rafmacalaba/data-use-mentions-extended huggingface dataset:
, then the OLS estimate of β (namely, RIF-OLS estimator) provides a consistent estimator of the marginal effect on the unconditional quantile of a small location shift in the distribution of X, holding else constant. So, one can decompose any two distributions at quantiles in a similar spirit as Oaxaca-Blinder approach. It is worth noting, however, that the assumption of linearity used in implementing this detailed decomposition implies that the outcome distribution depends on the marginal distribution of covariates only through their mean (Rothe 2010b).

The decomposition of test score change over-time can be rewritten as<sup>3</sup> : where and are approximation errors that appear because of the first order approximations and the assumption of linear specification. They are calculated as differences between the aggregate explained effect and the total composition effect: , and that between unexplained component and the total coefficients structure effect: .

An identification problem exists in this sort of detailed decompositions as pointed out by Oaxaca and Ransom (1999), as the coefficients effect is not invariant to the choice of reference group; this problem has no easy solution. One approach is to derive results using more than one alternative reference group. The other is to use one of the solutions suggested to deal with this problem. We used the averaging approach proposed by Yun (2005).

# **3. Data and Summary Statistics**

# _3.1. Data_

We used the Trends in International Mathematics and Science Study (TIMSS) data for 8<sup>th</sup> grade Ghanaian students. TIMSS is an international assessment conducted every four years in order to generate information about trends in mathematics and science achievement in each country and over time. The age of tested student population is 9 to10 years (4<sup>th</sup> grade) and 13 to 14 years (8<sup>th</sup> grade) in more than 60 countries; the outcome is an extensive pool of data about the quantity, quality, and
changes to tax and investment laws (c.f. Auerbach and Hassett 1991; Cummins, Hassett, and Hubbard 1996; Handley 2014). With respect to the latter, scholars have used political regime types and veto points (Kenyon and Naoi 2010, Frye 2010, Jensen 2003, Henisz and Zelner 2001), political polarization between parties (Frye 2010, Frye 2002), leadership change and elections (Nishide and Nomi 2009; Kim et al. 2012; Jens 2013; Julio and Yook 2013; Kelly, Lubos, and Pastor 2014), and political violence (Barro 1991, Brunetti et al. 1998) as proxies indicating changes in the incentive structure underpinning the state’s preferences. Most such work has found that policy uncertainty decreases investment at both the micro- and macro-levels.

Studies focused on measuring inconsistency in regulatory enforcement have tended to do so directly, by examining the number of anti-trust cases brought over time (Bittlingmayer 2001), the number of offices responsible for permitting (Feiock and Jeong 2002), history of passage and repeal of regulation (Fabrizio 2012), retroactive changes in investment regulation (Lyons and Mayo 2005), survey responses on the anticipated direction of policy (Barrodale 2010; Engau and Hoffmann 2009), and surveys of bureaucratic discretion (Beazer 2012). A more recent body of work has also begun to examine the differences between _de jure_ expectations on the time needed to receive various government services and the _de facto_ time needed (Hallward-Driemeier and Pritchett 2015), although this body of work has been more concerned with documenting this gap and is correlates rather than its effect on investment. Work on corruption, although rarely couched in terms of regulatory uncertainty, has instead tended to use survey based measures: focusing on both measures of “grand” corruption – high-level corruption assessed via expert surveys – and the actual experiences of individuals and firms assessed through direct survey questions. Although evidence for a direct effect of corruption on investment is mixed (c.f. Mauro 1995; Slinko
verify that the net impact of the cooperative price on catch,  0 , is positive. This is a necessary prerequisite to the model’s assumption that the cooperative can control its members’ effort by changing cooperative buying prices.

We use the following idea to address the identification concerns: Unlike in the model, changes in _Pct_ and changes in _X t_ and fishing costs do not happen at exactly the same point in time. We assume that in reality, when the cooperative changes _Pct_ , both individual catch _qict_ * and aggregate effort _Ht_ respond to the change immediately; however, the stock _X t_ and unobservable time-varying shocks to fishing do not respond immediately. Under this identifying assumption, if we can examine a narrow enough window around the price change, we can reasonably assume that the expected value of the stock _X t_ and unobservable fishing costs is similar on either side of the price change.

To operationalize this idea, we estimate equation 17 using fixed effects at the fishing teamspecies-month level and the fishing team-species-week level. The fishing team is not identified in the Sargento data, so we restrict the analysis to Pichilingue and Abreojos. Unlike in the model, in reality members may not fish for certain species at certain times. Consequently, some members have zero catch for a species in particular periods. The results below first examine the responsiveness of catch to prices including just the intensive margin, and then include both the intensive and extensive margin.

The first set of results appear in table 3, which examines fishers who catch a positive amount of a species. The first panel (columns 1–3) uses the Pichilingue sample, while the second panel (columns 4–6) uses the Abreojos sample. Both panels are structured analogously: the first column estimates equation 17 using fixed effects at the fishing team-species-month level and conventional standard errors, the second column does the same but clusters standard errors at the fishing-team-species month level, and the third column uses fixed effects and clustered standard errors at the fishing team-species-week level. Moving
advantage of this measure is that it does not impose a limit for the share of top performing firms, which can vary with business cycles. A disadvantage is that the growth rate per se does not take into consideration the differences in initial size, nor relative average differences across countries.

An alternative to the OECD approach is a definition based exclusively on a fixed share of top performing firms, such as the top 1%, 5%, or 10% of highest growing firms in the period. Several studies adopted this measure (Goedhuys and Sleuwaegen 2010, Holzl and Friesenbichler 2010, Lopez-Garcia and Putente 2012, Bjuggren et al. 2010, Capasso et al. 2013, Coad et al. 2014, Bianchini and Secchi 2016, and Daunfeldt and Halvarssonin 2016). This definition is also based exclusively on the growth rate of the firms but keeps the share of HGFs constant. A drawback of these definitions is that, in case there is an unexpected event where all firms have low growth, it still identifies the top percentile of firms as HGF.

The Birch index (Birch, 1979) is likely the most well-known HGF definition in the second group, which also considers the initial size of the firm. The index combines both the absolute and relative growth rates. It is defined as �X� �X���� �� ~~,~~ where Xt is the number of employees at the period ���� t. The HGF definition following this method selects a given share of firms in a top percentile of the Birch index distribution.

Another index, following the aim of controlling for differences in the initial size of firms is �� � ���� provided by Davis, Haltiwanger, and Schuh (1996). The DHS index, defined as ~~� ]~~ , �.� ��������� where, X� is the number of employees at the period t. This index measures the growth rate of the firm relative
.9|1.4|38.3|2.2|

_Source:_ Jamaica Survey of Living Conditions, November 1989, 1990, 1991.

In 1993, total costs of the program amounted to roughly 0.1 1 percent of GDP. During the period 1989-1992, the program reached between 12 and 20 percent of all Jamaican households (Table 1). During these same years, 30 to 40 percent of households in the poorest quintiles gained access to food stamps compared with 3 to 6 percent of households in the highest quintiles. These numbers illustrate the fact that the FSP has excellent targeting outcomes (compared to similar programs in other countries). With regard to access based on gender, Louat, Grosh and Van der Gaag (1993) found no 7
between regions that are above a threshold level of financial development compared to those that are not.

A key empirical challenge in addressing this question is that large-scale infrastructure investment is typically endogenous, making it extremely difficult to causally identify whether a strong financial market needs to be in place first or whether financial development appropriately mirrors and develops alongside major investment efforts. We study this question using India's Golden Quadrilateral (GQ) highways investment as a natural experiment, examining the spatial development of banking at the district level before and after. The GQ network connects the four major cities of Delhi, Mumbai, Chennai, and Kolkata and is the fifth-longest highway in the world. Conceived in 1999, the GQ upgrades began in 2001, with a target completion date of 2004, and 95% of the work was completed by the end of 2006.

Several studies have subsequently documented the importance of the GQ upgrades for Indian manufacturing development along the highway system but have not focused on the role of finance.<sup>2</sup> This project connects the GQ work to the financial sector and makes two main contributions: First, we use comprehensive and detailed data on bank lending across India over an extended period of time, drawn from the Reserve Bank of India. This database gives us detailed information on each outstanding loan above a small threshold, reported annually by every branch of every scheduled commercial bank in India. We have invested substantially over this project in accessing and preparing these data. They constitute a major new tool for the economic and financial development and growth literatures. Second, the context of the GQ infrastructure project allows us to generate strong causal results of the relationship between infrastructure investment and local financial development, using straight line IV analyses and comparing results to the planned, but not completed NS-EW corridor. To understand the interaction between infrastructure and finance, we examine how the results vary based on the pre-existing financial development of districts adjacent to the highway. This allows us to speak directly

> 2 Using a very short time
Fiscal policy can reduce some gender inequalities directly. For example, conditional cash transfers providing household-level transfers for every child enrolled in school can create positive incentives for girls to remain in school longer and for households to reduce the time spent by school-age girls in care for younger dependents.<sup>14</sup> Here too a direct reduction in gender inequality in one area (time spent caring for younger dependents) may lead indirectly to a reduction in gender inequalities in another area (a reduction in the wage gap for externally supplied labor).

Fiscal policy can also directly reduce or exacerbate gender differences in paid employment. Around the world, women’s labor force participation rates are lower than men’s (ILO 2023). Women enter and exit the labor force more frequently than do men, which means their participation is more discontinuous than men, and they are more likely to be in part-time and seasonal jobs (ILO 2023). Women on average earn less than men, even after controlling for standard human capital variables (age, education, job experience), though the gap has narrowed in many countries over the last decade (Chamberlain, Zhao, and Stansell 2019). Women tend to dominate in informal employment, especially in low-income settings. Revenue policy can promote female employment by eliminating higher marginal rates on secondary earners in married couples; public expenditures can support unemployed women through unemployment insurance or informally employed women through social protection benefits. Here too, direct impacts today can lead to indirect impacts tomorrow. For example, women’s participation in the paid labor force can help rebalance expectations and social norms regarding women’s and men’s participation in social reproduction activities. An increase in labor force participation is good for the macroeconomy, and any policy encouraging labor force participation can potentially reduce gender employment gaps.<sup>15</sup> Fiscal policy can also support or undermine social reproduction. As noted earlier, social reproduction is the production and maintenance of human capabilities. It involves both
# Table 3 (cont.) The Gains From Agricultural Tariff Liberalization Aggregated Data

|Country|Aggregate<br>Gains|St.Dev.<br>Gains|Consumption<br>Efects|Income<br>Efects|Pro-Poor<br>Bias|Gains<br>Poor|Gains<br>Rich|
|---|---|---|---|---|---|---|---|
|Developing world|2.39|0.85|4.33|-1.94|-0.33|2.16|2.48|
|Liberia|2.39|0.52|3.18|-0.79|-0.87|1.81|2.67|
|Madagascar|1.13|0.52|3.49|-2.36|-1.03|0.67|1.70|
|Malawi|0.74|0.88|2.98|-2.25|-2.16|-0.05|2.10|
|Mali|2.29|1.50|3.62|-1.33|3.58|4.18|0.60|
|Mauritania|3.84|1.00|5.14|-1.29|2.30|4.79|2.49|
|Moldova|0.78|0.35|1.40|-0.62|0.44|1.15|0.70|
|Mongolia|2.42|0.47|2.94|-0.53|1.20|2.90|1.69|
|Mozambique|2.32|1.88|4.32|-2.01|-4.76|0
|0.51|0.54|0.53|0.52|0.52|
|Wall==wood/concrete|0.18|0.18|0.18|0.19|0.18|
|Number of rooms|3.57|3.63|3.61|3.60|3.60|
|Refrigerator|0.81|0.85|0.84|0.84|0.83|
|Freezer|0.13|0.15|0.14|0.14|0.14|
|Washing machine|0.56|0.62|0.60|0.59|0.58|
|Smart devices – tablet|0.21|0.25|0.23|0.23|0.23|
|Jewellery|0.14|0.16|0.16|0.15|0.15|
|Observations|1491|1214|1214|1213|1213|

Note: Variables marked with asterisks are used both as reweighting target variables and as variables included in the SWIFT poverty projection model. To avoid repetition, we only include these variables in the first section (reweighting target variables) but exclude them from the second section (SWIFT model variables). Source: authors’ estimation using HBS 2016.

# _III.3. Results from experiments with the_ _<mark>2018 URHS</mark>_

The poverty estimate of the 2018 URHS is 47.1 percent, and the actual poverty headcount rate of the phone owner subsample is 38.8 percent. The lower poverty rate with the unadjusted weights in the phone sample resonates with the findings in the existing literature that the phone owners are much richer than the full sample of refugees.

Like Rwanda EICV5 and Saint Lucia HBS 2016, three types of weights were calculated to adjust for the sampling bias in the phone owner sample of URHS 2018
less agency within the household and in the society to begin with, due to social norms around inheritance practices. Consistent with improving living standards and expectations that family support may be less available than in the past, the proportion of 65-year-old heads with more than 5 years’ worth of consumption in net worth increased from 30% in 2001 to 50% in 2018. To the extent that pooling all wealth in housing is suboptimal, this pattern suggests a potential demand for long-term saving schemes designed for the informal sector.

While safe, housing is a relatively illiquid asset, which takes resources away from short-term consumption smoothing. According to Findex, only 3 percent of those aged 15 years and above in Pakistan report being able to rely on savings for emergency funds, while 49 percent say it is not possible to come up with emergency funds. The main source of emergency funds tends to be family or friends, according to 41 percent of the population aged 15 years and above; 25 percent report borrowing for medical expenditures. Policies that allow greater use of real estate assets as collateral to borrow against, through formal financial institutions, could in theory reduce the need for liquid precautionary savings, and free up resources to save for retirement. However, such initiatives may also encourage over-indebtedness and lead to evictions.

Lack of other safe, liquid forms of saving can also limit earning opportunities offered by self-employment. The self-employed tend to be older than informal wage workers but with similar levels of schooling. Almost half of the self-employed have no education. The older age of the self-employed might suggest that initial working years are spent acquiring start-up capital, as most of the self-employed enterprises are started using own capital (LSS Employer Survey 2014, Bossavie et al, forthcoming). According to the Findex surveys, only 11 percent of people aged 15 years and above borrow to start or expand a business.

Improving opportunities for safe long-term saving outside housing in the form of government-sponsored or subsidized old-age savings instruments could yield greater independence in old-age and reduce the burden on
|YES|NO|YES|NO|YES|
|Year FE|YES|YES|YES|YES|YES|YES|YES|YES|
|HH FE|YES|YES|YES|YES|YES|YES|YES|YES|
|Region-waveFE|NO|NO|YES|YES|NO|YES|NO|YES|

_Note:_ Dependent variables are household log total consumption and consumption split into food and nonfood consumption. In column 4, households that report having received assistance have been removed from the sample. Data used are from the three waves of the GHS and telephone survey for conflict. All regressions are conducted using weights. Controls include all household and geographical variables listed in appendix table C.1. Standard errors clustered at the local government area level. Significance: *** _p_ < 0.01; ** _p_ < 0.05; * _p_ < 0.1 36
.407|
|No. of obs.|4,888|3,703|1185|491|525|761|491|566|3,455|1,433|
|Est.population|1,709,593|1,214,953|494,640|184,147|167,765|327,931|150,558|251,872|1,186,526|523,067|

_Source_ : Own computation from 2018 Quarterly Labor Force Survey conducted by Central Statistical Office of Zambia. Sampling weights adjusted with non-response probabilities are used to estimate the mean values.

21
**Polac,Pnning, and Research |**

# **World Development Report|**

When a country's planning and budgeting system is dilapidated, an important first step is to rehabilitate basic budgetary and accounting functions and to generate public expenditure data that can provide a starting point for rational planning. Other basic measurce. include: The budget process should first determine what resources are available and adopt aggregate revenue and expenditure targets. Then the entire set of public expenditure issues should be looked at simultaneously. If total expenditure is allowed to be the outcome of the aggregation of sectoral bids, the overal expenditure is almost certain to be unsustainable.

process should be made public in order to educate public opinion about economic altematives, build a consensus, and spread responsibility for public spending choices.

* Monitoring development projects and programs requires explicit information on actual expenditures of individual projects and the entire program, including simple breakdowns by implementing agency, sector, source of finance, and so on. For investment programs, it must be possible to relate expenditure infomiation to a financial plan for each project. The use of standardized project profiles for all approved projects is an invaluable technique.

- The responsibility for reconciling expenditure bids with agreed overal targets must be decentralized. Sectoral ministries should be given ceilings within which to prepare their estirdtes.

* It is vital that recurrent and development expenditure programs be considered simultaneously in each sector, since a country's ability to sustain the recurrent costs arising from new investrnent may be doubtful. In restructuring recurrent budgets, it is important to establish "norms ' for the level and distribution of expenditure to provide properly for key services.

* In the long run, the budgeting and planning

* The financial woes of developed countries increase the value of extemal aid and the leverage exercised by aid agencies. To minimize friction with aid agencies, govemments should exercise careful aid management by monitoring project preparation and implementation, working to minimize project problems, and encouraging dialogue between the govemment and aid agencies.

This is a
, with monetary poverty, fiscal and debt deficits, or greenhouse-gas emissions—has led to incomplete definitions and long lists of principles, attributes and conditions that a country, a city or a community must display to be socially sustainable. Such lists include aspects as wide-ranging as social equity, intra- and intergenerational well-being, quality of life, satisfaction of basic needs, social interactions and interconnectedness, freedom, safety, security, and access to basic infrastructure and services. Both approaches, either vague or long-winded characterizations, are unhelpful in delivering a definition that can be understood, agreed upon, and operationalized.

Instead of laboring to develop yet another definition, we construct a global database of indicators related to social sustainability from readily available data sources, covering many of the principles cited in the literature, flexibly clustered around four components, and conveniently aggregated in simple and parsimonious indices. This global database contains 71 indicators, covers 193 countries and 37 territories for the period between 2016 and 2020, and builds indices of social inclusion, resilience, social cohesion, and process legitimacy. The choice of components and the number of indicators in each of these components follows three simple criteria (being an outcome, capturing unidimensional concepts, and relying on objective data or direct vulnerable groups’ perceptions). These criteria are sometimes relaxed when serious data 23
Policy Research Working Paper 5851

# **Abstract**

In this paper, a unique post-earthquake survey designed to provide a rapid assessment of food insecurity in Haiti is used in order to see how adequately emergency assistance programs have been allocated. When modelling the impact of various covariates upon assistance allocation, the location of households emerges as the main criterion. This helps to explain why, five months after the quake, government and agencies still seemed unable to provide an efficient allocation of emergency assistance. What is more, those who benefited less from assistance appeared to be on the one hand families headed by women and on the other hand households with disabled members: this obviously runs counter to an “optimal” targeting that would make the most vulnerable ones eligible for assistance in priority. Furthermore, the fact that associations may favour assistance allocation is an interesting result that should be considered further. It is also found that asset losses had no significant impact on the food consumption score, whereas household preearthquake wealth did. This result demonstrates that the impact of the shock has been buffered when households had previously enforced coping strategies, regardless of the effects of emergency assistance programs.

This paper is a product of the Social Protection Sector, Latin America and the Caribbean Region. 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://econ.worldbank.org. The author may be contacted at damien.echevin@usherbrooke.ca.

_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 expressed in this paper are entirely those of the authors. They do not necessarily