rafmacalaba/datause-encoder-data huggingface dataset:
Next the teacher invites the students to ask teacher-like questions to one another to support learning (Palinscar & Brown, 1984).

Use of roles in the classroom can contribute to students’ leadership skills in that teachers can create opportunities for students to set goals for their work, plan projects, and decide how to work with others in a team (Hay & Dempster, 2004). Teachers can also assign roles that relate to real school problems that need resolving (e.g., peer mediation to deal with school bullying) (Drago-Severson, 2004; Irvin & White, 2004; Wallin, 2003). Further, assigning roles may encourage students’ more active engagement in and deeper understanding of the content (National Research Council, 2012). Taken together, existing work shows the value of activities that allow students to take on different roles and responsibilities.

# _3. Students volunteer to participate in the classroom_

Classroom participation indicates active engagement in learning and is viewed as a highly desirable precursor of student learning. Classroom participation has two aspects. At the base level, the presence versus absence of student participation is one important indicator of classroom quality (Chen & Yang, 2017). Further, the extent to which most students volunteer to participate (versus just a few) stems from whether teachers have been successful at establishing a supportive classroom environment in which all students are comfortable and willing to take on roles in the classroom. Classroom dynamics studies find that students who generally volunteer their answers in class tend to be more intrinsically motivated to learn and perform at a higher level academically than those who do not volunteer (Evertson et al., 1980; Hattie et al., 2014), suggesting the importance of focusing attention on this element.

# **3.4.2. Perseverance**

Learning is not always fun – it requires effort, and failures and frustrations are unavoidable. Thus teachers need to encourage students to persevere through learning challenges by (i) helping them understand that their abilities and knowledge can be developed, (ii) providing them with strategies for developing their abilities and knowledge, and (iii) reassuring them that setbacks are an integral part of learning (e.g., Dweck, 1999, 2002, 2013). Teachers should also encourage students to set learning goals for themselves, and to persevere in their efforts to reach these goals (e.g., Duckworth, Peterson, Matthews, & Kelly, 2007). Teachers can have longstanding influence on their students’ perseverance, as 31
Policy Research Working Paper 5193

# **Abstract**

Accelerating development in Sub-Saharan Africa will require massive expansion of access to electricity— currently reaching only about one-third of households. This paper explores how essential economic development might be reconciled with the need to keep carbon emissions in check. The authors develop a geographically explicit framework and use spatial modeling and cost estimates from recent engineering studies to determine where stand-alone renewable energy generation is a cost effective alternative to centralized grid supply. The results suggest that decentralized renewable energy will likely play an important role in expanding rural energy access. But it will be the lowest cost option for a minority of households in Africa, even when likely cost reductions over the next 20 years are considered. Decentralized renewables are competitive mostly in remote and rural areas, while grid connected supply dominates denser areas where the majority of households reside. These findings underscore the need to de-carbonize the fuel mix for centralized power generation as it expands in Africa.

This paper—a product of the Environment and Energy Team, Development Research Group—is part of a larger effort in the department to assess options for cleaner energy in developing countries and overcoming barriers to their adoption and sustainability. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at udeichmann@worldbank.org, cmeisner@worldbank.org, smurray@worldbank.org and dwheeler@cgdev.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
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25
and 60 percent of children respond correctly, the mean ability is 425. By comparison, the same result on item 21 would suggest a higher mean ability level since the question is more difficult.

The key advantage of IRT in large testing situations is this ability to link tests, either in a cross-section (when different children are administered different test questions) or over time (when children are tested more than once). Formally, IRT equates competence levels by identifying off the set of common items across the tests and defining a reference population. Absent a reference population, the IRF given by (1) provides competence levels and item parameters that are identified up to an affine transformation—poor performance cannot be distinguished from a difficult test and a large variance in achievement cannot be distinguished from a highly discriminating test. Specifically, the transformations will yield identical characteristic curves, so that _Pg_ ( _θ_<sup>_′_</sup> ; _a_<sup>_′_</sup> _g_<sup>_, b′_</sup> _g_<sup>_, c′_</sup> _g_<sup>)=</sup><sup>_Pg_(</sup><sup>_θ_;</sup><sup>_ag, bg, cg_).However,</sup> _if item parameters are fixed_ , the scale of _θ_ —the mean and variance—is fixed as well. Thus by calibrating items using a defined reference group we can score the performance of all other children relative to that group, regardless of which items children actually complete. In our case, the reference group is given by the TIMSS knowledge scale. This scale fixes the item parameters such that the TIMSS 1995 sample of eighth grade children have mean 500 and standard deviation 100 (Yamamoto & Kulick 2000).

In our application, all students receive the same exam and all item parameters are fixed using TIMSS. In general, however, this need not be the case. Students can receive different exams and new items so long as each item can be linked to a common set of fixed items or a fixed reference population. For example, three two-item exams with item pairs (1,2), (2,3) and (3,4) can all be linked provided that one of the four items is fixed, even if each test is administered to a different population.<sup>4</sup>

> 4To see this, note that if we fix item 1—drawing it from the TIMSS item bank, say—we can estimate the

7
# I. **Introduction**

> This paper assesses the importance of the regulatory framework as a determinant of private sector investment in infrastructure, using recently compiled data on private and public sector investment in the water, power, telecommunications, roads and railways sectors in nine large countries in Latin America. Controlling for standard'determinants of investment, we

> analyze the impact of variables that represent different aspects of the prevailing regulatory regime on a country's ability to attract private investment in infrastructure.

During the last decades of the twentieth century many countries in Latin America undertook public sector reform and introduced private participation in formerly state-dominated sections of their economies through management contracts, concessions or outright privatizations. In the infrastructure sectors this was motivated by a desire to improve performance and increase efficiency in service provision, as well as by the fact that govemments were constrained in increasing service coverage or improving public utility performance by limited fiscal resources and a multitude of competing claims on these resources. But investment in infrastructure is characterized by large up-front, usually sunk, costs that lead to a high risk of expropriation, long gestation lags before revenues are generated and revenues that are usually generated in local currency. These aspects lead to a need for both long-term commitment and long-term financing in local currencies. However, the limited depth of nascent capital markets is rarely able to generate funding of the maturity and volume that were necessary to finance private infrastructure investment in Latin America, which resulted in an effort to attract foreign capital. Analysts agree that an environment of macroeconomic and political stability, policy credibility, and the existence of a sound regulatory framework are necessary for lowering the perceived risk of expropriation and thus for attracting private capital. In particular, the character 3
- 22 -

**Qaotas on steel.** For thirty years after World War II, world consumption of steel grew by 5 percent to 6 percent a year. But the oil crisis of ldte 1974 and. the following world recession brought dramatic challenges to the steel industry -- consumption in 1975 was 10 percent less than in 1974 and growth of demand disappeared. It would tale 10 years, until 1984, for world demand to make up the 10 percent drop recorded on 1975, and growth after that would be much slower than before 1975. Besides the change of demand and the resulting overcapacity of the world industry, significant changes of competitive structure had also occurred. These changes allowed Japan and eventually Korea to enjoy a cost advantage in producing standardized products over traditional producers in Europe and North America. In response to this challenge, both the United States and the European Community established comprehensive systems of quantitative restrictions on imports.

David Tarr has published an analysis of the effects of these US and EC restrictions on exporting countries, particularly Korea. He found, first of all, that though the cutback of export sales caused the price of steel to fall in Korea, the comprehensive systems of controls in place in the US and in the EC actually allowed Korean export prices to rise. Korea's output of steel was reduced, and because Korea has comparative advantage in world trade in steel, this meant that there were efficiency losses to the world economy and specifically to Korea. But Tarr estimates that the "rent" Korean exporters collected by way of the higher-than-competitive prices in the US and EC markets are several times larger than the efficiency losses, leaving the Korean economy more than 32 million dollars a year better off than it would be if US and EC steel imports were not controlled.

Antidumping **orders against color television sets."** The Korean electronics industry began as a modern industry in 1958, when it first produced radios on an assembly line. By 1988, total production was $24 billion. Of this output, $15 billion, almost two-thirds, was exported.

1 This subsection draws from Bark (1991).
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Dobbs, L. (2007). Stuck in the Slow Lane: Reconceptualizing the Links between Gender, Transport and Employment. _Gender, Work & Organization_ , _14_ (2), 85–108. https://doi.org/10.1111/j.1468-0432.2007.00334.x Dominguez Gonzalez, K., Machado, A. L., Bianchi Alves, B., Raffo, V., Guerrero, S., & Portabales, I.

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_Journal of Planning Literature_ , _27_ (2), 153–169. https://doi.org/10.1177/0885412211431984 39
level survey data collected through the Chinese Annual Industrial Survey for the 2003-2008 period and using multiple empirical strategies and identifications, Filippini et al. (2020) estimate the impact of a national EE program on firms’ TFP growth in China's iron and steel industry. They find a positive and statistically significant effect. Using a simulation model to analyze the impacts of adopting selected energy-efficient technology in the chemical industry, Li et al. (2021a) find that adopting clean technologies would reduce more than 40% of the production costs for the same output level from the industry. Huang and Wu (2021) report a reduction in production costs in the cement industry due to energy-efficient technologies in Taiwan. The results of several studies are presented in Table 2. Most studies show positive impacts of clean or energy-efficient technologies on productivity. As expected, the impacts vary across the studies. Some studies, such as Boyd and Pang (2000), explain how an increased EE enhances the productivity of a firm, presenting an example of the glass industry, which is an energy-intensive industry.

Some studies find that investments in the development or deployment of clean technologies also increase labor productivity. Using data from firms involved in developing and adopting energy-efficient technologies during the 2012-2014 period in Austria, Germany, Switzerland, Arvanitis et al. (2017) find that the investments on clean technologies increase labor productivity. However, the positive relationship between the adoption of clean technologies and a firm’s productivity could be conditional on other policies or activities. For example, Hottenrott et al. (2016) find that firms gain productivity by adopting environmental technologies only in the presence of supportive organizational structures. Using the panel data on the adoption of environmental technologies in German manufacturing and service firms for the 2000-2008 period, they find firms that adopted green technologies together with changes to their organizational structures utilize green technologies better than those firms that only adopted green technologies without having supportive organizational structures.

**Table 2. Selected empirical studies examining the relationship between clean investment and cost of production in the manufacturing sector**

|Study|Method|Findings|
|---|---|---|
|Li et al. (2021a)|Simulation method using<br>Aspen Plus software for|Retrofitting the coal chemical industry (CCI) with more<br>efficient petrochemical technologies reduced the total|
||the chemical industry.|annual costs (operating and capital expenditure) of CCI by<br>41.3% with total product yield almost unchanged.|

18
32

# Table 2: Descriptive statistics

||Ful<br>|lsample<br>||SH<br>|I = 1<br>|||SHI =0<br>||
|---|---|---|---|---|---|---|---|---|---|
||Mean|SD|Obs|Mean|SD|Obs|Mean|SD|Obs|
|Tot. health exp. per capita|174.30|166.46|872|235.87|210.91|409|119.92|81.45|463|
|PYLL cancer of colon|93.85|32.70|1158|87.77|29.32|594|100.24|34.82|564|
|PYLL breast cancer|224.61|67.76|1158|207.79|73.50|594|242.33|55.97|564|
|PYLL cervical cancer|60.20|42.27|1158|63.50|49.86|594|56.72|32.09|564|
|PYLL diabetes|56.60|46.59|1162|64.99|61.25|598|47.70|18.51|564|
|PYLL ischemic heart disease|527.32|291.84|1162|423.92|211.29|598|636.95|323.89|564|
|PYLL cerebrovascular disease|243.25|132.84|1162|257.21|141.66|598|228.46|121.17|564|
|PYLL influenza pneumonia|229.75|366.43|1162|302.81|472.14|598|152.28|169.80|564|
|PYLL pregnancy|29.33|54.45|1154|41.40|70.74|597|16.39|21.46|557|
|PYLL perinatal causes|746.39|623.71|1162|862.32|687.16|598|623.48|521.64|564|
|Formal sector employment|0.77|0.13|1112|0.74|0.14|575|0.81|0.09|537|
|Employment|0.66|0.08|1163|0.65|0.08|620|0.67|0.08|543|

Note: Health expenditure per capita is at 1960 prices and converted at PPP. PYLL are expressed per 100 000 population. Formal sector employment is as a share of total employment. Employment is as a share of the population aged 15-65.

Table 3: Tests of reverse causality

||DI<br>mo|D<br>del|Rando<br>mo|m trend<br>del|Differen<br>mo|tial trend<br>del|
|---|---|---|---|---|---|---|
||Lead SHI d<br>on eq|ummy test<br>n (3)|Lead SH<br>test on|I dummy<br>eqn (5)|Lead SH<br>test on|I dummy<br>eqn (8)|
|Dependent variable|Coef|p-value|Coef|p-value|Coef|p-value|
|Tot. health exp. per capita|-0.007|0.641|-0.001|0.953|-0.012|0.572|
|PYLL cancer of colon|-0.076|0.198|-0.073|0.198|-0.075|0.279|
|PYLL breast cancer|-0.084|0.189|-0.081|0.206|-0.094|0.167|
|PYLL cervical cancer|-0.032|0.782|-0.026|0.822|-0.039|0.736|
|PYLL diabetes|0.052|0.253|0.058|0.316|0.046|0.381|
|PYLL ischemic heart disease|-0.031|0.003|-0.027|0.014|-0.031|0.003|
|PYLL cerebrovascular disease|0.079|0.102|0.081|0.085|0.075|0.137|
|PYLL influenza pneumonia|-0.060|0.212|-0.068|0.128|-0.069|0.205|
|PYLL pregnancy|0.037|0.774|0.024|0.853|0.047|0.740|
|PYLL perinatal causes|0.007|0.909|0.005|0.944|-0.013|0.869|
|Formal sector employment|-0.011|0.004|-0.009|0.014|-0.011|0.001|
|Employment|-0.002|0.780|-0.002|0.757|-0.001|0.821|
# **1 Introduction**

The past 30 years have seen an unprecedented push for trade liberalization with 262 regional trade agreements (RTAs) involving 188 countries entering into force over this period. While the reduction in trade barriers offers tremendous potential for economic growth and productivity gains, the impacts of trade liberalization may not be universally positive. In particular, there is mounting evidence suggesting that increased global trade may lead to environmental degradation (e.g. Abman and Lundberg, 2020; Zhang _et al._ , 2017; Leblois _et al._ , 2017) which has attracted attention from policy makers, scholars, and the public alike. Indeed, the potential for increased deforestation in Brazil has become a critical stumbling block that has all but halted the ongoing ratification process of the EU-Mercosur trade agreement. Concern over potential adverse impacts of opening trade has stimulated a debate on whether trade agreements should include specific provisions to limit the negative consequences thereof. While some see provisions in trade agreements targeting the environment as a form of thinly veiled protectionism, others perceive them as an important tool for mitigating potential harm from opening trade and a commitment device for environmental policy reform (Frankel, 2009). Despite negotiations and policy discussions around the inclusion of such provisions, there has been little in the way of careful, rigorous work exploring whether these provisions actually function as designed.

Assessing whether environmental provisions in trade agreements work is as difficult as it is important. First, until recently there was a scarcity of detailed information on the specific provisions included in trade agreements. Second, from a methodological point of view, carefully assessing the impact of environmental provisions on environmental outcomes presents a number of econometric challenges that stem from the non-random inclusion of such provisions.

In this paper, we study the effectiveness of environmental provisions in trade agreements in mitigating environmental harm. We use high-resolution, satellite-derived estimates of deforestation as a measure of environmental damage. Deforestation is one of the most pressing environmental challenges of the modern era, both in its threat to biodiversity through destruction of sensitive habitat as well as its prominent role in global climate change through associated greenhouse gas 1