Business,housing, and credit cycles

We use multivariate unobserved components models to estimate trend and cyclical components in gross domestic product (GDP), credit volumes, and house prices for the USA and the five largest European economies. With the exception of Germany, we find large and long cycles in credit and house prices, which are highly correlated with a medium‐term component in GDP cycles. Differences across countries in the length and size of cycles appear to be related to the properties of national housing markets. The precision of pseudo real‐time estimates of credit and house price cycles is roughly comparable to that of GDP cycles.     

Measuring Synchronization and Convergence of Business Cycles for the Euro area,UK and US*

This paper investigates business cycle relations among different economies in the Euro area. Cyclical dynamics are explicitly modelled as part of a time series model. We introduce mechanisms that allow for increasing or diminishing phase shifts and for time‐varying association patterns in different cycles. Standard Kalman filter techniques are used to estimate the parameters simultaneously by maximum likelihood. The empirical illustrations are based on gross domestic product (GDP) series of seven European countries that are compared with the GDP series of the Euro area and that of the US. The original integrated time series are band‐pass filtered. We find that there is an increasing resemblance between the business cycle fluctuations of the European countries analysed and those of the Euro area, although with varying patterns.     

Growth, cycles and convergence in US regional time series

This article reports the results of fitting unobserved components (structural) time series models to data on real income per capita in eight regions of the United States. The aim is to establish stylised facts about cycles and convergence. It appears that while the cycles are highly correlated, the two richest regions have been diverging from the others in recent years. A new model is developed in order to characterise the converging behaviour of the six poorest regions. The model combines convergence components with a common trend and cycles. These convergence components are formulated as a second-order error correction mechanism which allows temporary divergence while imposing eventual convergence. After fitting the model, the implications for forecasting are examined. Finally, the use of unit root tests for testing convergence is critically assessed in the light of the stylised facts obtained from the fitted models.     

Asymptotically perfect and relative convergence of productivity

In this paper we examine the extent to which countries are converging in per capita productivity levels. We propose to use cluster analysis in order to allow for the endogenous selection of converging countries. We formally define convergence in a time series analytical context, derive the necessary and sufficient conditions for convergence, and introduce a cluster analytical procedure that distinguishes several convergence clubs by testing for these conditions using a multivariate test for stationarity. We find a large number of relatively small convergence clubs, which suggests that convergence might not be such a widespread phenomenon. Copyright © 2000 John Wiley & Sons, Ltd.     

Estimation of Common Factors under Cross‐Sectional and Temporal Aggregation Constraints

The paper estimates a large‐scale mixed‐frequency dynamic factor model for the euro area, using monthly series along with gross domestic product (GDP) and its main components, obtained from the quarterly national accounts (NA). The latter define broad measures of real economic activity (such as GDP and its decomposition by expenditure type and by branch of activity) that we are willing to include in the factor model, in order to improve its coverage of the economy and thus the representativeness of the factors. The main problem with their inclusion is not one of model consistency, but rather of data availability and timeliness, as the NA series are quarterly and are available with a large publication lag. Our model is a traditional dynamic factor model formulated at the monthly frequency in terms of the stationary representation of the variables, which however becomes nonlinear when the observational constraints are taken into account. These are of two kinds: nonlinear temporal aggregation constraints, due to the fact that the model is formulated in terms of the unobserved monthly logarithmic changes, but we observe only the sum of the monthly levels within a quarter, and nonlinear cross‐sectional constraints, since GDP and its main components are linked by the NA identities, but the series are expressed in chained volumes. The paper provides an exact treatment of the observational constraints and proposes iterative algorithms for estimating the parameters of the factor model and for signal extraction, thereby producing nowcasts of monthly GDP and its main components, as well as measures of their reliability.     

Issue Information

Much research studies US inflation history with a trend‐cycle model with unobserved components, where the trend may be viewed as the Fed's evolving inflation target or long‐horizon expected inflation. We provide a novel way to measure the slowly evolving trend and the cycle (or inflation gap), by combining inflation predictions from the Survey of Professional Forecasters (SPF) with realized inflation. The SPF forecasts may be treated either as rational expectations (RE) or updating according to a sticky information (SI) law of motion. We estimate RE and SI state‐space models with stochastic volatility on samples of consumer price index and gross national product/gross domestic product deflator inflation and the associated SPF inflation predictions using a particle Metropolis–Markov chain Monte Carlo sampler. The trend converges to 2% and its volatility declines over time—two tendencies largely complete by the late 1990s.     

The next hundred years of growth and convergence

World gross domestic product per capita is forecast to grow at 2.6% annually over the next 100 years. Convergence of less-developed countries toward output levels of the world frontier accounts for much of the forecast. Projecting recent growth in China and India accounts for much of the forecast convergence. The forecast differs from the earlier literature because the facts of convergence have changed in recent decades. A Markov-switching model is estimated for each country, allowing each country to switch on or off a path of convergence to the world output frontier. Bayesian estimates of the historical process and posterior forecasts are offered.     

The Millennium Peak in Club Convergence: A New Look at Distributional Changes in The Wealth of Nations

This paper proposes an easy‐to‐use nonparametric indicator for club convergence, or convergence within clusters of countries: it measures whether the modes of the gross domestic product (GDP) per capita distribution become more pronounced over time. Relying on changes in the critical bandwidth for unimodality, the indicator is a dynamic extension of concepts from often‐used multimodality tests. Its evolution suggests the new empirical result of a ‘millennium peak’ in club convergence in the worldwide GDP per capita distribution. The club convergence movements of the 1980s and 1990s, when groups of poor and rich countries converged to two separate points, was followed by a de‐clubbing movement after the turn of the millennium. Copyright © 2016 John Wiley & Sons, Ltd.     

The dynamics of Central European equity market comovements

This paper examines short-term and long-term comovements between developed European Union (EU) stock markets and those of three Central European (CE) countries which recently joined the EU. Dynamic cointegration and principal components methods are applied, in addition to static tests. While we find no evidence of cointegration for the period July 1995–February 2005 as a whole, dynamic tests reveal alternating period of cointegration disrupted by episodes dominated by short-term domestic factors. Principal components analysis reveals that a stable factor explains a large proportion of return variances. Ultimately, despite the decade-long process of alignment by CE countries with the EU, evidence of steadily increasing convergence of equity markets is lacking.     

Forecasting economic activity with mixed frequency BVARs

Mixed frequency Bayesian vector autoregressions (MF-BVARs) allow forecasters to incorporate large numbers of time series that are observed at different intervals into forecasts of economic activity. This paper benchmarks the performances of MF-BVARs for forecasting U.S. real gross domestic product growth against surveys of professional forecasters and documents the influences of certain specification choices. We find that a medium–large MF-BVAR provides an attractive alternative to surveys at the medium-term forecast horizons that are of interest to central bankers and private sector analysts. Furthermore, we demonstrate that certain specification choices influence its performance strongly, such as model size, prior selection mechanisms, and modeling in levels versus growth rates.     

THE GROWTH AFTERMATH OF NATURAL DISASTERS

This paper traces the yearly response of gross domestic product growth—both aggregated and disaggregated into its agricultural and non‐agricultural components—to four types of natural disasters: droughts, floods, earthquakes, and storms. The paper uses a methodological approach based on pooling the experiences of various countries over time. It consists of vector autoregressions in the presence of endogenous variables and exogenous shocks (VARX), applied to a panel of cross‐country and time series data. The analysis finds heterogeneous effects on a variety of dimensions. First, the effects of natural disasters are stronger on developing than on advanced countries. Second, not all natural disasters are alike in terms of the growth response they induce, and some can even have positive effects on economic growth. Third, severe disasters often carry much worse effects than moderate effects do. Fourth, the timing of the growth response varies with both the type of natural disaster and the sector of economic activity. Copyright © 2011 John Wiley & Sons, Ltd.     

House price convergence in euro zone and non-euro zone countries

This study investigates whether single currency use increased house price convergence among various countries. First, the panel unit root test results indicate that the house prices in euro zone countries were more correlated than the house prices in non-euro zone countries. Second, the house prices in various European countries converged towards the house prices in Germany, which uses the single currency, rather than towards those in the United Kingdom, indicating that single currency use increased the influence of the German housing market on other markets. Finally, the log t regression model, a new convergence test, was employed and determined that the house prices in various European countries were not converging before 1992 but began to do so after that year. After the euro was implemented as an official currency, the house prices in various countries converged towards a consistent level. On the basis of the relative transition paths, this study determines that the differences among housing markets in various countries have continuously decreased since 1992. The empirical results indicate that the law of one price is applicable to tradable goods and that single currency use can integrate housing markets, which include non-tradable goods.     

Tests of seasonal integration and cointegration in multivariate unobserved component models

This paper considers tests of seasonal integration and cointegration for multivariate unobserved component models. First, the locally best invariant (LBI) test of the null hypothesis of a deterministic seasonal pattern against the alternative of seasonal integration is derived for a model with Gaussian i.i.d. disturbances and deterministic trend. Then the null hypothesis of seasonal cointegration is considered and a test for common nonstationary components at the seasonal frequencies is proposed. The tests are subsequently generalized to account for stochastic trends, weakly dependent errors and unattended unit roots. Asymptotic representations and critical values of the tests are provided, while the finite sample performance is evaluated by Monte Carlo simulation experiments. Finally, the tests are applied to the series of industrial production of the four largest countries of the European Monetary Union. It is found that Germany does not appear to cointegrate with the other countries at most seasonal frequencies, while there seems to exist a common nonstationary seasonal component between France, Italy and Spain. Copyright © 2006 John Wiley & Sons, Ltd.     

Public banking and economic growth: The experiences of 10 countries since the 1950s until 2017

Despite the limited number of empirical works assessing the implications of public banks for economic growth, a wave of these institutions has arisen since 2000. With this in mind, this paper investigates the linkage between these banks and long-run growth in 10 countries. We find discouraging evidence on the role of these institutions in the growth process as public banks contributed to long-run economic growth in only two countries. More precisely, the public bank raised the gross domestic product in the Dominican Republic and investment in Singapore. In the remaining eight countries, long-run growth was harmed, or we did not find a long-run nexus running from the public bank. This is particularly surprising because some public banks in our sample have a long history of proper management and were given an important role in their country's development. We find long-run reverse causality in five countries, and, in all of them but in one, a larger gross domestic product per capita expanded public banks’ assets. Therefore, public banks were following the economic cycle. Considering all this, governments that aim to accelerate economic growth should be more cautious about the creation or promotion of these entities.     

Convergence in international output

This paper proposes and tests new definitions of convergence and common trends for per capita output. We define convergence for a group of countries to mean that each country has identical long-run trends, either stochastic or deterministic, while common trends allow for proportionality of the stochastic elements. These definitions lead naturally to the use of cointegration techniques in testing. Using century-long time series for 15 OECD economies, we reject convergence but find substantial evidence for common trends. Smaller samples of European countries also reject convergence but are driven by a lower number of common stochastic trends.     

Capital accumulation and growth: a new look at the empirical evidence

Using annual data for 75 countries in the period 1960–2000, we present evidence of a positive relationship between investment as a share of gross domestic product (GDP) and the long‐run growth rate of GDP per worker. This result is robust for our full sample and for the subsample of non‐OECD countries, but not for the subsample of OECD countries. Our analysis controls for time‐invariant country‐specific heterogeneity in growth rates, and for a range of time‐varying control variables. We also address endogeneity issues, and allow for heterogeneity across countries in model parameters and for cross‐section dependence. Copyright © 2010 John Wiley & Sons, Ltd.     

A Bounded Model of Time Variation in Trend Inflation,Nairu and the Phillips Curve

In this paper, we develop a bivariate unobserved components model for inflation and unemployment. The unobserved components are trend inflation and the non‐accelerating inflation rate of unemployment (NAIRU). Our model also incorporates a time‐varying Phillips curve and time‐varying inflation persistence. What sets this paper apart from the existing literature is that we do not use unbounded random walks for the unobserved components, but rather bounded random walks. For instance, NAIRU is assumed to evolve within bounds. Our empirical work shows the importance of bounding. We find that our bounded bivariate model forecasts better than many alternatives, including a version of our model with unbounded unobserved components. Our model also yields sensible estimates of trend inflation, NAIRU, inflation persistence and the slope of the Phillips curve. Copyright © 2015 John Wiley & Sons, Ltd.     

What Drives Output Volatility? The Role of Demographics and Government Size Revisited

This paper studies the determinants of output volatility in a panel of 22 OECD countries. In contrast to the existing literature, we avoid ad hoc estimates of volatility based on rolling windows, and we account for possible non‐stationarity. Specifically, output volatility is modelled within an unobserved components model where the volatility series is the outcome of both macroeconomic determinants and a latent integrated process. A Bayesian model selection approach tests for the presence of the non‐stationary component. The results point to demographics and government size as important determinants of macroeconomic (in)stability. A larger share of prime‐age workers is associated with lower output volatility, while higher public expenditure increases volatility.     

A small monetary system for the euro area based on German data

Previous euro area money demand studies have used aggregated national time series data from the countries participating in the European Monetary Union (EMU). However, aggregation may be problematic because macroeconomic convergence processes have taken place in the countries of interest. Therefore, in this study, quarterly German data until 1998 are combined with data from the euro area from 1999 until 2002 and these series are used for fitting a small vector error correction model for the monetary sector of the EMU. A stable long‐run money demand relation is found for the full sample period. Moreover, impulse responses do not change much when the sample period is extended by the EMU period provided the break in the extended data series is captured by a simple dummy variable. Copyright © 2006 John Wiley & Sons, Ltd.