rafmacalaba/datause-encoder-data huggingface dataset:
not only be able to improve their ability to respond to possible immediate difficulties, but can also address long-standing development needs supporting the preservation of asset values in situations where financial institutions must undergo restructuring or be resolved.

# **4. THE CHALLENGE OF GLOBALIZATION**

Integration into international financial markets has been a second important and controversial aspect of financial-sector policy over the past decades. Although capital account restrictions are still in place in many countries, these are often more de-jure than de-facto. And while capital account liberalization has many benefits, it has to be managed carefully on the macroeconomic level and accompanied with appropriate regulatory policies. The benefits of increased capital inflows will be reaped only in the presence of well-developed local financial institutions and markets, but capital inflows can in turn accelerate financial and institutional deepening.<sup>22</sup> As in the case of government interventions, a context-specific and pragmatic approach is therefore called for.<sup>23</sup> While there has been a focus on opening capital accounts toward developed countries, the potential of regional financial integration has been much less exploited, although there are large economies of scale to be reaped by cooperation in technical areas such as harmonizing approaches to bank regulation or payment systems.<sup>24</sup> Reducing if not eliminating intra-regional capital account restrictions can help deepen and broaden financial systems within the region. It allows more efficient risk diversification for financial and non-financial corporations alike. It can help overcome the scale problem for financing large projects, such as those in infrastructure.

> 22 See Kose et al. 2009 for a more detailed discussion on the threshold values for benefits from capital account liberalization and its “collateral” benefits.

> 23 For a more in depth discussion, see Beck et al. 2009.

> 24 World Bank 2007b.

22
to refugee settlements. In sum, whether proximity to refugees has different effects on host communities’ attitudes and behaviors in low-income contexts is an open question, which our study seeks to begin addressing.

Using the case of Uganda, we hypothesize that in low-income countries, communities with greater refugee presence will not experience a backlash against migrants and refugee policies as long as these policies (especially those related to resource allocation) ensure that said communities do not carry a disproportionate burden of hosting refugees. We examine redistributive efforts that are designed to ameliorate possible _congestion effects_ .

Uganda is an important setting for exploring how refugee presence might affect host communities. Home to 1.4 million refugees (the most in Africa), it is the fourth-largest refugee-hosting country in the world and the seventh largest in the world on a per capita basis (UNHCR, 2020). Uganda has adopted relatively generous hosting policies such as maintaining an “open door” for displaced persons; allowing refugees to freely move and participate in economic activities; granting plots of land for permanent shelters and farming; and, with the help of humanitarian aid agencies, providing access to health care and education services (Ronald, 2020). Given the sheer scale of the refugee inflow and its welcoming asylum and refugee policy, our finding that Uganda has _not_ experienced a backlash against refugees among those most directly affected by the country’s asylum and refugee policies offers important lessons.

To explore the effects of refugees’ presence in Uganda, we combine publicly available geocoded Afrobarometer survey data with newly constructed fine-grained georeferenced panel data on service delivery in three domains: access to (primary and secondary) education, health care access and utilization, and road density. We focus on service delivery inputs rather than outcomes since service providers—governments, humanitarian organizations, and UN agencies—can directly affect access, but linking access to outcomes (such as infant mortality) is more complex, materializes with a long lag, and depends on several factors that are outside policy makers’ control. We use ACLED data to explore possible conflict dynamics.

We report two sets of findings. First, we find no evidence that a larger refugee presence increases support for restrictive migration policies (though in some years it is associated with a somewhat heightened sense of personal insecurity). Second, using a difference-in-differences (DiD) research design, we find robust evidence that access to education, health care, and roads significantly improved for those living near refugee settlements, and that these residents recognized 4
13 As in Pakistan, the majority of the ow ers of STWs are medium to large landholders. Yet the substantial growth in STWs has benefitted the small landholder through a more active water market. In one World Bank funded project area it was found that for each STW owner, there were about fourteen water purchasers. A Bank study found that for each hectare irrigated by an STW owner, water purchasers irrigated another 2 hectares. At present, Bangladesh apparently has ample quantities of groundwater to supply a continuing growth in tubewells.

Private wells development has also become increasingly popular in India and has been strongly encouraged by government policies. The government has provided low interest loans, through the National Bank for Agriculture and Rural Development (NABARD), for the purchase of pumps. In addition, a flat rate for electricity use was introduced in 1982. The result was rapid exploitation of the available water with electric pumps. Since farmers with electric pumps do not face a marginal cost for the open access groundwater that they pump, there is no incentive to conserve water. Furthermore, farmers can sell pumped water to neighbors who do not own their own pumps at prices below the margina. social cost. The result has been a rapid decline in the water table in a number of areas. For example ,in parts of the states of Tamil Nadu and Karnataka the average water table level dropped from only 25 to over 160 feet below the surface (Chandrakanth and Romrn, 1990). These declining water tables greatly increase the cost of pumping, cause the failure of many shallow wells, and result in an ecological imbalance in environmentally sensitive areas. Thus unrestricted private tubewell development can have a significant negative effects overtime. This could be corrected by establishing tradeable groundwater rights or by effectively regulating well installation and withdrawal rates.

# C. Decentralized Delivery **of** Water Supply

In many developing countries the performance of the water supply delivery organizations is poor, with maintenance a chronic problem. Many water supply systems are plagued by high levels of
the total quantity of tobacco produced in Malawi underwent little variation over the same period. In the end, the participation of smallholders in total production and exports of tobacco grew as well. A similar picture is uncovered by Figure 2, which reveals a positive correlation between the proportion of burley produced by smallholders and the ratio of clubs to tobacco growers in a cross-section of districts in 2004. This implies that the districts characterized by high smallholder tobacco participation are those districts where burley tobacco clubs tend to be more popular among tobacco growers.

Before formally exploring the relationship between burley clubs and smallholder tobacco production, we describe some basic characteristics of this nonmarket institution. Each tobacco club is governed by a set of rules and regulations, and provide various services to abiding members. We discuss these rules, regulations, and services next.

# **2.1 Tobacco Club Constitutions: Rules and Regulations**

Tobacco clubs are ruled according to their own regulations. These establish the rights and duties of the members, the structure of governance, the acceptance of new members, and the renewal and withdrawal of membership. Often, these regulations can be found in a written document, a club “constitution.” One instance of such document is in Figure 3, which displays the written rules of the Zebedayo Tobacco Club. In other cases, the regulations are just part of the common knowledge of the members.<sup>9</sup> For our purposes, it is important to quantitatively describe the main barriers to club participation. Some of these regulations comprise a sort of eligibility condition that can be exploited to achieve identification in our empirical analysis. In order to document these regulations, we set up the Tobacco Clubs Survey (TCS) in the summer of 2007. The TCS was deployed on 238 clubs nationwide with the aim of collecting basic information on the structure of clubs, their mandate, major problems and constraints, and key services. The TCS is described in Appendix 1.

Table 1 summarizes the main regulations of tobacco clubs in Malawi. Almost all of the

> 9Written constitutions exist even in these cases. However, they are usually stored in the bank where the club has an account at the time of registration. The rules are then passed from one member to another by word of mouth.

7
- 40 -

# Streeten, P. (1986) "Structural Adjustment: A Survey of the Issues and Options", Boston University, processed.

# World Bank (1988) "Interim Report on Adjustment Lending", Strategic Planning and Review Department, Report No. R88-15.

# (1987) World Development keport.

- (1987a) "Trade and Industrial Policies in the Developing

- Countries of East Asia", Report No. 6952.

- (1987b) "Annual Review of Bank Operations FY87: Industry,

- Trade and Finance", Industry and Energy Department, Preliminary Draft.

- (1987c) "Strategic and Design Issues for Agricultural Projects

- in Sub-Saharan Africa", Agricultural and Rural Development Department, Preliminary Draft.

- (1986a) "Structural Adjustment Lending: A First Review of

- Experience", Operations Evaluation Department, Report No. 6409.

- __ _ (1986b) "Sector Adjustment Lending", Progress Report CPD, Report No. 1986-9.

- _______ (1986c) Poverty in Latin America, The Impact of Depression, September.

- Yagci, F. et al (1985) "Structural Adjustment Lending: An Evaluation of Proper Design", World Bank Staff Working Paper No. 661.

- Yagei, F. and S. Kamin (1986) "Macroeconomic Policies and Adjustment in Yugoslavia", World Bank, EPDCO, July, Processed.
<mark>Table 4: Poverty Dynamics from - Synthetic vs. Actual Panel Data</mark> <u><mark>Using Income as the Welfare Measure</mark></u>

|<br>Status in Year[1],<br>Year[2]|<br>Lower Bound<br>Estimates|<br>Truth|<br>Upper Bound<br>Estimates|
|---|---|---|---|
||[1]|[2]|[3]|
|_Panel A: Nicaragua_||||
|Poor,Poor|41.66|(32.57,39.77)|29.42|
|Poor,Non-poor|7.80|(6.10,10.20)|17.35|
|Non-poor,Poor|12.16|(14.78,20.50)|24.40|
|Non-poor,Non-poor|38.38|(34.38,41.66)|28.83|
|_Panel B: Peru_||||
|Poor,Poor|27.06|(20.47,23.81)|16.15|
|Poor,Non-poor|7.54|(11.89,14.63)|20.23|
|Non-poor,Poor|3.74|(7.52,9.78)|14.65|
|Non-poor,Non-poor|61.66|(53.93,57.93)|48.97|
|Observations Panel A|684|684|684|
|Observations Panel B<br>Data source: Nicaragua|2,368<br>EMNV 2001, and|2,368<br>2005; Peru Per|2,368<br>uvian National|

<mark>Data source: Nicaragua EMNV 2001, and 2005; Peru Peruvian National Household Survey (ENAHO) 2008 and 2009. Note: R-squared is calculated for opposite halves of the total 2008 sample. Results are constrained to the panel sample of households whose heads are between 25 and 65 years old. Results are weighted using household-level survey-sampling weights. Results in columns [1] and [3] are based on a model with household time invariant characteristics, sub-national controls from census, and interactions between household time invariant characteristics and sub-national controls. Panel A shows results for Nicaragua, while panel B shows results for Peru+A2. Results in column [2] show actual mobility. 95 percent confidence interval between parentheses. Upper bound estimations are based on 50 repetitions.</mark> 27
Another body of literature has examined the impact that infrastructure improvements have on poor people and social outcomes. An extensive survey of the literature by Brenneman and Kerf (2002) finds strong evidence of positive impacts of infrastructure on education (particularly for transport and energy services), and on health outcomes (especially for water/sanitation, energy and transportation, although less so for telecommunications). Datt and Ravaillon (1998) find that between 1960 and 1990 rural poverty levels changed considerably in Indian states—and that states starting with better infrastructure and human resources saw significantly higher long-term rates of poverty reduction. Deninger and Okidi (2003) obtain similar results in exploring factors underlying growth and poverty reduction in Uganda during the 1990s. Their work indicates the importance of improving access to basic education and health care, but progress also depends on complementary investments in electricity and other infrastructure. Fan et al. (2002) document the critical role of infrastructure development, particularly roads and telecommunications, in reducing rural poverty in China between 1978 and 1997. The authors show that poverty fell because of the growth in rural nonfarm employment that followed expansion of infrastructure.

Access to infrastructure can have little effect, however, if services are not affordable, and appropriate pricing of services often has been the most controversial aspect of sector reform. Governments must bear this in mind when setting service prices—particularly when average prices must cover average costs to support private sector participation. In the past, cross-subsidization was the most common method for dealing with this issue, but this created perverse incentives against networks expanding to serve poor households. More recently, other solutions have been pursued. A large body of experience across 9
# **1 Introduction**

The Sustainable Development Goals (SDGs) lay out an ambitious agenda including that of achieving gender equality by 2030. This agenda is paired with a set of goals and targets measured by concrete indicators and is adopted by nearly all countries. SDG 5 focuses on gender equality and sets 9 measurable targets (with 14 indicators) on issues that especially affect women and girls (United Nations, 2022). But gender cuts across a far wider range of the SDGs than just the indicators under Goal 5. For example, SDG 3 on ensuring good health and well-being includes a target on reducing maternal mortality (target 3.1). The SDG agenda also calls for sex disaggregated data across several goals where monitoring of gender disparities is essential for effective policy. For example, SDG 8 on promoting decent work and economic growth sets a target of achieving full employment and equal pay for all women and men (target 8.5). These gender data are promoted as key to understanding if and how patterns of progress differ between women and men or girls and boys (UN Women, 2022). Countries are, however, falling short on reporting on gender-related indicators of the SDGs. This paper analyzes the patterns underlying these data gaps.

The objective of this paper is to look at this globally agreed-upon set of gender data indicators and identify key country patterns related to the existence, or lack of, such data. We focus on the availability of data reporting on the SDGs since they represent an internationally agreedupon set of goals to meet and for countries to report on (UNSD, 2022).

Missing gender data is not a new concern. There are different approaches to diagnosing the causes of the lack of gender data. One approach put forth by Bonfert et al (2022) emphasizes four obstacles to more gender data (Figure 1): (i) lack of data sources such as core and/or specialized surveys, censuses or relevant administrative data (that is, the data simply are not collected); (ii) methodological flaws in data collection (e.g., collecting land holdings of households but not 2
moments are obtained from the hp-filtered cyclical components of per capita output, consumption, and investment.

The trend in one of the key variables of the present analysis, namely, relative consumption volatility, is depicted in figure 4. The mean of relative consumption volatility shows an increase in the post reform period (figure 4).

The change in business cycle facts for the Indian economy from 1951–2009 are depicted in table 4. Per capita Real GDP has become less volatile in the postreform period in India. The _level_ of volatility is still high and comparable to emerging economies. The absolute per capita consumption volatility, as well as the relative consumption volatility with respect to output, increased in the post-reform period. Per capita investment volatility show a small decline in the post-reform period, while volatility in investment relative to output volatility has increased following reform. Contemporaneous correlation of consumption and investment with output has increased in the post-reform period. No significant persistence in the output and consumption cycle is seen in the pre-reform period. In the postreform period, output and consumption cycle are observed to have higher persistence. Persistence in the investment cycle rises in the post-reform period.

There has been a sharp increase in access to finance after reforms. The ratio of bank accounts to total population was merely 20% in 1980; it has jumped to above 70% in 2010, except for a period of decline in the trend during 1990–2005. Similarly, bank branches per 100,000 population in 2010 were more than double the value in 1970.

As seen in table 4, relative consumption volatility in India has risen from 0.83 during 1951–91 to 1.04 during 1992–2012. Thus, after improved access to savings instruments and credit, fluctuations in consumption relative to fluctuations in income has increased.

_Calibration_ 20
<mark>coefficient of the shock itself, which implies that 4Ps is able to provide only partial rather than full protection to the consumption of 4Ps beneficiaries.</mark>

**Table 2:  The impacts of typhoons on PCE and access to 4Ps (using wind damage index)**

||PCE<br>Total<br>(1)|PCE<br>on Food<br>(2)|PCE<br>Non-Food<br>(3)|PCE<br>Protein<br>(4)|PCE<br>Fruit<br>(5)|PCE<br>Cereal<br>(6)|PCE<br>Education<br>(7)|PCE<br>Medical<br>(8)|
|---|---|---|---|---|---|---|---|---|
|f203_hy|-0.0856|-0.125*|-0.0371|-0.307***|-0.00294|-0.0462|-0.0203|-0.0664|
||(-1.64)|(-2.44)|(-0.54)|(-3.87)|(-0.03)|(-0.99)|(-0.12)|(-0.39)|
|4Ps|-0.105***|-0.0731***|-0.154***|-0.160***|-0.0460***|-0.0019|-0.0705***|-0.118***|
||(-20.45)|(-15.86)|(-22.52)|(-19.92)|(-5.96)|(-0.42)|(-3.96)|(-7.09)|
|4Ps x<br>f203_|||||||||
|hy|0.0612|0.0938*|0.0285|0.096|0.0519|0.049|-0.0182|-0.00051|
||(1.41)|(2.31)|(0.47)|(1.35)|(0.80)|(1.06)|(-0.10)|(-0.00)|
|adj. R2|0.618|0.473|0.628|0.349|0.279|0.134|0.275|0.244|
|N|167,960|167,956|167,960|167,134|167,275|167,558|100,366|144,019|

Notes: Additional explanatory variables included but not reported here: family size, head is female, age of head, marital status of head, education level of head, head has a job, building type (single house vs, apartment etc.), type of material for roof, type of material for wall, floor area, type of toilet, water source, and separate binary variables for semester, year, and region, along with a complete set of interactions among these binary variables. Standard errors are corrected for clustering at the barangay level.

# Testing the robustness of the results

## (i) Changing the reference period of the shock

Table 3 presents estimates of the impact of typhoons by changing the reference period over which the index is calculated. The shock variable f203_bhy, is constructed using the maximum wind speed observed in the barangay during the first half (or the first 6 months) of the 12-month period preceding the month of interview of the household. This change in the ff reference period offers the opportunity to investigate the possibility of lagged effects of typhoons on the outcome variables of interest. The results in table 3 reveal that there are no significant lagged effects of typhoons on total household PCE or any of its components.

17
and Imbens, 2006). Bertrand et al. (2004) provide some evidence of standard error consistency issues in difference-in-differences estimates due to serially correlated outcome variables. Following Bertrand et al. (2004), I investigate the robustness of my inference. To do so, I collapse the time series information, for each merchant, by taking the average of the outcome variables in the pretreatment and post-treatment periods. Then I regress, in the cross-section of merchants, the change in outcome variables (i.e., the change in sales and number of new customers) between the pretreatment and the post-treatment period on a dummy variable for the treatment group indicator. I perform this exercise both on the matched sample (Panel A, Table 9) and on the full unmatched sample (Panel B, Table 9). Both tests give similar results to the original panel.

Abadie and Imbens (2006) point out the inconsistency of the standard errors for the matching estimators. Since my main analysis is performed on the matched sample based on nearest neighbor propensity score matching, I use the correction procedure proposed by Abadie and Imbens (2006). To do this, as before, I reduce the panel to a single cross-section and use the change in outcome variables between the pre-treatment period and the post-treatment period as dependent variables. Following the literature on non-parametric matching estimators (Imbens, 2004; Abadie and Imbens, 2006), I estimate the treatment effect based on the binary status of treatment group. I study two different specifications of matching estimators: nearest neighbor and radius with caliper. Results in Panel C-D of Table 9 show that merchants with contactless technology (the treatment group) respond robustly to the shock compared to merchants without contactless payment technology. Throughout the robustness tests, my main conclusions remain very similar and robust.

31