rafmacalaba/data-use-mentions-extended huggingface dataset:
fixed effects. Since we rely only on administrative data on nonenrolled students, spillover results are limited to school grades and behavior reports.

Table 4 shows the results of spillover effects. We find evidence that the interaction of students with a greater share of ASP participants generates positive effects on their reading, math and science grades, and reduces their bad behavior at school. Estimations indicate that adding 3 treated students in a classroom of 22 (almost a 1 standard deviation increase in treated students, 13.4% on average) increases academic achievement up to 0.095 standard deviations, (e.g., on math grades: 13 _._ 4% _×_ 0 _._ 007 = 0 _._ 095), and reduces bad behavior reports by 0.15 standard deviations (13 _._ 4% _×_ 0 _._ 011).<sup>21</sup> These results have similar signs to some evidence previously found in the literature. For example, Carrel and Hoekstra (2010) use the share of classmates coming from troubled families—that is, the share of children exposed to domestic violence—to measure its effect on grades and classroom misbehavior. They found that making 5% of a class troubled students (1 standard deviation) significantly decreases reading and math test scores by 0.69 percentage points, and increases misbehavior in the classroom by 0.09 more infractions.

To sum up, the spillover results yield two findings. First, these positive spillovers on nonenrolled students indicate that the ASP’s direct effects described in subsection 4.1-A are lower bounds of the total effect of the intervention in the context of these highly violent schools. Second, combining these results with those from Carrel and Hoekstra (2010), we can conclude that it is possible to outweigh the negative effects of misbehaving children by incorporating students with improved or positive behavior in their classrooms. This result particularly contributes to the evidence of optimal class design, indicating that
significant with this finer cluster definition.

Table 12 shows results using clusters at the location stratification level. The number of observations increased to 7,003 and reduced the number of clusters to 64. The interaction term between sales and bribery indicator continues to be significant. Table 13 includes results over country groupings and for SMEs only and excluding small economies; this table is comparable to results in Table 9.

# <u>D. Panel Estimation</u>

Lastly, we repeat our analysis over a set of firms that were surveyed in both 2010 and 2006 (Table 14). The panel data is available for fourteen countries as Caribbean and several Central 21
# <u>Introduction</u>

There are artificial distinctions of method that limit us as social scientists. We economists think of ourselves as quantitative social scientists. Cultural anthropologists and some sociologists see themselves as ethnographers who rely on participant observation and qualitative methods. The reasons for this divide are a vestige of disciplinary history, how scholars are trained and assessed for tenure. By limiting ourselves to one set of methods, we limit the questions we can ask and constrain ourselves in the data available to answer them. The methods lead the questions, rather than the other way around.

It did not begin this way. Charles Booth, whose magnificent multi-volume _Life and Labour of the People in London_ (1892-97) helped set the stage for all social science research, triangulated between data from household surveys, participant observation and open-ended interviews to create detailed “poverty maps” of London. These maps drew on data, both quantitative and qualitative, that Booth and his team collected from every one of London’s four million residents to visualize where the poor and the rich lived. The maps drew a finely detailed picture of households and their living standards, the nature of their work, and many other characteristics that Booth grouped into three categories: Employment, “Circumstances” (illness, infirmity, family size, etc.) and “Questions of Habit” (what he called problems of “drunkenness and thriftlessness”). The task took seventeen years to complete (1886-1903), filled seventeen volumes and had a tremendous influence on economic and social policy, and on social science. (For more on Charles Booth’s work, see Mary Morgan’s (2019) excellent book.<sup>2</sup> ) Over the course of the 20<sup>th</sup> century, most social scientists moved away from this grounded, multi-method process of enquiry. Economics, in its quest toward greater scientific precision, became almost entirely focused on the analysis of quantitative data. Other less homogenous
disaggregated form. It also includes transaction accounts for domestic sales, imports and export in the same fashion as in the SAMs used by IFPRI Standard Model.<sup>**7**</sup> Our 2008 SAM includes six households. The groups were formed on the basis of an application of cluster analysis to Moldovan household budget survey data, with the aim of grouping the households into groups that, in terms of income sources, are as homogeneous as possible internally and as heterogeneous as possible between the groups. Consumption parameters for the six household groups were estimated from the Moldovan 2008 household survey data. The consumption parameter values are presented in the tables of Appendix A<sup>**8**</sup> .

# **4 Alternative Scenarios for Moldova to 2020**

In this section, we analyze the importance of different factors for the development of Moldovan economy during the period 2012-2020. First, we will present our _base_ scenario (Section 4.1). The remaining scenarios are divided into the following groups: In section 4.2 we study the role of productivity growth and increased access to exports markets for agriculture and food industry, as well as for other, non-food industry. We also study the importance of productivity growth within the Moldovan transport sector. In section 4.3 we examine the effects of fuel prices and remittances, as well as the role of government transfers to households. Finally, in section 4.5 we present two summarizing scenarios combining shocks from the earlier scenarios.

The basic idea is to evaluate the likely economy-wide effects of growth impulses in different economic sectors, as well of the likely benefits of achievements in different areas of economic policy. In a similar fashion, we also study the likely effects of potential adverse developments. Table 4 below presents the acronyms and short descriptions of the scenarios. We will define the scenarios in greater detail in the corresponding sections below.

**Table 4. Non-base scenarios**

|Scenario|Description|
|
higher due to the treatment are: how easy or difficult is it for you to (1) work towards reaching your goals; (2) focus on your most important goals; (3) live up to your responsibilities; and (4) fulfill your duties and obligations.<sup>30</sup> There are several possible explanations for why the effects on the measures of conscientiousness are so small. As mentioned above, these include issues related to the local context, but also could be due to high values for the baseline level of conscientiousness across all measures (ranging from 3.8 to 4.8 for the control group at baseline with an average of 4.4 across all traits) indicating very high response scores, saturated close to their maximum value of five. This might be because respondents feel pressured into making positive judgements about themselves to appear socially desirable or signal their willingness to keep their job at the construction company. Such high baseline scores leave little room for change/improvement in these measures as a result of the intervention.

> 28Given the fact that the end-line survey was conducted over the phone, concerns over the reliability of data on such measures when collected by phone survey and time constraints meant that the conscientiousness module was not included in the end-line.

> 29The measures we used were translated from English into French and then into the local language Wolof, which may affect reliability.

> 30It should be noted that we lose statistical significance when we adjust the _p_ -values using List et al.’s (2019) approach (see Appendix Tables D.3 and D.4).

12
Time Series Data for Germany,‖ CER-ETH Economics Working Paper 03/28, Center of Economic Research, Swiss Federal Institute of Technology (ETH), Zurich.

Esty, D., and M. Porter. 2005. ―National Environmental Performance: An Empirical Analysis of Policy Results and Determinants.‖ _Environment and Development Economics_ 10 (4): 391–434 Gale, Lewis R. and Mendez, Jose A., 1998. "The empirical relationship between trade, growth and the environment," _International Review of Economics & Finance_ , Elsevier, vol. 7(1), pages 53-61.

Gamper-Rabindran, Shanti, and Shreyasi Jha. 2004. ―Environmental Impact of India’s Trade Liberalization.‖Working Paper, University of North Carolina at Chapel Hill, Department of Public Policy .

Grether, Jean-Marie, Nicole A. Mathys, and Jaime de Melo. 2007. ―Trade, Technique, and Composition Effects: What Is Behind the Fall in World-Wide SO2 Emissions 1990–2000?‖Working Paper 2007.93, Fondazione Eni Enrico Mattei, Milan.

21
these data are collected for only a very small number of observations, the degrees of freedom are relatively few. Column 5 and 6 of Table 9 show all of the sectoral dummies to be insignficant. However, the standard deviations are significant for self-employment with no employees and civil employment. The risk aversion variable reduces these in only the slightest degree suggesting that, for our small sample, it is not the source of heterogeneity.<sup>30</sup> Thus, while our sample is very small and our risk-aversion measure crude, we tentatively conclude that differences in risk aversion are not driving differences in job satisfaction. However, since our estimates are imprecise further research is necessary to validate this inference.

# 7 Conclusion

This paper employs mixed (stochastic parameter) ordered probit estimators to characterize the distribution of subjective wellbeing across employment sectors for Ghana, which is broadly representative of sub-Saharan African countries. The extraordinarily detailed Ghana Urban Household Panel Survey offers unusual insight into developing country labor markets. The self-reported job and life satisfaction measures it collects are useful proxies for wellbeing as they are comprehensive and rely on individuals own weighting of the importance of various job attributes, thereby mitigating the limitations of objective proxies such as earnings. The random parameter methodology permits quantification of sectoral satisfaction premia as well as how conditional satisfaction varies across agents within sectors, thereby allowing us to document heterogeneity in conditional subjective wellbeing that fixed parameter models cannot detect. They are thus a useful tool in characterizing different employment sectors, and offer important insight into the debate over the functioning of developing country labor markets in general and, the role of the informal sector particular. Analogous to the debate over self-employment in the advanced countries, understanding whether (and to what extent) the latter is, indeed, the inferior part of a segmented labor market, or offers superior employment opportunities for those employed in it requires quantification of the

> 30In an attempt to regain some power, we also ran static specifications (fixed parameter-not shown to conserve space but available upon request).
_Matthew Crawford got a PhD in Political Philosophy from the University of Chicago. Then he abandoned academia after a year, abandoned a Washington DC think-tank job after five months, and opened a one-man motorcycle repair shop. He thinks more now than when he worked at think-tank. He’s part of a vibrant, intuitive, well-educated community. He’s proud of his work, which matters deeply to his customers. His decisions aren’t arbitrarily changed by a superior. His job won’t suddenly be shipped to India. Of course, most people assume fixing motorcycles was the only job he could get._ Business Insider, May 24, 2009.

Among the key questions trade economists need to be able to answer is: When a trade shock strikes such as liberalization, trade agreement, or expansion of a foreign export power, who benefits and who is hurt, and by how much? There are as many ways of approaching these questions as there are ways of dividing people into economically meaningful subgroups. The oldest literature divided people by what can be called ‘class’ lines, making a distinc– tion between workers and the owners of physical or human capital the Stolper-Samuelson approach. More recent approaches have divided up workers based on their industry of employment (Revenga (1992), Pavcnik, Attanasio and Goldberg (2004), Artu ̧c, Chaudhuri and McLaren (2010)); region of residence (Topalova (2007), Kovak (2010), Hakobyan and McLaren (2010)); and age (Artu ̧c (2012a)), in each case attempting to quantify how trade shocks affect people in the different groups differently.

More recently, several studies have focussed on a division of workers by _occupations_ , often making use of a data set explored by Autor, Levy, and Murnane (2003) that breaks down the ‘task’ composition of a wide range of occupations in US labor data. Authors who exploit these distinctions to look at the differential effects of trade shocks on
climate and governance performance, and Greece the worst. Portugal and Spain fall in between and their performances mirror each other’s. Poor performance on these indicators is likely to have a negative impact on growth (Olson et al, 2000).<sup>76</sup> Figure 14a‐d shows GIPS’s most recent global competitiveness ranking (GCR) and other related measures. The evolution of these indicators provides insight on outcomes. Greece’s performance is 3 times worse in the GCR in 2012‐2014 than it was at the beginning of the decade (Figure 14a). On almost all measures of institutional quality (Figures 14b, c, d), government effectiveness, rule of law, regulatory quality, the strength of auditing and accounting, resolving insolvency and, in particular, corruption, Greece shows a widening difference with the other countries and a much worse deterioration. Table 10 below shows how GIPS compare with other countries at similar or lower GDP per capita. Portugal outperforms Greece, despite being poorer. Since 2012, some indicators show that Greece’s relative performance is improving. For example, the doing business indicator shows the largest improvement in Greece and Portugal’s relative rankings and a deterioration in Ireland’s and Spain’s. The OECD’s product market regulation index also shows an improvement for Greece, but both Portugal and Spain’s changes outperform it. Yet, a net positive output response to structural reforms takes time, particularly after crisis, when the rate of firm destruction is hastened. Despite, these selected improvements in GPS, they clearly have a substantial reform agenda ahead.

**Table 10: GDP per capita and Governance**

||GDP pe<br>(constant<br>|r capita<br>2010 US$)<br>|Control of<br>|corruption<sup>1</sup><br>|Glo<br>competitiv<br>|bal<br>eness
# 4.2 Survey Statistics

The responses to the questions concerning current situation of solid waste collection and disposal service show that people think the solid waste is causing serious problems in this county. Over 85% of the respondents mentioned the solid waste problem in their neighborhood to be one of the most urgent environmental problems. 70% of the respondents mentioned the trash problem to be one of the most urgent social problems. 66% of the respondents believe the residential solid waste to be a serious problem in Eryuan, among which 38% believe the problem to be very serious.

The survey also shows that Eryuan solid waste collection and disposal service lags significantly behind. 53% of the respondents, including all respondents in the three towns to be covered by the project, report that there are no solid waste collection and disposal activities in their neighborhood and another 21%, which are supposed to be covered by the old system, reported only irregular collection and disposal activities. Over 20% of the respondents believe their trash is only simply dumped and 42% do not know how their solid waste is treated.

The obvious lack of solid waste treatment service has caused negative impact on people located around the current solid waste dump site. 88% of the respondents believe the solid waste treatment project to be necessary and 94% of the respondents expressed their willingness to cooperate with the new project.

As shown in Table 2, 218 responses can be used for WTP estimations. Two observations have to be deleted as the respondents gave the same uncertainty responses to all of the proposed bid prices<sup>14</sup> , and another observation has to be deleted from the analysis as it did not give a positive (―probably yes‖ or ―definitely yes‖) answer even at the price of zero<sup>15</sup> .

The statistics of the responses to the MBDC WTP question are summarized in Table 3. For each price listed in the questionnaire, the percentage of respondents who choose a specific likelihood
vices Colombia offers all forced migrants (regardless of status) or unwilling to exercise these rights for fear of being identified and deported. Table A.1 describes the services provided to all Venezuelan forced migrants and the additional services and benefits PEP offers.

The PEP program aimed to foster the integration of forced migrants into Colombia’s society and economy by providing access to formal labor markets and entrepreneurship, and by removing barriers to education, healthcare, and other public and private services.

# **II. B Rollout and eligibility**

The Colombian government first introduced two waves of the PEP program that targeted more affluent Venezuelans who migrated through official immigration checkpoints and had lawful migratory status. Nearly 182,500 permits were issued during these two waves but this excluded a large share of Venezuelans in Colombia because the majority had migrated through illegal border crossings, overextended stays, or with a temporary document ( _Tarjeta de Movilidad Fronteriza_ ) that only allowed short stays in border areas.<sup>7</sup> To address the large share of forced migrants still without regularized status, the Colombian government introduced a third PEP wave in August 2018 for all Venezuelans who had registered in the Administrative Registry of Venezuelan migrants (again, RAMV for its Spanish acronym). RAMV had been implemented between April 6 and June 8, 2018—two months prior to PEP’s enactment. Recall that RAMV was not designed to grant work permits and was not advertised in that way; it was only instituted to count the Venezuelan migrants who had not yet regularized their migratory status. However, in August 2018, just a few weeks before leaving office, Colombian President Juan Manuel Santos unexpectedly declared that forced migrants who had registered in RAMV were now eligible for a new wave of the regularization program: PEP-RAMV, the focus of this work. For brevity, we refer to PEP-RAMV simply as PEP. Figure 1 illustrates the rollout of RAMV and PEP.

Unlike previous regularization programs around the world, PEP did not impose eligibility

> 7The _Tarjeta de
, a detailed OaxacaBlinder threefold decomposition was performed and the results are presented in

**Table 9. Oaxaca-Blinder threefold and twofold decomposition of** **<u>monthly wages of male and female employees</u>**

||2008|2009|
|---|---|---|
|Natu|ral Log of Monthly Ear|nings|
|Male|10.062*** (0.011)|10.146*** (0.012)|
|Female|9.970***(0.012)|10.100*** (0.014)|
|Wage Differential|0.092*** (0.016)|0.046* (0.018)|
|**Threefold Decomp**|**osition**||
|Endowments (E)|-0.110*** (0.019)|-0.098***(-0.021)|
|Coefficients (C)|0.144*** (0.015)|0.106***(0.017)|
|Interaction (I)|0.058*** (0.018)|0.038*(0.019)|
|**Twofold Decompos**|**ition**||
|Explained|- 0.064***(0.013)|-0.071***(0.014)|
|Unexplained|0.156***(0.015)|0.117***(0.016)|

Robust standard errors are in parentheses; ***, **, * denote statistical significance at 1%, 5% and 10% respectively Source: Estimates are based on Serbia LFS, 2008 and 2009 surveys

**Table 10. Gender Wage Gap at Quartiles,
the positive eects of globalization (smaller impact of borders) on international trade. The dip in 2002 is probably a reection of the economic recession during this period, while, due to the use of three-year intervals, the deep global economic recession of 2009 is not captured in our graph.

In column (2) of Table 1 we allow for heterogeneous eects between shallow vs. deep trade agreements. To this end, we capitalize on the data from World Bank's DCRTA, cf. Hofmann et al. (2019) and Mattoo et al., eds (2020), to dene _DTAij,t_ as an indicator that takes a value of one for deep trade agreements (i.e., we use the variable `pta_mapped' 22
evidence in Cirera et al. (2021) confirms this pattern using BPS data. Our work suggests that the elasticity of change in employment with the drop in sales was comparable for both formal and informal firms in the first phase of the crisis. In the recovery phase, however, informal firms show a nearly inelastic response to employment growth with the recovery in sales. This is in contrast to formal firms where the change in employment is slower but still positive (Figure 6, panel a). Using a sharper definition of fully formal firms, we illustrate that not only do all types of informal firms show signs of relatively slow job recovery, and particularly the parasite ones, but that the fully formal firms are remarkably different (Figure 6, panel b). This implies that the degree of formality matters. Given the presence of a large informal sector in South Asian countries, this does not bode well for job recovery in the post-crisis period.

> 14Mean size in our sample is ten employees for necessity firms, 13 for De Soto, 12 for parasite firms, and 48 for fully formal. We test the robustness of our result to adding uncertainty and change in sales as controls in Table B4, and the results do not change.

18