rafmacalaba/datause-encoder-data huggingface dataset:
effect is due to the increased (due to higher indirect tax rate) prices of consumption goods which induce consumers to work slightly more. To maintain an unchanged government budget balance, the sales tax rate has to rise by 13 percent—not a very large change in absolute terms since initial sales taxes for most products are quite low. For example, the sales tax rate on food products increases from 1.3 percent to 1.5 percent. Since public saving remains unchanged and household saving rises due to higher labor income, investment also increases, which creates additional demand for goods.

# **4.4 Sensitivity analysis: what if remittances are received by specific households and the labor markets are less flexible?**

Two basic assumptions are implicit in the analysis up to this point and deserve some further scrutiny. The first is the adoption of a single representative ‘average’ household and the second is that labor is fully mobile across sectors.

Assuming a single representative household has two important drawbacks: a) the same household decides how much skilled _and_ unskilled labor to offer in the market, and b) remittances are distributed evenly across different households. In other words, adopting a single representative household implies that there are no biases in the distribution of remittances among recipient households, and that, contrary to the empirical evidence for Jamaica, remittances are not likely to be a more important source of income for poorer households who are also more likely to be endowed with unskilled labor when compared to richer households.

In order to better understand the distribution of remittance income across different groups of households, we have conducted some preliminary analysis using the combined data from the 2002 Labor Force Survey and the 2002 Survey of Living Conditions. The first observation is that remittance income is much more likely to be received by rural than urban households: 25 percent of rural households report remittance income compared to only 14 percent of their urban counterparts.<sup>23</sup> Households where the head is unemployed are 10 percent more likely to report remittance income, and households where the head is outside the labor force are 20 percent more likely to report remittance income (see Table 7). In both agriculture and services, one-fifth of households report remittance income, while for households where the head is employed in manufacturing that share is 16 percent.

Households with a more educated head are much less likely to receive remittances than households where the head has completed less than secondary school: 20 percent of households

> 23We define urban areas as the following three parishes: Kingston, St. Andrew, and St. Catherine. The other 11 parishes are defined as rural. Under this definition, urban areas are home to 32 percent of all households in the survey.

19
- The levels of government domestic and foreign borrowing that are imposed permit the government to reduce its total debt in 2022 by 10 percentage points of GDP compared to 2012.

- Private savings increase sufficiently to ensure enough financing to gradually raise domestically financed private investment from 9.4 percent of GDP in 2012 to 11.9 percent in 2022.

- Domestic tax revenues (direct and indirect) increase gradually and modestly, by 0.4 percent of GDP.

- The government is assumed to use increased fiscal space to expand spending on infrastructure while keeping spending in other areas constant in real terms.

Figure 4.5. Base: Investment and savings data (% of GDP) <!-- Start of picture text --> 20<br>18 total investment &<br>16 savings<br>14<br>private investment<br>12<br>10<br>8 government<br>investment<br>6<br>4 private savings<br>2<br>0 government savings<br>-2<br>-4<br>foreign savings<br>-6<br>Figure 4.6. Base: Growth decomposition<br>8<br>7<br>6<br>5<br>GDP at factor cost<br>4<br>Factor employment<br>3<br>TFP<br>2<br>1<br>0<br>% of GDP<br>% growth<br><!-- End of picture text --> Figures 4.7-4.8 show the evolution of savings, investment, GDP, TFP, and factor accumulation for _hi-grw_ . Total investment and savings gradually increase from 14 to 18 percent of GDP, with private investment accounting for around 70 percent of total investment. On the financing side, the major change is a strong increase in government savings, from -3 to around 1 percent of 33
Cyber Resilience of Autonomous Mobility Systems: Cyber Attacks and Resilience-Enhancing Strategies Bo Zou<sup>(1)</sup> , Pooria Choobchian<sup>(1)</sup> , Julie Rozenberg<sup>(2)</sup> (1) University of Illinois at Chicago, (2)World Bank

**JEL** : R42 R48

**Keywords** : autonomous mobility systems; cyber resilience; cyber attacks; vehicle- and system-level strategies
# **Informal – formal “bridge”**

To investigate the possible “bridge” (i.e., regular similarities that could be found in the survey data) between the informal and formal companies we undertook an analysis focusing on two specific samples in both surveys. These samples represent those formal businesses who reported they had been operating for a while before formalizing, and those informal businesses who reported likelihood for formalization within the next two years. A note should be made that the two surveys used different methodologies<sup>6</sup> , and that sometimes makes the comparison rather difficult.

The analysis that follows will try to investigate what kinds of businesses tend to be more frequently part of this “bridge” between formal and informal.

# **Sector**

Due to different methodologies and different structures of the formal and informal economies, the sector structure of two samples (formal and informal businesses) is not comparable without some regrouping of categories. In order to compare these samples three broad sectors were newly established:

- Agriculture, forestry, fishing, mining, construction and manufacturing

- Trade

- Other Services

# **Figure 7: Operating before registering (for formal businesses) and likelihood of registering (for informal businesses)**

<!-- Start of picture text --> 88<br>89<br>87<br>86<br>12<br>11<br>13<br>14<br>66<br>62<br>66<br>78<br>34<br>38<br>34<br>22 Percentage of businesses<br><!-- End of picture text -->

> 6 Formal survey was done using telephone interviewing as a data collection method while informal survey was done “face – to – face”. The formal survey was based on a

> representative sample  of SMMEs registered with SARS while the informal survey used area based sampling.

7
market access interests jointly; or 3) their governments have undertaken efforts to provide foreign market access monitoring on their behalf.<sup>8</sup> Because these three options for monitoring are less likely outside industrialised countries, insufficient private sector resources are dedicated to monitoring the foreign market access interests of exporters in developing countries.

Given this theory and evidence, Bown (2009a, chapter 8) takes the approach of proposing a new independent and multilateral monitoring body called the Institute for Assessing WTO Commitments (IAWC).<sup>9</sup> While the proposed IAWC would rely on the rules and procedures of the WTO system for providing its assessments, it would be established, funded and governed separately and independently from the WTO Secretariat.<sup>10</sup> The primary purpose of the IAWC would be to address the problem that we 8 See Bown (2009a, chapter 5) for a more complete discussion and examples of 1) and 2). Examples of 3) would include the US Trade Representative’s _National trade estimate report on foreign trade barriers_ , the EC Directorate General-Trade’s _Market access database,_ and Japanese Ministry of Economy, Trade and Industry (METI)’s _Report on the WTO inconsistency of trade policies by major trading partners_ . Most developing countries do not have such a sophisticated system in place. This is not to suggest that devoting resources at the national level is the optimal approach, this is merely to provide evidence that national governments in industrialised countries have recognised the need for the public sector to provide additional monitoring of WTO commitments and this is how they have chosen to respond. Our proposal below presents an alternative approach where monitoring is not constrained to take place at the national level.

9 For examples of similar calls for increased monitoring and surveillance by the extra-WTO community, see Gallagher and Stoler (2009) and also Hufbauer (2009).

10 It is not necessary for the reader to take the IAWC literally. Instead it is sufficient to think of the proposed IAWC as identifying the different topic areas that a number of groups might target separately. Such groups might include networks of think tanks, research institutes, and even more technically 11
# Table 6.8 (Coaet.)

||Based<br>in|on Value-Added<br>Domestic Prices|Based<br>in|on Value-Added<br>World Priccs|
|---|---|---|---|---|
||1|2<br>3||<br>|
||<br>|<br> <br> <br>|4<br>|5<br>6<br>|
|% F.1r,-AU<br>%El!'<br>|.04.025<br>>(O.853)|1.252,<br>0.370<br>(0.746)<br>(0.621)|.0.110<br>(0.934)|_1.62e_<br>0.208<br>(0.253)<br>(0.707)|
|Ianwts<br>|||||
|In (Senegcalese<br>Slilled and Unskilled)<br>|0.476<br>(0386)<br>||_OA18_<br>(0.422)||
|In(OheAfrican<br>Skilcd and Unskcd)<br>|1.71B-4<br>((3.4E-4)||_4AE-4_<br>(3.8E-4)||
|In (Non-African<br>Skilld and Unsklled)<br>|8.0E-4<br>3.9E-4||7.6134<br>(4.3E-4)||
|In (Senegalese Middle and<br>Upper Management)<br>|-1.6E-4<br>(3.1E-4)||-1.9E-4<br>_(3AE-4)_||
|In (Other African Middle<br>and Upper Management)<br>|7.8E4<br>(5-5S-4)||9.8E4<br>(6.1E4)||
|In (Non-African Middle<br>and Upper Management)<br>|-3.014<br>(6.01E4)||_-4AE4_<br>(6.8E-4)||
|In (Unsillcd)<br>||0.665<br>*<br>(0.215)1<br>0.732<br>(0Q176)||0<br>0.81<br>(0200)|
|In (Skilled)||6.514<br>(9.6E.4<br>(4.2134)||(4.8134)|
Table 6: Medium-term impacts of _Mais Educação_ on educational outcomes

|Dependent variable|Dropout rates|Test score Math|Test score<br>Portuguese|
|---|---|---|---|
||(1)|(2)|(3)|
|Panel A: Impa|cts on fifth-grade|variables||
|Dummy_Mais Educação_* year 2011|1.265|−3.374*|−2.086|
||(1.522)|(1.725)|(1.568)|
|_R_ <sup>2</sup>|0.686|0.817|0.823|
|Observations|1,992|1,992|1,992|
|Dummy year 2011|Yes|Yes|Yes|
|School fixed effects|Yes|Yes|Yes|
|Panel B: Impa|cts on ninth-grade|variables||
|Dummy_Mais Educação_* year 2011|−0.292|−3.821*|−0.664|
||(1.265)|(2.011)|(1.898)|
|_R_ <sup>2</sup>|0.749|0.792|0.798|
|Observations|1,730|1,730|1,730|
|Dummy year 2011|Yes|Yes|Yes|
|School fixed effects|Yes|Yes|Yes|

_Sources:_ Authors’ calculations using MEC/FNDE administrative data, Prova Brasil, School Census, and INEP.

_Note:_ Treatment group are schools that joined _Mais Educação_ in 2008 and remained in the program until 2011. This table reports coefficients from the ordinary least squares estimation of equation (5) in the paper, where the dependent variable is in column (1) is dropout rates, in column (2) mathematics grades in _Prova Brasil,_ and in column (3) Portuguese grades in Prova Brasil. Panel A reports these estimates for the schools from the fifth-grade sample. Panel B reports these estimates for schools from the ninth-grade sample. All variables are at school level. ***significance at the 1% level; **significance at the 5% level; *significance at the 10% level. Robust standard errors, clustered at school level, are reported in parentheses. All regressions include school fixed effects and time dummies. All regressions are weighted by propensity score matching weights.
responds more strongly to reductions in customs clearance time than growth in imports from CEFTA or from Turkey, although the latter also responds significantly.

We also look for differential effects that can be linked to per capita income in the origin countries. On the one hand, lower rates of inspection might favor imports from countries with high per capita incomes because they tend to export higher quality products that might be more time-sensitive.<sup>51</sup> On the other hand, exporters from lower-income countries may have more difficulties coping with delays in customs.<sup>52</sup> Columns (3)-(4) and (7)-(8) of Table 7 show results from estimating by 2SLS-IV Eqs. (4)-(5) with the variable � being an indicator variable for highincome trading partners.<sup>53</sup> The effect of reductions in customs delays on import growth is driven entirely by imports from high-income countries whereas by contrast the effect for the imports from the average country is insignificant. If we investigate more thoroughly the identity of the high-income countries separating the high-income trading partners in the EU from those elsewhere (e.g., Australia, Canada, Switzerland, the U.S.) in columns (4) and (8) we find that the effects are attributable to the high-income countries in the EU alone. This suggests that whatever the impacts of inspections on trade with high-income countries, they are specific to factors that are particular to the EU countries. Perhaps the most likely factors are geographic proximity or membership in a preferential trading arrangement.

To understand further our finding of a stronger effect on EU imports we explore two possible channels. First, one might suspect that inspection rates fell relatively faster for imports from the EU, given the preferential trading arrangement with the EU, for example. To explore this we estimated conditional probabilities of inspection over the sample period for the different types of countries, reporting the results in Appendix Table C.1. There is a larger decline in conditional inspection rates for imports from EU countries relative to those from non-preferential partner countries and for rich EU countries relative to poor countries. But the declines for EU imports

> 51 For example, apparel from high-income countries may be more time-sensitive because it is more oriented to fashion.  More generally it may be that the time cost of delay for higher-value goods is higher, and it may be that, conditional on product, highincome countries send higher-value products.

> 52 It may be for example, that firms from lower-income countries must pay higher interest rates for trade finance, and thus face a higher cost of delays. Such firms may also have less sophisticated logistics operations, which could mean they have fewer mechanisms for coping with delays, but might also mean that they are constructed to be less time-sensitive.

> 53 High-income countries are defined according to the World Bank country income classification.

31
**Table 3.2**

**Changes in the wage premium and the relative supply and demand for unskilled workers (high schooldropouts) assuming**  **HD=2 and**  **HD=3 (annual log changes multiplied by 100). Summary of results**

||Wage p|remium|Relative|supply|σh<br>Relative|d=2<br>demand|σh<br>Relative|d=3<br>demand|
|---|---|---|---|---|---|---|---|---|
||1990s|2000s|1990s|2000s|1990s|2000s|1990s|2000s|
|Argentina|1.4|0.1|0.6|6.8|3.3|6.9|4.7|7.0|
|Bolivia|-2.7|-0.8|2.6|5.2|-2.8|3.6|-5.5|2.8|
|Brazil|-1.7|-2.1|4.5|7.3|1.0|3.1|-0.8|0.9|
|Chile|0.5|-1.8|6.9|4.8|8.0|1.2|8.5|-0.6|
|Colombia|-0.1|-0.9|6.4|3.4|6.1|1.6|6.0|0.6|
|Costa Rica|-0.5|0.7|1.7|2.8|0.8|4.2|0.3|5.0|
|Ecuador||-1.0||2.8||0.7||-0.3|
|El Salvador|-0.7|-0.9|7.1|3.3|5.7|1.5|5.0|0.7|
|Honduras|-1.8|0.4|0.4|-1.7|-3.2|-0.8|-5.1|-0.4|
|Mexico|-1.5|-1.2|4.6|-0.2|1.7|-2.7|0.2|-3.9|
|Nicaragua|-0.2|-0.1|2.1|4.0|1.6|3.8|1.4|3.6|
|Panama|-1.2|-0.7|2.9|5.0|0.5|3.5|-0.8|2.8|
|Paraguay|-0.9|-4.0|2.6|5.9|0.7|-2.2|-0.2|-6.2|
|Peru|1.0|-2.1|1.7|1.5|3.6|-2.7|4.6|-4.8|
|Uruguay|-0.5|1.2|-5.0|-4.5|-6.0|-2.1|-6.5|-0.9|
|Venezuela|0.0|-2.7|2.9|7.6|3.0|2.3|3.0|-0.4|
|Mean|-0.6|-1.0|2.8|3.4|1.6|1.4|1.0|0.4|

Source: own computations based on SEDLAC (CEDLAS and World Bank).

31
Policy Research Working Paper 11029

# **Abstract**

This paper investigates the impact of a large-scale poverty alleviation program targeted at the 62 poorest districts in Viet Nam. The analysis of multiple data sets spanning the past 20 years uses a regression discontinuity design with district fixed effects. The findings do not reveal significant program effects on household welfare (as measured by per capita income and poverty) or local economic development (as measured by nighttime light intensity and establishment of new firms). However, the findings show that the program facilitates a shift from farm to nonfarm employment and significantly increases the share of nonfarm income for rural households. A possible explanation for the positive effects on nonfarm employment is the improved access to credit that the program provides to participating households. The findings also show that the program increases household access to electricity, public transfers, educational subsidies for students residing in the program districts, and health care utilization, possibly through improving the availability of commune health care centers.

This paper is a product of the Development Data and the Development Research Groups, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank. org/prwp. The authors may be contacted at hdang@worldbank.org and vietcuong@vnu.edu.vn.

_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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **The Impact of Roads on Poverty Reduction**

# **A Case Study of Cameroon**

Marie Gachassin<sup>1</sup> , Boris Najman<sup>2</sup> , Gaël Raballand<sup>3</sup>

**Keywords:** Roads, Poverty, Labor, Infrastructure, Cameroon. **JEL:** I32, J22, O11.

> 1 CES (CNRS and University of Paris I), marie.gachassin@gmail.com,

> 2 CES (CNRS and University of Paris I), bnajman@univ-paris1.fr,

> 3 The World Bank, <u>graballand@worldbank.org.</u>

> We are grateful to the National Institute of Statistics of Cameroon for having provided the ECAM II data; the French Embassy and in particular Colonel René BASSET for the “gendarmerie” stations location. We are also grateful to Mathilde Maurel and Karine Marazyan for their helpful suggestions and to the participants of the 2009 Journées Doctorales CES-CERDI-LEO. We also want to thank Tanguy Bernard and the participants to the international conference on “infrastructure economics and development” held in Toulouse in January 2010.
premium. While this is an interesting extension, here, for the sake of simplicity, we choose to focus solely on productivity as a determinant of country risk-premium.

We choose the parameters �� and the variance of ��� in specification (10) and coefficient �� and the variance of ��� in specification (11) to generate the same persistence and volatility of �<sup>�</sup> � in the model as in the data for the OECS countries. In particular, we target the average persistence of �<sup>�</sup> � equal to 0.245 and the average standard deviation of �<sup>�</sup> � equal to 2.69% in the data.

# _Functional forms and parameters_

In this section we describe the functional forms and parameters chosen in the model economy. The functional forms for the utility function, capital adjustment costs and bond holding costs are borrowed from Neumeyer and Perri (2005) and Mendoza (1991). In particular, the period utility function is Here 1/σ is the intertemporal elasticity of substitution, ν-1 is the inverse of the elasticity of labor supply with respect to the real wage. These preferences are well-known from the work of Greenwood, Hercovitz, Huffman (1988) which we will refer to as GHH. These preferences have been widely used in the literature as they provide a better description of consumption and the trade balance for small open economies than alternative specifications. The key feature introduced by GHH preferences is that there is no wealth effect on labor supply.

Following Neumeyer and Perri (2005) we set σ=5 and the curvature of labor ν is set to 1.6. This value is within the range of values used in the literature. For example, Mendoza (1991) uses ν equal to 1.455 for Canada, while Correia et al. (1995) set ν to 1.7 for Portugal.

The rest of the model parameters are set to match the properties of the balanced growth path in the model with the long-run trends in the OECS data over 1980-2014 period. In particular, we set the growth rate γ in the model to replicate the average real GDP growth rate in the OECS of 3% per year. Subjective discount factor β is set to match the average real interest rate in the OECS countries equal to 7.2% per year. Parameter α is set to match the labor income share of 0.6, while depreciation rate δ – to replicate the average investment to output ration in the OECS countries of 26.5%. Parameter ψ in the utility function is set to match an average time spent working of 20% of total time.

We assume that the capital adjustment cost technology is given by where φ �0 is a constant level parameters. This parameter is calibrated to replicate the volatility of investment relative to the volatility of output in our sample, equal to 4.57.

The bond holding costs are assumed to have the following functional form: 15