rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> Volume in Monitored Outlets: Milk<br>(01/21/92-08/25/92)<br><!-- End of picture text --> <!-- Start of picture text --> ............. . 9500<br>.* A o<br>450- .' '* / \ -8500 W<br>* . . .. . . .<br>I~~~~~~~~~~~<br>**7 t3X ; A \ -8000<br>200 - .------ --1---- ---- ---------------------- ------ . . V 1---------- ---------------------------- ------ -6000<br>5000<br>01/21 O0204 02/18 03117 04/07 04/21 05/05 05/19 08109 06/23 07/07 07/21 08/04 08/18<br>Date<br>|- Market Volume ... State Volume<br><!-- End of picture text -->

42
18' from agriculture to rural nonfarm activities. Rural electrification possibly encourages farm mechanization and hence reduces farm employment. However, it increases agricultural wage by inducing labor demand in rural nonfarm activities. The response of government investment in rural electrification is the highest for both the rural nonfarm employment and agricultural output with an elasticity of 0.11 followed by agricultural real wage with an elasticity of 0.06. Its response elasticity for farm employment is -0.06.

The rainfall has a positive effect on both the agricultural output and real wage. These results are consistent with expectations. Unlike output and wage variables, employment (both farm and nonfarm) data come from the decennial census and so annual rainfall is not expected to influence the employment status of rural population.

The effects of agroclimatic endowments measure their direct impacts on the dependent variables other than via their impact on public institutions and infrastructure. Agricultural wage growth is higher in area where irrigation potential is high, i.e., where growth in agricultural output, farm and nonfarm employment is favorable. Agricultural wage growth is also high in wheat producing regions (i.e., where the number of cool months is high). Also, growth in farm and nonfarm employment is high in areas with high rainy months.
> Equation (1) defines sector-specific productivity, π . It is composed of three components—two of which are sector specific, α and χ , and the third is economy-wide, γ . The first sector-specific

parameter is a sectoral shifter that allows baseline productivity differentials across sectors. For example, it is typically assumed that productivity in manufacturing is higher than in services. The second sector-specific parameter is linked to the export-output ratio. It is calibrated (through the β parameters) in the baseline simulation so that it represents some fixed percentage of total productivity. It is assumed for the purposes of this simulation that it represents 40 percent of total productivity growth. The economy-wide parameter is calibrated in the baseline simulation as a residual to achieve a prespecified target for GDP growth. In most reform scenarios, all three factors are exogenously fixed. In the alternative scenario, where productivity is permitted to be influenced by openness, the χ -factor will evolve depending on the elasticity, ε , which is here assumed to be equal to 1 for manufactures and 0.5 for agriculture.<sup>23</sup> Assume, for example, that the total sectoral productivity growth rate is 5 percent and the χ -factor in the baseline is 2 percent. If the reform scenario leads to a 10 percent increase in the export-output ratio, the χ - factor will increase to 2.2 percent. Therefore, total (labor-augmenting) productivity in the sector will increase to 5.2 percent, or an increase of 4 percent over the baseline level.<sup>24</sup> Key results pertaining to the trade-productivity linkages are summarized in Table 3. The main dynamic gains occur for developing countries. Whereas high-income countries see an

> 23. The agricultural elasticity is set to one-half of the manufacturing elasticity for several reasons. One is that most of the econometric evidence has been linked to manufacturing only, with little or no empirical support in agriculture. As well, agriculture in many developing countries is still dominated by subsistence farming, with weak linkages even to the domestic market. Many of the more developed agricultural exporters—for example, Chile and Brazil— are already closely integrated with world markets. Enhancing productivity in the short and medium terms will be driven more by changes in land tenure policies, as well as improvements in local infrastructure and extension services. Finally, based on estimates from Martin and Mitra (1999), a relatively high level of agricultural productivity in the baseline is assumed.

24. See _Global Economic Prospects_ ([GEP] World Bank 2002) for further discussions on these assumptions and how they compare with other studies. For more details on the specification, see van der Mensbrugghe (2004a).

15
**<mark>Table A1: Distribution of refugees and hosts in the most affected clusters of Kasulu, Ngara and Karagwe between 1992 and 1994</mark>**

|||**_Kasulu_**|||**_Ngara_**|||**_Karagwe_**||
|---|---|---|---|---|---|---|---|---|---|
||1992|1993|1994|1992|1993|1994|1992|1993|1994|
|Tanzanians|400,320|410,400|420,480|176,153|181,227|184,230|324,853|334,210|337,316|
|Refugees|5,140|120,043|16,460|30,000|56,310|403,304|NA|NA|159,160|
|**_Proportion_**|**_1.28%_**|**_29.25%_**|**_3.91%_**|**_17.03%_**|**_31.07%_**|**_218.91%_**|**_NA_**|**_NA_**|**_47.18%_**|
|Total|405,460|530,443|436,940|206,153|237,537|587,534|324,853|334,210|496,476|

**<mark>Source:</mark>** <mark>UNHCR Population Statistics.</mark>

# **<mark>Figure A5: Distribution of refugees and hosts in the most affected clusters of Kasulu, Ngara and Karagwe between 1992-1994</mark>**

<!-- Start of picture text --> Population of refugees and hosts in affected districts during the influx<br>450000<br>400000<br>350000<br>300000<br>250000<br>200000<br>150000<br>100000<br>50000<br>0<br>1992 1993 1994 1992 1993 1994 1992 1993 1994<br>Kasulu Ngara Karagwe<br>Tanzania Refugees<br><!-- End of picture text -->

**<mark>Source:</mark>** <mark>UNHCR Population Statistics.</mark>

39
6 expenditure-based incidence approach can be especially useful for examining the distributional impact of marginal changes in the government's budget.

Benefit incidence studies typicaily examine public expendiures by three major categories: public spending on general goods, such as defense, public spending on specific public goods, such as education and health care, and cash and in-kind transfers. We follow that rubric in examining benefit incidence methods for public expenditures. We also examine below the appropriate allocation of capital expenditure, interest payments and side payments made to government officials. We then make a number of recommendations to help insure that future research is as useful as possible.

# General Benefits

Attribution rules for general benefits can be distinguished by whether they are (i) rigorously derived from assumptions about preferences (Aaron and McGuire, 1970; Maital, 1973), or (iij simply postulated (ad hoc) as intuitively appealing. Aaron and McGuire develop a utilitybased method to allocate the expenditure on pure (general) public goods among households. The Aaron and McGuire approach requires that utility functions be separable in public and private goods and that the public good is consumed in equal amounts by all individuals. In addition, their approach requires choosing parameters for the utility function. The ad hoc methods, on the other hand, allocate expenditures on pure public goods to households on the basis of their proportion of total income or of their proportion of total population.

Both the utility-based distributors and the more ad hoc distributors can lead to implausible results. For exnample, with United States data, Maital (1973), using Aaron and McGuire's approach, finds a strongly pro-rich incidence for general public goods.<sup>4</sup> In another study of expenditures in the United States, Reynolds and Smolensky (1977) use an ad hoc allocation rule and fmd benefits for pure public goods to be more pro-poor than even public cash transfer programs. Moreover, Denzau and MacKay (1976) and Philpotts (1987) question Aaron and McGuire's assumptions of separable utility in private and public goods and of all individuals receiving the same amount of the public good. Indeed, by lumping expenditures on several general public goods together, researchers assume that the benefit-income relationship is invariant
Francois, J. and B. Hoekman (2010) “Services Trade and Policy”, _Journal of Economic Literature_ , Vol. 48, No. 3, pages 642‐692.

Griffith, R., S. Redding and J. van Reenen (2004) “Mapping the Two Faces of R&D: Productivity Growth in a Panel of OECD Industries”, _Review of Economics and Statistics_ , Vol. 86, No. 4, pages 883‐895.

Hsieh, C‐T. and P. Klenow (2009) “Misallocation and Manufacturing TFP in China and India”, _Quarterly Journal of Economics_ , Vol. 124, Issue 4, pages 1403‐1448.

Hsieh, C‐T. and P. Klenow (2014) “The Life Cycle of Plants in India and Mexico”, _Quarterly Journal of Economics_ , Vol. 129, Issue 3, pages 1035‐1084.

Inklaar, R., M. Timmer and B. van Ark (2007) “Mind the Gap! International Comparisons of Productivity in Services and Goods Production”, _Germany Economic Review_ , Vol. 8, No. 5, pages 281‐307.

Inklaar, R., M. Timmer and B. van Ark (2008) “Market Services Productivity across Europe and the US”, _Economic Policy_ , Volume 23, pages 141‐194.

Kalinova, B., A. Palerm and S. Thomsen (2010) “OECD's FDI Restrictiveness Index: 2010 Update”, OECD Working Papers on International Investment, 2010/03, OECD Publishing.

Koske, I., I. Wanner, R. Bitetti and O. Barbiero (2014) “The 2013 Update of the OECD Product Market Regulations: Policy Insights for OECD and non‐OECD Countries”, OECD Economics Department Working Papers, OECD Publishing.

Levinsohn, J. and Am Petrin (2003) “Estimationg Production Functions Using Input Control for Unobservables”, _Review of Economic Studies_ , Vol. 70, No. 2, pages 317‐341.

Maijoor, S., W. Buijink, R. Meuwissen and A. van Witteloostuijn (1998) “Towards the Establishment of an Internal Market for Audit Services within the European Union”, _European Accounting Review_ , Vol. 7, No. 4, pages 655‐673.

Mattoo, A., R. Rathindran and A. Subramanian (2006) “Measuring Services Trade Liberalization and its Impact on Economic Growth: An Illustration”, _Journal of Economic Integration_ , Vol. 21, pages 64‐98.

McMorrow, K., R. Werner and A. Turrini (2010) “Determinants of TFP Growth: A Close Look at Industries Driving the EU‐US TFP Gap”, _Structural Change and Economic Dynamism_ , Vol. 21, No. 3, pages 165‐180.

<mark>Miroudot, S. and E. van der Marel (2014) "The Economics and Political Economy of Going Beyond the GATS",</mark> _<mark>Review of International Organizations</mark>_ <mark>, Volume 9, Issue 2, pages 205‐239.</mark> Nicoletti, G. and S. Scarpetta (2003) “Regulation, Productivity and Growth: OECD Evidence”, _Economic Policy_ , Vol. 19, No. 36, pages 9‐72.

Nielson, J. and T. Taglioni (2003) “Services Trade Liberalization: Identifying Opportunities and Gains”, OECD Trade Policy Working Paper No. 1: OECD Publishing.

Olley, S. and A. Pakes (1996) “The Dynamics of Productivity in the Telecommunications Equipment Industry”, _Econometrica_ , Vol. 64, Issue 6, pages 1263‐1295.

Robinson, S., Z. Wang and W. Martin (2002) “Capturing the Implications of Services Trade Liberalization”, _Journal of Economic Systems Research_ , Vol. 14, No. 1, pages 3‐33.

26
**Figure 4.  Central government tax revenue vs. per capita GDP (2000)**

<!-- Start of picture text --> 35<br>30<br>25<br>20<br>15<br>10<br>5<br>6 7 8 9 10 11<br>Per capita GDP (log)<br>Selected countries throughout the world Selected countries - LAC<br>Total tax revenue (% of GDP)<br><!-- End of picture text --> Why is tax collection so low in Latin America? Conceptually, there are two possible reasons: low statutory tax rates, and narrow tax bases. Of course, each of the two may play differently for different taxes. Table 2 offers a comparative perspective on tax rates across world regions, for both income and value added taxes. Latin America’s income tax rates are at the low end of the spectrum, for both personal and corporate income. Indeed, income tax rates have declined across the region over the last two decades. The average top personal income tax rate fell from 49.5 percent in 1985 to about 30 percent in 2004. Likewise, the average top corporate tax rate declined from 43.9 percent in 1986 to 26.6 percent in 2004 (Gómez-Sabaini 2005). As for VAT rates, they have followed the opposite trend: the regional average of countries’ general rates rose from 12 percent in 1992 to 15 percent in 2004 (Gómez-Sabaini 2005). Still, Table 2 shows that they are not high by international standards.

**Table 2 Comparative perspective on Tax Rates**

|**Region**||**Tax Rate**||
|---|---|---|---|
||**Personal**|**Corporate**|**VAT**|
|East Asia Pacific|33.50|31.50|10.00|
|Latin America and the Caribbean|29.00|26.60|15.00|
|Middle East & North Africa|48.00|40.00|17.00|
|OECD|45.00|35.00|17.25|
|South Asia|39.50|41.00|15.00|
|Sub Saharan Africa|38.00|36.00|17.50|

Source: Author’s calculations based on Eichhorn (2006), WDI 2006, OECD tax Database, Doing Business Database. Figures refer to last available date.

What about tax bases? Narrow tax bases can be the result of plain tax evasion, or too generous tax concessions and loopholes. One rough way of gauging tax bases is by looking at tax productivity, defined as actual revenues (as a percentage of GDP) relative 11
Direct effects are the price and quantity changes that apply to the final consumer when subsidies on final products are changed. These include the short-term crude change in prices (also called first-round effects) and the medium-term behavioral response of the final consumer in terms of quantities consumed (also called second-round effects, behavioral changes or **demand responses** to price changes).

Indirect effects are those that measure the “trickle down” effect on the final consumers of subsidies applied to intermediaries. The “trickle-down” effects evidently depend on the behavior of the intermediary and on what proportion of subsidies are transferred onto the final consumer. Thus, indirect effects can be considered as the **supply responses** to price changes.

To simplify the exposition, we will consider **partial equilibrium effects** those that consider only direct effects of price reforms and **general equilibrium effects** those that consider both direct and indirect effects on the whole economy.

# **Focus of the work**

Subsidies cover a wide array of products and services and, in very broad terms, one could argue that all government expenditures can be considered as a form of subsidy. Analysis of subsidies and simulations of subsidies reforms can also cover a wide array of technical issues and become extremely complex exercises. This section delimits the boundaries of the manual.

The following restrictions will apply:

- Two agents are considered, the government and consumers represented by households. The government sets the prices of subsidized commodities and households react to changes in prices. If more detailed information on production is available the analyst will be enabled to use some of this information in order to refine the estimation of the impact of reforms.

- Products considered will be those that are <u>consumed</u> by households and <u>subsidized by the</u> government. This typically restricts the range of products to a few items in any given country.

- The analysis is restricted to two prototype products that cover most typologies of subsidized - -

- products. The distinction is between <u>single priced</u> products and <u>multiple priced</u> products. By single priced-products we mean consumers‟ products for which the government fixes the unit price irrespective of quantities consumed. Examples are set prices for bread or sugar. By multiple-priced products we mean products for which the government fixes different prices according to different levels of consumption. Examples are set prices for electricity or water.

- The data requirement is restricted to only one household consumption survey. Users will be enabled to import into the analysis estimations made through other means such as input-output tables or computable general equilibrium models but the assumption is that the analyst has access to only one cross-section household survey. This is the most likely scenario faced by analysts when they first visit a country to carry out a subsidies analysis.

- The focus will be on the medium-term effects as defined further as opposed to short-term and long-term effects.

7
Policy ReseaRch WoRking PaPeR 4548

# **Abstract**

Using an extensive survey that addresses risk factors faced by the population in the shantytowns (favelas) of Fortaleza, Brazil, the aim of this paper is to study risktaking behavior by youth, focusing on drug use and teenage pregnancy. The paper analyzes the impact of factors such as exposure to mass media, the existence of support networks, self-esteem, and the occurrence of violence at home and in the neighborhood, on the probability of risk-taking behavior. A bivariate probit model is estimated. The findings indicate that reliance on support networks and exposure to mass media are associated with a lower probability of either type of risk behavior. Living in a violent home increases drug consumption. Race does not have a significant impact on either type of behavior.

This paper—a product of the Sustainable Development Division, Social Development—is part of a larger effort in the department to reduce poverty and increase social inclusion. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at dverner@worldbank.org.

_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
39 1984.1986 period.<sup>5</sup> The average annual growth of the base wage over these years was 4.18 percent. Given that the rate of inflation (as measured by the cost of living index) was approximately 13 percent a year from 1984 to 1986, it is dear that the industril wage (in terms of the base or tot;l) has not been keeping up with the cost of living.

Table 4.12 also examines the growth of total compensation by its principal components within the major skill categories found TABLE 4.12 Senegal Average Annual Percentage Growth of Nominal Monthy Compensadon by Skill Category, 19841986

|Categoiy|_Bae_<br>Wage<br>_(%)_|Bonuses<br>_(%g)_|Supplements<br>_(%)_|TtO<br>Compenaon<br>_(%)_|
|---|---|---|---|---|
|High level manager|6.87|3.08|51.80||
|Upper-level technicians<br>and middle level managers|5.35|7.11|16.43|17.76<br>JO|
|Mliddle-level technicians<br>and lower level managers|2.89|8.51|15.59||
|Skilled employees<br>-|1.96|8.53|11.16|5.48|
|Skled workers and<br>unskiled employees<br>Laborers and unskilled<br>workers|2.63<br>7.28|10.16<br>14.11|8.19<br>6.33|3.50|
|Average Annual Growth|4.18|9.90|12.88|_655_|

Source: Survey of workers in 17 firms.

5. Mhis time period is, of course, a short time period for drawing conclusions about wage trends. However, because the data come from worker surves, they represent a useful complement to our other data.
||Nigerian 2006’s SAM||GTA|P database version 8.1|Aggregated 21 GTAP sectors|
|---|---|---|---|---|---|
|No.<br>Code|Description|No.|Code|Description|No.<br>Code<br>Description|
|61cpser|Public administration|||||
|||_45_|_wtr_|_Water_||
|Zero sector||57|dwe|Dwellings||

Ω Electricity and water are one sector in the Nigerian SAM of Nwafor et al. (2010); however, the Nigerian IOT (Siddig and Luckmann, 2013) contributed to GTAP database separates the two sectors. The water sector is included in the “Other services” sector among the 21 sector aggregation.

34
Differentiated and progressive tax rates vary widely between 0.4 and 25 percent.<sup>10</sup> We show large variation in tax obligations by comparing the rate of taxation under the STR (based on turnover) and the CIT regime (based on profit) in each country that has either a proportional or differentiated/progressive rate of TOT. We examine the profit rate that businesses would need to make for their level of taxation to be equal under both regimes, which we call the ”break-even” profit rate (Figure 2). Businesses that have higher rates of profitability than the break-even profit rate would pay relatively less tax under the STR, while businesses that have lower rates of profitability than the break-even profit rate would pay relatively more tax under the STR. This break-even profit rate ranged from around 2 to 20 percent across countries. As such, the tax burden faced by businesses under the STR, relative to the CIT regime, varied considerably. For example, in Uganda, a business with a profit rate of 2 percent or more would pay less taxes under the STR, whereas in Cabo Verde, only business with profits above 18 percent would pay less taxes under the STR.

In sum, the analysis of real-world STRs in SSA shows a wide variety of design decisions that lead to substantial differences in the trade-off between tax equity, simplicity, and revenue collection. First, when it comes to tax equity, roughly half of the simplified regimes have some equity element by design (progressive tax rate and/or minimum threshold). Second, when considering simplicity, roughly half of countries with an STR apply a single proportional TOT rate, which is one of the simplest ways to calculate tax liability. Last, many countries with proportional or differentiated/progressive tax rates have set tax liabilities higher than what businesses would pay if they were under the CIT regime, suggesting that collecting revenue from these businesses is a priority of these regimes. The insights in this section have focused on the _de jure_ features of STRs. In the next section, we examine the _de facto_ implementation of Kenya’s STR and taxpayers’ responses.

> 10Only S ̃ao Tom ́e and Pr ́ıncipe and Cote d’Ivoire apply rates above 20 percent to some businesses, subject to simplified accounting or depending on turnover. Under the simplified regime in S ̃ao Tom ́e and Pr ́ıncipe, businesses maintain simplified accounting records for computing taxable profit, which is subject to the standard CIT rate (25 percent). Cote d’Ivoire applies a tax rate of 25 percent on profits (standard CIT rate) of companies with a turnover between XOF 200 million and XOF 500 million ($3250 - $8000). In both cases, these higher tax rates apply to profits and are similar to the standard CIT rate.

14
<!-- Start of picture text --> Boo $150<br>400 V/ $90<br>oY * AN I\ —— Merch. Exports pe (constant 94 MK}<br>300 Vy, ay $70<br>non TD7 A Ny- ARN $60 -------VRER (1980100)<br>_ $30<br>— i /<br>Q -$10<br>om OO NNO Or The OM Om Ww<br>SSESSSSESESSSSLSS<br><!-- End of picture text -->