rafmacalaba/datause-encoder-data huggingface dataset:
# **Online Appendix**

## **Table A1 - List of Senate Committees**

The table displays the list of relevant committees studied in this paper. Column 2 presents a brief description of their main objectives, while the states and Legislature term for the chairman are indicated in columns 3 and 4. For each committee, the last column lists the sectors that are directly supervised according to 2007 North American Industry Classification System (NAICS) classification.

|Committee|Objective|Legislature|State of Chairman|NAICS|
|---|---|---|---|---|
||Supervises the senate|LIX|Tlaxcala||
|Administration|<br>budget|LX|Tlaxcala|All|
||.|LXI<br>|Chiapas<br>||
||Dlt f|LIX|Hidalgo|111112|
|Agriculture|eveopmen o<br>ill|LX|Colima|.,<br>11511152|
||agrcutura sector|LXI|Colima|,,|
||il d|LIX|Coahuila|21,222,123|
|Commerce|Promote natona an<br>international trade|LX|Nuevo Leon|31-33|
|||LXI|Nuevo Leon|43,46,52|
|||LIX|Puebla||
|Constitution|Reforms and additions to<br>the constitution|LX<br>LXI|Quintana Roo<br>Puebla|All|
||Si d dl th|LIX|Campeche|21,22,2371|
|Energy|upervse an eveop e<br>ener sector|LX|Sinaloa|324,325|
||gy|LXI|Sinaloa|486,148,624,869|
||il|LIX|Jalisco||
|Governance|Legsates on matters<br>ld ih|LX|Hidalgo|All|
||reate wt transparency|LXI|Hidalgo||
||Coordinate initiatives of|LIX|Michoacán<br>||
|Legislation|<br>other committees|LX|Coahuila|All|
|||LXI|San Luis Potosi||
||Cdit iititi f|LIX|Colima||
|Legislation I|oornae naves o<br>th itt|LX|Baja California|All|
||oer commees|LXI|Colima||
|||LIX|DF||
|Legislation II|Coordinate initiatives of<br>th itt|LX|Zacatecas|All|
||oer commees|LXI|Michoacán||
|||LIX|Coahuila||
|Justice|Supervise the judicial<br>branch|LX|Baja California|All|
|||LXI|Baja California||
|||LIX|-||
|Telecommunications|Supervise and disseminate<br>information|LX|Colima|512,515|
|||LXI<br>|Zacatecas||
|||LIX|-||
|Tt|Develop transportation|<br>LX|<br>G|2373.2379|
|ranspor|d lii||uerrero|484951|
||an teecommuncatons|LXI|Baja California|,,|
|||LIX|DF||
|Treasury|Supervise public spending|LX|Zacatecas|All|
|||LXI|Zacatecas||

49
induces competition. As a result, profit margins compress, and firms have more incentives to reduce costs through improved productivity.

**Table 4 – DID for Log of Labor Productivity**

|VARIABLES|(1)<br>Base|(2)<br>Firm-level|
|---|---|---|
|MobileAccess*Post|0.0501|0.233*|
||(0.152)|(0.137)|
|Observations|2,334|2,289|
|R-squared|0.063|0.265|
|Year FE|NO|YES|

Note: Column (1) is the baseline specification. Column (2) adds firm-level controls, including firm size, firm age, and capital intensity. Robust standard errors are clustered on Woreda. Robust standard errors in parentheses (*** p<0.01, ** p<0.05, * p<0.1) With more competition and lower profit margins, the incentives to lower production costs are magnified. This induces firms to attempt lowering production costs to increase profitability. If productivity-enhancing investments are expanded, this can induce both higher labor productivity as well as TFP. In Table 5, we find 17%-18% increase in TFP although moderately significant.

**Table 5 – DID for Log of TFP (ACF)**

|VARIABLES|(1)<br>Base|(2)<br>Firm-level|
|---|---|---|
|MobileAccess*Post|0.185**|0.178**|
||(0.0864)|(0.0836)|
|Observations|2,597|2,545|
|R-squared|0.085|0.168|
|Year FE|NO|YES|

Note: Column (1) is the baseline specification. Column (2) adds firm-level controls, including firm size, firm age, and capital intensity. Robust standard errors are clustered on Woreda. Robust standard errors in parentheses (*** p<0.01, ** p<0.05, * p<0.1) 22
3

# **1. INTRODUCTION**

The Services Trade Restrictions Database collects and makes publicly available information on services trade policy assembled in a comparable manner across 103 countries, five sectors (telecommunications, finance, transportation, retail and professional services) and the key modes of service supply. This paper is a guide to the database and provides a description of the data that has been collected, how it was collected, how policy information was quantified, and how the data are presented in the publicly available, interactive Web database. An analytical account of the emerging patterns of policy across countries and sectors can be found in Borchert, Gootiiz and Mattoo (2012). This companion paper also presents evidence on the impact of policy barriers on investment flows and access to services.

The database is best seen as a first response to the strong demand for better information from policy-makers, negotiators, researchers and the private sector. Even in its present version, we see the database as playing an important role in advancing policy reform by facilitating the analysis of services policies; in informing international negotiations by providing data on actual policies; and in provoking dialogue and refinements by making information on policies publicly available. Thus, we do not regard the initial version of the database as providing a definitive picture of trade policy but as a first approximation which will, through feedback from various interested parties, evolve into a collectively created public good – along the lines of a “wiki-database.” The entire database – including all qualitative and quantitative information, annotated descriptions of policies, as well as detailed documentation – is publicly available at http://iresearch.worldbank.org/servicestrade.<sup>1</sup> To the best of our knowledge, no other data source provides similar information on barriers to services trade in a comparable manner for such a large cross-section of countries.

1 Any inquiries or feedback regarding the database can be sent to servicestrade@worldbank.org.
in 2001, the intensive margin explained most of the export growth, whereas the extensive margin became the main source of export growth once the currency appreciated.

# **3.2 The Role of Trade Agreements**

Trade agreements arguably played an important role in helping countries integrate into the global economy and are key to understanding globalization dynamics. Baier et al. (2019) show that trade agreements effects are heterogeneous, not only between agreements but mostly within agreements. In columns 1 and 2, table (2) provides the results of estimating globalization dynamics for the period 1965-2000. It shows a total effect in 2000 of [exp(1.51) _−_ 1] _×_ 100 = 352% when RTAs effects are not controlled and an effect of [exp(1.43) _−_ 1] _×_ 100 = 318% growth if the RTA variable is included.<sup>16</sup> While there is a 34% difference, this is small compared to the total magnitude of globalization during this period. Also, these results control for the average RTA effect, assuming that all RTAs have the same effect on bilateral trade. This is a strong assumption as shown by Baier et al. (2019). For this reason, to disentangle the role played by RTAs in globalization dynamics, one needs to consider the country-specific effects of trade agreements. I use the case of Spain as an example. Spain is a particular case captured in the data used in this paper, going from autarky to a deep trade integration process into the global and European economy since the 1970s. Spain requested to access the EU on 26 July 1977. These aspirations came to fruition on 12 June 1985. I use this event to disentangle the effect of Spanish RTAs on its globalization dynamics.

Columns 3 to 6 of table (2) show the results of estimating the globalization dynamics of the Spanish economy.<sup>17</sup> Figure (6) plots these results. It shows how while Spain did not sign any trade agreement, the globalization dynamics controlling and not controlling for RTAs effects are the same, as expected. These dynamics started differing as soon as the Spanish accessed the European Communities in 1986. The globalization dynamics that omit RTA effects (the RTA variable is included in the regression) have the same trend along the period. But the slope of the dynamics that include the effect of RTAs (the

> 16Note that the world average effect of globalization by 2000 is different to the one shown before. In this case, I only use the Long-WIOD data. Results in figure (2a) are a more robust world average estimating since they cover many more countries.

> 17Column 3 does not include the RTA variable, column 4 includes the average world effect of RTAs, column 5 considers the specific effect of RTAs for Spain, and column 6 allows this specific RTA effect for Spain to evolve over time.

17
4

# H. IMPACT ON SELECrED RENEWABLE ENERGY TECHNOLOGIES

8. In this chapter, renewable energy technologies that compete directly in the modern sector as relatively large-scale petroleum substitutes are discussed initially. Those that serve to meet small-scale, mainly rural energy needs are discussed later. It will become readily apparent that the economics of RETs in the first group are far more sensitive to lower oil prices than those in the second.

# iDendrothermal Power Plants

9. A dendrothermal power (DTP) system consists of a wood burning power plant and a dedicated plantation of short-rotation tree species. The most recent DTP installations are in the Philippines, where the Government has established dendrothermal power plants in the 3 to 5 MW range as part of its rural S lectrification plan. Similar installations are contemplated in Thailand, India, Indonesia, Brazil, and other countries. No evaluation reports are available so far on the performance of the Philippine plants. Since wood burning plants use more or less conventional technology, few technical difficulties are expected on the power plant side. Problems have, however, been reported on the plantation side, related mainly to factors which influence biomass yield, such as choice of species and condition of the land. Analysis indicates that overall plant economics is likely to be sensitive to biomass yield, which dictates the size of the dedicated plantation and therefore the magnitude of plantation development and maintenance costs.

10. In assessing the impact of reduced oil prices on DTP systems, there are two basic difficulties. First, plantation development, wood hauling and other costs are very site-specific. For a given plant size, DTP generation costs can vary widely with location. Therefore, any comparison with oil-based alternatives can only be made in a general way. As widely varying site-specific costs are common to most renewable technologies analysed in this paper, the impacts of lower oil prices assessed throughout this paper are limited to general statements. Second, it is not easy to identify the most appropriate alternative system to which the DTP plant should be compared. If deployed as a unit contributing to the base load of a power grid, the criterion for comparison would be related to the minimum LRMC and the alternative to the DTP plant may very well be a non-oil based installation, such as a coal-fired or a hydro plant.

11. Nevertheless, it is possible to obtain some insight from a Bank study of the likely costs at various sizes of a generic DTP plant.<sup>5</sup> ' Based largely on Philippine data and at 1983/84 prices, the study calculated generation costs of about 12.1, 8.4 and 6.6e/kWh; base capital costs of 2,100, 1,700 and 1,300 $/kW installed; and plantation areas of 2,000, 6,700 and 31,000 hectares for 3, 10 and 50 MW, respectively. The key assumptions include biomass yield at 10 bone-dry World Bank, 'echnical and Cost Characteristics of Dendrothermal Power Systeme, **Enetgy** DepL Paper No. 31, _5/_ December 1985.
a few regions of India, and the exposure of different areas of Brazil to soap operas in which all the female characters had few or no children) caused more-or-less simultaneous mental model switches by many interdependent actors and, thus, led to substantial behavioral changes that may help sustain the initial exogenous change in context.<sup>10</sup> The paper describes laboratory, field, and natural experiments that we believe provide convincing evidence of observed behavioral changes that are markedly different from what standard economics would predict. There are social impacts on behavior that _cannot_ be accounted for only by changes in choice sets and information, but that are best understood as changes in preferences and sociallydetermined cognition. Section 7 discusses the normative considerations raised by policies that try to affect individuals’ mental models, and section 8 concludes.

# **2   Interpersonal effects in standard models:  Interdependent utility**

This section summarizes the way that standard economics has been extended to incorporate social determinants of choices. The extensions do this by allowing others’ consumption to directly affect one’s own welfare. They retain the assumption of standard economics that the individual’s preferences and ways of processing information are _fixed,_ unaffected by social elements. Behavior is described as if the individual maximizes a utility function defined over his own and possibly others’ consumption (actions). For many decades, economists worked on enriching the standard models while retaining the core assumption of fixed preferences and a fixed way of processing information.

It is straightforward to extend the standard framework to include the consumption of others: (2.1) Max U<sup>i</sup> ( **xi** , **x-i). xi** The individual’s utility in (2.1) depends on the vector of his own consumption, **xi** , and that of others, **x-i** ; there are externalities. With utility functions of this form, preferences—how an individual ranks alternative consumption bundles—depend in general on others’ consumption, i.e. there is not separability, as in:

> 10 The examples are, respectively, from (a) Beaman et al. 2009, 2012 and Iyer et al. 2012; (b) Sanyal, Rao, and Majumdar 2015; and (c) La Ferrara, Chong, and Duryea 2012.

12
expenditures (monetary and nonmonetary) on different energy sources, other expenditures, and income. Energy expenditure is included as the total amount paid during the period, but quantities of energy are not reported (i.e. kilowatts, liters of gasoline, etc.). The data also includes the sociodemographic characteristics of the members of the household, the characteristics of the house, and the level of access to different services. These surveys are used for the official measures of poverty in Mexico, and they are representative of both urban and rural areas.<sup>2</sup> Our sample consists of 27,544 households, of which we exclude those not reporting energy consumption in the aggregate. We keep those with consumption of at least one of the energy sources. We also exclude those observations with no positive total income, and those with energy consumption above the total income of the household, which leaves 25,714 households in the sample for the analysis.

The ENIGH surveys record all energy consumption, but we exclude batteries, candles (all households with this expense have electricity too), diesel, and other energy sources such as paper, coal, and oil, since their expenditure share is too low for estimations. We do not consider wood either because quantities and prices are not available, only an amount if households paid for it, and the survey does not include collected wood. In addition, the share of expenditure is about 15% for the rural low income deciles, but is not relevant for other deciles or urban households.

We focus on LPG, natural gas, gasoline, and electricity. However, natural gas is only available in some urban municipalities where there is an authorized distributor. Therefore, we restrict our analysis to households in urban areas with a distributor. Confirmation on the locations of distributors was taken from the Commission for Energy Regulation (Comision Reguladora de Energia, CRE).

> 2 At the state level, in 2010 only five states have a sampling that it is representative at the state level.

8
The data used here are the best available to look at the age patterns of migration in a comparable way across a number of countries in the world. One caveat is that youth are more likely to migrate illegally than older migrants.<sup>4</sup> To the extent that censuses and surveys undercount illegal migrants, the share of youth amongst total migrants will be even higher than calculated here.

# **4. Age and Gender Patterns of Migration**

Figure 1 then uses this microdata to plot kernel densities of the age distribution of the migrant flow in different countries around the world. This is supplemented by Table 1, which gives the share of migrants who are aged 12 to 24, and 12 to 29 in each country, and by Table 2, which gives the share of young migrants who are female.

This figure and the tables confirm that youth make up a large share of migrants around the world, but also show that there is considerable diversity in the age flow and gender patterns. The share of females among youth migrants varies from 39% in South Africa and 42% in the U.S. to 65% in Argentina. The share of 12 to 24 year olds in the migrant flow varies from only 20% in Canada to 45% in Côte d’Ivoire. In most cases youth are a much larger share of the flow than of the stock, suggesting that a good number of migrants stay for extended periods of time in their host countries. For comparison with the microdata, cross-tabulations from Oman show that 10 to 24 year olds comprise only 9.5 percent of the stock of male migrants, and 19.7 percent of the stock of female migrants.

> 4 This is seen in both Mexico and Albania. See World Bank (2006).

- 8 -
This model presents two groups of predictions. The first group is “static” in the sense that it predicts that exporting firms are larger and have more productivity. The second group is “dynamic” in the sense that the model can be used to decompose the expected change in employment from an increase in the foreign price (i.e. following a trade agreement) into that due to changes in the extensive and internal margins. The model predicts that most of the employment gains from a trade agreement come along the extensive margin. Existing firms increase employment, but less than new firms entering the export market. In addition, we would expect employment to be higher among firms that have always exported, while lower for firms that are new exporters. We can compare these predictions with firm-level data described below.

# **_Data_**

We use the World Bank Enterprise Surveys (ES) to evaluate the link between exports and employment at the firm level. The ES are representative samples of an economy’s privatesector firms based on interviews with business owners and top managers about several topics, including trade and employment. In Morocco, ESs conducted in 2007, 2013, and 2019<sup>11</sup> cover businesses from manufacturing, construction, motor vehicle sales and repair, wholesale, retail, hotels and restaurants, storage, transportation, communications, and IT sectors. They only consider firms with more than five workers, and a minimum of 1 percent of private ownership.<sup>12</sup> The ES reveal significant firm-level heterogeneity in Morocco. From the 1,096 interviewed firms in 2019, 28 percent were large (307 firms), 35 percent medium (384 firms), and 37 percent small (405 firms). By sector, 11 percent operate in the food sector, 16 percent in garments, 16 percent in other manufacturing, 17 percent in retail, and 41 percent in other services. In fact, 63 percent of firms have been in operation less than 20 years. Regarding international trade, only 20 percent of firms export more than 10 percent of their sales directly, compared with the MENA average of only 17 percent. While the proportion of firms that use foreign inputs for production is 42 percent, it is considerably lower than the average 64 percent for the MENA region.

# **_Static Analysis_**

This section presents evidence at the firm level to increase the understanding of the characteristics of exporting firms and their linkage with employment in Morocco. Results (Appendix A) show significant variation across firms – both exporters and those that sell only to the domestic market in terms of sales and employees. We also present an estimate of firm ́s probability of being an exporter conditional on several variables. We also evaluate the relationship of employment with being an exporter and export sales.

> 11 For the evolution of the same firms (panel) we analyze the trends from 2013 to 2019.

> 12 They exclude firms from agriculture, fishing, mining, public utilities, financial intermediation, public administration, education, health, and social work. They do not consider either business with less than five workers, informal firms, and 100% state-owned firms.

24 | P a g e
# **Technical Appendix**

## **A.1 Data sources**

measured respectively by imports as a share of global exports, capital outflows as a share of global inflows, and patents as a share of global patents. The imports measure corrects for reexports for the major entrept economies of Singapore and Hong Kong, and for intra-monetary union trade using bilateral trade flows data. The capital outflows measure includes FDI and portfolio capital, but excludes derivative transactions. The patents measure utilizes patent approvals to all national patent bodies reporting to the World Intellectual Property Office. The expanded polarity measure additionally includes weights for the migration channel, as measured by immigrant stock as a share of global immigrants.

_Population growth_ was measured as the growth rate of the total population, _investment_ was gross fixed capital formation share of GDP, _enrollment_ was the primary school enrollment rate, _income per capita_ was real per capita GDP measured in 2000 U.S. dollars, _health status_ was the life expectancy of the population, the _dependency ratio_ is ratio of the population younger than 15 or greater than 65 relative to the working age population, and _government size_ was the government expenditure share of GDP. Alternative measures for enrollment, health, and dependency used were the secondary school enrollment rate, the under-5 mortality rate, and the old-age dependency ratio. Additional controls: _Technology diffusion_ was proxied by mobile cellular subscriptions coverage, _infrastructure_ by road density, and the regional dummies included _Africa_ , _Latin America_ , and _East Asia_ .

The measure of _institutional quality_ was a composite measure obtained by taking the proportion-weighted sum of the first three principal components of 11 subcomponents of the ICRG political risk measure: government stability, corruption, law and order, bureaucracy quality, socioeconomic conditions, investment profile, internal conflict, external conflict, military in politics, religious tensions, and ethnic tensions (only the first three components obtained an eigenvalue greater than unity, justifying their inclusion). Alternative institutional quality measures applied: (a) inclusion of democratic accountability to the subcomponents used in the principal components analysis; (b) restriction of the measure to only the first four subcomponents (and taking the proportion-weighted sum of only the first two principal components); and (c) restriction of the measure to only the first four subcomponents (but weighting each subcomponent equally). _Economic integration_ was total trade (imports plus export) as a share of GDP, and _geography_ was the latitudinal distance from the equator.

30