rafmacalaba/datause-encoder-data huggingface dataset:
||Changes in<br>|Government D<br>SelectedLa<br>Chan<br>Total<br> <br>|Table <br>omestic D<br>rge Develo<br>ge in Perce<br><br>|3<br>ebt and Its Major Holders 1995-<br>ping Countries<br>nt ofGDP<br><br> <br>|2004<br>|
|---|---|---|---|---|---|
||TotalGov.|C.Gov.<br>C.G|ov.in<br>C.G|ov.in<br>C.Gov.<br>Other"|Central|
||<br>Dom.Debt|<br><br>DomDebtC.|Bank<br>=Com|<br><br>.Ba**n**ks<br>iPensions|BankDebt|
|Argentina|<br>422|<br>42.2|<br> <br>114|<br> <br>187<br>TS<br>46|<br>0.0|
|Brazil”|199|272|12.8|14.5<br>o.0<br>o.0*|73|
|Mexico|162|142|7|<br>18<br>33<br>BA|2.0|
|Chile|95|-44|77|o4<br>29<br>o.0*|5.1|
|Colombia|19.5|198|03|<br>g2<br>5<br>as|03|
|Peru|10.0|69|0.5|L?<br>2.6<br>3.1|3.1|
|Uruguay”|22.0|192|6.0|39<br>a3<br>o.0*|28|
|Venezuela|32|42|3.4|<br>-15<br>o.0<br>a1|-10|
|Average|155|16.2|22|60<br>4.1<br>40|-0.7|
|China|142|9.0|7|oF<br>o.0|528|
|Bangladesh|34|3.5|13|22<br>o.0*|0.1|
|India|152|152|67|<br>114<br>10.6|0.0|
|Pakistan|3.6|3.6|75|-d4<br>154|0.0|
|Average|93|78|34|47<br>63|14|
|Indonesia|20.7|278|11.0|13.4<br>34|20|
|Malaysia|a1|33|09|23<br>40|37|
|Philippines|3.5|3.5|-10.4|Tl<br>as|0.0|
|Thailand|248|23.1|L4|Ta<br>138|17|
|Average|168|149|03|77<br>70|18|
|CzechRep.|Tl|Fl|09|68<br>12|0.0|
|<br>Hungary|-36.1|35.4|53.0|-2.6<br>20.2|0.6|
|Poland|16.1|159|3.4|A?<br>20.0|O41|
|Russia|Tl|Tl|72|O.1<br>a *|0.0|
|SlovakRep”|17.0|10.5|-45|3.5<br>65|65|
|Turkey|35.5|34.6|45|22.5<br>76|O28|
|Average|54|43|-10.7|58<br>92|11|
|Egypt|27.0|27.0|23.9|10<br>a*|0.0|
|Morocco|173|173|-23|<br>-13<br>20.9|0.0|
|Tunisia|a8|28|03|Al<br>09|0.0|
|Average|isi|15.7|7S|13<br>72|00|
|OverallAverage|12.7|12.1|-146|5.6<br>67|06|
|<br>* Country figures dete|rmuned<br>bysumof gov|ernmentdebtimthe|centralbank,|commercialbanksandpensions;<br>byassu|mptionotherisze|
|“Residualwhichinclude|<br>sinvestmentfunds,|<br>pensionfundsouts|<br>ideLatinAmer|<br> <br>ica,foreign holders,etc.||

*Total for C. Gov. Debt increase reflects changes in sum of central bank's, comm banks and pension holdings

* 1995-2003

Sources: DFS. country data, Cowan, ANOS
The profile of crisis‐vulnerable households is consistent with our _a priori_ intuition. The reduction in labor income is the primary channel of impact for households that are predicted to become poor as a direct result of the crisis. Compared to the general population, households vulnerable to the crisis are disproportionately employed in manufacturing because output and income losses are expected to occur in these sectors. They are also less skilled than the general population, but quite similar in terms of dependency, household size, and rural‐urban composition.

The crisis‐vulnerable or the “newly poor” households as a result of the crisis are also different in a number of key aspects from the more permanently poor. Compared to the structurally poor, they have “better” characteristics (lower dependency, higher skills, living in urban areas and employed outside agriculture) – characteristics that our simulations indicate would have taken them out of poverty had there been no crisis.

**Figure 6: Growth incidence curves (crisis vs. benchmark, 2010)**

<!-- Start of picture text --> (a) Per capita income: Philippines (b) Per capita income: urban and rural<br>0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100<br>Percentile Percentile<br>Urban Rural<br>0.00 0.00<br>-1.00 -1.00<br>-2.00 -2.00<br>-3.00 -3.00<br>-4.00 -4.00<br>% Change % Change<br>-5.00 -5.00<br>-6.00 -6.00<br>-7.00 -7.00<br>-8.00<br>-8.00<br><!-- End of picture text --> _Source_ : Own simulations based on FIES (2006) _Note_ : 1) GICs have been smoothed to eliminate sharp kinks in the original curves 2) Percentiles of income on the horizontal axis are for the relevant group <u>(all country, urban, rural, etc.)</u>

**How income losses between benchmark and crisis scenarios are distributed** . This analysis is similar to the familiar growth incidence curves (GICs), in examining how the changes in per capita income between benchmark and crisis scenarios in 2010 vary across the income distribution. GICs are commonly used to look at the distribution of growth over time; however the same device is useful to see changes between two “states” of the world as well, in this case the benchmark (no‐crisis) and crisis states for the same point in time. A GIC in this case will plot the percentage change in per capita income between 2010 benchmark and crisis scenarios for every centile (1% of the population) in the benchmark distribution of per capita income (when the households are ordered by per capita income).

For the country overall, the GIC of loss in per capita income (as a percentage of the benchmark income) shows significant losses (ranging from 3% to just above 4%) for households the 10<sup>th</sup> and 90<sup>th</sup> percentiles of the income distribution (Figure 6a). The largest losses (4‐7%) occur for the bottom 10 percent of the distribution, but this finding is of less significance since the errors in measuring income can be high for 18
4 One relevant question in this regard is whether SHI purchasers do better than those in tax-financed systems in terms of costs and quality by virtue of being more accountable to the public. It is indeed possible that a contributory system could result in a public that is more inclined to ask questions when the quality of care fails to meet its expectations, while the public in a tax-financed system can never point to specific taxes that were used to finance the health system. In practice, it is far from clear that SHI purchasers are more accountable to their members. On the face of it, the Philippines SHI agency, known as PhilHealth, has good governance arrangements. Yet it has successfully resisted calls to use its surplus to finance a more generous benefit package, and there have been claims that politicians have sought to use it to influence the outcomes of elections by appointing allies to jobs within the agency and having them allocate free insurance cards to marginal voters. A World Bank report in the late 1990s on health insurance in Argentina (World Bank 1997), commenting on the purchasing capacity of health insurers, argued that “it is acknowledged by Argentines that personal connections and corrupt practices, instead of quality and economy, weigh heavily in the award of capitated contracts and other payments to medical providers and suppliers, and this adds substantially to the inefficiency and high cost of health care in Argentina” (p.7). The World Bank recommended stronger regulation of health insurers and competition between them. Corruption in SHI agencies on an even bigger scale has recently been highlighted in Armenia, Kazakhstan, and Kenya (Gottret and Schieber 2006).

A likely common problem in these situations is that contributions do not automatically translate into accountability. By contrast, in a tax system, the electorate typically has the chance to express its views about the way the government has spent its taxes through the ballot box. One way that accountability can be enhanced in a SHI system is by letting members vote with their feet—i.e. giving them the option of choosing their insurer. Germany has discussed this
-17-

|E.ployment<br>in B<br>As Recorded by Demogra|**TABLE 2.2**<br>razilian<br>Manura<br>phic<br>Census and|cturing<br>198I<br>Industrial<br>Ce|nsus|
|---|---|---|---|
||Demographic<br>Census|Industrial<br>Census|Ratio<br>Demographic/<br>Industrial|
|Food and Kindred Products|904,328<br>|604,484<br>|149.6<br>|
|Beverages|115,850<br>|58,962<br>|196.5<br>|
|Tobacco Products|42,144|25,306<br>|180.8|
|Textiles|613,331<br>|379,484<br>|161.6<br>|
|Clothing<br>and Footwear|551,810|449,136|122.9|
|Wood Products|538,774<br>|252,569<br>|213.3<br>|
|Furniture|307,918|170,268<br>|180.8|
|Paper and Allied Products|138,071|106,485|129.7|
|Printing<br>and Publishing|231,696<br>|138,843<br>|166.9<br>|
|Chemicals|402,400|162,687|247.3|
|Rubber Goods|66,745|55,917|119.4|
|Plastic Goods|139,324|116,606|119.4|
|Leather and Leather Products|48,243|42,537|113.4|
|Stone, Clay and Glass Products|546,969<br>|427,728<br>|127.9<br>|
|Metal Products|945,936|523,212|180.8|
|Machinery<br>(except<br>electric)|335,683|530,119|63.3|
|Electric Machinery and Equipment|<br>302,590|238,972|126.6|
|Transport<br>Equipment|466,064|276,508|168.6|
|Miscellaneous<br>Manufactures|241,545|106,406|227.0|
|Total Manufacturing|6,939,421|4,839,253|143.4|

Source: Population census figures from IBGE (1983). Industrial census figures **from** IBGE (1984).
**Table 9: The Real Exchange Rate and Export Surges (Tobit Regressions)**

||**I**|**II**|**III**|**IV**|**V**|**VI**|
|---|---|---|---|---|---|---|
||**Merch**|**andise**|**Tradit**<br>**Servi**|**ional**<br>**ces**|**Modern**|**Services**|
|RER, percent change|0.63***|0.77***|0.83***|0.81**|1.24***|1.42*|
||[3.68]|[2.97]|[4.59]|[1.97]|[2.95]|[1.76]|
|RER*Dummy for Developing Countries||-0.18||0.03||-0.24|
|||[0.54]||[0.07]||[0.23]|
|Log Per Capita Income, Lag|0|0|0|0|0.04|0.04|
||[0.20]|[0.21]|[0.14]|[0.14]|[1.13]|[1.13]|
|Year Fixed Effects|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|1964|1964|1925|1925|1955|1955|
|Pseudo R-squared|0.19|0.19|0.14|0.14|0.057|0.057|

Note: *, **, *** indicate that coefficients are significant at 10, 5, 1 percent levels respectively. Standard errors are robust and clustered at countries. Regressions are estimated using the Tobit model and marginal effects are reported. Regressions include data up to the first year of the surge episodes. Percent change in real exchange rate is the average of the three previous years. Per capita income is lagged by one year.

# 7. **Conclusion**

The role of exports in economic growth and, in turn, of the real exchange rate in export promotion is prominent in the literature on openness and development. But much of this literature dates from the era when exports were exports of merchandise, whereas today exports increasingly mean exports of services. This raises the question of whether the emphasis in the earlier literature on the importance of a competitively valued exchange rate for promoting exports carries over to this environment.

We have studied the response of exports of merchandise and both traditional and modern services to changes in the real exchange rate in this paper. We analyze both changes in average rates of export growth and sharp surges in exports. We find that the exports of services, and especially modern services, respond even more than the exports of merchandise to changes in the real exchange rate. This may reflect the fact that services, especially modern services, use fewer imported inputs, that these sectors have lower fixed costs of entry, making for a more elastic supply response, or that the demand for these exports is more price elastic. In contrast, we do not find differential effects across advanced and developing countries. Nonetheless, as less-advanced countries shift in the course of development from exporting primarily commodities and merchandise to exporting traditional and modern services, these findings suggest that appropriate policies toward the real exchange rate become, if anything, even more important.

This said, relying on an undervalued exchange rate to encourage the growth of exports of services, as of merchandise, has its limitations. Limiting the natural tendency for the real exchange rate to appreciate as an economy develops can have costs as well as benefits. Eichengreen (2008) and Haddad and Pancaro (2010) caution that depreciation and undervaluation can be used to spur growth only in the short term, because a country cannot maintain a depreciated real exchange rate indefinitely. Potential problems include tensions with 18
_35_ Table 5: Labor Force in Selective Sectors (unit=million)

|Year|Agriculture<br>Sta|Indust<br>te<br>Non-|rv<br>state|Construction|Transportation|Commerce|
|---|---|---|---|---|---|---|
|* 1978|283.73|31i39|29.52|8-75|7.35|11.55|
|1979|286592|32.08|30.90|9.43|7.65|12.48|
|- .<br>1980|291.81|33.34|33.80|10.22|7.87.|13.81.|
|*<br>1981|298.36|34.88|_34.87_|10.58|8.24|15.11|
|1982|309.17|35.82|36.22|11.73|8.50|16.04|
|1983|312.09|36.32|37.65|13.14|9.07|17.62|
|1984|309.27|36.69|42.67|16.92|10.81|20.36|
|1985|311.87|38.15|45.34|20.69|12.22|23.63|
|1986|313.11|39.55|50.25|22.71|13.05|24.85|
|1987|317.20-|40.86|52.57|24.19|13.73|26.55|
|1988|323.08|42.29|54.32|25.27|14.34|28.29|
|1989|332.84|42.73|52.95|24.44|14.32|28.60|
|1990|341.77|43.64|53.33|24.61|14.69|29.37|
|1991|350.16|44.72|54.75|25.21|15.15|31.00|
|1992|348.55|45.21|56.98|27.02|15.73|33.12|

Source: China Statistical Yearbook, 1993, p. 98. and p.107 Table 6: Index and Growth Rate of National Income in Selective Sectors Year Total Agriculture Industrvy' Construction Transportation Commerce Total State Index (1952=100) 1952 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1978 453.4 161.2 1438.9 3345.3 573.5 546.9 296.4 1992 1473.2 332.9 7011.2 9825.7 2455.0 18B8.5 749.2 Average Annual Growth Rate (percent) 1952-78 6.0 1.9 10.8 14.S 6.9 .6 *8 4.3 1978-92 8.8 5.3 13.2 8.0 _10.9_ 9.2 _6.9_ Source: China Statistical Yearbock, 1993, p. 34 and p. 413.

Note: *Gross value of industrial output measured at constant prices.
Concerning fiscal balance, all countries except Sri Lanka registered large deterioration (figure 15). The fiscal deficit widened most for Pakistan, rising from 2.4 percent of GDP in 2004 to 7.4 percent in 2008. India had made good progress in reducing fiscal deficit between 2003 and 2007. This progress was reversed in 2008 due to a sharp increase in the fuel subsidy (growing from 1 % of GDP in FY2007 to an estimated 4% of GDP in

# **Figure 15. Fiscal Deficits in South Asia**

<!-- Start of picture text --> 12<br>10<br>8<br>6<br>4<br>2<br>0<br>2002 2003 2004 2005 2006 2007 2008<br>Bangladesh India Nepal Pakistan SriLanka<br>Percent of GDP<br><!-- End of picture text --> Source: Data collected from concerned government authorities FY2009) that threatens to wipe off the gains made so painfully over the past few years. Bangladesh took steps to contain the fiscal deficit. Even so, budget deficit widened to almost 5 percent in 2008 and is projected to grow further, mostly due to increases in food and petroleum subsidies and spending on safety nets<sup>4</sup> . Nepal’s fiscal deficit has also grown from its low level in 2004 owing mainly due to fuel subsidy. Sri Lanka is the only surprising exception. It has long suffered from high fiscal deficits linked to the ongoing civil war. As a result, it had little space to expand further the deficit. Instead, Sri Lanka passed on most of the global price increases in petroleum to consumers.

**Impact on inflation:** Rising food and fuel prices have been a major source of inflationary pressure in South Asian countries (Figure 16).  In Afghanistan, Sri Lanka, Pakistan, Bangladesh and Nepal, food prices made a bigger impact on inflation than fuel prices.  In India, however, the main surge to inflation came from fuel price increases. Pakistan experienced the most rapid change in the rate of inflation, rising from 8 percent in 2006 to 25 percent in July 2008.  This is in part due to the global food price hike, but also due to domestic demand pressure emerging from unsustainable macroeconomic policies.  Sri Lanka had already been experiencing inflationary pressure from expansionary fiscal and monetary policies; the surge in food and fuel prices accelerated the pace.  Afghanistan’s inflation hike came primarily from food prices.  Since the increase in grain prices for Afghanistan much exceeded other South Asian countries

> 4 Includes off-budget subsidies.  Recent reduction in world fuel prices if sustained will help keep fiscal deficit at the 5% of GDP level.

17
Second, for each infrastructure contract, we reviewed the webpage of CDR to identify the actualized expenditure of each contract _,_ as well as the names of design and supervision consultants. We also recorded the values of supervision consultancies and matched each consultancy to its corresponding infrastructure contract.

# **The dependent variables**

Our key dependent variables are the contract values for infrastructure and consultancy projects. We chose contracts—rather than projects—since bargaining takes place over contracts.<sup>5</sup> Of the 394 contracts in our data set, we record 384 contracts for which we can identify the contractor, 361 of which contained information on the supervision consultancy and 233 of which we can associate a design contract (Table 1). The missing contracts are distributed relatively evenly among sectors in terms of share of contracts, total value, and mean value of contracts. Exceptions are the irrigation and solid waste sectors in which our subsample includes larger values, which are, however, the smallest sectors with 11 and 12 observations. In total, we capture 99.5 percent and 80.6 percent of all contract values with our subsample of supervision and design contracts.

Table 1: Composition of data set based on infrastructure contracts

|||**Transport**|**Water works**|**Solid waste**|**Irrigation**|**Education**|**Other**|**Total**|
|---|---|---|---|---|---|---|---|---|
||n|79|106|12|11|73|103|384|
|**Total**|Total contract<br>value|1,162|1,189|507.4|413.6|321.4|392.5|3,986|
||Mean con-<br>tract value|14.7|11.2|42.3|20.7|4.4|3.8|10.1|
||n|74|103|11|8|73|92|361|
||% of all con-<br>tracts|93.7%|97.2%|91.7%|72.7%|100.0%|89.3%|94.0%|
|**Super-**<br>**vision**|Total contract<br>value|1,158|1,186|505.4|406.9|321.5|385.9|3,964|
||% of total<br>contract value|99.7%|99.8%|99.6%|98.4%|100.0%|98.3%|99.5%|
||Mean con-<br>tract value|15.7|11.5|45.9|50.9|4.4|4.2|10.9|
||n|41|72|8|8|37|67|233|
|**Di**|% of all pro-<br>jects|51.9%|67.9%|66.7%|72.7%|50.7%|65.0%|60.7%|
|**esgn**|Total contract<br>value|718.8|1,054|499.4|406.9|222.7|309.4|3,211|
||% of total<br>contract value|61.9%|88.7%|98.4%|98.4%|69.3%|78.8%|80.6%|

5 Contracts can encompass multiple projects, all of which are implemented by the same contractor and consultant and pertain to the same contract ID. See Mahmalat, Atallah and Maktabi (2021) for a detailed description.

9
hierarchical system marked by disagreement and contestation around social norms, on the contrary will serve as a fractious basis on which democracy, even if introduced by external intervention, will perish. Moreover, much of this scholarship does not contend with the existence of inequality. In fact, some scholars like Lyotard (1984) and Luhmann (1982) have criticized Habermas’s emphasis on reaching consensus via deliberation, interpreting such consensus as a new form of hegemony that may potentially mask the interests and narratives of marginalized groups. However, despite such theoretical criticisms, the ideal of deliberative democracy tends to maintain its intellectual dominance in thinking about how democracy should indeed operate in the real world. This dominance is reflected in the few existing empirical studies, like the extremely insightful ethnographies of Manbridge (1980: rural Vermont) and Baiocchi (2005: Porte Allegre, Brazil), which emphasize deliberative, consensual agreement.

However, a useful cultural approach to democracy, we argue, has been suggested by scholars of communication (Barnett 2003) who have pointed out that, in cultural terms, democracy itself is an ‘artful practice’ in that it involves “the formal and informal cultivation of competencies of judging, reasoning, appreciating, performing and responding” (199). Scholars have duly emphasized the importance of deconstructing “representation” - asking “Who speaks?”, given that speaking “depends on an individual’s position within regulated systems of discourse” (Barnett 2003: 16) - and focusing on the “technologies and techniques of persuasion” used in speaking (Morris 1998: 230). This idea of democracy as an artful cultural practice reinforces our argument in favor of considering discursive styles as part of a cultural tool-kit and political 11
# 8 **References**

- Aghion, P. 1995. "Formal and Reality in Organizations". Mimeograph, Oxford University.

- Agion, P. and Dewatripont, M., and Rey, P. 1994. "Renegotiation<sup>Design with</sup> Unverifiable Information". _Econometrica._ 62:257-82.

- Alchian, A., and Demsetz, H. 1972. "Production, Information<sup>Costs, and</sup> Economic Organization". _American Economic Review,_ 62(5):777-95.

- Chandler, A.D. 1990. Scale and Scope: The Dynamics of Industrial<sup>Capitalism..</sup> Cambridge, Mass.: Harvard University Press.

- Coase, R.H. 1937. "The Nature of the Firm". _Economica._ 4:386-405.

- Coase, R.H. 1960. "The Problem of Social Cost". _Journal of Law and_<sup>_Economics_</sup> _and Organization._ 4(1):33-47.

- Cremer, Jacques. 1994. "A Theory of Vertical Integration Based on Monitoring Costs". Mimeo, IDEL.

- Cremer, Jacques, Antonio Estache and Paul Seabright. 1995. "The Decentralization of Public Services: Lessons from the Theory of the Firm", in Antonio Estache (ed.), Decentralizing Infrastructure: Advantages and Limitations. World Bank Discussion Paper #290. Washington, D.C.: World Bank.

- Dewatripont, M. 1989. "Renegotiation and Information Revelation over<sup>Time:</sup> The Case of Optimal Labor Contracts". _Quarterly Journal of Economics._ 104(3), 589-619.

- Dewatripont, M. and Tirole, J. 1994. "A Theory of Debt and Equity: Diversity<sup>of</sup> Securities and Manager-Shareholder Congruence". _Quarterly Journal of Economics._ 109:1027-54.

- Eid, Florence. Forthcoming, Spring 2000. "Changing the Managerial Mindset: the FONDEVE in Conchali, Chile", in: Campbell, Tim, and Harald Fuhr (eds.). Making Decentralization Work: Innovations in Local Government in Latin America. Washington, D.C.: The World Bank.

- Eid, Florence. 1999b. "Governance and Incentives in Corporatized public hospitals: The case of Lebanon." Unpublished paper.

38
Analyses of HIV discordant couples have mainly been published in the medical literature. Serwadda and others (1995), Quinn and others (2000) and Gray and others (2001) use data from discordant couples from the same community based study in the Rakai district in Uganda to explore the dynamics of HIV transmission, to measure HIV incidence per person year, the rates of male-to-female and female-to-male transmission and the probability of HIV transmission per coital act. Interestingly, Quinn and others (2000) found that out of 415 discordant couples in their study area, in 228 couples the male partner was HIV positive, while it was the female partner in 187 couples. This ratio of discordant male over discordant female couples is in the range of the ratios reported in table 1 and confirms that in rural Uganda as well, there is a substantial fraction of the discordant couples where it is the woman who is HIV positive. Carpenter and others (1999) also find, in a neighboring district in Uganda, that the proportion of discordant female couples is similar to the proportion of discordant males.

Siriwasin and others (1998) find that in Bangkok twenty-six percent of partners of HIVpositive pregnant women are HIV negative and consider this an unexpected result. Read from this angle, table 1 reveals results than are even more unexpected that the ones from Thailand: comparing the rows for concordant positive and for discordant female indicates that in the five African countries, the proportion of discordant female couple is always higher and that therefore certainly more than one half of the married or cohabiting women who are HIV positive have not been infected by their current partner. A similar conclusion can be made for HIV positive men, except in Kenya.

The remainder of the paper will investigate the robustness of the two surprising findings about the large fraction of discordant couples and of couples who are discordant female. Section II presents the data and the methodology. Section III investigates the fact that the majority of infected couples are discordant while section IV focuses on verifying that the finding on the substantial proportion of discordant female couples is robust. Section V compares discordance in HIV status among couples with discordances in self-reported sexual behaviors. Section VI concludes.

5