Do permanent shocks explain income levels? a common cycle-common trend analysis of regional income levels for China

In this paper, we analyse per capita income levels of China's three main regions: the western region, the eastern region and the central region using common cycle and common trend tests. Our main contribution is that we impose the common cycle and common trend restrictions in decomposing shocks into permanent and transitory components. We find that: (i) there is evidence for two cointegrating relationships and one common cycle; and (ii) the variance decomposition analysis of shocks provides evidence that over short horizons, permanent shocks play a large role in explaining variations in regional per capita incomes.

Common trends and common cycles in per capita GDP : the case of the G7 Countries, 1870-2001

In this paper we analyze per capita incomes of the G7 countries using the common cycles test developed by Vahid and Engle (Journal of Applied Econometrics, 8:341–360, 1993) and extended by Hecq et al. (Oxford Bulletin of Economics and Statistics, 62:511–532, 2000; Econometric Reviews, 21:273–307, 2002) and the common trend test developed by Johansen (Journal of Economic Dynamics and Control, 12:231–254, 1988). Our main contribution is that we impose the common cycle and common trend restrictions in decomposing the innovations into permanent and transitory components. Our main finding is permanent shocks explain the bulk of the variations in incomes for the G7 countries over short time horizons, and is in sharp contrast to the bulk of the recent literature. We attribute this to the greater forecasting accuracy achieved, which we later confirm through performing a post sample forecasting exercise, from the variance decomposition analysis.

An investigation of the behaviour of Australia's business cycle

In this paper we examine the relative importance of permanent and transitory shocks in explaining variations in income, consumption and investment at business cycle horizons for Australia. We use the common trend–common cycle restrictions to estimate a variance decomposition of shocks, and find that over short horizons the bulk of the variations in income and investment are due to permanent shocks, while transitory shocks explain the bulk of the variations in consumption. The former finding is consistent with real business cycle models which attribute business cycles to aggregate supply shocks, while the findings for consumption are consistent with the Keynesian view, which attributes business cycles to aggregate demand shocks.

Understanding the importance of permanent and transitory shocks at business cycle horizons for the UK

The goal of this paper is to examine the relative importance of permanent and transitory shocks in explaining variations in macroeconomic aggregates for the UK at business cycle horizons. Using the common trend–common cycle restrictions, we estimate a variance decomposition of shocks, and find that over short horizons the bulk of the variations in income and consumption were due to permanent shocks while transitory shocks explain the bulk of the variations in investment. Our findings for income and consumption are consistent with real business cycle models which emphasize the role of aggregate supply shocks, while our findings for investment are consistent with the Keynesian school of thought, which emphasizes the role of aggregate demand shocks in explaining business cycles.

Common trends and common cycles in stock markets

In this paper we examine the role of permanent and transitory shocks in explaining variations in the S&P 500, Dow Jones and the NASDAQ. Our modeling technique involves imposing both common trend and common cycle restrictions in extracting the variance decomposition of shocks. We find that: (1) the three stock price indices are characterized by a common trend and common cycle relationship; and (2) permanent shocks explain the bulk of the variations in stock prices over short horizons.

The importance of common cyclical features in VAR analysis: a Monte-Carlo study

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models. First, we show that the ìbestî empirical model developed without common cycle restrictions need not nest the ìbestî model developed with those restrictions. This is due to possible differences in the lag-lengths chosen by model selection criteria for the two alternative models. Second, we show that the costs of ignoring common cyclical features in vector autoregressive modelling can be high, both in terms of forecast accuracy and efficient estimation of variance decomposition coefficients. Third, we find that the Hannan-Quinn criterion performs best among model selection criteria in simultaneously selecting the lag-length and rank of vector autoregressions.

A Common-feature approach for testing present-value restrictions with financial data

It is well known that cointegration between the level of two variables (labeled Yt and yt in this paper) is a necessary condition to assess the empirical validity of a present-value model (PV and PVM, respectively, hereafter) linking them. The work on cointegration has been so prevalent that it is often overlooked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. The basis of this result is the use of rational expectations in forecasting future values of variables in the PVM. If this condition fails, the present-value equation will not be valid, since it will contain an additional term capturing the (non-zero) conditional expected value of future error terms. Our article has a few novel contributions, but two stand out. First, in testing for PVMs, we advise to split the restrictions implied by PV relationships into orthogonality conditions (or reduced rank restrictions) before additional tests on the value of parameters. We show that PV relationships entail a weak-form common feature relationship as in Hecq, Palm, and Urbain (2006) and in Athanasopoulos, Guillén, Issler and Vahid (2011) and also a polynomial serial-correlation common feature relationship as in Cubadda and Hecq (2001), which represent restrictions on dynamic models which allow several tests for the existence of PV relationships to be used. Because these relationships occur mostly with nancial data, we propose tests based on generalized method of moment (GMM) estimates, where it is straightforward to propose robust tests in the presence of heteroskedasticity. We also propose a robust Wald test developed to investigate the presence of reduced rank models. Their performance is evaluated in a Monte-Carlo exercise. Second, in the context of asset pricing, we propose applying a permanent-transitory (PT) decomposition based on Beveridge and Nelson (1981), which focus on extracting the long-run component of asset prices, a key concept in modern nancial theory as discussed in Alvarez and Jermann (2005), Hansen and Scheinkman (2009), and Nieuwerburgh, Lustig, Verdelhan (2010). Here again we can exploit the results developed in the common cycle literature to easily extract permament and transitory components under both long and also short-run restrictions. The techniques discussed herein are applied to long span annual data on long- and short-term interest rates and on price and dividend for the U.S. economy. In both applications we do not reject the existence of a common cyclical feature vector linking these two series. Extracting the long-run component shows the usefulness of our approach and highlights the presence of asset-pricing bubbles.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

Ciclos de la producción industrial en Colombia: extracción del ciclo del sector y de sus ramas de actividad

En este documento empleamos el filtro de Butterworth para analizar la producción industrial total y por ramas de actividad mediante la extracción de señales en las frecuencias bajas y altas. En las frecuencias bajas la tendencia de la producción al interior del sector exhibe una dinámica que difiere fuertemente entre actividades. En las frecuencias altas, la mayoría de las ramas industriales presentan una mayor sensibilidad al ciclo común del sector que a los ciclos particulares o idiosincráticos, evidenciando una sincronización en la respuesta de la producción frente a choques exógenos.

Estimating exchange rate responsiveness to shocks

The goal of this paper is to examine the importance of permanent and transitory shocks using a more efficient trend-cycle decomposition of the real exchange rate series. Our main contribution is that in measuring the impact of shocks, we not only impose common trend restrictions but also common cycle restrictions. We later confirm, through a post sample forecasting exercise, the efficiency gains from imposing common cycle restrictions. Our results indicate that permanent shocks are responsible for the bulk of the real exchange rate variations for Japan, Italy, Germany, France, and the UK vis-à-vis the US dollar over short horizons. For Canada, however, transitory shocks are dominant over the short horizon. In sum, while for Japan, France, and Italy, around 15% of the variation in real exchange rate is due to transitory shocks, for Canada, Germany and the UK, over 25% of the variations over the short horizon are due to transitory shocks. Thus, we claim that the role of transitory shocks should not be ignored.

What drives stock markets over short horizons? Evidence from emerging markets

The goal of this paper is to examine the importance of permanent and transitory shocks in explaining variations in stock prices for Singapore, Taiwan, and South Korea using a trend-cycle decomposition technique. This study is novel in that in measuring the impact of shocks we not only impose common trend restrictions but also common cycle restrictions. We later undertake a post-sample forecasting exercise to confirm the efficiency gains from imposing common cycle restrictions. We find that over short horizons, transitory shocks are the dominant source of variations in stock prices for South Korea, while permanent shocks explain the bulk of the variations in stock price of Singapore and Taiwan.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We compare the performance of our index with other currently popular coincident indices of economic activity.

Previsão de preços de ativos usando restrições do modelo de valor presente

Motivados pelo debate envolvendo modelos estruturais e na forma reduzida, propomos nesse artigo uma abordagem empírica com o objetivo de ver se a imposição de restrições estruturais melhoram o poder de previsibilade vis-a-vis modelos irrestritos ou parcialmente restritos. Para respondermos nossa pergunta, realizamos previsões utilizando dados agregados de preços e dividendos de ações dos EUA. Nesse intuito, exploramos as restrições de cointegração, de ciclo comum em sua forma fraca e sobre os parâmetros do VECM impostas pelo modelo de Valor Presente. Utilizamos o teste de igualdade condicional de habilidade de previsão de Giacomini e White (2006) para comparar as previsões feitas por esse modelo com outros menos restritos. No geral, encontramos que os modelos com restrições parciais apresentaram os melhores resultados, enquanto o modelo totalmente restrito de VP não obteve o mesmo sucesso.