rafmacalaba/datause-encoder-data huggingface dataset:
While not a channel that has been greatly explored in modern growth theory, it is plausible that growth is enhanced in countries with lower poverty, all else equal. Poverty reduction could serve to increase market size (e.g. greater disposable income), enhance labor productivity (e.g. health improvements), and enhance innovation through improved human capital (e.g. less poor populations might invest more in education; there may be less scope for innovation in an agrarian society, etc.). If such linkages are important, ensuring that all sections of the population are provided with infrastructure could indirectly boost growth by reducing poverty. It is notable that East Asia has been more successful in providing rural access to all-weather roads than other developing regions. Access to roads has been shown in numerous studies to have a significant effect on rural poverty (Jacoby, 2000; Gibson and Rozelle, 2003).

|**Table 3: Proportion of rural population living**|**within two kilometers of an all-weather road**|
|---|---|
|Sub-Saharan Africa|30|
|Middle East & North Africa|34|
|Latin America & Caribbean|38|
|South Asia|58|
|Europe & Central Asia|75|
|East Asia|94|
|Source: Roberts et al (2006).||

Theoretical speculation on the relationship between infrastructure and growth should be tested against empirical observations. Examining 80 econometric specifications from 30 studies using macro-level data, Straub (2007) reports a significant positive effect of infrastructure on output or growth in 56 percent of specifications, no significant effect in 38 percent, and a significant negative effect in 6 percent. Among the studies that do find positive effects there is wide variation in their estimated magnitude.

There are several possible reasons for the variation in empirical results. It seems quite likely that the effects of infrastructure investment do, indeed, vary from location to location, and across different stages of economic development. A further source of variation is the theoretical framework used. Straub (2007) observes that a positive effect of infrastructure on growth is more likely to be detected in studies based on a production function than studies using cross-country regressions. The empirical literature frequently fails to set out the theoretical issues that are being tested so that results may not be strictly comparable, a number of methodological problems are either not considered or cannot be addressed with macro6
valorem duty, which is relatively nondiscriminatory across trading partners. Instead, Turkey structures its applied safeguards as either _specific duties_ or _price undertakings_ (based on minimum price thresholds, above which no additional duties are imposed); these policies can have much more discriminatory effects across foreign sources.<sup>21</sup> One telling example began in 2006 when Turkey initiated a safeguard investigation on imports of almost $500 million in footwear. Figure 4 reveals that more than half of these imports derived from China, though other major foreign suppliers included the European Union (nearly $100 million), Vietnam ($42 million), and Indonesia ($20 million). Figure 4 and Figure 5 indicate that imports of footwear from both China and the EU had been increasing in the years leading up to the initiation of Turkey’s safeguard investigation. Finally, of the nearly $100 million in Turkey’s annual footwear imports deriving from the European Union, roughly 70 percent was from Italy, with much smaller shares of the Turkish import market arriving from Spain, Portugal and Romania (Figure 5).

Turkey applied a safeguard in the form of a $2 - $3 specific duty per pair of footwear, depending on the category of investigated product. However, the applied specific duty did not depend on the trading partner; i.e., Turkey also applied the duties to imports from customs union partner countries in the EU. Figure 6 provides additional information on Turkish import prices for footwear across different foreign sources. The unit value data on Turkish import prices revealed by Figure 6 suggests that the $2 to $3 specific duty would have had much less of an effect on imports of European-produced footwear than on imports from other foreign sources. The average imported price of footwear in 2006 was $41 per pair from EU countries, whereas it was $11 per pair from China, $18 per pair from Indonesia, and $21 per pair from Vietnam. Thus, to the extent that footwear imports from some EU members were higher

> 21 Turkey has recently applied safeguards as price undertakings on vacuums, motorcycles, electrical appliances, and matches; in these cases it has established price cutoffs (under which duties would be applied) that were well below the average price of imports from the EU of the goods under investigation.  Turkey has also recently applied safeguards as specific duties on steam irons, spectacle frames, and travel goods and handbags. Data on average Turkish import prices across foreign sources frequently suggest that significant imports from the EU in these particular products derived from countries such as Italy and France and may have been in higher-end varieties for which a safeguard applied as a specific duty would be expected to have less of an impact.

21
from different spending was collected from mid-2017 to mid-2018, so we have matched it to the 2018 fiscal data.

# Taxes

Tax revenues account for about 15 percent of GDP in 2018 (Table 1). The lines in bold type are included in this study. Indirect general taxes on goods and services are by far the largest component, with personal and corporate income taxes making up most of the rest. In this study we do not analyse corporate income tax, the incidence of which cannot usually be allocated out to households.<sup>3</sup> We also do not include taxes on the commercial sector. We similarly exclude indirect taxes on the commercial sector. As a result, we only capture just over half of total tax revenues.

Jordan’s GST standard rate is 16 percent, and there are reduced 4 percent and 0 percent rates, as well as items exempted from GST. Exempt items do not have GST charged, but there is an indirect ‘tax’ paid by consumers as producers cannot recover the GST paid on the inputs used to produce them, the cost of which is passed on to consumers. A Special Sales Tax (SST) applies to cigarettes and tobacco,<sup>4</sup> mobile phone subscriptions,<sup>5</sup> soft drinks,<sup>6</sup> and alcohol<sup>7</sup> based on the quantity purchased. We cannot distinguish between taxes charged to domestic and imported goods in household consumption and so apply the same rates to both.

PIT in 2018 was levied on gross income from all sources less exemptions and deductions.<sup>8</sup> The income tax rate is progressive on the income level: the first 12,000 Jordanian dinars (JOD) of an individual’s income is exempt; income between JOD 12,000 and JOD 24,000 is taxed at 7 percent; income between JOD 24,000 and 36,000 is taxed at 14 percent; anything above is taxed at 20 percent. There is a single deduction for dependents of an additional JOD 12,000. PIT is entirely borne by the worker.

**_Table 1. Jordan government revenues, 2018_**

|||**2018**<br>**Percent of total**||
|---|---|---|---|
||**JOD Million**|<br>**revenues**|**Percent of GDP**|
|_Total Domestic Revenues_|6,945|100|23|
|_Tax Revenues_|4,536|65|15|
|1 - Taxes on income and profits, of which:|965|14|3|
|**Individuals**|**53**|**1**|**0.2**|
|**Salaried Employees**|**150**|**2**|**0.5**|
|Income Tax from Companies & Projects|762|11|3|
|2 - Taxes on Financial Transactions (real estate’s tax)|93|1|0|

3 One exception where the household survey data allow this is Chile (see World Bank 2014).

4 The SST schedule for cigarettes is based on the number of cigarette packs purchased. Other types of tobacco products (cigar, aarghile, etc.) are subject to a tax per gram of tobacco. We assume that one cigar has approx. 2g, a pack of tombak is 40g and aarghileh 40g.

5 26 percent rate. 6 10 percent rate.

7 2.5 fils/lit for beer and 5.5 fils/lit for other types of alcohol. We assume one bottle of beer has 330 liters and one bottle of other alcoholic beverages, 700 liters.

8 The personal income tax law was revised in October 2018 to take force at the beginning of 2019. We will discuss these changes later.
To construct a water-resource indicator, we draw on two sources of information.

The first is an estimated geographic distribution of excess demand for water resources (surface and sub-surface) in Vörösmarty, et al. (2000). We use GIS to compute the total population residing in excess-demand areas identified by this research. The second information source is a database of deaths and injuries from floods maintained by the Centre for Research on the Epidemiology of Disasters (CRED, Université Catholique de Louvain). For each of the Bank's partner countries, we calculate the sum of deaths and injuries for all recorded floods since 1960. In constructing an indicator for flood damage, we weight deaths to injuries in the ratio 50:1. Using equal weights, we combine our indicators for demand pressure and floods into a composite indicator of water-related problems.<sup>4</sup> We derive our indicator for environmental policy and institutional problems from two sources. The first is the World Bank's Country Policy and Institutional Assessment (CPIA) database, which rates environmental policies and institutions on a numerical scale of 1 (the lowest) to 6. For this exercise, we reverse the scaling (1 becomes the highest) and normalize the ratings so that countries with the greatest problems score 100. To proxy the scale of the problems confronted by environmental institutions, we compute the mean value of our five thematic indicators (global emissions, pollution, natural resource degradation, biodiversity threats, water-related problems).<sup>5,6</sup> To assure equal weighting

> 4  Our index of demand pressure also provides a useful proxy for economic damage from drought conditions.   We are indebted to our colleagues in the Bank’s Middle East / North Africa region for this observation.

> 5  While the CPIA ratings provide useful information for comparing institutional needs, they are not sufficient for judging investment priorities because they do not account for differences in the scale of environmental problems faced by a country's institutions.  If Brazil and Bhutan receive the same CPIA rating, for example, ignoring their scale difference will lead to assignment of identical lending in the optimization model.

> 6  We recognize that an equal-weighted index is only one of numerous plausible indicators for general environmental problems.  In Appendix 2, we develop alternative indices and analyze their association with

6
which upon substitution of the 2010 market prices and parameters gives max _c_ 0 _s_<sup>'</sup> = $1,022/mt. Notice that a corresponding processing cost in Argentina, an important exporter of soybeans and soybean products to southern African countries, is estimated to be $355/mt.<sup>17</sup> If Zambia’s soybean oil processing facilities required the same crushing margins as in Argentina, the maximum price for soybeans that would preserve the current production/trade pattern in Zambia would be $460/mt.

In a similar manner, we can determine an approximation of the bounds for biodiesel production. We have shown that under the current biodiesel processing cost, biodiesel producers in Zambia are unlikely to produce if the price of the feedstock (soybean oil) is more than $1,180/mt. To begin production at the 2010 biodiesel and soybean oil prices, their processing cost would have to be no more than $0.12/liter, which is almost 80 percent less than the current level.

But biodiesel production does not automatically imply biodiesel consumption unless an appropriate policy is in place or if the biofuel is competitive vis-à-vis diesel (e.g., because of a high diesel price or a low fuel tax). Invoking equation (6), the maximum price that makes biodiesel competitive with diesel is $0.82/liter. Contrast this with the current biodiesel market price of $1.31/liter in Zambia.

# _Policy Simulations_

No binding biofuel policy is currently implemented in Zambia. However, in April 2011, the government issued a 5 percent blending target for biodiesel (B5) that is to be achieved by 2015. It is therefore of interest to analyze the potential market and welfare impacts of this policy as well as the impacts of a possible expansion of the mandatory biodiesel blending to 10 or 20 percent. The upper panel of Table 2 gives market effects for individual scenarios, whereas the bottom panel presents welfare changes associated with each scenario relative to the no policy (i.e., status quo) baseline. We assume that the government requires blending of biodiesel produced domestically; otherwise all biodiesel would be imported because no biodiesel production currently exists due to a high soybean oil price that does not allow biodiesel

> 17 This cost has been calculated as per equation (2), using the market prices and parameters pertaining to the Argentinean market in 2010: (0.19 x 936 + 0.81 x 336 – 382)/0.19.

12
markets through advised bans on share tenancy and limits on cash rental fees. From a theoretical point of view, the expected impact would be ambiguous. On the one hand, there is a negative direct effect as prohibition of tenant eviction precludes the landlord from using the threat of eviction as a device to elicit higher effort by the tenant and would therefore be expected to reduce productivity. On the other hand, the reallocation of bargaining power in favor of the tenant would increase incentives to supply effort and thus productivity. While one would expect the adverse incentive effect to dominate at low wealth levels, the positive effect would be dominant for farmers with intermediate wealth(Banerjeeand Ghatak, 1997).

Empirically, district level data from West Bengal suggest that effective implementation of tenancy registration which protected tenants from being evicted and fixed an upper ceiling for rent yielded significant productivity gains of about 40% - larger than the static loss estimated by Shaban (Banerjee and Ghatak, 1997). While this suggests that tenancy reforms can be effective, one should not forget that the study area is thie only state in India where regulation of tenancy was actually implemented, that costs of implementation need to be considered in making an assessment of the economic benefits from such a measure, and that tenancy reform may not have been the only alternative available.

Regulatory interventions such as tenancy regulation lead to reduced investment incentives on the part of the landlord, while tenants may not perceive sufficient security to invest at what would be a socially optimal level. The trade-off between the positive effect of greater security to tenants and the investment incentives of owners is not easily balanced. Therefore, scarce financial and administrative resources might be better spent in efforts to foster general pro-poor development (e.g. education, infrastructure, credit and insurance, markets, and off-farm employment opportunities) that improve the bargaining position of would-be tenants, and that facilitate more fixed rent contracts, than in trying to enforce tenancy regulations. The difficulty of striking such a balance is illustrated by the fact that, in areas where tenancy was prohibited, wage labor (which is less conducive to productivity than tenancy or owneroperated farming due to lower effort by workers) is common, leading to inefficient factor substitution away from labor (Otsuka et al. 1993).

# 4.3 **REDISTRIBUTIVE LAND REFORM**

Our earlier discussion pointed out that unmitigated operation of land markets alone would not necessarily produce an optimal land allocation. In the land sales market, credit constraints would restrict the ability of the poor to acquire land (or any other indivisible asset), a phenomenon that has, in a more general context, been shown to be associated with intergenerational persistence of poverty (Banerjee and 31
O G) O **C** z **0** r m **0** 0 I > a RX & a **0.** o R~~~~~~~~~~~ U-

|**Table B9. Informal Perceptions of**<br>EmploymentStatus<br>from Informal Sector Surveys conducted by the author|<25 hours per<br>week<br>Taxicabs|245 hours<br>per week<br>Taxicabs|Entire<br>Sample<br>Taxicabs|Entire<br>Sample<br>Kiosks|Entire<br>Sample<br>S<br>S<br>Markets|<br>Entire<br> <br>Sample<br>treet Services &<br>taeets Sendics &<br> <br>Vendors|
|---|---|---|---|---|---|---|
|Number of Observations (actual number may vary depending on the|99|101|308|245|137|<br>80|
|<br>question)|||||||
|Response to duureg census"Are you employed?"|||||||
|Yes|69.1|36.6|46.7|25.5|11.7|<br>25.0|
|Among those not employed, the reason provided to the duureg|||||||
|1-illness, looking after someone|3.3|6.5|8.1|14.6|10.7|<br>18.3|
|2-seasonal work|10.0|3.2|5.6|3.9|2.5|0.0|
|3-not finding professional work|26.7|30.7|27.5|16.3|23.1|<br>21.7|
|4-fired, organization doesn't work|30.0|21.0|23.1|15.7|17.4|<br>23.3|
|5-other ("no reason")|16.7|25.8|22.5|30.9|32.2|<br>20.0|
|6-other (listed reason)|0.0|0.0|0.6|0.0|0.0|0.0|
|7-pensioner orstudent or disabled|13.3|12.9|12.5|18.5|14.1|<br>16.7|
|Among those not employed, the percentage actively looking for job.|||||||
|Yes|33.3|33.9|32.9|15.5|46.2|<br>45.0|
|Registration at the employment regulation office.|||||||
|Current|29.6|15.5|15.7|11.6|17.4|<br>3.3|
|Previous, not current|11.1|22.4|15.7|16.1|9.6|20.0|
|Never|59.3|62.1|68.6|72.3<br>-|73.0<br>.|<br>76.7|

a'

**1%.**
sourcing provision is present in 58 percent of the sample. Because of the strong overlapping between preferential treatment and domestic sourcing (81 of the 83 countries that have domestic sourcing provision also have preferential treatment provisions in their procurement law), we use a composite indicator that equals one if the country is protectionist in all the three areas (discrimination, preferential treatment and domestic sourcing).

Figures 1 and 2 display the relationship between the protectionist indicators derived from the coding of procurement law and relevant economic and institutional characteristics. The national legal provisions might reflect the commitments that governments have taken in international agreements concerning their procurement markets. This is supported by our data. Countries that are members of the WTO GPA, a plurilateral agreement promoting openness in government procurement, have a significantly lower level of protectionism. A portion of the difference between WTO GPA signatories and non-signatories can be attributed to EU member countries, as these represent 65 percent of WTO GPA members. As depicted in Figure 1, the average value of the protectionist index is indeed lower for EU countries. We also find that middle and low income countries have legal systems that are more protectionist than those of high income countries in our sample (as classified by the World Bank).

In Figure 2, we explore the relationship between the protectionist indicators and institutional characteristics, as measured by the World Governance Indicators (WGI) database. We calculate the average percentile rank across the six governance indicators (voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption) for each country, using available data for each year. We then take the average across years for each country. Figure 2 shows a negative correlation between this overall measure of quality of institutions and protectionism in government procurement. Countries where procurement laws lack an equal treatment provision, provide for preferential treatment or impose domestic sourcing have worse institutions on average, with the difference being particularly large when considering domestic sourcing. Given the strong correlation between the different WGI indicators, we will use the average measure from Figure 2 in our empirical analysis. Overall, since the legal, economic and institutional characteristics considered in Figures 1 and 2 might well correlate with imports as well, we will control for their influence in our empirical analysis.

7
other hand, non-poor people are known to consume more nutritious food than poor people. Indeed there is evidence that nutritional deficiencies increase the susceptibility to arsenic health effects. Using data from West Bengal, Mitra et al. (2004) investigate whether dietary micro- and macronutrient intake alters the risk of arsenic-induced skin lesions, including alterations in skin pigmentation and keratoses. The authors conclude that low intake of calcium, animal protein, folate, and fiber may increase susceptibility to arsenic-caused skin lesions although the magnitude of increased risks related to these dietary deficiencies is small.

The findings discussed above have obvious implications for children’s cognitive development. There are at least four reasons why educational development of children is likely to be hampered owing to exposure to arsenicosis. First, children who have continuously drank from Arsenic contaminated tube-wells are likely to have poorer health status and under-perform in schools compared to the peers who have grown up in arsenic unaffected households. Second, arsenicosis at home may cause adverse income shocks. Labor productivity of wage-earning adult members is likely to be reduced owing to declining health conditions. Given binding credit constrains in rural areas, such income shocks would have adverse effect on school participation and attainment.

Third, there is an emerging body of medical evidence documenting a direct impact of arsenic exposure on the intellectual development of children. A study in Mexico by Calderon et al. (2001) found that chronic malnutrition combined with exposure to arsenic influences verbal ability and long term memory. Arsenic concentration in urine was inversely correlated with verbal IQ, concepts factor (language), and knowledge factor (verbal comprehension and long-term memory). The negative effect of arsenicosis in verbal IQ scores remained even after accounting for nutritional status and other confounders. More recent research on arsenicosis and cognition also corroborates these findings. For example, Wasserman et al. (2004) concluded that exposure to arsenic in drinking water in Bangladesh was associated with reduced intellectual function in children<sup>3</sup> . Exposure was measured in terms of both well-water and urinary arsenic. Exposure to arsenic from drinking water was associated with

> 3 Test instrument on intellectual function was drawn from the Wechsler Intelligence Scale for Children, version III.

6