socio-demographic earnings gaps

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Understanding socio-demographic disparities in the labor market: the case for a motivation-based theory

Understanding socio-demographic disparities in the labor market: the case for a motivation-based theory

The Þndings above suggest that hiring discrimination may be involved in occupational segregation: it might result from more severe employer discrimination in some occupations than in others. We can come again to taste-based theories of discrimination at this stage. Indeed, even though they are not very well suited to predict lasting gaps in average earnings, they support sustainable lasting segregation - blacks (women) being absent from industries for which labor demand is prejudiced. Yet, there is no obvious way to explain the distrib- ution of prejudice among industries. The customer discrimination perspective suggests that labor demand should be more discriminatory for sales occupations: the table above does not carry unequivocal support to such a prediction. Assuming a situation where unprejudiced employers are numerous enough to hire all black (female) workers, 28 the employer discrimination perspective does not make any particular prediction as for the industries that are more likely to exhibit segregated work force. Thereby, those theories can predict horizontal occupational segregation but hardly where it should arise. 29 The story involving prejudiced co-workers 30 is of particular interest as regards vertical occupa- tional segregation. It brings an explanation to a "glass ceiling" impeding women’s (resp.
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Informal versus Formal: A Panel Data Analysis of Earnings Gaps in Madagascar

Informal versus Formal: A Panel Data Analysis of Earnings Gaps in Madagascar

Being specifically designed to capture informal sector jobs, the 1-2-3 Surveys allow us to capture the concept of informal sector following the international definition strictly (ILO, 2003; European Commission et al., 1993). In Madagascar, the informal sector is defined as all private unincorporated enterprises that produce at least some of their goods and services for sale or barter, are not registered (statistics licence, supposed to be compulsory for all kind of businesses) or do not keep book accounts. Apart from our formal/informal sector divide, special care is dedicated to get reliable measures of variables where informality status may lead to sampling and measurement errors, due to its characteristics. In particular, the questionnaire includes a detail set of questions to capture information on activity status, the classical procedures leading to the under-declaration of informal sector workers participation for those with the weakest labour market attachment. We compute the labour income associated with each remunerated job. For wage workers, the survey capture their current monthly wage, while for self-employed workers earnings correspond to the disposable income (before taxation). For those who don't want to declare (or don't know) their precise earnings, a complementary question ask for intervals, proposed in detailed ranges (10) of minimum wage. Hourly earnings used in the econometric analysis are deduced using the total number of hours worked per month. Additionally, all the classical individual and household based socio-demographic variables are appended to our database. Finally, time deflators CPI are used to compute real earnings.
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Informal versus Formal: A Panel Data Analysis of Earnings Gaps in Madagascar

Informal versus Formal: A Panel Data Analysis of Earnings Gaps in Madagascar

Being specifically designed to capture informal sector jobs, the 1-2-3 Surveys allow us to capture the concept of informal sector following the international definition strictly (ILO, 2003; European Commission et al., 1993). In Madagascar, the informal sector is defined as all private unincorporated enterprises that produce at least some of their goods and services for sale or barter, are not registered (statistics licence, supposed to be compulsory for all kind of businesses) or do not keep book accounts. Apart from our formal/informal sector divide, special care is dedicated to get reliable measures of variables where informality status may lead to sampling and measurement errors, due to its characteristics. In particular, the questionnaire includes a detail set of questions to capture information on activity status, the classical procedures leading to the under-declaration of informal sector workers participation for those with the weakest labour market attachment. We compute the labour income associated with each remunerated job. For wage workers, the survey capture their current monthly wage, while for self-employed workers earnings correspond to the disposable income (before taxation). For those who don't want to declare (or don't know) their precise earnings, a complementary question ask for intervals, proposed in detailed ranges (10) of minimum wage. Hourly earnings used in the econometric analysis are deduced using the total number of hours worked per month. Additionally, all the classical individual and household based socio-demographic variables are appended to our database. Finally, time deflators CPI are used to compute real earnings.
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Strategic interactions in the labor market, self-esteem motivations and socio-demographic disparities

Strategic interactions in the labor market, self-esteem motivations and socio-demographic disparities

In a previous work, we have posited a theory of socio-demographic disparities in the labor market based on a special kind of occupational segregation. From the characterization of a subset of selective (upon socio-demographic criteria) jobs within the set of jobs 1 we have made explicit potential consequences of this occupational segregation on socio-demographic gaps in average earnings. This gap - favorable to the agents who "Þt in" the workplace identity - may be a consequence of the fact that, depending on certain conditions, the share of selective jobs is an increasing function of the wage standard under consideration: hiring is more likely to be selective among better-paid jobs. This results from the fact that, all other things equal, a job compensation increases with its degree of demands and that the more demanding a job, the stronger employers’ propensity to mobilize intrinsic motivation from workers i.e. to arouse the workplace identity. That is precisely on criteria predisposing certain working persons to the workplace identity that selective hiring occurs in our analysis. Our explanation of socio-demographic gaps in average earnings (as a statistical fact) is thus very simple: female workers and black workers would earn less than white male workers because of their concentration among less demanding jobs.
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Accounting for Labor Gaps

Accounting for Labor Gaps

In average, the fictive French employee works longer and has more chance to be employed than the US employee. The productivity gap explains these hours and employment gaps: the French worker being initially poorest than the American, he chooses to work longer and accept a lower reservation wage that gives incentives for firms to hire. If we look at the evolution of hours per worker, we can notice that starting from the mid 1970s, once completed the technological catch-up process, the evolution of hours would have mimicked that one of the US: this is natural once we set the preference parameters to be the same in the two countries. If we look at the evolution of the employment rate, it seems that with the labor market institutional arrangements which characterize the US, France would have observed a spectacularly high employment rate: at the end of the simulation, the employment is 87.5% in this "fictive" France, whereas it is equal to 62.5% in the "real" economy. This simulation then gives the relative importance of the labor gaps: when both hours and employment gaps are simultaneously decreased, it appears that the employment rate is the more elastic (38) .
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Gaps in Peer Design

Gaps in Peer Design

economic considerations, became charged with other meaning and eventually caused the system’s demise 22 . In conclusion, assessing the advantages and disadvantages of peer design is a foremost example of a long-standing heavily discussed issue: whether a technical architecture should be centralized or decentralized, its design based on equal interaction among peers or on a client/server architecture. It is important to underline that, when it comes to discussing the degree of (de-)centralization, protocols are not intrinsically good or bad. The two cases we have examined – the gaps and shortcomings they show when it comes to peer design, and the strategies that developers and users display to counter them – ultimately illustrate that choices related to the design of technical architectures “come with” a number of social, organizational and at-large political dynamics, and lead to stories of compromises and trials 23 .
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Disentangling the effects of urban form and socio-demographic context on street tree cover: A multi-level analysis from Montréal

Disentangling the effects of urban form and socio-demographic context on street tree cover: A multi-level analysis from Montréal

Level 2 – neighbordhood’s socio-economics (n=308) Social strat. Val_Dwell Housing value (thousand dollars) 267.53 79.92 Uni_Dip Percentage of university degree holders 16.86 9.61 Low_inc Percentage of low-income households 30.26 11.52 Rec_immi Percentage of recent immigrants 10.02 7.34 Lifestyle With_Child Percentage of households with children 34.86 12.54 PctFrench Percentage of French speakers 66.86 24.13 270

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Non-consent to a wrist-worn accelerometer in older adults: the role of socio-demographic, behavioural and health factors.

Non-consent to a wrist-worn accelerometer in older adults: the role of socio-demographic, behavioural and health factors.

anthropometric factors was investigated in a model adjusted for socio-demographic factors and mutually adjusted for smoking status, units of alcohol consumption, frequency of fruit and vegetable consumption, hours of moderate and vigorous physical activity, and BMI. Sitting time variables were added to the model separately as they had more missing values than the other covariates. Finally, the association with health-related factors was examined in models adjusted for socio-demographic variables and for each health-related variable separately due to potential collinearity. To test linearity in the association between these variables and non-consent, continuous (age, hours of moderate and vigorous physical activity, etc) and ordinal (educational level, self-rated general health, etc) variables were entered in the model as a linear term. In a final model, age and all variables associated with non-consent in previous analyses were entered in the logistic regression model simultaneously. The statistical analyses in this study were performed using SAS version 9.3 (SAS Institute, Inc., Cary, North Carolina) and STATA12 statistical software (Stata- Corp LP, College Station, Texas).
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Gender and Ethnic Earnings Gaps in Seven West African Cities

Gender and Ethnic Earnings Gaps in Seven West African Cities

Key words: earnings equations, gender wage gap, ethnic wage gap, West Africa Résumé Dans cette étude nous analysons le poids et les déterminants des différentiels de rémunérations entre genre et groupes ethniques dans sept métropoles d’Afrique de l’Ouest (Abidjan, Bamako, Cotonou, Dakar, Lomé, Niamey and Ouagadougou), en mobilisant une base de données unique et parfaitement comparable, provenant des enquêtes 1-2-3 réalisées dans les sept villes en 2001 et 2002. Cette question soulève un certain nombre de questions méthodologiques que nous tentons de traiter en détail, notamment en tenant compte des différences de composition ethnique et de genre entre les secteurs public, privé formel et informel qui sont susceptibles de jouer sur les écarts de revenus. Les résultats mettent en évidence l’existence d’un déficit systématique de rémunération pour les femmes, les caractéristiques des emplois expliquant moins de la moitié de ces écarts. A contrario, les groupes ethniques majoritaires ne semblent pas bénéficier d’une situation avantageuse et les écarts de revenus suivant le groupe ethnique sont relativement faibles par rapport à ceux que l’on observe suivant le genre. Quel que soit le signe de ce différentiel (positif ou négatif), la contribution expliquée par les caractéristiques observées de l’emploi varie très sensiblement d’une ville à l’autre. Les estimations montrent qu’une grande partie de l’écart de revenu selon le genre provient de l’allocation sectorielle, et que cette dernière est toujours défavorable aux femmes. En revanche, dans le cas des écarts suivant le groupe ethnique, la distribution par secteur institutionnel joue parfois de façon positive dans le sens d’une réduction des écarts. Finalement, une désagrégation plus fine des groupes ethniques, au-delà de la partition majoritaire/minoritaire, confirme que l’entrée ethnique est systématiquement moins significative sur les revenus du travail que le genre.
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Stock Market Overreaction to Management Earnings Forecasts

Stock Market Overreaction to Management Earnings Forecasts

Table 9: Event-Day Share Turnover Multivariate Regressions This table reports the coe fficients from a regression of share turnover on multiple variables. Low RP equals 1 when at least one analyst quarterly EPS forecast equals the low point of the company issued quarterly EPS guidance range on the day of the event, and 0 otherwise. High RP equals 1 when at least one analyst quarterly EPS forecast equals the high point of the company issued quarterly EPS guidance range on the day of the event, and 0 otherwise. Low & High RP equals 1 when at least one analyst quarterly EPS forecast equals the low point and at least one analyst quarterly EPS forecast equals the high point of the company issued quarterly EPS guidance range on the day of the event, and 0 otherwise. Mean Analyst Forecast is the average analyst quarterly EPS forecast on the event day. CIG Range Midpoint is the middle point of the company issued quarterly EPS guidance range. Market Cap is the number of shares outstanding multiplied by the price, in millions of dollars. Book-to-Market is the book value of common equity divided by the market capitalization. Momentum is the firm’s monthly compounded stock return over the past year. Analyst Coverage is the number of analysts that have provided an EPS forecast for the firm over the past year. Standardized Unexpected EPS is the ratio of the quarterly earnings surprise to the standard deviation of earnings surprises over the past four quarters. EPS Volatility is the standard deviation of realized quarterly EPS over the past four quarters. Turnover is the ratio of volume to shares outstanding in percent on the day of the event. The numbers in parentheses are t-statistics based on simple t-tests. ***, ** or * signify that the test statistic is significant at the 1, 5 or 10% two-tailed level, respectively.
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Corporate bond repurchases and earnings management

Corporate bond repurchases and earnings management

Thus, the partial recognition of some unrealized gains/losses in prior periods makes it more difficult for firms which elect to record bonds at fair value to meet [r]

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Accounting for Labor Gaps

Accounting for Labor Gaps

1 Introduction As it is well known, the evolution of total hours worked during the post-WWII period is characterized by sharp dierences across developed economies. If we look in particular at the US and three selected European countries (France, Germany, and the UK), we can observe a sharp decline in hours in the two continental European countries, at least until the mid-eighties, while in the UK the decline is less signicant. At the opposite, total hours increased in the US (see Figure 1, top panel). The gaps in terms of total labor supply between the US and the European continental countries have evolved over time until the 1990s, when they stabilized: whereas in the 1960s, total hours were 15% higher in Europe than in the US, today they are 20% lower (see Figure 1, bottom panel). In this long term perspective, the last crisis has had a large impact in the US, whereas structural changes seem to be the main drivers of the total hour changes in European countries.
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Cyclical dynamics of airline industry earnings

Cyclical dynamics of airline industry earnings

Aggregate  airline  industry  earnings  have  exhibited  large  amplitude  cyclical  behavior  since   deregulation  in  1978.    To  explore  the  causes  of  these  cycles  we  develop  a  behavioral   dynamic  model  of  the  airline  industry  with  endogenous  capacity  expansion,  demand,   pricing,  and  other  feedbacks;  and  model  several  strategies  industry  actors  have  employed   in  efforts  to  mitigate  the  cycle.    We  estimate  model  parameters  by  maximum  likelihood   methods  during  both  partial  model  tests  and  full  model  estimation  using  Markov  chain   Monte  Carlo  methods  to  establish  confidence  intervals.    Contrary  to  prior  work  we  find   that  the  delay  in  aircraft  acquisition  (the  supply  line  of  capacity  on  order)  is  not  a  very   influential  determinant  of  the  profit  cycle.    Instead  we  find  that  aggressive  use  of  yield   management—varying  prices  to  ensure  high  load  factors  (capacity  utilization)—may  have   the  unintended  effect  of  increasing  earnings  variance  by  increasing  the  sensitivity  of  profit   to  changes  in  demand.  
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Are long-term earnings targets forecasts?

Are long-term earnings targets forecasts?

The specification in Panel A, Column (6) includes (Y ActualBEs-YJ ForecastG)/Assets, or the difference between actual I/B/E/S income before extraordinary items for the [r]

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Introducing Unobserved Heterogeneity in Earnings Mobility

Introducing Unobserved Heterogeneity in Earnings Mobility

. These distributions are presented in Table 5. For example, for the 90’s, at the stationnary equilibrium, we see that 8.4% of the type 2 individuals are in the quintile 0, 10.9%, 55.6%, 22.4%, 2.7% and 0.0% in the quintiles 1, 2, 3, 4 and 5 respectively. This means that a majority of type 2 individuals are each year, at the stationnary equilibrium, in the quintile 2, or in other words that type 2 individuals spend most of their time, at the stationnary equilibrium, in quintile 2. Table 5 shows that this result is true for all types, for the 80’s and the 90’s. This confirms the idea that the nature of the heterogeneity is to attract individuals towards a specific quintile in the 80’s and the 90’s. Thus the presence of heterogeneity in the earnings mobility process leads to a segmentation of the population. The meaning of that segmentation, in the 80’s and the 90’s, is that each individual spends most of the time in the same quintile, revolving around from time to time. For the 70’s, type 2-3 individuals spend at the stationnary equilibrium respectively 42.1% and 35.1% of their time in the quintiles 2 and 3, and type 3-4 individuals 29.4% and 49.3% in the quintiles 3 and 4. These two types of individuals spend most of their time in two quintiles. The difference between the 70’s and the following decades is that, in the middle of the distribution in the 70’s, the zones are not centered around a specific quintile but are rather composed of two quintiles that are both regularly visited. Thus in the middle of the distribution, the zones in which individuals move are larger and have a greater intersection in the 70’s, which means that the segmentation was less pronounced at that time.
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Earnings Dispersion, Risk Aversion and Education

Earnings Dispersion, Risk Aversion and Education

1 Introduction The acquisition of general human capital through education is one of the most important activities by which young individuals increase their potential lifetime earnings. While enrolled in school, individuals typically receive parental sup- port and give up potential earnings in favor of higher future earnings. Parental transfers can take the form of housing services and other living expenses (such as food and transportation) and are typically una®ected by those random elements a®ecting household income. As opposed to parental transfers, which are most likely non-stochastic from the perspective of young individuals, future earnings are usually unknown. Both wages and unemployment rates are random variables that may vary over the life cycle and their distributions are potentially a®ected by human capital. Indeed, it is well known that schooling can reduce substantially the incidence of unemployment over the life cycle and can also increase lifetime earnings.
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Predicting dementia using socio-demographic characteristics and the Free and Cued Selective Reminding Test in the general population

Predicting dementia using socio-demographic characteristics and the Free and Cued Selective Reminding Test in the general population

To construct the FCSRT “residual scores”, the crude scores were modeled using linear regression models that included, as independent variables, age, age-squared, sex and education level (primary school: 0 –5 years of educa- tion; vocational school certificate; French junior-school dip- loma; French high-school diploma; graduate studies). The total proportion of variance of the crude scores explained by the linear model was expressed using the coefficient of determination, denoted R 2 . The estimated beta coefficients were used to generate the estimated FCSRT scores for each individual. The “residual scores” were then defined and computed as the difference between the estimated and the crude FCSRT scores. Consequently, the variability of these “residual scores” corresponds to the FCSRT residual vari- ance after removing the part of variance associated with the socio-demographics variables [19].
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Stock Market Overreaction to Management Earnings Forecasts

Stock Market Overreaction to Management Earnings Forecasts

Table 2: Management Forecast Abnormal Return Multivariate Regressions This table reports the coefficients from a regression of management forecast 3-day cumulative abnormal returns (Mgmt Forecast CAR) and subsequent earnings announcemement 61-day cumulative abnormal returns (Earnings CAR) on multiple variables. A Negative Surprise occurs when the management forecast estimate is below the current analyst forecast consensus. A Positive Surprise occurs when the management forecast estimate is above the current analyst forecast consensus. Mean Analyst Forecast is the average analyst quarterly EPS forecast on the event day. Mgmt Forecast is the forecast point or middle point of the management quarterly EPS forecast range. Range is the difference between the Mgmt Forecast high and low points, divided by the stock price at the end of the prior month. Market Cap is the number of shares outstanding multiplied by the price, in millions of dollars. Book-to-Market is the book value of common equity divided by the market capitalization. Analyst Coverage is the number of analysts that have provided an EPS forecast for the firm over the past year. SUE is the ratio of the quarterly earnings surprise to the standard deviation of earnings surprises over the past four quarters. Abnormal return is calculated using a Fama-French 3-factor model to estimate the expected return. The numbers in parentheses are t-statistics based on heteroscedasticity consistent standard errors. ***, ** or * signify that the test statistic is significant at the 1, 5 or 10% two-tailed level, respectively.
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Cereal yield gaps across Europe

Cereal yield gaps across Europe

When considering sustainable intensification in the context of European cereal production, it is essential to consider the large het- erogeneity of Europe’s agricultural landscape. Europe has a wide geo- graphic extent comprising a variety of farm structures and intensities combined with pronounced differences in environmental conditions, rendering substantial variation in inputs (nutrients, pesticides, irriga- tion) and outputs (crop yields), as well as future yield potential. We use the concept of yield gaps (Van Ittersum et al., 2013) to identify the regions with unlocked yield potential. A yield gap is the difference between potential and actual yield. Potential yields can be calculated for irrigated (yield potential) and rainfed (water-limited yield potential) conditions. Yield potential assumes unconstrained crop growth and perfect management that avoids yield limitations from nutrient defi- ciencies and water stress, and yield reductions from weeds, pests and diseases. Yield potential is therefore location and year specific and depends on the crop genotype along with solar radiation and air tem- perature during the crop growing season. In addition, water-limited yield potential depends on water supply as dictated by precipitation and soil available water. Full yield gap closure is generally not eco-
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Employment Vulnerability and Earnings in Urban West Africa

Employment Vulnerability and Earnings in Urban West Africa

worker without an extended social network who is shaken by a household shock cannot develop a viable, stable or profitable business, for lack of time to invest, conduct market studies, etc. Lastly, the use of the control function provides a direct test of the assumption of the endogeneity of vulnerability in the earnings function. The significance of the coefficient assigned to the correction term µ ˆ (the vulnerability equation residual) indicates whether the unexplained variation in vulnerability intensity also affects the variation in the level of individual earnings. In other words, in the cases where this coefficient is significant, the assumption of endogeneity of vulnerability cannot be rejected. The findings for the informal sector (Table 5) confirm that, in the four out of seven cases (Ouagadougou, Bamako, Lome and Abidjan), the endogeneity of vulnerability cannot be rejected. This contrasts with the diagnosis for the formal private sector (Table 4), where endogeneity has to be rejected in six of seven cases, the exception being Dakar. In the following, however, rather than using a method for each sector and each city, we refer to estimations derived from models corrected for endogeneity in all cases in order to maintain uniform treatment for all the cities studied.
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