rafmacalaba/data-use-mentions-extended huggingface dataset:
their traditional enforcement strategies and find it difficult to optimally monitor compliance with self-reported income taxes.

In this context, technology may be instrumental in boosting the performance of income tax collection in many ways. On the taxpayer side, technology can be used to simplify tax registration processes, such as the creation of one-stop shops for firms. In addition, taxpayer e-services such as e-filing and e-payment facilities, as well as web tax portals, can significantly ease the burden to comply, increase transparency and predictability of taxes, and reduce scope for corruption, factors which may increase willingness to comply. On the tax administration side, IT solutions such as Electronic Fiscal Devices, can provide crucial data on sales which can then be cross-checked automatically with self-reported income tax declarations. Similarly, the tax administration can obtain and crosscheck data from thirdparty reporting such as VAT data from clients and vendors and rental income withholding with self-reported income. Against these promises, the existing evidence is, once again, rather mixed, and we summarize it below.

# **5.1 Pay As You Earn**

In theory, given the at-source deduction of PAYE tax by the employer, there is less scope for evasion with PAYE compared to self-declared income (Kleven et al., 2011), however, there is very limited empirical evidence from Africa on this. Rather, the existing descriptive evidence suggests that large gaps persist in the quality of PAYE returns data, thus undermining the capacity of revenue authorities to make best use of it and opening loopholes for tax evasion.

One issue is lack of proper tax identification of individuals. Descriptive evidence from both Uganda (Mayega et al., 2021) and Ethiopia (Mascagni and Mengistu, 2019) reveals that tax identification numbers (TINs) for employees are largely missing or incorrect in employers’ PAYE returns. This means that the tax authority is unable to track payments by individuals over time and match individuals’ records with other databases. Reporting aggregated PAYE taxes at the employer level and not linking to individuals also creates
across countries, these findings are consistent with the notion that shrinking the gap in quality determinants might also shrink the gap in outcomes.

This paper contributes to several literatures. First, we link to work on the role of program quality determinants in higher education on graduates’ outcomes. This literature typically focuses on bachelor’s degree programs, uses data from a single country, and examines a single determinant such as availability or use of funding options;<sup>7</sup> curriculum structure, training, and academic remediation;<sup>8</sup> availability of infrastructure for practical training;<sup>9</sup> practices related to faculty assessment, training, and hiring;<sup>10</sup> practices to promote student employability and industry engagement;<sup>11</sup> and other program and institution characteristics such as governance.<sup>12</sup> Bailey et al (2015) focus on community colleges in the US and describe the practices of successful institutions and programs yet do not provide systematic, quantitative evidence. Our paper is novel in collecting evidence and analyzing multiple determinants for several countries and specifically SCPs.<sup>13</sup>

- 7 See studies on scholarships, grants, and awards (Andrews et al., 2020; Barrow et al., 2014; Castleman et al., 2016; Cohodes and Goodman, 2014; Field, 2009), loan availability and take-up (Armona et al., 2018; Wiederspan, 2016), and tuition (Denning, 2017; Dynarski and Scott-Clayton, 2013; Martorell et al., 2014; Scott-Clayton, 2011).

- 8 Examples are studies on credits for longer degrees or transfers (Andrews and Lovenheim, 2014), teaching a second language (Chin et al., 2013), teaching math or reading skills (Xu and Jaggars, 2011), and providing academic remediation (Bettinger and Long 2009).

- 9 This literature refers
measured in the World Bank STEP surveys, Valerio et al. (2016) point to serious reliability concerns.<sup>5</sup> Where SEM skills have been measured successfully, such as the longitudinal Young Lives project in Ethiopia, India, Peru, and Vietnam, the panel of respondents is still too young to enter the labor force. These data are already providing important insights into the importance of SEM skills, but as of yet, they do not include labor market outcomes; only the latest (yet-to-be-released) round of

> 5 They find that four coefficients are positive and statistically significant at the 90% level of confidence, three coefficients that are negative and statistically significant and 42 coefficients that are small and imprecise. As the standard errors are not adjusted for multiple-hypotheses testing, even the statistically significant results are likely due to chance. The authors write, “ _It must be noted that the noncognitive skills measures are a function of scores on three to five items each. We believe the limited number of items for each (noncognitive skill) scale could be limiting the reliability of these measures and obscuring the true relationship between noncognitive skills and earnings._ ” (Valerio et al., 2016: 26).

6
Starting with the top row, our study is set during a period in which plant counts and output are growing for the organized sector, but employment levels are shrinking overall. This is true in general, and the divergence is even more pronounced for entrants. Accordingly, labor productivity for establishments is rising on average.

Looking at differences in growth patterns by distance from the GQ network, non-nodal districts within 10 km of the GQ network demonstrate growth that exceeds that in districts 10-50 km from GQ in every column. Moreover, in five of the seven columns, the growth in these very proximate districts also exceeds that in districts over 50 km away from the network. For convenience, we tabulate this ratio near the bottom of Panel A. The share changes in Panel B also tend to be quite strong considering the big increases in the nodal cities that are factored into these share changes.

Distance from the NS-EW highway system provides an interesting contrast, even at the level of these descriptive statistics. First, it is clear that we should be careful about assigning all of the changes observed for the GQ upgrades in nearby districts to the project, as districts near the NS-EW network also tend to exhibit growth differences compared to districts 50+ km away as a raw statistic despite the fact that the upgrade of NS-EW has only just begun by our sample end point. Second, districts near the GQ network appear to have especially increased plant counts and labor productivity compared to districts near the NSEW corridor. These patterns are not conclusive, perhaps most importantly because districts can be close to both highway systems as shown in Figure 1 (about 8% of GQ is also part of NS-EW), but they provide a suggestive starting point for our work.

# **Section 4: Empirical Analysis of the Impact of Highways on Economic Activity**

This section analyzes the impact of highway construction on manufacturing activity across districts. We use simple linear models with outcome variables expressed in logs, with the exception of TFP, which is expressed in unit
to obtain a relevant and useful measurement tool. The desiderata described above will be invoked several times in what follows.

# **3.2.4. Dimensions**

The concept adopted here views the statistical capacity of an NSS in terms of its range of products, and the processes it uses to produce and disseminate them. The production process for statistical outputs has certain similarities to the traditional production model from economics, and this analogy might be useful for identifying the salient dimensions of a statistical capacity measure. The production process begins with a technology that is used in generating the statistical products, and the level of this technology is clearly a relevant component of statistical capacity. The resulting statistical outputs might be divided into two general categories. First are the intermediate products, which have direct use for specialists but require additional processing to create products suitable for general use. For example, a census can be helpful for policy analysts but must be processed to obtain useful statistics. Second are the final products, which are available in a form that can be understood by the public. The key macro statistics of a country would naturally be viewed as final products. Even after the products have been created, their existence does not imply that potential users will actually have access to them. Statistical products may be available to only a few users, or available to all. The final dimension then covers the extent to which statistical products are disseminated.

This simple framework helps to identify four coherent dimensions for a measure of statistical capacity, namely: (i) Methodology, Standards and Classifications (MSC), which provides information on the technology being used by the NSS; (ii) Census and Surveys (CS), which describes the intermediate products of the NSS; (iii) Availability of Key Indicators (AKI), which 13
000 20,000 30,000 40,000<br>Potential years of life lost per 100,000 Cases<br>* Health exp per capita ’ Average cost<br>» SFM- efficient exp ' SFM- efficient exp<br>—— SFM- deterministic section —— SFM- deterministic section<br>— Hybrid frontier —— Hybrid frontier<br>Notes: Stochastic frontier model is time-invariant half-normal panel-data model. California data refer to 313 unified school districts, and cover the period 2003/2004 - 2008/2009.<br>The PISA data refer to 49 countries, and cover some or all the years 2000, 2003 and 2006. The OECD health system data refer to 29 countries, and cover the period 1960-2005.<br>The Vietnam data referto 795 district hospitals with between 50 and 500 beds, and cover the period 1998-2000.<br><!-- End of picture text -->
6.9|69.9|
|EU15|64.3<br>7.7|69.7|

- Data not available

Note: Labor Force Survey data Definitions: Working-age population: 15-64 Labor force = employed plus unemployed (aged 15+) Labor force participation rate = labor force 15-64 as a percentage of working age population Employment rate = employed 15-64 as a percentage of working age population Unemployment rate = unemployed as a percentage of the labor force 7
15 During March and April 2009 we collected ownership, licensing, programming and other details on all 68 radio stations operating in Benin; we used direct observations by enumerators and interviews with key informants to assess the availability and quality of public goods in 210 villages across the 32 northern communes; and we implemented a survey of the service access, policy knowledge, and political attitudes of 4200 households residing in these villages, randomly selecting 20 households from each village. Radio access was determined in two ways. Village-level key informants listed which radio stations they were able to receive, and the enumerators used their own transistors to verify and expand on this, if they received additional signals. The codes of the radio listed as accessible to the village were then matched with the radio survey data to examine the nature of programming available to the village. Table 1 summarizes the number and types of radio stations covering this study area.

**Table 1:  Access to Radio Stations in North Benin**

||No. of<br>stations<br>accessible to<br>the region|No. of sampled<br>villages covered<br>(Total=210)|Average<br>Signal<br>Strength|No. of<br>education<br>programs<br>broadcast<br>(over the past<br>3 mths)|
|---|---|---|---|---|
|Government-owned Public<br>Radio|3|200|2667 watts|33|
|Private Non-commercial or<br>Community Radio|21|195|231 watts|50.6|
|Private Commercial Radio|10|49|476 watts|21|
|Religious Radio|2|71|.|.|

In addition to the ubiquitous national public radio, this region of Benin is primarily covered by a number of local community radio stations. These stations are non-commercial in part by vocation, but in
and financial variables displays a number of regularities during the four global recessions. The 2009 global recession, which saw by far the largest declines in many indicators of activity, otherwise followed a pattern broadly similar to the previous episodes. The impact of global recessions often varied across different groups of countries and regions.

Sharp contraction in real activity. In the four global recessions, per capita global output (market exchange rate weighted) declined on average by 1.3 percent, which is 3.5 percentage points below the average annual growth rate of 2.2 percent during the 19502019 non-recession years (Table 3). With PPP weights, the decline in per capita output during global recessions was, on average, 0.8 percent, while growth during expansion years was 2.5 percent.

> 23 Imbs (2010), using monthly industrial production data, concludes that the degree of cross-country business cycle correlation during the latest recession was the highest over the past three decades. Other research also indicates that shocks originating in credit markets have been influential in driving global activity during global recessions, including the 2009 episode (Helbling et al. 2011; Eickmeir and Ng 2015; Bacchetta and van Wincoop 2016; Perri and Quadrini 2018).

12
|20.9|1.1|
|Car|12.2|7.1|0.6|
|Washing Machine|15.1|16.8|1.1|
|Vacuum Cleaner|7.7|7.7|1.0|
|Small livestock|36.3|48.6|1.3|
|Large livestock|45.8|45.6|1.0|
|**Dwelling Characteristics**||||
|Roof material: Concrete|23.4|23.4|1.0|
|Wall material: Concrete|22.6|18.0|0.8|
|No Toilet|6.8|2.9|0.4|
|**Consumption in the last 7 days**||||
|Beans/Pulses|78.7|80.8|1.0|
|Meat|57.5|60.2|1.0|
|Milk|41.1|48.3|1.2|
|Apples|22.6|11.4|0.5|
|Eggs|42.6|65.3|1.5|
|Chocolate|58.9|75.1|1.3|
|Fuel for Car|24.7|26.0|1.1|

**_Source_** _: World Bank estimations using IE-LFS households surveys and AMWS rounds. Note: Shows characteristic of households that participated in both the IE-LFS 2019/20 and IE-LFS 2021, and those AWMS R3 participants whose identity match original IE-LFS respondents._

> 10 For the sample from the IE-ELFS 2019/20, the identity of the original respondents was done directly as the name of the household head was available in the information the NSIA shared. In the case of the IE-LFS 2021, no information on the names of previous respondents was available. Instead, we
medium” (but close to low) human development by the UNDP. The ranking of Suriname (124) is also considered “medium”. The scores of Belize (118), Saint Lucia (108), and Dominica (97) are considered “high”. Our survey data provides additional insight into the socioeconomic context, as shown in Table 1. To facilitate comparisons by level of economic development, here and throughout all other exhibits in this paper we order countries by GDP per capita. The share of households headed by a woman ranges from 30 percent in Belize to a little over 40 percent in Haiti. The share of household heads who completed tertiary education ranges from 15 percent in Suriname to 27 percent in Dominica and Saint Lucia. Self-reported urbanization rates differ substantially across countries. There is also substantial variation in the demographic characteristics of households across countries. The share of households with children ranges from 32 percent in Saint Lucia to 86 percent in Suriname, whereas the share of households with elderly members ranges from 24 percent in Suriname to 81 percent in Haiti.

7
40 significant and could be better obtained from traditional surveys. These should be dropped in future efforts, so that the assessment could concentrate on qualitative information-gathering.

- The assessment had concentrated too much on clients' PHN beliefs and practices. It should have focused also on clients' perceptions and use of modern PHN nervices in the project area vis-a-vis the traditional healers in the area. Service providers and traditional healers would have been useful interviewees as well as clients.

- Such assessments should be repeated during implementation, both to fill the above gaps, and to see how clients' and providers' perceptions and use of services change as the project progresses, so as to facilitate rapid mid-course correction.

## -<eneral

- A broad assessment of this type is likely to be useful during project preparation. It will open areas of inquiry and allow the formulation of questions to be pursued in narrower and deeper assessments carried out during implementation.

- Although in Ethiopia the client group was diverse, it was quite homogeneous in terms of class and income strata. In other countries, it might be important to stratify interviewees and the presentation of findings by strata within communities, as well as or instead of by ethnic groupings.

# Case 4: THE NIGFRIA IMO STATE HEALTH PROJECT: THE USE OF FOCUS GROUP INTERVIEWING IN PROJECT PREPARATION

# Background

Focus groups bring together a small group of part,cipants (usually six to twelve) for an informal group discussion on particular topics, led by a moderator working from a prepared discussion guide. Participants should feel comfortable and secure and at ease to express their views frankly, even when they differ from prevailing norms. The session works best when participants respond one to another, leading to deeper probing of issues than would be possible in a formalized interview. Experience shows this to be most feasible when the participants are of more or less equal status and have similar perspectives on the subject under discussion. It requires skill to lead the discussions properly--to dispel inhibitions and draw out the participants without letting
, the timing of privatization is estimated as a function of the quality of the provincial bank, the political affiliation of the key decision-makers, and the fiscal situation of the province.I" The hazard rate in this model - - which, loosely, is the rate at which banks are privatized after time t given that they were not privatized prior to time t -- is:'<sup>9</sup> _A(t)_ = _AO(t)_ **_e8x1+ +flkxk_** _Ao(t)_ is the "baseline" hazard function, a non-parametric function of time; , is the parameter vector; and x is the vector of covariates (e.g. the bank quality variables). In the results, a positive coefficient indicates that an increase in that variable increases the 17 The privatization process for Corrientes started in October 1991, however this province is omitted from all analysis due to missing data in 1990 and 1991.

18 The partial likelihood model was first presented in Cox, D. (1972) "Regression Models and Life Tables." Journal of the Royal Statistical Society B, 34, pp. 187-220. Other sources which discuss this class of models include Kalbfleisch, J and Ross L. Prentice (1980) _The Statistical Analysis of Failure Time Data._ New York: John Wiley and Sons; and Greene, W. (1997) _Econometric Analysis 3rd ed_ New York: Macmillan.

**19** The time of privatization is when the law enabling privatization was passed. This point, which is the start of a process which often lasted several years, is relevant because this is when the political decision to privatize is being made.

11
056|229,810|83,078|
|2012|1,050,626|197,592|82,509|
|2013|1,113,905|219,078|79,813|
|2014|1,150,439|241,056|77,840|
|2015|1,168,369|137,177|87,125|
|2016|1,210,658|89,337|87,664|
|2017|1,297,371|165,574|84,563|
|2018|1,350,917|172,908|93,001|
|2019|1,429,118|39,262|211,450|
|2020|1,320,042|102,489|143,212|
|Sum|18,942,610|3,280,019|2,338,114|

Source: own elaboration with data from Brazil’s Ministry of Infrastructure. Note: To keep notation of investment as a one-time disbursement (I0), one could consider investment to be zero and include it as part of operational cost ct.

To perform simulations for each of the eight countries, we use national Consumer Price Index rates as discount factor δt and inflation adjusted US Dollar exchange rates Xt. These values are shown in Tables 11 and 12.

46
by comparable surveys within countries, over 3 to 7-year periods.<sup>13</sup> We use both the historical database which contains 467 spells for 121 countries, of which 88 countries were published in the most recent version in March 2021.<sup>14</sup> Since this database overlaps considerably with the PovcalNet database, we do not add these observations to our main data set, but rather create a complementary sample based on more recent, harmonized and comparable data with medium spell lengths useful for understanding how growth rates in surveys differ from those of national accounts. Results for this data set are presented as robustness checks in Section 4.

# **_Putting it all together_**

Of the 2,095 household survey estimates we compile; we match 2,082 to GDP per capita data and 2,020 to HFCE for the same country and year.<sup>15</sup> This sample is substantially larger and more recent than those included in past studies. Deaton (2005) presented results from 557 surveys for 127 countries between 1979 and 2000. Ravallion (2003) used a smaller sample of survey means from 90 countries, and a panel of 142 growth spells for 60 countries. We also have substantially better coverage of High-Income countries, than Ravallion (2003), Karshenas (2003) and Deaton (2005).

We generate growth spells with annualized growth rates by matching all observations for each country and type (income/consumption), which gives more than 15,000 possible spells (including overlapping spells) and 1,881 consecutive (non-overlapping) spells. In contrast, Ravallion (2003) generates 142 spells between successive household surveys for 60 countries in the 1980s and 1990s. Our practice of matching all observations with each other within each country-type panel maximizes our potential power in estimation, but we also conduct analyses of

> 13 Global Database of Shared Prosperity, circa 2013-2018, available at <u>http://www.worldbank.org/
and significant spillovers effects in the third ring at 2-3km. In the second ring at 1-2km the two forces seem to offset each other. And by ring 4 beyond 3km any effects have dissipated. These results are similar to those for advertising in Manhattan in Arzaghi and Henderson (2008), except the succession as we move away from the own firm of competition, spillover, and dissipation occurs at much shorter distances than in Kamapala.

# **7 Conclusions**

This paper evaluates the use of different measures of economic density in assessing urban agglomeration effects. These density measures are based on Landscan data. While Landscan measures ambient population at the grid square level with error, a ground-truthing exercise for Nairobi and Kampala suggests that Landscan does a better job of capturing within city clustering than other measures derived from smearing population into grid squares based on ground cover such as Landsat type data. The empirical work focuses on Africa, where there is a perception that African cities have low economic density due to a lack of clustering of economic activity. We find that Africa as a region has economic density and cluster measures similar to other developing countries in Asia and North Africa and higher than those found in the developed world or Latin America.

To assess economic density measures, we examine how well they explain household income differences across cities and neighborhoods. We have simple scale and density measures and more nuanced ones which capture in second moments the extent of clustering within cities. Noting that the extent of clustering is measured with error in Landscan resulting in attenuation bias, the evidence we have suggests that a simple density measure explains income differences across cities as well as or even better than more nuanced measures attempting to capture within city differences in the extent and nature of clustering. However, simple city scale measures such as total population are inferior to density measures and to some degree misleading. On the big picture side, there are very large household income premiums from being in bigger and particularly denser cities over rural areas in Africa, indicating migration pull forces remain