The Brazilian wage curve: new evidence from the National Household Survey

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E SIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.IZA Discussion Paper No. 8468 September 2014 ABSTRACTThe Brazilian Wage Curve: New Evidence from the National Household Survey This paper reconsiders the Brazilian wage curve using individual data from the National Household Survey at 27 Federative Units over the period 2002 -2009. We find evidence in favor of the Brazilian wage curve with an unemployment elasticity of -0.08 when the lagged unemployment rate is used as an instrument for current unemployment rate. We also find that males in Brazil are significantly more responsive to local unemployment rates (-0.13) than their female counterparts. In fact, we find that the unemployment elasticity for women is statistically insignificant. Applying gender specific unemployment rates, the elasticity for men decreases to -0.09, while the elasticity for women remains statistically insignificant. This paper also finds that the estimates for Brazilian wage curve are completely different for the case of formal and informal workers. JEL Classification:C26, J30, J60

Urban agglomeration, city size, and spatial density effects on wage flexibility: New evidence on the wage curve in Brazil

“…In general, elasticities were lower or even became negative, a sign that the wage curve seemed to better express this specific period. This regression covered the same period studied by Baltagi et al (2017). Even though their results seemed to better confirm the expected shape of the wage curve, the main conclusions were very similar to the ones found here.…”

“…Santolin and Antigo (2009) found that the wage curve seems to be non-dynamic in six metropolitan regions (PNAD data, 1997(PNAD data, -2005, but there is a higher wage flexibility for the whole group of workers (À0.15) than for formal workers (À0.05). More recently, Baltagi et al (2017) controlled for individual observed heterogeneity and state-level fixed effects, with the lagged unemployment rate as an instrument for current unemployment rate (PNAD, 2002(PNAD, -2009. They found that only for the informal sector is the unemployment elasticity significant (À0.251), and compared workers in the formal and informal sectors with similar probabilities of being formal, finding unemployment elasticities of À0.129 and À0.305, respectively.…”

The Wage Curve, Once More with Feeling: Bayesian Model Averaging of Heckit Models

“…For the selection equation (the probability of working), the following variables were considered as potential control covariates: (1) education, (2) age, (3) gender, (4) a dummy variable equal to one for formal businesses, (5) a dummy variable equal to one if the person is indigenous, (6) the number of family members and (7) a dummy variable equal to one if the person is a household head. These variables were selected based on data availability and also following previous studies such as Baltagi et al (2017), who estimated the wage curve for Brazil and considered as control covariates the age of the individual, gender, race, education, the individual's years of tenure at a firm and formality of employment, among other variables available for Brazil. In Bolivia, the level of education and experience have a direct effect on the salary and on the probability of working; also, it is expected that differences in salary may exist for different age categories and between males and females.…”

“…Based on the reviewer's suggestion, we updated the estimation with data from the more recent survey and, thus, this section presents results based on data from the 2017 household survey of Bolivia. In the results for 2006, the estimate of the wage curve elasticity for Bolivia was equal to 7%.3 A similar variable was included byBaltagi et al (2017) as a control covariate, household type, where the response categories were couples without children, couples with children, single mother with children, and…”

Debt, Investment, and Growth in Developing Countries with Segmented Labor Markets

“…But the wage variable is net of taxes and the estimates control for firm size. South Africa, 2000Africa, -2004 Close to zero in the short run and approximately -0.1 in the long run Baltagi et al (2017) Brazil, 2002 Aggregate = -0.107…”