rafmacalaba/data-use-mentions-extended huggingface dataset:
invaluable insights on dimensions of governance.<sup>11</sup> Here we note that these types of data may also be thought of as imperfect proxies for the broader concepts of governance that that they measure, and therefore also are subject to margins of error. In addition, as a practical matter, such measures of corruption or other dimensions of governance most often are generated only for a specific country at a single point in time, and therefore cannot be included in a regularly updated cross-country dataset like the WGI.

Second, the data source must provide original primary data produced using a credible structured methodology, rather than simply be a compilation of existing data. For example, we do not use the Transparency International Corruption Perceptions Index as a data source for the WGI Control of Corruption Indicator because the Corruption Perceptions Index is itself a compilation of existing data sources and does not involve new data collection. Third, the data sources must cover multiple countries, so that cross-country comparisons are possible. For example, a survey of public officials carried out in just one country can be extremely valuable for diagnosing governance constraints across institutions within a country. However, if this survey is not also carried out with the same questions and methodology in other countries, it cannot be used in the WGI which is designed to inform cross-country comparisons. Fourth and finally, the data sources must be regularly updated – ideally annually – although we do use several data sources that are updated only once every two or every three years, in which case we use the most recently available data until a new update becomes available.<sup>12</sup> This requirement is needed for the data to be able to inform over-time comparisons of the aggregate indicators.

The number of data sources included in the WGI has increased over time. The WGI data for 1996 are based on just 12 data sources, while the data for 2023 are based on 30 data sources (see Table 1). This reflects a sharp increase over the past 25 years
the rich variation afforded by disaggregated trade data and does so in a manner that is motivated by and consistent with theory. We study the case of China and find that its exchange rate changes can have significant and robust spillover effects.

These findings may have important policy implications for developing countries and for the multilateral system if exchange rate movements (or the lack thereof) stem from policy actions. Since we have found that the resulting spillover effects are significant, one country’s policies can then potentially have substantial export implications for other countries.

Importantly, we would emphasize that this paper identifies precisely and in a robust way a very specific mechanism of influence from exchange rates to trade (the ―spillover effect‖ of Chinese exchange rate movements on exports of competitor countries to third markets). There could be other beneficial effects on developing country exports to China which we do not measure. For example, a depreciation of the renminbi could increase developing country exports of raw materials and intermediate goods to China to be used in the production of China’s exports to third countries. Similarly, if China’s depreciation boosts its own growth, that could increase its demand for all goods and services, which could also lead to greater developing country exports. Thus, the effect of China’s exchange rate on overall exports of other countries remains an open question. Finally, we have not directly estimated any effects of China’s exchange rate movements on its own exports. Further research is needed to precisely identify all these other effects.

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we provide regression results using GAP measures as dependent variable. Table C.4 shows the average technology sophistication by sector and country for EXT and GAP measures. Finally, we compute the cross-firm variance of technology sophistication by sector and country for of EXT and GAP measures in Table C.5.

For the regional analysis, we examine the relationship between technology and productivity at the regional-level. As explained above, we compute both region-level technology and productivity based on the FAT data, because the region level GDP per capita (or any other productivity measures) is not available in Senegal and Vietnam. For the region-level technology, we used three measures including the average, cross-firm variance, and average of within-firm variance of technology sophistication. Table C.6 presents the regression results of regional technology sophistication on productivity. Table C.7 shows the relationship between regional cross-firm variance and productivity. Finally, Table C.8 provides the relationship 70
<br>70%<br>IQD 50,000<br>60%<br>50% IQD 40,000<br>40%<br>IQD 30,000<br>30%<br>IQD 20,000<br>20%<br>IQD 10,000<br>10%<br>0% IQD 0<br>Unemployment Per Capita Consumption (IQD)<br>working member)<br>Per capita consumption<br>Unemployment (% of households with zero<br>Sep-17 Oct-17 Nov-17 Dec-17 Jan-18 Feb-18 Mar-18 Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 Dec-18 Jan-19<br><!-- End of picture text --> _Data Source_ : CLCI Legacy Database.

# 4.3 Likely Eligibility of Future Humanitarian Beneficiaries under MoLSA Targeting

Following the completion of the MCNA survey in 2018, the Cash Working Group (CWG) updated the vulnerability assessment criteria for their cash transfer programs. Since the new models were yet to be fielded, there was no database similar to the legacy database to perform similar analysis. However, we 18
11 The elasticity of population density for the total road equation is negative and statistically significant, suggesting that holding total population equal, lower population density (or higher per capita--and national--land area) is associated with longer total road length. The total road network in a country usually expands to connect all population distributed across the country. Therefore, a larger area requires more extensive road network to serve. In contrast, there is a weak relationship between population density and the total length of paved roads. This is because roads are paved for facilitating high volume of motorized traffic, instead of improving connectivity to human settlements and economic activities. Empirical analyses by Canning (1998) also provided similar findings.

Road provision at the urban level differs greatly from that at the national level. The urban results shown in Table 3 are based on panel data from 36 cities in both developing and developed countries, and the elasticities take into account the strong negative correlation between per capita income and population density at the urban level. (The results are from equations using the historical spatial endowment index, Appendix tables 5 and 7.) As the results indicate, urban road length has a population elasticity of 0.8, suggesting a decreasing scale effect. The elasticity of urban road length with per capita income is non-constant (increasing with income), and its elasticity with population density (negative) is much stronger than at the national level. Another maj or difference with the urban results is the relatively large differences between the long run (cross section) and short run (first difference) elasticity estimates--particularly for the elasticity of road provision with respect to income. Urban road length increases over time very slowly with income. The first difference elasticities of population and population density are also smaller than the cross section estimates. The cross section data and equation estimates of the relation between road length and income are summarized in Figure 3.

The strong non-linear relationship between urban road length and per capita income reflects the non-linear relationship
mean and standard deviation.<sup>7</sup> As a measure of the child-parent relationship, we collected self-reports from the primary caregiver on how often they used various parenting practices related to their warmth, consistency, and hostility. The questionnaire was adapted from the Longitudinal Study of Australian Children (Zubrick et al. 2008). Higher total parenting scores correspond to higher levels of warmth and consistency, and lower levels of hostility. We standardized the variable to have a mean of 0 and standard deviation of 1, using the younger cohort’s mean and standard deviation.

# **4. Empirical Strategy**

To estimate the causal effect of the project on the younger cohort, we would ideally compare the change in outcomes between age 1 and age 5 (or between age 1 and age 8) for children in the treatment villages, relative to the change in outcomes for children in the comparison villages (i.e., a difference-in-differences approach). However, children in the younger cohort were too young to have baseline measures of enrollment in early childhood education as they were not yet age eligible. These children were also too young to have baseline measures of the EDI as they were not old enough for the instrument.

Instead, we evaluate the impact of the project using the following regression specification:

> 7 A comparison of assets ownership by households in the evaluation sample with that of the rural subsample of the SUSENAS (a nationally representative household survey) suggests average rates of asset ownership and education levels are by and large similar between the two. See also Hasan, Hyson and Chang (eds.) 2013.

7
# **Need for Further Research**

The findings of this study suggest a need for more comprehensive ECA region-wide policy and empirical research focused on rental tenure choice and sector, so that a full comparative understanding can be compiled including actual practice cases of various policies, programs, and instruments for others to learn about, discuss, and possibly adapt to their own countries. Regardless of the number of countries covered, there is a need for follow-up research on both empirical and policy themes.

In empirical research there is a need for institutionalized monitoring of the rental sector, through improved census work and housing sector reporting, and supplementary specialized surveys on rental housing at various levels of government.<sup>2</sup> For tenure policy research two themes are relevant: (i) detailed analysis of country rental housing policy frameworks; and (ii) cross-country comparative policy studies to deepen understanding of actual practice. There is also a need for better understanding of the impact and constraints of specific policy measures and programs. Analogies from other sectors could broaden the feasible policy menu. This should include alternative taxation models and regulatory incentives or impediments.

Linkages to broader economic issues should include the role in poverty alleviation and labor mobility strategies of the public sector acting as a rental housing investor providing “market additionality”, while not replacing the formal private rental market. Partly due to political and ideological inclination toward homeownership, research into new public investment strategies in the form of rental PPPs, or non-profit rental forms has almost subsided over the recent decades, so there is a need to resume research in these directions.

The issue of inter- and intra-governmental housing policy institutional architecture should be studied to improve understanding of where housing policy is formulated and implemented. Anecdotal evidence suggests a wide variety of institutional anchors for housing policy both within central governments and between central, regional, and local government levels. The institutional fragmentation of housing policy formulation and implementation has discouraged development of comprehensive and cohesive housing strategy in many countries. Realignment of institutional infrastructure
deviation. The average treatment effect of NSP on the perception of security in the two eastern districts is not statistically significant from those in the other eight districts.

Despite a strong positive effect of NSP on perceptions of security, the program has no significant effect on security incidents in or around villages as reported by villagers (

**<u>Table 5</u>** ). In both treatment and control villages, approximately 3 percent of respondents indicate that their village experienced an attack in the past year and that they themselves were affected by insecurity in the village or on roads around the district. In the two eastern districts, the results are similar.

Objective measures of security, which are not affected by the usual concerns with the survey data (Bertrand and Mullainathan, 2001), are provided by the ISAF dataset. Figure 2 presents estimates of the effect of NSP on these incidents.<sup>20</sup> The results indicate that, in non-eastern districts, NSP reduces the probability of security incidents both in the short-run and in the long-run, but the effect is stronger in the long-run. In the short-run the effect is significant at the 10 percent level for 4 km., 7 km., and 8 km. radii and is the strongest for the 8 km. radius, for which it corresponds to a decrease of 4 percentage points in the probability of a security incident. In the long-run, the effect is significant at 10 percent for radii between 7 km. and 11 km., with effects being significant at 5 percent for 1 km. and 8 km. radii. The effect is the strongest for the 9 km. radius, which it is significant at 1 percent level. In the eastern districts, where the initial levels of violence are high, there is no statistically significant effect on security for any of the radii either in the short run or in the long run.

Overall, there is strong evidence that perceptions of security are better in villages receiving NSP
ban, etc.). A unique feature of the project is that it includes information on the date of announcement, implementation, and removal (if applicable) of each reported measure.<sup>10</sup> As of mid-July 2020, the data set documented 414 trade policy measures taken by over 100 distinct jurisdictions. The measures include 209 measures liberalizing imports of protective equipment, medical supplies and medicines implemented in 106 jurisdictions and 191 export controls imposed by 91 countries for the same set of products. The most common liberalizing measures were reduction in import tariffs, while export bans were the most common restrictive measure across countries. Data on trade policy measures are available for 133 countries.

We focus on the first seven months of 2020 because this is the period in which most trade policy measures were imposed. Our research question is whether attributes of prevailing PP regimes are associated with the imposition of trade measures. While the supply of essential goods was largely fixed in the initial period of the crisis, over time, as supply responds to increased demand, this will attenuate the perceived need for exports controls and import liberalization, confounding inferences regarding the possible relationship between PP regulation and use of trade policy in the initial period of a public emergency which is what we are interested in. The GTA data set shows that some governments began to roll back trade measures starting in June 2020, a pattern that strengthened in the summer and fall of 2020 (see Evenett et al. 2020).<sup>11</sup> A weekly evolution of trade restrictive measures on imports and exports of medical products according to the date of implementation of the measures, shows that the number of restrictive measures on medical products increased exponentially as of the end of March (Figure 1). This coincides with the beginning of the COVID-19 pandemic and the growing demand for medical products worldwide. There were a limited number of liberalizing measures implemented for medical products during the first two months of the year. However, the trend changed drastically as
determined by the focus of legal aid organizations themselves and the fact that they came into existence mainly to provide women with recourse against family disputes – is also unclear.

_There is a high perception of insecurity in public places_ : When women were asked if they had heard of a rape in the last year over 11 percent said yes compared to the fact that only 4 percent of men said yes (WBGNS, 2006). Only 49 percent of older women and 38 percent of younger women feel safe going out at any time within their settlement (village or urban neighborhood). And strangely while a smaller proportion of men report having heard of rape, yet a larger proportion of them compared to women believe the external environment to be more unsafe for women. Men also do not regard actual harassment or spousal violence to be as high as women do. However, we have to address the issue of women‘s feelings of insecurity with some caution. It is for instance likely that this sense of insecurity is instilled in them by their families or by the community narrative to ensure that women do not venture outside of acceptable public spaces – a narrative tied up as much by actual happenings in some historical past as well as by a feeling of protection for (or control of) women<sup>7</sup> . As is true of other countries, in Bangladesh too, women living in urban areas report feeling more unsafe, as do women in certain divisions. This result holds even after controlling for other background characteristics (World Bank, 2008).

<!-- Start of picture text --> Figure 2: Perception of safety of women Perception of safety of women<br>100 Source: World Bank Gender Norms Survey 2006Source: World Bank Gender Norms Survey 2006<br>90 Older Women (45-60)<br>80 Younger Women (15-25)<br>70 Men (25-50)<br>60<br>50<br>40<br>30<br
1 Methodology**

To estimate the effect of fiscal policy on output, the analysis proceeds in four steps. First, to quantify the effects of changes in commodity prices on output, panel regressions are used to obtain the response of real GDP to changes in country-specific commodity price indexes.<sup>15</sup> Results show that a 10 percent increase in commodity export prices increases output by 0.63 to 0.85 percent in EMDE commodity exporters and 0.18 to 0.26 percent in advanced-economy commodity exporters (Table 5).<sup>16</sup> Second, panel regressions are used to estimate a fiscal policy reaction function (that is, the response of government spending to changes in commodity prices). The results show that EMDEs increase government spending when commodity export prices rise, indicating a procyclical fiscal policy (Table 6). Specifically, a 10 percent increase in commodity export prices leads to an increase in government spending of about 0.6 percent to 0.8 percent. In contrast, advanced economies respond countercyclically: a 10 percent increase in commodity export prices elicits a reduction in government spending of about 0.7 percent to 1.2 percent.

Third, an average fiscal multiplier is estimated for commodity exporters using a panel structural vector

> 14 Kaminsky, Reinhart, and Végh (2004) focused on net capital inflows, finding that such flows were associated with an increase in government expenditure in emerging markets and developing economies (EMDEs), while net capital outflows were associated with a decline in government expenditure. A variety of other drivers could lead to procyclical fiscal behavior.

> 15 Two control variables are used: overall terms of trade (which includes terms of trade for all traded goods and services, not just commodities, using data from the IMF) to control for trade effects, and the lagged dependent variable to capture underlying growth unrelated to commodity prices. The country-specific commodity export price index is an index that weights commodity prices by their relevance in a country
Eastern Europe and the Commonwealth of Independent States (CIS). The 2002 edition also analyses the second round of the Business Environment and Enterprise Performance Survey, covering close to 6,000 enterprises in 26 countries of the region. The survey provides useful insight into the quality of the business environment in the region and how it varies between countries and different types of firm. The first round of the survey which was analyzed in the 1999 Transition Report, examined how reforms influence the performance of firms, by considering differences in reforms both at the country level, in terms of the pervasiveness of soft budget constraints and assessments of the investment climate, and at the level of enterprises themselves, in particular the degree of competition faced by firms and their origin and ownership.

# _<u>World Business Environment Survey (WBES)</u>_

The World Business Environment Survey (WBES) is a survey of over 10,000 firms in 80 countries and one territory conducted in 1999-2000 that examines a wide range of interactions between firms and the state. Based on face-to-face interviews with firm managers and owners, 7 ____________________________________________________________________________________________________________
to 14 percent in 2010 (Walton (2010)).<sup>5</sup>

> 2 Among the developing countries, China and India are two prominent examples where impressive economic growth has been accompanied by an increase in inequality. For a discussion on rising inequality in Asia, see Jushong and Kanbur (2012). The recent decline in intergenerational mobility in USA and UK has also attracted a lot of attention; see, for example, Deparle in New York Times (January 4, 2012) and Mazumder (2012) on USA, and Dearden et al. (1997) and Blanden et al. (2005) on UK.

> 3 For evidence on rising inequality in India after 1991, see Ravallion (2000), Deaton and Dreze (2002), Sen and Himanshu (2004). A recent survey of the available evidence shows that consumption inequality has increased slightly, but the income inequality in India is much higher than what is usually thought of (close to Brazil) (World Bank (2011)). It is now widely appreciated that the available estimates of consumption and income inequality may be significantly biased downward, because the household surveys fail to cover the top income households.

> 4 Dreze and Sen (2011) argue that Indian economic reform has been an ―unprecedented success‖ in terms of economic growth, but an ―extraordinary failure‖ in terms of improvements in the living standards of general people and social indicators.

> 5The volatility in the wealth of billionaires reflects the volatility in the stock market. The common perception about a significant increase in inequality is reinforced by spectacular conspicuous consumption by the super-rich: Mukesh Ambani, the chairman of Reliance Industries in India owns and lives in the first billion dollar house in the world (Woolsey, M, Forbes.com, April 30, 2008), and in the mega wedding of two sons of Subrata Roy, the  ̳chief

2