Informal sector, labor markets, and returns to education in Peru

LSM - 32 APRIL 1987 Liv ing StandAarLkS M ea1nnSLzenLen ,i 'ANorking~ P)a,,-(. %\k) -)- P'eru Informal Sector, Labor Mlar-kets, and Returns to Education  LSMS WORKING PAPER SERIES No. 1. Living Standards Surveys in Developing Countries. No. 2. Poverty and Living Standards in Asia: An Overview of the Main Results and Lessons of Selected Household Surveys. No. 3. Measuring Levels of Living in Latin America: An Overview of Main Problems. No. 4. Towards More Effective Measurement of Levels of Living", and "Review of Work of the United Nations Statistical Office (UNSO) Related to Statistics of Levels of Living. No. 5. Conducting Surveys in Developing Countries: Practical Problems and Experience in Brazil, Malaysia, and the Philippines. No. 6. Household Survey Experience in Africa. No. 7. Measurement of Welfare: Theory and Practical Guidelines. No. 8. Employment Data for the Measurement of Living Standards. No. 9. Income and Expenditure Surveys in Developing Countries: Sample Design and Execution. No. 10. Reflections on the LSMS Group Meeting. No. 11. Three Essays on a Sri Lanka Household Survey. No. 12. The ECIEL Study of Household Income and Consumption in Urban Latin America: An Analytical History. No. 13. Nutrition and Health Status Indicators: Suggestions for Surveys of the Standard of Living in Developing Countries. No. 14. Child Schooling and the Measurement of Living Standards. No. 15. Measuring Health as a Component of Living Standards. No. 16. Procedures for Collecting and Analyzing Mortality Data in LSMS. No. 17. The Labor Market and Social Accounting: A Framework of Data Presentation. (List continues on the inside of the back cover)  LSMS Working Paper Number 32 PERU INFORMAL SECTOR, LABOR MARKETS, AND RETURNS TO EDUCATION Ruben M. Surez-Berenguela Development Research Department The World Bank Nashington, D.C. 20433, U.S.A.  This is a working document published informally by the Development Research Department of The World Bank. The World Bank does not accept responsiblity for the views expressed herein, which are those of the authors and should not be aLtributed to the World Bank or to its affiliated organizations. The findings, interpretations, and conclusions are the results of research supported by the Bank; they do not necessarily represent official policy of the Bank. The designations employed, the presentation of materials, and any maps used in this document are solely for the convenience of the reader and do not imply the expression of any opinion whatsoever on the part of the World Bank or its affiliates concerning the legal status of any country, territory, city, area, or of its authorities, or concerning the delimitation of its boundaries, or national affiliation. The LSMS working paper series may be obtained from the Living Standards Measurement Study, Development Research Department, The World Bank, 1818 H Street, N.W., Washington, D.C. 20433, U.S.A. Ruben Suarez-Berenguela is a consultant to the Living Standards Unit of The World Bank. April 1987  LIVING STANDARDS MEASUREMENT STUDY The Living Standards Measurement Study (LSMS) was established by the World Bank in 1980 to explore ways of improving the type and quality of household data collected by Third World statistical offices. Its goal is to foster increased use of household data as a basis for policy decision making. Specifically, the LSMS is working to develop new methods to monitor progress in raising levels of living, to identify the consequences for households of past and proposed government policies, and to improve communications between survey statisticians, analysts, and policy makers. The LSMS Working Paper series was started to disseminate intermediate products from the LSMS. Publications in the series include critical surveys covering different aspects of the LSMS data collection program and reports on improved methodologies for using Living Standards Survey (LSS) data. More recent publications recommend specific survey, questionnaire and data processing designs, and demonstrate the breadth of policy analysis that can be carried out using LSS data.  Acknowledgments I am grateful to Dennis de Tray, Peter Moock, and Luis Riveros for comments on an earlier version of this paper, and to Peter and Ana Maria Arriagada for providing the background material. I benefited, in addition, from comments and suggestions from Constantino Lluch and Morton Stelcner. Any remaining errors and omissions are, of course, my responsibility. I also thank Carmen Martinez for typing the various drafts and Meta de Coquereaumont and Bruce Ross-Larson for editing the manuscript.  ABSTRACT This paper presents a review of the literature about the labor market, the informal sector of the labor market and returns to education in Peru. After summarizing some conceptual and methodological issues related to the use of the formal-informal analytical categories, I present estimates about the importance of informal sector activities and characteristics of workers in informal economic units (IEUs). I point out that both the magnitude of the informal sector and characteristics of informal workers are highly sensitive to the conceptual and operational criteria chosen to differentiate between formal and informal activities. I argue that a clear- cut approach to the underlying formal-informal issues could be obtained by identifying homogenous socioeconomic groups for which classificational critera are directly linked to the available policy instruments. To discuss formal- informal labor markets issues I present data on the composition and employment levels of the Peruvian labor force, labor market structures resulting from alternative segmenting criteria and estimates of the effects of labor legislation on the demand for labor and actual levels of output and employment. Econometric estimates, found in the literature, of the effects of labor laws on the level of output and employment are inconclusive. No serious work has been done in testing market segmentation hypothesis or the role of labor market regulations in affecting the functioning of the labor market. Further empirical work in these areas is needed. Finally, after presenting a summary of the educational composition of the Peruvian labor force, I report findings about the determinants of participation rates and estimates about rates of return to human capital. I also point out some of the issues and areas of research that can be pursued with data from the World Bank-INE Household survey recently completed in Peru.  - i - Informal Sector, Labor Markets, and Returns to Education in Peru Table of Contents Summary ............................................... iv Introduction ...........................................1 The Informal Sector in Peru: An Overview .............. 2 a. Formal and Informal Sectors as Analytical Categories ........ . 2 b. Magnitude of Informal Sector in Peru .............. 6 c. Characteristics of Informal Sector Workers and Informal Economic Units .................... 11 II. Segmenting the Labor Market: Formal and Informal Sectors .23 a. Measuring Labor Supply .23 b. Population, Urbanization, and Labor Force .24 c. Alternative Criteria for Labor Market Segmentation .27 d. The Cost of Regulation .33 III. Education and Returns to Human Capital .39 a. Basic Characteristics, Skills, and Formal Education of the Labor Force .39 b. Determinants of Labor Supply: Participation Rates .43 c. Returns to Education: Education and Income . 47 Appendix .56 References .73  I - ii - List of Tables I.1 Formal and Informal Sectors: Descriptive Features I.2 Informal Sector: Operational definitions I.3 Latin America: Segmentation of the Economically Active Population (EAP), 1950-80 I.4 Peru: Economic Active Population by Sectors: Modern (Formal), and Backward (Informal), around 1972. I.5 Metropolitan Lima: Economically Active Population in Formal and Informal Sectors (around 1982). I.6 Peru: Socioeconomic Characteristics of Formal and Informal Urban EAP, 1970. I.7 Metropolitan Lima: IEU and Informal Workers by Sectors of Economic Activity and Firm Size, 1982. I.8 Metropolitan Lima: IEU, Length of the Working Week by Sectors of Economic Activity, 1982. I.9 Metropolitan Lima: IEU, Capital Labor Ratios and Firm Size, 1982. I.10 Metropolitan Lima: IEU, Distribution of Informal EAP by wage levels 1982. lI.1 Peru: Population in Rural and Urban Areas, National Census 1940, 1961, 1972, 1981. II.2 Peru Labor Force: Employment, Unemployment and Underemployment, Rates in Agricultural and Non-Agricultural activities: 1970, 1975, 1980-83. II.3 Metropolitan Lima: EAP by employment levels, 1979. II.4 Peru: Segmenting Labor Markets, Business Sector criterion: 1972, 1975. II.5 Peru: Segmenting the Labor Market: Occupational Category Criterion: 1981 II.6 Peru Institutional Markets: Labor Force Composition by Business Sector and Wage Setting Schemes. II.7 Peru; Distribution of Urban EAP by Units of Legal Minimum Wage; 1979. III.1 Peru: Population 6 Years Old and More by Levels of Schooling, 1982.  - iii - III.2 Peru: Per Capita Family Income and Female Participation Rates in Urban Areas, 1974-78. III.3 Metropolitan Lima: Income Distribution by Educational Levels, 1968- 69. (Indexes; Average = 1.00). III.4 Metropolitan Lima: Earning Functions: Regression Analysis Using Socioeconomic Characteristics, 1968-60.  - iv - SLUMARY This paper reviews the literature on the size and characteristics of the informal sector in the Peruvian economy, the structure of labor markets and the effects of labor regulations on employment and output, and education as a determinant of social and private rates of return to human capital. The Informal Sector Many conceptual and methodological approaches have been used to define and apply the categories of formal and informal sectors. How these terms are defined and used affects the resultant estimates of the size and economic significance of the informal sector in the Peruvian economy. Estimates of national labor participation rates in the informal sector for 1972 range from 60 to 78 percent of the economically active population (EAP). Estimates for metropolitan Lima for 1980 are between 30 and 60 percent of Lima's EAP. The different conceptual and methdological criteria applied to informal sector activities account for the large range of these estimates. Studies using firm size and employment status/income level criteria to compare informal and formal sector workers found lower incomes and education levels among informal sector workers and a larger proportion of very old, very young, and female workers in the informal sector. No significant differences were found in the concentration of migrant workers or in their status (old or new migrants). A study on the characteristics of informal economic units (IEUs) found that IEUs and informal sector workers were concentrated in small-scale trade and manufacturing activities and that 50 percent of the IEUs have been in operation for more than five years. Although the proportion varies by economic activity, many IEUs operate within households and are not included in national enumeration surveys. IEUs are also characterized by a low capital-labor ratio (US$430 versus US$10,000 in the formal sector). A large proportion of IEUs have no physical capital, and many (30 percent) make use of non-paid family workers. Approximately 40 percent of informal sector workers (including zero-income workers) earn less than the minimum wage (about US$40 a month), and 33 percent earn more than 1.5 times the minimum wage. There are two important implications of these findings: many IEUs (those paying less than the minimum wage) can be classified as "illegal" or "clandestine," and some informal sector workers have higher incomes than some formal sector workers. Because the variety of definitions and operational criteria applied result in broad variations in the identified composition of the EAP in the informal sector, the criteria are not very useful in identifying target groups for policy purposes. Needed are classification criteria for identifying homogenous socieconomic groups, thus permitting a more uniform and consistent examination of the underlying issues of employment, income distribution, market distortion, industrial organization, and technology.  Labor Markets and the Informal Sector Recent literature on employment and labor markets in Peru shows that in the last 15 years the rural sector has remained almost stagnant while urban areas have absorbed more than 90 percent of total population growth and EAP growth. In 1981, almost two-thirds of the population and a slightly lower proportion of the EAP were concentrated in urban areas or urban occupations. The rapid urbanization of the population and the EAP is occurring despite the relatively higher and rising rates of unemployment and underemployment in urban occupations. Both unemployment and underemployment have become essentially urban problems. Substantial disagreement characterizes discussions about conceptual issues related to employment levels and labor market conditions, such as what constitutes an adequate definition of the labor supply and the EAP (should the EAP include the "disguised" unemployed who no longer believe they will find work and have stopped looking?) However formal and informal are defined, there is general agreement that wages and employment in these sectors are determined simultaneously; the existence of segmented or dual labor markets is rejected. The description of labor market structures varies according to the criterion chosen to distinguish between formal and informal sectors. Among the segmenting criteria examined are those based on employment status, income level, business sector, occupational category, and institutional control of the labor market. The employment status criterion classifies all underemployed workers as informal, or approximately 50 percent of the Peruvian EAP in 1983. According to the business sector criterion, all workers outside the corporate (government and private) sector of the economy are considered informal sector workers; using the self-employed and workers in nonregistered firms as proxy indicators, informal sector workers would constitute about 60 percent of the following distribution of EAP. Use of the occupational category criterion results in the EAP: 42 percent formal sector white- and blue-collar workers; 48 percent informal sector self-employed and independent workers, and 10 percent informal sector family and domestic workers. According to the institutional control of the labor market criterion, which is based on officially registered wage contracts, only about 30 percent of the Peruvian EAP was receiving an officially registered wage in 1985. Because of widespread distortions in the Peruvian economy and methodological flows in the studies, results of analysis of the impact of regulations on income and employment levels and the demand for labor at both micro and macro levels are inconclusive. The Instituto Libertad y Democracia (ILD) estimated that without labor regulations, employment in the manufacturing sector would have been approximately 26 percent higher and income 38 percent higher. Two Ministry of Labor studies used regression analysis to explore the relationships between employment and minimum nominal wage, real wage, and income variables. The studies found no significant relationships between these variables. Because the validity of the results for both the ILD and the Ministry of Labor studies is questionable however, further study is required.  - vi - Data on the distribution of the urban EAP by wage levels and by wage earnings as a proportion of total family income also suggest only a limited direct effect of wage policies. In 1980, about 17 percent of the urban EAP received earnings within a range of + 25 percent of the legal minimum wage; 30 percent were below that range and 54 percent above. For large formal sector firms in metropolitan Lima, 12 percent of workers fell in the minimum wage range, with 10 percent below and 77 percent above that range. The limited scope of wage policies is also supported by the findings of an early household survey that approximately one-fourth of urban families had no wage earners and that wage income represented only one-half of total family income. A more recent Ministry of Labor study estimated that about 44 percent of the urban EAP and 80 percent of low-income groups were not covered by minimum wage laws. This problem seems to be more acute in rural areas. Education and Income The results of studies of the effects of education level on labor participation rates and income levels were also varied. Studies show important differences in the composition of the EAP in terms of literacy, primary language (Spanish or other), and educational level. In 1972, the overall illiteracy rate of the EAP was estimated at 18 percent (of which 70 percent were in rural occupations); however, for the noneconomically active population, illiteracy was approximately 40 percent. For about 30 percent of the adult population, mostly those living in rural areas, Spanish is not the primary language. These figures suggest that a large segment of the EAP does not possess the basic skills to engage in formal contractual agreements or to seek employment in labor markets requiring at least minimal reading skills. Data also show, however, that between 1972 and 1982, the average years of schooling of the adult population increased greatly. The effect of this educational heterogeneity of the labor force on income differences between and within urban and rural areas should be explored. Multiple regression analysis found that male and female labor force participation rates were significantly affected by education, marital status, socioeconomic status, and age. Working experience for men and number of children for women were also found to be statistically significant variables. Studies using time series and cross-sectional data found no significant correlation between female participation rates and income of the head of family. Studies on female participation rates for 1974-1978 suggest an inverse relationship between income of male household members and female participation rates. No clear association was shown between female participation rates and different family (male) income categories. An inverse relationship was found betwen the income level of the head of household and the number of working members in the family. Estimates of the social rate of return to education show that between 1950 and 1960 improvements in the education levels of the population have been a minor factor explaining Peru's overall rate of economic growth. But data from the ECIEL household survey of 1968-69 show a positive association between family income and the educational level of the head of household. The survey  - vii - also found that the higher the educational level, the higher the total household income in all categories: wage, independent, and capital income. Estimates of global earning functions confirmed the hypothesis of a statistically significant positive correlation between education and income. Educational level and type of occupation appear to be the main determinants of income. Estimates in 1972 of underemployment rates by level of education, using a minimum income criterion, as such education level found no significant differences in underemployment rates across educational levels. Using the correspondence between educational levels and appropriate occupational categories to define adequate employment levels shows that the underemployment rate of the educated EAP rose from 11 to 19 percent between 1961 and 1972. Conclusion The review of the literature on the informal sector in Peru shows that the concepts of "formal and "informal" have been loosely used to achieve many ends. Discussions of the informal sector have involved issues of technology, employment, income, productivity, industrial organization, taxation, and regulations. Further clouding the use of the term "informal" is the variety of operational criteria applied in measuring the magnitude of the informal sector and identifying informal sector workers. Difference in empirically based estimates are explained mainly by the type of conceptual and operational criteria chosen. Although formal and informal are useful descriptive categories, what is important for analysis is how the underlying economic or social problems can explain differences in income and productivity among social groups. The roles of technology, education, health, unions, corporate hiring practices, government regulations, output market distortions, and small-scale enterprises as employment- and income-generating alternatives must be examined more consistently. The best way to do this is through the identification and examination of homogeneous socioeconomic groups classified according to criteria linked directly to explicitly defined economic issues and policy instruments. Updated data and new studies are needed. Most of what is known has been derived from 10- to 15-year-old surveys conducted in periods of economic stability and relatively rapid growth. The Peruvian economy is now in the worst recessionary period in this century. Data from the World Bank-National Institute of Statistics household survey recently conducted in Peru could be used to clarify some of the unresolved issues about the role of productive household activities, the composition and character of the Peruvian labor force, and the effects of education and other socioeconomic variables on income and productivity.  Introduction This paper reviews the literature on the informal sector, labor markets, and returns to education in Peru. Three main issues are addressed: (1) the conceptual and methodological difficulties in measuring the magnitude of informal sector activities, (2) the use of the categories "formal" and "informal" in examining the structure and functioning of Peruvian labor markets, and (3) the relationships between human capital endowments, income and employment levels, and labor productivity. Section I discusses alternative conceptual and operational criteria for distinguishing between "formal" and "informal" sectors, noting that the choice of criterion frequently seems to be determined by the type of economic problem being studied. Different estimates of the magnitude of informal sector activities in the Peruvian economy result from the variations in definitions, data sources, and method used. Section II discusses the use of the categories formal and informal in analyzing the structure and functioning of labor markets in Peru. It includes data on changes in the composition of the Peruvian labor force in terms of urban and rural occupations and employment levels. The different characteristics of the labor market structures that result from using alternative segmentating criteria (employment status/income level, occupation categories, business sector, and institutional control of labor markets) are summarized, as are findings on the impact of labor regulations on demand for labor and levels of income and employment. Section III summarizes studies on education level as a determinant of labor market participation rates and income level. New studies are suggested on these issues, using data from the World Bank, The Central Bank of Peru and  - 2 - The Peruvian National Institute of Statistics (INE) household survey. - Section IV summarizes the findings and presents research recommendations. I. The Informal Sector in Peru: An Overview Formal and Informal Sectors as Analytical Categories Table I.1 summarizes the features most commonly used to describe formal and informal sectors and activities. Most of these features are nonexclusive, so the point of discussion is what constitutes the essential features of "informal." The categories formal and informal have been used in so many contexts to address so many different issues that there is little agreement on their meaning. Most researchers studying the issues related to the informal sector and its activities complain about the "dualistic" implication of and arbitrariness in defining the formal and informal sectors. Further complications arise in trying to select operational criteria for measuring the size and extent of informal sector activities. Several operational definitions or criteria have been used to identify informal sector workers and informal economic units (IEUs). A firm-size criterion will define IEUs as all enterprises with fewer than an arbitrarily selected number of workers (usually fewer than 9, 5, or 4, depending on the type of economic activity). Workers in these small units would be classified as informal workers. / The Living Standards National Household Survey 1985-86 (Encuesta Nacional de Hogares Sobre Medicion de Niveles de Vida, 1985-86) implemented by the National Institute of Statistics (INE), the World Bank, and the Central Bank of Peru. Henceforth referred to as the Bank-INE Household Survey.  - 3 - Table 1.1: Formal and Informal Sectors: Descriptive Features Formal Sector Informal Sector Market Structure Output Market: - Barriers to entry - No barriers to entry - Oiigopolistic structure - Competitive firms - Brand name, standardized - Nonstandard, nonregistered products products - Protected markets (quotas, - Unprotected markets import licenses, tariffs) Factor Markets: - Restricted access, unionization - Easy access, competitive - Subject to labor legislation - Not in compliance with labor legislation - Access to domestic & foreign credit - No access to credit, self-financed enterprises - Generalized credit transactions - Highly monetized activities Technologies - Imported (modern) technology - Adapted (traditional) technology - Capital intensive - Relatively labor intensive - Imported inputs Ddomestic inputs - Requires formal education - Nonformal learning by doing Industrial - Large, corporate, registered firms - Small, unincorporated, unregistered firms Organization -Specialized firms - Highly diversified units - Large-scale operation - Small-scale operation - Diffuse domestic and foreign ownership - Domestic (family) enterprises - Permanent full-time occupations - Permanent and seasonal part-time activities - Limited direct tax evasion - Generalized tax evasion - Wage earners, formal labor contracts - Self-employed, piecework, nonremunerated family workers - Profit-maximizing firms, whose main - Income-generating firms, whose main goal is goal is capital accumulation labor force "reproduction"  - 4 - An occupational-category criterion considers white- and blue-collar as formal sector workers and independent, self-employed (with some exceptions) domestic and nonpaid family workers as informal sector workers. The employment status/income level criterion uses the legal minimum wage, an arbitrarily defined poverty line, or a combination of income, willingness to work, and length of the working week (underemployment definition) to distinguish between formal and informal workers. A legal criterion or one based on institutional control of labor markets defines as informal those units and workers whose activities do not comply with regulations governing business activities. Table I.2 summarizes the operational criteria most commonly used in estimating the size of the informal sector. Although it is not always explicitly stated, the selection of the operational criterion to define the informal sector is closely related to or even determined by the type of social or economic problems that are emphasized by the researchers. Studies of rural-urban migration will identify the types of labor markets opportunities open to rural migrants, given their education and skill levels. Special emphasis is put on the role of the trade and services sectors and on self-employment or independent occupations as the main source of emplyment opportunities. The firm-size criterion is used to discuss income and productivity differentials between workers in large and small firms and across different sectors of economic activity. This criterion is also used to analyze sector performance, labor mobility, and any complementarity and substitutability that might exist between formal and informal sectors. Legal issues are important in discussing market distortions and the effects of regulation on the behavior of economic agents. From a economic  - 5 - Table 1.2: Operational Criteria Commonly Used in Defining the Informal Sector Criterion Authors Firn Size Fewer than four or five wrkers Vega (1984); Althaus & Morelly (1983) Occupational Status/Incone Level - Below legal minimum vuge PREAIL 1/ (1974); Kafka (1984) - Below povery line Sethuraman (1974); OIT 2/ (1973) - Underemployed workers Occupational Category - Self-employed (own-arcount) Henriquez (1983) (professionals might be excluded) PREALC 1/ (1981); Choy (1976) - 1Tndependent workers (dmnestic servants and nonremunerated family workers) Legal Criteria - Illegal unregistered business de Soto (1984) - Activity and/or econanic status - No wll-defined property rights - No legal contractual agreements - Tax evasion - Nxienumerated enterprises Finn Size, Ozcupational Category Webb (1976, 1977), PREALC (1975a, b, c) Finm Size, Occupational Category, Business Sector Chavez (1983, 1984) Carbonetto (1983), Vega (1984) 1/ PREALC: Programa Regional del Empleo de America Latina y el Caribe (Latin American and Caribean Employment Program). 2/ OIT: Organizaci6n Internacional del Trabajo, (International Labor Office: (ILO).  -6- efficiency perspective, the emphasis is on the effect of excessive regulation on segmenting or distorting output and factor markets. From a fiscal perspective, the issue is foregone tax revenue and moral hazard generated by informal activities. The employment status/income level criterion emphasizes the role of small-scale enterprises in generating adequate employment opportunities. According to this criterion, the issue is the low income and productivity of informal sector workers. From this perspective, the differentiation of "small-scale enterprises" from "family productive units" is crucial in designing employment policies. In most cases, the operational definition is also constrained by the availability of information. Whatever the operational criterion selected, proxy indicators are always used to estimate the size of the informal sector. Magnitude of the Informal Sector in Peru Table I.3 presents PREALC (Latin American and Caribean Employment Program) estimates of the proportion of the economically active population (EAP) in formal and informal occupations in urban and rural areas for a group of fourteen Latin American countries (including Peru) for the years 1950 and 1980. Urban informal sector workers were defined by the occupational category criterion: independent (own-account), self-employed, unpaid family workers, and domestic employees. Wage earners would be classified within the formal sector. Urbanization was rapid during this period; the urban labor force increased from 44 to 64 percent of the total EAP. Growth of urban formal and informal sector employment occurred at the expense of the modern and  traditional sectors of rural areas. Employment in the urban informal sector in these fourteen countries grew from 15.3 to 19.4 percent of the total EAP. A similar increase was observed in formal sector activities: employment increased from 30.5 to 44.9 percent of the total EAP. No major change occurred in the composition of urban employment: in 1950 and 1980, formal sector employment represented about 70 percent of total urban employment and informal sector employment, 30 percent. The same patterns hold for Peru. Table 1.3: Segmentation of the Economically Active Population in Peru and in a Group of Fourteen Latin American Countries, 1950 and 1980 Percentage of the Economically Active Population Urban Agricultural Country Year Formal Informal Total Modern Traditional Total Mining Peru 1950 19.1 16.9 36.0 21.9 39.4 61.3 2.7 1980 35.0 23.8 58.8 8.0 32.0 40.0 1.2 Latin America-/ 1950 30.5 13.7 44.1 22.2 32.9 54.7 1.2 1980 44.9 19.4 64.3 12.3 22.6 34.9 0.8 a/ Average for 14 countries, using the occupational category criterion: see Table A.II.1 for detail. Source: PREALC (1981, Table 1), from Portes and Berton (1984), p. 593. These results suggest that the general perception of the growing importance of informal activities in urban areas might be the result of an absolute increase in the number of workers in marginal occupations in urban  - 8 - areas rather than of a decline in the absorption of labor in formal sector occupations. Both formal and informal sector occupations have contributed almost equally to the absorption of-the rapidly growing urbasn labor force. Few studies of Peru directly address the issue of the informal sector. Most estimates are derived from studies of the performance of the Peruvian economy in terms of development strategies, patterns of growth, and income distribution. The categories formal and informal are less frequently used in these studies than are urban and rural, modern and traditional, large, medium scale and small enterprises, corporate and noncorporate, registered and nonregistered activities, wage and nonwage workers, and small and large productive units. In most cases, the terms "formal" and "informal" were only loosely associated with these other categories. A PREALC study summarized the estimates of the size of formal and informal sector activities that resulted from matching the formal-informal concept with some of these other categories (see Table I.4). According to these estimates, informal sector activities during the mid-1970s ranged from 60 to 78 percent of the total EAP, or between 2.7 million and 3.5 million workers (total EAP in 1972 was about 4.5 million). The lowest estimate, PREALC's 61 percent, is based on the occupational category criterion. Webb's estimate of 78 percent was derived using a combination of firm size and occupational category criteria. The intermediate estimates are Choy's 74 percent, based on a distinction between wage earner and nonwage earner workers (institutional control of the labor market criterion) and Fitzgerald's estimate of 64 percent, based on the business sector criterion--corporate versus noncorporate economic units (large  - 9 - and small enumerated firms are included in the corporate or modern sector of the economy; nonenumerated firms and self-employed workers are considered as informal). Table I.4: Peru: Economically Active Population by Sectors: Modern (Formal) and Traditional (Informal), Around 1972 Webb Fitzgerald Sciara Choy PREALC Sectors (1973) (1976) (1976) (1976) (1976) Modern (Formal) 22 36 35 26 39 Rural 12 11 Urban 24 28 Backward (Informal) 78 64 65 74 61 Rural 45 33 38 34 27 Urban 33 31 27 40 34 Source: From Wendorff (1985) p. 155. Table I.5 presents more recent estimates of informal sector activities in metropolitan Lima. Depending on the operational criterion selected, the portion of the EAP engaged in informal sector activities ranges from 30.7 to 60 percent. The lowest estimates, 30.7 and 32.8, are reported by Corbonetto (1983) and Chavez (1983) and are derived from a combination of occupational category, business sector, and firm size criteria. Both estimates used data from a Ministry of Labor employment survey in metropolitan Lima. Differences are explained by Carbonetto's exclusion of unemployed workers.  - 10 - The highest estimate, 60 percent, is reported by de Soto (1984) and seems to refer to the total Peruvian EAP. According to de Soto, this estimate is derived from official data, "critical" macroeconomic estimates, and informants in the informal sector; de Soto has not yet published a detailed explanation of this methodology. Table 1.5: Metropolitan Lima: Percentage of the Economically Active Population in the Formal and Informal Sectors, around 1982 Household Informal Workers Formal Criterion Source Chavez (1983) a/ 32.8 6.5 60.7 Occupational cate- Ministry of Labor gory, business Employment Survey 1983 b/ sector, and firm size de Soto (1984) c/ 60.0 40.0 Legal status Official surveys, macro- economic evaluations, and informants in the informal sector Kafka (1984) 43.0 57.0 Employment status Ministry of Labor Employment Survey 1983 b/ Wendorff (1984c) 48.0 Occupational category Carbonetto (1983) d/ 30.7 6.0 56.8 Occupational cate- Employment Survey 1981* gory, business Ministry of Labor sector, and firm size a/ Percentage of employed EAP. b/ Periodic survey conducted by the Ministry of Labor: Survey on Employment Levels in Metropolitan Lima (Encuesta de Niveles de Empleo en Lima Metropolitana), Direccion General del Empleo, Lima, Peru. c/ Seems to refer to the total national EAP. d/ Percentage of total EAP, including unemployed. Source: Derived from de Soto (1984); Carbonetto (1983), p. 14-15; Kafka (1983), p. 17.  - 11 - The intermediate estimates are derived using the employment status (underemployment rate) criterion (Kafka 1980) and the occupational category (self-employed and independent) criterion (Wendorff 1984). In early studies, the terms "formal" and "informal" were generally used descriptively in discussing general aspects of income distribution, employment and productivity, and rural-urban migration. Recent discussions emphasize the role and dynamics of the informal sector in the context of the severe depression of the Peruvian economy. The focus is now on the capacity of informal small-scale enterprises to generate stable employment/income opportunities for the rapidly growing urban population, including migrants from rural areas and workers displaced from the formal sector of the economy. The concept of informal sector economic policies is now widely used. Although the terms "formal" and "informal" sectors might be useful as descriptive categories, their usefulness in policymaking is doubtful. Because the variety of definitions and operational criteria result in broad variations in the identified composition of the EAP of the informal sector, it becomes very difficult to identify target groups for policy actions. What is needed to clarify the policy issues involved in for identifying homogeneous socioeconomic groups, a classification criterion that is directly linked to economic issues and policy instruments. This would permit a more uniform and consistent examination of the underlying issues of employment, income distribution, market distortion, industrial organization, and technology. Characteristics of Informal Sector Workers and Informal Economic Units Two groups of studies have analyzed the characteristics of informal sector workers and informal economic units (IEUs). Webb (1976) analyzed the  - 12 - socioeconomic characteristics of formal and informal sector workers in urban areas using data from a 1970 Labor Force National Sample Survey conducted by OTEMO, an office of the Ministry of Labor. Sectoral distinction was based on the firm size and occupational category criteria: self-employed and independent workers and workers in units with fewer than five workers were considered as informal sector workers. The second group of studies was based on the 1982 Ministry of Labor survey on the socioeconomic characteristics of IEUs in metropolitan Lima, using the mixed households-establishments methodology proposed by PREALC. Workers in IEUs were identified using the occupational category, business sector, and firm size criteria. A list of these IEUs was used as a sample to conduct a detailed survey of "informal establishments". Information from this survey was then used to derive some of the characteristics of informal sector workers and IEUs. Most of the analysis of these data was conducted by Chavez and Bernedo (1982), Chavez (1983, 1984), and Corbonetto (1983). -/ Not surprisingly, Webb's analysis and the Ministry of Labor studies resulted in different descriptions of the composition of the informal EAP by occupational category and sector of economic activity. According to Webb, informal sector workers in metropolitan Lima represented 52.9 percent of the labor force or EAP. Informal sector workers were concentrated in small-scale commerce activities (30 percent) and personal services (e.g. waitresses, bakers, laundries) (12 percent). / Henceforth referred to as the Ministry of Labor studies based on "Encuesta a Estratos No Organizados en Lima Metropolitana 1982" Ministerio de Trabajo y Promocion Social, Direccion General del Empleo, Lima, Peru.  - 13 - Results based on the Ministry of Labor survey indicate that informal sector workers represented only 33 percent of the EAP. Wholesale and retail trade constituted 46 percent of the EAP population (versus 30 percent in Webb's estimates); workers producing consumer, capital, and intermediate goods constituted 20 percent (versus 4 percent in Webb's classification). Personal services and construction workers also represented a larger proportion than in Webb's estimates. Domestic workers were included as informal sector workers in Webb's but excluded in the Ministry of Labor definition (see Tables A.I.3 and A.I.4). The disparity of these results shows the sensitivity of the measurement of the size and composition of the informal sector to the operational criterion chosen to define the sector. Webb's interest in income distribution oriented his research toward the identification of the distinctive socioeconomic characteristics of formal and informal sector workers. The Ministry of Labor emphasis on employment issues directed their studies toward an analysis of the features of IEU that affect the IEUs' potential to generate employment opportunities for the growing urban population. Table I.6 summarizes Webb's findings on the socioeconomic characteristic sector workers. He found that the average income of formal sector workers was more than twice as high as that of informal sector workers. However, some informal sector occupations (firm ownership) provide higher incomes than some formal sector occupations (blue-collar). Formal sector white-collar and government employees have the highest average incomes. Domestic and self-employed workers (informal sector) are the lowest income group and represented approximately one-third of urban EAP. Smaller  - 14 - differences existed between formal sector employees and formal sector blue- collar workers. The average years of schooling was 10.3 for the "better paid" white- collar employees of the formal sector and 4.4 and 3.1 years, respectively, for self-employed and domestic workers, the lowest income groups in the informal sector. I/ The percentage of migrant workers in urban formal and informal sectors was very similar, although there was a slightly larger proportion of migrants in informal sector occupations in metropolitan Lima (the largest urban city). This finding suggests the inaccuracy of the perception that migrant workers are concentrated in informal sector activities. Rather, it suggests a hierarchical pattern of migration by city size and supports the hypothesis of the informal sector as an entry point to urban labor markets. There were two other distinctive features of the composition of informal sector workers: the large proportion of women (46 percent versus 18 percent in formal sector occupations) and of young and old workers (approximately one-third of informal sector workers were younger than 20 or older than 50 years of age, versus 17 percent in the formal sector). The composition of the labor force in informal sector activities does not support the hypothesis of the informal sector as a bridge to formal sector occupations. For the young, however, informal sector occupations might be temporary, part-time occupations for students or an apprenticeship period that will facilitate their access to formal sector labor markets. / The average of 10.3 years of schooling corresponds to "some university"; 4.4 and 3.1 years correspond to "some primary" education.  Table 1.6: Peru: Socioeconomic Characteristics of Economically Active Population in the Urban, Formal and Informal Sectors, 1970 Average EAO Migrants EAP Migrants Newly Arrived EAP Women Those Younger Than Income % of Average Years as % of Total % of Immigrants (less than as % 20 or Older Than 50 US$ EAP of Schooling Urban EAP Lima EAP 6 years) as % of EAP of EAP as % of EAP Informal 50 58.7 4.8 63 72 17 46 33 Owners 112 5.4 6.5 58 64 4 17 21 Employees a/ 53 16.5 5.7 65 67 22 22 32 Self-employed b/ 41 30.6 4.4 57 69 11 61 36 Domestic workers 31 6.2 3.1 89 88 50 93 50 Formal 114 41.3 7.0 63 67 12 18 17 White-collar employees 166 9.7 10.3 51 55 9 22 13 Blue-collar employees 68 18.4 5.0 72 78 14 7 20 Government employees 140 13.2 9.9 59 62 10 29 15 a/ Includes manual and nonmanual workers, salesmen, waiters, white-collar workers. b/ Includes nonremunerated manual workers. Source: Webb (1974), in Cotlear (1984), pp. 89-90, 92. Data from OTEMO, Ministry of Labor, National Sample Survey, 1970.  - 16 - Table 1.7 presents Ministry of Labor data on the distribution of IEUs and workers by type of economic activity and unit size in 1982. Trade and manufacturing activities (especially those in textiles, leather, and shoe manufacturing) constituted three-fourths of all IEUs. Transport (including bus, minibuses, truck and taxi drivers) activities (12 percent) and services (11 percent) made up the next largest groups of IEUs. The distribution of sectoral employment was very similar to the sectoral distribution of establishments. The trade sector (e.g., small shops, retailers, peddlers, newsboys) accounted for 52 percent of IEUs and 47 percent of the EAP in the informal sector. The manufacturing sector (including constructon) represented 25 percent of the IEUs and 29 percent of informal sector occupations. The services sector represented 11 percent of employment and transport occupations, 10 percent. Seventy-one percent of IEUs were one-person units, and 96 percent had fewer than three workers. As one would expect, one-person activities predominated in trade and transport sectors. Notice, however, that the distribution of IEUs by size is heavily affected by the sample selection rather than being a sample result. I/ Are informal sector activities transitory? Is the informal sector a temporary learning laboratory for employees before they move into formal sector activities? According to Ministry of Labor survey data, approximately 50 percent of the IEUs have been in operation for more than five years. Only about 5 percent of the firms have been in business for less than one year. In An issue that I have been unable to clarify is that these results were derived from a sample of 4293 IEUs; a similar distribution by size and sectors was reported by Vega (1984) on a preliminary sample of 720 IEUs.  Table 1.7: Metropolitan Lima: Distribution of Informal Economic Units (IEUs) and Informal Sector Workers by Economic Activity and Firm Size, 1982 Firm Size (number of workers) as a Percentage of ISUs by Sector Total No. of Sub- Informal Sector IEUs % sample 1 (2-3) (4-5) 6+ Total EAP % Manufacturing 1073 25.00 980.00 65.00 26.00 6.00 3.00 100.00 1823.00 28.60 Textiles, Shoes Leather, etc. 343 8.00 336.24 Construction 258 6.00 252.18 Furniture 172 4.00 168.12 Others - - - - - - - - 3201.00 50.24 Trade 2232 52.00 2261.0 71.00 26.00 3.00 1551.75 1420.61 Transport 515 12.00 496.0 85.00 14.00 1.00 100.00 623.00 9.77 Services 472 11.00 466.0 64.00 33.00 3.00 100.00 726.00 11.39 Total No. of IEU's 4293 100.00 4203.00 2984.13 1050.75 126.09 42.03 4203.00 No. of Employees in IEU's 71.00 25.00 3.00 1.00 100.00 As % of Total IEU's IEU's Employment -/ _ 2959.0 2662.0 516.0 2.36 - 6374.0 _ _ _ 46.4 41.8 8.1 3.7 100.0 100.0 100.0 a/ Expanded figures from data on composition and average firm size. b/ Reported by Chavez E. Source: Elaborated from Chavez, E. (1983), tables 1-3, pp. 7-9.  - 18 - general, IEUs appear to be well-established economic units. The small proportion of firms (15 percent) with less than two years in business suggests a low business turnover rate (see Table A.I.5); however, the proportion of IEUs that fail or change their line of business is not known. The survey included only successful firms and major occupational activities. The Bank/INE survey may provide information on the turnover rate and part-time nature of these informal sector activities. Data on the distribution of IEUs by place of business show that approximately 50 percent of IEUs operated in a separate shop or in the house (see Table A.I.6). A large part of informal sector economic activity occurs within the household, particularly in manufacturing (40 percent) and services (28 percent). Most of these activities are not included in national accounts or sectorial enumeration surveys. The Bank-INE survey will provide more comprehensive information about these household activities in terms of income (production) and employment levels. Tables I.8-1.10 summarize labor productivity, capital/labor ratios, and income levels in IEUs. Table I.8 shows average length of the work week in IEUs by type of economic activity. Based on this information Chavez (1983) argued that 80 percent of IEUs have work weeks longer than 48 hours, although the data indicate that only 44 percent of IEUs are in this category. The average work week in IEUs is 48.6 hours (compared with the hours for formal- sector firms with more than ten workers) (Chavez, 1983, p. 13). 1/ These data / In estimating the average work week in IEU's, I used as a weight the mean of the range of the closed intervals and an average of 20 and 73 hours for lower and upper ranges respectively.  - 19 - Table 1.8: Metropolitan Lima: Length of the Work Week in Informal Economic Units, by Sectors of Economic Activity, 1982 Length of Work Week (Hours) Sector Up to 24 24 to 35 36 to 48 49 to 60 60 and more Total Manufacturing 8.0 5.0 53.0 16.8 17.2 100.0 Trade 10.0 10.0 32.0 22.0 26.0 100.0 Transport 7.0 7.0 24.0, 31.0 31.0 100.0 Services 10.0 15.0 43.0 20.0 12.0 100.0 Total (%) 10.0 9.0 37.0 21.0 23.0 100.0 (Number) (4198) Source: Chavez (1983), Table-6, p. 14. do not support the hypothesis that longer working weeks compensate for lower productivity in the informal sector (see Chavez, 1983, p. 13; Carbonetto, 1983, p. 59-60). The finding of a shorter than expected work week in informal sector firms may have resulted from the limitation of the survey to those for whom the informal sector activity was the main occupation. Longer work weeks are more characteristic of families than of individual workers; that is, poor families have, on average, more low-income and low-productivity informal sector workers, although each member may work an average work week similar to that in the formal sector. The Bank/INE Household Survey should clarify some of the issues concerning the nature of the household labor supply and family participation decisions of different income groups.  - 20 - Table I.9 shows the distribution of IEUs by capital/labor ratio. The most striking finding is the low capital/labor ratios of IEIJ. The US$430 average capital/labor ratio for IEUs is much lower than the US$10,000 average for formal sector firms. Twenty-seven percent of IEUs used no capital (machinery, tools, etc.), and approximately two-thirds have an average capital/labor ratio of US$30. The lowest capital/labor ratios are in one- person trade activities; the highest are in transport and manufacturing activities (Chavez, 1983, p. 15; Carbonetto, 1983, p. 33). 1/ Table I.9: Metropolitan Lima: Capital/Labor Ratios of Informal Economic Units by Percentage Distrition, 1982 Capital/Labor Ratio % Of EAP by Value (thousand of soles) US$ -/ % of IEUs of Machinery per IEU 0 0 27.0 70.0 1-99 1-160 36.0 4.0 100-500 161-800 20.0 9.1 500-939 801-1600 6.9 5.9 > 1000 > 1600 11.0 nd 3.7 (x = 276)b (x = 430) 100.0 No. of cases (4293) 100.0 a/ US$ approximated using an exchange rate of US$=600 soles. x = weighted average. ,urce: Derived from Ministry of Labor data, DGE, "Encuesta a Estratos, No Organizados en Lima-Metropolitan, 1982," reported in Chavez (1983) pp. 8, 15-16. See Chavez (1983), p. 15. Also Carbonetto (1983), p. 33.  - 21 - The distribution of informal sector workers by income (multiples of the minimum wage) is consistent with the capital/labor ratios. Forty percent of informal sector workers earn less than the legal minimum wage (see Table I.10). Almost 30 percent of informal sector workers received no monetary wages for their services. These findings support two hypotheses about the informal sector: that a group of "clandestine" or "illegal" economic units Table 1.10: Metropolitan Lima: Distributions of Informal Sector Workers by Wage Levels, 1982 Minimum Wage Units % of workers 0 income 29.0 Less than minimum wage 11.0 1 to 1.5 times minimum wage 24.8 1.5 to 2 times minimum wage 16.9 2 to 4 times minimum wage 14.2 More than 4 times minimum wage 2.6 Source: Ministry of Labor, DGE, Encuesta a Estratos No-Organizados, from Chavez (1983), p. 16. exist whose workers earn less than the legal minimum wage and that the participation of family or "nonremunerated workers is an important feature of IEUs. The preceding discussion on the socioeconomic characteristics of informal sector workers and the composition of formal and informal sector economic activity shows the sensitivity of the findings to the conceptual and operational criteria choosen to distinguish between formal and informal sectors. Initially used only as analytical categories to distinguish labor market structures, the concepts of informal and formal sectors are now widely  - 22 - used to discuss income distribution, employment, taxation, industrial performance, industrial organization, and even issues related to strategies of development and growth.  - 23 - II. Segmenting the Labor Market: Formal and Informal Sectors The concepts of formal and informal sectors have also been used in discussing employment levels and the functioning of urban labor markets, particularly the existence of labor markets that are separated by entry restrictions, institutional constraints, or technological conditions. Whatever the criteria chosen to define formal or informal, the general view is that wages and employment in these sectors are determined simultaneously. The idea of market segmentation or dual labor markets is often rejected. The following sections discuss conceptual issues in measuring labor supply and unemployment, underemployment, and present data on changes in the Peruvian population and labor force, the size of informal labor markets as determined by alternative segmenting criteria, and results of studies analyzing the impact of regulations on demand for labor and employment levels. a. Measuring Labor Supply Much of the discussion of employment and labor market problems in Peru deals with conceptual issues about how to measure the labor supply and unemployment and underemployment rates. Traditionally the labor supply has been associated with the actual EAP or the sum of those h"adequately"l employed, the underemployed, and the openly unemployed. More recently, the concept of "potential" EAP has been developed to which a fourth category of "disguised unemployment" or "discouraged workers" has been added. (Discouraged workers are those who want paid employment, but are not actively searching for it  - 24 - because they think they will not find it. 1/ Potential EAP has been used to estimate employment gaps or occupational deficits (Whicht, 1980, p. 46). Related to this issue is whether actual EAP should include family members engaged in productive activities in which women and children, especially in rural areas, are overrepresented. According to Verdera (1983), inclusion in the EAP of "nonmarket" family workers will raise the labor participation rate of the population over six years old from 7.8 to 87.8 percent. A second group of related issues concern: (a) the vagueness of the criteria (of exogenously defined minimum income, willingness to work more, and length of the working week) for distinguishing between "adequately employed" and "underemployed" workers, (b) the slippery distinction between "open" and "disguised" unemployment because of high sensitivity to the time reference period, and (c) whether total EAP (actual or potential) or the wage-earning working population should be used to estimate unemployment and underemployment. A detailed presentation of these arguments is beyond the scope of this; for a discussion of these topics see Flores (1980); Verdera (1983); DGE (1971); Maletta (1970). b. Population, Urbanization, and Labor Force Labor market conditions and urban informal sector activities are affected by the relative performance of agricultural and nonagricultural economic activities and by the dynamics of population growth and migration. / United Nations has suggested that this category be included in census data collection.  - 25 - From 1961 to 1981, the rural population increased from 5.2 to 6.0 million while the urban population almost tripled, from 4.7 to 11.0 million, or from 47 to 65 percent of the total population (see Table II.1). The Peruvian population in 1986 ie estimated at 19.5 million,with an average yearly growth rate of 2.6 percent. The urban population is estimated at 13.9 million, or 69.7 percent of the total population. While the rural population remains almost stagnant at about 6 million people, the urban population is growing at an average yearly rate of 4.4 percent. Table II.1: Peru: Population in Urban and Rural Areas National Census: 1940, 1961, 1972, 1981 (thousands) 1940 1961 1972 1981 Rural Population 4,011 5,209 5,480 5,976 Urban Population 2,197 4,698 8,058 11,029 Total Population 6,208 9,907 13,538 17,005 Economically Active Population 4,500 5,958 Urban (%) (35.3) (47.4) (59.5) (64.9) Source: Prepared by Central Bank of Peru. National Population Census data from Nogues(1984). Changes in the agricultural and nonagricultural labor forces are similar to those in the rural and urban populations. Table II.2 shows the composition of the-labor force by agricultural and nonagricultural occupations. Between 1970 and 1982 the total labor force grew at an average  - 26 - yearly rate of 3.1 percent, of which growth in agricultural (rural) occupations was 1.1 percent, and growth in nonagricultural (urban) occupations was 4.5 percent. Between these years the EAP increased from 4.2 to 6.0 million, with 90 percent of the increase absorbed by nonagricultural urban activities. Table II.2: Peru: Employment, Unemployment, and Underemployment Rates in Agricultural and Nonagricultural Activities, 1970, 1975, 1980-1983 1970 1975 1980 1981 1982a 1983a Population (000) 12,791.0 14,607.0 6,580.0 17,005.0 17,442.0 17,889.0 Labor Force (000) 4,167.3 4,817.5 5,665.2 5,779.0 5,958.0 6,136.7 -- Agriculture 1,879.5 1,955.9 2,052.2 2,072.7 2,097.2 2,118.2 -- Nonagriculture 2,287.8 2,861.6 3,553.0 3,706.3 3,860.8 4,018.5 (% of Total) (54.0 (63.4) (64.1) (64.8) (65,0) Unemployed (%) -- Total 4.7 4.9 7.0 6.8 7.0 8.8 -- Agriculture 0.3 1.3 0.3 0.3 0.3 0.3 -- Nonagriculture 8.3 8.1 10.9 10.4 10.6 13.3 Underemployed (%) -- Total 45.9 42.4 51.2 47.9 49.9 53.9 -- Agriculture 64.3 68.2 68.2 61.a5 60.9 68.2 -- Nonagriculture 30.9 24.8 41.4 40.3 43.9 46.3 a Preliminary; the growth rate between 1982 and 1983 is estimated at 2.6. Source: Ministry of Labor.  - 27 - c. Alternative Criteria for Labor Market Segmentation i) Employment Status/Income Levels Table II.2 also shows that rapid growth in the nonagricultural labor force has occurred amid rising unemployment and underemployment in urban areas. Unemployment rose from 5 percent in the mid-seventies to almost 9 percent in 1983. However, unemployment in agricultural occupations remained steady at about 0.3 percent, while in nonagricultural sectors it rose from 8.1 percent to 13 percent. Similar patterns exist in underemployment. Underemployment rates in rural areas have fluctuated between 60 and 68 percent, while in urban areas the rate rose dramatically from 25-30 percent during the 1970s, to 46 percent in 1983. Underemployment is clearly becoming a severe urban problem. The unemployment and underemployment associated with the concentration of the labor force in urban areas underlies the growing interest in understanding the functioning of labor markets in the urban economy. Using underemployment rates as a proxy indicator for estimating the size of informal labor markets (see Kafka, 1984) indicates that about 68 percent of the labor force in rural areas and aproximately 46 percent of urban workers could be classified as informal sector workers. But because this concept of underemployment (based on willingness to work more, income, and length of work week) does not involve individual decisions about the supply and demand for labor or the functioning of labor markets, it has been argued that what this concept actually captures is a problem of widespread low-wage equilibrium occupatons. Table II.3 presents a breakdown of: employment, underemployment (by time and income), and open unemployment rates. Combining these figures with  - 28 - those on the average length of the work week in formal and informal sectors (46 and 48 hours, respectively) supports the conclusion that underemployment in Peru is essentially a problem of-widespread low-income occupations rather than of short work weeks (see Figueroa, 1974; Iguiniz, 1983). Table II.3 Metropolitan Lima: Economically Active Population by Employment Level, 1979 Employment level Percentage Open Unemployment 6.5 Underemployment 33.0 Underemployment By Income: acute 8.8 average 8.1 mild 12.7 Underemployment By Time 3.1 By Income and/or Time 0.3 Adequately Employed 60.5 Total 100.0 Source: Ministry of Labor, DGE, from INIDE ii) Business Sector Business sector is another proxy for measuring formal and informal sector labor markets. Table II.4 presents estimates on the magnitude of informal sector activities using this criterion (Fitzgerald, 1976; Henriquez, 1983). Fitzgerald distinguishes between the labor force in the legally registered corporate sector and workers in nonenumerated small firms and self- employed (noncorporated) workers; he uses the latter group as a proxy to  - 29 - measure the magnitude of the gap in the informal sector. Henriquez (1983) distinguishes between the labor force working for the central government, state-owned enterprises, and private business firms (formal sector) and self- employed or independent workers (informal sector). Table II.4 Peru: Labor Market Segmentation Using the Business Sector Criterion, 1972, 1975 (in thousands) Henriquez Fitzgerald 1975 % 1972 % Corporate a/ (2,645.0) (54.9) 1,5841.0 (36.0) Central Government Institutions -b 303.0 6.3 State-Owned Enterprises 132.0 2.7 Private Firms 2,210. 0 45.9 Noncorporate -a (2,173.0) (45.1) 2,817.0 (64.0) Self-employed 2,173.0 45.1 Total 4,818.0 100.0 4,401.7 100.0 a) These categories are not presented by Henriquez. b) Excluding the army. Source: Derived from Henriquez (1983), p.ll8; Wendernoff (1983) p. 222. Data Source: INP-APS Study, data from Ministry of Finance, Ministry of Labor and National Institute of Statistics. EAP 1972: INE-Direccion General del Empleo. Proyecciones de la PEA 1972-80, Lima, Peru According to these definitions, informal sector represents between 45 and 65 percent of the labor force. Fitzgerald's estimate is higher because he excludes from the formal sector all noncorporate firms whose labor agreements are outside the scope of the labor legislation and therefore whose wages are established using different guidelines. However, even in the formal sector  - 30 - different regulations apply to wage negotiation, job security, and compulsory and voluntary fringe benefit schemes, all differentially affecting the payroll of firms. There are also various labor regimes within the public sector -- for different government agencies and for state-owned enterprises and parastatals. These differences seem to have affected the ease of labor mobility within the formal sector and between formal and informal sectors; however, there has been little investigation of these issues. iii) Occupational Category The occupational category criterion classifies blue-collar and white- collar workers as formal sector employees and independent, self-employed, family, domestic workers as informal sector workers. Based on this criterion, about 40 percent of the labor force in Peru would be considered as formal sector workers and 60 percent as informal sector (48 percent independent and/or self-employed workers, 6 percent family workers, and 3 percent domestic workers) (See Table II.5). Each of these categories is subject to different regulations affecting labor prices including general labor laws, income tax requirements, and contributions to social security and other types of voluntary and compulsory fringe benefits. For example, independent workers' contributions to social security system are voluntary. These workers lack the fringe benefits of payroll workers, and they are under a different income tax scheme. In the mid-1970s, domestic workers were included under laws governing the minimum wage, job security, and social security; however, it is estimated that very few domestic workers have actually been affected by these changes. Most of them work under nonformal labor contracts, without social security or  - 31 - other types of benefits. No studies have examined the effects of regulation on the efficiency of the various segments of the labor markets. Table 11.5: PERU: Economically Active Population by Occupational Category, 1981 Occupational Total Category (000) Percentage White-collar 1,092.3 18.8 Blue-collar 1,329.3 22.9 Independent 2,797.9 48.3 Owner 21.7 0.5 Family workers 350.8 6.1 Domestic worker 192.5 3.4 Total 5,792.5 100.0 Source: INIDE and Estudio sobre Puno. iv) Institutional Control of Labor Markets Another segmenting criterion based on the institutional arrangement of labor markets limits the formal sector workers to those covered by officially registered wage contracts (Table II.6). Table II.6 further distinguishes those belonging to trade unions and those whose wages were determined through "registered" collective negotiations; that is, with Ministry of Labor arbitration. Across sectors of economic activity, I distinguish between those workers engaged in officially registered wage contracts and within this category those belonging to trade unions, and of those for which wage negotiations were settled through "registered" collective negotiations; i.e., with the arbitration of the Ministry of Labor.  - 32 - Using Ministry of Labor data, Wicht (1980) estimated that from 1974 to 1980, the proportion of the labor force working under some form of wage contract increased from 47 percent to 49 percent. This means that more than 50 percent of the EAP is outside the scope of labor policies, especially minimum wage policies. Table II.6 shows that in 1985 only 1.8 million workers (30 percent of a total working population of 6.3 million), received an officially registered wage or income. Approximately 40 percent of these workers were in the public sector. Whereas all employees in the public sector might be classified as formal workers using this criterion, only the 25- percent of private sector workers receive an officially registered wage (in general above the legal minimum wage) would be considered formal sector workers. Although officially registered wage workers are protected by the general labor laws, wage negotiation procedures vary accross different sectors. In the private sector many factors affect wage adjustments. For some workers, indexation is used as a regular measure so the basic issue becomes the frequency of adjustment in periods of high inflation. For others, such as some textile workers, wage adjustments are linked to productivity (piece-work). Average company income and the spread between the highest and lowest paid workers are other criteria often applied in determining wages in some state-owned enterprises. Given the variety of methods for establishing wages, the importance of the minimum wage in regulating labor markets is probably less than has been generally attributed to it in the literature on labor markets.  - 33 - The next section discusses the effects of wage-labor tenure policies and other regulations on the levels of income and employment and on the functioning of the labor markets. Table 11.6: Labor Force Composition by Type of Wage-Setting Scheme and Business Sector (thousands) 1985 1975 Receiving 1983 Registered Business Number of Officially Belonging to For Collective Sector Workers a/ Registered Wage b/ Trade Unions Bargaining . _________________________ (No.) (%) Public Sector Central Government 303.0 State-Owned Enterprises 132.0 756.0 (40.0) Armed Forces _ 350.00 Private Sector (2,210.0) 1,134.0 (60.0) Self-Employed & Independent 2,173.0 _ _ Total 4,818.0 1,890.0 (100.0) 1,050.0 350.0 (% of Total) (30.0) (16.9) (5.6) EAP, base 4,818.0 6,300.0 6,200.0 6,200.0 6,200.0 a/ Excluding the army. b/ Including the army. Source: Derived from Henriquez (1983), p. 118; Analisis Laboral (1985), p. 101-ff; (data on registered wage and trade union workers are figures reported by Yepes and Bernerdo in a newspaper clip: el Comercio (1984). d. The Cost of Regulation The costs of regulation can affect the prices of output, factors of production, and those related to organizational aspects of the firms. The overall effect of each of these costs depends on the output level and relative importance of the corresponding factors of production in the firm's cost structure.  - 34 - Efforts to analyze the adverse effects on the labor market of government regulations at both micro- and macro-levels are affected by widespread distortions in the Peruvian economy that make it difficult to determine the net effect of various distorting counter forces. While government regulations such as minimum wage laws and compulsory fringe benefits and other types of payroll taxes increase the costs of production, other tax benefits, government services, and government subsidy of utilities, food, housing, transport, and foreign exchange work in an opposite direction. The emphasis in these analyses has been on the adverse effect of labor and business registration on the level of production and demand for labor. De Soto (ILD) simulated the actual registration process required for setting up a small manufacturing firm of around US$5,000. The cost of licensing, registering, and obtaining clearance from central, sectoral, and municipal government agencies was about US$271. The largest "cost" (82 percent of the registration cost) was the interest foregone (US$1400) on the idle capital invested in the firm while waiting for the registration process to be completed (289 days). Fifty percent of the registration period was assumed to be time during which the firm could have been operating. ILD also estimated the extra cost of complying with government regulations in running a firm (that is, the cost of operating within the formal sector). For a firm with annual gross production of US$12,000, and a wage bill of US$2,380 (five workers at US$40 monthly each), the extra costs attributable to labor laws (minimum wage, social security, job security, fringe benefits) were estimated at US$703. Income and municipal taxes added another US$32, and other "bureaucratic costs" were estimated at US$60. Because formally registered firms are not eligible for the subsidized utility  - 35 - rates available to domestic users, the difference in price (US$211) was also added to the cost. For this small firm, after-tax yearly profits were estimated at US$3,600. The extra operational costs for a formal sector firm was US$1,006 dollars, or approximately 8 percent of the total cost of production. The ILD argues that these extra costs for establishing and operating a firm are the major reason for the existence of the small manufacturing industries in the informal sector. The ILD studies, however, are flawed both on methodological and in their selection of figures on capital/labor ratios, productivity, and profitability of informal sector firms, which differ significantly from those in other studies (see Section I.d). Macro-level studies have analyzed the effects of minimum wage and labor tenure regulations on income and employment. Table II.7 shows the distribution of the urban EAP by three wage categories related to the minimum wage: