rafmacalaba/data-use-mentions-extended huggingface dataset:
# **2. Empirical Strategy**

Our ultimate goal is to estimate the impact of aid receipt on household consumption outcomes. To do that, we address the potential endogeneity of household aid receipt by relying on instrumental variable regressions and novel instrumental variables that are strong predictors of household aid receipt but that do not directly affect household consumption outcomes, except through their impact on household aid receipt. Our instrumental variables are derived from a monthly data set on humanitarian aid distribution data provided by the World Food Programme and covering the period 2012-2017. Data is provided at the traditional authority (TA)-level and includes food and cash aid recipient households.

Following the instrumental variable strategy pursued in Ravallion and Wodon (2000), we first estimate TA-level aid distribution as a function of explicit geographic targeting characteristics as well as other factors that may affect aid receipt. We do this for three reasons. The first is to generate evidence on factors affecting aid distribution, which provides important policy-relevant evidence in and of its own right. The second is to establish that included variables actually do a good job predicting placement, supporting the validity of our instrumental variable strategy. The third reason is to evaluate the potential for identifying additional instruments.

Specifically, we argue that the rainfall metrics used by the Food Assistance Response Programme (FARP) and the Malawi Vulnerability Assessment Committee (MVAC)<sup>3</sup> introduce exogenous variation in the aid distribution. Previous work on the impact of extreme weather events on crop production outcomes, using the same data set informing our analysis here, evaluated a wide range of GIS-based drought and flood measures, and determined that the best drought and flood measures were constructed using different variables and data sources than those used by the FARP (McCarthy et al., 2021). The

> 3 The FARP was called the Food Insecurity Response Programme in 2015 and 2016.  The FARP relies, in part, on inputs provided by MVAC.  MVAC is a government-led committee set up in early 2002, following the
|**Variable**|**Per**|**centage (weight**|**ed) **<sup>**n(raw)**</sup>|
|---|---|---|---|
||Poorest|27.24|421|
||Second|24.28|420|
||Third|19.51|421|
||Fourth|16.07|420|
||Richest|12.90|420|

# _Note._

*Denominator is out of those who experienced some flooding impact in either 2023 or 2022 **Denominator is out of those who reported experiencing some level of discrimination

Refugee households, households with a mother with less than a primary education, and households in rural areas on average had children with significantly lower levels of child development for children 0-35 months, measured by CREDI Z-scores, compared to a global population (Table 3). As such, the average non-refugee child in this population would be considered to be developmentally on track (CREDI Z-score= -1.69 SDs) while the average refugee child in this population would not be considered to be developmentally on track (CREDI Z-score= -2.35). In terms of child development for children 36-72 months, measured by percentage correct on the AIM-ECD, the same differences were seen but only some relationships were statistically significant. Specifically, there were no significant differences by refugee-status, but mothers with less than a primary education had children with significantly lower AIM-ECD scores on all domains except for executive functioning, where the same trend was seen but it was not a statistically significant difference. Mothers living in rural areas had children with significantly lower AIM-ECD scores on all domains of development.

Across both age groups, mothers in refugee households experienced significantly higher levels of depression, on average, and no significant differences were seen for depression levels by maternal education status (Table 4a, Table 4b
<sup>9</sup> Our main focus in this paper is to compare these “added” employment and work definitions using project data to the market and extended work definitions obtained exclusively from an approach that focuses on individual responses on their activities.

The various measures of work presented in the paper are laid out conceptually in Figure 2, which is not drawn to scale. The market 7-day definition of work is the narrowest and corresponds to the definition of employment currently used in the Egyptian LFS and the Tunisian Employment Survey. It is subsumed in all the other work definitions. The extended 7-day definition of work adds to the market 7-day definition those engaged in subsistence activities as ascertained by the individual questionnaire, while the market 3-month definition adds those who were employed in the three months reference period, but not in the 7-day reference period, again as ascertained by the individual questionnaire. This may include some individuals engaged in subsistence but not market work in the 7-day reference period. The extended 3-month definition of work includes all those engaged in market work or employment in the three-month reference period, as well as those engaged in subsistence work in the 7-day reference period.<sup>10</sup> The added market definition (12 months) is our most comprehensive definition of employment. It adds to the market 3-month definition those who reported to be engaged in household agricultural or non-agricultural

> 9 Due to the absence of information about individual household members’ involvement in crops and other agricultural products in Tunisia, our “added” measures only include added involvement in non-agricultural enterprises and livestock rearing in the Tunisia setting.

> 10 As mentioned earlier, we do not have a separate measure in the individual questionnaire for those engaged in subsistence work in the three-month period but not in the 7-day period.

8
|0.414|1.597|0.076|
|Observations|8881|8881|8881|8881|
|_Information experim_|_ent_||||
|Treatment (1 year)|0.045**|0.072***|-0.087|-0.002|
||(0.021)|(0.021)|(0.466)|(0.058)|
|WY _p_-value|0.130|0.010|0.990|0.990|
|Control mean|0.245|0.203|1.534|-0.094|
|Observations|7950|7950|7950|7950|
|_Single grant observat_|_ion_||||
|Treatment (1 year)|-0.038|-0.043|0.694|-0.039|
||(0.036)|(0.031)|(0.610)|(0.072)|
|WY _p_-value|0.560|0.550|0.560|0.580|
|Control mean|0.306|0.270|2.591|-0.013|
|Observations|6288|6288|6288|6288|

Notes: Robust standard errors in parentheses. Westfall and Young (WY) p-values reported. Dependent variables in columns (1) and (2) are binary (where 1=Yes). Dependent variable in columns (3) and (4) are continuous. Data source: Student surveys. * p _<_ 0.1, ** p _<_ 0.05, *** p _<_ 0.01
to the SSA region. These rates were chosen to reflect the lowest growth of imports observed in Europe and China in the post-crisis years, while for SSA it is the average of the same rates weighted by the share of exports from SSA to Europe and China (0.193 and 0.141, respectively). The exercise then assumes that the increasing external financing gap in the current account is covered from

> 15 Using IMF and WDI data we calculate the average share over 2005-2013, although periods may differ among countries if country data is not available in all years.

18
information on GPA in the analysis, we do not have an indicator for the student’s motivation. When SOFES students are more motivated than the average student, we might find a positive treatment effect on student performance while this is actually a selection effect. To take such selection effects into account, the question whether SOFES students put in more effort can yield some insight into the importance of “credit-induced” motivation, although it only captures part of the story.

These potential sources of selection bias should be kept in mind. However, as we shall describe in more detail below, our econometric strategy employing the administrative data does not suffer from selection bias, as treatment is “randomly” assigned. A comparison of the results from both data sources should enable us to get an idea of the quantitative importance of selection bias in the survey data.

An alternative to a controlled experiment is a natural experiment, in which the researcher uses creative solutions to construct a randomly selected treatment group. In our case, we can design a natural experiment by using discretionary changes in the assignment rules. As we have seen in Section 3, the amount of credit a student can receive depends on the student’s so-called economic need factor (ENF) in a discretionary way. For instance, a student can receive a credit of 30% of the tuition fee when her ENF is 0.079, but she can receive a credit of 40% when her ENF is 0.08. However, students just below and just above the threshold will be closely comparable. Assignment to treatment thus involves a random element around the threshold. This identification strategy is known as the Regression-Discontinuity (RD) approach (cf. Van der Klaauw, 2002; Kane, 2003). Formally, the financial aid allocation process can be characterized as: where 1{} is the indicator function, taking the value 1 if the logical condition in brackets holds and the value 0 if not. In words, this equation says that the credit level assigned
our estimates with those of BJS2013 who use commodity price data from the International Finance Statistics (IFS) to estimate the persistence of petroleum, copper, gold and sugar. For the sake of comparison, we report the estimates in Cashin _et al_ (2000) (their Table 3) in the last column. They estimate the persistence of the commodity price shocks using monthly IMF data between 1957-1998 and a median-unbiased estimator, including — a time trend. One can see that for most commodities and especially the most persistent commodities — our estimates of persistence are generally lower than those in Cashin _et al_ (2000).<sup>37</sup> This means that, if anything, our estimates of the optimal fiscal rule are not pro-cyclical enough.

Table 7. Calibration of Commodity Price Persistence (in years)

||**Persistence**|**Half Life**|OSR<br>_θp_|**Source**|**Sample**|**Half**<br><1|**Life **<br>1-4|**from**<br>5-8|**Cash**<br>9-18|**in et al**<br>_∞_|
|---|---|---|---|---|---|---|---|---|---|---|
|Petroleum|0.94|11.2|0.73|IFS/BJS(2013)|1970–2008|||||X|
|Beef|0.90|6.6|0.56|WB PinkSheet|1960-2016|||X|||
|Natural Gas|0.89|6|0.53|IFS/BJS(2013)|1985–2008|||||X|
|Copper|0.89|
0.151)|(0.0913)|(0.0838)|
|**Constant**|7.665***|6.677***|6.830***|6.465***|7.059***|5.993***|
||(0.160)|(0.0229)|(0.322)|(0.0500)|(0.175)|(0.0273)|
|**Household fixed effects**|**no**|**yes**|**no**|**yes**|**no**|**yes**|
|**Observations**|1733|1733|1480|1480|1733|1733|
|**R-squared**|0.266|0.014|0.204|0.048|0.172|0.017|

Notes: Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0. Controls not shown but included in the regressions without fixed effects are characteristics of the household head (age, age squared, education, sex), the number of children aged 0 to 14 in the household and province dummies.

**Table 3: HIV status, the 2008 food crisis and child nutritional status indicators. OLS regressions with household/child fixed effects**

||**H**|**ousehold fixed effe**|**cts**||**Child fixed effect**|**s**|
|---|---|---|---|---|---|---|
|**VARIABLES**|**Weight-for-age**|**Height-for-age**|
Financial Regulation and Development

# **Introduction**

Financial development promotes poverty-reduction and investment: plenty of evidence and associated mechanisms support this claim (e.g., Beck, Levine and Loayza 2000; Burgess and Pande 2005; Demirg ̈u ̧c-Kunt, 2004; Kaboski and Townsend 2005, 2011, 2012; Levine 2005; Karlan and Zinman 2010; etc.). However, there remains an unanswered key question: _how_ to promote financial systems in low-income countries and, in particular, financial inclusion via branch installation . In this paper, we argue that: 1) financial development is a story of banking; 2) a moderate degree of financial regulation can promote financial development and branch expansion in the context of underdevelopment. The first point is descriptive: banks manage around 90% of assets in most low- and middle-income countries, and hence understanding the determinants of banks’ outreach is key.<sup>1</sup> Furthermore, banks play a central role in financial development for at least three reasons beyond the classical intermediation activities: 1) to invest in reaching new customers, providing a public good (“the formal economy”); 2) to introduce alternative payment systems, facilitating within-country trade; 3) to manage liquidity risk, contributing to shape macroeconomic volatility.

Our second, and most important, contribution links a moderate degree of regulation to the promotion of financial development and branch expansion in a context of underdevelopment. We introduce a regulation puzzle: can financial regulation, as a mandatory safe asset purchase, promote lending? Figure 1 shows the monthly volume of private sector lending by all Ethiopian banks between January 2010 and June 2013. In April 2011 (vertical line), the National Bank of Ethiopia (NBE) introduced a directive forcing all private banks to purchase 0.27 negative-yield government bonds for every birr (Ethiopian currency) of private sector lending. The upper panel shows no slowdown after this measure, while the lower panel distinguishes between private banks (affected by the policy
sample is likely to be representative of the policy-relevant sample: those who would participate in international migration and have some borrowing ability to finance migration.

# **Balance**

Moreover, among the interviewed applicants, time-invariant or retrospective characteristics are balanced across treatment groups. Though we did not have a baseline survey collected before the outcome of the lottery, we collected data on several individual specific characteristics that are unlikely to change over time. We also collected retrospective data on outcomes before the lottery was conducted. As **Table 1** shows, except for a couple of characteristics, most are balanced across treatment groups. Group T1 is 0.22 inches (0.3 percent) taller on average than the control group. Group T2 is 0.16 inches (0.2 percent) taller than the control group. Similarly, group T2 is 2.5 percentage points less likely to be a Muslim, whereas group T1 is 1.5 percentage points more likely to be a Muslim compared to the control group. A joint test across all of these outcomes, however, fails to reject the null that the characteristics are balanced across the lottery outcomes.

13
Random close designs, such as the one used in Comprasnet’s e-reverse auctions, are not common in modern-day online auctions. However, they have far predated the emergence of the Internet: Cassidy (1967) provides several examples of candle auctions, a type of auctions used in Great Britain in the 17th and 18th centuries, in which the random closing time is determined by a lit candle and the auction ends when the flames die.

In Comprasnet, the auction duration is randomly determined by the system based on a uniform distribution. According to Celiktemur and Szerman (2012), the fact that the random close is rarely observed outside Comprasnet could be due in part to IBM’s patent of the system. Using transactional data from Comprasnet, Celiktemur and Szerman (2012) report interesting patterns of bidding behavior in Comprasnet’s random close auctions. They find that (i) bidders tend to defer bidding to the end of the auction; (ii) a large part of the auctions is resolved early; (iii) bid increments are usually small; and (iv) large increments are more likely to occur early in the auction. They conclude that random close designs do not necessarily prevent late bidding and consider that random close mechanisms may lead to suboptimal prices when auctions are closed in the heat of bidding. Finally, they suggest that this effect could be offset or outweighed by increased participation since randomness increases the chances of weak bidders to win the auction.

Our paper aims to complement previous work by: (i) evaluating how Comprasnet’s random close design impacts the prices of goods and services purchased by the Federal Government of Brazil and (ii) estimating the savings that could be generated if the closing rule was set differently compared to the current random setting. Building upon a framework for measuring fiscal efficiency in public procurement that has been tested and refined through implementation in eight Latin American countries, including Brazil (World Bank, 2017), we propose a model that extends the specifications used in the previous studies
is helpful to utilize a previous survey from the same or a similar population to assign a few key items to the core module. In the best case, the selected items are still highly consumed and will improve the estimates of poverty. In the worst case, the selected items are no longer important in which case they will hardly affect the time savings compared to a design with zero core items and also equal its performance. In countries with large variation in diet across regions, subnational core modules can potentially improve estimates even further.

This paper also demonstrates the difficulty of achieving convincing results using alternative methods. Simply removing items from the consumption aggregate to create time savings, but without adjusting the poverty line, can lead to considerable bias in the poverty estimates. Better results can be achieved by adjusting the poverty line based on a previous survey in order to accommodate the reduced number of items, but without conserving the shape of the consumption distribution measured by the Gini. Furthermore, the potential for large changes in consumption patterns, which cannot be determined under this approach, creates considerable uncertainty in the resulting estimates. Similarly, a survey based only on covariates and their structural relationship with poverty estimates from a previous survey introduces a large bias in the estimates, at least in the studied case with a 10-year gap between surveys. The proposed rapid approach outperforms all these approaches, only at the cost of increased complexity.

The rapid approach introduces additional complexity into both the questionnaire design and the estimation of poverty. The capacity of enumerators is often low in developing countries. While the rapid approach increases the complexity of the questionnaire, CAPI technology easily solves this problem. Survey software can automatically compile a single consumption module based on the core and optional modules for each household, without making the partition explicit to the enumerator or demanding the execution of complex skip patterns. Furthermore, advanced CAPI technology can be used to generate the questionnaire automatically based on the assignment of the household to an optional module. While enumerators should be made aware that different households
5 changed dramatically and past performance measures can be poor guides to future performance. Nevertheless, firms in the Czech Republic do report quite complete information and accounting data on profitability have improved considerably since the onset of the transition. Especially in the last year of our sample, profitability can be expected to reflect some of the effects of ownership structures on corporate governance. Stock market data also have some weaknesses. While the stock market is reasonably active in the Czech Republic and the firms selected for this paper are the most liquidly traded, liquidity is clearly lower than in market-economies. Furthermore, there is much block-trading off-the-exchange, often at prices different from those on the exchange. The prices at the exchange may then be more a reflection of the valuation of firms by minority shareholders, and not necessarily incorporate the value of control. While both profitability and market valuation of firms can be expected to reflect the influence of ownership patterns, each will have some advantages and disadvantages.

For testing these relationships, we follow the approaches of Morck, Shleifer and Vishny (1988, MSV from now on) and McConnell and Servaes (1990, MS from now on). MSV and MS investigate, for samples of 371 and about 1000 US firms respectively, the cross-sectional relationship between ownership (by management and institutional investors) and Tobin's Q and profitability. Tobin's Q is defined as the ratio of the market value of a firm-value of equity, i.e., number of shares times the secondary market price, plus the market value of its debt-to the replacement value of the net fixed assets of the firm; profitability is defined as the ratio of the inflation corrected deprecation cash-flow to the replacement value of fixed assets. The higher the Tobin's Q, the more valuable the firm is considered as a going concern and the more value the market thus attributes to the ability of management to generate profits from its assets. The link between the level of profitability and the quality of corporate governance is obvious. It is likely
# **PPP-effects on productivity growth**

To establish the effects of differences in relative prices on the level of output across economies, the Penn World Tables draw on multiple years of data from the World Bank’s ICP, with data beginning in 1970. Because their PPP-adjustments are updated across multiple years, their impact is not just on the level of output per worker but the growth rate of output per worker. The PPP-adjusted growth rate of output in each economy often differs substantially from the nationalaccounts growth rate used in the market-exchange rate approach (where exchange rates are fixed in one year). This occurs for two reasons, both of which cause the prices recorded by the ICP to 41
better measuring pro-social preferences, and attempt to disentangle the roles of different sources of non-pecuniary motivation, whether arising from integrity or conscientiousness to do one’s job as tasked, or, preferences for public goods. The currently available measure of Public Service Motivation is drawn from a literature focused on American bureaucracies and the political context of the United States (Perry, 1996) and needs greater testing and validation in poor country contexts. As mentioned before, we regard the results we present here as just a start, albeit an important first step, towards closing the empirical gap between theory and empirics on the role of non-pecuniary motivation in shaping productivity of bureaucracies.

# **6 Discussion of mechanisms**

The interpretation we offer of the robust correlation between political integrity and health service delivery is that in districts where higher integrity politicians are endogenously selected, these politicians are more motivated to perform their multiple roles within the complex organization of district bureaucracies to improve public health, including sensitizing citizens to the value of health services, and monitoring and supporting health workers at the frontlines to deliver. As discussed in section 2, government institutions in Uganda explicitly provide a role to locally elected politicians to monitor and facilitate service delivery, working as liaisons between citizens and the technocrats in charge of delivering nationally-mandated programs. In particular, primary health and education services in Uganda have been examined in prior research as areas where local politicians exercise influence (Akin et al, 2005; Reinikka and Svensson, 2004; Brosio, 2000). This prior research has, in fact, raised concerns about local political accountability for providing public goods and managing fiscal resources. For example, Akin et al (2005) argue that district governments are more likely (than the center) to spend on private goods rather than public goods. Brosio (2000) refers to opinion surveys of local councilors in Uganda to suggest that these councilors are more concerned about paying themselves allowances rather than ensuring that health facilities are well equipped with drugs and implements. In a celebrated study of 30