Survey topic and unit nonresponse

Survey topic as a factor influencing participation rates is becoming increasingly important, as there is a growing trend in social science research for surveying specific populations about specific topics. Previous research has shown that respondents with high topic interest (often referred to as salience) are more likely to participate in surveys. However, the identification of mechanisms that affect respondents’ interest in a survey topic has been largely neglected in research literature. We present an explanatory model of participation that conceptualizes topic interest as a function of an actor’s relational position in a particular social setting. To illustrate the relationship between survey topic and participation behavior, we use an online survey on mating conducted on the user population of an online dating site. For our nonresponse analysis we use web-generated process data, consisting of profile and interaction data, which describe all units of the sample frame. Thus, comprehensive information is available for both participants and non-participants of the online survey on an individual level, enabling a particularly accurate analysis of nonresponse. Results show that the probability of participation varies according to a user’s chances of success on the mating market. Users who can be described as less attractive (e.g. older people, less educated men, overweight women) show a higher probability of participation, which we explain with the mechanism of topic salience. We conclude with general implications regarding (1) the relationship between survey topic and survey participation and (2) the potential of web-generated process data for (online) survey research.     

K-means clustering of item characteristic curves and item information curves via functional principal component analysis

Quality & Quantity - The assessment of students’ performances and learning skills plays a key role in the educational context. Common tools for analyzing test data are item response...     

Estimation of collective household models with Engel curves

The structural consumer demand methods used to estimate the parameters of collective household models are typically either very restrictive and easy to implement or very general and difficult to estimate. In this paper, we provide a middle ground. We adapt the very general framework of [Browning, M., Chiappori, P.A., Lewbel, A., 2004. Estimating Consumption Economies of Scale, Adult Equivalence Scales, and Household Bargaining Power, Boston College Working Papers in Economics 588] by adding a simple restriction that recasts the empirical model from a highly nonlinear demand system with price variation to a slightly nonlinear Engel curve system. Our restriction has an interpretation in terms of the behaviour of household scale economies and is testable. Our method identifies the levels of (not just changes in) household resource shares, and a variant of equivalence scales called indifference scales. We apply our methodology to Canadian expenditure data.     

Testing non-nested semiparametric models: an application to Engel curves specification

This paper proposes a test statistic for discriminating between two partly non-linear regression models whose parametric components are non-nested. The statistic has the form of a J-test based on a parameter which artificially nests the null and alternative hypotheses. We study in detail the realistic case where all regressors in the non-linear part are discrete and then no smoothing is required on estimating the non-parametric components. We also consider the general case where continuous and discrete regressors are present. The performance of the test in finite samples is discussed in the context of some Monte Carlo experiments. The test is well motivated for specification testing of Engel curves. We provide an application using data from the 1980 Spanish Expenditure Survey. © 1998 John Wiley & Sons, Ltd.     

An item response model with single peaked item characteristic curves: The PARELLA model

In this paper an item response model (the PARELLA model) designed specifically for the measurement of attitudes and preferences will be introduced. In contrast with the item response models currently used (e.g. the Rasch model and, the two and three parameter logistic model) the item characteristic curve is single peaked instead of monotonically increasing. The model and its properties will be introduced. After this the consequences of these properties for the item writing stage, the evaluation of the concordance of data and model, and the applicability of the model will be discussed. The paper is finished with an example concerning the measurement of change in the attitude in the car-environment issue.     

An econometric method of correcting for unit nonresponse bias in surveys

Past approaches to correcting for unit nonresponse in sample surveys by re-weighting the data assume that the problem is ignorable within arbitrary subgroups of the population. Theory and evidence suggest that this assumption is unlikely to hold, and that household characteristics such as income systematically affect survey compliance. We show that this leaves a bias in the re-weighted data and we propose a method of correcting for this bias. The geographic structure of nonresponse rates allows us to identify a micro compliance function, which is then used to re-weight the unit-record data. An example is given for the US Current Population Surveys, 1998–2004. We find, and correct for, a strong household income effect on response probabilities.     

Constructing the true cost of living index from the Engel curves of the PIGLOG model

This paper investigates the properties of the Tornqvist index and shows how this can be used to construct a true cost of living index from a simple system of Engel curves. This allows the substitution bias inherent in a fixed weight index to be estimated using the maximum degree of commodity disaggregation available in the data. Furthermore the proposed index can be decomposed to show the impact of inflation on households with different expenditure levels and household chararacteristics. An empirical application of the method is given, using data on UK food expenditures.     

The power of online panel paradata to predict unit nonresponse and voluntary attrition in a longitudinal design

The objective of this study is to identify factors affecting participation rates, i.e., nonresponse and voluntary attrition rates, and their predictive power in a probability-based online panel. Participation for this panel had already been investigated in the literature according to the socio-demographic and socio-psychological characteristics of respondents and different types of paradata, such as device type or questionnaire navigation, had also been explored. In this study, the predictive power of online panel participation paradata was instead evaluated, which was expected (at least in theory) to offer even more complex insight into respondents’ behavior over time. This kind of paradata would also enable the derivation of longitudinal variables measuring respondents’ panel activity, such as survey outcome rates and consecutive waves with a particular survey outcome prior to a wave (e.g., response, noncontact, refusal), and could also be used in models controlling for unobserved heterogeneity. Using the Life in Australia? participation data for all recruited members for the first 30 waves, multiple linear, binary logistic and panel random-effect logit regression analyses were carried out to assess socio-demographic and online panel paradata predictors of nonresponse and attrition that were available and contributed to the accuracy of prediction and the best statistical modeling. The proposed approach with the derived paradata predictors and random-effect logistic regression proved to be reasonably accurate for predicting nonresponse—with just 15 waves of online panel paradata (even without sociodemographics) and logit random-effect modeling almost four out of five nonrespondents could be correctly identified in the subsequent wave.

     

Panel unit root tests under cross-sectional dependence

In this paper alternative approaches for testing the unit root hypothesis in panel data are considered. First, a robust version of the Dickey-Fuller t -statistic under contemporaneous correlated errors is suggested. Second, the GLS t -statistic is considered, which is based on the t -statistic of the transformed model. The asymptotic power of both tests is compared against a sequence of local alternatives. To adjust for short-run serial correlation of the errors, we propose a pre-whitening procedure that yields a test statistic with a standard normal limiting distribution as N and T tends to infinity. The test procedure is further generalized to accommodate individual specific intercepts or linear time trends. From our Monte Carlo simulations it turns out that the robust OLS t -statistic performs well with respect to size and power, whereas the GLS t -statistic may suffer from severe size distortions in small and moderate sample sizes. The tests are applied to test for a unit root in real exchange rates.     

开放经济条件下我国潜在产出水平的估算与解析——基于新凯恩斯主义的理论框架

目前有关估算我国潜在产出的研究,大多是在封闭条件下进行的,在我国对外贸易依存度和对外开放程度逐渐增强的背景下,忽略国际市场因素对我国实体经济的影响可能会导致对潜在产出水平的估计出现较大偏差.为此,本文引入开放条件下"产出一通胀"菲利普斯曲线作为我国总供给函数,通过建立状态空问模型并运用多变量卡尔曼滤波法对我国潜在产出水平进行估算,然后将估算结果与趋势分解法和封闭条件下的模型估算结果进行比较.     

Identification and Estimation of Engel Curves with Endogenous and Unobserved Expenditures

When dealing with the estimation of Engel curves, measurement errors in expenditure data and simultaneity are likely sources of endogeneity. In this paper we study identification of the parameters that characterize an Engel curve in the presence of both. We consider specifications where budget shares are polynomials in the logarithm of total expenditure, which is the case frequently encountered in empirical applications. We propose an estimation procedure which is an extension of that in Lewbel ( 1996 ) and exploits a control function assumption to correct for the endogeneity of the true unobserved total expenditure. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimating a public school expenditure model under binding spending limitations

A model explaining desired expenditure on education is estimated for a sample of New Jersey school districts. Because the limit on annual increases in school spending is binding for a subsample of jurisdictions, the Tobit estimation procedure is used. We test for equality of the pre- and postlimitation structures and find substantial similarity. The cap on expenditure increases was part of a court-ordered reform of New Jersey school finance law. The results can be used to explain the failure of the existing school finance laws in lessening expenditure disparities at the lower end of the distribution.     

Urbanization effects on survey nonresponse: a test within and across cities

This paper addresses differences in survey response across city size by applying an explanation from House and Wolf to areas within cities. The data are from Toronto, Hamilton and Kitchener, in Canada. Consistent with other literature, response falls sharply from largest to smallest place, but variation in response rates within the cities is negligible. The intra-city analysis is accomplished by factor analyzing variables such as population density, crime rate and ethnic structure, mostly computed for census tracts, into a variable labelled social disorganization. What House and Wolf termed compositional variation in response is handled by record linking with municipal assessment information. The analysis is based on micro data taking the people listed for the sample as unit of observation.     

The Engel curve for alcohol and the rank of demand systems

This paper shows that the quadratic shape of the Engel curve for alcohol is induced by preference heterogeneity between drinkers and abstainers in a Japanese data set. With controlling the heterogeneity, it is shown that the Engel curve for alcohol slopes monotonically downwards for drinkers, and that the probability of being a drinker is an increasing function of total expenditure. These two relationships generate a quadratic shape for the Engel curve for alcohol. Other goods in this data set appear to have nearly linear Engel curves, so if the alcohol Engel curve for drinkers is also linear, then after controlling for this preference heterogeneity the rank of this demand system would be two. Copyright © 2006 John Wiley & Sons, Ltd.     

A comparison of nonresponse in mail,telephone, and face-to-face surveys

This article reports a meta-analysis of 45 studies that explicitly compare the response obtained using a mail, telephone or face-to-face survey. The data analysis uses a generalized hierarchical linear model. Sampling procedure (e.g., local convenience sample, random general sample), saliency of topic, and research organization (university, government versus market research) had an effect on the response. On the average, the face-to-face condition achieved the highest completion rate (70.3%), the telephone survey the next highest (67.2%), and the mail survey the lowest (61.3%). There is a significant interaction with the year of publication: The response to face-to-face and telephone surveys is going down in the period covered by this analysis (1947 to 1992), but the response to mail surveys is going up slightly. We attribute this to the large amount of research on nonresponse problems with mail surveys, and recommend more research and development in this direction for face-to-face and telephone methods.     

Estimating school district expenditure functions under conditions of closed-end matching aid

Several studies have used ordinary least squares (OLS) to estimate school district expenditure functions for states with closed-end matching aid. The present paper demonstrates that the estimates of these studies may be inconsistent. A two-stage technique which guarantees consistent estimates is described and is used to estimate the price elasticity of expenditure for Pennsylvania school districts. The two-stage estimates indicate expenditure to be substantially more price-elastic than do the OLS estimates. The two-stage technique is appropriate for estimating any input demand or expenditure function when closed-end matching aid is involved.