On Markov error‐correction models,with an application to stock prices and dividends

This paper considers Markov error‐correction (MEC) models in which deviations from the long‐run equilibrium are characterized by different rates of adjustment. To motivate our analysis and illustrate the various issues involved, our discussion is structured around the analysis of the long‐run properties of US stock prices and dividends. It is shown that the MEC model is flexible enough to account for situations where deviations from the long‐run equilibrium are nonstationary in one of the states of nature and allows us to test for such a possibility. An empirical specification procedure to establish the existence of MEC adjustment in practice is also presented. This is based on a multi‐step test procedure that exploits the differences between the global and local characteristics of systems with MEC adjustment. Copyright © 2004 John Wiley & Sons, Ltd.     

Why are gasoline prices sticky? A test of alternative models of price adjustment

Macroeconomic models of business cycles rely on the assumption that firms adjust prices infrequently to generate the short‐run non‐neutrality of money documented by the monetary transmission literature. They posit different mechanisms to generate price stickiness, with correspondingly different implications for inflation dynamics. Using an autoregressive conditional binomial model, we test which mechanism is most consistent with the pattern of price adjustment found in daily wholesale gasoline price data. Our results lead us to reject menu costs and information‐processing delays but suggest that strategic considerations related to the idea of ‘fair pricing’ play an important role in accounting for price stickiness. Copyright © 2009 John Wiley & Sons, Ltd.     

Nonlinearities and Fractional Integration in the US Unemployment Rate*

This paper proposes a model of the US unemployment rate which accounts for both its asymmetry and its long memory. Our approach introduces fractional integration and nonlinearities simultaneously into the same framework, using a Lagrange multiplier procedure with a standard null‐limit distribution. The empirical results suggest that the US unemployment rate can be specified in terms of a fractionally integrated process, which interacts with some nonlinear functions of labour‐demand variables such as real oil prices and real interest rates. We also find evidence of a long‐memory component. Our results are consistent with a hysteresis model with path dependency rather than a non‐accelerating inflation rate of unemployment (NAIRU) model with an underlying unemployment equilibrium rate, thereby giving support to more activist stabilization policies. However, any suitable model should also include business cycle asymmetries, with implications for both forecasting and policy‐making.     

Comovements and asymmetric tail dependence in state housing prices in the USA: A nonparametric approach

We reexamine the methods used in estimating comovements among US regional home prices and find that there are insufficient moments to ensure a normal limit necessary for employing the quasi‐maximum likelihood estimator. Hence we propose applying the self‐weighted quasi‐maximum exponential likelihood estimator and a bootstrap method to test and account for the asymmetry of comovements as well as different magnitudes across state pairs. Our results reveal interstate asymmetric tail dependence based on observed house price indices rather than residuals from fitting autoregressive–generalized autoregressive conditional heteroskedasticity (AR‐GARCH) models.     

STRUCTURAL VECTOR AUTOREGRESSIONS: CHECKING IDENTIFYING LONG‐RUN RESTRICTIONS VIA HETEROSKEDASTICITY

Long‐run restrictions have been used extensively for identifying structural shocks in vector autoregressive (VAR) analysis. Such restrictions are typically just‐identifying but can be checked by utilizing changes in volatility. This paper reviews and contrasts the volatility models that have been used for this purpose. Three main approaches have been used, exogenously generated changes in the unconditional residual covariance matrix, changing volatility modelled by a Markov switching mechanism and multivariate generalized autoregressive conditional heteroskedasticity models. Using changes in volatility for checking long‐run identifying restrictions in structural VAR analysis is illustrated by reconsidering models for identifying fundamental components of stock prices.     

Sluggish quantity adjustment in a non-clearing market—a disequilibrium econometric application to the loan market

The paper argues that the estimated speed of price adjustment in a disequilibrium econometric model is likely to be biased if allowance is not made for quantity adjustment inertia on both sides of the market. Furthermore, if the model estimated is static rather than dynamic then, in certain circumstances, an excess demand regime may be mistaken for one of excess supply and vice-versa. In an empirical application to the loan market for the clearing banks in Ireland we can claim to have obtained some support for this belief.     

New insights into the role of global factors in BRICS stock markets: A quantile cointegration approach

Because of the acceleration in marketization and globalization, stock markets in the BRICS (Brazil, Russia, India, China, and South Africa) countries are affected by various global factors, for example, oil prices, gold prices, global stock market volatility, global economic policy uncertainty, financial stress, and investor sentiment. This paper offers new insights into the short- and long-run linkages between global factors and BRICS stock markets by applying the quantile autoregressive distributed lags (QARDL) approach. This novel methodology enables us to test short- and long-run linkages accounting for distributional asymmetry. That is, the nonlinear dynamic relationship between the global factors and BRICS stock prices depends on market conditions. Our empirical results show that the effects of gold prices and global stock market volatility on BRICS stock prices are more significant in the long run than in the short run. A decrease in global stock market volatility is associated with higher stock prices, while gold prices demonstrate upward co-movement in dynamic correlations with stock markets. Irrational factors, such as economic policy uncertainty, financial stress, and investor sentiment, play a critical role in the short term, and negative interdependence is dominant. Finally, the rolling-window estimation technique is used to examine time-varying patterns between major global factors and BRICS stock markets.     

Investigating properties of commodity price responses to real and nominal shocks

This paper studies dynamic adjustments of 49 world commodity prices in response to innovations in the nominal exchange rate and the world real GDP. After we estimate the dynamic elasticity of the prices with respect to these shocks, we obtain the kernel density of our estimates to establish stylized facts on the adjustment process of the commodity price toward a new equilibrium path. Our empirical findings imply, on average, that the law of one price holds in the long-run, whereas the substantial degree of short-run price rigidity was observed in response to the nominal exchange rate shock. The real GDP shock tends to generate substantial price fluctuations in the short-run because adjustments of the supply can be limited, but have much weaker effects in the long-run as the supply eventually counterbalances the increase in the demand. Overall, we report persistent long-lasting effects of the nominal exchange rate shock on commodity prices relative to those of the real GDP shock.     

Econometric models of asymmetric ascending auctions

We develop econometric models of ascending (English) auctions which allow for both bidder asymmetries as well as common and/or private value components in bidders’ underlying valuations. We show that the equilibrium inverse bid functions in each round of the auction are implicitly defined (pointwise) by a system of nonlinear equations, so that conditions for the existence and uniqueness of an increasing-strategy equilibrium are essentially identical to those which ensure a unique and increasing solution to the system of equations. We exploit the computational tractability of this characterization in order to develop an econometric model, thus extending the literature on structural estimation of auction models. Finally, an empirical example illustrates how equilibrium learning affects bidding during the course of the auction.     

A nonparametric measure of convergence towards purchasing power parity

It has been claimed that the deviations from purchasing power parity are highly persistent and have quite long half‐lives under the assumption of a linear adjustment of real exchange rates. However, inspired by trade cost models, nonlinear adjustment has been widely employed in recent empirical studies. This paper proposes a simple nonparametric procedure for evaluating the speed of adjustment in the presence of nonlinearity, using the largest Lyapunov exponent of the time series. The empirical result suggests that the speed of convergence to a long‐run price level is indeed faster than what was found in previous studies with linear restrictions. Copyright © 2006 John Wiley & Sons, Ltd.     

Oil prices,economic activity and inflation: evidence for some Asian countries

In this paper we study the oil prices–macroeconomy relationship by means of studying the impact of oil price shocks on both economic activity and consumer price indexes for six Asian countries over the period 1975Q1–2002Q2. The results suggest that oil prices have a significant effect on both economic activity and price indexes, although the impact is limited to the short run and more significant when oil price shocks are defined in local currencies. Moreover, we find evidence of asymmetries in the oil prices–macroeconomy relationship for some of the Asian countries.     

Price competition in the spatial real estate market: allies or rivals?

This paper examines whether real estate firms can avoid price competition when properties in the vicinity are priced by allies. An oligopoly model with differentiated products generally suggests that real estate firms engage in price competition with their spatially closest rivals. Yet, they can raise property prices when the market share of their allies increases. To test this prediction, a spatial autoregressive model with spatial autoregressive disturbances, including a share of allies in the vicinity, is estimated using data on the prices of residential condos in central Tokyo, Japan. The model prediction is supported by the empirical results. In the data set, the magnitude of the market share on property prices increases with the expansion of the size of the spatial market.     

The Incremental Predictive Information Associated with Using Theoretical New Keynesian DSGE Models vs. Simple Linear Econometric Models*

In this paper we construct output gap and inflation predictions using a variety of dynamic stochastic general equilibrium (DSGE) sticky price models. Predictive density accuracy tests related to the test discussed in Corradi and Swanson [Journal of Econometrics (2005a), forthcoming] as well as predictive accuracy tests due to Diebold and Mariano [Journal of Business and Economic Statistics (1995) , Vol. 13, pp. 253–263]; and West [Econometrica (1996) , Vol. 64, pp. 1067–1084] are used to compare the alternative models. A number of simple time‐series prediction models (such as autoregressive and vector autoregressive (VAR) models) are additionally used as strawman models. Given that DSGE model restrictions are routinely nested within VAR models, the addition of our strawman models allows us to indirectly assess the usefulness of imposing theoretical restrictions implied by DSGE models on unrestricted econometric models. With respect to predictive density evaluation, our results suggest that the standard sticky price model discussed in Calvo [Journal of Monetary Economics (1983), Vol. XII, pp. 383–398] is not outperformed by the same model augmented either with information or indexation, when used to predict the output gap. On the other hand, there are clear gains to using the more recent models when predicting inflation. Results based on mean square forecast error analysis are less clear‐cut, although the standard sticky price model fares best at our longest forecast horizon of 3 years, it performs relatively poorly at shorter horizons. When the strawman time‐series models are added to the picture, we find that the DSGE models still fare very well, often outperforming our forecast competitions, suggesting that theoretical macroeconomic restrictions yield useful additional information for forming macroeconomic forecasts.     

Inflation,output and stock prices: evidence from Latin America

Research in economics and finance documents a puzzling negative relationship between stock returns and inflation rate in markets of industrialized economies. The present study investigates this relationship for the developing markets of Peru and Chile. Fama's model of linkages between inflation and real economic activity constitutes the theoretical framework of this paper. The study tests whether the negative relationship between equity returns and inflation is a result of a ‘proxy effect’, namely, a negative relationship between inflation and real economic activity. The evidence for Peru and Chile does not provide strong support for Fama's hypothesis. It is shown that the negative relationship between the real stock returns and unexpected inflation persists after purging inflation of the effects of the real economic activity. The long‐run equilibrium between stock prices and general price levels is weak, as indicated by the findings of the Johansen and Juselius co‐integration tests. However, in both economies, stock prices and general price levels seem to show a strong long‐run equilibrium with the real economic activity. These findings suggest that in the long‐run, Fama's propositions A and B are supported for Peru and Chile. The disparity between traditional regression and co‐integration test results suggest that it may be prudent to re‐examine the proxy effect in the framework of a long‐run relationship before denying its validity. Copyright © 1999 John Wiley & Sons, Ltd.     

Housing market dynamics: Evidence of mean reversion and downward rigidity

House prices often exhibit serial correlation and mean reversion. Using two large panel datasets, this paper analyzes the price dynamics in two significantly different types of markets, cyclical (or volatile) and non-cyclical (or tame), by applying an autoregressive mean reversion (ARMR) model. Our results show that cyclical markets have larger AR coefficients than non-cyclical markets. As a result, house prices in cyclical markets tend to have larger price cycles. We also find that the upward periods have larger AR coefficients than the downward periods. This demonstrates that house prices are likely to overshoot the equilibrium in appreciating markets while experiencing downward rigidity during periods of decline. The model developed in this paper can produce a forecast with rich house price dynamics across markets. Our results can also be used to determine how house prices in overvalued markets will ultimately adjust.     

Combining Forecasts from Nested Models*

Motivated by the common finding that linear autoregressive models often forecast better than models that incorporate additional information, this paper presents analytical, Monte Carlo and empirical evidence on the effectiveness of combining forecasts from nested models. In our analytics, the unrestricted model is true, but a subset of the coefficients is treated as being local‐to‐zero. This approach captures the practical reality that the predictive content of variables of interest is often low. We derive mean square error‐minimizing weights for combining the restricted and unrestricted forecasts. Monte Carlo and empirical analyses verify the practical effectiveness of our combination approach.     

Heterogeneous expectations in the gold market: Specification and estimation

The increase in the price of gold between 2002 and 2011 appears to be a candidate for a potential asset price ‘bubble’, suggesting that chartists (feedback traders) were highly active in the gold market during this period. Hence, this paper develops and tests empirically several models incorporating heterogeneous expectations of agents, specifically fundamentalists and chartists, for the gold market. The empirical results show that both agent types are important in explaining historical gold prices but that the 10-year bull run of gold in the early 2000s is consistent with the presence of agents extrapolating long-term trends. Technically this paper is a further step toward providing an empirical foundation for certain assumptions used in the heterogeneous agents literature. For example, the empirical results presented in this paper compare the economical and statistical significance of numerous switching variable specifications that are generally only introduced ad hoc.     

Volatility forecasting in the Bitcoin market: A new proposed measure based on the VS-ACARR approach

This paper proposes a new volatility-spillover-asymmetric conditional autoregressive range (VS-ACARR) approach that takes into account the intraday information, the volatility spillover from crude oil as well as the volatility asymmetry (leverage effect) to model/forecast Bitcoin volatility (price range). An empirical application to Bitcoin and crude oil (WTI) price ranges shows the existence of strong volatility spillover from crude oil to the Bitcoin market and a weak leverage effect in the Bitcoin market. The VS-ACARR model yields higher forecasting accuracy than the GARCH, CARR, and VS-CARR models regarding out-of-sample forecast performance, suggesting that accounting for the volatility spillover and asymmetry can significantly improve the forecasting accuracy of Bitcoin volatility. The superior forecast performance of the VS-ACARR model is robust to alternative out-of-sample forecast windows. Our findings highlight the importance of accommodating intraday information, spillover from crude oil, and volatility asymmetry in forecasting Bitcoin volatility.     

Money‐output Causality Revisited – A Bayesian Logistic Smooth Transition VECM Perspective*

This article proposes a Bayesian approach to examining money‐output causality within the context of a logistic smooth transition vector error correction model. Our empirical results provide substantial evidence that the postwar US money‐output relationship is nonlinear, with regime changes mainly governed by the output growth and price levels. Furthermore, we obtain strong support for nonlinear Granger causality from money to output, although there is also some evidence for models indicating that money is not Granger causal or long‐run causal to output.     

Unbeatable Value Low‐Price Guarantee: Collusive Mechanism or Advertising Strategy?

This paper investigates the effects of a low-price guarantee (price-beating guarantee) on the patterns of price setting of three supermarkets using micro-level price data. Following recent theoretical developments, the paper analyzes the ability of low-price guarantees to sustain anticompetitive prices. My empirical analysis suggests instead that this low-price guarantee may serve as an advertising device to signal low prices. The supermarket offering the low-price guarantee, aware of its price advantage in a subset of products, uses it to signal low prices to induce consumers to switch supermarkets.