The role of no-arbitrage on forecasting: lessons from a parametric term structure model

Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.

The influence of materialism on consumption indebtedness in the context of low income consumers from the city of São Paulo

This research is in the domains of materialism, consumer vulnerability and consumption indebtedness, concepts frequently approached in the literature on consumer behavior, macro-marketing and economic psychology. The influence of materialism on consumer indebtedness is investigated within a context that is characterized by poverty and by factors that cause vulnerability, such as high interest rates, limited access to credit and to quality affordable goods. The objectives of this research are: to produce a materialism scale that is well adapted to its environment, characterizing materialism adequately for the population studied; to compare results obtained with results of other studies; and to measure the relationship between materialism, socio-demographic variables, attitude to debt and consumption indebtedness. The primary data used in the analyses were collected from field research carried out in August, 2005 that relied on a probabilistic household sample of 450 low income individuals who live in poor regions of the city of Sao Paulo. The materialism scale, adapted and translated into Portuguese from Richins (2004), proved to be very successful and encourages new work in the area. It was noted that younger adults tend to be more materialistic than older ones; that illiterate adults tend to be less materialistic than those who did literacy courses when they were already adults; and that gender, income and race are not associated with the materialism construct. Among the other results, a logistic regression model was developed in order to distinguish those individuals who have an installment plan payment booklet from those who do not, based on materialism, socio-demographic variables and purchasing and consumer habits. The proposed model confirms materialism as a behavioral variable useful for forecasting the probability of an individual getting into debt in order to consume, in some cases almost doubling the chance of occurrence of this event. Findings confirm the thesis that it is not only adverse economic factors that lead people to get into debt; and that the study of demand for credit for consumption purposes must, of necessity, include variables of a psychological nature. It is suggested that the low income materialistic consumer experiences feelings of powerlessness and exclusion because of the gap that exists between their possessions and their desires. Lines of conduct to combat this marginalization from the consumer society are drawn targeting marketing professionals, public policy makers and vulnerability researchers. Finally, the possibility of new studies involving the materialism construct, which is central to literature on consumer behavior, albeit little used in empirical studies in Brazil, are discussed.

Education, preferences for leisure, and the optimal income tax schedule

Recent advances in dynamic Mirrlees economies have incorporated the treatment of human capital investments as an important dimension of government policy. This paper adds to this literature by considering a two period economy where agents are di erentiated by their preferences for leisure and their productivity, both private information. The fact that productivity is only learnt later in an agent's life introduces uncertainty to agent's savings and human capital choices and makes optimal the use of multi-period tie-ins in the mechanism that characterizes the government policy. We show that optimal policies are often interim ine cient and that the introduction of these ine ciencies may take the form of marginal tax rates on labor income of varying sign and educational policies that include the discouragement of human capital acquisition. With regards to implementation, state-dependent linear taxes implement optimal savings, while human capital policies may require labor income taxes that depend directly on agents' schooling.

Income inequality in a job-search model with heterogeneous discount factors: (revised version, forthcoming 2006, Revista Economia)

This paper investigates the income inequality generated by a jobsearch process when di§erent cohorts of homogeneous workers are allowed to have di§erent degrees of impatience. Using the fact the average wage under the invariant Markovian distribution is a decreasing function of the discount factor (Cysne (2004, 2006)), I show that the Lorenz curve and the between-cohort Gini coe¢ cient of income inequality can be easily derived in this case. An example with arbitrary measures regarding the wage o§ers and the distribution of time preferences among cohorts provides some insights into how much income inequality can be generated, and into how it varies as a function of the probability of unemployment and of the probability that the worker does not Önd a job o§er each period.

Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: a Monte-Carlo study

Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The Örst reduces parameter space by imposing long-term restrictions on the behavior of economic variables as discussed by the literature on cointegration, and the second reduces parameter space by imposing short-term restrictions as discussed by the literature on serial-correlation common features (SCCF). Our simulations cover three important issues on model building, estimation, and forecasting. First, we examine the performance of standard and modiÖed information criteria in choosing lag length for cointegrated VARs with SCCF restrictions. Second, we provide a comparison of forecasting accuracy of Ötted VARs when only cointegration restrictions are imposed and when cointegration and SCCF restrictions are jointly imposed. Third, we propose a new estimation algorithm where short- and long-term restrictions interact to estimate the cointegrating and the cofeature spaces respectively. We have three basic results. First, ignoring SCCF restrictions has a high cost in terms of model selection, because standard information criteria chooses too frequently inconsistent models, with too small a lag length. Criteria selecting lag and rank simultaneously have a superior performance in this case. Second, this translates into a superior forecasting performance of the restricted VECM over the VECM, with important improvements in forecasting accuracy ñreaching more than 100% in extreme cases. Third, the new algorithm proposed here fares very well in terms of parameter estimation, even when we consider the estimation of long-term parameters, opening up the discussion of joint estimation of short- and long-term parameters in VAR models.

Inflation and income inequality: a shopping-time aproach: (Forthcoming, Journal of Development Economics)

Our work is based on a simpliÖed heterogenous-agent shoppingtime economy in which economic agents present distinct productivities in the production of the consumption good, and di§erentiated access to transacting assets. The purpose of the model is to investigate whether, by focusing the analysis solely on endogenously determined shopping times, one can generate a positive correlation between ináation and income inequality. Our main result is to show that, provided the productivity of the interest-bearing asset in the transacting technology is high enough, it is true true that a positive link between ináation and income inequality is generated. Our next step is to show, through analysis of the steady-state equations, that our approach can be interpreted as a mirror image of the usual ináation-tax argument for income concentration. An example is o§ered to illustrate the mechanism.

Income inequality in a job-search model with heterogeneous time preferences

This paper explores the use of an intertemporal job-search model in the investigation of within-cohort and between-cohort income inequality, the latter being generated by the heterogeneity of time preferences among cohorts of homogenous workers and the former by the cross-sectional turnover in the job market. It also offers an alternative explanation for the empirically-documented negative correlation between time preference and labor income. Under some speciÖc distributions regarding wage offers and time preferences, we show how the within-cohort and between-cohort Gini coe¢ cients of income distribution can be calculated, and how they vary as a function of the parameters of the model.

On the positive correlation between income inequality and unemployment

Several empirical studies in the literature have documented the existence of a positive correlation between income inequalitiy and unemployment. I provide a theoretical framework under which this correlation can be better understood. The analysis is based on a dynamic job search under uncertainty. I start by proving the uniqueness of a stationary distribution of wages in the economy. Drawing upon this distribution, I provide a general expression for the Gini coefficient of income inequality. The expression has the advantage of not requiring a particular specification of the distribution of wage offers. Next, I show how the Gini coefficient varies as a function of the parameters of the model, and how it can be expected to be positively correlated with the rate of unemployment. Two examples are offered. The first, of a technical nature, to show that the convergence of the measures implied by the underlying Markov process can fail in some cases. The second, to provide a quantitative assessment of the model and of the mechanism linking unemployment and inequality.

Towards a measure of income inequality freed from the volatility caused by variations in the rate of unemployment

By mixing together inequalities based on cyclical variables, such as unemployment, and on structural variables, such as education, usual measurements of income inequality add objects of a di§erent economic nature. Since jobs are not acquired or lost as fast as education or skills, this aggreagation leads to a loss of relavant economic information. Here I propose a di§erent procedure for the calculation of inequality. The procedure uses economic theory to construct an inequality measure of a long-run character, the calculation of which can be performed, though, with just one set of cross-sectional observations. Technically, the procedure is based on the uniqueness of the invariant distribution of wage o§ers in a job-search model. Workers should be pre-grouped by the distribution of wage o§ers they see, and only between-group inequalities should be considered. This construction incorporates the fact that the average wages of all workers in the same group tend to be equalized by the continuous turnover in the job market.

A search-theoretic explanation for the negative correlation between labor income and impatience

Lawrance (1991) has shown, through the estimation of consumption Euler equations, that subjective rates of impatience (time preference) in the U.S. are three to Öve percentage points higher for households with lower average labor incomes than for those with higher labor income. From a theoretical perspective, the sign of this correlation in a job-search model seems at Örst to be undetermined, since more impatient workers tend to accept wage o§ers that less impatient workers would not, thereby remaining less time unemployed. The main result of this paper is showing that, regardless of the existence of e§ects of opposite sign, and independently of the particular speciÖcations of the givens of the model, less impatient workers always end up, in the long run, with a higher average income. The result is based on the (unique) invariant Markov distribution of wages associated with the dynamic optimization problem solved by the consumers. An example is provided to illustrate the method.

Inflation and income inequality: A link through the job-search process

In this paper I devise a new channel by means of which the (empirically documented) positive correlation between ináation and income inequality can be understood. Available empirical evidence reveals that ináation increases wage dispersion. For this reason, the higher the ináation rate, the higher turns out to be the beneÖt, for a worker, of making additional draws from the distribution of wages, before deciding whether to accept or reject a job o§er. Assuming that some workers have less access to information (wage o§ers) than others, I show that the Gini coe¢ cient of income distribution turns out to be an increasing function of the wage dispersion and, consequently, of the rate of ináation. Two examples are provided to illustrate the mechanism.

Estimating the term structure of volatility and fixed income derivative pricing

Estimating the parameters of the instantaneous spot interest rate process is of crucial importance for pricing fixed income derivative securities. This paper presents an estimation for the parameters of the Gaussian interest rate model for pricing fixed income derivatives based on the term structure of volatility. We estimate the term structure of volatility for US treasury rates for the period 1983 - 1995, based on a history of yield curves. We estimate both conditional and first differences term structures of volatility and subsequently estimate the implied parameters of the Gaussian model with non-linear least squares estimation. Results for bond options illustrate the effects of differing parameters in pricing.