rafmacalaba/datause-encoder-data huggingface dataset:
# **Changing demographic structure**

As countries develop, they go through a demographic transition (Figure 6). The initial phase of development is accompanied by improvements in health, which reduces infant and child mortality and increases life expectancy (Pritchett and Summers 1996). Fertility decline typically follows, but with a lag (Lee 2003) for a host of reasons, including improved survival of children, preference for fewer children, focus on _quality_ rather than _quantity_ of children, higher opportunity cost of childbearing and childcare, and potentially the availability of contraceptives. This means that countries undergo a youth bulge as they develop. Developed countries are far ahead in this transition, and their populations have stabilized (or are even declining) with the trend expected to continue. By contrast, developing countries are experiencing various stages of a demographic transition with some experiencing a youth bulge and others nearing a fall in their populations.

## **Figure 6 The share of children falls and the share of the elderly increases with development**

_Sources_ : Original calculations based on demographic data from UN DESA 2022 and GDP data from the Penn World Tables (PWT) 10.0 (Feenstra, Inklaar, and Timmer 2015).

_Note_ : The figure show the relationship between the population shares of children (ages 0–14) and the elderly (ages 65+) and GDP per capita. Each line on the background traces the evolution of population shares and GDP for each country between 1960 and 2020. The solid lines in the foreground plot the smoothened locally linear estimate pooling all countries and years between 1960 and 2020. CI = confidence interval.

The demographic transitions that accompany development, by themselves, can create demand for and supply of migrant labor. Developed countries tend to have an aging population and workforce, which increases the demand for younger workers in the economy. In addition, an aging populace increases the demand for care services, which can further fuel migrant demand. On the other hand, less developed countries, early in their demographic transition, may face increasing competition for economic opportunities for youth, who may seek opportunities abroad (Hatton and Williamson 2002). Taken together, these forces can lead to increases in emigration from low-income countries as they develop, fueled by the increased supply of potential migrants, as well as the increased demand from aging high-income countries.

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The latter two motives were responsible for the creation of Transparency International’s widely-cited “Corruption Perceptions Index,” and subsequently WBI’s “Control of Corruption” index (Kaufmann, Kraay and Mastruzzi, 2005). Although the statistical methods vary somewhat, both of these indexes standardize corruption indicators from numerous sources to place them on a comparable scale, and compute an average (unweighted for TI, weighted for WBI) of them to obtain one value for each country. Missing values on any indicator for a given country are ignored, so are in effect imputed as the average of all indicator values for which data are available for the country. By this procedure, an index value can be computed for any country with data available from even one of the many sources used.<sup>13</sup> The original purpose for the TI index was to raise awareness of corruption, and to provide researchers with better data for analyzing the causes and consequences of corruption. It has achieved these goals in spectacular fashion, and is regularly cited in news reports on corruption around the world. The WBI index, appearing several years after the TI index, was intended by its authors to improve and expand on TI in several ways. First, the WBI index provides a value for any country with data available from even one source, while the official TI index requires three sources. Second, the WBI index incorporates data from more sources, including ICRG and others which TI rejects on various grounds (Lambsdorff, 2005a). Third, using many of the same data sources, WBI constructs five other broad “governance” indexes.<sup>14</sup> Fourth, WBI weights available sources differently, in contrast to the equal weighting in TI of available sources for each

> 13 The index on TI’s web site lists only countries for which three or more data sources are available.  The index on Johan Lambsdorff’s web site lists index values for all countries with available data on one or more sources.  Lambsdorff is the creator of the TI index.  See  http://www.icgg.org/corruption.index.html 14 These five include Rule of Law, Voice and Accountability, Political Stability and Violence, Regulatory Quality, and Government Effectiveness.

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4 from domestic firms in this political market. Thus, lobbyists do not need to play zero- or negative-sum rent-shifting games, as is the case of protectionism. Rather, foreign lobbying takes the form of conveying information.

The link between tourism and development is relevant and empirically well-documented. That tourism promotes economic growth is confirmed in Dritsakis (2004) for Greece, Balaguer and Cantavella-Jordá (2002) for Spain, Oh (2005) for Korea, Durbarry (2004) for Mauritius, and Tosun (1999) and Guduz and Hatemi (2005) for Turkey. Cross-country studies by Sequeira and Campos (2006) and Brau, Lanza and Pigliaru (2003) demonstrate that tourism-specialized countries grow more than others. Sinclair’s (1998) survey indicates that the main channel by which tourism helps growth is from the provision of foreign currency which can finance imports of capital goods. Further, since tourists consume goods with high domestic content, their arrival benefits domestic manufacturing and service sectors. Tourism boosts government revenues generated by taxes on incomes from tourism employment and tourism businesses, and by direct levies such as departure taxes. In sum, promoting tourism appears to be good for growth and development. We find that to be compelling motivation for our study.

The paper proceeds as follows. Section 2 provides important background information about foreign lobbying institutions in the US. In Section 3 we view foreign lobbying in tourism as a mechanism for resolving informational asymmetries. We supply primary survey evidence in support of this idea. Section 4 describes the data and panel econometric models we use to study the impact of informational lobbying on tourism. Section 5 discusses the empirical results. Section 6 concludes.

# **2. Foreign Tourism Lobbying in the US**

The data set used in the estimation of our empirical model was assembled using reports that FARA requires the US Attorney General to make available to Congress. The report collects information about foreign agents operating within the United States. A foreign agent, in the view of the US Department of Justice, is somebody who (a) engages in political activities or acts in a public relations capacity for a foreign principal, (b) solicits or dispenses anything of value within the United States for a foreign principal, or (c) who represents the interests of a foreign principal before any agency or official of the US government. Each entry in the FARA annual reports contains (i) the name and address of the foreign agent, (ii) the name of the foreign
In some cases, the peace might fail soon after the two-year cutoff point and as with many interventions, we would expect the benefits of UN missions to be concentrated in the short run. In the long run, new challenges develop that can undermine the peace that may be unrelated to the previous war or to the peace process. But countries that have had some UN assistance during their peace processes should have a better chance at achieving self-sustaining peace, largely because of the much needed help they receive in the critical first years of their transition from war.

Survival analysis can be used to analyze the duration of the peace in the longer term. Survival models estimate the “hazard” (or risk) of peace failure at time t given that failure has not occurred until then and it can account for right-censoring (the fact that the peace has not failed up to the end of analysis time does not mean that it cannot fail afterwards).<sup>33</sup> The dependent variable ( _peace duration_ ) is coded as a continuous variable in months, counting from the start of the peace process until the peace fails or up to a censoring point, at the end of December 1999. Peace failure implies that a new civil war starts in the country. This is a departure from the complex definition of participatory peace used up to this point. We now focus on war recurrence (we discuss the duration of participatory peace in our supplements). We begin with the same single-record singlefailure dataset used this far and then switch to a time-series cross-section (TSCS) version of the data. The model must by necessity be somewhat different for the TSCS data analysis since we could not code time-series for all the variables from the original model.

# _War Recurrence as Peacebuilding Failure_

Our analysis of the long-term effects of UN missions focuses on the negative definition of peace as the absence of war. This is a fairly common standard in the literature (cf. Fortna 2004) that we use because our measure of participatory peace cannot be coded accurately as a continuous variable. There are no reliable data on levels of residual violence over time and levels of political openness can vary over time, so it is theoretically possible that some cases would “fail” according to our participatory peace measure, then “succeed” a few years later, and then “fail” again if their polity score dipped below our threshold. Coding undivided sovereignty is also tricky without some 33 For a methodological discussion, see Box-Steffensmeier and Jones (2003).

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# References

Adams Jr., R. (2004). Economic Growth, Inequality and Poverty: Estimating the Growth Elasticity of Poverty. _World Development_ 32(12): 1989-2014.

Aghion, P. and Bolton, P. (1997). “A Theory of Trickle-Down Growth and Development”. _Review of Economic Studies_ 64: 151-172.

Anderson, M. (2008). “Multiple inference and gender differences in the effects of early intervention: A reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects”. _Journal of the American statistical Association_ 103(484): 1481–1495.

Annual Development Effectiveness Review 2013. Towards sustainable growth for Africa Barro, R. (1991). “Economic Growth in a Cross Section of Countries”. _The Quarterly Journal of Economics_ 106(2): 407-443.

Batuo, M., Kararach, G., and Malki, I. (2022). The dynamics of income inequality in Africa: An empirical investigation on the role of macroeconomic and institutional forces. World Development 157: Bénabou, R. (1996). “Inequality and Growth”. In Bernanke, B. and Rotemberg, J. (eds). National Bureau of Economic Research Macroeconomics Annual, Cambridge: MIT Press.

Benjamini, Y., Krieger, A., and Yekutieli, D. (2006), “Adaptive Linear Step-up Procedures that Control the False Discovery Rate,” _Biometrika_ , 93, 491–507.

Berardi, N. and Marzo, F. (2017). “The Elasticity of Poverty with Respect to Sectoral Growth in Africa”. _Review of Income and Wealth_ 63(1): 147-168.

Bergstrom, K. (2022). “The Role of Income Inequality for Poverty Reduction”. _The World Bank Economic Review_ 36(3): 583-604.

Bourguignon, F. (2003). “The Growth Elasticity of Poverty Reduction: Explaining Heterogeneity across Countries and Time Period”. In: Eicher, T. and Turnovsky, S., Eds., _Inequality and Growth, Theory and Policy Implications_ , The MIT Press, Cambridge.

Chambers, D. and Dhongde, S. (2011). “A Non-Parametric Measure of Poverty Elasticity.” _Review of Income and Wealth_ 57(4) Chancel, L., Cogneau, D., Gethin, A., Myczkowski, A., and Robilliard, A.S. (2023). “Income Inequality in Africa: 1990-2019: Measurement, patterns, determinants. _World Development_ 163(3): Christiaensen, L. and Hill, R. (2019). “Poverty in Africa”. In: Beegle, K. and Christiaensen, L. (2019). “Accelerating Poverty Reduction in Africa”. Washington DC: The World Bank.

Corral, P., Irwin, A., Krishnan, N., Gerszon Mahler, D. and Vishwanath. T. (2020). Fragility and Conflict: On the Front Lines of the Fight against Poverty. Washington, DC: World Bank.

Dabla-Norris, E., Kochhar, K., Suphaphiphat, N., Ricka, F. and Tsounta, E. (2015). “Causes and Consequences of Income Inequality: A Global Perspective”. _IMF Staff Discussion Note_ SDN/15/13. Washington DC: The International Monetary Fund.

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“ _The absence of a new economic philosophy that integrates economics and finance has been a great failing._ ” Henry Kaufman<sup>2</sup> “ _During normal times prices can be trusted to reflect the “wisdom of the crowds.” During times of distress, investors react instinctively and emotionally: the wisdom of crowds becomes the “madness of mobs._ ” Andrew W. Lo<sup>3</sup>

# **1. Introduction**

A series of insightful papers by Crockett (2000) and Borio (2003) in the aftermath of the East Asian crisis reached the important conclusion that the conditions for financial systems’ stability do not necessarily coincide with those for individual financial institutions’ stability. Quite the contrary, the pursuit of the latter often generates destabilizing externalities on the system as a whole. They dubbed micro-prudential the traditional focus on individual intermediaries – prone to the fallacy of composition – and macro-prudential the complementary approach – able to combine the stability of individual institutions with a systemic perspective. An integration of the two approaches – a marriage – was strongly recommended.

Yet, the decade separating the East Asian from the Subprime crisis has been dominated more by the traditional micro-prudential approach, embedded in the Basel II capital accord, than by the development of a new macro-prudential mindset, let alone an integration of the two. Only the effects of the dramatic financial crisis of 2007 and its legacy of lingering financial instability has brought macro-prudential supervision and surveillance to the center of the academic and policy debate and led to the establishment of macro-prudential oversight units within financial supervisory authorities worldwide (Banca d’Italia, 2009; Bank of England, 2009).

The question is then: Why did it take so long for the micro and the macro-prudential dimensions of financial stability to come together? Why does the marriage – so clearly announced more than 10 years ago – take place only now? I argue that the delay largely

> 2 Financial Times, June 1, 2010. 3 Financial Times, October 1, 2009.

2
world _individuals_ ) because the number of people who live in various countries is taken into account even if they are all assumed to have the average income (GDP per capita) of their country. This assumption is abandoned in global inequality (or Concept 3) which calculates inequality across world citizens, taking in principle everybody’s actual income into account.

When going from Concept 2 to Concept 3 inequality, another important methodological change occurs, namely while Concept 1 and 2 are calculated from national accounts data, Concept 3 inequality can be calculated only from household surveys (since this is the only source for national income inequalities which are needed to get to Concept 3 inequality).<sup>10</sup> This creates two problems: national accounts and household survey means do not always coincide and have moreover recently been in many countries moving apart<sup>11</sup> ; and second, household surveys for a sufficiently large number of countries (such that they would cover more than 90% of world population and 95% of world income) are available only from the late 1980s onward. They are also not available at annual intervals for most countries, thus necessitating the use of benchmark years, say spaced at 5-year intervals (so that all countries that have had surveys within that interval are included).

With these caveats in mind, we proceed to the calculations. Figure 1 shows the calculations of Concept 1 and Concept 2 international inequality for the period 19522006.

> 10 We obviously cannot calculate Concept 3 from national accounts; but we can calculate  Concepts 1 and 2 from household surveys. The reason why the alternative approach is preferred is that it enables us to have a much longer time series, since national accounts (unlike household surveys) are available for most countries in the world for the last 50 years.

> 11 For discussion see  Ravallion (2000), Deaton (2005), Anand and Segal (2008).

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# Table 4. Subsidies to Natural Gas (billion US $)

|Sectors:|Power|Industry|Trans|Agr|Comm|Res|Total|Pd/p"I|
|---|---|---|---|---|---|---|---|---|
|Former USSR<br>Chlki|20.0|21.0|1.0|1.0|7.0|13.0|63.0|0.12|
|zecosovaa<br>Vl|||||0.35|0.11|0.46|0.85|
|enezuea<br>Mi|0.4|1.0<br>||||0.35|1.75|0.15|
|exco<br>E||0.3||||0.3|0.6|0.85|
|gypt<br>I|0.35<br>||||||0.35|0.48|
|ran<br>Ri|0.7<br>|0.6<br>||||1.0|2.3|0.05|
|omana|0.2|0.2||||0.4|0.8|0.84|
|Total<br>Source: Author's calc|21.65<br>ulations.|23.1|1.0|1.0|7.35|15.16|69.26||

I/Ratio of weighted average domestic prices to world prices.
Policy ReseaRch WoRking PaPeR 4449

# **Abstract**

This paper estimates the impact of registering for taxes on firm profits in Bolivia, the country with the highest levels of informality in Latin America. A new survey of micro and small firms enables the authors to control for a rich set of measures of owner ability and business motivations that can affect both profits and the decision to formalize. The paper identifies the impact of tax registration on business profitability using the distance of a firm from the tax office where registration occurs, conditional on the distance to the city center, as an instrument for registration. Proximity to the tax office provides firms with more information about registration, but is argued to not directly affect profits. The findings show that tax registration leads to significantly higher profits for the firms that the instrument affects. However, there is also evidence of heterogeneous effects of tax formality on profits. Tax registration is found to increase profits for the mid-size firms in the sample, but to lower profits for both the smaller and larger firms, in contrast to the standard view that formality increases profits. The analysis shows that owners of large firms who have managed to stay informal have higher entrepreneurial ability than formal firm owners, in contrast to the standard view (correct among smaller firms) that informal firm owners have low ability.

This paper—a product of the Finance and Private Sector Development Team, Development Research Group—is part of a larger effort in the department to study the causes and consequences of informality. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at dmckenzie@worldbank.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
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# 4.1 Pakistani textile industry

We tested the joint hypotheses "unexerted market power, partial or no tax shifting" and "perfect competition, no tax shifting" against each other by implementing a pair of non-nested hypothesis tests. Table (1) reports the results from these tests.

Table **M11** Pakistani textile **industry** Results from the non-nested hvnothesis tosts

|Specif.|Ho: perfect<br>partial|competition,<br>or no tax shifting|HO:unex<br>no t|erted market power,<br>ax shifting|
|---|---|---|---|---|
||10|t|.|t|
|WI=WL|0.974|18.53 Ho reiected|0.0219|0.566Honot rej.|
|1 =WM|0.965|2.68 Ho reiected|0.000181|0.896 Ho not rej.|

These results suggest quite strongly that the joint hypotheses of perfect competition and no tax shifting have to be rejected in favour of the hypotheses of market power and partial or no tax shifting. Making the conventional assumption of perfect competition for the textile industry of Pakistan would thus have involved a mis-specification of the econometric model, since the hypothesis of perfect competition was rejected quite decisively for this industry. However, even though our results indicate that the firms of the Pakistani textile industry had market power during the sample period instead of being perfectly competitive, the firms did not succeed completely in shifting the CIT forward in the short run. Therefore the parameters of the CIT entered the expression for the rental price of the services from physical capital, so that tax incentives had an effect on the user cost of capital of firms in this industry during the sample period.

To give an idea of the quality c- the estimation results, we report in table (2) below the elasticities of the demand for labour and for materials with respect to changes in the input prices for the mid-point of the sample. The results of table (2) show that both own-price elasticities have the correct