rafmacalaba/datause-encoder-data huggingface dataset:
The fifth group includes one solvency measure: the interest coverage ratio, defined as the ratio of EBIT over interest expenses. This interest coverage ratio is a standard measure of credit risk-the higher cash flows are relative to interest payments for debt service, the less likely the company is at risk of default on its debt service.

The sixth group includes two measures of debt maturity structure: the relative use of short-term debt, defined as the ratio of short-term debt to long-term debt; and the ratio of short-term debt to working capital, indicating the use of short-term debt to finance different types of assets. The ratio of short-term debt to long term debt provides a measure of roll-over risks and risks of short-term liquidity crunches. The ratio of shortterm debt to working capital tries to capture the risk of the firm running into financial distress when it can not liquidate some of its investments. This risk is exacerbated in bad economic times, since lenders would be more concerned with collecting their loans, and would be less willing to roll over debt.

Lastly, we have three profitability measures: the net income margin, defined as the ratio of net-income before preferred dividends to sales; the rate of return on equity, defined as the ratio of earnings before interest but after taxes relative to the book value of common equity; and the rate of return on assets, defined as the ratio of earnings before interest but after taxes relative to total assets, with all ratios averaged for 1995-96. The latter two are deflated with the average annual GDP deflator (obtained from the IMF's IFS), to obtain profitability measures in real terms. The three profitability measures are not influenced directly by financing patterns of the firm as they exclude interest payments. The net income margin is not influenced by inflation.

17
The impact of the EU’s measures on local fishing communities around Lake Victoria will reflect the great dependency that these communities now have on the industrial fish processing sector which, in turn, is highly export-oriented (Ong’ang’a, 2002). In view of the decline in artisanal processing at landing beaches and the inability of local markets to absorb significant additional volumes of Nile perch, any decline in demand is generally absorbed through reductions in the landed price of fish. In turn, because of the limited alternative sources of cash incomes available to fishers this generally translates into a decline in earnings within the local fishing communities (Mkisi, 1991; Jansen, 1997).

**Figure 23. Mean annual landed price of Nile Perch in Kenyan areas of Lake Victoria, 19962002:**

<!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>1996 1997 1998 1999 2000 2001 2001<br>Nominal Real<br>KSh/Kg<br><!-- End of picture text --> _Note: Real prices deflated using IMF consumer price index (1995=100). Source: Fisheries Department._ No data are available on the income of fishers and how this changed over the period 1996-2001. Thus it is not possible to assess whether and the degree to which livelihoods within the communities around Lake Victoria were adversely affected. However, the significant and prolonged decline in the real price of Nile perch combined with reductions in the total landed catch would suggest that the cash incomes of fishers diminished. Indeed, the aggregate real landed value of fish declined from US$103.3 million in 1996 to US$63.0 million in 1997 (Figure 25). Following the removal of restrictions on exports to the EU, although the landed price of Nile perch increased, this was offset by a decline in landed volumes of all fish, such that the aggregate value of fish landed through 2001 and 2002 remained below the level of 1996.

50
evidence is broadly consistent with the view that there is a greater scope for spending increases to stimulate economic activity during recessions rather than during booms.

A second potential source of heterogeneity in estimated multipliers has to do with the extent of trade openness of the country. For example, simple open-economy Keynesian models imply that when the marginal propensity to import is high, a fraction of the increase in income due to an increase in government spending "leaks" into imports, reducing the multiplier. To consider this possibility, I calculate the average trade share of GDP for each country-decade, and then divide my sample in half at the median country-decade-average trade ratio. The estimated multipliers in the two subsamples are reported Panel B of Table 8. Qualitatively, the results here are again unambiguous -- in all six specifications the estimated multiplier is larger in the more closed half of the sample. For the 2SLS estimates, the differences in estimated multipliers are also fairly large: in the more closed subsample, the multipliers range from 0.57 to 0.71 and are statistically significantly different from zero, while in the more open subsamples the multipliers vary between 0.12 and 0.18 and are insignificantly different from zero. While identification is respectable in several of the subsamples, these differences in estimated multipliers are however small relative to estimated standard errors, and are again not statistically significant.

Yet another potential source of heterogeneity has to do with the exchange rate regime. A textbook implication of the basic Mundell-Fleming model is that increases in government spending are more expansionary under a flexible-exchange rate regime, as the resulting depreciation of the exchange rate has an additional expansionary effect (at least when capital mobility is limited, which seems a plausible benchmark for this set of developing countries). In Panel C of Table 8, I use the Ilzetzki, Reinhart and Rogoff (2008) classification of exchange rate regimes to identify country-year observations corresponding to flexible and fixed exchange rates.<sup>28</sup> Qualitatively, the findings are again consistent with this basic theory, with estimated multipliers that are larger in the flexible exchange rate regime in five out of six specifications. In this case, however, the magnitude of the differences is less stark: in the flexible exchange rate regime the 2SLS estimates of the multiplier vary from 0.32 to 0.48 across country samples, while in the fixed exchange rate group the multipliers range from 0.19 to 0.45.<sup>29</sup>

> 28 I classify the exchange rate regime as fixed where the IRR "coarse" measure is equal to 1 or 2, corresponding to fixed or slowly-crawling pegs, and flexible otherwise. .

> 29 Interestingly, this finding is the opposite of Ilzetzki, Mendoza and Vegh (2011) who work with a set of developed and emerging market economies where financial openness is likely to be greater than in my developing country

26
Maloney, W.F. (2004) “Informality Revisited” World Development 32(7) 1159-1178.

Maloney, W., P. Fajnzylberg, and G. Montes. (2003). "Estimating the Effect of Formality as a Treatment on Micro-Firms." World Bank, Washington, D.C.

- Maloney, W. and Nunez Mendez, J. (2004) "Measuring the Impact of Minimum Wages: Evidence from Latin America." In James Heckman & Carmen Pages eds. “Law and Employment: Lessons from Latin America and the Caribbean,” U. Chicago Press and NBER

- Maloney, W. and E. Pontual Rivero. (2001). “Employment and Wage Effects of Mexican Unions. A Case of Extreme Efficient Bargaining.” Mimeographed. World Bank. Washington, D.C.

- Marcouiller, D., V. Ruiz de Castilla, and C Woodruff (1997) “Formal measures of the informal sector wage gap in México, El Salvador and Peru.”  Economic Development and Cultural Change 45 (2):367-92.

- Marquez, G. (1998) “Proteccion al empleo y funcionamiento del mercado de trabajo:una aproximacion comparativa” working paper, Office of the Chief Economist, Inter-American Development Bank, Washington, DC.

- Marquez, G. (2002) “Training the Workforce in Latin America” What Needs to be Done?”, InterAmerican Development Bank, Washington DC, USA.

- Marquez, G. and C. Pages. (1998). "Trade and Employment: Evidence from Latin America and the Caribbean." Research Department Working Paper No. 366. Inter American Development Bank, Washington, D.C.

- Marrufo,  G. M.. (2001). “Financing Social Security Programs in Mexico: Who Bears the Cost?.” WP 135. Stanford Center for International Development Working Paper Series. Stanford, CA

- McArdler and Blom (forthcoming) “Firm and Worker Training in the Caribbean”, World Bank Background Paper, Washington DC, USA and Kingston Jamaica

- Menezes-Filho, N., H. Zylberstajn, J. P. Chahad, and E. Pazello. (2002). “Unions and the Economic Performance of Brazilian Establishments.” Working Paper R-464. Inter American Development Bank, Washington, D.C.

- Mondino, G. and Montoya, S. (2002). “The Effects of Labor Market Regulations on Employment Decisions by Firms. Empirical Evidence for Argentina”, in Law and Employment: Lessons from Latin America and the Caribbean, James Heckman and Carmen Pagés Eds, forthcoming from The University of Chicago Press. Chicago, IL

- Montenegro, Claudio (2001). “Wage Distribution in Chile: Does Gender Matter? A Quantile Regression Approach.” Policy Research Report on Gender and Development. Working Paper Series No. 20. The World Bank, Washington D.C.

- Montenegro. C. and C. Pagés. (2003). "Who Benefits from Labor Market Regulations? Chile 19601998." NBER Working Paper No. w9850. Cambridge, MA.

- Montes, G. and M. Santamaría. (Forthcoming). Productivity and Labor Markets in Mexico, Mimeo. Washington, DC.

- Morduch, J. (1999) Between the Market and State: Can Informal Insurance Patch the Safety Net?’ World Bank Research Observer14:187-207

Murillo, M. V., M. Tomassi, L. Ronconi, and J. Sanguinetti. (2002). “The Economic Effects of Unions in Latin America: Teachers’ Unions and Education in Argentina” Working Paper R-463. Inter American Development Bank, Washington, D.C.

31
We carry out a detailed examination of data on developing countries’ use of the ACWL, and we also make comparisons to cases from countries that could have used the ACWL but chose not to do so. Our initial examination of the data on ACWL involvement in WTO dispute settlement indicates that the ACWL caseload largely mirrors the full WTO caseload involving developing countries. Notably, the ACWL has assisted developing countries in their self-enforcement efforts with respect to both developed country and developing country markets.

As a second step, we use economic theory to identify ways that introduction of the ACWL might be expected to affect the developing country dispute initiation and prosecution caseload. We then examine the data for evidence that the ACWL may be having such effects. For example, introduction of the ACWL can lower the cost to a developing country of pursuing a WTO dispute, and this may affect the observed country-level DSU caseload pattern through changes at two different margins. The ACWL may affect the DSU caseload through the intensive margin, i.e., lower enforcement costs to countries using ACWL services may lead to more WTO disputes brought forward by the _same_ countries that have brought disputes forward previously. The ACWL may also affect the pattern of DSU cases at the country-level extensive margin, i.e., new complainants without a history of using WTO dispute settlement may begin using the DSU for the first time. The limited evidence available from use of the ACWL from 2001 through 2008 suggests that the ACWL has affected the volume of disputes almost entirely through the intensive margin: the same developing countries have been making greater use of the DSU process. Given this result, we examine the data on these DSU-using developing countries to determine how the establishment of the ACWL may have affected the way they use WTO enforcement. The lower cost of access to WTO enforcement could lead developing countries to pursue the same types of disputes as they have in the past, but with differences in the way the cases are pursued. Alternatively, they may pursue different types of cases.

We present evidence from three channels through which the ACWL may affect developing country use of WTO self-enforcement. First, we provide evidence that, by lowering the cost to the developing countries of litigation, the ACWL allows countries to file more sole-complainant disputes on 4
_Table 8: Geographic Distribution of HLE Households_

|**District**|**Distribution of**<br>**Households**|
|---|---|
|Mosul|33%|
|Tikrit|11%|
|Ramadi|9%|
|Tel Afar|9%|
|Shirqat|7%|
|Kirkuk|5%|
|Qa’im|5%|
|Falluja|5%|
|Baiji|5%|
|Ana|4%|
|Sinjar|3%|
|Hamdaniya|2%|
|All Others|2%|
|_Data Source_:|CLCI LegacyDatabase.|

Thirty percent of the high likelihood sample is female headed, which is roughly in line with CLCI vulnerability data broadly (not shown). The average household has 8 members (slightly higher than the national and CLCI average).

The average household size and member disaggregation does not change between female- and male-headed households, and nor by district – in the most populous districts the number of women drops to 3 in Mosul and the number of children increases to 3 in Shirqat, Tel Afar, and Tikrit. The average head of household age is 40 across the entire sample, dropping to 38 among female-headed households. In terms of head-ofhousehold specific vulnerabilities, 16 percent are disabled, and 36 percent have a chronic illness, with female heads of household more often having chronic illnesses (59 percent). For 91 percent with a disability and 89 percent with a chronic illness, their condition prevents them from working. The average household has 1 disabled and 1 chronically ill member (not shown). Majority of the household heads have either no education, or have completed only primary education (Figure 8). This shifts markedly among femaleheaded households, among whom 50 percent received no education.

<!-- Start of picture text --> Figure 2: Educational achievement of household head Figure 3: Household monthly income by number of<br>working members.<br>60%<br>IQD 400,000<br>50%<br>IQD 350,000<br>40%<br>IQD 300,000<br>30%<br>IQD 250,000<br>20%<br>IQD 200,000<br>10%<br>IQD 150,000<br>0%<br>IQD 100,000<br>IQD 50,000<br>IQD 0<br>0 1 2 3<br>All Female-Headed Number of working members<br>Data Source : CLCI Legacy Database. Data Source : CLCI Legacy Database.<br>None Primary Secondary Undergraduate Technical College<br><!-- End of picture text --> The average monthly income across the sample is IQD 137,041 / $115 (not shown). As expected, this increases with level of education and with household level of economic activity. Households with heads having an undergraduate degree earn 173% more than those having completed no education (not shown).

16
average of 51 percent reported in 2011. Growth in developing economies was even higher, increasing to 71 percent in 2021 from 42 percent in 2011—a more than 70 percent increase.<sup>1</sup> Financial account holders use their accounts for a range of purposes, such as storing money and making payments using electronic transfers, cards, the internet, or a mobile phone. “Accounts” can be with a regulated financial institution like a bank, credit union, or microfinance institution, any of which may offer internet or mobile phone-based access. Accounts may also be offered by mobile money service providers, which include telecommunications operators and “fintechs” (nonbank financial technology providers). In the case of mobile money, users often have the option of accessing their mobile money accounts through their mobile phones or using a brickand-mortar agent network. These agents are often located in kiosks or convenience-type stores. The Global Findex database defines _account ownership_ as ownership of an individual or jointly owned account either at a financial institution or through a mobile money provider.

The specific factors fueling the global rise in financial inclusion differ region-by-region and even country-by-country and may not be related to the economic bracket to which a country belongs. In Sub-Saharan Africa, for example, account ownership increased to 55 percent by 2021 from 23 percent in 2011, fueled by the adoption of mobile money accounts (33 percent of adults in the region have one). India, in contrast, achieved a 78 percent account ownership rate by 2017, largely driven by a government-led program that provided both digital IDs and bank accounts.

Access to a financial account can lead to a number of positive development outcomes for account holders. Research on the topic shows relationships between expanded account ownership and reductions in poverty (Beck, Demirgüç-Kunt, and Levine 2007); increased consumption (Karlan and Zinman 2012; Burgess and Pande 2005); increased productivity (Allen et al. 2016; Bruhn and Love 2009); greater investment in preventive health (Dupas and Robinson 2013; and Cramer 2023); and overall higher levels of savings (Karlan, Ratan, and Zinman 2014).

Partially through its facilitation of increased savings, formal financial inclusion holds significant implications for financial health during economic downturns. Owning an account allows adults

> 1 Unless otherwise indicated in the text or through a footnote, all data in this paper is from the Global Findex 2021. The Global Findex 2021 Database, the fourth edition since 2011, includes comparable indicators of financial inclusion for 139 economies, including 15 economies in 2022. The data is collected through nationally representative surveys of about 1,000 adults per country. To download the complete database and for more information on the survey methodology, see: https://globalfindex.worldbank.org.

3
Policy Research Working Paper 9264

# **Abstract**

This paper describes the Services Trade Policy Database, a joint initiative by the World Bank and the World Trade Organization Secretariat, which builds on a database developed by the World Bank nearly 10 years ago and draws on a recent Organisation for Economic Co-operation and Development database. The Services Trade Policy Database offers comparable information on services trade policies for 68 economies in 23 subsectors across five broad areas—financial services, telecommunications, distribution, transportation, and professional services. The database features several improvements. First, the data are collected according to a newly developed policy classification, consistent with the earlier World Bank database and the current Organisation for Economic Co-operation and Development database, enabling a comparison of services policies over a significant period and across a large cross-section of industrial and developing economies. Second, in addition to trade policies, the database contains information on licensing conditions and data restrictions. Third, policy restrictiveness is quantified following a more systematic approach that aggregates the information within a single consistent and transparent framework. Building on these innovations will make it possible to identify global patterns of services trade policies and secular trends in policy making over the past decade.

This paper is a product of the Development Research Group, Development Economics and the Office of the Chief Economist, East Asia and Pacific Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at i.borchert@sussex.ac.uk, Joscelyn.Magdeleine@wto.org, juan.marchetti@wto.org, and amattoo@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
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instrumented through securities, not from government debt issued in captive markets or liabilities associated with arrears and overdrafts.

For the _Debt Structure Sample_ in 1996-2011, Figure 3 shows the composition of the domestic public debt portfolio in terms of major instruments defined by the GFSM (IMF, 2001), namely loans, securities, other accounts payable (e.g., Central Bank advances), insurance technical reserves, and currency and deposits (e.g., judiciary deposits). Securities and Central Bank advances to the Treasury are the main sources of domestic financing in LICs. On average, since the early 2000s securities constitute three-quarters of domestic debt whereas Central Bank advances are nearly one-fifth. The breakdown in HIPCs and non-HIPCs reveals a remarkable difference in the structure of government debt: the share of securities is much higher in non-HIPCs and, conversely, the share of Central Bank advances is larger in HIPCs (possibly because their markets are relatively less developed and the pressures of fiscal dominance and debt monetization are more acute). Interestingly, we find out an upsurge of Central Bank advances in response to the financial crisis in both groups.

The box-plot in Figure 3 and the Table A2 in the Appendix show differences across individual countries. On average, Kenya, Ghana, and Tanzania issue securities exclusively, in contrast to Guinea-Bissau, Haiti, Guinea, and Burundi, in which securities are a small share of the domestic public debt.

**<u>Figure 3: Domestic Debt by Type of Instrument.</u>**

<!-- Start of picture text --> Domestic debt composition by instruments Debt securities (as % of Domestic Debt)<br>Year<br>Currency and Deposit Debt securities<br>Loans Insurance<br>Other accounts payable Non classified Year<br>Domestic debt composition by instruments. HIPCs Domestic debt composition by instruments. Non-HIPCs.<br>Year Year<br>Currency and Deposit Debt securities Currency and Deposit Debt securities<br>Loans Insurance Loans Insurance<br>Other accounts payable Non classified Other accounts payable Non classified<br>1996199719981999200020012002200320042005200620072008200920102011<br>1996199719981999200020012002200320042005200620072008200920102011<br>1996199719981999200020012002200320042005200620072008200920102011 1996199719981999200020012002200320042005200620072008200920102011<br>1<br>100<br>80<br>.8<br>60<br>.6<br>40<br>20 .4<br>0<br>Debt instrument (as % Domestic Debt) .2<br>Debt securities (as % of Domestic Debt)<br>0<br>100 100<br>80 80<br>60 60<br>40 40<br>20 20<br>0 0<br>Debt instruments (as % of Domestic Debt ) Debt instruments (as % of Domestic Debt)<br><!-- End of picture text --> _Source: our elaboration on the LIC domestic public debt dataset._ 14