rafmacalaba/datause-encoder-data huggingface dataset:
that property rights are more secured as an economy develops (Besley and Persson, 2009) and economic and political interests become more aligned and equal (Acemoglu and Robinson, 2005).

Figures 2 and 3 show the simple correlation between the insecurity of contract enforcement and both moments (income level and inequality). Contrary to my expectation, contract breaches tend to occur more as a country develops up to the upper-middle income level, which includes Argentina, Brazil, Malaysia, Mexico, and Turkey (see Figure 2).

Figure 3 shows the correlation between BOC risk and income inequality (measured by theh Gini coefficient from the World Bank’s PovCal Net). Except for several countries that breached contracts more than ten times in history, non-parametric estimates of the probability of contract breach remains flat as income inequality rises. The little correlation remains even when different poverty measures, such as headcounts of the poor population and the poverty gap (which captures the depth of poverty), are used.

The two figures characterize a puzzling fact; higher incidence of dispute events in relatively wealthier nations as well as the little correlation of contractual disputes with inequality. This implies that wealthier countries have more resources and opportunities for coercive government to be extractive. This observation motivates me to investigate further the trigger of BOC, which can be explained by contractual design, external shocks, or political institutions.

Table 2 summarizes the sectoral distribution of contractual disputes. More PPP contracts have been signed in OGM, transport and energy sectors, leaving other sectors underrepresented. The table shows that the probability of BOC events differs by sector. Therefore, sectoral heterogeneity is controlled when estimating hazard rate (the likelihood of BOC in the next period on condition that the contract survives in the current period) and the probability of BOC in the following sections.

# _3.3.  Existing Evidence_

What are the potential triggers of BOC risk? Some anecdotal evidence exists, but the facts are scattered and do not answer which triggers are the most relevant.<sup>7</sup> Aside from academic papers, there is an accumulation

> 7 Using the PPI data set, World Bank (2004) examines the determining factor of renegotiation on infrastructure concessions in Latin America, showing that country-level institutions (regulation) and concession award criteria explain larger part of the probability of renegotiation compared to macroeconomic factors.  Woodhouse (2006) also use same data and offers case studies and highlights the importance of micro-level contractual factors which affect bargaining powers between host countries and international investors and the performance of PPP projects in the power sector. Jensen et al (2013) uses a different contract-level data from OPIC to address how external factors can drive governments to breach contracts, claiming that governments have less incentive to expropriate firms during the period of crisis and with larger foreign intervention (through foreign aid or IMF agreement) to avoid reputational cost.

6
Data Surces andi uJnt Root Taests The data used are obtained by from the quarterly database compiled by Agenor, McDermott and Prasad (2000). The quarterly dataset covers the following years for the countries in the sample: 1978:01-2001:01 for Chile and Korea, 1981:01-2000:04 for Philippines, and 1981:01-2001-01 for Turkey. The variables and the sources of them axe as follows

- 7r is the percentage change in the consumner price index. Source: International Monetary Fund (IMF).

- y is the log difference of output to the trend component of output, where output is the ir.dustrial production index. The trend component is calculated using a generalized version of the Baxter-King filtering method, as explained in the text. Source: IMF.

- z is the rate of change of the real effective exchange rate, defined as the difference between the inflation rate and the sum of the growth rate of nominal effect exchange rate and the growth rate of import prices. A rise is a depreciation for the nominal effective exchange rate. Source: IMF.

Each series used in the regressions is tested for stationarity. Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests are employed. The null hypothesis is that a unit root exists and the alternative hypothesis is that the series is trend stationary. Results of these tests are reported in Table Al. In general, both test statistics give similar results. The presence 17
index of industrial products in order to separately identify quantity<sup>6</sup> . _Kijt_ , capital, is defined as the value of fixed assets, which is deflated by the fixed assets investment index, and _Lijt_ is the total number of employees. _Mijt_ represents the intermediate inputs purchased by firms to use for production of final products, which is deflated by the intermediate input price index.<sup>7</sup> _ForeignShareHKTMijt_ , _ForeignShareFRijt_ and _StateShareijt_ are defined as the share of the firm‘s total equity owned by Hong Kong-Taiwan-Macau investors, foreign investors, and the state respectively. The omitted share, the non-state domestically-owned share, is represented by the constant term. By construction, these three firm-level controls are continuous variables and range from 0 to 1 in value<sup>8</sup> .

The motivation for separating foreign share into two types is two-fold. First, we would like to see whether some types of foreign investment are more likely to result in productivity spillovers than others. Second, anecdotal evidence suggests large quantities of so-called foreign investors in China are actually domestic investors who channel investment through Hong Kong–Taiwan-Macau in order to take advantage of special treatment for foreign firms (so-called ―round tripping‖). If this is the case, then we would expect that foreign investment of this type might have a smaller impact on domestic firms.

Following Javorcik (2004), we define three sector-level FDI variables. First, _Horizontaljt_ captures the extent of foreign presence in sector _j_ at time _t_ and is defined as foreign equity participation averaged over all firms in the sector, weighted by each firm‘s share in sectoral output. In other words, where _ForeignShareit_ is the sum of _ForeignShareHKTM_ and _ForeignShareFR_ .

Second, _Backwardjt_ captures the foreign presence in the sectors that are supplied by

> 6 Sector-specific ex-factory price indices for industrial products came from China Urban Life and Price Yearbook (2008, Table 4-3-3). The price indices are published for 29 individual sectors.

> 7 Price indices for fixed investment and industry-wide intermediate inputs are obtained from the Statistical Yearbook (2006) (obtained from the website of the National Bureau of Statistics of China).

> 8 In some specifications, we run regressions with domestic firms only. In these cases, we use the sample of pure domestic firms, which have zero foreign investment. Then we regress either the log of the firm‘s output or productivity on sector-level FDI without the variable ―Foreign Share‖.

7
# **Table VII:** Program impacts on height-for-age z-scores (children of beneficiaries: **baseline dropouts** <u>)</u>

|**Panel A: Born During Program**|**Raw Effect**<br>Gender|+ Maternal<br>Selection<br>weights|+ Paternal<br>Selection<br>Controls|+ Child Age|**Direct Effect**<br>+ Mother<br>Age|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|
|=1 if Conditional Schoolgirl|-0.015|-0.174|-0.139|-0.154|-0.051|
||(0.128)|(0.149)|(0.143)|(0.140)|(0.136)|
|Sample Size|367|367|367|367|367|
|**Panel B: Born Within 9 Months of Program E**|**nded**|||||
|=1 if Conditional Schoolgirl|0.353|0.518*|0.394|0.411*|0.577**|
||(0.296)|(0.303)|(0.249)|(0.234)|(0.260)|
|Sample Size|88|88|88|88|88|
|**Panel C: Born More than 9 Months After Prog**|**ram Ended**|||||
|=1 if Conditional Schoolgirl|-0.269|-0.175|-0.127|-0.137|-0.183|
||(0.168)|(0.192)|(0.161)|(0.154)|(0.152)|
|Sample Size|287|287|287|287|287|
|Control Structure:||||||
|Maternal selection controls + propensity weight||X|X|X|X|
|Father selection controls|||X|X|X|
|Cubic in child age in months||||X|X|
|Maternal age inyears,age interactions|||||X|

_Notes:_ Regressions are OLS models with robust standard errors clustered at the EA level. All regressions are weighted to make them representative of the target population in the study EAs. The height-for-age z-score is calculated using the 2006 WHO child growth standards. Specification (1) controls for the gender of the child. Specification (2) adds selection weights and controls directly for maternal baseline characteristics ( stratum indicators, household asset index, highest grade attended, and an indicator for never had sex). Specification (3) adds controls for paternal attributes (highest education level, religion, ethnicity, main activity, and likely HIV status). Specification (4) adds a linear, quadratic, and cubic in child age. Specification (5) adds maternal age and maternal age interacted with the other baseline covariates. We restrict the sample to respondents who were surveyed during the latest household survey conducted two years after the program (Round 4). Parameter estimates statistically different than zero at 99% (***), 95% (**), and 90% (*) confidence.
Table 2: Trade Gains ($million) from Capacity Building by Each of South Asian Countries and Entire South Asia Region in Trade Facilitation<sup>31</sup>

||Port efficiency<br>(Air and<br>Maritime)|Customs|Regulation|Service-sector<br>infrastructure|All|
|---|---|---|---|---|---|
|Bangladesh|228|144|71|339|782|
|India|314|193|123|519|1,149|
|Pakistan|74|29|42|191|336|
|Sri Lanka|97|63|41|175|377|
|South Asia|712|429|278|1,224|2,644|

Source: Authors’ calculation based on Wilson, Mann, Otsuki database 2004 Among the four trade facilitation indicators, results suggest that capacity building in information technology and services infrastructure, reflected in expanded internet access and use, would lead to the greatest gains to intra-regional trade. Capacity building in port (air and maritime) efficiency would achieve the second largest trade gains. This suggests that the South Asia region is currently underdeveloped more in areas related to information technology infrastructure than in administrative or regulatory aspects of trade facilitation at the border. It is important to note that these results should be considered an indication of where priorities may be most important, however, and not viewed alone. For instance, the "services-sector infrastructure" may reflect to some extent the effect of other variables (e.g. inland transport, or specific policy and institutional issues related to border clearance) that the model does not include. This highlights the importance of new datasets and data gathering for analysis, among other issues.

Until now, we have considered a transitional scenario toward the regional harmonization of capacity in trade facilitation. As an informative exercise, we will now consider a harmonization of the other influencing factors that are represented by tariff barriers, and will speculate how much improvement will be needed for the South Asian countries to achieve the formerly set goal (halfway toward the East Asia average). In our gravity model estimation, we have obtained the elasticity of trade flow with respect to tariff rates. The elasticity is used to predict the trade flow at a common tariff rate, namely, the average tariff rate in South Asia, and calculated the amount of capacity building needed to achieve the trade flow at the common tariff rate. In this exercise, we consider the capacity building in trade facilitation in only importing countries since tariff rates are assumed to be changed only by importing countries for simplicity. Tariff data were not available for some South Asia countries in the studied period, thus, those countries are not included in this exercise.

We find, under this scenario, that a 65 percent improvement in port efficiency from the status quo level is needed for Bangladesh to achieve the target level of trade, and that a

> 31 To calculate the predicted values of regulation and service infrastructure, we regressed the indicators with logarithm of GDP and obtained the fitted value.

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# **Preface**

This report is part of a project on risk-based supervision of pension funds coordinated by the Financial and Private Sector Development Division of the World Bank, and initiated in response to a growing number of requests from member countries for assistance in the area of pension supervision. The project is being implemented in collaboration with the International Organization of Pension Supervisors (IOPS), and involves the identification of good practices in risk-based supervision of pension funds, based on a number of carefully selected country studies. These good practice guides are expected to benefit a large number of supervision agencies in developed and emerging countries, and contribute to a better performance of private pension systems.

The project will draw on the experience learned in countries that have implemented a risk-based supervision approach and apply this knowledge to assist developing countries. Models of risk-based supervision demonstrate benefits to be gained from moving away from a focus on individual transactions and strict compliance with a range of specific rules towards greater awareness of the risk profiles of supervised entities. A risk-based approach provides encouragement to supervised entities to place a greater focus on risk management in their daily operations, and promotes a safer and sounder financial system. It is expected that over time moving to a risk-based approach to supervision will create scope for supervisors to focus resources on areas of highest risk and, over time, result in a more efficient use of supervisory resources.

The Australian case provides a model of risk-based supervision which applies to both defined contribution and defined benefit pension funds, covers a broad range of institutions in terms of size and complexity, and applies to both open “public offer” funds and closed occupational funds. The Australian case provides a structured methodology for ranking pension funds according to the relative threat of failure and maps this to a supervisory response framework. The main focus is to ensure that all pension entities meet their “financial promises” to members and beneficiaries. Within the Australian model some additional focus is given to funds which offer defined benefits. The model makes a distinction between larger funds which are subject to detailed assessment and smaller funds which are subject to a streamlined and more automated assessment.

This report is a condensed version of a more detailed analysis of the Australian system undertaken by Graeme Thompson. The author is a consultant and former Chief Executive Officer of the Australian Prudential Regulation Authority. The author is grateful to Chris Gaskell, Juanita Hoare, Karen Kay, Charles Littrell, Darryl Roberts, Peter Vodicka and Melisande Waterford at APRA for their assistance and for Roberto Rocha for comments on earlier drafts. The condensed version of the report includes some minor changes to reflect developments since the original report was written.
course does not mean that other factors do not also affect feelings of deprivation, satisfaction and more generally happiness, as pointed out by Dean (2007) among others.

While other authors (e.g., Berrebi and Silber, 1985; Bishop, Chakraborti and Thistle, 1991, and Sen, 1973) have used the same social welfare function, Yitzhaki relies on this function specifically in the context of relative deprivation, as opposed, for example, to the argument that individuals may compare themselves to others when evaluating their level of well-being (Duclos, 1998, and Hey and Lambert, 1979). It may well be true that individuals compare themselves to others,<sup>5</sup> and the Gini index itself can be written as a sum of such pairwise comparisons of income, but the logic in Runciman’s argument is different. It relies on the idea that scarcity determines the value attached to each unit of income, and in Yitzhaki’s formalization of this idea, on a given measure of scarcity. Ebert and Moyes (2000) present axiomatic derivation for the relative deprivation function<sup>6</sup> .

The idea that individuals value goods (in order to assess their satisfaction or deprivation) in relationship to their rank in the overall population as a measure of scarcity has been suggested in other settings. Within a firm, the value of a position depends on how high the position is in the overall distribution of positions (Stark and Yitzhaki, 1988). The smaller the number of Vice Presidents, the higher the value of being a Vice President.

Another imperfect, yet possibly revealing analogy is that of the decathlon, an athletic two-day event with ten different disciplines (100 meters sprint, long jump, shotput, high jump, and 400 meters in that order on the first day, and 110 meters hurdle, discus, pole vaults, javelin,

> 5 Duesenberry (1951), Frank (1985), and Kapteyn et al. (1980) present evidence on the dependency of preferences on others. For a survey of the issues involved, see Weiss and Fershtman (1998).

> 6 There have also been a number of extensions of and alternatives to the approach proposed by Yitzhaki to analyze relative deprivation.  For example, Verme and Izem (2008) suggest an alternative index of relative deprivation that allows for the selection of the reference group and imperfect information, with an application to US wage data.  See also Hopkins (2008) for a survey of different theoretical models of relative concerns and their link to inequality.

4
effect on these income variables. In our regressions, we control for different linear time trends in Azteca and non-Azteca municipalities to correct for these biases. Overall, there is no indication that differences in trends across municipalities could lead us to find a positive effect that is not actually there, implying that our estimates are on the conservative side.

We also use a number of individual background variables from the ENE as control variables in the regressions. These variables include age, gender, marital status, and education dummies. Summary statistics for these background variables and their pre-period changes are not included in the tables to save space, but they are available from the authors upon request.

# **IV. Results**

# **IV. a. Business Owners**

We first investigate the impact of Banco Azteca opening on entrepreneurial activity. Table 2 presents the results for the informal and formal business owner dummies as dependent variables. We find that the opening of Banco Azteca had a positive and statistically significant impact on the fraction of informal business owners. The coefficient on our variable of interest remains statistically significant and similar in size when we include a separate time trend for the group of Azteca and non-Azteca municipalities in the regressions (Column2). The coefficient is also similar when including municipality specific time trends (Column 3). Overall, the results suggest that the opening of Banco Azteca increased the fraction of informal business owners by 0.0062, which corresponds to 7.6 percent of the preAzteca fraction of 0.082.

The effect on registered business owners is negative in the specification without time trends, but this effect is not robust to including time trends in the regression. It is perhaps not surprising that the fraction of formal business owners did not increase due to Banco Azteca opening. In contrast to informal business owners, formal business owners typically have access to commercial banks, since they have the necessary documentation, and commercial banks tend to offer lower interest rates.

Figure 4 is a graphic illustration of the effect of Banco Azteca opening on the fraction of informal business owners. It displays the fraction of informal business owners in municipalities with and without an Azteca branch in 2002-IV over time. We observe a steep 12
earnings growth can be misleading due to presence of “cohort effects” in the assimilation estimates. Following “synthetic cohorts” - i.e. sets of individuals who immigrated during a certain period - through the US Censuses 1970 and 1980<sup>12</sup> , Borjas found that the unobservable part in the quality of successive US immigrant cohorts<sup>13</sup> , measuring precisely the ability and motivation - not related to education - that supposedly help migrants’ earnings grow faster than natives’, has steadily declined over time.

Borjas’s results of lower assimilation compared to estimates produced by cross-section studies were restated in Borjas (1995) following addition of US Census 1990 to the analysis. Borjas (1989) and Funkhouser and Trejo (1995) confirmed presence of positive cohort effects for US immigrants using longitudinal survey and Current Population Survey (CPS), respectively, instead of US Census data. Implementing Borjas’s synthetic cohort approach, Baker and Benjamin (1994) also provided evidence of decline in the unobservable quality for immigrants to Canada. Nevertheless, despite the general perception of both lower nominal entry earnings and larger education gaps relative to natives for the US 1970s and 1980s immigrant cohorts, a significant part of the literature could not reach conclusive evidence of a decline in the “unobserved” cohort quality even when using the same methodology introduced by Borjas (1985). Thus, Chiswick (1986) detects no significant cohort differentials in the unmeasured dimensions of productivity - such as language fluency, the quality of schooling and experience, and ability – although the study confirms that recent US immigrants are indeed less favorably selected on the basis of their level of schooling. Using Social Security Administration longitudinal data, Duleep and Dowhan (2002) find that immigrants’ wages are lower at arrival, but then reach and even exceed those of natives, result which is in line with the optimistic depiction of migrants’ trajectory in Chiswick (1978). LaLonde and Topel (1990) use data from Censuses 1970 and 1980, as well as Borjas’s “synthetic cohort” approach amended by several methodological changes and show that, within the immigrant groups studied<sup>14</sup> , assimilation estimates resemble the ones predicted by the “cross-section” studies, and that there is no evidence of a significant decline in cohort quality (measured as unobservable skills) over time. LaLonde and Topel motivate the difference in findings compared to Borjas (1985) based on the choice of

> 12 Composition of a synthetic cohort is not directly comparable across censuses because individuals surveyed for one census are not necessarily the ones selected to fill out the questionnaires for the subsequent censuses.  However, they refer to the same population, which nevertheless changes over time due to natural causes as well as out-migration.

> 13 Proxied by relative entry earnings of migrants relative to natives while keeping constant the impact of other determinants of entry earnings (age, education etc).

> 14 Europe, Canada, Australia; East and South Asia; Middle East; Mexico; Latin America

6