rafmacalaba/datause-encoder-data huggingface dataset:
financial firms and banks, given that there is lack of information on the maturity structure of time deposits and we are particularly interested about debt maturity. We also eliminate from the sample firms for which we have information for less than three periods. Given that available data only exist for publicly traded firms, we are mostly studying large companies.' To measure financial integration at the firm level, we construct indicators of access to international bond and equity markets. First, we use data on international bond issues **by** firms from emerging economies. The data come from the database of H. Kalsi and **A.** Mody, World Bank Prospects Group, and **JP** Morgan. The data measure the access to international bond markets. Second, to capture access to international equity markets, we use the proportional value traded on American Depositary Receipts (ADRs), in the New York Stock Exchange, and on Global Depositary Receipts (GDRs), in the London Stock Exchange. This proportion is calculated relative to the total value traded for that firm's equity in all markets. Data on ADRs and GDRs come from Bloomberg.' To measure financial liberalization in these economies, we employ the index of financial controls constructed **by** Kaminsky and Schnukler **(1999).** This is a qualitative multidimensional index of financial liberalization. The index takes into account controls on interest rates, legal restrictions for firms and banks to borrow in foreign markets, level of

> **_5_** Appendix 2 presents, for each country, the number of firms and time periods covered in the sample. **6** Data on publicly traded firms exist because firms have to submit their balance sheets regularly to the stock market authorities of each country. Accounting standards for other firms are different and there is no centralized agency that collects such data. **If** the data existed, it would be very interesting to analyze those firms.

> **'** Given the data availability, it is very difficult to obtain the proportional value traded of bonds in international markets, as we do for equity trading. That is why we use a dummy variable for access to international bond markets. Also, there is no publicly available data on the amount of outstanding ADRs

> and GDRs. That is why we use the value traded as a proxy for access to international equity markets.

**6**
_-45_ 94. Experience in the establishment of such municipal credit agencies has frequently been disappointing.U Accordingly, direct involvement by the Ministry of Finance and Economy may be necessary both in approving and supplying funds for local govemment capital projects in the near fiuture in Albania, in the context of a formal public investment program that includes local investmens.

# **VIII. THE** CONTINUING PROCESS OF **INTERGOVERNMENTAL**

## RELATIONS

95. The process of managing intergovemrmental relations will not cease after the present legislation has been adopted and implemented. There will be a continuing need to perfrm technical and nonlpolitical functions concerming intergovernmental relations in the Government of Albania. Because of the role currently being played by the Council of Ministers coupled with the short term desire to limit bureaucracy, this is likely to be an effective location for an _intergovernmentaO coordinationfnction._ 96. An important role for such a coordinatdng body arses from the fact that ceral government contributions to each local government budget are to be presented for approval to Parliament each year under the _Lawfor Local Budgets._ The intergovernmental coordinating body might be given the task **of** analyzing local goverment submissions and preparing recommendations on these budgets. Parliamentary deliberations might also benefit from preparation of an annual report to Parliament by the Mbinier for Local Governments, which would be prepared by the coordinating body. Such a report would present social, economic and financial data relating to the revenues and responsibilities of local governments.
In terms of the quality of roads, the data only exists for 1998. In 1998, 21 percent of the households lived in communes that did not have a road, and of these 21 percent, 14 percent had waterways, leaving only 7 percent of the households with no transportation access. Similarly, of the 23 percent of households who lived in communes with dirt roads, 3 percent of them had access through waterways. Households living in communes with waterway access are treated separately from the ones with the roads, and the roads are separated into 3 quality levels. Of these, only 7 percent of households had no access either through waterways or through roads. And 11 percent live in communes with asphalt roads.

As Figure A.1 in the Annex illustrates, the quality of roads as measured by the passability<sup>16</sup> has an important impact on household welfare and market integration<sup>17</sup> . Households that have access to at best partially passable roads, without alternative transport structure (i.e. waterways) are less commercialized compared to those that have access to full quality roads or waterways.

In Vietnam the households’ commercialization (market participation) or the ability to produce crops for sale are strongly related to the quality of the transport they have access to. However, the road quality as measured by the type of road (Dirt, Gravel, etc) turns out to be not as important as the passability of the road. Consequently, the condition of the road seems to matter more in measuring the transport costs in Vietnam. On the other hand, other transport related variables such as the existence of public transportation, or the frequency of it does not seem to have any significant effect on both the levels of income and its growth.

Subsequent to the transport system, the second most important variable that is used in the literature (for having a significant impact on income) is the existence of product and input markets. In Vietnam, almost half of the households lived in communes that had a permanent daily market. Other communes also had periodic markets. Since little information is available about the frequency or the specific role of these periodic markets, we will focus on the daily markets.

> 16 Fully passable category also includes waterways.

> 17 Market integration is proxied by two commercialization ratios. First is the ratio of crop sales to gross agricultural income and second is the ratio of crop sales to total income.

12
<!-- Start of picture text --> Country Image Marketing<br>88<br>¢<br>&<br>28 x<br>_2<br>e<br>oo<br>2019 2021 2019 2021<br>Export support services Research<br>g3<br>8 3<br>Be Ke<br>2&<br>oo<br>2019 2021 2019 2021<br><!-- End of picture text --> <!-- Start of picture text --> Marketing<br>High income Low income<br>B<br>=<br>8<br>&<br>2<br>o<br>2019 2021 2019 2021<br>RJ<br>Lower middle income Upper middle income<br>B<br>=<br>8<br>&<br>2<br>o<br>2019 2021 2019 2021<br>ME oo MS <10% MN 10-25%<br>MO 25-50% MN so-75% MEM 75-100%<br>Graphs by inc_group<br><!-- End of picture text -->
# **Figure 2 Percent of SOEs generating losses before receiving subsidies, by sector, 2009–18**

# **a. Power companies**

<!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>2009 2010 2011 2012 2013 2014 2015 2016 2017 2018<br>c. Roads<br>100<br>80<br>60<br>40<br>20<br>0<br>2009 2010 2011 2012 2013 2014 2015 2016 2017 2018<br>Percent of firms<br>Percent of firms<br><!-- End of picture text -->

# **b. Airlines and airports**

<!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>2009 2010 2011 2012 2013 2014 2015 2016 2017 2018<br>d. Railways<br>100<br>80<br>60<br>40<br>20<br>0<br>2009 2010 2011 2012 2013 2014 2015 2016 2017 2018<br>Percent of firms<br>Percent of firms<br><!-- End of picture text --> _Source_ : World Bank Infrastructure SOE Database.

_Note_ : Losses were calculated using adjusted net income, which subtracts operational subsidies from total profit (loss) for the year.

Part of the fiscal risk we examine stems from the fact that infrastructure SOEs have very little slack to deal with shocks. They use most of their revenues to cover payroll or maintenance expenses, leaving little net income for retained earnings—a key capital buffer for writing off the losses from large shocks. Figure 3 displays the variation across sectors of key expense items as a percent of operating income. Employment costs are extremely large in the railway and the airlines and airports sectors. Employment costs at railways average 145 percent of revenues (the median across sectors is 55 percent). Any demand shock that reduces revenues can therefore end up generating losses. Without fiscal transfers, on average, over 80 percent of company-year observations in railways have net losses. Some of those losses seem predictable. In Croatia and 14
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It may also hamper Investment In mobile capital (e.g., machines), because uncertainty regarding re..location of plots can Imply also uncertalnty regarding the future size of the farm and thus uncertainty regarding tPe marginal productivity of capital once the contract explres. However, when there Is a relatively longterm land lease, concerns regarding future farm size would not have a strong kmpact on Investment during the first years, as It will be fully or almost fully depreclated by contract expiration date.

Investment In housing Is viewed by Chinese farmers as completely risk free, because hcuses have been privately owned even In the years of collective agriculture, and are likely to remain privately owned. It sihould be further noted that housing Is a consumption Item with high Incc... o elasticily. The income effect Is augmented by demographic factors. In China's rural areas, a new house has become a precondition for marriage eligibility for young males. With the coming of age of Individuals born In the baby boom of the ear!y 60's, the demand for housing has Increased. These facts, and the substantlal pent-up demand due to the absence of any significant housing Investment In the pre-reform years could produce a maJor adJustment In the housing stocK once Incomes have rlsen and private construction activities have become feasible.

C. Finance Inadequacy Credit constralnts can be another factor Inhibiting investment. Most Investment outlays (and housing Investment as well) ten, to be lumpy, requirlng a substantlal amount of liquld resources. Because of this lumpiness, the necessary funds cannot typically be saved from one year's Income, and long or medlum-torm credit, or accumulated savings, are needed to finance Investment. Aggregate statistics Indicate that the share of medium and long-term loans In the portfolio of the rural credit cooperatives (the main lending institutlon
The scores achieved in the tests of the Program for International Student Assessment (PISA) of the OECD in Georgia and Azerbaijan in 2009 and 2015 are used to estimate the level of access to quality education. Gathered in 2015, data of the Integrated Living Conditions Survey in Armenia, the Monitoring Survey for Social Welfare in Azerbaijan, and the Monitoring of Households Survey in Georgia are used to estimate human capital inputs. The standard HOI among children is applied to examine the dimensions along which the inequality of opportunity in access to basic human capital inputs during the formative years may be most salient. Specifically, in this framework, opportunities are defined as access to running water and sanitation among children ages 0–16 and reflect the quality of health services in the early years of life.

The circumstances that may affect the access of children to running water and sanitation, are measured with the following variables: the number of 0- to 15-year-olds in the household, the educational attainment of the household head, the gender of the household head, the household consumption quintile, the gender of the child, and the location of the household (urban or rural area and province or region). Unlike the HOI framework for determining the access to a good job, all factors contributing to inequality, that is, the circumstances, are independent of the choice of children. Without a panel data structure, the HOI on human capital can only be generated for the current young generation, which is not directly relatable to the current labor force on which the HOI estimation of good jobs is focused.

# 3. Results

The empirical findings of the study are organized into three topics: the perceived fairness of the process, inequality of opportunity in the labor market, and inequality in human capital inputs (see the Methodology section). In this section, how people in South Caucasus generally perceive fairness in the processes involved in obtaining access to good jobs is described by way of perceptions on the role of connections. The next and more substantial part of the section highlights the level of access to good jobs in South Caucasus, measures the inequality of access to good jobs, and uses the HOI framework to decompose the sources of inequality and to determine the level of unfair inequality in accessing good jobs. The last part of the section presents the results produced by applying the HOI framework to determine the amount of the access of children to basic human capital inputs and provide some early indication on the extent to which inequality in access to good jobs is associated with inequality in access to human capital inputs.

# 3.1. Perceptions of the fairness of processes

The analysis generally finds that the populations of the countries of South Caucasus perceive that connections play a crucial role in gaining access to good jobs. Among Eastern Europe and Central Asia countries, the share of the population that believes connections are essential or important in obtaining good jobs in both the private sector and the public sector is the largest in 12
Since 2001, the Ministry of Human Resources and Social Security (formerly Ministry of Labor) has maintained a labor force observation network, which compiles information from both firm and labor force surveys conducted in 159 cities.<sup>2</sup> From this data source, information on vacancies and job seekers may be combined to provide an indication of changing demand for labor. As the data presented in Figure 4, show, the demand for labor dropped sharply, falling from 0.97 to 0.85 from the third to the fourth quarter of 2008. This finding is consistent with information from an Internet-based recruitment company **,** which reported that the growth in vacancies fell off significantly between the third quarter of 2008 and the first quarter of 2009 (Zeng, Cui, and Ding 2009).

The ministry also reports this statistic by gender, based on assumptions about the gender composition of occupations and jobs typically held by men and women. According to variation in this statistic, fewer men than women are typically available for each vacancy: the ratio of vacancies to job seekers is always higher in male-dominated occupations than in femaledominated occupations. With the onset of the financial crisis, however, the percentage drop in vacancies per job seeker was steeper for men than for women (Figure 5), suggesting that the shock hit the demand for male labor harder.

The labor market observation data have two shortcomings: first, the firm survey over-samples firms and vacancies in the formal sector, and the associated labor force survey oversamples longterm urban residents. Second, because the firm surveys are representative of enterprises operating at each period of time, they miss those shocks to employment that result from firm bankruptcy.

Interesting insights on the relationship among firm survival, migrant employment, and the financial crisis are provided by Kong, Meng, and Zhang (2009). This study makes use of a household sampling frame of migrants that was constructed by first sampling enterprises where migrants work and then randomly sampling migrants.<sup>3</sup> A first census of 489 blocks in 15 cities was conducted in 2007, and then the first wave of the survey was conducted in the spring of 6
# **(c) Other aspects of Indian capital markets**

**(i) Financing of project costs:** In addition to the RBI and ICICI data on company finances, RBI provides detailed information on the financing of project costs. It is interesting to analyze this data as a consistency check on the robustness of the results reported above. However, it is important to note at the outset that this data refers only to capital expenditures and not all uses of funds as was the case earlier. Therefore, these patterns in financing of project costs are more amenable to a direct comparison with the estimates provided by Singh (1995) and Singh and Hamid (1992) for Indian firms. Based on considerations outlined earlier, apriori, one would expect the stock market to play a more important role as a source of finance in the financing of capital expenditures compared to its role in all uses of funds.

Tables 8, 9, 10 provide details of financing of project costs by new, existing, and all Indian firms for the 1971-1993 period; however, the breakdown between new and existing firms is available only for the 1971-1984 period. These trends can best be summarized by looking at the patterns for the 1971-1993 period for all firms (table 10). While internal finance provided 6 percent of all project costs, external equity, debentures, loans from banks, and loans from FIs provided 33 percent, 9 percent, 11 percent, and 28 percent respectively. These results are therefore consistent with the previous finding that internal finance is less important for Indian firms than external finance. Also, external debt plays a bigger role than external equity, even though the 33 percent figure for external equity as a source of finance for project costs is significantly higher than the 5 percent figure for external equity as a source of finance that was found earlier. This difference could be due to two factors. First, unlike the earlier data on sources and uses of funds, data on financing of project costs excludes depreciation as a source 23
|**Table A4.2: Comparison of Baseline**|**Characteristics of No**<br>Ful|**n‐Attritors t**<br>l Sample|**o Attritors**|**, and Balan**|**ce on Non‐Att**<br>Sample of No|**iting Sampl **<br>n‐Attritors|**e**|
|---|---|---|---|---|---|---|---|
||Non‐Attritors|Attritors|p‐value|Control|Individual|Group|p‐value|
|Number of Employees|58.9|59.8|0.921|54.9|68.2|52.9|0.441|
|Small Firm (<=50 employees)|0.58|0.61|0.716|0.67|0.51|0.57|0.426|
|Medium Firm (>50 employees)|0.42|0.39|0.716|0.33|0.49|0.43|0.426|
|Cundinamarca|0.50|0.43|0.349|0.58|0.51|0.43|0.480|
|Valle|0.16|0.17|0.939|0.18|0.08|0.23|0.174|
|Labor Productivity|30|32|0.460|26|32|32|0.054|
|Financing Practices|51|51|0.964|51|48|53|0.154|
|Human Resources Practices|44|40|0.069|45|43|44|0.906|
|Logistics Practices|47|44|0.147|50|44|48|0.106|
|Marketing Practices|46|44|0.281|47|45|47|0.841|
|Production Practices|47|45|0.480|47|48|46|0.867|
|Level 2 Supplier|0.94|0.93|0.679|0.94|0.95|0.94|0.993|
|Metal Products|0.57|0.65|0.353|0.79|0.46|0.49|0.004|
|Plastic Products|0.15|0.22|0.276|0.09|0.16|0.20|0.404|
|Firm Age (Years)|24.1|24.1|0.997|27.6|24.6|20.2|0.085|
|Anexo K score|47.0|44.9|0.218|48.1|45.5|47.6|0.538|
|USD Sales in 2013|2877978|2252395|0.342|2043854|3515012|3013064|0.133|
|Export at all in 2013|0.47|0.41|0.480|0.48|0.46|0.46|0.969|
|Sample Size<br>Notes: Attrition defined as not havin|105<br>g firm sales and empl|54<br>oyment data|reported f|33<br>rom firm re|37<br>cords in Dece|35<br>mber 2017.|This|

<mark>Notes: Attrition defined as not having firm sales and employment data reported from firm records in December 2017. This can arise from firms refusing to provide this information, as well as from firm death. P‐value in column 3 is for a t‐test of equality of means by attrition status. Columns 4 through 6 provide baseline means by treatment status for the sample of non‐attritors. P‐value in column 7 is for F‐test of equality of means.</mark> 55
# _Diversification Opportunities_

The previous section focused mainly on the upgrading opportunities for Penang. In this section, the focus of the discussion is on the diversification opportunities. The first step is to see what kind of new products entered the export basket, by combing through the export data set. Between 1995 and 2000, Penang added 43 new products to its export basket (see Table 15). Among these 43 items, 6 are classified as high-tech. Between 2000 and 2007, Penang added further 26 products to its export mix, although only one was classified as high-tech (see Table 16). These new products are aircraft parts, power plant parts, and some medical related products.<sup>7</sup> There is scope for further diversification into biomedical products. In 2006, Penang accounted for 70 percent of all medical devices produced in Malaysia, some by MNCs such as B. Braun, Ambu, and Cardinal Health (Rajah 2007).<sup>8</sup> The entry of firms such as AlphaBiologics is a good start.<sup>9</sup> Other opportunities for diversification, by and large, involve non-electronic products which have been increasing their share of Penang’s export bundle. By 1995, Penang was already exporting most products in the 4-digit electronics classification and this has persisted through 2007 (see Figure 13 especially in comparison to Figure 1). The analytic approach employed here and the findings reported in Yusuf and Nabeshima 2008, suggest that for Penang and Malaysia as a whole, the more promising opportunities for diversification as distinct from upgrading are in primary products, agro-based products, and other resource-based products (see Figure 14 and Figure 15).

These product groups are aligned more closely with Malaysia’s evolving technological capabilities and offer better opportunities for deepening and earning profits than products or services in the life sciences or IT which are high-tech, but could be beyond the reach of current and medium term capabilities. Even for those products identified as promising diversification possibility, it will not be easy. From 1995 to 2007,

> 7 Already, there are several biomedical firms in Penang such as Straits Orthopaedics (a producer of kits for joint replacement surgeries), Vigilenz Medical Devices (a producer of sutures), and AlphaBiologics. 8 Like the electronics industry, the medical device industry started with foreign direct investment, by B. Braun in 1972 (Rajah 2007).  70 percent of the medical device exports are medical gloves and contraceptives.

> 9 Symmetry Medical, orthopedic manufacturer based in the United States, is also considering establishing a subsidiary in Penang.

20