rafmacalaba/datause-encoder-data huggingface dataset:
a website, the mechanisms to register consumer complaints, the agency’s annual report and institutional strategy, and employees’ training.

# **A. Regulatory tools:**

<!-- Start of picture text --> The region shows a better performance in regulatory than in institutional tools. Benchmarking,<br>mainly to determine tariffs, is used in 78 percent of the region, with a smaller percentage of<br>countries having the full complement of tools listed in the survey (See question 73 of the survey).<br>Figure 22: Regulatory Tools Index<br>Regulatory Tools Index<br>Source: LAC Electricity Regulatory Governance Database, The World Bank, 2007.<br>1<br>.8<br>.6<br>Index (0-1) .4<br>.2<br>0<br>PER GUA ESV BRA URU T&T ARG JAM C R T1 COL BOL BAR PAN HON R D NIC ECU CHI T2 MEX<br><!-- End of picture text --> A significant number of countries are in Tier 1, reflecting the importance given by LAC agencies to the development of several tools to implement their regulatory decisions. Peru, Guatemala, El Salvador, and Brazil achieve full score leading those countries grouped in Tier 1. Mexico is the only country that is in Tier 3 and which does not meet the minimum requirements demanded in this index.

Leading countries in this index make use not only of benchmarking but also of tools to conduct regulatory policies such as a database for regulatory accountability, methodology for tariff revision, methodology for annual tariff readjustment, instruments for monitoring quality and technical standards, methodology for monitoring technical standards, methodology for defining interconnection tariffs, and five-year revisions of these tools. Moreover, 90 percent of the countries in the region have developed specific legislation to regulate electricity consumers’ rights.

Countries at the bottom of the index differ in their performances. While none of them make use of benchmarking, Ecuador and Chile achieve average scores in regulatory instruments with Mexico having the lowest results in this last indicator. The poor performance of Mexico in this aspect might be related to the lack of reforms in the electricity sector and the concentration of tariff determination powers in the sector ministry. A large percentage of the tools in the index are related to tariff determination and readjustment.

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- McKenzie, David (2007) “Paper Walls are Easier to Tear Down: Passport Costs and Legal Barriers to Emigration”, _World Development_ 35(11): 2026-39.

- McKenzie, David, John Gibson and Steven Stillman (2006) “How important is selection? Experimental versus non-experimental measures of the income gains from migration”, _World Bank Policy Research Working Paper No. 3906._

- New Zealand Department of Labour (2007) _Recognised Seasonal Employer: Interagency Understanding: Vanuatu_ . New Zealand Department of Labour and Republic of Vanuatu Ministry of Internal Affairs.

- Pritchett, Lant (2006) _Let Their People Come. Breaking the Gridlock on Global Labor Mobility_ . Center for Global Development, Washington, D.C.

UNDP (2007) _Human Development Report 2007/2008_ _<u>http://hdrstats.undp.org/countries/country_fact_sheets/cty_fs_VUT.html</u>_ [accessed April 29, 2008].

- Winters, L. Alan (2003) The temporary movement of workers: GATS Mode 4', Chapter 3 in Bridging the Differences: Analyses of Five Issues of the WTO _Agenda,_ Consumer Unity Trust Society, Jaipur, India, pp111-146, September.

- World Bank (2008) _Migration and Remittances Factbook 2008._ World Bank: Washington D.C.

- World Bank (2006a) _Global Economic Prospects: Economic Implications of Remittances and Migration_ . World Bank: Washington, D.C.

- World Bank (2006b) _Expanding Job Opportunities for Pacific Islanders Through Labour mobility at Home and Away_ . World Bank: Washington D.C. and Sydney, Australia.

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**Figure 22: The ETCR Indicator for Croatia** a) Aggregate ETCR

<!-- Start of picture text --> b) Disaggregated ETCR<br><!-- End of picture text --> <!-- Start of picture text --> Croatia EU-15 average OECD average Airlines Telecom Elecricity Gas Post Rail Road<br>6.0<br>6.0<br>5.0<br>5.0<br>4.0<br>4.0<br>3.0<br>3.0<br>2.0 2.0<br>1.0 1.0<br>0.0 0.0<br>1975 1980 1985 1990 1995 2000 2005 1991 1993 1995 1997 1999 2001 2003 2005 2007<br><!-- End of picture text -->

**The gap in regulatory restrictiveness with the EU is equally large for barriers to entry and public ownership.** The ETCR can be decomposed in its various components, thus allowing us to trace the restrictiveness of regulation to its sources. The dimensions considered are tailored to each sector and include public ownership and barriers to entry (see Annex). Under both dimensions, the regulatory framework in Croatia is more restrictive than the EU and OECD averages (Figure 23).

**<u>Figure 23: Barriers to entry and public ownership</u>**

<!-- Start of picture text --> a) Entry Barriers b) Public Ownership<br>Croatia EU-15 average OECD average Croatia EU-15 average OECD average<br>6.0 6.0<br>5.0 5.0<br>4.0 4.0<br>3.0 3.0<br>2.0 2.0<br>1.0 1.0<br>0.0 0.0<br>1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005<br><!-- End of picture text -->

**Product market policies that are more conducive to competition would have a significant impact on Croatia’s convergence to higher income levels.** Conway et al. (2006) show that the ETCR is highly correlated with the overall restrictiveness of a country’s regulatory environment across OECD countries. This allows using the ETCR in regression analysis as a proxy for the degree to which overall product market policies restrict competition. Simulations based on regression analysis conducted for Croatia indicate that a reduction of the regulatory burden as represented by the ETCR indicator to the less restrictive level of the EU15 would be associated with an increase in the level of GDP per capita of between 1.35% and 2.77% (Figure 24). As argued by Conway et al. (2006), restrictive product market regulation negatively affects income convergence by slowing the process of adjustment through which positive productivity shocks diffuse across borders and new technologies are incorporated into the production process. Furthermore, Conway et al (2006) show that the gains from further product market reform are more significant the more distant a country is from the productivity frontier. For a country like Croatia, which is far from the world productivity frontier, progressive integration with the EU is

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response to FMS reports mostly replicates inequalities at the demand level rather than ameliorating or exacerbating them.

Our results match those of Hamel and Holliday (2019) in the US who find that there are minimal differences in how quickly US municipalities respond to 311 requests from rich and poor neighborhoods. At least so far, there is little evidence that local governments either correct for or exacerbate reporting biases in service requests.

Once again, we do not see a simple translation of inequalities in technology access to inequalities in the impact on people. The participant profile on FMS does not match the inequalities in technology access in the UK and instead looks more similar to the demographic divides seen in traditional offline forms of participation such as voting.

These participation inequalities do not straightforwardly translate into unequal demands made through the platform either. The educational divide in participation is the only inequality that translates directly from participation to the demands made. The gender and ethnic minority divides are absent in terms of demands made and the age gradient actually reverses.

The link between the demands made and the impact on people is straightforward in the case of FMS. Local governments appear to fix problems at the same rate regardless of what type of area the report was received from. This means the distributive effect of FMS is determined by how equal the demands made through the platform are.

# **Case study 3: Iceland Crowd-sourced 2011 Constitution**

Our third case study concerns the development of a new constitution for Iceland using input from the population through online engagement. The financial crisis of 2008-2009 had an especially strong effect on the Icelandic economy and was widely seen as discrediting the political establishment. This led to sustained calls for revising the Icelandic constitution.

21
First, brain drain has been and continues to be an area of tremendous policy concern in many countries. Over the past decade, Factiva shows an average of 5,000 news articles in English per year about this topic. There are many claims that brain drain decimates healthcare and educational systems in developing countries, and that failure to stop it could lead to ―economic and social catastrophe on an unprecedented scale‖ (Sattaur, 1989). The extent to which such claims are true should matter to economists.

Second, brain drain takes place in the context of what is probably the largest distortion in the international global economic system: barriers on the mobility of labor. Constraints on movement lead to very large gaps between the incomes that can be earned in different destinations – gaps which are orders of magnitude larger than one sees with internal movements. In a recent study of the top academic students from five countries, we document increases in income of $40,000-$60,000 per year when the highly skilled emigrate from developing countries (Gibson and McKenzie, 2010). These barriers also restrict the extent to which less-skilled workers can react to the migration decisions of the higher-skilled. In these ways, international migration is quite different from within-country migration. Unskilled Floridians are free to move to other states if skilled Floridians move, whereas unskilled workers in developing countries have much more limited opportunities to follow skilled compatriot workers who migrate.

Third, the economic literature on brain drain has long been concerned about the existence and extent of production and fiscal externalities. Almost a half century ago, Grubel and Scott (1966) noted that if labor markets are competitive and individuals are paid their marginal product, then if there are no externalities, the departure of highly skilled emigrants would not reduce the welfare of those left behind. In practice, if skilled and unskilled labor are complements in production, and skilled workers do not capture all of the increase in production value that comes from this complementarity, then the departure of skilled workers could lower the pay or employment levels of unskilled workers. When discussing the consequences of possible out-migration from (say) Florida to the other 49 states, it is important to recognize that this would be in a context in which skills within Florida remain reasonably abundant, unskilled workers are also mobile, and a federal taxation system ensures that residents of Florida still benefit fiscally from the earnings of high-skilled individuals who migrate out of the state. Such conditions seem less likely to hold in most developing countries. Bhagwati and Hamada (1974) argued that the fiscal cost was particularly important, with many developing countries 6
_The importance of self-employment varies across the region_ Self-employment plays the most important part in the low-income CIS, where on average it accounts for 50 percent of total employment. The share of self-employment is much lower in the middle-income CIS (17 percent), and in CEE (20 percent). By way of comparison, in EU15 countries, self-employment accounts for about 15 percent of total employment.

There is substantial degree of variation in the share of self-employment within regions. It is particularly pronounced in CEE (Figure 5). On the one extreme are countries such as Estonia and Slovakia, where self-employment plays a minor part, accounting for less than 10 percent of total employment. On the other extreme there are countries such as Romania, Lithuania or Poland, where self-employment plays a major role, accounting for some 30 to 40 percent of total employment. In interpreting these figures one should notice that self-employment is often agricultural employment by a different name. That is, in countries where agriculture plays an important part self-employment as a share of total employment tends to be high as farmers are as a rule counted as the self-employed. This is obviously not to deny, that self-employment plays an important part outside agriculture.

In addition, cross-country and time comparisons may be obscured by the fact that in some cases there is little difference between dependent wage employment and self-employment. For example in Bulgaria and Poland some health care sector employees were turned into independence, self-employed contractors. This obviously inflated the number of the selfemployed, although there was no corresponding change in the nature of jobs. These measurement problems notwithstanding, there is little doubt that self-employment gained in prominence in transition economies and often accounts for a considerable fraction of jobs.

**Figure 5  Self-employment plays a critical role in CIS-7 and a negligible one in BRU whereas CEE countries are between these two extremes**

# **Self-employment, 2002 as percentage of total employment**

<!-- Start of picture text --> 80.0<br>70.0<br>60.0<br>50.0<br>40.0<br>30.0<br>20.0<br>10.0<br>0.0<br>AzerbaijanKyrgiz R.GeorgiaArmenia_CIS-7TajikistanMoldovaRomaniaLithuaniaPolandUzbekistan _CEELatviaCzech R.Slovenia EU15HungaryUkraineSlovak R. _BRUEstoniaRussiaBelarus<br>percent<br><!-- End of picture text --> Source: Eurostat, CIS-stat (2003) 14
be able to proceed with further trade liberalization and facilitation by expanding and improving their port facilities. Second, as port infrastructure projects are economically viable long-term investments, private-sector participation in the projects could be a major vehicle for finance, such as through private-public partnerships.

Third, active investment in the region could bolster economic recovery over time in East Asia. Since investment in port infrastructure can be justified and viable to reduce bottlenecks even in the period of recession, this will provide a useful tool for governments in the developing economies in both macroeconomic demand and supply terms. Forth, the nature of the effect of port infrastructure improvements is equivalent to across-the-board uniform tariff reductions. As such, importing countries would suffer less from trade diversion and port investment may face less serious resistance in a public policy context. Finally, future research to extend our analysis on economic welfare and growth (through trade) in different countries is also an important empirical and policy question.

# (References)

Abe, K. and Wilson, J. S. (2008), Journal of International Economic Studies, “Trade, Transparency, and Welfare in the Asia Pacific,” 12 (2): 35-87.

Anderson, J. and van Wincoop (2004) “Trade Costs,” _Journal of Economic Literature_ , vol.XLII, pp.691-751.

Bank of Japan (2005) “Revision of Compilation Methodology for Balance of Payment Statistics on Sea Freight Fares and Freight Insurance Premiums,” at the home page of the Bank of Japan. Blonigen, B. and Wilson, W. (2008) “Port Efficiency and Trade Flows,” _Review of International Economies_ , vol.16(1), pp.21-36.

Clark, X., Dollar, D. and Micco, A. (2004) “Port Efficiency, Maritime Transport Costs and Bilateral Trade,” _NBER Working Paper Series_ , No. 10353.

Simeon, D, Freund, C. and Pham, C. S. (2008) “Trading on Time,” _Review of Economic Studies_ . Helbel, M., Sheperd B. and Wilson, J. (2007) _Transparency and Trade Facilitation in the Asia Pacific: Estimating the Gains from Reform_ , Asia Pacific Economic Cooperation and the World Bank.

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Beyond the Income Effect: Impacts of Conditional Cash Transfer Programs on Private Investments in Human Capital<sup>_∗_</sup> Marcio Cruz<sup>_†_</sup> and Zacharias Ziegelh ̈ofer<sup>_‡_</sup>

**JEL Classification:** C21, D04, D12, I15, I25, I38

**Keywords:** Conditional cash transfer; Bolsa Fam ́ılia program; Child human capital; Household expenditure; Regression Discontinuity Design.

> _∗_ We thank Jean-Louis Arcand, Erich Battistin, Ugo Panizza, Nicolas Berman, Francisco Ferreira, Mathilde Maurel, Michael Carter, Dany Jaimovich, Natascha Wagner, Matthias Sch ̈undeln, Sebastian Krautheim, Matthias Rieger, Selsah Pasali, Sarah Nohr, Abbad El-Rayyes, Deborah Wetzel, Magnus Lindelow, Joana Silva, Rafael Proen ̧ca, Aleksandra Zaronina and Tehani Pestalozzi for their useful suggestions. We have also benefited from comments received from the participants of Development Therapy Seminar in Geneva (October 2011), International Conference on Poverty Traps in Paris (October 2011), Rigonomics BBL in Geneva (April 2012), Guest Seminar in Development Economics at the Goethe University in Frankfurt (July 2012) and the 18th Annual LACEA Meeting in Mexico City (November 2013).

> _†_ Graduate Institute of International and Development Studies (Geneva), Federal University of Paran ́a and the World Bank. Email: Marcio.Cruz@graduateinstitute.ch.

> _‡_ Graduate Institute of International and Development Studies (Geneva) and the United Nations Economic Commission for Africa (UNECA). Email: Zacharias.Ziegelhoefer@graduateinstitute.ch.

i
researchers and is consistent across countries. The baseline is for a “normal” day so, for example, Monday mobility data is measured as the deviation from the “normal” Monday baseline and similarly for other weekdays. The “normal” day reflects the median value from five weeks of pre-crisis data from January 3 through February 6, 2020. The data are aggregated to monthly values at the first subnational administrative division in each country. The index is measured for six places, including workplaces, residential, grocery and pharmacy, transit stations, retail and recreation, as well as parks.

The real-time indicators at the levels of subnational administrative division by month are merged with the aggregated HFPS panel data at the same administrative level, yielding the panel data used for the analysis.

# 2.3 Multiple Imputation

Because Google mobility data are missing for several regions, we employ multiple imputation techniques to fill them. Google does not disclose at least one mobility indicator in a total of 559 out of 1,096 regions, across the 6 indicators (Residential, Retail and Recreation, Workplace, Transit Stations, Groceries/Pharmacies, and Parks). Using multiple imputation techniques allows us to include these regions in the models, which generate more precise estimates of the relationship between outcomes and other non-mobility predictors. To fill in missing Google mobility indicators, we create 100 imputations using imputation by chained equations, based on the other mobility indicators, night-time lights, NO2, and vegetation index (EVI). The chained equations approach carries out imputation iteratively for each of the Google Mobility variables, each time substituting values drawn from the conditional distribution for missing values, until convergence is achieved. Because we carry out analysis on two different samples, one for initial impacts and one for the subsequent evolution of the crisis, we perform two imputation exercises: one only for data from the first wave, and one for data for all waves. In the first case, mobility values are imputed for between 65 and 135 of the 311 total regions, depending on the Google mobility indicator. When using the data for all waves, we demean the data using each region’s mean, to isolate the variation over time, and impute the demeaned variables. For this case, mobility values are imputed for between 315 and 540 of the 1,096 total region-waves.

10
6 competitiveness in wo:lzi markets. Curiously, in these countries, expenditures on the environment were generally among the lowest of the industrial countries and even declined in the oOs (sec table 9 below). This would suggest no systematic link between trade performance in the sensitive goods and environmental expenaitures. The reason for changes in market shares is likely to lie outside the changes in environ,mental standards. Japan switched away from environmentally sensitive goods and spe .ialized in other products with impressive gains. Its env<sup>4</sup> -onmental costs were the highest of all industrial countries in 1980, but have since declined considerably as share of GDP (Table 9).

The lack of negative impact of higher environmental expenditures on trade performance in environmentaliy sensitive goods is confirmed by correlation coefficients between changes in wurld trade shares of the sensitive goods and changes in envirunmental expenditure. While crosscountry comparisens are unreliable because of the considerable differences in the measurement of environmental expenditures, reasonable time series data for the trade and expenditure variables are available for Austria, Germany. Japan and the United States. Correlation coefficients were calculated for both total and private environmental expendi,ure in GDP, when available (Table 3). The correlation coefficient for Austria and Germany was positive, 0.7 and 0.12 respectively. For Germany it was not statistically significant, but for Austria the positive correlation was very significant at 2.5% level. The US coefficient was negative, but stat '4cally insignificant. For Japan the coefficient was negative, failed to be s'atistically significant. This means that only in tht case of Austria was there any correlation between environmental expenditures and trade performance.