rafmacalaba/datause-encoder-data huggingface dataset:
# **China double its per capita income at a remakable rate**

<!-- Start of picture text --> Lnited Kingdom<br>(1780-1838)<br>United States<br>(1839-86)<br>Japan (1885-1919)<br>Korea, Rep. of<br>(1966-77)<br>China (1978-87)<br>China (1987-96)<br>0 10 20 30 40 50 60<br>Years taken to double per capita incomes<br><!-- End of picture text -->

**Key** Challenges

Despite China's achievements since 1978, the Govemnment faces significant challenges over the medium-term, which can be broadly divided into two sets: (i) achieving sustainable growth within a stable macroeconomic environment; and (ii) reducing poverty and maintaining a relatively egalitarian distribution of income and wealth.

- Sustainable Growth and Stability. China's economy has experienced a strongly cyclical pattern of growth, withl periodic episodes of overheating and inflation followed by contractionary policies leading to slharp declines in growth. Large _aggregate putblic sector deficits_<sup>_3_</sup> estimated at 11.5% of GDP over 1987-93 developed, driven by weak tax collections, SOE investment demand and the political commitment to support loss-making SOEs. This fueled inflationary pressures which, in the absence of indirect macroeconomic policy instruments, could only be held in check by the application of blunt administrative measures. The fundamental causes of macroeconmic instability remain, even though the recent cycle (1994-95) of overheating was cooled down through a skillful use of administrative measures, and "soft landing" was achieved. Growth is further hampered by bottlenecks in infrastrLcture and energy. In addition. development activities increasingly strain theenvironment, and some of China's cities are now among the most polluted in Asia.

- Managing financial risks and averting crisis. State-owned bank are burdened with bad-loans accounting for about 20 percent of its total assets. It needs to be re-capitalized if financial crisis is to be prevented. Public finances, already weakened by difficulties in revenue collection, will continue to face pressures, both from the support of SOEs as well as from the long-term need for substantial expenditure increases in key areas such as infrastructure,

- The aggregate public sector deficit measures the excess of expenditures over revenues for the consolidated government and state-enterprise system.

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a global investor, as in CAPM. Second, we investigate whether the tails of the returns distribution (e.g., 10th percentile, 90th percentile) vary with country characteristics by estimating Equation (1) as a quantile regression. The quantile regressions allow us to make statements about whether country characteristics make certain markets riskier in the sense that tail outcomes are worse in those markets, compared to markets with different characteristics. An additional advantage of the quantile regressions is that they are not sensitive to the positive outliers and right-skew that characterize returns data.

# **3 Data**

## **3.1 Background on the International Finance Corporation**

The source of the data is the International Finance Corporation (IFC). The IFC seeks through its investments to contribute to improvements in social and environmental outcomes aligned with the United Nations’ Sustainable Development Goals (IFC 2019b). Historically, before the elaboration of these goals, it sought to provide capital to economies in which it was scarce. The institution is owned and governed, its policy determined, and equity capital provided by 185 member countries. Development-related investments account for $43 billion of its approximately $99 billion balance sheet, the remainder being liquid securities (IFC 2019c). The carrying value of its equity investment portfolio is 30 percent of development-related investments. Figure 1 charts the institution’s financial history in three ratios: return on equity (net income/total capital), leverage (total assets/total capital), and administrative expense (non-interest expense/total assets). Values used in calculating these ratios were transcribed from the annual reports and are reported in Table A1 (to our knowledge this series does not exist elsewhere).

The IFC’s first loan, made in 1957, provided $2 million to Siemens’ Brazilian affiliate (IFC 2018). A 1961 amendment to the charter allowing the holding of equity led to a surge in equity investment during 1963-64 to about 50 percent of total investment (Kapur et al. 1997). Since the 1960s, this share has fluctuated between 15 and 35 percent. Equity investment in private markets has been the basis for growth in the capital base through retained earnings, with realized gains from these investments leading, as seen in Panel A, to high points in return on equity in 1989 (RoE = 12.4 percent) and 2005 (20.5 percent).

Funds for the IFC’s operations are raised in international capital markets. Its leverage ratio, as shown in Figure 1, Panel B, was 3.6 in 2019. The extent of borrowing varies substantially across institutions owned by governments seeking to promote economic development through investment in private firms.<sup>6</sup>

> 6For instance, the 1.0 leverage ratio of the United Kingdom’s CDC Group (2019) indicates it does not borrow at all; while the 5.8 leverage ratio of the European Investment Bank (2020) and 12.9 leverage ratio of the China Development Bank (2017) show these banks borrow considerably relative to their capital base. The CDC Group and the European Investment Bank are signatories to the Operating Principles for Impact

6
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- **Devictor, Xavier, Quy-Toan Do, and Andrei A Levchenko.** 2021. “The globalization of refugee flows.” _Journal of Development Economics_ , 150: 102605.

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- **Durkheim, Emile.** 1897. _Le Suicide: Etude de Sociologie._ Presses universitaires de France.

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- **Fasani, Francesco, Tommaso Frattini, and Luigi Minale.** 2021 _a_ . “Lift the Ban? Initial Employment Restrictions and Refugee Labour Market Outcomes.” _Journal of the European Economic Association_ , forthcoming.

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- **Felfe, Christina, Helmut Rainer, and Judith Saurer.** 2020. “Why birthright citizenship matters for immigrant children: Short-and long-run impacts on educational integration.” _Journal of Labor Economics_ , 38(1): 143–182.

- **Fisman, Raymond, Pamela Jakiela, and Shachar Kariv.** 2015. “How did distributional preferences change during the great recession?” _Journal of Public Economics_ , 128: 84–95.

- **Gathmann, Christina Monscheuer, et al.** 2020. “Naturalization and citizenship: Who benefits?” _IZA World of Labor_ .

- **Gehrsitz, Markus, and Martin Ungerer.** 2017. “Jobs, crime, and votes: A short-run evaluation of the refugee crisis in Germany.” _IZA DP No. 10494_ .

- **Giuliano, Paola, and Antonio Spilimbergo.** 2014. “Growing up in a Recession.” _Review of Economic Studies_ , 81(2): 787–817.

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the delays are independent of unobservable characteristics in the program areas that may also influence program impact. An evaluation of Madagascar’s SEECALINE program defined the start of the program in each treatment site as the date of the first child-weighing session in that site. The area-specific date takes into account the program’s approach of gradual and sequential expansion, as well as the expected delays between the signing of the contract with the implementing NGO and when a treatment site is actually open and operational (Galasso and Yau 2006). This method requires detailed program monitoring data.

If a program has many components, the solution could hinge on the evaluator’s understanding of the technical production function and thus on identifying the elements that must be present for the program to be effective. For example, in a school improvement program that requires additional teacher training as well as instructional materials, the materials might arrive in schools at about the same time, but the additional teacher training might be achieved only over a period of several months, perhaps due to differences in teacher availability. Whether the effective program start should be defined according to the date when the materials arrive in schools or when all (or majority?) of the teachers have completed their training is a question that an evaluator has to address in deciding on the timing of the evaluation. In the Madagascar example above, although the program has several components (e.g., growth monitoring, micronutrient supplementation, de-worming), the inception date of each site was pegged to a growth monitoring activity, that of the first weighing session (Galasso and Yau 2006).

Although the primary objective of evaluations usually is to measure the impact of programs, often they also monitor progress during the course of implementation and thus help to identify problems that need correction. An evaluation of the Bolivia Social Investment Fund illustrates this point clearly (Newman et al. 2002). One of the program components was to 9
from being the ideal indicator. Since there is only one indicator, we do not need to use PCA. Instead, Table 4 shows the top, middle and bottom terciles.

**Table 4 - Active Labor Market Policy Spending Results**

|**Active Labor Market Policy**<br>**Spending**|**Country**|
|---|---|
|Low|Albania, Armenia, Bulgaria, Georgia,<br>Macedonia FYR, Moldova, Serbia,<br>Ukraine|
|Medium|Czech Republic, Hungary, Kazakhstan,<br>Latvia, Russian Federation, Slovak<br>Republic,Turkey|
|High|Azerbaijan, Croatia, Estonia, Lithuania,<br>Poland,Romania,Slovenia|

Source: Authors’ calculations There is significant variation in ALMP spending per unemployed in the ECA region. On the one hand, countries like Azerbaijan, Croatia, Estonia, Lithuania, Poland, Romania, and Slovenia are relatively high spenders - almost all are spending more than 1000 USD on average. On the other hand, Albania, Armenia, Bulgaria, Georgia, Macedonia FYR, Moldova, Serbia, and Ukraine all spend under 200 USD per person.

# _d. Social protection_

Given the need to provide a safety net for workers that are displaced by the introduction or increase in the price of carbon, the social protection dimension refers to the readiness of the social assistance and the unemployment benefit system to respond to the shock. Social protection has been identified as a critical component of not only a proper response to climate change challenges, but more broadly, of any government response to economic and social shocks (EU, 2008; World Bank, 2011b).

As indicators of this dimension, we use the total spending on social assistance benefits, the duration of unemployment benefits, benefit levels (average unemployment benefit/average wage) and a quality indicator of last resort social assistance and child benefit programs developed by the ECA Social Protection team<sup>18</sup> for the readiness of social benefits to respond to shocks.

**Table 5 - Principal Component Analysis – Social Protection Performance Results**

|**Social Protection Readiness**|**Country**|
|---|---|
|Low|Latvia, Macedonia FYR, Moldova,<br>Russian Federation, Slovenia, Serbia,<br>Turkey|
|Medium|Albania, Azerbaijan, Bulgaria, Croatia,<br>Kazakhstan,Poland,Romania|
|High|Armenia, Czech Republic, Estonia,<br>Georgia, Hungary, Lithuania, Slovak<br>Republic,Ukraine|

Source: Authors’ calculation

> 18 The ECA SP team monitored social benefits responses on a monthly basis using administrative data in 14 countries from 200810 to track the response of benefits to the global crisis. See findings in report by Isik-Dikmelik (forthcoming).

16
De Loecker Jan. 2007. “Do Exports Generate Higher Productivity? Evidence from Slovenia.” _Journal of International Economics_ , 73, September 2007, 69–98 Foster, Lucia, John Haltiwanger and Chad Syverson. 2005. “Reallocation, Firm Turnover, and Efficiency: Selection on Productivity or Profitability?” Institute for the Study of Labor IZA DP No. 1705, August.

Görg, Holger and Eric Strobl. 2001. "Multinational companies and productivity spillovers: A meta-analysis." _Economic Journal_ 111, F723-F739 Greenaway, David and Richard Kneller. 2007. “Firm Heterogeneity, Exporting and Foreign Direct Investment: A Survey.” _Economic Journal_ 117, F134-F161.

Hallward-Driemeier, Mary, Giuseppe Iarossi and Kenneth L. Sokoloff. 2002. “Export and Manufacturing Productivity in East Asia: A Comparative Analysis with Firm-Level Data.” NBER Working Paper 8894.

Isgut, Alberto and Ana Fernandes. 2007. "Learning-by-Exporting Effects: Are They for Real?" MPRA Paper 3121, University Library of Munich, Germany.

Kaufmann, Daniel, Kraay, Aart and Massimo Mastruzzi, 2007. **"** Governance Matters V: Governance Indicators for 1996-2006, **"** World Bank Policy Research Working Paper 4280.

Lileeva Alla and Daniel Trefler. 2007. “Improved Access to Foreign Markets Raises PlantLevel Productivity ... for Some Plants.” NBER Working Paper No. 13297.

López, Ricardo A. 2005. “Trade and Growth: Reconciling the Macroeconomic and Microeconomic Evidence.” _Journal of Economic Surveys_ 19, 623-648.

Melitz, M. J. (2003). “The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity.” _Econometrica_ 71, 1695-1725.

Oulton, Nicholas and Mary O’Mahony. 1994. “Productivity Growth – A Study of British Industry 1954-1986”, The National Institute of Economic and Social Research Occasional Papers XLVI, Cambridge: Cambridge University Press.

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could argue that it would be harder to increase the average income of such large masses of people than would be the case in a smaller country. Other than China, the other fastest growing deciles are the relatively poor deciles in El Salvador, Costa Rica, Ireland, the UK and Chile.

|<br>**Table 5: Winners an**<br>**annualised growth**|<br>**d losers in**<br>**(1988-2008**|<br>**terms of aver**<br>**)**|<br>**age**|
|---|---|---|---|
|**20 biggestga **|**iners**|**20 bigg **|**est losers**|
|**(best at the**|**top)**|**(worst at t**|**he bottom)**|
|**decile**|**growth**|**decile**|**growth**|
|El Salvador-1|9.6%|Bulgaria-1|-4.4%|
|Costa Rica-1|7.9%|Lithuania-6|-4.5%|
|China-urban-10|7.7%|Romania-8|-4.6%|
|Ireland-1|7.2%|Lithuania-4|-4.7%|
|Mexico-10|6.6%|Estonia-2|-4.7%|
|China-urban-9|6.5%|Romania-7|-4.9%|
|China-urban-8|6.1%|Estonia-3|-4.9%|
|China-urban-7|5.9%|Lithuania-5|-4.9%|
|China-urban-6|5.7%|Estonia-7|-5.1%|
|China-rural-10|5.6%|Romania-6|-5.1%|
|Ireland-2|5.6%|Romania-5|-5.3%|
|China-urban-5|5.6%|Estonia-4|-5.3%|
|UK-1|5.5%|Romania-4|-5.5%|
|China-urban-4|5.4%|Estonia-6|-5.5%|
|Ireland-3|5.3%|Romania-3|-5.6%|
|China-rural-9|5.1%|Estonia-5|-5.6%|
|China-urban-3|5.1%|Romania-2|-5.8%|
|Ireland-4|5.1%|Bolivia-1|-6.0%|
|Chile-1|5.0%|Estonia-1|-6.4%|
|China-urban-2|4.9%|Romania-1|-7.4%|
|_Notes: Only for coun_<br>_which have at least_<br>_numbered 1 to 10, w_|_tries observ_<br>_one 5-year g_<br>_ith 1 being_|_ed in 1988 an_<br>_rowth interv_<br>_the bottom d_|_d 2008, and_<br>_al. Deciles are_<br>_ecile._|

Among the bottom, there is a similar concentration. With the exception of Bolivia, East European deciles are almost solely filling up the ranks of the most unsuccessful groups.<sup>79</sup> Practically all deciles in Romania and Bulgaria seem to have experienced negative growth. An average decline of 3-4% per annum translates, after 20 years, in a real income loss of about one-half. The results

> 79 Ranking by 20-year growth rates changes the results slightly as the bottom deciles of Honduras and Paraguay are amongst the twenty least successful deciles. This is also the case for the least successful deciles in terms of 15-year growth rates (Appendix Table 4), where Kenya and Tanzania have performed particularly poorly.

45
where supply and demand depend on the system of prices. Policies are introduced as shocks; the system changes with optimal supply and demand behaviors adjusting, and the allocation and the supporting price system evolve towards a new equilibrium. Therefore, as with all CGE models, RHOMOLO evaluates the interaction effects between all agents through markets, imposing complete consistency. Given the regional focus of RHOMOLO, particular attention is devoted to the explicit modeling of spatial linkages, interactions, and spillovers between regional economies. For this reason, models such as RHOMOLO are referred to as Spatial Computable General Equilibrium (SCGE) models. Each region is inhabited by households aggregated into a representative agent with preferences characterized by a love for variety à la Dixit-Stiglitz (Dixit and Stiglitz, 1977). Transport costs for trade between and within regions are assumed to be of the iceberg type and are sector- and region-pair specific. This framework implies a 5 x 267 x 267 asymmetric trade cost matrix derived from the European Commission’s transport model TRANSTOOLS (see Brandsma et al., 2015).

# **2.1 The Italian Context**

Regarding the regional CGE models presented for Italy, Gesualdo and Rosignoli (2013) presented TUSCANI, a single-region comparative-static CGE model for the Tuscan economy. It is a SAM-based model built by the Institute for Regional Economic Planning of Tuscany (IRPET) and refers to 2008. It focuses on the income generation process and re-distribution for the households. In TUSCANI, the regional SAM consists of 37 industries, 54 commodities, and 17 institutional sectors. The households are divided into ten groups by percentiles of gross income. The interregional trades are estimated using a gravity model. This model is consistent with the neoclassical theory. TUSCANI does not explicitly model margins.

In 2018, Paniccià and Rosignoli (2018) proposed the most recent IRPET methodology as a NUTS2 level multiregional Supply and Use Table for 2011. This new model updates the previous one by considering more regional data and differentiating multiregional and foreign trade in final and intermediate flows.

Fondazione ENI Enrico Mattei (Standardi et al., 2014) proposed an innovative method to estimate bilateral trade flows across sub-national areas and analyze the implications of different assumptions. They used the GTAP model (Hertel, 1997) for Italy and split the Italian economic system into ten sectors and three macro-regions (North, Centre, and South). The regionalization is obtained through a two-step approach: (1) working on a database creating a sub-national SAM for interactions between sub-national areas and with the rest of the world; and (2) working on the model structure, which allows the introduction of different degrees of factors and goods mobility. The model consists of 57 sectors, and the 4
have specifically summarized the (quasi‐)experimental literature and their scope was narrower. For instance, Page & Scott Clayton (2016) focus only on college access in the United States, while Deming & Dynarski (2009) only discuss financial aid. In addition, these reviews discuss the conclusions of the literature in a narrative form without systemically providing the estimates on which they are based. The present overview conveys the results in a narrative form but also rigorously gathers, provides, and compares the causal effects on both access and completion.

The present review discusses 75 studies that provide causal estimates of the impact of outreach and financial aid interventions on access or completion rates of disadvantaged students in higher education. Outreach interventions are defined as policies that target youth in secondary education and aim to raise participants’ aspirations and readiness for higher education. These include interventions that provide information, counseling, and/or focused academic tutoring in order to increase and facilitate transition to higher education. Financial aid includes monetary help provided to students to meet, at least partially, their financial need for higher education. In this category, we discuss universal, need‐based, merit‐based, and performance‐based grants, loans and tax incentives. Finally, we discuss the effects of interventions which have combined outreach and financial aid. In addition to outreach interventions and financial aid policies, a number of other interventions may help reduce inequalities in higher education but the available (quasi‐)experimental evidence on their efficiency is currently insufficient for a literature review and these results are not discussed here.

# **2. Barriers faced by disadvantaged students in higher education**

Outreach and financial aid may help disadvantaged students to access and complete higher education if these interventions efficiently address some of the barriers met by disadvantaged students in higher education. We summarize the most common hypotheses discussed in the current literature on education inequality mechanisms. These include (1) financial barriers, (2) lack of academic preparation, (3) lack of information and, (4) behavioral barriers. While there may be additional mechanisms that prevent disadvantaged students from succeeding in higher education (e.g. negative self‐identities or discrimination), these mechanisms are not specifically addressed by financial aid or outreach programs and are not discussed here.

3
44

# **TABLE 24**

# **KNOWLEDGE OF ENTITLEMENTS IN RELATION TO INDUSTRY TYPE**

(%)

|B.a|SZ-.o5<br>,|.<br>,:'<br>:.................|..................<br>**.........**|**.........**|,SSE:|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|Textile|51|<br>41.2|58.8|41.2|58.8|39.2|60.8|52.9|47.1|33.3|66.7|
|Garment|127|<br>47.2|52.8|33.9|66.1|27.6|72.4|37.0|63.0|30.7|69.3|
|Footwear|76|<br>28.9|71.1|22.4|77.6|17.1|82.9|19.7|80.3|15.8|84.2|

|*.EEERBBE:R<br>gxRRR$EE>Ns<br>Sgx**.**<br>'..<br>RXs..<br>..<br>><br>...en|<br>E,,,,,,,,sX|g||||||
|---|---|---|---|---|---|---|---|
|Textile|60|28.3|71.7|5.0|95.0|5.0|95.0|
|Garment|155|28.4|71.6|1.9|98.1|1.9|98.1|
|Footwear|r85|16.5|83.5|1.2|988|1.2|98.8|

Note: UMR Minimum Regional Wage The level of awareness is further determined by other characteristics such as where workers are from, their age, level of education and work experience. Respondents from Java have a higher level of awareness of the rules and regulations compared to respondents from other places (Table 25). An explanation for this difference is that most of the respondents are from Java and that there is the spread of information through communication between workers. From the 300 respondents interviewed, 43 percent are from Central Java and East Java. People from the same area usually live in the same proximity, and this adds to the sharing of information.