).

International concern about potential weaknesses in the way international standards developed in the early part of the last century interact with modern ways of doing business is not new.<sup>4</sup> Similarly, governments in many countries had long-standing concerns about banking secrecy and the use of offshore financial centers for tax evasion. But the financial crisis gave these concerns new prominence and new urgency.

The first sign of a renewed determination to tackle cross-border evasion and avoidance came in April 2009, when the G20 meeting in London declared that the “era of banking secrecy is over”.<sup>5</sup> This led to several countries withdrawing their reservations to the exchange of information on request article contained in model double taxation agreements. The Global Forum on Transparency and Exchange of Information (the Global Forum) was restructured to strengthen implementation of the international standard on exchange of information, through a process of peer review. Subsequently, the standard itself was enhanced to encompass automatic exchange of information about financial accounts.<sup>6,7</sup> That new standard was codified as the “Common reporting Standard” (CRS) and supported by a Model Competent Authority Agreement.<sup>8</sup> The introduction of the CRS is a major development.<sup>9</sup> It is notable that the CRS requires information to be exchanged that includes details of the beneficial owners of entities, including trusts, that might otherwise be used to disguise the true ownership of financial accounts.<sup>10</sup> This is enhancing the ability of governments in both developed and developing countries to detect funds that have been lodged in undisclosed offshore accounts for the purposes of tax evasion and other criminal reasons.<sup>11</sup> Some behavioral changes in individuals’ use of offshore jurisdictions can already be observed. De Simone et al
Policy Research Working Paper 10000

# **Abstract**

This paper studies the impacts of the large-scale Road Sector Development Program in Ethiopia between 1997 and 2016 on local economic activity and land cover (urbanization and cropland). It exploits spatial and temporal variation in road upgrades across Ethiopia, together with high-resolution panel data derived from satellite imagery. The findings show that road upgrades contributed to increases in local economic activity, as proxied by nighttime lights and urban land area. However, there is significant heterogeneity in the results across baseline levels of economic activity. Specifically, gains from road upgrades are concentrated in areas with moderate-to-high initial levels of economic activity. By contrast, there was little, or even negative, growth in areas with low levels of initial economic activity. Finally, the findings show that road upgrades contributed to a reduction in cropland in areas with medium-to-high baseline nighttime lights. The results suggest that Ethiopia’s ambitious road infrastructure development program overall increased local economic activity and urbanization, but that it also had important distributional implications that need to be taken into account when planning such infrastructure programs.

This paper is a product of the Development Impact Evaluation Group, Development Economics. 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/prwp. The authors may be contacted at aduhaut@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

_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
this analysis. Textiles are also considered by themselves because, arguably, the textile industry is one of the most mature and sophisticated export sectors in Lao PDR and this is where the experience effects are expected to be strongest – this is indeed what is found (i.e. the diminution of the hazard rate from experience variables is the largest).

The last two specifications look at the impact of changes in the definition of death (i.e. the gap between two consecutive transactions is considered too long for it to be the same contract). The standard in the literature is 12 months (also to account for seasonal exports), but it is also customary to investigate whether the effect holds for 6 or 18 months. A death after only a 6 months break could be too radical because it would exclude, for example, exports of fruit that grow only once a year, or exports of warm clothes to Europe. In fact this alteration produces the most significant change, but even this is quite close to the Main specification.

Overall, the findings are confirmed and therefore strengthened by these checks. The coefficients do change, but not to a large extent, and the significance levels are sometimes diminished as compared to the specification of choice (Main). More importantly, though, the direction of the impact on the odds of termination is not changed in either of these alternate setups.

# **6 Discussion and Conclusions**

This paper has analyzed the exporter population of Laos for the period 2005-2010 at the level of monthly activity of individual firms based on a recent dataset of Customs transactions. Its analysis has focused on the impact of firm experience and network effects on the odds that a trade contract (operationalized as a firm-product-destination triplet) survives in subsequent months. This “micro” approach to export survival (looking at contracts rather than firms) was justified by the higher level of refinement with which such variables could be constructed. The analysis has not looked at changes in investment climate or trade facilitation