rafmacalaba/datause-encoder-data huggingface dataset:
household surveys to construct an index to measure the distance of household dwellings to the nearest service provider. This indicates whether households in Jordan have access to services such as education, health or other infrastructure that either increase consumption or creates savings. Two criteria were used to identify these services: the depth of reforms and transformation that occurred in these sectors in the past decade, this is the case for education and health, or the lack of access and lack of public investments in the case of sewage networks<sup>47</sup> . Sixth, sectoral<sup>48</sup> employment for various household members is also examined. This helps capturing the changes in consumption due to sectoral transformation that occurred between 2002 and 2010. Changes that occurred in value added, productivity and employment, and which often translates into changes in household returns (income or wages) coming from those sectors. Finally, the paper controls for regional residency in order to capture the effect of governorates on household spending<sup>49</sup> .

_V.3. Services and Income Sources as Determinants of Welfare Growth_ Tables 8 and 9 (in Annex) display the findings from running the Re-centered Influence Function (RIF) regression for 2002 and 2010. The signs and the statistical significance of the covariates coefficients across the different percentiles reveal that the regional welfare bias towards Amman and urban areas has been indeed been reduced in the past decade. With 6 out of the 11 coefficients turning positive and statistically significant across the entire population distribution, findings suggest that consumption levels in the governorates are catching up with the capital and consequently reducing the household welfare gap. This confirms earlier results on the role of the decline in intra-regional disparities and it effects in reducing overall inequality in Jordan<sup>50</sup> . Furthermore, the economic transformation that occurred in the past decade in Jordan seems to have accentuated the role of rent in increasing household welfare as opposed to labor income. Indeed Tables 8 and 9 suggest that receipt of rent and income from capital assets has contributed positively to the increase in household consumption in both 2002 and 2010, with the

> 47 Access to services controls for the supply side effects and their implications on household welfare. It should be noted that services such as electricity and water are very much accessible by all Jordanians and were therefore omitted from the empirical model.

> 48 Sectors were grouped as to match the ones presented in the official Jordanian National Accounts.

> 49 A list of the above covariates along with summary statistics on the differences in means between 2002 and 2010 can be found in Table 7 (refer to Annex).

> 50 Reflects the results found earlier on the dominance of the between-group component for reducing inequality.

24
16 ERPs developed extensively and a number of studies computed ERPs for large groups of countries.9 In spite of the efforts made by a number of experts to g.neralize the applicability of ERPs and DRCs, both concepts have important limitations within a general equilibrium framework. Perhaps the most serious problem is that in a world with more than two final goods ERPs give no information on the way in which resources will be reallocated in the case of changes in the tariff structure. This limitation of ERPs has led a number of experts to argue that the concept of effective rate of protection should be abandoned altogether (see for example Dixit and Norman 1980 and Dixit 1986; Bhagwati and Srinivasan 1983 provide a fairly detailed discussion on the properties and limitations of ERPs and DCRs; see Balassa and Schydlowsky on the relation between ERPs and DRCs).

Although both ERPs and DRCs are much more limited than what it once was thought, they do provide some valuable information; abandoning them would be clearly an overreaction. More specifically, ERPs and DCRs give us information on the extent of inefficiency "society", or perhaps more accurately the "government", is willing to grant a particular sector.'° Even though this is a much more modest role than that assigned to these indicators in the past, it is a particularly important one in political economy studies of trade policy. What is critically important, however, is to be aware of the limitations of these concepts.

9See, for example the studies directed by Balassa (1971, 1982).

10The reason for this interpretation follows directly from the definition of ERP as the percentage deviation of domestic unit value added from world (Ind efficiently produced) unit value added in industry J.
crude measure of productivity. We also use indicators for whether the firm hires relatives from outside the household. A similar measure indicates whether the firm hires any non-relatives.<sup>18</sup>

# **2.4. Firm Dynamics**

Since the ELMPS follows households in four waves, 1998, 2006, 2012 and 2018, we can trace the dynamics of firms in our data set. Dynamics can occur over three pairs of waves: 1998-2006, 2006-2012, or 20122018. An observation for our dynamic model thus has data from a base wave and a subsequent wave, e.g. for 1998-2006 the base wave is 1998 and the subsequent wave is 2006.

Creating a panel of firms from a household survey presents a number of complexities. We restrict all analyses to cases where the household was observed in both the base and subsequent wave of a pair, so we do not classify a firm as being created simply because a household joined our data set, nor a firm exited because the household attrited. We do track splits, so cases such as where an unmarried son may have had a household enterprise and then took it with him to his new household when he married and moved out (split) are captured as a firm surviving, so long as we successfully located the split household. We define an enterprise that existed in the base wave as having survived over a pair of waves if at least one household member still has an enterprise of the same economic activity (identified on the one-digit level using ISIC 4 coding). We examine the outcome of exit (closure) as the complement to an enterprise surviving. We also consider the formation of new household enterprises, that is, among households that were not engaging in an economic activity in the base wave of a pair, new enterprises in the subsequent wave. We further consider – among enterprises that survived across a pair of waves – the dynamics of (in)formalization, that is, changing formality status between the base and subsequent wave. We also consider, again among surviving enterprises across a pair of waves, employment growth, specifically whether the total number of workers in the enterprise is larger in the subsequent period than it was in the base period.

# **3. Methods**

# **3.1. Situating our universe of firms and employment**

We begin our analyses by situating our focus – private non-agricultural establishments with 1-24 workers – within the landscape of employment in Egypt. We describe the percentage of employment and the number of workers in this segment of the economy, in comparison to other sectors. We also describe employment formality by segment; note that this is distinct from firm formality, both in terms of the denominator, and in that, while a firm must be formal to have formal employees, not all employees within a formal firm are necessarily formal.

> 18 The distinction between relatives and non-relatives is not available in 1998 or 2006, so when analyzing dynamics we simply use an indicator for employment outside the household, which is available in all waves.

7
- 19 -

These results--positive impacts on monthly earnings and hours worked but no systematic effect on hourly wage--raise questions about whether training actually increases productivity, in which-case one might expect higher hourly wages, or whether it raises earnings by inducing greater work effort among trainees. We believe the answers lie in the kinds of jobs that trainees find after completing training. The raw data suggest that a higher proportion of trainees eventually find jobs in large enterprises as compared to the control group. For the sample as a whole, employment in large firms is associated with longer hours of work per week and higher monthly salaries, which may partially explain the results that we find. To explore this hypothesis more rigorously, we estimated an ordered logit model for the probability of employment in ten (increasingly larger) size categories of firms. As regressors, we included measures of experience, duration of previous unemployment, time dummy variables, and an indicator variable for participation in the PROBECAT program.

Table 13 reports the results for three different model specifications: training by itself, training interacted with a quadratic schooling measure, and training interacted with indicator variables for each schooling level. Compared to the control group, all three specifications suggest that trainees are more likely to find jobs in larger firms. The fully interacted specification reveals an inverted-U pattern of effects by schooling group, similar to the previous findings for earnings and hour of work. In short, the PROBECAT program appears to raise trainees' monthly earnings and work hours by facilitating their entry into larger firms offering higher pay and more stable, full-time employment. It may achieve this result either by retraining the unemployed in skills for which there is demand, i.e. a matching effect, or by making them more trainable, i.e. providing them with learning skills. PROBECAT may also indirectly impact their future earnings potential by placing them in large firms that tend to provide employees with more on-the-job training.&W Trainees will have to be followed over a longer time period for us to verify this hypothesis.

To summarize, the results suggest that participation in PROBECAT increases monthjv earnings of male trainees, and that this occurs primarily through their increased hours of work. The disaggregated analyses by schooling reveals that this effect varies with schooling attainment. The effects of training on monthly earnings are largest for those with secondary education (7 to 9 years of schooling). The hours of work effects are large and positive _211_ Estimates drawn from the 1988 National Employment Survey show that the proportion of workers receiving training in the workplace varies from 5% in micro enterprises to 23% in large firms (those with more than 250 employees).
offset by the inclusion of these environmental provisions. This suggests that provisions may limit agricultural land expansion, but not intensification. Net increases in agricultural exports are also lower in RTAs with environmental provisions, but not entirely offset. We find little evidence that production of timber products of forest exports are significantly affected. We find that separate, supplemental dispute settlement mechanisms unique to these environmental provisions are not any more effective in mitigating forest loss than general scope dispute settlement mechanisms in RTAs. We validate our primary findings using an alternative identification strategy based on a multiple event study model at the country level that features different identifying variation. This alternative approach yields similar qualitative and quantitative findings and provides supporting evidence that our results describe a common, underlying causal response to the inclusion of environmental provisions in RTAs.

Our primary contribution with this paper is to provide the first causal evidence on the effectiveness of environmental provisions in regional trade agreements.<sup>1</sup> In particular, we show that the inclusion of forest-related provisions has mitigated forest loss resulting from trade liberalization. Relative to Baghdadi _et al._ (2013), an early attempt to evaluate the impact of environmental provisions in RTAs on emissions, our empirical framework accounts for the potential endogeneity of RTA content, yielding policy-relevant insights into the causal impacts of such measures.<sup>2</sup> Our work contributes to the large literature studying the effects of trade agreements. This literature has consistently found that trade agreements significantly increase trade flows between member countries.<sup>3</sup> The more recent strand of this work has emphasized the importance of the varying content of RTAs in assessing their trade effects. Baier _et al._ (2014) find evidence of differential trade effects from different types of agreements (e.g. partial scope agreements, free trade agreements or custom unions), while Mattoo _et al._ (2017) show that “deep” agreements (i.e. RTAs that cover a larger number of policy areas beyond tariff reduction) are associated with a stronger

> 1Furthermore, to our knowledge this work is the first to develop a strategy to identify causal effects of RTA content more broadly.

> 2The treatment of endogeneity in Baghdadi _et al._ (2013) addresses endogenous bilateral selection into trade agreements as in Baier and Bergstrand (2004, 2007); Egger _et al._ (2008), but does not discuss selection bias in environmental provisions.

> 3Seminal works include Baier and Bergstrand (2007); Egger _et al._ (2011); Bergstrand _et al._ (2015). See Lim ̃ao (2016) for a survey.

3
The Northeast also experienced a fall in the headcount poverty ratio of household heads after 1994. In 1999, in Pernambuco, the state with the highest per-capita GDP in the Northeast, 41.6 percent of the people were poor. The respective figure is slightly lower for Rio Grande do Norte, namely, 39.7 percent, but substantially higher for Maranhão (52 percent). In the 1993-99 period, the incidence of poverty in Pernambuco, Maranhão and Rio Grande do Norte fell by 12.2 percent, 13.4 percent and 14.7 percent, respectively. Rio Grande do Norte and Paraíba experienced thus the highest reduction in poverty in the Northeast namely 14.8 percent and 17.5 percent, respectively, which is more than twice the national rate (7.3 percent).

Considering the past two decades, the headcount ratio fell in the Northeast, Maranhão, and Rio Grande do Norte by 5.4, 12.0 and 9.7-percentage points, respectively since 1981. In Pernambuco, poverty is actually slightly higher (by 0.8 percent) in 1999 than in 1981.

**Figure 6: Squared Poverty Gap: Indigence Line**

<!-- Start of picture text --> 30.0%<br>25.0%<br>20.0%<br>15.0%<br>10.0%<br>5.0%<br>Brazil NE Maranhao Rio Grande do Norte Pernambuco<br>0.0%<br>1981 1985 1988 1990 1993 1995 1997 1998 1999<br><!-- End of picture text --> _Source:_ Authors’ calculations based on PNADs 1981 to 1999.

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- **Greenstone, Michael, and B Kelsey Jack.** 2015. “Envirodevonomics: A Research Agenda for an Emerging Field.” _Journal of Economic Literature_ , 53(1): 5–42.

- **Hansman, Christopher, Jonas Hjort, Gianmarco Le ́on-Ciliotta, and Matthieu Teachout.** 2020. “Vertical Integration, Supplier Behavior, and Quality Upgrading among Exporters.” _Journal of Political Economy_ , 128(9): 3570–3625.

- **Hazen, Elliott L, Kylie L Scales, Sara M Maxwell, Dana K Briscoe, Heather Welch, Steven J Bograd, Helen Bailey, Scott R Benson, Tomo Eguchi, Heidi Dewar, et al.** 2018. “A dynamic ocean management tool to reduce bycatch and support sustainable fisheries.” _Science Advances_ , 4(5): eaar3001.

- **Hodgson, Charles.** 2021. “Information Externalities, Free Riding, and Optimal Exploration in the UK Oil Industry.” Working paper.

- **Huang, Ling, and Martin D Smith.** 2014. “The Dynamic Efficiency Costs of CommonPool Resource Exploitation.” _American Economic Review_ , 104(12): 4071–4103.

- **IMARPE.** 2018. “Situaci ́on del Stock Norte-Centro de la anchoveta peruana (Engraulis ringens) al 01 de Abril de 2018 y perspectivas de explotaci ́on para la primera temporada de pesca de 2018.” Instituto del Mar del Per ́u (IMARPE).

- **IMARPE.** 2019. “Elaboraci ́on de la Tabla de Decisi ́on para la determinaci ́on del L ́ımite M ́aximo de Captura Total Permisible por temporada de pesca en la pesquer ́ıa del Stock Norte-Centro de la anchoveta peruana.” Instituto del Mar del Per ́u (IMARPE) IMPDGIRP/AFDPERP Edici ́on 4 Revisi ́on 1.

- **Instituto Humboldt, and SNP.** 2017. “Segundo conversatorio sobre el dise ̃no de las redes de cerco de anchoveta y el dise ̃no de una red experimental para su uso en Operaciones Eureka.” Instituto Humboldt de Investigaci ́on Marina y Acu ́ıcola (Instituto Humboldt) and Sociedad Nacional de Pesquer ́ıa (SNP).

- **Instituto Humboldt, SNP, and CeDePesca.** 2018. “Propuesta de modificaciones al r ́egimen sancionador pesquero en relaci ́on con las limitaciones de selectividad y el incentivo de pr ́acticas que apoyen la sostenibilidad de la pesquer ́ıa del recurso anchoveta desde la perspectiva de la pesca industrial.” Instituto Humboldt de Investigaci ́on Marina y Acu ́ıcola (Instituto Humboldt), Sociedad Nacional de Pesquer ́ıa (SNP), Centro Desarrollo y Pesca Sustentable (CeDePesca).

- **Isaksen, Elisabeth Thuestad, and Andries Richter.** 2019. “Tragedy, Property Rights, and the Commons: Investigating the Causal Relationship from Institutions to Ecosystem Collapse.” _Journal of the Association of Environmental and Resource Economists_ , 6(4): 741–781.

- **Joo, Rocio, Omar Salcedo, Mariano Gutierrez, Ronan Fablet, and Sophie Bertrand.** 2015. “Defining fishing spatial strategies from VMS data: Insights from the world’s largest monospecific fishery.” _Fisheries Research_ , 164: 223–230.

49
Sergio Firpo and Alysson Portella. Decline in Wage Inequality in Brazil: A Survey labor supply, while Haanwinckel (2018) includes changes in demand and minimum wage. Consequently, it comes as no surprise that almost all changes in inequality are driven by movements in the relative supply of skills. Although the push towards more structural models that account for the role of occupations is certainly a valuable contribution, future research should try to extend them in the direction of accommodating other features of labor markets and workers’ characteristics. Particularly, a dynamic model in which workers build up experience would not only help in accounting for the contribution of other worker characteristics, but also in understanding the reasons behind the observed decrease in the experience premium.

# **3 Changes in Demand: Trade Liberalization, Commodity Shocks, and Technological Change**

In the first years of the 21st century, Brazil was hit by a positive demand shock that resulted in favorable terms of trade and spurred growth in the commodity sector of the economy, together with economy-wide gains. Similarly, in the early 1990s, Brazil underwent important economic reforms that liberalized markets both through reduced tariff and non-tariff barriers on imports. Traditional neoclassical models predict that both shocks, by changing the relative price of goods that are intensive in a particular kind of factor - in our case, low or high-skilled labor - can lead to changes in income distribution. At the same time, important technological changes took place around the world, which researchers point out as potential sources of polarization and increasing wage inequality in the developed countries since these new technologies increased the demand for high-skilled workers (Autor and Dorn, 2013; Autor and Handel, 2013). In this section we investigate the possible impacts each of these factors may have had in the Brazilian wage distribution.

## **3.1 Trade liberalization and its impact on inequality**

It is widely agreed among economists that international trade can affect the distribution of earnings within countries by changing the relative prices of products and factors. For instance, the well-known Stolper-Samuelson theorem within the HecksherOhlin model predicts that increases in the relative price of a given product will increase the remuneration of the factor most intensively used in its production. Moreover, it predicts that trade liberalization increases the relative prices of the relatively more abundant factor of production. By using two types of labor, skilled and unskilled, this theorem can help us understand relative changes in the wages of low and high educated workers.

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**Figure 12:** Growing indebtedness

<!-- Start of picture text --> 100<br>75<br>50<br>25<br>0<br>Current Debt / GDP (%)<br>Future Debt / GDP (%)<br>0 25 50 75 100<br><!-- End of picture text --> upper threshold is declining for Argentina, which is in line with a higher probability of a panic. For South Africa, the threshold has remained fairly constant.

**Figure 13:** Illustrating time varying debt thresholds

<!-- Start of picture text --> ZAF ARG<br>80.0 120.00<br>70.0<br>100.00<br>60.0<br>80.00<br>50.0<br>40.0 60.00<br>30.0<br>40.00<br>20.0<br>20.00<br>10.0 Debt Upper Lower Debt Upper Lower<br>0.0 0.00<br>% GDP % GDP<br>2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020<br><!-- End of picture text -->

# **4 Results and tests**

Apart from using the DVA as a means of uncovering underlying vulnerabilities, one can also test how well it does in terms of predicting defaults. This is an essential part of an early warning system. Does it warn that a country is becoming more exposed to shocks (and hence more vulnerable) and does it indicate whether a country’s default probability is rising? The empirical results are only useful if they provide reasonable signals about actual 20
Extra Training: For the groups of students that received extra training, on top of books, similar matching results are presented in Table A.1 in the annex. After matching, the covariates that could inuence test scores, such as students' and their families' characteristics, teachers' qualications, and school features also did not dier signicantly between the treatment and control groups. In addition, the baseline test scores are generally equivalent among the treated and control groups of students, with a mean total score of 25.2 and 24.0, respectively. Scores on individual tests are also comparable. During the endline survey, students in both groups improved their total mean score, but there is no pronounced widening of the gap in the mean score between treatment and control groups (Table A.3).

Books only: For this intervention, after matching, there was no systematic dierence in teachers' qualications, students' and their families' characteristics as well as school conditions between treatment and control groups (see Table A.2). Similarly, there was no systematic dierence between control and treatment groups at baseline in terms of achievement. The mean of total test scores for treatment and control groups of students were 23.6 and 24.6 points, respectively. Baseline scores on individual tests are also similar across the two groups. The means of total scores on the follow-up tests for treatment and control students were 31.6 and 29.0 points, respectively (Table A.3).

# 4.2 Analytic results

This section presents estimated treatment eects using the empirical approach outlined in subsection 3.2. In the subsequent section, we assess heterogeneity in treatment eects, and also present robustness checks by re-estimating ATEs under dierent specications. The results show that when in-service teacher training and books are are provided individually, they weakly improve test scores on some, though not all, subjects. However, when teachers are trained and students are provided with the necessary books to facilitate the implementation of knowledge acquired during training, test scores improve considerably. The impact of each intervention is discussed below.

Training and Books Intervention: For the group of students who accessed books through classroom libraries and whose teachers participated in training, test scores on almost all tests improved substantially. Table 3 presents ATE on individual test scores as well as on the total score. The total test score increased by equivalent to 34.9 percent 17