rafmacalaba/datause-encoder-data huggingface dataset:
**Table .42.4**

**India: Tariff Structure, 1990-1996**

||**1990/91**|**1992/93**|**1993/94**|**1994/95**|**1995/96**|
|---|---|---|---|---|---|
|Mean and Standard Diviations||||||
|Whole economy|128|94|71|55|42|
||(41)|(34)|(30)|(25)|(21)|
|Agricultural Products|106|59|39|31|26|
|Mining|||71|48|37|
|Consumer goods|142|92|76|59|43|
|Intermediates|133|104|77|59|45|
|Capital goods|109|86|58|42|35|
|Imported weighted average||||||
|Whole Economy|87|64|47|33|27|
|Agricultural Products|70|30|25|17|15|
|Mining|..|..|33|31|30|
|Consumer goods|164|144|33|48|39|
|Intermediates|117|55|40|31|24|
|Capital goods|97|76|50|38|30|

Notes: Standard Diviations are in parentheses. In 1990/91 and 1992/93, mining is included in intermediates.

Source: Ministry of Finance, Government of India and World Bank estimates. Also in Ahluwalia 1996.

# �hyestment Reforms

Discouraged by a tight regulatory regime as well as the highly distorted economy, capital flows to India have historically been low. Direct investment was limited, averaging around $200 million a year over 1985-90. A key component of the economic reform program launched in July 1991 was the adoption of a much more open approach to foreign investment. At the outset, approval for direct investment participation up to _51%_ in priority areas was made automatic, while the criteria for approval were liberalized more generally. In February 1992, it was announced that Indian firms in good standing would be allowed to raise funds through equity and convertible bond issues in euromarkets. In September 1992, registered Foreign Institutional Investors (FIT's) were allowed to purchase both equity and debt securities directly on local markets. To encourage these flows further, in March 1993 budget the tax on interest and dividend income on FIT holdings was set at 20 percent while capital gains tax was set at 30 percent on investment held for less than one year and 10 percent thereafter. The response to these liberalization measures was strong: total FDI and portfolio investment rose to $5.1 billion in 1994/1995, from $585 million in 1992/93 and $148 million in 1991/92. (Charles Collyns, 1995)

# �)j�ustrial Sector

Measures to deregulate the industrial sectors included removing investment licensing requirements in most industrial sectors, with the exception of only a few areas such as petroleum, coal, and agroprocessing. Anti-trust legislation was amended to eliminate the restraints to large _firms'_ expansion, diversification, merger and acquisition. Many price controls _(for_ example, on steel, aluminum, and cement) were eliminated.

These reforms have produced positive results for the Indian private sector. Investment picked up

**53**
ECCAS’S INFRASTRUCTURE: A REGIONAL PERSPECTIVE

**Figure 1.1b. Infrastructure’s potential future contribution to economic growth (% GDP per year)**

<!-- Start of picture text --> 6<br>5<br>4<br>3<br>2<br>1<br>0<br>North West East Southern Central Africa<br>Africa Africa Africa Africa Africa<br>Telecom Power Roads<br>Source: Calderón 2009.<br>Note: GDP = gross domestic product.<br>per capita<br>Potential impact of better infrastructure on growth<br><!-- End of picture text -->

# Why regional integration matters

With its large number of isolated economies, including island states, ECCAS’s economic geography is particularly challenging. Of the member countries, two are landlocked and rely on regional corridors, seven have populations below 10 million people, and eight have economies smaller than $10 billion per year (figure 1.2a). Central Africa’s economic geography stands out from the other regions for the considerable distances that exist between areas of economic agglomeration and vast environmentally sensitive areas. Inland waterways feature prominently in this region as an alternate cost-effective, but typically underutilized, mode of transport.

Levels of economic activity are very low throughout ECCAS, and exceed $5 million per 100 square kilometers only around Kinshasa-Brazzaville. A small area around Bujumbura in Burundi also records dense economic activity. There are patches of moderate economic activity around the capital cities of the regional economic community member states, but these taper off inland (figure 1.2b).

Regional integration is the only likely way to overcome these handicaps and to allow ECCAS member states to participate in the global economy. Sharing infrastructure addresses problems of small scale and adverse location. Joint provision increases the scale of infrastructure construction, operation, and maintenance. Economies of scale are particularly important in the power and ICT sectors. Big hydropower projects that would not be economically viable for a single country make sense when neighbors share their benefits. Connecting countries via undersea cable or satellite communications requires large up-front investments that require a regional approach. Integrating physical infrastructure is both a precursor to and enabler for deeper economic integration, thereby allowing countries to gain scale economies and harness regional public goods.

3
Figure 3.18 Household expenditure on tutoring of Grade 9 students (marginal change in probability) <!-- Start of picture text --> Child's school performance top<br>Child's school performance upper middle<br>Child's school performance middle<br>Child's school performance lower middle<br>Family economic condition-well off<br>Family economic condition-middle<br>Parent has post-secondary education<br>Parent has upper sec or equivalent education<br>Child attending school in rural area<br>Child attending school in city area<br>-1000 -500 0 500 1000 1500 2000<br>CNY per term<br><!-- End of picture text --> _Source_ : Authors’ calculation based on the CEPS.

Exam-driven systems can inhibit intrinsic motivation and stifle creativity. Such abilities are often gained beyond traditional classrooms and through extracurricular activities. Preparing for the highstake test at Grade 9—sorting students into secondary school tracks—basically has become the dominant and often the sole activity toward the last year of junior secondary school, during one of the most important formative periods of their lives. The CEPS data show the time allocation of Grade 9 students. Students in urban areas tend to have the highest pressure—on average they sleep a little over seven hours—with more than three hours of homework per day. More than half of them study during school vacation. While over half of the total students reported participation in extracurricular activities, the extracurricular activities in the survey also include further studies of selected subjects. Excluding these advanced studies, only 18 percent of the surveyed Grade 9 students spend any time on any extracurricular activities.

Table 3.2 Grade 9 student activities by school location

|**School location**|**Hour/d**<br>**ay**<br>**sleep**|**hour/d**<br>**ay**<br>**home**<br>**work**|**%**<br>**students**<br>**with**<br>**hobbies**|**Study**<br>**during**<br>**school**<br>**vacation**<br>**(%)**|**Never been**<br>**to museum,**<br>**zoo, science**<br>**exhibition**<br>**(past year)**<br>**(%)**|**Never been**<br>**to movies,**<br>**performance,**<br>**sport games**<br>**(%)**|<br>**No**<br>**extracur**<br>**ricular**<br>**activities**<br>**(%)**|
|---|---|---|---|---|---|---|---|
|**City center**|7.19|3.10|14.5|51.0|33.64|20.72|35|
|**City outskirt**|7.51|2.90|15.5|27.0|51.95|38.69|66|
|**City/rural**<br>**bordering**|7.62|2.64|14.8|34.6|39.85|33.82|58|
|**Town outside city**|7.93|2.74|15.8|20.6|62.81|53.60|72|
|**Rural**|7.96|2.87|17.0|23.2|58.57|55.60|75|
|Total|**7.57**|**2.91**|**15.4**|**35.1**|**46.88**|**37.28**|**56**|

_Source_ : Authors’ calculation based on the CEPS.

Further looking into the key factors associated with student time allocation, we find that less sleeping time has a positive correlation with student academic performance—not only with student 41
15

# Protection in MENA

The last point brings to the fore the issue of the repression of agriculture in MENA by inappropriate economywide policies. Despite the importance of agriculture and, more generally, the rural economy in the region, protection from imports of manufactures and other products remains high in many countries **in** the Middle East and North Africa, contributing significantly to overvaluation of the real exchange rate (the relative price of nontraded goods to traded goods), and thereby to repression of domestic relative prices in subsectors of agriculture in MENA that are internationally competitive.

Table 6 indicates the magnitude of protection during the last decade in the MENA countries for which data on import tariffs and nontariff barriers (NTBs) are available.'<sup>9</sup> The data on tariffs reveal the combined magnitude of ad valorem customs duties and other fiscal charges on imports (so-called para-tariffs). The NTB data, on the other hand, indicate the percentage of national tariff schedule lines in each product category affected by quantitative restrictions and other nontariff barriers, as compiled by the U.N. Conference on Trade and Development (UNCTAD) for its inventory of trade control measures in industrial and developing countries (UNCTAD 1994).

The most open countries in MENA are the high-income Persian Gulf countries (Kuwait and Saudia Arabia), with average tariff rates not exceeding about 10 percent and average NTB rates not exceeding about 5 percent. Most other countries in the region are inward-looking, with average tariff rates widely exceeding 20 percent and average NTB rates widely exceeding 30 percent. This is true of low-income countries such as Egypt and Sudan, but also middle-income countries such as Algeria, Iran, and Turkey. The high nontariff barriers are particularly costly in economic terms

> '9 The discussion here focuses on protection in output markets for agricultural and other products. Although protection for production inputs is also important, estimates of effective rates of protection are beyond the scope of the present analysis. Notably however, computed effective rates of protection are often highly correlated with nominal rates of protection.
# 1. INXTR'RODUCIION

"While an agricultural-led growth<sup>strategy entails substantial risks, its success</sup> greatly reduces the most onerous risk<sup>humans face-the risk of dropping below the</sup> poverty line" John Mellor (1990).

Over the past few years, the case<sup>for agriculture as the engine of growth for the poor</sup> countries of the developing World,<sup>especially in Sub-Saharan Africa, has gained considerable</sup> support as lessons and evidence gained<sup>from past experiences and analytical and methodological</sup> advances started to influence our understanding<sup>of the process.' Citing past and recent evidence</sup> obtained from large sets of data from several<sup>developing countries, many authors (eg. T. Schultz,</sup> Kuznets, Mellor, Lal, and Johnston) have<sup>vigorously and persuasively argued for this particular</sup> strategy of economic development. This<sup>position is su.cinctly represented by the following three</sup> arguments advanced by Mellor (1990).<sup>First, because of its large initial size and the powerful</sup> stimulus it provides to the growth of<sup>other sectors, accelerated agricultural growth hastens decline</sup> in the relative size of agriculture by fostering<sup>more rapid growth in the nonagricultural sector.</sup> Second, concentration of public investment<sup>in agriculture tends to accelerate diversification within</sup> agriculture and in the rest of the economy.<sup>Third, agricultural growth by raising rural incomes</sup> and providing the oipportunity to earn<sup>higher incomes, makes the farming of high-risk,low-income,</sup> and possibly enviroi ,ntally unsustainable<sup>land unnecessary and undesirable.</sup> Taking the above argument as a maintained<sup>position, this paper will attempt to address</sup> two inter-related issues critical to th.; role<sup>of agriculture in the context of economic development</sup> 'Narain (1965), Krishna (1963), Behrman<sup>(1968), Schultz (1978), among others, provide some</sup> of the early evidence on the price responsiveness<sup>of the third world farmers. A more recent</sup> evidence on this as well as on the effects<sup>of agricultural technology on productivity and rural</sup> income is provided in Eicher and Staatz<sup>(1986) for example, in the context of the broader debate</sup> regarding the role of agriculture in economic<sup>development.</sup>
||3|Moderate|Complicated<br>licensing<br>procedure;<br>regulations<br>impose<br>substantial burden on business; existing regulations may be<br>applied haphazardly and in some instances are not even<br>published by the government; corruption may be present<br>and poses minor burden on businesses||http://www.heritage.org/research/features/index/index.html|
|---|---|---|---|---|---|
||4|High|Government-set production quotas and some state<br>planning; major barriers to opening a business; complicated<br>licensing process; very high fees; bribes sometimes<br>necessary; corruption present and burdensome; regulations<br>impose a great burden on business|||
||5|Very high|Government impedes the creation of new businesses;<br>corruption rampant; regulations applied randomly|||
|**TRADE**||||||
|**Variable name in**<br>**corresponding**<br>**database**||**Scale**|**Description**|**Years**|**Source**|
|**(name in our**<br>**database)**||||||
|Trade<br>(ief_trade)|1|Very low|Weighted average tariff rate less than or equal to 4 percent.|1995-<br>2003<br>(annual)|**The Index of Economic Freedom, Heritage Foundation**|
||2|Low|Weighted average tariff rate greater than 4 percent but less<br>than or equal to 9 percent||Based on: The Economist Intelligence Unit, Country<br>Report and Country Commerce, 2002; International<br>Monetary Fund, Government Finance Statistics Yearbook<br>|
||3|Moderate|Weighted average tariff rate greater than 9 percent but less<br>than or equal to 14 percent||and International Financial Statistics on CD–ROM, 2002;<br>Office of the U.S. Trade Representative, 2002 National<br>Trade Estimate Report on Foreign Trade Barriers; U.S.<br>Department of State, Country Commercial Guide 3 and|
||4|High|Weighted average tariff rate greater than 14 percent but<br>less than or equal to 19 percent||Country Reports on Economic Policy and Trade Practices<br>for 2001 and 2002; World Bank, World Development<br>Indicators 2002; World Trade Organization, Trade Policy<br>|
||||||Reviews, 1995 to June 2001; and official government|
||5|Very high|Weighted average tariff rate greater than 19 percent.||publications of each country. For all the European Union<br>countries, the authors have based the score on data<br>reported by the World Bank.|
|i Hidden import|0 to 10|<br>(0= heavy|No barriers other than published tariffs and quotas.|1995,|**Economic Freedom of the World, The Fraser Institute**|
|barriers||regulation)||2000, and||
|(efw_bi)||||2001|From Section:|
|ii Costs of importing|||The combined effect of import tariffs, license fees, bank||4 Freedom to Exchange with Foreigners|
|<br>(efw_bii)|||<br>fees, and the time required for administrative red-tape||<br>B. Regulatory Trade Barriers|

38
When Distance Drives Destination, Towns Can Stimulate Development<sup>*</sup> Joachim De Weerdt<sup></sup> Luc Christiaensen<sup></sup> Ravi Kanbur<sup>§</sup>

**JEL Codes:** J61, O15, O55.

**Key Words:** Africa, internal migration, urbanization, secondary towns.

> * We thank Kalle Hirvonen for useful comments and Economic Development Initiatives (EDI), the Tanzanian National Bureau of Statistics (NBS) and the Organisation for Economic Co-operation and Development (OECD) for making the underlying data publically available. We acknowledge funding from Excellence of Science (EOS) Research Project 30784531 at the Research Foundation – Flanders (FWO).

>  IOB, University of Antwerp & LICOS, KU Leuven. E-mail joachim.deweerdt@uantwerp.be

>  The World Bank. E-mail lchristiaensen@worldbank.org

> § Cornell University. Email sk145@cornell.edu
|eriod)<br>(8)<br>Judge<br>more strict<br>(share)<br>0.051***<br>(0.012)<br>-0.001***<br>(0.000)<br>0.004***<br>(0.001)<br>0.027<br>Yes<br>Yes<br>No<br>0.122<br>0.151<br>0.058<br>3883<br>ble A-1. 5297<br>only for cases|
|---|
|justment p<br>(7)<br>Pre-trial<br>likelihood<br>of being<br>heard<br>0.034*<br>(0.019)<br>-0.001**<br>(0.000)<br>0.002<br>(0.001)<br>0.364<br>Yes<br>Yes<br>No<br>0.852<br>0.152<br>0.173<br>3879<br>ols 2-4, Ta<br>g), col 8 (|
|ncluding ad<br>(6)<br>Number of<br>pretrial<br>hearings<br>-1.480***<br>(0.404)<br>-0.059***<br>(0.013)<br>0.085***<br>(0.026)<br>0.043<br>Yes<br>Yes<br>No<br>8.059<br>6.415<br>0.137<br>5297<br>ee notes for c<br>an one hearin|
|al stage (i<br>(5)<br>Fast-<br>tracked<br>0.030<br>(0.029)<br>0.004***<br>(0.001)<br>-0.002<br>(0.002)<br>0.469<br>Yes<br>Yes<br>No<br>0.148<br>0.355<br>0.068<br>5297<br>eedings. S<br>ve more th|
|e on pre-tri<br>(4)<br>Desk<br>rejection<br>0.167***<br>(0.019)<br>-0.000<br>(0.000)<br>-0.005***<br>(0.001)<br>0.003<br>Yes<br>Yes<br>No<br>0.000<br>0.019<br>0.077<br>5297<br>re-trial proc<br>ases that ha|
|of the decre<br>(3)<br>Likelihood<br>of pre-trial<br>completion<br>in 4<br>months<br>0.165***<br>(0.035)<br>0.002**<br>(0.001)<br>-0.009***<br>(0.002)<br>0.040<br>Yes<br>Yes<br>No<br>0.501<br>0.500<br>0.127<br>5297<br> reform on p<br> 7 (only for c|
|1: Impact <br>(2)<br>Hazard<br>ratio -<br>fnishing<br>pre-trial<br>1.203**<br>(0.091)<br>1.007***<br>(0.002)<br>0.985***<br>(0.005)<br>Yes<br>Yes<br>No<br>5297<br>pacts of the<br>soring), col|
|Table A<br>(1)<br>Duration<br>of pre-trial<br>hearings<br>(in days)<br>Entered after decree -33.561***<br>application (_β_)<br>(10.454)<br>Trend<br>-1.404***<br>(0.326)<br>Interaction<br>0.698<br>(0.668)<br>P-value 6pWCBoot<br>0.101<br>Chamber FEs<br>Yes<br>Calendar month FEs<br>Yes<br>Without adj. period<br>No<br>Pre-mean<br>152.462<br>Pre-sd<br>144.237<br>R-Squared<br>0.192<br>Observations<br>5064<br>Notes<br>: Estimates of case-level im<br>observations, except for col 1 (cen<br>that have any adjournments).|

55
WPS3784

# **Trade Costs, Export Development and Poverty in Rwanda**

Ndiame Diop<sup>a</sup> , Paul Brenton<sup>a</sup> and Yakup Asarkaya<sup>b*</sup>

## **Abstract**

For Rwanda, one of the poorest countries in the world, trade offers the most effective route for substantial poverty reduction. However, the poor in Rwanda, most of whom are subsistence farmers in rural areas, are currently disconnected from markets and commercial activities by extremely high transport costs and by severe constraints on their ability to shift out of subsistence farming. The constraints include lack of access to credit and lack of access to information on the skills and techniques required to produce commercial crops. The paper is based on information from the household survey and a recent diagnostic study of constraints to trade in Rwanda. It provides a number of indicative simulations that show the potential for substantial reductions in poverty from initiatives that reduce trade costs, enhance the quality of exportable goods and facilitate movement out of subsistence into commercial activities.

### World Bank Policy Research Working Paper 3784, December 2005

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> *<sup>a</sup> Trade Department, World Bank.<sup>b</sup> University of Virginia. We would like to thank Ataman Aksoy, John Baffes, Kene Ezemenari and Waly Wane for helpful comments and Yakup Asarkaya for research assistance.

1
above, neither the price of coca base nor coca base production has shown any increasing tendency between 2000 and 2005 (see Figure 5). According to UNODC (2005) the price of coca base increased between 2001 and 2003. However, this is true only in nominal terms. The price of coca base has been stable (when seen in dollar terms) or decreasing (in real pesos) ever since the beginning of the implementation of Plan Colombia in 2001, precisely the moment when coca cultivation started to decrease rapidly. According to some sources, this apparent puzzle – of lower cultivation of coca and lower prices of coca base – can be partially explained by the offsetting effects of larger imports of coca paste from Peru and the large increases in productivity per hectare in the production of coca base.<sup>16</sup> The next section will elaborate on this and on a “twin puzzle”, namely the stability of prices of cocaine in the US market despite the large decrease in aggregate coca cultivation between 2000 and 2003 in the three producer countries and a relatively stable aggregate demand for cocaine in the consumer countries.

# iii. Potential Cocaine Production

Using yields per hectare as well as technical coefficients for each of the main links in the cocaine production chain, UNODC produces an estimate of potential manufacture of cocaine for each one of the three producer countries in the Andean region. Until 2004 UNODC’s estimates relied on information of technical coefficients from other sources, the main one being _Operation Breakthrough,_ a DEA project designed to estimate the amount of cocaine produced in the Andean region by examining the

> 16 Despite the successful closure of the air bridge between Peru and Colombia, the organizations involved in coca cultivation and cocaine production figured out other ways (perhaps less efficient but still profitable, such as transportation by river, or using mules to travel jungle paths) to move coca paste from Peru to Colombia (see Kawell, 2001).

12
12 vocational school leavers. Table 6 presents the results of the estimations. Column I shows a simple Mlncerian model. Column 2 shows the full model with the strict match between field of study and work, while column 3 shows the same model, with the wider match dummy variable.

Table 6 Earningc Functions. Brazilian Full Time Males Private Sector Workers (dependent variable Lin monthly eamings)

|Independent<br>variables|Simple<br>coeff.<br>(1)|Model<br>t<br>|Match<br>coeff.<br>(2)|1 Mode<br>t<br>|l Match<br>coeff.<br>(3)|2 Model<br>t|
|---|---|---|---|---|---|---|
|Intercept|6.694*|73.64|<br>6.606*|68.97|6.603*|69.12|
|EXPER|0.104*|24.43|<br>0.098*|23.35|0.098*|23.40|
|EXPERSQ|-0.001*|16.30|-0.001*|15.81|.0.001*|15.90|
|SPLYRSC2|0.190*|21.12|<br>0.172*|19.52|0.172*|19.60|
|SPLYRSC3|0.214*|21.70|<br>0.183*|17.70|0.175*|16.88|
|SPLYRSC4|0.179*|21.49|<br>0.161*|19.28|0.155*|18.35|
|SPLYRSC5|0.175*|17.90|<br>0.159*|16.44|0.155*|15.94|
|MATCHI|||0.166*|<br>2.20|||
|MATCH2|||||0.284*|<br>4.34|
|SERVICE|||-0.290*|7.93|-0.283*|<br>7.74|
|FARMW|||-0.279*|3.91|-0.276*|<br>3.16|
|SALES|||0.008|0.22|0.002|0.06|
|CLERICAL|||-0.082|2.78|-0.068*|<br>2.29|
|NONDEF|||-0.032|0.57|-0.024|0.42|
|REGiN|||-0.107|0.73|-0.112|0.76|
|REG2N|||-0.238*|6.78|40.238*|6.79|
|REG4N|||-0.118*|3.73|-0.119*|<br>3.75|
|REGSN|||-0.143*|2.63|.0.150*|2.77|
|SOCSEC|||0.426*|9.09|0.422*|9.03|
|MIGRANT|||0.100*|4.20|0.100*|4.21|
|R<sup>2</sup>|0.391||0.443||0.445||
|Number obs.|2,742||2,742||2,742||

* Significant at the .001 level or better.

The results presented in Column 1 are closely in line with those from other countries and prior research in Brazil. Psacharopoulos (1986) estimates a return to schooling in Brazil of 19.2 percent in 1970. Dabos and Psacharopoulos (1987) estimate a 16.4 percent return to general secondary schooling and a 19.8 percent return to vocational secondary schooling, for the overall male Brazilian labor force In 1980. Note that the latter report does not indicate whether these retums are statistically different.