Fractional Integration and the Dynamics of UK Unemployment*

This article is concerned with estimating the dynamic behaviour of UK unemployment using fractional integration methods. The question it considers is whether an unemployment model using a relatively small set of determinants of unemployment is consistent with the persistence which estimates an integrated model yield, or the much long‐lasting estimates obtained from fractional integration. Our empirical tests favour the latter version. The results show that when accounting for UK unemployment in terms of lagged values of the real oil price and the real interest rate, unemployment appears fractionally integrated. This finding means that although unemployment is mean reverting, once it is shocked it may take a very long time to recover, and our estimates of the response times are considerably in excess of those previously reported in the literature.     

Anticipating Long‐Term Stock Market Volatility

We investigate the relationship between long‐term US stock market risks and the macroeconomic environment using a two‐component GARCH‐MIDAS model. Our results show that macroeconomic variables are important determinants of the secular component of stock market volatility. Among the various macro variables in our dataset the term spread, housing starts, corporate profits and the unemployment rate have the highest predictive ability for long‐term stock market volatility. While the term spread and housing starts are leading variables with respect to stock market volatility, for industrial production and the unemployment rate expectations data from the Survey of Professional Forecasters regarding the future development are most informative. Copyright © 2014 John Wiley & Sons, Ltd.     

Okun's Law Revisited*

In the light of modern theoretical studies, the negative relationship between output and unemployment may take a nonlinear form, in the sense that changes in output can cause asymmetric changes in the unemployment rate. A regime‐dependent specification of Okun's law, where the inverse relationship between cyclical unemployment and cyclical GDP is allowed to differ across recessions and expansions, is estimated for the US economy. Using both the Hodrick–Prescott filter and a bivariate structural time series model to isolate the cyclical component of the variables of interest, the nonlinear specification is highly significant when tested against the linear alternative independently of the method used for extracting the cycle of unemployment and GDP. The estimation results imply that the contemporaneous effect of growth on unemployment is asymmetric and significantly higher in recessions than in expansions, and shocks to unemployment tend to be more persistent in the expansionary regime.     

Multiple shifts and fractional integration in the US and UK unemployment rates

This paper analyses the long-run behaviour of the US and UK unemployment rates by testing for possibly fractional orders of integration and multiple shifts using a sample of over 100 annual observations. The results show that the orders of integration are higher than zero in both series, which implies long memory. If we assume that the underlying disturbances are white noise, the values are higher than 0.5, i.e., nonstationary. However, if the disturbances are autocorrelated, the orders of integration are in the interval (0, 0.5), implying stationarity and mean-reverting behaviour. Moreover, when multiple shifts are taken into account, unemployment is more persistent in the US than in the UK, implying the need for stronger policy action in the former to bring unemployment back to its original level.     

Money‐output Causality Revisited – A Bayesian Logistic Smooth Transition VECM Perspective*

This article proposes a Bayesian approach to examining money‐output causality within the context of a logistic smooth transition vector error correction model. Our empirical results provide substantial evidence that the postwar US money‐output relationship is nonlinear, with regime changes mainly governed by the output growth and price levels. Furthermore, we obtain strong support for nonlinear Granger causality from money to output, although there is also some evidence for models indicating that money is not Granger causal or long‐run causal to output.     

Monetary Policy in the Greenspan Era: A Time Series Analysis of Rules vs. Discretion*

Relationships between the Federal funds rate, unemployment, inflation and the long‐term bond rate are investigated with cointegration techniques. We find a stable long‐term relationship between the Federal funds rate, unemployment and the bond rate. This relationship is interpretable as a policy target because deviations are corrected via the Federal funds rate. Deviations of the actual Federal funds rate from the estimated target give simple indications of discretionary monetary policy, and the larger deviations relate to special episodes outside the current information set. A more traditional Taylor‐type target, where inflation appears instead of the bond rate, does not seem congruent with the data.     

Nonlinear dynamics of interest rate and inflation

According to several empirical studies US inflation and nominal interest rates as well as the real interest rate can be described as unit root processes. These results imply that nominal interest rates and expected inflation do not move one‐for‐one in the long run, which is incongruent with theoretical models. In this paper we introduce a new nonlinear bivariate mixture autoregressive model that seems to fit quarterly US data (1953 : II–2004 : IV) reasonably well. It is found that the three‐month Treasury bill rate and inflation share a common nonlinear component that explains a large part of their persistence. The real interest rate is devoid of this component, indicating one‐for‐one movement of the nominal interest rate and inflation in the long run and, hence, stationarity of the real interest rate. Copyright © 2006 John Wiley & Sons, Ltd.     

On Business Cycle Asymmetries in G7 Countries

We investigate whether business cycle dynamics in seven industrialized countries (the G7) are characterized by asymmetries in conditional mean. We provide evidence on this issue using a variety of time series models. Our approach is fully parametric. Our testing strategy is robust to any conditional heteroskedasticity, outliers, and/or long memory that may be present. Our results indicate fairly strong evidence of nonlinearities in the conditional mean dynamics of the GDP growth rates for Canada, Germany, Italy, Japan, and the US. For France and the UK, the conditional mean dynamics appear to be largely linear. Our study shows that while the existence of conditional heteroskedasticity and long memory does not have much effect on testing for linearity in the conditional mean, accounting for outliers does reduce the evidence against linearity.     

Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment*

We introduce a general class of periodic unobserved component (UC) time series models with stochastic trend and seasonal components and with a novel periodic stochastic cycle component. The general state space formulation of the periodic model allows for exact maximum likelihood estimation, signal extraction and forecasting. The consequences for model‐based seasonal adjustment are discussed. The new periodic model is applied to postwar monthly US unemployment series from which we identify a significant periodic stochastic cycle. A detailed periodic analysis is presented including a comparison between the performances of periodic and non‐periodic UC models.     

Dynamics of worker flows and vacancies: evidence from the sign restriction approach

This paper establishes robust dynamic features of the worker reallocation process in the US labor market. I use structural VARs with sign restrictions, which take the form of restricting the short‐run negative relationship between vacancies and unemployment (i.e., Beveridge curve). Despite the ‘weakness’ of these restrictions, they reveal a clear, unambiguous pattern that, when unemployment increases and vacancies drop, (i) both the separation rate and gross separations rise quickly and remain persistently high, (ii) the job finding rate and vacancies drop in a hump‐shaped manner, and (iii) gross hires respond little initially, but eventually rise. These results point to the importance of job loss in understanding US labor market dynamics. This pattern also holds with respect to different kinds of shocks that induce the same Beveridge curve relationship. This paper also considers the ‘disaggregate model’, which uses data disaggregated into six demographic groups and incorporates transitions into and out of the labor force. I show that the separation rate continues to play a dominant role among prime‐age male workers, while, for other groups, changes in the job finding rate are more important. Copyright © 2009 John Wiley & Sons, Ltd.     

The impact of the shutdown policy on the asymmetric interdependence structure and risk transmission of cryptocurrency and China’s financial market

By taking Bitcoin, Litecoin, and China’s gold and RMB/US dollar exchange rate market as research objects, this paper apply the MF-ADCCA and time-delayed DCCA methods to study the impact of China’s mainland shutdown of cryptocurrencies trading on the non-linear interdependent structure and risk transmission of cryptocurrencies and its financial market. Empirical results show that the cross-correlation between cryptocurrencies and China’s financial market has a long memory and asymmetric multifractal characteristics. After the shutdown, the long memory between cryptocurrencies and Chinese gold has weakened, and the long memory between cryptocurrencies and the RMB/US dollar exchange rate market was strengthened. China’s shutdown policy has a certain risk prevention effect. Specifically, after the implementation of the policy, the risk transmission of cryptocurrencies to China’s financial market has weakened, but the influence of China’s financial market has gradually strengthened.     

Structural FECM: Cointegration in large‐scale structural FAVAR models

Starting from the dynamic factor model for nonstationary data we derive the factor‐augmented error correction model (FECM) and its moving‐average representation. The latter is used for the identification of structural shocks and their propagation mechanisms. We show how to implement classical identification schemes based on long‐run restrictions in the case of large panels. The importance of the error correction mechanism for impulse response analysis is analyzed by means of both empirical examples and simulation experiments. Our results show that the bias in estimated impulse responses in a factor‐augmented vector autoregressive (FAVAR) model is positively related to the strength of the error correction mechanism and the cross‐section dimension of the panel. We observe empirically in a large panel of US data that these features have a substantial effect on the responses of several variables to the identified permanent real (productivity) and monetary policy shocks.     

A nonlinear long memory model, with an application to US unemployment

Two important empirical features of US unemployment are that shocks to the series seem rather persistent and that it seems to rise faster during recessions than that it falls during expansions. To jointly capture these features of long memory and nonlinearity, we put forward a new time series model and evaluate its empirical performance. We find that the model describes the data rather well and that it outperforms related competitive models on various measures of fit.     

A Bayesian Semiparametric Competing Risk Model with Unobserved Heterogeneity

This paper generalizes existing econometric models for censored competing risks by introducing a new flexible specification based on a piecewise linear baseline hazard, time‐varying regressors, and unobserved individual heterogeneity distributed as an infinite mixture of generalized inverse Gaussian (GIG) densities, nesting the gamma kernel as a special case. A common correlated latent time effect induces dependence among risks. Our model is based on underlying latent exit decisions in continuous time while only a time interval containing the exit time is observed, as is common in economic data. We do not make the simplifying assumption of discretizing exit decisions—our competing risk model setup allows for latent exit times of different risk types to be realized within the same time period. In this setting, we derive a tractable likelihood based on scaled GIG Laplace transforms and their higher‐order derivatives. We apply our approach to analyzing the determinants of unemployment duration with exits to jobs in the same industry or a different industry among unemployment insurance recipients on nationally representative individual‐level survey data from the US Department of Labor. Our approach allows us to conduct a counterfactual policy experiment by changing the replacement rate: we find that the impact of its change on the probability of exit from unemployment is inelastic. Copyright © 2014 John Wiley & Sons, Ltd.     

Unemployment or credit: Which one holds the potential? Results for a small open economy with a low degree of financialization

This paper investigates the relative importance of unemployment versus credit in determining the potential level of real activity for a small open economy with a low degree of financialization. We use a multivariate unobserved component model (MUC) to derive the potential output and the associated output gap for the Lithuanian economy. The model is estimated via Bayesian methods and the time paths of unobserved variables are extracted via the Kalman filter. The inclusion of unemployment in the MUC model substantially improves the estimates of the output gap in real time. Adding information about credit further emphasizes the overheating of the economy in the pre-crisis period, both in real time and ex post. Including credit preserves the conclusions regarding turning points. We uncover a strong negative correlation between the model-implied unemployment gap (without accounting for credit) and real credit growth. Data revisions do not appear to be the primary source of revisions of output gap estimates.     

Macroeconomic forecasting and structural change

The aim of this paper is to assess whether modeling structural change can help improving the accuracy of macroeconomic forecasts. We conduct a simulated real‐time out‐of‐sample exercise using a time‐varying coefficients vector autoregression (VAR) with stochastic volatility to predict the inflation rate, unemployment rate and interest rate in the USA. The model generates accurate predictions for the three variables. In particular, the forecasts of inflation are much more accurate than those obtained with any other competing model, including fixed coefficients VARs, time‐varying autoregressions and the naïve random walk model. The results hold true also after the mid 1980s, a period in which forecasting inflation was particularly hard. Copyright © 2011 John Wiley & Sons, Ltd.     

The Relative Importance of Symmetric and Asymmetric Shocks: The Case of United Kingdom and Euro Area*

We show how a simple model with sign restrictions can be used to identify symmetric and asymmetric supply, demand and monetary policy shocks in an estimated two‐country structural VAR for the UK and Euro area. The results can be used to deal with several issues that are relevant in the optimal currency area literature. We find an important role for symmetric shocks in explaining the variability of the business cycle in both economies. However, the relative importance of asymmetric shocks, being around 20% in the long run, cannot be ignored. Moreover, when we estimate the model for the UK and US, the degree of business cycle synchronization seems to be higher. Finally, we confirm existing evidence of the exchange rate being an independent source of shocks in the economy.     

Turning Unemployment into Self‐Employment: Effectiveness of Two Start‐Up Programmes*

Turning unemployment into self‐employment has become a major focus of German active labour market policy (ALMP) in recent years. If effective, this would not only reduce Germany's persistently high unemployment rate, but also increase its notoriously low self‐employment rate. Empirical evidence on the effectiveness of such programmes is scarce. We evaluate the effectiveness of two start‐up programmes for the unemployed, where we include the probability of being employed, the probability of being unemployed and personal income as outcome variables. Our results show that at the end of the observation period, both programmes are effective. The considerable positive effects present a stark contrast to findings from evaluations of other German ALMP programmes in recent years. Hence, ALMP programmes aimed at moving the unemployed into self‐employment may prove to be among the most effective, both in Germany and elsewhere.     

On the cyclicality of unemployment: Resurrecting the participation margin

This paper considers a real business cycle model with search frictions in the labor market and labor supply which is elastic along the participation margin. Previous authors have found that such models generate counterfactually procyclical unemployment and a positively sloped Beveridge curve. This paper presents a calibrated model which succeeds at generating countercyclical unemployment and a negatively sloped Beveridge curve, despite the presence of a participation margin.