rafmacalaba/datause-encoder-data huggingface dataset:
participants divided by gender, age, and social status. In each urban Ward, eight focus group discussions were held, including seven groups of local people and one group of local officials. These included:

- Unregistered poor female migrants

- Unregistered poor male migrants

- Local poor women

- Local poor men

- Young people (mixed male and female groups) aged 18-26 years

- Children aged 12-16 years

- SME owners and entrepreneurs

- Ward and District officials.

Each of these urban groups was allocated 3 to 5 discussion themes from the research framework so that every theme could receive sufficient opinions from women, men, the poor, adults, young people, business people and officials at both ward and district levels. Ethnicity was also a concern in these urban districts since the proportion of ethnic Chinese in some selected wards ranged from 50% to 80% of the population.

In all urban and rural locations, focus group discussions were also held with District and Commune/Ward leaders and officials, representatives from concerned sector services and mass associations. These generally took the form of one-day workshops, in which the participants were divided into thematic or sectoral groups relating to different components of the Strategy. For instance, the District participants in Lao Cai Province were divided into three thematic discussion groups as follows:

- _District leadership, planning and finance sectors:_ District Peoples Committee; the Party; Fatherland Front; Peoples Council; Women's Union; District Planning Section; Finance Section; Bank for the Poor; and the District Treasury.

- _Social sectors:_ District Health Section; Education Section; Insurance Company; Culture Section; Radio and television service; the Labor, Invalids and Social Affairs Section; Women's Union; and Youth Union.

- _Production and construction sectors:_ District Agriculture and Rural Development Section (extension & irrigation); Construction Section; Cadastral Office; Fixed cultivation and settlement; and the Farmers Association.

# **Factors influencing participation**

A range of factors that influenced representation and participation in the consultation meetings. In some cases it was not possible to get adequate representation from the intended participant groups, while in others there was over representation of certain groups. In one of the consultation sites where only limited participatory research of this type had been done before, it was found 25
<u>Table 5. Mean hours per day, by the presence of children at home, type of activity and sex</u>

|||<br>Unaid<br>Wo|<br> <br>men|<br>Leisure<br>Without Childr|<br>en at Hom|<br>Unaid<br>e<br>M|<br>en|<br>Leisure|
|---|---|---|---|---|---|---|---|---|
||Market<br>work|<br>p<br>domestic<br>work|Personal<br>care|<br>,<br>social and<br>study|Market<br>work|<br>p<br>domestic<br>work|Personal<br>care|<br>,<br>social and<br>study|
|Albania|1.96|5.59|11.34|5.05|4.31|0.65|12.04|6.96|
|Argentina|2.94|3.08|n.a.|0.04|4.68|1.27|n.a.|0.03|
|Bangladesh|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|
|Colombia|3.16|3.65|10.27|7.32|5.32|1.18|9.98|7.52|
|Ecuador|2.95|3.94|9.76|5.00|5.22|1.27|9.51|5.02|
|Ghana|3.07|4.12|12.99|4.86|3.46|3.23|11.97|6.36|
|Guatemala|2.67|6.75|10.88|2.61|6.75|1.27|10.94|3.17|
|Iraq|1.03|4.51|n.a.|6.90|4.74|1.48|n.a.|7.21|
|Mexico|3.54|3.75|n.a.|13.84|6.01|1.43|n.a.|13.75|
|Moldova|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|
|Mongolia|2.96|5.69|11.72|3.78|3.18|5.12|11.59|4.58|
|Pakistan|0.53|5.98|13.99|3.44|4.63|2.96|12.63|3.76|
|West Bank and Gaza|1.34|0.20|12.30|6.65|4.77|0.07|11.53|7.09|
|Peru|3.74|4.19|9.77|5.71|5.98|1.91|9.55|6.13|
|South Africa|3.58|3.86|12.72|3.93|6.20|2.16|11.95|4.15|
|Timor|1.65|1.61|n.a.|n.a.|2.97|1.06|n.a.|n.a.|
|Turkey|0.93|4.21|11.19|5.74|3.02|0.50|10.91|6.02|
|Uruguay|4.62|5.16|9.43|2.49|6.25|1.93|9.26|2.33|
|USA|3.74|2.62|10.88|5.96|4.64|1.86|10.41|6.63|

|||Unaid<br>Wo|men|Leisure<br>With Childre|n at Home|Unaid<br>M|en|Leisure|
|---|---|---|---|---|---|---|---|---|
||Market<br>work|<br>p<br>domestic<br>work|Personal<br>care|<br>,<br>social and<br>study|Market<br>work|<br>p<br>domestic<br>work|Personal<br>care|<br>,<br>social and<br>study|
|Albania|2.30|5.26|11.23|5.13|5.07|0.47|11.93|6.53|
|Argentina|2.36|4.63|n.a.|0.03|5.61|1.31|n.a.|0.02|
|Bangladesh|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|
|Colombia|2.93|4.62|10.12|6.25|5.89|1.17|9.86|6.85|
|Ecuador|2.61|6.39|9.76|4.31|5.91|1.43|9.50|4.41|
|Ghana|2.54|6.33|12.29|4.07|2.83|4.26|11.97|6.00|
|Guatemala|2.62|6.65|11.06|2.36|6.76|1.01|11.15|3.09|
|Iraq|0.49|4.54|n.a.|5.97|5.54|1.38|n.a.|6.35|
|Mexico|2.96|7.08|n.a.|13.04|7.00|1.85|n.a.|12.79|
|Moldova|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|n.a.|
|Mongolia|2.87|6.77|11.37|3.07|3.69|5.59|11.53|3.63|
|Pakistan|0.47|8.65|12.49|2.36|5.41|3.04|12.14|3.40|
|West Bank and Gaza|0.85|3.92|10.86|6.07|5.58|0.52|11.20|6.35|
|Peru|2.99|6.31|9.77|4.43|6.59|2.28|9.54|5.10|
|South Africa|2.43|5.55|12.16|4.00|5.79|2.23|12.03|4.67|
|Timor|1.05|2.38|n.a.|n.a.|2.68|1.30|n.a.|n.a.|
|Turkey|0.92|5.71|10.81|4.89|4.19|0.47|10.74|4.93|
|Uruguay|3.91|8.50|9.44|2.11|7.19|2.93|9.08|1.98|
|USA|2.98|4.28|10.62|4.93|5.30|2.55|10.25|5.30|

Source: Authors’ elaboration based on survey data. Notes: Women and men aged 15 to 64. In Argentina, the starting age is 18. Children defined as 14 years of age or less except for Pakistan and South Africa where they are defined as 6 years of age or less.

33
unemployment rates on its own, but the effects tend to be modest. A sustained reduction in unemployment rates requires an integrated and well coordinated package of policy interventions. We argue that an integrated package that can rapidly reduce unemployment rates for all categories of workers would seek the following general objectives: (i) foster total factor productivity growth through better quality and the improved relevance of the diplomas/specialization supplied by the higher education and VT system, as well as better incentives to invest in in-service training; (ii) increase investments and promote faster growth in sectors intensive in highly-skilled workers; and (iii) reform the social security system to control labor costs. Such a package could also reduce the size of the informal sector, which implies an improvement in the average quality of the jobs created. The challenge of course is to identify the specific policies that would achieve these objectives. Several are discussed in a recent report on skills development, social protection, and employment in Morocco (see World Bank, 2007).

# **_References_**

Abdelkalek T. and J.M. Dufour. 2006. “Confidence Regions for Calibrated Parameters in Computable General Equilibrium Models, _Annales d’Économie et de Statistique_ , N° 81, pp. 1-31.

P.R. Agenor A. Izquierdo and H.T. Jensen. 2007. _Adjustment Policies, Poverty, and Unemployment: The IMMPA Framework_ , Blackwell Publishing.

Agénor, P.R. and K. El Aynaoui, 2003. “Labor Market Policies and Unemployment in Morocco: A Quantitative Analysis”, _Policy Research Working Paper_ N°3091, the World Bank, Washington D.C.

Blanchflower D. and Oswald A. (1994). _The Wage Curve_ , MIT Press.

Cogneau D., M. Razafindrakoto et F. Roubaud. 1996. « Le secteur informel urbain et l'ajustement au Cameroun », _Revue d'économie du développement_ , (3), pp. 27-63.

Bchir M.H., Y. Decreux, J.L. Guerin and S. Jean. 2002., “MIRAGE, a Computable General Equilibrium Model for Trade Policy Analysis”, _CEPII Working Paper_ N°17.

Bodor Andras, David Robalino, and Michal Rutkowski. 2007. “Assessing the Distortions of Mandatory Pensions on Labor Supply Decisions and Human Capital Accumulation: Options to Bridge the Gap between Economic Theory and Policy Analysis”. _Policy Research Working Paper Series_ . No. xx World Bank. Washington. DC.

26
|**Table 9: Determinants of female empowerment inge**<br>|**neration II**<br>**Dummy: Fema**<br>**individual b**|**le spouse has an**<br>**ank account**<br>|**Dummy: Ha**<br>**lat**|**ving a sanitary**<br>**rine**|
|---|---|---|---|---|
|Female spouse’s father died after 1994 or alive|-0.013|-0.015*|-0.068|-0.063|
||(0.005)|(0.005)|(0.039)|(0.026)|
|Education gap female-male||-0.001<br>(0.008)||-0.012**<br>(0.002)|
|Share of female spouse’s gifts at marriage||0.078<br>(0.133)||0.004<br>(0.166)|
|Reform*Female spouse’s father died|0.048***|0.047***|0.127*|0.119**|
|after 1994 or alive|(0.005)|(0.005)|(0.039)|(0.026)|
|Reform*Education gap female-male||0.007||0.015**|
|||(0.008)||(0.002)|
|Reform*Share of female spouse’s gifts at marriage||-0.147<br>(0.133)||-0.117<br>(0.166)|
|Observations|1,201|1,201|1,059|1,059|
|R-squared|0.415|0.416|0.605|0.609|

_Note:_ All regressions include village fixed effects as well gender and state specific year of birth fixed effects. Figures in brackets are robust standard errors clustered by state. * significant at 10%; ** significant at 5%; *** significant at 1%.

24
labor is cheaper and markets are booming. [<sup>24</sup> ] But the district's comparative advantage continues. Southeast Asia and China may be able to bend metal and assemble goods more cheaply, but it is Ota's artisans who have the skills to refine precision equipment and create the molds used in Asia's complex assembly lines, and it is Ota's artisans who can make the wide variety of customized prototypes required by developed country markets.

Ota's craftsmen have fashioned unpretentious but useful creations, like the pull tab that doesn't cut fingers, or a mechanism that sucks air out of bottles before they are recycled (Beech 2000). But they also fashion some of the world's most advanced technologies. Ota is replete with "niche top companies," firms defined by METI as possessing a 50 percent or larger share of the domestic and overseas markets for their products. One Ota company, for example, produces core components for high pressure oil pump motors, and holds 80 percent of the domestic market and 70 percent of the world market in those particular components. Niche top companies, recent government research indicates (METI, MHLW, and ME 2003), possess high levels of skill, know-how and technology, invest heavily in R&D, are close in proximity, engage in frequent face-to-face communication with their customers, and have the capacity to cultivate their own market networks. Almost three-quarters fall into three industrial categories: materials (11%), components (31%) and devices and machines (30%). A third earned over 5 billion yen in 2002.

_Niche top firms._ Yasuhisa Koki and Okano Industrial Corporation exemplify Tokyo niche top companies in the medical equipment field. The Ota firm, Yasuhisa Koki Ltd., led by President Fumio Tanaka, is a world leader in making core components for artificial hearts. Ironically, in an age of high technology, computers can't make the most advanced scientific instrument in the medical field; it can only be done manually, using the craft skills of an artisan. An artificial heart must have the strength and endurance to pump blood without stopping, a surface smooth enough to prevent thrombosis, and a structure that facilitates blood circulation. Making such a complicated device requires as much time and patience as a traditional craft. "The first step is to thinly spread a solution of polyurethane on an iron pattern, which is rotated at a uniform speed for about 3 hours to dry, this process is repeated 30 times, over a total of 90 hours, to produce the outer casing of an artificial heart. The job of making membranes used to pump blood requires even more diligence and care, as a single bubble on a membrane could cause potentially lethal blood clots" (Nikkei Weekly 10 March 2003).

23
# **b. Colombia**<sup>**4**</sup>

Authorities in Colombia adopted in 2002 a System for the Administration of Credit Risk (SARC), which is a collection of rules, procedures, methodologies, tools, knowledge, and human and physical capital aimed at the understanding, measurement and control of credit risk. According to the current legislation, expected losses related to credit risk have to be overcome using general or specific provisioning on the exposed portfolio, with expected losses estimated using the internal evaluation model(s) of each bank. The system explicitly acknowledges that provisioning should consider counter–cyclical adjustments, per the discussion of section 2. Interestingly, countercyclical provisioning can be performed either on an individual or a general basis. Prior to the adoption of SARC, provisioning in Colombia appeared to be firmly procyclical as seen in Figure 4; for example, provisions declined in the years up to 1998 when growth was relatively strong and soared in the recession that began later that year. Initially, legislation merely permitted countercyclical provisioning but did not require it or even define how it could be implemented.5 As seen in Figure 5, provisioning behavior changes markedly in 2005, even though the system was still not mandatory. It is not clear if there was any attempt at ‘moral suasion’ on the part of the authorities to achieve this result.

> 4  This section draws on reports and circulars from the Banco de la Republica, Fedesarrollo (2009), and Martinez, Pineda, and Salamanca (2005).

> 5 Though intended to commence in 2003, the SARC had several revisions, extending the period that was allowed for institutions to present their internal models and to comply with the required data dissemination standards.  There were difficulties in the construction of the internal models between 2003-2005 and on January 1st 2005 the Superintendencia Financiera de Colombia (SFC) presented a transition model or benchmark model for risk assessment while the internal models were evaluated and approved.  The 2005 benchmark model included the use of countercyclical provisions but it did not have an explicit methodology for its use.  In 2007 the SARC was modified and amended with a benchmark model for the constitution of countercyclical provisions for commercial credit only, and the following year a benchmark model was introduced for consumption credit lines. Thus between 2005 - 2007 the countercyclical scheme was voluntary.

15
## **Insurers: Too Many, Too Few, or “Just Right”?**

## **Initial Observations on a Cross-Country Dataset of Concentration and Competition Measures**

# **Introduction and Motivation**

In many markets, industry and policymakers agree that there may be too many insurers. In others, the consensus is that there could be benefit from more competition. But this broad consensus is often supported by evidence that is more qualitative, anecdotal, or judgmental despite being unanimous. What is less clear, however, is how far will consolidation or liberalization go, how fast, and when it will end. Is there some indication of the more natural level of competition and market composition? In a consolidating market, how many companies will remain after the process ends? When liberalizing, how many companies might be the result and how many applications can the new supervisor expect to have to deal with?

“Too many insurers” can be undesirable for shareholders, policyholders and supervisors. Companies struggle to achieve economies of scale and long-term sustainable returns on equity. In pursuit of market scale, irrational price wars break out further eroding returns to shareholders and risking the financial security of firms. Policyholders ultimately pay through reduced product value and the limited ability for firms to invest in innovation so as to provide solutions to fully meet customer needs. In the extreme, companies could fail due to inadequate prices and claims are not paid. Expectations for growth in the overall market may justify continued market participation in the short run but it is also likely that merger and acquisition activity will achieve economies more quickly. Companies will be looking to gain market advantage through stepped change in scale. Regulation, in such situations, needs to ensure the pathway to change of control is clear, transparent, and available. A full range of intervention tools needs to be available to watchful supervisors. New market participants are more likely to enter through acquisition unless they have a distinct and unique business model or some other specific reason.

“Too few insurers” can support inefficient operations. Management and shareholder comfort with returns may provide limited incentive to invest to develop technical capacity with the consequence that risk management and product innovation lags behind more dynamic markets. Opportunities for new entrant ‘green-field’ startups can become attractive. In the event that strategic direction is also less than fully dynamic then, combined with an absence of technical capacity, prudential risk will increase particularly when new entrants put existing market participants under competitive pressure.

In some markets, the starting point is a monopoly insurer facing a liberalizing market. When markets are liberalized, supervisors, regulators, and existing company management and owners are interested in understanding what will be the reasonable expectation for 3
|**Table 6: Double**|**difference**|**estimates of i**<br>**Total sam**|**ncrements to di**<br>**ple**|**fferent typ**|**es of rural ro**<br>**Treatment su**|**ads during pro**<br>**pport**|**ject perio**|**d (total km)**<br>**Common su**<br>**PS kernel**|<br>**pport**|
|---|---|---|---|---|---|---|---|---|---|
||**DD**|**PS kernel**<br>**matched DD**|**PS weighted**<br>**DD**|**DD**|**PS kernel**<br>**matched DD**|**PS weighted**<br>**DD**|**DD**|**matched**<br>**DD**|**PS weighted**<br>**DD**|
|**Road building**||||||||||
|Paved, all-weather|-0.06|0.25|0.32|-0.09|0.25|0.32|-0.06|0.25|0.35|
||(0.35)|(0.28)|(0.32)|(0.36)|(0.28)|(0.33)|(0.36)|(0.28)|(0.33)|
|Paved, sometimes|0.14|0.16|0.16|0.14|0.16|0.16|0.15|0.17|0.17|
|impassable|(0.09)|(0.10)|(0.09)|(0.08)|(0.10)|(0.09)|(0.09)|(0.10)*|(0.10)|
|Earth, all-weather|1.50|1.73|2.03|1.48|1.73|2.03|1.12|1.28|1.66|
||(0.80)*|(1.03)*|(0.67)**|(0.82)*|(0.91)*|(0.67)**|(0.76)|(1.02)|(0.58)**|
|Earth, sometimes|-0.08|0.44|0.49|-0.001|0.44|0.49|0.04|0.45|0.53|
|impassable|(0.34)|(0.36)|(0.41)|(0.33)|(0.38)|(0.41)|(0.34)|(0.40)|(0.42)|
|**Road rehabilitati**|**on**|||||||||
|Paved, all-weather|1.19|1.30|1.49|1.23|1.31|1.49|1.12|1.11|1.38|
||(0.56)**|(0.64)**|(0.57)**|(0.55)**|(0.67)**|(0.57)**|(0.58)*|(0.59)*|(0.59)**|
|Paved, sometimes|0.31|0.40|0.40|0.30|0.40|0.40|.33|0.42|0.43|
|impassable|(0.21)|(0.16)**|(0.19)**|(0.21)|(0.16)**|(0.19)**|(0.22)|(0.18)**|(0.20)**|
|Earth, all-weather|1.16|2.35|2.99|1.00|2.35|2.99|0.87|2.00|2.85|
||(1.21)|(1.26)*|(1.35)**|(1.22)|(1.37)*|(1.35)**|(1.24)|(1.39)|(1.35)**|
|Earth, sometimes|0.31|0.33|0.61|0.22|0.33|0.61|0.01|0.11|0.39|
|impassable|(1.06)|(1.09)|(1.21)|(1.08)|(1.07)|(1.21)|(1.06)|(1.31)|(1.20)|

Note: (i) Standard errors clustered at the district level are given in parentheses; (ii) ** and * indicate significance levels of 5 and 10%. (iii) The total sample has 194 observations (96 comparison and 98 project communes); treatment support has 191 observations (93 comparison and 98 project communes); common support has 185 observations (93 comparison and 92 project communes).

29
- 20 -

the Thai tax code. By adopting the United Nation's definition, some of the existing taxpayers would no longer be subject to tax. Tax deductions are also more liberal under the U.N. convention than the Thai tax code. Moreover, many of the withholding taxes for treaty partners are set lower than Thailand's standard rates. For instance, the dividend NWT is reduced from 20% to 15% (or 10%) in some cases, interest from 25% to 20% and the royalty tax from 20% to TABLE 4

|Country|Treaty Status|Sha<br>1986|res of Inv<br>1987|estment<br>Jan-Sep.<br>1<sup>988</sup>(p)|
|---|---|---|---|---|
|Japan|Renegotiated|44.32|69.38|48.54|
|United States|No|18.80|16.87|11.47|
|United Kingdom|Yes|3.56|6.98|3.40|
|West Germany|Yes|2.33|9.51|1.71|
|France|Yes|1.32|2.82|1.24|
|Netherlands|Yes|(0.84)|<br>1.58|1.11|
|Italy|Yes|1.15|0.15|0.16|
|Canada|Yes|0.53|0.24|0.21|
|Australia|No|2.09|0.55|0.18|
|Hong Kong|No|13.69|(36.55)|<br>10.92|
|Singapore|Yes|5.86|(4.68)|<br>6.07|
|Malaysia|Yes|0.11|(0.20)|<br>0.05|
|Philippines|Yes|(0.86)|<br>0.01|0.01|
|Taiwan|_Nol_|1.92|14.59|10.66|
|Others|..|6.03|18.75|4.32|
|||100.00|100.00|100.00|

Source: Bank of Thailand, May 15, 1989, for the share of direct investment. Revenue Department for treaty status.

J/ Thailand does not have a separate tax treaty with Taiwan, although it does with the People's Republic of China.
## 1.3 Outline of Data and Methodology

A gendered global database was first constructed by incorporating female employment and wages across sectors and countries in select South Asian countries. The study followed an approach similar to the one developed by Narayanan and Walmsley (2011) and Narayanan et al (2016) in the context of child labor, to generate gender differentiated employment and wages data in the current GTAP database version 9.

To generate gender differentiated employment and wages data in the current GTAP database, gendered employment data and industry average wages, across industry and occupations, for each country, were compiled and reconciled using the Yearbook of Labor Statistics from the International Labor Organization (ILO). To fill in the data gaps, data were obtained from various published government sources for the select countries. For instance, in case of India, latest data from summary results from national sample survey (NSS) 68th round on employment and unemployment 2011-2012 were used.

Female labor force participation and the gender wage gap were calculated using data disaggregated by economic activity according to the International Standard Industrial Classification of All Economic Activities (ISIC) at the 2-digit level of the classification and for the latest data available for that country. The gender pay gap is defined as a measure of the difference between men’s and women’s average earnings. It is measured as “female average wage/salary as a percentage of male average wage/salary” for different industrial sectors where data are available.

In the context of green trade, the approach proposed in Narayanan and Khorana (2011) was used to split the green trade sectors from others. The trade data were obtained from UN COMTRADE and the classification used follows the one used by the United States Bureau of Labor Statistics (BLS) to split green sectors. BLS has identified 333 detailed industries where green goods and services are produced.

# **2. Review of the Literature**

In the existing literature, there are several studies that have quantitatively examined the impact of trade liberalization on labor markets for both developed and developing countries. However, a very few of these studies have focused on measuring the impact of trade liberalization on women’s employment and wages. In the empirical literature, the trade-gender nexus has been examined - using cross-country, country or sector multiple regression analysis, or computable general equilibrium (CGE) models. Moreover, in most cases this gender-differentiated impact of trade liberalization has been assessed using single-country CGE models only. Also, given the paucity of gender differentiated data, most of these studies have assessed trade impacts on gender focusing mainly on labor market impacts for the manufacturing sector. Though there are many other descriptive studies that have analyzed gender-specific effects of trade liberalization, the focus of this review is on empirical studies, especially the ones that have used CGE models.

7