The Wage Penalty for Married Women of Career Interruptions: Evidence from the 1970s and the 1990s

The goal of this paper is to assess how the wage penalty for career interruptions by married women changed between the 1970s and the 1990s. We estimate the wage penalty for career interruptions using the work-history model and PSID data. We use several approaches to control for various forms of endogeneity and selection bias. Our empirical results suggest that (i) the wage penalty for married women's career interruptions increased from 40.4% to 73.7% over the period, (ii) the ratio of the wage penalty for married women to that of married men also increased, from 1.33 to 2.43, (iii) Blinder–Oaxaca decompositions show that changes in education- or occupation-specific wage penalties account for most of the wage penalty increase.     

Unexplained gaps and Oaxaca–Blinder decompositions

We analyze four methods to measure unexplained gaps in mean outcomes: three decompositions based on the seminal work of Oaxaca (1973) and Blinder (1973) and an approach involving a seemingly naïve regression that includes a group indicator variable. Our analysis yields two principal findings. We show that the coefficient on a group indicator variable from an OLS regression is an attractive approach for obtaining a single measure of the unexplained gap. We also show that a commonly-used pooling decomposition systematically overstates the contribution of observable characteristics to mean outcome differences when compared to OLS regression, therefore understating unexplained differences. We then provide three empirical examples that explore the practical importance of our analytic results.     

Sustainable financing practices through green bonds: What affects the funding size?

Financing through the supply‐driven green bonds market has significantly surged in recent years. In this paper, we examine the factors influencing the size of financing though green bond supply, using cross‐section OLS regressions on a global dataset for 8 years (2010–2017) sourced from Bloomberg. We consider a set of tridimensional factors: bond characteristics, issuer characteristics, and market characteristics and examine their effects on issue size. Alongside whole sample estimation, we produce year‐wise estimations to realize the evolution and persistence of the effects over time. We then produce estimates across rating grades of the bonds. Finally, we carry Blinder–Oaxaca decomposition to see if average issue size has significantly changed over time and whether the factors considered can explain the difference. We find a large number of factors affecting issue size asymmetrically; however, many of the effects do not persist over time and are heterogeneous across rating grades. In contrast to the aggregate market trend, we find no evidence of increases in average issue size in the recent year. Furthermore, the average financing size is found significantly lower for high‐grade bonds. The paper provides a basis for encouraging green bond supply, particularly considering the rating of the bonds and the issuers.     

Effects on earnings of the removal of direct discrimination in minimum wage rates: A validation of the Blinder decomposition

Prior to 1969, the Australian labour market was characterised by institutionalised gender wage discrimination. Wages for the majority of the workforce were set by government wage tribunals, and these tribunals set the wages of women at 75 percent of the male rate of pay. Following equal pay decisions in 1969 and 1972, the award rates of pay for all work were, by June 1975, to be determined without consideration of the sex of the worker. Examination of data from surveys conducted in 1973 and 1989 show that the removal of this institutionalised discrimination is captured by the Blinder (1973) and Oaxaca (1973) wage decompositions as a marked decline in the absolute value of the ‘discrimination’ component of the gender pay gap. The analyses also reveal some merit in the decomposition proposed by Cotton (1988).     

Credit rationing and threshold effects in the relation between money and output

The possibility that the effect of monetary policy on output may depend on whether credit conditions are tight or loose can be expressed as a non-linearity in the relation between real money supply and output, of which a simple case is a threshold effect. In this case, consistent with the credit-rationing model of Blinder (1987), the monetary variable has a more powerful effect if it is below some threshold than when it is above. Testing for the importance of this threshold is straightforward if the appropriate threshold value is known a priori, but where the value is not known and must be chosen based on the sample, the testing problem becomes more difficult. We apply recently-developed tests applicable in this situation to both US and Canadian data, and find substantial evidence of a threshold effect, particularly in US data. However, the estimated threshold values are high.     

Variable selection for varying coefficient models with measurement errors

This paper focuses on variable selections for varying coefficient models when some covariates are measured with errors. We present a bias-corrected variable selection procedure by combining basis function approximations with shrinkage estimations. With appropriate selection of the tuning parameters, we establish the consistency of the variable selection procedure, and derive the optimal convergence rate of the regularized estimators. A simulation study and a real data application are undertaken to assess the finite sample performance of the proposed variable selection procedure.     

Performance Measurement in Government Service Provision: The Case of Police Services in New South Wales

The NSW Government is implementing a financial framework which is designed to encourage government service providers to become more efficient and effective. NSW Treasury is using Data Envelopment Analysis (DEA) to measure the efficiency of major government service providers, such as police, courts and hospitals. This paper outlines the progress in implementing the new financial framework and illustrates the way NSW Treasury will use DEA to help improve the efficiency of government service providers by describing an analysis of the NSW Police Service. The results suggest that NSW police patrols (local police districts) could, on average, reduce input usage by 13.5 percent through better management, and by 6 percent if the patrols could be restructured to achieve the optimal scale. Results also indicate that differences in operating environments, such as location and socioeconomic factors, do not have a significant influence upon the efficiency of police patrols.     

On the relation between currency and banking crises in developing countries, 1980–2010

This paper investigates the relationship between the occurrence of currency and banking crises using high-frequency data for a sample of 94 countries during 1980–2010. The two types of crises are proxied by continuous, multi-categorical and dummy variables based on market pressure indexes, and a dummy variable from the Laeven–Valencia banking crises database. Results suggest that a bidirectional leading relationship exists between the two types of crises. However, banking crises do not lead currency crises robustly when banking crises are proxied by dummies based on market pressure indexes. Finally, currency crises have robust state dependence, but this is not the case for banking crises.     

Bartlett correction to the likelihood ratio test for MCAR with two‐step monotone sample

Assuming that two‐step monotone missing data is drawn from a multivariate normal population, this paper derives the Bartlett‐type correction to the likelihood ratio test for missing completely at random (MCAR), which plays an important role in the statistical analysis of incomplete datasets. The advantages of our approach are confirmed in Monte Carlo simulations. Our correction drastically improved the accuracy of the type I error in Little's (1988, Journal of the American Statistical Association, 83 , 1198–1202) test for MCAR and performed well even on moderate sample sizes.     

Formation of firms' production decisions in finnish manufacturing industries

Business survey data have recently been used in several studies to shed light on the formation of firms' plans and expectations. The main tool for analysis has been the multivariate conditional log-linear model. The trichotomous answers in a typical business survey have an ordering. This makes it possible to analyse firms' production decisions with a categorized version of Cox's proportional hazards model. In this paper the production decisions of Finnish firms are investigated using data from the Finnish business survey. The results obtained are largely in accord with the implications of the production smoothing model of Blinder (1982).     

Are there racial differences in faculty salaries?

Many studies have used micro-level data in estimating earnings differentials by gender for college professors. None has studied racial earnings differences for faculty except by employing a dummy variable for race in its regression models. The availability of the 1993 National Study of Postsecondary Faculty has made such a study possible. We use a variant of the Oaxaca decomposition technique suggested by Cotton (1988) and Neumark (1988). Although the salaries of black faculty trail those of their white counterparts at the Associate and Full Professor levels, the reverse is true at the Assistant Professor level. The increased emphasis in recent years on increasing diversification in the racial composition of college faculty are possible explanations. The authors are indebted to various colleagues for comments on earlier drafts. They also wish to thank an anonymous referee who suggested significant changes to this article. The authors remain responsible for any remaining errors or omissions.     

Estimation of multivariate models for time series of possibly different lengths

We consider the problem of estimating parametric multivariate density models when unequal amounts of data are available on each variable. We focus in particular on the case that the unknown parameter vector may be partitioned into elements relating only to a marginal distribution and elements relating to the copula. In such a case we propose using a multi‐stage maximum likelihood estimator (MSMLE) based on all available data rather than the usual one‐stage maximum likelihood estimator (1SMLE) based only on the overlapping data. We provide conditions under which the MSMLE is not less asymptotically efficient than the 1SMLE, and we examine the small sample efficiency of the estimators via simulations. The analysis in this paper is motivated by a model of the joint distribution of daily Japanese yen–US dollar and euro–US dollar exchange rates. We find significant evidence of time variation in the conditional copula of these exchange rates, and evidence of greater dependence during extreme events than under the normal distribution. Copyright © 2006 John Wiley & Sons, Ltd.     

Work–home enrichment and health: an analysis of the mediating role of persistence in goal striving and vulnerability to stress

Extant research has shown that work–home enrichment (WHE) generates favorable effects on individuals' work-related and nonwork-related outcomes because of the synergistic combinations realized between work and home lives. In this paper, I explore the link between WHE and self-reported health. Despite this relationship has been already investigated in prior research, scholars have mostly adopted a simplistic approach that directly linked WHE to health, resulting in a limited understanding of what factors are conducive of such positive effects. In this paper, I test a more sophisticated model that link WHE to self-rated health indirectly, through the mediating role of persistence in goal striving and vulnerability to stress. By using data collected through the second follow-up of the National Survey of Midlife Development in the United States (MIDUS II; 2004–2006) and involving a large national sample of working adults, the results show that individuals experiencing high levels of WHE report a better health status because of an enhanced determination to persist in goal striving even when facing difficulties and a lower vulnerability to stress. Implications of these findings for research and practice are discussed.     

Informal adult care and caregivers' employment in Europe

I discuss instrumental variable estimates of the effect of providing unpaid adult care on the caregivers' probability of being employed, using eight waves of the European Community Household Panel. I focus on men aged 40–64 and women aged 40–59 from thirteen Member States, aggregated in two groups of Northern-Central and Southern countries. Previous papers with European data found that IV estimates are more negative than estimates assuming exogeneity of caregiving. I show that this difference is not robust once account is taken of time-invariant unobserved heterogeneity. Indeed, instruments turn out not to be needed, and the estimated effect is negative, but small in both groups of countries.     

Is the Quarter of Birth Endogenous? New Evidence from Taiwan,the US,and Indonesia

Recent evidence based on US data suggests that the quarter or month of birth (QOB or MOB) may be endogenous, since family characteristics can explain up to 50% of the effects of QOB on the education outcomes and earnings of adult males. In this study, based on a sample of one million Taiwanese siblings, we examine university admission at age 18 as our outcome variable and find that at school entry, the oldest (September born) children are 31–38% more likely to be admitted into university at age 18 than the youngest (August born) children, indicating strong seasonality in university admission. The inclusion of controls for family background is found to explain only a small portion of these effects, particularly for males. Given that such results are at odds with the recent US evidence, we revisit the US Census data and find that when racial differences are properly controlled for in the estimation, even a rich set of family characteristics is capable of explaining only a minor proportion of the QOB effects. Furthermore, using data from the US and Indonesia, we find that seasonal temperature variation is unlikely to be an important contributor to the US‐Taiwan disparity. Our findings imply that the validity of using QOB or MOB as an instrumental variable may be dependent on the population being studied and the sample selected.     

Digital economy,agglomeration, and entrepreneurship in Chinese cities

This study investigates the digital economy's influence on entrepreneurship and the role of economic agglomeration in its mechanism. Employing yearly prefecture-level city data from China (2011–2019) and panel econometric techniques, we show that the digital economy has a significant positive effect on entrepreneurship activity; this effect is maintained following endogeneity, alternative explanatory variable, sample composition, and other robustness checks. Regional heterogeneity analysis shows that the digital economy's impact was greatest on the western region, followed by the central and eastern regions. We also identify agglomeration-related channels (output and employment density) through which the digital economy promotes entrepreneurship.     

Bayesian estimation based on ranked set sample from Morgenstern type bivariate exponential distribution when ranking is imperfect

In this paper we consider Bayes estimation based on ranked set sample when ranking is imperfect, in which units are ranked based on measurements made on an easily and exactly measurable auxiliary variable X which is correlated with the study variable Y. Bayes estimators under squared error loss function and LINEX loss function for the mean of the study variate Y, when (X, Y) follows a Morgenstern type bivariate exponential distribution, are obtained based on both usual ranked set sample and extreme ranked set sample. Estimation procedures developed in this paper are illustrated using simulation studies and a real data.     

Building a global database: consequences for the national I–O data

ABSTRACT

Global economic analysis requires consistent and balanced data, which necessitates the reconciliation of datasets from both national and international sources. In the case of the Global Trade Analysis Project Data Base, datasets supplied by international sources are considered preferable to national input–output (I–O) tables. As a result, the national I–O data can experience significant adjustments during the reconciliation process due to differences between the national and international datasets. The purpose of this paper is to examine the extent to which national I–O data change during reconciliation. The results demonstrate that the I–O data are altered by the construction process, particularly from the reconciliation of the national I–O data to the international trade and energy datasets. Closer examination reveals potential issues with both the trade and energy datasets, as well as the national I–O data – illustrating the challenges associated with reconciling data from multiple sources.     

Firm-level Disclosures and the Relative Roles of Culture and Legal Origin

In this paper, I investigate the relative roles of legal origin and national culture in explaining firm‐level disclosure levels internationally. Using a significantly larger and more representative sample than prior research, I document, using univariate and multivariate analyses, that both legal origin and culture (as operationalized by Hofstede and Schwartz) are important in explaining firm disclosure. Neither legal origin nor culture dominates with respect to overall explanatory power for variations in disclosure levels. Consequently, it is premature to write off culture as an important factor in the financial reporting environment. Furthermore, I find that legal origin is an important conditioning variable for the role of culture. Finally, although legal origin is a key determinant of disclosure levels, I hypothesize and find that its importance decreases with the richness of a firm's information environment.     

Estimation of the threshold stochastic frontier model in the presence of an endogenous sample split variable

Heterogeneity among firms has been an important issue in studying firms’ technical efficiencies. If firms do not randomly fall into different groups with different technologies but by self-selection, statistically it implies the data are subject to the sample selection bias. In this paper, we generalize the stochastic frontier (SF) model to accommodate heterogeneous technologies among firms by considering the threshold SF model with an endogenous threshold variable. We discuss the econometric techniques appropriate for the threshold SF model with panel data. To determine the optimal number of regimes, we use modified the model selection criteria of Gonzalo and Pitarakis (J Econom 110(2):319–352, 2002) and investigate their finite sample performance by some Monte Carlo experiments. Finally, we also demonstrate our approach by an empirical example.