We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...

Dynamic factor models based on Kalman Filter techniques are frequently used to nowcast GDP. This study deals with the selection of indicators for this practice. We propose a two-tiered mechanism which is shown in a case study to produce more accurate nowcasts than a benchmark stochastic process...

This paper gives a detailed overview of the current state of research in relation to the use of state space models and the Kalman-filter in the field of stochastic claims reserving. Most of these state space representations are matrix-based, which complicates their applications. Therefore, to...

The level of capital tax gains has high explanatory power regarding the question of what drives economic inequality. On this basis, the authors develop a simple, yet micro-founded portfolio selection model to explain the dynamics of wealth inequality given empirical tax series in the US. The...

Firms provide substantial insurance against wage fl uctuations and job loss. This paper studies how the interaction between shock size and persistence affects the firm's ability to insure workers against idiosyncratic firm-level shocks. Using linked employer-employee data from Germany, I find...

We propose a multivariate simultaneous unobserved components framework to determine the two-sided interactions between structural trend and cycle innovations. We relax the standard assumption in unobserved components models that trends are only driven by permanent shocks and cycles are only...

We use Google search data with the aim of predicting unemployment, CPI and consumer confidence for the US, UK, Canada, Germany and Japan. Google search queries have previously proven valuable in predicting macroeconomic variables in an in-sample context. To our knowledge, the more challenging...

We provide a simulation smoother to a exible state-space model with lagged states and lagged dependent variables. Qian (2014) has introduced this state-space model and proposes a fast Kalman filter with time-varying state dimension in the presence of missing observations in the data. In this...

This study revisits the import demand function for Turkey using the newly defined national income data and examines the evolution of the income and price elasticities over time. In this respect, demand functions are estimated for the total imports and its subcomponents separately, and the...

The conditional capital asset pricing model (CAPM) theory postulates that the systematic risk ( β ) of an asset or portfolio varies over time. Several dynamics are thus given to systematic risk in the literature. This article looks for the dynamic that seems to best explain the returns of the...

Firms provide substantial insurance against wage fl uctuations and job loss. This paper studies how the interaction between shock size and persistence affects the firm's ability to insure workers against idiosyncratic firm-level shocks. Using linked employer-employee data from Germany, I find...

This article extends the Factor-Augmented Vector Autoregression Model (FAVAR) to mixed-frequency and incomplete panel data. Within the scope of a fully parametric two-step approach, the alternating application of two expectation-maximization algorithms jointly estimates model parameters and...

This paper analyzes why the Philippines' growth performance has improved significantly in recent years. As in the medium to long term actual growth adjusts to potential, we posit that the reason behind this improvement is that the country's potential growth is increasing. We derive an estimate...

The People's Republic of China's (PRC) remarkable growth performance over the last 3 decades has been associated to very robust export growth, so much so that many refer to it as a clear example of export-led growth (ELG). Using the concept of the balance-of-payments equilibrium (BOPE) growth...

The study analyses financial cycles based on a global sample of 34 advanced and developing countries over the period 1960Q1 to 2015Q4. We use dynamic factor models and state-space techniques to estimate financial cycles in credit, housing, bond and equity markets, as well as aggregate...

The paper reports estimation results and technical details on the estimation of financial cycles for a global sample of 34 advanced and developing countries over the period 1960Q1–2015Q4, as well as introduces a database of financial cycles. We estimate several versions of financial cycles for...

Over the last decades, the estimation of the slack in the economy has become an essential piece of analysis for policymakers, both on the monetary policy and the fiscal policy front. Output gap estimation techniques have flourished accordingly, although there is no consensus on a best-performing...

We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...

This paper studies the evolution of long-run output and labour productivity growth rates in the G-7 countries during the post-war period. We estimate the growth rates consistent with a constant unemployment rate using time-varying parameter models that incorporate both stochastic volatility and...

I extend the model of Laubach and Williams (2003) by introducing an explicit role for the financial cycle in the joint estimation of the natural rates of interest, unemployment and output, and the sustainable growth rate of the US economy. By incorporating the financial cycle - arguably an...

Dynamic factor models based on Kalman Filter techniques are frequently used to nowcast GDP. This study deals with the selection of indicators for this practice. We propose a two-tiered mechanism which is shown in a case study to produce more accurate nowcasts than a benchmark stochastic process...

Inflation has been persistently weak in the euro area despite the economic recovery since 2013. We investigate the sources behind this protracted low inflation by building a time-varying parameter model that jointly explains the dynamics of inflation and inflation expectations from the ECB's...

This paper analyzes why the Philippines' growth performance has improved significantly in recent years. As in the medium to long term actual growth adjusts to potential, we posit that the reason behind this improvement is that the country’s potential growth is increasing. We derive an estimate...

This paper studies the evolution of long-run output and labour productivity growth rates in the G-7 countries during the post-war period. We estimate the growth rates consistent with a constant unemployment rate using time-varying parameter models that incorporate both stochastic volatility and...

The equilibrium real interest rate is one of the most discussed variables in economics, although it is unobservable. While it has been estimated with respect to various developed countries, this paper is the first to estimate it for five developing countries - the BRICS countries. To do so the...

We develop a vector autoregressive model with time variation in the mean and the variance. The unobserved time-varying mean is assumed to follow a random walk and we also link it to long-term Consensus forecasts, similar in spirit to so called democratic priors. The changes in variance are...

The study analyses financial cycles based on a global sample of 34 advanced and developing countries over the period 1960Q1 to 2015Q4. We use dynamic factor models and state-space techniques to estimate financial cycles in credit, housing, bond and equity markets, as well as aggregate...

Presidential elections can impact world peace, global economics, and overall well-being. Recent news indicates that fraud on the Web has played a substantial role in elections, particularly in developing countries in South America and the public discourse, in general. To protect the...

We develop novel multivariate state-space models wherein the latent states evolve on the Stiefel manifold and follow a conditional matrix Langevin distribution. The latent states correspond to time-varying reduced rank parameter matrices, like the loadings in dynamic factor models and the...

I extend the model of Laubach and Williams (2003) by introducing an explicit role for the financial cycle in the joint estimation of the natural rates of interest, unemployment and output, and the sustainable growth rate of the US economy. By incorporating the financial cycle - arguably an...

Over the last decades, the estimation of the slack in the economy has become an essential piece of analysis for policymakers, both on the monetary policy and the fiscal policy front. Output gap estimation techniques have flourished accordingly, although there is no consensus on a best-performing...

A novel class of dimension reduction methods is combined with a stochastic multi-factor panel regression-based state-space model in order to model the dynamics of yield curves whilst incorporating regression factors. This is achieved via Probabilistic Principal Component Analysis (PPCA) in which...

Nonlinear, non-Gaussian state space models have found wide applications in many areas. Since such models usually do not allow for an analytical representation of their likelihood function, sequential Monte Carlo or particle filter methods are mostly applied to estimate their parameters. Since...

The People's Republic of China's (PRC) remarkable growth performance over the last 3 decades has been associated to very robust export growth, so much so that many refer to it as a clear example of export-led growth (ELG). Using the concept of the balance-of-payments equilibrium (BOPE) growth...