rafmacalaba/datause-encoder-data huggingface dataset:
# 5. Does global inequality matter?

There are two views on this matter (as pretty much on everything else discussed here). One group of people believe that global inequality is irrelevant. There are two reasons why it may be so. According to Bhagwati (2004) even a calculation of global inequality is a ”lunacy.” It is a mere number. There is no “addressee’” to whom this mere number matters because there is no global government and there is no global civil society. According to this view, national inequalities matter because they become the stuff of political discourse; they are used to form political parties, platforms, to organize interest groups. But at the global level none of that exists because there is no global polity. Another reason adduced for the irrelevancy of global (or for that matter, all) inequality is that only changes in absolute income matter to the poor and the rich alike (Krueger 2002, Feldstein 1999). In words of Ann Krueger (2002) “Poor people are desperate to improve their material conditions...rather than to march up the income distribution [ladder].” Thus even if the absolute income gap between an average American and an average African increases, these authors are unconcerned. After all, they argue, the average African would be a bit less poor. This of course assumes that our income relative to the income of others does not matter. Yet this conclusion is at odds with psychological studies that invariably show that people do not care only about their absolute dollar income but also about where they stand in the social pyramid, and also whether they think this position to be fair (Graham and Felton 2005, Frank 2005).<sup>39</sup> Or—differently—global inequality may matter. On this side of the issue, there are also different approaches. For Pogge and Reddy (2002) and Singer (2002) global poverty and global inequality are ethical issues. Hence the rich world cannot disown all interest in global poverty and inequality: to some extent, the fate of every individual in the world affects us. Distributional justice within a nation and in the world as a whole are, from an ethical perspective, the same thing (see Singer 2002, Chapter 5).

> 39 Not surprisingly, rich people have less aversion to inequality (see for example, the results reported in World Bank, 2005, p. 84).

25
small, imprecisely estimated difference in hypothetical future use of the court for commercial disputes across the decree application cutoffs (cols 5 and 6, Table 9). Third, firms that underwent legal disputes after the reform have, on average, a more positive perception of the justice system (cols 7 and 8, Table 9).

Taken together, evidence from our firm survey reinforces our findings from tax filings: firms are willing to pay in order to secure the speed gains realized by the reform and that, if anything, perception of the justice system may have improved after the decree, suggesting net positive benefits of the reform on firms.

# **6.3 Robustness of the results**

We now discuss robustness of the firm results along two dimensions: robustness of the event study of starting pre-trial, and robustness to attrition in the tax records and firm survey relative to the court sample.

As discussed in Section 5.2.3, our main identifying assumption in estimating the impact of entering pre-trial on firm revenues is that entering pre-trial is the main source of variation in firm revenue in the year around the event and that, in the absence of a court case, firm revenues would have followed a steady trend, conditional on party and (month _×_ year) fixed effects. Hence, we consider threats to identification from four classes of selection issues: selection on level, selection on trend, selection on shock, and selection on trend shock. First, bias coming from potential selection on level is eliminated by the within-party differencing. Second, the event study graph allows us to rule out selection on pre-event trends, conditional on party and (month _×_ year) fixed effects. Third, selection on shock or selection on trend shock would introduce bias. The event being entering pre-trial, bias from selection on shock or trend shock would require that, for instance, the plaintiff targeted whom to sue and the timing of the case based on own or the defendant’s economic performance, or both, or on the expectation of a differential change in own or the defendant’s growth. If this were true, 28
# **[Insert Figure 8]**

# **4.2.3 Accompanying policies proposed by respondents**

Respondents were provided an opportunity to qualitatively identify accompanying policy measures that would lead them to support a reduction in subsidies that increased energy prices, and their answers reinforced the quantitative results showing that improvements in education and health care were top priorities. Over 60 percent of respondents identified a policy measure that would lead them to support a reduction in subsidies. From this group of respondents, it was possible to categorize around 90 percent of responses into 410 keywords and 25 themes using a similar approach to that of Ferrario and Stantcheva (2022); the results are presented across countries in a word cloud in Figure 9 (Appendix D provides details about the methodology and additional results). Around 40 percent of responses across countries referred to education or health care, and these were typically the most common keywords in each country (see Appendix D for details). Other popular keywords suggested support for the creation of employment and jobs, support for environmental policies (such as green energy alternatives like solar power), and support for policies that aim to assist poorer households (e.g., assisting with the cost of food). There were also broad suggestions about improvements in living standards, with one in six responses indicating a desire to see the government work “on the country,” “on the economy” or “for the people.”

# **[Insert Figure 9]**

The qualitative suggestions made by respondents who had only conditional support for subsidy reform differed substantially from the suggestions of those who had unconditional support. Keyness analysis<sup>15</sup> was conducted by examining the relative frequency of themes

> 15Keyness analysis is a corpus-based procedure that identifies the frequency of terms across two groups. Keyness analysis uses a Chi-Squared value to consider both the size and statistical significance of the frequency difference. It compares the difference between the actual frequencies observed in the corpus and the frequencies we would expect if no factor other than chance had been operating to affect the frequencies.

34
# **C.   Credit Cycles**

Figure II-3 shows our estimated medium-term cyclical component of fluctuations in real credit growth (solid line) compared to the real growth of credit (dashed line) across all the countries. The differences between the solid and dashed lines are the components of credit growth that fall into the short- and long-term frequencies: shorter than 6 years and longer than 15 years. As is evident in the figures for Saudi Arabia and Egypt, the medium-term cycle is much less synchronized with the real credit than what we observe for the United States. As Figure VI-7 in the appendix shows the fluctuations of medium and short-term credit cycles are of the same importance for all the Western countries and Japan in our sample, and this importance is more for short-term cycles for many of the countries in MENA (Bahrain, the Islamic Republic of Iran, Kuwait, Algeria, Libya, etc.).

**Figure II-3: Real Credit Growth and Medium-term Credit Cycle**

<!-- Start of picture text --> Saudi Arabia: Real Credit Egypt: Real Credit<br>(in percent) (in percent)<br>1967 1977 1987 1997 2007 2017 1967 1977 1987 1997 2007 2017<br>year year<br> Medium-term cycle Real credit growth (y/y) Medium-term cycle Real credit growth (y/y)<br>60<br>100<br>40<br>50<br>20<br>0 0<br>-20<br>-50<br><!-- End of picture text --> <!-- Start of picture text --> USA: Real Credit<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term cycle Real credit growth (y/y)<br>15<br>10<br>5<br>0<br>-5<br>-10<br><!-- End of picture text --> 8
purpose vehicles (SPVs) to finance infrastructure investments, which carry “inherent” risks as they often circumvent borrowing limits and create contingent liabilities.

Regression analysis using time series data through the 1990s for seven large federal countries (Argentina, Australia, Brazil, Canada, Germany, India, and the United States) reveals that subnational government finance is overwhelmingly pro-cyclical, implying that the behavior of state governments in the United States is not an exception but the general rule (Rodden and Wibbels 2010). Only Canada was found to be engaged in harmonized expenditure smoothing in that decade.

In the recent crisis, other countries also harmonized their policies. China, with its combination of high savings and large fiscal space, provides an important example of a countercyclical subnational response (Ter-Minassian and Fedelino 2010; Fardoust, Lin, and Luo 2012). Expansionary subnational government spending played a key role in strengthening the overall impact of the stimulus and sustaining economic growth. A less dramatic example is India, where the central government eased borrowing constraints on state governments in 2009 and 2010.

Global economic growth recovered in 2010 but slowed in 2011. Serious concerns have emerged that the relatively fast-growing economies are also beginning to experience a downturn. In view of these trends, the IMF’s 2012 assessments recommend a gradual fiscal adjustment, cautioning governments against drastic cuts in their deficits and spending, lest they exacerbate the contraction. This advice is based on the conclusion drawn from empirical studies that the “fiscal multiplier” is especially large during times of crisis.

Over the past decade, subnational spending as a share of government spending increased in many federal countries (Ter-Minassian and Fedelino 2010). The change has important implications for the size of fiscal multipliers and their impact on the national economy and for policy/institutional reform for improved coordination across government levels in implementing a harmonized crisis response.

This paper is a follow-up to a research project carried out at the World Bank on the macroeconomic impact of the Great Recession in developing countries. The results of that project, which focused on the macroeconomic events of the 2008–09 crisis and national 5
2% for girls; in rural area, child working rate has decreased from 15% to 13% for boys and from 12% to 10% for girls.

Another competing “activity” for children against schooling is being “inactive”, meaning not being enrolled in school or formally in the labor force based on the definition described earlier. The rate of being “inactive” decreased from 1998/1999 to 2005/2006. In urban areas, the rate of being inactive decreased from 16% to 13% for boys and from 25% to 23% for girls; in rural areas, the rate of being inactive decreased from 20% to 16% for boys and 52% to 41% for girls.

Child labor and schooling decision varies with age and sex, which is illustrated in Figure 2. Children are less likely to go to school when age increases, for both girls and boys. Conversely, children are more likely to work when age increases, especially for boys. However, when they get older, girls are more likely to be inactive and boys are less likely to be inactive. The relationship is quite smooth without significant drop around 12 – 14 years old at which age children are supposed to transit to middle school. This is primarily because many poor children in Pakistan start school fairly late; thus they do not necessarily transit to middle school when they are 12-14 years old.

# **_5.3. Child Labor by Employment Status_**

The employment status is very different between urban and rural areas for both working boys and girls. In rural areas, working children are more likely to be unpaid workers but in urban areas they are more likely to be paid workers. Table 2 shows the descriptive statistics. Take the most recent survey in 2005/2006, in rural areas about 67% of working boys are unpaid family workers and about 33% are paid workers; however, in urban areas about 78% of working boys 11
# **References**

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16
# **CHAPTER 3:  USERS OF FINANCIAL SERVICES AND PROFILE OF THE UNBANKED**

1. This chapter presents the demand side perspective of financial exclusion in Bogotá.  To this end, the chapter draws on data from several sources. The introductory part is drawn from the results of a nationwide survey by the Colombian Association of Media Investigation (ACIM).  The presentation of the socio-economic characteristics of the unbanked is the result of a joint household survey by the Colombian government’s department of statistical studies, DANE, the World Bank and Universidad de los Andes.

2. ACIM carried out a household consumer survey (the General Media Survey or EGM, acronym in Spanish) through the National Consulting Center in 2000. A section of the survey centers on the possession of financial services. The survey was applied to 12,218 households in 16 of Colombia’s most important cities: Bogotá, Barranquilla, Cartagena, Medellín, Pereira, Manizales, Cali, Popayán, Ibagué, Bucaramanga, Neiva, Cúcuta, Villaviciencio, Santa Marta, Armenia and Tunja. This sample is representative for a population of 11,850,560 inhabitants and was extrapolated to the total population. The survey tabulated use of: savings and checking accounts, credit and debit cards, certificates of deposit (CDT), mortgages, personal credit, banking services by telephone, savings account with special awards, stocks and bonds.

3. Financial services, whether provided by banks, by cooperatives or by micro-finance institutions, reach a very limited percentage of Colombia’s urban population. The ACIM survey, which covered 16 Colombian cities, suggests that the percentage of unbanked increases outside of Bogotá. Figure 3.2 shows the percentages of households using different types of financial services. Considering the unbanked to be households without access to savings accounts, the ACIM survey suggests that the unbanked in urban Colombia reach close to 70%. A similar survey by the same company, in Mexico, reported findings of unbanked households at 85%.

4. The DANE survey, applied to a representative sample of 1,600 Bogotá households in 2002, was sponsored by the World Bank, but designed and implemented by the Center for Economic and Development Studies in the University of Los Andes (CEDE) in conjunction with the National Administrative Statistics Department (DANE)’s program of Household Surveys (ECH).

5. In this study the term ‘banked’ refers to households and to individuals who maintain deposits (savings, checking or CDT account) in some formal sector financial institutions, including commercial and social interest banks, regulated cooperatives and credit unions (these last 45
||(0.028)|(0.028)|
|---|---|---|
|N|919|904|
|R-sq|0.183|0.182|
|F-test of instruments (p-value)|0.000|0.000|
|Hausman test (p-value)|0.999|0.977|
|Hansen J -test of overidentifying restrictions (p-value)|0.615|0.796|
|Country fixed effects|N|N|
|Time fixed effects|N|N|
|_Panel B_|(1)|(2)|
|Non-deposit funding|-41.004**|-39.635**|
||(16.639)|(16.986)|
|Assets|-1.056|-1.031|
||(0.659)|(0.667)|
|Equity|13.294|10.004|
||(9.707)|(9.961)|
|Assets growth|16.741**|15.660**|
||(7.397)|(7.080)|
|Overhead|-63.889**|-51.935**|
||(25.261)|(20.717)|
|Inflation|-39.978|-50.142|
||(35.678)|(48.896)|
|GDP growth|-92.731*|-101.761*|
||(51.868)|(57.128)|
|GDP per capita|0.636***|0.608***|
||(0.070)|(0.077)|
|_First-stage_|0.012|0.016|
|Instrumental variables|0.137|0.02|
|Investment bank dummy|0.164***|0.148***|
||(0.019)|(0.019)|
|Non-bank credit institution dummy|0.226***|0.248***|
||(0.025)|(0.025)|
|Other dummy|0.002|-0.004|
||(0.025)|(0.025)|
|N|918|902|
|R-sq|0.115|0.109|
|F-test of instruments (p-value)|0.000|0.000|
|Hausman test (p-value)|0.645|0.703|
|Hansen J -test of overidentifying restrictions (p-value)|0.135|0.020|
|Country fixed effects|N|N|
|Time fixed effects|N|N|

54
43 Table 7 gives the results of regression (11). The fourteen independent variables, capturing the effects of quality differences, license holding concentration, quota size, quota utilization ratio and fashion risk, explain some 90 per cent of the variation in the price differential. The intercept is substantial -- almost $14 -- and it is statistically significant at the 20 per cent level. The quota utilization rate is significant at the 1 per cent level -- all else constant, a 10 per cent increase in the utilization rate closes the price gap by about $0.50. As rationalized earlier, a high quota utilization rate, all else constant, makes import licenses more scarce; this drives up the license price, which in turn drives up the Hong Kong price. The coefficient on the numbers equivalent is negative but not significant. The coefficient on the quota level is inexplicably negative, although it, too, is not significant.

The effect of the fashion proxy appears to be the opposite of what was expected. Note that fashion items may also be better quality items. For example, Yeung and Taylor (1989) conclude from their survey of Hong Kong apparel manufacturers that: "From the buyer's point of view, more fashionable items denoted special quality consideration. J.C. Penney, Sears and The Gap demand high quality."<sup>20</sup> The apparel group dummies capture these fixed quality effects, so that the fashion proxy represents the risk effect alone. This risk effect turns out to be insignificant. The "risk" story may not be applicable to Hong Kong anyway. since the Hong Kong apparel manufacturers pride themselves on their adaptability and quick response to market changes.
four countries, providing evidence that more productive firms (‘good’) are ‘taxed’ more. Interestingly, the bulk of these misallocations across firms of different productivity levels arise largely due to frictions in the output market. The misallocation due to factor market friction has a fairly modest effect on more productive firms.

We also find evidence that the measured distortions are correlated with various measures of business environment, and suggest that these are likely to play an important role explaining the pervasive resource misallocation. These findings suggest that paradoxically, while industrialization and productivity growth in manufacturing are important policy objectives in these countries, the misallocation induced by uneven regulations and poor business environment are undermining a larger contribution of manufacturing in these economies. Improving the business environment should, therefore, be a priority for policy also from an industrialization point of view.

Our analysis has abstracted from many factors which may be worth exploring further. First, our analysis covers firms in the manufacturing sector, ignoring non-manufacturing sectors. Distortions affecting firms in the manufacturing sector may have potential economy-wide implications though linkages in the input-output network with other sectors. An interesting future research area will be to assess the extent of misallocation in a multi-sector framework by accounting for all the potential linkages between sectors. Second, although we attempted to make a connection between various business environment measures and resource misallocation, establishing this relationship with robustness requires firm-specific policy variation of the cost of doing business, which constitutes a profitable area for future research.

# **References**

- Acemoglu, D. and Dell, M. (2010). Productivity differences between and within countries. _American Economic Journal: Macroeconomics_ , 2(1):169–188.

- Ackah, C., Adjasi, C., and Turkson, F. (2014). Scoping study on the evolution of industry in ghana. Technical report, WIDER Working Paper.

- Allcott, H., Collard-Wexler, A., and OConnell, S. D. (2015). How do electricity shortages affect industry? evidence from india.

- Altenburg, T. (2010). Industrial policy in ethiopia.

- Asker, J., Collard-Wexler, A., and De Loecker, J. (2014). Dynamic inputs and resource (mis) allocation. _Journal of Political Economy_ , 122(5):1013–1063.

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- Brownbridge, M. and Gockel, A. F. (1996). _The impact of financial sector policies on banking in Ghana_ . Institute of Development Studies.

31