rafmacalaba/datause-encoder-data huggingface dataset:
of the social cohesion index (i.e. “willingness to interact with outgroups”), participants were asked to imagine that they need to become part of a committee to decide what type of amenities should be provided in the park that they saw in the VR experience. They were then told that in this committee they would be working with one other person, who was always shown to be a member of the opposite sex and of a randomly assigned ethnic group. The selection of the social cohesion indicators was informed by Naef and Schupp (2009), Wilson (2017), and Glaeser, et. al. (2000) for the measures of trust; Strangor (2012) on stereotypes and prejudice; and UNICEF’s Compilation of Tools for Measuring Social Cohesion, Resilience, and Peacebuilding on inclusion and tolerance. They were relevant for the study context, where other data sources had shown that perceptions and trust toward other groups were low—according to the 2018 World Values Survey, nearly 70 percent of the Pakistanis mistrust people of another religion and 74 percent believe that most people cannot be trusted.

The variable definitions are provided in Table 1.<sup>14</sup> Because the survey included a wide set of questions, four indices were constructed to reduce the dimensionality of the data and the number of statistical tests performed: where refers to the index score for each individual , defined as the sum of the z-scores of the variable DD included in the index. The control mean and standard deviation were used to construct the z- DDii II DD zz scores. Additionally, was standardized for ease of interpretation. Cronbach’s Alpha, which shows the ii strength of the consistency of the components included in each index, indicates that three of the indices DD II (“use of public spaces”, “trust toward outgroups” and “perceptions toward outgroups”) have a coefficient higher than 0.6, while one index (“willingness to interact with outgroups”) has a coefficient of 0.51, just above the threshold.

Table 1. Variable Definitions

> 14 For all questions, “positive” responses were grouped and assigned a value of 1, whereas all “negative” and “neutral” responses listed below were grouped and assigned a value of 0. The positive responses included: “I somewhat like it and I like it a lot”, “Likely and Extremely likely”, “Agree and Agree strongly”, “Trust somewhat and Trust completely”, and “Relaxed and Happy”. The negative or neutral responses included: “I didn’t like it at all, I somewhat didn’t like it, and Neutral”, “Extremely unlikely, Unlikely, and Neutral/Indifferent”, “Disagree strongly, Disagree, and Neither agree nor disagree”, “Do not trust at all, Do not trust much, and Neither trust nor distrust”, “Angry, Tense, and Indifferent”.

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8 In the end, only 6 of the 16 countries - Argentina, Bolivia, Brazil, Colombia, Costa Rica, and Guatemala, - increased export taxes at the start of the trade reforms, as indicated by the implicit export duty3 (see appendix table A.5). The case of Argentina demonstrates the use of higher export taxes to offset the loss in government revenues from tariff reform. In Argentina, the implicit export duty rose from 2.95 percent in 1988 to 14.94 percent in 1989 (see appendix table AS5) while the implicit import duty<sup>4</sup> declined during the same period from 16.08 percent to 7.02 percent (see appendix table A.6). For the other countries for which information is available, the implicit export duty was 1 percent or less prior to the reforms and diminished even further as the reforms progressed. In 5 countries, there were no export taxes following the reforms.

Thus, raising export taxes prior to reducing tariffs was not a common practice despite the concerns of countries over losing public revenues. Moreover, this concern proved to be unfounded, as trade tax revenues rose in most cases due to the replacement of QRs by import tariffs, import and export growth, and the valuation of trade flows at depreciated exchange rates.

The second issue with respect to sequencing that arose for these countries was the order in which quantitative restrictions and tariffs were to be reduced. Like the first issue, this also involved fiscal concerns. The norm has been to reduce QRs first by converting them into tariffs, which has the advantage of raising tariff revenues prior to any tariff reductions and thereby undermining revenue-based opposition to such tariff cuts. Reducing QRs and tariffs simultaneously works to neutralize the possible negative effects of tariff cuts on tariff revenues, while also providing a stronger signal of the direction of government policy. Note that these arguments presume that tariff reductions lead to revenue losses, but the removal of inordinately high tariffs or import surcharges would not reduce revenues if those rates were prohibitive and precluded imports.5 3 The iplicit export duty is the raio of export duties collected to the fo.b. valuo of merchandise expots; implicit export duties are used instead of the nominal export tax rates because the latter are not unifonrdy available.

4 1Tho rdo of the total import duties colLected to the c.i.f. value of merchandise impos.

5 In fact, tariff revenues ny actaally **_increase_** if imports are stimulated by the lower tariffs, fo11owing a Laffer curve. However, evidonce for this is not available because of lack of adequate time wAies data on tariff rates.
progression, narrower access to social protection and pension schemes, limited access to unemployment benefits, unequal access to training and lower wages (Cazes and de Laiglesia, 2014).

Figure 12: Sweden has the highest share of temporary employment among both young workers and older workers in the OECD <!-- Start of picture text --> 60<br>50<br>40<br>30<br>20<br>10<br>0<br>Sweden EU15 Finland OECD Norway Denmark United<br>average average Kingdom<br>Ages 15-24 Ages 25-64 Age 65+<br>total employees, 2013<br>Temporary employees as percentage of<br><!-- End of picture text --> Source: Eurostat, Labour Force Survey database, 2014 edition; OECD Employment and Labour Market Statistics database, 2014 edition.

Unlike other European and OECD countries, Sweden also has a high share of temporary contracts among workers age 65 or above—the highest among Nordic countries. Forty-seven percent of all workers in this age group in Sweden have a temporary contract, compared with 20 percent on average in OECD countries and 28 percent in Finland, the Nordic country with the second highest incidence. The higher concentration of temporary employment among more fragile groups, such as older workers, less educated workers and non-EU immigrants, reinforces the concern about the risk of duality in the labor market already discussed for youth (OECD, 2012).

If temporary employment is the result of voluntary sorting determined by individual preferences and career choices, it is of less concern for researchers and policy makers. A good indicator in this regard is the number of involuntary temporary workers as a percentage of total temporary workers. This percentage is particularly high in Sweden, especially among youth (Figure 13). Fifty-five percent of youth in temporary employment in Sweden did not choose to work with a temporary contract (they either could not find a permanent job or were in a probationary period), compared with an average of 41 percent in the EU15 and 36 percent in other Nordic countries. This confirms the disadvantaged position of youth in the Swedish labor market.

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- d) Infrastructure (e.g. road density). Roads, ports, airports, communication facilities, power, and safe water access also tend to be relatively limited in all countries, although they especially affect countries like Bulgaria or Moldova.

- e) Financial markets (e.g. domestic credit to private sector). Credit markets are also relatively thin in countries like Romania or Moldova.

- f) Volatility (e.g. inflation, consumer prices). Macroeconomic and relative price volatility is typically more extreme in countries like Romania or Moldova than in other economies like the Czech Republic or Lithuania<sup>7</sup> .

- g) Governance (e.g. procedures to enforce a contract). Red tape is also relatively high in countries like Poland or Romania, for this reason the protection of contract enforcement can be problematic<sup>8</sup> .

The information on the economic characteristics of the countries analyzed was taken from different World Bank publications. A synthesis is shown in Table 1.

> 7 ―All developing regions do worse than the industrialized countries‖, Hausmann and Gavin (1996).

> 8 ―Anti-trust policy is also often weak, as are environmental standards‖ Brunetti (1997).

5
10 The data set is summarized in Table I and figure 5. We took fifteen Par and Discount Brady bonds for nine major Brady agreements. The choice of bonds has been driven by criteria of liquidity (see the last column of the Table I) and homogeneity.<sup>12</sup> <!-- Start of picture text --> 2100 2000 2100 2100<br>12D0 800o 1200 6( 1200 1200ID<br>8D SW 1200 Boo^;4tM_ 10<br>400 400 SW40D<br>0 ~~~~~~~~~~~~~0 ~~~~~~~~400~ 0<br>4 90 1/05? 2106/92 61494 ~ 2)04494 ~ ~ ~ ~ ~ ~ 4 MM2 IU 4 3/ 2 MRWITM<br>}_ARt;De j_MGPffl P-ff<br>2800 2800 2400 20tK<br>2400 2400 2000 1500<br>2000 2000<br>160D 1600 t100150<br>1200 1200 1200 500<br>8001 4//9 _____________________ 2/69 014 1/0696 800 4/5690 ______________ 2/06/2 2/04/94 1 /0S/9 _ 87 4,06/6 __ 31092 2/49 _ 1056 40/0 0 _ 20/9 2044 1036<br>2000 __ _ _ _ _ _ _ _ _ _ _ _ _ _ 4000 _ _ _ _ _ _ _ _ _ _ _ _ _ 2500 __ _ _ _ _ _ _ _ _ _ _ _ _ _ 1200 _ _ _ _ _ _ _ _ _ _ _ _ _<br>3500<br>1I00oo( 2000 10D0<br>2500 1500 600<br>1000<br>_m 1500<br>1000 ~~~~~500 400<br>0 500 52<br>4 92 4 /0 94 /0~ ~ 4 ~ ~ ~~~~ ~~~~ 2 W94 i/0 2 ~ ~~<br>1200 _______________ 2500 2500<br>1000 2000 2000<br>B00 1500<br>1500<br>000 1000<br>400 1000 5oo<br>200 _ _ _ _ _ _ _ _ _ _ _ _ 5001 0<br>4/06/90/06/92 /04/94 /55/56 4/5,9 2/5/0 2/94/9 i/OS/ 4/06/0 30/2 2/4/0 1/05/6<br>Figure S<br><!-- End of picture text --> We concentrate on the _sovereign (stripped) spreads_ for several reasons. First, we want to exclude the effects of changes in the (same maturity) US interest rates on yields comovements. Note that, if the solvency of a country is in doubt, an increase in the US interest rate can have an effect on the sovereign premium as well. But we would expect 12 The data are provided by Salomon Brothers and are based on weekly (usually Wednesday) close of the day bid prices quoted in NY. We have data beginning on the week Salomon Brothers has started trading on the loans included in the Brady agreements, even though the bonds have been in all cases formally issued few months later. At this point we suggest to the reader not familiar with the Brady bond market to have a look at the Appendix.
2-3Aid model. Except for the new features, calibration and implementation follow Devarajan and Go (1998).

# Simulations<sup>11</sup>

## **Economy with Forward-Looking Investment and Consumption**

**_Simulation 1:_** _Foreign official grants increase by 2 percent of output permanently_

A significant increase in foreign grants will not necessarily lead to a real exchange rate appreciation or a Dutch disease problem. In any economy with an active private sector undertaking significant investment but facing an existing debt stock and an upwardsloping supply of debt, the effect is to increase investment, consumption, and output over time as expected (see figures 1 and 2). However, the dynamically optimal decisions in investment and consumption will result in the real exchange rate depreciating immediately (rather than appreciating), as well as the external debt stock declining over time (see figures 3 and 4). The effects are interrelated.

**Figure 1 Investment Ratio to Base: Permanent versus Temporary Increase in Foreign Aid**

<!-- Start of picture text -->
1.45<br>1.4<br>1.35<br>1.3<br>1.25<br>1.2<br>1.15<br>1.1<br>1.05 AID-P AID-P & trade AID-T10 AID-T10 & trade<br>1<br>1 4 7 10 13 16 19 22 25 28 31 34 37 40<br>time periods (years)<br>investment ratio<br><!-- End of picture text -->

_Source: Authors’ calculations._

> 11 All simulations are presented as deviations to the levels in the reference run (equals 1.0), which is defined as a balanced growth or steady-state run.

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as may the ECR. Whenever such circumstances prevail the three calculations come to the same number. In other words, under such circumstances, the growth in currency (cash flow or financing effect), would approximately equal the inflation rate times the currency (inflation tax), or the measure used in this paper (currency tax). Empirical applications in less stable environments force us to be more specific and precise in our measurements. Indeed, the difference between the cash flow measure of seignorage and our evaluation of the currency tax was as high as several percent of GDP in some years for some of the countries in our study.

While most empirical studies have employed the cash flow approach to measuring seignorage, and are thus implicitly focussing on the financing aspect, in the present context the fiscal approach is clearly the relevant one.

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# **Multinational Corporation Affiliates, Backward Linkages, and Productivity Spillovers in Developing and Emerging Economies: Evidence and Policy Making**

Jacob A. Jordaan, Willem Douw, Christine Zhenwei Qiang

## **JEL: F23, D24, F61, O38**

**Key Words:** FDI, MNC affiliates, backward linkages, local suppliers, productivity spillovers, policy making
38 326–342.

- Rossi, Federico, “Human Capital and Macroeconomic Development: A Review of the Evidence,” _The World Bank Research Observer_ , 04 2020, _35_ (2), 227–262.

- Schoellman, Todd, “Education Quality and Development Accounting,” _Review of Economic Studies_ , 2012, _79_ (1), 388–417.

- and Bart Hobijn, “Structural Transformation by Cohort,” Technical Report 2017.

- Shi, Shouyong, “A Divisible Search Model of Fiat Money,” _Econometrica_ , 1997, _65_ (1), 75–102.

- The Atlantic, _Minorities Are More Likely to Believe Education Will Help Their Careers._ , The Atlantic, November 13, 2013.

- Trostel, Philip, Ian Walker, and Paul Woolley, “Estimates of the economic return to schooling for 28 countries,” _Labour Economics_ , 2002, _9_ (1), 1–16.

- Unesco, _International Standard Classification of Education: ISCED 2011_ 2012.

- UNESCO, _UNESCO COVID-19 education response: how many students are at risk of not returning to school?_ , Paris: Unesco, 2020.

- , _What Have We Learnt? Overview of findings from a survey of ministries of education on national responses to COVID-19_ , Paris: Unesco, 2020.

- , _Global Monitoring of Schools Database_ 2021.

- United Nations, _World Population Prospects: The 2019 Revision_ 2019.

- , _COVID-19 and its economic toll on women: The story behind the numbers_ 2020.

- Uzawa, Hirofumi, “Optimum Technical Change in An Aggregative Model of Economic Growth,” _International Economic Review_ , 1965, _6_ (1), 18–31.

- World Bank, _International Income Distribution Database Harmonization Manual_ , Washington DC: The World Bank, 2013.

- , _World Development Report 2019: The Changing Nature of Work_ , World Bank Publications, 2018.

- , _COVID is hurting women economically, but governments have the tools to offset the pain_ 2020.

- , _World Development Indicators_ 2020.
MACTool also reports the investment needed in different emission reduction scenarios. While the abatement costs are computed using the social discount rate entered by the user, MACTool can also compute the carbon price signal that would be required to trigger investments from the private sector, taking into account the opportunity cost of capital for private actors (that is higher than the social discount rate, especially in developing countries).

# **2. Proof of concept: Re-analyzing the case of Brazil by 2030**

In a theoretical framework, we found that focusing on short-term targets and disregarding constraints on implementation speed would lead to suboptimal strategies, and could lead to carbon-intensive lock-ins that make the longer-term target impossible or too expensive to reach (Vogt-Schilb and Hallegatte, 2014). We developed a simple optimization model to factor implementation speed in the analysis and avoid this problem.

Here, we perform a proof of concept for these ideas, reanalyzing the data used at the World Bank to create a MAC curve for Brazil with MACTool (de Gouvello, 2010). We confirm using this data the findings of the theoretical paper, and we test the optimization model using proxies and indirect methods to reconstruct data on implementation speed constraints.

# _2.1. Objective_

We take the point of view of a social planner who chooses in 2010 an emissionreduction schedule to comply with a future emission target for 2030. We use two simulations. In the first one, an emission-reduction target is set for year 2030 and an optimal emission strategy is created taking into account implementation speed constraints. Then, the abatement obtained in 2020 in this optimal strategy is used as a target for 2020, and the MAC curve is used to design a mitigation strategy between 2010 and 2020, disregarding the constraint in terms of implementation speed. We then investigate differences of the optimal emission reductions up to 2020 in the two simulations, to confirm on this case the findings of the theoretical paper: using a MAC curve without taking into account implementation speed and long-term objectives would lead to insufficient short-term investments in options with high potential and slow implementation speed.

# _2.2. Methods and data_

We use a spreadsheet program based on the model proposed by Vogt-Schilb and Hallegatte (2014). The program provides the least-cost emission-reduction schedule that complies with the abatement target. As inputs, it requires a list of measures, characterized by a marginal abatement cost, a maximum diffusion speed, and a maximum abatement potential (see Appendix A).

Note that the abatement potential may evolve through time. For instance, if available technology limits intermittent wind power to 20% of the electricity production and electricity production is expected to grow over time, then the abating potential of wind power grows over time. On the other hand, if natural resources provide only few opportunities to build dams, the abating potential of hydro power is fixed, regardless of total electricity demand growth.

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2005, 2006 and 2007 for both old and new EU members. Specifically, we have survey data available for the following West and South European countries: Austria, Belgium, Cyprus, Denmark, Finland, France, Great Britain, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain and Sweden. We have survey data for eight countries that joined the EU in 2005: Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic, and Slovenia.<sup>8</sup> The EU-SILC is a census-based stratified survey with at least 3,500 households per country. It collects timely and comparable data on income, expenditures and social exclusion in countries of the European Union. Critically, the survey contains information about (i) whether households own with or without mortgage or rent their current residence, (ii) whether they are in arrears on different credit obligations, and (iii) whether they see their housing costs as financial burden. In addition, the SILC database provides information on several types of variables: those measured at the household level, including household size, composition, and others; basic individual and demographic characteristics of household members (including education, health status, access to health care, detailed labor market activity and age). In our analysis, we focus on households rather than individuals. Where we use individual-level information, we use the information provided by either the household head (if (s)he is the one responding to the survey) or the information provided by the household member with the highest income.

The EU-SILC database offers certain advantages for our purposes as well as limitations. The main strength of the database is that it is consistent across 23 countries, thus allowing us valid comparisons between the new EU members in Central and Eastern Europe and the Baltic region and the old EU member countries in Western European. Further, most survey questions are asked in all countries, which again enables us to undertake cross-country comparisons. Finally, there are detailed

> 8 While Cyprus is also a new EU country, we group it together with the old EU countries given its level of economic and financial development. At the time of the first wave of SILC (2005), Bulgaria and Romania were not yet members of the EU. Data for Germany were excluded in the database received from Eurostat.

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# **5. Conclusion**

This paper is an initial attempt to assess the effect of accessibility to transport on rural development in Sub-Saharan Africa. To the best of our knowledge, our paper is the first to investigate the relation between access to markets from road improvements and the spatial expansion of cultivated land using geo-referenced panel data. Our analysis was carried out for a 35-year span when roads were constructed and cropland area expanded in the region quantifies the link between the two. In accordance with the theory, we find suggestive evidence that improved market access leads to more land put into cultivation. The effect, however, is quite modest as a doubling of our measure of market access leads to an increase in cropland by approximately 2 to 6 percent. This, however, seems driven by increases in local population much more than by improved accessibility from better roads, which is suggestive of agriculture mainly responding to local demand. Complementary to this result, we also find that cropland expansion only marginally increases local GDP, which is consistent with the idea that a significant part of cropland expansion in Sub-Saharan Africa is not accompanied by the development of commercial agriculture and that trade of agricultural goods is to a certain extent limited to the immediate vicinity of production. In the wake of our study on the extensive margin of agriculture (cropland expansion), further research will be needed to assess whether market access has an impact on the intensive margin (yields), which, however, are known to have been stagnating in the region. More generally, research will also be needed to identify the enabling environment that could allow transport investment to better support rural development in the region.

> 1 Based on calculations from Fischer and Shah (2010), Deininger et al. (2011) report figures for suitable land in nonforest areas under different population density criteria: 68 million hectares (respectively 201 million hectares) for areas of less than 5 people (respectively 25 people) per km<sup>2</sup> (see Table A2.6 page 165).

> 2 Ideally, the measure should account for the income of potential consumers, but this information is usually not available, hence the use of population numbers. Examples of papers using a similar market access measure include

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