rafmacalaba/datause-encoder-data huggingface dataset:
|Commissioned<br>service-type QGI|All QGIs except fund-managing<br>QGIs|70|69|74|73|
|---|---|---|---|---|---|
|Nonclassified Public<br>Institution|All public institutions excluding<br>PCs and QGIs|185|200|203|208|
|Total SOEs||302|316|323|332|

# **4. Analytic Design**

# **4.1 Hypotheses**

Corporate governance intends to address the “principal-agent problem,” which deals with how the principal (shareholder) can prevent the agent (generally, the management) from maximizing his or her own self-interest (Biswas and Bhuiyan 2008). The theory argues that, when the principal and agent are different, their interests and objectives can differ, resulting in potential miscommunications about expectations and performance. The problem is exacerbated by asymmetric information (with the agent having more information), making it difficult to monitor performance. The challenge is to align the conflicting objectives and introduce rules and processes to enhance the flow of information and performance monitoring. The role of corporate governance is to identify clear reporting rules and objectives for agents, performance criteria against which they will be evaluated, and incentives (or consequences) that flow from the evaluation results. Solutions to agency problems have involved establishing contracts between the owners and management of the company, setting clear legal frameworks, and improving the composition and independence of the board of directors. Firm performance can be expected to improve with enhanced corporate governance mechanisms because, with better oversight and processes, the principal-agent problem would be mitigated as managers are more likely to better understand the principal’s expectations, invest in value-maximizing projects, and operate more efficiently (Love 2011). The following hypotheses will be tested to address the research questions about the relationship between corporate governance and firm performance.

# _H1: Separation of the positions of CEO and Board Chairman leads to better SOE performance_

The board leadership structure of a firm is considered to have an important impact on firm performance. Based on the agency theory, separation of the positions of CEO and Board Chairman would allow the operational and oversight arms of the firm to function independently and therefore more effectively. Under this structure, the CEO is responsible for day-to-day management, while the Chair leads the board and monitors the performance of the CEO and the firm. Were the same person to manage both the operational and oversight functions, the board’s ability to oversee the firm may become compromised, and the lack of accountability may in turn adversely affect firm performance (Heenetigala and Armstrong 2011; World Bank 2014).

# _H2: Larger board size is associated with better SOE performance_

The advantages of a larger board size include more diversity in handling problems and increasing the company’s impact on society due to the relationships of board members. Firms with many 7
17 compensate women for the increase in the retirement age. In November 2005, the federal council announced, that the conversion factor will be gradually further reduced to 6.4 percent over the next ten years. This initiative has not yet been confirmed by parliament.

Pension funds are free to apply any other conversion rate to the super-mandatory part of the retirement savings. Nonetheless, very few companies have used this option until a few years ago. This has been changing recently due to financial constraints. The large insurance companies providing insurance predominantly for many small and medium companies have recently reduced the conversion factor for non-mandatory retirement capital in quite a dramatic way to 5.4 percent - 5.8 percent. The fact that virtually all companies came up with an identical number for the reduced male conversion factor to the third digit after the decimal point (= 5.835) caused a considerable protest. Although insurance companies use identical mortality tables, this coincidence does not really suggest a high degree of competition among the insurance providers.

It is important to mention that a pension fund can apply a lower rate than the legal conversion factor under certain conditions. For this purpose it has to use the resources freed up as a consequence of a lower conversion rate to improve the benefits for the covered individuals. The law does not put restrictions on how these means should be distributed. In practice, many pension funds make use of this possibility, though no data exist on the importance of this alternative measure. Most of the funds finance early retirement programs and inflation indexing. A deviation from the (too high) legal conversion factor has several advantages. It allows the fund to tailor the benefits to the needs of the beneficiaries, and gives more flexibility and financial leeway to the fund. However, there is also a risk if the supplemental benefits are distributed unequally among different subgroups of the potential beneficiaries.

**Table** **<u>5  Legal Conversion Factors for Women and Men (mandatory part)</u>**

|Year|Birth Y.<br>Women|RA<br>Women|Women<br>BVG|Men<br>BVG|Women<br>(lowest)|Men<br>(lowest)|
|---|---|---|---|---|---|---|
|2000|1938|62|7.20%|7.20%|||
|2001|1939|62|7.20%|7.20%|||
|2002|1940|62|7.20%|7.20%|||
|2003|1941|62|7.20%|7.20%|||
|2004|1942|62|7.20%|7.20%|5.454%(62)|5.835%|
|2005||(64)|(7.20%)|7.15%|5.454% (62)|5.835%|
|||||7.15%|5.718%(64)|5.835%|
|2006|1943|63 (64)|7.15%|7.10%|||
|2007|1943|64|7.20%|7.10%|||
|2008|1944|64|7.10%|7.05%|||
|2009|1945|64|7.00%|7.05%|||
|2010|1946|64|6.95%|7.00%|||
|2011|1947|64|6.90%|6.95%|||
|2012|1948|64|6.85%|6.90%|||
|2013|1949|64|6.80%|6.85%|||
|2014|1950|64|6.80%|6.80%|||

The last two columns give the lowest quoted rates for capital exceeding the mandatory level. Retirement ages (RA) are for women (RA men = 65), the numbers in parenthesis correspond to the legal, but not effective RA (women turning 64 in the years 2005 and 2006 would have retired before). Source: www.bsv.admin.ch and own research
governance if only the village head was trained but there was a large improvement in governance if both the village head and the community leader were trained (Lieberman, 2005).<sup>26</sup> Once we had identified all of the on-the-line cases, we selected all cases where a positive on-the-line case was paired with a negative on-the-line case in the same geographic strata (defined by wards and land classification). This resulted in the selection of four “village head only” villages and six “village head plus community leader” villages for qualitative research, with these villages falling into four distinct geographic strata.

In each of the ten villages, the qualitative research involved conducting interviews and focus groups. First, we interviewed the village head alongside advisers of his or her choosing. Second, we conducted two focus groups, one with a group of about 8 villagers organized by the village head, and one with the random sample of 8 villagers included in the follow-up survey. In addition, in each village, we conducted a one-on-one interview with the civil society leader included in the training sessions (or, in cases where no civil society leader was trained, the civil society leader the village head said he would have liked to have included in the training sessions if he had been given the opportunity).

We use the qualitative evidence to consider three aspects of the dynamics of change relevant to adjudicating the mechanism: (1) Did the civil society leader become a competitor to or integrated into the traditional village governance structure? (2) Did the civil society leaders simply change the capacity of the village head to accomplish reforms they already favored or did they also change their incentives to implement reforms? (3) Did the civil society leader directly pressure the village head to accomplish change, or did he or she levy pressure indirectly by informing higher leaders or mobilizing villagers?

The qualitative evidence suggests that the civil society leader who was trained alongside the village head often took on new responsibilities and powers after the training session, but these responsibilities were through existing traditional institutions, not independent of them. In particular, the trained community leaders often became advisers to the village head. Although we did not observe an increase in the status of civil society leaders as a whole vis-a-vis village heads on the cruder measures included in the quantitative survey, the qualitative evidence suggests there were important changes in how the village head viewed the 26We focused on understanding the differences in the effects of training both the village head and a civil society leader versus only training the village head both because these are the effects of greatest theoretical interest and because the program had been rolled out in the year 2 villages by the time of the qualitative research, making a comparison to the year 1 control villages impossible.

36
of an ODR recognizes that debt problems for one sovereign in our integrated world are likely to have implications for other sovereigns as well as for exposed systemic banks, domestic and foreign.

The next section provides a historical overview, including the origins of sovereign debt crises. This is a followed by a distillation of lessons from past sovereign debt restructurings in sections 3 and 4. Section 5 presents desirable features of an ODR based on insights from the previous sections. Section 6 discusses the vexing problem of procrastination as an impediment to ODRs while section 7 concludes.

# **2. Historical Overview**

This overview provides a thumbnail sketch of the origins of debt crises, some numbers on debt restructuring for EMs and proposed mechanisms to aid the process of sovereign debt restructuring.

# _Origins of Debt Crises_

One set of constants has marked all serious debt crises since the 1980s: fixed exchange rates, open capital accounts, weak growth prospects and concerns about fiscal solvency. In fact, remarkably similar country narratives can be constructed regarding the origin of sovereign debt crises starting with the 1980s (as described above) and going right up to Greece 2010. Fiscal fundamentals play a crucial role, either at the outset or eventually, as a result of bailing out the domestic private sector. In addition, even though the crisis itself typically involves an abrupt economic disruption, its seeds tend to get sown over long periods, reflecting policy and political economy.

Heavy external borrowing preceded the 1980s debt crisis. Such borrowing may have been motivated by the need to finance development, sometimes via ill-advised public investments; by social spending needs; and even by the desire to enrich well-connected groups.<sup>3</sup> Money-center banks were happy to roll over maturing principal and even interest payments

> 3 Drawn from Sachs (1990), an overview of a volume of country studies on the 1980s debt crisis.

4
# _B. Data and Variables_

The firm-level data is taken from the survey responses and IFC databases. In particular, the firm’s size (in terms of the number of employees), the average number of MBAs hired each year, the type of MBA graduates the firm requires (either General Management or Specific Expertise), and the ratings of MBA students (in the areas of technical skills, communications skills, language skills, and overall) were obtained from the survey. The information on the sector of each firm was taken from the IFC “ _Edocs_ ” database which contains specific project documents with information about firms and projects.

The country-level data is taken from the _Unified Survey Database_ (taken from the most recent Bank-wide survey on economic data) and the _UNESCO Education Database_ .

Dummy variables were created for each region. The base region (when all the regional dummy variables equal zero) for the regional dummies was Europe, and thus all the other regional dummy results are in comparison to the quality of European MBA students. At this point it should be noted again that the firms that responded from the European region were located in Eastern Europe and Central Asia. Regional dummies were created for Africa, East Asia, Latin America and the Caribbean, the Middle East, and South Asia.

The sectoral analysis also used dummy variables. In particular, dummy variables were created for: (1) the Finance and Insurance sector, (2) the Industrial and Consumer production sector, (3) the Metallic and Non-metallic Mineral Production sector, (4) the Oil, Gas and Chemicals sector, and (5) the Transportation, Warehousing and Retail Trade sector. The base sector is the Food and Agro-business sector. In the analysis that follows, the introduction of all the sectoral dummy variables looks at the effects of each sector as compared to the base sector. But after looking at alternative specifications, the only significant specification was the one that contained the Finance and Insurance (F&I) Dummy, which compares the quality of MBAs from F&I firms with firms in all other sectors.

The firm-level hiring requirements were also put into dummy variables. First, a dummy variable was created for firms that hired MBAs with specific skills as compared to firms that hire MBAs with general management skills. Also, two more dummy variables were created, for firms which hired MBAs with finance skills and firms that hired MBAs with marketing skills. This was done because finance and marketing skills were the two most required specific skills from graduating MBAs from firms in developing countries, according to the survey responses.

# _C.  Estimation Technique_

The dependent variables in the three regressions that analyzed specific MBA characteristics (technical skills, communication skills, and language skills) were limited dependent variables based on the scale: (i) Lacking, (ii) Inadequate, (iii) Adequate, and (iv) Good. The dependent variable in the regression looking at the overall quality of MBA graduates was also a limited dependent variable that followed the scale: (i) Inadequately prepared, (ii) Fairly well prepared, (iii) Well prepared.

24
- 27 -

## **Table 4.** **<u>Scenarios with different transport node improvements</u>**

|||Mombasa|Dar es<br>Salaam|Border<br>points|
|---|---|---|---|---|
|Baseline|Current costs|77.99|96.16|10.81-16.26|
|Scenario 1|Total port costs (both fees and time cost) are halved|38.99|48.08||
|Scenario 2|Total border costs (both fees and time cost) are halved|||5.41- 8.13|
|Scenario 3|Port fees are halved|67.96|84.43||
|Scenario 4|Time costs atport are halved|49.02|59.82||

## **Table** **<u>5. Predicted impacts on firm inventory</u>**

|Country|City|Baseline<br>Days|Scenario<br>Days %|1<br>change|Scenar<br>Days|io 2<br> <br>% change|Scenari<br>Days|o 3<br>% change|Scenari<br>Days|o 4<br>% change|
|---|---|---|---|---|---|---|---|---|---|---|
|Burundi|Bujumbura|13.3|10.3|-22.5|12.6|<br>-5.7|12.7|<br>-5.0|11.1|<br>-16.6|
|Kenya|Kisumu|10.8|7.5|-30.3|10.8|<br>0.0|10.0|<br>-7.8|8.4|<br>-22.5|
||Mombasa|22.8|11.7|-48.8|22.8|<br>0.0|19.9|<br>-12.5|14.5|<br>-36.2|
||Nairobi|21.6|14.7|-32.0|21.6|<br>0.0|19.8|<br>-8.2|16.5|<br>-23.7|
||Nakuru|11.8|7.9|-33.2|11.8|<br>0.0|10.8|<br>-8.5|8.9|<br>-24.7|
|Rwanda|Butare|8.4|6.6|-21.9|8.0|<br>-5.6|8.0|<br>-4.9|7.1|<br>-16.2|
||Kigali|17.3|13.4|-22.8|16.3|<br>-5.8|16.4|<br>-5.1|14.4|<br>-16.8|
|Tanzania|Arusha|12.3|8.2|-33.6|11.7|<br>-5.1|11.2|<br>-8.6|9.2|<br>-24.9|
||Dar es Salaam|16.7|8.6|-48.8|16.7|<br>0.0|14.7|<br>-11.9|10.6|<br>-36.9|
||Mbeya|8.8|5.9|-33.2|8.8|<br>0.0|8.1|<br>-8.1|6.6|<br>-25.1|
|Uganda|Jinja|11.5|8.8|-23.0|11.2|<br>-2.5|10.8|<br>-5.9|9.5|<br>-17.1|
||Kampala|13.9|10.6|-23.8|13.2|<br>-5.0|13.0|<br>-6.1|11.4|<br>-17.7|
||Lira|6.4|4.9|-23.2|6.1|<br>-4.8|6.0|<br>-6.0|5.3|<br>-17.2|
||Mbale|8.2|6.2|-25.2|7.8|<br>-5.3|7.7|<br>-6.5|6.7|<br>-18.7|
||Mbarara|8.5|6.6|-21.7|8.1|<br>-4.5|8.0|<br>-5.6|7.1|<br>-16.1|

# **VII. CONCLUSION**

Firms normally keep certain inventories, including raw materials, work-in-progress and finished goods, in order to operate seamlessly and not to miss possible business opportunities. The optimal firm inventory differs depending on various economic conditions. Theoretically, transport infrastructure plays an important role to determine the optimal inventory level. If transport infrastructure is unreliable and the costs of ordering and purchasing materials and goods are high, firms are likely to hold more inventories.
**Figure 17. Quarterly Unemployment Rate Figure 18. Average monthly wages (by sector)**

<!-- Start of picture text --> 15 35%<br>Philippines Services<br>13<br>30%<br>11 Total<br>9 25%<br>7<br>China (Urban) 20% Industry<br>5<br>Agriculture<br>3 15%<br>Malaysia<br>Thailand<br>1<br>10%<br>Source: National Statistical Coordination Board, Source: Author’s elaboration on Lanzona and National<br>2007. Statistical Coordination Board Annual Business<br>Q1-2000Q3-2000Q1-2001Q3-2001Q1-2002Q3-2002Q1-2003Q3-2003Q1-2004Q3-2004Q1-2005Q3-2005Q1-2006Q3-2006 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003<br>%<br>Nominal pesos/GDP per capita<br><!-- End of picture text --> _Source:_ Author’s elaboration on Lanzona and National Statistical Coordination Board Annual Business Surveys, 2007.

**Qualified workers are increasingly moving overseas** (Table 8). Wage-setting does not reflect supply and demand. Despite the higher wages in the service sector (Figure 18), 32.3 percent of the unemployed were high-school graduates and 18.4 percent were college graduates.

**<u>Table 8. Overseas Workers by Occupation</u>**

|_Based on work contracts only(in percent)_|**1993**|**2004**|
|---|---|---|
|Service workers|34.9|40.2|
|Professionaland technical|25.3|33.4|
|Production|36.4|22.6|
|Clerical|1.6|1.9|
|Sales|1.0|1.4|
|Administrative andmanagerial|0.1|0.2|
|Agricultural|0.7|0.2|

_Source:_ Philippine Overseas Employment Administration, 2007.

# **As oligopolistic rents secure “national labor peace”, the formal labor market is for well-**

**paid insiders...** Recent comparisons suggest that local wages tend to be high for the unskilled workers (Figure 19) and the skilled ones (Figure 20). By paying higher wages - relative to other Asian countries - to the salaried insiders, the politically-connected corporate conglomerates use the rents resulting from the government’s preferential treatment<sup>34</sup> to stabilize the economic system, secure “national labor peace”, and perpetuate the status quo.

> 34 For example, laws that prevent foreigners from owning land impede foreign banks to collateralize their loans and hence limit their lending ability. But also, as discussed, monopolistic or oligopolistic privileges: a dominant position and considerable pricing power.

25
|**Table 1: Village council**|**level conflict**<br>|**indicator (two-wee**<br>|**k periods since t**<br>|**he start of the co**<br>|**nflict)**<br>||
|---|---|---|---|---|---|---|
||**Crop ar**<br>**Yes**|**ea damage**<br>**if yes, area**|**Occupied**<br>**Occupied**|**Active**<br>**Fighting**|**Troops**<br>**present**|**Any**<br>**indicator**|
|P1: Feb 24 - Mar 12|0.009|268|0.04|0.08|0.12|0.122|
|P2: Mar 13-26|0.023|450|0.097|0.059|0.156|0.163|
|P3: Mar 27 - Apr 10|0.006|161|0.08|0.019|0.099|0.103|
|P4: Apr 11 - 24|0.011|458|0.081|0.018|0.099|0.102|
|_Subtotal P1 - P4_|0.037|498|0.122|0.104|0.177|0.184|
|P5: Apr 25 - May 7|0.008|254|0.080|0.018|0.098|0.100|
|P6: May 8-22|0.009|184|0.080|0.018|0.098|0.101|
|P7: May 23 - Jun 3|0.014|286|0.080|0.018|0.098|0.103|
|P8: Jun 4-18|0.011|272|0.080|0.018|0.098|0.101|
|_Total P1 - P8_|0.048|614|0.123|0.106|0.179|0.187|

_Note:_ The sample comprises 10,125 Village Councils (VCs) that were under Ukrainian control in 2015 (i.e. excluding Crimea and areas occupied in 2014) that have a positive area cultivated with winter crops in 2019-2022. _Source:_ Own computation from satellite images (col. 1-2) and open source data <u>https://novy.tv/ru/news/2022/06/02/karta-bojovyhdij-v-ukrayini/</u> and https://liveuamap.com/ru/time (col. 3-5) 15
# **A Test Using Chinese Provincial Data on SOEs**

The above Granger causality test is a powerful tool but it does not deal with the causality head on. We therefore, utilize the “natural experiment” made possible by the economic restructuring of state-owned enterprises (SOEs) in China and the consequent massive layoff of workers across thirty Chinese provinces.<sup>44</sup> This “exogenous” shock allows us to identify the effect of income on health outcomes. Because individuals could not affect the economic restructuring by changing their health status, we do not have to worry about reverse causality in this case. It is possible that other unidentified factors may affect both the drop in SOE employment and people’s health outcomes. To minimize that risk, we control for per capita GDP and the urbanization rate of each province, and use the fixed effects model to control for any unobserved time-invariant individual province effects.

From the 1950s onwards, China’s SOEs more or less kept their promise of providing lifetime employment, housing, health care and pensions until the mid-1990s. However, the relative inefficiency of these enterprises and the costs they imposed on the rest of the economy resulted in a succession of reforms starting in the early 1980s and culminating in a massive divestiture, closure and privatization of small and medium sized SOEs starting in 1997 (Yusuf, Nabeshima, and Perkins 2005). It administered a real employment shock with 4.37 million SOE staff and workers being forced out of jobs. This dramatic drop in employment affected million of workers’ welfare and their families through wage and pension arrears and sharp decline in health benefits. The employment shocks were particularly hard on older workers and women (Giles, Park, and Cai 2006).

# _Data_

The tests were run using panel data on provincial total population, rural population, GDP, death rates, birth rates, the total number of staff and workers, SOE staff and workers, industrial production as a share of GDP for 31 provinces from 1995 to 2004. These were drawn from the China Statistical Yearbook and China Data Online. GDP data for 1995, death rate and birth rate data for 2000 data, for Chongqing for 1996

> 44 Chongqing became a provincial-level city in 1997. The data for Chongqing in 1996 is missing and we used the data for 1995 instead.

23