rafmacalaba/datause-encoder-data huggingface dataset:
LAC still has a long way to go in raising the sophistication of its institutional investors, as most of the savings are still channeled to government bonds and bank deposits.

# **7.1. Main Financial Intermediaries**

Although banks continue to play a significant and stable role, nonbank financial intermediaries, such as pension funds, mutual funds, and insurance companies, have been gaining considerable space in LAC7 countries and in other emerging markets around the world (figure 20). For instance, pension fund assets represent 19 percent of GDP in LAC7 countries and 15 percent in Asian countries, while mutual funds and insurance companies are usually larger on average in Asian countries than in LAC7 countries. Eastern European countries have smaller but also fastgrowing institutional investors. As with most other features of the markets examined so far, these intermediaries are still smaller on average in LAC7 countries than in developed countries, reflecting, to some extent the developed countries’ advanced financial systems.

The size of each type of institutional investor varies among LAC7 countries, reflecting, in large part, differences in their institutional and regulatory environments. On average, pension funds in LAC7 countries are usually the largest institutional investors (20 percent of GDP), with mutual funds averaging 10 percent of GDP and insurance companies averaging 6 percent. In contrast, in Chile pension funds reach almost 70 percent of GDP, while mutual fund assets are 15 percent of GDP and insurance company assets are 19 percent of GDP. Mutual funds in Brazil are the largest institutional investors (42 percent of GDP) with significantly smaller percentages for insurance companies (8 percent) and pension funds (16 percent).

Due to data availability, we can get only a glimpse of the private equity and venture capital funds. These funds, through which investors acquire a percentage of an operating firm, are particularly important for the financing of SMEs. Unsurprisingly, however, private equity and venture capital funds are still relatively underdeveloped in LAC countries. Private equity funds raised on average US$4.9 billion per year in LAC, a strong contrast to the almost US$46 billion raised in Asia between 2003 and 2009.<sup>21</sup> Moreover, over the same period LAC represented only 1.1 percent of total worldwide private equity fund raisings, compared with almost 10 percent for Asian countries, with the rest taking place in the United States and in Europe. Venture capital funds are even less represented in emerging markets in general, with a total of US$12 billion per year raised on average outside the United States and Europe during

> 21 These statistics are from Preqin, the industry’s leading source of information where country-level information is not available. Therefore, regional statistics cited include all countries geographically located within each region, making them different from the rest of this paper.

26
> - **16** -

1988). Thus rising agrkcultural productivity may be Instrumental In ducng a structural transformation of the rural nonfarm economy.

# S. Prior EvIdence

_23._ Not all analysts have expressed ccnfidence In the prospects for agriculturalled growth. In a provocative and often-cited revIow, Vyas and Mathal (1978) argue that agricultural growth has not In fact stknulated development of the rural nonfarm economy. Using the population census data reproduced In Table 1, they point out that the nonfarm share of rural and urban employfment remained unchangod between 1961 and 1971. In their viow, skewed Income gains In agriculture lhited consumption linkages, while Inadequate rural Infrastructure lknlted the ability of rural firms to supply the modest Increases In Input and consumer demands.

24. Yet most subsequent analyses -- based on longer the series or disaggregated at the state of district level -- disputo Vyas and Mathals posshulstlc concluslon.<sup>8</sup> Tkne sories ovidence from fast-growing agricultural states document the strongest connections between agriculture and the nonfarm economy (Chadha, 1986a). Studies of the Punjab (Chadha, 1986b; Bhalla, et al. 1989) and Haryana (Bhalla, 1981) all highlight the knportance of rising demand for consumer goods and agricultural Inputs as the result of Increased agrIcultural production. Chadha, In particular, emphasIzes the Importance of farm machinery and other Input supply In the Punjab. He notes that whilo state manufacturlng grew at the same rate as agriculture In the 19609. It grew much faster than agriculture In the 19709. Because of first-mover advantages, he believes, machinery manufacture established to supply Its own state agricultur6 stood poised to export to other states In the 1970s. If so, these spilovers caution that IdentifyIng the spatial distributlon of agricultural growth llnkages may be complex.

a The **most** direct **ebuttal, based** on longer **time** _rio, **come** fron **Doehpand.** and **Le.hpand. (1965).**
Figure 1: Model Baseline <!-- Start of picture text --> Allocation of Land Land Based GHG Emissions<br>6 200<br>9<br>8 4 150 Natural Land<br>7 Protected Forests 100 Conversion<br>6 Unmanaged Forests 2 50 Livestock<br>5 Managed Forests 0 0 Biofuels' Offsets<br>43 Pasture LandBiofuel Crops -2 -50 Use of Fertlizers<br>2 Livestock Feed -100 ForestSequestration<br>1 Food Crops -4 -150 Net GHGAccumulation<br>0 -6 -200<br>2005 2030 2055 2080 2105 2005 2030 2055 2080 2105<br>Land Based Goods and Services Consumption of Biofuels<br>600 40%<br>1800<br>1600 500 35%<br>1400 30% Consumption of 2g<br>1200 Ecosystem Sevices 400 25% Biofuels<br>1000800 Processed TimberEnergy Services 300 20% Consumption of 1gBiofuels<br>600 Processed Livestock 200 15% Share of Biofuels in<br>400 Processed Crops 10% Liquid Fuel<br>200 100 Consumption<br>5%<br>0<br>2005 2030 2055 2080 2105 0 0%<br>Note. Real terms, base year =2004 2005 2030 2055 2080 2105<br>Billion Ha GtCO2e/yr GtCO2e<br>Million toe<br>USD per person<br><!-- End of picture text --> 150 million hectares, whereas pasture land declines, losing 120 million hectares by 2035. Managed and unmanaged forest areas decline by 3 million and 205 million hectares respectively. Changes in areas dedicated to biofuels feedstocks and protected natural forests remain insignicant. By mid-century, slower population growth, rising real income, shifting diets, and technology improvements in food processing, storage and transportation result in a decline in demand for food crops. By 2100 area dedicated to food crops falls to 1.25 billion hectares, which is 12 percent lower than in 2004. Improvements in crop technology and agricultural yields result in greater intensication of livestock production. Pasture land continues to decline, reaching 2.33 billion hectares, which is 15 percent smaller than 2004. Area dedicated to animal feed increases signicantly to reach 0.73 billion hectares, which is nearly six times greater than 2004. Rising energy prices in the baseline result in signicant growth in the land area dedicated to biofuels, which reaches 0.14 billion hectares by 2100. Managed forest area is little changed. Rising real incomes, growing demand for ecosystem services, and improvements in management of natural forest lands result in strong growth in protected natural land area, which increases signicantly to 0.68 billion hectares (about three times greater than 2004) in 2100.

21
# **1. Introduction**

Dramatic surges in food prices around the world will undoubtedly have a devastating effect on the world’s poor. From 2007 to 2008, the price of major staples, wheat and rice, rose by 121 percent and 76 percent, respectively (World Bank 2010 ), and global food prices almost doubled in the same period of time. The rising cost of food has slowed the pace of poverty reduction worldwide. About 65 million people were estimated to subsist under the $2 per day poverty line in 2009 as a result of the crisis (World Bank 2009).

The assumption that a food crisis will result in increased child labor is largely based on the notion that child labor is a result of poverty. In fact, the negative consequences of income shocks on children’s education and health are well documented (Funkhouser 1999; Jensen 2000; Hoddinott 2001; Thomas, Beegle et al. 2004; Beegle, Dehejia et al. 2006). The mechanism to support this conclusion in the case of a food crisis focuses more on the real income loss caused by higher food prices, which leaves little money to pay for children’s education. In the worst cases, children are pulled into the labor market in order to provide the family with enough additional income to buy the food they need.

However, as Ferreira and Schady (2009) noted, actual empirical findings do not reveal a simple connection between an aggregate economic shock and negative education and health outcomes. Likewise, in the case of a food price crisis, the impact of the shock depends on whether households have access to other coping mechanisms, such as insurance (Guarcello, Mealli et al. 2010) and household assets (Beegle, Dehejia et al. 2006). Different types of households may respond to a food crisis differently. Agricultural households may be unaffected or even benefit from higher food prices because these households can consume self-produced foods and/or sell their self-produced foods for a higher price in the market. On the other hand, non-agricultural households are likely to be more severely affected by high food prices.

Within households, limited resources sometimes force parents to make choices about the activities their children can engage in: going to school, working, or staying home. The trade-offs that parents have to make are not easy, and may not be based only on demographic 2
Sergio Firpo and Alysson Portella. Decline in Wage Inequality in Brazil: A Survey determined in Brazil. The little evidence on this is provided by Corseuil et al. (2018), who confirm that it had an effect in boosting the demand for more skilled workers; and by Haanwinckel (2018) who finds evidence that technological changes, defined as increases in the complexity of tasks performed by firms, increase wage inequality and polarization. The effect studied by Haanwinckel (2018), however, is small, being dwarfed by other demand shocks that resulted from reduced entry cost gap between goods and convergence in productivity. He argues that these two shocks are also responsible for reductions in cross-firm wage dispersion, which is a third factor associated with decreases in inequality that has not yet been properly explained. Alvarez et al. (2018) point out that compression in productivity dispersion does not seem to be the factor driving this convergence, but rather reductions in pass-through, while Engbom and Moser (2018) argues that minimum wages are responsible for this observed reduction in pass-through. However, other possible explanations for the decline in interfirm wage premia may be a decline in monopsony power (Tucker, 2017; Card et al., 2018), a decline in gender and racial gaps (Gerard et al., 2018; Morchio and Moser, 2019), and changes in international commerce (Helpman et al., 2010; Messina and Silva, 2017). We believe this to be a promising area of research.

Finally, the new line of research based on tax records may provide useful information on the dynamics of inequality in Brazil. As for now, it seems that including such information in the estimations of inequality leads to the conclusion of its stagnation in the past decades, especially because the role of top earners in inequality seems to have increased in the period (Medeiros et al., 2014, 2015). However, an underestimation bias of inequality in usual official sample surveys such as PNAD is not necessarily true if the cases of omitted income reporting are equally distributed across the distribution. For instance, Barros et al. (2007) argue that poorer families may omit non-monetary income or occasional income transfers from the government (such as unemployment insurance) or from relatives. In fact, Barros et al. (2007) compute similar or smaller measures of inequality using different sources of information than the traditional Brazilian Household Survey (PNAD). Hence, more research is needed on this topic to clarify the role of top earners in inequality and its dynamics.

# **5.2 What to expect in the coming years**

In the last years, the decline in inequality in Brazil has stalled, displaying a small increase in the last quarters. Should we expect a halt in the process of inequality reduction in the coming years, even an increase? Also, what could be done for Brazil to return to the previous path of inequality reduction?

Real minimum wage increase, one of the main factors behind the decrease in wage 29
provinces, districts, and even cities resulted in a renegotiation of state–business relationships (Hill, 2007) and the ascendency of businessmen into politics (Fukuoka, 2012).

Rather than leading to a wholesale disappearance of the dominant business elite, democratization led to its repositioning (Johansson, 2014) and gave it direct access to political power (Fukuoka, 2012 **)** . Some entrepreneurs were elected as heads of administrative units. In many other cases, they won the support of heads of local cabinets by backing them during election campaigns (Hadiz, 2004). Though regime turnover led to personnel changes as well as changes to the rules of the game, close ties between business and politics and the “gift exchange” nature of doing business do not appear to have changed much (Eklof, 2003; Carney and Child, 2013), helping explain why even greater changes are not seen among the firms and industries that had been connected to Suharto.

Many people with close connections to Suharto managed to maintain positions of power and prominence. All of his children except Titiek were accused of corruption at some point, but none of them was convicted on such charges. Tommy Suharto was convicted for ordering the assassination of a Supreme Court judge in 2002, but he was released in 2006, having served only 4 years of his 15-year sentence. Testimony to the Suharto family’s lasting political prominence was the candidature of Suharto’s son-inlaw, Prabowo Subianto, for the presidency in June 2014 (he was not elected).

Economic growth in Indonesia resumed in 2000, but it never reached its pre-crisis levels. Productivity growth did not recover fully after the crisis, and the process of “creative destruction” did not improve much (Hallward-Driemeier and Rijkers, 2013). Hill (2007) suggests that slow recovery was caused by imperfect implementation of the reforms and political instability.

In summary, the collapse of the regime decreased the value of connections to Suharto. The restructuring of politically connected companies, the elimination of a number of production and trade monopolies, and restrictions on investment are arguably all manifestations of reduced capture. If they are, one would expect increased competition, especially in industries where firms with connections to Suharto accounted for substantial market share. That the reform agenda and changes in business practices were not more sweeping, however, may limit the size of the effects.

# **3 Data**

This study draws on a number of data sets that are described in more detail in the online appendix A. Our primary data comes from the plant-level Annual Manufacturing Survey ( _Survei Tahunan Perusahaam Industri Pengolahan_ ), collected by Indonesia’s Central Bureau of Statistics ( _Badan Pusat_ 8
group. _ELF_ lies between 0 and 1 with higher values implying a more fragmented country. Data used to construct _ELF_ belong to the early 1960s and details are provided in Appendix A2. Figure 2 shows the relationship between _Law_ and _ELF_ which is along expected lines.

<!-- Start of picture text --> Law and Ethnolinguistic Fractionalization<br>2.5<br>2<br>1.5<br>1<br>R 2 = 0.23<br>0.5<br>0<br>-0.5 0 0.2 0.4 0.6 0.8 1<br>-1<br>-1.5<br>-2<br>-2.5<br>Ethnolinguistic Fractionalization<br>Figure 2<br>Rule of Law<br><!-- End of picture text --> Countries in our sample have one of the following legal origins: _English_ , _French_ , _German_ , _Scandinavian_ and _Socialist_ . There is some work which suggests that _LO_ may be an important and exogenous determinant of _Law_ . Broadly, legal systems can be viewed as proxies for the relative power of the state vis-a-vis property owners. The _English_ common law has developed to some extent as a defense of Parliament and property owners against the attempts of sovereign to regulate and expropriate rents from private agents either directly or indirectly by favoring interest groups. The _French_ civil law, in contrast, developed more as an instrument used by the government for state building and controlling economic life. The _Socialist_ system represents the extreme case of control 14
informal sector yo. We also need to define the functional form for the distribution of skills and the idiosyncratic shock processes.

The calibration is performed in 4 steps. In the first step we set the values of 5 of the parameters using standard values from the literature. The value of leisure or unemployment benefit is normalized to zero b = 0. The bargaining power of workers is set β = 1/2. The interest rate is obtained for the Mexican Central Bank for Mexico and it is set to 4% for Indonesia. For the parameters of the matching function we set ρ = 1/2 and normalize ξ = 1. These are standard normalizations that do not affect the simulation results. We explore how sensitive our results are to the predefined parameters.

In a second step we determine the parameters of the production function in agriculture and earnings in the informal sector. According to the model, agricultural earnings ya are the average product of labor: ya = Aalaγ−1. We use the value of the elasticity of output with respect to agricultural employment γ, estimated by other authors. For Mexico we use the elasticity found by Bravo‐Ortega and Lederman (2004). For Indonesia we use the value estimated by Suryadarma et al (2007). Using the observed value of labor (l) and earnings (ya) from the respective household surveys, we are then able to back‐up the implied value of Aa, which corresponds to the technological parameter of the production function. Earnings in the informal sector are exogenous in the model, and we set them equal to the observed average earnings of all those working in this sector, which we obtain from the household surveys.

In a third first step we specify the parameters of the exogenous shock process G(y) that hit jobs and of the distribution of skills among active the working population F(y). As it is standard in the literature, we assume that the shock process is described by a uniform distribution with support [0, y]. In other words when a shock arrives the new level of productivity of worker of type y will be between 0 and y, with equal probability of ending up anywhere in this support. The uniform distribution is completely specified by its support. To model the distribution of skills of the labor force, F (y), we assume that skills are distributed according to the Beta distribution, and we proxy skill by the level of education of workers. The Beta distribution is a very flexible distribution with finite support between [0, 1]. Depending on its two parameters abeta, and bbeta it can display a broad range of behaviors, it can be skewed or have a bell shape. Let abeta and bbeta denote the two parameters. Then, the mean will be given by _E[y] =abeta/ (abeta + bbeta)_
# Estimating a Poverty Trend for Nigeria between 2009 and 2019

Jonathan Lain, Marta Schoch, and Tara Vishwanath<sup>1</sup> (JEL: I30, I32, C53, D30) Keywords: Poverty Measurement, Survey-to-Survey Imputations, Nigeria 1 All authors are with the World Bank. Corresponding authors: Jonathan Lain (jlain@worldbank.org) and Marta Schoch (mschoch@worldbank.org). The authors are extremely grateful for guidance received from Dean Jolliffe, Christoph Lakner, Berk Ozler, Aibek Baibagysh Uulu, Nobuo Yoshida, Paul Corral, Roy Van der Weide, Shinya Takamatsu, and the members of the Global Poverty Working Group. <mark>The authors gratefully acknowledge financial support from the UK government through the Data and Evidence for Tackling Extreme Poverty (DEEP) Research Programme.</mark>
# **Volatility and Contagion in a Financially-Integrated World: Lessons from East Asia's Recent Experience**

By Pedro Alba% Amar Bhattacharya, Stijrn Claessens*, Swati Ghosh*, and Leonardo Hernandez"

## World Bank* and Central Bank of Chile*

Recent events in East Asia have highlighted the risks of financial structures in a financially integrated world. This paper documents that the buildup of vulnerabilities in East Asia was mainly the result of weaknesses in domestic financial intermediation, poor corporate governance, and deficient government policies, including poor macro-economic policy responses to large capital inflows. Weak due diligence by external creditors, in part fueled by ample global liquidity, also played a role in building up vulnerabilities, but g lobal factors were more important in triggering the crises than in causing them. In spite of these policies and weaknesses, we argue, however, that for most East Asian countries a large financial crisis was not "inevitable," but was mainly triggered by spillovers from nearby countries. Differences between countries, both in degree of vulnerability and depth of crisis, support this conclusion. The paper concludes with some lessons for other countries.

Paper presented at the PAFTAD 24 conference, "Asia Pacific Financial Liberalization and Reform", May 20-22, 1998, Chiangmai, Thailand, hosted by School of Development Economics, NIDA, in collaboration with PAFTAD International Steering Committee. This paper has really been a group effort. We would like to thank Jos Jansen and Peter Montiel for very useful contributions, Sergio Schmukler for his insights, Michael Dooley, the discussant, Akira Kohsaka, and seminars participants for comments, and the PAFTAO steering committee for guidance. This paper draws on and extends the analysis in the joint-World Bank-ADB study: _Managing Global Financial Integration In Asia: Emerging Lessons and Prospective Challenges,_ March 10-12, 1998, for comments. The opinions expressed do not necessarily reflect those of the World Bank or of the Central Bank of Chile.