rafmacalaba/datause-encoder-data huggingface dataset:
relation to those in neighboring developing countries. This tendency supported a clear vertical orientation in outward investment from Singapore to Asian developing economies, particularly in ASEAN, as headquarters operations in the former sought lower-wage labor for production in the latter. Based on the results using ASEAN market size, some of this trend could be ascribed to incoming investments from industrialized countries in skill-intensive regional headquarters services in Singapore, which in turn re-invest in ASEAN. Finally, analysis of the earlier and later sub-periods suggests that in the 1988-2003 period inward FEI, especially from industrialized countries, was strongly attracted by the growing relative skilled-labor abundance in Singapore.

These findings have important resonance for policy issues. As part of its economic development policy, the GOS followed the “complementary strategy” of rapidly building its skills base while remaining open to investment from abroad. Our results indicate that the policy has been highly successful as MNEs, particularly from the industrialized economies, increasingly invest in skill-intensive sectors in Singapore. Many international firms also use skill-abundant Singapore as a base from which to invest in neighboring ASEAN developing countries.

More fundamentally, to the extent that foreign direct investment contributes to such transformations, Singapore’s success in building its labor skills improved both its own growth prospects and the economic development of its developing-country investment partners, such as Malaysia, Thailand and Indonesia. This has been particularly the case since the late 1980s. Thus, from the point of view of both developing countries, particularly in ASEAN, and Singapore itself, the need for continued skills development in Singapore should be emphasized.

32
25 .

Table 1: Determinants of the Private Saving Ratio to Income in Previous Panel Studies ;

|Variable Category|Specific Variable|Expected Sign|Empirical|Findings|
|---|---|---|---|---|
|Income|Income level:<br>actual<br>Temporary / permanent<br>Terms of trade:<br>actual<br>Temporary / permanent<br>Growth rate:<br>actual|Oor+<br>+/Oor+<br>Oor+<br>+/Oor+<br>Ambiguous|+(1,2,3,4)<br>+ (2, 4, 6)<br>+ (2, 3)|0(5,8)<br>0 (4, 5, 6)|
|Rates of return|interest rate|Ambiguous|0 (1, 3, 5, 6)|+ (2)|
|Uncertainty|Variance ofinnovations to<br>saving determinants<br>Inflation orothermeasures of<br>macro instability<br>Measures of political instability|+<br>+<br>+|— (4)<br>0 (1|, 2, 3, 6)|
|Domestic borrowing<br>constraints|Private credit flows<br>Broad money flows<br>Income|-<br>-<br>_|+ (3)||
|Foreign borrowing<br>constraints|Foreign lending<br>Current account deficit|~<br>-|—(1, 2, 3)||
|Financial depth|Private ordomestic credit<br>stocks<br>Money stocks|Ambiguous<br>Ambiguous|~ (5)<br>+ (1, 3, 4)||
|Fiscal policy<br>,|Public saving<br>Public surplus<br>Public consumption|-<br>-<br>Ambiguous|- (1,3)<br>— (2, 5, 6)<br>- (2,6)|0 (4)|
|Pension system|Pay-as-you-go pension<br>“transfers to ald<br>Mandatory fully-funded<br>pension system contributions<br>Fullyfunded pension assets|0 or-<br>Oort+<br>Ambiguous|— (3, 4, 5)<br>+ (4)<br>0/ + (5)||
|Demographics|Old and/oryoung-age<br>population dependency<br>Urbanization<br>-|-<br>Ambiguous|— (2, 3, 4)<br>— (3)|0 (5, 6)|
|Incorne and wealth<br>distribution|Income concentration<br>Wealth conceniration|+<br>+|0 (3)||
||Capitalincomeshare<br>-|+|||

" Note: the qualitative results listed in the last column of this table summarize significant signs of saving regressors in the corresponding tables and columns of the following five studies: 7. Corbo and Schmidt-Hebbel (1991) (Table 4); 2. Masson, Bayoumi, and Samiei (1995) (Table 2, “restricted model” column); 3. Edwards (1996) (Table 2, column 5); 4. Dayal-Ghulati and Thimann (1997) (Table 4, column 2); 5. Bailliu and Reisen (1998) (Table 1, columns 3 and 4); and 6. Haque, Pesaran, and Sharma (1999) (Table 6, columns 4 and 5). Significant coefficient signs are identified by a plus or a minus. Results identified by a zero mean either an insignificant coefficient in the corresponding column of the original study or, when the variable is omitted from the particular specification reported in the column, a significant or insignificant variable in a different column of the same table.
**Figure 3.10: Total annual outage duration by cause in the US (top) and in Europe (bottom)**

<!-- Start of picture text --> 500,000 Combination of non-natural causes USA<br>Natural shock<br>450,000<br>Vandalism<br>400,000 unknown<br>350,000<br>300,000<br>250,000<br>200,000<br>150,000<br>100,000<br>50,000<br>0<br>30,000 Natural causes<br>Europe<br>Non-natural causes<br>25,000 Unknown<br>20,000<br>15,000<br>10,000<br>5,000<br>0<br>Total annual outage duration (minutes)<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br>Total annual outage duration (minutes)<br>2010 2011 2012 2013 2014 2015 2016<br><!-- End of picture text --> _Source: authors. Note: The peak in duration of outages caused by climatic events in 2014 in Europe is driven by one particular event: an ice storm in Slovenia that left the country out of power for several days._

# 4. Drivers of outages: natural shocks and external factors

Previous sections have shown that natural hazards, and storms in particular, are the leading cause of power outages in developed economies and an important factor elsewhere. Naturally, reducing corresponding economic costs presupposes understanding of exposure risk and identification of resilience factors to be harnessed for policy design. For example, this section will show that differential exposure to storms alone cannot fully explain the distribution of storm-related power outages. To assess underlying mechanisms, this section empirically tests a range of external factors that may modify the vulnerability of the electricity grid.

19
understanding from staff, with the result that many declarations are lost. Against this issue, the revenue authority is providing sustained training to staff. Extensive training takes place at RRA in Rwanda as well, where even minute changes (for instance, small modifications in a single module) are discussed at length with the staff, which get fully trained to deal with these changes. The same pattern is confirmed in Nigeria, where technology is ubiquitous and staff seem to be embracing the change.

These conversations with tax administrators highlight the importance of ensuring that digitalization is accompanied by a broad shift in work culture and structural changes in how staff are organized. This means not having an isolated IT department in charge of digitalization. Instead, there need to be deep changes in how operational departments are organized: hiring, reallocating and retraining staff as needed to maximize the impact of newly acquired data and monitoring capacity on compliance, for example, shifting from case-by-case enforcement to large-scale, data-driven interventions. These structural changes are especially important when digitalization is accompanied by an expansion in the number of registered taxpayers. Relatedly, since digitalization programs are typically very expensive, it is crucial to ensure a right match between the needs of the tax authority and the IT solutions procured. The procurement process should involve extensive consultations with staff as well as maintenance contracts that allow for some flexibility and future adjustments in the software.<sup>10</sup>

# **6.2 Issues among Taxpayers**

Our African tax administrator respondents’ description of factors affecting effective adoption of technology by taxpayers echoes some of the findings from the desk review, such as reliable infrastructure and connectivity, adequate awareness and knowledge around tax e-services, and the deliberate misuse of an IT solution to avoid taxes.

> 10Occhiali, Akol and Kargbo (forthcoming) discuss procurement lessons from in-depth case studies of the adoption process of Integrated Tax Administration System (ITAS) in Uganda and Sierra Leone, based on a series of semi-structured interviews with revenue authority and ministry of finance officials.

27
Policy Research Working Paper 8514

# **Abstract**

This paper constructs a new dataset of quarterly capital flows by sector and establishes four facts. First, the co-movement of capital inflows and outflows is driven by banks. Second, procyclicality of capital inflows is driven by banks and corporates, whereas sovereigns’ external liabilities move acyclically in advanced and countercyclically in emerging countries. Third, procyclicality of capital outflows is driven by advanced countries’ banks and emerging countries’ sovereigns (reserves). Fourth, capital inflows and outflows decline for banks and corporates when global risk aversion increases, whereas sovereigns’ flows show no response. These facts are inconsistent with a large class of theoretical models.

This paper is a product of the Development Research Group, Development Economics. 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/research. The authors may be contacted at lserven@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
_District power equalization grants_ , used in Indiana and Washington, include incentives for increased tax effort in an equalizing grant. The formula used is: grant = (per capita average fiscal capacity – per capita fiscal capacity of the district) x district tax rate _<u>Source</u>_ <u>: Vaillancourt (1998).</u> Conceptually, full capitalization requires a small open area with costless mobility. Most federations and even states in large countries do not fulfill this condition. As a result, criticism of fiscal equalization using the capitalization argument may have only weak empirical support (Shah, 1988a).

In principle, a properly designed fiscal equalization transfers program corrects distortions that may cause fiscally induced migration by equalizing net fiscal benefits across states. A reasonable estimate of the costs and benefits of providing public services in various states is essential to measure net fiscal benefits. Measures of differential revenue-raising abilities and the needs and costs of providing public services in different states must be developed. Equalization of net fiscal benefits could then be attempted by adopting a standard of equalization and establishing the means of financing the needed transfers.

# _Measuring Fiscal Capacity_

Estimating fiscal capacity—the ability of governmental units to raise revenues from their own sources—is conceptually and empirically difficult. The two most common ways of doing so are with macroeconomic indicators and the representative tax system.

Various measures of income and output serve as indicators of the ability of residents of a state to bear tax burdens. Among the better known measures are the following:

- _State gross domestic product (GDP)._ State GDP represents the total value of goods and services produced within a state. It is an imperfect guide to the ability of a state government to raise taxes, since a significant portion of income may accrue to nonresident owners of factors of production. For example, the Northern Territory has the highest per capita income in Australia, but it is treated as the poorest jurisdiction in federal-state fiscal relations.

- _State factor income._ State factor income includes all income—capital and labor— earned in the state. It makes no distinction between income earned and income retained by residents.

- _State factor income accruing to residents only._ This measure represents a more useful measure, provided states are able to tax factor income.

- _State personal income._ The sum of all income received by residents of a state is a reasonable measure of the state’s ability to bear tax burdens. It is an imperfect and partial measure of the ability to impose tax burdens, however, and therefore not a satisfactory measure of overall fiscal capacity.

- _Personal disposable income._ Personal disposable income equals personal income minus direct and indirect taxes plus transfers. This concept is subject to the same limitations affecting personal income.
|Power - Water Project||
|---|---|
|Power - Water Project||
|Power - Water Project||
|Power - Water Project||
|Power - Water Project||
|Economic Management and TrainingProject<br>||
|Economic Management and TrainingProject||
|Economic Management and TrainingProject||
|Economic Management and TrainingProject||
|Economic Management and TrainingProject||
|Mali Sud Project(02)||
|Mali Sud Project(02)||
|Mali Sud Project(02)||
|Mali Sud Project(02)||
|Mali Sud Project(02)||
|Mali Sud Project(02)||
|Mali Sud Project(02)||
|Education Project(03)||
|Education Project(03)||
|Education Project(03)<br>||
|Education Project(03)||
|Education Project(03)||
|Education Project(03)||
|Education Project(03)||
|Biomass Alcohol and EnergyEfficiencyProject||
|Biomass Alcohol and EnergyEfficiencyProject||
|Biomass Alcohol and EnergyEfficiencyProject||
|Biomass Alcohol and EnergyEfficiencyProject||
|Biomass Alcohol and EnergyEfficiencyProject||
|Biomass Alcohol and EnergyEfficiencyProject||
|Biomass Alcohol and EnergyEfficiencyProject||
|Biomass Alcohol and EnergyEfficiencyProject||
|Health Project(01)||
|Health Project(01)||
|Health Project(01)||
|Health Project(01)||
|Health Project(01)||
|Health Project(01)||
|Health Project(01)||
|Health Project(01)||
|Rural Water SupplyProject|Marie Yvonne Powers|
|Rural Water SupplyProject|Marie Yvonne Powers|
|Rural Water SupplyProject|Marie Yvonne Powers|
|Rural Water SupplyProject|Marie Yvonne Powers|
|Rural Water SupplyProject|Marie Yvonne Powers|
|Rural Water SupplyProject|Marie Yvonne Powers|
|Rural Water SupplyProject|Marie Yvonne Powers|
INFRASTRUCTURE AND GROWTH IN AFRICA

# References

Alesina, A., and R. Perotti. 1996. “Income Distribution, Political Instability, and Investment.” _European Economic Review_ 40: 1202–1229.

- Alonso-Borrego, C., Arellano, M. 1999. “Symmetrically Normalized Instrumental-Variable Estimation Using Panel  Data.” _Journal of Business and Economics Statistics 17_ , 36–49.

- Arellano, M. and Bond, S., 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations." _Review of Economic Studies 58 (2)_ , 277–97.

- Arellano, M. and Bover, O., 1995. "Another Look at the Instrumental Variable Estimation of ErrorComponent Models." _Journal of Econometrics 68 (1)_ , 29–51.

- Blanchard, O., and F. Giavazzi. 2004. “Improving the SGP Through Proper Accounting of Public Investment.” CEPR Discussion Paper 4220.

- Blundell, R. and Bond, S., 1998. “Initial Conditions and Moment Restrictions in Dynamic Panel Data Models.” _Journal of Econometrics_ 87 (1), 115–43.

- Calderón, C., and A. Chong. 2004. “Volume and Quality of Infrastructure and the Distribution of Income: An Empirical Investigation.” _Review of Income and Wealth_ 50: 87–105.

- Calderón, C., and L. Servén. 2004a. “The Effects of Infrastructure Development on Growth and Income Distribution.” Policy Research Working Paper 3400, World Bank, Washington, DC.

- ———. 2004b. “Trends in Infrastructure in Latin America, 1980–2001.” Policy Research Working Paper 3401, World Bank, Washington, DC.

- Canning, D. 1998. “A Database of World Stocks of Infrastructure, 1950–95.” _The World Bank Economic Review_ 12: 529–547.

- Easterly, W. 2001. “The Lost Decades: Explaining Developing Countries’ Stagnation in spite of Reform 1980–1998.” _Journal of Economic Growth_ 6(2): 135–157.

- Easterly, W., and R. Levine. 1997. “Africa’s Growth Tragedy: Policies and Ethnic Divisions.” _The Quarterly Journal of Economics_ 112(4): 1203–1250.

- Easterly, W., and L. Servén. 2003. _The Limits of Stabilization: Infrastructure, Public Deficits, and Growth in Latin America._ Washington, DC: World Bank; California: Stanford University Press.

- Estache, A., V. Foster, and Q. Wodon. 2002. “Accounting for Poverty in Infrastructure Reform: Learning from Latin America’s Experience.” WBI Development Studies, World Bank, Washington, DC.

- Galiani, S., P. Gertler, and E. Schargrodsky. 2005. “Water for Life: The Impact of the Privatization of Water Services on Child Mortality.” _Journal of Political Economy_ 113(1): 83–120.

Hulten. 1996.

- Hulten, C., 1996. "Infrastructure Capital and Economic Growth: How Well You Use It May Be More Important than How Much You Have." NBER Working Paper 5847, December.

20
|Country|Recovery<br>Rate (cents<br>on the<br>dollar)|MENA|OECD|ECA<br>(Europe<br>and Central<br>Asia)|LAC (Latin<br>American<br>and<br>Caribbean)|South Asia|Sub-Saharan<br>Africa|
|---|---|---|---|---|---|---|---|
|Algeria|41.7|29.9|68.6|31.6|26.8|20.4|17|
|Bahrain|63.2|29.9|68.6|31.6|26.8|20.4|17|
|Egypt|16.8|29.9|68.6|31.6|26.8|20.4|17|
|Djibouti|15.9|29.9|68.6|31.6|26.8|20.4|17|
|Iran|23.1|29.9|68.6|31.6|26.8|20.4|17|
|Iraq|Nopractice|29.9|68.6|31.6|26.8|20.4|17|
|Kuwait|34.5|29.9|68.6|31.6|26.8|20.4|17|
|Jordan|27.3|29.9|68.6|31.6|26.8|20.4|17|
|Lebanon|19.0|29.9|68.6|31.6|26.8|20.4|17|
|Libya|Nopractice|29.9|68.6|31.6|26.8|20.4|17|
|Morocco|35.1|29.9|68.6|31.6|26.8|20.4|17|
|Qatar|52.7|29.9|68.6|31.6|26.8|20.4|17|
|Oman|35.1|29.9|68.6|31.6|26.8|20.4|17|
|Saudi Arabia|37.5|29.9|68.6|31.6|26.8|20.4|17|
|Syria|29.5|29.9|68.6|31.6|26.8|20.4|17|
|Tunisia|52.3|29.9|68.6|31.6|26.8|20.4|17|
|UAE|10.2|29.9|68.6|31.6|26.8|20.4|17|
|West Bank & Gaza|Nopractice|29.9|68.6|31.6|26.8|20.4|17|
|Yemen|28.6|29.9|68.6|31.6|26.8|20.4|17|

**The DoingBusiness results show some anomalies, which bear further analysis** _._ The DoingBusiness results suggest that some countries, such as Bahrain with a 2.5 year timeframe for closing a business, which compares favorably to the OECD average of 1.7 years, may be more advanced than other sources on MENA countries would suggest.  It is important to remember, however, that this metric tracks secured creditor recoveries and that even the seemingly positive results may mask a bankruptcy system that returns little or nothing to unsecured creditors.

**There are several countries that fare particularly poorly compared to the averages of other regions, and even in comparison to fellow MENA countries** _._ One of the main reasons for the lag in ratings for MENA countries, both individually and generally, seems to be, simply, that there has been less reform in the insolvency area in these MENA countries than in many others. Especially in OECD countries laws are continually revised in response to their performance in the market. In many ECA countries, as well, there have been extensive attempts at reform over the last two decades that helped to modernize their laws and improve recovery rates and shorten the time involved in proceedings.  Many of the MENA country insolvency laws date back a decade, or even several decades. As noted, some, such as Jordan, Yemen, Iran, do not have comprehensive bankruptcy laws. As previously discussed, they do not meet international standards for best practices. Those that have undertaken significant reform, such as Morocco and Tunisia, fare better in the rankings in the Doing Business report.

12
amended. Local governments are responsible for ensuring law and order within their jurisdictions. but, as in many other countries, with a few exceptions such as defence, most responsibilities are shared more on the basis of the size of the projects than the type of expenditure. Large investment projects, the benefits of which spill over to a number of provinces, are central responsibilities, while small projects benefiting mainly the residents of a province are undertaken by the provinces. Thus, all major irrigation, flood control and embankment projects and national highways are central responsibilities, but the maintenance and repair of minor irrigation works and roads other than national highways is a local responsibility. Similarly, primary and secondary education is primarily assigned to the provinces, but higher education is central, and major hospitals are managed by the center, while the provinces run hospitals in provincial towns and districts. Provinces are also responsible for the public health centers run at the communal level.

Table 8 Share of Provincial Expenditures **in** Total, 1992

||Total<br>Expenditure<br>(Bn. Dongs)|Provincial<br>Expenditure<br>(Bn. Dongs)|Share of Provincial<br>Expenditure in<br>Total (Per cent)|
|---|---|---|---|
|1. Currcnt Expenditure|18671.0|6697.5|35.9|
|1. Gencral administrative services|2404.0|1076.7|43.1|
|2. Economic services|1490.0|1176.3|78.9|
|3. Social services<br>(i) Education|6245.0<br>1495.0|2872.6<br>1325.0|46.0<br>88.6|
|(ii) Health|1136.0|1000.3|88.1|
|(iii) Others|3614.0|547.2|15.1|
|4. Other expenditures|8532.0|1612.0|18.9|
|11. Capital Expenditure|4955.8|1706.6|34.4|
|111. Total Expenditure|23626.|8404.1|35.5|

Source:Ministry of Fmance, Government of Viet Nam.

17