A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

A Multiple Break Panel Approach to Estimating United States Phillips Curves

Phillips curves are often estimated without due attention being paid to the underlying time series properties of the data. In particular, the consequences of inflation having discrete breaks in mean have not been studied adequately. We show by means of simulations and a detailed empirical example based on United States data that not taking account of breaks may lead to biased, and therefore spurious, estimates of Phillips curves. We suggest a method to account for the breaks in mean inflation and obtain meaningful and unbiased estimates of the short- and long-run Phillips curves in the United States.

The Global Side of the Investment-Savings Puzzle

In this paper we re-examine the long standing and puzzling correlation between national savings and investment in industrial countries. We apply an econometric methodology that allows us to separate idiosyncratic correlation at the country level from correlation at the global level. In a major break with the existing literature, we find no evidence of a long run relationship in the idiosyncratic components of savings and investment. We also find that the global components in savings and investments comove, indicating that they react to shocks of a global nature.

On the Relationship between Market Power and Bank Risk Taking

We analyse risk-taking behaviour of banks in the context of spatial competition. Banks mobilise unsecured deposits by offering deposit rates, which they invest either in a prudent or a gambling asset. Limited liability along with high return of a successful gamble induce moral hazard at the bank level. We show that when the market power is low, banks invest in the gambling asset. On the other hand, for sufficiently high levels of market power, all banks choose the prudent asset to invest in. We further show that a merger of two neighboring banks increases the likelihood of prudent behaviour. Finally, introduction of a deposit insurance scheme exacerbates banks’ moral hazard problem.

Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach

This paper uses an infinite hidden Markov model (IIHMM) to analyze U.S. inflation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling structural breaks. It allows for an unknown number of breakpoints and is a flexible and attractive alternative to existing methods. We found a clear structural break during the recent financial crisis. Prior to that, inflation persistence was high and fairly constant.

Nominal Interest Rates and Stationarity

This paper investigates the (break) stationarity null hypothesis using data for 25 interest rates with different maturities and risk characteristics in Canada and the US. In contrast to a large part of the literature, this paper reports strong empirical evidence in favour of the null hypothesis of stationarity for the interest rate series.

The Changing Inter-Industry Wage Structure of the Organised Manufacturing Sector in India, 1973-74 to 2003-04

This study examines the inter-industry wage structure of the organised manufacturing sector in India for the period 1973-74 to 2003-04 by estimating the growth of average real wages for production workers by industry. In order to estimate the growth rates, the study adopts a methodological framework that differs from other studies in that the time series properties of the concerned variables are closely considered in order to obtain meaningful estimates of growth that are unbiased and (asymptotically) efficient. Using wage data on 51 manufacturing industries at three digit level of the National Industrial Classification 1998 (India), our estimation procedure obtains estimates of growth of real wages per worker that are deterministic in nature by accounting for any potential structural break(s). Our findings show that the inter-industry wage structure in India has changed a lot in the period 1973-74 to 2003-04 and that it provides some evidence that the inter-industry wage differences have become more pronounced in the post-reforms period. Thus this paper provides new evidence from India on the need to consider the hypothesis that industry affiliation is potentially an important determinant of wages when studying any relationship between reforms and wages.

Growth Rate Estimation in the presence of Unit Roots

This study addresses the issue of the presence of a unit root on the growth rate estimation by the least-squares approach. We argue that when the log of a variable contains a unit root, i.e., it is not stationary then the growth rate estimate from the log-linear trend model is not a valid representation of the actual growth of the series. In fact, under such a situation, we show that the growth of the series is the cumulative impact of a stochastic process. As such the growth estimate from such a model is just a spurious representation of the actual growth of the series, which we refer to as a “pseudo growth rate”. Hence such an estimate should be interpreted with caution. On the other hand, we highlight that the statistical representation of a series as containing a unit root is not easy to separate from an alternative description which represents the series as fundamentally deterministic (no unit root) but containing a structural break. In search of a way around this, our study presents a survey of both the theoretical and empirical literature on unit root tests that takes into account possible structural breaks. We show that when a series is trendstationary with breaks, it is possible to use the log-linear trend model to obtain well defined estimates of growth rates for sub-periods which are valid representations of the actual growth of the series. Finally, to highlight the above issues, we carry out an empirical application whereby we estimate meaningful growth rates of real wages per worker for 51 industries from the organised manufacturing sector in India for the period 1973-2003, which are not only unbiased but also asymptotically efficient. We use these growth rate estimates to highlight the evolving inter-industry wage structure in India.

Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables

Macroeconomists working with multivariate models typically face uncertainty over which (if any) of their variables have long run steady states which are subject to breaks. Furthermore, the nature of the break process is often unknown. In this paper, we draw on methods from the Bayesian clustering literature to develop an econometric methodology which: i) finds groups of variables which have the same number of breaks; and ii) determines the nature of the break process within each group. We present an application involving a five-variate steady-state VAR.

Contagious Illiquidity I: Contagion through Time

This paper is an investigation into the dynamics of asset markets with adverse selection a la Akerlof (1970). The particular question asked is: can market failure at some later date precipitate market failure at an earlier date? The answer is yes: there can be "contagious illiquidity" from the future back to the present. The mechanism works as follows. If the market is expected to break down in the future, then agents holding assets they know to be lemons (assets with low returns) will be forced to hold them for longer - they cannot quickly resell them. As a result, the effective difference in payoff between a lemon and a good asset is greater. But it is known from the static Akerlof model that the greater the payoff differential between lemons and non-lemons, the more likely is the market to break down. Hence market failure in the future is more likely to lead to market failure today. Conversely, if the market is not anticipated to break down in the future, assets can be readily sold and hence an agent discovering that his or her asset is a lemon can quickly jettison it. In effect, there is little difference in payoff between a lemon and a good asset. The logic of the static Akerlof model then runs the other way: the small payoff differential is unlikely to lead to market breakdown today. The conclusion of the paper is that the nature of today's market - liquid or illiquid - hinges critically on the nature of tomorrow's market, which in turn depends on the next day's, and so on. The tail wags the dog.