rafmacalaba/data-use-mentions-extended huggingface dataset:
# **Introduction**

How has public attention to poverty changed over time? Has less poverty in the world as a whole deflected that attention or enhanced it? How has it reflected economic and social thought more broadly? Were some periods more enlightened about poverty than others? Prevailing historical narratives that might throw light on such questions have relied heavily on the careful human reading of texts. While this is understandable, it seems that historians might also exploit the digital age.<sup>2</sup> The technology of digitizing texts has opened up new options for systematically searching words and phrases, as a complement to more traditional historical research methods.

A new window has recently been opened on the prominence of ideas in the writings of their time. The _<u>Google Books Ngram Viewer</u>_ (the _Viewer_ hereafter) was introduced by JeanBaptiste Michel et al. (2010). In this context, an “n-gram” is just a phrase, made up of words (“1grams”). Michel et al. created a corpus of n-grams (for n=1,5) from 5.2 million books (excluding periodicals). The Michel et al. corpus holds over 500 billion words (360 billion in English). By conventional human reading, it would take the working lives of 347 people to read the entire corpus at 300 words per minute.<sup>3</sup> The _Viewer_ is fast; word searches and plots over hundreds of years take only a small fraction of a second. Naturally the total number of words in a given year has increased over time. Michel et al. estimate that there were about one million words in English in 2000, but barely half that number in 1900. (And most of that growth was in the latter half of the 20th century.) The _Viewer_ ‟s counts are normalized by the total number of n-grams in the corpus for that year. I will refer to the normalized frequency as
formal education system.

# **4 Data and Empirical Strategy**

To estimate the impact of introducing preparatory school years in Romania on maternal employment we employ difference-in-difference (DiD) estimation techniques and estimate equation 1; we compare the employment rate of women with and without kids aged six years old, before and after 2012: _P_ ( _Eist_ ) = _f_ ( _β_ 1 _Mom_ 6 _ist_ + _β_ 2 _Post_ 2012 _ist_ + _β_ 3 _Mom_ 6 _ist × Post_ 2012 _ist_ + _β_ 4 _Xist_ + _δs_ + _γt_ + _εist_ ) _._ (1) The variable _Eist_ is binary and denotes if a mother with a six-year-old child is employed. i identifies a mother at the individual level, s the respective state, and t the time period. _Mom_ 6 _ist_ determines if a woman is a mother of a six-year-old child, while _Post_ 2012 _ist_ indicates if a year is after the reform in 2012. _Mom_ 6 _ist × Post_ 2012 _ist_ is the DiD effect of interest. We expect the effect of _β_ 2 to be positive given that the preparatory school year replaced childcare provided by mothers. _Xist_ are individual-level controls that vary at the individual, state, and year-level, _δs_ are state-fixed effects to control for time-invariant, state-specific characteristics and _γt_ are time-specific, state-invariant characteristics. _εist_ is an error term. We report average marginal effects from a logit specification throughout (unless otherwise stated). Standard errors are clustered at the state level.

We estimate equation 1 using data from the European Labor Force Survey (EU-LFS) from 2010 to 2019. The treatment group consists of all mothers with the youngest child of age six. We consider two different control groups. First, we consider mothers with the youngest child of age three or four given that this group of women might be more similar to our treatment group on unobservable characteristics. We do not consider younger children because previous evidence shows that parents are less reluctant to put children below three 8
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education, however, wages in Abidjan are below those in other cities. This is consistent with our earlier observation of higher earnings in the formal private sector in other cities relative to Abidjan.

The results of the comparison in Table 37 should be treated with caution. Splitting the sample according to level of education raises the question of what determines access to different levels of education. Clearly, the progression to higher levels of education is not a random event. This brings about the possibility of selection bias in OLS estimated earning functions. The two-step methodology we used earlier in this paper to incorporate the selection into different kinds of employment can also be applied to the selection into types or levels of education. The first step then becomes the estimation of a probit model with the determinants of access to education as regressors. The key empirical problem, however, is to obtain a proper set of such regressors. Relevant variables are personal ability (motivation, intelligence, etc.), scholastic achievement, migration and school attendance history, and parental background (education, occupation, wealth, income) at the time the education choices are made. It is obvious that such variables are not readily available in survey data. The consideration of schooling selection is therefore empirically less tractable that than of employment selection.27/ The CILSS data did not contain sufficient information to permit us to explicitly consider selection into schooling types in this paper.

27/ For a further discussion of selection into types of schooling, see, for example, Appendix 3 in Jimenez and Kugler (1986).
.

In Table 1, we assume that only one biofuel policy is in place at a time. However, because higher crude oil prices result in increasing biodiesel prices under the tax credit and decreasing prices under the mandate, we can determine the minimum crude oil price that makes the tax credit binding; in Table 1, this price is approximately $84/barrel. This break-even crude oil price is important for small developing countries because, as we have shown earlier, the crude oil price has differential impacts on commodity prices, depending on which biofuel policy binds. For example, one implication of Table 1 is that if the large country pursues a biodiesel mandate and oil prices are below $84/barrel, then an increase in the crude oil price will, _ceteris paribus_ , result in lower soybean oil prices, and hence the prices of soybeans.

> 17 In 2010, the U.S. blender’s tax credit for biodiesel was $1/gallon and the diesel tax $0.55/gallon. We set the blend mandate equal to 0.7 percent, which is equal to the observed energy share of biodiesel in the total biodiesel and diesel blend.

> 18 The predicted diesel price is calculated as: diesel price = 0.055 + 0.029 times the crude oil price; the coefficients were estimated using OLS on historical data for diesel and crude oil.

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- Brown, J. (n.d.). Quitters never win: The (adverse) incentive effects of competing with superstars. Kellogg School of Management, Northwestern University.

- Castell-Climent, A. (2008). On the distribution of education and democracy, _Journal of Development Economics_ **87** (2): 179–190.

- CIPPEC (2004). _Los estados provinciales frente a las brechas socioeducativas. Una sociolog ́ıa pol ́ıtica de las desigualdades educativas en las provincias argentinas_ , Area de Pol ́ıtica Educativa, Buenos Aires.

- Coleman, J. S. e. (1966). _Equality of educational opportunity_ , Government Printing Office, Washington, DC: U.S.

- Duflo, E., Dupas, P. & Kremer, M. (forthcoming). Peer effects, teacher incentives, and the impact of tracking: Evidence from a randomized evaluation in kenya, _American Economic Review_ . (also NBER Working Paper No. 14475).

- Duflo, E., Kremer, M. & Robinson, J. (forthcoming). Nudging farmers to use fertilizer: Evidence from kenya, _American Economic Review_ . Unpublished Manuscript, Massachusetts Institute of Technology.

- Duflo, E. & Saez, E. (2003). The role of information and social interactions in retirement plan decisions: evidence from a randomized experiment, _Quarterly Journal of Economic_ **118** (3): 815842.

- Etchart, M., Gasparini, L., Bohorquez, P., Curia, J., Ferroni, B. & Hontakly, P. (2004). Las po ́ıticas compensatorias mejoran la equidad? plan social educativo, educaci ́on primaria.

- Evans, W. N., Oates, W. E. & Schwab, R. M. (1992). Measuring peer group effects: A study of teenage behavior, _Journal of Political Economy_ **100** (5): 966–
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6 The idea central to Ball and Mankiw's 1995 model is the firms' response to supply (cost) shocks. Authors assume that responding to shocks by changing prices is costly because of various menu costs that have to be incurred. In such a setting firms do not react if shocks are relatively small and respond only to shocks large enough to rnake paying menu costs worthwhile. With the assumption that the average relative shock is zero, Ball and Mankiw consider different distributions of shocks and look at the consequences that these differences have after the imposition of menu costs. In a symmetric distribution, the range of inaction arising from menu costs covers the same number of positive and negative shocks and the net effect on the price level is zero. However, when a distribution is skewed 5 to the right the upper tail is larger than the lower tail and menu costs imply that firms react to more positive shocks than they do to negative. Finally, if the distribution is skewed to the left the situation is reversed: the mass in the lower tail of the distribution is bigger and more firms experience downward shocks to their prices which results in the fall of the aggregate price level.

The basic implication of this reasoning is that in periods during which the distribution of shocks is skewed to the right, aggregate price level may rise as menu costs imply more price increases than price decreases. The authors formalize these ideas in a one-period theoretical model. They also observe that the analysis refers to the relationship of the distribution of **_unobserved_** real sectoral shocks and the rate of inflation. Recognizing that fact, they carry out a numerical analysis that proves that the relationship between the first, second and third moment of the distribution of unobserved shocks carries over to actual price changes under reasonable assumptions. In other words, one can use relative price data as a proxy for unobserved shocks since the two phenomena move monotonically closely together.

While Ball and Mankiw's 1995 paper offers sound justification for including skewness of the distribution of relative
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locations despite the presence of strong forces of economic geography that tend to generate or magnify the gaps.

India is not the only large developing economy where regional disparities in industrial development constitute an active policy issue. In various forms and to different degrees regional equity in industrial development seems to be a policy issue in countries such as China and Brazil as well. We therefore hope that our results would inform prospective studies in that broader context. To the extent that regional inequality in industrial development is a legitimate policy concern, we hope the paper contributes to better understanding of the business environment as an instrument of policy intervention. The notion seems too common in development circles that better performing locations or regions must have better business environment on the average. Our paper suggests that this is not necessarily true unless one defines business environment widely enough to subsume all aspects of the economic environment of producers including the region’s economic geography. This would certainly make the concept of business environment tautological and redundant. If we define it to include only those aspects of the economic environment that government policy can influence in the medium to the short run, then it is not necessarily the case that the most productive locations have the best policy environment. The case for improving the business environment of relatively backward regions through policy reforms need not thus be that those policies are necessarily worse than those in more advanced locations. It can be that, in the presence of sources of cost advantages no one controls, it makes sense for governments to compensate for them by acting on factors that they can influence.

Our findings should be qualified by a major data limitation that we have pointed out in the paper. This is that our data come from the most industrially advanced cities in India. In terms of regions, each state is represented in the World Bank Investment Climate Survey by the top three or four industrial cities in that state. We are therefore comparing locations across the top end of the size distribution of cities and urban centers. It is possible that as we move
ways in which people interact with the state, as well as their perceptions and levels of trust. These are themes which LITS2 is uniquely positioned to address: the survey includes an expanded module on governance and service delivery which enables new analysis on the links between the ways in which people use, experience and interact with public services, their perceptions and trust in providers and institutions, and the quality of service delivery itself.

There are obviously a number of caveats in the interpretation of satisfaction data. The presence of externalities (e.g. additional social benefits of education, public health, etc.), may mean that users‘ satisfaction does not capture the full extent of desired social outcomes. Second, even if individuals and society share the same goal – such as more rapid student learning – some persons may have been conditioned to have low expectations, leading them to report high satisfaction despite poor service delivery outcomes. A third reason for caution is information asymmetries: this is particularly evident in health services, where providers have technical information and expertise that patients lack and cannot therefore evaluate properly (Fiszbein, Rogers and Ringold, 2011; Das and Hammer, 2007). Still, subjective data on peoples‘ experiences and perceptions of service delivery quality can help complement more objective measures of service delivery (e.g. from facilities surveys) to help policy makers and development practitioners track progress of country programs and strategies.

Using data from the 2010 Life in Transition Survey Round 2 (LITS2), this paper examines the levels of citizens‘ satisfaction with public service delivery in Europe and Central Asia and identifies some factors that may help explain how levels of satisfaction with service delivery vary across different population sub-groups and change over time. Section 2 describes the coverage of governance and service delivery in LITS2 and presents the key findings on the prevalence of unofficial payments, and utilization of and satisfaction with public services. Section 3 analyzes differences across individuals and across countries (over time) in utilization and satisfaction with public services. We conclude
We considered all observational research including, but not limited to, studies using quantitative data that is longitudinal or cross-sectional, individual or aggregate (e.g., at the level of schools) on the effect of the COVID-19 pandemic on learning loss among students.

To be included in our sample, the outcome measure must be a valid measure of learning progress. These include measures using scores from school-based tests or from assessments administered by researchers or international assessment programs, including EGRAs, and any study that can be scaled to the Harmonized Learning Outcomes (HLO) (Angrist et al 2021). In addition, studies must have measured learning loss with pre-COVID control data, and during or post-COVID treatment data. Studies using projections and simulations were excluded.

Secondary research such as systematic reviews were excluded from the analysis but used to identify further relevant studies. Given the focus on the COVID-19 pandemic, we restricted our search to papers published between March 1, 2020, and March 1, 2022.

Studies were screened according to the following selection criteria: Studies that conducted student analyses and reported impacts on learning progress (either positive, negative, or insignificant) because of COVID-19 school disruptions were included. Factors for rejecting studies from our review included the absence of student analyses or recorded impacts on learning progress, analyses occurring before the onset of COVID-19, or hypothesized results. We collected study details such as author name(s), sample size, information on the age of students in sample, length of closures, measures of social background recorded, outcomes measured, follow-up period(s), and the effect sizes. We recorded the data in an MS Excel spreadsheet. We assessed the methodological rigor of each study and subsequently rated the robustness of the overall body of evidence across all outcomes.

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3 .. .. Section 5 with applications to problems of external-internal balance in the medium-run. .economy faces an intertemporal budget constraint are raised in Section 6. Finally applications that deal with policy choice when the

# 2. A One Sector Hodel

> It is widely accepted that for medium-run issues, the Salter-Swan dependent economy model is the most appropriate specification to represent the

> external sector in a developing economy. prices are given and hence the external terms-of-trade are exogenous, and doaestically produced tradable goods are perfect substitutes for foreign

> produced goods.

> homogenous primary commodities, the implication of this specification -- goods. Indeed the empirical evidence at the most disaggregated levels [e.g. rate changes on domestic: prices is small. _11_ In addition, trade statistics

> indicate significant cross-hauling even at a very disaggregated commodity level, also suggesting the inappropriateness of the perfect substitution

> assumption of the Salter-Swan framework.

> In that specification, foreign

> In applied work however, with the exception of a few

> naaely that changes in foreign prices or trade policy are entirely passed through t.o competing domestic traded goods -- is unrealistic: for most traded Isard 1977, Aspe and Giavazzi, 1982] shows that the pass through of exchange

use. This apecific:ation, which is used on the import side should also be Then domestically produced goods for export sale are imperfect substitutes for domestically produced goods for sale on the domestic market. appropriate for ec:onomywide models that are fairly aggregated is not without The alternative, now found in most CGE models, is to assume that foreign goods and domestic import-competing goods are imperfect substitutes in incorporated on the export side for similar reasons. This assumption, while ' --~ . ' .
the control (or comparison) groups. Moreover, studies using matching methods needed to clearly state the eligibility criteria of the program to make the case that the problem of selection bias was (mostly) due to observed characteristics.

Importantly, as described in the previous section, this review includes studies that considered the impact of six different types of business-support services based on firm performance. In addition, our study is more complete as it examines different firm-level outcomes and does not restrict the analysis to employment outcomes as in Grimm and Paffhausen (2014).<sup>5</sup> Our review covers studies that looked at both intermediate (or secondary) outcomes (such as access

> 4 Further, the European Union and the World Bank (see, for instance, the Enterprise Survey website <u>www.enterprisesurveys.org) adopt 250 employees as a cut-off to classify SMEs.</u>

> 5 Though the literature recommends that synthesis is informed by the theory of change embedded in the design of an intervention (see Waddington et al., 2012b), our focus extends beyond the outcomes directly anticipated by an intervention to also include unanticipated outcomes.

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BCB. Using administrative data was the most obvious choice since we do not have students’ contact information or addresses. All data for the short-term impact evaluation was collected in schools and the students would have left those schools by now (most of them would have graduated in 2012). Additionally, the administrative data are provided by authorized third parties, meaning that they do not suffer from self-reporting bias.

# **_3.b. Sample Selection for the Long-Term Impact Evaluation_**

As a starting point, we take the full sample of 35,346 students who participated in any of the surveys conducted during the short-term impact evaluation. Any given survey conducted during the short-term impact evaluation covered at most 24,473 students, but the composition of students changed throughout the study due to students rotating and repeating a year, which is why the full sample includes over 35,000 students. To match these students with the long-term follow-up data from the administrative sources housed at the BCB, we need their CPFs (the 11-digit Brazilian taxpayer identification number).

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functions. Regarding taxation and public services, it finds that the Latin American middle class is more likely than other groups to consider that citizens should pay their taxes, and less likely to consider that taxes are too high or justify tax evasion. The middle class is also less satisfied with the provision of public services, compared to the more affluent. The analysis, however, is based on households’ self-perceived position in the income distribution, which can differ substantially from their actual position (see below).

Using data from the World Values Survey for 80 countries, Amoranto, Chun and Deolalikar (2010) examine how perceived class status relates to values that may be associated with higher economic growth and greater accountability in public services. They find that people who perceive themselves as middle class are found to have values that are more likely to contribute to economic growth than the lower class for six indices, but generally have less liberal values and attitudes than the upper class 4
own calculations; Pigato (1999).

**a** The business climate index is defined as net FDI inflows normalized by GDP and the total value of natural resources in each host country.

b Political risk rating based on the opinion of banks, TNCs and other institutional investors indicating corruption, political and judicial institutions.

**c** Institutional Investor rating measures a country's creditworthiness, which is mostly determined by economic and financial variables.

The ranking of 29 African countries according to the indicator proposed above is presented in table 2 (first column). In 1995-1997, the most attractive country was Namibia, followed by Mali, Mozambique, Zambia, Chad and Senegal.<sup>6</sup> The least attractive were Congo, Sierra Leone and Ethiopia. Preliminary findings for 1998 indicate

**6** The good ranking of Chad and Zambia reflects that the first country offers great oil reserves (not reflected in our indicator of natural resources) that have attracted companies interested to explore those

6