Journal of Applied Econometrics
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GENERALIZED AUTOREGRESSIVE SCORE MODELS WITH APPLICATIONS SUMMARY We propose a class of observation‐driven time series models referred to as generalized autoregressive score (GAS) models. The mechanism to update the parameters over time is the scaled score of the likelihood function. This new approach provides a unified and consistent framework for introducing time‐varying parameters in a wide class of nonlinear models. The GAS model encompasses other well‐known models such as the generalized autoregressive conditional heteroskedasticity, autoregressive conditional duration, autoregressive conditional intensity, and Poisson count models with time‐varying mean. In addition, our approach can lead to new formulations of observation‐driven models. We illustrate our framework by introducing new model specifications for time‐varying copula functions and for multivariate point processes with time‐varying parameters. We study the models in detail and provide simulation and empirical evidence. Copyright © 2012 John Wiley & Sons, Ltd.
Journal of Applied Econometrics - Tập 28 Số 5 - Trang 777-795 - 2013
Growth Determinants Revisited Using Limited‐Information Bayesian Model Averaging Summary We revisit the growth empirics debate using a novel limited‐information Bayesian model averaging framework in short T panels that addresses model uncertainty, dynamics, and endogeneity. We construct an estimator without restrictive distributional assumptions, illustrate its performance using simulations, and apply it to the investigation of growth determinants. Once model uncertainty, dynamics, and endogeneity are accounted for, we identify several factors that are robustly correlated with growth. We find the strongest support for the neoclassical growth variables including initial income and proxies for physical and human capital accumulation, as well as evidence in favor of both fundamental and proximate factors including macroeconomic policy, geography, and ethnic heterogeneity. In addition, we demonstrate that applying methodologies that do not account for either dynamics or endogeneity yields different sets of robust determinants. Copyright © 2015 John Wiley & Sons, Ltd.
Journal of Applied Econometrics - Tập 31 Số 1 - Trang 106-132 - 2016
THE ROLE OF INVENTORIES AND SPECULATIVE TRADING IN THE GLOBAL MARKET FOR CRUDE OIL SUMMARY We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short‐run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil. Copyright © 2013 John Wiley & Sons, Ltd.
Journal of Applied Econometrics - Tập 29 Số 3 - Trang 454-478 - 2014
A simple panel unit root test in the presence of cross‐section dependence Abstract A number of panel unit root tests that allow for cross‐section dependence have been proposed in the literature that use orthogonalization type procedures to asymptotically eliminate the cross‐dependence of the series before standard panel unit root tests are applied to the transformed series. In this paper we propose a simple alternative where the standard augmented Dickey–Fuller (ADF) regressions are augmented with the cross‐section averages of lagged levels and first‐differences of the individual series. New asymptotic results are obtained both for the individual cross‐sectionally augmented ADF (CADF) statistics and for their simple averages. It is shown that the individual CADF statistics are asymptotically similar and do not depend on the factor loadings. The limit distribution of the average CADF statistic is shown to exist and its critical values are tabulated. Small sample properties of the proposed test are investigated by Monte Carlo experiments. The proposed test is applied to a panel of 17 OECD real exchange rate series as well as to log real earnings of households in the PSID data. Copyright © 2007 John Wiley & Sons, Ltd.
Journal of Applied Econometrics - Tập 22 Số 2 - Trang 265-312 - 2007
Anchoring the yield curve using survey expectations Summary The dynamic behavior of the term structure of interest rates is difficult to replicate with models, and even models with a proven track record of empirical performance have underperformed since the early 2000s. On the other hand, survey expectations can accurately predict yields, but they are typically not available for all maturities and/or forecast horizons. We show how survey expectations can be exploited to improve the accuracy of yield curve forecasts given by a base model. We do so by employing a flexible exponential tilting method that anchors the model forecasts to the survey expectations, and we develop a test to guide the choice of the anchoring points. The method implicitly incorporates into yield curve forecasts any information that survey participants have access to—such as information about the current state of the economy or forward‐looking information contained in monetary policy announcements—without the need to explicitly model it. We document that anchoring delivers large and significant gains in forecast accuracy relative to the class of models that are widely adopted by financial and policy institutions for forecasting the term structure of interest rates.
Journal of Applied Econometrics - Tập 32 Số 6 - Trang 1055-1068 - 2017
Bounds testing approaches to the analysis of level relationships Abstract This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend‐ or first‐difference stationary. The proposed tests are based on standardF ‐ andt ‐statistics used to test the significance of the lagged levels of the variables in a univariate equilibrium correction mechanism. The asymptotic distributions of these statistics are non‐standard under the null hypothesis that there exists no level relationship, irrespective of whether the regressors areI (0) orI (1). Two sets of asymptotic critical values are provided: one when all regressors are purelyI (1) and the other if they are all purelyI (0). These two sets of critical values provide a band covering all possible classifications of the regressors into purelyI (0), purelyI (1) or mutually cointegrated. Accordingly, various bounds testing procedures are proposed. It is shown that the proposed tests are consistent, and their asymptotic distribution under the null and suitably defined local alternatives are derived. The empirical relevance of the bounds procedures is demonstrated by a re‐examination of the earnings equation included in the UK Treasury macroeconometric model. Copyright © 2001 John Wiley & Sons, Ltd.
Journal of Applied Econometrics - Tập 16 Số 3 - Trang 289-326 - 2001
How do respondents process stated choice experiments? Attribute consideration under varying information load Abstract The popularity of stated choice (SC) experiments has produced many design strategies in which researchers use increasingly more ‘complex’ choice settings to study choice behaviour. When the amount of information to assess increases, we wonder how an individual handles such information in making a choice. Defining the amount of information as the number of attributes associated with each choice set, we investigate how this information is processed as we vary its ‘complexity’. Four ordered heterogeneous logit models are developed, each for an SC design based on a fixed number of attributes, in which the dependent variable defines the number of attributes that are ignored. We find that the degree to which individuals ignore attributes is influenced by the dimensionality of the SC experiment, the deviation of attribute levels from an experienced reference alternative, the use of ‘adding up’ attributes where feasible, the number of choice sets evaluated, and the personal income of the respondent. The empirical evidence supports the view that individuals appear to adopt a range of ‘coping’ strategies that are consistent with how they process information in real markets, and that aligning ‘choice complexity’ with the amount of information to process is potentially misleading. Relevancy is what matters. Copyright © 2006 John Wiley & Sons, Ltd.
Journal of Applied Econometrics - Tập 21 Số 6 - Trang 861-878 - 2006
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