rafmacalaba/datause-encoder-data huggingface dataset:
# **1 Introduction**

How has globalization affected the relative taxation of labor and capital, and why? Has international economic integration eroded the amount of taxes effectively paid by capital owners, shifting tax burdens to workers? If so, which countries have been most affected by this process and through which mechanisms? Answering these questions is critical to better understand the macroeconomic effects and long-run social sustainability of globalization.

To address these questions, this paper builds and analyzes a database of effective tax rates on labor and capital covering more than 150 countries since 1965. Constructed following a common methodology that combines government revenue statistics with national accounts data, these series allow us to study trends in labor and capital taxation comprehensively, globally, and over a long period of time. Our database captures all taxes paid at all levels of government: corporate income taxes, individual income taxes, payroll taxes, property taxes, estate and inheritance taxes, consumption taxes, and other indirect taxes. This makes it possible to estimate total tax wedges, for instance the gap between what it costs to employ a worker and what the worker receives. Because our series are based on national accounts data that are harmonized across countries, they can be used to meaningfully compare effective tax rates internationally and over time. Last, since capital income is always more concentrated than labor income, the relative taxation of the two factors of production is closely linked to the progressivity of the overall tax system. Our database thus provides insights into changes in tax redistribution over the last half-century.

To maximize the time and geographical scope of this database, we conducted a largescale digitization and harmonization of historical data published by national statistical offices, which we combine with existing (but limited in coverage) series published by the United Nations, the OECD, and the IMF. The construction of our effective tax rates proceeds in three steps. Using national accounts data we first compute total labor and capital income in each country. Using government revenue statistics we then classify all government revenue sources into either labor taxes, capital taxes, or indirect taxes. Combining these two inputs, we compute effective macroeconomic tax rates on labor and capital by dividing 1
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# Table: THE WELFARE ORDERING OF COMMODITY TAXES IN THE COTE D'IVOIRE

# Commodity/Tax Base

<!-- Start of picture text -->
1. Telephone  dominates  A/  dominates  &/  dominates dominates<br>2. Electricity  does not  dominates dominatej<br>dominate<br>3. Gasoline  dominates  dominates<br>4. Alcoholic  does not<br>beverages  dominate<br>5. Public<br>transportation<br><!-- End of picture text -->

- A/ A close examination of the individual observations for bread and water reveals that the curve intersects the X-axis for the very last observation. If this sample exactly portrayed the population, a social welfare function that is linear over the whole range of the distribution and concave between the second richest family and the richest one would show that subsidizing bread at the expense of water would be welfare decreasing. However, we suspect that this is a result of the sampling error. Where we take the average of two consecutive observations this anomaly disappears.

Tuuatios **In the** Cote **DlvorL/Uhirkzuk:b1510188** Kssall*/Welfare **Dminano.** A **the** Design **of toles**
<u>Panel C. Sample used in Column 11 of Table 1 Panel B</u>

|**Variable**|**Observations**|**Mean**|**Std.**<br>**Dev.**|**Min.**|**Max.**|
|---|---|---|---|---|---|
|Unemployment|91|7.51|5.45|0.96|27.22|
|Internet<br>payments|91|25.32|27.61|0.222|84.23|
|Internet users|91|32.5|26.85|1.2|85.68|
|Informality|91|43.13|36.18|0|99.01|
|GDP deviation<br>from trend|91|-11.68|18.25|-85.18|15.79|
|Severancepay|91|6.89|7.24|0|33.33|
|Bank Credit|91|51.47|46.57|2.69|285.7|

<u>Panel D. Sample used in Column 9 of Table 1 Panel C</u>

|**Variable**|**Observations**|**Mean**|**Std.**<br>**Dev.**|**Min.**|**Max.**|
|---|---|---|---|---|---|
|Unemployment|59|7.32|6.34|0.96|27.22|
|Internet<br>payments|59|6.58|5.03|0.22|22.13|
|Internet users|59|14.99|12.01|1.2|45.23|
|Informality|59|66.52|21.18|15.07|99.01|
|GDP deviation<br>from trend|59|-16.09|19.21|-85.18|15.79|
|Severance pay|59|8.68|7.54|0|33.33|
|Bank Credit|59|30.72|38.2|2.7|285.7|

31
The differences in control structures across firm size bring about a more complete picture of cross-country differences at the 20% cut-off level once we weigh by market capitalization (Table 4). State ownership becomes much more pronounced, especially in Singapore (40.1%), Malaysia (34.8%), Thailand (24.1%), and Korea (19.9%). The control of widely-held financial institutions and corporations is diminished, so is control by families.

# _B. Differences in Control due to Age of Companies_

Another possible determinant of the control structure of companies is their age. In particular, some previous papers argue that younger companies are more likely to have a few ultimate owners, while older companies are more frequently widely-held. Anecdotally, this argument holds some appeal if one were to look at the US market where the recent deluge of technology-related companies may have increased the number of companies with a few owners with large stakes. Microsoft, for example, has one ultimate owner, Bill Gates, with 24% of the stock; so does Yahoo! where the Japanese entrepreneur Masayoshi Son has 29% of the voting rights. The evidence is less convincing in the international context. It is difficult to explain, for example, why Belgium and Sweden rank high in family control in La Porta, Lopez-de-Silanes, and Shleifer (1998); companies in these two countries are surely older than companies in (say) Australia, yet Australian companies are predominantly widely-held.

To investigate the relation between age and corporate control structures, we run simple correlations between the number of years the corporation has been in operation (the year of incorporation is obtained from Worldscope; 1996 is considered the end year) and the control stake (voting rights) of the largest owner. The results are presented in Table 5. Interestingly, only in Japan are older firms more widely-held. In the other eight countries, the correlation coefficients are always positive (older firms have more concentrated corporate control), and these coefficients are statistically significant for the Indonesian, Malaysian, and Taiwanese samples. Note that the average age of listed Japanese corporates is about twice as high (57.2 years) as that of the other samples.

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**(contd) Table 2b: Consumption per capita growth volatility with private credit**

|**Dep. Var:**|OLS|OLS|OLS|GMM|
|---|---|---|---|---|
|**stddev_cons.pc**|(1)|(2)|(3)|(4)|
|privatecredit|-0.0313***|-0.0510***|-0.0422***|-0.0436***|
||(0.000)|(0.000)|(0.000)|(0.004)|
|privatecredit<sup>2</sup>|0.0001***|0.0002***|0.0002***|0.0001**|
||(0.001)|(0.000)|(0.000)|(0.013)|
|financialopenness|0.0001|-0.0001|-0.0006|-0.0001***|
||(0.867)|(0.891)|(0.168)|(0.008)|
|tradeopenness|0.0071**|0.0095***|0.0132***|0.0127***|
||(0.013)|(0.000)|(0.000)|(0.001)|
|log_initialgdppc|-0.5663***|-0.2060|-0.4334***|-0.4244**|
||(0.000)|(0.106)|(0.000)|(0.038)|
|std_exchangerate|0.0641*||||
||(0.084)||||
|tot_change||0.0041|||
|||(0.644)|||
|commodityexporter|||1.0831***|0.9711**|
||||(0.000)|(0.029)|
|Constant|7.9294***|5.8570***|6.9072***|6.9775***|
||(0.000)|(0.000)|(0.000)|(0.000)|
|# of Obs.|388|462|775|781|
|R-squared|0.254|0.124|0.185||
|Prob > F|0.000|0.000|0.000|0.000|
|# of countries||||133|

Robust p-values are presented in parentheses and significance at 1% (***), 5% (**), and 10%(*) levels are indicated.

# **_Section 1b: Does volatility depend on who borrows?_**

This section examines the relationship between different types of credit and their relationship to volatility. The dependent variables are the same as in the previous section (as are the control variables). However, the explanatory variable is now either household credit as a ratio to GDP or the share of household credit in total private credit. The estimations using share in GDP of household and firm credit to explain economic volatility are shown in Tables 3 and 4.

13
Policy Research Working Paper 6945

# **Abstract**

The paper combines state-level fiscal data with household survey data to assess the links between sub-national fiscal policy and income inequality in Brazil over the period 1995–2011. The results indicate that a tighter fiscal stance at the sub-national level is not associated with a deterioration in inequality measures. This finding contrasts with the conclusions of several papers in the burgeoning literature on the effects of fiscal consolidation on inequality using national data for OECD economies. In addition, the authors find that a tighter stance is typically positively associated with a measure of “shared prosperity”. Hence, the results caution against extrapolating policy implications of the literature focusing on advanced economies to other settings.

This paper is a product of the Poverty Reduction and Economic Management Team, Europe and Central Asia Region in collaboration with colleagues from the IMF and the IADB. 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. This paper was also issued as IMF Working Paper 14/85. The authors may be contacted at jazevedo@worldbank.org, adavid@imf.org, FRodriguesBastos@imf.org, emiliopi@iadb.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
# **5.2. How does the gender gap in spending evolve over time and across the expenditure distribution?**

To answer this question, we run quantile-conditional regressions following the model described by equation 2. We run two models per wave independently shown in Tables A.3. and A.4. These regressions allow us to identify how gender effects vary at different points in the income distribution. With this in mind, Figure 5 shows how the coefficient associated with the principal applicant's gender changes for each expenditure level. Recall that in the last section we had found that, on average, female-headed households had lower levels of spending compared to those headed by men, especially in the 2017-18 wave.

**Figure 5.** Gender gap between PAs (Female – Male). Estimated coefficients from log expenditure quantile regressions

Note: This figure shows estimated coefficients from a quantile regression model. The y axis, thus, measure log changes in expenditure or percent changes (i.e., -0.1 is a 10 percent reduction).

Figure 5 shows that the estimate of this coefficient does indeed change depending on the quantile used. In particular, we found that at the lowest expenditure quantile (the 10th), the expenditure gap between male- and female-headed households is the largest, disadvantaging households with female PAs. The result in this quantile holds regardless of the wave of data used. The figure also shows that 26
# **Table A7: Bertelsmann Transformation Index (BTI)**

**Data Provider Description**

**Website Data Source Type Respondents Frequency Coverage Public Access Description**

## Bertelsmann Foundation

Nongovernmental organization headquartered in Berlin, Germany, with goal to study social challenges and problems and propose solutions. www.bertelsmann-stiftung.de Bertelsmann Transformation Index Expert Assessment Staff of Bertelsmann Foundation Every three years since 2003 Global sample of countries Yes We use data on the subcomponents of the Status Index (SI -- rating countries along dimensions of democracy and market economy status) and the Management Index (MI -- rating countries according to progress in achieving democracy and market economy status). Note that the MI rating captures information up to two years earlier. For instance, the BTI 2008 MI looked at events from 2005 to 2007. We have mapped them however only to 2007 (and carried forward to 2008). Note also that the corruption variable was drawn from one of the sub-components of resource efficiency.

|**Voice and Accountability**|2008|2007|2006|2005|2004|2003|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|---|---|---|
|Political Participation (SI)<br>|X|X|X|X|X|X|X||||
|Stability of Democratic Institutions (SI)|X|X|X|X|X|X|X||||
|Political and Social Integration (SI)|X|X|X|X|X|X|X||||
|**Political Stability and Absence of Violence**|||||||||||
|NA|||||||||||
|**Government Effectiveness**|||||||||||
|Consensus Building (MI)|X|X|X|X|X|X|X||||
|Governance Capability (MI)|X|X|X|X|X|X|X||||
|Resource Efficiency (MI)|X|X|X|X|X|X|X||||
|**Regulatory Quality**|||||||||||
|Competition (SI)|X|X|X|X|X|X|X||||
|**Rule of Law**|||||||||||
|Rule of Law (SI)|X|X|X|X|X|X|X||||
|**Control of Corruption**|||||||||||
|Anti-Corruption policy|X|X|X|X|X||||||
|**Country Coverage**|**125**|**125**|**119**|**119**|**119**|**116**|**116**|**..**|**..**|**..**|
|**Year of Publication**|**2007 **|**2007 **|**2005 **|**2005 **|**2005 **|**2002 **|**2002**|**..**|**..**|**..**|

46
particular, trade’s impact on the effective tax on capital (0 _._ 250, p-value=0 _._ 018) remains positive, and larger than that on labor taxation (0 _._ 133, p-value=0 _._ 013).

In Panel D, we include the set of country-year varying controls contained in _Xct_ in addition to the NDP weights. The inclusion of controls can help improve the precision of the estimates and could increase the likelihood that the exclusion restriction holds. Indeed, the controls lower the p-values and trade continues to have a positive impact on the capital factor share, and a larger positive impact on capital factor taxation than on labor taxation. Throughout the panels, we see in column 5 that the coefficients on the ETR on corporate profits mirror that of _ETRK_ , and are more precise.

The IV-results are robust to a battery of checks. First, we show that they hold with different measures of trade intensity (Table A4). Second, since one of the instruments relies on oil price variation, we allow oil-rich countries to be on a separate non-parametric time path; this addresses the concern that our estimating variation is correlated with trends in factor shares and effective taxation specific to oil-producing countries, and re-enforces the results (Table A5). Third, the results are broadly similar when we change our measurement assumptions to construct factor shares and ETRs (Table A6). The results are robust to the alternative assignment of taxes to capital versus labor proposed by Mendoza, Razin, and Tesar (1994); to changing the share of the PIT assigned to capital vs labor; and to using the ILO (2019) method to attribute mixed-income to labor vs capital, although the coefficients on _ETRK_ and _ETRL_ are now closer. Fourth, the results based on each individual instrument are comparable to the joint IV results (Table A7).

Finally, Table A3 directly reports the reduced-form impact of trade on our outcomes, leveraging the fact that the two instruments have opposite effects on trade. We find that the effects of globalization are symmetric: expanded openness increases both _ETRL_ and _ETRK_ , while reduced cross-border trade decreases the effective taxation of both factors.

# **7.3 Mechanisms and heterogeneity by income levels**

These results re-enforce the findings of the previous sections, that trade raises effective tax rates, especially on capital. One conjecture to explain these results is that trade exerts 27
((0)) Table 1. Ratio of Government Revenue to GNP and National Income, 1978-1992 (yuan bllion)

|Year||Goverrment<br>R<br>,__<br>_ _|evenue<br> _**_**_ _ _ _<br>_<br>_ _ _ _ _ _ _|Government<br>_ _ _ _ _ _ _ _ _|Expendlture<br>_ _ _ _ _ _ _ _ _ ___|Revenue/<br> <br>GNP|Deficit&<br>G|D.fioit/<br>G NP|
|---|---|---|---|---|---|---|---|---|
|||ChLness<br>Definition|Standard<br>Definition|Chlne..<br>Definition|standard<br>Definition|(percent)||(percent)|
||1978|112.1|124.8|111.1|123.8|34.8|-1.0|-0.3|
||1979|110.3|126.7|127.4|147.4|31.7|20.7|5.2|
||1980|108.5|130.1|121.3|147.1|29.1|17.0|3.8|
||1981|109.0|130.2|111.5|140.1|27.3|9.9|2.1|
||1982|112.4|140.9|115.3|.152.3|27.1|11.3|2.2|
||1983|124.9|160.7|129.3|173.0|27.7|12.3|2.1|
||1984<br>|150.2|184.3|154.6|196.5|26.5|12.2|1.8|
||1985|186.6|229.7|184.5|236.5|26.8|6.8|0.8|
||1986|226.0|244.6|233.1|265.6|25.2|20.9|2.2|
||1987<br>|236.9<br>|257.5|244.9|282.5|22.8|25.0|2.2|
||1988|262.8|2a0.4|270.7|315.3|19.9|34.9|2.5|
||1989|294.8|326.4|304.0|363.8|20.4|37.4|2.3|
||1990|331.3|351.5|345.2|403.1|19.6|51.6|2.9|
||1991|361.1|365.9|381.4|432.3|18.5|66.4|3.4|
||1992|415.3|368.8|439.0|483.4|17.3|114.6|4.7|

Notes Standard defLnition of revenue meanu subtracting borrowing from Chinese definitlon and addlng to the Chinese defLnitLon subsLdLes that were counted as negative revenue. Standard definition of expenditure mean. adding to the Chlnese definltion subsLdies that were consldered negative subsidies. ' revenues uslng standard definitLons. W expendLtures minus revenues using standard definitions. Sources KoKlnnon (1993) and State StatLitical Bureau (1993).

23
bond yields, probably reflecting the fact that complementary policies and forward guidance were on the whole less expansionary than previously expected by financial markets. Exchange rates and equity-market developments have also been mixed in the euro area.

# **4.5. Comparison of NIRP with other monetary policies in the euro area: An event study**

A natural question to ask is whether the responses of key financial variables to NIRP announcements differ from those of other types of monetary policies. One approach could be to compare the initial market response following NIRP announcements with that following conventional rate cuts in positive territory and QE announcements. To do this, another event study in the context of the ECB policies is conducted.<sup>20</sup> This event study is subject to the same caveats mentioned above.

This exercise leads to the following observations (Figure 10). First, compared with policy rate cuts during the easing cycle of the early-2000s, the reaction of money market rates and bond yields to recent NIRP announcements was qualitatively similar, but often smaller. This mainly reflects

**Figure 10. ECB policy announcements: changes in selected financial variables over one-day window**

<!-- Start of picture text --> A. Money market rates and bond yields B. Exchange rates and equities<br>Basis points Pre-crisis cuts Post-crisis cuts Percent Pre-crisis cuts Post-crisis cuts<br>2 QE NIRP cuts 2 QE NIRP cuts<br>0<br>1<br>-2<br>0<br>-4<br>-1<br>-2<br>NEER Equities<br>1-month interbank rate 3-month interbank rate 2-year government bond yields 10-year government bond yields<br><!-- End of picture text --> Sources: Bloomberg, Haver Analytics, European Central Bank, World Bank. Notes: Variable definitions are the same as in Figure 9. Pre-crisis policy rate cuts includes seven cuts to the main refinancing operation (MRO) rate over the period 2001 to 2003. Post-crisis policy rate cuts includes twelve cuts to the MRO rate over the period 2008 to 2013 (a period that also included hikes to the MRO rate during 2011). QE announcements include nine official policy announcements or expansions of the following programs: the covered bond purchase program, the securities market program, the outright monetary transactions program, the asset-backed securities purchase program, the public sector purchase program, and the corporate sector purchase program. NIRP announcements include four announcements which have resulted in the ECB’s deposit facility rate moving into, or further into, negative territory.

> 20 The specific focus on the ECB reflects its systemic nature and the broad range of policy easing measures it undertook both prior and after the global financial crisis.

24
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whether yields are affected by increased local control over water delivery. Third, we estimate a stochastic frontier production function to assess the decrease in overall production in-efficiency. We then look at distributional issues related to yield impacts to understand whether irrigation reforms have a similar effect on rich and poor farmers.

This paper is based on data from a survey of 1020 households and 68 irrigation associations covering the Magat River Integrated Irrigation System, a reservoir irrigation system in the Philippines. The section below first describes the irrigation management system in the Philippines. This is followed by a discussion on methodological issues and data. Results and conclusions follow.

# **2. Irrigation Management Transfer in the Philippines**

In the Philippines, some 50 percent of the irrigation service area is managed publicly under national irrigation systems; another 37% is managed by communal irrigation systems and 13% by private irrigation systems. The national systems are owned and operated by the National Irrigation Administration (NIA), a semi-autonomous government corporation that is responsible for irrigation development. (Sabio and Mendoza 2002, Bagadion 2002).

The Philippines history of organizing farmers to improve production goes back to the late 1960s. However, a more participatory approach to irrigation management was first developed in the mid-1970s for communal systems, and then expanded to national 6