Processes with volatility-induced stationarity: an application for interest rates

In this paper we propose a refinement of the existing definition of volatility-induced stationarity that allows us to distinguish between processes with drift and diffusion induced stationarity and processes with pure volatility-induced stationarity. We also propose a classification of stationary processes with volatility-induced stationarity according to the volatility that is needed to inject stationarity. Processes with volatility-induced stationarity are potentially applicable to interest rate time-series since, as has been acknowledged, mean-reversion effects occur mainly in periods of high volatility. As such, we provide evidence that the logarithm of the Fed funds rate can be modelled as a local martingale with volatility-induced stationarity.     

Regime switching in stochastic models of commodity prices: An application to an optimal tree harvesting problem

This paper investigates whether a regime switching model of stochastic lumber prices is better for the analysis of optimal harvesting problems in forestry than a more traditional single regime model. Prices of lumber derivatives are used to calibrate a regime switching model, with each of two regimes characterized by a different mean reverting process. A single regime, mean reverting process is also calibrated. The value of a representative stand of trees and optimal harvesting prices are determined by specifying a Hamilton-Jacobi-Bellman Variational Inequality, which is solved for both pricing models using a implicit finite difference approach. The regime switching model is found to more closely match the behavior of futures prices than the single regime model. In addition, analysis of a tree harvesting problem indicates significant differences in terms of land value and optimal harvest thresholds between the regime switching and single regime models.     

Model selection in stochastic frontier analysis with an application to maize production in Kenya

This paper shows how to compute the standard errors for partial effects of exogenous firm characteristics influencing firm inefficiency under a range of popular stochastic frontier model specifications. We also develop an R²-type measure to summarize the overall explanatory power of the exogenous factors on firm inefficiency. The paper also applies a recently developed model selection procedure to choose among alternative stochastic frontier specifications using data from household maize production in Kenya. The magnitude of estimated partial effects of exogenous household characteristics on inefficiency turns out to be very sensitive to model specification, and the model selection procedure leads to an unambiguous choice of best model. We propose a bootstrapping procedure to evaluate the size and power of the model selection procedure. The empirical application also provides further evidence on how household characteristics influence technical inefficiency in maize production in developing countries.

Panel data methods for fractional response variables with an application to test pass rates

We revisit the effects of spending on student performance using data from the state of Michigan. In addition to exploiting a dramatic change in funding in the mid-1990s and subsequent nonsmooth changes, we propose nonlinear panel data models that recognize the bounded nature of the pass rate. Importantly, we show how to estimate average partial effects, which can be compared across many different models (linear and nonlinear) under different assumptions and estimated using many different methods. We find that spending has nontrivial and statistically significant effects, although the diminishing effect is not especially pronounced.     

A flexible parametric GARCH model with an application to exchange rates

Many asset prices, including exchange rates, exhibit periods of stability punctuated by infrequent, substantial, often one‐sided adjustments. Statistically, this generates empirical distributions of exchange rate changes that exhibit high peaks, long tails, and skewness. This paper introduces a GARCH model, with a flexible parametric error distribution based on the exponential generalized beta (EGB) family of distributions. Applied to daily US dollar exchange rate data for six major currencies, evidence based on a comparison of actual and predicted higher‐order moments and goodness‐of‐fit tests favours the GARCH‐EGB2 model over more conventional GARCH‐t and EGARCH‐t model alternatives, particularly for exchange rate data characterized by skewness. Copyright © 2001 John Wiley & Sons, Ltd.     

Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers

We consider classes of multivariate distributions which can model skewness and are closed under orthogonal transformations. We review two classes of such distributions proposed in the literature and focus our attention on a particular, yet quite flexible, subclass of one of these classes. Members of this subclass are defined by affine transformations of univariate (skewed) distributions that ensure the existence of a set of coordinate axes along which there is independence and the marginals are known analytically. The choice of an appropriate m-dimensional skewed distribution is then restricted to the simpler problem of choosing m univariate skewed distributions. We introduce a Bayesian model comparison setup for selection of these univariate skewed distributions. The analysis does not rely on the existence of moments (allowing for any tail behaviour) and uses equivalent priors on the common characteristics of the different models. Finally, we apply this framework to multi-output stochastic frontiers using data from Dutch dairy farms.     

A non-linear filtering approach to stochastic volatility models with an application to daily stock returns

This paper develops a new model for the analysis of stochastic volatility (SV) models. Since volatility is a latent variable in SV models, it is difficult to evaluate the exact likelihood. In this paper, a non-linear filter which yields the exact likelihood of SV models is employed. Solving a series of integrals in this filter by piecewise linear approximations with randomly chosen nodes produces the likelihood, which is maximized to obtain estimates of the SV parameters. A smoothing algorithm for volatility estimation is also constructed. Monte Carlo experiments show that the method performs well with respect to both parameter estimates and volatility estimates. We illustrate our model by analysing daily stock returns on the Tokyo Stock Exchange. Since the method can be applied to more general models, the SV model is extended so that several characteristics of daily stock returns are allowed, and this more general model is also estimated. Copyright © 1999 John Wiley & Sons, Ltd.     

Utility maximization in a stochastic affine interest rate and CIR risk premium framework: a BSDE approach

Decisions in Economics and Finance - This paper investigates optimal investment problems in the presence of stochastic interest rates and stochastic volatility under the expected utility...     

Cost efficiency of Slovenian water distribution utilities: an application of stochastic frontier methods

This study estimates cost inefficiency and economies of scale of Slovenian water distribution utilities over the 1997–2003 period by employing several different stochastic frontier methods. The results indicate that significant cost inefficiencies are present in the utilities. An introduction of incentive-based price regulation scheme might help resolve this problem. However, the inefficiency scores obtained from different cost frontier models are not found to be robust. The levels of inefficiency estimates as well as the rankings depend on the econometric specification of the model. The established lack of robustness can be at least partly explained by different ability of the models to separate unobserved heterogeneity from inefficiency. Newly proposed true fixed effects model (Greene, J Econom 126:269–303, 2005; J Prod Anal 23(1):7–32, 2005) appears to perform better than the conventional panel data models with respect to distinguishing between unobserved heterogeneity and inefficiency. On the other hand, different models produce fairly robust results with respect to estimates of economies of output density, customer density and economies of scale. The optimal size of a company is found to closely corresponds to the sample median. Economies of scale are found in small-sized utilities, while large companies exhibit diseconomies of scale.

Econometric methods for fractional response variables with an application to 401(k) plan participation rates

We develop attractive functional forms and simple quasi-likelihood estimation methods for regression models with a fractional dependent variable. Compared with log-odds type procedures, there is no difficulty in recovering the regression function for the fractional variable, and there is no need to use ad hoc transformations to handle data at the extreme values of zero and one. We also offer some new, robust specification tests by nesting the logit or probit function in a more general functional form. We apply these methods to a data set of employee participation rates in 401(k) pension plans.     

Continuous and discrete models in finance,in particular for stochastic interest rates

The paper explains a general method for constructing interest rate models in discrete time. The relevant term structure can be computed recursively in the Markovian case with finite state space. Calculations become particularly easy for binary and ternary tree structures.It is instructive to look at the diffusion limits of such Markov Chains. This diffusion limit does not inherit all properties of the Markov Chain which it approximates.     

The quantilogram: With an application to evaluating directional predictability

We propose a new diagnostic tool for time series called the quantilogram. The tool can be used formally and we provide the inference tools to do this under general conditions, and it can also be used as a simple graphical device. We apply our method to measure directional predictability and to test the hypothesis that a given time series has no directional predictability. The test is based on comparing the correlogram of quantile hits to a pointwise confidence interval or on comparing the cumulated squared autocorrelations with the corresponding critical value. We provide the distribution theory needed to conduct inference, propose some model free upper bound critical values, and apply our methods to S&P500 stock index return data. The empirical results suggest some directional predictability in returns. The evidence is strongest in mid range quantiles like 5–10% and for daily data. The evidence for predictability at the median is of comparable strength to the evidence around the mean, and is strongest at the daily frequency.     

Markov analysis of land use change—an application of stochastic processes to remotely sensed data

The change of land use on San Juan Island, Washington, during the period 1949–1971 is studied to see if the process is compatible with the Markov hypothesis: that past land use is not helpful in predicting future land use, given the present pattern. This hypothesis is tested using a χ²-test and the conclusion is that the data is more compatible with the hypothesis than not. The conclusions have implications for the design of programs for collecting aerial photographic information as well as information systems based on such data. The emphasis of the paper is, however, on the use by planners for projecting land use change when the Markov hypothesis holds.     

The sensitivity of efficiency scores to input and other choices in stochastic frontier analysis: an empirical investigation

Journal of Productivity Analysis - Productivity and efficiency analysis have gained substantial attention in many industries over the last two decades, and stochastic frontier analysis has been one...     

National sovereignty and transnational labour: the case of Mexican seasonal agricultural workers in British Columbia,Canada

This article analyses the experience of recently unionised Mexican seasonal agricultural workers in British Columbia, Canada, whose visa reapplications were blocked by Mexico and a concomitant complaint to the province's labour board. Illustrating the significance of this sending state's actions, it reveals the growing disjuncture between nationally based labour relations systems and transnational labour.     

More powerful panel data unit root tests with an application to mean reversion in real exchange rates

Unit root tests, seeking mean or trend reversion, are frequently applied to panel data. We show that more powerful variants of commonly applied tests are readily available. Moreover, power gains persist when the modifications are applied to bootstrap procedures that may be employed when cross‐correlation of a rather general sort among individual panel members is suspected. Copyright © 2004 John Wiley & Sons, Ltd.     

The performance implications of the work-oriented cognitions of shopfloor workers: a study of British retailing

While a number of studies have been conducted into individual employee cognitions and organizational performance, few studies have examined the combined effect of a range of cognitions. This gap in extant knowledge is particularly apparent in the retail sector where store performance and consequently company profitability are largely dependent on the relationship between shopfloor workers and customers. This paper presents the results of a study into the performance implications of work-oriented cognitions of shopfloor workers in the retail sector. The paper presents a series of analyses which find that the performance of individual stores is affected, to varying degrees, by a range of cognitions. The paper concludes by discussing the implications of the study and highlighting the issues which merit further research attention.     

The age profile of mobility measures: an application to earnings in West Germany

This paper develops a technique for estimating age-profiles of earnings mobility using conditional kernel density estimation and establishes their statistical properties. Both pointwise and simultaneous confidence intervals are derived. The paper then examines the age-profile of short-run earnings mobility in Germany between 1983 and 1993 using the Socio-Economic Panel data. It turns out that earnings mobility is significantly higher for young people than for elder ones. Mobility declines rather rapidly until the age of thirty-five or so and remains constant thereafter. The shape of the profile does not change significantly during the observation period. © 1998 John Wiley & Sons, Ltd.