U.S. Monetary Regimes and Optimal Monetary Policy in the Euro Area

Monetary policy in the United States has been documented to have switched from reacting weakly to inflation fluctuations during the 1970s, to fighting inflation aggressively from the early 1980s onward. In this paper, I analyze the impact of the U.S. monetary policy regime switches on the Eurozone. I construct a New Keynesian two‐country model where foreign (U.S.) monetary policy switches regimes over time. I estimate the model for the U.S. and the Euro Area using quarterly data and find that the United States has switched between those two regimes, in line with existing evidence. I show that foreign regime switches affect home (Eurozone) inflation and output volatility and their responses to shocks, substantially, as long as the home central bank commits to a time‐invariant interest rate rule reacting to domestic conditions only. Optimal policy in the home country instead requires that the home central bank reacts strongly to domestic producer‐price inflation and to international variables, such as imported goods relative prices. In fact, I show that currency misalignments and relative prices play a crucial role in the transmission of foreign monetary policy regime switches internationally. Interestingly, I show that only marginal gains arise for the Euro Area when the European Central Bank (ECB) adjusts its policy according to the monetary regime in the United States. Thus, a simple time‐invariant monetary policy rule with a strong reaction to Producer Price Index (PPI) inflation and relative prices is enough to counteract the effects of monetary policy switches in the United States.     

Moments of renewal shot-noise processes and their applications

In this paper, we study the family of renewal shot-noise processes. The Feynmann–Kac formula is obtained based on the piecewise deterministic Markov process theory and the martingale methodology. We then derive the Laplace transforms of the conditional moments and asymptotic moments of the processes. In general, by inverting the Laplace transforms, the asymptotic moments and the first conditional moments can be derived explicitly; however, other conditional moments may need to be estimated numerically. As an example, we develop a very efficient and general algorithm of Monte Carlo exact simulation for estimating the second conditional moments. The results can be then easily transformed to the counterparts of discounted aggregate claims for insurance applications, and we apply the first two conditional moments for the actuarial net premium calculation. Similarly, they can also be applied to credit risk and reliability modelling. Numerical examples with four distribution choices for interarrival times are provided to illustrate how the models can be implemented.     

Pricing mortgage insurance contracts under housing price cycles with jump risk: evidence from the U.K. housing market

Previous studies have investigated the determinants of housing price cycles in the housing market; however, we observed the phenomenon of housing price jumps in the 2007 subprime crisis. This paper presents a discussion on the housing price cycle and abnormal price jumps to describe the behavior of housing prices in the United Kingdom. The empirical results show that the impact factors of housing cycles are market risk and the switching factor. Furthermore, the impact factors of jump risks include the bursting of the housing bubble and financial crises. Therefore, in this paper, we employ the Markov switching model with jump risks to value the MI contracts and analyze the influences of housing price cycles, jump risks, risks of market interest rate, and the prepayment risks on MI premiums. The results of sensitivity analysis show that more volatile housing price index returns, as well as longer periods of higher volatility in housing prices, raise MI premiums. Moreover, the MI premium is positively related to the absolute value of the average jump amplitude and the shock frequency of abnormal events. There is the tradeoff between the market interest rate and the prepayment risk. The influences of market interest rate are different on MI premium with/without prepayment risks.     

Dynamic Currency Linkages and Their Determinants: An Empirical Study for East Asian Economic Community Region

In this article, Copula GARCH models have been employed to study the inter-temporal process of currency market co-movements between ASEAN+6 countries (referred to in this study as East Asian Economic Community) and ASEAN+6 currency market index. Empirical results show that the sample countries of the region exhibit varying levels of currency co-movements with the Asian benchmark. Markov regime switching results show that many of the countries which had high dependences with the regional currency index as was found in copula estimations had also overlapping currency market cycles. Using Principal Component Analysis, we find that three statistical factors explain exchange rate co-movements which came out to be trade linkages, economic risk, and currency market openness in our dynamic panel data estimation.     

Do rice prices follow a random walk? Evidence from Markov switching unit root tests for Asian markets

This study revisits the issue of mean reversion in the import rice prices of six Asian countries over the period between 1995 and 2015. Augmented Dickey Fuller tests with a conventional linear regression model support the presence of a unit root in the levels of the price data. However, when regressions allow for Markov switching in coefficients and variances to capture periodic shifts in levels and volatilities, there is strong evidence against the unit‐root null hypothesis in favor of stationarity over much of the observation period.     

Numerical Maximisation of Likelihood: A Neglected Alternative to EM?

There is by now a long tradition of using the EM algorithm to find maximum‐likelihood estimates (MLEs) when the data are incomplete in any of a wide range of ways, even when the observed‐data likelihood can easily be evaluated and numerical maximisation of that likelihood is available as a conceptually simple route to the MLEs. It is rare in the literature to see numerical maximisation employed if EM is possible. But with excellent general‐purpose numerical optimisers now available free, there is no longer any reason, as a matter of course, to avoid direct numerical maximisation of likelihood. In this tutorial, I present seven examples of models in which numerical maximisation of likelihood appears to have some advantages over the use of EM as a route to MLEs. The mathematical and coding effort is minimal, as there is no need to derive and code the E and M steps, only a likelihood evaluator. In all the examples, the unconstrained optimiser nlm available in R is used, and transformations are used to impose constraints on parameters. I suggest therefore that the following question be asked of proposed new applications of EM: Can the MLEs be found more simply and directly by using a general‐purpose numerical optimiser?     

MODELLING A REGIME‐SHIFTING BEVERIDGE CURVE

This paper offers new insights into Beveridge curve analysis by modelling the unemployment–vacancy rate relationship within a Markov regime‐switching environment in which the probabilities of curve‐shifting are determined endogenously by shift factors. Shift factors include structural factors such as labour market participation and net migration, while cyclical variables include GDP growth, the real rate of interest, and labour productivity. This approach enables us to estimate regime‐specific parameters and to assess the role played by these factors in influencing the transition probabilities of switching between regimes. Using New Zealand data, we show that increases in the participation rate have shifted the Beveridge curve inward, while increases in net migration have shifted the curve outward.     

Examination of Taiwan's travel and tourism market cycle through a two-period Markov regime-switching model

This study analyzes the Taiwan travel and tourism (T&T) market cycle. According to data of the weighted Taiwan tourism stock index from January 1997 to August 2015, the two-period Markov regime-switching model identifies two distinct regimes of the T&T cycle and incorporates a specific set of mean and variance parameters for each period to control for the structural changes in Taiwan's T&T market. The effect of China visitor arrivals to Taiwan on the T&T market is also verified. The empirical findings offer essential information and policy implications for Taiwan's government tourism policymakers and business managers.     

Overlapping Generations and Environmental Policy： An Introduction

A small but growing body of literature uses overlapping generations （OLG） models to study environmental policy for long-lived problems such as climate change. An OLG model, unlike the infinitely lived representative agent model, dis- tinguishes between impatience with respect to one＇s own future utility, and attitudes toward successors＇ utility. I discuss the problem of time inconsistency, the role of Markov perfection, and show that a class of OLG models can be studied using me- thods developed to analyze models of non-constant discounting. An example illu- strates the techniques and determines the conditions under which, in equilibrium, there is under-investment or over-investment in natural capital.