Desired and excess fertility in Europe and the United States: Indirect estimates from World Fertility Survey data

Calhoun, Charles A.

doi:10.1007/bf01796615

Cited by 10 publications

(11 citation statements)

References 15 publications

(13 reference statements)

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“…There is a growing empirical literature which makes use of bivariate probit models. Greene and Hanser (2009) cite more than 20 different papers applying this methodology from 1997 to 2007, though first applications are due to Calhoun (1989Calhoun ( , 1991Calhoun ( , and 1994.…”

Section: Main Goal and Methodologymentioning

confidence: 99%

“…Neither the level of learning nor the level of satisfaction are directly observable from answers to survey questions; hence, following Greene . Provided that the specification proposed by [3] and [4], which represent seemingly unrelated equations, does not imply any identification problem, we can use the same set of explicative variables. In fact, there are not any theoretical reasons to exclude some variable from one particular equation.…”

Section: Model Descriptionmentioning

confidence: 99%

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Analysis of Emerging Barriers for e-Learning Models: An Empirical Study

Calvo¹,

Rungo²

2010

ERSJ

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The diffusion of the e-learning model during the last decade has contributed to solve many problems concerned with education at the workplace. Technological progress has significantly contributed to eliminating most limitations of the traditional education model, through improved access, diffusion of information, and the adaptation to individual needs. However, e-learning is an instrument, which does not ensure the automatic achievement of intended goals. Some studies have demonstrated that the mere conversion of course materials into an e-learning course may reduce motivation and thus, the level of effective learning. In addition, appropriate design of course materials for e-learning programs might not be sufficient to achieve optimal results. In order to maximize the benefits of implementing an e-learning program, it is if fact necessary to take into account organizational issues, such as the existence of incentives, the distribution of time for learning at the workplace, or the management system being used, for example. This paper analyzes some organizational features, which are linked to learning in organizations and might help to better explain success of an e-learning program. In particular, we attempt to assess the impact of both incentives and the assignment of a specific period of time for education to personal satisfaction and the level of learning. To this end, we proposed a specific survey to users of e-learning courses at a consulting company, which includes questions about satisfaction, self-assessed learning and monetary or long-term (career) incentives, among others. The impact of different organizational characteristics on satisfaction and learning has been then estimated by a bivariate ordered probit model, which allows for considering both the nature of dependent variables and the possible correlation between equations. The analysis sheds light on key practical organizational features, which should be taken into account in order to improving results of e-learning programs The main goal of this analysis has been to provide evidences to support policies aimed to increase effectiveness of e-learning models. We have based on the e-learning experience of a consulting company, evaluating the effectiveness of this new model in terms of two variables: learning perceived and level of satisfaction of participants. In order to analyze the determinants of both learning and satisfaction, we collected data from participants of e-learning programs. We found out that self-assessed satisfaction and perceived learning are likely to be affected by the same set of variables. On considering these relationships, and the nature of available data, both a simultaneous bivariate ordered probit model and a simultaneous bivariate probit model have been used in order to assess the impact of different factors on both satisfaction and perceived learning.

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Section: Main Goal and Methodologymentioning

confidence: 99%

Section: Model Descriptionmentioning

confidence: 99%

Analysis of Emerging Barriers for e-Learning Models: An Empirical Study

Calvo¹,

Rungo²

2010

ERSJ

View full text Add to dashboard Cite

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“…3 For additional reports in the series Comparative Studies: ECE Analyses of WFS Surveys in Europe and USA, see Berent (1982Berent ( , 1983, Jones (1982) and Ford (1984). More recent studies that have used the UNECE comparative analysis file include analyses of the distributional aspects of human fertility by Lutz (1989) and desired and excess fertility by Calhoun (1991). 4 Since the research reported in the present paper was undertaken more recent cross-national data have become available.…”

Section: Methodsmentioning

confidence: 97%

The impact of children on the labour supply of married women: Comparative estimates from European and US data

Calhoun

1994

Eur J Population

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This paper presents estimates of the impact of the age pattern and level of fertility on the probability of labor force participation by married and cohabiting women in 12 eastern and western European countries and the US. Logit models for labor force participation probabilities are estimated conditional on age, age at marriage or union, educational attainment, current parity, and number of years in parity, using data on married and cohabiting women from the UN Economic Commission for Europe (UNECE) Comparative Study of World Fertility Surveys. The estimated models are used to simulate the age profiles of labor force participation conditional on the level and timing of fertility. The simulation results are presented in a series of charts grouped according to similarities in the effects of fertility on the age profiles of labor force participation. Four distinct patterns are identified that depend on the empirical significance of distinct number-of-children and age-of-youngest-child effects. The role of family policies and the extent to which the labor supply reductions associated with childbearing can be interpreted as opportunity costs are considered.

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“…Assuming normality and that μ i is where d ijl 1 if y 1i j and y 2i l, and d ijl 0 otherwise. Here, the vector Ψ b consists of β, γ , α 1 , α 2 , and the parameters associated with the trivariate distribution of , μ . Regarding identification of the parameters in the model defined by 2.1 through 2.5 with normality assumption, we note that the mean parameter joint choice probability associate with the observed response vector y i depends nonlinearly on the probability of zero inflation Φ −z i γ and choice probability Pr y 1i j, y 2i l coming from the BOP submodel.…”

Section: 5mentioning

confidence: 99%

Bayesian Approach to Zero-Inflated Bivariate Ordered Probit Regression Model, with an Application to Tobacco Use

Gurmu

Dagne

2012

Journal of Probability and Statistics

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This paper presents a Bayesian analysis of bivariate ordered probit regression model with excess of zeros. Specifically, in the context of joint modeling of two ordered outcomes, we develop zeroinflated bivariate ordered probit model and carry out estimation using Markov Chain Monte Carlo techniques. Using household tobacco survey data with substantial proportion of zeros, we analyze the socioeconomic determinants of individual problem of smoking and chewing tobacco. In our illustration, we find strong evidence that accounting for excess zeros provides good fit to the data. The example shows that the use of a model that ignores zero-inflation masks differential effects of covariates on nonusers and users.

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Desired and excess fertility in Europe and the United States: Indirect estimates from World Fertility Survey data

Cited by 10 publications

References 15 publications

Analysis of Emerging Barriers for e-Learning Models: An Empirical Study

Analysis of Emerging Barriers for e-Learning Models: An Empirical Study

The impact of children on the labour supply of married women: Comparative estimates from European and US data

Bayesian Approach to Zero-Inflated Bivariate Ordered Probit Regression Model, with an Application to Tobacco Use

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