Payroll taxes,wages and employment: Identification through policy changes

This paper investigates the effect of changes in payroll taxes on wages and employment in Argentina. The analysis, based on administrative data, focuses on the impact of a series of major changes in payroll taxes which varied across geographical areas. This setup offers two main advantages over previous studies. First, using longitudinal data, the variation in tax rates across space and time provides a plausible source of identification of their effects on employment and wages. Second, the use of legal tax rates for each area at each point in time provides a remedy for the measurement error bias raised by the use of empirical rates constructed from observed tax and wage bills. Once this bias is accounted for, the results indicate that changes in payroll tax rates are only partially shifted onto wages, and they point to the absence of any significant effect on employment.     

Respondent Related Correlates of Response Behaviour in Audience Research

Audience research by means of surveys has a long tradition, certainly withinarts and humanities oriented research. Yet, due to selective sampling and unitnonresponse it frequently lacks the methodological rigour to make scientificallyvalid statements based on sample estimates. This is one of the first attempts toexplore unit nonresponse in audience research. More specifically, it focuses onthe explanation of nonresponse by the socio-demographic and more topic relatedcharacteristics of a theatre audience. Using a two-step procedure for the on-sitecollection of data, the characteristics of respondents are compared with those ofnonrespondents. In step 1 the composition of the theatre audience is comparedto a proxy of a theatre population benchmark based on a weighted sample of theFlemish population (APS-2000). The validity of this best available method isdiscussed. Step 2 compares respondents with nonrespondents on a micro-level:ignoring unit nonresponse in step 1, we use logistic regression to map selectionin step 2. The chance of cooperating with the survey has been found to increasewith educational attainment and vary according to occupational category. Moreover,involvement with survey topic is confirmed as a strong predictor of survey participation.Gender, age and experience with theatre remain insignificant in predicting responsebehaviour. These findings are compared with the socio-demographic correlates ofresponse behaviour in general populations. Implications for statistically controllingfor nonresponse bias in audience research are discussed. Suggestions for furtherresearch are presented.     

ALCOHOL CONSUMPTION AND HUMAN CAPITAL: A RETROSPECTIVE STUDY OF THE LITERATURE

Abstract Grossman proposed an individual's health can be viewed as one aspect of their human capital. Following this line of thought a number of recent papers have reported a positive impact of alcohol consumption on earnings. The rationale for the existence of such a relationship is the positive impact of alcohol on physical and mental health. We conduct a meta‐analysis to determine whether such factors as: the estimation technique, the presence of ex‐drinkers in the sample, possible sample selection bias and publication bias may all contribute to these findings. An additional suggestion for the positive relationship between alcohol and wages is the presence of a common set of personality traits that determines drinking behaviour and also leads to higher earnings. We examine this relationship by reviewing the literature that investigates if the personality influencing aspects of alcohol consumption influences measures of human capital. We also survey the significant body of research that has examined how alcohol consumption has been found to influence educational outcomes and the work force participation of problem drinkers.     

Testing a method to estimate county-level demand for educational attainment

Recent changes in federal support for local workforce training programs have created an increased need for methods of assessing demand for educational attainment in sub-state regions. This research extends current non-survey methods for estimating demand for educational attainment at the county level. It then evaluates the non-survey method on theoretical grounds, and compares survey and non-survey estimates for two West Virginia counties. We found significant differences between survey and non-survey results and conclude that current non-survey methodology will not consistently provide reasonably accurate estimates. We thus propose adjustments to this methodology that should improve its accuracy. Many, if not most, jurisdictions do not have the expertise or funds to carry out periodic employment surveys. Many local policymakers would therefore benefit from development of an inexpensive, straightforward non-survey methodology that provides reasonably accurate information on local employer demand for labor force characteristics such as educational attainment.     

Self-employment,educational attainment and employment protection legislation

We analyse how educational attainment and employment protection influence an individual's decision to become self-employed. By altering expected income from dependent employment, employment protection is likely to affect an individual's choice of occupation, although such a link has not been established in the literature so far. We argue that an interaction between an individual's educational attainment and the institution of employment protection exists when it comes to the decision regarding whether to become self-employed. Based on survey data from OECD countries, we find evidence for a negative interaction, and conclude that only after taking this interaction into account can the effect of employment protection and educational attainment on self-employment rates be assessed.     

A nonparametric test for equality of distributions with mixed categorical and continuous data

In this paper we consider the problem of testing for equality of two density or two conditional density functions defined over mixed discrete and continuous variables. We smooth both the discrete and continuous variables, with the smoothing parameters chosen via least-squares cross-validation. The test statistics are shown to have (asymptotic) normal null distributions. However, we advocate the use of bootstrap methods in order to better approximate their null distribution in finite-sample settings and we provide asymptotic validity of the proposed bootstrap method. Simulations show that the proposed tests have better power than both conventional frequency-based tests and smoothing tests based on ad hoc smoothing parameter selection, while a demonstrative empirical application to the joint distribution of earnings and educational attainment underscores the utility of the proposed approach in mixed data settings.     

Estimates of the return to schooling in Sweden from a large sample of twins

A large sample of twins was used to examine whether conventional estimates of the return to schooling in Sweden are biased because ability is omitted from the earnings–schooling relationship. Ignoring measurement error, the results indicate that omitting ability from the earnings–schooling relationship leads to estimates that are positively biased. However, reasonable estimates of the measurement-error-adjusted returns are both above and below the unadjusted estimates, showing that the results depend crucially on a parameter not known at this time. However, an estimate of the reliability ratio was obtained using two measures on educational attainment. With this estimate of the reliability ratio, the measurement-error-adjusted estimate of the return to schooling in the sample of identical twins indicates that there is at most a slight ability bias in the conventional estimates of the return to schooling. The fundamental assumption of this kind of study is that within-pair differences in educational attainment are randomly determined. This assumption was also tested, but no strong evidence to reject it was found.     

Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling

We consider the problem of causal effect heterogeneity from a Bayesian point of view. This is accomplished by introducing a three-equation system, similar in spirit to the work of Heckman and Vytlacil (1998), describing the joint determination of a scalar outcome, an endogenous “treatment” variable, and an individual-specific causal return to that treatment. We describe a Bayesian posterior simulator for fitting this model which recovers far more than the average causal effect in the population, the object which has been the focus of most previous work. Parameter identification and generalized methods for flexibly modeling the outcome and return heterogeneity distributions are also discussed.Combining data sets from High School and Beyond (HSB) and the 1980 Census, we illustrate our methods in practice and investigate heterogeneity in returns to education. Our analysis decomposes the impact of key HSB covariates on log wages into three parts: a “direct” effect and two separate indirect effects through educational attainment and returns to education. Our results strongly suggest that the quantity of schooling attained is determined, at least in part, by the individual’s own return to education. Specifically, a one percentage point increase in the return to schooling parameter is associated with the receipt of (approximately) 0.14 more years of schooling. Furthermore, when we control for variation in returns to education across individuals, we find no difference in predicted schooling levels for men and women. However, women are predicted to attain approximately 1/4 of a year more schooling than men on average as a result of higher rates of return to investments in education.     

RETURN TO EXPERIENCE AND INITIAL WAGE LEVEL: DO LOW WAGE WORKERS CATCH UP?

This paper estimates the relationship between initial wage and return to experience. We use a Mincer‐like wage model to non‐parametrically estimate this relationship allowing for an unobservable individual permanent effect in wages and unobservable individual return to experience. The relationship between return to experience and unobservable individual ability is negative when conditioning on educational attainment, while the relationship between return to experience and educational attainment is positive. We link our findings to three main theories of wage growth, namely search, unobserved productivity and learning, and human capital. We devise several empirical tests in order to separate the theories. We find evidence in favor of the unobserved productivity and learning model and mixed evidence regarding the search model. We find no evidence in support of the human capital model. Copyright © 2013 John Wiley & Sons, Ltd.     

Family income and children's education: Using the Norwegian oil boom as a natural experiment

Parental income is positively correlated with children's educational attainment. This paper addresses the causality of this observed link. We have a unique data set for Norwegians born in the period 1967–1969, with a measure of permanent family income in the children's adolescence. This enables us to examine the long-term effect of family income on children's educational attainment. The Norwegian oil shock in the 1970s is used as an instrument, because this – in some regions but not in others – implied a general increase in income unrelated to parents' abilities. This variation in income is used to estimate the causal effect of family income on children's educational attainment. We find no such causal relationship. This result is robust with respect to different specification tests.     

Increasing the credibility of the twin birth instrument

Twin births are an important instrument for the endogenous fertility decision. However, twin births are not exogenous either as dizygotic twinning is correlated with maternal characteristics. Following the medical literature, we assume that monozygotic twins are exogenous, and construct a new instrument, which corrects for the selection although monozygotic twinning is usually unobserved in survey and administrative datasets. Using administrative data from Sweden, we show that the usual twin instrument is related to observed and unobserved determinants of economic outcomes, while our new instrument is not. In our applications we find that the classical twin instrument underestimates the negative effect of fertility on labor income. This finding is in line with the observation that high earners are more likely to delay childbearing and hence have a higher risk to get dizygotic twins.     

Noncognitive skills, occupational attainment, and relative wages

This paper examines whether men's and women's noncognitive skills influence their occupational attainment and, if so, whether this contributes to the disparity in their relative wages. We find that noncognitive skills have a substantial effect on the probability of employment in many, though not all, occupations in ways that differ by gender. Consequently, men and women with similar noncognitive skills enter occupations at very different rates. Women, however, have lower wages on average not because they work in different occupations than men do, but rather because they earn less than their male colleagues employed in the same occupation. On balance, women's noncognitive skills give them a slight wage advantage. Finally, we find that accounting for the endogeneity of occupational attainment more than halves the proportion of the overall gender wage gap that is unexplained.     

Assessing inherent model bias: An application to native displacement in response to immigration

There is a long-standing debate among academics about the effect of immigration on native internal migration decisions. If immigrants displace natives this may indicate a direct cost of immigration in the form of decreased employment opportunity for native workers. Moreover, displacement would also imply that cross-region analyses of wage effects systematically underestimate the consequences of immigration. The widespread use of such area studies for the US and other countries makes it especially important to know whether a native internal response to immigration truly occurs. This paper introduces a microsimulation methodology to test for inherent bias in regression models that have been used in the literature. We show that some specifications have built biases into their models, thereby casting doubt on the validity of their results. We then provide a brief empirical analysis with a panel of observed US state-by-skill data. Together, our evidence argues against the existence of native displacement. This implies that cross-region analyses of immigration’s effect on wages are still informative.     

The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys

Qualitative expectational data from business surveys are widely used to construct forecasts. However, based typically on evaluation at the macroeconomic level, doubts persist about the utility of these data. This paper evaluates the ability of the underlying firm-level expectations to anticipate subsequent outcomes. Importantly, this evaluation is not hampered by only having access to qualitative outcome data obtained from subsequent business surveys. Quantitative outcome data are also exploited. This required access to a unique panel dataset which matches firms’ responses from the qualitative business survey with the same firms’ quantitative replies to a different survey carried out by the national statistical office. Nonparametric tests then reveal an apparent paradox. Despite evidence that the qualitative and quantitative outcome data are related, we find that the expectational data offer rational forecasts of the qualitative but not the quantitative outcomes. We discuss the role of “discretisation” errors and the loss function in explaining this paradox.     

Estimation in Surveys Using Conditional Inclusion Probabilities: Simple Random Sampling

In survey sampling, auxiliary information on the population is often available. The aim of this paper is to develop a method which allows one to take into account such auxiliary information at the estimation stage by means of conditional bias adjustment. The basic idea is to attempt to construct a conditionally unbiased estimator. Four estimators that have a small conditional bias with respect to a statistic are proposed. It is shown that many of the estimators used in the literature in the case of simple random sampling can be obtained by using this estimation principle. The problem of simple random sampling with replacement, poststratification, and adjustment of a 2 x 2 dimensional contingency table to marginal totals are discussed in the conditional framework. Finally it is shown that the regression estimator can be viewed as an approximation of an application of the conditional principle.     

Do Higher Real Minimum Wages Lead to More High School Dropouts? Evidence from Maryland Across Races, 1993–2004

We explore whether higher levels of the real minimum wage have differing effects on high school dropout rates across students of various races and ethnicities (whites, African Americans, Hispanics, and Asians). Using a panel of data across Maryland counties and annual observations in 1993–2004, we found higher real minimum wages to be associated with higher dropout rates for Hispanic students, but not for other races and ethnicities. We used a variety of model specifications and explanatory variables, including real income, the unemployment rate, teen pregnancy rates, and educational attainment among adults. Several of our findings are broadly consistent with commonly reported sociological observations regarding how behavioral choices may be affected by different levels across races and ethnicities of cultural integration of recent immigrants, family cohesiveness, the value placed on education, small business ownership, and hourly (vs. salaried) employment.     

Interpreting the results of studies using latent variable models to assess data quality: an empirical example using confirmatory factor analysis

Latent variable models (LVMs) offer one route to examine the quality of data collected in surveys. The possibility exists that individuals equivalent in their true level of a construct or variable being measured are unlikely to have equivalent observed responses as a function of an extraneous variable, e.g., group membership. This potential is labeled here as differential item functioning (DIF). Survey methods generally considers measurement bias to be estimators that do no not accurately reflect true values. DIF may be thought of as differential measurement bias, i.e., measurement bias conditional on group membership. As a function of group membership, the degree, amount, or type of measurement bias changes. DIF has the potential to negatively affect the quality of data. LVMs, e.g., confirmatory factor analysis (CFA), offer one tool to assess DIF. However, few published examples exist in the survey research field and training in the interpretation of these models is lacking. The purpose of the current paper is to describe CFA sufficiently for interpretive purposes and demonstrate an empirical application of CFA to assess survey data quality to provide further interpretive guidance. References are provided for analysts wishing to conduct analyses of this type.     

Discussion: Efficiency and Self-efficiency With Multiple Imputation Inference

By closely examining the examples provided in Nielsen (2003), this paper further explores the relationship between self-efficiency (Meng, 1994) and the validity of Rubin's multiple imputation (RMI) variance combining rule. The RMI variance combining rule is based on the common assumption/intuition that the efficiency of our estimators decreases when we have less data. However, there are estimation procedures that will do the opposite, that is, they can produce more efficient estimators with less data. Self-efficiency is a theoretical formulation for excluding such procedures. When a user, typically unaware of the hidden self-inefficiency of his choice, adopts a self-inefficient complete-data estimation procedure to conduct an RMI inference, the theoretical validity of his inference becomes a complex issue, as we demonstrate. We also propose a diagnostic tool for assessing potential self-inefficiency and the bias in the RMI variance estimator, at the outset of RMI inference, by constructing a convenient proxy to the RMI point estimator.     

Education and Intergenerational Mobility in Occupations

A bstract The problem of measuring the intergenerational transmission of inequality and its implications for social welfare is studied. A possible decomposition of relevant factors–namely, educational attainments and other factors–is proposed and applied to three individual data sets regarding Germany, Italy, and the United States. The main result is that educational attainment is responsible for almost half of observed immobility The possibility that increasing equality of opportunity in entering the educational system may result in less inequality in income distribution is considered.     

Comparing survey data with an official administrative population: assessing sample-selectivity in the IAB Establishment Panel

The IAB Establishment Panel is a large annual establishment survey and serves as a data source for many empirical analyzes, e.g., on labor demand, wages and industrial relations but also for influential policy evaluations. We analyze the selectivity of the IAB Establishment Panel compared with the administrative population of all establishments in Germany to test whether the IAB Establishment Panel is biased towards “good employers”. By design the survey over-samples large, thus high paying and stable establishments. After flexibly controlling for elements of the sampling design, we do not detect any meaningful difference between establishments participating in the survey and the full population regarding key economic performance indicators. If anything, we observe a slight overrepresentation of stable and slow growing establishments. For applied research, the results highlight that “typical” econometric specifications may not be sufficient to control for selectivity.