rafmacalaba/data-use-mentions-extended huggingface dataset:
during the 1990s, bankruptcies were higher in countries with Anglo-Saxon legal systems, greater judicial efficiency, market-oriented financial systems (characterized by multiple banking relationships), and overall greater economic development (Claessens and Klapper, 2005). These results confirm earlier findings that the legal environment is the main regulator of bankruptcy and transactions between entrepreneurs (Guislain, 1995).

For example, an analysis of publicly listed firms that filed for bankruptcy under new bankruptcy laws introduced during the East Asian financial crisis finds that seeking bankruptcy protection is higher in countries with strong creditor rights and greater judicial efficiency (Claessens, Djankov, and Klapper, 2003). This study highlights the importance of establishing a balance between protection of creditors’ rights (such as the sale of assets in the case of default), which is essential for firms’ access to finance, and identification and reorganization of viable enterprises.

Differences between debtor-friendly regimes and creditor-friendly regimes also influence a firm’s decision to use in or out-of-court reorganizations. In this regard, distressed firms are more likely to use in-court reorganizations in debtor-friendly regimes (White, 1993). A study of 169 financially distressed firms finds that firms that settle out-of-court have more intangible assets, a larger percentage of debt owed to banks, and fewer lenders (Gilson et al., 1990). On the other hand, an earlier study shows that firms that resolve financial distress out-of-court are more likely to remain highly leveraged and are more prone to experience further financial distress (Gilson, 1997). Bankruptcy laws might also affect the ex-ante behavior of firm managers and owners in operating and financing the firm (La Porta et al., 1997). Debtor friendly laws might encourage managers to seek bankruptcy protection from their creditors at an earlier point, which may increase the likelihood of the firm’s survival and may ultimately benefit its claimants. Such 8
# Early Impacts of Indonesia’s Investment Reforms: A Preliminary Analysis<sup>*</sup>

Angella Faith Montfaucon<sup>†</sup> Victor Kidake Senelwa<sup>‡</sup> Aufa Doarest<sup>§</sup>

## _JEL classification_ : F13, F21, F23, D25, L51

_Keywords_ : Investment liberalization, foreign direct investment, domestic direct investment, trade policy

> *The authors would like to thank Bayu Agnimaruto for help in assembling the realized investment data and Peter Kusek for help in accessing the planned investment data. We thank Csilla Lakatos and Yu Cao for their comprehensive comments. We thank Gerlin May U. Catangui and Frederico Gil Sander, Habib Rab, Wael Mansour, Aristomene Varoudakis and Massimiliano Cali for helpful discussions. The views herein do not necessarily reflect the views of the World Bank. All errors are our own.

- †World Bank, amontfaucon@worldbank.org.

- ‡World Bank. vsenelwa@worldbank.org

- §World Bank. adoarest@worldbank.org
**Caveats** The main limitation of this study is the lack of data on wages in the Tunisian labor force survey (ENPE). The joint prediction of the theoretical model described in this paper is that foreign demand shocks that concentrate on male-intensive industries should decrease both the female-tomale employment ratio and the female relative wage. There is quite extensive documentation in the literature that is indeed happened in other contexts<sup>5</sup> . Therefore, it would be surprising if male wages did not increase relative to female wages after a male-intensive positive foreign demand sock. Furthermore, the fact that we were able to identify that, in Tunisia, the changes in the female-tomale employment ratio work primarily through changes in the behavior of married women serves as an additional check on the theoretical mechanism, since it suggests that the mechanism operates through joint household decisions.

Another caveat relates to aggregation. The empirical strategy developed here relies on exploiting differential regional variation in exposure to exports. However, as documented by Chodorow-Reich (2020), strategies that rely on this kind of cross-sectional variation only capture the effect of additional exposure to exports relative to other regions<sup>6</sup> . One cannot extrapolate from the cross-sectional to the aggregate effect without imposing additional assumptions. In this case, one variable that could make aggregation harder is migration. If households move across provinces in response to negative (positive) shocks, they could make relative estimates larger (smaller) than aggregate estimates.

The empirical specification above only captures short-run effects, since it was limited to using the previous period as the base period. In that context, unless there are no mobility costs, the migration channel is likely more muted. If one thinks of labor as immobile, spillovers are a function of domestic trade patterns. Intuitively, if the provincial consumption basket of a province exposed to a foreign demand shock to its male-intensive sector is tilted towards the male-intensive sector, this will exacerbate the aggregate effect with respect to our estimates. Conversely, if
succeeded and became the first industrialized nation from the East because of the right choice of targeting countries.

# **Section 2.3 The post WWII era: The US showed the way to Japan and other geese**

The economies of Western Europe and Japan have enjoyed unprecedented growth and technological upgrading in the decades since World War II, or, the so-called Golden Age of Capitalism (1950-1974). During this period, nearly all developing countries pursued ― _dirigiste_ capitalism‖ but except for Japan, Korea and other East Asian Tigers, they did not succeed. _Why?_ The NSE contends that the crux of Japan and East Asia‘s success was that their development followed closely their comparative advantage or was CAF and their governments played the facilitation role (Lin 2010, Lin and Monga 2010, Lin and Monga 2011). Just before WWII, textiles and other light industrial goods accounted for 60 – 75 percent of all Japanese exports. Japan‘s textile industry was at its peak before the Second World War (Ito 1992, p. 24). In the 1960s, when its per capita GDP was about 40 percent of that of the US and it had established a strong industrial base, Japan targeted U.S.‘s industries (Table 2.1). Japan‘s historical labor statistics record that a rising share of labor in Japan‘s manufacturing sector coincided with a declining share of labor in the US‘s manufacturing sectors. In the 1960s-1970s, Japan supported its heavy manufacturing sectors including machinery and automobiles. In the 1980s-1990s, just as the US was upgrading its industrial base, Japan acquired shares in the home appliances, electronics and computer markets (Figure 2.3-2.5).

**Figure 2.3  Structural transformation in Japan: employment in manufacturing increased during 1920-1973, followed by a slow decline as the services sector expanded**

<!-- Start of picture text --> 100%<br>90%<br>80%<br
The Role of Cash Transfers in Smoothing the Income Shock of COVID-19 in the Arab Republic of Egypt<sup>1</sup> Romeo Gansey World Bank Maria Eugenia Genoni World Bank Imane Helmy World Bank Keywords: COVID-19, microsimulation, poverty, labor income, cash transfers JEL codes: <mark>E27, H22, H23, H31, I32</mark>

> 1 Corresponding author: Maria Eugenia Genoni (mgenoni@worldbank.org). Valuable comments were contributed by Gabriel Lara Ibarra, Nelly Elmallakh, and Lili Mottaghi. This paper was prepared as a background paper for the forthcoming Egypt Poverty Assessment 2024 (P179530). The authors gratefully acknowledge financial support from the Office of the Chief Economist for the Middle East and North Africa (MNACE) under the regional Labor and Gender Research Programs.
,882|
|5|51823|Betioky-<br>Atsimo|98.9|11106|Antananarivo|57,074|
|6|51824|Betioky-<br>Atsimo|98.9|41102|Mahajanga-1|55,586|
|7|51825|Betioky-<br>Atsimo|98.9|51305|Morombe|53,842|
|8|51818|Betioky-<br>Atsimo|98.8|52101|Ambovombe-<br>Androy|51,662|
|9|51821|Betioky-<br>Atsimo|98.8|13107|Miarinarivo|50,751|
|10|51830|Betioky-<br>Atsimo|98.8|61101|Antsiranana-1|47,019|

Source: Authors’ estimations

# Small area stunting maps

In Demographic and Health Surveys (DHS), stunting is measured through the collection of anthropometric data from children under the age of five. Specifically, children's height is measured and compared to standardized growth references, typically provided by the World Health Organization (WHO) Child Growth Standards. Stunting is assessed by calculating the height-for-age z-score (HAZ) for each child, which quantifies how many standard deviations their height deviates from the median height of a healthy reference population. Children with a HAZ score of less than -2 are classified as stunted, indicating that their height falls significantly below the expected average for their age. The 2021 DHS in Madagascar uses this data to monitor and assess the prevalence and severity of stunting in different countries, providing valuable insights for public health interventions and policy planning.

3 We deliberately kept the names of the communes anonymous.

11 | P a g e
Survey-reported outage duration was also substantially lower than the box-based duration on average. For the previous day, estimates derived from survey responses were about 18 minutes less than automated monitoring of outage duration. Over prime hours during the previous day and the day before, respondents underreported by a smaller number of minutes. When asked over the previous ten days, estimates from survey data were lower by slightly more than two days, and average duration was underreported by an average of about 16 minutes. These differences are statistically significant at customary levels and suggest that data gathered using surveys in this context results in systematic underreporting of outages. Differences were relatively smaller over shorter and more concrete reference periods (past day/between 6 and 10PM), though systematic bias (in the form of underreporting) remained.

Another means of drawing these comparisons is provided in table 4, which focuses on measurements of “any outage yesterday” and “any outage the day before yesterday.” The possible outcomes were i) both the survey and the boxes report an outage, ii) both the survey and boxes report no outage, iii) the survey reports an outage, and the boxes report no outage, and iv) the boxes report an outage, and the survey reports no outage. The estimates of “survey underreporting” bias should be comparable in this approach to the estimates provided in table 3 and indeed, summary statistics reported in table 4 align as expected.

9
like to control for the ownership structure of banks, but face the problem that the ownership dummy is not well populated in Bankscope and only reflects the current ownership structure. We therefore control for the ownership structure on the country level, using data from Barth, Caprio, and Levine (2008). The foreign bank share ranges from zero to 100%, while the government ownership share ranges from zero to 98%. On average, the foreign (government) ownership share is 35% (17%).

In some of our regressions, we also include several country-level indicators. Specifically, we include GDP per capita as indicator of economic development, GDP growth, Private Credit to GDP as measure of financial development and the three-bank concentration ratio. A large literature has related bank concentration to both the efficiency and stability of financial systems 13
# **D VenRePS Survey**

The survey was administered in two steps to ensure targeting of the forced migrants who fulfilled the characteristics laid out in the sampling frame, and to define (with respondents) the best time to call and administer the questionnaire.

First, forced migrants received a text that introduced the survey team from IPA, described the broad objectives of the research project and the monetary incentive for participation, and mentioned that the team would call them in the next few days to conduct the survey. The text also included a link to the project’s website that had more detailed information.

A few days later, the survey was administered by phone.<sup>16</sup> First, a short screening module was administered to verify the respondent’s eligibility and to obtain informed consent. RAMV migrants were asked if they or other family members had registered in the RAMV census and whether they had PEP. Non-RAMV migrants were asked for their migration date because the targeted migrants had arrived in Colombia between January 2017 and December 2018, were older than 18 years, did not have a different PEP, and did not have a valid passport.<sup>17</sup> Following the screening, the survey was administered with a focus on the family head, partner, or another adult member of the family. The original questionnaire was adjusted and trimmed because of the challenges posed by phone surveys. We decided not to collect data for the entire household roster, and collected the labor module only for the respondent and one other member of the nuclear family.<sup>18</sup> In total, we collected information from 3,455 Venezuelan families living in Colombia. This sample included families with some members who were Colombian, either from birth or

> 16The call was rescheduled when the respondent was not available. When ineligible respondents were called, the team included them in a raffle for 50,000 COP (approximately $USD 18).

> 17As discussed above,
%|18%|
|Post-natal care,0-5|16|24|1.0%|92%|8%|
|Prenatal care,0-4|48|73|3.1%|82%|18%|
|Immunization vaccines,0-4|89|85|-0.5%|42%|58%|
|Non-wasting,0-4|87|75|-1.5%|75%|25%|
|Non-stunting,2-17|65|67|0.3%|33%|67%|
|Non-underweight,0-17|77|82|0.7%|67%|33%|
|_Aggregate HOIs_||||||
|IOHa9-15-HousingServices|36|77|4.6|71%|29%|
|IOHa0-4-HousingServices|22|64|4.7|82%|18%|
|IOHa0-4-Nutrition & ECD|12|12|0.0|---|---|
|_Source_: HIECS 2000 and 2009 surveys, EDH|S 2000 and|2008, an|d authors’ ca|lculations.||

# **_3.2 Regional Differences_**

_Better Opportunities for Metropolitan Children Relative to Their Peers in Other Regions._ Table 5 presents the HOIs across the four main regions in 2000 and 2009, and at the bottom of the table shows three aggregate HOIs (two for housing services 0-4 and 9-15 years of age, and a third one for nutrition plus early childhood development). The evidence indicates that in 2009 the three overall aggregate HOIs were highest in Metropolitan areas (95, 97 and 18 points, respectively) and lowest in Upper Egypt (64, 74 and 10 points, respectively), with Lower Egypt and Frontier Governorates in between. Moreover, the gaps between the best and worst region have been substantially reduced between 2000 and 2009, particularly in housing services, but much less in nutrition and early childhood development. However, based
. The funds are primarily domiciled in developed market jurisdictions, in fact, 80% of the funds are domiciled (in order of importance by the number of funds) in Luxembourg, the U.S., the U.K., and Ireland.<sup>17</sup> Average total net assets (first computed within fund and then across all funds) is around 620 million U.S. dollars for both equity and bond funds.

> 14 Information on ISIN is not available for the EPFR Global mutual funds, so we match the return data with the EPFR Global data according to the mutual fund name and family, using an algorithm that compares the (Levenshtein) distance across names. We then manually screen out incorrect matches and complete the matching process. The total number of fund price observations is 255,510.

> 15 We believe this is a reasonable approximation given the documented synchronicity of returns across assets within countries, especially in developing countries (Morck et al., 2000). Furthermore, we find a strong correlation between the return of a fund computed directly from its NAV and the return computed from the portfolio of country investments and country-level returns, which provides additional validity to our approximation.

> 16 Time coverage is January 1999-November 2010 for stock market indexes and July 2002-November 2010 for bond market indexes. The total number of observations of stock and bond market indexes across countries and over time is 23,272.

> 17 Interested readers are referred to Raddatz and Schmukler (2011) for a classification of funds by mutual fund family and a more detailed description of the data.

8
) estimator for panel data developed by Arellano and Bond (1991) and Arellano and Bover (1995). We estimate the impact of the middle class on policies and institutions in three broad categories: social policy regarding public expenditures on health and education, market-oriented economic structure on international trade and finance, and quality of governance regarding democratic participation and absence of official corruption. Our analysis thus also relates to the literature investigating the association between poverty, institutions and growth (Dollar and Kraay, 2002; Lopez and Serven, 2009).

We find that when the size of the middle class increases, social policy on health and education becomes more active, and the quality of governance regarding democratic participation and official corruption improves. This does not occur at the expense of economic freedom, as an expansion of 3
In this section we present information on trends in policies sold by BASIX through its company Krishna Bhima Samruddhi Local Area Bank since 2003, using administrative data generously provided to us by them. BASIX was the vendor for ICICI Lombard’s original pilots of rainfall insurance in 2003. After an initial two-year launch with several hundred policyholders in Andhra Pradesh, BASIX expanded into five states in 2005. In that year, 6,694 households purchased over 20,000 phases of insurance, including 43 distinct contracts.

[Figure 6.4 here] [Table 6.1 here] Trends in sales of rainfall insurance by BASIX in Andhra Pradesh are presented in Figure 6.4 and Table 6.1.<sup>6</sup> These data show that there has been a secular increase in the number of phases of insurance sold, as well as the number of customers served. The number of purchasers increases from 194 households in 2003 to 7,567 households in 2009, accounting for 14,542 policies. Note that in the table we draw a scored line below 2004. This is because from 2005 onwards, households were able to purchase individual phases of insurance. (In 2003 and 2004, farmers could only buy a policy covering all three phases of the monsoon—we count that as three phases of coverage for the purposes of calculating figures in Table 6.1.) Note that these trends are not due to any government subsidies, since WBCIS is not active in Andhra Pradesh. Policies are priced and sold on a purely commercial basis.

The “sum insured” in Table 6.1 is the maximum payout of the insurance, meant to correspond to cases of crop failure. As shown by the final column of the table, this amount is generally more than ten times as large as the policy premium in each year of the sample. Thus, the policy provides a very high rate of return in the worst-case scenario, when rainfall is very low.
reduction of the height z‐score by 1.9365. A similar exercise using calories in Column 2 of Table 3 shows a reduction of the height z‐score by 1.7723. Changes in the height z‐score by the above magnitude over 3 years are relatively large to induce a long term adverse impact on subsequent human capital outcomes unless those who were adversely affected have a chance to catch up later on. However, given that children in the non‐producer households had the initial advantage of growing fast, our finding points to convergence in child growth between the two groups.

# **6. Conclusions**

This paper examined the impact of food price spikes experienced during the 2007/08 food price crisis on child nutrition status using rural household panel data in Indonesia. The empirical results show that food price spikes had a significant negative impact on child growth, measured by the height z‐score, among the food non‐producers. There are a few important implications. First, food

> 17 Roles of formal safety net programs such as unconditional cash transfers and rice subsidy program are potentially important.  However, the data cannot identify whether households were eligible in 2007. The (self‐reported) eligibility status in 2010 is an endogenous outcome of changes in food price and household decision makings after 2007.  For this reason, we have not included this variable in the above analysis.

16
can sometimes be positive potential information/incentive effects of quality information being released, as with school report cards (Aturupane et al. 2014; Andrabi, Das, and Khwaja 2017; Bassok, Dee, and Latham 2019). We recommend against using QAS results for sanctions or rewards on a teacher level (raises, promotion, bonuses, retention, or firing), given their imprecision. Likewise, we recommend against rewards or sanctions on a school level for performance. Recognition (e.g., certificates, banners) for top performing teachers or schools may be inaccurate but also may incentivize quality (Cotofan 2021).

When governments lack the resources to provide interventions universally, the QAS can help target interventions. Although imprecise, the information in the monitoring tool is nonetheless an upgrade from not knowing how to target at all. For some interventions, such as hiring additional teachers to reduce class size, other systems (e.g., enrollment and staffing data) may allow equally good or better targeting. For other interventions, such as reading tutors or literacy training, knowing which schools have more children struggling with literacy can be helpful for targeting. QAS results may be too imprecise to accurately target professional development or coaching for teachers. Yet, they could act as a starting point for activities such as coaching (which then includes subsequent observations as well, providing further data on quality). However, implementing tailored coaching at scale can also be quite difficult.

In terms of QAS design, while children’s skills are naturally variable, they do seem to be one of the better-measured items in QAS. Especially since links between observed quality and child outcomes have been found to be weak in QRIS (Zellman et al. 2008; Elicker et al. 2011; Tout et al. 2011; Keys et al. 2013), directly including standards and monitoring children’s skills is also 24