Unexplained Part Research Articles

Can Education Reduce or Mitigate Discrimination? An Investigation on Earnings of PhD Recipients in the US

<p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">Spence’s signaling model (Spence, 1973) suggests that education can signal workers’ unobserved ability to employers thereby mitigating discrimination. There have been several studies concerning education’s impact on labor market discrimination against minority or disadvantaged groups. Our approach in this inquiry is unique in that we utilize the data of PhD recipients, a group of people with the highest education attainment, to test Spence’s theory. Another novelty of this paper is that in addition to examining possible discrimination against women and foreign-born, as has been done in previous studies, we further explore possible discrimination against the physically challenged individuals. Our baseline results show conflicting results that Ph.D. education can reduce discrimination against disability and foreign-born but not against gender. Further analysis by the Blinder-Oaxaca Decomposition shows that the wage gaps of gender and disability come more from the unobserved part than the explained part, while the foreign-born wage gap come more from the observable human capital differences. Since prejudice is an unobserved factor and we know that the disadvantaged groups are likely to suffer from prejudice (Oaxaca, 1973; Blinder, 1973; Montes-Rojas et al., 2017; Deshpande and Khanna, 2018), we conjecture that prejudice might be attributable to the unexplained part of the wage gaps. Furthermore, prejudice might be deeply rooted in one’s mind, thus difficult to remove even with the influence of education. Hence, our results reveal that it would be hard for Ph.D. education to eradicate the discrimination against gender and disability, but not against foreign-born.</span></p>

Gender pay gap in the Czech Republic: focused on management

The existence of a gender pay gap is well known. This paper focuses on the issue of the pay gap in managerial positions. It aims to examine the development of the gender pay gap in managerial positions in the Czech Republic and to identify the unexplained part of the gender pay gap, which could be an indication of gender pay discrimination. To estimate the unexplained part of the gender pay gap data from the European Union Statistics on Income and Living Conditions (EU-SILC) was used and the Oaxaca-Blinder decomposition was applied. The results show that in the period 2005-2019, the average raw gender pay gap in management was 0.22 and the unexplained part was 0.13, using the Neumark’s variant of the decomposition. Differences in women’s and men’s personal and firm characteristics could explain about one-third of the pay gap. The results also suggest that the situation has not changed much over the period considered and that the unexplained part of the gender pay gap has decreased only slightly between 2005 and 2019. Thus, reducing the gender pay gap remains a major challenge for both economic policy makers and companies in promoting corporate social responsibility policies.

The gender pay gap in the Visegrad Groups

PurposeThe gender pay gap is a well-documented phenomenon in labor economics. Based on the 2018 Structure of Earnings Survey (SES), the authors estimate the impact of observable characteristics on the gender pay gap in Visegrad Group countries and provide policy recommendations on reducing the gender pay gap.Design/methodology/approachThe Oaxaca-Blinder decomposition is applied to estimate the values of explained and unexplained parts of the gender pay gap. Gender pay gap in unadjusted as well as adjusted form is estimated using data on the individual level.FindingsThe results show that unadjusted gender pay gap proved to be stable at more than 20%. The authors found evidence that education widens gender pay gap implying that men have higher returns on education than women. Tertiary education proved to be the highest contributor to widening of gender pay gap. Results also show that there is strong sectoral and occupational segregation. Decomposition proved that only 21% of gender pay gap could be explained by observed characteristics. The unexplained part showed negative values, meaning women would have higher wages, if they had characteristics like men.Research limitations/implicationsStructure of Earnings Survey data are published every four years; therefore the authors’ dataset from year 2018 might not completely reflect today's reality. Unfortunately, newer data are note available yet. Second, Structure of Earning Survey data do not contain variables representing social factors of respondents like marital status, number of children or labour market absence due to birth or childcare. Third, data used for this study do not contain firms that have less than 10 employees; therefore, considerable portion of the labour market is omitted.Originality/valueResults of this study will help policymakers understand the roots and causes of the gender pay gap in Visegrad Group countries but addressing this issue requires further research.

Western European emission estimates of CFC-11, CFC-12 and CCl4 derived from atmospheric measurements from 2008 to 2021

Abstract. Production and consumption of CFC-11 (trichlorofluoromethane, CCl3F), CFC-12 (dichlorodifluoromethane, CCl2F2) and CCl4 (carbon tetrachloride) are controlled under the regulations of the Montreal Protocol and have been phased out globally since 2010. Only CCl4 is still widely produced as a chemical feedstock. After 2010, emissions of CFC-11 and CFC-12 should therefore mostly originate from existing banks (e.g. from foams, mobile air conditioning units and refrigerators); however evidence has emerged of an increase in global emissions of CFC-11 in the last decade, some of which has not been fully accounted for. The motivation for this work was to assess the emissions of CFC-11, CFC-12 and CCl4 from western Europe. All countries in this region have been subject to the controls of the Montreal Protocol since the late 1980s and, as non-Article 5 Parties, have been prohibited from producing CFCs and CCl4 for dispersive use since 1996. Four different inverse modelling systems are used to estimate emissions of these gases from 2008 to 2021 using data from four atmospheric measurement stations: Mace Head (Ireland), Jungfraujoch (Switzerland), Monte Cimone (Italy) and Tacolneston (UK). The average of the four model studies found that western European emissions of CFC-11, CFC-12 and CCl4 between 2008 and 2021 were declining at 3.5 % yr−1 (2.7 % yr−1–4.8 % yr−1), 7.7 % yr−1 (6.3 % yr−1–8.0 % yr−1) and 4.4 % yr−1 (2.6 % yr−1–6.4 % yr−1), respectively. Even though the emissions were declining throughout the period, the area including northern France, Belgium, the Netherlands and Luxembourg showed consistently elevated emissions of CFC-11 compared with the surrounding regions. Emissions of CFC-12 were slightly elevated in the same region. CCl4 emissions were the highest in the south of France. France had the highest emissions of all three gases over the period 2008–2021. Emissions from western Europe (2008–2021) were on average 2.4 ± 0.4 Gg (CFC-11), 1.3 ± 0.3 Gg (CFC-12) and 0.9 ± 0.2 Gg (CCl4). Our estimated decline in emissions of CFC-11 is consistent with a western European bank release rate of 3.4 % (2.6 %–4.5 %). This study concludes that emissions of CFC-11, CFC-12 and CCl4 have all declined from 2008 to 2021 in western Europe. Therefore, no evidence is found that western European emissions contributed to the unexplained part of the global increase in atmospheric concentrations of CFC-11 observed in the last decade.

Transdiagnostic factors predicting the 2-year disability outcome in patients with anxiety and depressive disorders

BackgroundBoth anxiety and depressive disorders are associated with significant long-term disability. Since experienced impairments vary between patients independent of diagnosis and disease severity, identifying transdiagnostic factors that predict the course of disability may provide new targets to reduce disability. This study examines transdiagnostic factors predicting the 2-year disability outcome in patients with anxiety and/or depressive disorders (ADD), focusing on potentially malleable factors.MethodsSix hundred fifteen participants with a current diagnosis of ADD from the Netherlands Study of Depression and Anxiety (NESDA) were included. Disability was assessed at baseline and after 2 years of follow-up, using the 32-item WHODAS II questionnaire. Transdiagnostic predictors of 2-year disability outcome were identified using linear regression analysis.ResultsIn univariable analyses, transdiagnostic factors associated with the 2-year disability outcome were locus of control (standardized β = -0.116, p = 0.011), extraversion (standardized β = -0.123 p = 0.004) and experiential avoidance (standardized β = 0.139, p = 0.001). In multivariable analysis, extraversion had a unique predictive value (standardized β = -0.143 p = 0.003). A combination of sociodemographic, clinical and transdiagnostic variables resulted in an explained variance (R2) of 0.090). The explained variance of a combination of transdiagnostic factors was 0.050.ConclusionThe studied transdiagnostic variables explain a small but unique part of variability in the 2-year disability outcome. Extraversion is the only malleable transdiagnostic factor predictive of the course of disability independent of other variables. Due to the small contribution to the variance in the disability outcome, the clinical relevance of targeting extraversion seems limited. However, its predictive value is comparable to that of accepted disease severity measures, supporting the importance of looking beyond using disease severity measures as predictors. Furthermore, studies including extraversion in combination with other transdiagnostic and environmental factors may elucidate the unexplained part of variability of the course of disability in patients with ADD.

<p>The Multifaceted Dimensions of the Wage Gap in Ecuador</p>

This study examines the determinants of wage gap differences based on gender, ethnicity, and area of residence (urban vs. rural) in Ecuador for the years 2007 and 2017. By combining the Oaxaca-Blinder decomposition with unconditional quantile regression, we identify the extent to which the wage gap between two groups is due to characteristics (endowment) or unexplained factors at various points of the distribution, i.e. for low-, medium- and high-income workers. Results show that, on average, the gender and ethnic wage gap in 2017 increased slightly with respect to 2007, while the area wage gaps remained stable. However, progresses have mainly benefited those at the top of the income distribution, while disparities have widened for those at the bottom. As regards endowment effects, education mainly explains area and ethnicity wage gaps, while there is an important unexplained part that contributes more to gender wage differentials.

The Effects of Marital Status on Rational Modern Consumer Behaviors in the Framework of Behavioral Economics: The Case of Kocaeli

İktisat biliminin inceleme konusu olan tüketici davranışları üzerinde psikolojik faktörlerin etkili olduğu görülmektedir. Tüketicilerin satın alma karar süreçlerine etki eden bu psikolojik faktörler iktisat bilimi içinde yeni bir alanın oluşmasını sağlamıştır. İktisat-psikoloji ilişkisi sosyal bilim dallarının birlikte ele alınarak incelenmesine zemin hazırlamıştır. Bu yeni perspektif davranışsal iktisat olarak kavramsallaştırılmıştır. Davranışsal iktisat, iktisadi hayatta bireylerin davranışlarının anlamlandırılmasına ve açıklanamayan kısımların gerçek sebepleriyle birlikte ortaya konmasını sağlamaktadır. Amaç - Kocaeli’de yaşamını sürdüren evli ve bekâr tüketicilerin tüketim eğilimlerinin açıklanması amaçlanmaktadır. Yöntem/Metodoloji/Dizayn- Bu çalışmada bir anket uygulaması yapılmıştır. Anket soruları literatür incelemeleri ile evli ve bekâr tüketicilerin tüketim alışkanlıkları dikkate alınarak hazırlanmıştır. Sonuçlar- Tüketici davranışlarında psikolojik faktörlerin etkisinin araştırılmasıyla yeni bir alan olarak doğan davranışsal iktisat, ana akım iktisadi anlayışın katı duruşunun esnek bir hal almasını sağlamıştır. Tüketicilerin tüketim kararlarını verirken medeni durumları bu kararlar üzerinde etkili olmaktadır. Bekâr tüketiciler bir tüketim eğilimine rasyonel tavır sergilerken evli tüketicilerin aynı tüketim eğilimine farklı bir tavır sergilediği görülmektedir. Tam aksi bir şekilde bekâr tüketiciler bir tüketim kararında irrasyonel davranırken evli tüketicilerin rasyonel davranış sergileyebileceği tespit edilmektedir.

GVC involvement and the gender wage gap: Micro-evidence on European countries

We examine linkages between involvement in global value chains (GVCs) and gender wage inequalities. We use merged data from Structure of Earnings Survey and the World Input Output Database covering 18 European countries. We employ information on employees’ personal and company characteristics and a sectoral involvement in GVCs. In general, the wages of workers from sectors more involved in GVCs are lower. However, the relationship between GVC and wages differs according to gender: women are more affected by the negative impact of greater trade involvement than men. There is some education/skill heterogeneity: workers with a medium level of education and medium skills are most affected. Our results show different patterns for concentrated and competitive industries: a greater female wage penalty due to GVC intensification is observed in less competitive sectors. Finally, using the RIF decomposition we differentiate GWG into explained and unexplained part with GVC being responsible for the latter.

Contribution of sociodemographic determinants in explaining the nutritional gap between the richest-poorest women of Bangladesh: A decomposition approach.

Malnutrition among women disproportionately exists across socioeconomic classes of Bangladesh. According to our knowledge, studies which attempted to identify determinants and their contributions to explain BMI-based nutritional gap between the poorest and the richest categories of Wealth Index are still scarce. To identify the nutritional gap of women between the richest-poorest classes in Bangladesh, and to determine how much of this gap are attributed to differences in predictors and differences in coefficients. Reproductive-aged (15-49 years) women of Bangladesh. We utilized the latest round (2017-2018) data of the Bangladesh Demographic and Health Survey (BDHS). Body mass index (BMI) has been used to measure the nutritional status of women. The kernel density was used to visualize the nutritional gap. The Oaxaca-Blinder (OB) decomposition method was used to ascertain influential determinants and their contributions to the existing gap between the richest-poorest classes of women. We analyzed the data of 18,682 reproductive-aged women. There was a significant mean BMI gap of 4.1 unit (95% CI: 3.90-4.35) between the poorest-richest (25.6 vs 21.5) women. The overall prevalence of underweight, overweight and obese were 11.8%, 33.8% and 15.4%, respectively. The richest women were less underweight (7.5%) but more overweight (23.7%) and obese (42.2%). In contrast, the poorest women were more underweight (32.0%) but less overweight (13.9%) and obese (7.0%). According to results of OB decomposition method, all predictors combinedly can explain 1.62 units (95% CI: 1.31-1.93) of the total mean BMI gap (equivalent to 40%). Some of the major predictors were women years of education (0.45 units, 95% CI: 0.27-0.64), spouse years of education (0.16 units, 95% CI: -0.02-0.34), current working status (0.17 units, 95% CI: 0.10-0.34), access to Television (0.50 units, 95% CI: 0.28-0.72), and place of residence (0.37 units, 95% CI: 0.22-0.72). The unexplained part of the poorest-richest gap was 2.51 units (95% CI: 2.13-2.89), which means that this particular gap will remain unchanged even though the mean difference of the predictors was diminished. A large part of the nutritional gap (approximately 60%) between the poorest and richest classes of women are found to be unchanged by the predictors of the study. Therefore, further predictors should be identified to minimize such gap. Moreover, policy makers and relevant stakeholders should implement feasible strategies to minimize the existing differences in the major predictors.

Social norms and the gender gap in labor force participation: Evidence from Turkey

ABSTRACT We use a novel two-step empirical strategy to examine the relationship between social norms and the gender gap in labour force participation (LFP) across provinces of Turkey. In the first step, we identify the unexplained part of the gender gap in LFP that remains after accounting for differences in observed characteristics between women and men for each province by implementing a decomposition method. In the second step, we investigate the role of social norms in explaining cross-province variation in the unexplained part. The results reveal that more egalitarian gender role attitudes, smaller gender gap in tertiary education, lower fertility and consanguineous marriage rates, and lower level of religiosity significantly predict a smaller unexplained part of the gender gap in LFP favouring males.

The returns to school-quality-adjusted education of immigrants in Germany

This paper explores the role of school quality in immigrants’ home countries on their earnings in Germany, using native Germans as a benchmark. We propose an empirical analysis that highlights two important insights. First, there is a substantial gap in the returns to education between natives and immigrants in Germany, especially when we consider the quality of schooling in the source country where education was obtained. In particular, lower school quality reduces the endowment advantage that immigrants possess from their education. Second, quality-adjusted education helps us to better understand the potential driving force behind the native–immigrant wage gap. We show that this measure accounts for a substantial fraction of the unexplained part in the Oaxaca–Blinder decomposition. These findings emphasize the role of the school quality in explaining the imperfect transferability of human capital of immigrants in Germany.

Impact of multiple hurdles on Listeria monocytogenes dispersion of survivors

Pathogen exposure to multiple hurdles could result in variation in the number of survivors, which needs to be carefully considered using appropriate regression models for dealing with survivor dispersion. The aim of this study was to evaluate the impact of the hurdles on the random component of the measured variation and on its unexplained part (over or under-dispersion) representing the departure from randomness, i.e. non-randomness, in survivors of a multi-strain mixture of L. monocytogenes. The pathogen inactivation curves were fitted to the Weibull model within the Conway-Maxwell-Poisson process. In all the 20 hurdle combinations, the surviving cells, whether they showed an upward curvature or linear kinetics, displayed the randomness revealed by the degree of dispersion of the inactivation parameters (-b and p). In 15 combinations, a significant dispersion coefficient (c0), which reflected the non–random component of variation was evident, denoting either over–dispersion (c0 > 0 in 13 combinations) or under-dispersion (c0 < 0 in 2 combinations). The observed dependence of the under- and over-dispersion conditions on the inactivation rate was confirmed by a Monte Carlo simulation based on the inactivation parameter -b. Including both randomness and non-randomness provides a more accurate estimation of survivors, which certainly impacts on intervention practices.

How the Coronavirus Pandemic has Affected Gender Wage Inequality in Colombia

This article aims to compare how gender wage differences among Colombian workers have changed before and during the coronavirus pandemic. The parametric breakdown of Oaxaca-Blinder is performed based on microdata from the 2020 Large Integrated Household Survey and compared with the 2019 results. Among the results, the differential in hourly labor income against women has increased to 16% in 2020 versus 4% in 2019, especially in the lower part of the distribution. For both years and all income levels, most of the contribution to the gap is due to the unexplained part associated with discrimination. However, this effect is counterbalanced by women’s contributions, which are highly concentrated in the upper-income brackets.

Analysis of Gender differentials in the rate of return to education based on the gender wage gap

The rate of return to education has been paid much attention by the labor market in China. The mainstream literature maintains that women's rate of return to education is higher than men’s. Based on the perspective of gender wage gap and discrimination, this study uses the CFPS 2018 data to examine the gender differences in the educational yields and the gender wage discrimination faced by women at different levels of education. Mincer income equation and Oaxaca-Blinder decomposition method are used to establish the following two major findings. First, the educational yields of Chinese urban female workers were about higher than that of male workers by 3.6 percent in 2018. Second, the unexplained part of the gender wage gap decreases with the increase of workers’ years of education. Compared with male workers with the same educational level as female’s, female workers with higher education face much less discrimination than those with lower education level. References are provided for education policy and construction of the labor markets.

Real-time Face Recognition System using Python and OpenCV

Face recognition is a technique that an electronic device like a computer can determine and recognize a human face by comparing the given sample of facial attributes of that person. This subject or topic, using unbiased facial data, computer- based face recognition as an analysis is a largely unexplained part of research study. Here in this research paper we have tried to find and present a ideal way of face detection using Python and a computer device with active integrated web cam. This report contains how using python we have tried to implement one of the most important part of computer science, Deep learning, which can be used for detecting or recognizing human faces. We have proposed a system that can help in recognizing a human face in real-time. This can be used for various purpose and various machine and smart devices

Measurement report: Characterization and source apportionment of coarse particulate matter in Hong Kong: insights into the constituents of unidentified mass and source origins in a coastal city in southern China

Abstract. Coarse particulate matter (i.e. PM with an aerodynamic diameter between 2.5 and 10 µm – PM2.5 and PM10 – or PMcoarse) has been increasingly recognized for its importance in PM10 regulation because of its growing proportion in PM10 and the accumulative evidence for its adverse health impact. In this work, we present comprehensive PMcoarse speciation results obtained through a 1-year-long (January 2020–February 2021) joint PM10 and PM2.5 chemical speciation study in Hong Kong, a coastal and highly urbanized city in southern China. The annual average concentration of PMcoarse is 14.9 ± 8.6 µg m−3 (± standard deviation), accounting for 45 % of PM10 (32.9 ± 18.5 µg m−3). The measured chemical components explain ∼75 % of the PMcoarse mass. The unexplained part is contributed by unmeasured geological components and residue liquid water content, supported through analyses by positive matrix factorization (PMF) and the thermodynamic equilibrium model ISORROPIA II. The PMcoarse mass is apportioned to four sources resolved by PMF, namely soil dust/industrial and coal combustion, construction dust/copper-rich emissions, fresh sea salt, and an aged sea salt factor containing secondary inorganic aerosols (mostly nitrate). The PMcoarse concentration and source composition exhibit a distinct seasonal variation, a result mainly driven by the source areas the air masses have travelled through as revealed by back-trajectory analysis. In summer when the site is dominated by marine air mass, PMcoarse is the lowest (average = 8.1 µg m−3) and sea salt the largest contributor (47 %), followed by the two dust factors (36 % in total). In winter when the site receives air mass mainly from the northern continental region, PMcoarse concentration triples (24.8 µg m−3), with the two dust factors contributing three quarters of the aerosol mass. The potential dust source areas are mapped using the concentration-weighted trajectory technique, showing either the Greater Bay Area or the greater part of southern China as the origin of fugitive dust emissions leading to elevated ambient PMcoarse loadings in Hong Kong. This study, the first of this kind in our region, provides highly relevant guidance for other locations with similar monitoring needs. Additionally, the study findings point to the need for further research on the sources, transport, aerosol processes, and health effects of PMcoarse.

Civil rights experiments versus enrichment experiments in wage gap analysis

ABSTRACT The choice of the non-discriminatory vector of returns in Oaxaca-Blinder wage gap decompositions affects the results. Rather than being arbitrary, that choice should depend on the nature of the intended policy to address wage differentials in the labour market. The effectiveness of policies at the extensive margin, such as those offering greater access to higher education, is better estimated by the explained part of the wage gap, when choosing the lower-wage group’s vector of returns as non-discriminatory (the ‘enrichment experiment’). Alternatively, the effectiveness of affirmative action policies is better estimated by the unexplained part of the wage gap, when choosing the higher-wage group’s vector of returns as non-discriminatory (the ‘civil rights experiment’). We provide an example of applying this methodology for ethnic and gender wage differentials in the Georgian labour market.

Attitudes and personality in the Australian gender wage gap

ABSTRACT This paper estimates the effects of gender role attitudes and personality traits on the gender wage gap in Australia. Applying standard decomposition techniques and controlling for a wide range of variables, the paper finds that at least 67.8% of the total gender wage gap of 17.4% in 2019 remains unexplained – a figure which is lower than previous years. The results establish gender role attitudes as a key predictor of this pay gap both in the explained and unexplained part of the wage decomposition. It also shows that the impact of personality traits depends on whether the big five traits or the sub-traits are used in the analysis. Even some of the sub-traits belonging to the same category can influence the gender pay gap in opposite directions. Overall, the estimates establish the importance of psychological variables as more important than traditional human capital and other work-related characteristics in explaining the remaining gender wage gap in Australia.

FACTORS OF THE GENDER WAGE GAP AT UKRAINIAN ENERGY ENTERPRISES

Abstract. Using the results of the sample survey, conducted among the energy companies during the fourth quartal of 2020 within the grant, provided by ESP USAID we have obtained new empirical evidence of size and factors of the gender wage gap in Ukrainian energetics and about spreading of that phenomenon among different professions groups. As the main factors, determining the size of wage were considered the educational level (four groups were identified), length of service in the company (five groups were identified), and respondent’s position / workplace in the company’s qualification hierarchy (eight groups were identified). The results obtained evidences, that leading factor in the gender pay gap in Ukrainian energetics is the unequal access of women and men to gaining the characteristics necessary for increasing wages. In particular, the disparity in the distribution of the total number of female and male respondents between the qualification levels (the average qualification level of women is 4.8 vs. 5.4 for men). Gender gap formation through unequal remuneration of labour of women and men who have similar characteristics of experience, qualifications and complexity of the work is localized in the lower qualification levels (from the 2nd to the 4th), and through inequality of access to high-paying work is manifested in the absence of women at the highest (8th) qualification level, a clear predominance of men at the 7th qualification level and a noticeable predominance at the third qualification level, which in terms of payment outscores both the 5th and 6th qualification levels. Accordingly, the leading factor in the gender pay gap is the predominance of men at the three highest paid qualification levels. Localization of differences in remuneration of similar characteristics of qualifications, experience and complexity of work at lower levels of the qualification hierarchy, as well as the weakening of such inequality as the experience of employees increases, indicates that the problem of gender inequality is more inherent in the segment of «peripheral» employment. As the skills and experience grow (respectively, the value of employees to employers), the problem of gender pay inequality becomes less noticeable. However, the number of women who reach a level in their career growth where gender pay inequality is almost not observed is less than the number of men. Keywords: gender wage gap, unexplained part of gender wage gap, professions groups, inequality of access to high-paying work, energetics. JEL Classification J26, J16 Formulas: 0; fig.: 3; tabl.: 1; bibl.: 15.

Quantifying Hydraulic Roughness From Field Data: Can Dune Morphology Tell the Whole Story?

AbstractHydraulic roughness is a fundamental property in river research, as it directly affects water levels, flow strength and the associated sediment transport rates. However, quantification of roughness is challenging, as it is not directly measurable in the field. In lowland rivers, bedforms are a major source of hydraulic roughness. Decades of research have focused on dunes to allow parameterization of roughness, with relatively little focus on field verification. This study aims to establish the predictive capacity of current roughness predictors, and to identify reasons for the unexplained part of the variance in roughness. We quantified hydraulic roughness based on the Darcy‐Weisbach friction factor (f) calculated from hydraulic field data of a 78 km‐long trajectory of the river Rhine and river Waal in the Netherlands. This is compared to predicted roughness values based on dune geometry, and to the spatial trends in the local topographic leeside angle, both inferred from bathymetric field data. Results from both approaches show the same general trend and magnitude of roughness values (0.019 &lt; f &lt; 0.069). Roughness inferred from dune geometry explains at best 31% of the variance. Efforts to explain the remaining variance from statistics of the local topographic leeside angles, which supposedly control flow separation, were unsuccessful. Unexpectedly, multi‐kilometer depth oscillations explain 34% of the total roughness variations. We suggest that flow divergence associated with depth increase causes energy loss, which is reflected in an elevated hydraulic roughness. Multi‐kilometer depth variations occur in many rivers worldwide, which implies a cause of flow resistance that needs further study.