rafmacalaba/datause-encoder-data huggingface dataset:
-2-

# **Section 1 - Conceptual Framework**

Capital income includes returns on investment in financial and real assets. Individuals receive income from financial assets, in the form of interest payments (on bank deposits and on private or public bonds), dividends paid out to them as shareholders, or in the form of capital gains. Real assets (such as real estate) generate rents and capital gains. The focus of this paper is on financial assets, though many of the statements applying to financial assets carry over to real assets.

Three different tax legislation affect capital incomes: corporate income tax (CIT), personal income tax (PIT), and withholding tax schemes.2 These taxes apply to various degrees to different forms of capital income. The creation of hybrid financial instruments such as zero-bonds (which contain their entire return as capital gains rather than interest) or profit-sharing bonds (which combine fixed interest payments with dividend distributions) can be essentially explained by the need to circumvent the tax legislation.

# **Corporate and Personal Income Tax**

In many countries, capital income is taxed under the corporate and personal income tax. The interaction between the tax systems is clarified in figure 1 (taken from Cnossen2 which applies particularly to the taxation of company profits (dividends and capital gains). However, as indicated below, it is applicable to the taxation of interest as well.

Conceptually, as shown in figure 1, two pure systems are possible. At one extreme, there is no integration at all between corporate and personal income tax. This is the so-called ,,classical system" which implies that (distributed or retained) corporate profits are, first, taxed under the corporate income tax, then subject to the personal income tax. The shareholder is not granted credit for CIT paid on dividends against the personal income tax liability.

At the other extreme, in a full integration system, the corporation is regarded as a ,,conduit" (passthrough) for company profits. Proponents of this view argue that any separate taxation of corporate profits is unjustified since they are ultimately channeled to the shareholder (in the form of dividend payments or capital gains). This does not preclude the existence of a corporate profit tax, but the latter represents only a prepayment on the personal income tax liability of the shareholder.

> 2 We do not consider here taxes applied on capital _stocks,_ such as wealth taxes or property taxes.

> 3 Cnossen, 1993, and Sorensen, 1995, contain recent overviews on corporate income tax and its relation to the personal income tax.
39 Khwaja, Asim Ijaz. Forthcoming. Can Good Projects Succeed in Bad Communities? Forthcoming, _Journal of Public Economics_ .

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# **4. Discussion**

The results presented in Tables 2 and 3 show the relationship between the level of legal gender discrimination and the probability that firms with and without female owners began operations informally. On aggregate, the results suggest that firms with female owners are less likely to have begun operations informally when the legal framework treats men and women more equally. In contrast, legal equality is associated with an increased probability of beginning informally for firms that are fully owned by men. Similarly, the results presented in Table 4 show that legal equality is associated with a longer period of informality for firms that are fully owned by men. These are unexpected findings, which appear to result from the pooling of data from highly heterogeneous regions. When the results are disaggregated by region, a more nuanced picture emerges.

For firms with female owners in Sub-Saharan Africa, the probability of beginning operations informally is decreasing in the level of legal equality between genders at the time the firm began operations. The marginal effect is approximately -0.002 suggesting that a single point increase in the index is associated with a 0.2 percent reduction in the probability that a firm with female participation in ownership would begin operations informally. Over the past decade, the index has increased by an average of 8 percentage points in Sub-Saharan Africa; according to our model, this would be associated with a 1.6 percentage point decrease in the proportion of female owned firms that began informally. This effect may appear small, but it is meaningful—the enterprise survey data show that, in this region, on average, 13.6 percent of formal firms with a female owner began operating informally. Furthermore, we would not expect the magnitude of the effect to be large given that legal equality in the areas covered by the WBL index is only one of the many factors that may shape a female entrepreneur’s decision to begin operations informally.

For firms in Sub-Saharan Africa that are entirely owned by men, an increase in legal equality is associated with a marginally higher probability that the firm would begin operations informally. This coefficient may suggest that, in this region, there is some degree of crowding out that happens when more female-owned firms are in a position to begin operating as formal enterprises. To try to understand this unexpected relationship, we disaggregate the WBL index into two broad areas of the law. As noted in section 2.1, there are 35 data points underlying the WBL index; 18 of these are collected through the administration of a survey on family law, 14 are based on labor laws and the remaining three relate to laws on violence against women. As laws on violence only comprise three of the 35 data points, we allocate two of these data points (those that relate to sexual harassment in the workplace) into the broader area of labor law, and one (specifically, the data point assessing domestic violence laws) to the area of family. Column (1) of 27
inequality identified in the literature along with the two data sets used in this paper. Using data over the period 19802000, section 3 establishes that the correlation between trade liberalization and inequality follows patterns predicted by factor-proportions theories. These results are largely confirmed with a ‘high quality’ data set (based on deciles) covering the period 1988-98 in section 4. Section 5 concludes.

# **`2. Transmission Channels and Data`**

# 2.1 Transmission Channels

The debate on the channels through which openness might affect inequality has largely revolved around the role of opennessinduced changes in relative factor demands and their consequent expected effects on factor rewards. For naturalresource-rich countries, though they do not deal directly with trade liberalization, Leamer et al. (1999), provide plausible scenarios and some evidence as to why the development paths of such countries could lead to rising inequality.

Concentrating on accumulable endowments where rent effects should be minimal, Wood (2002) provides a convenient summary of the different channels via which globalization might affect wage inequality (see also Kremer and Maskin (2003)). As all forms of transaction costs fall with globalization, factor mobility (capital via FDI and Northern K-workers in the terminology of Wood) is enhanced, leading to greater cooperation of Northern K-workers who travel to work with skilled workers in the South. In the South, workers with little or no-education (and hence low wages) would then be expected to be confined to non-traded activities. Trade liberalization would then not only lead to rising wages for skilled workers in the North and in the South, but under 5
from frontier and tariffs also the Rajan-Zingales index<sup>37</sup> measuring the dependence from extenrnal finance (Rajan and Zingales 1998). The results are reported in Table 13 and confirm that our main results appear not to be driven by financial constraints as the coefficient of the triple interaction is not statistically different from zero.

# 5 Conclusions

In this paper we have shown that it is important, when analyzing the impact of exogenous policy shocks, to take into account micro-level heterogeneity. We started from a stylized fact showing an increase in the industrial inequality after NAFTA was implemented, despite a substantial exit of less productive plants. In order to rationalize such result we developed a neo-Schumpeterian growth model predicting that the impact of liberalization is asymmetric across different types of firms, with “good firms” benefitting more from the increase in competitive pressures than “bad ones”. In this model , the liberalization tends to generate two competing effects: on one side it spurs more innovative efforts, because of the increased entry threat by foreign competitors. On the other side, enhanced competition curtails expected profits and reduces the resources available to nance innovative activities. The “pro-competitive effect” is weaker for less advanced firms as for them it is harder to catch-up with the “technology frontier”.

We tested the predictions from our theoretical model and confirm that indeed liberalization affected asymmetrical different types of firms. In particular, a 10 percent reduction in tariffs spurred average productivity growth between 4 and 8 percent. However, while for backward firms this effect is much weaker if not close to zero, otherwise for more advanced ones this effect is stronger with productivity growing between 11 and 13 percent. Furthermore we showed that, as a confirmation of the technology-channel, these results appear to be stronger in those sectors where the scope for the innovative activities is more pronounced.

These findings have various implications. In the context of the empirical debate on the relationship between trade liberalization and growth they suggest that we should not be surprised by evidence that the effects of liberalization vary across countries because this could just be the consequence that the distribution of productivity across countries before the reforms differ. Furthermore, for policy makers being aware of the possible heterogenous effects of the reforms is potentially even more important than knowing about the average impact of the reforms in order to devise appropriate

> 37This index is a proxy to characterize the degree of dependence from external funds of a specific sector (at 4 digits) and it is equal to the average ratio of capital expenditures not financed with internal funds over total capital expenditures during the 1980-1990.

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to 1986. Thus, both the volume and regional distribution of sector work has undergone significant change. There is a relative shift from Asia, the traditional stronghold of population activities, to other regions, and specifically to Africa.

# _._ ScoDe of Sector Reports

Table II-3 shcws the distribution of sector reports by title. Only 16 reports deal exclusively with population and/or family planning 4issues. The majority (ten) of these specialized population sector reports were completed by 1979. From Table II3, we see that the increase in the volume of PHN related sector work since 1979 has been mainly due to health, nutrition, and combined PHN reports. Only six sector reports completed after 1979 focus exclusively on the population sector.

# TABLE II-3

Distribution of PHN related sector and economic reports since 1969, by title and time period

|Title|<72|72-75|76-79|80-83|>83|Tbtal|
|---|---|---|---|---|---|---|
|AgReform<br>I|<br>0<br>|0|0|1|0|1|
|Eco<br>I|7|0|5|4|2|1<br>18|
|Fert/Region<br>l|0|0|0|1|0|I<br>1|
|Fert/Trends<br>I|<br>0|0|0|0|1|1<br>1|
|Food<br>I|<br>0|0|2|0|0|1<br>2|
|Food/Nut|.0|0|0|0|1|1<br>1|
|FPP<br>I|2|5|0|0|0|I<br>7|
|H<br>I|<br>0|0|2|2|5|1<br>9|
|HumCapital<br>l|0|0|0|1|0|1<br>1|
|H/N<br>l|0|0|0|1|0|1<br>1|
|P<br>I|<br>0|3|0|2|2|1<br>7|
|PHN<br>I<br>|<br>0|0|0|1|12|1<br>13|
|P/H<br>I<br>|<br>0|0|0|1|3|1<br>4|
|P/HumResourcesl|0|0|0|1|0|1<br>1|
|P/SocialServ l|0|0|1|0|0|1<br>1|
|Spatial<br>I|<br>0|0|1|1|1|1<br>3|
|----------------------------------------------------------|------------||||||
||9|a|11|16|27|71|

# Source: Internal Documents Unit

Among the population variables, population distribution has received less attention in sector analysis than the questions of population size and growth. Only three sector reports (Colombia, 1976; El Salvador, 1979; and Indonesia, :.984) provide detailed 16
# **Referencias**

Amador, D., Bernal, R., and Peña, X. (2013). The rise in female participation in Colombia: Fertility, marital status, or education? _Ensayos sobre política económica_ , Vol. 31, No. 71, pp. 54-63.

Angulo, A., and López de Rodríguez, C. (1975). Female participation in economic activity in Colombia. Population and Employment, Working Paper No. 9, World Employment Programme, Population and Employment Project, International Labour Organisation, Geneva.

Arango, L.E., and Posada, C.E. (2007). Labor Participation of Married Women in Colombia. _Revista Desarrollo y Sociedad_ , second semester, pp. 93-126.

Sonia R. Bhalotra, S.R.; Venkataramani, A.; and Walther, S. (2022). Fertility and labor market responses to reductions in mortality. NBER Working Paper 30316. http://www.nber.org/papers/w30316 Blau, F., and Kahn, L. (2007). Changes in the Labor Supply Behavior of Married Women: 19802000. _Journal of Labor Economics_ , Vol. 25, No. 3 (July 2007), pp. 393-438.

Brown S., Roberts J., and Taylor K. (2011) The gender reservation wage gap: Evidence from British panel data. _Economics Letters_ , Vol. 113, No. 1, pp. 88-91.

Buzawa, E.S., Buzawa, C.G., and Stark, E. (2017). _Responding to domestic violence: The integration of criminal justice and human service_ s (5th ed.). Los Angeles, SAGE.

Calderón, V., Gáfaro, M., and Ibáñez, A. M. (2011). Desplazamiento forzoso, participación laboral femenina y poder de negociación en el hogar: ¿Empodera el conflicto a las mujeres? Documentos CEDE 009252, Universidad de los Andes – CEDE Castañeda, T. (1981). La participación de las madres en el mercado de trabajo urbano en Colombia. _Revista Desarrollo y Sociedad_ , No. 6 (July), pp. 363-377.

Castro Torres, A.F., Urdinola, B.P. (2019). Armed Conflict and Fertility in Colombia, 2000–2010. _Population Research and Policy Review_ 38, pp. 173–213. https://doi.org/10.1007/s11113-018-9489- <u>x.</u> Cavalcanti, T., and Tavares, J. (2008). Assessing the "Engines of Liberation": Home Appliances and Female Labor Force Participation. _The Review of Economics and Statistics,_ Vol. 90, No. 1, pp. 8188.

De la Croix, D., and Doepke M, (2003). “Inequality and Growth: Why Differential Fertility Matters.” _The American Economic Review,_ Vol. 93, No. 4, pp.1091-113.

Doepke, M., Hannusch, A., Kindermann, F., and Tertilt, M. (2022). “The Economics of Fertility: A New Era”. _NBER Working Paper_ No. 29948.

29
the planned pillar 2 and 3. Therefore, no explicit fiscal liabilities are expected from these programs in future.<sup>1</sup> I

# **_Health financing is likely to grow, either directly or through contingencies_**

Similarly to social security, Bulgaria's government also legally guarantees its citizens' access to healthcare. Health care has been available free of charge to the population, costing the government budget around 4 percent of GDP. Since population aging often has a stronger impact on the cost of health care than pensions, the budget may expect increasing pressures. In this respect, health-financing obligation of the state is of direct nature. The government, however, has been considering a reform that would reduce direct budgetary health outlays, but introduce another, contingent portion of public financing in the new health system. Law on Health Insurance, which has established a National Health Insurance Fund to partly cover health care cost, formulates an obligation for the state to cover the Fund's possible future deficits as well as to pay contributions of all of the state employees as their employer. Table 6 shows expected sources of health financing in the reformed system.

**Table 6 Health Fund: Expected Revenues**

||19|99|20|00|20|01|
|---|---|---|---|---|---|---|
||_BGNmil_|_% ofGDP_|_BGN mil_|_%of GDP_|_BGN mil_|_% of GDP_|
|Health insurance contributions|257|1.2|577|2.4|650|2.5|
|o/w from government|97|_0.5_|<br>213|(.9|231|_0.5_|
|State budget|806|3.6|840|4.0|1,035|4.1|
|**Total**|1063|4.8|1417|_6.4_|1,685|6.6|

Source: Ministry of Finance.

Contingent government liability arising from the new arrangement will realize, should the NHIF face difficulties in collecting health contributions. Collection difficulties may arise from the complexity of the Fund's contribution structure. Contributions will be levied on the higher income family member, with additional amounts imposed for dependlents and other non-wage earners. The system would require detailed monitoring of family relationships and incomes. Collection and enforcement problems are particularly expected vis-a-vis non-cash compensations and self employed. Furthermore, the Fund is designed to contract health services with health providers. Thus, government's obligation to cover the Fund's deficits is likely to erode incentives in the entire health system and to become costly, also for ihe state budget. Initially envisaged for mid-1999, actual payments under the new system have been postponed to mid2000 in view of the above-mentioned implementation problems.

# **_2. Direct implicit Risks_**

# **_Public Investment Program may generate significant fiscal pressures_**

Bulgaria's Public Investment Program, first developed in 1998 for years 1998-2001, offers many positive features but also suffer from weaknesses experienced earlier by other 10 In the early stages of the new program design, we found it impossible to estimate any possible implicit liabilities that might arise from pillars 2 and 3.

20
<!-- Start of picture text --> BIF bn<br>1,200<br>1,000<br>800<br>600<br>400<br>200<br>2012 2013 2014 2015 2016 2017<br>——Baseline ——OP1 ——OP2 ——OP3 ——OP4<br><!-- End of picture text --> <!-- Start of picture text --> % change<br>80%<br>60%<br>40%<br>20%<br>0%<br>2012 2013 2014 2015 2016 2017<br>——Baseline ——OP1 ——OP2 ——OP3 ——OP4<br><!-- End of picture text --> <!-- Start of picture text --> 0%<br>20 2013 2014 2015 2016 2017<br>-2%5<br>-455<br>-635<br>-B%<br>-10%<br>-12%<br>-14%<br>——GBaselne ——OPL ——OP2 ——OP3 ——OP4<br><!-- End of picture text --> <!-- Start of picture text --> 65%<br>60%<br>55%<br>50%<br>45%<br>40%<br>35%<br>30%<br>2012 2013 2014 2015 2016 2017<br>——Baselinme ——OPL ——oOP? ——oOPS ——OP4<br><!-- End of picture text -->
# **_The Impact of Reform_**

The elimination of barriers to entry in services provoked a dramatic response from foreign and domestic providers (Gordon and Gupta, 2004). FDI inflows into services following liberalization by far exceeded those into other sectors. Ten percent of FDI inflows during 1990-2005 went into the transport sector, 9.6 percent of the inflows were into the telecommunications sector, and 9.6 percent of the inflows were into the financial and other services sector (Ministry of Commerce and Industry, 2008). At the same time, the services sector grew by an average of 11 percent per year, with the more liberalized sectors generally growing at relatively faster rates (Chart 1, and Eichengreen and Gupta, 2010). The share of services in overall value added rose from 39 percent in 1993 to 50 percent in 2004 (National Accounts Statistics, 2005, constant 1993 Rs).

Growth has been particularly strong in the services sectors on which we focus in this paper: communication services displayed average annual growth rates of 13.6 percent in the 1990s, while banking grew by 12.7 percent on average, transport grew at an average rate of 6.9 percent and insurance grew at a rate of 6.7 percent (Gordon and Gupta, 2004). Output per worker in the services sectors in India has increased by over 7.5 percent per year during the 1990s, clearly outpacing the agricultural or industrial sectors (Bosworth and Collins, 2008, p.56). Other evidence suggests that strong total factor productivity growth was at the root of this remarkable performance, not capital deepening or higher markups (Bosworth, Collins, and Virmani, 2006; Gordon and Gupta, 2004). Indeed, services prices decreased relative to manufacturing prices, as indicated by a slower pace of growth in the services deflator than the overall GDP deflator.

The reforms produced striking improvements in sectoral performance. In 1990, the average turn-around time for a container at major ports in India was 8 days, and at major Mumbai ports the average was 11. This meant that manufacturing companies exporting their products or importing inputs had to factor in more than a week of transit time for their goods, which increased the cash outlays necessary for exporting and importing. By 2005, the average turn-around time at major ports in India had decreased to 3.5 days, with 4.5 days as the average time at Mumbai ports (see Charts 2 and 3). This reduction in transit time is likely to have improved the ability of Indian firms to compete in highly variable markets such as textiles and electronics in which the ability to respond quickly to changes in demand is crucial.

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