rafmacalaba/datause-encoder-data huggingface dataset:
# **2a. The public sector** **_cannot_ invest**

**As the government struggles with severe fiscal pressures, public investment keeps falling.** Decades of weak revenue performance, demanding debt service and fiscal constraints – along with a high cost of inputs, particularly for electricity, and an ineffective service delivery – led to expenditure compression; as a result, the government underinvested in infrastructure. Similar constraints have undermined the quality of education, historically a point of strength in the Philippines<sup>16</sup> , and health (Table 4).

**Table 4. Sectoral Budget Allocations, 2004-2006**

||**2004**|**2005**|**2006**|
|---|---|---|---|
|Economic Services|19.4|17.2|18.7|
|Agric. & Agr. Reform|3.3|2.8|2.6|
|Social Services|28.9|27.7|27.9|
|Education|14.9|14.7|13.9|
|Health|1.7|1.4|1.3|
|Defense|4.9|4.8|5.0|
|General Public Services|16.1|15.4|15.3|
|Net Lending|0.7|0.8|0.8|
|Debt Interest Payments|30.1|34.1|32.3|
|Total|100.0|100.0|100.0|

_Source:_ Government and Ateneo Center for Economic Research and Development, 2007.

**In 2002-05, deficit reduction was driven primarily by expenditure compression.** In recent years, despite the large spending needs, infrastructure and social spending growth has been slow (Table 4). In these key sectors, spending levels declined both as a share of GDP, as a share of the total budget, and on a per capita basis. Roads maintenance, an item with high economic return, was consistently under-funded.

**In 2006, policy credibility improved ...** The bulk of the adjustment was due to the implementation of the VAT reforms<sup>17</sup> . The fiscal consolidation fostered macroeconomic

> 16 The lack of resources available for both basic and higher education is already resulting in poor mathematics and science scores in international comparisons, and a declining proficiency in English (World Bank, 2005c).

> 17 The 2006 VAT reforms raised tax revenue by 22 percent, increasing the tax/GDP ratio from 13 percent in 2005 to about 14.2 percent in 2006. This marked the first significant increase in tax effort since the postAsian crisis collapse of tax revenue.

15
through detailed exit surveys, so that it becomes possible to adjust for a wide array of patient characteristics. Another approach, which has been used to study the quality of health care in high-income countries but not in low-income countries, is to use fake patients with standardized symptoms, which is another way of holding patient characteristics constant. The ethical, feasibility and estimation issues with either approach are yet to be worked out.

A third issue is the structure of market equilibrium, recognizing that location choices of doctors are endogenous. On average, less competent providers are in poorer areas, but considerable variation exists. Why do we find competent providers in poor localities when, a short distance away, their competitors are making more money? What is the process in the public sector whereby less competent providers are assigned to poorer areas? Some of these answers must be related to the demand for health care as a function of quality. Do high-income people see better doctors because they are more educated consumers and better judges of quality, or do better doctors choose to locate where markets are more lucrative? In recent work, households were asked to rank the same set of doctors that vignettes were administered to in India. Preliminary results suggest that the overall correlation between household’s ranks and vignettes performance is fairly high, although there is substantial variation across localities (rich people do worse). Furthermore, prices reflect competence, although the relationship disappears once observable characteristics of the doctors (his/her qualification and the neighborhood the practice is located in) are included (Das, Do and Hammer, 2007). These results are a start, but further work is required to understand the market equilibrium that simultaneously explains location and pricing as a function of competence.

In concluding, we submit that the research agenda on quality of medical care in lowincome countries has contributed to our understanding of health care in three ways. First, it has 28
Policy Research Working Paper Series

||Title|Author|Date|Contact<br>for paper|
|---|---|---|---|---|
|WPS1 384|Fiscal Decentralization<br>and<br>Intergovemmental<br>Flnances In the<br>Republic of Albania|David Sewell<br>Christine I. Wallich|November<br>1994|G. Langton<br>38392|
|WPS1 385|Fiscal Federalism<br>Dimensions<br>of Tax<br>Reform In Developing<br>Countries|Robin Boadway<br>Sandra Roberts<br>Anwar Shah|November<br>1994|C. Jones<br>37754|
|WPS138|6 EU Bananarama<br>liI|Brent Borrell|December 1994|G. Ilogon<br>33732|
|WPS1S8|7 Fiscal Decentralization<br>and the Size<br>of Government An Extension with<br>Evidence<br>from Cross-Country<br>Data|Jaber Ehdale|December 1994|C. Jones<br>37699|
|WPS138|8 Does Voice Matter? For Public<br>Accountabilty, Yes|Samuel Paul|December 1994|B. Moore<br>35261|
|WPS138|9 Ruble Overhang and Ruble Shortage<br>Were They the Same Thing?|: Patrick Conway|December<br>1994|L. Suki<br>33974|
|WVPS13|90<br>Regional Integration<br>and the Baltics:<br>Which Way?|Piritta Sorsa|December 1994|J. Ngaine<br>37947|
|WPS139|1 Where in the Wotid Is Population<br>Growth Bad?|Jeff Kling<br>Lant Pritchett|December<br>1994|S. Fallon<br>38009|
|WPS139|2 Some Economic Conseque ces of<br>the Transition<br>from Civil War to Peace|Jean-Paul Azam<br>David Bevan<br>Paul Collier<br>Stefan Dercon<br>Jan Gunning<br>Sanjay Pradhan|December1994|<br>C.Jones<br>37699|
|WPS139|3 The Interface of Trade, Investment,<br>andCompetition<br>Policies Issues and<br>Challenges<br>for Latin America|J. Luis Guasch<br>Sarath Rajapatirana|December<br>1994|J. Troncoso<br>37826|
|WPS139|4 Macroeconomic<br>Reform and Growth<br>in Africa:_Adjustment_<br>_in Africa_<br>Revisited|Lawrence Bouton<br>Christine Jones<br>Miguel Kiguel|December<br>1994|R. Martin<br>39026|
|WPS139|5 A Typology of Foreign Exchange<br>Auction Markets in Sub-Saharan<br>Africa|Janine Aron<br>Ibrahim Elbadawi|December<br>1994|R. Luz<br>39059|
|WPS139|6 Foreign LEhange Auction Markets<br>In Sub-Saharan<br>Africa: Dynamic<br>Models for Auction Exchange Rates|Janine Awn<br>Ibrahim Elbadawi|December<br>1994|R.Luz<br>39059|
# **I. INTRODUCTION**

The current gloom and doom about goods trade has obscured the quiet resilience of services trade. Services account for over one-fifth of global cross-border trade, and for some countries such as India and the US close to a third of all exports. This paper uses data on cross-border trade in services from the United States released in March and April 2009 to show that while trade in goods has declined drastically, trade in some services has held up remarkably well (Figure 1).<sup>1</sup> The more aggregate data available for other OECD countries also suggest that services trade has suffered less from the crisis than goods trade.<sup>2</sup> Monthly US imports and exports of goods declined by about _one-third_ in value terms from peaks of $195 bn and $121 bn, respectively, in July 2008, to $122 bn and $85 bn, respectively, in February 2009.<sup>3</sup> The corresponding decline in services imports and exports was only by about _one-tenth_ , from $29 bn and $38 bn, respectively, in July 2008, to $26 bn and $33, respectively, in February 2009.<sup>4</sup> Figure 1: US Monthly Imports and Exports of Goods and Services, January 2006 – February 2009 <!-- Start of picture text --> 250,000<br>200,000<br>150,000<br>100,000<br>50,000<br>0<br>Goods Imports Services Imports<br>Goods Exports Services Exports<br>2006 Jan2006 Apr2006 Jul2006 Oct2007 Jan2007 Apr2007 Jul2007 Oct2008 Jan2008 Apr2008 Jul2008 Oct2009 Jan<br>USD million<br><!-- End of picture text --> Source: BEA, US International Trade in Goods and Services, millions of dollars, months seasonally adjusted.

> 1 This data also includes consumption of services abroad (in the category “travel”), but does not encompass sales through foreign affiliates or through the presence of foreign natural persons.  Recent data is not available for sales through affiliates and sales by natural persons are not properly measured (see European Commission et al. (2002) and Maurer et al. (2008)).

> 2 The US accounts for about one-fifth of imports and exports of all OECD countries.

> 3 Part of the decline in the value of goods imports could be due to the fall in commodity prices.  But note that US goods exports also declined over the last seven months by one-third.

> 4 In February 2009, the year-on-year decline in the value of goods imports was 33 percent; the decline in the value of services imports was only 7 percent.  US exports present a similar picture of year-on-year declines: a decline in goods exports by 21 percent by February; in services exports by 6.5 percent.

2
Table 2. Descriptive Statistics for Adults

|Colombian|Venezuelan|Diff.|
|---|---|---|
|(1)|(2)|(1)-(2)|
|**_Panel A:_**_Individual characteristics_|||
|Male [=1]<br>0.32|0.37|-0.05**|
|[0.47]|[0.48]|(0.02)|
|Age (Years)<br>38.58|35.08|3.50***|
|[9.33]|[7.82]|(0.32)|
|Years of Education<br>10.12|10.12|0.00|
|[3.68]|[3.44]|(0.13)|
|Married [=1]<br>0.63|0.73|-0.10***|
|[0.48]|[0.44]|(0.02)|
|**_Panel B:_**_Access to services_|||
|Sisb ́en Enrollment [=1]<br>0.73|0.36|0.37***|
|[0.45]|[0.48]|(0.02)|
|Student [=1]<br>0.01|0.00|0.01***|
|[0.11]|[0.00]|(0.00)|
|Health Insurance [=1]<br>0.88|0.45|0.42***|
|[0.33]|[0.50]|(0.02)|
|**_Panel C:_**_Labor market characteristics_|||
|Unemployed [=1]<br>0.10|0.11|-0.01|
|[0.30]|[0.31]|(0.01)|
|Self-employed [=1]<br>0.33|0.44|-0.10***|
|[0.47]|[0.50]|(0.02)|
|Informal [=1]<br>0.42|0.88|-0.46***|
|[0.49]|[0.33]|(0.02)|
|Work contract [=1]<br>0.29|0.09|0.20***|
|[0.45]|[0.28]|(0.01)|
|Observations(Allpanels)<br>2,157|1,460|3,617|

_Notes:_ Columns (1) and (2) describe the mean values for the adults born in Colombia and Venezuelan, respectively. The last column illustrates a mean difference test between both groups. Standard errors are reported in brackets. Male is a dichotomous variable [=1] if the individual is male, Age is measured in years, and the years of education are determined by identifying the highest educational level attained by each individual and associating it with the corresponding number of years, which were standardized using the guidelines provided by the Ministry of Education. Married [=1] if the respondent indicates being married or declares a consensual union couple in the survey . Sisb ́en Enrollment [=1] indicates whether the adult is registered in the proxy mean test, used to target social programs in Colombia. Student [=1] if the respondent declares that they currently attend an educational establishment. Health Insurance [=1] if the adult declares being enrolled or registered to the Health Security System. Unemployed [=1] if the respondent was looking for work the week before the survey, self-employed [=1] if the adult works at their own business or as an independent contractor or freelancer, informal [=1] if the adult does not contribute to pensions or health insurance through her job. Work Contract [=1] if the respondent declares to hold a written contract.

23
14. Levine, Ross, and David Renelt. 1991. Cross-Country Studies of Growth and Policy: Methodological, Conceptual, and Statistical Problems. Working Paper WPS 608, World Bank, Washington, D.C.

_15._ Ingram, Gregory K. Note on the Macroeconomic Linkages of Infrastructure. World Bank, Washington, D.C., October 1989.

16. Aschauer, David A. Infrastructure Expenditures and Macro Trends. In Proceedings of the Africa Infrastructure Symposium, World Bank, Washington, D.C., 1989.

17. Chhibber, Ajay. The Aggregate Supply Response: A Survey. In Simon Commander, ed., Structural Adjustment and Agriculture: Theory and Practice in Africa and Latin America. Overseas Development Institute, London, 1989.

18. Binswanger, Hans. The Policy Response of Agriculture. In Proceedings of the World Bank Annual Conference on Development Economics 1989. World Bank, Washington, D.C., 1990.

19. Dhir, M., N. Lal and K. Mital. The Development of Low-Volume Roads in India. Fourth International Conference on Low-Volume Roads, Transportation Research Board, TRR 1106, Vol. 2, Washington, D.C., 1987.

20. Shah, Anwar. Dynamics of Public Infrastructure, Industrial Productivity and Profitability. World Bank, Washington, D.C., 1990 (Forthcoming, The Review of Econiomics and Statistics, Harvard University).

21. Washington Post, The. What Path Lies Ahead for U.S. Highways? No. 183, 114th Year, June 6, Washington, D.C., 1991.

22. Hirschman, Albert 0. The Strategy for Economic Development. Yale University Press, Inc., New Haven, 1958.

23. Aschauer, David A. Is Public Expenditure Productive? Journal of Monetary Economics 23, Elsevier Science Publishers B.V. (North-Holland), Amsterdam, 1989, p. 177-200.

24. Antle, John M. Infrastructure and Aggregate Agricultural Productivity: International Evidence. Economic Development and Cultural Change, Vol. 31, No. 3. The University of Chicago Press, April 1983.

25. Israel, Arturo. Infrastructure Framework Paper. Infrastructure and Urban Development Department, World Bank, Washington, D.C., 1991.

13
percent of national income.<sup>14</sup> Moreover, the percentage of population born in the 1970-1980s that receives inheritance equal to the capitalized lifetime earnings of a worker in the bottom half of the wage distribution is about 12%, again the same as a century ago. Among the coming generations it will likely reach 15% (Chapter 11). In conclusion, Piketty agrees, yes, today’s “patrimonial capitalism” is not exactly the same as a century ago: it has a broader base and the concentration of wealth at the top is less; high labor incomes are more frequent. But its key feature—ability to generate a satisfactory income without the pain of work—is still there. Rastignac’s dilemma is back.

Are labor incomes of bankers and financiers classical labor incomes determined by marginal productivity? Piketty doubts it. He cites evidence to show that such earnings at the top depend mostly on chance events which have nothing to do with the quality of management. He does not think that the marginal product of bankers and top managers can be determined with any certainty: their high wages are the product of a collusive agreement between themselves and the boards (Chapter 9). And in order to limit them, Piketty sees a role for high (“confiscatory”) taxation. High taxes on the super rich will have minimal revenue effect. But they will dissuade bankers and managers from asking for such exorbitant salaries. As Piketty points out, when, as in the 1960s and the 1970s, US marginal tax rate on highest incomes was in the neighborhood of 90%, it did not make sense for managers to insist on another million if 90% of it would end in taxman’s coffers. But with a marginal tax rate of 25%, the story is entirely different. So, the role of “confiscatory” (marginal) taxation is not to garner revenue but to limit “socially unproductive” high incomes which are a waste, in the sense that they are not needed to make greater output forthcoming. Taxation is also needed to curb political power of the rich.<sup>15</sup> In a nutshell, societies where the K/Y ratio is high, and the rate of return on capital exceeds the rate of growth of the economy, will always tend to convert entrepreneurs into “rentiers.” In such societies “the idea that free competition will put an end to a heritage-dominated society and will lead to an ever more meritocratic world is a dangerous illusion” (Chapter 11, p. 675).

> 14 This is a useful and new statistic which, in detailed form, Piketty writes, exists only for France and the UK. It is the sum of all bequests at the time of death and of “fiscal gifts” _inter vivos_ (“donations” in French) in a year divided by yearly national income. This topic is expanded in Piketty (2011).

> 15 Piketty says it clearly (Chapter 9, p. 533): “lowering of top tax rates leads to an explosion of high salaries which in turn increases political influence—through funding of political parties, pressure groups and think tanks—of the social group that has most interest in maintaining such low rates.”

12
# The Insurance Model:

The variables are identified in Section 2.A2, where the model is described. The control regressors are in Table 2 at the end of this section.

_Crisis,, = F(gross external liabilities, capital flight, control regressors) +_ E,, (2)

# The Eliquiditv Model:

The variables are identified in Section 2.A3, where the model is described. The control regressors are in Table 2 at the end of this section.

_Crisis, = F(net external liabilities, capital flight, control regressors) +_ e,, (3) The included regressors are summarized in Table 1:

**Table 1: The Explanatory Variables**

|**FOCUS**|CONTROL|
|---|---|
|logofexternalliabilitiesgross|logoffiscaldeficit|
|logofnetexternaldebt|logofmoney/nongoldreserves|
|fall**in**netstockofcapitalflight|logofGDP|
|volatilityinM2/non-gold reserves|changein currentaccountdeficit|
|Crisis(0,1)|indexofpolitical violence|
|GDPDUM:the variabledefinedas|domesticcredittothebankingsector|
|**_ytt_**||
||realdomesticinterestrate-realworld interestrate(bank<br>rate/discountrateadjustedfor inflationintheGDPdeflator)|
||Indexofcapitalaccountrestrictions|
||Indexofcurrentaccountrestrictions|

12
educational attainment and become employed more easily. Conversely, as women become more educated and enter the labor market, fertility rates tend to fall. This scenario thus considers this two-way relationship.

The final alternative scenario ( _all interventions_ ) considers the case when there a country can achieve all the individual demographic dividend enhancing interventions together: educational convergence, accelerated productivity growth, greater mobilization of savings, improvements in employment rates, and closing the gender gap in the labor market.

For all scenarios, changes in the poverty headcount rate from the GIDD can be decomposed into three sources. The first source is the change in poverty due to the changes in employment, skill premia, and income that would have occurred had there been no additional income growth or distribution shifts – the poverty reduction effect without demographic effects. The second source of poverty reduction is the mechanical change in the distribution of households due to demographic change. This is based on the reweighting of the household surveys, and captures the impact of there being fewer (or more) households with certain demographic characteristics that in the benchmark survey data are found to be poorer (or richer). This can be referred to as the demographic composition effect. The third source of poverty reduction is the additional change in income and the income distribution that may occur when economies are able to realize their demographic dividends by absorbing the additional entrants into the working-age cohort and by increasing savings and investment due to declining child dependency ratios.

# **4. ANALYSIS**

The rising working-age population shares in SACU economies can be beneficial for Botswana, Lesotho, Namibia, and Swaziland, although to varying degrees, considering the magnitude of the possible contribution of demographic change to future growth (Figure 5). The scenario analysis framework attributes half of the real GDP per capita growth for Lesotho and Swaziland to demographic change. The average annual growth rate is 1.2 percent (versus 2.6 in the baseline) if the labor supply only grows at the same rate as the total population – keeping workers per capita constant and implying that job creation is unable to keep up with the working-age population expansion – and if declining child dependencies do not translate into greater savings. Botswana’s and Namibia’s age-structures also contribute to their baseline income per capita growth rates – accounting for 2 to 13 percent of the growth.

15
relationship? c) How do households cope with scarcity? In particular, do women and men spend more time in fuelwood collection activities and less time in agriculture in response to scarcity? We attempt to answer these questions using household data from a nation-wide survey in Malawi. We also use satellite data to assess biomass scarcity in Malawi and link the satellite images to household fuelwood use.

While there is a generally accepted notion in many parts of the world that fuelwood demand contributes to forest degradation, the impact of wood fuel harvesting on wood resources and forest health is actually not straightforward. Forest degradation can occur as a result of unsustainable use of fuelwood to meet livelihood needs. For example, Barnes _et al._ (2001) show through a 46 country based study that widespread tree removal and forest depletion around urban areas can occur as urban energy demand grows. But this demand slows as cities get wealthier.

The extent to which fuelwood harvesting contributes to deforestation or degradation depends on factors such as source of demand and supply, nature of fuelwood and charcoal markets and household practices (Arnold _et al._ 2003). Fuelwood scarcity need not contribute to deforestation as long as entire trees and root stock are not destroyed. In fact, as Dewees (1989) argues, when harvesting involves hacking of branches and collection of dead wood, this can lead to increased productivity of woodland areas.

In the case of Malawi, there is both evidence of deforestation and concern about the implications for fuelwood availability (Walker 2004, Malawi SDNP 1998). A useful question to ask is what feeds this concern. Is it simply a reflection of long-standing global environmental worries related to the gap between fuelwood supply and demand, which is echoed by Malawian officials (Dewees 1995, Walker 2004)? Or, is fuelwood scarcity sufficiently high that it affects household well being? Physical scarcity of wood fuel does not always mean that households perceive it to be scarce. Whether wood fuel is economically scarce will depend on household constraints and whether and how they are able to respond to physical scarcity (Dewees 1989, 1995). Farmers in Malawi do seem to consider fuelwood scarcity a problem. In a recent paper by Walker (2004), 92% of the farmers he interviewed in Southern Malawi were aware of decreasing tree availability and 94 to 100% of them expected this to cause problems for meeting future needs.

Fuelwood scarcity in Malawi can affect household welfare in different ways. Poor households in particular may not have access to alternate energy resources and may increase the time spent on 3