Can overconfidence explain the consumption hump?

The standard neoclassical life-cycle model predicts that individual consumption should either increase, remain constant or fall monotonically depending on whether the market rate of return on savings is greater than, equal to or less than the discount rate. However, empirical evidence suggests that even after controlling for economic growth and family size, household consumption exhibits a robust hump at around age 45–55, with the ratio of peak consumption to consumption when entering the workforce greater than 1.1. This paper extends the “overconfidence” explanation (Caliendo and Huang, J. Macroecon 30(4):1347–1369, 2008) of this macroeconomic puzzle to a calibrated general equilibrium environment. The main finding is that although it is possible to identify parameter values under which overconfidence alone generates life-cycle consumption profiles and macro-indicators consistent with U.S. experience, quite extreme assumptions about both the magnitude and distribution of overconfidence in the population are generally required to obtain them.     

Complexity results for the weak axiom of revealed preference for collective consumption models

The purpose of this paper is to establish the complexity of alternative versions of the weak axiom of revealed preference (warp) for collective consumption models. In contrast to the unitary consumption model, these collective models explicitly take the multi-member nature of the household into account. We consider the three collective settings that are most often considered in the literature. We start with the private setting in which all goods are privately consumed by the household members. Next, we consider the public setting in which all goods are publicly consumed inside the household. Finally, we also consider the general setting where no information on the (private or public) nature of goods consumed in the household is available. We prove that the collective version of warp is np-hard to test for both the private and public settings. Surprisingly, we also find for the general setting that the collective version of warp is easy to test for two-member households.     

Tenure choice and the riskiness of non-housing consumption

This paper analyzes a household's choice of housing tenure within a dynamic utility maximization model that yields simple analytical results under uncertainty of income, housing prices, and rents. Given a housing consumption plan, we show that a decrease in the covariance between a household's earnings and housing rents increases the likelihood of ownership. A household who plans to remain in its home over a long period is more likely to own; a household who plans to remain in its home over a short period is more likely to rent. The higher the covariance between the user cost of a home and that of other properties a household is likely to consider in the future, the more likely the household is to own this home. These predictions of our model find support in recent empirical studies.     

A methodology for comparing predictions from many models to few data

A common problem in data analysis occurs when one has many models to compare to a single or just a few data sets. For example, a researcher may conduct an experiment in which subjects respond by choosing one category from a small set of categories. The data set then consists of the frequencies with which the categories occur. Many substantive models may yield predictions of these frequencies, so that the researcher is faced with the problem of comparing the data to many a priori equally attractive theoretical predictions. This paper proposes a method for the simultaneous study of the predictions and data. The method improves on the standard approach to judging goodness-of-fit by treating the predictions as rows in a two (or higher) way contingency table. Log linear models for the probabilities that subjects respond in specific ways are used to determine how the predictions compare to the data and to rank the predictions in terms of their accuracy.     

Forecasting electricity prices with expert,linear, and nonlinear models

This paper compares several models for forecasting regional hourly day-ahead electricity prices, while accounting for fundamental drivers. Forecasts of demand, in-feed from renewable energy sources, fossil fuel prices, and physical flows are all included in linear and nonlinear specifications, ranging in the class of ARFIMA-GARCH models—hence including parsimonious autoregressive specifications (known as expert-type models). The results support the adoption of a simple structure that is able to adapt to market conditions. Indeed, we include forecasted demand, wind and solar power, actual generation from hydro, biomass, and waste, weighted imports, and traditional fossil fuels. The inclusion of these exogenous regressors, in both the conditional mean and variance equations, outperforms in point and, especially, in density forecasting when the superior set of models is considered. Indeed, using the model confidence set and considering northern Italian prices, predictions indicate the strong predictive power of regressors, in particular in an expert model augmented for GARCH-type time-varying volatility. Finally, we find that using professional and more timely predictions of consumption and renewable energy sources improves the forecast accuracy of electricity prices more than using predictions publicly available to researchers.     

What do interest rates reveal about the functioning of real business cycle models?

This paper begins by documenting the extent to which the predictions of standard Real Business Cycle (RBC) models are incompatible with observed movements in real interest rates. The main finding of the paper is that extending the baseline model to include habit persistence in consumption and adjustment costs to capital significantly improves the model's empirical performance. In our evaluation of the model's performance, we take special care of estimating and testing predictions of the model using both moments drawn directly from the data and moments calculated after identifying shocks to the stochastic trend.     

General consumption constraints and regular economies

In the spirit of Smale’s work, we consider pure exchange economies with general consumption sets. In this paper, the consumption set of each household is described in terms of a function called possibility function. The main innovation comes from the dependency of each possibility function with respect to the individual endowments. We prove that, generically in the space of endowments and possibility functions, economies are regular. A regular economy has a finite number of equilibria, which locally depend on endowments and possibility functions in a continuous manner.     

Equivalent representations of non-exponential discounting models

I characterize the entire class of consumption rules for finite-horizon models in which consumption is proportional to lifetime wealth. Any such rule can be obtained from a preference model with CRRA period utility. In a steady state with constant interest rates, a proportional consumption rule can be derived from a model with time-consistent preferences or from a model with possibly time-inconsistent preferences in which a household continually reoptimizes future utility discounted relative to the present instant. These two preference models will only coincide for the special case when the discount function is exponential. More generally, there will be two distinct yet observationally equivalent preference models. Hyperbolic-like discounting may arise because that is a simpler way for the brain to process a standard exponential discount function after accounting for mortality risk.     

A model of population distribution,traffic congestion,and neighborhood crowding in a circular city

An idealized static equilibrium model of a circularly symmetric city is presented. The model allows one to compute the spatial distribution of residences, given certain simple and plausible assumptions about the “costs” of transport, housing and neighborhood crowding. The model is chosen so as to guarantee that in first approximation, the residential population distribution which would be considered optimal by a perfect planner is identical to the distribution reached in a push-shove, laissez-faire equilibrium. This aspect of the construction is shown to be related in a simple way to the familiar “external diseconomy” situation in which a free resource is allocated among alternative uses by equating average, rather than marginal products. The existence of an infinite class of models in which the associated planner's optimum and laissez-faire equilibria are equivalent follows naturally from the standard theory of the private and social costs of highway congestion. The model leads naturally to exponentially falling population distributions which exhibit an “urban-suburban” dichotomy, to a particular overall city size, and to an optimal allocation of land between transport and residential uses.     

INTEGRATING A HOUSEHOLD DEMAND SYSTEM IN THE INPUT–OUTPUT FRAMEWORK. METHODOLOGICAL ASPECTS AND MODELLING IMPLICATIONS

In this paper we argue that an accurate representation of household consumption behaviour is central to the analysis and comparison of policy interventions addressing sustainable consumption. Therefore, we propose to extend an input–output model with a specific household consumption model, at the core of which is a system of equations explaining the allocation of the households' overall expenditure across different purposes, such as buying food, the consumption of fuel for heating or electricity for cooling, education of children or travelling in terms of total expenditure and relative prices. This paper shows that the integration of a specific module for household consumption in a standard input–output model is an improvement for the analysis of the policies aimed at altering consumer behaviour.     

Long-run risk and hidden growth persistence

An extensive literature has analyzed the implications of hidden shifts in the dividend growth rate. However, corresponding research on learning about growth persistence is completely lacking. Hidden persistence is a novel way to introduce long-run risk into standard business-cycle models of asset prices because it tightly intertwines the cyclical and long-run frequencies. Hidden persistence magnifies endogenous changes in the forecast variance of the long-run dividend growth rate despite homoscedastic consumption innovations. Not only does changing forecast variance make discrimination between protracted spells of anemic growth and brief business recessions difficult, it also endogenously induces additional variation in asset price discounts due to the preference for early uncertainty resolution.     

Incomplete information and the time series behaviour of consumption

Pischke ( 1995 ) uses both microeconomic and macroeconomic US data to test the idea that, within an otherwise standard PIH framework, ignorance by agents of aggregate labour income can account for the observed degree of excess smoothness and sensitivity in consumption. His tests involve only the second moments of aggregate consumption and labour income. In this paper our main aim is to identify and test the restrictions his model implies for aggregate consumption dynamics, using US quarterly data over the period 1959–1996, but our framework allows us also to test an earlier, related model of Goodfriend ( 1992 ). We find that both models can be formally rejected: ignorance of aggregate labour income cannot by itself account for aggregate consumption dynamics; some other relaxation of the assumptions of the standard PIH is required. We give an example of one possible such relaxation and present evidence indicating that Pischke's version of imperfect information may, within that framework, have a significant role to play. Copyright © 2000 John Wiley & Sons, Ltd.     

Formal sector job growth and women’s labor sector participation : The case of Mexico

This paper looks at the effects of demand and supply on the determinants of labor sector (school, home work, informal, and formal) participation between Torreon and Tijuana, Mexico for married and single women. Comparisons between the two cities are used to capture differences in labor demand. Torreon is a traditional city with an agri-industrial base and Tijuana is a border city with large export processing (maquiladora) and tourism sectors, both of which demand female labor. Factors influencing labor supply include both individual and household characteristics. Married women, given the strong cultural tradition of working in the home, do not significantly increase their paid labor participation with higher labor demand or changing characteristics of the household. Personal characteristics have the greatest impact on labor sector participation. Single women do, however, increase their formal sector participation with additional employment opportunities and respond to household needs by moving in and out of the paid labor market. Results indicate that increases in labor demand in Mexico from the NAFTA could expand formal sector labor force participation of single women.     

Household production, full consumption and the costs of children

Recent work criticises both the logic and relevance of the theoretical basis of the approach to estimating the costs of raising children adopted in much of the economics literature. This tends to be restricted purely to models in which the household members consume market goods with given household income. The “costs of children” are perceived essentially as market consumption costs. This ignores the fact that an important, possibly preponderant element of child costs takes the form of parental time, which must be diverted from alternative uses such as market work, other household production activities, and leisure, to care for children. The studies also ignore the question of the differential incidence of child costs on adult members of the household. In this paper, we first of all argue that a satisfactory theoretical approach to modelling child costs must simultaneously incorporate an “individualistic” formulation of the household and a formal treatment of household production. We then provide such a model. Using data from a time use survey we estimate specialised versions of the model for families with two children and use the results to derive the intra-family distribution of resources and implied child-rearing costs.     

Efficient estimation and inference in linear pseudo-panel data models

We consider pseudo-panel data models constructed from repeated cross sections in which the number of individuals per group is large relative to the number of groups and time periods. First, we show that, when time-invariant group fixed effects are neglected, the OLS estimator does not converge in probability to a constant but rather to a random variable. Second, we show that, while the fixed-effects (FE) estimator is consistent, the usual t statistic is not asymptotically normally distributed, and we propose a new robust t statistic whose asymptotic distribution is standard normal. Third, we propose efficient GMM estimators using the orthogonality conditions implied by grouping and we provide t tests that are valid even in the presence of time-invariant group effects. Our Monte Carlo results show that the proposed GMM estimator is more precise than the FE estimator and that our new t test has good size and is powerful.     

Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.     

Growth vs. level effect of population change on economic development: An inspection into human-capital-related mechanisms

This paper studies the different mechanisms and the dynamics through which demography is channeled to the economy. We analyze the role of demographic changes in the economic development process by studying the transitional and the long-run impact of both the rate of population growth and the initial population size on the levels of per capita human capital and income. We do that in an enlarged Lucas–Uzawa model with intergenerational altruism. In contrast to the existing theoretical literature, the long-run level effects of demographic changes, i.e. their impact on the levels of the variables along the balanced growth path, are deeply characterized in addition to the more standard long-run growth effects. We prove that the level effect of the population rate of growth is non-negative (positive in the empirically most relevant case) for the average level of human capital, but a priori ambiguous for the level of per capita income due to the interaction of three transmission mechanisms of demographic shocks, a standard one (dilution) and two non-standard (altruism and human capital accumulation). Overall, the sign of the level effects of population growth depends on preference and technology parameters, but numerically we show that the joint negative effect of dilution and altruism is always stronger than the induced positive human capital effect. The growth effect of population growth depends basically on the attitude to intergenerational altruism and intertemporal substitution. Moreover, we also prove that the long-run level effects of population size on per capita human capital and income may be negative, nil, or positive, depending on the relationship between preferences and technology, while its growth effect is zero. Finally, we show that the model is able to replicate complicated time relationships between economic and demographic changes. In particular, it entails a negative effect of population growth on per capita income, which dominates in the initial periods, and a positive effect which restores a positive correlation between population growth and economic performance in the long term.     

Approximately normal tests for equal predictive accuracy in nested models

Forecast evaluation often compares a parsimonious null model to a larger model that nests the null model. Under the null that the parsimonious model generates the data, the larger model introduces noise into its forecasts by estimating parameters whose population values are zero. We observe that the mean squared prediction error (MSPE) from the parsimonious model is therefore expected to be smaller than that of the larger model. We describe how to adjust MSPEs to account for this noise. We propose applying standard methods [West, K.D., 1996. Asymptotic inference about predictive ability. Econometrica 64, 1067–1084] to test whether the adjusted mean squared error difference is zero. We refer to nonstandard limiting distributions derived in Clark and McCracken [2001. Tests of equal forecast accuracy and encompassing for nested models. Journal of Econometrics 105, 85–110; 2005a. Evaluating direct multistep forecasts. Econometric Reviews 24, 369–404] to argue that use of standard normal critical values will yield actual sizes close to, but a little less than, nominal size. Simulation evidence supports our recommended procedure.     

Time-varying (S, s) band models: Properties and interpretation

A recent strand of empirical work uses (S, s) models with time-varying stochastic bands to describe infrequent adjustments of prices and other variables. The present paper examines some properties of this model, which encompasses most micro-founded adjustment rules rationalizing infrequent changes. We illustrate that this model is flexible enough to fit data characterized by infrequent adjustment and variable adjustment size. We show that, to the extent that there is variability in the size of adjustments (e.g. if both small and large price changes are observed), (i) a large band parameter is needed to fit the data and (ii) the average band of inaction underlying the model may differ strikingly from the typical observed size of adjustment. The paper thus provides a rationalization for a recurrent empirical result: very large estimated values for the parameters measuring the band of inaction.