Nonlinear mean reversion in the term structure of interest rates

The expectations hypothesis implies that the yield curve provides information on the future change in the short-term interest rate. However, transaction costs exist in the financial market, which prevent investors from realizing the arbitrage opportunity, when the arbitrage does not fully cover the transaction costs. The purpose of this paper is to assess the effect of transaction costs on the predictability of the term structure by using the threshold vector error correction model, which allows for the nonlinear adjustment to the long-run equilibrium relationship. A significant amount of threshold effect is found, and the adjustment coefficients are regime-dependent. The empirical result supports the nonlinear mean reversion in the term structure of interest rates.     

ECONOMETRIC MODELS OF ASYMMETRIC PRICE TRANSMISSION

Abstract In this paper, we review the existing empirical literature on price asymmetries in commodities, providing a way to classify and compare different studies that are highly heterogeneous in terms of econometric models, type of asymmetries and empirical findings. Relative to the previous literature, this paper is novel in several respects. First, it presents a detailed and updated survey of the existing empirical contributions on price asymmetries in the transmission mechanism linking input prices to output prices. Second, this paper presents an extension of the traditional distinction between long‐run and short‐run asymmetries to new categories of asymmetries, such as: contemporaneous impact, distributed lag effect, cumulated impact, reaction time, equilibrium and momentum equilibrium adjustment path, regime effect, regime equilibrium adjustment path. Each empirical study is then critically discussed in the light of this new classification of asymmetries. Third, this paper evaluates the relative merits of the most popular econometric models for price asymmetries, namely autoregressive distributed lags, partial adjustments, error correction models, regime switching and vector autoregressive models. Finally, we use the meta‐regression analysis to investigate whether the results of asymmetry tests are not model‐invariant and find which additional factors systematically influence the rejection of the null hypothesis of symmetric price adjustment. The main results of our survey can be summarized as follows: (i) each econometric model is specialized to capture a subset of asymmetries; (ii) each asymmetry is better investigated by a subset of econometric models; (iii) the general significance of the F test for asymmetric price transmission depends mainly on characteristics of the data, dynamic specification of the econometric model, and market characteristics. Overall, our empirical findings confirm that asymmetry, in all its forms, is very likely to occur in a wide range of markets and econometric models.     

Testing for two-regime threshold cointegration in vector error-correction models

This paper examines a two-regime vector error-correction model with a single cointegrating vector and a threshold effect in the error-correction term. We propose a relatively simple algorithm to obtain maximum likelihood estimation of the complete threshold cointegration model for the bivariate case. We propose a SupLM test for the presence of a threshold. We derive the null asymptotic distribution, show how to simulate asymptotic critical values, and present a bootstrap approximation. We investigate the performance of the test using Monte Carlo simulation, and find that the test works quite well. Applying our methods to the term structure model of interest rates, we find strong evidence for a threshold effect.     

协整向量、调节参数同为非线性的阈值协整检验

针对经济变量的长期均衡和短期调节关系可能同时存在非线性的事实,本文扩展现有阈值协整模型,提出了协整向量、调节参数都为非线性的阈值协整模型,并着重探讨了该模型的检验方法。研究表明,在协整关系的检验中,Wald统计量有较好的有限样本性质。在协整关系的非线性检验中,LMW和LMG统计量的水平扭曲和检验势都较好。在调节参数的非线性检验中,当调节参数具有显著的非线性时,LMH统计量表现出较好的有限样本性质。     

Posterior Inference in Bayesian Quantile Regression with Asymmetric Laplace Likelihood

The paper discusses the asymptotic validity of posterior inference of pseudo‐Bayesian quantile regression methods with complete or censored data when an asymmetric Laplace likelihood is used. The asymmetric Laplace likelihood has a special place in the Bayesian quantile regression framework because the usual quantile regression estimator can be derived as the maximum likelihood estimator under such a model, and this working likelihood enables highly efficient Markov chain Monte Carlo algorithms for posterior sampling. However, it seems to be under‐recognised that the stationary distribution for the resulting posterior does not provide valid posterior inference directly. We demonstrate that a simple adjustment to the covariance matrix of the posterior chain leads to asymptotically valid posterior inference. Our simulation results confirm that the posterior inference, when appropriately adjusted, is an attractive alternative to other asymptotic approximations in quantile regression, especially in the presence of censored data.     

Testing the exogeneity specification in the complete dynamic simultaneous equation model

It is shown that in the complete dynamic simultaneous equation model exogenous variables cause endogenous variables in the sense of Granger (1969) and satisfy the criterion of econometric exogeneity discussed by Sims (1977a), but that the stationarity assumptions invoked by Granger and Sims are not necessary for this implication. Inference procedures for testing each implication are presented and a new joint test of both implications isderived. Detailed attention is given to estimation and testing when the error vector of the final form of the complete dynamic simultaneous equation model is both singular and serially correlated. The theoretical points of the paper are illustrated by testing the exogeneity specification in a small macroeconometric model.     

Testing Uncovered Interest Rate Parity and Term Structure Using a Three‐regime Threshold Unit Root VECM: An Application to the Swiss ‘Isle’ of Interest Rates*

In this article, a three‐regime multivariate threshold vector error correction model with a ‘band of inaction’ is formulated to examine uncovered interest rate parity (UIRP) and expectation hypothesis of the term structure (EHTS) of interest rates for Switzerland. Combining both UIRP and EHTS in a model that allows for nonlinearities, we investigate whether the Swiss advantage is disappearing with respect to Europe. Our results favour threshold cointegration and show that both hypotheses hold, at least in one of the three regimes of the process for Switzerland/Germany. The same is not true between Switzerland and the United States.     

Structural Analysis of Electricity Demand and Supply Interactions*

We specify a structural asymmetric vector error‐correction model to identify and estimate the demand and supply functions in hourly day‐ahead wholesale electricity markets. In doing so, we provide, inter alia, new insights into a well‐established but unresolved issue concerning the extent of the demand elasticity to price in these markets. We show that whilst demand appears to be inelastic in the short‐run, the quantity traded on the market is significantly influenced by the price level and responds to previous disequilibria in the supply curve through an asymmetric error‐correction mechanism, reacting to a positive disequilibrium but not to a negative one.     

Misspecification and Expectations Correction in New Keynesian DSGE Models

This paper focuses on the dynamic misspecification that characterizes the class of small‐scale New Keynesian models currently used in monetary and business cycle analysis, and provides a remedy for the typical difficulties these models have in accounting for the rich contemporaneous and dynamic correlation structure of the data. We suggest using a statistical model for the data as a device through which it is possible to adapt the econometric specification of the New Keynesian model such that the risk of omitting important propagation mechanisms is kept under control. A pseudo‐structural form is built from the baseline system of Euler equations by forcing the state vector of the system to have the same dimension as the state vector characterizing the statistical model. The pseudo‐structural form gives rise to a set of cross‐equation restrictions that do not penalize the autocorrelation structure and persistence of the data. Standard estimation and evaluation methods can be used. We provide an empirical illustration based on USA quarterly data and a small‐scale monetary New Keynesian model.     

Structural break threshold VARs for predicting US recessions using the spread

This paper proposes a model to predict recessions that accounts for non‐linearity and a structural break when the spread between long‐ and short‐term interest rates is the leading indicator. Estimation and model selection procedures allow us to estimate and identify time‐varying non‐linearity in a VAR. The structural break threshold VAR (SBTVAR) predicts better the timing of recessions than models with constant threshold or with only a break. Using real‐time data, the SBTVAR with spread as leading indicator is able to anticipate correctly the timing of the 2001 recession. Copyright © 2006 John Wiley & Sons, Ltd.     

Estimation of dynamic panel data models with sample selection

We propose a new method for estimating dynamic panel data models with selection. The method uses backward substitution for the lagged dependent variable, which leads to an estimating equation that requires correcting for contemporaneous selection only. The estimator is valid under relatively weak assumptions about errors and permits avoiding the weak instruments problem associated with differencing. We also propose a simple test for selection bias that is based on the addition of a selection term to the first‐difference equation and subsequent testing for significance of this term. The methods are applied to estimating dynamic earnings equations for women. Copyright © 2011 John Wiley & Sons, Ltd.     

The stochastic implications of rent maximization: an application to stumpage rates for timber in British Columbia

We construct a model of rent‐maximizing behaviour by a single seller of timber in the absence of a formal market, deriving the stochastic implications of rent maximization for timber prices (stumpage rates) when other input and output (lumber) prices are random. Subsequently, we examine the model's ability to describe monthly, time‐series, stumpage‐rate data from British Columbia, Canada between January 1979 and October 1999. Deviations of stumpage rates from their long‐run trend are also structured by an error‐correction model which suggests that between 13 and 20% of period‐to‐period changes in stumpage rates can be explained by an equilibrium adjustment term. Copyright © 2004 John Wiley & Sons, Ltd.     

Fiscal Policies and Credit Regimes: A TVAR Approach

This work investigates how the state of credit markets affects the impact of fiscal policies. We estimate a threshold vector autoregression (TVAR) model on US quarterly data for the period 1984–2010. We employ the spread between BAA‐rated corporate bond yield and 10‐year treasury constant maturity rate as a proxy for credit conditions. We find that the response of output to fiscal policy shocks is stronger and more persistent when the economy is in the ‘tight’ credit regime. Fiscal multipliers are significantly different in the two regimes: they are abundantly and persistently higher than one when firms face increasing financing costs, whereas they are feebler and often lower than one in the ‘normal’ credit regime. The results appear to be robust to different model specifications, fiscal foresight, alternative threshold variables, different measure of variables and sample periods. Copyright © 2014 John Wiley & Sons, Ltd.     

SEMIPARAMETRIC VECTOR MEM

Financial time series are often non‐negative‐valued (volumes, trades, durations, realized volatility, daily range) and exhibit clustering. When joint dynamics is of interest, the vector multiplicative error model (vMEM; the element‐by‐element product of a vector of conditionally autoregressive scale factors and a multivariate i.i.d. innovation process) is a suitable strategy. Its parameters can be estimated by generalized method of moments, bypassing the problem of specifying a multivariate distribution for the errors. Simulated results show the gains in efficiency relative to an equation‐by‐equation approach. A vMEM on several measures of volatility justifies a joint approach revealing full interdependence. Copyright © 2012 John Wiley & Sons, Ltd.     

Should I stay or should I go? A latent threshold approach to large‐scale mixture innovation models

We propose a straightforward algorithm to estimate large Bayesian time‐varying parameter vector autoregressions with mixture innovation components for each coefficient in the system. The computational burden becomes manageable by approximating the mixture indicators driving the time‐variation in the coefficients with a latent threshold process that depends on the absolute size of the shocks. Two applications illustrate the merits of our approach. First, we forecast the US term structure of interest rates and demonstrate forecast gains relative to benchmark models. Second, we apply our approach to US macroeconomic data and find significant evidence for time‐varying effects of a monetary policy tightening.     

The RWDAR model: A novel state-space approach to forecasting

This paper introduces the Random Walk with Drift plus AutoRegressive model (RWDAR) for time-series forecasting. Owing to the presence of a random walk plus drift term, this model shares some similarities with the Theta model of Assimakopoulos and Nikolopoulos (2000). However, the addition of a first-order autoregressive term in the state equation provides additional adaptability and flexibility. Indeed, it is shown that RWDAR tends to outperform the Theta model when forecasting both stationary and nearly non-stationary time series. This paper also proposes a simple estimation method for the RWDAR model based on the solution of the algebraic Riccati equation for the prediction error covariance of the state vector. Simulation results show that this estimator performs as well as the standard Kalman filter approach. Finally, using yearly data from the M3 and M4 competition datasets, it is found that RWDAR outperforms traditional forecasting methods.     

Non-linear and non-symmetric exchange-rate adjustment: Evidence from medium- and high-inflation countries

This paper analyses a model of non-linear exchange rate adjustment that extends the literature by allowing asymmetric responses to over- and under-valuations. Applying the model to Greece and Turkey, we find that adjustment is asymmetric and that exchange rates depend on the sign as well as the magnitude of deviations, being more responsive to over-valuations than undervaluations. Our findings support and extend the argument that non-linear models of exchange rate adjustment can help to overcome anomalies in exchange rate behaviour. They also suggest that exchange rate adjustment is non-linear in economies where fundamentals models work well.     

Habits,Complementarities and Heterogeneity in Alcohol and Tobacco Demand: A Multivariate Dynamic Model*

In this paper we test the existence of forward‐looking behaviour in a multivariate model for alcohol and tobacco consumption. The theoretical framework, based on a dynamic adjustment cost model with forward‐looking behaviour, is enhanced to include the intertemporal interactions between the two goods. The analysis of the within‐period preferences completes the intertemporal model, allowing to evaluate the static substitutability/complementarity relationships. The empirical strategy consists in a two‐step estimation procedure. In a first stage, we obtain the parameters of the demand system, while in a second stage Euler equations are estimated. Results, based on a cohort data set constructed from a series of cross‐sections of the Italian Household Budget Survey, reveal a significant complementarity relationship between alcohol and tobacco. Estimation of the Euler equations does not lead to rejection of the hypothesis of intertemporal dependence, providing evidence for a forward‐looking behaviour in alcohol and tobacco consumption. Moreover, we find significant intertemporal interactions that support the adjustment cost setting in a multivariate model with rational expectations.     

Asymmetric convergence in US financial credit default swap sector index markets

This study examines the asymmetric adjustments to the long-run equilibrium for credit default swap (CDS) sector indexes of three financial sectors – banking, financial services and insurance – in the presence of a threshold effect. The results of the momentum-threshold autoregression (M-TAR) models demonstrate that asymmetric cointegration exists for all pairs comprised of those three CDS indexes. The speeds of adjustment in the long-run are much higher in the case of adjustments from below the threshold than from above for all the pairs. The estimates of The MTAR-VEC models suggest that the dual CDS index return in each sector pair participates in the adjustment to equilibrium in the short- and long-run taken together. But in the long-run alone, only one of the two spreads in each pair participates. Policy implications are also provided.     

The sentiment pricing dynamics with short-term and long-term learning

Combining the behavioral characteristics of rational uninformed investors with learning information behavior of sentiment investors, this paper establishes a mathematical model about the impact of learning information behavior on the investor's transaction and asset equilibrium price under asymmetric information. Research shows that when rational uninformed investors learn information in the short term, on the one hand, they choose to bet against sentiment investors, thus reducing the influence of sentiment; on the other hand, they occasionally mistake sentiment for information to chase sentiment investors, then amplifying sentiment shocks. Furthermore, sentiment investors can also gain valuable information indirectly by observing the price in the long term. When sentiment investors learn information in the long term, the price fluctuations caused by sentiment and information, informativeness of the price system and market efficiency are no longer dependent on the quality of information.