scholarly journals Omitted-variable bias in demand-regime estimations: the role of household credit and wage inequality in Brazil

2021 ◽  
Vol 9 (3) ◽  
pp. 368-393
Author(s):  
Julia Burle ◽  
Laura Carvalho
Keyword(s):  
Wage Inequality ◽  
Statistical Significance ◽  
Commodity Prices ◽  
Relative Effect ◽  
Wage Distribution ◽  
Empirical Literature ◽  
Wage Share ◽  
Omitted Variable Bias ◽  
Household Credit ◽  
Variable Bias

In the Kaleckian theoretical framework, an economy's demand regime is characterized as either wage-led or profit-led depending on the relative effect of an increase in the wage share on consumption, investment, and net exports. Based on this framework, a vast empirical literature has focused on estimating demand regimes in numerous countries. Although they contribute to a better understanding of the relationship between distribution and demand in different economies and time periods, they also face various critiques on theoretical and methodological grounds. This paper aims to address one dimension of these critiques by investigating a potential omitted-variable bias in the estimated relationship between distribution and demand in the Brazilian economy between 1997 and 2014. Our results suggest that when controlling for some of the relevant factors in Brazil's inclusive growth experience of the early twenty-first century, namely wage inequality, commodity prices, and household credit, the empirical characterization of the Brazilian demand regime as profit-led loses its statistical significance. Also, the demand-regime definition was found to be most sensitive to intra-wage distribution, confirming previous findings in the Kaleckian empirical literature for the Brazilian case.

scholarly journals Performance pay and enterprise productivity: the details matter

2018 ◽  
Vol 1 (1) ◽  
pp. 61-73 ◽  
Author(s):  
Takao Kato ◽  
Antti Kauhanen
Keyword(s):  
Performance Measure ◽  
Empirical Literature ◽  
Cross Sectional ◽  
Productivity Effect ◽  
Content Type ◽  
Omitted Variable Bias ◽  
Individual Incentive ◽  
Productivity Gain ◽  
Variable Bias ◽  
Power Of Incentives

Purpose The purpose of this paper is to provide novel and rigorous evidence on the productivity effect of varying attributes of performance-related pay (PRP) and shows that the details of PRP indeed matter. Design/methodology/approach In doing so, the authors exploit the panel nature of the Finnish Linked Employer–Employee Data on the details of PRP. Findings The authors first establish that the omitted variable bias is serious, which makes the cross-sectional estimates on the productivity effect of the details of PRP biased upward substantially. Relying on the fixed effect estimates that account for such bias, the authors find: (first, group incentive PRP is more potent in boosting enterprise productivity than individual incentive PRP; second, group incentive PRP with profitability as a performance measure is especially powerful in raising firm productivity; third, when a narrow measure (such as cost reduction) is already used, adding another narrow measure (such as quality improvement) yields no additional productivity gain; and fourth, PRP with greater power of incentives (the share of PRP in total compensation) results in greater productivity gains, and returns to power of incentives diminishes very slowly. Originality/value Much of the empirical literature on PRP focuses on a question of whether the firm can increase firm performance in general and enterprise productivity in particular by introducing PRP and if so, how much. However, not all PRP programs are created equal and PRP programs vary significantly in a variety of attributes. This paper provides novel and rigorous evidence on the productivity effect of varying attributes of PRP and shows that the details of PRP indeed matter.

Econometric Analysis of Returns to Education of Rural and Urban Labour Markets Workers in Tamil Nadu

2020 ◽  
pp. 336-344
Keyword(s):  
Wage Inequality ◽  
Tamil Nadu ◽  
Returns To Education ◽  
Labour Markets ◽  
Wage Distribution ◽  
Rural Market ◽  
Rural And Urban ◽  
Rate Of Returns ◽  
Education Groups ◽  
Quantile Regression Method

The objective of this study was to empirically evaluate the returns to education of rural and urban labour markets workers in Tamil Nadu using the IHDS data with appropriate Econometric models. First, the present study estimated the earning functions of the rural and urban market's workers by OLS technique and standard Mincerian earning functions. Secondly, the quantile regression method was also used to examine the evolution of wage inequality. The findings of the study showed that the effects of education and experience on the log of hourly wages were positive, and these coefficients were statistically significant. The returns to education increased with the level of education and differed among the workers of rural and urban labour markets. The results showed that the rates of returns to primary, middle and higher secondary were higher in the urban market, whereas those of secondary and graduation were higher in the rural market. The study revealed that the effect of education was not the same across the rural and urban wage distribution. The rate of returns differed considerably within education groups across different quantiles of the wage distribution.

scholarly journals The impact of a minimum wage change on the distribution of wages and household income

2020 ◽  
Author(s):  
Paul Redmond ◽  
Karina Doorley ◽  
Seamus McGuinness
Keyword(s):  
Income Distribution ◽  
Minimum Wage ◽  
Wage Inequality ◽  
Household Income ◽  
Spillover Effects ◽  
Wage Distribution ◽  
Wage Increase ◽  
Minimum Wage Increase ◽  
Wage Change ◽  
The Impact

Abstract We use distribution regression analysis to study the impact of a 6% increase in the Irish minimum wage on the distribution of hourly wages and household income. Wage inequality, measured by the ratio of wages in the 90th and 10th percentiles and the 75th and 25th percentiles, decreased by approximately 8 and 4%, respectively. The results point towards wage spillover effects up to the 30th percentile of the wage distribution. We show that minimum wage workers are spread throughout the household income distribution and are often located in high-income households. Therefore, while we observe strong effects on the wage distribution, the impact of a minimum wage increase on the household income distribution is quite limited.

scholarly journals Internal devaluation and economic inequality in Portugal: challenges to industrial relations in times of crisis and recovery

2021 ◽  
pp. 102425892199500
Author(s):  
Maria da Paz Campos Lima ◽  
Diogo Martins ◽  
Ana Cristina Costa ◽  
António Velez
Keyword(s):  
Collective Bargaining ◽  
Wage Inequality ◽  
Economic Inequality ◽  
Industrial Relations ◽  
National Level ◽  
Wage Share ◽  
Recovery Dynamics ◽  
Wage Increases ◽  
The Impact ◽  
Wage Outcomes

Internal devaluation policies imposed in southern European countries since 2010 have weakened labour market institutions and intensified wage inequality and the falling wage share. The debate in the wake of the financial and economic crisis raised concerns about slow wage growth and persistent economic inequality. This article attempts to shed light on this debate, scrutinising the case of Portugal in the period 2010–2017. Mapping the broad developments at the national level, the article examines four sectors, looking in particular at the impact of minimum wages and collective bargaining on wage trends vis-à-vis wage inequality and wage share trajectories. We conclude that both minimum wage increases and the slight recovery of collective bargaining had a positive effect on wage outcomes and were important in reducing wage inequality. The extent of this reduction was limited, however, by uneven sectoral recovery dynamics and the persistent effects of precarious work, combined with critical liberalisation reforms.

scholarly journals Trends in Wage Inequality in the Netherlands

De Economist ◽  
2021 ◽  
Author(s):  
Colja Schneck
Keyword(s):  
Labor Market ◽  
The Netherlands ◽  
Wage Inequality ◽  
Wage Distribution ◽  
Labor Market Institutions ◽  
Market Institutions ◽  
Educational Degree ◽  
Over Time

AbstractIn this paper I analyze changes in the wage distribution in the Netherlands. I use a matched employer-employee dataset that covers the population of employees. Wage inequality increases over the period of 2001–2016. Changes in between-firm wage components are responsible for nearly the entire increase. Increases in the variance of workers’ skills and increases in worker sorting and worker segregation explain the majority of the rise in the variance of wages. These changes are accompanied by a pattern where variation in educational degree and firm average wages become more correlated over time. Finally, it is suggested that labor market institutions in the Netherlands play an important role in mediating overall wage inequality.

scholarly journals Omitted Variable Bias in GLMs of Neural Spiking Activity

2018 ◽  
Vol 30 (12) ◽  
pp. 3227-3258 ◽  
Author(s):  
Ian H. Stevenson
Keyword(s):  
Neural Activity ◽  
Single Neuron ◽  
Linear Models ◽  
Theory And Practice ◽  
Parameter Estimates ◽  
Omitted Variables ◽  
History Effects ◽  
Omitted Variable Bias ◽  
Wide Range ◽  
Variable Bias

Generalized linear models (GLMs) have a wide range of applications in systems neuroscience describing the encoding of stimulus and behavioral variables, as well as the dynamics of single neurons. However, in any given experiment, many variables that have an impact on neural activity are not observed or not modeled. Here we demonstrate, in both theory and practice, how these omitted variables can result in biased parameter estimates for the effects that are included. In three case studies, we estimate tuning functions for common experiments in motor cortex, hippocampus, and visual cortex. We find that including traditionally omitted variables changes estimates of the original parameters and that modulation originally attributed to one variable is reduced after new variables are included. In GLMs describing single-neuron dynamics, we then demonstrate how postspike history effects can also be biased by omitted variables. Here we find that omitted variable bias can lead to mistaken conclusions about the stability of single-neuron firing. Omitted variable bias can appear in any model with confounders—where omitted variables modulate neural activity and the effects of the omitted variables covary with the included effects. Understanding how and to what extent omitted variable bias affects parameter estimates is likely to be important for interpreting the parameters and predictions of many neural encoding models.

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