rafmacalaba/datause-encoder-data huggingface dataset:
health services and access to labor opportunities. In the paper, we look at all three channels with a focus on the third one. We assume that access to roads has a different impact on incomes, depending on the type of activity carried out. We underline that poverty reduction depends on the type of activity the household is involved in. Some activities could be considered as a poverty trap. Our particular interest lies in the difference between agricultural and non-farming activities since agriculture represented 61% of total employment in Cameroon in 2001 and constitutes the major activity in which poor households are involved.

Our second contribution lies in the use of data from the second Cameroonian national household surveys ("Deuxième Enquête Camerounaise Auprès des Ménages", ECAM II) from which the infrastructure side has been poorly (if not) used in the literature. It covers all the dimensions of poverty and introduces the basis of a monitoring and evaluation system of households' livelihoods. The three national households surveys (the first was in 1996 and the last one in 2007) are also at the core of the reduction poverty plan for Cameroon, since poverty in Cameroon is of major concern since the 80s<sup>4</sup> . Economic growth began to recover from 1994 but the first national household surveys revealed that 50.5% of the Cameroon population lived under the poverty line in 1996. In 1998/99, private consumption was stagnant thus highlighting the fact that economic growth did not reach population and more importantly the poorest part of it<sup>5</sup> .

Finally, unlike the majority of cross-section analyses of poverty and road access, our results do not call for huge, widespread investments in roads to fight against poverty. We demonstrate that road access, proxied by the time (in hours) needed to reach the closest tarred road, has no direct impact on consumption expenditures at the household level when we control for the three channels identified by the literature. Our results from a simultaneous estimate of consumption and labor activities determinants contribute to the idea that emphasis on roads investment should be given to locations where non-farming activities could be developed, which seriously questions the big push in infrastructure in Sub-Saharan Africa, all

> 4 While before 1985 Cameroon exhibited average annual growth rate of 7% thanks to a continuous development of the agricultural production and the exploitation of oil resources, after 1986 and the drop of oil and other exports rates, the economy suffered from a strong degradation (contraction of the economy of 8.2% of GDP and negative growth rate for the year 1986/87). The structural adjustments measures put in place did not suffice to deal with the adverse consequences of the shock. Between 1985/1986 and 1992/1993 consumption per capita fell by 40% and the investment rate was divided by 2 (27% to 13%). Employment and the supply of social services (health, education and other infrastructures services as roads) have also been seriously damaged. 5 Information are drawn from the report on ECAM II.

4
<!-- Start of picture text --> Proportion of Married Individuals By Age<br>surveyed individuals aged 40 or less<br>eo<br>oo oo<br>J Lf<br>=/<br>5<br>So iHl<br>om a<br>=) f<br>rai ?<br>i<br>sy :f<br>a<br>2 toa<br>a 10 20 30 40<br>Age<br>- Deaths per Year of Conflict<br>=<br>eo<br>ES<br>oo |<br>oo<br>w<br>a<br>ao<br>=<br>co<br>oo<br>=<br>o 001-2002<br>2052 2054 2056 2058 2060 2062<br>(1995-1996) Nepalese Calendar Year (2005-2006)<br><!-- End of picture text -->
'is

# Expenditure 2: Education Expenditure as Percent of Total goverrment Expenditure Suzmary Table

||Number|1975|1980|1985|
|---|---|---|---|---|
|ALL DEVELOPING<br>COUNTRIES|49|13.65<br>|13.70<br>|13.01<br>|
|Low Income|15|12.40<br>|11.10<br>|11.27<br>|
|Middle Income|34|14.20|14.85|13.78|
|AFRICA|11<br>|15.58<br>|16.30<br>|14.84<br>|
|Low Income|8<br>|15.93<br>|14.37<br>|13.87<br>|
|atiddle<br>Income|3|14.64|21.46|17.43|
|EAST ASIA|6|15.14|14.90|17.85|
|Low Income|1|8.87|8.31|10.42<br>|
|Middle Income|5|16.39|16.21|19.34|
|SOUTH ASIA|6<br>|8.29<br>|7.21<br>|7.94<br>|
|Low Income|6|8.29|7.21|7.94|
|EMEMA|12<br>|10.77|12.17<br>|11.37<br>|
|Middle<br>Income|12|10.77|12.17|11.37|
|EASTERN EUROPE|2|1.11<br>|1.50<br>|0.90<br>|
|Middle Income|2|1.11|1.50|0.90|
|_LAC_|12|18.78|17.53|15.11|
|Middle Income|12|18.78|17.53|15.11|

Note: Includes 2n1Z the countries with complete data for the periods in the table.

Source: IMfF Govertment Financial Statistics: Consolidated Central Government Expenditure.
trade has remained relatively constant since the 1980s. In part this is because of the dynamic growth that has occurred in merchandise trade – driven by fragmentation and global production sharing intra-industry trade – and in part it reflects the fact that many services remain less or nontradable. The relatively constant share of total services in world trade hides large changes in the composition of trade. Much of the recent growth in cross-border services trade has been in so-called business process outsourcing (BPO) services, which occurs mostly through mode 1- type transactions and is captured in the balance of payments category “other commercial services”. The rapid growth in trade in such activities has led to a significant decline in the shares of more traditional services – transport and travel (Figure 1).

**Figure 1. Sectoral shares of services in total world services exports, 1990-2004**

<!-- Start of picture text --> 1990<br>2000<br>Transportation 2004<br>Travel<br>Other commercial services<br>0 10 20 30 40 50<br><!-- End of picture text --> _Source_ : WTO (2005).

Mode 1 has become more controversial in policy terms as the absolute value of such trade has grown. Bhagwati, Panagariya and Srinivasan (2004) point out that mode 1 trade in services is analytically equivalent to a technical change that lowers the relative price (wage) of more skilled-intensive labor in the importing country.<sup>10</sup> This will have standard distributional consequences for factors of production and generate an overall gain for the economy in the absence of significant adverse terms of trade effects.<sup>11</sup> Such adverse effects may be possible, but in itself this is not something that is specific to the trade being in services or occurring via mode 1. More likely is that such trade will raise productivity if it is an input or raise real incomes if it

> 10 Bhagwati (1984b) pointed out that as services tend to be cheaper in developing countries, they have great potential to export services directly, as well as embodied in goods. Bhagwati was prescient in recognizing this and the associated policy implications—one of which is to reduce the pressure/need for migration. However, given that the scope for cross-border trade through telecommunications networks will be limited for many services, pressures for such factor movement—temporary or longer-term—will persist, explaining why mode 4 exports is an important subject for developing countries in the context of trade agreements.

> 11 Bradford Jensen and Kletzer (2005) assess the impacts of services trade on wages and employment of workers with different skill levels in the US.

6
_Figure 14. Probability of extreme poverty for selected household demographic types by specification_ <!-- Start of picture text --> 25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>Male adults, Female One Fem Other combo, One male One male one<br>with children adults, with adult, with with children adult, with fem, with<br>children children children children<br>Unconditional Within country Within country and controls<br><!-- End of picture text --> Note: Sample of 89 countries Source: WB Staff’s calculations based on GMD.

_Figure 15. Probability of extreme poverty for selected household economic types by specification_ <!-- Start of picture text --> 25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>No earners, adult One female earner, One male earner, One female earner,<br>deps, traditional adult deps, adult deps, No adult deps,<br>deps traditional deps traditional deps Traditional deps<br>Unconditional Within country Within country and controls<br>Share of households that are poor<br><!-- End of picture text --> Note: Sample of 71 countries Source: WB Staff’s calculations based on GMD.

32
# **References**

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- ASHRAF, N. (2009): “Spousal control and intra-household decision making: An experimental study in the Philippines,” _American Economic Review_ , 99, 1245–77.

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- BANK, W. (2011): _World development report 2012: Gender equality and development_ , The World Bank.

- BAR, R. AND A. ZUSSMAN (2017): “Customer discrimination: evidence from Israel,” _Journal of Labor Economics_ , 35, 1031–1059.

- BARTLETT, K. T. AND M. GULATI (2016): “Discrimination by Customers,” https://ilr.law.uiowa.edu/print/volume-102-issue-1/discrimination-by-customers/.

- BECKER, G. S. ET AL. (1971): “The Economics of Discrimination,” _University of Chicago Press Economics Books_ .

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- BLAU, F. D. AND L. M. KAHN (2017): “The Gender Wage Gap: Extent, Trends, and Explanations,” _Journal of Economic Literature_ , 55, 789–865.

- BORKER, G. (2021): “Safety First: Perceived Risk of Street Harassment and Educational Choices of Women,” _Working Paper_ .

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- CALIENDO, M., W.-S. LEE, AND R. MAHLSTEDT (2017): “The Gender Wage Gap and the Role of Reservation Wages: New Evidence for Unemployed Workers,” _Journal of Economic Behavior & Organization_ , 136, 161–173.

- CARD, D., A. R. CARDOSO, AND P. KLINE (2016): “Bargaining, sorting, and the gender wage gap: Quantifying the impact of firms on the relative pay of women,” _The Quarterly journal of economics_ , 131, 633–686.

- CASTILLO, M., R. PETRIE, M. TORERO, AND L. VESTERLUND (2013): “Gender Differences in Bargaining Outcomes: A Field Experiment on Discrimination,” _Journal of Public Economics_ , 99, 35–48.

17
55

# **Annex 4: Government Debt as Share of GDP**

# **Figure A4.1: Australia - Gross Government Debt as Share of GDP**

<!-- Start of picture text --> 25<br>States Commonwealth<br>20<br>15<br>10<br>5<br>0<br>1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009<br>Source: Australian Bureau of Statistics<br>% of GDP<br><!-- End of picture text -->

# **Figure A4.2: Brazil - Net Government Debt as Share of GDP**

<!-- Start of picture text --> 45<br>40 SNG CG<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>1993.01 1994.01 1995.01 1996.01 1997.01 1998.01 1999.01 2000.01 2001.01 2002.01 2003.01 2004.01 2005.01 2006.01 2007.01 2008.01 2009.01 2010.01<br>Note: SNG=Subnational Government, CG=Central Government<br>Source: Instituto de Pesquisa Econômica Aplicada (IPEA)<br>% of GDP<br><!-- End of picture text -->
# **B - Equatorial Guinea’s Economic Management until the Onset of Oil (1982 - 1995)**

The Government of Equatorial Guinea was confronted with two equally important issues which are: (i) to create favorable conditions for raising food and cash crop production and increasing exports, and (ii) to rebuild the public administration and social institutions needed to support the country’s reconstruction.

<!-- Start of picture text --> Equatorial Guinea: Revenue from Exports in million of US$<br>1980 - 1990<br>35<br>30<br>25<br>20 Cocoa<br>Timber<br>15 Coffee<br>10<br>5<br>0<br>1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990<br>Years<br>Exports in million of US$<br><!-- End of picture text --> Source: Equatoguinean authorities and World Bank Private sector involvement was slow and hesitant in the reconstruction process given the shortage of local entrepreneurs and the weakness and inconvertibility of the domestic currency. In that context, most economic activities remained under governmental control. The rehabilitation of the cocoa sector was slow because both domestic and foreign labor showed little interest in working there, because of the combination of the experience with forced labor under the former regime and inadequate economic incentives.

In an effort to attract foreign aid, the government presented a three year reconstruction program 1982-1984 to an International Donor conference in April 1982. The program identified agriculture and infrastructure as the main development priorities, and several donors expressed interest in financing projects. In addition, given the weak public administration and the limited capacity, the government decided to transfer responsibilities for some key sectors - petroleum and forestry - of the economy from the Ministries concerned to the presidency in order to centralize the decision-making process, minimize coordination problems, and to efficiently allocate the limited existing skills. This new economic program was not sustained.

In 1985, Equatorial Guinea became a member of the Bank of Central African States (BEAC). Efforts to rebuild the economy were renewed, but overall growth was marginal; although timber production increased appreciably and activity in the commerce and trade sectors expanded, the production and export of cocoa, the country’s main foreign exchange earning, stagnated far below levels achieved before independence and 6
6

**For MDG1, the poverty reduction value is calculated through a simplifying assumption.** Equation (4) assumes that poverty reduction is mostly driven by the growth of the economy, via the elasticity<sup>6</sup> of non-oil GDP on poverty.<sup>7</sup> The residual reduction is achieved through government spending, indicated with E _p_ . This shows the expenditure that each year needs to be allocated to poverty reduction programs to close the gap with the MDG1 target (or the expected cost of reaching each year’s poverty target), once the reduction of poverty associated with economic growth has been taken into account. Hence, for the period 2008-2015 equation (4) constructs an indicator, normalized between zero and one, by which the required change in poverty spending, or ΔEp, is equal to one minus the change in the elasticity of non-oil GDP on poverty.<sup>8</sup>

Once equation (4) determines ΔEp, equation (5) calculates E _p_ , by multiplying ΔEp by the budget allocated to poverty reduction programs in the previous year. Then, the financing gap for MDG1 is obtained with Equation (1), by subtracting from E _p_ the budget projection already officially allocated to poverty reduction programs.

> 6 In this paper we assume linearity between growth and poverty reduction – i.e.: growth reduces poverty uniformly across population’s quintiles. However, according to the evidence shown in recent literature, the elasticity of poverty reduction with respect to growth is not linear, especially in Africa – i.e.: the poorest the population, the lower the lifting effect of growth (Easterly, 2007).

> 7 Between 2008 and 2015, the elasticity of non-oil GDP with respect to poverty is calculated by using the available yearly projections for both non-oil GDP growth and poverty incidence until 2015.

> 8 The change in the required poverty spending is equal to the change in the absolute value of the elasticity of poverty on non-oil GDP; in this simulation however, it is calculated the other way, as it is easier to grasp intuitively.
generally show a higher incidence of poverty in all the surveys since 1989. In 2002, the per capita consumption in female-headed households (J$7,795) was nearly 22 percent lower than in male headed households.

Despite persistent high unemployment rates, average real wages and salary earnings in Jamaica have risen strongly in the late 1990s. As seen in Figure 1, between 1990 and 2002, average real weekly earnings in Jamaican dollars have more than doubled (a compound growth rate of 16 percent per year). In US dollars, earnings have also almost doubled.

**Figure 1 Unemployment Rate(%) and Average Annual Real Wage per Worker (J$/CPI), 1990-2002**

<!-- Start of picture text --> 25 2500<br>20 2000<br>15 1500<br>Unemployment<br>Real Wage<br>10 1000<br>5 500<br>0 0<br>Real Wage<br>Unemployment Rate(%)<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002<br><!-- End of picture text --> Source: Author's calculation from the survey. CPI is from the Central Bank of Jamaica. Note: The base year for CPI is 1995.

What are the causes of the growth in real wages under persistent unemployment in Jamaica? Labor productivity growth does not seem to be one of them. There is no evidence of a significant increase in average labor productivity in the industrial, agriculture or service sectors.<sup>4</sup> Nationally, productivity seems to be in fact declining, not increasing.

This drop in productivity is likely associated to a decline in the level of education of the labor force. The average years of education of the labor force by birth cohort has

> 4 Labor productivity (GDP/Employees) by sector is almost flat from 1995 to 2003. See World bank(2006a) and World Bank (2006c).

4
manufacturers to fully participate in global production sharing. These measures include more effective duty exemptions for intermediates used in the production of manufactured exports, tariff cuts intended to bring tariffs on manufactured products to around the 7% level prevailing in China post-Accession (Ianchovichina and Martin 2004, p11), and reduction in international transport costs to and from India by 20%.<sup>5</sup> We find that the impact of implementing a well-functioning duty drawback system in India on the world economy is relatively small. This is not surprising given the fact that India’s economy is not yet well integrated with the global economy. In 2001 India’s share in total intermediate imports of motor vehicles, machinery and equipment, electronics and other manufactures used in the production of exports was 1.7 percent, compared to 10.2 percent for China. India’s share in total intermediate imports used in the production of exports<sup>6</sup> was 1.2 percent in 2001.

The effect of implementing duty exemptions successfully and lowering tariffs and transport costs is small at the aggregate level, but significant for some industries in India (Table 2). India’s total welfare gain from these reforms is assessed at $5 billion per year (in 2001 dollars), or close to 1 percent of per capita real income. The largest part of this gain in welfare is from transport cost savings ($2.2 billion, nearly half of the welfare gain), followed by $1.6 billion from tariff cuts on manufactured goods, and $1.1 billion from successful implementation of duty drawbacks. Output expansion is strong for the sectors benefiting most strongly from duty exemptions. The electronics sector expands by 35 percent, machinery and equipment by 21 percent, apparel by 13 percent, leather goods by 12 percent, other manufactures by 9 percent, and motor vehicles and parts by 1 percent (Table 2). The sectors producing textiles, metals, chemicals, minerals, wood and paper products contract and their producer prices decline as a result of increased competition from imports (Table 2).

The results suggest that India will likely strengthen its ties with global production chains and expand its trade in manufactured products if duty exemption/drawback arrangements are made more effective, trade is liberalized and logistical efficiency increased. Exports of Indian manufactured products will

> 5 The tariff reduction is based on continuation of the rapid liberalization undertaken in India’s non-agricultural tariffs in recent years. The reduction in transport costs is based on broad estimates by trade-facilitation experts of the potential costreducing impacts of trade facilitation measures.

> 6 Source www.gtap.org

10
**Table 11:  Firm-level outcomes of city upgrading and city capacity for incumbents**

|**_Incumbent Firms_**|Log main<br>operating<br>revenue|Log main<br>operating<br>cost|Log main<br>operating<br>profit|Log # of<br>employees|Log labor<br>vocational|Log<br>wage per<br>employee|Log<br>export|
|---|---|---|---|---|---|---|---|
|**City**|-1.210**|-1.216**|-1.311**|-0.580|-0.252|-0.452*|-0.348|
||(0.504)|(0.501)|(0.537)|(0.390)|(0.357)|(0.262)|(0.925)|
|**Capacity**|-21.56***|-22.01***|-17.69***|-14.79***|-15.43***|-0.127|-7.195|
||(4.616)|(4.775)|(4.695)|(3.426)|(4.028)|(1.640)|(12.58)|
|**City × Capacity**|**46.61****|**46.65****|**49.13****|**18.57**|**8.353**|**17.37***|**8.777**|
||(20.33)|(20.12)|(21.80)|(15.02)|(13.86)|(10.38)|(37.08)|
|**Constant**|11.85***|11.43***|10.12***|6.673***|3.117***|8.353***|9.227***|
||(0.672)|(0.658)|(0.752)|(0.385)|(0.219)|(0.509)|(0.990)|
|Observations|32,517|32,428|21,283|18,193|3,892|17,496|4,759|
|R-squared|0.330|0.336|0.228|0.245|0.221|0.251|0.179|
|Block FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Industry**×**Year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Province FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

1. Significance levels of 10%, 5%, 1% are represented by *, **, ***, respectively.

2. Standard errors are in parentheses and clustered at county-level.

3. Analysis is restricted to firms opened before 1997.

4. Vocational labor data is only available in 2004.

16
pollution haven hypothesis predicts that this elasticity would fall (and become negative) as per capita income rises. They found the reverse: trade tended (at the margin) to shift SO2-intensive industry to relatively high income countries with relatively stringent pollution regulation. They conjecture that the explanation for this is that SO2-intensive industry is also capital intensive, and relative capital abundance is more important for determining trade patterns in such goods than differences in environmental policy. Ederington, Levinson and Minier (2004) found that US manufacturing production has shifted towards less polluting industries. They ask whether increased openness to trade can account for this. If the pollution haven hypothesis was operative, then one would expect that the shift to cleaner production would be explained in part by the pattern of trade liberalization. However, they find that tariff reductions over the past several decades cannot account for the shift in the composition of US manufacturing toward cleaner industries. They also compared the pollution<sup>8</sup> embodied in US imports from developing countries to the pollution embodied in US exports during the period 1972-94. They found that US imports became cleaner relative to exports during this period, a result that is inconsistent with the strong form of the pollution haven hypothesis. Levinson (2010) restricts his analysis to air pollutants, but accounts for pollution generated by intermediate goods production (previous work estimated only pollution from final goods). He also finds that the composition of U.S. imports has shifted towards cleaner goods.

What conclusions can we draw from this literature? Perhaps the most consistent theme underlying much of this work is that it has been difficult to find support for either the weak or strong version of the pollution haven hypothesis. This in part reflects data problems, but also reflects the fact that pollution abatement costs are a relatively small fraction of overall costs in most industries. The evidence suggests that factors such as capital abundance, labor abundance, location, institutions, and agglomeration effects are more important than environmental policy in determining firm location choice and

> 8 They looked at 14 pollutants tracked by the World Bank's Industrial Pollution Projection system (Hettige et al., 1995).  These include several air pollutants (such as SO2 and particulates), water pollutants (BOD and suspended solids) and toxic releases.

14