Search

In this paper, we provide empirical evidence that real wage rigidity is not a major cause of unemployment volatility. We argue that there is a disconnect between the theoretical and empirical literatures on this topic. While theoretical studies define real wage rigidity as the response of wages to changes in unemployment following productivity shocks, the empirical literature measures real wage rigidity as the estimated semi‐elasticity of wages with respect to unemployment, averaged over all shocks. We show that averaging over shocks gives a biased measure of real wage rigidity, as the impact of other shocks confounds the response to productivity shocks. Our results indicate that the estimated semi‐elasticity with respect to productivity shocks is twice as large as the estimated semi‐elasticity averaged over all shocks. This implies that one cannot attribute unemployment volatility to real wage rigidity. [ABSTRACT FROM AUTHOR]

This paper examines the effects of oil and natural gas prices on the oil and gas sectors of the BRIC countries (Brazil, Russia, India, and China) over the period over from 20013 to 2022. Unlike previous studies, it employs a time-varying capital asset pricing model based on the estimation of state-space mode. In brief, the findings highlight significant changes in the asset-pricing model parameters across all countries, indicating the limitations of using time-invariant estimates. Specifically, Brazil shows the highest volatility in oil price risk, followed by Russia, both being oil-exporting countries, while market beta values remain relatively stable. Time-varying estimates further suggest that natural gas parameters are relatively lower and less significant than those of oil prices. The Russian-Ukrainian conflict's energy crisis adversely affects the performance of oil and gas sectoral stock returns. This war has had a negative and significant impact on China's oil-gas stock return.

Against the background of deepening public finance reforms in China, this paper applies the time-varying parameter techniques to investigate the underlying structural variation in the systematic part of fiscal policy. Although the degree of activism of systematic fiscal policy to inflation is estimated to remain in a mostly stable regime, the findings reveal a trend towards a less systematic and predictable policy behaviour to output stabilization over the past few years. The dynamic relationship implies that the counter-cyclical policy capacity has been attenuated, and systematic fiscal policy becomes less effective at restraining uncertainties about the functioning of the economy. [ABSTRACT FROM AUTHOR]

This paper contributes to the trade-energy literature by examining the effect of export product diversification on the energy demand of 30 countries located in the Global North over the period 1980–2014. A nonparametric time-varying coefficient panel data model with fixed effects is employed for its ability to produce robust outcomes in the presence of parameter instabilities, nonstationarity, regime shifts, and time variations. As a second step, the paper also utilizes the nonparametric fixed effects extension of Driscoll and Kraay, which is robust to spatial/cross-sectional dependence, as well as to autocorrelation and heteroscedasticity. The results indicate that export diversification lowers overall energy demand in the Global North, and the size of the impact has been on a gradual increase over the years. The paper concludes that if a conscious effort is made to ensure that product diversification is towards energy-efficient goods, export product diversification can serve as a useful strategy for managing energy consumption and mitigating its negative environmental effects. [ABSTRACT FROM AUTHOR]

This paper analyzes the predictive ability of aggregate and disaggregate proxies of investor sentiment, over and above standard macroeconomic predictors, in forecasting housing returns in China, using an array of machine learning models. We find that our new aligned investor sentiment index has greater predictive power for housing returns than the principal component analysis (PCA)‐based sentiment index, used earlier in the literature. Moreover, shrinkage models utilizing the disaggregate sentiment proxies do not result in forecast improvement indicating that aligned sentiment index optimally exploits information in the disaggregate proxies of investor sentiment. Furthermore, when we let the machine learning models to choose from all key control variables and the aligned sentiment index, the forecasting accuracy is improved at all forecasting horizons, rather than just the short‐run as witnessed under standard predictive regressions. This result suggests that machine learning methods are flexible enough to capture both structural change and time‐varying information in a set of predictors simultaneously to forecast housing returns of China in a precise manner. Given the role of the real estate market in China's economic growth, our result of accurate forecasting of housing returns has important implications for both investors and policymakers. [ABSTRACT FROM AUTHOR]

The importance of tourism as one of the bedrocks of economic growth in South Africa suggests that volatility in the sector may have dire consequences. We therefore empirically analyse the impact of tourism volatility (TV) on the gross domestic product (GDP) volatility of the country, using time-varying approaches that treat the parameter estimations as functions of time, thereby overcoming the challenge posed by parameter instabilities, non-linearities, non-stationarity, regime shifts and time variations. We find that TV significantly aggravates GDP volatility (GDPV) in South Africa. The impact varies from year to year and is greatest during the periods characterized by economic turbulence and crime and violence against foreigners. The size of the coefficients has been on a steady increase over time, reflecting the growing importance of tourism and TV to the South African economy. We also find that TV is a significant predictor of GDPV in the country. We strongly recommend that policymakers pay serious attention to economic happenings around the world since TV is one of the channels through which global economic crises affect the South African economy. We also recommend that the minimization of crime and social disorder should form an essential component of tourism development and promotion strategy in South Africa. [ABSTRACT FROM AUTHOR]

Forecasting oil price volatility is considered of major importance for numerous stakeholders, including, policy makers, industries, and investors. This paper examines and evaluates the main factors that oil price volatility forecasters should consider before constructing their forecasting models. Such factors are related to (i) direct versus iterated forecasts, (ii) the incorporation of continuous and jump components, (iii) the importance of semi variance volatility measures, and (iv) ordinary least squares (OLS) versus time‐varying parameter (TVP) estimation procedures. We evaluate the performance of these factors for both the realized and implied volatility measures of the West Texas Intermediate (WTI) crude oil price, based on statistical loss functions, as well as their economic use. The results show that depending on whether end users are interested in forecasting the realized or the implied volatility, the factors influencing the accuracy of forecasts are different. In particular, for the realized volatility, direct forecasting based on TVP estimation procedure, as well as using the information obtained in the semi variance measures, is capable of producing significantly superior forecasts. By contrast, separating the continuous and the jump components of the realized volatility does not provide any added value to these forecasts. Turning to the oil price implied volatility index (OVX), based on the economic evaluation of our forecasts, the TVP estimation procedure seems to perform better. In addition, we find evidence that the continuous component and the semivariance measures of the realized volatility also yield better OVX forecasts in the longer run horizons. [ABSTRACT FROM AUTHOR]

Abstract This study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five countries based on a multi-factor asset pricing model using daily data from 29 May 1996 to 27 January 2020. The endogenous structural break test suggests the presence of serious parameter instabilities due to fluctuations in the oil and stock markets over the period under study. Moreover, the time-varying estimates indicate that the oil–gas sectors of these countries are riskier than the overall stock market. The results further suggest that, except for Indonesia, oil prices have a positive impact on the sectoral returns of all markets, whereas the impact of the exchange rates on the oil–gas sector returns varies across time and countries.

In this paper, we estimate the price and income elasticities for gasoline demand in selected energy gluttons—China, India, USA, Russia, and Japan. Specifically, we employ a time-varying parameter approach which adequately deals with potential parameter instabilities and nonlinearities and effectively captures price and income elasticity variations over time, with each time period having its own set of coefficients. Our empirical findings reveal the following: gasoline consumption is price-inelastic and income-inelastic, there are movements in both the price and income elasticities, and the movements generally correspond with business cycle patterns of each of the countries; overall, sensitivity to price and income changes increase during periods of economic crises. Constant elasticity models overestimate price and income elasticities, and income is predominantly more elastic than price. Our conclusion is that policy mechanisms that are price-based such as gasoline taxes are likely to be unsuccessful in achieving consumption-cum-pollution reduction objectives in the energy gluttons. Such policies may, however, be effective if they ensure that gasoline prices rise at a greater rate than income. Such policies may also be useful for revenue-raising purposes. [ABSTRACT FROM AUTHOR]

This article proposes two distinct contributions to econometric analysis of large information sets and structural instabilities. First, it treats a regression model with time-varying coefficients, stochastic volatility, and exogenous predictors, as an equivalent high-dimensional static regression problem with thousands of covariates. Inference in this specification proceeds using Bayesian hierarchical priors that shrink the high-dimensional vector of coefficients either toward zero or time-invariance. Second, it introduces the frameworks of factor graphs and message passing as a means of designing efficient Bayesian estimation algorithms. In particular, a generalized approximate message passing algorithm is derived that has low algorithmic complexity and is trivially parallelizable. The result is a comprehensive methodology that can be used to estimate time-varying parameter regressions with arbitrarily large number of exogenous predictors. In a forecasting exercise for U.S. price inflation this methodology is shown to work very well. for this article are available online. [ABSTRACT FROM AUTHOR]

Studies on the relationship between the informal economy and economic growth have been inconclusive as to whether the positive or negative relationship dominates. These results are partly due to the type of estimation technique such as fixed-parameter techniques. Fixed parameter techniques have been used to observe the relationship between economic growth and the informal economy. A caveat to the fixed-parameter estimation techniques used to observe the relationship between the informal economy and economic growth is the inability to account for annual disruptions. This paper seeks to examine the relationship between the informal economy and economic growth in Nigeria in the period from 1991 to 2015 using the Time-Varying Parameter (TVP) model. The TVP model is estimated in two stages. First, an Ordinary Least Squares (OLS) multiple regression is estimated and the outcome is subjected to the flexible least-squares approach. The results show the dominance of the negative effects of the informal economy on economic growth. The outcomes also reveal that overtime movements of time-varying parameters in the informal economy and economic growth are connected with economic and political events. This paper recommends the absorption of the informal economy into the official economy through government policy.

This study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five countries based on a multi-factor asset pricing model using daily data from 29 May 1996 to 27 January 2020. The endogenous structural break test suggests the presence of serious parameter instabilities due to fluctuations in the oil and stock markets over the period under study. Moreover, the time-varying estimates indicate that the oil–gas sectors of these countries are riskier than the overall stock market. The results further suggest that, except for Indonesia, oil prices have a positive impact on the sectoral returns of all markets, whereas the impact of the exchange rates on the oil–gas sector returns varies across time and countries. [ABSTRACT FROM AUTHOR]

Measuring treatment effects are a complicated task as the outcomes of receiving and not receiving the treatment cannot be observed simultaneously. Thus, the issue of obtaining accurate measurement is an issue of predicting the counterfactuals accurately. In this study, we explore the suitability of using time-varying parameter models in a panel to generate robust measure of counterfactuals, hence robust measure of treatment effects. We suggest some within-sample tests for constant parameter versus time-varying parameter models and diagnostic tools based on time-varying parameter framework as a flexible alternative to predict missing data. Monte Carlos and two empirical studies are examined in this framework. The results appear to show that if the focus is on minimizing the mean square error of the predicted treatment effects, a "straitjacket" approach relying on the best selected model from the pre-treatment data remains the best option in view of the missing post-treatment information on counterfactuals. On the other hand, the confidence band based on the time-varying parameter model provides a more robust inference to hedge against possible changes of the relations between the treated units and the controls in the post-treatment period. [ABSTRACT FROM AUTHOR]

Voices have been raised that the link between economic sentiment and hard macroeconomic data has considerably weakened over time, bringing agents' macroeconomic assessments of normal growth to a more modest, new normal level. We empirically test this hypothesis by linking consumer confidence to consumption growth for all individual EU member states, as well as for the EU and the euro area. Applying a battery of nonlinear econometric techniques, we find that normal consumption growth rates (as assessed by consumers) have recorded a long-term decline in about half of countries (dominantly old EU member states), while all other economies either contradict such a hypothesis or exhibit intermittent intervals of increasing and decreasing normal growth. Our calculations reveal that normal consumption growth rates are highly positively related to macroeconomic volatility, reflecting the postulates of psychophysics. In that sense, the new modesty hypothesis can to some extent be attributed to the Great Moderation era, which has diminished consumers' perceptive reactions to macroeconomic stimuli. [ABSTRACT FROM AUTHOR]

Copyright of Acta Economica is the property of University of Banja Luka, Faculty of Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, I undertake a novel approach to uncover the forecasting interconnections in the international housing markets. Using a dynamic model averaging framework that allows both the coefficients and the entire forecasting model to dynamically change over time, I uncover the intertwined forecasting relationships in 23 leading international housing markets. The evidence suggests significant forecasting interconnections in these markets. However, no country holds a constant forecasting advantage, including the United States and the United Kingdom, although the U.S. housing market's predictive power has increased over time. Evidence also suggests that allowing the forecasting model to change is more important than allowing the coefficients to change over time. [ABSTRACT FROM AUTHOR]

Despite the large amount of empirical research on monetary policy rules, there is surprisingly little consensus on the nature or even the existence of changes in the conduct of U.S. monetary policy. Three issues appear central to this disagreement: (1) the specific type of changes in the policy coefficients, (2) the treatment of heteroskedasticity, and (3) the real-time nature of the data used. This paper addresses these issues in the context of forward looking Taylor rules with drifting coefficients. The estimation is based on real-time data and accounts for the presence of heteroskedasticity in the policy shock. The findings suggest important but gradual changes in the rule coefficients, not adequately captured by the usual split-sample estimation. In contrast to Orphanides (2002, 2003), I find that the Fed's response to the real-time forecast of inflation was weak in the second half of the 1970s, perhaps not satisfying Taylor's principle as suggested by Clarida, Galì, and Gertler (2000). However, the response to inflation was strong before 1973 and gradually regained strength from the early 1980s onward. Moreover, as in Orphanides (2003), the Fed's response to real activity fell substantially and lastingly during the 1970s. [ABSTRACT FROM AUTHOR]

The monetary economics literature has highlighted four issues that are important in evaluating US monetary policy since the late 1960s: (i) time variation in policy parameters, (ii) asymmetric preferences, (iii) real-time nature of data, and (iv) heteroskedasticity. In this paper, we exploit advances in sequential monte carlo methods to estimate a time-varying nonlinear Taylor rule that addresses these four issues simultaneously. Our findings suggest that US monetary policy has experienced substantial changes in terms of both the response to inflation and to real economic activity, as well as changes in preferences. These changes cannot be captured adequately by a single structural break at the late 1970s, as has been commonly assumed in the literature, and play a non-trivial role in economic performance. [ABSTRACT FROM AUTHOR]

This article studies a volatility forecasting model based on volatility measurement error, and extends it with nonlinear time series model, expecting to improve the forecasting performance. According to the literature, volatility series may have both long memory and nonlinear characteristics. Heterogeneous autoregressive (HAR) model has long memory characteristic. Adjusting HAR model with measurement error promotes model persistence. Further combine the model with time-varying parameter model which is nonlinear, so that structure change and reduction of heteroscedasticity are achieved. Realized range-based volatility is computed based on high-frequency data of CSI300 (2652 trading days) to test the effect of the models. Among the fixed parameter models, the out-of-sample forecasting performance is significantly improved by adding measurement error as adjustment variable. Among the time-varying parameter models, most of the models with measurement error dominate their corresponding models without measurement error. The predictions of time-varying parameter models are in general significantly better than their counterparts with fixed parameters, especially when the prediction period is long. [ABSTRACT FROM AUTHOR]

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns. [ABSTRACT FROM AUTHOR]

This article investigates Okun’s law for Japan, Korea, Hong Kong and Singapore over the period 1986–2011. Two time-varying parameter models, first-order difference and gap models, are considered to find a negative time-varying relationship between the real output and the unemployment rate. The empirical findings show that there exist time-varying negative relationships between the real output and the unemployment rate for all economies. We also find that the estimated time-varying Okun’s coefficients are dominated by changes in the real GDP for Korea. However, the Okun’s coefficients are dominated by changes in the unemployment rate for Japan, Hong Kong and Singapore. [ABSTRACT FROM AUTHOR]

This paper estimates a forward-looking reaction function with time-varying parameters to examine changes in the Brazilian monetary policy under the inflation-targeting regime. As the monetary policy rule has endogenous regressors, the conventional Kalman filter cannot be applied. Thus, the two-step procedure proposed by Kim and Nelson (J Monet Econ 53:1949-1966, ) is used for consistent estimation of the hyper-parameters of the model. The results indicate that the reaction function parameters of the Central Bank of Brazil are time-varying and that the regressors of that function are endogenous. Besides, we observed that: (i) the monetary policy interest rate (Selic rate) responses to current inflation and the inflationary expectations present considerable changes and have diminished with the passing of time; (ii) since mid-2010, policy rule has violated the Taylor principle; (iii) the implicit target for the Selic interest rate has shown a decline over time; and (iv) the degree of interest rate smoothing has shown a relative stability. Finally, the policy instrument response to the output gap presents an increasing trend over the 2010-2011 period. [ABSTRACT FROM AUTHOR]

This study assumes that tourists' demand reactions to income and price changes are asymmetric at different phases of the business cycle. In order to test this hypothesis, we analyzed the demand for international tourism in five source markets using a modified growth rate (MGR) model. The empirical evidence demonstrates that income elasticity is indeed asymmetric across the business cycle in four source markets. In addition, asymmetric price effects were found for one source market. To compare forecasting performance, we also estimated a time-varying parameter (TVP) model. The results show that the MGR model generally outperforms the TVP model. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper tests the autonomy of domestic monetary policy in the context of the macroeconomic policy trilemma for a large data-set of developing and developed countries covering three different time periods characterized with different exchange rate regimes and capital controls. The existing literature uses fixed coefficient methodologies to examine monetary policy independence; whereas we show that the coefficients of interest are unstable as countries switch between different exchange rate regimes and/or capital controls over time. The contribution is in using a time-varying parameter model that better captures the effects of the heterogeneity in different exchange rate regimes and capital mobility restrictions on monetary policy independence over time, allowing a more accurate test of the macroeconomic trilemma. [ABSTRACT FROM AUTHOR]

The causal link between tourism receipts and GDP has recently become a major focus in the tourism economics literature. Results obtained in recent studies about the causal link appear to be sensitive with respect to the countries analysed, sample period and methodology employed. Considering the sensitivity of the causal link, we use rolling window and time-varying coefficient estimation methods to analyse the parameter stability and Granger causality based on a vector error correction model (VECM). When applied to South Africa for the period 1960–2011, the findings are as follows: results from the full-sample VECM indicate that there is no Granger causality between tourism receipts and GDP, while the findings from the time-varying coefficients model based on the state-space representation show that tourism receipts have positive-predictive content for GDP for the entire period, with the exception of the period between 1985 and 1990. Full-sample time-varying causality tests show bidirectional strong causality between tourism receipts and GDP. [ABSTRACT FROM PUBLISHER]

Taking iron and steel industry as an example, this paper aims to explore the market demand , s effect on and its mechanism for the investment and capacity allocation. Based on building a theoretical model containing a dynamic gap in demand according to the quarterly data of iron and steel industry since 2003, we employed the time-varying parameter model to test the asymmetric adjustment mechanism for the capacity allocation induced by demand. The results show obvious asymmetric features in the formation and exit phases of iron and steel productivity, which are caused by demand-induced dynamics and its asymmetric periodic motion ; self-correction made by the mechanism of productivity under the influence of frequent shifts between supply and demand is limited; once the deviation from the equilibrium level of production capacity goes beyond the threshold of the adjustment mechanism , it is unable to restore equilibrium through market regulation, thus leading to the huge "trial and error" cost. Grasping the above rules accurately is the precondition for achieving market's decisive role in the resource allocating process and at the same time for giving full play to government function. [ABSTRACT FROM AUTHOR]

We examine the evolution of monetary policy rules in a group of inflation-targeting countries (Australia, Canada, New Zealand, Sweden, and the United Kingdom), applying a moment-based estimator in a time-varying parameter model with endogenous regressors. From this novel flexible framework, our main findings are threefold. First, monetary policy rules change gradually, pointing to the importance of applying a time-varying estimation framework. Second, the interest-rate smoothing parameter is much lower than typically reported by previous time-invariant estimates of policy rules. External factors matter for all countries, although the importance of the exchange rate diminishes after the adoption of inflation targeting. Third, the response of interest rates to inflation is particularly strong during periods when central bankers want to break a record of high inflation, such as in the United Kingdom or Australia at the beginning of the 1980s. Contrary to common perceptions, the response becomes less aggressive after the adoption of inflation targeting, suggesting a positive anchoring effect of this regime on inflation expectations. This result is supported by our finding that inflation persistence typically decreased after the adoption of inflation targeting. [ABSTRACT FROM PUBLISHER]

Abstract: We examine whether and how selected central banks responded to episodes of financial stress over the last three decades. We employ a recently developed monetary-policy rule estimation methodology which allows for time-varying response coefficients and corrects for endogeneity. This flexible framework applied to the USA, the UK, Australia, Canada, and Sweden, together with a new financial stress dataset developed by the International Monetary Fund, not only allows testing of whether central banks responded to financial stress, but also detects the periods and types of stress that were the most worrying for monetary authorities and quantifies the intensity of the policy response. Our findings suggest that central banks often change policy rates, mainly decreasing them in the face of high financial stress. However, the size of the policy response varies substantially over time as well as across countries, with the 2008–2009 financial crisis being the period of the most severe and generalized response. With regard to the specific components of financial stress, most central banks seemed to respond to stock-market stress and bank stress, while exchange-rate stress is found to drive the reaction of central banks only in more open economies. [Copyright &y& Elsevier]

This paper estimates time-varying forward-looking monetary policy reaction functions for the central banks of France, Germany, Italy, and the United Kingdom. We utilize the framework developed by Kim [Economics Letters 91 (2006) 21–26] and Kim and Nelson [Journal of Monetary Economics (2006) 1949–1966] to deal with the issue of endogeneity in a time varying–parameter model. Our results find substantial time variation in the conduct of monetary policy in these four countries, which cannot be adequately captured by the conventional fixed-coefficient approach. Our findings suggest that there was a significant decline in the Bank of France's and the Bank of Italy's response to the German interest rate in 1992, and it coincided with the breakdown of the exchange rate management system in Europe. Our results suggest that the Bank of England was slower than the Bundesbank to increase its response to expected inflation, as its response to inflation became more than one-for-one only in the early 1980s. [ABSTRACT FROM PUBLISHER]

Purpose |!|#8211; The purpose of this paper is to apply the Becker-Murphy theory of rational addiction to the case of carbonated soft drinks. The research aims to reveal the rational addiction evidence of carbonated soft drinks and derive policy implications under this evidence. Consumers|!|#39; rational addictive evidence for carbonated soft drinks provides a warning for the Chinese government to regulate the industry, due to its bad health consequences. Design/methodology/approach |!|#8211; The authors empirically apply a time-varying parameter model and scanner data set from 46 US cities. Findings |!|#8211; Empirical results provide strong evidence that carbonated soft drinks are rationally addictive, thus opening the door to taxation and regulation. Taking rational addition into account, estimated demand elasticities are much lower than previous estimates using scanner data, which implies a limited role for taxes to curb consumption but a strong role to raise revenue to fund health promotion programs. Originality/value |!|#8211; This is the first study to test the rational addiction nature of carbonated soft drinks, thus adding to the scarce economic literature on food addiction. Although the empirical results derived are based on soft drink consumption in the USA, China is experiencing a similar consumption increase in carbonated soft drinks as in the USA, in the examined period. Therefore, the lessons from the USA are also valuable for the public policy makers in China. [ABSTRACT FROM AUTHOR]

Abstract: The diffusion process is a widely used statistical model for many natural dynamic phenomena but its inference is very complicated because complete data describing the diffusion sample path is not necessarily available. In addition, data is often collected with substantial uncertainty and it is not uncommon to have missing observations. Thus, the observed process will be discrete over a finite time period and the marginal likelihood given by this discrete data is not always available. In this paper, we consider a class of nonstationary diffusion process models with not only the measurement error but also discretely time-varying parameters which are modeled via a state space model. Hierarchical Bayesian inference for such a diffusion process model with time-varying parameters is applied to financial data. [Copyright &y& Elsevier]

We report evidence of a time-varying link between returns on national stock market indexes and exchange rate returns (exchange rate exposure). We use this evidence to analyze the sources of changes over time in exchange rate exposure. Using monthly data for 14 industrialized countries for the period 1975-2006, we report evidence of a cointegration relation between exchange rate exposure and the industry composition of a country's imports, and weaker evidence of a cointegration relation between exchange rate exposure and openness to trade. [ABSTRACT FROM AUTHOR]

Using the Savage-Dickey density ratio and an alternative approach that uses more relaxed assumptions, we develop methods to calculate the probability that a restriction holds at a point in time without assuming that the restriction holds at any other points in time. Both approaches use MCMC output only from the unrestricted model to compute the time-varying posterior probabilities for alt models of interest. Using U.S. data, we find the probability that the long-run Phillips curve is vertical to be fairly high, but decreases overtime. The probability that the NAIRU is not identified fluctuates over time, but increases after 1990. [ABSTRACT FROM AUTHOR]

Abstract: Among the assumptions upon which linear time-invariant models of floating bodies are based is that the body motions are so small that any change in the body’s angular position can be disregarded. However, it is often a major design requirement of a wave energy conversion device that the response amplitude is large, thereby invalidating one of the assumptions of the linear model. In particular, the immersed geometry of a body undergoes considerable variation when it is moved in pitch. With regard to this we investigate the difference in performance between a quasi-linear model in which the change of immersed surface is modelled by time-varying parameters and a basic linear model in which the immersed surface is time-invariant. The time-varying parameter model is realized by interpolation between the appropriate parameter values of a set of linear time-invariant (LTI) models derived for the different immersed surfaces that occur at discrete body displacements. It is shown that the responses predicted using the time-varying parameter model are closer to those measured experimentally than those of a standard frequency-domain model. Particular improvement occurs when the responses are large, such as at or near the resonance frequency. A problem which may limit the general use of the model is also discussed. [Copyright &y& Elsevier]

This paper investigates whether changes in U.S. and Japanese banks’ risk aversion, measured by changes in the relative risk aversion (RRA) coefficient, are associated with the 1997 Asian financial crisis. It finds that an increase in U.S. banks’ risk aversion is unambiguously associated with the Asian crisis, while an increase in Japanese banks’ risk aversion is only weakly associated. The results suggest that, in addition to deteriorating fundamentals of the affected countries, investors’ (banks’) increased risk aversion appears to have reinforced observed capital outflows. [ABSTRACT FROM AUTHOR]

This article is concerned with understanding how financial constraints on investment vary over the business cycle and whether these constraints are related to macroeconomic policies. These issues are investigated within the framework of a time-varying parameter model using US company panel data from 1971 to 1993 - A preliminary investigation of parameter stability in investment equations using cross-sectional estimation techniques indicates a pattern of parameter variation that confirms to the one captured by the 'return-to-normality' model. The return-to-normality model is estimated using a Bayesian approach. The estimation results provide evidence that support the predictons of the models of assymmetric information in capital markets. [ABSTRACT FROM AUTHOR]

• This paper estimates the impact of investors' risk perceptions (VIX) on the dynamic correlation among international stock markets. • Results show that VIX significantly impacts dynamic correlation of the U.S. with other international markets. • VIX Granger causes the dynamic correlation between the U.S. market and 17 out of 20 international stock markets. • The impact of VIX is positive on the correlation of the U.S. with European and Latin American markets. • The relationship of the U.S. with all the Asian markets weakens (strengthens) as the VIX index rises (falls). • The time-varying parameter model shows that the impact of VIX on dynamic correlations varies significantly across time. Investors' risk perceptions have significant implications for international stock markets. This paper estimates the time-varying impact of the VIX index – a widely used measure of investors risk perceptions – on the dynamic correlation across international stock markets. Results show that risk perceptions significantly impact the dynamic correlation between the U.S. market and the leading stock markets of the world. Further, in 17 out of 20 international stock markets, risk perceptions Granger cause dynamic correlations. The impact of VIX is positive on the correlation of the U.S. market with European and Latin American markets. In contrast, the relationship of the U.S. market with all the Asian markets weakens (strengthens) as the VIX index rises (falls). In all cases, the time-varying parameter model shows that the impact of VIX on these correlations varies significantly across time. [ABSTRACT FROM AUTHOR]