rafmacalaba/data-use-mentions-extended huggingface dataset:
the EU. From the estimated coefficients, and the indexes themselves, this implies a combined or composite productivity gain in market services in Italy of 66.3 percent. Of this, most follows from domestic regulation (38.0 percent), with the rest following from removing discriminatory barriers, that is, greater openness (20.5 percent). Although closed by West European standards, Italy is actually relatively close to the OECD norm in terms of openness (Austria, Japan, Slovenia, and the Czech Republic all rank more closed). It is an outlier in terms of domestic regulation, being near the upper range for overall domestic regulation issues.<sup>33</sup> The CGE experiment involves an application of the basic GTAP model, using GTAP8 data (benchmarked to 2007, the same year as our regulatory and MFP data). The basic aggregation scheme is summarized in Table 7.

Table 7: Database aggregation

|sectors|regions|
|---|---|
|primary sectors|Italy|
|processed foods, beverages|rest of European Union|
|textiles and clothing|rest of world|
|chemicals, petrochemicals||
|motor vehicles<br>other machinery||
|other manufacturing||
|utilities, construction||
|commercial services||
|public services||

In the basic GTAP family of models, changes to MFP can be modeled through efficiency coefficients (Hertel, Ianchovichina, and McDonald, 1997). In particular, national production is modeled as follows.

In equations (6), (7), and (8), the terms _X_ , _V A_ , and _IN_ refer to domestic goods/services, composite value added, and composite intermediate inputs, indexed for sector _i_ and production region _r_ . The elasticity of substitution at the upper-nest, the value added nest, and the primary input nests are represented by _σi, σi,V A_ , and _σi,IN_ . Primary factors are represented by Φ.
markets. For that the paper uses the Romanian firm-level data from the Ministry of Finance covering enterprises of all sizes (hereafter referred to as MoF firm-level data) for the period 2011-2020, combined with the new World Bank Businesses of the State (BOS) database that

> 5 According to the World Bank Businesses of the State database, SOEs with at least 10% state ownership accounted for  3.6% of the formal employment as of 2019 in Romania. Section 3, “Data Sources”, of this paper describes the World Bank Businesses of the State database.

2
|**In AD-E**|**UN-Domestic-Firms :**||
|**C.**|**COUNTRY**|The European country in which the plaintiff domestic firm is located|
|**In AD-E**|**UN-Foreign-Firms :**||
|**D.**|**PADMEASUREFIRM**|The firm-specific preliminary antidumping measure imposed|
|**E.**|**___**<br>**P_AD_MARGIN**|<br>The firm-specific preliminary antidumping margin imposed|
|**F.**|**F_AD_MARGIN**|The firm-specific final antidumping margin imposed|
|**G.**|**P_AD_DUTY**|The firm-specific preliminary antidumping duty imposed|
|**H.**|**F_AD_DUTY**|The firm-specific final antidumping duty imposed|
|**I.**|**NOTES**|Comments|

In terms of missing or incomplete data, the European Union dataset lacks information on reviews.

24
Figure 4. Job Quality Measure among the Wage Employed, by Industry <!-- Start of picture text --> Income Benefits Stability Working Conditions Share of Wage Employees<br>4.00 100%<br>90%<br>80%<br>3.00 0.68 0.61 0.59 70%<br>2.001.00 0.950.80 0.870.74 0.850.71 0.500.710.50 0.450.730.47 0.490.660.50 0.430.650.40 0.490.610.40 0.480.540.26 0.520.490.22 60%50%40%30%20%<br>0.87 0.88 0.87 0.81 0.86 0.82 0.80 0.74 0.81 0.62 10%<br>0.00 0%<br>JQM<br>Share of Wage Employees<br><!-- End of picture text --> _Source:_ Estimates based on multiple labor force and household surveys (see annex table A1). _Note:_ The figure shows JQMs by industry among the wage employed only and the share of the wage employed among all workers. These are simple averages across 37 countries in the sample (Panama, Philippines, and Thailand were excluded because they do not have information for one or more dimensions). The average of the stability dimension in public administration is not equal to one (which could be the case given that all public administration workers have a formal employer and therefore have stability according to the definition) because some countries do not have information on formality among private sector workers, and, thus, the formality indicator is not included to calculate the stability dimension in these countries.

Despite considerable progress in recent years, gender disparities persist across developing countries. Women now represent 40
- **Government effectiveness** : this variable captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Like other institutional variables, it is expected to be positively correlated with our SME financial inclusion index.

- **Control of corruption** : this captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests. Therefore, we expect a positive sign for this variable.

_Business environment_

- **Credit information** : this variable is proxied by the depth of credit information index, which measures rules and practices affecting the coverage, scope and accessibility of credit information available through either a credit bureau or a credit registry. The index ranges from 0 to 8, with higher values indicating the availability of more credit information to facilitate lending decisions. Given that reducing information asymmetries between lenders and borrowers is a critical step for improving access to finance by SMEs, we expect this variable to enter our model with a positive sign.

- **Rule of law** : this variable measures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts. These factors contribute to a stable and conducive business environment, facilitating transfer and collateralization of assets, ultimately easing access to finance constraints for SMEs. This variable should enter our model with a positive sign.

- **Tax burden** : this is proxied by a composite measure that reflects marginal tax rates on both personal and corporate income and the overall level of taxation (including direct and indirect taxes imposed by all levels of government) as a share of GDP. A high level of taxation can
Some studies have surveyed existing literature analyzing the relationship between infrastructure and economic growth (e.g., Munnell 1992<sup>3</sup> ; Gramlich 1994<sup>4</sup> ; Button 1998; Elburz et al. 2017). While the survey of Button (1998) examined the links between public capital and the role of endogenous growth processes, Elburz et al. (2017) offer new insights on variation in the empirical results investigating public investment infrastructure and regional growth. Elburz et al. (2017) conduct a meta-analysis of 42 studies published during the 1995-2014 period. The metaanalysis reports the following: (i) studies that employ data from the United States are more likely not to register a positive relationship between public infrastructure and economic growth; (ii) results differ across the studies due to difference in infrastructure measurement used, analytical methods, geographical scale of the study, and (iii) analysis that introduces interregional, interstate and interprovincial public infrastructure is likelier to yield negative effects, suggesting spillovers impact these investments.

Several studies report that whether or not infrastructure investment boosts economic growth depends on the stage of economic development of a country. In developed economies where infrastructure is not a constraint for economic development, infrastructure development may not furnish an economic growth effect. On the other hand, in countries where lack of infrastructure is a barrier to economic growth, the relationship between infrastructure investment and economic growth is strong (Sanchez-Robles 1998; Esfahani and Ramı́rez 2003). Examining the economic growth effect of public investment through a cross-country data, Sanchez-Robles (1998) shows that the indicator of infrastructure investment is positively and significantly correlated with economic growth in the sample of 19 Latin American countries. With an analysis using a panel of 75 countries around the world, Esfahani and Ramı́rez (2003) finds that the contribution of infrastructure services to GDP is substantial and, in general, exceeds the cost of provision of those services.

> 3 Munnell (1992) is the earliest
00]|0.86|(1.33)|1,422|
|FR Foregone Hospital Visits, Last 4 Weeks|1.08**|(0.54)|[0.38]|2.74|(3.83)|1,416|
|FR Health Expenditures (USD PPP), Last 4 Weeks|-10.17|(19.42)|[1.00]|65.77|(131.06)|1,422|
|FR Food Insecurity Last Week (=1)|0.11*|(0.07)|[0.38]|0.34|(0.47)|1,421|
|Adult Food Insecurity (Days)|0.05|(0.22)|[1.00]|0.78|(1.47)|1,391|

**_Notes_** :

- The table shows the regression results on pre-specified physical health outcomes using the 2021 in-person data. Each row is its own dependent variable.

- The outcomes that require definitions are: Normalized Symptom Index is defined as mean-effect index of common symptoms (Fever, Persistent cough, Always feeling tired, Muscle pain (myalgia), Headache/migraine, Stomach pain, Blood in stool, Rapid weight loss, Open sores/boils, Diarrhea/nausea/vomiting, Back pain or other muscle pain, Runny nose, Sore throat, Pneumonia, Loss of sense of smell/not being able to taste food, Frequent and excessive urination, Constant thirst/increased drinking of fluids, Skin rash or irritation, Difficulty swallowing, Fast or irregular heartbeat, Difficulty breathing/chest tightness). FR Subjective Health is based on the FR’s describtion of his or her general health and is categorized as good (4), fair (3), poor (2), or very poor (1). FR Major Health Problems
# **Figure A3.2: Impact of Changes in Combinations of Load Factors for Business Class on Carbon Footprint of HQ-Based Bank Staff Air Travel, 2009**

<!-- Start of picture text --> 350,000,000<br> 300,000,000<br> 250,000,000<br> 200,000,000<br>Business Class 30%<br> 150,000,000 Load<br>Business Class 90%<br> 100,000,000<br>Load<br> 50,000,000<br> -<br>0.3 0.4 0.5 0.6 0.7<br>First Class Load Factor<br>Overall Carbon Footprint (Kg)<br><!-- End of picture text --> Figure A3.3 charts the average passenger footprint per mile found across all distance classes and all aircraft in the sample used for the Phase III calculations, assuming a 60% load factor for both business and first classes. Figure 3 also shows the average fuel consumption per seat mile of those same flights, based on aircraft types found both in the ICAO base tables in their own methodology, which are again based on the modified CORINAIR tables in Version 3 of ICAO’s Carbon Emission Calculator.

The chart points out in both datasets that at first, as distances increase, the consumption per mile and resultant footprint goes down. As the distances increase, the consumption then increases again, because of the weight of the additional fuel to be used for the longer trip. A significant increase is seen between distance classes 7 (1,501 nm to 2,000 nm) and 8 (2001 nm to 2,500 nm), and 8 and 9 (2,501 nm to 3,000 nm). Between CY2009 and FY2012 a reduction of average distance per flight has occurred, making the average distance go from class 9 to
in the middle (see Appendix, Table 3.b, for further details).

The subsidies indicate that risk-taking is different among ownership forms. The gross subsidies across the different ownership forms are (in decreasing order of risk and due to merger activity. Commercial Bank of Korea and Hanil Bank merged in 1998 creating a new bank called Hanvit Bank, while Hana Bank announced on September 8'h, 1998 to merge with Boram Bank (to become effective in 1999). Korea First Bank has been sold to New Bridge Capital of the US as of December 30e, 1998, although trading was not suspended until June 25 , 1999, and Kookmin Bank announced a merger with Korea Long Term Credit Bank on August 25"', 1998. Accounting data for Seoul Bank continued to be reported until 1998, although the bank was nationalized in 1998, and subsequently sold to HSBC Bank on February 22nd, 1999. In Thailand, due to lack of data, we exclude Laem Thong Bank, Nakornthon Bank, and Union Bank of Bangkok. For 1998, we also do not have data on Bangkok Bank of Commerce, which was closed and de-listed in 1998, and on First Bangkok City Bank, which was acquired by the government in February of 1998 and merged with state-owned Krung Thai Bank in 1999.

13
# Table 1. Excess Demand in Supply-Use Table, 2007

|Sector|Demand<br>(Million Drams)|Supply<br>(Million Drams)|Excess Demand<br>(Million Drams)|Excess Demand<br>(% of total supply)|
|---|---|---|---|---|
|Agriculture, hunting, forestry and fishing|667674|946682|-279008|-29|
|Mining and quarrying|140383|265814|-125431|-47|
|<br>Manufacturing|2628702|1696509|932192|55|
|Electricity, gas and water supply|309011|167184|141827|85|
|Construction|1199096|1349184|-150089|-11|
|Wholesale and retail trade and repair|462281|511197|-48917|-10|
|Hotels and restaurants|103346|138806|-35460|-26|
|Transport, storage and communications|328311|436416|-108105|-25|
|Financial intermediation|69604|109189|-39585|-36|
|Real estate and professional services|95704|175056|-79352|-45|
|<br>Public administration and defence|176585|162771|13814|8|
|Education|203286|120656|82631|68|
|Health and social work|157127|129786|27341|21|
|Other social and personal services|29630|84707|-55077|-65|
|Source: Authors' calculations based on data fro|m National Statistical Of|fice of the Republic|of Armenia||

Table 2. Total GDP, 2007 (million Drams)

|GDP<br>Official Estimate|Supply-Use<br>Table|Authors'<br>balanced table|
|---|---|---|
|Income<br>3149283|2860584|3044640|
|Expenditure<br>3149283|3137365|3044640
the transition into self-employment.

Once youth enter the labor force, they do not necessarily give up their educational careers. Education increases the chances of getting better jobs and higher wages and young workers have lower “switching cost” of returning to school or college than prime age adults. Literature shows evidence of this pattern. Using a panel from 1989 to 1994 of urban adolescents in the city of Baltimore, US, Entwisle et al (2000) find that even though almost all students had begun work by age 17, only 23 percent worked every school year from age

> 5 For example, see OECD (2001) or World Economic Forum (2009)

4
15 There is no easy response to this dilemma. The politically least controversial response of assigning more resources to higher education through a higher overall budget to education runs into fiscal constraints."<sup>3</sup> Barring more public resources, the only option for expanding of investment in higher education (desired on efficiency grounds) without cutting public funding for primary education is by attracting greater private sector participation.

To facilitate greater private participation, it is useful to distinguish more clearly the roles of the private and public sectors. The classic assignment of responsibilities limits the public sector's involvement to the provision of public goods, as well as correction for market failures and externalities. In that context, it is often argued that the positive externalities from education are highest at the primary level and progressively decline at the higher levels; Schultz (1988). That is, at higher education levels, the individuals receiving the education capture a progressively larger share of the total social benefits yielded from the education in the form of higher wages. That being the case, there is less of a risk that private individuals left to their own devices would underinvest from a social viewpoint in higher education than that they would underinvest in primary education. The externalities from different levels of education are difficult to measure and compare empirically. However, if the rationale for state intervention in the provision of higher education services is based on the argument that rates of return were too low to induce the right amount of investment from the private sector, that rationale has certainly become less compelling with the significant increases in private rates of return observed in recent years.

The options for greater private sector participation in higher education are many. They range from greater participation in the funding of education services to greater participation in the direct provision of services.<sup>14</sup> At the very least, the rise in private rates of return for higher education makes a compelling case for increasing the level of cost-recovery in higher education, independently of whether it
dominates for low incomes. We use inverse log income because the log transformation increases our ability to differentiate effects at very low income levels.

For the relationship between CO2 concentration and income per capita, we expect (β12 > 0). In the income-squared term, we expect β13 < 0 (the EKC case) or β13 = 0 (a linear relationship). Heating requirements are greater in colder climates, so we expect the effect of heating degree days on CO2 emissions (β14) to be positive.

Clearly-exogenous variables in the model include fires in neighboring areas and the demographic and climate factors. We include georeferenced data on CO2-intensive industrial facilities because they should have important effects on observed CO2 concentrations above their locations. Their inclusion serves our principal objective, a relatively complete econometric accounting of city-level CO2 emissions that can be used for comparative performance benchmarking and exploration of residuals. However, we recognize the possibility of some estimation bias from interactions with income and local air pollutants. Industrial facilities emit locally-significant air pollutants (e.g., NO2, SO2, fine particulates) along with CO2. Technical measures to reduce local air pollutants (e.g., stack scrubbers for SO2 emissions) do not reduce CO2 emissions directly, but the associated costs may have significant indirect effects by altering facility location decisions. Stricter environmental regulation in higher-income cities may enhance this effect. In principle, we could treat the potential bias problem by using measures for input costs to instrument the facility-level variables. In practice, however, we have no prospect of measuring the relevant variables at the requisite spatial resolution. Joint determination of income and CO2 emissions could also be a significant problem for the EKC component of the model. Our results discussion will include some estimation exercises that shed further light on these issues.

# **3.  Data**

# **3.1 Sources**

Several satellite platforms provide CO2 measures (Pan et al. 2021, Table 1). Data from these platforms have been collected by different instruments, over
process, emigration alters the composition of the home-country population on several dimensions (notably education and ethnicity) that can in turn a¤ect democracy at home.

In this paper we ...rst document these channels and then consider dynamic-panel regressions to investigate the overall impact of emigration on institutions in a large sample of developing countries. We ...nd that openness to migration (measured by the total emigration rate) contributes to improve institutional quality (as measured by standard indicators of democracy and economic freedom) in the migrants’origin countries. This result is robust to the use of balanced/unbalanced panels, to the exclusion of certain groups of countries (e.g., former socialist countries) or to accounting for the low-coverage of certain countries in our migration data. We also ...nd that human capital (measured by the share of tertiary educated in the resident labor force) has a positive and signi...cant e¤ect on institutional quality. Since skilled emigration both increases total emigration and reduces average human capital, this raises the question of whether some countries can achieve an institutional gain through a brain drain. To answer this question we rely on numerical simulations which show a positive but generally statistically insigni...cant e¤ect of skilled emigration. However, once we account for the fact that emigration prospects provide additional incentives to invest in human capital, then the e¤ect of skilled emigration on institutional quality becomes positive for a limited set of countries in the short run and for many countries in the longer run.

33
_Tax Reform in Transition_

# **Revenue-productive Income Tax Structures and Tax Reforms** in **Emerging Market Economies**

# **Evidence from Bulgaria**

## _1. Introduction_

Almost all emerging market economies (EMEs) are contemplating fundamental reforms of their tax systems. These reforms are determined by country-specific combination of factors including the advice of external experts and international agencies (Tanzi, 1991, World Bank, 1988 and Harberger, 1993), acute pressures from expenditure and revenue sides of the budget (Bogetic and Hillman, 1994), the increasing complexity of the administrative task (Bird, 1989 and Tanzi, 1992), and the internal political economy of public finance reforms (Bogetic and Hillman, 1995).

Political economy factors, however, often clash with the recommendation of experts who emphasize simplicity and transparency in the tax systems. As a result, although tax reforms may start with good intentions and well-defined objectives of the reformers, the outcome is often different from what it was envisaged at the outset. For example, Shome and Escolano (1993), in their survey of tax policy in the Former Soviet Union countries show that despite substantial effort on tax policy reform, the tax systems are often becoming more, not less complicated and transparent. Also, the Bulgarian authorities initiated far-reaching tax reforms with the objective of creating a tax system consistent with a market economy (Chand and Lorie 1993); these include the replacement of the old turnover tax system by a modem, single-rate value added tax, and the reduction of the corporate income tax rates. But in other areas, notably personal income taxation, the tax reform has not resulted in a simpler tax structure which is compatible with the more demanding administrative task and powerful incentives for evasion that characterize EMEs. The amendment to the 1992 Personal Income
on a mobile app provided by the Global Forest Watch. The app relays real-time satellite imagery to alert users of possible deforestation and provide evidence when deforestation has occurred. In one case, a popular local TV channel reported that encroachments had taken place without being addressed by the department upon which the department used the satellite data and alerts to identify two locations of encroachment. As a result of this, legal actions were taken to stop the encroachments from expanding.

# **Granularity**

Data can be granular along a number of dimensions, for example granular by space, granular by time, or granular by demographic attribute, such as gender. A long-running and rich example of the value of granular data by gender is the Demographic and Health Surveys, which cover topics 13