rafmacalaba/datause-encoder-data huggingface dataset:
3

**sheets and adjusting their business models to varying degrees** . European banks gradually started deleveraging as part of the process of cleaning up their balance sheets and shrank by 10– 15 percent. Risk-weighted assets (RWAs), which stood at 12.4 times capital in 2007, fell to 9.5 times in 2010 (figure 4). Banks also sought more stable sources of funding such as retail deposits to substitute for more fickle, short-term wholesale funding sources, which helped reduce their loan to deposit (L/D) ratios from 175 percent to 138 percent from  2007 to 2010 (figure 5). Banks also bolstered capital cushions by 20 percent on average to ease solvency concerns, in part in response to market pressures, as well as to prepare for the phasing-in of the tighter Basel III capital rules over the 2013–19 period.

**Figure 2. Leverage and Reliance on Wholesale Funding**

<!-- Start of picture text --> Asset to Equity Ratio Tier 1 Capital Ratio<br>Q1 2007 and Q4 2010 2007 and 2010<br>25 20<br>20<br>15<br>15<br>10<br>10<br>5<br>5<br>0 0<br>ASIA CEE MENA SSA LATAM EUR OTHER ASIA CEE MENA SSA LATAM EUR OTHER<br>2010 2007 2010 2007<br>Loan to Deposit Ratio<br>Q1 2007 and Q4 2010<br>200<br>150<br>100<br>50<br>0<br>ASIA CEE MENA SSA LATAM EUR OTHER<br>Q4 2010 Q1 2007<br>Percent Percent<br>Percent<br><!-- End of picture text --> Source: Bankscope, Bureau van Dijk. EUR data from European Central Bank (ECB) Consolidated Banking Data Note: ASIA: Asia. CEE: Central and Eastern Europe MENA: Middle East and North Africa. LATAM: Latin America. EUR: Euro Area. SSA: sub Sahara Africa. OTHER: Other developed economies.

**3. Against this background, further reduction in European bank leverage is necessary, particularly because leverage levels are still high** . Some degree of deleveraging is desirable if it is carried out in an orderly fashion and if it involves exiting activities of doubtful economic value, thereby enhancing the soundness of the banking system. Moreover, despite some
9 emigration from country L to country j. Indeed, migration is mostly driven by differences in opportunities and living condition between countries. Since trade influences these differences, it is also likely to affect migratory flows. Markusen and Zahniser (1999) showed that increasing trade can promote economic growth and job creation in the countries involved and thereby diminish the economic reasons for people to migrate. However, introducing migration costs to the Heckscher-Ohlin-Samuelson model, Lopez and Schiff (1998) demonstrated that trade could also help people afford migration costs and thereby favor migratory flows.

In order to identify the causal effects of migration on trade, we need to find good instruments for bilateral migration (variables influencing bilateral migration but not bilateral trade, except through bilateral migration). They should vary both in time and by country pairs in order to be strongly related to bilateral migration and so as not to be dropped after the inclusion of either time or country-fixed effects.

The instrumental variable approach has been rarely used in the large migration-trade literature. Briant et al. (2009) and Combes et al. (2005) stand as exceptions in this regard. These authors have used as instrument the lagged stocks of migrants. In the literature related to the effect of migrant networks on foreign direct investments, Javorcik et al. (2011) proposed an original set of instruments, but most of them do not change over time and are 10 specific only to the migrant’s country of origin. Their only time-varying instrument is a measure of the importance of the existing network of migrants.

Our first instrument measures the existence of a network by the share of migrants from _i_ living in country _j_ with respect to the total of migrants from _i_ in the whole world 10 years 11 earlier. Indeed, a large literature has provided evidence that community networks, by reducing migration costs, positively influence the decision to migrate (Winters et al. 2001; Munshi 2003; Beine et al. 2011). We called this first instrumental variable NLNNNNNii.

Our second instrument, BBBBii, is a dummy equal to one if a bilateral social security agreement exists between the two countries. Bilateral social security agreements provide the

> 9 Parsons (2012) underlined the potential endogeneity bias arising from omitted bilateral variables that explain both trade and migration and include country pair fixed effects as an attempt to control for it.

> 10 Their instruments are the costs of acquiring a national passport in the migrants' country of origin, distance to the European Union, presence of a US military base in the migrant’s country of origin 20 years earlier, a dummy indicating whether the migrant's country of origin allows its citizens to hold dual citizenship. The inclusion of origin-country fixed effects in the estimation would therefore make impossible the use of these variables as instruments.

> 11 We resort to migration stocks of the year 1970 from the World Bank database to construct the instrumental variable for the stock of migrants in year 1980.

9
- 11 -

Even in the infrastructure sector, the number of firms who participate in each auction differs across sub-sectors. While the distributions of the number of bidders in road and telecommunications PPP contracts are not so concentrated, the energy sector has a more skewed distribution toward a left tail. In the water sector one can expect only one to three bidders in most cases.<sup>6</sup> Figure 6. Degree of Competition in PPP Auctions <!-- Start of picture text --> (Energy) (Telecommunications)<br>0.30 0.30<br>Avg. 3.77 Avg. 5.43<br>0.25 0.25<br>0.20 0.20<br>0.15 0.15<br>0.10 0.10<br>0.05 0.05<br>0.00 0.00<br>1 2 3 4 5 6 7 8 9 10 11 12 13~ 1 2 3 4 5 6 7 8 9 10 11 12 13~<br>Number of bidders Number of bidders<br>(Roads only) (Water and sewage)<br>0.30 0.30<br>Avg. 4.68 Avg. 3.61<br>0.25 0.25<br>0.20 0.20<br>0.15 0.15<br>0.10 0.10<br>0.05 0.05<br>0.00 0.00<br>1 2 3 4 5 6 7 8 9 10 11 12 13~ 1 2 3 4 5 6 7 8 9 10 11 12 13~<br>Number of bidders Number of bidders<br>Source: Author’s calculation based on PPI database.<br>Density Density<br>Density Density<br><!-- End of picture text --> The current paper pays particular attention to this difference across infrastructure sectors, which _is_ ignored in the previous work (Iimi, 2006). An obvious disadvantage of focusing on a certain sub-sector is the small sample problem. This is related to a more fundamental empirical question that researchers must consider. One might think that all development 6 Recall that these PPP contracts are not only for infrastructure construction, on which our sample projects focus. Rather, they normally include operation and maintenance after construction and thus tend to require more managerial and operational expertise from contractors. Therefore, the observed degree of competition in PPP auctions may not be directly comparable with our results.
|Land Management and Administration Project|Peter Jipp|
|---|---|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Land Management and Administration Project|Peter Jipp|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Coastal Marine and BiodiversityManagement|Salimata D. Follea|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Namibian Coast Conservation and Management Project|Claudia Sobrevila|
|Laguna de BayInstitutional Strengtheningand CommunityPa|rticipaGerardo Pio Francisco Parco|
|Laguna de BayInstitutional Strengtheningand CommunityPa|rticipaGerardo Pio Francisco Parco|
should form the basis of policy formulation on what drives structural change and growth. In this section we focus on one country, India, to illustrate this process in action. Our evidence base remains incomplete. Nonetheless the work we describe illustrates how microeconomic analysis at the sub-national level is beginning to provide the detail on what is important at the local level. It is this detail, which is directly useful to policy makers.

The basic pattern of structural change in India is shown in Figure 3 where we graph real agricultural and non-agricultural output per capita over the 1960-1997 period for the 16 main states of India. Agricultural output per capita remained relatively flat over the period. Economic growth was driven in large part by the rise in non-agricultural output. In 1960 average real state non-agricultural and agricultural output per capita were of similar magnitudes at Rs. 406 and Rs. 425 respectively. By 1997, non-agricultural output at Rs. 2,814 was more than double agricultural output (Rs. 1,266). The pattern of markedly different across states. A similar picture emerges in Figure 4 when we examine manufacturing, which is often seen as the engine of structural change.<sup>5</sup> Certain states -- Andhra Pradesh, Gujarat, Haryana, Karnataka, Punjab, Tamil Nadu and Maharashtra -- show rapid growth in registered and unregistered manufacturing, while states like Assam, Bihar, Jammu and Kashmir, Kerala, Uttar Pradesh and West Bengal display relative stagnation (albeit from different base levels).

And these differences in economic performance have profound consequences for welfare. India is unusual amongst developing countries in having carried out household expenditure surveys on a regular basis since the 1950s which allows consistent and comparable poverty series to be constructed (see Ozler, Datt and Ravallion, 1996). In Figure 5 we graph rural and urban poverty headcounts (which capture the percentage of the rural and urban population in poverty) for the 16 main Indian states across the 1958-2000 period.

5 Manufacturing in India is divided into a registered or organized sector (which is regulated, and covers firms with employment levels above 10 with electricity and above 20 without) and an unregistered or unorganised sector (which covers firms below these thresholds).

23
expanding supplies and falling world prices, quotas have been declining during much of this period. A similar program is employed in Europe.

Despite their name, antidumping duties, now the leading source of contingent protection, are sought and imposed to prevent sector-specific losses and not to counteract dumping.<sup>19</sup> For example, the steel industry, by far the largest user of U.S. antidumping law,<sup>20</sup> has historically benefited from many types of protection. The policies were clearly geared toward maintaining prices—as evidenced by the 1977 trigger-price mechanism, which established a minimum import price, and a series of voluntary restraint agreements. As those types of protection were gradually eliminated by the GATT, the sector has turned to antidumping to prevent losses when prices declined. A particularly interesting feature of the steel industry, which further demonstrates that antidumping is about losses, is that during world price slumps only a _declining subsector_ , the integrated producers, called for protection. From 1969 to 1999, price declines led to increased calls for protection from the old-fashioned integrated producers, where production was declining and profits were falling. In contrast, minimills, which used new electric-arc technology and experienced output and profit growth, refused to sign on to antidumping petitions. Figure 9 shows the U.S. and world prices of steel. Again, the clear picture is of one where domestic firms are sheltered from price declines. Before March of 1999, average domestic prices were kept above $350 per metric ton while the world price fluctuated between $230/ton and $450/ton. Only in recent years, as the integrated sector shrunk and many plants were shut down, protection level began to decline and domestic prices finally broke the $350/ton barrier.

Limiting losses is reflected in U.S. Trade Adjustment Assistance program as well. For example, the extent of assistance provided to farmers is based on the difference between the current price and the average price of a given product over the last five years, i.e. the industry losses. This is rather different from the estimated cost of adjusting to a more competitive environment, which is the original motivation behind the program.

In sum, the main forms of protection in use today are initiated by price declines and appear to be guided by a desire to maintain domestic prices above some reference

> 19 See Tharakan (1996) for a survey of the evidence. 20

> About half of the more than 200 antidumping orders currently in force are on imported steel.

26
_39_ <!-- Start of picture text --> Jamsostek's Retirement Program<br>Projected Fund Size<br>800.000 o . . - - . . .. . . . . .3.00%<br>600.000<br>/ i < fundsee \_ 2.00%<br>400.000 f | + fundszeeas%of<br>1.00%<br>200.000<br>0.000 0.00%<br>1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045<br><!-- End of picture text -->

_Disclosure_ Sponsors of approved company pensions are required to provide reports to members at least annually. In addition, independently audited financial statements as well as actuarial assessments must be submitted to regulators once a year. These rules do not apply to Jamsostek program, however. The disclosure under the program has been inadequate. Apart from the assets which have not been accounted for, individual members do not receive regular reports on the current status of their accounts. Some companies have been able to receive the reports upon requests, but only after long delays. Pt. Astek's management says that efforts are being made to upgrade the information system, with the hope of giving individual members electronic access to their accounts by way of "Jamsostek Cards." _Credibility_ Many features of the Jamsostek program have opened up significant opportunities for rent seeking. The mandatory-participation rule gives enforcement officials a chance to engage in petty extortion, particularly from small firms that have not enrolled. These firms may find it advantageous to pay a bribe, rather than making full contributions. Furthermore, since Pt. Astek is the sole administrator of the program with no competing service providers, its employees are in a position to extract personal benefits in return for any services rendered. More significantly, Pt. Astek is in charge of a large sum of assets. Those with the authority for making investment decisions may be guided more by self interests than by an abstract sense of fiduciary responsibility, as the experience of many state banks has shown.

# **Options for Reform**

The considerations above make Jamsostek a dubious choice of public policy. Of greater concern perhaps is the risk that the widespread public distrust of Jamsostek would undermine the credibility of a government that otherwise has an excellent record on promoting growth and social equity.

_Should Jamsostek be abolished?_ An emerging view among responsible public officials is to close down the Jamsostek program. Under the current circumstance, little would be lost by such measure. There would be considerable public support, from both companies and workers alike. Nearly half the Jamsostek subscribers are already covered by approved company plans.
We focus on the sample of male-owned enterprises as, similarly to the SLMS, Fafchamps et al. (2014) find no impact on female-owned businesses.

Firms were surveyed twice before treatment, in October-November 2008, and in February 2009. Then, firms that completed the baseline rounds were randomized into either a control group (396 firms), or a cash or in-kind treatment groups (198 firms each). Firms were then surveyed quarterly in May 2009, August 2009, November 2009, and February 2009. Following Fafchamps et al. (2014), we group these four follow-up rounds together. An additional long-term follow-up survey was conducted in March 2012, approximately three years after the intervention.

## <u>Variable details:</u>

- indicator to one if the still owns and

- Self-employment: equal respondent operates a business (survey introduction question 6), or if he is operating a different business (introduction question 11 ”What it your main activity now?”).

- Any employment: if the respondent is self-employed (see previous point) or wage worker (introduction question 11).

- Migration: all business owners participating in the study are initially living in either Accra, the capital city, or the nearby industrial city of Tema. We therefore code migration as moves outside the Greater Accra Region. We take migrants’ location from introduction question 6 (”If [the household is not living at the same address as the previous round], record the new address of the household”). Instances of migration mainly involve moves to the towns of Kasoa, to Nsawam or to Manhyia.

# **C.7 Nigeria Youth Enterprise With Innovation in Nigeria (YouWin!)**

The YouWin! competition was launched in late 2011 by the Nigerian government, attracting approximately 24,000 applications that presented ideas to start a new business or grow an existing one. The prize of the competition were grants averaging $50,000. Top applications were chosen to attend a four-day business plan training, after which program participants had to submit a detailed plan on how they would develop their initial business idea. Plans were again ranked and, of 2,400 semi-finalists, the 475 firms with highest scores (overall and within region) were selected as nonexperimental winners, while 1,841 firms entered the experimental sample (79 firms were dropped because of low score and 5 firms were disqualified). Among the experimental sample, treatment was randomized within strata (defined by region, gender, 64
Under the threat of sanctions, the migrant is truthful but only up to the threshold, which is sufficient to explain our empirical findings. Finally, our empirical analysis, together with theoretical insights, suggests that the reported earnings ratio is a useful summary statistic of direct and indirect effects of informational asymmetries on remittance flows, calling for further research.

# REFERENCES

Ambler, K. 2015. “Don’t tell on me: Experimental evidence of asymmetric information in transnational households.” _Journal of Development Economics_ 113, 52–69.

Ashraf, N. 2009. “Spousal Control and Intra-Household Decision Making: An Experimental Study in the Philippines.” _American Economic Review_ 99 (4): 1245–1277.

Ashraf, N., D. Aycinena, C. Martinez, and D. Yang. 2015. “Savings in Transnational Households: A Field Experiment Among Migrants from El Salvador.” _Review of Economics and Statistics_ 97 (2), 332–51.

Banerjee, B. 1981. “Rural–Urban Migration And Family Ties: An Analysis Of Family

- Considerations In Migration Behaviour In India.” _Oxford Bulletin of Economics and Statistics_ 43 (4), 321–55.

Chen, J. J. 2006. “Migration and Imperfect Monitoring: Implications for Intra-Household Allocation.” _American Economic Review Papers and Proccedings_ 96 (2), 227–31.

- ———. 2013. “Identifying Non-cooperative Behavior among Spouses: Child Outcomes in Migrant-Sending Households.” _Journal of Development Economics_ 100 (1), 1–18.

Chort, I., F. Gubert, and J. Senne. 2012. “Migrant Networks as a Basis for Social Control:

- Remittance Incentives among Senegalese in France and Italy.” _Regional Science and Urban Economics_ 42 (5), 858–74.

33
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|---|---|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|GH-GAMA Sanitation and Water Project|Yitbarek Tessema Mammo|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|Hubei XiangyangUrban Transport|Weimin Zhou|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|
|URBAN WATER SUPPLY AND WASTEWATER|AbedalrazqF. Khalil|