Is there a 'safe area' where the nonresponse rate has only a modest effect on bias despite non-ignorable nonresponse?

Rising nonresponse rates in social surveys make the issue of nonresponse bias contentious. There are conflicting messages about the importance of high response rates and the hazards of low rates. Some articles (e.g. Groves and Peytcheva, 2008) suggest that the response rate is in general not a good predictor of survey quality. Equally, it is well known that nonresponse may induce bias and increase data collection costs. We go back in the history of the literature of nonresponse and suggest a possible reason to the notion that even a rather small nonresponse rate makes the quality of a survey debatable. We also explore the relationship between nonresponse rate and bias, assuming non-ignorable nonresponse and focusing on estimates of totals or means. We show that there is a ‘safe area’ enclosed by the response rate on the one hand and the correlation between the response propensity and the study variable on the other hand; in this area, (1) the response rate does not greatly affect the nonresponse bias, and (2) the nonresponse bias is small.     

Accuracy of self-reports to the burdensome question: survey response and nonresponse error trade-offs

Survey self-reports to questions involving respondent burden are examined for: (1) overall accuracy, (2) direction of bias, and (3) influence on relationships. Self-reports by respondents to questions on an area of household finances are compared to error-free supplier records. The evidence shows self-reports in this case to be accurate at the overall, or aggregate, level, but inaccurate at the individual, or disaggregate, level. The trade-offs inherent in the nonresponse occurring as a consequence of attempting to acquire verified data versus response bias resulting from a reliance on self-reports from surveys are discussed. It is suggested that attempts by researchers to acquire error-free, verified information in surveys will lead in most cases to unacceptably high levels of item nonresponse. An alternative, algebraic procedure for adjusting for disaggregate level response bias in self-reports on the basis of a subsample of verified responses is provided.     

A Middle Class Image of Society

We studied undercoverage and nonresponse in a telephone survey among the population of the City ofGroningen, the Netherlands. The original sample, drawn from the municipal population register,contained 7000 individuals. For 37 percent of them, the telephone company was unable to produce a validtelephone number. Of those with a known telephone number, 49 percent did not answer the telephone orrefused to cooperate. As a result, the final respondents comprised merely 32 percent of the originalsample. To study distributional bias, we used individual-level data compiled from municipal records asour benchmark. Bivariate as well as multivariate analyses showed the undercoverage to be stronglyrelated to all sociodemographic variables studied, except gender. Nonresponse was related to age, countryof origin, marital status, and household size and composition, but not to gender, unemployment, socialassistance benefit, and education. Both undercoverage and nonresponse contributed to a strong middleclass bias in the final data set: middle-aged and older, economically secure people, of Dutch origin andliving with others in a household are overrepresented, while persons in disadvantaged and marginalpositions, such as the young, people of foreign stock, the unemployed, persons depending on publicincome support and singles are underrepresented.     

The asymmetric behavior of household consumption under the business cycle

In this study, we examine whether and to what extent the pattern of household consumption is asymmetrically sensitive to economic changes. We use a threshold model with error correction to characterize household consumption under the business cycle. Using data from the 1979–2014 Survey of Family Income and Expenditure in Taiwan, we find that household consumption has pro-cyclical characteristics during the business cycle. More importantly, household consumption responds asymmetrically to economic fluctuations such that changes in consumption tend to be larger during expansions than during downturns. Furthermore, the nature of this asymmetry differs across household income quantiles.     

Measuring the Benefits of Homeowning: Effects on Children

In this paper we examine whether homeowning benefits children by testing whether children of homeowners stay in school longer than children of renters and whether daughters of homeowners are less likely to have children as teenagers than daughters of renters. We use both probit models and a bivariate probit technique which takes account of possible selection bias due to differences between parents who choose to own versus rent. We find in several data sets that both effects are statistically significant and quantitatively important—particularly for low-income households. We also estimate that the dollar benefit per low- income household of parents being homeowners rather than renters is at least $31,000.     

Borrowing Constraints and Credit Demand in a Developing Economy

This paper investigates the determinants of credit demand in the presence of borrowing constraints in a developing economy. We model the determinants of observed debt for Chilean households while accounting for selection bias and the endogeneity of their income and specific household assets. Using a novel Chilean dataset, we estimate the relationship between household characteristics and consumer and mortgage debt. We find substantial differences in the nature of these relationships across the types of debt. For example, we find that the income elasticity for consumer debt is greater than 1 whereas for mortgage debt it is not. The results suggest the increased availability of credit, combined with the aging of the Chilean population, is likely to drastically change the distribution and level of Chilean debt. These findings are particularly relevant for other developing economies currently experiencing rapid income and debt growth. Copyright © 2015 John Wiley & Sons, Ltd.     

Direct Estimation of Equivalence Scales and More Evidence on Independence of Base

We explore a direct approach to estimating household equivalence scales from income satisfaction data. Our method differs from previous approaches to using satisfaction data for this purpose in that it can be used to directly fit and evaluate closed‐form and non‐parametric equivalence scales of any desired form. Its flexibility makes it easy to consider specific aspects such as income dependence or more specific information on household composition (such as whether household members live in a partner relationship). We estimate and evaluate a number of scales used in the literature. If the equivalence scale is assumed to be independent of income and to depend only on household size, we do not reject the validity of the widely used square‐root scale at conventional significance levels. We also test GESE and GAESE restrictions (Donaldson and Pendakur, 2003, 2006) and investigate in detail to what extent household economies of scale depend on income. Our results suggest that the income dependence differs fundamentally across household types (rising economies of scale for ‘family’ households, falling economies of scale for multi‐adult households without children and no income dependence for other households).     

Selectivity correction in discrete-continuous choice analysis: With Empirical Evidence for Vehicle Choice and Use

In modelling the relationship between the household's demand for consumer durables and their utilisation rate one typically observes the latter only for the chosen durable. The absence of data on the level of ‘consumption’ of the non-chosen durables is a potential source of selectivity bias. There exist many procedures for correcting for selectivity so that predictions of use levels of non-chosen durables can be obtained if one wishes to include use as an influence on durable choice, or if one wants to apply the utilisation model to obtain predictions of use of each type of durable within the class. In this paper we identify the main sources of selectivity and introduce correction formulae that are easy to implement and generalise to polychotomous choice. We assess the empirical implications of the alternative formulae in the context of household vehicle choice and level of use. The data are drawn from 1,436 households in the Sydney Metropolitan Area.     

Accuracy of self-reports on donations to charitable organizations

In this paper we assess overall accuracy in survey self-reports on giving to charitable organizations, direction of bias in self-reports, and the influence of this bias on relationships. We compare donations to one specific health charity reported in the Giving in the Netherlands Panel Study 2003 with donations recorded in the database (n =  191). We find that (a) reported donations are significantly higher than recorded donations; (b) reported amounts contributed are correlated very strongly with recorded contributions; (c) differences between amounts reported and amounts recorded are positively related to education, religious affiliation, and the tendency to social desirability, and negatively to household income. This suggests that effects of education are overestimated and effects of income and religious affiliation are underestimated using self-reports on donations rather than archival records.     

A Meta‐Analysis of β‐Convergence: the Legendary 2%

Abstract.  The topic of convergence is at the heart of a wide‐ranging debate in the growth literature, and empirical studies of convergence differ widely in their theoretical backgrounds, empirical specifications, and in their treatment of cross‐sectional heterogeneity. Despite these differences, a rate of convergence of about 2% has been found under a variety of different conditions, resulting in the widespread belief that the rate of convergence is a natural constant. We use meta‐analysis to investigate whether there is substance to the 'myth' of the 2% convergence rate and to assess several unresolved issues of interpretation and estimation. Our data set contains approximately 600 estimates taken from a random sample of empirical growth studies published in peer‐reviewed journals. The results indicate that it is misleading to speak of a natural convergence rate since estimates of different growth regressions come from different populations, and we find that correcting for the bias resulting from unobserved heterogeneity in technology levels leads to higher estimates of the rate of convergence. We also find that correcting for endogeneity of the explanatory variables has a substantial effect on the estimates and that measures of financial and fiscal development are important determinants of long‐run differences in per capita income levels. We show that although the odds of a study being published is not uniform for studies with different p ‐values, publication bias has no significant effect on the conclusions of the analysis.     

Does relative risk aversion vary with wealth? Evidence from households׳ portfolio choice data

We test whether relative risk aversion varies with wealth using the Panel Study of Income Dynamics data in the U.S. Our analytical results indicate the following implications. For each household, there are two channels through which the risky share responds to wealth fluctuations, the income channel and the habit channel. Across households, there are heterogeneous responses through both the habit channel and the income channel. Finally, two potential misspecification problems on time-varying relative risk aversion arise when both heterogeneous responses through the habit channel and the responses through the income channel are ignored. Our main empirical findings are to show the importance of the income channel and the heterogeneous responses, and to provide strong evidence of relative risk aversion varying with wealth, after correcting two misspecification problems.     

Nonresponse Bias and Stimulus Effects in the Dutch National Election Study

Bias is a much-debated issue in survey research. Answer effects (respondents claim to have behaved differently than they did in reality), nonresponse bias (nonrespondents differ on important variables from the respondents) and stimulus effects (by participating in a previous wave of a study, respondents change their behavior or attitude) can seriously distort the results of survey research. By using data from the 1998 Dutch National Election Study the authors show that the results of election research can indeed be affected by bias. Not only are significant effects found in the distribution of political attitude and voting behavior variables as a result of both nonresponse bias and stimulus effects, it is also shown that relations between variables change as a result of bias.     

Nonresponse and Recall Errors in a Study of Absence because of Illness: An Analysis of Their Effects on Distributions and Relationships

Using administrative data as validating standard, we studied the combined effects of two sources of survey error – nonresponse and recall errors – on distributional and substantive bias in a mail survey of absence because of illness among the employees of a Dutch road building company (response rate 77%). No distributional bias was found in five socio-demographic variables (sex, age, years of service, function, and district), but both nonresponse bias and recall bias occurred in our central dependent variables: frequency and duration of absence because of illness. Nonrespondents were on sick leave more frequently and longer than respondents. Furthermore, the self-reports of absence because of illness of our respondents proved to be rather inaccurate. Underreporting of frequency and duration of sick leave was more common than overreporting. Therefore, both sources of error had a cumulative effect.While nonresponse did not result in biased relationships, recall errors had clearly biasing consequences: seven out of 30 correlation coefficients analyzed were too biased to produce valid outcomes; another six were substantially biased. Multiple regression used for predicting recent absence because of illness among our respondents also led to different outcomes depending on the choice of data source (administration or questionnaire) for our absence variables.     

Equity aspects of VAT in emerging European countries: A case study of Serbia

A belief that consumption taxation is inherently inequitable has been entrenched in a significant portion of the general public and was supported by early empirical evidence that suggested a highly regressive annual VAT incidence. However, it has been shown that much of the estimated annual VAT regressivity is due to the income under-reporting bias inherent in sample surveys. This bias is particularly important in emerging European countries due to a high shadow economy and the evasion of direct income taxes, which suggests household expenditures as a more meaningful indicator of well-being than registered income. Furthermore, theoretical considerations favor the lifetime incidence approach, whereby VAT is estimated to be proportional or mildly progressive. A micro-simulation analysis of the Serbian expenditure survey data yields incidence estimates in line with the existing literature from other countries. We show that a significant presence of own-source (small) farming production of food in many emerging European countries, including Serbia, presents an important progressivity-enhancing buffer compared to the VAT incidence in developed European countries. We conclude that the common beliefs of inherently inequitable VAT taxation are vastly overstated and poorly founded in the economic reality of emerging European countries such as Serbia, where VAT can be most adequately described as being mildly progressive.     

Post‐Stratification Weighting in Organizational Surveys: A Cross‐Disciplinary Tutorial

Post‐stratification weighting is a technique used in public opinion polling to minimize discrepancies between population parameters and realized sample characteristics. The current paper provides a weighting tutorial to organizational surveyors who may otherwise be unfamiliar with the rationale behind the practice as well as “when and how to do” such weighting. The primary reasons to weight include: [1] reducing the effect of frame, sampling, and nonresponse bias in point estimates, and, relatedly, (2) correcting for aggregation error resulting from over‐ and underrepresentation of constituent groups. We briefly compare and contrast traditions within public opinion and organizational polling contexts and present a hybrid taxonomy of sampling procedures that organizational surveyors may find useful in situating their survey efforts within a methodological framework. Next, we extend the existing HRM literature focused on survey nonresponse to a broader lens concerned with population misrepresentation. It is from this broadened methodological framework that we introduce the practice of weighting as a remedial strategy for misrepresentation. We then provide sample weighting algorithms and standard error corrections that can be applied to organizational survey data and make our data and procedures available to individuals who may wish to use our examples as they learn “how to weight.” © 2018 Wiley ­Periodicals, Inc.     

Unofficial Development Assistance: A Model of Development Charities’ Donation Income

The empirical literature on the determinants of charities’ donation income, distinguishing the charitable cause, is small. We consider the case of development charities specifically. Using a panel covering a quarter of a century, we observe a strong fundraising effect and a unitary household income elasticity. We find evidence that the conventionally identified ‘price’ effect may simply be the product of omitted variable bias. Our results further suggest that public spending on development crowds in private donations for development. We find a positive spillover effect of fundraising, suggesting the efforts of one development charity may increase contributions to other development charities.     

Wealth Accumulation and Factors Accounting for Success

We use detailed income, balance sheet, and cash flow statements constructed for households in a long monthly panel in an emerging market economy, and some recent contributions in economic theory, to document and better understand the factors underlying success in achieving upward mobility in the distribution of net worth. Wealth inequality is decreasing over time, and many households work their way out of poverty and lower wealth over the seven year period. The accounts establish that, mechanically, this is largely due to savings rather than incoming gifts and remittances. In turn, the growth of net worth can be decomposed household by household into the savings rate and how productively that savings is used, the return on assets (ROA). The latter plays the larger role. ROA is, in turn, positively correlated with higher education of household members, younger age of the head, and with a higher debt/asset ratio and lower initial wealth, so it seems from cross-sections that the financial system is imperfectly channeling resources to productive and poor households. Household fixed effects account for the larger part of ROA, and this success is largely persistent, undercutting the story that successful entrepreneurs are those that simply get lucky. Persistence does vary across households, and in at least one province with much change and increasing opportunities, ROA changes as households move over time to higher-return occupations. But for those households with high and persistent ROA, the savings rate is higher, consistent with some micro founded macro models with imperfect credit markets. Indeed, high ROA households save by investing in their own enterprises and adopt consistent financial strategies for smoothing fluctuations. More generally growth of wealth, savings levels and/or rates are correlated with TFP and the household fixed effects that are the larger part of ROA.     

Evidence on the Demand for Mortgage Debt by Owner-Occupants

This paper explores the relationship between household mortgage debt burdens and housing consumption, periodic income, nonhousing wealth, the income tax position of the household, expected mobility, and other micro-level characteristics that proxy for household risk preferences and life cycle effects. We use 1985 and 1989 American Housing Survey data to estimate mortgage debt level equations simultaneous with house value equations, controlling for the contemporaneous nature of these two choices. We find that larger debt levels are positively associated with greater value residences and with the level of household income. Numerous household level demographic characteristics are also systematically related to mortgage demand. Of particular interest are our findings that the use of mortgage debt is affected significantly by the rate of tax savings on mortgage interest deductions and by the expected mobility of the household.     

Unemployment risk, house price risk and the transition into home ownership in the United Kingdom

Using household panel data, this paper examines the impact of income uncertainty, in the form of unemployment risk, on home ownership in the United Kingdom. The existing literature based on cross-sectional studies finds a negative relationship between income uncertainty and home ownership. This paper utilises data on transitions into home ownership and exogenous variation in unemployment risk, avoiding the endogeneity of employment to home ownership status. It also conditions the empirical estimates on a measure of house price volatility utilising a local-level house price index to control house price risk, which might also discourage home ownership. Results show a strong role for unemployment risk in lowering the likelihood of house purchase, but no statistically significant role for house price risk.     

Attitudes Toward Surveys, Attitude Accessibility and the Effect on Respondents’ Susceptibility to Nonresponse

This paper analyzes whether respondents’ attitudes toward surveys explain their susceptibility to item nonresponse. In contrast to previous studies, the decision to refuse to provide income information, not to answer other questions and the probability of ‘don’t know’ responses is tested separately. Furthermore, the interviewers’ overall judgments of response willingness was included as well. Respondents with a positive and cognitively accessible attitude toward surveys were expected to adopt a cooperative orientation and were thus deemed more likely to answer difficult as well as sensitive questions. Attitudes were measured with a 16-item instrument and the response latencies were used as an indicator for attitude accessibility. We found that respondents with more favorable evaluations of surveys had lower values on all kinds of nonresponse indicators. Except for the strong effect on the prevalence of ‘don’t knows’, survey attitudes were increasingly more predictive for all other aspects of nonresponse when these attitude answers were faster and thus cognitively more accessible. This accessibility, and thus how relevant survey attitudes are for nonresponse, was found to increase with the subjects’ exposure to surveys in the past.