rafmacalaba/datause-encoder-data huggingface dataset:
pattern of trade barriers in the multi-regional SAM. Table 7 presents _ad valorem_ import protection rates for each region by sector and supplier, along with other sectoral taxes on exports and production. Note that these rates _include_ the tariff equivalent of non-tariff barriers for agriculture and textiles, and antidumping duties for the US and EU.'° Because the GTAP data protection rates include non-agricultural NTBs for the US and EU, but only statutory tariff rates for Japan, the resulting protection rates suggest that the US and EU protect themselves much more heavily against Japanese products than Japan does against US and EU products. For example, US protection against Japan ranges from 5-24 percent in the industrial sectors, while the Japanese protection against US products (based only on official tariff schedules) ranges only from 2-7 percent. To compensate for this uneven coverage, we have incorporated additional information on the _ad valorem_ equivalent of Japanese NTBs, drawn from estimates provided in Sazanami, Urata, and Kawai (1995). These estimates, based on unit value index comparisons, suggest sizeable non-tariff protection across a wide range of industrial products. For our purposes, we have chosen to increase reported tariff and NTB rates by one-half of the NTB equivalent calculated by these authors, resulting in the higher bilateral protection rates for Japan reported in Table 7.

The import protection rates show substantial variations among commodity groups by sector and region. The high protection rates for agriculture and food products in the EU, Japan and Asian NIEs reflect the very high non-tariff barriers maintained in these regions. The average tariff rates in other sectors (except textiles) are generally low among developed countries and Asian NIEs, especially for mineral and energy products. But higher import barriers exist in ASEAN4 for almost all sectors.

> 10 As documented by Chyc et al (1995), the protection data in the GTAP database (version 1994) include not only tariffs, but also the tariff equivalent of non-tariff barriers in the case of agriculture and textiles/wearing apparel, and the anti-dumping duties of Canada, European Union and the United States. The tariff data draw on original country submnissions to the GATT for the Uruguay Round. The source for agriculture protection data is from OECD and USDA/ERS estimates of Producer and Consumer Subsidy Equivalent (PSEs and CSEs).

_Lewis, Robinson, and Wang_ 20
climate change in part because doing so raised fears of ontological security, emotions of helplessness and guilt, and was a threat to individual and collective senses of identity. In contrast to existing studies that focus on the public's lack of information or concern about global warming as the basis for the lack of public response, my work describes the way in which holding information at a distance was an active strategy performed by individuals as part of emotion management. Following Evitar Zerubavel, I describe this process of collective avoiding as the social organization of denial. Emotions played a key role in denial, providing much of the reason why people preferred to avoid information. Emotion management was also a central aspect of the process of denial, which in this community was carried out through the use of a cultural stock of social narratives that were invoked to achieve "perspectival selectivity" and "selective interpretation.".

Norgaard, Kari. 2006b. “We Don’t Really Want to Know’ The Social Experience of Global Warming: Dimensions of Denial and Environmental Justice” Organization and Environment 19(3): 347-470.

Meager public response in the form of social movement activity, behavioral changes, or public pressure on governments is noteworthy in all Western nations. Existing research emphasizes lack of information as a limiting factor for failed public response. This explanation cannot account for the significant population that knows about and express concernes for global warming. Ethnographic and interview data from a rural Norwegian community indicate that non-response is at least partially a matter of socially organized denial. Because Norwegian economic prosperity is tied to oil production, collectively ignoring climate change maintains Norwegian economic interests. Most environmental justice research focuses on people facing disproportionate exposure to environmental problems. This project examines wealthy citizens who perpetuate global warming as they turn a blind eye. Environmental justice implications of socially organized denial are discussed for global warming and beyond.

Opotow, Susan and Leah Weiss 2000. “New Ways of Thinking About Environmentalism: Denial and the Process of Moral Exclusion in Environmental Conflict” Journal of Social Issues 56, 3, 475-490.

The authors examine “moral orientations” that influence environmental conflict. Opotow and Weiss create a typology of three kinds of denial in environmental conflict: denial of outcome severity, denial of stakeholder inclusion, and denial of self-involvement. Opotow and Weiss describe how these forms of denial work together to produce “moral exclusion.” The article concludes with implications of this analysis for theory and practice.

Ungar, Sheldon 2003. “Misplaced Metaphor: A Critical Analysis of the ‘Knowledge Society’” <u>Canadian Review of Sociology and Anthropology 40(3): 331-347.</u> 58
Policy Research Working Paper 7934

# **Abstract**

This paper uses a regression discontinuity design to study the effect of Poland’s In-Tech program on innovation activities. The analysis focuses on a component of the program that provides grants to projects that are carried out by consortia of firms and research entities. Data from a 2016 follow-up survey of applicants to the 2012 and 2013 calls for proposals show that In-Tech largely funds projects that would not otherwise get funded by other agencies or by the consortia themselves, increasing the probability of a project being completed by almost 60 percentage points. The results also show that the program leads to more science-industry collaboration, and increases the probability of applying for a patent related to the proposed project, as well as the probability of publishing a research paper related to the project. The analysis also finds early effects on commercialization of products related to the proposed project, although these products currently still make up a small share of firm’s sales.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at mbruhn@worldbank.org and dmckenzie@worldbank.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
- Putnam, R. D. (2000). _Bowling alone: The collapse and revival of American community_ . Simon & Schuster Paperbacks, NY: New York.

- Rijkers, B., Baghdadi, L., and Raballand, G. (2015). Political connections and tariff evasion evidence from Tunisia. _The World Bank Economic Review_ .

- Ward, M. D., Stovel, K., and Sacks, A. (2011). Network analysis and political science. _Annual Review of Political Science_ , 14:245–264.

- Watts, D. J. (2003). _Six degrees: The science of a connected age_ . W.W. Norton & Company, NY: New York.

- Watts, D. J. and Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. _Nature_ , 393:440–442.

- World Economic Forum (2014). Global competitiveness report. Technical report, Geneva.

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# **D. D Impacts of a Larger Regularization Program**

Table D.4. Electoral Impacts of ETPV Program – Presidential Elections

||Election<br>Turnout|Shar<br>Left|e of Votes<br>Center|for<br>Right|Electoral<br>Competition|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|
|_Panel A. Presidential Elect_|_ions - Conti_|_nuous Var_|_iable_|||
|RUMVd_×_I(Post2018)t|-0.014<br>(0.006)|-0.047<br>(0.027)|0.019<br>(0.015)|0.027<br>(0.020)|-0.080<br>(0.040)|
|q-values|[0.157]|[0.157]|[0.157]|[0.157]|[0.157]|
|R-squared|0.988|0.959|0.969|0.953|0.879|
|Observations|198|198|198|198|198|
|Department FE|Yes|Yes|Yes|Yes|Yes|
|Year FE|Yes|Yes|Yes|Yes|Yes|

_Notes:_ This table presents the results of the effect of the ETPV program on electoral outcomes. The variable RUMVd is the total number of migrants who were issued the Registro Unico<sup> ́</sup> de Migrantes Venezolanos (RUMV) over the population in 2020 by department. Electoral competition was estimated following Chac ́on et al. (2006):1 - (% winning candidate - % second-place candidate). The estimates include department and electoral-year fixed effects, and they control for the interaction between electoral year dummies and a set of predetermined department characteristics, measured before the beginning of our period and listed in Table C.2. Clustered standard errors at the municipal level are reported in parentheses and False Discovery Rate (FDR) q-value in brackets *** significant at the 1%, ** significant at the 5%, and * significant at the 10%.

76
Among our explanatory variables, the one that we are most interested in is a set of policy variables as defined and numerically estimated by EBRD. We shall use these variables both as an indicator of the average intensity of reforms (taking an unweighted average of all nine EBRD reform indexes), and as each reform separately.<sup>5</sup> Other right-hand side variables are pretty straightforward. They include annual real growth rate, government expenditures as percentage of GDP, and annual inflation rate as measured by the change in the consumer price index (all three obtained from World Development Indicators). It may be worth briefly mentioning their evolution in time since all three are reflective of the transition process.

The growth rates are available annually for 24 countries.<sup>6</sup> The average unweighted rate at the onset of transition, in 1991 and 1992, was − 13 and − 19 percent.<sup>7</sup> Beginning with 1995, the average unweighted growth rate turned positive, almost monotonically increasing from about 1 percent in 1995 to more than 6 percent at the end of the period. This is a remarkable turnaround although the depth of the early depression means that 11 countries’ GDPs per capita are still below their 1990 levels.<sup>8</sup> The population-weighted area’s average GDP per capita is now only 2 percent above its 1990 level, and total real GDP of the area is exactly the same as sixteen years ago. However, illustrating the recent turnaround, we note, for example, that since 2000, there have been only five observations of negative (and mildly so) growth rates while there were 18 observations of growth rates in excess of 10 percent per annum. At the beginning of the period, the situation was exactly the reverse: in the years 1991 and 1992, there were no fewer than 30 observations of _double-digit_ negative growth.

5 The reform areas are the followings: large scale privatization, small scale privatization, governance and enterprise restructuring, price liberalization, trade and foreign exchange system, competition policy, banking reform and interest rate liberalization, securities markets and non-bank financial institutions, and infrastructure reform. The EBRD indices come from the EBRD Transition Report, reflecting progress in all of these areas. Each of these individual EBRD indices is reported on a 1 to 4+ scale with higher numbers indicating greater reform progress.

6 We do not have data for Bosnia and Herzegovina, and Montenegro.

7 The average unweighted means that each country/year counts as one observation.

> 8 GDP per capita (and total GDP) are measured at 2005 international prices.

8
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gas oil were about equal to the world prices, while the price of kerosene continued to be subsidized, being only two thirds the world market price.

Fuel taxes are regarded as the closest substitute for road user charges. The tax per km depends on the rate of the fuel tax (c per gallon) and on fuel consumption (km per gallon). The tax varies among different types of vehicles to the extent that they use different kinds of fuel and that they differ in their fuel consumption. In the absence of agreement on fuel consumption, two estimates were used: the high one, used by SWKP in their road project evaluations (1987, Vol. 2, pp. 61-62) and the low one adopted by GHA (1990). The results are presented in Table _15._ Table **15.** The Fuel Tax and Road Fund Levy, 1988 (C/km)*

||Car|Light<br>bus|Heavy<br>bus|Light<br>truck|Medium<br>truck|Heavy<br>truck|
|---|---|---|---|---|---|---|
|_Total taxes_|||||||
|Cedi/gallon|34.81|30.73|30.73|30.73|30.73|30.73|
|<br>M/gallon|15.5|13.7|13.7|13.7|13.7|13.7|
|_Road fund levy_|||||||
|Cedi/gallon|7.50|12.00|12.00|12.00|12.00|12.00|
|C/gallon|3.3|5.3|5.3|5.3|5.3|5.3|
|Fuel consumption|(km/gallon)||||||
|a.|42.04|34.14|20.25|28.74|18.39|10.00|
|b.|35.50|23.27|14.78|16.87|7.53|7.22|
|_Taxes per km (C)_|||||||
|Total<br>a.|0.37|0.40|0.68|0.48|0.74|1.37|
|b.|0.44|0.59|0.93|0.81|'.82|1.90|
|Road fund<br>a.|0.08|0.15|0.26|0.18|0.29|0.53|
|b.|0.09|0.22|0.36|0.31|0.70|0.73|

- It is assumed that cars use only premium gasoline and that all other vehicles use only diesel oil. Rate of exchange: 225 cedi per $.

- a. Based on SWKP estimates (SWKP, 1987, Vol. 2, pp. 61-62).

- b. Based on GHA estimates (1990).
For the analysis in this paper, expected deaths are estimated using a simple regression using 2015-2019 historical data, run separately by country and age-group, where observed deaths are modeled as a linear function of year and an error term.

The second issue often neglected in COVID-19 excess mortality discussions is that excess mortality represents a combination of effects. Specifically,

# _Net excess deaths_ =

# _[Direct COVID-19 deaths]_ + _[Indirect COVID-19 deaths]_ - _[Averted deaths]_

_Direct COVID-19 deaths_ are those that are due to infection with the virus. _Indirect COVID-19 deaths_ are those not due to the virus itself but in part due to factors such as congestion in the health system, delays in care-seeking, or mental health issues caused by the pandemic. _Averted deaths_ are those that would have taken place in the absence of the pandemic but did not occur as a result of pandemic-induced measures. These could include deaths due to other infectious diseases, violence, or traffic injuries that were avoided due to voluntary or mandated social distancing. The possibility of non-zero indirect deaths and averted deaths makes the interpretation of excess deaths more complex than is often recognized.

# _Slope calculation_

The shape of an age-mortality curve can be summarized in terms of the percent rate of increase in probability of death per year of additional age after age 45, calculated by fitting a line to the age-specific mortality rates as follows:

# log(r(x, i)) = αi + βix

D(x,i) where the age-specific mortality rate is r(x, i) = for the ten-year age group age _x_ to age _x_ N(x,i) + 9, ( _x_ = 45, 55, 65, 75, 85) in country _i_ , D(x, i) is the number of deaths in the age group and N(x, i) is the population of the age group in country _i_ .<sup>2</sup> The _x_ = 85 points correspond to the group consisting of all ages 85 and above.

To take into account the varying age structure across countries within this open interval, an adjustment factor based on indirect standardization was calculated. Following Goldstein and Lee

> 2 The slope is fitted starting at age 45 because there are few deaths in most countries below age 45.

4
granted to all beneficiaries younger than 21 years old who are enrolled in school. The educational stipend varies by grade and gender. It rises substantially after graduation from primary school and is higher for girls than boys during junior high and high school. Beneficiary children also receive money for school supplies once or twice a year. There is an upper limit in the total transfer received per household. Table 1 details transfer amounts in October 1997 prices.

When OPORTUNIDADES was first rolled out in rural areas starting in 1997, program eligibility was determined in two stages (Skoufias et al. 2001). First, the program identified underserved or marginalized communities and then identified low-income households within those communities. Selection criteria for marginalized communities were based on the proportion of households living in very poor conditions, identified by using data from the 1995 census ( _Conteo de Población y Vivienda_ ). For the selection of eligible households within marginalized communities, OPORTUNIDADES conducted a socio-economic survey, the _Encuesta de Características Socioeconómicas de los Hogares_ (ENCASEH). This census of households was used to classify households as eligible for treatment (“poor”) or ineligible (“non-poor”) using a proxy means test (PMT). Using the 1997 ENCASEH, the original classification scheme designated approximately 52% of households as eligible (“poor”)<sup>9</sup> .

All eligible households living in treatment localities were offered OPORTUNIDADES and a majority (90%) enrolled in the program. Once enrolled, households received benefits for a threeyear period conditional on meeting the program requirements. New households were not able to enroll until the next certification period which prevented migration into treatment communities for OPORTUNIDADES benefits. Households in rural areas were “recertified” (re-assessed with a proxy means test) after three years on the program to determine future eligibility. If a household was recertified as eligible, it would continue receiving benefits. If not recertified, the household was guaranteed three more years of support followed by three years of transitional support. Thus,

> 9 Later the Government decided that a subset of the “non-poor” households had been unduly excluded. They expanded the eligibility criteria to include a set of slightly wealthier households in a process called “densification” (Hoddinott and Skoufias 2004).

4
with the top 25 percent flood depth in each country as high flood risk areas. As this is an indicator of long-term flood risk, we have an index only for one time point. The flood risk maps for three case countries are shown in Figure 2.

Taking advantage of the panel data spanning over a long duration, we additionally analyzed rainfall anomalies as a climatic factor for Indonesia. The SPEI is a multiscalar drought index (Vicente-Serrano et al. 2010). The construction requires data on temperature, precipitation, and potential evaporation. Accordingly, we processed <mark>monthly precipitation and potential evapotranspiration derived from the terraclimate data from 1958 to 2020. T</mark> he <mark>SPEI</mark> data are fitted to a gamma distribution and normalized to a flexible multiple time scale such as 1, 4, 6, 12, 24, and 48 months. For the study, we considered a 12-month time scale for each year from 1993 to 2015 with two lag periods for each IFLS wave.<sup>7</sup> <mark>Negative SPEI values represent rainfall deficit—less than median precipitation—and high potential evapotranspiration (dry) starts when the SPEI value is equal to or below −1.0. On the other hand, positive SPEI values indicate rainfall surplus—greater than median precipitation—and low potential evapotranspiration (wet) starts when the SPEI value is equal to or above 1.0. F</mark> igure 3 <mark>illustrates the SPEI values in Indonesian districts as of March 2014.</mark>

> 7 The computation involves the following three steps (Harari and La Ferrara 2018). We first compute the difference (D) between precipitation and evapotranspiration (PET) and accounted for the climatic water balance defined at the monthly level. The Penman-Monteith equation is used to approximate the PET (as recommended by the Food and Agriculture Organization of the United Nations (FAO) as the best method for determining reference evapotranspiration). <mark>Maximum temperature, minimum temperature, vapor pressure, precipitation accumulation, downward surface shortwave radiation, and wind speed</mark> are used as input data. The next step is the aggregation of the climatic water balance at different time scales and finally, we standardize the time series according to a gamma distribution. The SPEI is then computed as the standardized values of the gamma function.

7
more poor people may also, simultaneously, be more susceptible to the allure of clientelist promises of individual transfers. All regressions therefore control for the log of per capita income from the _World Development Indicators_ , averaged over the duration of the loan.<sup>11</sup> The size of a loan can also affect its ratings. The larger a loan, the greater are the resources that are potentially applied to public sector reform, which may improve ratings. Larger loans may exhibit greater sectoral diversity, making the ratings noisier measures of public sector reform success. Larger loans may also attract stricter and more accurate scrutiny by the IEG, however, making them less noisy. All regressions therefore control for the loan amount and the percentage of the loan amount that is allocated to the public sector. Estimations also include a control for the duration of the loan. Longer duration loans could imply a more conscientious effort by countries to pursue loan objectives (consistent with the frequently-voiced argument that institutional reform takes longer). However, within the World Bank, slow loan disbursements can also be a red flag, indicating difficulties with implementation. In either case, duration is a rigorous control variable, since it may capture variation in IEG ratings that is actually due to political decisions linked to the presence or absence of programmatic political parties.

Larger countries may be more difficult to administer; on the other hand, there may be economies of scale in administering more populous countries (holding area constant). There is, in fact, some evidence that public sector reform is more likely to succeed in countries with more people. Therefore, all regressions control for population and land area,

> 11 The main results hold when we use project start year values instead of averages over the term of the loan.

25