Search results

The Bureau of Economics in the Federal Trade Commission has a three-part role in the Agency and the strength of its functions changed over time depending on the preferences and ideology of the FTC’s leaders, developments in the field of economics, and the tenor of the times. The over-riding current role is to provide well considered, unbiased economic advice regarding antitrust and consumer protection law enforcement cases to the legal staff and the Commission. The second role, which long ago was primary, is to provide reports on investigations of various industries to the public and public officials. This role was more recently called research or “policy R&D”. A third role is to advocate for competition and markets both domestically and internationally. As a practical matter, the provision of economic advice to the FTC and to the legal staff has required that the economists wear “two hats,” helping the legal staff investigate cases and provide evidence to support law enforcement cases while also providing advice to the legal bureaus and to the Commission on which cases to pursue (thus providing “a second set of eyes” to evaluate cases). There is sometimes a tension in those functions because building a case is not the same as evaluating a case. Economists and the Bureau of Economics have provided such services to the FTC for over 100 years proving that a sub-organization can survive while playing roles that sometimes conflict. Such a life is not, however, always easy or fun.

This study investigates the relation of bank loan delinquencies to Fed Survey delinquency data from 2003 to 2017. Bank-generated loans have lower delinquencies than all Fed Survey loan types. Survey mortgage and auto loan delinquencies are positively related to bank loan delinquencies indicating complimentary delinquency decisions for borrowers. Conversely, student loans delinquencies are negatively related to bank loans, consistent with borrowers substituting student loan payments for bank debt for the entire sample period. Student loan delinquencies are negatively related to per-capita bankruptcy, and all other types of debt have a positive relation. The relation between Fed Survey loan delinquencies and bank-generated loan delinquencies is time varying and changed after the financial crisis in 2008.

Seemingly Unrelated Regression is used to study delinquencies for three bank loan types and whether or not they are related to Fed Survey loan delinquencies. The sample is split into pre-financial crisis before 2008 and post-crisis after 2008.

Seemingly Unrelated Regression (SUR) results show that bank delinquencies for second mortgages and “Other” loan types are consistently complementary to Fed Survey mortgage loan delinquencies. Fed Survey auto loans delinquencies are also consistent with a complimentary relation, and these results are largely driven by the relation after the financial crisis of 2008 since pre-crisis regression results are not significant for every dependent variable. Credit card loan delinquencies have a negative and substitute relation with bank-generated first mortgage loan delinquencies prior to the crisis in 2008, and with bank-generated second mortgages after the crisis. Conversely, student loan delinquencies from the Fed Survey are negatively and significantly related to bank mortgages for the entire sample period, but only with bank-generated first mortgages after 2008. The student loan delinquency results are consistent with income smoothing, on average, although this is not explicitly tested at the micro level since this study uses macro-level data and not borrower-specific data. These findings are also consistent with conventional wisdom that student loans provide “financial slack” and borrower flexibility.

A limiting factor is this study uses macro-level data and not borrower-specific data.

Empirical findings are consistent with prior research that student loans provide income smoothing and “financial slack,” and borrowers with payment challenges will pay other debt before student loans.

Borrowers in financial trouble tend to be delinquent for all debt, and more so for student debt.

To investigate whether Fed Survey delinquencies of auto loans, first mortgages, student loans and credit card loans from all sources have complementary or substitution effects with bank debt at a macro level. The study investigates whether bank debt follows “market trends” as a complementary effect, or if bank debt has a negative relation to other debt indicating a substitution effect.

The purpose of this paper is to focus on the relationship between attitudinal data from the long-running Michigan Surveys of Consumers and US real GDP growth. One survey question asks, “Generally speaking, do you think now is a good time or a bad time to buy a house?” with the follow-up question “Why do you say so?” There are several factors for consumers to choose as reasons. Given the strong link between US housing market activity and business cycles, the authors ask whether the responses to the follow-up question explain the behavior of output growth.

The authors employ an augmented autoregressive model to investigate the relationship between output growth and the responses to the follow-up question for 1986–2007 and for 1986–2018, which includes the 2008 financial crisis. The authors follow the general-to-specific approach to obtain the final model estimates for interpretation. For a deeper analysis, the authors estimate the model using the responses of survey participants in the bottom 33 percent, middle 33 percent and upper 33 percent income categories, separately. While avoiding aggregation bias, this approach helps reveal important information embodied in the cross-sectional distribution of the data.

The follow-up question focuses on such factors as home prices, mortgage rates, houses as a good/bad investment, timing, uncertain future and affordability. The authors find that the majority of these factors chosen as reasons by consumers in the middle and upper 33 percent income categories explain the behavior of output growth. Among the factors chosen as reasons by consumers in the bottom 33 percent income category, only the mortgage rate and uncertain future explain output growth.

This study provides new insights into the usefulness of detailed consumer survey data in explaining the behavior of output growth and further underlines the usefulness of such measures across different income categories for revealing important information contained in the cross-sectional distribution of the data.

The research aims to investigate consumer decision‐making strategies using quantitative and qualitative methods. Two decision theories are contrasted: neoclassical theory proposes compensatory and optimising strategies with complete information, whilst bounded rationality theory suggests simplified and non‐compensatory strategies. The research assesses whether these theories will explain consumers' decision‐making strategies when completing a survey, and the extent to which qualitative and quantitative methods provide convergent validity of the explanations.

A computer‐based choice survey was administered to university students and staff. The choice task was to select a preferred potato from sets of potatoes with different attributes. Information for each attribute was initially hidden by a “card”; respondents had to reveal the information by clicking on the card with the computer mouse. The survey recorded the order of mouse clicks, providing quantitative data on decision strategies. Some respondents were also interviewed about their decision processes, which provided qualitative data on strategies.

Respondents left over one‐fifth of the cards unopened. Interview findings confirmed that respondents generally did not obtain all available information and used simplified strategies. The qualitative data were generally validated by the quantitative data and provided improved descriptions of decision strategies.

Some qualitative data can not be verified with quantitative data, and the convenience sample of university students and staff may limit the generalisability of the findings.

The paper suggests that consumers may not use all available information when making choices. The neoclassical assumption of full information may therefore not hold. It also indicates that probing decision strategies with qualitative questioning provides accurate data and better details than could be obtained quantitatively.

The purpose of this paper is to present a detailed and critical look at the evolution of online survey research since Evans and Mathur’s (2005) article on the value of online surveys. At that time, online survey research was in its early stages. Also covered are the present and future states of online research. Many conclusions and recommendations are presented.

The look back focuses on online surveys, strengths and weaknesses of online surveys, the literature on several aspects of online surveys and online survey best practices. The look ahead focuses on emerging survey technologies and methodologies, and new non-survey technologies and methodologies. Conclusions and recommendations are provided.

Online survey research is used more frequently and better accepted by researchers than in 2005. Yet, survey techniques are still regularly transformed by new technologies. Non-survey digital research is also more prominent than in 2005 and can better track actual behavior than surveys can. Hybrid surveys will be widespread in the future.

The paper aims to provide insights for researchers with different levels of online survey experience. And both academics and practitioners should gain insights.

Adhering to a strong ethics code is vital to gain respondents’ trust and to produce valid results.

Conclusions and recommendations are offered in these specific areas: defining concepts, understanding the future role of surveys, developing and implementing surveys and a survey code of ethics. The literature review cites more than 200 sources.

Responses to minimum income and minimum spending questions are used to produce economic well-being thresholds. Thresholds are estimated using a regression framework. Regression coefficients are based on U.S. Survey of Income and Program Participation (SIPP) data and then applied to U.S. Consumer Expenditure Survey (CE) data. Three different resource measures are compared to the estimated thresholds. The first resource measure is total before-tax money income, and the other two are expenditure based. The first of these two refers to expenditure outlays and the second to outlays adjusted for the value of the service flow of owner-occupied housing (rental equivalence). The income comparison is based on SIPP data while the outlays comparisons are based on CE data. Results using official poverty thresholds are shown for comparison. This is among the earliest work in the U.S. in which expenditure outlays have been used for economic well-being determinations in combination with personal assessments, and the first time rental equivalence has been used in such an exercise. Comparisons of expenditures for various bundles of commodities are compared to the CE derived thresholds to provide insight concerning what might be considered minimum or basic.

Results reveal that CE and SIPP MIQ thresholds are higher than MSQ thresholds, and resulting poverty rates are also higher with the MIQ. CE-based MSQ thresholds are not statistically different from average expenditure outlays for food, apparel, and shelter and utilities for primary residences. When reported rental equivalences for primary residences that are owner occupied are substituted for out-of-pocket shelter expenditures, single elderly are less likely to be as badly off as they would be with a strict outlays approach in defining resources.

The purpose of this paper is to provide insightful advice that can improve the practice of using consumers’ pre-launch awareness and preference (AP) changes to predict the sales of new movies.

This paper applies a new movie box-office revenue forecasting model based on consumers’ weekly AP measures, to take advantage of the industry’s practice of using weekly survey data containing the AP measures of upcoming new movies. Specifically, a sales forecasting model is developed on the basis of the theory that the combination of the nature of new product preference (positive vs negative) and the timing of new product awareness (early vs recent) influences entertainment product sales.

This paper shows that early awareness consumers are as important as late awareness consumers in determining new product sales, suggesting that more marketing resources need to be allocated earlier than currently practiced. This paper also shows that when negative preferences dominate positive preferences well ahead of a product’s release, marketing efforts cannot overcome the negative sentiment of the market. Finally, the empirical application illustrates that three consumer segments varying in product expertise and consumption frequency reveal different AP patterns among high-, medium- and low-performance products.

This paper is intended to provide insightful advice that can improve the AP-based approach in entertainment industries. Toward that end, the authors emphasize two major aspects in association with new entertainment product sales: rethinking survey-based AP measures and examining heterogeneous consumer segments’ differential AP patterns.

The purpose of this study was to identify the major quality features of wearable technology embedded products that have the greatest impact on consumer satisfaction using the Kano model, an organized approach to specify consumer requirements and expectation through a preference classification technique.

Using a quantitative research method, an online survey was conducted with a convenience sample of US consumers aged between 19 years old and over. A total of otal 471 useable data were obtained and used for the data analysis.

This study identified that the 11 quality features of wearables belong to one-dimensional quality category among the five Kano categories, although the impact of each quality feature's performance on consumer satisfaction varies. The results also showed that the performance level of durability, long battery life, usability, product safety, comfortability and reasonable price has the greatest impact on consumer satisfaction of wearables.

This study has implications for future research by integrating the Kano model with other design and product development related theoretical models when designing, developing and evaluating various wearable products.

This study quantified the key quality features of wearables using the Kano model, which can be a great measurement tool for future researchers to adopt in their studies. The findings of this study help designers, developers and producers of wearables to prioritize the quality features during the product design, development and manufacturing process.

This study is concerned with evaluating the Federal Reserve forecasts of light motor vehicle sales. The goal is to assess accuracy gains from using consumer vehicle-buying attitudes and expectations about future business conditions derived from the long-running Michigan Surveys of Consumers.

Simplicity is a core principle in forecasting, and the literature provides plentiful evidence that combining forecasts from different methods and models reduces out-of-sample forecast errors if the methods and models are valid. As such, the authors construct a simple vector autoregressive (VAR) model that incorporates consumer vehicle-buying attitudes and expectations about future business conditions. Comparable forecasts of vehicle sales from this model are then combined with the Federal Reserve forecasts to assess accuracy gains.

The findings for 1994–2016 indicate that the Federal Reserve and VAR forecasts contain distinct and useful predictive information, and the combination of the two forecasts shows reductions in forecast errors that are more significant at longer horizons. The authors thus conclude that there are accuracy gains from using consumer survey responses.

This is the first study that is concerned with evaluating the Federal Reserve forecasts of vehicle sales and examines whether there are accuracy gains from using consumer vehicle-buying attitudes and expectations.

The purpose of this paper is to define the sustainability attributes of frozen and fresh food consumption in a typical household. The reason for writing this paper is that food preservation is often overlooked when developing sustainability strategies.

This study uses established carbon footprint data for specific food types and consumer survey data to determine how consumers use fresh and frozen products in the home. Consumption and waste data for 83 households was obtained using a combination of narrative and graphical association questions.

The results show greenhouse gas emissions associated with a diets containing frozen food are reduced because 47 per cent less frozen foods is wasted as compared to fresh foods with a typical household wasting 10.4 per cent of fresh food and 5.9 per cent frozen food.

This research has highlighted the importance of understanding the waste impacts of catering and food service consumption outside the home.

This research will guide future product development for frozen foods with regard to dietary planning and portion control.

The cost and sustainability benefits of meal planning are identified and these will inform policy making and education to improve dietary choices.

This work extends the scope of current consumer surveys that assess quality, value and taste attributes to sustainability criteria and it will enable collaboration between fresh and frozen product categories to deliver sustainable dietary options.