rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> PO Tw<br>[1| Descriptor Motes 2005 2006 2007 2008 2003 2010 20n<br>|2 Firstprojections year oF<br>[at | No-Policy-Change Scenario Fill in yellow cells, based on no-policy-change scenaria<br>Default is unchanged primarg balance, in percent of GOP<br>a4 Insert alternative values into yellow cells, if more elaborate scenario is assumed<br>| | 47,197,000.0<br>| 3596 | Public sector balaexpe n diturece 346,050-22,129 , 170298 . 34 359,225,9762,297,970.1 395,123,152290,610.9 424,924,601, 9 ,61167.9 457 176,9729,616,463.0 15,966,326.4491,421,330 23,395,659.9527,899,201<br>| Of primary 292,650,170.3 325,719,643.8 357,241,263.0 338,065,319.6 421,725,986.0 455,315,062.3 498,073,894.0<br>|_ 9938 | Public sector interestrevenue expenditure (and grants] [grass] 323,920,881953,400,000.0 36032 ,5 2306 , 946332 . 24 395413,762.637,881,588.7 42936 , 864,251.8531479.2 46635 , 793446 , 335886 .0 507,33,106, 287,656 268 . 29 29,825,307.4551294,8611<br>100 | Gross domestic product, current prices 481,813,760.6 536,258, 722.5 588,155,326.0 639,903,475.6 694,328,352.2 754,561,336.7 820,019,522.7<br>101 | Gross domestic product, constant prices 143,253.8 150, 416.5 167,937.3 165, 834.2 174,125.9 182,832.2 191,973.8<br>Exchange rate, national currency per U.S. Dollar, end of period 1,460,000.0 1496,579.2 1517 867.3 1525,271.5 1628,452.5 1531,640.0 1531,640.0<br>104 Exchange rate, national currency per U.S. Dollar, average 1,378,148.1 1,469, 730.6 1,498,531.7 1,512,525.2 1,519,903.4 1527, 317.5 1527,317.56<br>8 || PublicConsumer debt Price Index (net) 295,086,759428,683.5 287,762,8354544045 261,244,523474,047.23 271,469,1204910491 255,811,149508,235.28 235,216,076B26,024.1 202,063,5745444349<br>Fonts<br>108 | GOP Deflator (percent change) 6.00 445 346 3.50 3.50 3.50<br>[10[103| Real revenue and grants TSS6LE 79339.4 $3306.9 era?22 a145.8 964381 101260.0<br>iin | RealGrowth non-interestin real rev e nuxp e nditures and grants B8267.2 FIBSO5 . 50 T5264.65.0 Foo27.85.0 S2973.25.0 8712815.0 31434.65.0<br>Growth of real non-interest expenditures: 5.0 5.0 5.0 5.0 5.0 5.0<br>Share of Foreign-currency denominated debt in total debt (previous period) O3 O.3 O.3 0.3 o4 o4<br>(114_| Interest rate on public domestic debt ga 125 12.3 12.0 115 7<br>ae Real interest rate on public debt, including capital gains on the exchange rate 4.63 Rie o.27 Tae 7.59 F.03<br>Gross financing need 17,193,029.9 19,736,383. 18,425,132.1 10,410,537.0 4160,673.6 -3,368,653.9 ~~<br>Mo 40> WK Instructions }Input_fiscal / Seigniorage / Table f StochSim / Table_SR, /Table_Gr. f 2|<¢ ><br><!-- End of picture text -->
development has been concentrated in the capital cities (which are often the only cities of any appreciable size).

The next most significant factors for increasing household welfare in the FSU were the household's entrepreneurial activity, either through owning an enterprise or farming a private plot of land, and the household's link to the labor market, as proxied by the share of wages in total household income. However, the ranking of these factors was countryspecific. In Estonia, land ownership and owning an enterprise was significant but most important was the share of wages in household income, which can increase welfare by one-third. In Russia, land ownership was not significant,'<sup>6</sup> but the share of wages in household income and ownership of household businesses were important, raising household welfare 30 and 24 percent respectively. In Kyrgyz Republic, after location, ownership of a private plot had the largest effect on welfare, increasing it by 25 percent, while-household welfare increased 20 percent from increasing participation in the official economy (as captured by an increase in the share of wages in total household income).

In all three countries, the presence of an unemployed household head (or household member) was found to significantly decrease household welfare. In Estonia and Russia, specifications based on the number of unemployed demonstrated that adding an unemployed household member reduced household welfare per equivalent adult between

> 16 Ths is possibly due to recordinWmeasurement errors for this variable which is carried in the data set as hectares of land held by the household. When the raw data were examined, there were several improbable outliers. Unfortunately, removing these outliers did not significantly improve perfornance, nor did the subsitutation of a dummy variable for land ownership. The dummy variable did perform better in Russia than the number of hectares, so it was retained. Sonewhat similar measurement problems also plagued the Kyrgyz Republic data (the two surveys were conducted by the same consulting group), but the dununy variable was significant for Kyrgyz Republic. In Estomia, a different survey and methodology recorded only whether the household had access to land, not the amount of hectares.

73
22

# 42 Labor Force, Employment, and Unemployment

The data on overall labor force participation, employment, and unemployment are perhaps the least reliable of the demographic statistics. We report the official data for the sake of completeness, but we prefer to place more emphasis on the data from our enterprise and worker samples, which we present in the following sections of this chapter.

As of 1982, the number of people 10 years of age or older was estimated to be 4,111 million, of whom 2,274 million (55 percent) were less than 30 years old. The labor force in 1982 was estimated at 2,917 million, of whom 359,000 (12.3 percent) were classified as unemployed (where unemployed is defined as persons not gainfully employed and looking for work).

Over one-half of the employed population works in the traditional rural sector. The breakdown of employment by sectors, as reported by the Ministry of Planning for 1982 is:

|Modem sector|905,000|(35 %)|
|---|---|---|
|Urban Informal sector|282,000|(11 %)|
|Traditional sector|1,371,000|(54 %)|
|Total|2,558,000|(100 %)|

Within the moderi- sctor, 317,000 of those employed are reported to holepermanent jobs, 494,000 hold seasonal jobs, 15,000 are cassified as daily workers, and 79,000 work on a temporary or occasional basis. The striking aspect of these statistics is, the large number of nonpermanent (especially easonal) workers relative to the permanent ones. This finding runs counter to many widely held beliefs, and it is corroborated by data from our industrial sample. In contrast, within the informal sector a surprisingly large number of workers (223,00G out of 282,000) is classified as permanent. Given the nature of this sector, the definition of a permanent worker is presumably different - probably meaning any worker who engaged in any informal sector activity for an extended period of time.

The official breakdown of total employment in 1982 by agriculture and resource extraction, industry, and services suggests that a sizable portion of employment in the modern sector (as classified above) is nonindustrial. In particular, the primary
54

|**Country**|**Types of fuel andprices**|**Source**|
|---|---|---|
||effective Jan 20, 2009, they are weight-averaged for that<br>month.||
|Côte d’Ivoire|91 RON gasoline, LPG in 6-kg cylinders in Abijan. All<br>prices maximum retail prices.|Government announcements at<br>www.commerce.gouv.ci.|
|Dominican<br>Republic|89 RON gasoline, premium diesel with 0.2 percent<br>sulfur. Weekly prices are averaged for the month of Jan.|www.seic.gov.do.|
|Egypt, Arab Rep.|90 RON gasoline, LPG in 12.5-kg cylinders|Government announcements|
|El Salvador|90 RON gasoline, LPG in 25-pound (11.4-kg) cylinders.<br>Retail reference prices set by government for gasoline<br>and diesel, maximum retail prices for LPG.|www.minec.gob.sv|
|Ethiopia|91 RON gasoline, LPG in 12.5-kg cylinders. All retail<br>prices in Addis Ababa, averaged over the month for<br>gasoline, diesel, and kerosene accounting for price<br>adjustments during the month.|Ministry of Trade and Industry for<br>gasoline, diesel, and kerosene,<br>www.csa.gov.et for LPG|
|Gabon|91 RON gasoline, LPG in 12.5-kg cylinders in<br>Libreville.|www.totalmarketing.ga|
|Ghana|91 RON gasoline, LPG price independent of cylinder<br>size.|www.npa.gov.gh.|
|Guatemala|88 RON gasoline, LPG in 25-pound (11.4-kg) cylinders.<br>All prices in Guatemala City.|www.mem.gob.gt.|
|Guinea-Bissau|Prices are for gasoline and diesel that are not duty-free.|World Bank office in Bissau.|
|Honduras|87/88 RON gasoline, LPG in 25-pound (11.4-kg)<br>cylinders.|www.sieca.int.|
|India|91 RON non-branded gasoline, non-branded diesel,<br>subsidized kerosene sold through the Public Distribution<br>System, and subsidized LPG in 14.2-kg cylinders, all in<br>New Delhi.|www.iocl.com.|
|Indonesia|88 RON subsidized gasoline, subsidized diesel,<br>subsidized kerosene, and LPG sold in 3-kg cylinders.|www.pertamina.com.|
|Iran, Islamic<br>Rep.|Rationed and subsidized gasoline. See table A2.2 for<br>more detail. For Jan 2012, this paper takes 4,000 rials<br>per liter for regular gasoline and 3,500 rials per liter for<br>diesel.|www.niordc.ir.|
|Iraq|Regular gasoline with 84 RON|Central Organization for Statistics.|
|Jamaica|87 octane index gasoline containing 10% ethanol. Ex-<br>refinery prices inclusive of taxes for pass-through<br>calculations.|www.petrojam.com.|
|Jordan|90 RON gasoline, LPG in 12.5-kg cylinders.|www.jopetrol.jo.|
|Kazakhstan|92 RON gasoline. Country-wide averages of gasoline<br>and diesel prices for the month of January.|www.stat.kz.|
|Kenya|91 RON gasoline. For Jan 2012, regulated maximum<br>prices for gasoline, diesel, and kerosene in Nairobi and<br>reported LPG prices in Mombasa.|www.erc.go.ke for gasoline, diesel,<br>and kerosene, and news articles for<br>LPG.|
|Lao PDR|<br>91 RON gasoline, prices in Vientiane.|laostatefuel.com/ for gasoline and<br>diesel, Vientiane Times for LPG.|
|Liberia|Maximum prices set by government.|Announcements by the Ministry of<br>Commerce and Industry.|
|Madagascar|Gasoline with 95 RON (regular gasoline with 91 RON<br>was phased out in 2011), LPG in 12.5-kg cylinders.<br>Maximum prices for gasoline, diesel, and kerosene, and<br>average LPGprices in Antananarivo.|www.omh.mg.|
39 F. 8ome Sugae_tlons for **ReseH r** While a compendium of provisions of Ul programs In developing countris exists (ISSA, 1983), there has been no basic research on the economics of these programs that might bo useful In modifying them and In structuring programs for other countries. The research summarized In Section D all Is from developed economies. Studies from developing countries are needed; but such research should not merely replicate the myriad studies of microaconomic behavior In the presence of Ul programs In developed countries. Rather, it should aim toward providing answers to the theoretical questions raised In Section E that determine the transferability of what we have leamed In developed countrbies.

The Issue underlying the most Important recommendation In Section E Is the existence of labor-market dualism. Clearly, much effort has been devoted to studying this Issue empiricaly. It should, though, be examined in the context of Ul programs. If dualism Is not Important, and Ul programs are financed by Imperfectly experience-rated payroll taxes, we will observe greater employment fluctuations In covered Industries than In otherwise similar uncovered employment. The question, of course, Is what Is 7otherwise similar." A study that can answer the questions would use Industry data on employment and output In several developing countries that have Ul systems, and compare employmentoutput elasticities there to those from similar industries In carefully chosen developing countries that do not offer Ul. Essentially, pairwise comparisons of elsiticitles by Industry should be examined.

If we find that the elasticitles are higher In covered industries compared to the same Industries In countries wthout Ul, we can infer that labor markets In countries with Ul are not characterized by dualism, at least for the purposes of analyzing the Impact of Ul. Alternatively, if we cannot discem any difference between elastickles, we may Infer that the Ul program does not alter employment pattems, perhaps because real wages are Indeed rigid. That Information should be useful in determining the appropriate structure of Ul programs In developing countries, as it tells us whether Figure 1 or Figure 2 Is more appropriate.

The other major Issues In Section E were the transferability of the goal of maintaining consumption, and the appropriate potential duratlon of benefts and the net replacement rate. Studying
Policy ReseaRch WoRking PaPeR 4362

# **Abstract**

This paper presents a selective overview of the literature on modeling labor market policies in developing countries. It considers welfare economics, theoretical models, and empirical evidence to highlight the three general features needed in future research on labor market policy in developing countries. The author identifies desirable research components (welfare economics, theoretical modeling, and empirical modeling) and pitfalls in the literature (inappropriate use of productivity, reliance on wrong kinds of empirical studies, lack of cost-benefit analysis, attention to only a subset of the goods and bads, and fallacy of composition). The paper concludes with suggested topics and methods for future research. The author states that sound labor market policy requires sound labor market models. The paper makes a case for developing policy based on explicit evaluation criteria, specific theoretical models, and comprehensive empirical evidence.

This paper—a product of the Development Economics Department, Research Support Unit (DECRS)—is part of a larger effort by the World Bank’s Research Committee, in consultation with Regions and Networks, to commission surveys of recent policy research and diagnostic analyses of the current state-of-the-art in priority areas for developing countries. All available Policy Research Working Papers are posted on the Web at http://econ.worldbank.org. For information, contact jdethier@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
yet an independent country,<sup>10</sup> and therefore allows me avoid loosing my oldest cohorts. These time spans also permit me to explore whether democracy has intergenerational effects or not; that is, the variable defined by Equation (a) is statistically significant and it is statistically bigger than that defined by Equation (b) –and as such, historical legacies are important contemporaneously.

Figure 1: Stock of democracy by birth cohort <!-- Start of picture text --> (a) (b)<br>Birth cohort Birth cohort<br>r=0.01 r=0.03 r=0.01 r=0.03<br>r=0.06 r=0.10 r=0.06 r=0.10<br>95% confidence intervals 95% confidence intervals<br>150 150<br>100 100<br>50 50<br>0 0<br>Average stock of democracy<br>Average stock of democracy, 30years before birth to 20 years after −50 birth year to 20 years after birth −50<br>1936−38 1939−41 1942−44 1945−47 1948−50 1951−53 1954−56 1957−59 1960−62 1963−65 1966−68 1969−71 1972−74 1975−77 1936−38 1939−41 1942−44 1945−47 1948−50 1951−53 1954−56 1957−59 1960−62 1963−65 1966−68 1969−71 1972−74 1975−77<br><!-- End of picture text --> Source: Author’s calculations based on data from Latin American household surveys, 1995-2009, biannual and Polity IV Project.

# **4 Approach**

Given the panel settings of my data (panel of successive cross-sections), we can model the relationship between democracy and inequality as follows: where _Yc,g,p,e_ denotes the Gini index of birth-cohort _c_ , of gender _g_ , of country _p_ and survey _e_ ; _Dc,p_ is a proxy for the accumulated quality of democratic institutions; and _<u>ε</u> c,g,p,e_ denotes the idiosyncratic error. Given that my interest lies on the historically determined component of institutions, this regression does not (cannot) control for a full set of cohort dummies. Since I have more than one observation per cohort, but my key regressor only varies by cohort, I cluster the standard errors by birth-cohort and country. This equation, however, is misspecified.

> 10The one thousand days war was a civil armed conflict between the liberal and conservative parties in the newly created Republic of Colombia. After the peace treaty Panama separated from Colombia.

10
1

# **1. Introduction**

The number of motor vehicles in the world is growing rapidly. Between 1980 and 1995-just fifteen years-the global fleet of cars, trucks, and buses increased by 60 percent, with a third of the increase in developing countries. The increasing number of vehicles brings many benefits but is associated with worsening negative externalities including congestion and air pollution. In addition, motor vehicles need roads, and road networks have been expanding to accommodate the increasing number of vehicles. Roads are costly to build and maintain, and they also produces externalities. For example, road network expansion is a major determinant of development patterns, particularly in urban areas. Opinions are divided on the desirability of increased motorization. The effects of the growth of motor vehicle use and road networks are viewed by some commentators as inevitably adverse,' while others argue that national patterns of motor vehicle use are sustainable.<sup>2</sup> The analysis presented here reviews past trends in vehicle ownership and road network expansion. It analyzes the determinants of past growth so that we can better understand what future patterns of motor vehicle and road network growth are likely to be, and how policy interventions can influence future growth. Because motorization raises different issues at the urban and national levels, city-level and national patterns are analyzed using data from a sample of cities and countries covering all income levels.

Motor vehicles are central to policy debates on urban transport because their increased use causes congestion, contributes to low-density development, and reduces transit use.<sup>3</sup> Some analysts have argued that urban development densities must be increased to reduce auto dependence and promote transit use.<sup>4</sup> Moreover, vehicular emissions have contributed to the degradation of the air quality in many cities, particularly in developing countries.

Motor vehicle use and road provision are concerns at the national level because large investments are needed for road infrastructure, and because countries want to ensure that their national transport policy reflects the comparative advantages of each transport mode (road, rail, water, and air). And at the national and global levels, emissions from

> 1 "Taming the Beast--A Survey on Living with the Car," _The Economist_ (22 June 1996), p. 1-18.

> 2 Remy Prud'homme, Richard Darbera, David Newbery, Achim Diekman, and Bent Elbeck, _Is Our Present Transport System Sustainable?_ (Observatoire de l'Economie et des Institutions Locales, Universite de Paris, 1997).

3For a summary of these arguments, see John R. Meyer and Jose A. Gomez-Ibanez, _Auto, Transit, and Cities_ (Harvard University Press, 1981).

See, for example, Peter Newman and Jeffrey Kenworthy, _Cities and Automobile Dependence_ (Aldershot, England: Gower Publishing Company Limited, 1989).
# **Introduction**

Minimum wage systems exist in about 90 percent of the International Labour Organization’s (ILO) 193 member states (Benassi, 2011). These minimum wage regulations aim to protect low-paid workers and typically take one of two broad forms: A single base minimum wage rate for a country or region, or a more complex system of multiple minimum wage rates by sector and/or occupation. In Mauritius, minimum wages have been legislated in the latter form, with specified wage rates for varying occupations across 30 industry-specific remuneration orders. There has, however, been little work on the nature and impact of these stipulated wage rates in the country. In this paper, we thus consider the effects of these minimum wages on employment and hours worked in Mauritius.

The standard textbook theoretical model of minimum wages predicts that in a competitive equilibrium, there is a negative relationship between minimum wages and employment. Early studies on the effect of the minimum wage on employment, dating as far back as the work of Stigler (1946), predicted that in a competitive labor market, the relationship between minimum wages and employment is a negative one. A growing number of later studies however suggested that the relationship between the minimum wage and employment is not necessarily always negative (Katz and Krueger, 1992; Card, 1992 a, b).

Based on the work of Neumark and Wascher (2007) and 17 more recent studies focusing on low- and middle-income (LMI) countries, DPRU (2016) presents the employment effects of minimum wage increases across various developed and developing countries derived from a review of 115 studies. The results include aggregate impacts for all workers coupled with the employment impacts for specific demographic groups, regions and sectors. Overall, employment elasticities in the studies reviewed a range from 2.17 (Katz and Krueger, 1992) to

-4.6 (Abowd, Kramarz, and Margolis, 1999). The mean and median of all the cumulative elasticities are -0.22 and -0.11, respectively, suggesting that on average the impacts of various minimum wage hikes in the countries under review have been marginally negative.

For LMI countries specifically, DPRU (2016) notes 32 statistically significant minimum wageemployment elasticity estimates from 11 countries. The elasticities range from a negative value of -1.3 to a positive value of 1, with a median elasticity of -0.08 and a mean elasticity of -0.11. Empirical studies on the effect of increased minimum wages on employment in LMI countries thus suggest that increases in wages will have either benign or only slightly negative employment effects.

This is the first study to consider the effect of minimum wages on employment in Mauritius specifically. Using data between 2004 and 2014, we find that a 10 percent increase in the minimum wages brings about a slightly positive effect on employment in the covered sector, with an estimated employment elasticity of 0.113. This is within the range of elasticities found in previous studies of employment effects of minimum wages in LMI countries.

2