rafmacalaba/datause-encoder-data huggingface dataset:
markets of the EU, this reduction in long-distance transport costs would tend to facilitate trade significantly, all other things equal. This reduction in “effective distance” raises even further the relative importance of lowering the transactions costs of trade.

Integration into the EU will, over time, clearly engender enhanced trade facilitation. EU membership will make it possible to move goods freely between member states without the need to complete formal import and export documentation or pay import VAT or customs duties. This should result in a more rapid movement of goods (and services) between member states and reduce transactions costs. The harmonization and implementation of the _acquis communautaire_ also require new member countries to make major improvements in their overall economic environment—both at the border and behind the border.

On a global basis, the estimates by WMO (2004) suggest that improvements among the four dimensions of trade facilitation that are the focus of this paper—port efficiency, customs regimes, regulatory policy, and information technology infrastructures—can lead to significant trade gains. Their analysis indicates that for the 75 sample countries, raising capacity halfway to the global average would yield a $377 billion gain to world trade.

Our paper takes as the starting point the same analytical framework underpinning the global assessment but focuses on a subset of 12 ECA countries—eight of the current members of the EU: Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia and Slovenia (hereafter EU8); and four candidate EU members: Bulgaria, Croatia, Romania, and Turkey<sup>4</sup> . We also move beyond the evaluation of trade facilitation based on a single parameter, such as the price of imports, the productivity of the transport sector or the costs of transportation, and examine the four dimensions of trade facilitation noted above. We use a gravity model of bilateral trade flows for our estimations, rather than a computable general equilibrium (CGE) approach. The scenarios examined here do not assume that all countries in our sample (those that have acceded to the European Union or candidate members) improve capacity by the same amount. To keep our scenarios realistic, we assume that countries improve their trade facilitation capacity half-way to the EU15 level– the countries

> 4 The data on port efficiency, customs regimes, regulatory policy and information technology infrastructures for Cyprus, Malta and Croatia are not available. Given the relatively small economic size of Cyprus and Malta, we focus on the study of the other eight new member countries of EU.  Data for Croatia are not currently available.

5
LIBERIA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Table 17. Estimated demand for power from mining, forestry and agriculture by 2040**

<u>US$ millions</u>

||MW|
|---|---|
|Mines||
|-<br>Iron ore (close to grid)|332|
|-<br>Iron ore (far from grid)|400|
|-<br>Gold|110|
|Forestry|116|
|Rubber|30|
|Oil Palm|10|
|Agriculture|5|
|Total|1,003|

Source: World Bank, 2010 — = data not available.

Given the size of the funding gap, clear principles for prioritization and sequencing of infrastructure investments are essential. Since infrastructure is only a means to an end, it is important to define infrastructure development plans in close coordination with the national growth vision. The government of Liberia is currently envisaging a growth strategy based around key development corridors that anchor economic activities in a number of key sectors including agriculture, forestry, and mining. Scoping out the infrastructure packages needed to support development along these corridors would help to prioritize the overall national requirements identified in this report.

In addition to looking at domestic corridors, Liberia needs to examine ways to exploit regional corridors. Regional integration relates Liberia’s infrastructure development path in a variety of ways. For example, Monrovia’s transport infrastructure can provide a platform for exports from eastern Sierra Leone. Similarly, the power and transport infrastructure in the region of Saint Pedro in western Cote d’Ivoire may be relevant to the development of Liberia’s isolated southeastern region. Finally, regional power trade is potentially a significant component in Liberia’s long-term power development strategy.

In any case, it will likely take Liberia longer than a decade to reach the illustrative infrastructure targets outlined in this report _._ Under business as usual assumptions on spending and efficiency, it would take at least forty years for Liberia to reach these goals. Yet with a combination of increased finance, improved efficiency, and cost-reducing innovations, the goals should be attainable within a significantly shorter period.

35
experiences. Finally, comparison with the OECD or high income EU15 countries helps identify longer-term objectives for policymakers.<sup>6</sup> 19. These benchmarks are used in the graphs. Romania’s score relative to the full set of countries (30 OECD members in 2003, Brazil in 2004 and Bulgaria in 2006) is shown in Appendix I for all PMR indicators.

# **THE ROMANIAN CONTEXT**

20. Until 2000, Romania was one of the poorest performing economies of Central and Eastern Europe. The turnaround in 2000 was preceded by a protracted and precipitous decline in GDP, a peaking of the poverty rate to 36 percent, and inflation of 54 percent per year. EU accession aspirations and the opening of official entry negotiations with the EU in December 1999 spurred Romania’s commitment to reforms. This led to significant macroeconomic consolidation and impressive growth in recent years.

21. As a result of the reforms, the economy has been growing at a robust 5 to 6 percent per year over the last six years. The main drivers for this growth have been investment and exports - and occasionally domestic consumption - that responded strongly to improved confidence in banks and macroeconomic stabilization. Inflation declined from above 40 percent in 2000 to 4.9 percent in 2006, the lowest level since the start of the transition. Fiscal consolidation, characterized by a cut in public expenditures of around 4% of GDP, allowed for a reduction in both inflationary pressures and the consolidated budget deficit. The latter shrank from 4.1 percent of GDP in 2000 to 1.7 percent in 2006. In addition, a combination of sustained growth and external migration permitted a substantial decrease in registered unemployment, down to around 5 percent of the labor force.

22. The EU accession process also set the stage for a broad and sustained structural and institutional reform agenda. Privatization of commercial companies picked up, especially in banking and the energy sector, though it slowed down somewhat in 2006. Foreign direct investment (FDI) substantially increased after 2000, with inflows exceeding 5-6 percent of GDP per year recently. Institutional and governance reforms advanced, with the first generation measures, focused on the establishment of the legal framework and the redesign of the institutional architecture of the public sector, either adopted or in the process of being implemented.

23. Important steps were also taken to upgrade the regulatory framework for businesses, remove administrative barriers and enhance the business climate. A major step forward was the adoption by the government, starting with 2001, of an annual Action Plan to remove administrative barriers to businesses.<sup>7</sup> The implementation of the Action Plan, updated annually, is overseen by a working group representing stakeholders, and its results are measured through surveys. This has led to the simplification of administrative

> 6 The EU15 includes Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, United Kingdom.

> 7 This was supported by a program with the World Bank (the PSAL and subsequent PAL programs).

7
- 30 -

they also appear in farm.villages. Osusus operated in four of five villages studied during the time of research (the exception being a Fula village in Upper River Division), though some villagers everywhere knew the idea and some had belonged to other osusu groups when living outside their villages.<sup>33</sup> In the 1987 survey, 17 percent of the women interviewed currently belonged to osusu groups, and only one (1Z) of the men. In the 1988 survey, farmers were asked whether anyone in their compounds had ever belonged to one. 192 percent said one or more women had belonged; 4 percent said one or more men had belonged. 89 percent of the respondents' osusus were in the respondents' home villages, 3 percent were in nearby towns, and 8 percent were in the cities of Banjul and nearby Serrekunda.

Nearly all the groups in the villages were female-only, and many of these included only persons of comparable ages internally (many participants variously described the age-ranges as "young", "middle aged", or "old"). The groups in the towns and cities were more likely to include mixed sexes. Each women's osusu group represented in the sample existed within a single village, town, or city; and in the largest village they were composed of members of the same neighborhoods. Most rural village osusus consisted of women roughly the same ages (year of circumcision is sometimes used to determine association membership). Some consisted entirely of kin, others not. One group was based on ethnic identity, its members representing a minority in their village. The overlaying ties of neighborhood, gender, age, kinship, and ethnicity all seem to give the groups the capacity for peer-group pressure that may be needed to ensure members' regular participation. Each group did, however, have a recognized leader or organizer.
cost of service provision. Countries such as Chile, Peru and Uganda have put in place such mechanisms, which have helped to expand services to areas that otherwise would not have access. Based on the Chilean experience,<sup>16</sup> Kenny and Keremane (2007) estimate that an upper bound on the amount needed for achieving universal access to basic telecommunications using competitively awarded subsidies to private providers in developing countries is some $5.7 billion. Of this amount, $1.8 billion could not be supplied by a reasonable tax on existing providers, and would need to be generated from outside the sector. Most of this – some $1.5 billion –would be needed in Africa.

An international arrangement that replicates the key elements of successful national schemes may be one way to use additional aid for trade resources to increase support for pro-competitive reforms. This could involve countries (or regions) that are willing to eliminate barriers to investment being given assistance to put in place both the necessary regulatory reforms _and_ granted access to a “universal service provision fund” in instances where the investment response from domestic and foreign firms had been inadequate. Funds would be made available to provide a subsidy to firms to create infrastructure and/or provide services in the relevant region or country at pre-specified terms. Along the lines of the policies put in place in Chile, the Dominican Republic, Peru, and Uganda, these terms could be established as the result of an reverse auction or bidding process under which firms would indicate the minimum level of subsidy they would require to fulfill the mandate set out by the government. Note that this form of assistance does not target specific industries or firms, as would industrial policies or trade preferences. Rather the objective would be to improve the availability and quality of services for all firms, farms and households in areas that would otherwise be underserved.<sup>17</sup>

> 16 The subsidy needed to provide universal access in Chile varied across sub-regions, with poor, sparsely populated areas requiring a larger per capita subsidy. Income density explains over 60 percent in the variation of subsidy cost. Kenny and Keremane (2007) therefore use income density data for other countries to estimate what would be needed to achieve universal access.

17 In the case of trade preferences proposals have been made to shift towards financial instruments, on both efficiency and systemic grounds, and as a mechanism to compensate beneficiary countries for the erosion of the value of preferences as MFN barriers are lowered. The services “aid for trade” proposals made in this paper could also be part of an effort to address preferences erosion losses, but they are primarily focused on the set of countries that have not been able to utilize preferences as a result of supply constraints. See e.g., Hoekman and Prowse (2005) for a discussion of preferences and aid for trade.

19
# **<u>Appendix Table 1 (contd.): Data and Their Sources</u>**

|**Variable**|co2_emission_mil<br>mettons 2008|pop_2008|gdp_ppp_percap<br>2008|mtco2e_1970to20<br>06|g_bau|e_bau|
|---|---|---|---|---|---|---|
|**Description**|Carbon dioxide<br>emissions|Population in<br>year 2008|Gross domestic<br>product per<br>capita|Cumulative<br>carbon dioxide<br>emissions from<br>1970 to 2006|Per capita<br>GDP growth in<br>business-as-<br>usual|<br>Carbon dioxide<br>emissions in<br>business-as-usual|
|**Unit**|in millions metric<br>tons|in millions|in US dollars|in metric tons<br>carbon|in %|in %|
|**Source**|World Bank<br>(WB) World<br>Development<br>Indicators (WDI)|World Bank<br>(WB) World<br>Development<br>Indicators (WDI)|<br>International<br>Monetary Fund<br>(IMF) World<br>Economic<br>Outlook (WEO),<br>April 2010|Climate Analysis<br>Indicator Tool<br>(CAIT) World<br>Resources<br>Institute (WRI)|Birdsall and<br>Subramanian<br>(2009)|Birdsall and<br>Subramanian<br>(2009)|
|**Country**|||||||
|Thailand|254|0|8,232|3,576|5.0|2.3|
|UAE|199|0|37,442|1,956|3.0|1.4|
|Kazakhstan|199|0|11,434|7,611|5.0|1.0|
|Venezuela|184|0|12,717|3,981|3.8|2.1|
|Argentina|172|0|14,408|4,127|3.8|2.4|
|Egypt|165|0|5,897|2,951|4.3|2.7|
|Malaysia|162|0|14,082|2,310|4.8|3.1|
|Singapore|159|0|51,846|932|4.8|0.3|
|Belgium|155|0|36,345|4,517|2.2|0.2|
|Pakistan|148|0|2,624|2,258|5.4|4.5|
|Uzbekistan|125|0|2,599|4,448|5.0|3.4|
|Greece|107|0|30,189|2,498|2.2|‐0.1|
|Algeria|106|0|6,753|2,142|5.5|4.6|
|Romania|103|0|12,638|5,231|3.9|1.0|
|Czech Republic|102|0|25,061|5,458|2.3|‐0.4|
|Iraq|101|0|3,477|2,021|4.8|4.1|
|Nigeria|100|0|2,162|2,116|5.4|5.7|
|Vietnam|94|0|2,794|1,190|4.9|3.0|
|Hong Kong|84|0|43,754|1,344|4.8|2.7|
|Kuwait|82|0|39,941|1,471|2.7|1.6|
|Philippines|80|0|3,515|1,750|4.8|3.4|
|Austria|70|0|39,887|2,223|2.2|‐0.1|
|Israel|70|0|28,474|1,334|2.4|1.2|
|Belarus|68|0|12,313|3,130|3.8|0.9|
|Colombia|65|0|8,928|1,778|3.8|2.6|
|Chile|65|0|14,592|1,252|3.2|1.8|
|Morocco|40|0|4,362|844|5.6|3.5|

_Note: For historic emissions, Hong Kong’s was assumed to be the same in per capita terms as Singapore. Emissions for some of the Former Soviet Union countries for the early 1990s were extrapolated backwards._ 43
customers are positively correlated for female-owned firms to build. Note that we find no statistically significant results between the proportion of working capital financed by supplier credit and mobile money use for the whole sample as well as for female or male-owned firms subsamples. Results for the regression that include the proportion of sales sold on credit are presented separately (table 2, columns 4-6) as the data are unavailable for Kenya, and thus implying considerable changes in the sample composition.<sup>6</sup> The ES also collects responses from respondents on why they have chosen to adopt or avoid mobile money.<sup>7</sup> The findings by gender of the owner are presented in table A1. Most female-owned firms cite satisfying customer requests (31 percent of mobile-money adopting firms), followed by reduction of time spent in financial transactions (25 percent) and reduction of costs of financial transactions (19 percent). Most male-owned firms cite reduction in time spent in financial transactions (42 percent), followed by satisfy customer request (25 percent) and then reduction of costs of financial transactions (17 percent). The differences in reasons provided by female versus male-owned firms are not statistically significant with the exception of reduction of time spent in financial transactions (25 percent female owned firms vs. 42 percent male-owned firms).

For firms that do not adopt mobile money, the lack of use by customers or suppliers are the most cited reasons, regardless of gender of owner (table A1).<sup>8</sup> Fewer female-owned firms cited high fees than male-owned firms for not adopting mobile money (7 percent vs. 23 percent). Fewer female-owned firms cited “not easy to use” as a reason for not adopting mobile money than maleowned firms (10 percent vs. 18 percent). Both differences are statistically significant at the 1 percent level. The indication may be that women firm-owners are more experienced with mobile money than male-owned firms and thus ease of use is not a barrier to adoption. It also may be that female-owned firms engage in smaller transactions and thus do not see high fees as a barrier to adopting mobile money as male-owned firms. It is also worth noting that 20 percent of femaleowned firms and 25 percent of male-owned firms that did not adopt mobile money cite “don’t know enough” as the reason why. This may imply there is scope for awareness campaigns to improve mobile money adoption.

> 6 The survey question on proportion of sales sold on credit has been removed from recent rounds of the Enterprise Surveys and thus the Kenya 2019 survey does not have this information.

> 7 Note that this excludes Zimbabwe.

> 8 Note that Kenya is excluded as the exact survey question was not included in the questionnaire.

11
> profitability was low, though still satisfactory, in- 1999 as a result of the effects of

> protracted drought.

Table 4: Cyclicality of Finmcial results, 1997-2001

||1997|1998|1999|2000|2001|
|---|---|---|---|---|---|
|OwnFunds/TotalLiabilities%|10.7|10.4|10.0|9.5|9.7|
|LTInsurFund/TotalLiabilities%|72.3|73.3|75.7|_e_76.9|77.6|
|GeneralInsurReserves/TotalLiabilities%|<br>7.6|6.8|6.1|5.7|5.2|
|ROA|2.19|2.02|1.54|1.61|2.00|
|ROE|20.6|19.4|15.4|17.0|20.7|
|Profits/GrossPremiums(%)|8.33<br>Source:FSC|8.50|6.87|7.18|8.48|

Insurance companies have adequate asset diversification. According to FSC statistics, government securities represented 8 percent of total assets and corporate securities (both equities and debentures) 35 percent (Table **5)6** Housing loans account for 23 percent of assets. They used to be the largest type of asset but have declined in recent years, reflecting the growing presence of banks in this important market. Although the long-term insurance fund, representing the assets of life business, can be invested overseas up to a limit of 25 percent and despite the presence of several large privately owned companies, foreign securities absorb less than 10 percent of total assets. In fact, SICOM, the state-owned company, invests more in foreign assets than even the large private companies. Other assets absorb 11 percent of total assets. They include loans to shareholders, which in the case of some small companies, are large relative to capital (see below).

Table 5: Asset Allocation of Insurance Companies, 1997-2001

|(percentoftotal)|1997|1998|1999|2000|2001|
|---|---|---|---|---|---|
|MortgageLoans|30|26|25|25|23|
|OtherLoans|8|5|_5_|_5_|4|
|Government Securities|7|9|6|7|8|
|Shares&Debentures|22|26|30|35|35|
|Land&Property|6|7|6|_5_|_5_|
|Deposits&Securities|16|16|17|13|14|
|OtherAssets|11|11|11|10|11|
|Total|100|100|100|100|100|
|TotalAssets(MURmnillion)|14130|16672|19200|21123*|23971|

Source: FSC

# KY0 Long-Term (LTe) nsuraimce

14 companies operate in the life sector. 11 of these are composites and only 3 specialize in life insurance -(2 Mauritian companies plus the local branch of the Life Insurance Corporation of India). Concentration in the sector is very high. The largest 3

> **6** As noted above, official statistics probably understate the share of government securities in the portfolios of insurance companies.

6
bene...ts measured by the bene...ts-earnings replacement ratio, B=E, reduce the private saving rate. The results of the regression do not reject this hypothesis.

Edwards (1996) works with a sample of 32 countries (including developed and developing countries) and a panel of more than 200 observations to study the determinants of private saving. Among them he includes a social security variable that is de...ned as the ratio of public expenditure on social security and welfare to total public expenditures. In all the regressions presented in his paper, the social security variable has a negative coe¢ cient that is signi...cantly di¤erent from zero.

# 3.4 Funded programs-time series

In contrast to the implications of the life-cycle theory, two well known cross sectional studies by Cagan (1965) and Katona (1965) have shown that employees covered by private pensions do not save less and may even save more than employees not covered by private pensions. Cagan interpreted the results by saying that pension coverage showed the importance of saving for retirement and saving could increase due to this ”recognition e¤ect”. Katona had a di¤erent explanation for the phenomenon based on the idea that the e¤ort employed to achieve a goal increases when the distance to the goal decreases. In this case the goal would be an adequate retirement consumption.

Munnel (1976) obtained completely di¤erent ...ndings using a sample of 5,000 men who were between ages of 45 and 59 in 1996. In fact, she presented evidence showing that employees covered by private pensions save substantially less than employees not covered by private pensions.

19
# **Table A2. Changes in GDP Growth Across the Business Cycle on Compensation to Employees: Elasticities from Fixed Effects and IV Regressions for Emerging and Advanced Economies**

|VARIABLES|(1)<br>Emerging<br>economies -<br>FE|(2)<br>Advanced<br>economies -<br>FE|(3)<br>Emerging<br>economies -<br>IV|(4)<br>Advanced<br>economies -<br>IV|
|---|---|---|---|---|
|GDP Growth * Exp|0.92<br>[0.145]***|0.34<br>[0.124]**|0.92<br>[0.159]***|0.34<br>[0.095]***|
|GDP Growth * Rec|0.34|-0.15|0.29|-0.16|
||[0.218]|[0.125]|[0.237]|[0.145]|
|Lagged Compensation to Employees Growth|-0.06|0.26|-0.06|0.29|
||[0.088]|[0.066]***|[0.084]|[0.122]**|
|Lagged General Government Expense Growth|0.07|0.07|0.07|0.03|
||[0.039]*|[0.086]|[0.045]|[0.059]|
|Constant|0.02<br>[0.006]**|0.01<br>[0.003]**|||
|Observations|873|432|866|418|
|R-squared|0.086|0.128|||
|Number of Countries|42|18|42|18|
|Country Fixed Effect|Yes|Yes|Yes|Yes|
|Adjusted R-squared|||0.034|0.082|
|**First Stage IV Estimates**|||**First Stage **|**First Stage **|
|Trade Weighted Growth * Exp|||1.19<br>[.03]***|1.27<br>[.02]***|
|Trade Weighted Growth * Rec|||1.36<br>[.03]***|1.43<br>[.04]***|
|**Underidentification - Weak Identification - Wea**|**k Instruments Tes**|**ts**|||
|LM test statistic for underidentification|||84.54|33.42|
|p-value of underidentification LM statistic (Anderso<br>F statistic for weak identification (Cragg-Donald or|n or Kleibergen-P<br>Kleibergen-Paap)|aap)|0<br>857.5|7.42e-09<br>804.6|
|Anderson-Rubin chi-sqared test of significance of e|ndogenous regress|ors|40.41|13.91|
|p-value of Anderson-Rubin chi-sqared test of endog|enous regressors||1.68e-09|0.000952|

Source: Authors’ calculations based on World Economic Outlook database 2019.

Robust standard errors in brackets.*** p<0.01, ** p<0.05, * p<0.1.Underidentification tests. Ho: matrix of reduced form coefficients has rank=K1-1 -underidentified. Ha: matrix has rank=K1-identified. Weak identification test. Ho: equation is weakly identified. Weak-instrument-robust inference. Tests of joint significance of endogenous regressors B1 in main equation. Ho: B1=0 and overidentifying restrictions are valid.