Handbook of US consumer economics

Handbook of US consumer economics

"Handbook of U.S. Consumer Economics presents a deep understanding on key, current topics and a primer on the landscape of contemporary research on the U.S. consumer. This volume reveals new insights into household decision-making on consumption and saving, borrowing and investing, portfolio al...

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Bibliographic Details
Other Authors: Haughwout, Andrew, editor (editor), Mandel, B. J. (Benjamin J.), editor
Format: eBook
Language:Inglés
Published: London, England : Elsevier [2019]
Edition:[First edition]
Subjects:
Consumption (Economics) > United States.
United States > Economic conditions.
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009835426006719
Table of Contents:
  • Front Cover
  • Handbook of US Consumer Economics
  • Handbook of US Consumer Economics
  • Copyright
  • Contents
  • Contributors
  • Preface
  • 1 - Empirical analysis of the US consumer: fact, fiction, and the future
  • 1. Big(ger) data: new sources and new questions
  • 2. Consumer spending and the aggregate economy
  • 3. Household finance
  • 4. Responding to shocks
  • 5. Spending over the life cycle
  • 6. Measurement issues
  • 7. International perspectives
  • 8. Concluding thoughts
  • References
  • 2 - Handbook of the consumer chapter: trends in household debt and credit
  • 1. Overview
  • 2. Data
  • 3. Decomposing the borrowing cycle
  • 4. Trends in borrower characteristics
  • 5. Trends in other debt
  • 6. Perspectives on current household debt
  • 6.1 Change in debt composition
  • 6.2 Implications of the change in debt composition
  • 6.3 Delinquencies
  • 7. Conclusion
  • References
  • 3 - Trends in household portfolio composition∗
  • 1. Introduction
  • 2. Survey of consumer finances data and comparison to aggregates
  • 2.1 Wealth measurement: comparing the Survey of Consumer Finances to macroaggregates
  • 2.2 The Survey of Consumer Finances and other household finance research
  • 3. Composition of average household portfolios
  • 4. Household portfolios across the asset distribution
  • 4.1 Across time
  • 5. Asset concentration
  • 6. Cohorts
  • 6.1 Interpreting the cohort figures
  • 6.2 Median household assets
  • 6.3 Ownership of risky assets: business, equity, and housing
  • 6.4 Business ownership
  • 6.5 Equity ownership
  • 6.6 Home-ownership
  • 6.7 Mortgage holding
  • 6.7.1 The risky asset share
  • 6.8 Business share
  • 6.9 Equity share
  • 6.10 Housing share
  • 6.11 Combined risk asset share
  • 7. Financial vulnerability, shocks, and the health of the household balance sheet
  • 7.1 Risk from asset price shocks.
  • 7.2 Financial vulnerability: income and asset price shocks18
  • 7.3 Trends in vulnerability across time
  • 8. Conclusion
  • References
  • 4 - Household debt and recession in Brazil∗
  • 1. Introduction
  • 2. Aggregate view
  • 3. Novel data set on Brazilian household debt
  • 4. Characteristics of the household debt boom
  • 4.1 Composition of household debt
  • 4.2 Government-controlled banks and a tale of two booms
  • 4.3 Credit growth across the income distribution
  • 5. Potential causes of the household debt boom
  • 5.1 Macroeconomic context
  • 5.2 Institutional reforms and domestic programs
  • 5.3 International factors
  • 6. Concluding remarks
  • References
  • 5 - Rationality in the consumer credit market: choosing between alternative and mainstream credit∗
  • 1. Introduction
  • 2. Pawn credit as an alternative to regular bank credit
  • 3. Background: how pawnbroking works
  • 4. Data and summary statistics
  • 4.1 Data
  • 4.2 Summary statistics
  • 5. Main results
  • 5.1 Empirical implementation
  • 5.2 Access to mainstream credit for all swedes versus alternative credit users
  • 5.2.1 Awareness about creditworthiness and immigrant status
  • 6. Conclusion
  • References
  • 6 - How do consumers respond to real income shocks?
  • 1. Introduction
  • 2. JPMCI research on consumer spending responses to income and price changes
  • 2.1 Healthcare spending and tax refunds
  • 2.2 Consumer spending around job loss and the expiration of unemployment insurance benefits
  • 2.3 Consumer spending and the decline of gas prices between 2014 and 2015
  • 2.4 Consumption, investment, and mortgage resets
  • 2.5 Income fluctuations around mortgage defaults
  • 3. Conclusion
  • Appendix
  • References
  • 7 - Spending to and through retirement
  • 1. Introduction
  • 2. Description of data sources
  • 2.1 CE Survey
  • 2.2 HRS/CAMS Survey
  • 2.3 Chase data
  • 3. Literature review.
  • 3.1 The phased retirement hypothesis
  • 3.2 Quantitative evidence of spending reductions in retirement
  • 3.3 The retirement transition period
  • 4. The life cycle of spending
  • 4.1 Data Refinement
  • 4.2 The J.P. Morgan expenditure model
  • 4.3 Generational view
  • 4.4 Investable wealth levels
  • 4.5 Accounting for long-term care costs
  • 4.6 Implications of the life cycle of spending for plan providers and employers
  • 4.7 Implications of the life cycle of spending for firms that provide financial planning
  • 5 Shifting into retirement
  • 5.1 The retirement transition period data filter
  • 5.2 Defining "retirement"
  • 5.3 At what age do people retire?
  • 5.4 Average spending the year before versus the year after retirement
  • 5.5 Average spending the year before versus the year after retirement: households with at least 500,000 in investable wealth
  • 5.6 Beyond averages: distribution of changes in spending the year before versus the year after retirement
  • 5.7 Evidence of a retirement spending surge
  • 5.8 Spending volatility
  • 5.9 Spending volatility beyond the transition phase
  • 6. Implications
  • 6.1 Key takeaways for employers
  • 6.2 Ideas for firms that develop retirement plans for individuals
  • 7. Suggestions for further research
  • 8. Closing
  • References
  • 8 - Are millennials different?∗
  • 1. Introduction
  • 2. Definitions of generations and a review of research on age, generations, and economic decisions
  • 3. A comparison of demographics by generation
  • 4. Comparison of income and balance sheets by generation
  • 4.1 Income
  • 4.2 Debt
  • 4.3 Assets and net worth
  • 5. Comparison of consumption behavior by generation
  • 5.1 Household spending in the CE survey by age and generation
  • 5.2 An empirical assessment of generational consumption patterns
  • 5.3 Do millennials have a unique consumption basket?.
  • 6. Case study I: vehicle purchases
  • 6.1 Case study II: spending on food and housing
  • 7. Conclusion
  • Data appendix
  • References
  • 9 - China's consumer spending e-commerce: facts and evidence from JD's festival online sales∗
  • 1. Introduction
  • 2. Overall development of China's e-commerce
  • 2.1 China's main online retailers
  • 2.2 JD's E-Commerce data
  • 3. Patterns and key features of China's e-commerce
  • 3.1 Online consumer spending, by festival
  • 3.2 Online consumer spending, by product
  • 3.3 Online consumer spending, by age cohort
  • 3.4 Online consumer spending, by region
  • 4. E-commerce spending and regional income
  • 4.1 Trends and patterns against regional income
  • 4.2 Estimation results
  • 5. Concluding remarks
  • Appendices
  • References
  • 10 - Consumer expectations and the macroeconomy
  • 1. Disentangling preferences and expectations
  • 2. Survey data on subjective expectations
  • 3. Quantitative and probabilistic question formats
  • 4. The information content of probabilistic questions
  • 5. Are expectations data predictive?
  • 6. Integrating subjective expectations data into economic models of behavior
  • 7. Summary and directions for future research
  • References
  • 11 - Macro forecasting using alternative data
  • 1. The importance of macroeconomic measurement and prediction
  • 2. Important economic data releases and prediction
  • 3. Macro Data are Noisy
  • 3.1 The revision problem in traditional data
  • 3.2 Increased noise in times of low growth
  • 4. Our goal: real-time macro data with less noise
  • 4.1 Nowcasting
  • 4.2 The pyramid-like framework of nowcasting
  • 5. Alternative data
  • 5.1 The microfoundations of macro: alternative data in the context of the Lucas and Romer critique
  • 6. An framework for alternative data
  • 7. Predicting data releases with search data
  • 7.1 Why curate? The Google Flu story.
  • 7.2 Modeling differences rather than levels
  • 7.3 Housing, retail, and auto sectors with alternative data
  • 8. Modeling case study: Nonfarm payrolls
  • 8.1 Interpretable versus Blackbox or top-down versus bottom-up models via Kuhn
  • 8.2 The practical reason: modeling noise in small data sets
  • 8.3 The five keys: clean data, internal consistency, shrinkage, bootstrapping, and ensembling
  • 8.4 The model overconfidence metric
  • 8.5 Discussion of case study results
  • 9. Live production results
  • 9.1 Prediction in practice: the main mistakes17
  • 9.2 Public benefits of microfoundations of macro
  • 9.3 Two main contributions: accurate measurement and more detail
  • 9.4 Mitigating data colonialism?
  • Acknowledgments
  • References
  • 12 - Regional price parities in the United States
  • 1. Introduction
  • 2. Price levels for CPI areas
  • 3. Regional price parities for states and metropolitan areas
  • 4. Selected results
  • 4.1 Regional price parities for states
  • 4.2 Adjusted personal incomes for metropolitan and nonmetropolitan portions of states27
  • 5. Concluding remarks
  • Acknowledgments
  • References
  • 13 - Measuring prices and real household consumption of medical goods: service-based versus disease-based approaches
  • 1. Introduction
  • 2. Basic theoretical framework
  • 2.1 Utility and health
  • 2.2 Medical price and cost of living indexes
  • 2.3 Decomposing nominal expenditures
  • 3. The current service-based approach to medical measurement
  • 3.1 Current methods
  • 3.2 What current price indexes measure and do not measure
  • 4. The disease-based approach
  • 4.1 Single-disease price indexes
  • 4.2 General disease-based price indexes
  • 5. BLS experimental disease-based price indexes
  • 6. Data
  • 7. Results
  • 7.1 Trends in utilization by disease
  • 7.2 Disease-based price indexes
  • 7.3 Decomposition of nominal expenditures.
  • 8. Discussion and future work.

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